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Deng Y, Ma T, Ngai FW, Wang HH, Yang L, Sun Q, Xie YJ. Association of a healthy lifestyle index with anthropometric indices and obesity in Hong Kong Chinese women: Evidence from the MECH-HK cohort study. Obes Res Clin Pract 2025:S1871-403X(25)00002-X. [PMID: 39809642 DOI: 10.1016/j.orcp.2025.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 12/19/2024] [Accepted: 01/03/2025] [Indexed: 01/16/2025]
Abstract
AIM This cross-sectional study aimed to examine the associations of a healthy lifestyle index (HLI) with several anthropometric indices and obesity among Hong Kong Chinese women. SUBJECTS/METHODS A total of 3174 women (56.16 ± 8.43 years) were included. The HLI consisted of diet, physical activity, sedentary time, sleep duration, skipping breakfast, smoking, and alcohol. Each factor was scored as 0 (unhealthy) or 1 (healthy). The overall HLI was the sum of these points, ranging from 0 (the least healthy) to 7 (healthiest). Percent body fat (PBF), body fat mass (BFM), fat free mass (FFM), waist circumference (WC), waist-to-hip ratio (WHR), height, and weight were measured using the InBody 270 device. RESULTS The number of women with 0-2, 3, 4, 5, 6-7-point HLI groups were 551, 759, 954, 645, and 265, respectively. As HLI increased, most anthropometric indices declined while FFM increased. The adjusted βs (95 % confidence intervals (95 % CIs)) for PBF (%), BFM (kg), WC (cm), WHR, height (cm), weight (kg), BMI (kg/m^2), and FFM (kg) were -0.653 (-0.829, -0.476), -0.582 (-0.751, -0.414), -0.719 (-0.971, -0.467), -0.005 (-0.006, -0.004), -0.181 (-0.347, -0.015), -0.602 (-0.850, -0.355), -0.188 (-0.282, -0.095), and 0.339 (0.213, 0.465), respectively. Additionally, compared to the 0-2-point group, the odds ratios (95 % CIs) of the 6-7-point groups were 0.54 (0.38-0.75) for central obesity and 0.55 (0.37-0.82) for general obesity. CONCLUSIONS HLI was inversely associated with PBF, BFM, WC, WHR, height, weight, BMI, central obesity, and general obesity, but was positively associated with FFM.
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Affiliation(s)
- Yunyang Deng
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 171 77, Sweden.
| | - Tongyu Ma
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
| | - Fei Wan Ngai
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China.
| | - Harry Haoxiang Wang
- School of Public Health, Sun Yat-Sen University, Guangzhou, China; College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh EH8 9AG, UK.
| | - Lin Yang
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China.
| | - Qi Sun
- Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA.
| | - Yao Jie Xie
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China.
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Wang Y, Yang P, Liu H, Cao S, Liu J, Huo Y, Xu K, Zhang B, Wang M, Huang Q, Yang C, Zeng L, Dang S, Mi B. Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults. Prev Med Rep 2025; 49:102934. [PMID: 39691358 PMCID: PMC11648257 DOI: 10.1016/j.pmedr.2024.102934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 11/18/2024] [Accepted: 11/19/2024] [Indexed: 12/19/2024] Open
Abstract
Objectives To examine the association between physical activity (PA) and leisure-time sedentary time and cardiovascular disease (CVD). Methods This cross-sectional study used baseline data from the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019. PA and leisure-time sedentary time were self-reported. Logistic regression models analyzed the association of PA and leisure-time sedentary time with CVD prevalence individually and jointly. Restricted cubic spline analyses assessed dose-response relationships. Isotemporal substitution models were used to investigate substituting leisure-time sedentary time, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) with CVD prevalence. Results The prevalence of CVD was 31.8 %. Compared to the lowest quartile, participants in the highest quartile of total PA had a 32 % lower CVD prevalence (odds ratio [OR]: 0.68, 95 % confidence interval [CI]: 0.62-0.74; P for trend <0.001). The fully adjusted OR for the highest quartile of leisure-time sedentary time compared to the lowest quartile was 1.09 (1.01-1.18; P for trend =0.04). An L-shaped dose-response relationship was observed between PA and CVD prevalence. An active lifestyle and reduced daily leisure-time sedentary time were associated with a 26 % (0.74 [0.63-0.86]) lower CVD prevalence. Additionally, substituting 30 min/day of leisure-time sedentary time with equivalent MVPA was associated with a 2 % (0.98 [0.97-0.99]) reduction in CVD prevalence. Substituting sedentary time with LPA was associated with a lower CVD prevalence in females. Conclusions An active lifestyle was associated with a lower prevalence of CVD in regional populations, suggesting a feasible strategy for CVD prevention and regional health promotion.
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Affiliation(s)
- Yutong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Peiying Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Huimeng Liu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Suixia Cao
- Department of Neurology, The First Affilated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Jingchun Liu
- Ministry of Science and Technology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Yating Huo
- Dongcheng District Center for Disease Control and Prevention, Beijing 100009, China
| | - Kun Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Binyan Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Mengchun Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Qian Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Chunlai Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Lingxia Zeng
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Shaonong Dang
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
| | - Baibing Mi
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
- Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China
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Nasueb S, Kosiyaporn H, Cetthakrikul N, Adhibai R, Thiphong J, Pumsutas Y, Waleewong O. Associations of work characteristics with obesity, behavioral risk factors and NCDs in Bangkok, Thailand. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0004000. [PMID: 39636952 PMCID: PMC11620629 DOI: 10.1371/journal.pgph.0004000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Accepted: 11/11/2024] [Indexed: 12/07/2024]
Abstract
Non-communicable diseases (NCDs) are one of the premature causes of death in Thailand especially among working age group. This study aims to examine the associations between work characteristics and NCDs, obesity, and behavioral risk factors in Bangkok, the Capital of Thailand. This study employed secondary data analysis of cross-sectional data from the Health Behavior of Population Survey 2021 by the National Statistical Office (NSO). The respondents who were 15-60 years old and resided in Bangkok were included in this study (n = 4,925). The data were analyzed by descriptive statistics of work characteristics, and multiple logistic regression between working groups and behavioral risks adjusted with other demographic and socioeconomic variables. The study found that all workers showed a lower likelihood of reporting NCDs compared to the unemployed. Professional/administrative/managerial workers had 44% less chances of reporting NCDs compared to unemployed (AOR = 0.56; 95%CI = 0.43-0.75; P-value <0.001. All working groups showed a significant association with alcohol consumption, smoking, and dietary intake. In particular, skilled, semi-skilled, unskilled workers, technicians, clerks, and service or sales workers were more likely to smoke and drink alcohol compared to those who were unemployed. Nevertheless, work characteristics did not affect the likelihood of inappropriate fruit and vegetable intake, insufficient physical activity, and sedentary behavior. The study found a link between work characteristics and NCDs in the working-age population, identifying specific work characteristics associated with behavioral risk factors such as alcohol consumption, smoking, and high dietary risk. The findings suggest a need for NCD prevention strategies targeting diverse workplaces such as smoking regulations, healthy canteens, and promoting opportunities for physical activity, with a regulatory focus on labor laws and policy incentives. Finally, disaggregated occupational data should be emphasis for effective monitoring and evaluation in NCD policy.
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Affiliation(s)
- Sopit Nasueb
- International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand
| | - Hathairat Kosiyaporn
- International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand
| | - Nisachol Cetthakrikul
- International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand
| | - Rujira Adhibai
- International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand
| | - Jiranun Thiphong
- International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand
| | - Yanisa Pumsutas
- International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand
| | - Orratai Waleewong
- International Health Policy Program, Ministry of Public Health, Nonthaburi, Thailand
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Chen Y, Yu W, Lv J, Sun D, Pei P, Du H, Yang L, Chen Y, Zhang H, Chen J, Chen Z, Li L, Yu C. Early adulthood BMI and cardiovascular disease: a prospective cohort study from the China Kadoorie Biobank. Lancet Public Health 2024; 9:e1005-e1013. [PMID: 38885669 PMCID: PMC11617502 DOI: 10.1016/s2468-2667(24)00043-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND The associations of early adulthood BMI with cardiovascular diseases have yet to be completely delineated. There is little reliable evidence about these associations among east Asian populations, that differ in fat distribution, disease patterns, and lifestyle factors from other populations. We aimed to study the associations between early adulthood BMI and cardiovascular diseases in a Chinese population, and the effect of midlife lifestyle factors on outcomes. METHODS In this prospective analysis, we used data from the China Kadoorie Biobank, a large and long-term cohort from five urban areas and five rural areas, using participants aged 35-70 years. The primary outcome was the incidence of cardiovascular diseases as a group, ischaemic heart disease, haemorrhagic stroke, and ischaemic stroke, which were obtained mainly through linkage to disease registries and the national database for health insurance claims. Early adulthood BMI was assessed through self-report at baseline survey. We used Cox proportional hazards regression models to examine the prospective associations. We also undertook multiplicative and additive interaction analyses to investigate the potential modification effect of midlife healthy lifestyle factors (a combined score covering smoking, drinking, physical activity, and diet). FINDINGS Participants were recruited for baseline survey between June, 2004, and July, 2008. During a median follow-up of 12·0 years (IQR 11·3-13·1), we documented 57 203 (15·9%) of incident cardiovascular diseases in 360 855 participants. After adjustment for potential confounders, monotonic dose-response associations were observed between higher early adulthood BMI and increased risks of incident cardiovascular diseases. Compared with an early adulthood BMI of 20·5-22·4 kg/m2 (the reference group), the hazard ratios for a BMI of less than 18·5 kg/m2 was 0·97 (95% CI 0·94-1·00), 18·5-20·4 kg/m2 was 0·97 (0·95-0·99), 22·5-23·9 kg/m2 was 1·04 (1·02-1·07), 24·0-25·9 kg/m2 was 1·12 (1·09-1·15), 26·0-27·9 kg/m2 was 1·19 (1·14-1·24), 28·0-29·9 kg/m2 was 1·34 (1·25-1·44), and ≥30·0 kg/m2 was 1·58 (1·42-1·75). Except for haemorrhagic stroke, lower early adulthood BMI (<20·5 kg/m2) was associated with decreased incident cardiovascular disease risks. No significant interaction was found between midlife healthy lifestyle factors and early adulthood BMI on cardiovascular disease risks. INTERPRETATION Increased risks of cardiovascular disease incidence were found among participants with high early adulthood adiposity, including ischaemic heart disease, haemorrhagic stroke, and ischaemic stroke. Our findings suggest early adulthood as an important time to focus on weight management and obesity prevention for cardiovascular health later in life. FUNDING National Natural Science Foundation of China, National Key Research and Development Program of China, Chinese Ministry of Science and Technology, Kadoorie Charitable Foundation, and the Wellcome Trust.
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Affiliation(s)
- Yuanyuan Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Wei Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Bejing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Pei Pei
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Huaidong Du
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huanxu Zhang
- Tongxiang Center for Disease Control and Prevention, Zhejiang, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Bejing, China.
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Sun Z, Yuan Y, Farrahi V, Herold F, Xia Z, Xiong X, Qiao Z, Shi Y, Yang Y, Qi K, Liu Y, Xu D, Zou L, Chen A. Using interpretable machine learning methods to identify the relative importance of lifestyle factors for overweight and obesity in adults: pooled evidence from CHNS and NHANES. BMC Public Health 2024; 24:3034. [PMID: 39487401 PMCID: PMC11529325 DOI: 10.1186/s12889-024-20510-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2024] [Accepted: 10/24/2024] [Indexed: 11/04/2024] Open
Abstract
BACKGROUND Overweight and obesity pose a huge burden on individuals and society. While the relationship between lifestyle factors and overweight and obesity is well-established, the relative contribution of specific lifestyle factors remains unclear. To address this gap in the literature, this study utilizes interpretable machine learning methods to identify the relative importance of specific lifestyle factors as predictors of overweight and obesity in adults. METHODS Data were obtained from 46,057 adults in the China Health and Nutrition Survey (2004-2011) and the National Health and Nutrition Examination Survey (2007-2014). Basic demographic information, self-reported lifestyle factors, including physical activity, macronutrient intake, tobacco and alcohol consumption, and body weight status were collected. Three machine learning models, namely decision tree, random forest, and gradient-boosting decision tree, were employed to predict body weight status from lifestyle factors. The SHapley Additive exPlanation (SHAP) method was used to interpret the prediction results of the best-performing model by determining the contributions of specific lifestyle factors to the development of overweight and obesity in adults. RESULTS The performance of the gradient-boosting decision tree model outperformed the decision tree and random forest models. Analysis based on the SHAP method indicates that sedentary behavior, alcohol consumption, and protein intake were important lifestyle factors predicting the development of overweight and obesity in adults. The amount of alcohol consumption and time spent sedentary were the strongest predictors of overweight and obesity, respectively. Specifically, sedentary behavior exceeding 28-35 h/week, alcohol consumption of more than 7 cups/week, and protein intake exceeding 80 g/day increased the risk of being predicted as overweight and obese. CONCLUSION Pooled evidence from two nationally representative studies suggests that recognizing demographic differences and emphasizing the relative importance of sedentary behavior, alcohol consumption, and protein intake are beneficial for managing body weight status in adults. The specific risk thresholds for lifestyle factors observed in this study can help inform and guide future research and public health actions.
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Affiliation(s)
- Zhiyuan Sun
- College of Physical Education, Yangzhou University, Yangzhou, 225127, China
- School of Sport and Brain Health, Nanjing Sport Institute, Nanjing, 210014, China
| | - Yunhao Yuan
- School of Information Engineering, Yangzhou University, Yangzhou, 225127, China
| | - Vahid Farrahi
- Institute for Sport and Sport Science, TU Dortmund University, 44227, Dortmund, Germany
| | - Fabian Herold
- Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, 14476, Potsdam, Germany
| | - Zhengwang Xia
- School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Xuan Xiong
- Department of Physical Education, Nanjing University, Nanjing, 210033, China
| | - Zhiyuan Qiao
- College of Physical Education, Yangzhou University, Yangzhou, 225127, China
| | - Yifan Shi
- College of Physical Education, Yangzhou University, Yangzhou, 225127, China
| | - Yahui Yang
- College of Physical Education, Yangzhou University, Yangzhou, 225127, China
| | - Kai Qi
- College of Physical Education, Yangzhou University, Yangzhou, 225127, China
| | - Yufei Liu
- Department of Sport, Gdansk University of Physical Education and Sport, Gdansk, 80-336, Poland
| | - Decheng Xu
- College of Physical Education, Yangzhou University, Yangzhou, 225127, China
| | - Liye Zou
- Body-Brain-Mind Laboratory, School of Psychology, Shenzhen University, Shenzhen, 518060, China.
| | - Aiguo Chen
- College of Physical Education, Yangzhou University, Yangzhou, 225127, China.
- School of Sport and Brain Health, Nanjing Sport Institute, Nanjing, 210014, China.
- Nanjing Sport Institute, Nanjing, 210014, China.
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Zhang Q, Wu SP, Liu X, Wang YL. Mediterranean diet and atrial fibrillation: a case-control study from China. Front Nutr 2024; 11:1433274. [PMID: 39539360 PMCID: PMC11557386 DOI: 10.3389/fnut.2024.1433274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Accepted: 10/21/2024] [Indexed: 11/16/2024] Open
Abstract
Objective The aim of this study was to assess the association between adherence to Mediterranean diet and the presence of atrial fibrillation (AF) in a Northern Chinese population. Methods This study was a single center, case-control study. A total of 952 low risk participants in Beijing Anzhen Hospital from 2016 to 2021 were collected, including 476 patients with first diagnosed of atrial fibrillation and 476 age and sex matched controls. According to the food frequency questionnaire (FFQ), the alternate Mediterranean diet score (AMED) was calculated, which was 0-9 points, indicating the adherence to the Mediterranean diet from low to high. Results The average age of the participants was 57.6 ± 9.1 years old, and 70.2% were men. After analyzing every component of AMED, vegetable consumption shows a negative correlation with the risk of AF, whereas alcohol consumption demonstrates a positive correlation with it (OR = 0.61, 95% CI 0.44-0.80, p < 0.001; OR = 1.99, 95% CI 1.48-2.58, p < 0.001). All patients were grouped according to AMED score. A significant inverse association between AMED and the risk of AF was observed. Compared with participants with AMED<4, the multivariable-adjusted ORs of AF were 0.75 (95% CI 0.55-1.06) for AMED 4-5 and 0.61 (95% CI 0.43-0.89) for AMED ≥6, with a trend in risk (p = 0.008). Results were consistent in stratified analyses of gender, age, BMI and smoking. Conclusion The Mediterranean diet was inversely associated with the risk of AF in this Northern Chinese population.
