Objective <p>To discover the associations between long-term body mass index (BMI) trajectories and dyslipidemia, and the internal mechanism within different BMI trajectory populations.</p> Methods <p>We chose 11,499 adults from China Health and Nutrition Survey (CHNS) for trajectory modeling. Selected those with two blood lipid measurements (<i>n</i> = 2,003), and determine the risk trajectory group associated with dyslipidemia. We selected two subsets of the 2015 CHNS, CHNS-1 (<i>n</i> = 3,061) and CHNS-2 (<i>n</i> = 1,409) for gut microbiome analysis. A Lasso regression in both the CHNS-1 and the CHNS-2 confirmed the dominant genera of each dyslipidemia risk trajectory. We also used a subset of CHNS-2 (<i>n</i> = 779) with metabolomics data to identify the differential metabolites. We ascertained the connection between microbiome and metabolites via correlation analysis.</p> Results <p>We identified three BMI trajectories: The developing into overweight (DO) group and the overweight to obesity (OTO) group had increased dyslipidemia risks compared to the normal stable (NS) group, OR: 1.69(95%CI: 1.30,2.20);1.93(95%,CI:1.34,2.77). There are significant differences in gut microbiota between OTO/DO group and NS group, PERMANOVA R² = 0.50 and 0.23, <i>p</i> &lt; 0.001. we found six taxa in the OTO group and five taxa in the DO group had lower abundance than in the NS group. after adjusting for covariates, yielded an AUC of 0.759 and 0.646 in the validation set. In the OTO and DO groups we also found 36 metabolites and 5 metabolites, respectively, with differential concentrations than in the NS group.</p> Conclusions <p>A high-level BMI change trajectory will increase the risk of developing dyslipidemia in the future. The growth trajectory of BMI affects lipid metabolism mediated by gut microbiota.These findings may reveal the mechanism of BMI changes leading to dyslipidemia, and indicate the corresponding microbiome targets for prevention.</p>