Metabolic Scarring: The Persistent Impact of Past Obesity on Long-Term Metabolic Health Despite Weight Loss

Abstract

Background

Conventional cardiometabolic risk assessment relies primarily on a patient's current body mass index, yet individuals who have lost weight after a period of obesity may continue to harbour elevated metabolic risk. We sought to quantify the persistent impact of past obesity on glycaemic control and to develop a clinical risk score that integrates weight history with current risk factors.

Methods

We performed a cross-sectional analysis of 15,422 adults (≥ 18 years) from the 2011–2020 NHANES cycles. Participants with complete self-reported weight history (highest adult weight, weight 1 year ago, number of ≥ 5% weight-loss episodes) and measured BMI were included. Metabolic scarring was defined by elevated haemoglobin A1c (HbA1c ≥ 5.7%) or HOMA-IR ≥ 2.5. We applied inverse-probability-weighted logistic regression to estimate the association between prior obesity and current HbA1c, adjusting for confounders. We then refit a survey-weighted logistic model using age per decade, current BMI, weight-history category, sex and race/ethnicity, converting regression coefficients into an integer point-based score. Discrimination was evaluated by survey-weighted area under the receiver-operating characteristic curve (AUC).

Results

Formerly obese individuals exhibited significantly higher HbA1c than never-obese peers (adjusted β = 0.58%, p < 0.002), indicative of metabolic scarring. The derived risk score ranged from −31 to +90 points (median = 6; IQR = −3 to 16) and achieved an AUC of 0.79 (95% CI 0.77–0.81). Age per decade, BMI, and weight history contributed 4, 1 and up to 4 points, respectively; female sex and Non-Hispanic White race subtracted points. Calibration across predicted-risk deciles was excellent (slope = 0.98).

Conclusions

A history of obesity imparts a lasting glycemic risk that is not captured by current BMI alone. Our metabolic scarring risk score offers a pragmatic tool for identifying individuals at elevated metabolic risk despite weight normalisation.