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Affiliation(s)
- Qian Zhang
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
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Chang X, Chen X, Wu X, Chen X, Zhang N, Lv J, Yu C, Sun D, Pei P, Cheng Y, Liu Y, Wu X. Association between sleep behaviors and stroke in Southwest China: a prospective cohort study. BMC Public Health 2024; 24:2937. [PMID: 39443903 PMCID: PMC11515456 DOI: 10.1186/s12889-024-20361-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Accepted: 10/10/2024] [Indexed: 10/25/2024] Open
Abstract
BACKGROUND Sleep can function as a potential modifiable risk factor in the control and prevention of stroke. Geography significantly influences sleep patterns. The association of sleep with stroke in population of Southwest China has not so far been investigated. METHODS A total of 55,001 residents aged from 30 to 79 years in Southwest China were included in this study, obtaining their complete information of baseline survey and follow-up in China Kadoorie Biobank (CKB). Sleep-evaluating score was constructed on the basis of short/long sleep duration, insomnia, and snoring. The multivariate Cox proportional hazards regression was used to analyze the association between sleep behaviors and stroke. RESULTS During 11.15 years of follow-up, 3410 stroke cases (572.78 cases/100,000 person-years) were documented. There exists no association of sleep-evaluating score with the risk of stroke in the total population. Male-predisposing association between sleep-evaluating score and risk of stroke was observed (for total stroke, HR = 1.52, 95% CI: 1.03-2.23; for hemorrhagic stroke, HR = 2.31, 95% CI: 1.22-4.34), with anisotropism in male residents with overweight and obesity (HR = 1.93, 95% CI: 1.03-3.63), and those without hypertension (HR = 1.76, 95% CI: 1.01-3.07) in the baseline survey. CONCLUSIONS There exists the male-predisposing association between sleep-evaluating score and the risk of stroke in Southwest China. Improving sleep is required for reducing the risk of stroke.
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Affiliation(s)
- Xiaoyu Chang
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, No. 1163 Xinmin Street, Chaoyang District, Changchun, Jilin Province, 130021, China
- Department of Chronic and Non-Communicable Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, No. 6 Zhongxue Road, Wuhou District, Chengdu, Sichuan Province, 610041, China
| | - Xiaofang Chen
- Department of Epidemiology and Statistics, Chengdu Medical College, Chengdu, 610000, China
| | - Xia Wu
- Pengzhou Center for Disease Control and Prevention, Pengzhou, 611900, China
| | - Xiaofang Chen
- Pengzhou Center for Disease Control and Prevention, Pengzhou, 611900, China
| | - Ningmei Zhang
- Department of Chronic and Non-Communicable Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, No. 6 Zhongxue Road, Wuhou District, Chengdu, Sichuan Province, 610041, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Pei Pei
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China
| | - Yi Cheng
- The Cardiovascular Center, the First Hospital of Jilin University, Changchun, 130000, China
| | - Yawen Liu
- Department of Epidemiology and Statistics, School of Public Health, Jilin University, No. 1163 Xinmin Street, Chaoyang District, Changchun, Jilin Province, 130021, China.
| | - Xianping Wu
- Department of Chronic and Non-Communicable Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, No. 6 Zhongxue Road, Wuhou District, Chengdu, Sichuan Province, 610041, China.
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Deressa A, Firdisa D, Birhanu A, Debella A, Gamachu M, Eyeberu A, Dechasa DB, Jibro U, Balis B, Tolera M, Regassa LD, Mussa I. Investigating factors influencing overweight and obesity among adult households in Ethiopia: a multilevel ordered analysis of 2016 EDHS data. Front Endocrinol (Lausanne) 2024; 15:1408090. [PMID: 39469574 PMCID: PMC11513308 DOI: 10.3389/fendo.2024.1408090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 09/10/2024] [Indexed: 10/30/2024] Open
Abstract
Background In both high- and low-income countries, including Ethiopia, overweight and obesity have emerged as public health issues of the 21st century. Hence, obtaining conclusive evidence concerning the factors that influence adults' body mass index is important. Therefore, using representative data, our study sought to provide solid evidence on factors influencing overweight and obesity among adults in Ethiopia. Methods The 2016 Ethiopia Demographic and Health Survey (EDHS), a dataset composed of a nationally representative sample of the survey, served as the basis for the study. Both descriptive and analytic findings were produced using STATA version 14. The data collection were conducted from January to June 2016. A total sample of 39,749 adults, 18 years and older, were included. Predictors were assessed using multivariable ordinal logistic regression analysis, and the results were presented as an adjusted proportional ratio (POR) with a 95% confidence interval. Statistical significance was declared at a p-value of <0.05. Results Overall, the magnitude of overweight and obesity among adults in Ethiopia was 8.5% (95% CI: 8.2% to 8.7%) and 2.9% (95% CI: 2.7% to 3.1%), respectively. Predictor variables such as smoking (POR = 0.53, 95% CI: 0.42-0.67); being female (POR = 1.21, 95% CI: 1.13-1.30); being married (POR = 1.91, 95% CI: 1.26-2.90); having a secondary education (POR = 1.42, 95% CI: 2.23-1.64); having a diploma and above education (POR = 1.78, 95% CI: 1.44-2.21); having a poorer (POR = 1.22, 95% CI: 1.13-1.31), middle (POR = 1.30, 95% CI: 1.20-1.40), richer (POR = 1.35, 95% CI: 1.25-1.47), and richest (POR = 3.13, 95% CI: 2.79-3.51) wealth index rating; and having a rural residence (POR = 0.48, 95% CI: 0.43-0.54) were significantly associated with overweight and obesity. Conclusions Overall, 8.5% and 2.9% of Ethiopian adults were overweight and obese, respectively. Factors such as smoking, sex, marital status, educational status, wealth index, residence, and region were significantly associated with overweight and obesity among adult households. As a result, enhancing lifestyle modifications is enormous, and it is necessary to have more tangible evidence concerning the factors influencing body mass index utilizing more representative data from local and global.
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Affiliation(s)
- Alemayehu Deressa
- School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Dawit Firdisa
- School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Abdi Birhanu
- School of Medicine, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Adera Debella
- School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Mulugeta Gamachu
- School of Medicine, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
- Department of Public Health, Rift Valley University, Harar, Ethiopia
| | - Addis Eyeberu
- School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Deribe Bekele Dechasa
- School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Usmael Jibro
- School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Bikila Balis
- School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Moti Tolera
- School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Lemma Demissie Regassa
- School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
| | - Ibsa Mussa
- School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia
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Zhang Y, Ding Y, Yu C, Sun D, Pei P, Du H, Yang L, Chen Y, Schmidt D, Avery D, Chen J, Chen J, Chen Z, Li L, Lv J. Predictive value of 8-year blood pressure measures in intracerebral haemorrhage risk over 5 years. Eur J Prev Cardiol 2024; 31:1702-1710. [PMID: 38629743 PMCID: PMC7616516 DOI: 10.1093/eurjpc/zwae147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 03/21/2024] [Accepted: 04/09/2024] [Indexed: 05/07/2024]
Abstract
AIMS The relationships between long-term blood pressure (BP) measures and intracerebral haemorrhage (ICH), as well as their predictive ability on ICH, are unclear. In this study, we aim to investigate the independent associations of multiple BP measures with subsequent 5-year ICH risk, as well as the incremental value of these measures over a single-point BP measurement in ICH risk prediction. METHODS AND RESULTS We included 12 398 participants from the China Kadoorie Biobank (CKB) who completed three surveys every 4-5 years. The following long-term BP measures were calculated: mean, minimum, maximum, standard deviation, coefficient of variation, average real variability, and cumulative BP exposure (cumBP). Cox proportional hazard models were used to examine the associations between these measures and ICH. The potential incremental value of these measures in ICH risk prediction was assessed using Harrell's C statistics, continuous net reclassification improvement (cNRI), and relative integrated discrimination improvement (rIDI). The hazard ratios (95% confidence intervals) of incident ICH associated with per standard deviation increase in cumulative systolic BP and cumulative diastolic BP were 1.62 (1.25-2.10) and 1.59 (1.23-2.07), respectively. When cumBP was added to the conventional 5-year ICH risk prediction model, the C-statistic change was 0.009 (-0.001, 0.019), the cNRI was 0.267 (0.070-0.464), and the rIDI was 18.2% (5.8-30.7%). Further subgroup analyses revealed a consistent increase in cNRI and rIDI in men, rural residents, and participants without diabetes. Other long-term BP measures showed no statistically significant associations with incident ICH and generally did not improve model performance. CONCLUSION The nearly 10-year cumBP was positively associated with an increased 5-year risk of ICH and could significantly improve risk reclassification for the ICH risk prediction model that included single-point BP measurement.
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Affiliation(s)
- Yiqian Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
| | - Yinqi Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 38 Xueyuan Road, Haidian District, Beijing 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 38 Xueyuan Road, Haidian District, Beijing 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, 38 Xueyuan Road, Haidian District, Beijing 100191, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Dan Schmidt
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Jianwei Chen
- Liuyang Centers for Disease Control and Prevention, NO.11 Section 2 Lihua Road, Jili Subdistrict, Liuyang, Changsha, Hunan 410300, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, 37 Guangqu Road, Chaoyang District, Beijing 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 38 Xueyuan Road, Haidian District, Beijing 100191, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 38 Xueyuan Road, Haidian District, Beijing 100191, China
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
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10
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Zeng G, Lin Y, Xie P, Lin J, He Y, Wei J. Association between physical activity & sedentary time on frailty in adults with chronic kidney disease: Cross-sectional NHANES study. Exp Gerontol 2024; 195:112557. [PMID: 39181192 DOI: 10.1016/j.exger.2024.112557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 08/05/2024] [Accepted: 08/21/2024] [Indexed: 08/27/2024]
Abstract
OBJECTIVE A considerable percentage of individuals with chronic kidney disease (CKD) are reported to be frail. Lower physical activity and higher sedentary time are most consistently associated with frailty among the potentially alterable risk factors. Although the single effect of physical activity or sedentary time on suppressing frailty have been widely studied, whether physical activity can mitigate or counteract the detrimental consequences of higher sedentary time on frailty among CKD population has never been explored. This study aims to explore whether and to what extent the correlation between sedentary time and frailty was diminished by physical activity among CKD population. STUDY DESIGN AND SETTING Data were acquired from the National Health and Nutrition Examination Survey (NHANES) 2007 to 2018 cycles. Frailty index was assessed using 49-item deficit model. Physical activity and sedentary time were measured using the Global Activity Questionnaire. Weighted binary logistic regression models, restricted cubic spline models and sensitivity analyses were performed to investigate the aforementioned relationship. RESULTS The final sample included 2551 adults aged ≥20 years with CKD, which is represented a weighted number of 4.98 million noninstitutionalized US population. In the fully adjusted model, the group with low physical activity was 1.56 (95 % CI:1.19, 2.03) times more likely to develop frailty than the group with high physical activity and each unit of increase of sedentary time was associated with an 41 % increased risk of frailty (OR = 1.41, 95 % CI = 1.04-1.89). Our findings also indicated that engaging in 1240-6200 MET-min/week of high physical activity was associated with a decreased risk of frailty related to moderate-to-high sedentary time among CKD population (OR = 0.69, 95 % CI = 0.49-0.99, P = 0.044). In subgroup analyses, high physical activity was associated with a 0.43-fold (95%CI: 0.24, 0.77) decreased risk of moderate-to-high sedentary time associated with frailty in female groups and a significant modification effect of gender was uncovered (Pinteraction = 0.024). CONCLUSION High physical activity was associated with a decreased risk of frailty related to moderate-to-high sedentary time in adults with CKD, especially in females subgroups.
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Affiliation(s)
- Guixing Zeng
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yujie Lin
- The Second Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Peirui Xie
- The First Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jiarong Lin
- Second Affiliated Hospital, Guangzhou University of Chinese Medicine (Guangdong Provincial Hospital of Chinese Medicine), Guangzhou, China
| | - Yaxing He
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China
| | - Junping Wei
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
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11
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Cao F, Wang R, Wang L, Li YZ, Wei YF, Zheng G, Nan YX, Sun MH, Liu FH, Xu HL, Zou BJ, Li XY, Qin X, Huang DH, Chen RJ, Gao S, Meng X, Gong TT, Wu QJ. Plant-based diet indices and their interaction with ambient air pollution on the ovarian cancer survival: A prospective cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 284:116894. [PMID: 39154500 DOI: 10.1016/j.ecoenv.2024.116894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 07/15/2024] [Accepted: 08/13/2024] [Indexed: 08/20/2024]
Abstract
BACKGROUND Ambient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions. METHODS The present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales. RESULTS Throughout a median follow-up of 37.60 (interquartile: 24.77-50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend < 0.01), whereas no significant associations were found between either overall PDI or hPDI and OC survival. Higher APS (HR for per interquartile range = 1.27, 95 % CI = 1.01, 1.60) was significantly associated with worse OC survival, and the association was exacerbated by adherence to uPDI. Notably, an additive interaction was identified between combined air pollution and uPDI (P < 0.005 for high APS and high uPDI). We also found that adherence to overall PDI aggravated associations of air pollution with OC survival (P-interaction = 0.006). CONCLUSIONS Joint exposure to various ambient air pollutants was significantly associated with lower survival among patients with OC, particularly for those who predominantly consumed unhealthy plant-based foods.
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Affiliation(s)
- Fan Cao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ran Wang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lan Wang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yi-Zi Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Gang Zheng
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Xin Nan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ming-Hui Sun
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Fang-Hua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - He-Li Xu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bing-Jie Zou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiao-Ying Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Dong-Hui Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ren-Jie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China.
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), National Health Commission, Shenyang, China.
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Shen Y, Hu Y, Liu L, Zhong J, Zhang Y, Wu S, Chen C, Hong F. Association Between the Copper-to-Zinc Ratio and Cardiovascular Disease Among Chinese Adults: A China Multi-ethnic Cohort (CMEC) Study. Cardiovasc Toxicol 2024; 24:1005-1017. [PMID: 39134881 DOI: 10.1007/s12012-024-09904-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Accepted: 07/19/2024] [Indexed: 09/12/2024]
Abstract
The impact of metal exposure on cardiovascular diseases has become an increasingly concerning topic. To date, few studies have investigated the relationship between the copper-to-zinc ratio and CVD (Cardiovascular disease). This China multi-ethnic cohort study explored the association between the copper-to-zinc ratio and CVD in Chinese adults. The study included a sample size of 9878 people. Logistic regression analysis was used to examine the correlation between urinary copper, urinary zinc, and the copper-to-zinc ratio and CVD prevalence. Restricted cubic spline (RCS) analysis was used to investigate the potential dose-response relationships among copper-to-zinc ratio, urinary copper, urinary zinc, and CVD prevalence. In addition, the least absolute shrinkage and selection operator (LASSO) regression method was used to identify significant risk factors associated with CVD, leading to the development of a nomogram. The predictive performance of the nomogram model for CVD was assessed using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Compared with the copper-to-zinc ratio in Q1, the copper-to-zinc ratio in Q4 was associated with CVD after adjusting for all potential confounders (Model 3) (Q4, odds ratio [OR] 0.608, 95% confidence interval [CI] 0.416-0.889, P = 0.010). After adjusting for all potential confounders (Model 3), urinary copper levels in Q4 were associated with CVD (Q4, odds ratio [OR] 0.627, 95% confidence interval [CI] 0.436-0.902, P = 0.012). No significant difference was found between urinary zinc levels and CVD. The RCS showed a linear dose-response relationship between the copper-to-zinc ratio and CVD (P for overall = 0.01). The nomogram based on the influencing factors examined with LASSO showed good predictive power, and the AUC was 76.3% (95% CI 73.7-78.9%). Our results suggest that there is a significant linear negative correlation between the copper-to-zinc ratio and CVD in Chinese adults and that it has good predictive value for CVD.
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Affiliation(s)
- Yili Shen
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China
| | - Yuxin Hu
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China
| | - Leilei Liu
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China
| | - Jianqin Zhong
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China
| | - Yuxin Zhang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China
| | - Shenyan Wu
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China
| | - Cheng Chen
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China
| | - Feng Hong
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 561113, China.
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13
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Song M, Han Y, Zhao Y, Lv J, Yu C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Yang X, Yao W, Chen J, Chen Z, Genovese G, Terao C, Li L, Sun D. Association of autosomal mosaic chromosomal alterations with risk of bladder cancer in Chinese adults: a prospective cohort study. Cell Death Dis 2024; 15:706. [PMID: 39349436 PMCID: PMC11443067 DOI: 10.1038/s41419-024-07087-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 09/10/2024] [Accepted: 09/16/2024] [Indexed: 10/02/2024]
Abstract
Little is known about the prospective association between autosomal mosaic chromosomal alterations (mCAs), a group of large-scale somatic mutations on autosomes, and bladder cancer. Here we utilized data from 99,877 participants who were free of physician-diagnosed cancer at baseline (2004-2008) of the China Kadoorie Biobank to estimate the associations between autosomal mCAs and bladder cancer (ICD-10: C67). A total of 2874 autosomal mCAs events among 2612 carriers (2.6%) were detected. After a median follow-up of 12.4 years, we discovered that participants with all autosomal mCAs exhibited higher risks of bladder cancer, with a multivariable-adjusted hazard ratio (HR) (95% confidence interval [CI]) of 2.60 (1.44, 4.70). The estimate of such association was even stronger for mosaic loss events (HR [95% CI]: 6.68 [2.92, 15.30]), while it was not significant for CN-LOH events. Both expanded (cell fraction ≥10%) and non-expanded autosomal mCAs, as well as mosaic loss, were associated with increased risks of bladder cancer. Of interest, physical activity (PA) significantly modified the associations of autosomal mCAs and mosaic loss (Pinteraction = 0.038 and 0.012, respectively) with bladder cancer. The increased risks of bladder cancer were only observed with mCAs and mosaic loss among participants with a lower level of PA (HR [95% CI]: 5.11 [2.36, 11.09] and 16.30 [6.06, 43.81]), but not among participants with a higher level of PA. Our findings suggest that peripheral leukocyte autosomal mCAs may represent a novel risk factor for bladder cancer, and PA may serve as a potential intervention target for mCAs carriers.
