Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults
Objectives: To examine the association between physical activity (PA) and leisure-time sedentary time and cardiovascular disease (CVD). Methods: This cross-sectional study used baseline data from the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019. PA and leisure-time sede...
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Elsevier
2025-01-01
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| Series: | Preventive Medicine Reports |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211335524003498 |
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| author | Yutong Wang Peiying Yang Huimeng Liu Suixia Cao Jingchun Liu Yating Huo Kun Xu Binyan Zhang Mengchun Wang Qian Huang Chunlai Yang Lingxia Zeng Shaonong Dang Baibing Mi |
| author_facet | Yutong Wang Peiying Yang Huimeng Liu Suixia Cao Jingchun Liu Yating Huo Kun Xu Binyan Zhang Mengchun Wang Qian Huang Chunlai Yang Lingxia Zeng Shaonong Dang Baibing Mi |
| author_sort | Yutong Wang |
| collection | DOAJ |
| description | Objectives: To examine the association between physical activity (PA) and leisure-time sedentary time and cardiovascular disease (CVD). Methods: This cross-sectional study used baseline data from the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019. PA and leisure-time sedentary time were self-reported. Logistic regression models analyzed the association of PA and leisure-time sedentary time with CVD prevalence individually and jointly. Restricted cubic spline analyses assessed dose-response relationships. Isotemporal substitution models were used to investigate substituting leisure-time sedentary time, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) with CVD prevalence. Results: The prevalence of CVD was 31.8 %. Compared to the lowest quartile, participants in the highest quartile of total PA had a 32 % lower CVD prevalence (odds ratio [OR]: 0.68, 95 % confidence interval [CI]: 0.62–0.74; P for trend <0.001). The fully adjusted OR for the highest quartile of leisure-time sedentary time compared to the lowest quartile was 1.09 (1.01–1.18; P for trend =0.04). An L-shaped dose-response relationship was observed between PA and CVD prevalence. An active lifestyle and reduced daily leisure-time sedentary time were associated with a 26 % (0.74 [0.63–0.86]) lower CVD prevalence. Additionally, substituting 30 min/day of leisure-time sedentary time with equivalent MVPA was associated with a 2 % (0.98 [0.97–0.99]) reduction in CVD prevalence. Substituting sedentary time with LPA was associated with a lower CVD prevalence in females. Conclusions: An active lifestyle was associated with a lower prevalence of CVD in regional populations, suggesting a feasible strategy for CVD prevention and regional health promotion. |
| format | Article |
| id | doaj-art-e9dd8625b1ac4df9991fb8a677376d85 |
| institution | Kabale University |
| issn | 2211-3355 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Preventive Medicine Reports |
| spelling | doaj-art-e9dd8625b1ac4df9991fb8a677376d852025-01-11T06:41:14ZengElsevierPreventive Medicine Reports2211-33552025-01-0149102934Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adultsYutong Wang0Peiying Yang1Huimeng Liu2Suixia Cao3Jingchun Liu4Yating Huo5Kun Xu6Binyan Zhang7Mengchun Wang8Qian Huang9Chunlai Yang10Lingxia Zeng11Shaonong Dang12Baibing Mi13Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China; Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Department of Neurology, The First Affilated Hospital of Xi'an Jiaotong University, Xi'an 710061, China; Ministry of Science and Technology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China; Dongcheng District Center for Disease Control and Prevention, Beijing 100009, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China; Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Department of Neurology, The First Affilated Hospital of Xi'an Jiaotong University, Xi'an 710061, China; Ministry of Science and Technology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China; Dongcheng District Center for Disease Control and Prevention, Beijing 100009, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China; Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Department of Neurology, The First Affilated Hospital of Xi'an Jiaotong University, Xi'an 710061, China; Ministry of Science and Technology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China; Dongcheng District Center for Disease Control and Prevention, Beijing 100009, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, ChinaDepartment of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China; Shaanxi Open Sharing Platform of Critical Disease Prevention and Big Health Data Science, Xi'an 710061, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an 710061, China; Corresponding author at: Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China.Objectives: To examine the association between physical activity (PA) and leisure-time sedentary time and cardiovascular disease (CVD). Methods: This cross-sectional study used baseline data from the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019. PA and leisure-time sedentary time were self-reported. Logistic regression models analyzed the association of PA and leisure-time sedentary time with CVD prevalence individually and jointly. Restricted cubic spline analyses assessed dose-response relationships. Isotemporal substitution models were used to investigate substituting leisure-time sedentary time, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) with CVD prevalence. Results: The prevalence of CVD was 31.8 %. Compared to the lowest quartile, participants in the highest quartile of total PA had a 32 % lower CVD prevalence (odds ratio [OR]: 0.68, 95 % confidence interval [CI]: 0.62–0.74; P for trend <0.001). The fully adjusted OR for the highest quartile of leisure-time sedentary time compared to the lowest quartile was 1.09 (1.01–1.18; P for trend =0.04). An L-shaped dose-response relationship was observed between PA and CVD prevalence. An active lifestyle and reduced daily leisure-time sedentary time were associated with a 26 % (0.74 [0.63–0.86]) lower CVD prevalence. Additionally, substituting 30 min/day of leisure-time sedentary time with equivalent MVPA was associated with a 2 % (0.98 [0.97–0.99]) reduction in CVD prevalence. Substituting sedentary time with LPA was associated with a lower CVD prevalence in females. Conclusions: An active lifestyle was associated with a lower prevalence of CVD in regional populations, suggesting a feasible strategy for CVD prevention and regional health promotion.http://www.sciencedirect.com/science/article/pii/S2211335524003498Physical activitySedentary behaviorCardiovascular diseaseIsotemporal substitution modelRegional population |
| spellingShingle | Yutong Wang Peiying Yang Huimeng Liu Suixia Cao Jingchun Liu Yating Huo Kun Xu Binyan Zhang Mengchun Wang Qian Huang Chunlai Yang Lingxia Zeng Shaonong Dang Baibing Mi Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults Preventive Medicine Reports Physical activity Sedentary behavior Cardiovascular disease Isotemporal substitution model Regional population |
| title | Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults |
| title_full | Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults |
| title_fullStr | Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults |
| title_full_unstemmed | Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults |
| title_short | Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults |
| title_sort | substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest chinese adults |
| topic | Physical activity Sedentary behavior Cardiovascular disease Isotemporal substitution model Regional population |
| url | http://www.sciencedirect.com/science/article/pii/S2211335524003498 |
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