Population-Based Estimates of Decreases in Quality-Adjusted Life Expectancy Associated with Unhealthy Body Mass Index
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Updated: Nov 20, 2025

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
Published on: June 7, 2024
Haomiao Jia1, Matthew M Zack2, William W Thompson3
1Columbia University, Mailman School of Public Health and School of Nursing, Department of Biostatistics, New York, NY.
Objective:
Being classified as outside the normal range for body mass index (BMI) has been associated with increased risk for chronic health conditions, poor health-related quality of life (HRQOL), and premature death. To assess the impact of BMI on HRQOL and mortality, we compared quality-adjusted life expectancy (QALE) by BMI levels.
Methods:
We obtained HRQOL data from the 1993-2010 Behavioral Risk Factor Surveillance System and life table estimates from the National Center for Health Statistics national mortality files to estimate QALE among U.S. adults by BMI categories: underweight (BMI <18.5 kg/m(2)), normal weight (BMI 18.5-24.9 kg/m(2)), overweight (BMI 25.0-29.9 kg/m(2)), obese (BMI 30.0-34.9 kg/m(2)), and severely obese (BMI ≥35.0 kg/m(2)).
Results:
In 2010 in the United States, the highest estimated QALE for adults at 18 years of age was 54.1 years for individuals classified as normal weight. The two lowest QALE estimates were for those classified as either underweight (48.9 years) or severely obese (48.2 years). For individuals who were overweight or obese, the QALE estimates fell between those classified as either normal weight (54.1 years) or severely obese (48.2 years). The difference in QALE between adults classified as normal weight and those classified as either overweight or obese was significantly higher among women than among men, irrespective of race/ethnicity.
Conclusions:
Using population-based data, we found significant differences in QALE loss by BMI category. These findings are valuable for setting national and state targets to reduce health risks associated with severe obesity, and could be used for cost-effectiveness evaluations of weight-reduction interventions.
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