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Affiliation(s)
- Mingyu Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yuting Han
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yuxuan Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Iona Y Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Robin G Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Huaidong Du
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Xiaoming Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Wei Yao
- NCDs Prevention and Control Department, Tongxiang CDC, Tongxiang, Zhejiang, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
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14
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Iona A, Bragg F, Fairhurst-Hunter Z, Millwood IY, Wright N, Lin K, Yang L, Du H, Chen Y, Pei P, Cheng L, Schmidt D, Avery D, Yu C, Lv J, Clarke R, Walters R, Li L, Parish S, Chen Z. Conventional and genetic associations of BMI with major vascular and non-vascular disease incidence and mortality in a relatively lean Chinese population: U-shaped relationship revisited. Int J Epidemiol 2024; 53:dyae125. [PMID: 39385593 PMCID: PMC11464668 DOI: 10.1093/ije/dyae125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 09/11/2024] [Indexed: 10/12/2024] Open
Abstract
BACKGROUND Higher body mass index (BMI) is associated with higher incidence of cardiovascular and some non-cardiovascular diseases (CVDs/non-CVDs). However, uncertainty remains about its associations with mortality, particularly at lower BMI levels. METHODS The prospective China Kadoorie Biobank recruited >512 000 adults aged 30-79 years in 2004-08 and genotyped a random subset of 76 000 participants. In conventional and Mendelian randomization (MR) analyses, Cox regression yielded adjusted hazard ratios (HRs) associating measured and genetically predicted BMI levels with incident risks of major vascular events (MVEs; conventional/MR 68 431/23 621), ischaemic heart disease (IHD; 50 698/12 177), ischaemic stroke (IS; 42 427/11 897) and intracerebral haemorrhage (ICH; 7644/4712), and with mortality risks of CVD (15 427/6781), non-CVD (26 915/4355) and all causes (42 342/6784), recorded during ∼12 years of follow-up. RESULTS Overall, the mean BMI was 23.8 (standard deviation: 3.2) kg/m2 and 13% had BMIs of <20 kg/m2. Measured and genetically predicted BMI showed positive log-linear associations with MVE, IHD and IS, but a shallower positive association with ICH in conventional analyses. Adjusted HRs per 5 kg/m2 higher genetically predicted BMI were 1.50 (95% CI 1.41-1.58), 1.49 (1.38-1.61), 1.42 (1.31-1.54) and 1.64 (1.58-1.69) for MVE, IHD, IS and ICH, respectively. These were stronger than associations in conventional analyses [1.21 (1.20-1.23), 1.28 (1.26-1.29), 1.31 (1.29-1.33) and 1.14 (1.10-1.18), respectively]. At BMIs of ≥20 kg/m2, there were stronger positive log-linear associations of BMI with CVD, non-CVD and all-cause mortality in MR than in conventional analyses. CONCLUSIONS Among relatively lean Chinese adults, higher genetically predicted BMI was associated with higher risks of incident CVDs. Excess mortality risks at lower BMI in conventional analyses are likely not causal and may reflect residual reverse causality.
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Affiliation(s)
- Andri Iona
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Fiona Bragg
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Health Data Research UK Oxford, University of Oxford, Oxford, UK
| | - Zammy Fairhurst-Hunter
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Neil Wright
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kuang Lin
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Liang Cheng
- Qingdao Shinan District Centre for Disease Control and Prevention, Shinan District, Qingdao, China
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Canqing Yu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Jun Lv
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Sarah Parish
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
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15
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Zhang Y, Sun Q, Yu C, Sun D, Pang Y, Pei P, Du H, Yang L, Chen Y, Yang X, Chen X, Chen J, Chen Z, Li L, Lv J. Associations of traditional cardiovascular risk factors with 15-year blood pressure change and trajectories in Chinese adults: a prospective cohort study. J Hypertens 2024; 42:1340-1349. [PMID: 38525868 PMCID: PMC7616121 DOI: 10.1097/hjh.0000000000003717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 01/12/2024] [Accepted: 02/13/2024] [Indexed: 03/26/2024]
Abstract
OBJECTIVE How traditional cardiovascular disease (CVD) risk factors are related to long-term blood pressure change (BPC) or trajectories remain unclear. We aimed to examine the independent associations of these factors with 15-year BPC and trajectories in Chinese adults. METHODS We included 15 985 participants who had attended three surveys, including 2004-2008 baseline survey, and 2013-2014 and 2020-2021 resurveys, over 15 years in the China Kadoorie Biobank (CKB). We measured systolic and diastolic blood pressure (SBP and DBP), height, weight, and waist circumference (WC). We asked about the sociodemographic characteristics and lifestyle factors, including smoking, alcohol drinking, intake of fresh vegetables, fruits, and red meat, and physical activity, using a structured questionnaire. We calculated standard deviation (SD), cumulative blood pressure (cumBP), coefficient of variation (CV), and average real variability (ARV) as long-term BPC proxies. We identified blood pressure trajectories using the latent class growth model. RESULTS Most baseline sociodemographic and lifestyle characteristics were associated with cumBP. After adjusting for other characteristics, the cumSBP (mmHg × year) increased by 116.9 [95% confidence interval (CI): 111.0, 122.7] for every 10 years of age. The differences of cumSBP in heavy drinkers of ≥60 g pure alcohol per day and former drinkers were 86.7 (60.7, 112.6) and 48.9 (23.1, 74.8) compared with less than weekly drinkers. The cumSBP in participants who ate red meat less than weekly was 29.4 (12.0, 46.8) higher than those who ate red meat daily. The corresponding differences of cumSBP were 127.8 (120.7, 134.9) and 70.2 (65.0, 75.3) for BMI per 5 kg/m 2 and WC per 10 cm. Most of the findings of other BPC measures by baseline characteristics were similar to the cumBP, but the differences between groups were somewhat weaker. Alcohol drinking was associated with several high-risk trajectories of SBP and DBP. Both BMI and WC were independently associated with all high-risk blood pressure trajectories. CONCLUSIONS Several traditional CVD risk factors were associated with unfavorable long-term BPC or blood pressure trajectories in Chinese adults.
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Affiliation(s)
- Yiqian Zhang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Qiufen Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Xiaoming Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | | | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University
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16
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Hua Y, Fan X, Yang M, Su J, Guo J, Jin J, Sun D, Pei P, Yu C, Lyu J, Tao R, Zhou J, Lu Y. Association between socioeconomic status and risk of chronic obstructive pulmonary disease in China: a prospective cohort study. BMC Public Health 2024; 24:2077. [PMID: 39085848 PMCID: PMC11292937 DOI: 10.1186/s12889-024-19490-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 07/15/2024] [Indexed: 08/02/2024] Open
Abstract
OBJECTIVE Socioeconomic status (SES) has been proven to be associated with chronic obstructive pulmonary disease (COPD) in Western populations, but the evidence is very limited in China. This study aimed to investigate the association between SES and the risk of COPD incident. METHODS This study was based on the China Kadoorie Biobank (CKB) project in Wuzhong District, Suzhou. A total of 45,484 adults aged 30-79 were included in the analysis during 2004-2008. We used Cox proportional hazard models to investigate the association between SES and the risk of COPD. Household income, education, private property and consumption potential was used to measure SES. Incident COPD cases were ascertained using hospitalization records, death certificates, and active follow-up. RESULTS A total of 524 COPD cases were identified during a median follow-up of 11.2 years. Household income was inversely associated with the risk of COPD (Ptrend<0.005). The adjusted hazard ratios (95% confidence intervals) for incident COPD were 0.88 (0.69-1.14), 0.77 (0.60-0.99), and 0.42 (0.31-0.57) for participants with annual household income of 10,000 ~ 19,999 yuan, 20,000 ~ 34,999 yuan and ≥ 35,000 yuan respectively, in comparison to participants with an annual household income < 10,000 yuan. Furthermore, we found that education level, refrigerator use, private toilet, private phone, and motor vehicle were adversely associated with COPD risk, while ownership of newly renovated flats was positively correlated with COPD incident. CONCLUSIONS This prospective study suggests that SES is associated with the risk of COPD in Chinese adults. Population-based COPD prevention strategies tailored for people with different SES could help reduce the burden of COPD in Chinese.
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Affiliation(s)
- Yujie Hua
- Department of Non-communicable Chronic Disease Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou, 215004, China
| | - Xikang Fan
- Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, Jiangsu, China
| | - Mengshi Yang
- Department of Epidemiology and Health Statistics, Southeast University, Nanjing, 210009, China
| | - Jian Su
- Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, Jiangsu, China
| | - Jia Guo
- Department of Non-communicable Chronic Disease Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou, 215004, China
| | - Jianrong Jin
- Wuzhong District Disease Control and Prevention Centre, Suzhou, 215000, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Jun Lyu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Ran Tao
- Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, Jiangsu, China
| | - Jinyi Zhou
- Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, Jiangsu, China.
| | - Yan Lu
- Department of Non-communicable Chronic Disease Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou, 215004, China.
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17
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Mossavarali S, Vaezi A, Heidari A, Shafiee A, Jalali A, Alaeddini F, Saadat S, Masoudkabir F, Hosseini K, Vasheghani-Farahani A, Sadeghian S, Boroumand M, Karimi A. Prevalence of insufficient physical activity among adult residents of Tehran: a cross-sectional report from Tehran Cohort Study (TeCS). BMC Public Health 2024; 24:1722. [PMID: 38937758 PMCID: PMC11212377 DOI: 10.1186/s12889-024-19201-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 06/19/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND Insufficient physical activity (PA) is a major risk factor for non-communicable diseases (NCDs) and one of the leading causes of premature mortality worldwide. This study examined the prevalence and independent determinants of insufficient PA among adults resident of Tehran utilizing Tehran Cohort Study Data (TeCS). METHOD We used the recruitment phase data from the TeCS with complete data on PA. PA was assessed through a Likert-scaled question and categorized into three groups. Utilizing data from the 2016 national census, the age- and sex-weighted prevalence of insufficient PA in Tehran was determined. The adjusted logistic regression model is used to neutralize influencing factors and determine the factors associated with insufficient PA. RESULT The weighted prevalence of insufficient PA was 16.9% among the 8213 adult citizens of Tehran, with a greater prevalence among females (19.0% vs. 14.8% among males). Additionally, older age groups, unemployed, housewives, and illiterate educated participants displayed a much higher prevalence of insufficient PA (p < 0.001). Moreover, Tehran's central and southern districts had higher rates of insufficient PA. Concerning the adjusted regression model, older age (Odds ratio [OR]: 4.26, 95% confidence interval [95% CI]: 3.24-5.60, p < 0.001), a lower education level (p < 0.001), unemployment (OR: 1.80, 95% CI: 1.28-2.55, p = 0.001), being a housewife (OR: 1.44, 95% CI: 1.15-1.80, p = 0.002), higher body mass index (BMI) (OR for BMI > 30: 1.85, 95% CI: 1.56-2.18, p < 0.001), opium consumption (OR: 1.92, 95% CI: 1.46-2.52, p < 0.001), diabetes mellitus (OR: 1.25, 95% CI: 1.06-1.48, p = 0.008), hypertension (OR: 1.29, 95% CI: 1.11-1.50, p = 0.001), and coronary artery diseases (OR: 1.30, 95% CI: 1.05-1.61, p = 0.018), were significantly associated with insufficient PA. CONCLUSIONS The identified associated factors serve as a valuable guide for policymakers in developing tailored intervention strategies to address the needs of high-risk populations, particularly among older adults and females.
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Affiliation(s)
- Shervin Mossavarali
- Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Vaezi
- Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Amirhossein Heidari
- Cardiac Primary Prevention Research Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
- Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Akbar Shafiee
- Cardiac Primary Prevention Research Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Arash Jalali
- Cardiac Primary Prevention Research Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran.
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
- Department of Cardiovascular Research, Tehran Heart Center, North Kargar Ave, Tehran, 1411713138, Iran.
| | - Farshid Alaeddini
- Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Soheil Saadat
- Department of Emergency Medicine, University of California, Irvine, CA, USA
| | - Farzad Masoudkabir
- Cardiac Primary Prevention Research Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Kaveh Hosseini
- Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Vasheghani-Farahani
- Cardiac Primary Prevention Research Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Saeed Sadeghian
- Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohamamdali Boroumand
- Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Abbasali Karimi
- Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
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18
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Yu B, Tang W, Fan Y, Ma C, Ye T, Cai C, Xie Y, Shi Y, Baima K, Yang T, Wang Y, Jia P, Yang S. Associations between residential greenness and obesity phenotypes among adults in Southwest China. Health Place 2024; 87:103236. [PMID: 38593578 DOI: 10.1016/j.healthplace.2024.103236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 02/27/2024] [Accepted: 03/21/2024] [Indexed: 04/11/2024]
Abstract
BACKGROUND Although exposure to greenness has generally benefited human metabolic health, the association between greenness exposure and metabolic obesity remains poorly studied. We aimed to investigate the associations between residential greenness and obesity phenotypes and the mediation effects of air pollutants and physical activity (PA) level on the associations. METHODS We used the baseline of the China Multi-Ethnic Cohort (CMEC) study, which enrolled 87,613 adults. Obesity phenotypes were defined based on obesity and metabolic status, including metabolically unhealthy obesity (MUO), non-obesity (MUNO), metabolically healthy obesity (MHO), and non-obesity (MHNO). Greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 500-m buffer zones around the participants' residence. Multivariable logistic regression was used to estimate the associations between greenness and obesity phenotypes. Stratified analyses by age, sex, educational level, and urbanicity were performed to identify how the effect varies across different subgroups. Causal mediation analysis was used to examine the mediation effects of air pollutants and PA level. RESULTS Compared with MHNO, each interquartile range (IQR) increase in greenness exposure was associated with reduced risks of MHO (ORNDVI [95% CI] = 0.87 [0.81, 0.93]; OREVI = 0.91 [0.86, 0.97]), MUO (ORNDVI = 0.83 [0.78, 0.88]; OREVI = 0.86 [0.81, 0.91]), and MUNO (ORNDVI = 0.88 [0.84, 0.91]; OREVI = 0.89 [0.86, 0.92]). For each IQR increase in both NDVI and EVI, the risks of MHO, MUO, and MUNO were reduced more in men, participants over 60 years, those with a higher level of education, and those living in urban areas, compared to their counterparts. Concentrations of particulate matter (PM) and PA level partially mediated the associations between greenness exposure and obesity phenotypes. CONCLUSIONS Exposure to residential greenness was associated with decreased risks of MHO, MUO, and MUNO, which was mediated by concentrations of PM and PA level, and modified by sex, age, educational level, and urbanicity.
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Affiliation(s)
- Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Yunzhe Fan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunlan Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tingting Ye
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Changwei Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yiming Xie
- Jianyang Center for Disease Control and Prevention, Jianyang, China
| | - Yuanyuan Shi
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Kangzhuo Baima
- High Altitude Health Science Research Center of Tibet University, Lhasa, Tibet, China
| | - Tingting Yang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Yanjiao Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China; Hubei Luojia Laboratory, Wuhan, China; School of Public Health, Wuhan University, Wuhan, China.
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China.
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19
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Li X, Lu Z, Liu T, Sun Y. Impact of home quarantine on physical fitness of school-aged children in Xi'an during COVID-19 lockdown: a cross-sectional study. BMC Public Health 2024; 24:1169. [PMID: 38664808 PMCID: PMC11047002 DOI: 10.1186/s12889-024-18607-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND The emergence of the COVID-19 pandemic has sparked unprecedented global challenges. This study intends to investigate changes in the physical fitness of students aged 6-22 during the COVID-19 pandemic and to assess how the pandemic lockdown period affected these markers. METHODS According to the National Student Physical Health Standard, a stratified cluster sampling method was used to evaluate the body shape, body function, and physical fitness of children and adolescents (n = 8092) in Xi'an from 2019 to 2021. This study uses SPSS 26.0 (IBM, Chicago, IL, USA) for data statistics and analysis. The connection between physical fitness and years was measured using the one-variable analysis in the general linear model (GLM). Independent t-tests were used to determine the sex (male/female) and area (urban/rural) differences. RESULTS During the lockdown period, Body Mass Index (BMI) and flexibility showed an upward trend, while aerobic, strength, speed, and endurance showed a downward trend. In addition to the BMI of middle and high school students, almost all indicators show significant sex differences. There are urban-rural differences in some indicators, such as chin-ups. CONCLUSION During the pandemic of COVID-19, the physical fitness of children and adolescents in Xi'an did not change significantly, and there were slight differences among different grades. During the pandemic lockdown period, lifestyle changes and reduced outdoor activities for children and adolescents may be the reasons for the changing trend of various indicators.
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Affiliation(s)
- Xinglu Li
- School of Physical Education, Shaanxi Normal University, Xi'an, 710119, China
| | - Zijun Lu
- School of Physical Education, Shaanxi Normal University, Xi'an, 710119, China
| | - Tao Liu
- School of Physical Education, Shaanxi Normal University, Xi'an, 710119, China
| | - Yuliang Sun
- School of Physical Education, Shaanxi Normal University, Xi'an, 710119, China.
