Original Article

Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations

Abstract

Background: This study was determined to describe the patterns of lifestyle behaviors and their associations with metabolic profiles among Chinese urban and rural adults.

Methods: This was a cross-sectional study set in the Nanjing (5,824) and Hefei (20,269) Community Cardiovascular Risk Surveys from 2011-2013, using random cluster sampling. Questionnaires were completed via face-to-face interview, and data on lifestyle behaviors including daily night sleep duration, nap duration (if any) and sitting time, and weekly physical activity (measured using the International Physical Activity Questionnaire, in metabolic equivalents of task × minutes, and separated into walking and moderate-to-vigorous physical activity (MOVPA) according to intensity) was collected. The patterns of physical activity in Chinese urban and rural populations and the metabolic profile in each pattern were identified by the latent class analysis.

Results: Six distinct clusters were determined, with the sizes ranging from 45% to 5% of the total population. For example, the most common cluster was associated with a sufficient night and nap sleep duration, a long sitting time, and above WHO recommended physical activities for both walking and MOVPA, and the smallest cluster was featured by its huge amount of MOVPA and limited amount of walking activity. Difference in proportion of each cluster was observed between the two survey sites. No obvious abnormal blood measures were seen in any cluster.

Conclusion: Common lifestyle behavior clusters were described, leading to a better understanding of people’s routine activities.

1. Xiao J, Shen C, Chu MJ, et al (2016). Physi-cal Activity and Sedentary Behavior Asso-ciated with Components of Metabolic Syndrome among People in Rural China. PLoS One,11(1):e0147062.
2. Oftedal S, Vandelanotte C, Duncan MJ (2019). Patterns of Diet, Physical Activity, Sitting and Sleep Are Associated with So-cio-Demographic, Behavioural, and Health-Risk Indicators in Adults. Int J En-viron Res Public Health,16(13): 2375.
3. Ding D, Rogers K, van der Ploeg H, et al (2015). Traditional and Emerging Life-style Risk Behaviors and All-Cause Mor-tality in Middle-Aged and Older Adults: Evidence from a Large Population-Based Australian Cohort. PLoS Med,12(12):e1001917.
4. Pontt JL, Rowlands AV, Dollman J (2015). Comparison of sedentary behaviours among rural men working in offices and on farms. Aust J Rural Health,23(2):74-9.
5. Strugnell C, M N Renzaho A, Ridley K, et al (2015). Physical activity and sedentary be-haviour among Asian and Anglo-Australian adolescents. Health Promot J Austr,26(2):105-114.
6. Oftedal S, Kolt GS, Holliday EG, et al (2019). Associations of health-behavior patterns, mental health and self-rated health. Prev Med,118:295-303.
7. Champion KE, Mather M, Spring B, et al (2018). Clustering of Multiple Risk Behav-iors Among a Sample of 18-Year-Old Australians and Associations With Mental Health Outcomes: A Latent Class Analy-sis. Front Public Health,6:135.
8. Costa RM, Minatto G, Costa BGG, et al (2021). Clustering of 24-h movement be-haviors associated with cardiorespiratory fitness among adolescents: a latent class analysis. Eur J Pediatr,180(1):109-117.
9. Miranda VPN, Dos Santos Amorim PR, Bastos RR, et al (2019). Evaluation of life-style of female adolescents through latent class analysis approach. BMC Public Health,19(1):184.
10. Evenson KR, Herring AH, Wen F (2017). Accelerometry-Assessed Latent Class Patterns of Physical Activity and Seden-tary Behavior with Mortality. American Journal of Preventive Medicine,52(2):135-143.
11. Yu L, Cai Y, Qin R, et al (2019). Association between triglyceride glucose index and abnormal liver function in both urban and rural Chinese adult populations: Findings from two independent surveys. Medicine (Baltimore),98(50):e18265.
12. Craig CL, Marshall AL, Sjöström M, et al (2003). International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc,35(8):1381-95.
13. Jetté M, Sidney K, Blümchen G (1990). Met-abolic equivalents (METS) in exercise testing, exercise prescription, and evalua-tion of functional capacity. Clin Cardi-ol,13(8):555-65.
14. Chen Y, Chen Y, Geng B, et al (2021). Physical activity and liver health among urban and rural Chinese adults: results from two independent surveys. Journal of Exercise Science & Fitness,19(1):8-12.
15. Yu D, Chen T, Cai Y, et al (2017). Associa-tion between pulmonary function and re-nal function: findings from China and Australia. BMC Nephrology,18(1):143.
16. Shi R, Cai Y, Qin R, et al (2020). Dose-response association between physical ac-tivity and clustering of modifiable cardio-vascular risk factors among 26,093 Chi-nese adults. BMC Cardiovasc Dis-ord,20(1):347.
17. Chen Y, Campbell P, Strauss VY, et al (2018). Trajectories and predictors of the long-term course of low back pain: co-hort study with 5-year follow-up. Pain,159(2):252-260.
18. Hoekstra T, Twisk JWR (2015). The Analysis of Individual Health Trajectories Across the Life Course: Latent Class Growth Models Versus Mixed Models. In: Bur-ton-Jeangros C, Cullati S, Sacker A, Blane D, eds. A Life Course Perspective on Health Trajectories and Transitions. Springer./
19. Zhu Z, Tang Y, Zhuang J, et al (2019). Physical activity, screen viewing time, and overweight/obesity among Chinese chil-dren and adolescents: an update from the 2017 physical activity and fitness in Chi-na-the youth study. BMC Public Health,19(1):197.
20. Ge Y, Xin S, Luan D, et al (2019). Associa-tion of physical activity, sedentary time, and sleep duration on the health-related quality of life of college students in Northeast China. Health Qual Life Out-comes,17(1):124.
Files
IssueVol 51 No 5 (2022) QRcode
SectionOriginal Article(s)
DOI https://doi.org/10.18502/ijph.v51i5.9423
Keywords
Physical activity Sedentary time Sleep duration Latent class analysis

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How to Cite
1.
Cui Q, Chen Y, Ye X, Cai Y, Qin R, Chen T, Yan T, Yu D. Patterns of Lifestyle Behaviors and Relevant Metabolic Profiles in Chinese Adults: Latent Class Analysis from Two Independent Surveys in Urban and Rural Populations. Iran J Public Health. 2022;51(5):1076-1083.