Patterns of multimorbidity across obesity severity and fat distribution in Anhui, China: a community-based study.

Abstract

Introduction: Obesity and multimorbidity are prevalent worldwide. However, the relationships of obesity severity and fat distribution with multimorbidity patterns among the Chinese population are still unclear. We sought to investigate multimorbidity patterns among people with various obesity severity and fat distribution in Anhui, China.

Methods: We used cross-sectional data including 123,148 adults aged 35-76 years in 12 districts from Anhui Province, China. Multimorbidity referred to the presence of at least two chronic conditions from a defined set of nine. We used logistic regression models, stratified by gender, to analyze the associations of different obesity severity and fat distribution with the risk of multimorbidity by adjusting for confounders of age, region, marriage, education level, annual income, insurance, smoking, drinking, rational diet, weight control, physical exercise, adequate sleep and regular checkup. Subgroup and interaction analyses examined how varying obesity severity and fat distribution relate to multimorbidity risk. Association rule mining (ARM) utilized the Apriori algorithm to analyze disease combinations under different obesity subgroups in males and females.

Results: Multimorbidity occurred in 10.3%(n=12,644) of the participants, with 10.7%(n=5,324) in males and 9.96% (n=7,320) in females, and the majority (80.5%, n=10,177) had two chronic diseases. Compared to normal-weight participants, there were progressively higher odds of multimorbidity in overweight, mild, moderate, and severe obesity in both males and females (P for trend <0.001). Individuals with general obesity (male: OR = 1.366, 95% CI: 1.234-1.513; female: OR = 1.315, 95% CI: 1.197-1.445), central obesity (male: OR = 2.168, 95% CI: 1.857-2.532; female: OR = 1.567, 95% CI: 1.401-1.752), or compound obesity (male: OR = 2.223, 95% CI: 1.996-2.476; female: OR = 1.998, 95% CI: 1.822-2.190) had significantly higher multimorbidity rates than their non-obese counterparts. Subgroup analysis and interaction analysis results showed that males, people aged < 60 years, and smokers may worsen the effects of obesity on multimorbidity. ARM revealed that the disease cluster comprising diabetes, hypertension, and dyslipidemia exhibited the strongest association. Notably, males with severe obesity face an elevated risk of cardiovascular metabolic comorbidity.

Conclusions: Both overweight and obesity are independent risk factors for multimorbidity, and males exhibit significantly higher multimorbidity risks than females. Individuals with obesity are more vulnerable to multiple coexisting conditions such as diabetes, hypertension, and dyslipidemia. Therefore, adopting health management and intervention measures for obesity individuals can help control multimorbidity.