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Wang W, Zhou H, Qi S, Yang H, Hong X. The association between physical activities combined with dietary habits and cardiovascular risk factors. Heliyon 2024; 10:e28845. [PMID: 38596005 PMCID: PMC11002288 DOI: 10.1016/j.heliyon.2024.e28845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 03/26/2024] [Accepted: 03/26/2024] [Indexed: 04/11/2024] Open
Abstract
Objectives The aim of this study was to investigate the association between physical activities combined with dietary habits and cardiovascular risk factors in adults from Nanjing, China. Methods The cross-sectional survey conducted in 2017 involved a sample of 60 283 individuals aged ≥18 years in Nanjing municipality, China. The sampling method used was multistage stratified cluster sampling. The primary outcomes from multivariate logistic regression analysis with adjusted potential confounders were the relationships between physical activities combined with dietary habits and cardiovascular risk variables. Relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S) were used to assess an additive interaction between dietary habits and physical activities. Results After adjusting potential confounders, cardiovascular risk factors were significantly associated with the association of physical inactivity and unhealthy diet, with the highest odds ratios (ORs) for low density lipoprotein-cholesterol (HLDL-c) (1.64, 95% CI [1.47, 1.84]) and hypertension (1.55, 95% CI [1.46, 1.64]). Additive interactions between physical inactivity and unhealthy diet were found in on cardiovascular risk factors of higher low-density lipoprotein-cholesterol (HLDL-c) (S, 2.57; 95% CI [1.27, 5.21]), type 2 diabetes (T2D) (S, 1.96; 95% CI [1.23, 3.13]), dyslipidemia (S, 1.69; 95% CI [1.08, 2.66]) and hypertension (S, 1.46; 95% CI [1.12, 1.89]). Their RERI was 0.39 (95% CI [0.18, 0.60]), 0.22 (95% CI [0.09, 0.35]), 0.11 (95% CI [0.03, 0.19]) and 0.17 (95% CI [0.06, 0.28]), respectively. OR of being HLDL-c, T2D, hypertension and dyslipidemia in participants of physical inactivity and unhealthy diet was 24%, 15%, 11% and 8.3%, respectively. Multiplicative interaction was detected in obesity, hypertension, T2D and HLDL-c. Conclusion An unhealthy diet and physical inactivity were strongly linked to cardiovascular risk factors. This study also showed that an unhealthy diet and physical inactivity combined to produce an additive effect on T2D, hypertension, HLDL-c, and dyslipidemia, suggesting a higher risk than the total of these factors, especially HLDL-c. Preventive strategies aimed at reducing cardiometabolic risks such as hypertension, T2D, HLDL-c, and dyslipidemia are necessary for targeting physical inactivity and unhealthy diet.
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Affiliation(s)
- Weiwei Wang
- Department of Non-communicable Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Hairong Zhou
- Department of Non-communicable Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Shengxiang Qi
- Department of Non-communicable Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Huafeng Yang
- Department of Non-communicable Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, China
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xin Hong
- Department of Non-communicable Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, China
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
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21
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Lu R, Qin Y, Xie C, Tan X, Zhu T, Tan J, Wang S, Liang J, Qin Z, Pan R, Pei P, Sun D, Su L, Lan J. Secondhand smoke exposure can increase the risk of first ischemic stroke: A 10.7-year prospective cohort study in China. Ann Epidemiol 2024; 92:25-34. [PMID: 38367798 DOI: 10.1016/j.annepidem.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 02/13/2024] [Accepted: 02/13/2024] [Indexed: 02/19/2024]
Abstract
INTRODUCTION Passive smoking is considered a major public health issue in China. Prospective evidence regarding the link between secondhand smoke (SHS) and ischemic stroke in China is scarce. METHODS The China Kadoorie Biobank (CKB) study in Liuzhou City recruited 50,174 participants during 2004-2008. Of these 30,456 never-smokers were included in our study. The median follow-up period was 10.7 years. The incidence of ischemic stroke was obtained through the China Disease Surveillance Points (DSP) system and the Health Insurance (HI) database. Cox proportional risk models were used to evaluate the association between SHS exposure and ischemic stroke. RESULTS During 320,678 person-years of follow-up, there were 2059 patients with ischemic stroke observed and the incidence of ischemic stroke was 6.42 per thousand person-years. Participants exposed to SHS daily faced a 21 % higher risk of ischemic stroke (HR = 1.21, 95 %CI: 1.09-1.34) compared to those exposed to SHS less than once a week. Subgroup analyses revealed that daily SHS exposure was linked to heightened risk of ischemic stroke among women, non-employed, and non-weekly tea drinkers. CONCLUSIONS Daily SHS exposure was associated with higher risks of ischemic stroke. Proactive tobacco control strategies are necessary to decrease the risk of ischemic stroke in never smokers.
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Affiliation(s)
- Rumei Lu
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Yulu Qin
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Changping Xie
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Xiaoping Tan
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Tingping Zhu
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Jinxue Tan
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Sisi Wang
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Jiajia Liang
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Zhongshu Qin
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Rong Pan
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Dianjianyi Sun
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China; Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing 100191, China
| | - Li Su
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China.
| | - Jian Lan
- Liuzhou Center for Disease Prevention and Control, Liuzhou, Guangxi Zhuang Autonomous Region 545007, China.
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22
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Zhang Y, Lv Q, Yin Y, Wang H, Bueber MA, Phillips MR, Li T. Research in China about the biological mechanisms that potentially link socioenvironmental changes and mental health: a scoping review. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2024; 45:100610. [PMID: 38699292 PMCID: PMC11064722 DOI: 10.1016/j.lanwpc.2022.100610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
China's rapid socioeconomic development since 1990 makes it a fitting location to summarise research about how biological changes associated with socioenvironmental changes affect population mental health and, thus, lay the groundwork for subsequent, more focused studies. An initial search identified 308 review articles in the international literature about biomarkers associated with 12 common mental health disorders. We then searched for studies conducted in China that assessed the association of the identified mental health related-biomarkers with socioenvironmental factors in English-language and Chinese-language databases. We located 1330 articles published between 1 January 1990 and 1 August 2021 that reported a total of 3567 associations between 56 specific biomarkers and 11 socioenvironmental factors: 3156 (88·5%) about six types of environmental pollution, 381 (10·7%) about four health-related behaviours (diet, physical inactivity, internet misuse, and other lifestyle factors), and 30 (0·8%) about socioeconomic inequity. Only 245 (18·4%) of the papers simultaneously considered the possible effect of the biomarkers on mental health conditions; moreover, most of these studies assessed biomarkers in animal models of mental disorders, not human subjects. Among the 245 papers, mental health conditions were linked with biomarkers of environmental pollution in 188 (76·7%), with biomarkers of health-related behaviours in 48 (19·6%), and with biomarkers of socioeconomic inequality in 9 (3·7%). The 604 biomarker-mental health condition associations reported (107 in human subjects and 497 in animal models) included 379 (62·7%) about cognitive functioning, 117 (19·4%) about anxiety, 56 (9·3%) about depression, 21 (3·5%) about neurodevelopmental conditions, and 31 (5·1%) about neurobehavioural symptoms. Improved understanding of the biological mechanisms linking socioenvironmental changes to community mental health will require expanding the range of socioenvironmental factors considered, including mental health outcomes in more of the studies about the association of biomarkers with socioenvironmental factors, and increasing the proportion of studies that assess mental health outcomes in humans.
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Affiliation(s)
- Yamin Zhang
- Department of Neurobiology and Affiliated Mental Health Center, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qiuyue Lv
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yubing Yin
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Han Wang
- West China School of Medicine, Chengdu, Sichuan, China
| | - Marlys Ann Bueber
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Michael Robert Phillips
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
- Departments of Psychiatry and Epidemiology, Columbia University, New York, NY, USA
| | - Tao Li
- Department of Neurobiology and Affiliated Mental Health Center, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang, China
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23
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Liao J, Hu M, Imm K, Holmes CJ, Zhu J, Cao C, Yang L. Association of daily sitting time and leisure-time physical activity with body fat among U.S. adults. JOURNAL OF SPORT AND HEALTH SCIENCE 2024; 13:195-203. [PMID: 36240998 PMCID: PMC10980870 DOI: 10.1016/j.jshs.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 07/21/2022] [Accepted: 08/25/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Prolonged sitting and reduced physical activity lead to low energy expenditures. However, little is known about the joint impact of daily sitting time and physical activity on body fat distribution. We investigated the independent and joint associations of daily sitting time and physical activity with body fat among adults. METHODS This was a cross-sectional analysis of U.S. nationally representative data from the National Health and Nutrition Examination Survey 2011-2018 among adults aged 20 years or older. Daily sitting time and leisure-time physical activity (LTPA) were self-reported using the Global Physical Activity Questionnaire. Body fat (total and trunk fat percentage) was determined via dual X-ray absorptiometry. RESULTS Among 10,808 adults, about 54.6% spent 6 h/day or more sitting; more than one-half reported no LTPA (inactive) or less than 150 min/week LTPA (insufficiently active) with only 43.3% reported 150 min/week or more LTPA (active) in the past week. After fully adjusting for sociodemographic data, lifestyle behaviors, and chronic conditions, prolonged sitting time and low levels of LTPA were associated with higher total and trunk fat percentages in both sexes. When stratifying by LTPA, the association between daily sitting time and body fat appeared to be stronger in those who were inactive/insufficiently active. In the joint analyses, inactive/insufficiently active adults who reported sitting more than 8 h/day had the highest total (female: 3.99% (95% confidence interval (95%CI): 3.09%-4.88%); male: 3.79% (95%CI: 2.75%-4.82%)) and trunk body fat percentages (female: 4.21% (95%CI: 3.09%-5.32%); male: 4.07% (95%CI: 2.95%-5.19%)) when compared with those who were active and sitting less than 4 h/day. CONCLUSION Prolonged daily sitting time was associated with increased body fat among U.S. adults. The higher body fat associated with 6 h/day sitting may not be offset by achieving recommended levels of physical activity.
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Affiliation(s)
- Jingwen Liao
- Guangdong Provincial Key Laboratory of Physical Activity and Health Promotion, Guangzhou Sport University, Guangzhou 510500, China; Scientific Research Center, Guangzhou Sport University, Guangzhou 510500, China.
| | - Min Hu
- Guangdong Provincial Key Laboratory of Physical Activity and Health Promotion, Guangzhou Sport University, Guangzhou 510500, China
| | - Kellie Imm
- Division of Epidemiology & Genetics, Department of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA
| | - Clifton J Holmes
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA; Center for Human Nutrition, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jie Zhu
- Department of Plastic and Reconstructive Surgery, Shanghai East Hospital, Tongji University, Shanghai 200070, China
| | - Chao Cao
- Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA; Center for Human Nutrition, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Lin Yang
- Department of Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary T2S 3C3, Canada; Department of Oncology and Community Health Sciences, University of Calgary, Calgary T2N 1N4, Canada
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HU SS. Influencing Factors on Cardiovascular Health in China. J Geriatr Cardiol 2024; 21:4-33. [PMID: 38440341 PMCID: PMC10908586 DOI: 10.26599/1671-5411.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024] Open
Abstract
The Annual Report on Cardiovascular Health and Diseases in China (2022) intricate landscape of cardiovascular health in China. This is the first section of the report, which dissects influential factors across diverse domains. The investigation identifies tobacco use as a paramount concern, portraying China as the global epicenter of tobacco consumption. Cigarette smoking, exacerbated by second-hand smoke exposure, emerges as a critical and preventable risk factor, contributing to a surge in attributable deaths over the past three decades. In the realm of dietary nutrition, the study discerns an overall improvement, yet discerns worrisome deviations, notably an escalating fat intake surpassing recommended guidelines. The shifting dietary structure reveals diminished consumption of cereals and vegetables juxtaposed with an uptick in animal foods, while excessive intake of cooking oil and salt persists, straying substantially from endorsed levels. The exploration of physical activity patterns unfolds a nuanced narrative. Varied trends are observed among students, with concerns arising from sedentary behaviors and inadequate adherence to recommended guidelines. The analysis spans a trajectory of declining physical activity in Chinese adults, coupled with an alarming surge in sedentary leisure time, ultimately linking these factors to heightened risks of cardiovascular diseases and increased adiposity. An examination of overweight and obesity trends uncovers a relentless upward trajectory, projecting substantial prevalence by 2030. Noteworthy prevalence rates underscore the imperative for targeted interventions to curtail this burgeoning health crisis, with the anticipated prevalence extending to nearly two-thirds of the adult population. Psychological factors, notably depression, constitute an integral facet of cardiovascular health. Prevalence rates among patients with coronary artery disease and acute myocardial infarction underscore the intricate interplay between mental health and cardiovascular outcomes. Additionally, persistent depressive symptoms are shown to significantly elevate the risk of cardiovascular diseases and mortality. This first section underscores the multifaceted challenges facing cardiovascular health in China, emphasizing the imperative for tailored interventions across tobacco control, dietary habits, physical activity, obesity management, and psychological well-being to mitigate the escalating burden of cardiovascular diseases in the population.
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Affiliation(s)
- Sheng-Shou HU
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
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25
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Li Y, Guo B, Meng Q, Yin L, Chen L, Wang X, Jiang Y, Wei J, Wang J, Xia J, Wang Z, Duoji Z, Li X, Nima Q, Zhao X. Associations of long-term exposure to air pollution and physical activity with the risk of systemic inflammation-induced multimorbidity in Chinese adults: results from the China multi-ethnic cohort study (CMEC). BMC Public Health 2023; 23:2556. [PMID: 38129832 PMCID: PMC10734128 DOI: 10.1186/s12889-023-17518-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 12/18/2023] [Indexed: 12/23/2023] Open
Abstract
OBJECTIVE Previous studies proved the effect of long-term exposure to air pollution or physical activity (PA) on the risk of systemic inflammation-induced multimorbidity (SIIM), while the evidence regarding their joint effects was rare, especially in low- and middle-income countries. Therefore, we aimed to examine the extent of interaction or joint relations of PA and air pollution with SIIM. METHODS This study included 72,172 participants from China Multi-Ethnic Cohort.The average concentrations of ambient particulate matter pollutants (PM1, PM2.5, and PM10) were estimated using satellite-based random forest models. Self-reported information on a range of physical activities related to occupation, housework, commuting, and leisure activities was collected by an interviewer-administered questionnaire. A total of 11 chronic inflammatory systemic diseases were assessed based on self-reported lifetime diagnosis or medical examinations. SIIM was defined as having ≥ 2 chronic diseases related to systemic inflammation. Logistic regression models were used to assess the complex associations of air pollution particulate matter and PA with SIIM. RESULTS We found positive associations between long-term air pollution particulates exposure and SIIM, with odds ratios (95%CI) of 1.07 (1.03 to 1.11), 1.18 (1.13 to 1.24), and 1.08 (1.05 to 1.12) per 10 µg/m3 increase in PM1, PM2.5, and PM10. No significant multiplicative interaction was found between ambient air pollutant exposure and PA on SIIM, whereas negative additive interaction was observed between long-term exposure to PM2.5 and PA on SIIM. The positive associations between low volume PA and SIIM were stronger among those exposed to high-level air pollution particulates. Compared with individuals engaged in high volume PA and exposed to low-level ambient air pollutants, those engaged in low volume PA and exposed to high-level ambient air pollutants had a higher risk of SIIM (OR = 1.49 in PM1 exposure, OR = 1.84 in PM2.5 exposure, OR = 1.19 in PM10 exposure). CONCLUSIONS Long-term (3 years average) exposure to PM1, PM2.5, and PM10 was associated with an increased risk of SIIM. The associations were modified by PA, highlighting PA's importance in reducing SIIM for all people, especially those living in high-level air pollution regions.
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Affiliation(s)
- Yajie Li
- Tibet Center for Disease Control and Prevention, 21 North linkuo Road, Lhasa, Tibet, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, 610041, Chengdu, China
| | - Qiong Meng
- School of Public Health, Kunming Medical University, Kunming, China
| | - Li Yin
- Meteorological Medical Research Center, Panzhihua Central Hospital, 617067, Panzhihua, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, China
- Dali University, Dali, China
| | - Lin Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, 610041, Chengdu, China
| | - Xing Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, 610041, Chengdu, China
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, 610041, Chengdu, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Junhua Wang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Jinjie Xia
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Zihao Wang
- Chongqing Center for disease Control and prevention, Chongqing, China
| | | | - Xianzhi Li
- Meteorological Medical Research Center, Panzhihua Central Hospital, 617067, Panzhihua, China.
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, China.
- Dali University, Dali, China.
| | - Qucuo Nima
- Tibet Center for Disease Control and Prevention, 21 North linkuo Road, Lhasa, Tibet, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, 610041, Chengdu, China.
