Physical activity, sedentary behavior, and cardiovascular disease risk in Korea: a trajectory analysis
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OBJECTIVES: To identify the distinct trajectories of sedentary behavior (SB) and explore whether reduced cardiovascular disease (CVD) risk was associated with a distinct trajectory of physical activity (PA). METHODS: We analyzed data from 6,425 people who participated in the Korean Health Panel Survey over a period of 10 years. The participants’ self-reported SB and PA were assessed annually, and trajectory groups were identified using a group-based trajectory model for longitudinal data analysis. Logistic regression analysis was performed to assess the association between CVD risk (10-year cumulative incidence) and the trajectories of SB and PA. The adjusted variables included socio-demographic factors, the predisposing diseases of CVD, and baseline health behaviors. RESULTS: Trajectory analysis identified 4 SB trajectory groups: SB group 1 (low and slightly increasing trend, 53.1%), SB group 2 (high and rapidly decreasing trend, 14.7%), SB group 3 (high and slightly decreasing trend, 9.9%), and SB group 4 (low and rapidly increasing trend, 22.2%). The 3 PA trajectory groups were PA group 1 (moderate and slightly decreasing trend, 32.1%), PA group 2 (low and slightly decreasing trend, 57.3%), and PA group 3 (maintained inactivity, 10.7%). By the 10-year follow-up, 577 cases of incident CVD had occurred. We also noted a 50% reduction in the risk of CVD when SB group 4 was accompanied by PA group 1 (odds ratio, 0.50; 95% confidence interval, 0.28 to 0.90). CONCLUSIONS: Despite increased time spent in SB, maintaining PA about 2 days to 3 days per week reduced the occurrence of CVD.
Abstract
OBJECTIVES: To identify the distinct trajectories of sedentary behavior (SB) and explore whether reduced cardiovascular disease (CVD) risk was associated with a distinct trajectory of physical activity (PA). METHODS: We analyzed data from 6,425 people who participated in the Korean Health Panel Survey over a period of 10 years. The participants’ self-reported SB and PA were assessed annually, and trajectory groups were identified using a group-based trajectory model for longitudinal data analysis. Logistic regression analysis was performed to assess the association between CVD risk (10-year cumulative incidence) and the trajectories of SB and PA. The adjusted variables included socio-demographic factors, the predisposing diseases of CVD, and baseline health behaviors. RESULTS: Trajectory analysis identified 4 SB trajectory groups: SB group 1 (low and slightly increasing trend, 53.1%), SB group 2 (high and rapidly decreasing trend, 14.7%), SB group 3 (high and slightly decreasing trend, 9.9%), and SB group 4 (low and rapidly increasing trend, 22.2%). The 3 PA trajectory groups were PA group 1 (moderate and slightly decreasing trend, 32.1%), PA group 2 (low and slightly decreasing trend, 57.3%), and PA group 3 (maintained inactivity, 10.7%). By the 10-year follow-up, 577 cases of incident CVD had occurred. We also noted a 50% reduction in the risk of CVD when SB group 4 was accompanied by PA group 1 (odds ratio, 0.50; 95% confidence interval, 0.28 to 0.90). CONCLUSIONS: Despite increased time spent in SB, maintaining PA about 2 days to 3 days per week reduced the occurrence of CVD.
참고문헌 (27)
- Carson V, "Patterns of sedentary time and cardiometabolic risk among Canadian adults", Prev Med, 65, pp.23~27 (2014)
- Barnett TA, "Distinct trajectories of leisure time physical activity and predictors of trajectory class membership : a 22 year cohort study", Int J Behav Nutr Phys Act, 5, pp.57~ (2008)
- Chomistek AK, "Relationship of sedentary behavior and physical activity to incident cardiovascular disease : results from the Women’s Health Initiative", J Am Coll Cardiol, 61, pp.2346~2354 (2013)
- Aggio D, "Trajectories of physical activity from midlife to old age and associations with subsequent cardiovascular disease and all-cause mortality", J Epidemiol Community Health, 74, pp.130~136 (2020)
- Dunton GF, "Joint associations of physical activity and sedentary behaviors with body mass index: results from a time use survey of US adults", Int J Obes(Lond), 33, pp.1427~1436 (2009)
- 이예나, "Association of Sedentary Time and Physical Activity with the 10-Year Risk of Cardiovascular Disease: Korea National Health and Nutrition Examination Survey 2014–2017", Korean Journal of Family Medicine, 41(6), pp.374~380 (2020), 대한가정의학회[DOI]
- 박정하, "Sedentary Lifestyle: Overview of Updated Evidence of Potential Health Risks", Korean Journal of Family Medicine, 41(6), pp.365~373 (2020), 대한가정의학회[DOI]
- Stamatakis E, "Sitting time, physical activity, and risk of mortality in adults", J Am Coll Cardiol, 73, pp.2062~2072 (2019)
- "Data provided by National Health and Nutrition Survey"[URL]
- Li X, "Replacement of sedentary behavior by various daily-life physical activities and structured exercises : genetic risk and incident type 2 diabetes", Diabetes Care, 44, pp.2403~2410 (2021)
- Schmid D, "Replacing sedentary time with physical activity in relation to mortality", Med Sci Sports Exerc, 48, pp.1312~1319 (2016)
- Meyer J, "Changes in physical activity and sedentary behavior in response to COVID-19 and their associations with mental health in 3052 US adults", Int J Environ Res Public Health, 17, pp.6949~ (2020)
- Mok A, "Physical activity trajectories and mortality : population based cohort study", BMJ, 365, pp.l2323~ (2019)
- Jee Y, "Trajectory of smoking and incidence of atherosclerotic cardiovascular disease among Korean young adult men", Int J Environ Res Public Health, 16, pp.2219~ (2019)
- Jeon J, "Waist circumference trajectories and risk of type 2 diabetes mellitus in Korean population : the Korean genome and epidemiology study(KoGES)", BMC Public Health, 19, pp.741~ (2019)
- Jones BL, "Advances in group-based trajectory modeling and an SAS procedure for estimating them", Sociol Methods Res, 35, pp.542~571 (2007)
- Lim HJ, "Trajectories of depression and their predictors in a population-based study of Korean older adults", Int J Aging Hum Dev, 93, pp.834~853 (2021)
- Hagströmer M, "The International Physical Activity Questionnaire(IPAQ) : a study of concurrent and construct validity", Public Health Nutr, 9, pp.755~762 (2006)
- "Proc TRAJ: a SAS procedure for group-based modeling of longitudinal data" (2007)[URL]
- Fagerland MW, "A goodness-of-fit test for the proportional odds regression model", Stat Med, 32, pp.2235~2249 (2013)
- Patterson R, "Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes : a systematic review and dose response meta-analysis", Eur J Epidemiol, 33, pp.811~829 (2018)
- Diaz KM, "Patterns of sedentary behavior in us middle-age and older adults : the REGARDS Study", Med Sci Sports Exerc, 48, pp.430~438 (2016)
- "Global strategy on diet, physical activity and health" (2020)[URL]
- Fennell C, "The relationship between cell phone use, physical activity, and sedentary behavior in adults aged 18-80", Comput Human Behav, 90, pp.53~59 (2019)
- Stamatakis E, "Sitting time, physical activity, and risk of mortality in adults", J Am Coll Cardiol, 73, pp.2062~2072 (2019)
- Gilchrist SC, "Association of sedentary behavior with cancer mortality in middle-aged and older US adults", JAMA Oncol, 6, pp.1210~1217 (2020)
- Ekelund U, "Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women", Lancet, 388, pp.1302~1310 (2016)