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Kakkoura MG, Walters RG, Clarke R, Chen Z, Du H. Milk intake, lactase non-persistence and type 2 diabetes risk in Chinese adults. Nat Metab 2024:10.1038/s42255-024-01128-2. [PMID: 39294475 DOI: 10.1038/s42255-024-01128-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 08/15/2024] [Indexed: 09/20/2024]
Affiliation(s)
- Maria G Kakkoura
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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Dunneram Y, Lee JY, Watling CZ, Fraser GE, Miles F, Prabhakaran D, Shridhar K, Kondal D, Mohan V, Ali MK, Narayan KMV, Tandon N, Tong TYN, Chiu THT, Lin MN, Lin CL, Yang HC, Liang YJ, Greenwood DC, Du H, Chen Z, Yu C, Kakkoura MG, Reeves GK, Papier K, Floud S, Sinha R, Liao LM, Loftfield E, Cade JE, Key TJ, Perez-Cornago A. Methods and participant characteristics in the Cancer Risk in Vegetarians Consortium: a cross-sectional analysis across 11 prospective studies. BMC Public Health 2024; 24:2095. [PMID: 39095780 PMCID: PMC11296327 DOI: 10.1186/s12889-024-19209-y] [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: 01/17/2024] [Accepted: 06/20/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND The associations of vegetarian diets with risks for site-specific cancers have not been estimated reliably due to the low number of vegetarians in previous studies. Therefore, the Cancer Risk in Vegetarians Consortium was established. The aim is to describe and compare the baseline characteristics between non-vegetarian and vegetarian diet groups and between the collaborating studies. METHODS We harmonised individual-level data from 11 prospective cohort studies from Western Europe, North America, South Asia and East Asia. Comparisons of food intakes, sociodemographic and lifestyle factors were made between diet groups and between cohorts using descriptive statistics. RESULTS 2.3 million participants were included; 66% women and 34% men, with mean ages at recruitment of 57 (SD: 7.8) and 57 (8.6) years, respectively. There were 2.1 million meat eaters, 60,903 poultry eaters, 44,780 pescatarians, 81,165 vegetarians, and 14,167 vegans. Food intake differences between the diet groups varied across the cohorts; for example, fruit and vegetable intakes were generally higher in vegetarians than in meat eaters in all the cohorts except in China. BMI was generally lower in vegetarians, particularly vegans, except for the cohorts in India and China. In general, but with some exceptions, vegetarians were also more likely to be highly educated and physically active and less likely to smoke. In the available resurveys, stability of diet groups was high in all the cohorts except in China. CONCLUSIONS Food intakes and lifestyle factors of both non-vegetarians and vegetarians varied markedly across the individual cohorts, which may be due to differences in both culture and socioeconomic status, as well as differences in questionnaire design. Therefore, care is needed in the interpretation of the impacts of vegetarian diets on cancer risk.
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Affiliation(s)
- Yashvee Dunneram
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK.
- Human Nutrition Research Centre, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, NE2 4HH, UK.
| | - Jia Yi Lee
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK
| | - Cody Z Watling
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK
| | - Gary E Fraser
- Centre for Nutrition, Healthy Lifestyle, and Disease Prevention, School of Public Health, Loma Linda University, Loma Linda, CA, USA
| | - Fayth Miles
- Centre for Nutrition, Healthy Lifestyle, and Disease Prevention, School of Public Health, Loma Linda University, Loma Linda, CA, USA
| | - Dorairaj Prabhakaran
- Centre for Chronic Disease Control, New Delhi, India
- Public Health Foundation of India, Gurugram, Haryana, India
- Emory Global Diabetes Research Center, Woodruff Health Sciences Centerand, Emory University , Atlanta, GA, USA
- London School of Hygiene and Tropical Medicine, London, UK
| | - Krithiga Shridhar
- Centre for Chronic Disease Control, New Delhi, India
- Centre for Health Analytics, Trivedi School of Bioscience, Ashoka University, Research, and Trends, Sonipat, Haryana, India
| | - Dimple Kondal
- Centre for Chronic Disease Control, New Delhi, India
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation (ICMR Center for Advanced Research On Diabetes) and Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Mohammed K Ali
- Emory Global Diabetes Research Center, Woodruff Health Sciences Centerand, Emory University , Atlanta, GA, USA
- Hubert Department of Global Health, Emory University, Atlanta, GA, USA
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, GA, USA
| | - Kabayam M Venkat Narayan
- Emory Global Diabetes Research Center, Woodruff Health Sciences Centerand, Emory University , Atlanta, GA, USA
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Nikhil Tandon
- Department of Endocrinology, All India Institute of Medical Sciences, New Delhi, India
| | - Tammy Y N Tong
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK
| | - Tina H T Chiu
- Department of Nutritional Science, Fu-Jen Catholic University, New Taipei City, Taiwan
| | - Ming-Nan Lin
- Department of Family Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Chiayi, 622, Taiwan
- Department of Family Medicine, College of Medicine, Tzu Chi University, Hualien, 970, Taiwan
| | - Chin-Lon Lin
- Buddhist Tzu Chi Medical Foundation, Hualien City, Taiwan
| | - Hsin-Chou Yang
- Institute of Statistical Science, Academia Sinica, Taipei City, Taiwan
| | - Yu-Jen Liang
- Institute of Statistical Science, Academia Sinica, Taipei City, Taiwan
| | | | - Huaidong Du
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield, Department of Population Health , University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield, Department of Population Health , University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
| | - Maria G Kakkoura
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield, Department of Population Health , University of Oxford, Oxford, UK
| | - Gillian K Reeves
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK
| | - Keren Papier
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK
| | - Sarah Floud
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK
| | - Rashmi Sinha
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Linda M Liao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Erikka Loftfield
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Janet E Cade
- Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, Leeds, UK
| | - Timothy J Key
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK.
| | - Aurora Perez-Cornago
- Cancer Epidemiology Unit,Nuffield, Department of Population Health , University of Oxford, Oxford, OX3 7LF, UK
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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] [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, Beijing 100191, China
| | - Qiufen 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
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - 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
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - Yuanjie Pang
- 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
- 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 100191, China
| | - 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
| | - 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
| | - Xiaoming Yang
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Xiaofang Chen
- Chengdu Medical College, Chengdu, Sichuan 610500, 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
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - 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
- 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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Su J, Fan X, Li M, Yu H, Geng H, Qin Y, Lu Y, Pei P, Sun D, Yu C, Lv J, Tao R, Zhou J, Ma H, Wu M. Association of lifestyle with reduced stroke risk in 41 314 individuals with diabetes: Two prospective cohort studies in China. Diabetes Obes Metab 2024; 26:2869-2880. [PMID: 38685601 DOI: 10.1111/dom.15606] [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: 01/22/2024] [Revised: 04/03/2024] [Accepted: 04/04/2024] [Indexed: 05/02/2024]
Abstract
AIM To investigate the associations of individual and combined healthy lifestyle factors (HLS) with the risk of stroke in individuals with diabetes in China. METHODS This prospective analysis included 41 314 individuals with diabetes [15 191 from the Comprehensive Research on the Prevention and Control of the Diabetes (CRPCD) project and 26 123 from the China Kadoorie Biobank (CKB) study]. Associations of lifestyle factors, including cigarette smoking, alcohol consumption, physical activity, diet, body shape and sleep duration, with the risk of stroke, intracerebral haemorrhage (ICH) and ischaemic stroke (IS) were assessed using Cox proportional hazard models. RESULTS During median follow-up periods of 8.02 and 9.05 years, 2499 and 4578 cases of stroke, 2147 and 4024 of IS, and 160 and 728 of ICH were documented in individuals with diabetes in the CRPCD and CKB cohorts, respectively. In the CRPCD cohort, patients with ≥5 HLS had a 14% lower risk of stroke (hazard ratio (HR): 0.86, 95% confidence interval (CI): 0.75-0.98) than those with ≤2 HLS. In the CKB cohort, the adjusted HR (95% CI) for patients with ≥5 HLS were 0.74 (0.66-0.83) for stroke, 0.74 (0.66-0.83) for IS, and 0.57 (0.42-0.78) for ICH compared with those with ≤2 HLS. The pooled adjusted HR (95% CI) comparing patients with ≥5 HLS versus ≤2 HLS was 0.79 (0.69-0.92) for stroke, 0.80 (0.68-0.93) for IS, and 0.60 (0.46-0.78) for ICH. CONCLUSIONS Maintaining a healthy lifestyle was associated with a lower risk of stroke, IS and ICH among individuals with diabetes.
