Association of Relative Fat Mass with Incident Depressive Symptoms among Older Adults: A 14-Year Analysis of the ELSA and HRS Cohorts.

Higher baseline RFM predicted incident depressive symptoms in both the ELSA and HRS cohorts over approximately 8.6 years of follow-up.

• ELSA cohort: n = 4176, mean follow-up 8.60 years, 1467 participants developed incident depressive symptoms
• HRS cohort: n = 5054, mean follow-up 8.57 years, 1769 participants developed incident depressive symptoms
• Participants were adults ≥50 years without baseline depressive symptoms (CES-D-8 <3)
• Incident depressive symptoms defined as CES-D-8 ≥3 at follow-up
• Follow-up was biennial for up to 14 years

Each 1-standard deviation increase in RFM was independently associated with significantly higher hazard of incident depressive symptoms in both cohorts.

• ELSA fully adjusted Model 3: HR = 1.15, 95% CI = 1.06–1.25
• HRS fully adjusted Model 3: HR = 1.10, 95% CI = 1.05–1.16
• RFM was examined both continuously (per 1-SD increase) and by tertiles
• Cox proportional hazards models were used with progressive covariate adjustment

Compared with the lowest RFM tertile, the highest RFM tertile was associated with substantially greater risk of incident depressive symptoms in both cohorts.

• ELSA high vs. low RFM tertile: HR = 1.37, 95% CI = 1.12–1.67
• HRS high vs. low RFM tertile: HR = 1.29, 95% CI = 1.14–1.46
• Associations persisted after progressive covariate adjustment

The dose-response relationship between RFM and incident depressive symptoms followed a J-shaped pattern.

• Dose-response was assessed using restricted cubic splines
• A J-shaped association was suggested across both cohorts
• This implies risk is elevated at higher RFM values with a nonlinear pattern

RFM demonstrated superior time-varying predictive discrimination for incident depressive symptoms compared with BMI and waist circumference across follow-up.

• Predictive performance was compared using time-dependent AUCs
• RFM consistently outperformed both BMI and waist circumference (WC) across the follow-up period
• RFM is computed from measured height and waist circumference

Findings were robust across sensitivity analyses using multiple imputation and propensity-score matching.

• Sensitivity analyses included multiple imputation to address missing data
• Propensity-score matching was also applied as a sensitivity analysis
• Results were consistent with primary analyses in both cohorts

The study used harmonized data from two nationally representative aging cohorts to examine whether RFM predicts late-life depressive symptoms better than conventional anthropometrics.

• Data came from the English Longitudinal Study of Ageing (ELSA) and the US Health and Retirement Study (HRS)
• Both cohorts included adults ≥50 years without baseline depressive symptoms
• RFM was computed from measured height and waist circumference
• Conventional comparators were BMI and waist circumference (WC)