Abstract: Objective This study, grounded in the health ecology model, aims to hierarchically analyze the prevalence and determinants of hypertension, diabetes, and dyslipidemia among residents of the Western Anhui region, thereby providing a reference for the research on the prevention, control, and management of chronic diseases. Method A multistage sampling methodology was employed to conduct a health survey among residents aged 18 and older across four counties in the Western Anhui region. The χ² test and binary logistic regression analysis were utilized to examine the determinants of hypertension, diabetes, and dyslipidemia. Results A total of 2 930 subjects were included in the study, with a male-to-female ratio of 1∶1.45. The mean age of the cohort was (55.55 ± 15.89) years, with 65.73% of participants aged over 45 years. The prevalence rates for hypertension, diabetes, and dyslipidemia were 46.55% (n=1 364), 11.50% (n=337), and 33.34% (n=977), respectively. Hierarchical regression analysis revealed a progressive improvement in the model's goodness-of-fit with the sequential addition of influencing factors across five models. Factors associated with an increased risk for these three conditions included being in the 45 to <60 age group (OR=1.989) or the ≥60 age group (OR=4.667), having a BMI classified as overweight (OR=1.739) or obese (OR=2.946), presenting with central obesity (OR=1.834), having a midday napping habit (OR=1.223), reporting fair (OR=1.455) or poor (OR=1.836) self-rated health, and possessing a college-level education or higher (OR=1.550). Conversely, being female (OR=0.557), having a BMI classified as underweight (OR=0.524), being married or cohabiting (OR=0.642), residing in a rural area (OR=0.783), and having medical insurance (OR=0.224) were identified as significant protective factors. Conclusion The prevalence of hypertension, diabetes, and dyslipidemia is notably high in the Western Anhui region. The determinants of these conditions are multi-level, multi-dimensional, and intricately interrelated. It is therefore imperative to strengthen prevention and management strategies for these cardiometabolic diseases across multiple ecological levels.

Key words: Health ecology, Hypertension, Diabetes mellitus, Dyslipidemia, Morbidity, Risk factors