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Affiliation(s)
- Jian Su
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Xikang Fan
- Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Mengyao Li
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Hao Yu
- Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Houyue Geng
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yu Qin
- Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yan Lu
- Department of Non-communicable Chronic Disease Control and Prevention, Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Dianjianyi Sun
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education (Peking University), Beijing, China
| | - Canqing Yu
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education (Peking University), Beijing, China
| | - Jun Lv
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Ministry of Education (Peking University), Beijing, China
| | - Ran Tao
- Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Jinyi Zhou
- Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ming Wu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
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Moll van Charante EP, Hoevenaar-Blom MP, Song M, Andrieu S, Barnes L, Birck C, Brooks R, Coley N, Eggink E, Georges J, Hafdi M, van Gool WA, Handels R, Hou H, Lyu J, Niu Y, Song L, Wang W, Wang Y, Wimo A, Yu Y, Zhang J, Zhang W, Brayne C, Wang W, Richard E. Prevention of dementia using mobile phone applications (PRODEMOS): a multinational, randomised, controlled effectiveness-implementation trial. THE LANCET. HEALTHY LONGEVITY 2024; 5:e431-e442. [PMID: 38763155 DOI: 10.1016/s2666-7568(24)00068-0] [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: 12/21/2023] [Revised: 04/11/2024] [Accepted: 04/15/2024] [Indexed: 05/21/2024] Open
Abstract
BACKGROUND The expected increase of dementia prevalence in the coming decades will mainly be in low-income and middle-income countries and in people with low socioeconomic status in high-income countries. This study aims to reduce dementia risk factors in underserved populations at high-risk using a coach-supported mobile health (mHealth) intervention. METHODS This open-label, blinded endpoint, hybrid effectiveness-implementation randomised controlled trial (RCT) investigated whether a coach-supported mHealth intervention can reduce dementia risk in people aged 55-75 years of low socioeconomic status in the UK or from the general population in China with at least two dementia risk factors. The primary effectiveness outcome was change in cardiovascular risk factors, ageing, and incidence of dementia (CAIDE) risk score from baseline to after 12-18 months of intervention. Implementation outcomes were coverage, adoption, sustainability, appropriateness, acceptability, fidelity, feasibility, and costs assessed using a mixed-methods approach. All participants with complete data on the primary outcome, without imputation of missing outcomes were included in the analysis (intention-to-treat principle). This trial is registered with ISRCTN, ISRCTN15986016, and is completed. FINDINGS Between Jan 15, 2021, and April 18, 2023, 1488 people (601 male and 887 female) were randomly assigned (734 to intervention and 754 to control), with 1229 (83%) of 1488 available for analysis of the primary effectiveness outcome. After a mean follow-up of 16 months (SD 2·5), the mean CAIDE score improved 0·16 points in the intervention group versus 0·01 in the control group (mean difference -0·16, 95% CI -0·29 to -0·03). 1533 (10%) invited individuals responded; of the intervention participants, 593 (81%) of 734 adopted the intervention and 367 (50%) of 734 continued active participation throughout the study. Perceived appropriateness (85%), acceptability (81%), and fidelity (79%) were good, with fair overall feasibility (53% of intervention participants and 58% of coaches), at low cost. No differences in adverse events between study arms were found. INTERPRETATION A coach-supported mHealth intervention is modestly effective in reducing dementia risk factors in those with low socioeconomic status in the UK and any socioeconomic status in China. Implementation is challenging in these populations, but those reached actively participated. Whether this intervention will result in less cognitive decline and dementia requires a larger RCT with long follow-up. FUNDING EU Horizon 2020 Research and Innovation Programme and the National Key R&D Programmes of China. TRANSLATION For the Mandarin translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Eric P Moll van Charante
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
| | - Marieke P Hoevenaar-Blom
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Manshu Song
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China; School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Sandrine Andrieu
- Aging Research Team, Centre for Epidemiology and Research in Population Health, INSERM-University of Toulouse UPS, Toulouse, France; Department of Epidemiology and Public Health, Toulouse University Hospital, Toulouse, France
| | - Linda Barnes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Rachael Brooks
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Nicola Coley
- Aging Research Team, Centre for Epidemiology and Research in Population Health, INSERM-University of Toulouse UPS, Toulouse, France; Department of Epidemiology and Public Health, Toulouse University Hospital, Toulouse, France
| | - Esmé Eggink
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | | | - Melanie Hafdi
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Willem A van Gool
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Ron Handels
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Solna, Sweden; Faculty of Health, Medicine, and Life Sciences Department of Psychiatry and Neuropsychology, Alzheimer Centre Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Haifeng Hou
- Centre for Precision Health, Edith Cowan University, Perth, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia; School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Jihui Lyu
- Centre for Cognitive Disorders, Beijing Geriatric Hospital, Beijing, China
| | - Yixuan Niu
- Department of Geriatrics, The Second Medical Centre & National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Libin Song
- Comvee Research Institute, Fuzhou Comvee Network & Technology, Fuzhou, China
| | - Wenzhi Wang
- Department of Neuroepidemiology, Beijing Neurosurgical Institute, Beijing, China
| | - Youxin Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China; Centre for Precision Health, Edith Cowan University, Perth, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Anders Wimo
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Solna, Sweden
| | - Yueyi Yu
- Innovation Centre for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jinxia Zhang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China; Centre for Precision Health, Edith Cowan University, Perth, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Wei Zhang
- Centre for Cognitive Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Carol Brayne
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Wei Wang
- Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing, China; Centre for Precision Health, Edith Cowan University, Perth, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia; School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China; Department of Neuroepidemiology, Beijing Neurosurgical Institute, Beijing, China; The First Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Edo Richard
- Department of Public and Occupational Health, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
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6
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Song S, Wu Z, Lv J, Yu C, Sun D, Pei P, Pan L, Yang L, Chen Y, Du H, Chen L, Schmidt D, Avery D, Duan L, Chen J, Chen Z, Li L, Pang Y. Dietary factors and patterns in relation to risk of later-onset ulcerative colitis in Chinese: A prospective study of 0.5 million people. Aliment Pharmacol Ther 2024; 59:1425-1434. [PMID: 38654428 DOI: 10.1111/apt.17963] [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: 12/09/2023] [Revised: 02/27/2024] [Accepted: 03/10/2024] [Indexed: 04/26/2024]
Abstract
BACKGROUND There is limited evidence on the associations of dietary factors and patterns with risk of later-onset ulcerative colitis (UC) in Chinese adults. AIMS To investigate the associations of dietary factors and patterns with risk of later-onset UC in Chinese. METHODS The prospective China Kadoorie Biobank cohort study recruited 512,726 participants aged 30-79. Dietary habits were assessed using food frequency questionnaires. Dietary patterns were derived by factor analysis with a principal component method. Cox regression analysis was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS During a median follow-up of 12.1 years, 312 cases of newly diagnosed UC were documented (median age of diagnosis 60.1 years). Egg consumption was associated with higher risk of UC (HR for daily vs. never or rarely: 2.29 [95% CI: 1.26-4.16]), while spicy food consumption was inversely associated with risk of UC (HR: 0.63 [0.45-0.88]). The traditional northern dietary pattern, characterised by high intake of wheat and low intake of rice, was associated with higher risk of UC (HR for highest vs. lowest quartile of score: 2.79 [1.93-4.05]). The modern dietary pattern, characterised by high intake of animal-origin foods and fruits, was associated with higher risk of UC (HR: 2.48 [1.63-3.78]). Population attributable fraction was 13.04% (7.71%-19.11%) for daily/almost daily consumption of eggs and 9.87% (1.94%-18.22%) for never/rarely consumption of spicy food. CONCLUSIONS The findings highlight the importance of evaluating dietary factors and patterns in the primary prevention of later-onset UC in Chinese adults.
