Abstract
The dynamic and heterogeneous process of obesity measurement can be better assessed by change trajectories. Utilizing multiple metrics to assess obesity could provide more comprehensive insights. Currently, the associations of adiposity measures trajectories with metabolic diseases and plant-based dietary patterns remain unclear. Using latent class mixed modeling approach, we identified body mass index (BMI), waist-to-hip ratio (WHR) and fat mass index (FMI) trajectory groups based on measures acquired at four time points. We examined associations between adiposity measures trajectories and plant-based dietary patterns, using logistic regression. Cox proportional hazards regression models were applied to investigate the association between adiposity measures trajectories and metabolic diseases. We identified two latent classes of BMI trajectories: low-smooth and high-growth-decline, two WHR trajectories: low-growth and high-growth, and two FMI trajectories: low-smooth and high-growth-decline. Participants who had a high healthful plant-based diet index had lower odds of being in the high-growth-decline BMI trajectory (OR = 0.491, 95% CI: 0.402, 0.600), the high-growth WHR trajectory (OR = 0.526, 95% CI: 0.438, 0.632) or the high-growth-decline FMI trajectory (OR = 0.533, 95% CI: 0.446, 0.638). We found that participants in the high-growth-decline BMI trajectory (HR = 1.925, 95% CI: 1.542, 2.404), the high-growth WHR trajectory (HR = 1.314, 95% CI: 1.003, 1.722) or the high-growth-decline FMI trajectory (HR = 1.562, 95% CI: 1.236, 1.975) had higher risks. A healthy plant-based dietary pattern assists in maintaining normal body size over time. Concurrently, long-term stabilization of a normal body size may be linked to a reduced risk of metabolic diseases.