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Zheng C, Liu Y, Xu C, Zeng S, Wang Q, Guo Y, Li J, Li S, Dong M, Luo X, Wu Q. Association between obesity and the prevalence of dyslipidemia in middle-aged and older people: an observational study. Sci Rep 2024; 14:11974. [PMID: 38796639 PMCID: PMC11127928 DOI: 10.1038/s41598-024-62892-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/22/2024] [Indexed: 05/28/2024] Open
Abstract
This study aimed to explore the link between various forms of obesity, including body mass index (BMI) and waist circumference (WC), and the risk of dyslipidemia among Chinese residents. We selected the study population through a multi-stage random sampling method from permanent residents aged 35 and older in Ganzhou. Obesity was categorized as non-obesity, general obesity, central obesity, or compound obesity according to established diagnostic criteria. We employed a logistic regression model to assess the relationship between different types of obesity and the risk of dyslipidemia. Additionally, we used the restricted cubic spline model to analyze the association between BMI, WC, and the risk of dyslipidemia. The study included 2030 residents aged 35 or older from Ganzhou, China. The prevalence of dyslipidemia was found to be 39.31%, with an age-standardized prevalence of 36.51%. The highest prevalence of dyslipidemia, 58.79%, was observed among those with compound obesity. After adjusting for confounding factors, we found that the risk of dyslipidemia in those with central and compound obesity was respectively 2.00 (95% CI 1.62-2.46) and 2.86 (95% CI 2.03-4.03) times higher than in the non-obese population. Moreover, the analysis using the restricted cubic spline model indicated a nearly linear association between BMI, WC, and the risk of dyslipidemia. The findings emphasize the significant prevalence of both dyslipidemia and obesity among adults aged 35 and above in Ganzhou, China. Notably, individuals with compound obesity are at a substantially increased risk of dyslipidemia. Therefore, it is crucial to prioritize the use of BMI and WC as screening and preventive measures for related health conditions.
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Affiliation(s)
- Chuanlei Zheng
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Yanhong Liu
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Cong Xu
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Shaobo Zeng
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Qi Wang
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Yixing Guo
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Jian Li
- School of Basic Medicine, Gannan Medical University, Ganzhou, 341000, China
| | - Sisi Li
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Minghua Dong
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China
| | - Xiaoting Luo
- Division of Academic Affairs, Gannan Medical University, Ganzhou, 341000, China
| | - Qingfeng Wu
- School of Public Health and Health Management, Gannan Medical University, Ganzhou, 341000, China.
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Liang C, Lee PF, Yeh PC. Relationship between Regular Leisure-Time Physical Activity and Underweight and Overweight Status in Taiwanese Young Adults: A Cross-Sectional Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:284. [PMID: 36612603 PMCID: PMC9819382 DOI: 10.3390/ijerph20010284] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/18/2022] [Accepted: 12/20/2022] [Indexed: 06/16/2023]
Abstract
The aim of this study was to determine the association between regular leisure-time physical activity (LTPA) and various body mass index (BMI) categories in Taiwanese young adults. A total of 10,802 young adults (18−44 years) were enrolled in a national telephone survey. The questionnaire data from this survey included socio-demographic characteristics, zip code of residence, LTPA behaviors, self-reported health status, and self-evaluated anthropometric measurements, which included height, body weight, and BMI. Regular and non-regular LTPA behaviors were defined as follows: (1) Regular LTPA: participants who reported breathing quickly and sweating when participating in 150−300 min per week of moderate-intensity LTPA or 75−150 min per week of vigorous-intensity LTPA. (2) Non-regular LTPA: the rest of the participants. The various BMI categories were defined as (1) underweight (BMI < 18.5 kg/m2), (2) normal weight (18.5 ≤ BMI < 24 kg/m2), (3) overweight (24 ≤ BMI < 27 kg/m2), and (4) obese (BMI ≥ 27 kg/m2). When compared with participants with non-regular LTPA, participants with regular LTPA exhibited lower risks of being overweight (odds ratio [OR], 0.837; 95% confidence interval [CI] 0.738−0.948) and underweight (OR, 0.732; 95% CI 0.611−0.876). However, there was no significant relationship between regular LTPA and obesity risk when using non-regular LTPA as the baseline after adjusting for potential confounders. The study results revealed that regular LTPA effectively reduced the risks of being underweight and overweight. However, for people with obesity, regular LTPA was unable to significantly decrease their obesity risk.
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Affiliation(s)
- Chyi Liang
- Graduate Institute of Sport, Leisure and Hospitality Management, National Taiwan Normal University, Taipei City 106, Taiwan
| | - Po-Fu Lee
- Department of Leisure Industry and Health Promotion, National Ilan University, Yilan County 260, Taiwan
- College of Humanities and Management, National Ilan University, Yilan County 260, Taiwan
- Exercise and Recreation Development Center, National Ilan University, Yilan County 260, Taiwan
| | - Ping-Chun Yeh
- Graduate Institute of Business Administration, Fu Jen Catholic University, New Taipei City 242, Taiwan
- Sports Medicine Center, Fu Jen Catholic University Hospital, New Taipei City 243, Taiwan
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Zhang X, Wang Y, Huang F, Zhang B, Wang Z, Du S, Wang H. Multiple trajectories of any intensities of physical activity are better than sustained sedentary time on improving waist circumference and body mass index among Chinese adults: China Health and Nutrition Survey, 2004-2018. Nutr Res 2022; 107:1-11. [PMID: 36156350 PMCID: PMC10026591 DOI: 10.1016/j.nutres.2022.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/04/2022] [Accepted: 08/08/2022] [Indexed: 02/02/2023]
Abstract
Higher levels of physical activity (PA) may be associated with more favorable measures of adiposity, and sedentary time (ST) is associated with adverse health outcomes independent of PA. We hypothesized that multiple routes of different PA intensities PA combined with ST would be associated with coexisting latent waist circumference (WC) and body mass index (BMI) trajectories among Chinese adults. Thus, we aimed to determine multiple routes of PA and ST and their associations with trajectories of WC and BMI. We used data from 13 137 adults in the China Health and Nutrition Survey between 2004 and 2018. Using group-based multitrajectory modeling, we determined multiple trajectories of light-, moderate-, and vigorous-intensity PA (LPA, MPA) and ST (PA trajectories) and concurrent WC and BMI trajectories. Then, we explored logit regressions between them. We identified 4 PA trajectories. The majority (high LPA, 43.5%) exhibited decreasing high LPA levels. The rest were high ST (9.0%), decreased MPA (15.8%), and high vigorous-intensity PA (31.7%). People with high ST showed higher odds of having abdominal obesity (odds ratio [OR] = 2.23) or severe abdominal obesity (OR = 1.73) than those with decreased MPA (OR = 1.85 and 1.71) and high LPA (OR = 1.43 for abdominal obesity). They also showed higher odds of being overweight (OR = 1.73) than those with decreased MPA (OR = 1.58) and high LPA (OR = 1.39). Any level of PA is better than sustained ST for improving adiposity indicators among Chinese adults.