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Affiliation(s)
- Shuyao Song
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhiyu Wu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Lang Pan
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lingli Chen
- Tongxiang Center for Disease Control and Prevention, Tongxiang, 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
| | - Liping Duan
- Department of Gastroenterology, Peking University Third Hospital, Beijing, 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, UK
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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7
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Liu D, Tan S, Zhou Z, Gu S, Zuo H. Trimethylamine N-oxide, β-alanine, tryptophan index, and vitamin B6-related dietary patterns in association with stroke risk. Nutr Metab Cardiovasc Dis 2024; 34:1179-1188. [PMID: 38218714 DOI: 10.1016/j.numecd.2023.12.002] [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: 04/27/2023] [Revised: 11/17/2023] [Accepted: 12/06/2023] [Indexed: 01/15/2024]
Abstract
BACKGROUND AND AIMS The aim of this study was to examine the associations of dietary patterns derived by reduced-rank regression (RRR) model reflecting variation in novel biomarkers (trimethylamine N-oxide, β-alanine, tryptophan index, and vitamin B6) with stroke risk. METHODS AND RESULTS We performed analyses based on a community-based cohort study "the Prospective Follow-up Study on Cardiovascular Morbidity and Mortality in China (PFS-CMMC)". Factor loadings were calculated by RRR using 11 food groups collected via a validated food frequency questionnaire and the four response variables based on its nested case-control data (393 cases of stroke vs. 393 matched controls). Dietary pattern scores were derived by applying the factor loadings to the food groups in the entire cohort (n = 15,518). The associations of dietary pattern with the stroke risk were assessed using Cox proportional hazards models. The dietary pattern characterized with higher intakes of red meat and poultry but lower intakes of fresh vegetables, fresh fruits, and fish/seafoods were identified for further analyses. The hazard ratios (HR) for the highest vs. lowest quartile was 1.55 [95 % confidence interval (CI): 1.18-2.03, P trend = 0.001] for total stroke, 2.96 [95 % CI: 1.53-5.71, P trend <0.001] for non-ischemic stroke, after adjustment for sex, age, educational attainment, current smoking, current drinking, body mass index, total energy intake, family history of stroke, hypertension, diabetes, hyperlipidemia, and estimated glomerular filtration rate. CONCLUSION Our findings highlight the importance of limited meat intake and increased intakes of fresh vegetables, fruits, and fish/seafoods in the prevention of stroke among Chinese adults.
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Affiliation(s)
- Dong Liu
- School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China; School of Public Health, Nantong University, Nantong, China
| | - Siyue Tan
- School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China
| | - Zhengyuan Zhou
- Department of Chronic Disease Control and Prevention, Changshu Center for Disease Control and Prevention, Suzhou, China
| | - Shujun Gu
- Department of Chronic Disease Control and Prevention, Changshu Center for Disease Control and Prevention, Suzhou, China.
| | - Hui Zuo
- School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China; Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, China; MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, China.
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8
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Shi X, Chen M, Pan Q, Zhou J, Liu Y, Jiang T, Lin Y, Huang J, Shen X, Lu D, Li Y. Association between dietary patterns and premenstrual disorders: a cross-sectional analysis of 1382 college students in China. Food Funct 2024; 15:4170-4179. [PMID: 38482855 DOI: 10.1039/d3fo05782h] [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: 04/23/2024]
Abstract
Premenstrual disorders (PMDs) are common among young women and have been linked to metabolic dysfunction. Limited evidence exists regarding the associations between dietary patterns and PMDs. This cross-sectional study involved young female adults recruited from the Care of Premenstrual Emotion (COPE) cohort study in China to examine the relationship between dietary patterns and PMDs in young adulthood. PMDs were assessed using the Calendar of Premenstrual Experiences, and the consumption frequency of 12 common food groups was evaluated using a Food Frequency Questionnaire. We used principal component analysis to identify the dietary patterns and employed logistic regression to investigate the association between dietary pattern adherence and PMDs. The study included 1382 participants, of whom 337 (24.4%) reported having PMDs. Three dietary patterns were identified and named based on regional food preferences: the Traditional North China Diet (TNCD), the Traditional South China Diet (TSCD), and the Lacto-ovo Vegetarian Diet (LVD). The TSCD, characterized by high consumption of rice, red meat, and poultry, showed a significant inverse association with PMDs. This pattern held good for both premenstrual syndrome and premenstrual dysphoric disorder. These findings suggest that targeted dietary modifications could serve as a localized strategy for PMDs prevention.
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Affiliation(s)
- Xinyi Shi
- Health Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, China.
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.
| | - Min Chen
- Health Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, China.
| | - Qing Pan
- Health Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, China.
| | - Jing Zhou
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Yuqing Liu
- Health Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, China.
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.
| | - Tingting Jiang
- Youth League Committee (Youth Work Department, Medical and Social Work Office), West China Hospital, Sichuan University, Chengdu, China
| | - Yifei Lin
- Health Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, China.
| | - Jin Huang
- Health Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, China.
| | - Xi Shen
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Donghao Lu
- Health Management Center, General Practice Medical Center, Innovation Institute for Integration of Medicine and Engineering, West China Hospital, Sichuan University, Chengdu, China.
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Yuchen Li
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.
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9
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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 hemorrhage risk over 5 years. Eur J Prev Cardiol 2024:zwae147. [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 03/21/2024] [Accepted: 04/16/2024] [Indexed: 05/07/2024]
Abstract
AIMS The relationships between long-term blood pressure (BP) measures and intracerebral hemorrhage (ICH), as well as their predictive ability on ICH, were unclear. We aimed 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 We included 12,398 participants from the China Kadoorie Biobank (CKB) who completed three surveys every four to five 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). RESULTS The hazard ratios (95% confidence intervals) of incident ICH associated with per SD increase in cumSBP and cumDBP 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 & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Yinqi Ding
- 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
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - 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
- 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 100191, China
| | - 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
| | - 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
| | - Dan Schmidt
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom
| | - Jianwei Chen
- Liuyang Centers for Disease Control and Prevention, Liuyang, Changsha, Hunan, 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
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education
| | - 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
- 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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10
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Ma S, Zhu J, Xie S, Chen R, Li X, Wei W. Suboptimal dietary quality is associated with mental symptoms among adults aged 40 years and over in China: A population-based cross-sectional study. J Affect Disord 2023; 340:802-811. [PMID: 37597777 DOI: 10.1016/j.jad.2023.08.071] [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: 05/15/2023] [Revised: 08/13/2023] [Accepted: 08/14/2023] [Indexed: 08/21/2023]
Abstract
BACKGROUND The previous studies an association between dietary patterns and psychiatric symptoms. However, few studies have examined the association of quality of dietary patterns and anxiety, depressive symptoms in the Chinese population. METHODS Between 2017 and 2019, a population-based, cross-sectional survey was carried out in China. Uniformed questionnaires collected the demographic characteristics and food data. The dietary quality of the adults was evaluated using the revised Diet Balance Index 2016 (DBI-16). We measured anxiety and depression symptoms using the the Generalized Anxiety Disorder (GAD)-7 and Patient Health Questionnaire (PHQ)-9. RESULTS A total of 73,737 participants were recruited during the survey period. 17.6 % and 13.7 % of residents suffer from anxiety and depression symptoms, respectively. The DBI-16 indicates that participants with anxiety or depression symptoms had higher scores of low bound score (LBS, refers to inadequate food intake) and dietary quality distance (DQD, refers to unbalanced food intake) than those without anxiety or depression. The logistic regression models showed that high levels of LBS and DQD problems were more strongly associated with anxiety (LBS:OR = 1.20, DQD:OR = 1.30) and depressive symptoms (LBS:OR = 1.21, DQD:OR = 1.44). On the contrary, higher bound score (HBS, refers to excessive food intake) was significantly negatively correlated with symptoms of anxiety and depression. Moreover, each increase in the food group was associated with 4 % lower odds of anxiety and 6 % lower odds of depression symptoms. LIMITATIONS Cross-sectional design and self-reporting of psychological symptoms and dietary information limit the generalizability of the results. CONCLUSION The dietary quality of adults aged 40 years and over in China is suboptimal, with excessive and inadequate food intake simultaneously. Dietary imbalance, and low dietary diversity may be related to anxiety and depressive symptoms.