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Sheng C, Zhang X, Liu B, Lynn HS, Chen K, Dai H. Interplay between oral health and lifestyle factors for cancer risk in rural and urban China: a population-based cohort study. JOURNAL OF THE NATIONAL CANCER CENTER 2023; 3:279-285. [PMID: 39036669 PMCID: PMC11256589 DOI: 10.1016/j.jncc.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 07/23/2024] Open
Abstract
Background Although poor oral health and several lifestyle factors have been found to be associated with cancer risk, their joint relationship has rarely been studied. Methods We prospectively examined the associations of oral health and healthy lifestyle factors with cancer risk among 0.5 million rural and urban residents from the China Kadoorie Biobank (2004-2015). Oral health status was assessed from self-reported baseline questionnaires. A healthy lifestyle index comprising non-smoking, non-drinking, ideal body shape, physical activity and healthy diet was calculated for each participant, and categorized into favorable, intermediate and unfavorable lifestyle behavior. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) relating oral health and healthy lifestyle index to cancer risk using Cox proportional hazards models. We estimated the population attributable risk percent (PAR%) and 95% CIs using multivariate models. Results During a median follow-up of 9 years, 23,805 new cancer cases were documented, with 52% from rural areas and 48% from urban areas. Compared with those with good oral health and favorable lifestyle, participants with poor oral health and unfavorable lifestyle had a higher risk of developing cancer in both rural (adjusted HR, 1.55 [95% CI, 1.39-1.74]; P for trend < 0.001) and urban areas (adjusted HR, 1.44 [95% CI, 1.24-1.67]; P for trend < 0.001). A significant multiplicative interaction between oral health and healthy lifestyle index on cancer risk was found in rural residents (P for interaction = 0.004) rather than in urban residents (P for interaction = 0.973). Assuming poor oral health as an additional risk factor, the PAR% of total cancer increased by 3.0% and 1.1% for participants with intermediate lifestyle and unfavorable lifestyle, respectively. Conclusions These findings suggest a joint effect of oral health and common lifestyle factors on cancer risk. Promotion of healthy lifestyle by integration of good oral health would be beneficial to consider in cancer prevention strategies.
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Affiliation(s)
- Chao Sheng
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Xi Zhang
- Clinical Research Unit, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ben Liu
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Henry S Lynn
- Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
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27
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Wang Z, Davey Smith G, Loos RJF, den Hoed M. Distilling causality between physical activity traits and obesity via Mendelian randomization. COMMUNICATIONS MEDICINE 2023; 3:173. [PMID: 38036650 PMCID: PMC10689836 DOI: 10.1038/s43856-023-00407-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 11/16/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND Whether obesity is a cause or consequence of low physical activity levels and more sedentary time has not yet been fully elucidated. Better instrumental variables and a more thorough consideration of potential confounding variables that may influence the causal inference between physical activity and obesity are needed. METHODS Leveraging results from our recent genome-wide association study for leisure time moderate-to-vigorous intensity (MV) physical activity and screen time, we here disentangle the causal relationships between physical activity, sedentary behavior, education-defined by years of schooling-and body mass index (BMI), using multiple univariable and multivariable Mendelian Randomization (MR) approaches. RESULTS Univariable MR analyses suggest bidirectional causal effects of physical activity and sedentary behavior with BMI. However, multivariable MR analyses that take years of schooling into account suggest that more MV physical activity causes a lower BMI, and a higher BMI causes more screen time, but not vice versa. In addition, more years of schooling causes higher levels of MV physical activity, less screen time, and lower BMI. CONCLUSIONS In conclusion, our results highlight the beneficial effect of education on improved health and suggest that a more physically active lifestyle leads to lower BMI, while sedentary behavior is a consequence of higher BMI.
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Affiliation(s)
- Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marcel den Hoed
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden.
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Huang DH, Zhang YX, Wang XB, Sun MH, Guo RH, Leng X, Du Q, Chen HY, Nan YX, Wu QJ, Pan BC, Zhao YH. Association between dietary total antioxidant capacity and semen quality among men attending an infertility clinic: a cross-sectional study. Hum Reprod Open 2023; 2023:hoad041. [PMID: 37954934 PMCID: PMC10639034 DOI: 10.1093/hropen/hoad041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/16/2023] [Indexed: 11/14/2023] Open
Abstract
STUDY QUESTION Is dietary non-enzymatic antioxidant capacity related to semen quality? SUMMARY ANSWER The only statistically significant association of semen quality parameters with dietary total antioxidant capacity (DTAC) detected was an inverse association between DTAC and ejaculate volume. WHAT IS KNOWN ALREADY Growing interest exists regarding the role of diet in influencing semen quality. While DTAC is linked to favorable health outcomes, its association with semen quality, especially among men attending infertility clinics, remains understudied. STUDY DESIGN SIZE DURATION This cross-sectional study was carried out between June and December of 2020. In total, 1715 participants were included in the final analysis. PARTICIPANTS/MATERIALS SETTING METHODS Men who attended an infertility clinic in China were enrolled. Experienced clinical technicians performed the semen analysis. The DTAC indices included the ferric-reducing ability of plasma, oxygen radical absorbance capacity, total reactive antioxidant potential, and Trolox equivalent antioxidant capacity. The quantile regression model was used for multivariate analysis. MAIN RESULTS AND THE ROLE OF CHANCE After adjustment for a variety of confounding variables, a significant inverse association was identified between DTAC and ejaculate volume (βcontinuous FRAP = -0.015, 95% CI = -0.023, -0.006, βT3 vs T1 = -0.193, 95% CI = -0.379, -0.006, Ptrend = 0.007; βcontinuous TRAP = -0.019, 95% CI = -0.041, 0.002, βT3 vs T1 = -0.291, 95% CI = -0.469, -0.112, Ptrend = 0.002). The majority of DTAC indices have no statistically significant association with semen quality parameters. LIMITATIONS REASONS FOR CAUTION We cannot infer causality because of the nature of the cross-sectional study design. The robustness of the conclusion may be compromised by the exactness of non-enzymatic antioxidant capacity estimation. WIDER IMPLICATIONS OF THE FINDINGS Our findings demonstrated no association between DTAC indices and semen quality parameters among men attending an infertility clinic, except for ejaculate volume. Even though our findings are mostly non-significant, they contribute novel knowledge to the field of study while also laying the groundwork for future well-designed studies. STUDY FUNDING/COMPETING INTERESTS This work was supported by the JieBangGuaShuai Project of Liaoning Province [grant number 2021JH1/10400050], the Clinical Research Cultivation Project of Shengjing Hospital [grant number M1590], and the Outstanding Scientific Fund of Shengjing Hospital [grant number M1150]. The sponsors had no role in study design, or in the collection, analysis, and interpretation of data, or in the writing of the report, or in the decision to submit the article for publication. There are no conflicts of interest to declare. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Dong-Hui Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
| | - Yi-Xiao Zhang
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiao-Bin Wang
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ming-Hui Sun
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
| | - Ren-Hao Guo
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xu Leng
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qiang Du
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hong-Yu Chen
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
| | - Yu-Xin Nan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
- NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), National Health Commission, Shenyang, China
| | - Bo-Chen Pan
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
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Yin R, Wang Y, Li Y, Lynn HS, Zhang Y, Jin X, Yan LL. Changes in physical activity and all-cause mortality in the oldest old population: Findings from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Prev Med 2023; 175:107721. [PMID: 37802195 DOI: 10.1016/j.ypmed.2023.107721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 10/08/2023]
Abstract
BACKGROUND Insufficient or decreasing physical activity is common in older adults. Most studies on physical activity changes and mortality were conducted in adults younger than 80 years old in developed countries. We aimed to investigate the relationship between changes in physical activity and longevity in the oldest old (80 years or older) population using the Chinese Longitudinal Healthy Longevity Survey. METHODS Participants aged 80 or older at baseline were categorized into four groups: 1) remaining physically inactive (n = 14,287), 2) remaining physically active (n = 5411), 3) shifting from being inactive to active (n = 1364), and 4) shifting from being active to inactive (n = 1401). We fitted accelerated failure time Weibull survival regression models, adjusting for baseline sociodemographics, lifestyle factors and disease status. We further examined whether the associations differed by subgroups. RESULTS A total of 15,707 participants died during follow-up (median duration of follow-up = 3.0 years). Compared with participants who remained physically inactive, those who remained active (fully adjusted event time ratio (ETR): 1.14, 95%CI: 1.11-1.17) or shifted from being inactive to active (fully adjusted ETR: 1.14, 95%CI: 1.08-1.20) had statistically significant longer survival time. No significant association was observed between remaining physically inactive and shifting from being active to inactive. Subgroup analyses showed consistent associations in nearly all strata. CONCLUSION Maintaining frequent physical activity or shifting from being physically inactive to active was consistently associated with longer survival time in the oldest old population. Our findings provide evidence for encouraging older adults to regularly engage in physical activity to gain longevity benefits.
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Affiliation(s)
- Ruoyu Yin
- Global Health Research Center, Duke Kunshan University, No. 8 Duke Avenue, Kunshan, Jiangsu, China; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
| | - Yinsu Wang
- Global Health Research Center, Duke Kunshan University, No. 8 Duke Avenue, Kunshan, Jiangsu, China.
| | - Yaxi Li
- Global Health Research Center, Duke Kunshan University, No. 8 Duke Avenue, Kunshan, Jiangsu, China; Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Henry S Lynn
- School of Public Health, Fudan University, Shanghai, China; School of Public Health, Xinjiang Medical University, Xinjiang, China.
| | - Yueqian Zhang
- Global Health Research Center, Duke Kunshan University, No. 8 Duke Avenue, Kunshan, Jiangsu, China.
| | - Xurui Jin
- MindRank AI Ltd., Hangzhou, Zhejiang 310000, China..
| | - Lijing L Yan
- Global Health Research Center, Duke Kunshan University, No. 8 Duke Avenue, Kunshan, Jiangsu, China; School of Public Health, Wuhan University, Wuhan, China; Duke Global Health Institute, Duke University, Durham, NC, USA; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; The George Institute for Global Health, China.
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Zhang Y, Xia Y, Chang Q, Ji C, Zhao Y, Zhang H. Exposure to ambient air pollution and metabolic kidney diseases: evidence from the Northeast China Biobank. Nephrol Dial Transplant 2023; 38:2222-2231. [PMID: 36866507 DOI: 10.1093/ndt/gfad042] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND At present, there is no epidemiological evidence of the association between metabolic kidney diseases (MKD) and exposure to air pollution. METHODS We investigated the association between exposure to long-term air pollution and the risk of developing MKD using samples from the Northeast China Biobank. RESULTS Data from 29 191 participants were analyzed. MKD prevalence was 3.23%. Every standard deviation increment in PM2.5 increased the risk of MKD [odds ratio (OR) = 1.37, 95% confidence interval (CI) 1.19-1.58), diabetic kidney disease (DKD) (OR = 2.03, 95% CI 1.52-2.73), hypertensive kidney disease (BKD) (OR = 1.31, 95% CI 1.11-1.56), hyperlipidemic kidney disease (PKD) (OR = 1.39, 95% CI 1.19-1.63) and obese kidney disease (OKD) (OR = 1.34, 95% CI 1.00-1.81). PM10 increased the risk of MKD (OR = 1.42, 95% CI 1.20-1.67), DKD (OR = 1.38, 95% CI 1.03-1.85), BKD (OR = 1.30, 95% CI 1.07-1.58) and PKD (OR = 1.50, 95% CI 1.26-1.80). Sulfur dioxide increased the risk of MKD (OR = 1.57, 95% CI 1.34-1.85), DKD (OR = 1.81, 95% CI 1.36-2.40), BKD (OR = 1.44, 95% CI 1.19-1.74) and PKD (OR = 1.72, 95% CI 1.44-2.04). Ozone decreased the risk of PKD (OR = 0.83, 95% CI 0.70-0.99). Age, ethnicity and air pollution interacted to affect the risk of MKD, BKD and PKD. Associations between air pollution and CKD or metabolic disease were weaker than those with MKD. The association between air pollution and MKD became stronger when compared with participants with non-metabolic disease. CONCLUSIONS Air pollution may cause MKD or facilitate the progression from metabolic disease to renal failure.
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Affiliation(s)
- Yixiao Zhang
- Department of Urology Surgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yang Xia
- Department of Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qing Chang
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical Universtiy, Shenyang, China
| | - Chao Ji
- Department of Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yuhong Zhao
- Department of Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical Universtiy, Shenyang, China
| | - Hehua Zhang
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical Universtiy, Shenyang, China
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Liu YY, Gong TT, Li YZ, Xu HL, Zheng G, Liu FH, Qin X, Xiao Q, Wu QJ, Huang DH, Gao S, Zhao YH. Association of pre-diagnosis specific color groups of fruit and vegetable intake with ovarian cancer survival: results from the ovarian cancer follow-up study (OOPS). Food Funct 2023; 14:8442-8452. [PMID: 37622277 DOI: 10.1039/d3fo01443f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
Background: The colors of fruits and vegetables (FV) reflect the presence of pigmented bioactive compounds. The evidence of pre-diagnosis specific FV color group intake contributing to ovarian cancer (OC) survival is limited and inconsistent. Methods: A prospective cohort study was conducted between 2015 and 2020 with 700 newly diagnosed OC patients. Pre-diagnosis dietary information was assessed by a validated food frequency questionnaire. We classified FV into five groups based on the color of their edible parts (e.g., green, red/purple, orange/yellow, white, and uncategorized groups). Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of specific color groups of FV before diagnosis with OC survival. Potential multiplicative and additive interactions were assessed. Results: 130 patients died during a median follow-up of 37.57 (interquartile: 24.77-50.20) months. We observed the improved survival with a higher pre-diagnosis intake of total FV (HRtertile 3 vs. tertile 1 = 0.63, 95%CI = 0.40-0.99), total vegetables (HRtertile 3 vs. tertile 1 = 0.57, 95%CI = 0.36-0.90), and red/purple FV (HRtertile 3 vs. tertile 1 = 0.52, 95%CI = 0.33-0.82). In addition, we observed significant dose-response relationships for per standard deviation increment between total vegetable intake (HR = 0.79, 95%CI = 0.65-0.96) and red/purple group intake (HR = 0.77, 95%CI = 0.60-0.99) before diagnosis with OC survival. Additionally, pre-diagnosis green FV intake was borderline associated with better OC survival (HRper standard deviation increment = 0.83; 95%CI = 0.69-1.00). In contrast, we did not observe significant associations between pre-diagnosis intake of total fruits, orange/yellow, white, and uncategorized groups and OC survival. Conclusion: Pre-diagnosis FV intake from various color groups, especially the green and red/purple ones, may improve OC survival. Further studies are needed to validate our findings.
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Affiliation(s)
- Yu-Yang Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
| | - Yi-Zi Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - He-Li Xu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Gang Zheng
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Fang-Hua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
| | - Qian Xiao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China
| | - Dong-Hui Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Shenyang, Liaoning, 110001, China.
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
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de Oliveira AB, Katzmarzyk PT, Dantas WS, Benseñor IJM, Goulart ADC, Ekelund U. Profile of leisure-time physical activity and sedentary behavior in adults in Brazil: a nationwide survey, 2019. EPIDEMIOLOGIA E SERVIÇOS DE SAÚDE 2023; 32:e2023168. [PMID: 37585879 PMCID: PMC10421589 DOI: 10.1590/s2237-96222023000200016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 06/06/2023] [Indexed: 08/18/2023] Open
Abstract
OBJECTIVES to estimate the prevalence of leisure-time physical activity and sedentary behavior in adults in Brazil. METHODS this was a cross-sectional, population-based study carried out in a sample of 88,531 Brazilians, using data from the 2019 National Health Survey; leisure-time physical activity (overall and aerobic exercise) was measured according to the World Health Organization guidelines; the weighted prevalence and respective 95% confidence intervals (95%CI) of physical activity, physical inactivity and sedentary behavior were estimated. RESULTS according to the selected sample, 26.4% (95%CI 25.9;27.1) of Brazilian adults were physically active, 14.0% (95%CI 13.5;14.4) were insufficiently physically active and 59.5% (95%CI 58.8;60.2) were physically inactive; sedentary behavior ≥ 6 hours was reported by 30.1% (95%CI 29.5;30.8) of the population; only 8.6% (95%CI 8.2;8.9) met the recommendations for muscle-strengthening activities. CONCLUSION most Brazilian adults were physically inactive and did not meet international recommendations for leisure-time physical activity and reduction in sedentary behavior.