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Affiliation(s)
- Xiaofan Zhang
- National Institute for Nutrition and Health, Chinese center for disease control and prevention; Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Yun Wang
- National Institute for Nutrition and Health, Chinese center for disease control and prevention; Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Feifei Huang
- National Institute for Nutrition and Health, Chinese center for disease control and prevention; Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Bing Zhang
- National Institute for Nutrition and Health, Chinese center for disease control and prevention; Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Zhihong Wang
- National Institute for Nutrition and Health, Chinese center for disease control and prevention; Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China
| | - Shufa Du
- Department of Nutrition and Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Huijun Wang
- National Institute for Nutrition and Health, Chinese center for disease control and prevention; Key Laboratory of Trace Element Nutrition, National Health Commission of the People's Republic of China, Beijing 100050, China.
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Zhao R, Zhao L, Gao X, Yang F, Yang Y, Fang H, Ju L, Xu X, Guo Q, Li S, Cheng X, Cai S, Yu D, Ding G. Geographic Variations in Dietary Patterns and Their Associations with Overweight/Obesity and Hypertension in China: Findings from China Nutrition and Health Surveillance (2015-2017). Nutrients 2022; 14:nu14193949. [PMID: 36235601 PMCID: PMC9572670 DOI: 10.3390/nu14193949] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 09/14/2022] [Accepted: 09/21/2022] [Indexed: 02/07/2023] Open
Abstract
Regional dietetic cultures were indicated in China, but how dietary patterns geographically varied across China is unknown. Few studies systematically investigated the association of dietary patterns with overweight/obesity and hypertension and the potential mechanism with a national sample. This study included 34,040 adults aged 45 years and older from China Nutrition and Health Surveillance (2015−2017), who had complete outcome data, reliable intakes of calorie and cooking oils, unchanged diet habits, and without diagnosed cancer or cardiovascular disease. Outcomes were overweight/obesity and hypertension. By using the Gaussian finite mixture models, four dietary patterns were identified—common rice-based dietary pattern (CRB), prudent diversified dietary pattern (PD), northern wheat-based dietary pattern (NWB), and southern rice-based dietary pattern (SRB). Geographic variations in dietary patterns were depicted by age−sex standardized proportions of each pattern across 31 provinces in China. We assessed the association of these dietary patterns with outcomes and calculated the proportion mediated (PM) by overweight/obesity in the association of the dietary patterns with hypertension. Evident geographic disparities in dietary patterns across 31 provinces were observed. With CRB as reference group and covariates adjusted, the NWB had higher odds of being overweight/obese (odds ratio (OR) = 1.44, 95% confidence interval (CI): 1.36−1.52, p < 0.001) and hypertension (OR = 1.07, 95%CI: 1.01−1.14, p < 0.001, PM = 43.2%), while the SRB and the PD had lower odds of being overweight/obese (ORs = 0.84 and 0.92, 95%CIs: 0.79−0.89 and 0.85−0.99, p < 0.001 for both) and hypertension (ORs = 0.93 and 0.87, 95%CIs: 0.87−0.98 and 0.80−0.94, p = 0.038 for SRB and p < 0.001 for PD, PMs = 27.8% and 9.9%). The highest risk of overweight/obesity in the NWB presented in relatively higher carbohydrate intake (about 60% of energy) and relatively low fat intake (about 20% of energy). The different trends in the association of protein intake with overweight/obesity among dietary patterns were related to differences in animal food sources. In conclusion, the geographic distribution disparities of dietary patterns illustrate the existence of external environment factors and underscore the need for geographic-targeted dietary actions. Optimization of the overall dietary pattern is the key to the management of overweight/obesity and hypertension in China, with the emphasis on reducing low-quality carbohydrate intake, particularly for people with the typical northern diet, and selection of animal foods, particularly for people with the typical southern diet.
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Affiliation(s)
- Rongping Zhao
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Liyun Zhao
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Xiang Gao
- Department of Nutritional Sciences, The Pennsylvania State University, State College, PA 16802, USA
| | - Fan Yang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Yuxiang Yang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Hongyun Fang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Lahong Ju
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Xiaoli Xu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Qiya Guo
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Shujuan Li
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Xue Cheng
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Shuya Cai
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Dongmei Yu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
- Correspondence: (D.Y.); (G.D.)
| | - Gangqiang Ding
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
- Correspondence: (D.Y.); (G.D.)
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Guo Q, Xue T, Wang B, Cao S, Wang L, Zhang JJ, Duan X. Effects of physical activity intensity on adulthood obesity as a function of long-term exposure to ambient PM 2.5: Observations from a Chinese nationwide representative sample. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 823:153417. [PMID: 35093342 DOI: 10.1016/j.scitotenv.2022.153417] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 01/09/2022] [Accepted: 01/21/2022] [Indexed: 06/14/2023]
Abstract
Long-term exposure to PM2.5 has been associated with increased obesity risk, while physical activity (PA) is a suggested protective factor. This raises a dilemma whether the increased dose of PM2.5 due to PA-intensified ventilation would offset the benefits of PA. Using a national representative sample, we aim to (1) ascertain inclusive findings of the association between PA and obesity, and (2) examine whether PM2.5 exposure modifies the PA-obesity relationship. We recruited 91,121 Chinese adults from 31 provinces using a multi-stage stratified-clustering random sampling method. PM2.5 was estimated using a validated machine learning method with a spatial resolution of 0.1° × 0.1°. PA intensity was calculated as metabolic equivalent (MET)-hour/week by summing all activities. Body weight, height, and waist circumference (WC) were measured after overnight fasting. Obesity-related traits included continuous outcomes (Body mass index [BMI], WC, and waist-to-height ratio (WHtR)) and binomial outcomes (general obesity, abdominal obesity, and WHtR obesity). Generalized linear regression models were used to estimate the interaction effects between PM2.5 and PA on obesity, controlling for covariates. The results indicated that each IQR increase in PA was associated with 0.078 (95% CI: -0.096 to -0.061) kg/m2, 0.342 (-0.389 to -0.294) cm, and 0.0022 (-0.0025 to -0.0019) decrease in BMI, WC, and WHtR, respectively. The joint association showed that benefits of PA on obesity were attenuated as PM2.5 increased. Risk of abdominal obesity decreased 11.3% (OR = 0.887, 95% CI: 0.866, 0.908) per IQR increase in PA among the low-PM2.5 (≤55.9 μg/m3) exposure group, but only 5.5% (OR = 0.945, 95% CI: 0.930, 0.960) among the high-PM2.5 (>55.9 μg/m3) exposure group. We concluded the increase in PA intensity was significantly associated with lower risk of obesity in adults living across mainland China, where annual level of PM2.5 were mostly exceeding the standard. Reducing PM2.5 exposure would enhance the PA benefits as a risk reduction strategy.
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Affiliation(s)
- Qian Guo
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Tao Xue
- Institute of Reproductive and Child Health, Ministry of Health Key Laboratory of Reproductive Health, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100083, China
| | - Beibei Wang
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Suzhen Cao
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Limin Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Junfeng Jim Zhang
- Nicholas School of the Environment and Global Health Institute, Duke University, Durham, NC, USA; Duke Kunshan University, Kunshan, Jiangsu Province, China
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.
