How much do universal anthropometric standards bias the global monitoring of obesity and undernutrition?

Obes Rev. 2016 Nov;17(11):1030-1039. doi: 10.1111/obr.12449. Epub 2016 Jul 7.

Abstract

Each year, hundreds of articles in population health and nutrition, many in high-profile journals, use standard cutoffs based on weight and height as assessments of obesity and undernutrition. These global efforts to monitor overweight and underweight often rest on the assumption that ethnic differences in underlying body form are sufficiently small to permit universal anthropometric cutoffs for comparing excess and insufficient body fat across populations. However, a century of work in human biological variation suggests that human populations can vary dramatically in underlying body form in a way that may require population-sensitive cutoffs for monitoring. Here, we describe recently developed methods that can provide population-sensitive assessments of both excess and insufficient energy reserves in a wide range of countries. We use this approach to illustrate how worldwide variation in human body form is far more widespread than previously thought, and that it can occur at several geographic scales, including the level of world regions, countries and populations within countries. The findings also suggest that using standard cutoffs that ignore this variation can underestimate current obesity levels in adults by more than 400-500 million while also incorrectly prioritizing high-risk areas for undernutrition in children in key regions around the world.

Keywords: Anthropometric; body mass index; growth standards; undernutrition; weight-for-height.

Publication types

  • Review

MeSH terms

  • Analysis of Variance
  • Anthropometry / methods*
  • Body Height
  • Body Mass Index
  • Body Weight
  • Developed Countries
  • Developing Countries
  • Global Health* / standards
  • Humans
  • Malnutrition / diagnosis*
  • Malnutrition / epidemiology*
  • Nutrition Surveys
  • Obesity / diagnosis*
  • Obesity / epidemiology*
  • Population Surveillance / methods*
  • Prejudice*
  • Reference Standards
  • Socioeconomic Factors