Obesity prevalence: comparison of traditional and new classification approaches in a Swiss population-based study (2005–2024)
Authors' conclusion
Adding anthropometric measures to BMI substantially improves obesity detection. Choosing the combination of anthropometric measures and BMI with awareness of sex and age-related changes better identifies at risk individuals. This new definition can be a powerful low-cost tool in detecting individuals on the obesity spectrum early in primary care settings and prevent complications.
Study context
- Population
- Population-based study in Geneva, Switzerland (2005–2024); mean age 48.2 ± 13.7; 51.4% women
- Participants
- 14,658 participants
- Exposure
- New obesity classifications vs body mass index (BMI) alone
- Outcome
- Obesity prevalence by traditional and new definitions
Methodological detailspopulation-based
- Population-based
Main finding
As reported in the abstract
Obesity prevalence
New classifications
10.8% to 39.9%
BMI alone
13.1%
P < 0.001
Observational data: associations, not effects.
Further findings
Reclassification
- Reclassifications differed among men and women and with age
Discrimination for cardiovascular and metabolic outcomes
- New classifications showed superior discriminative performance vs BMI alone
Association with diabetes, hypertension and dyslipidemia
- BMI + WHR, diabetes: aOR
- 4.61; 3.87-5.47 (CI)
- BMI + WHR, hypertension: aOR
- 3.61; 3.18-4.09 (CI)
- Waist-to-hip and waist-to-height ratio, dyslipidemia: aOR
- 1.95; 1.75-2.16 (CI)
Original publication
Obesity prevalence: comparison of traditional and new classification approaches in a Swiss population-based study (2005–2024). Int J Obes (Lond). Published 1 April 2026. doi:10.
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