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Mo Z, Wang H, Zhang B, Ding G, Popkin BM, Du S. The Effects of Physical Activity and Sedentary Behaviors on Overweight and Obesity among Boys may Differ from those among Girls in China: An Open Cohort Study. J Nutr 2022; 152:1274-1282. [PMID: 35018425 PMCID: PMC9071318 DOI: 10.1093/jn/nxab446] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 11/04/2021] [Accepted: 12/24/2021] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Childhood overweight and obesity are increasing steadily in China, yet few studies have focused on exploring the risk factors associated with sex differences. OBJECTIVES We tested the hypothesis that the effects of physical activity and sedentary behaviors on overweight and obesity differ between boys and girls. METHODS We used data collected from 4520 children and adolescents aged 6-18 y from 2004 to 2015 in an ongoing open-cohort study, the China Health and Nutrition Survey, to explore the effects of physical activity and sedentary behaviors on the risk of overweight and obesity in Chinese children and adolescents. We collected detailed information on physical activity and sedentary behavior along with dietary data, and we measured height and weight with standardized methods. We used random-effects logistic regression models to analyze the associations between total physical activity and sedentary behavior and overweight and obesity. RESULTS The effects of sedentary behaviors and vigorous physical activity were only significant among girls. Vigorous physical activity decreased the risk of overweight and obesity by 63% (OR: 0.37; 95% CI: 0.20, 0.67) among girls ages 6-11 y and by 54% (OR: 0.46; 95% CI: 0.25, 0.85) among girls ages 12-18 y. High sedentary-hour values increased the risk by 96% (OR: 1.96; 95% CI: 1.09, 3.54) among girls ages 12-18 y. None of the effects were significant among boys. CONCLUSION Low physical activity and high sedentary time increase the risk of overweight and obesity, particularly among adolescent girls. The effects of physical activity and sedentary behaviors on overweight and obesity among boys may differ from those among girls. Sex effects should be taken into consideration when promoting physical activity. Whether this sex difference is a result of high male preferences in China that preclude many activities among boys or other factors requires further study.
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Affiliation(s)
- Zhe Mo
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China
| | - Huijun Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Bing Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Gangqiang Ding
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Barry M Popkin
- Department of Nutrition and Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Shufa Du
- Department of Nutrition and Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Health Behaviors of Austrian Secondary School Teachers and Principals at a Glance: First Results of the From Science 2 School Study Focusing on Sports Linked to Mixed, Vegetarian, and Vegan Diets. Nutrients 2022; 14:nu14051065. [PMID: 35268041 PMCID: PMC8912656 DOI: 10.3390/nu14051065] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/17/2022] [Accepted: 03/01/2022] [Indexed: 12/12/2022] Open
Abstract
Lifestyle behaviors are key contributors to sustainable health and well-being over the lifespan. The analysis of health-related behaviors is crucial for understanding the state of health in different populations, especially teachers who play a critical role in establishing the lifelong health behaviors of their pupils. This multidisciplinary, nationwide study aimed to assess and compare lifestyle patterns of Austrian teachers and school principals at secondary levels I and II with a specific focus on physical activity and diet. A total number of 1350 teachers (1.5% of the eligible Austrian sample; 69.7% females; 37.7% from urban areas; mean age: 45.8 ± 11.4 years; mean BMI: 24.2 ± 4.0) completed a standardized online survey following an epidemiological approach. Across the total sample, 34.4% were overweight/obese with a greater prevalence of overweight/obesity in males than females (49.5% vs. 29.2%, p < 0.01) and rural vs. urban environments (35.9% vs. 31.3%). Most participants (89.3%) reported a mixed diet, while 7.9% and 2.9% were vegetarians and vegans, respectively. The average BMI of teachers with mixed diets (24.4 ± 4.0 kg/m2) was significantly higher than vegetarians (23.1 ± 3.2 kg/m2) and vegans (22.7 ± 4.3 kg/m2). Vegans reported a lower level of alcohol intake (p < 0.05) among dietary groups. There was no between-group difference in smoking (p > 0.05). The prevalence of engagement in regular physical activity was 88.7% for leisure-time sports/exercises and 29.2% for club sports. Compared with the previous reports on general populations, the present data suggest an acceptable overall health status among Austrian teachers.
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Associations of changes in physical activity and discretionary screen time with incident obesity and adiposity changes: longitudinal findings from the UK Biobank. Int J Obes (Lond) 2022; 46:597-604. [PMID: 34853431 DOI: 10.1038/s41366-021-01033-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/11/2021] [Accepted: 11/18/2021] [Indexed: 11/09/2022]
Abstract
BACKGROUND Physical activity (PA) and discretionary screen time (DST; television and computer use during leisure) are both associated with obesity risk, but little longitudinal evidence exists on their combined influence. This study examined the independent and joint associations of changes in PA and DST with incident obesity, body mass index (BMI) and waist circumference (WC). METHODS We analysed the data of individuals aged 40-69 years from the UK Biobank, a large-scale, population-based prospective cohort study. PA was measured using the International Physical Activity Questionnaire and DST was defined as the total of daily TV viewing and non-occupational computer use. Changes in PA and DST over time were defined using departure from sex-specific baseline tertiles and categorised as worsened (PA decreased/DST increased), maintained, and improved (PA increased/DST decreased). We then used each exposure change to define a joint PA-DST change variable with nine mutually exclusive groups. We used multivariable adjusted mixed-effects linear and Poisson models to examine the independent and joint associations between PA and DST changes with BMI and WC and incident obesity, respectively. Development of a BMI ≥ 30 kg/m2 was defined as incident obesity. RESULTS Among 30,735 participants, 1,628 (5.3%) developed incident obesity over a mean follow-up of 6.9 (2.2) years. In the independent association analyses, improving PA (Incident Rate Ratio (IRR) 0.46 (0.38-0.56)) was associated with a lower risk of incident obesity than maintaining PA, maintaining DST, or improving DST. Compared to the referent group (both PA and DST worsened), all other combinations of PA and DST changes were associated with lower incident obesity risk in the joint association analyses. We observed substantial beneficial associations in the improved PA groups, regardless of DST change [e.g., DST worsened (IRR 0.31 (0.21-0.44)), maintained (IRR 0.34 (0.25-0.46)), or improved (IRR 0.35 (0.22-0.56)]. The most pronounced decline in BMI and WC was observed when PA was maintained or improved and DST was maintained. CONCLUSION We found that improved PA had the most pronounced beneficial associations with incident obesity, irrespective of DST changes. Improvements in PA or DST mutually attenuated the deleterious effects of the other behaviour's deterioration.
