Abstract
OBJECTIVES: This study aimed to investigate the impacts of chronic diseases such as hypertension, dyslipidaemia and diabetes on personal and household income among ageing Chinese adults. The primary hypothesis was that these chronic diseases have differential effects on the socioeconomic status of individuals and households, with gender and age influencing these relationships. DESIGN: Prospective cohort study using double/debiased machine learning (DDML) techniques to analyse data from the China Health and Retirement Longitudinal Study (CHARLS). SETTING: Nationally representative sample of ageing Chinese adults, with data collected from multiple regions across China. The sample represents a variety of both urban and rural settings. PARTICIPANTS: A total of 69 457 participants entered the study, with 69 457 completing it. The sample included both male and female participants, with the majority being of Han Chinese ethnicity. Participants were selected based on the presence of hypertension, dyslipidaemia and diabetes, and exclusion criteria included: no information on age (n=4307), no information on gender (n=12), no information on medical insurance (n=177). PRIMARY OUTCOME MEASURES: The primary outcome measures, as outlined in the study protocol, were the associations between three chronic diseases (hypertension, dyslipidaemia and diabetes) and personal income (LPI) as well as household income (LHI). These associations were measured using the DDML method, which provided both overall measurements and gender-specific subgroup analyses. There were no significant deviations between the planned and actual outcome measures, and all outcomes were assessed as originally intended. RESULTS: Dyslipidaemia was positively associated with LPI (coefficient=0.078, 95% CI 0.052 to 0.105) but negatively associated with LHI (coefficient=-0.049, 95% CI -0.084 to -0.015). Diabetes showed stronger positive effects on LPI (coefficient=0.093, 95% CI 0.052 to 0.135) and negative effects on LHI (coefficient=-0.094, 95% CI -0.147 to -0.041). Gender-specific analyses revealed that dyslipidaemia had a stronger association with LPI in males (95% CI 0.080 to 0.163) compared with females (95% CI 0.007 to 0.075). For diabetes, males experienced larger increases in LPI (95% CI 0.053 to 0.190) compared with females (95% CI 0.015 to 0.117). Additionally, reductions in LHI were more pronounced in females with diabetes (95% CI -0.187 to -0.043). CONCLUSIONS: Chronic diseases, particularly dyslipidaemia and diabetes, significantly affect the socioeconomic status of ageing Chinese adults, with distinct gender-specific impacts. These findings highlight the importance of targeted interventions to address the income disparities linked to chronic diseases. Further research is needed to explore the long-term effects of disease management on socioeconomic outcomes. TRIAL REGISTRATION NUMBER: Prospective, observational, community-based cohort study using 2011-2018 CHARLS data from 28 provinces in mainland China, with the registration number IRB00001052-11015, following ethical approval from the Biomedical Ethics Committee of Peking University.