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Affiliation(s)
- Shanrui Ma
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Juan Zhu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Shuanghua Xie
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Ru Chen
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xinqing Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Wenqiang Wei
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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11
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Zhai L, Pan H, Cao H, Zhao S, Yao P. Reliability and validity of a semi-quantitative food frequency questionnaire: dietary intake assessment among multi-ethnic populations in Northwest China. JOURNAL OF HEALTH, POPULATION, AND NUTRITION 2023; 42:111. [PMID: 37858218 PMCID: PMC10585915 DOI: 10.1186/s41043-023-00452-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 10/06/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND Few multi-ethnic dietary culture-sensitive food frequency questionnaires (FFQ) have been developed due to the complexity and diversity of cooking methods and styles. This study aimed to develop and validate a specific FFQ among multi-ethnic groups in Northwest China. METHODS In the reliability study, 139 participants aged 20-65 completed two identical FFQs separated by 3 months. The relative validation of the FFQ was assessed by three 24-h recalls (24HR) employed in the interval of two FFQs, as a reference. Stratified analyses were also conducted by the major ethnic groups (Han nationality or Ethnic minority). RESULTS For reproducibility, the median (range) of Spearman's correlation coefficients (SCC) was 0.71 (0.43-0.84) for nutrients. The intra-class correlation coefficients (ICC) covered a spectrum from 0.39 to 0.78 (median: 0.64). Meanwhile, the weighted kappa values ranged from 0.11 to 0.64. For validity, the median (range) of Pearson's correlation coefficients derived from the energy unadjusted and the adjusted values between FFQ and 24HR were 0.61 (0.12-0.79) and 0.56 (0.12-0.77), respectively. The results of correlation coefficients were similar between the two ethnic groups. Moreover, the Bland-Altman plots likewise demonstrated a satisfactory level of agreement between the two methods. CONCLUSIONS The FFQ showed acceptable reproducibility and moderate relative validity for evaluating dietary intake among multi-ethnic groups in northwest China. It could be a credible nutritional screening tool for forthcoming epidemiological surveys of these populations.
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Affiliation(s)
- Leilei Zhai
- The First Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No.393, Xinyi Road, Urumqi, 830011, Xinjiang Uygur Autonomous Region, China
| | - Huiyue Pan
- The First Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No.393, Xinyi Road, Urumqi, 830011, Xinjiang Uygur Autonomous Region, China
| | - Hanqi Cao
- The First Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No.393, Xinyi Road, Urumqi, 830011, Xinjiang Uygur Autonomous Region, China
| | - Shupeng Zhao
- The First Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No.393, Xinyi Road, Urumqi, 830011, Xinjiang Uygur Autonomous Region, China
| | - Ping Yao
- The First Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, No.393, Xinyi Road, Urumqi, 830011, Xinjiang Uygur Autonomous Region, China.
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12
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Huang X, Li J, Cao W, Lyu J, Guo Y, Pei P, Xia Q, Du H, Chen Y, Ling Y, Kerosi R, Stevens R, Yang X, Chen J, Yu C, Chen Z, Li L. Association between fresh fruit consumption and the risk of chronic obstructive pulmonary disease-related hospitalization and death in Chinese adults: A prospective cohort study. Chin Med J (Engl) 2023; 136:2316-2323. [PMID: 37537725 PMCID: PMC10538915 DOI: 10.1097/cm9.0000000000002591] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Existing evidence suggests that fruit consumption is a significant influencing factor for chronic obstructive pulmonary disease (COPD), but this is unclear in the Chinese population. We examined the association of fresh fruit consumption with the risk of COPD-related hospitalization and death in a nationwide, population-based prospective cohort from China. METHODS Between 2004 and 2008, the China Kadoorie Biobank recruited >0.5 million adults aged 30 to 79 years from ten diverse regions across China. After excluding individuals diagnosed with major chronic diseases and prevalent COPD, the prospective analysis included 421,428 participants. Cox regression was used to calculate the hazard ratios (HRs) for the association between fresh fruit consumption and risk of COPD-related hospitalization and death, with adjustment for established and potential confounders. RESULTS During a mean follow-up of 10.9 years, 11,292 COPD hospitalization events and deaths were documented, with an overall incidence rate of 2.47/1000 person-years. Participants who consumed fresh fruit daily had a 22% lower risk of COPD-related hospitalization and death compared with non-consumers (HR = 0.78, 95% confidence interval [CI]: 0.71-0.87). The inverse association between fresh fruit consumption and COPD-related hospitalization and death was stronger among non-current smokers and participants with normal body mass index (BMI) (18.5 kg/m 2 ≤ BMI < 24.0 kg/m 2 ); the corresponding HRs for daily fresh fruit consumption were 0.78 (95% CI: 0.68-0.89) and 0.69 (95% CI: 0.59-0.79) compared with their counterparts, respectively. CONCLUSIONS High-frequency fruit consumption was associated with a lower risk of COPD in Chinese adults. Increasing fruit consumption, together with cigarette cessation and weight control, should be considered in the prevention and management of COPD.
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Affiliation(s)
- Xin Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Jiachen Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Jun Lyu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing 100191, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China
| | - Yu Guo
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing 100037, China
| | - Pei Pei
- National Coordinate Center, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Qingmei Xia
- National Coordinate Center, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Huaidong Du
- Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Yiping Chen
- Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Yang Ling
- Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Rene Kerosi
- Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Rebecca Stevens
- Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Oxford OX3 7LF, UK
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
| | - Xujun Yang
- Maiji Center for Disease Control and Prevention, Tianshui, Gansu 741020, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing 100191, China
| | - Zhengming Chen
- Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), 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
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing 100191, China
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13
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Jing H, Teng Y, Chacha S, Wang Z, Shi G, Mi B, Zhang B, Cai J, Liu Y, Li Q, Shen Y, Yang J, Kang Y, Li S, Liu D, Wang D, Yan H, Dang S. Is Increasing Diet Diversity of Animal-Source Foods Related to Better Health-Related Quality of Life among Chinese Men and Women? Nutrients 2023; 15:4183. [PMID: 37836467 PMCID: PMC10574670 DOI: 10.3390/nu15194183] [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: 08/20/2023] [Revised: 09/12/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
Diet plays a crucial role in regulating individuals' lifestyles and is closely related to health. The intake of animal-sourced foods (ASF) provides the human body with high-quality protein and various micronutrients. This study aimed to investigate whether the diversity of animal foods has a positive impact on the health-related quality of life (HRQoL) among residents. The data came from the Shaanxi baseline survey of the Northwest Chinese Regional Ethnic Cohort Study, which recruited more than 100 thousand participants aged 35 to 74 from five provinces between June 2018 and May 2019. A total of 39,997 participants in Shaanxi (mean age: 50 years; 64% women) were finally included in this current study. The animal source food diet diversity score (ASFDDS) was established based on the frequency of consuming pork, mutton, beef, poultry, seafood, eggs, pure milk, and yogurt. The physical component score (PCS) and mental component score (MCS), ranging from 0 to 100 on the 12-Item Short Form Survey (SF-12), were used to assess participants' HRQoL. Better PCS/MCS was defined as scores higher than the 90th percentile. The results showed that men had a higher intake of ASF and ASFDDS than women. After adjusting for potential confounders, compared with those who never or rarely consumed animal foods, the likelihood of having better PCS and MCS increased by 16% (OR = 1.16, 95%CI: 1.01-1.34) and 24% (OR = 1.24, 95%CI: 1.03-1.448), respectively, in men with an ASFDDS ≥ 2. In women, a 34% increase (OR = l.34, 95%CI: 116-l.54) likelihood for better PCS was observed for an ASFDDS ≥ 2, but no association was observed for MCS. Increasing each specific animal source's food intake was associated with better PCS after adjusting for all covariates. However, for MCS, positive associations were only observed in seafood consumption among men and eggs among women. Restricted cubic splines showed a substantial dose-response association between intake frequency of animal-source foods and PCS, both in men and women. The study suggests that a diverse intake of animal-sourced foods can potentially improve the HRQoL of Chinese adults.