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Wang J, He L, Yang N, Li Z, Xu L, Li W, Ping F, Zhang H, Li Y. Occupational and domestic physical activity and diabetes risk in adults: Results from a long-term follow-up cohort. Front Endocrinol (Lausanne) 2022; 13:1054046. [PMID: 36568093 PMCID: PMC9780271 DOI: 10.3389/fendo.2022.1054046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Physical activity (PA) has been associated with decreased incidence of diabetes. However, few studies have evaluated the influence of occupational and domestic PA on the risk of diabetes with a long-term follow-up. We aimed to examine the association between occupational and domestic PA and the risk of diabetes in a long-term prospective cohort of Chinese adults. METHODS A total of 10,343 adults who were followed up in the China Health and Nutrition Survey from 1997 to 2015 were included in our analysis. Occupational and domestical PA were collected with detailed seven-day data and were converted into metabolic equivalents values. Total PA included occupational, domestic, transportation, and leisure time PA. Diabetes cases were identified by self-reported doctor/health professional diagnosis of diabetes, fasting blood glucose ≥7.0 mmol/L, and glycosylated hemoglobin (HbA1c) ≥6.5%. Cox proportional hazards models were used to calculate hazard ratios (HR) and 95% confidence intervals (CI). RESULTS During up to 18 years of follow-up (median 10 years), there were 575 diabetes cases documented. Occupational PA accounted for the majority of total PA (68%) in Chinese population, followed by domestic PA (25%). With adjustments for possible covariates, the highest quartiles of total PA (HR, 0.728 [95% CI, 0.570-0.929]) and occupational PA (HR, 0.765 [95% CI, 0.596-0.982]) were significantly associated with a lower risk of diabetes compared with lowest quartiles. The association between domestic PA and the risk of diabetes was insignificant (P >0.05). CONCLUSION Higher levels of occupational PA were associated with a decreased risk of diabetes risk in the Chinese population. Domestic PA was not associated with the incidence of diabetes.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Yuxiu Li
- *Correspondence: Huabing Zhang, ; Yuxiu Li,
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Sagelv EH, Ekelund U, Hopstock LA, Fimland MS, Løvsletten O, Wilsgaard T, Morseth B. The bidirectional associations between leisure time physical activity change and body mass index gain. The Tromsø Study 1974-2016. Int J Obes (Lond) 2021; 45:1830-1843. [PMID: 34007009 DOI: 10.1038/s41366-021-00853-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/13/2021] [Accepted: 04/27/2021] [Indexed: 02/04/2023]
Abstract
OBJECTIVES To examine whether leisure time physical activity changes predict subsequent body mass index (BMI) changes, and conversely, whether BMI changes predict subsequent leisure time physical activity changes. METHODS This prospective cohort study included adults attending ≥3 consecutive Tromsø Study surveys (time: T1, T2, T3) during 1974-2016 (n = 10779). If participants attended >3 surveys, we used the three most recent surveys. We computed physical activity change (assessed by the Saltin-Grimby Physical Activity Level Scale) from T1 to T2, categorized as Persistently Inactive (n = 992), Persistently Active (n = 7314), Active to Inactive (n = 1167) and Inactive to Active (n = 1306). We computed BMI change from T2 to T3, which regressed on preceding physical activity changes using analyses of covariance. The reverse association (BMI change from T1 to T2 and physical activity change from T2 to T3; n = 4385) was assessed using multinomial regression. RESULTS Average BMI increase was 0.86 kg/m2 (95% CI: 0.82-0.90) from T2 to T3. With adjustment for sex, birth year, education, smoking and BMI at T2, there was no association between physical activity change from T1 to T2 and BMI change from T2 to T3 (Persistently Inactive: 0.89 kg/m2 (95% CI: 0.77-1.00), Persistently Active: 0.85 kg/m2 (95% CI: 0.81-0.89), Active to Inactive: 0.90 kg/m2 (95% CI: 0.79-1.00), Inactive to Active 0.85 kg/m2 (95% CI: 0.75-0.95), p = 0.84). Conversely, increasing BMI was associated with Persistently Inactive (odds ratio (OR): 1.17, 95% CI: 1.08-1.27, p < 0.001) and changing from Active to Inactive (OR: 1.16, 95% CI: 1.07-1.25, p < 0.001) compared with being Persistently Active. CONCLUSIONS We found no association between leisure time physical activity changes and subsequent BMI changes, whereas BMI change predicted subsequent physical activity change. These findings indicate that BMI change predicts subsequent physical activity change at population level and not vice versa.
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Affiliation(s)
- Edvard H Sagelv
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.
| | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway.,Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Laila A Hopstock
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Marius Steiro Fimland
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway.,Unicare Helsefort Rehabilitation Centre, Rissa, Norway
| | - Ola Løvsletten
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Tom Wilsgaard
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Bente Morseth
- School of Sport Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
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11
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Pan XF, Wang L, Pan A. Epidemiology and determinants of obesity in China. Lancet Diabetes Endocrinol 2021; 9:373-392. [PMID: 34022156 DOI: 10.1016/s2213-8587(21)00045-0] [Citation(s) in RCA: 601] [Impact Index Per Article: 200.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 01/15/2021] [Accepted: 02/12/2021] [Indexed: 12/11/2022]
Abstract
Obesity has become a major public health issue in China. Overweight and obesity have increased rapidly in the past four decades, and the latest national prevalence estimates for 2015-19, based on Chinese criteria, were 6·8% for overweight and 3·6% for obesity in children younger than 6 years, 11·1% for overweight and 7·9% for obesity in children and adolescents aged 6-17 years, and 34·3% for overweight and 16·4% for obesity in adults (≥18 years). Prevalence differed by sex, age group, and geographical location, but was substantial in all subpopulations. Strong evidence from prospective cohort studies has linked overweight and obesity to increased risks of major non-communicable diseases and premature mortality in Chinese populations. The growing burden of overweight and obesity could be driven by economic developments, sociocultural norms, and policies that have shaped individual-level risk factors for obesity through urbanisation, urban planning and built environments, and food systems and environments. Substantial changes in dietary patterns have occurred in China, with increased consumption of animal-source foods, refined grains, and highly processed, high-sugar, and high-fat foods, while physical activity levels in all major domains have decreased with increasing sedentary behaviours. The effects of dietary factors and physical inactivity intersect with other individual-level risk factors such as genetic susceptibility, psychosocial factors, obesogens, and in-utero and early-life exposures. In view of the scarcity of research around the individual and collective roles of these upstream and downstream factors, multidisciplinary and transdisciplinary studies are urgently needed to identify systemic approaches that target both the population-level determinants and individual-level risk factors for obesity in China.
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Affiliation(s)
- Xiong-Fei Pan
- Department of Epidemiology and Biostatistics and Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Limin Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - An Pan
- Department of Epidemiology and Biostatistics and Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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12
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Longitudinal association between physical activity and blood pressure, risk of hypertension among Chinese adults: China Health and Nutrition Survey 1991-2015. Eur J Clin Nutr 2021; 75:274-282. [PMID: 32404900 DOI: 10.1038/s41430-020-0653-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 04/17/2020] [Accepted: 04/29/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVES To examine the effects of physical activity (PA) in adults with or without prehypertension at baseline on systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension risk by gender. METHODS A total of 5986 men and 6525 women (≥18 years old) without hypertension-related disease at baseline who attended surveys from China Health and Nutrition Survey (1991-2015) at least twice were selected. In terms of the nested data structure, three-level random intercept growth model and three-level logistic regression were used to estimate the relationship between the PA and SBP/DBP or hypertension risk. RESULTS The incidence of hypertension increased from 10.86% in 1991 to 20.34% in 2015, and the median of PA dropped from 408 MET·h/week in 1991 to 104 MET·h/week in 2015. After adjusting confounders, PA in the third and fourth quartiles decreased SBP (by 0.98 and 0.96 mm Hg, p < 0.05) and DBP (by 0.30 and 0.38 mm Hg, p < 0.05), and it reduced the odds of hypertension by 12 and 15% (p < 0.05), compared with PA in the lowest quartile. For normotensive women in the third quartile of PA and prehypertensive women in the fourth quartile of PA, the risk of hypertension was reduced 15 and 22%, compared with women in the lowest quartile of PA. CONCLUSIONS Physical activity should be improved to the relatively high level to be effective in controlling blood pressure. Normotensive women had an association between physical activity and SBP, DBP, and the risk of hypertension.