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Affiliation(s)
- Arão Belitardo de Oliveira
- Centro de Pesquisa Clínica e Epidemiológica, Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil
| | - Peter T. Katzmarzyk
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Estados Unidos da América
| | - Wagner Silva Dantas
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Estados Unidos da América
| | | | | | - Ulf Ekelund
- Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Noruega
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Zhao JQ, Wang XB, Leng X, Wei YF, Huang DH, Lv JL, Du Q, Guo RH, Pan BC, Wu QJ, Zhao YH. Dietary fat and fatty acid consumptions and the odds of asthenozoospermia: a case-control study in China. Hum Reprod Open 2023; 2023:hoad030. [PMID: 37547665 PMCID: PMC10403433 DOI: 10.1093/hropen/hoad030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/09/2023] [Indexed: 08/08/2023] Open
Abstract
STUDY QUESTION Are dietary fat and fatty acid (FA) intakes related to the odds of asthenozoospermia? SUMMARY ANSWER Plant-based fat consumption was associated with decreased asthenozoospermia odds, while the consumption of animal-based monounsaturated fatty acid (MUFA) was positively related to asthenozoospermia odds. WHAT IS KNOWN ALREADY Dietary fat and FA are significant ingredients of a daily diet, which have been demonstrated to be correlated to the reproductive health of men. However, to date, evidence on fat and FA associations with the odds of asthenozoospermia is unclear. STUDY DESIGN SIZE DURATION The hospital-based case-control study was performed in an infertility clinic from June 2020 to December 2020. Briefly, 549 asthenozoospermia cases and 581 controls with normozoospermia were available for final analyses. PARTICIPANTS/MATERIALS SETTING METHODS We collected dietary data through a verified food frequency questionnaire of 110 food items. Asthenozoospermia cases were ascertained according to the World Health Organization guidelines. To investigate the correlations of dietary fat and FA consumptions with the odds of asthenozoospermia, we calculated the odds ratios (ORs) and corresponding 95% CIs through unconditional logistic regression models. MAIN RESULTS AND THE ROLE OF CHANCE Relative to the lowest tertile of consumption, the highest tertile of plant-based fat intake was inversely correlated to the odds of asthenozoospermia (OR = 0.68, 95% CI = 0.50-0.91), with a significant dose-response relation (OR = 0.85, 95% CI = 0.75-0.97, per standard deviation increment). Inversely, animal-based MUFA intake (OR = 1.49, 95% CI = 1.04-2.14) was significantly correlated to increased odds of asthenozoospermia, and an evident dose-response relation was also detected (OR = 1.24, 95% CI = 1.05-1.45, per standard deviation increment). Subgroup analyses showed similar patterns of associations to those of the primary results. Moreover, we observed significant interactions on both multiplicative and additive scales between animal-based MUFA and cigarette smoking. LIMITATIONS REASONS FOR CAUTION Selection bias and recall bias were unavoidable in any of the observational studies. As we failed to obtain the information of trans-fatty acid (TFA) consumption, the relation of TFA intake and asthenozoospermia odds was unclear. WIDER IMPLICATIONS OF THE FINDINGS This study indicated that different sources of fat and FAs might exert different effects on the etiology of asthenozoospermia, and cigarette smoking could exacerbate the adverse effect of high animal-based MUFA intake on asthenozoospermia. Our findings provide novel evidence pertaining to the fields of prevention of asthenozoospermia through decreasing animal-derived fat and FA consumptions and smoking cessation. STUDY FUNDING/COMPETING INTERESTS This work was supported by the JieBangGuaShuai Project of Liaoning Province, Natural Science Foundation of Liaoning Province, Clinical Research Cultivation Project of Shengjing Hospital, and Outstanding Scientific Fund of Shengjing Hospital. All authors have no conflict of interest to declare. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
| | | | - Xu Leng
- Center of Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Dong-Hui Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jia-Le Lv
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qiang Du
- Center of Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ren-Hao Guo
- Center of Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bo-Chen Pan
- Correspondence address. Center of Reproductive Medicine, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615; E-mail: (B.-C.P.); Department of Clinical Epidemiology, Clinical Research Center, Department of Obstetrics and Gynecology, NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615-13652; E-mail: (Q.-J.W.); Department of Clinical Epidemiology, Clinical Research Center, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615-13652; E-mail: (Y.-H.Z.)
| | - Qi-Jun Wu
- Correspondence address. Center of Reproductive Medicine, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615; E-mail: (B.-C.P.); Department of Clinical Epidemiology, Clinical Research Center, Department of Obstetrics and Gynecology, NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615-13652; E-mail: (Q.-J.W.); Department of Clinical Epidemiology, Clinical Research Center, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615-13652; E-mail: (Y.-H.Z.)
| | - Yu-Hong Zhao
- Correspondence address. Center of Reproductive Medicine, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615; E-mail: (B.-C.P.); Department of Clinical Epidemiology, Clinical Research Center, Department of Obstetrics and Gynecology, NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615-13652; E-mail: (Q.-J.W.); Department of Clinical Epidemiology, Clinical Research Center, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, China. Tel: +86-24-96615-13652; E-mail: (Y.-H.Z.)
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Zou Q, Su C, Du W, Ouyang Y, Wang H, Zhang B, Luo S, Tan T, Chen Y, Zhong X, Zhang H. The Mediation and Moderation Effect Association among Physical Activity, Body-Fat Percentage, Blood Pressure, and Serum Lipids among Chinese Adults: Findings from the China Health and Nutrition Surveys in 2015. Nutrients 2023; 15:3113. [PMID: 37513531 PMCID: PMC10383535 DOI: 10.3390/nu15143113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
Physical activity (PA) is of benefit and particularly important for cardiovascular disease risk factors as being sedentary becomes a lifestyle habit. Research into Chinese complex association among physical activity, body-fat percentage (BF%), blood pressure, and serum lipids is limited. The present study is based on an observational study among adults (>18 years old) residing in fifteen provinces in China. Data of 10,148 adult participants in the 2015 China Health and Nutrition Survey (CHNS) were analyzed. The simple mediation effect models with covariates were utilized to assess the association among PA and blood pressure or serum lipids, and BF% was played as a mediator. The serial multiple-mediator models with covariates were constructed to the further analysis of the relationship between PA and blood pressure, and BF% was the mediator 1 and blood lipids were the mediator 2. Based on the above hypothesis, the moderated mediation models with covariates were used to analyze the association among PA, BF%, and blood pressure; in addition, BF% was used as the mediator and blood lipids played as the moderator. In the simple mediation models, the model with a dependent variable was high-density lipoprotein cholesterol (HDL-C) or low-density lipoprotein cholesterol (LDL-C); BF% was played as the partly mediation effect and the proportion of contribution was 0.23 and 0.25, respectively. In the serial multiple-mediator models, blood lipids, as the second mediator, played the mediation effect; however, the effect was smaller than the BF%. In the moderated mediation model, blood lipids had the moderation effect as the moderator variable. HDL-C played a moderating role in the latter pathway of the "PA→BF%→SBP/DBP" mediation model, and LDL-C/TC played a moderating role in the direct effect of the "PA→BF%→DBP". In conclusion, BF% played a mediating role in the relationship between PA and blood pressure. HDL-C, LDL-C, and TC were more likely to act as moderating variables in the mediation model "PA→BF%→SBP/DBP". PA could directly and indirectly benefit to control the CVD risk factors simultaneously.
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Affiliation(s)
- Qinpei Zou
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
- School of Public Health, Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China
- Department of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing 400036, China
| | - Chang Su
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Wenwen Du
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Yifei Ouyang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Huijun Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Bing Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Shuquan Luo
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
| | - Tao Tan
- Chongqing Health Statistics Information Center, Chongqing 401120, China
| | - Yaokai Chen
- Department of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing 400036, China
| | - Xiaoni Zhong
- School of Public Health, Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China
| | - Huadong Zhang
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
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Zhao JQ, Lv JL, Wang XB, Wei YF, Guo RH, Leng X, Du Q, Huang DH, Wu QJ, Pan BC, Zhao YH. Phytochemical consumption and the risk of teratozoospermia: findings from a hospital-based case-control study in China. Hum Reprod Open 2023; 2023:hoad025. [PMID: 37346245 PMCID: PMC10279649 DOI: 10.1093/hropen/hoad025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 05/06/2023] [Indexed: 06/23/2023] Open
Abstract
STUDY QUESTION Are dietary phytochemicals associated with the risk of teratozoospermia? SUMMARY ANSWER Dietary intake of carotene, including total carotene, α-carotene, β-carotene as well as retinol equivalent, and lutein + zeaxanthin, were inversely correlated with the risk of teratozoospermia. WHAT IS KNOWN ALREADY Phytochemicals are natural plant derived bioactive compounds, which have been reported to be potentially associated with male reproductive health. To date, no study has investigated the association between phytochemical intake and the risk of teratozoospermia. STUDY DESIGN SIZE DURATION This hospital-based case-control study, which included 146 newly diagnosed teratozoospermia cases and 581 controls with normozoospermia from infertile couples, was conducted in a hospital-based infertility clinic in China, from June 2020 to December 2020. PARTICIPANTS/MATERIALS SETTING METHODS Dietary information was collected using a validated semi-quantitative 110-item food frequency questionnaire. Unconditional logistic regression was applied to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between phytochemical (i.e. phytosterol, carotene, flavonoid, isoflavone, anthocyanidin, lutein + zeaxanthin, and resveratrol) intake and the risk of teratozoospermia. MAIN RESULTS AND THE ROLE OF CHANCE We observed a decreased risk of teratozoospermia for the highest compared with the lowest tertile consumption of total carotene (OR = 0.40, 95% CI = 0.21-0.77), α-carotene (OR = 0.53, 95% CI = 0.30-0.93), β-carotene (OR = 0.47, 95% CI = 0.25-0.88), retinol equivalent (OR = 0.47, 95% CI = 0.24-0.90), and lutein + zeaxanthin (OR = 0.35, 95% CI = 0.19-0.66), with all of the associations showing evident linear trends (all P trend <0.05). In addition, significant dose-response associations were observed between campestanol and α-carotene consumption and the risk of teratozoospermia. Moreover, there was a significant multiplicative interaction between BMI and lutein + zeaxanthin intake (P interaction <0.05). LIMITATIONS REASONS FOR CAUTION The cases and controls were not a random sample of the entire target population, which could lead to admission rate bias. Nevertheless, the controls were enrolled from the same infertility clinic, which could reduce the bias caused by selection and increase the comparability. Furthermore, our study only included a Chinese population, therefore caution is required regarding generalization of our findings to other populations. WIDER IMPLICATIONS OF THE FINDINGS Dietary phytochemicals, namely carotene, lutein, and zeaxanthin, might exert a positive effect on teratozoospermia. These phytochemicals are common in the daily diet and dietary supplements, and thus may provide a preventive intervention for teratozoospermia. STUDY FUNDING/COMPETING INTERESTS This study was funded by Natural Science Foundation of Liaoning Province (No. 2022-MS-219 to X.B.W.), Outstanding Scientific Fund of Shengjing Hospital (No. M1150 to Q.J.W.), Clinical Research Cultivation Project of Shengjing Hospital (No. M0071 to B.C.P.), and JieBangGuaShuai Project of Liaoning Province (No. 2021JH1/1040050 to Y.H.Z.). All authors declared that there was no conflict of interest. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
| | | | - Xiao-Bin Wang
- Correspondence address. Center for Reproductive Medicine, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615; E-mail: (X.-B.W.); Department of Clinical Epidemiology, Clinical Research Center, Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Department of Obstetrics and Gynecology, NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615-13652; E-mail: (Q.-J.W.); Department of Clinical Epidemiology, Clinical Research Center, Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615; E-mail: (Y.-H.Z.)
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ren-Hao Guo
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xu Leng
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qiang Du
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Dong-Hui Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qi-Jun Wu
- Correspondence address. Center for Reproductive Medicine, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615; E-mail: (X.-B.W.); Department of Clinical Epidemiology, Clinical Research Center, Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Department of Obstetrics and Gynecology, NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615-13652; E-mail: (Q.-J.W.); Department of Clinical Epidemiology, Clinical Research Center, Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615; E-mail: (Y.-H.Z.)
| | - Bo-Chen Pan
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Hong Zhao
- Correspondence address. Center for Reproductive Medicine, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615; E-mail: (X.-B.W.); Department of Clinical Epidemiology, Clinical Research Center, Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Department of Obstetrics and Gynecology, NHC Key Laboratory of Advanced Reproductive Medicine and Fertility (China Medical University), Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615-13652; E-mail: (Q.-J.W.); Department of Clinical Epidemiology, Clinical Research Center, Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning 110004, P. R. China. Tel: +86-24-96615; E-mail: (Y.-H.Z.)
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Xie Z, Guo X, Han L, Wang X, Yan Q, Shu C, Fan Z, Zhao M. Differences in primary and secondary stroke prevention strategies for Chinese men and women. Prev Med Rep 2023; 33:102219. [PMID: 37223569 PMCID: PMC10201908 DOI: 10.1016/j.pmedr.2023.102219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 03/17/2023] [Accepted: 04/23/2023] [Indexed: 05/25/2023] Open
Abstract
This study aimed to explore whether stroke prevention strategies differ for men and women. Data used were from China Kadoorie Biobank. According to the China-PAR Project model, a predicted 10-year stroke risk of ≥7% is defined as a high stroke risk. The effects of risk factor control and medication use as primary and secondary stroke prevention strategies were assessed, respectively. Logistic regression models were used to assess the sex-specific differences in the primary and secondary stroke prevention practices. Of the 512,715 participants (59.0% women), 218,972 (57.4% women) had a high risk of stroke and 8884 (44.7% women) had an established stroke. Of high-risk participants, women were considerably less likely than men to receive antiplatelets (odds ratio [OR], 0.80; [95% confidence interval, CI, 0.72-0.89]), antihypertensives (0.46[0.44-0.48]), and antidiabetics (0.65[0.60-0.70]). Meanwhile, stroke women were significantly less likely to receive antiplatelets (0.75[0.65-0.85]) but more likely to receive antidiabetics (1.56 [1.34-1.82]) than their male counterparts. Besides, differences were found in risk factor control between women and men. Sex-specific differences in stroke prevention strategies are prevalent in China. Effective prevention requires the implementation of better overall nationwide strategies and special emphasis on women.
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Affiliation(s)
- Zenghua Xie
- Department of Neurology, Beilun District People’s Hospital, Ningbo, Zhejiang, China
| | - Xu Guo
- Department of Rehabilitation Medicine, Hwa Mei Hospital, University of the Chinese Academy of Sciences, Ningbo, Zhejiang, China
| | - Liyuan Han
- Hwa Mei Hospital, Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, University of Chinese Academy of Sciences, Ningbo, Zhejiang, China
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, Zhejiang, China
| | - Xin Wang
- Department of Neurology, Beilun District People’s Hospital, Ningbo, Zhejiang, China
| | - Qianqian Yan
- Hwa Mei Hospital, Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, University of Chinese Academy of Sciences, Ningbo, Zhejiang, China
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, Zhejiang, China
| | - Chang Shu
- Tianjin Cerebral Vascular and Neural Degenerative Disease Key Laboratory, Tianjin Neurosurgery Institute, Tianjin Huanhu Hospital, Tianjin, China
| | - Zhenyi Fan
- Department of Neurology, Hwa Mei Hospital, University of Chinese Academy of Science, Ningbo, Zhejiang, China
| | - Miaomiao Zhao
- Department of Health Management, School of Public Health, Nantong University, Nantong, Jiangsu, China
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Li YZ, Huang SH, Shi S, Chen WX, Wei YF, Zou BJ, Yao W, Zhou L, Liu FH, Gao S, Yan S, Qin X, Zhao YH, Chen RJ, Gong TT, Wu QJ. Association of long-term particulate matter exposure with all-cause mortality among patients with ovarian cancer: A prospective cohort. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 884:163748. [PMID: 37120017 DOI: 10.1016/j.scitotenv.2023.163748] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/19/2023] [Accepted: 04/22/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND Evidence of the association between particles with a diameter of 2.5 μm or less (PM2.5) in long term and ovarian cancer (OC) mortality is limited. METHODS This prospective cohort study analyzed data collected between 2015 and 2020 from 610 newly diagnosed OC patients, aged 18-79 years. The residential average PM2.5 concentrations 10 years before the date of OC diagnosis were assessed by random forest models at a 1 km × 1 km resolution. Cox proportional hazard models fully adjusted for the covariates (including age at diagnosis, education, physical activity, kitchen ventilation, FIGO stage, and comorbidities) and distributed lag non-linear models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) of PM2.5 and all-cause mortality of OC. RESULTS During a median follow-up of 37.6 months (interquartile: 24.8-50.5 months), 118 (19.34 %) deaths were confirmed among 610 OC patients. One-year PM2.5 exposure levels before OC diagnosis was significantly associated with an increase in all-cause mortality among OC patients (single-pollutant model: HR = 1.22, 95 % CI: 1.02-1.46; multi-pollutant models: HR = 1.38, 95 % CI: 1.10-1.72). Furthermore, during 1 to 10 years prior to diagnosis, the lag-specific effect of long-term PM2.5 exposure on the all-cause mortality of OC had a risk increase for lag 1-6 years, and the exposure-response relationship was linear. Of note, significant interactions between several immunological indicators as well as solid fuel use for cooking and ambient PM2.5 concentrations were observed. CONCLUSION Higher ambient PM2.5 concentrations were associated with an increased risk of all-cause mortality among OC patients, and there was a lag effect in long-term PM2.5 exposure.
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Affiliation(s)
- Yi-Zi Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shu-Hong Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Wen-Xiao Chen
- Department of Sports Medicine and Joint Surgery, The People's Hospital of Liaoning Province, Shenyang, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bing-Jie Zou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Wei Yao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lu Zhou
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Fang-Hua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shi Yan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ren-Jie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China.
