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Prevalence of Suboptimal Health Status and the Relationships between Suboptimal Health Status and Lifestyle Factors among Chinese Adults Using a Multi-Level Generalized Estimating Equation Model

Tao Xu, Guangjin Zhu, Shaomei Han

2020International Journal of Environmental Research and Public Health46 citationsDOIOpen Access PDF

Abstract

This study examined the prevalence of suboptimal health among Chinese adults based on a large-scale national survey and clarified the relationship between suboptimal health and lifestyle factors. We used multi-level generalized estimating equation models to examine the relationships between suboptimal health and lifestyle factors. Of the 48,978 respondents, 34,021 reported one or more suboptimal health symptoms, giving a suboptimal health status prevalence of 69.46%. After controlling for the cluster effect of living areas and confounding effect of demographic characteristics, factors associated with suboptimal health were: current smoking (odds ratio (OR) = 1.083, 95% confidence interval (CI): 1.055-1.111), drinking alcohol (OR = 1.075, 95% CI: 1.025-1.127), family history of disease (OR = 1.203, 95% CI: 1.055-1.111), sleeping <6 h per day (OR = 1.235, 95% CI: 1.152-1.256), poor sleep quality (OR = 1.594, 95% CI: 1.515-1.676), stress (OR = 1.588, 95% CI: 1.496-1.686), negative life events (OR = 1.114, 95% CI: 1.045-1.187), unhealthy diet choices (OR = 1.093, 95% CI: 1.033-1.156), and not regularly having meals at fixed hours (OR = 1.231, 95% CI: 1.105-1.372). Respondents who exercised regularly had lower odds of having suboptimal health status (OR = 0.913, 95% CI: 0.849-0.983). Suboptimal health has become a serious public health challenge in China. The health status of the population could be effectively improved by improving lifestyle behaviors.

Topics & Concepts

MedicineConfidence intervalOdds ratioGeneralized estimating equationConfoundingDemographyPublic healthOddsEnvironmental healthPopulationStructural equation modelingGerontologyLogistic regressionInternal medicineStatisticsSociologyMathematicsNursingCardiovascular Health and Risk FactorsNutritional Studies and DietHealth disparities and outcomes