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Liu Q, Liu F, Li J, Huang K, Yang X, Chen J, Liu X, Cao J, Shen C, Yu L, Zhao Y, Wu X, Zhao L, Li Y, Hu D, Lu X, Huang J, Gu D. Sedentary behavior and risk of incident cardiovascular disease among Chinese adults. Sci Bull (Beijing) 2020; 65:1760-1766. [PMID: 36659249 DOI: 10.1016/j.scib.2020.05.029] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 02/23/2020] [Accepted: 03/26/2020] [Indexed: 01/21/2023]
Abstract
Although emerging studies from high-income countries investigated the relationship between sedentary behavior (SB) and cardiovascular risk, little evidence came from developing countries. Moreover, the benefits of reallocating time from SB to physical activity (PA) on incident cardiovascular disease (CVD) are unknown. Using three cohorts from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project, we included 93 110 adults who were free from CVD at baseline. Cox proportional hazards models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD, including stroke, coronary heart disease, and CVD death. Isotemporal substitution models were applied to estimate the per-hour effects of replacing SB with PA. After 5.8 years follow-up, 3799 CVD cases were identified. A gradient positive association between sedentary time and incident CVD was observed. Relative to those with < 5 h/d sedentary time, the multivariable-adjusted HRs (95% CIs) of CVD incidence were 1.07(0.96-1.20), 1.27(1.13-1.43) and 1.51(1.34-1.70) for those having 5-<8, 8-<10, and ≥ 10 h/d sedentary time, respectively. When participants were cross-classified by SB and moderate to vigorous physical activity (MVPA) level, the CVD risk was highest in those with ≥ 10 h/d SB and < 150 min/week MVPA. Among those who reported ≥ 5 h/d sedentary time, per-hour substitution of SB with light, moderate, and vigorous PA reduced incident CVD risk by 5%, 6%, and 8%, respectively. The study first found that sedentary time was associated with increased incident CVD risk among Chinese adults and that substitution of SB with PA of any intensity could convey cardiovascular benefits among those with ≥ 5 h/d SB.
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Affiliation(s)
- Qiong Liu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Jianxin Li
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Keyong Huang
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xueli Yang
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Jichun Chen
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou 510080, China
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou 350014, China
| | - Yingxin Zhao
- Shandong First Medical University, Jinan 271099, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu 610041, China
| | - Liancheng Zhao
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Ying Li
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Dongsheng Hu
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen 518071, China; Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Jianfeng Huang
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China; Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China; School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China.
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Fan J, Ding C, Gong W, Yuan F, Ma Y, Feng G, Song C, Liu A. The Relationship between Leisure-Time Sedentary Behaviors and Metabolic Risks in Middle-Aged Chinese Women. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17197171. [PMID: 33007979 PMCID: PMC7594022 DOI: 10.3390/ijerph17197171] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 09/28/2020] [Accepted: 09/29/2020] [Indexed: 01/11/2023]
Abstract
The prevalence of metabolic diseases has increased over the past few decades, and epidemiological studies suggest that metabolic diseases may be associated with lifestyle. The purpose of the present study was to investigate the relationship between leisure-time sedentary behaviors (LTSBs) and metabolic risks in middle-aged women in China. Data came from the China National Nutrition and Health Surveillance (CNNHS) in 2010–2012. A total of 2643 women aged 46 to 53 years were involved. Multiple linear regression was used to examine the association of leisure-time sedentary duration (LTSD) with total cholesterol (TC), triglyceride (TG), waist circumference (WC), and body mass index (BMI). Restrictive cubic splines (RCS) were used to plot the curves between LTSD and the risk of metabolic diseases. Region, education, income, alcohol consumption, exercise, daily energy intake, and fat energy ratio were adjusted for all models. After adjusting for potential influencing factors, the results of multiple linear regression showed that for each additional hour increase in LTSD, TC and TG increased by 0.03 mmol/L and 0.04 mmol/L, respectively. The results of RCS curves showed that the risks of MetS (p for trend = 0.0276), obesity (p for trend = 0.0369), hypertension (p for trend = 0.0062), and hypercholesteremia (p for trend = 0.0033) increased with the increase in LTSD. LTSB was associated with the risks of MetS, obesity, hypertension, and hypercholesteremia in middle-aged women. Reducing LTSD may be an effective way of preventing metabolic diseases in middle-aged women.
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Affiliation(s)
| | | | | | | | | | | | | | - Ailing Liu
- Correspondence: ; Tel.: +86-10-6623-7059
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15
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Liu Y, Wang X, Zhou S, Wu W. The association between spatial access to physical activity facilities within home and workplace neighborhoods and time spent on physical activities: evidence from Guangzhou, China. Int J Health Geogr 2020; 19:22. [PMID: 32563255 PMCID: PMC7305624 DOI: 10.1186/s12942-020-00216-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 06/15/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Urban residents from the developing world have increasingly adopted a sedentary lifestyle and spend less time on physical activities (PA). Previous studies on the association between PA facilities and individuals' PA levels are based on the assumption that individuals have opportunities to use PA facilities within neighborhoods all day long, ignoring the fact that their willingness and opportunities to use nearby facilities depend on how much discretionary time (any time when people have a choice what to do) they have. Further, scant attention has been paid to the influence of PA facilities within both residential and workplace neighborhoods in the dense urban context. To address the above research gaps, this study investigated the links between the spatial access to PA facilities within home/workplace neighborhoods and time spent on PA among working adults, focusing on whether results were different when different measures of accessibility were used and whether participants' discretionary time over a week affected their time spent on PA. METHOD This study used data from a questionnaire survey (n = 1002) in Guangzhou between June and July 2017 and point of interest (POI) data from online mapping resources. Outcome variables included the amount of time spent on physical activity/moderate and vigorous intensity physical activity (PA/MVPA) over the past week. Home/workplace neighborhoods were measured as different distance buffers (500 m circular buffers, 1000 m circular buffers, and 1080 m network buffers) around each respondent's home/workplace. Spatial access to PA facilities was measured using two indicators: the counts of PA facilities and proximity to PA facilities within home/workplace neighborhoods. The amount of discretionary time was calculated based on activity log data of working day/weekend day from the Guangzhou questionnaire survey, and regression models were used to examine relationships between the spatial access of PA facilities, the time spent on PA/MVPA, and the amount of discretionary time, adjusted for covariates. Associations were stratified by gender, age, education, and income. RESULTS Using different measures of accessibility (the counts of and proximity to PA facilities) generated different results. Specifically, participants spent more time on PA/MVPA when they lived in neighborhoods with more PA facilities and spent more time on MVPA when worked in closer proximity to PA facilities. A larger amount of discretionary time was associated with more time spent on PA/MVPA, but it did not strengthen the relationship between access to PA facilities and PA/MVPA time. In addition, relationships between access to PA facilities and PA levels varied by gender, age, education, and income. CONCLUSION This study contributes to the knowledge of PA-promoting environments by considering both the home and workplace contexts and by taking into account the temporal attributes of contextual influences. Policymakers and urban planners are advised to take into account the workplace context and the temporal variability of neighborhood influences when allocating public PA facilities and public spaces.
