Quality of Life Research

, Volume 23, Issue 4, pp 1371–1376 | Cite as

The impact of weight loss on health-related quality-of-life: implications for cost-effectiveness analyses

  • Amy E. RothbergEmail author
  • Laura N. McEwen
  • Andrew T. Kraftson
  • Gina M. Neshewat
  • Christine E. Fowler
  • Charles F. Burant
  • William H. Herman



To assess the impact of weight loss on health-related quality-of-life (HRQL), to describe the factors associated with improvements in HRQL after weight loss, and to assess the relationship between obesity as assessed by body mass index (BMI) and HRQL before and after weight loss.


We studied 188 obese patients with BMI ≥ 32 kg/m2 with one or more comorbidities or ≥35 kg/m2. All patients had baseline and follow-up assessments of BMI and HRQL using the EuroQol (EQ-5D) and its visual analog scale (VAS) before and after 6 months of medical weight loss that employed very low-calorie diets, physical activity, and intensive behavioral counseling.


At baseline, age was 50 ± 8 years (mean ± SD), BMI was 40. 0 ± 5.0 kg/m2, EQ-5D-derived health utility score was 0.85 ± 0.13, and VAS-reported quality-of-life was 0.67 ± 0.18. At 6-month follow-up, BMI decreased by 7.0 ± 3.2 kg/m2, EQ-5D increased by 0.06 [interquartile range (IQR) 0.06–0.17], and VAS increased by 0.14 (IQR 0.04–0.23). In multivariate analyses, improvement in EQ-5D and VAS were associated with lower baseline BMI, greater reduction in BMI at follow-up, fewer baseline comorbidities, and lower baseline HRQL. For any given BMI category, EQ-5D and VAS tended to be higher at follow-up than at baseline.


Measured improvements in HRQL between baseline and follow-up were greater than predicted by the reduction in BMI at follow-up. If investigators use cross-sectional data to estimate changes in HRQL as a function of BMI, they will underestimate the improvement in HRQL associated with weight loss and underestimate the cost-utility of interventions for obesity treatment.


Obesity Body mass index Very low-calorie diet EQ-5D Health utility score Cost-utility analysis 



The work was supported by Grant Number DK089503 (MNORC) and Grant Number P30DK092926 (MCDTR) from the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health. Additional support was provided by the A. Alfred Taubman Medical Institute and the Robert C. and Veronica Atkins Foundation.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Amy E. Rothberg
    • 1
    Email author
  • Laura N. McEwen
    • 1
  • Andrew T. Kraftson
    • 1
  • Gina M. Neshewat
    • 1
  • Christine E. Fowler
    • 1
  • Charles F. Burant
    • 1
  • William H. Herman
    • 2
  1. 1.Division of Metabolism, Endocrinology and Diabetes, Department of Internal MedicineUniversity of MichiganAnn ArborUSA
  2. 2.Departments of Internal Medicine and EpidemiologyUniversity of MichiganAnn ArborUSA

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