Literature DB >> 27383689

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

D J Hruschka1, C Hadley2.   

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.
© 2016 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.

Entities:  

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

Mesh:

Year:  2016        PMID: 27383689     DOI: 10.1111/obr.12449

Source DB:  PubMed          Journal:  Obes Rev        ISSN: 1467-7881            Impact factor:   9.213


  11 in total

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Review 4.  What is normal, healthy growth? Global health, human biology, and parental perspectives.

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5.  Weight, gender, and depressive symptoms in South Korea.

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6.  Anthropometric indices for non-pregnant women of childbearing age differ widely among four low-middle income populations.

Authors:  K Michael Hambidge; Nancy F Krebs; Ana Garcés; Jamie E Westcott; Lester Figueroa; Shivaprasad S Goudar; Sangappa Dhaded; Omrana Pasha; Sumera Aziz Ali; Antoinette Tshefu; Adrien Lokangaka; Vanessa R Thorsten; Abhik Das; Kristen Stolka; Elizabeth M McClure; Rebecca L Lander; Carl L Bose; Richard J Derman; Robert L Goldenberg; Melissa Bauserman
Journal:  BMC Public Health       Date:  2017-07-24       Impact factor: 3.295

7.  Body Composition Findings by Computed Tomography in SARS-CoV-2 Patients: Increased Risk of Muscle Wasting in Obesity.

Authors:  Paola Gualtieri; Carmela Falcone; Lorenzo Romano; Sebastiano Macheda; Pierpaolo Correale; Pietro Arciello; Nicola Polimeni; Antonino De Lorenzo
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8.  The association of quantitative insulin sensitivity indices (HOMA-IR and QUICKI) with anthropometric and cardiometabolic indicators in adolescents.

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9.  Material wealth in 3D: Mapping multiple paths to prosperity in low- and middle- income countries.

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Journal:  PLoS One       Date:  2017-09-08       Impact factor: 3.240

10.  Body mass index vs deuterium dilution method for establishing childhood obesity prevalence, Ghana, Kenya, Mauritius, Morocco, Namibia, Senegal, Tunisia and United Republic of Tanzania.

Authors:  Adama Diouf; Theodosia Adom; Abdel Aouidet; Asmaa El Hamdouchi; Noorjehan I Joonas; Cornelia U Loechl; Germana H Leyna; Dorcus Mbithe; Thabisile Moleah; Andries Monyeki; Hilde Liisa Nashandi; Serge Ma Somda; John J Reilly
Journal:  Bull World Health Organ       Date:  2018-09-10       Impact factor: 9.408

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