Diabetes
Patterns of Body Mass Index Trajectories and Incident Diabetes Across Adulthood: a 24-year U.S. cohort study Jane Obi* Jane Obi Obi Obi Obi Obi obi.jane.c@gmail.com
Background: Excess body weight is a major risk factor for type 2 diabetes, yet most epidemiologic studies rely on single-time body mass index (BMI) measures that obscure how weight changes unfold across adulthood. Trajectory-based approaches may better capture the timing and pattern of weight gain relevant to metabolic risk.
Methods: We analyzed longitudinal anthropometric data from 18,527 U.S. adults in the Panel Study of Income Dynamics (1999-2023). BMI trajectories were identified separately for early adulthood (ages 20-39) and mid-adulthood (ages 40-59) using group-based trajectory modeling among participants with at least three observations per window and no diabetes at baseline. Diabetes-free survival was estimated using age-scale Cox proportional hazards models with delayed entry, adjusting for sex, race and ethnicity, education, marital status, income, and baseline BMI. Sensitivity analyses assessed robustness to age-period-cohort (APC) parameterizations.
Results: Three trajectory groups were identified in each age window. In early adulthood, compared with a low-stable trajectory, diabetes hazards were 2.45-fold higher for a moderate-increasing trajectory (95% CI: 1.83-3.29) and 3.10-fold higher for a high-accelerating trajectory (95% CI: 2.11-4.57). In contract, in mid-adulthood, corresponding associations were weaker in magnitude, though still elevated (1.56 [95% CI: 1.23-1.99] and 2.19 [95% CI: 1.61-2.97], respectively). Findings were robust across APC sensitivity analyses.
Conclusions: BMI trajectories reveal substantial heterogeneity in diabetes risk that is not captured by static BMI classification alone. The magnitude of risk associated with adverse trajectories is greatest when high-risk patterns emerge in early adulthood, underscoring timing as a critical dimension of adiposity-related risk. These results support life-course approaches to diabetes prevention that incorporate longitudinal weight history to identify high-risk individuals earlier.