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Affiliation(s)
- Ye Liu
- School of Geography and Planning, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, 510275 China
- Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, 510275 China
| | - Xiaoge Wang
- School of Geography and Planning, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, 510275 China
- Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, 510275 China
| | - Suhong Zhou
- School of Geography and Planning, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, 510275 China
- Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, 510275 China
- Guangdong Provincial Engineering Research Center for Public Security and Disaster, Guangzhou, 510275 China
| | - Wenjie Wu
- College of Economics, Jinan University, Guangzhou, 510632 China
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Wennman H, Härkänen T, Hagströmer M, Jousilahti P, Laatikainen T, Mäki-Opas T, Männistö S, Tolonen H, Valkeinen H, Borodulin K. Change and determinants of total and context specific sitting in adults: A 7-year longitudinal study. J Sci Med Sport 2020; 23:596-602. [DOI: 10.1016/j.jsams.2019.12.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 12/09/2019] [Accepted: 12/15/2019] [Indexed: 12/19/2022]
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17
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Bao R, Chen ST, Wang Y, Xu J, Wang L, Zou L, Cai Y. Sedentary Behavior Research in the Chinese Population: A Systematic Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E3576. [PMID: 32443711 PMCID: PMC7277100 DOI: 10.3390/ijerph17103576] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 05/12/2020] [Accepted: 05/17/2020] [Indexed: 12/11/2022]
Abstract
Background: The negative effects of sedentary behavior (SB) on public health have been extensively documented. A large number of studies have demonstrated that high prevalence of SB is a critical factor of all-cause mortality. Globally, the frequency of SB research has continued to rise, but little is known about SB in the Chinese population. Therefore, this review was conducted to scope the research situation and to fill the gaps related to the effects of SB in the Chinese population. Methods: Using a scoping review based on York methodology, a comprehensive search of published journal articles and grey literature was carried out through 12 databases. The literature research was conducted by two authors in July 2019, and included journal articles that targeted on the Chinese population were published between 1999 and 2019. The two authors screened the records independently and included those research topics related to SB in the Chinese population. Results: The number of included studies increased from 1 to 29 per year during the analyzed period, during which, a remarkable climb happened from 8 in 2013 to 19 in July 2019. Out of the 1303 screened studies, a total of 162 studies (81 English and 81 Chinese journal articles) met the inclusion criteria in this review. Most of the included studies (66.0%) reported the overall estimated prevalence of SB, in which, 43.2% of studies reported the average time of SB, and 40.0% of studies reported the cutoff point of SB. Besides this, 54.9% and 23.5% of studies focused on the outcomes and correlates/determinants of SB, and the proportions of studies based on testing the validation of measurement tools and on interventions were 3.7% and 4.9%, respectively. Nearly all of the reviewed articles used data from cross-sectional studies (75.9%) and longitudinal studies (13.6%), while intervention trials are less developed. The majority of the studies (64.8%) used self-reported surveys, and only 3.7% studies used device-based measurement tools. Furthermore, 35.8% of the included studies were focused on children and adolescents, while only a few studies investigated infants/toddlers and older adults. Both female and male were examined in most studies, and non-clinical populations were investigated in the context of SB in a relatively large number of studies. Conclusions: The number of research articles on SB in the Chinese population published per year has increased year by year, indicating a growing interest in this research area. More studies using population subgroup samples are needed, particularly among infants/toddlers, older adults, and clinical populations. To provide stronger evidence of the determinants and outcomes of SB, longitudinal studies using device-based measures of SB are required.
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Affiliation(s)
- Ran Bao
- School of Physical Education and Sport Training, Shanghai University of Sport, Shanghai 200438, China; (R.B.); (J.X.); (L.W.)
| | - Si-Tong Chen
- Institute for Health and Sport, Victoria University, Melbourne 3000, Australia;
| | - Yanlei Wang
- Harbin Institute of Physical Education, Harbin 150006, China;
| | - Jun Xu
- School of Physical Education and Sport Training, Shanghai University of Sport, Shanghai 200438, China; (R.B.); (J.X.); (L.W.)
| | - Lei Wang
- School of Physical Education and Sport Training, Shanghai University of Sport, Shanghai 200438, China; (R.B.); (J.X.); (L.W.)
| | - Liye Zou
- Exercise and Mental Health Laboratory, Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen 518060, China;
| | - Yujun Cai
- School of Physical Education and Sport Training, Shanghai University of Sport, Shanghai 200438, China; (R.B.); (J.X.); (L.W.)
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Zou Q, Su C, Du W, Ouyang Y, Wang H, Wang Z, Ding G, Zhang B. The association between physical activity and body fat percentage with adjustment for body mass index among middle-aged adults: China health and nutrition survey in 2015. BMC Public Health 2020; 20:732. [PMID: 32429924 PMCID: PMC7238529 DOI: 10.1186/s12889-020-08832-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 05/01/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The inverse association between physical activity and body fat percentage (%) varies among different populations. We aim to examine whether the significant association between them was uniform across the subpopulations after taking into account body mass index (BMI). METHODS Our study relied on data from China Health and Nutrition Surveys in 2015, including 5763 participants aged 40-64 years from 15 regions. Physical activity was calculated as metabolic equivalent task hours per day (MET·h/d). Body fat% was measured by bioelectrical impedance analysis. Body mass index < 24 kg/m2 was defined as normal weight and BMI ≥ 24 kg/m2 was overweight/obese. The effects of physical activity on body fat% were estimated using the Kruskal-Wallis test among sex, age, BMI groups, education, income, region and urbanization. Quantile regression analyses were utilized to describe the relationship between physical activity and body fat% distribution. RESULTS Older adults, overweight/obese, higher education, higher income, residents of central China and those living in areas of higher urbanization had the lower physical activity. Participants who engaged in the highest level of physical activity had 2.0 and 1.5% lower body fat% than the lowest level of physical activity group (23.4, 34.8%) for men and women, respectively. There were 10.4 and 8.8% of normal weight males and females called normal weight obese. Overall, 1 h extra 4.5 MET•h/d was significantly associated with 0.079 and 0.110% less total body fat% at the 75th and 90th percentiles in normal weight males, with 0.071% less at the 25th percentiles in overweight/obese males, with 0.046-0.098% less at the 25th to 90th percentiles in normal weight females, and with 0.035-0.037% less from the 50th to 90th percentiles in overweight/obese females. The inverse association between physical activity and total body fat% was stronger in normal weight obese participants than other subgroups. CONCLUSIONS In middle-aged Chinese adults, the inverse association between physical activity and body fat% was only in particular subpopulations rather than the entire population. We should pay much attention to normal weight obese and give a suitable physical activity guideline taking into account people with different body fat%.
