Abstract

Multimorbidity significantly impacts health, well-being, and the economy; therefore, exploring notable factors associated with multimorbidity across all age groups is critical. For this investigation, we focused on the relationship between four lifestyle factors and multimorbidity risk. We recruited 11,031 Chinese citizens aged ≥ 12 years from 31 provinces between July 2021 and September 2021 using a quota sampling strategy to ensure that the socioeconomic characteristics (sex, age, rural–urban distribution) of those participating in this research were representative of national demographics. In the first stage, multivariable logistic regression models were utilized as a means of investigating the relationship between lifestyle factors and multimorbidity. Then, a multinomial logistic regression model was used with the aim of examining the Healthy Lifestyle Profile (HLP) related to the number of chronic diseases. Multivariable logistic regression models assessed the interaction effects and joint association among the four lifestyle factors. Overall, 18% of the participants had at least one disease, and 5.9% had multimorbidity. Approximately two-thirds of the participants were physically inactive, 40% had consumed alcohol, 39% were underweight or overweight, and 20% were or had been smokers. Participants who maintained one HLP showed a 34% lower multimorbidity risk (adjusted OR, 0.66; 95% CI, 0.48 to 0.92), while participants who maintained 4 HLP showed a 73% lower multimorbidity risk (adjusted OR, 0.27; 95% CI, 0.17 to 0.43), as compared to those who had 0 HLP. The joint association analysis revealed that participants with all four healthy lifestyle factors had 0.92 times lower odds of multimorbidity (95% CI: 0.90, 0.94) in comparison with the all-unhealthy reference cluster. Notably, individuals with a combination of healthy smoking status and healthy body weight had the highest minimized odds of multimorbidity (OR: [0.92], 95% CI: 0.91, 0.94). Common lifestyle habits, alone or in combination, are associated with multimorbidity risk. This study provides insights for public health programs to promote a healthy lifestyle at a younger age and to alleviate multimorbidity risk in older people.

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