Association of area- and individual-level socioeconomic status with five lifestyles: data based on a nationwide population cohort (ChinaHEART project)

Background Modifiable lifestyle factors, which are key behavioral risk factors contributing to the global burden of disease, are significantly influenced by socioeconomic status (SES). However, compared to individual-level SES, the relationship between area-level SES and a comprehensive range of lifestyle risk factors remains poorly understood. Methods This study examined the independent and combined associations of individual- and area-level SES with five key health behaviours in 1,271,221 adults aged 35–75 years from the nationwide ChinaHEART cohort. Individual-level SES was derived from education, household income, and occupation using latent class analysis. Area-level SES was constructed for 2,844 counties using principal component analysis of national census data and categorized into tertiles. Five behavioral risk factors were assessed: current smoking, excessive alcohol consumption (>15 g/day), insufficient leisure-time physical activity (LTPA), unhealthy diet (Healthy Eating Score <4/6), and unhealthy sleep duration (<6 or >8 hours). Multivariable logistic regression models were employed to assess the independent and combined effects of individual- and area-level SES on the five behavioral risk factors. Results People with higher individual- and area-level SES generally exhibited lower behavioral risk. However, high individual-level SES was associated with increased odds of unhealthy sleep duration (OR 1.47, 95% CI 1.41-1.52), and high area-level SES was associated with increased odds of excessive alcohol consumption (OR 1.13, 95% CI 1.11-1.16). Significant synergistic interactions between individual- and area-level SES were observed for all five behaviours (P<0.001). Subgroup analyses further revealed that the inverse association between area-level SES and smoking was stronger in females, and its association with unhealthy sleep was most pronounced in urban and younger subgroups. Conclusions This study illustrates SES at both the individual and area levels independently and synergistically influences various lifestyles, with its impact differing across distinct subgroups. It underscores the critical importance of implementing tailored interventions at multiple hierarchical levels to reduce health inequities.