Association of cumulative exposure and dynamic change patterns of metabolic syndrome score with cardiometabolic multimorbidity progression among middle-aged and older Chinese adults: a longitudinal analysis based on CHARLS

Abstract Background Cardiometabolic multimorbidity (CMM) leads to adverse health outcomes. Based on data from the China Health and Retirement Longitudinal Study (CHARLS), we aimed to explore the cumulative exposure and dynamic change patterns of metabolic syndrome score (MetSS) with CMM progression among middle-aged and older Chinese adults. Methods Age and sex specific MetSS was assessed according to equations which were developed for Chinese. K-means clustering analysis was used to classify MetSS changes, and cumulative MetSS (cuMetSS) was calculated as follows: (MetSS2012 + MetSS2015)/2 × time (2015 − 2012). The progression of CMM was defined starting with CMD-free, developing into first CMD (FCMD), further progressing into CMM. Logistic regression analyses and restricted cubic splines (RCS) were performed to evaluate the association of MetSS with CMM progression in 3 models. Subgroup and interaction analyses were subsequently undertaken to investigate the effect of physical activity on the associations of baseline MetSS, cuMetSS and MetSS change patterns with FCMD and CMM risk, respectively. Results A total of 3,322 participants were eligible for analysis, of whom 679 experienced FCMD and 101 progressed to CMM. The K-means method classified 4 clusters. Logistic analyses revealed that the risk of CMM both increased with baseline MetSS and cuMetSS increment in all 3 models. Baseline MetSS on continuous scale was not significantly associated with FCMD (all P > 0.05). Yet cuMetSS on continuous scale was significantly associated with increased risk of FCMD when adjusted age and gender (model 1: OR, 95% CI, P: 1.02, 1.01 to 1.03, 0.006), additionally adjusted education, marital status, residence, drinking status, smoking status, BMI and comorbidity (model 2: 1.02, 1.00 to 1.03, 0.008). Further additional adjustment for physical activity (model 3) yielded no statistical significance (P > 0.05). Further subgroup analyses suggested that significance was only noted in subgroups with inactive or vigorous physical activity. Conclusions Our findings indicate that cumulative exposure and dynamic change patterns of MetSS were associated with FCMD and CMM, yet there is a modifiable effect of physical activity on the associations of cuMetSS and MetSS change patterns with FCMD risk. Graphical Abstract