Association between relative fat mass and asthma risk in middle-aged and elderly Chinese population: a retrospective cohort study based on the CHARLS database

This study aims to clarify the potential association between Relative Fat Mass (RFM) and new-onset asthma. A retrospective cohort study design was adopted, with data sourced from the China Health and Retirement Longitudinal Study (CHARLS) database. Participants aged 45 years and above without a history of asthma in 2011 were included as the baseline. Follow-ups were conducted in 2013, 2015, 2018, and 2020. After excluding individuals with missing key variables such as height, waist circumference, and smoking history, a total of 8,577 subjects were finally included. Restricted cubic spline plots were used to visualize the association pattern between RFM and asthma risk. A piecewise regression model was applied to identify the association threshold. The likelihood ratio test was used to compare the goodness-of-fit between linear and non-linear models, and sensitivity analysis was performed to verify the robustness of the results. All models were adjusted for confounding factors including age, gender, and marital status. Among the 8,577 participants, 3,899 (45.46%) were males and 4,678 (54.54%) were females. During the follow-up period, 657 participants (7.66%) were diagnosed with asthma. Restricted cubic spline analysis showed a significant non-linear association between RFM and new-onset asthma (overall P=0.020, non-linear P=0.019). The piecewise regression model identified the association threshold of RFM as 28.933. When RFM ≥28.933, each 1-unit increase in RFM was significantly associated with a 9.4% increase in asthma risk (odds ratio [OR]=1.094, 95% confidence interval [CI]: 1.022-1.171, P=0.010), while there was no significant association between RFM and asthma when RFM <28.933 (OR=0.979, 95% CI: 0.944-1.015, P=0.245). The likelihood ratio test confirmed that the goodness-of-fit of the non-linear model was significantly better than that of the linear model (P=0.027). To verify the stability of the results, we excluded the 2020 follow-up data and performed stratified analyses by covariates. In addition, multiple imputation was used to handle individuals with missing variables for sensitivity analysis. In addition, mediation analysis showed that the inflammation score did not play a significant mediating role in the association between RFM and asthma (β=0.06, 95% CI: -0.02-0.15, P=0.154). This study confirms that higher Relative Fat Mass (RFM) is positively associated with an increased risk of new-onset asthma in some middle-aged and elderly Chinese populations, which may provide clues for further exploration of asthma prevention and control strategies in specific populations.