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Affiliation(s)
- Qinpei Zou
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
- Chongqing Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Chang Su
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Wenwen Du
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Yifei Ouyang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Huijun Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Zhihong Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Gangqiang Ding
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Bing Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
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Huang WZ, Yang BY, Yu HY, Bloom MS, Markevych I, Heinrich J, Knibbs LD, Leskinen A, Dharmage SC, Jalaludin B, Morawska L, Jalava P, Guo Y, Lin S, Zhou Y, Liu RQ, Feng D, Hu LW, Zeng XW, Hu Q, Yu Y, Dong GH. Association between community greenness and obesity in urban-dwelling Chinese adults. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 702:135040. [PMID: 31726339 DOI: 10.1016/j.scitotenv.2019.135040] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 10/14/2019] [Accepted: 10/16/2019] [Indexed: 05/23/2023]
Abstract
Living in greener places may protect against obesity, but epidemiological evidence is inconsistent and mainly comes from developed nations. We aimed to investigate the association between greenness and obesity in Chinese adults and to assess air pollution and physical activity as mediators of the association. We recruited 24,845 adults from the 33 Communities Chinese Health Study in 2009. Central and peripheral obesity were defined by waist circumference (WC) and body mass index (BMI), respectively, based on international obesity standards. The Normalized Difference Vegetation Index (NDVI) was used to quantify community greenness. Two-level logistic and generalized linear mixed regression models were used to evaluate the association between NDVI and obesity, and a conditional mediation analysis was used also performed. In the adjusted models, an interquartile range increase in NDVI500-m was significantly associated with lower odds of peripheral 0.80 (95% confidence interval [CI]: 0.74-0.87) and central obesity 0.88 (95% CI: 0.83-0.93). Higher NDVI values were also significantly associated with lower BMI. Age, gender, and household income significantly modified associations between greenness and obesity, with stronger associations among women, older participants, and participants with lower household incomes. Air pollution mediated 2.1-20.8% of the greenness-obesity associations, but no mediating effects were observed for physical activity. In summary, higher community greenness level was associated with lower odds of central and peripheral obesity, especially among women, older participants, and those with lower household incomes. These associations were partially mediated by air pollutants. Future well-designed longitudinal studies are needed to confirm our findings.
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Affiliation(s)
- Wen-Zhong Huang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Hong-Yao Yu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Michael S Bloom
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; Department of Environmental Health Sciences and Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Iana Markevych
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland 4006, Australia
| | - Ari Leskinen
- Finnish Meteorological Institute, Kuopio 70211, Finland; Department of Applied Physics, University of Eastern Finland, Kuopio 70211, Finland
| | - Shyamali C Dharmage
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population & Global Health, The University of Melbourne, Melbourne, VIC 3010 Australia
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW 2037, Australia
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, Queensland 4001, Australia
| | - Pasi Jalava
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, FI 70211, Finland
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Shao Lin
- Department of Environmental Health Sciences and Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA; Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany
| | - Yang Zhou
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Ru-Qing Liu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Dan Feng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Qiang Hu
- Department of Pediatric Surgery, Weifang People's Hospital, Weifang 261041, China.
| | - Yunjing Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China.
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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20
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Guo C, Zhou Q, Zhang D, Qin P, Li Q, Tian G, Liu D, Chen X, Liu L, Liu F, Cheng C, Qie R, Han M, Huang S, Wu X, Zhao Y, Ren Y, Zhang M, Liu Y, Hu D. Association of total sedentary behaviour and television viewing with risk of overweight/obesity, type 2 diabetes and hypertension: A dose-response meta-analysis. Diabetes Obes Metab 2020; 22:79-90. [PMID: 31468597 DOI: 10.1111/dom.13867] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 08/25/2019] [Accepted: 08/25/2019] [Indexed: 01/08/2023]
Abstract
AIMS To explore the quantitative dose-response association of total sedentary behaviour and television viewing with overweight/obesity, type 2 diabetes and hypertension in a meta-analysis. MATERIALS AND METHODS We searched three databases to identify English-language reports that assessed the association of total sedentary behaviour or television viewing with the aforementioned health outcomes. Restricted cubic splines were used to evaluate possible linear or non-linear associations of total sedentary behaviour and television viewing with these health outcomes. RESULTS We included 48 articles (58 studies) with a total of 1 071 967 participants in the meta-analysis; 21 (six cohort and 15 cross-sectional) studies examined the association of total sedentary behaviour with overweight/obesity, 23 (13 cohort and 10 cross-sectional) studies examined the association with type 2 diabetes and 14 (one cohort and 13 cross-sectional) studies examined the association with hypertension. We found linear associations between total sedentary behaviour and type 2 diabetes (Pnon-linearity = 0.190) and hypertension (Pnon-linearity = 0.225) and a non-linear association between total sedentary behaviour and overweight/obesity (Pnon-linearity = 0.003). For each 1-h/d increase in total sedentary behaviour, the risk increased by 5% for type 2 diabetes and 4% for hypertension. We also found linear associations between television viewing and type 2 diabetes (Pnon-linearity = 0.948) and hypertension (Pnon-linearity = 0.679) and a non-linear association for overweight/obesity (Pnon-linearity = 0.007). For each 1-h/d increase in television viewing, the risk increased by 8% for type 2 diabetes and 6% for hypertension. CONCLUSIONS High levels of total sedentary behaviour and television viewing were associated with overweight/obesity, type 2 diabetes and hypertension.
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Affiliation(s)
- Chunmei Guo
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Qionggui Zhou
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Dongdong Zhang
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Pei Qin
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Quanman Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Henan, Zhengzhou, People's Republic of China
| | - Gang Tian
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Henan, Zhengzhou, People's Republic of China
| | - Dechen Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Henan, Zhengzhou, People's Republic of China
| | - Xu Chen
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Henan, Zhengzhou, People's Republic of China
| | - Leilei Liu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Henan, Zhengzhou, People's Republic of China
| | - Feiyan Liu
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Cheng Cheng
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Ranran Qie
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Minghui Han
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Shengbing Huang
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Xiaoyan Wu
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Yang Zhao
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Yongcheng Ren
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Ming Zhang
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Department of Epidemiology and Health Statistics, School of Public Health, Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Yu Liu
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
| | - Dongsheng Hu
- Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
- Study Team of Shenzhen's Sanming Project, Affiliated Luohu Hospital of Shenzhen University Health Science Centre, Shenzhen, Guangdong, People's Republic of China
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Temporal Trends and Recent Correlates in Sedentary Behaviors among Chinese Adults from 2002 to 2010-2012. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 17:ijerph17010158. [PMID: 31878308 PMCID: PMC6982214 DOI: 10.3390/ijerph17010158] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 12/15/2019] [Accepted: 12/23/2019] [Indexed: 12/31/2022]
Abstract
Evidence suggests that more time spent in sedentary behaviors (SB) increases health risk independent of physical activities. Trends in SB among adults have not been fully described in China, and the sociodemographic correlates of SB have not been systematically evaluated either. This study examined the temporal trends of SB among 184,257 adults (2002: n = 52,697, 2010-2012: n = 131,560) using data from the China National Nutrition and Health Survey in 2002 and 2010-2012, and analyzed the recent correlates of SB in Chinese adults. Overall, an increase (+0.29 h/d) was seen in total SB across the survey years, and there was a slight increase (+0.14 h/d) in leisure time SB and a decrease (-0.39 h/d) in occupational SB. From 2002 to 2012, the proportion of Chinese adults whose total SB time over 4 h/d increased from 35.4% to 43.0%, and the proportion of leisure SB time over 3 h/d increased from 42.0% to 48.0%, and the proportion of occupational SB time over 4 h/d decreased from 63.4% to 53.0%. Male, urban areas, employed, unmarried, and with higher educational and family economic level were all positively associated with high sedentary time (HST) in 2010-2012. These trends and correlates are important for health policy in China and other countries that are facing similar challenges.