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Affiliation(s)
- Hui Jing
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yuxin Teng
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Samuel Chacha
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Ziping Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Guoshuai Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Baibing Mi
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Binyan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Jiaxin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yezhou Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Qiang Li
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yuan Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Jiaomei Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Yijun Kang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Shanshan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Danmeng Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Duolao Wang
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool L7 8XZ, UK;
| | - Hong Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
| | - Shaonong Dang
- Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (H.J.); (Y.T.); (S.C.); (Z.W.); (G.S.); (B.M.); (B.Z.); (J.C.); (Y.L.); (Q.L.); (Y.S.); (J.Y.); (Y.K.); (S.L.); (D.L.)
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14
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Dong J, Gao M, Li L, Pan X, Chen SY, Li J, Smith-Warner SA, Li X, Wang H, Zheng J. Associations of Dietary Inflammatory Potential with Esophageal Precancerous Lesions and Esophageal Squamous-Cell Cancer: A Cross-Sectional Study. Nutrients 2023; 15:4078. [PMID: 37764860 PMCID: PMC10537352 DOI: 10.3390/nu15184078] [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: 08/09/2023] [Revised: 09/11/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
Chronic inflammation plays a central role in the progression from esophageal precancerous lesions (EPLs) to esophageal squamous-cell cancer (ESCC). However, few studies have investigated the relationship between the overall inflammatory potential of diets and EPLs and ESCC. We aimed to study the association between the Dietary Inflammatory Index (DII) and EPLs and ESCC. As part of the National Cohort of Esophageal Cancer (NCEC) in China, 3967 residents (1993 men and 1974 women) aged from 40 to 69 years living in Yanting County received free gastroscopy screenings from 2017 to 2019. Dietary intake during the past year was assessed at enrollment of the cohort before screening and DII scores were calculated based on 28 food parameters. EPLs (classified into mild, moderate, and severe dysplasia) and ESCC were histologically confirmed by biopsy. Multivariable logistic regression was used to examine the associations of DII scores with EPLs and ESCC. A total of 312 participants were diagnosed with EPLs (226 with mild dysplasia, 40 with moderate dysplasia, and 46 with severe dysplasia) and 72 were diagnosed with ESCC. A statistically significant positive association was observed between DII scores and overall EPLs (ORT3 vs. T1 = 1.45, 95%CI = 1.01-2.09); the association was similar but not statistically significant for mild dysplasia (ORone-unit-increment = 1.11, 95%CI = 0.95-1.34) and for moderate and severe dysplasia combined (ORone-unit-increment = 1.15, 95%CI = 0.87-1.51). The association with ESCC was similar in magnitude but not significant, likely due to the small number of cases. In this cross-sectional study of a population in China at high risk of ESCC, DII scores were positively associated with odds of EPLs and ESCC. Consumption of anti-inflammatory foods may be beneficial to prevent EPLs and ESCC.
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Affiliation(s)
- Jingwen Dong
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; (J.D.); (S.-Y.C.); (S.A.S.-W.)
| | - Min Gao
- School of Public Health, Capital Medical University, Beijing 100069, China;
| | - Lin Li
- Cancer Prevention and Treatment Office, Yanting Cancer Hospital, Mianyang 621600, China; (L.L.); (J.L.)
| | - Xiaoyu Pan
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA 02115, USA;
| | - Sheng-Yin Chen
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; (J.D.); (S.-Y.C.); (S.A.S.-W.)
| | - Jun Li
- Cancer Prevention and Treatment Office, Yanting Cancer Hospital, Mianyang 621600, China; (L.L.); (J.L.)
| | - Stephanie A. Smith-Warner
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; (J.D.); (S.-Y.C.); (S.A.S.-W.)
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA 02115, USA;
| | - Xiaoguang Li
- Department of Food Safety and Toxicology, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (X.L.); (H.W.)
| | - Hui Wang
- Department of Food Safety and Toxicology, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (X.L.); (H.W.)
| | - Jiali Zheng
- Department of Epidemiology and Biostatistics, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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15
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Sun D, Liu C, Zhu Y, Yu C, Guo Y, Sun D, Pang Y, Pei P, Du H, Yang L, Chen Y, Meng X, Liu Y, Zhang J, Schmidt D, Avery D, Chen J, Chen Z, Lv J, Kan H, Li L. Long-Term Exposure to Fine Particulate Matter and Incidence of Esophageal Cancer: A Prospective Study of 0.5 Million Chinese Adults. Gastroenterology 2023; 165:61-70.e5. [PMID: 37059339 PMCID: PMC7615725 DOI: 10.1053/j.gastro.2023.03.233] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 02/22/2023] [Accepted: 03/02/2023] [Indexed: 04/16/2023]
Abstract
BACKGROUND & AIMS Evidence is sparse and inconclusive on the association between long-term fine (≤2.5 μm) particulate matter (PM2.5) exposure and esophageal cancer. We aimed to assess the association of PM2.5 with esophageal cancer risk and compared the esophageal cancer risk attributable to PM2.5 exposure and other established risk factors. METHODS This study included 510,125 participants without esophageal cancer at baseline from China Kadoorie Biobank. A high-resolution (1 × 1 km) satellite-based model was used to estimate PM2.5 exposure during the study period. Hazard ratios (HR) and 95% CIs of PM2.5 with esophageal cancer incidence were estimated using Cox proportional hazard model. Population attributable fractions for PM2.5 and other established risk factors were estimated. RESULTS There was a linear concentration-response relationship between long-term PM2.5 exposure and esophageal cancer. For each 10-μg/m3 increase in PM2.5, the HR was 1.16 (95% CI, 1.04-1.30) for esophageal cancer incidence. Compared with the first quarter of PM2.5 exposure, participants in the highest quarter had a 1.32-fold higher risk for esophageal cancer, with an HR of 1.32 (95% CI, 1.01-1.72). The population attributable risk because of annual average PM2.5 concentration ≥35 μg/m3 was 23.3% (95% CI, 6.6%-40.0%), higher than the risks attributable to lifestyle risk factors. CONCLUSIONS This large prospective cohort study of Chinese adults found that long-term exposure to PM2.5 was associated with an elevated risk of esophageal cancer. With stringent air pollution mitigation measures in China, a large reduction in the esophageal cancer disease burden can be expected.