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Pan C, Sun X, Song J, Yu C, Guo Y, Wang S, Gao R, Ning F, Pang Z, Chen Z, Li L. The Prospective Associations of Egg Consumption with the Risk of Total Cerebrovascular Disease Morbidity among Chinese Adults. Nutrients 2023; 15:nu15081808. [PMID: 37111029 PMCID: PMC10142563 DOI: 10.3390/nu15081808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 04/02/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
BACKGROUND Studies investigating the relationship between egg consumption and the risk of cerebrovascular disease (CED) have yielded inconsistent results. This study evaluated the association between egg consumption and the risk of CED among Chinese adults. METHODS Data were obtained from China Kadoorie Biobank, Qingdao. A computerised questionnaire was used to collect information regarding egg consumption frequency. CED events were tracked through linkage with the Disease Surveillance Point System and the new national health insurance databases. Cox proportional hazards regression analyses were used to evaluate associations between egg consumption and CED risk controlling for potential confounders. RESULTS After a median follow-up of 9.2 years, 865 and 1083 CED events among men and women, respectively, were documented. More than 50% of participants consumed eggs daily with an average age of 52.0 (10.4) years at baseline. No association between egg consumption and CED were identified in the whole cohort and women. However, a 28% lower risk of CED was observed in those who consumed eggs at a higher frequency (HR = 0.72, 95% CI: 0.55-0.95) and a significant trend for the association (p for trend = 0.012) in a multivariable model in men. CONCLUSION Higher frequency of egg consumption was associated with a lower risk of total CED events among men but not women in Chinese adults. The beneficial effect on women warrants further investigations.
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Affiliation(s)
- Chi Pan
- School of Public Health, Qingdao University, Qingdao 266071, China
| | - Xiaohui Sun
- Qingdao Municipality Center for Disease Control and Prevention, Qingdao 266033, China
- Qingdao Institute of Preventive Medicine, Qingdao 266033, China
| | - Jiahui Song
- School of Public Health, Qingdao University, Qingdao 266071, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Shaojie Wang
- Qingdao Municipality Center for Disease Control and Prevention, Qingdao 266033, China
- Qingdao Institute of Preventive Medicine, Qingdao 266033, China
| | - Ruqin Gao
- School of Public Health, Qingdao University, Qingdao 266071, China
| | - Feng Ning
- Qingdao Municipality Center for Disease Control and Prevention, Qingdao 266033, China
- Qingdao Institute of Preventive Medicine, Qingdao 266033, China
| | - Zengchang Pang
- Qingdao Municipality Center for Disease Control and Prevention, Qingdao 266033, China
- Qingdao Institute of Preventive Medicine, Qingdao 266033, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
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Huang D, Zhang Y, Wang X, Guo R, Leng X, Du Q, Wu Q, Pan B, Zhao Y. Dietary total antioxidant capacity and the risk of developing asthenozoospermia: a hospital-based case-control study in China. Hum Reprod 2023; 38:537-548. [PMID: 36728412 DOI: 10.1093/humrep/dead010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/06/2023] [Indexed: 02/03/2023] Open
Abstract
STUDY QUESTION Is dietary total antioxidant capacity (DTAC) associated with the odds of developing asthenozoospermia in Chinese men? SUMMARY ANSWER There is no statistically significant association between DTAC indices and the odds of developing asthenozoospermia. WHAT IS KNOWN ALREADY Both diet and oxidative stress may be related to sperm quality; however, few studies have investigated the association between DTAC and sperm quality. STUDY DESIGN, SIZE, DURATION This case-control study was conducted from June 2020 to December 2020. Those diagnosed with asthenozoospermia were assigned to the case group, whereas those with normal sperm parameters were assigned to the control group. Data from a total of 553 cases and 586 controls were included in the final analysis. PARTICIPANTS/MATERIALS, SETTING, METHODS Men who had been referred to the infertility clinic of Shengjing Hospital of China Medical University were enrolled. Dietary intake was assessed using a validated food frequency questionnaire. DTAC was based on ferric-reducing ability of plasma (FRAP), total oxygen radical absorbance capacity (T-ORAC), hydrophilic oxygen radical absorbance capacity (H-ORAC), lipophilic oxygen radical absorbance capacity (L-ORAC), total phenolics (TP), total radical-trapping antioxidant parameter (TRAP), and Trolox equivalent antioxidant capacity (TEAC). Asthenozoospermia was defined according to the criteria published in the fifth edition of the World Health Organization laboratory manual for the examination and processing of human semen. MAIN RESULTS AND THE ROLE OF CHANCE No significant association was observed between the DTAC indices and the odds of asthenozoospermia after multivariable adjustment (T3 vs T1, odds ratio (OR) = 0.99, 95% CI: 0.73-1.33 for FRAP; OR = 1.05, 95% CI: 0.77-1.42 for T-ORAC; OR = 0.88, 95% CI: 0.65-1.18 for H-ORAC; OR = 0.98, 95% CI: 0.71-1.34 for L-ORAC; OR = 1.03, 95% CI: 0.76-1.39 for TP; OR = 1.18, 95% CI: 0.87-1.59 for TRAP; and OR = 1.15, 95% CI: 0.85-1.55 for TEAC). Both additive and multiplicative interaction analyses suggested that smoking might modify the association of T-ORAC with the odds of developing asthenozoospermia (relative excess risk due to interaction = 0.45, 95% CI: 0.07-0.83, attributable proportion due to interaction = 0.46, 95% CI: 0.07-0.84 for additive interaction; P = 0.033 for multiplicative interaction). LIMITATIONS, REASONS FOR CAUTION Recall bias and protopathic bias were inevitable in this retrospective case-control study. The estimation accuracy of the DTAC indices may have also affected the findings. WIDER IMPLICATIONS OF THE FINDINGS To the best of our knowledge, this is the first study to specifically investigate whether an association exists between DTAC and the odds of developing asthenozoospermia. Although no significant association was found, this study provides novel information pertaining to the fields of nutrition and human reproduction. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by the JieBangGuaShuai Project of Liaoning Province (2021JH1/10400050), the Shengjing Hospital Clinical Research Project (M0071), and the Outstanding Scientific Fund of Shengjing Hospital (M1150). All authors have no competing interests to disclose. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Donghui Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
| | - Yixiao Zhang
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xiaobin Wang
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Renhao Guo
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xu Leng
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qiang Du
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qijun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
- Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China
| | - Bochen Pan
- Center for Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yuhong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning, China
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Sun D, Liu C, Ding Y, Yu C, Guo Y, Sun D, Pang Y, Pei P, Du H, Yang L, Chen Y, Meng X, Liu Y, Liu J, Sohoni R, Sansome G, Chen J, Chen Z, Lv J, Kan H, Li L. Long-term exposure to ambient PM 2·5, active commuting, and farming activity and cardiovascular disease risk in adults in China: a prospective cohort study. Lancet Planet Health 2023; 7:e304-e312. [PMID: 37019571 PMCID: PMC10104773 DOI: 10.1016/s2542-5196(23)00047-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/12/2023] [Accepted: 02/15/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Increased physical activity is associated with a reduced risk of cardiovascular disease, but outdoor physical activity can be accompanied by increased inhalation of fine particulate matter (PM2·5). The extent to which long-term exposure to PM2·5 can offset the cardiovascular benefits of physical activity is unknown. We aimed to evaluate whether the associations between active commuting or farming activity and incident risks of cerebrovascular disease and ischaemic heart disease were consistent between populations with different ambient PM2·5 exposures. METHODS We did a prospective cohort study using data from people aged 30-79 years without cardiovascular disease at baseline from the China Kadoorie Biobank (CKB). Active commuting and farming activity were assessed at baseline using questionnaires. A high-resolution (1 × 1 km) satellite-based model was used to estimate annual average PM2·5 exposure during the study period. Participants were stratified according to PM2·5 exposure (54 μg/m3 or greater vs less than 54 μg/m3). Hazard ratios (HRs) and 95% CIs for incident cerebrovascular disease and ischaemic heart disease by active commuting and farming activity were estimated using Cox proportional hazard models. Effect modifications by PM2·5 exposure were tested by likelihood ratio tests. Analyses were restricted to the period from Jan 1, 2005, to Dec 31, 2017. FINDINGS Between June 25, 2004, and July 15, 2008, 512 725 people were enrolled in the CKB cohort. 322 399 eligible participants completed the baseline survey and were included in the analysis of active commuting (118 274 non-farmers and 204 125 farmers). Among 204 125 farmers, 2985 reported no farming time and 201 140 were included in the farming activity analysis. During a median follow-up of 11 years, 39 514 cerebrovascular disease cases and 22 313 ischaemic heart disease cases were newly identified. Among non-farmers with exposure to annual average PM2·5 concentrations of less than 54 μg/m3, increased active commuting was associated with lower risks of cerebrovascular disease (highest active commuting vs lowest active commuting HR 0·70, 95% CI 0·65-0·76) and ischaemic heart disease (0·60, 0·54-0·66). However, among non-farmers with exposure to annual average PM2·5 concentrations of 54 μg/m3 or greater, there was no association between active commuting and cerebrovascular disease or ischaemic heart disease. Among farmers with exposure to annual average PM2·5 concentrations of less than 54 μg/m3, increased active commuting (highest active commuting vs lowest active commuting HR 0·77, 95% CI 0·63-0·93) and increased farming activity (highest activity vs lowest activity HR 0·85, 95% CI 0·79-0·92) were both associated with a lower cerebrovascular disease risk. However, among farmers with exposure to annual average PM2·5 concentrations of 54 μg/m3 or greater, increases in active commuting (highest active commuting vs lowest active commuting HR 1·12, 95% CI 1·05-1·19) and farming activity (highest activity vs lowest activity HR 1·18, 95% CI 1·09-1·28) were associated with an elevated cerebrovascular disease risk. The above associations differed significantly between PM2·5 strata (all interaction p values <0·0001). INTERPRETATION For participants with long-term exposure to higher ambient PM2·5 concentrations, the cardiovascular benefits of active commuting and farming activity were significantly attenuated. Higher levels of active commuting and farming activity even increased the cerebrovascular disease risk among farmers with exposure to annual average PM2·5 concentrations of 54 μg/m3 or greater. FUNDING National Natural Science Foundation of China, National Key Research and Development Program of China, Kadoorie Charitable Foundation, UK Wellcome Trust.
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Affiliation(s)
- Dong Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC 12 Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and 13 Governance on Weather or Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yinqi Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Pei Pei
- Chinese Academy of Medical Sciences, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC 12 Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and 13 Governance on Weather or Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jiben Liu
- Prevention and Health Department, Yongqinglu Community Health Service, Qingdao, China
| | - Rajani Sohoni
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Gary Sansome
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China.
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC 12 Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and 13 Governance on Weather or Climate Extremes Impact and Public Health, Fudan University, Shanghai, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China.
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Sun Q, Sun D, Yu C, Guo Y, Sun D, Pei P, Yang L, Chen Y, Du H, Schmidt D, Stevens R, Kang K, Chen J, Chen Z, Li L, Lv J. Impacts of solid fuel use versus smoking on life expectancy at age 30 years in the rural and urban Chinese population: a prospective cohort study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 32:100705. [PMID: 36824348 PMCID: PMC9942113 DOI: 10.1016/j.lanwpc.2023.100705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 12/21/2022] [Accepted: 01/19/2023] [Indexed: 02/15/2023]
Abstract
Background The impact of solid fuel use on life expectancy (LE) in less-developed countries remains unclear. We aimed to evaluate the potential impact of household solid fuel use on LE in the rural and urban Chinese population, with the effect of smoking as a reference. Methods We used data from China Kadoorie Biobank (CKB) of 484,915 participants aged 30-79 free of coronary heart disease, stroke, or cancer at baseline. Analyses were performed separately for solid fuel use for cooking, solid fuel use for heating, and smoking, with participants exposed to the other two sources excluded. Solid fuels refer to coal and wood, and clean fuels refer to electricity, gas, and central heating. We used a flexible parametric Royston-Parmar model to estimate hazard ratios of all-cause mortality and predict LE at age 30. Findings Totally, 185,077, 95,228, and 230,995 participants were included in cooking-, heating-, and smoking-related analyses, respectively. During a median follow-up of approximately 12.1 years, 12,725, 7,531, and 18,878 deaths were recorded in the respective analysis. Compared with clean fuel users who reported cooking with ventilation, participants who used solid fuels with ventilation and without ventilation had a difference in LE (95% confidence interval [CI]) at age 30 of -1.72 (-2.88, -0.57) and -2.62 (-4.16, -1.05) years for men and -1.33 (-1.85, -0.81) and -1.35 (-2.02, -0.67) years for women, respectively. The difference in LE (95% CI) for heating was -2.23 (-3.51, -0.95) years for men and -1.28 (-2.08, -0.48) years for women. In rural men, the LE reduction (95% CI) related to solid fuel use for cooking (-2.55; -4.51, -0.58) or heating (-3.26; -6.09, 0.44) was more than that related to smoking (-1.71; -2.54, -0.89). Conversely, in urban men, the LE reduction (95% CI) related to smoking (-3.06; -3.56, -2.56) was more than that related to solid fuel use for cooking (-1.28; -2.61, 0.05) and heating (-1.90; -3.16, -0.65). Similar results were observed in women but with a smaller magnitude. Interpretation In this Chinese population, the harm to LE from household use of solid fuels was greater than that from smoking in rural residents. Conversely, the negative impact of smoking was greater than solid fuel use in urban residents. Our findings highlight the complexity and diversity of the factors affecting LE in less-developed populations. Funding National Natural Science Foundation of China, National Key R&D Program of China, Kadoorie Charitable Foundation, UK Wellcome Trust.
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Affiliation(s)
- Qiufen Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Dong Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Rebecca Stevens
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Kai Kang
- NCDs Prevention and Control Department, Henan CDC, Zhengzhou, Henan, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - China Kadoorie Biobank Collaborative Grouph
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
- NCDs Prevention and Control Department, Henan CDC, Zhengzhou, Henan, China
- China National Center for Food Safety Risk Assessment, Beijing, China
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Yu K, Lv J, Liu G, Yu C, Guo Y, Yang L, Chen Y, Wang C, Chen Z, Li L, Wu T. Cooking and future risk of all-cause and cardiopulmonary mortality. Nat Hum Behav 2023; 7:200-210. [PMID: 36482078 DOI: 10.1038/s41562-022-01486-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 10/24/2022] [Indexed: 12/14/2022]
Abstract
Cooking is practiced worldwide and is associated with multiple social, economic and environmental factors; thus, understanding cooking-related health effects would have broad public health implications. Here, we show that after an average 9.9 years of follow-up for 510,106 Chinese adults, always cooking with clean fuels was associated with lower risks of all-cause (0.90 [95% confidence interval 0.87-0.93]; P = 1.39 × 10-9), cardiovascular (0.83 [0.78-0.87]; P = 6.83 × 10-11) and respiratory (0.88 [0.79-0.99]; P = 0.026) mortality compared with non-cooking, of which 50.1% (14.5-85.6%) to 66.0% (38.5-85.8%) could be attributed to increased household physical activity. The mortality risks decreased with extended duration of cooking with clean fuels in dose-response manners, with the lowest hazard ratios of 0.74 (0.68-0.80; P = 1.20 × 10-13) for all-cause and 0.62 (0.55-0.71; P = 3.15 × 10-12) for cardiovascular mortality among never-smokers reported over 25 years of cooking. Our findings suggest lower future mortality risks may be gained only when cooking with clean fuels.
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Affiliation(s)
- Kuai Yu
- Department of Occupational and Environmental Health and Department of Epidemiology and Biostatistics, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing, China
| | - Ling Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
| | - Tangchun Wu
- Department of Occupational and Environmental Health and Department of Epidemiology and Biostatistics, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Zhao JQ, Ma QP, Wei YF, Zheng G, Zou BJ, Du ZD, Gao S, Yan S, Qin X, Gong TT, Zhao YH, Wu QJ. Nutrients-Rich Food Index Scores and the Overall Survival of Ovarian Cancer Patients: Results from the Ovarian Cancer Follow-Up Study, a Prospective Cohort Study. Nutrients 2023; 15:nu15030717. [PMID: 36771422 PMCID: PMC9920592 DOI: 10.3390/nu15030717] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 01/27/2023] [Accepted: 01/27/2023] [Indexed: 02/02/2023] Open
Abstract
Background: The nutrients-rich food (NRF) index provides a score of diet quality. Although high diet quality is associated with survival of ovarian cancer (OC), the associations between NRF index scores and OC survival remain unevaluated. Methods: The prospective cohort study enrolled 703 women with newly diagnosed epithelial OC to assess the correlations between NRF index scores and overall survival (OS) in OC patients. Dietary consumption was evaluated through a food frequency questionnaire and diet quality was calculated based on NRF index scores, including three limited nutrients and six (NRF6.3), nine (NRF9.3), or eleven (NRF11.3) benefit nutrients. All-cause deaths were ascertained through medical records combined with active follow-up. Immunohistochemistry (IHC) analyses were conducted to evaluate the expression of IHC indicators (including Estrogen Receptor, Progesterone Receptor, p53, Vimentin, and Wilms' tumor 1), which were identified by two independent pathologists. The Cox proportional hazards regression models were applied for estimating the hazard ratios (HRs) and 95% confidence intervals (CIs). Moreover, we performed the penalized cubic splines model to assess the curvilinear associations of NRF index scores with OC survival. Results: During the median follow-up of 37.17 (interquartile: 24.73-50.17) months, 130 deaths were documented. Compared to the lowest tertiles, the highest tertile of index scores [NRF9.3 (HR = 0.63, 95% CI = 0.41-0.95), NRF6.3 (HR = 0.59, 95% CI = 0.39-0.89), and NRF11.3 (HR = 0.57, 95% CI = 0.38-0.87)] were correlated to better OS, showing an obvious linear trend (all p trend < 0.05). Interestingly, the curvilinear association between the NRF6.3 index score and OC survival was also observed (p non-linear < 0.05). Subgroup analyses, stratified by clinical, demographic, and IHC features, showed similar risk associations as the unstratified results. Furthermore, there were significant multiplicative interactions between NRF index scores and Progestogen Receptors as well as Wilms' tumor 1 expressions (all p interaction < 0.05). Conclusions: Higher NRF index scores were associated with an improved OS in OC patients.