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22
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Wang F, Zhang LY, Zhang P, Cheng Y, Ye BZ, He MA, Guo H, Zhang XM, Yuan J, Chen WH, Wang YJ, Yao P, Wei S, Zhu YM, Liang Y. Effect of Physical Activity on Hospital Service Use and Expenditures of Patients with Coronary Heart Disease: Results from Dongfeng-Tongji Cohort Study in China. Curr Med Sci 2019; 39:483-492. [PMID: 31209822 DOI: 10.1007/s11596-019-2063-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2017] [Revised: 11/30/2018] [Indexed: 01/09/2023]
Abstract
The intervention of behaviors, including physical activity (PA), has become a strategy for many hospitals dealing with patients with chronic diseases. Given the limited evidence available about PA and healthcare use with chronic diseases, this study explored the association between different levels of PA and annual hospital service use and expenditure for inpatients with coronary heart disease (CHD) in China. We analyzed PA information from the first follow-up survey (2013) of the Dongfeng-Tongji cohort study of 1460 CHD inpatients. We examined factors such as PA exercise volume and years of PA and their associations with the number of inpatient visits, number of hospital days, and inpatient costs and total medical costs. We found that the number of hospital days and the number of inpatient visits were negatively associated with intensity of PA level. Similarly, total inpatient and outpatient costs declined when the PA exercise volume levels increased. Furthermore, there were also significant associations between the number of hospital days, inpatient costs or total medical costs and levels of PA years. This study provides the first empirical evidence about the effects of the intensity and years of PA on hospital service use and expenditure of CHD in China. It suggests that the patients' PA, especially the vigorous PA, should be promoted widely to the public and patients in order to relieve the financial burden of CHD.
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Affiliation(s)
- Fang Wang
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Liu-Yi Zhang
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Ping Zhang
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yao Cheng
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Bei-Zhu Ye
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Mei-An He
- Institute of Occupational Medicine and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Huan Guo
- Institute of Occupational Medicine and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xiao-Min Zhang
- Institute of Occupational Medicine and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jing Yuan
- Institute of Occupational Medicine and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Wei-Hong Chen
- Institute of Occupational Medicine and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - You-Jie Wang
- Institute of Occupational Medicine and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Ping Yao
- Institute of Occupational Medicine and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Sheng Wei
- Department of Epidemiology and Biostatistics and the Ministry of Education (MOE) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yi-Mei Zhu
- School of Media, Communication and Sociology, University of Leicester, Leicester, LE1 7JA, UK
| | - Yuan Liang
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Jakicic JM, Powell KE, Campbell WW, DiPietro L, Pate RR, Pescatello LS, Collins KA, Bloodgood B, Piercy KL. Physical Activity and the Prevention of Weight Gain in Adults: A Systematic Review. Med Sci Sports Exerc 2019; 51:1262-1269. [PMID: 31095083 PMCID: PMC6527311 DOI: 10.1249/mss.0000000000001938] [Citation(s) in RCA: 89] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
PURPOSE To conduct a systematic literature review to determine if physical activity is associated with prevention of weight gain in adults. METHODS The primary literature search was conducted for the 2018 Physical Activity Guidelines Advisory Committee and encompassed literature through June 2017, with an additional literature search conducted to include literature published through March 2018 for inclusion in this systematic review. RESULTS The literature review identified 40 articles pertinent to the research question. There is strong evidence of an association between physical activity and prevention of weight gain in adults, with the majority of the evidence from prospective cohort studies. Based on limited evidence in adults, however, there is a dose-response relationship and the prevention of weight gain is most pronounced when moderate-to-vigorous intensity physical activity (≥3 METs) is above 150 min·wk. Although there is strong evidence to demonstrate that the relationship between greater time spent in physical activity and attenuated weight gain in adults is observed with moderate-to-vigorous intensity physical activity, there is insufficient evidence available to determine if there is an association between light-intensity activity (<3 METs) and attenuated weight gain in adults. CONCLUSIONS The scientific evidence supports that physical activity can be an effective lifestyle behavior to prevent or minimize weight gain in adults. Therefore, public health initiatives to prevent weight gain, overweight, and obesity should include physical activity as an important lifestyle behavior.
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Affiliation(s)
- John M. Jakicic
- Department of Health and Physical Activity, University of Pittsburgh, Pittsburgh, PA
| | | | - Wayne W. Campbell
- Departments of Nutrition Science, Purdue University, West Lafayette, IN
| | - Loretta DiPietro
- Milken Institute School of Public Health, George Washington University, Washington, DC
| | - Russell R. Pate
- Arnold School of Public Health, University of South Carolina, Columbia, SC
| | | | - Katherine A. Collins
- Department of Health and Physical Activity, University of Pittsburgh, Pittsburgh, PA
| | | | - Katrina L. Piercy
- Office of Disease Prevention and Health Promotion, U.S. Department of Health and Human Services, Rockville, MD
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Zhang Y, Xie G, Huang J, Li S. A new leisure-time physical activity in China: square dancing. Minerva Med 2019; 110:180-181. [PMID: 30612421 DOI: 10.23736/s0026-4806.18.05932-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
| | - Gang Xie
- Wuxi Research Institute of Sports Science, Wuxi, China
| | - Jianya Huang
- Jiangsu Institute of Sports Science, Nanjing, China
| | - Sen Li
- Jiangsu Institute of Sports Science, Nanjing, China
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Nam S, Song M, Lee SJ. Relationships of Musculoskeletal Symptoms, Sociodemographics, and Body Mass Index With Leisure-Time Physical Activity Among Nurses. Workplace Health Saf 2018; 66:577-587. [PMID: 29792132 DOI: 10.1177/2165079918771987] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Nurses have a high prevalence of musculoskeletal symptoms from patient handling tasks such as lifting, transferring, and repositioning. Comorbidities such as musculoskeletal symptoms may negatively affect engagement in leisure-time physical activity (LTPA). However, limited data are available on the relationship between musculoskeletal symptoms and LTPA among nurses. The purpose of this study was to describe musculoskeletal symptoms and LTPA, and to examine the relationships of musculoskeletal symptoms, sociodemographics, and body mass index with LTPA among nurses. Cross-sectional data on sociodemographics, employment characteristics, musculoskeletal symptoms, body mass index, and LTPA were collected from a statewide random sample of 454 California nurses from January to July 2013. Descriptive statistics, bivariate and multiple logistic regressions were performed. We observed that non-White nurses were less likely to engage in regular aerobic physical activity than White nurses (odds ratio [OR] = 0.61; 95% confidence interval [CI] = [0.40, 0.94]). Currently working nurses were less likely to engage in regular aerobic physical activity than their counterparts (OR = 0.48; 95% CI = [0.25, 0.91]). Nurses with higher body mass index were less likely to perform regular aerobic physical activity (OR = 0.93; 95% CI = [0.89, 0.97]) or muscle-strengthening physical activity (OR = 0.92; 95% CI = [0.88, 0.96]). This study found no evidence that musculoskeletal symptoms may interfere with regular engagement in LTPA. Physical activity promotion interventions should address employment-related barriers, and particularly target racial minority nurses and those who have a high body mass index.
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Campbell SDI, Brosnan BJ, Chu AKY, Skeaff CM, Rehrer NJ, Perry TL, Peddie MC. Sedentary Behavior and Body Weight and Composition in Adults: A Systematic Review and Meta-analysis of Prospective Studies. Sports Med 2017; 48:585-595. [DOI: 10.1007/s40279-017-0828-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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