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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 Laboratory of Public Health Safety of the Ministry of Education, National Health Commission Key Laboratory of Health Technology Assessment, Integrated Research on Disaster Risk, International Centers of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yunqing Zhu
- 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; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 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; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 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 and Response, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit and Epidemiological Studies Unit, 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, Oxford, United Kingdom; Clinical Trial Service Unit and Epidemiological Studies Unit, 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, Oxford, United Kingdom; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, National Health Commission Key Laboratory of Health Technology Assessment, Integrated Research on Disaster Risk, International Centers of Excellence on Risk Interconnectivity and Governance on Weather/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, Georgia
| | - Jun Zhang
- Suzhou Center for Disease Prevention and Control, Suzhou, China
| | - Dan Schmidt
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit, 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 and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - 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; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
| | - Haidong Kan
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, National Health Commission Key Laboratory of Health Technology Assessment, Integrated Research on Disaster Risk, International Centers of Excellence on Risk Interconnectivity and Governance on Weather/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; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
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16
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Pan L, Shi K, Lv J, Pang Y, Guo Y, Pei P, Du H, Millwood I, Yang L, Chen Y, Gao R, Yang X, Avery D, Chen J, Yu C, Chen Z, Li L. Association of dietary patterns, circulating lipid profile, and risk of obesity. Obesity (Silver Spring) 2023; 31:1445-1454. [PMID: 37037666 DOI: 10.1002/oby.23720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 12/08/2022] [Accepted: 01/01/2023] [Indexed: 04/12/2023]
Abstract
OBJECTIVE The aim of this study was to simultaneously explore the associations of major dietary patterns (DP) with lipid profiles and the associations of these profiles with general and central obesity risks and to evaluate the extent to which the metabolites mediate such associations. METHODS Habitual food consumption of 4778 participants with an average age of 47.0 from the China Kadoorie Biobank was collected using a 12-item food frequency questionnaire. Plasma samples were analyzed via targeted nuclear magnetic resonance (NMR) spectroscopy to quantify 129 lipid-related metabolites. Anthropometric information was measured by trained staff. RESULTS Two DPs were derived by factor analysis. The newly affluent southern pattern was characterized by high intakes of rice, meat, poultry, and fish, whereas the balanced pattern was characterized by consuming meat, poultry, fish, fresh fruit, fresh vegetables, dairy, eggs, and soybean. The newly affluent southern pattern was positively associated with 45 metabolites, which were positively associated with risks of obesity at the same time. The global lipid profile potentially explained 30.9%, 34.7%, and 53.1% of the effects of this DP on general obesity, waist circumference-defined central obesity, and waist-hip ratio-defined central obesity, respectively. CONCLUSIONS The newly affluent southern pattern points to an altered lipid profile, which showed higher general and central obesity risks. These findings partly suggest the biological mechanism for the obesogenic effects of this DP.
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Affiliation(s)
- Lang Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Kexiang Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing, China
| | - 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, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruqin Gao
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, China
| | - Xiaoming Yang
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, China
| | - Daniel Avery
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, 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 & Response, Beijing, 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, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
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17
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Su J, Geng H, Chen L, Fan X, Zhou J, Wu M, Lu Y, Hua Y, Jin J, Guo Y, Lv J, Pei P, Chen Z, Tao R. Association of healthy lifestyle with incident cardiovascular diseases among hypertensive and normotensive Chinese adults. Front Cardiovasc Med 2023; 10:1046943. [PMID: 36937945 PMCID: PMC10017485 DOI: 10.3389/fcvm.2023.1046943] [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: 09/17/2022] [Accepted: 02/13/2023] [Indexed: 03/06/2023] Open
Abstract
Background Whether lifestyle improvement benefits in reducing cardiovascular diseases (CVD) events extend to hypertensive patients and whether these benefits differ between hypertensive and normotensive individuals is unclear. This study aimed to investigate the associations of an overall healthy lifestyle with the subsequent development of CVD among participants with hypertension and normotension. Methods Using data from the Suzhou subcohort of the China Kadoorie Biobank study of 51,929 participants, this study defined five healthy lifestyle factors as nonsmoking or quitting for reasons other than illness; nonexcessive alcohol intake; relatively higher physical activity level; a relatively healthy diet; and having a standard waist circumference and body mass index. We estimated the associations of these lifestyle factors with CVD, ischemic heart disease (IHD) and ischemic stroke (IS). Results During a follow-up of 10.1 years, this study documented 6,151 CVD incidence events, 1,304 IHD incidence events, and 2,243 IS incidence events. Compared to those with 0-1 healthy lifestyle factors, HRs for those with 4-5 healthy factors were 0.71 (95% CI: 0.62, 0.81) for CVD, 0.56 (95% CI: 0.42, 0.75) for IHD, and 0.63 (95% CI: 0.51, 0.79) for IS among hypertensive participants. However, we did not observe this association among normotensive participants. Stratified analyses showed that the association between a healthy lifestyle and IHD risk was stronger among younger participants, and the association with IS risk was stronger among hypertensive individuals with lower household incomes. Conclusion Adherence to a healthy lifestyle pattern is associated with a lower risk of cardiovascular diseases among hypertensive patients, but this benefit is not as pronounced among normotensive patients.
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Affiliation(s)
- Jian Su
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Houyue Geng
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lulu Chen
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Xikang Fan
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Jinyi Zhou
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Ming Wu
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yan Lu
- Department of Noncommunicable Chronic Disease Control and Prevention, Suzhou City Center for Disease Control and Prevention, Suzhou, China
| | - Yujie Hua
- Department of Noncommunicable Chronic Disease Control and Prevention, Suzhou City Center for Disease Control and Prevention, Suzhou, China
| | - Jianrong Jin
- Wuzhong District of Suzhou City Center for Disease Control and Prevention, Suzhou, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - 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
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ran Tao
- Department of Noncommunicable Chronic Disease and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
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18
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Chen L, Zhang Y, Yu C, Guo Y, Sun D, Pang Y, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Liu Y, Burgess S, Stevens R, Chen J, Chen Z, Li L, Lv J. Modeling biological age using blood biomarkers and physical measurements in Chinese adults. EBioMedicine 2023; 89:104458. [PMID: 36758480 PMCID: PMC9941058 DOI: 10.1016/j.ebiom.2023.104458] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 01/15/2023] [Accepted: 01/17/2023] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum. METHODS The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004-08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI). FINDINGS The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (-0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019). INTERPRETATION In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade. FUNDING This work was supported by National Natural Science Foundation of China (82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303), and Chinese Ministry of Science and Technology (2011BAI09B01).
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Affiliation(s)
- Lu Chen
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yiqian Zhang
- 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
| | - Yuanjie Pang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 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
| | - Iona Y Millwood
- 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
| | - Robin G Walters
- 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
| | - Yongmei Liu
- Qingdao Centers for Disease Control and Prevention (CDC), Qingdao, China
| | - Sushila Burgess
- 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
| | - 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.
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Yu W, Shi K, Cao W, Lv J, Guo Y, Pei P, Xia Q, Du H, Chen Y, Yang L, Sun X, Sohoni R, Sansome S, Chen J, Chen Z, Li L, Yu C. Association between Fish Consumption and Risk of Chronic Obstructive Pulmonary Disease among Chinese Men and Women: an 11-Year Population-Based Cohort Study. J Nutr 2023; 152:2771-2777. [PMID: 36205613 DOI: 10.1093/jn/nxac232] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/16/2022] [Accepted: 09/29/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Epidemiological evidence on the relation between fish consumption and chronic obstructive pulmonary disease (COPD) is limited, especially among Chinese. OBJECTIVES The aim was to explore the prospective association between fish consumption and COPD among a large population-based Chinese cohort. METHODS The China Kadoorie Biobank recruited over 0.5 million participants from 10 geographically diverse regions across China from 2004 to 2008. Consumption frequency of fish at baseline was assessed by a validated food-frequency questionnaire. A total of 169,188 men and 252,238 women who had no prior COPD or other major chronic diseases at baseline were included in our analyses. Cox proportional hazard models were used to estimate HRs and 95% CIs for fish consumption categories in relation to incident COPD. RESULTS During a median follow-up of 11.1 y, 11,292 incident COPD cases were documented. Fish consumption was inversely associated with COPD risk among women, with a 17% reduction in risk for participants who consumed fish ≥4 d/wk compared with nonconsumption (HR: 0.83; 95% CI: 0.70, 0.99; P-trend = 0.017), whereas we did not observe such a dose-response relation among men (HR: 0.89; 95% CI: 0.76, 1.05; P-trend = 0.373). The joint analysis showed that COPD risk was 38% and 48% lower in men and women who consumed fish ≥4 d/wk and had a healthy lifestyle [having ≥4 of the following healthy lifestyle factors: not smoking currently; never or rarely drinking alcohol; adequate physical activity; BMI (kg/m2): 18.5-23.9; normal waist circumference; reasonable diet], compared with participants with fish consumption <4 d/wk and an unhealthy lifestyle (≤1 factors). CONCLUSIONS Higher fish consumption was associated with lower COPD risk among Chinese women but not men. This association was independent of lifestyle factors. Eating adequate fish with an overall healthy lifestyle might help lower the risk of COPD.