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Affiliation(s)
- Jun-Qi Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Qi-Peng Ma
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Gang Zheng
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Bing-Jie Zou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Zong-Da Du
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Shi Yan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Correspondence: (Y.-H.Z.); (Q.-J.W.); Tel.: +86-24-96615-13652 (Y.-H.Z.); +86-24-96615-13652 (Q.-J.W.)
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China
- Correspondence: (Y.-H.Z.); (Q.-J.W.); Tel.: +86-24-96615-13652 (Y.-H.Z.); +86-24-96615-13652 (Q.-J.W.)
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Chen L, Jia Y, Guo Y, Chen G, Ciren Z, Chen H, Duoji Z, Xu J, Yang T, Xu H, Feng S, Jiang Y, Guo B, Meng Q, Zhao X. Residential greenness associated with decreased risk of metabolic- dysfunction-associated fatty liver disease: Evidence from a large population-based epidemiological study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 249:114338. [PMID: 36508840 DOI: 10.1016/j.ecoenv.2022.114338] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Numerous studies have shown that residential greenness positively correlates with enhanced health. Metabolic dysfunction-associated fatty liver disease (MAFLD) affects about a quarter of the population while lacking specific treatments. Given that the association between green space and MAFLD is still unknown, we explored the association between residential greenness and MAFLD as well as the potential mechanisms based on the baseline survey of the China Multi-Ethnic Cohort (CMEC). METHODS Residential greenness was expressed as normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). MAFLD was assessed through hepatic steatosis, the presence of overweight/obesity, type 2 diabetes mellitus, and evidence of metabolic dysregulation. We used logistic regression to examine the association between NDVI/EVI and the prevalence of MAFLD. Moreover, we utilized causal mediation analyses to explore the role of physical activity and ambient particulate matters (PM1, PM2.5, and PM10) on the association between residential greenness and MAFLD. RESULTS We included 72,368 participants from the CMEC and found that residential greenness was negatively associated with the prevalence of MAFLD. For an interquartile range (IQR) increase in NDVI500 m and EVI500 m, the odds ratio (OR) of MAFLD were 0.78 (95 %CI: 0.75, 0.81) and 0.81 (95 %CI: 0.78, 0.84), respectively. Greater association between residential greenness and MAFLD was observed among males. Air pollutants and physical activity could mediate a partial effect (8.5-22.9 %) of residential greenness on MAFLD. CONCLUSION Higher residential greenness was associated with decreased risk of MAFLD. Moreover, the association was greater among males. The protective effects of residential greenness may be achieved by mitigating the hazardous effects of air pollutants and encouraging physical activity.
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Affiliation(s)
- Lin Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yiping Jia
- Department of Ultrasound, West China School of Public Health and West China Fourth Hospital, Sichuan, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Gongbo Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China; Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhuoga Ciren
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet, China
| | - Heng Chen
- Chengdu Center for Disease Control & Prevention, China
| | - Zhuoma Duoji
- School of Medicine, Tibet University, Lhasa, Tibet, China
| | - Jie Xu
- Chongqing Municipal Center for Disease Control and Prevention, China
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, China
| | - Huan Xu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Shiyu Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Qiong Meng
- Department of Epidemiology and Health Statistics School of Public Health, Kunming Medical University, West Chunrong Road, Chenggong Zone, Kunming, Yunnan 650500, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
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Liu Y, Chen L, Zhou H, Guan H, Feng Y, Yangji B, Liu Q, Liu X, Xia J, Li J, Zhao X. Does awareness of diabetic status increase risk of depressive or anxious symptoms? Findings from the China Multi-Ethnic cohort (CMEC) study. J Affect Disord 2023; 320:218-229. [PMID: 36191641 DOI: 10.1016/j.jad.2022.09.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 09/24/2022] [Accepted: 09/27/2022] [Indexed: 02/02/2023]
Abstract
INTRODUCTION People with diabetes mellitus (DM) have increased risk of depressive symptoms (DS) or anxious symptoms (AS). This study explores whether awareness of DM will contribute to prevalence of DS or AS. METHODS The baseline data including 81,717 adults from Southwest China was analyzed. DS and AS were assessed using PHQ-2 and GAD-2. Exposures were defined as 1) having self-reported physician diagnosis of diabetes (self-reported DM), 2) no prior diagnosis of diabetes but meeting diagnostic criteria (newly diagnosed DM), 3) having self-reported physician diagnosis or meeting criteria of non-diabetic diseases (non-diabetic patients), 4) healthy participants. Generalized linear mixed models were used to assess impact of presence and awareness of DM on DS or AS, adjusting for regional and individual related factors. RESULTS The prevalence of DS in self-reported DM, newly diagnosed DM, non-diabetic patient and healthy participants was 7.08 %, 4.30 %, 5.37 % and 3.17 %. The prevalence of AS was 7.80 %, 5.77 %, 6.37 % and 3.91 %. After adjusting for related factors, compared with healthy participants, self-reported DM and non-diabetic patients were associated with DS [AORDS, self-reported = 1.443(1.218,1.710), AORDS, nondiabetic patients = 1.265(1.143,1.400)], while the association between newly diagnosed DM and DS was not statistically significant. The associations between self-reported DM, newly diagnosed DM, non-diabetic patients and AS were all statistically significant. LIMITATIONS DS and AS were assessed through self-report and may suffer recall or information bias. CONCLUSIONS The association between awareness of diabetes and DS/AS suggests to pay attention to distinguish between self-reported and newly diagnosed DM and screening for DS and AS in diabetic population.
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Affiliation(s)
- Yuanyuan Liu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liling Chen
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Hanwen Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Han Guan
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, Guizhou, China
| | - Yuemei Feng
- School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Baima Yangji
- School of Medicine, Tibet University, Lhasa, Tibet Autonomous Region, China
| | - Qiaolan Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiang Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinjie Xia
- Chengdu Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Jingzhong Li
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
| | - Xing Zhao
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
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Su J, Jiang Y, Fan X, Tao R, Wu M, Lu Y, Hua Y, Jin J, Guo Y, Lv J, Pei P, Chen Z, Li L, Zhou J. Association between physical activity and cancer risk among Chinese adults: a 10-year prospective study. Int J Behav Nutr Phys Act 2022; 19:150. [PMID: 36510257 PMCID: PMC9743544 DOI: 10.1186/s12966-022-01390-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 11/25/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND In China, the quantity of physical activity differs from that in Western countries. Substantial uncertainty remains about the relevance of physical activity for cancer subtypes among Chinese adults. OBJECTIVE This study aimed to investigate the association between total daily physical activity and the incidence of common types of cancer. METHODS A total of 53,269 participants aged 30-79 years were derived from the Wuzhong subcohort of the China Kadoorie Biobank study during 2004-2008. We included 52,938 cancer-free participants in the final analysis. Incident cancers were identified through linkage with the health insurance system and death registries. Cox proportional hazard models were introduced to assess the associations of total daily physical activity with the incidence of 6 common types of cancer. RESULTS During a follow-up of 10.1 years, 3,674 cases of cancer were identified, including 794 (21.6%) from stomach cancer, 722 (19.7%) from lung cancer, 458 (12.5%) from colorectal cancer, 338 (9.2%) from liver cancer, 250 (6.8%) from breast cancer, and 231 (6.3%) from oesophageal cancer. Compared to the participants in the lowest quartile of physical activity levels, those in the highest quartile had an 11% lower risk for total cancer incidence (hazard ratio [HR]: 0.89, 95% confidence interval [CI]: 0.81-0.99), 25% lower risk for lung cancer incidence (HR: 0.75, 95% CI: 0.60-0.94), and 26% lower risk for colorectal cancer incidence (HR: 0.74, 95% CI: 0.55-1.00). There were significant interactions of physical activity with sex and smoking on total cancer (both P for interaction < 0.005), showing a lower risk for females and never smokers (HR: 0.92, 95% CI: 0.87-0.98 and HR: 0.93, 95% CI: 0.87-0.98, respectively). CONCLUSIONS Higher physical activity levels are associated with a reduced risk of total, lung, and colorectal cancer.
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Affiliation(s)
- Jian Su
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Yuchen Jiang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xikang Fan
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Ran Tao
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Ming Wu
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Yan Lu
- Department of Noncommunicable Chronic Disease Control and Prevention, Suzhou City Center for Disease Control and Prevention, Suzhou, 215004, China
| | - Yujie Hua
- Department of Noncommunicable Chronic Disease Control and Prevention, Suzhou City Center for Disease Control and Prevention, Suzhou, 215004, China
| | - Jianrong Jin
- Wuzhong District Center for Disease Control and Prevention, Suzhou, 215100, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, 102308, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China
| | - Pei Pei
- Chinese Academy of Medical Sciences, Beijing, 102308, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China
| | - Jinyi Zhou
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
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Aronsen S, Conway R, Lally P, Roberts A, Croker H, Beeken RJ, Fisher A. Determinants of sleep quality in 5835 individuals living with and beyond breast, prostate, and colorectal cancer: a cross-sectional survey. J Cancer Surviv 2022; 16:1489-1501. [PMID: 34750779 DOI: 10.1007/s11764-021-01127-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 10/27/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE The present study aimed to quantify the level of sleep problems in 5835 breast, prostate, and colorectal cancer survivors, and explore a number of potential determinants of poor sleep quality in the present sample. BMI, diet, and physical activity were of particular interest as potential determinants. METHODS Participants who completed the 'Health and Lifestyle after Cancer' survey were adults who had been diagnosed with breast, prostate, or colorectal cancer (mean time since cancer diagnosis was 35.5 months, SD=13.56). Sleep quality was assessed using the Pittsburgh Sleep Quality Index. BMI was calculated from self-reported height and weight. Participants were categorised as meeting/not meeting the World Cancer Research Fund (WCRF) recommendations for fibre, fruit and vegetables, added sugar, red meat, processed meat, fat, alcohol, and physical activity. Analyses accounted for demographic and clinical factors. RESULTS Fifty-seven percent of those with sleep data were classified as poor sleepers (response rate 79%). Being female, having a higher number of cancer treatments, more comorbid conditions, and being more anxious/depressed increased the odds of being a poor sleeper. After adjustment for these factors, there were no associations between diet/alcohol/physical activity and sleep. However, BMI was associated with sleep. Individuals in the overweight and obese categories had 22% and 79% higher odds of being poor sleepers than individuals in the underweight/healthy weight category, respectively. CONCLUSIONS The findings suggest that there may be a need to develop sleep quality interventions for cancer survivors with obesity. Even after adjustment for multiple clinical and demographic factors, BMI (particularly obesity) was associated with poor sleep. Thus, researchers and health professionals should find ways to support individuals with overweight and obesity to improve their sleep quality. IMPLICATIONS FOR CANCER SURVIVORS The present findings highlight that poor sleep is a common issue in cancer survivors. Interventions seeking to improve outcomes for cancer survivors over the longer term should consider sleep quality.
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Affiliation(s)
- Silje Aronsen
- Research Department of Behavioural Science and Health, University College London, Gower Street, London, WC1E 6BT, UK.
| | - Rana Conway
- Research Department of Behavioural Science and Health, University College London, Gower Street, London, WC1E 6BT, UK
| | - Phillippa Lally
- Research Department of Behavioural Science and Health, University College London, Gower Street, London, WC1E 6BT, UK
| | - Anna Roberts
- Research Department of Behavioural Science and Health, University College London, Gower Street, London, WC1E 6BT, UK
| | - Helen Croker
- Research Department of Behavioural Science and Health, University College London, Gower Street, London, WC1E 6BT, UK
| | - Rebecca J Beeken
- Research Department of Behavioural Science and Health, University College London, Gower Street, London, WC1E 6BT, UK
| | - Abigail Fisher
- Research Department of Behavioural Science and Health, University College London, Gower Street, London, WC1E 6BT, UK
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Wang Q, Duoji Z, Feng C, Fei T, Ma H, Wang S, Ciren W, Yang T, Ling H, Ma B, Yu W, Liu H, Zhou J, Zhao X, Jia P, Yang S. Associations and pathways between residential greenness and hyperuricemia among adults in rural and urban China. ENVIRONMENTAL RESEARCH 2022; 215:114406. [PMID: 36152883 DOI: 10.1016/j.envres.2022.114406] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 09/01/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Residential greenness may decrease the risk for hyperuricemia in rural areas, but the urban-rural disparities in this association and underlying pathways have not been studied. OBJECTIVES To investigate the associations and potential pathways between residential greenness and hyperuricemia in urban and rural areas. METHODS The baseline survey of the China Multi-Ethnic Cohort (CMEC) was used. Hyperuricemia was defined as serum uric acid (SUA) > 417 μmol/L for men and >357 μmol/L for women. The satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were used to capture residential greenness. A propensity score inverse-probability weighting method was used to assess urban-rural differences in the associations between residential greenness and hyperuricemia, with possible mediation effects of physical activity (PA), body mass index (BMI), PM2.5, and NO2 examined by causal mediation analyses. RESULTS A total of 72,372 participants were included. The increases in the EVI500m and NDVI500m residential greenness were associated with a decreased risk for hyperuricemia and the SUA level in both urban and rural areas. For example, each 0.1-unit increase in EVI500m was associated with a decreased hyperuricemia risk of 7% (OR = 0.93 [0.91, 0.96]) and a decreased SUA level of -1.77 μmol/L [-2.60, -0.93], respectively; such associations were stronger in urban areas for both the risk for hyperuricemia (OR = 0.84 [0.83, 0.86]) and SUA level (-7.18 μmol/L [-7.91, -6.46]). The subgroup analysis showed that the greenness-hyperuricemia/SUA association varied by age, sex, and annual household income. The percentage of the joint mediation effect of PA, BMI, PM2.5, and NO2 on the association between EVI500m and the risk for hyperuricemia was higher in urban (34.92%) than rural areas (15.40%). BMI, PM2.5, and PA showed significantly independently mediation effects for the greenness-hyperuricemia association in both rural and urban areas. CONCLUSIONS Exposure to residential greenness was associated with a decreased risk for hyperuricemia, partially through the pathways of PA, BMI, PM2.5, and NO2, which varied in urban and rural areas.
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Affiliation(s)
- Qinjian Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Zhuoma Duoji
- School of Medicine, Tibet University, Lhasa, China
| | - Chuanteng Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Institute for Disaster Management and Reconstruction, Sichuan University-The Hongkong Polytechnic University, Chengdu, China
| | - Teng Fei
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Hua Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Songmei Wang
- School of Public Health, Kunming Medical University, Kunming, China
| | - Wangla Ciren
- Lhasa Chengguan District Center for Disease Control and Prevention, Lhasa, China
| | - Tingting Yang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Hua Ling
- Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Bangjing Ma
- Qingbaijiang District Center for Disease Control and Prevention, Chengdu, China
| | - Wanqi Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Hongyun Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Junmin Zhou
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China.
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China.
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Cardiovascular disease prevention and mortality across 1 million urban populations in China: data from a nationwide population-based study. THE LANCET PUBLIC HEALTH 2022; 7:e1041-e1050. [DOI: 10.1016/s2468-2667(22)00170-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Revised: 06/06/2022] [Accepted: 07/01/2022] [Indexed: 12/03/2022] Open
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Wang Y, Liu H, He D, Zhang B, Liu Y, Xu K, Cao S, Huo Y, Liu J, Zeng L, Yan H, Dang S, Mi B. Association between physical activity and major adverse cardiovascular events in northwest China: A cross-sectional analysis from the Regional Ethnic Cohort Study. Front Public Health 2022; 10:1025670. [PMID: 36466532 PMCID: PMC9713839 DOI: 10.3389/fpubh.2022.1025670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 11/02/2022] [Indexed: 11/18/2022] Open
Abstract
Background To examine the association between daily physical activity (PA) and major adverse cardiovascular events (MACEs) in northwest China. Methods The data in this analysis were part of the baseline survey of the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019 in Shaanxi Province. This study used standardized self-reported total physical activity (continuous and categorical variables) and self-reported outcomes of MACEs. All analyses were conducted using the logistic regression model and stratified by age, sex, body mass index (BMI), and region. The dose-response relationships were assessed with a restricted cubic spline. Results The average level of total PA was 17.60 MET hours per day (MET-h/d). Every increase of four MET-h/d of total PA was associated with a lower risk of MACEs [adjusted OR = 0.95 (95% CI, 0.93~0.98)]. Compared with participants in the bottom quartile of total PA, a lower risk of MACEs was observed in the top quartile group [≥23.3 MET-h/d, 0.68 (0.55~0.83)]. Stratified analyses showed similar results in males, females, participants over 45 years old, participants in the rural region, and normal weight range participants (BMI < 24 kg/m2). Total participants also observed a dose-response relationship after adjusting for socioeconomic and lifestyle factors. Conclusions A higher level of PA was associated with a lower MACE risk. Future research should examine the longitudinal association of prospectively measured PA and the risk of MACEs.
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