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Affiliation(s)
- Wei Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Kexiang Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Weihua Cao
- 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
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yu Guo
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Pei Pei
- Chinese Academy of Medical Sciences, Beijing, China
| | - Qingmei Xia
- Chinese Academy of Medical Sciences, Beijing, China
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom
| | - Xiaohui Sun
- NCDs Prevention and Control Department, Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Rajani Sohoni
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Sam Sansome
- Clinical Trial Service Unit and 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 and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
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Staple Food Preference and Obesity Phenotypes: The Regional Ethnic Cohort Study in Northwest China. Nutrients 2022; 14:nu14245243. [PMID: 36558402 PMCID: PMC9784345 DOI: 10.3390/nu14245243] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022] Open
Abstract
Staple food preference vary in populations, but evidence of its associations with obesity phenotypes are limited. Using baseline data (n = 105,840) of the Regional Ethnic Cohort Study in Northwest China, staple food preference was defined according to the intake frequency of rice and wheat. Overall and specifically abdominal fat accumulation were determined by excessive body fat percentage and waist circumference. Logistic regression and equal frequency substitution methods were used to evaluate the associations. We observed rice preference (consuming rice more frequently than wheat; 7.84% for men and 8.28% for women) was associated with a lower risk of excessive body fat (OR, 0.743; 95%CI, 0.669-0.826) and central obesity (OR, 0.886; 95%CI, 0.807-0.971) in men; and with lower risk of central obesity (OR, 0.898; 95%CI, 0.836-0.964) in women, compared with their wheat preference counterparties. Furthermore, similar but stronger inverse associations were observed in participants with normal body mass index. Wheat-to-rice (5 times/week) reallocations were associated with a 36.5% lower risk of normal-weight obesity in men and a 20.5% lower risk of normal-weight central obesity in women. Our data suggest that, compared with wheat, rice preference could be associated with lower odds ratios of certain obesity phenotypes in the Northwest Chinese population.
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Zhao L, Wang L, Wang W, Shi Z, Zhu Y, Li S, Wang T, Su Y, Li Z, Wen Y, Zhang L, Xu Q, Sharma M, Zhao Y. Association between modes of delivery and postpartum dietary patterns: A cross-sectional study in Northwest China. Front Nutr 2022; 9:985941. [DOI: 10.3389/fnut.2022.985941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 10/25/2022] [Indexed: 11/11/2022] Open
Abstract
ObjectivePuerperae’ dietary patterns (DPs) during the puerperium may be influenced by the mode of delivery, but population studies on this topic are scarce. This study aims to explore the relationship between DPs and different modes of delivery among puerperae.MethodsA cross-sectional study was conducted on 3,345 parturients in Lanzhou, China. The postpartum food intake was measured by a food frequency questionnaire (FFQ). Factor analysis was used to determine the DPs. Multiple linear regression was employed to examine the association between the mode of delivery and DP.ResultsIn this study, two DPs, i.e., traditional and modern DPs, were identified. Traditional DP was characterized by high energy-adjusted intake of tubers, coarse cereals, rice, whole grains, fishery products, and eggs. Modern DP included a high intake of coffee, non-sugary drinks, wine, tea, and fishery products. Compared with participants with vaginal delivery (reference category), cesarean section had an inverse association with modern DP (β: −0.11, 95% CI: −0.36, −0.09). A significant interaction was found between education level, monthly household income, alcohol drinking, and modes of delivery. The inverse association between cesarean section and modern DP or the intake of coffee was significant among puerperae with higher or lower monthly household income. However, the inverse association between cesarean section and traditional DP was only found among puerperae with higher monthly household income. Moreover, among the participants with high education, cesarean section was positively associated with intake of vegetables.ConclusionCesarean puerperae with higher levels of education and those with lower and higher monthly household income had less unhealthy foods intake than those who had vaginal delivery. They need to be accounted for in educational programs and interventions focused on healthy diet recommendations in puerperium.
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22
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Wang H, Chen L, Cao Y, Xie K, Wang C, Pei P, Guo Y, Bragg F, Yu M, Chen Z, Li L. Association between frequency of dairy product consumption and hypertension: a cross-sectional study in Zhejiang Province, China. Nutr Metab (Lond) 2022; 19:67. [PMID: 36180916 PMCID: PMC9526303 DOI: 10.1186/s12986-022-00703-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Hypertension, a well-known risk factor, contributes to millions of deaths from cardiovascular and renal diseases worldwide. However, evidence on the association between frequency of dairy product consumption and hypertension is inconsistent. METHODS The data for the present study are from the Tongxiang baseline dataset of the China Kadoorie Biobank prospective study. A total of 53,916 participants aged 30-79 years were included in the final analysis. Multivariable logistic regression was utilized to evaluate the association of dairy product consumption with hypertension, and multiple linear regression was conducted to assess the association of dairy product consumption with systolic and diastolic blood pressure. RESULTS Of the 53,916 participants, 2.6% reported consuming dairy products weekly, and 44.4% had prevalent hypertension. After adjusting for socio-demographic status, lifestyle factors, BMI, waist circumference, sleep duration and snoring, when compared with participants who never consumed dairy products, the odds ratios (95% CI) for hypertension among those consuming dairy products less than once per week, and ≥ 1 time per week were 0.85 (0.77-0.95) and 0.74 (0.65-0.84), respectively. The corresponding odds ratios (95% CI) for men were 0.85 (0.71-1.02) and 0.75 (0.61-0.92), respectively (Ptrend = 0.001), and for women were 0.88 (0.76-1.01) and 0.77 (0.65-0.91), respectively. (Ptrend < 0.001). CONCLUSIONS In this large epidemiological study, higher frequency of dairy product consumption is associated with significantly lower odds of hypertension among Chinese adults.
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Affiliation(s)
- Hao Wang
- grid.433871.aDepartment of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, #3399 Binsheng road, Binjiang District, Hangzhou, Zhejiang Province China
| | - Lingli Chen
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Yuan Cao
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Kaixu Xie
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Chunmei Wang
- Department of NCDs Control and Prevention, Tongxiang City Center for Disease Control and Prevention, Tongxiang, China
| | - Pei Pei
- grid.11135.370000 0001 2256 9319Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yu Guo
- grid.415105.40000 0004 9430 5605National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Fiona Bragg
- grid.4991.50000 0004 1936 8948Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- grid.4991.50000 0004 1936 8948Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Min Yu
- grid.433871.aDepartment of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, #3399 Binsheng road, Binjiang District, Hangzhou, Zhejiang Province China
| | - Zhengming Chen
- grid.4991.50000 0004 1936 8948Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- grid.4991.50000 0004 1936 8948Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liming Li
- grid.11135.370000 0001 2256 9319Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- grid.11135.370000 0001 2256 9319Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
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Associations of plasma carnitine, lysine, trimethyllysine and glycine with incident ischemic stroke: Findings from a nested case-control study. Clin Nutr 2022; 41:1889-1895. [DOI: 10.1016/j.clnu.2022.07.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 06/24/2022] [Accepted: 07/06/2022] [Indexed: 02/06/2023]
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Pan L, Chen L, Lv J, Pang Y, Guo Y, Pei P, Du H, Yang L, Millwood IY, Walters RG, Chen Y, Gong W, Chen J, Yu C, Chen Z, Li L. Association of egg consumption, metabolic markers, and risk of cardiovascular diseases: A nested case-control study. eLife 2022; 11:72909. [PMID: 35607895 PMCID: PMC9129873 DOI: 10.7554/elife.72909] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 04/29/2022] [Indexed: 11/13/2022] Open
Abstract
Background Few studies have assessed the role of individual plasma cholesterol levels in the association between egg consumption and the risk of cardiovascular diseases. This research aims to simultaneously explore the associations of self-reported egg consumption with plasma metabolic markers and these markers with the risk of cardiovascular disease (CVD). Methods Totally 4778 participants (3401 CVD cases subdivided into subtypes and 1377 controls) aged 30-79 were selected based on the China Kadoorie Biobank. Targeted nuclear magnetic resonance was used to quantify 225 metabolites in baseline plasma samples. Linear regression was conducted to assess associations between self-reported egg consumption and metabolic markers, which were further compared with associations between metabolic markers and CVD risk. Results Egg consumption was associated with 24 out of 225 markers, including positive associations for apolipoprotein A1, acetate, mean HDL diameter, and lipid profiles of very large and large HDL, and inverse associations for total cholesterol and cholesterol esters in small VLDL. Among these 24 markers, 14 were associated with CVD risk. In general, the associations of egg consumption with metabolic markers and of these markers with CVD risk showed opposite patterns. Conclusions In the Chinese population, egg consumption is associated with several metabolic markers, which may partially explain the protective effect of moderate egg consumption on CVD. Funding This work was supported by the National Natural Science Foundation of China (81973125, 81941018, 91846303, 91843302). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 81390541, 81390544), and Chinese Ministry of Science and Technology (2011BAI09B01). The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report, or the decision to submit the article for publication.
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Affiliation(s)
- Lang Pan
- Department of Epidemiology and Biostatistics, Peking UniversityBeijingChina
| | - Lu Chen
- Department of Epidemiology and Biostatistics, Peking UniversityBeijingChina
| | - Jun Lv
- Department of Epidemiology and Biostatistics, Peking UniversityBeijingChina
- Peking University Center for Public Health and Epidemic Preparedness & ResponseBeijingChina
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of EducationBeijingChina
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, Peking UniversityBeijingChina
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular DiseasesBeijingChina
| | - Pei Pei
- Chinese Academy of Medical SciencesBeijingChina
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Weiwei Gong
- NCDs Prevention and Control Department, Zhejiang CDCHangzhouChina
| | - Junshi Chen
- China National Center for Food Safety Risk AssessmentBeijingChina
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, Peking UniversityBeijingChina
- Peking University Center for Public Health and Epidemic Preparedness & ResponseBeijingChina
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Liming Li
- Department of Epidemiology and Biostatistics, Peking UniversityBeijingChina
- Peking University Center for Public Health and Epidemic Preparedness & ResponseBeijingChina
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Kakkoura MG, Du H, Guo Y, Yu C, Yang L, Pei P, Chen Y, Sansome S, Chan WC, Yang X, Fan L, Lv J, Chen J, Li L, Key TJ, Chen Z. Dairy consumption and risks of total and site-specific cancers in Chinese adults: an 11-year prospective study of 0.5 million people. BMC Med 2022; 20:134. [PMID: 35513801 PMCID: PMC9074208 DOI: 10.1186/s12916-022-02330-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 03/10/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Previous studies of primarily Western populations have reported contrasting associations of dairy consumption with certain cancers, including a positive association with prostate cancer and inverse associations with colorectal and premenopausal breast cancers. However, there are limited data from China where cancer rates and levels of dairy consumption differ importantly from those in Western populations. METHODS The prospective China Kadoorie Biobank study recruited ~0.5 million adults from ten diverse (five urban, five rural) areas across China during 2004-2008. Consumption frequency of major food groups, including dairy products, was collected at baseline and subsequent resurveys, using a validated interviewer-administered laptop-based food frequency questionnaire. To quantify the linear association of dairy intake and cancer risk and to account for regression dilution bias, the mean usual consumption amount for each baseline group was estimated via combining the consumption level at both baseline and the second resurvey. During a mean follow-up of 10.8 (SD 2.0) years, 29,277 incident cancer cases were recorded among the 510,146 participants who were free of cancer at baseline. Cox regression analyses for incident cancers associated with usual dairy intake were stratified by age-at-risk, sex and region and adjusted for cancer family history, education, income, alcohol intake, smoking, physical activity, soy and fresh fruit intake, and body mass index. RESULTS Overall, 20.4% of participants reported consuming dairy products (mainly milk) regularly (i.e. ≥1 day/week), with the estimated mean consumption of 80.8 g/day among regular consumers and of 37.9 g/day among all participants. There were significant positive associations of dairy consumption with risks of total and certain site-specific cancers, with adjusted HRs per 50 g/day usual consumption being 1.07 (95% CI 1.04-1.10), 1.12 (1.02-1.22), 1.19 (1.01-1.41) and 1.17 (1.07-1.29) for total cancer, liver cancer (n = 3191), female breast cancer (n = 2582) and lymphoma (n=915), respectively. However, the association with lymphoma was not statistically significant after correcting for multiple testing. No significant associations were observed for colorectal cancer (n = 3350, 1.08 [1.00-1.17]) or other site-specific cancers. CONCLUSION Among Chinese adults who had relatively lower dairy consumption than Western populations, higher dairy intake was associated with higher risks of liver cancer, female breast cancer and, possibly, lymphoma.
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Affiliation(s)
- Maria G Kakkoura
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Pei Pei
- Chinese Academy of Medical Sciences, Beijing, China
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sam Sansome
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Wing Ching Chan
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiaoming Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lei Fan
- NCDs Prevention and Control Department, Henan CDC, Zhengzhou, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Timothy J Key
- Cancer Epidemiology Unit (CEU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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26
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Pan L, Chen L, Lv J, Pang Y, Guo Y, Pei P, Du H, Yang L, Millwood IY, Walters RG, Chen Y, Hua Y, Sohoni R, Sansome S, Chen J, Yu C, Chen Z, Li L. Association of Red Meat Consumption, Metabolic Markers, and Risk of Cardiovascular Diseases. Front Nutr 2022; 9:833271. [PMID: 35495958 PMCID: PMC9051033 DOI: 10.3389/fnut.2022.833271] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 03/21/2022] [Indexed: 11/13/2022] Open
Abstract
Objective The metabolic mechanism of harmful effects of red meat on the cardiovascular system is still unclear. The objective of the present study is to investigate the associations of self-reported red meat consumption with plasma metabolic markers, and of these markers with the risk of cardiovascular diseases (CVD). Methods Plasma samples of 4,778 participants (3,401 CVD cases and 1,377 controls) aged 30-79 selected from a nested case-control study based on the China Kadoorie Biobank were analyzed by using targeted nuclear magnetic resonance to quantify 225 metabolites or derived traits. Linear regression was conducted to evaluate the effects of self-reported red meat consumption on metabolic markers, which were further compared with the effects of these markers on CVD risk assessed by logistic regression. Results Out of 225 metabolites, 46 were associated with red meat consumption. Positive associations were observed for intermediate-density lipoprotein (IDL), small high-density lipoprotein (HDL), and all sizes of low-density lipoprotein (LDL). Cholesterols, phospholipids, and apolipoproteins within various lipoproteins, as well as fatty acids, total choline, and total phosphoglycerides, were also positively associated with red meat consumption. Meanwhile, 29 out of 46 markers were associated with CVD risk. In general, the associations of metabolic markers with red meat consumption and of metabolic markers with CVD risk showed consistent direction. Conclusions In the Chinese population, red meat consumption is associated with several metabolic markers, which may partially explain the harmful effect of red meat consumption on CVD.
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Affiliation(s)
- Lang Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Lu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
- Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing, China
| | - Pei Pei
- National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Robin G Walters
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Yujie Hua
- Noncommunicable Diseases Prevention and Control Department, Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Rajani Sohoni
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Sam Sansome
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
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