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Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification
BACKGROUND: The methodology currently used for nutritional assessment of populations classifies children according to four conditions: eutrophy, wasting, stunting, and overweight. However, children can be stunted and wasted concomitantly. Similarly, they can be stunted and overweight. These conditio...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014708/ https://www.ncbi.nlm.nih.gov/pubmed/32046666 http://dx.doi.org/10.1186/s12887-020-1940-6 |
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author | Ferreira, Haroldo da Silva |
author_facet | Ferreira, Haroldo da Silva |
author_sort | Ferreira, Haroldo da Silva |
collection | PubMed |
description | BACKGROUND: The methodology currently used for nutritional assessment of populations classifies children according to four conditions: eutrophy, wasting, stunting, and overweight. However, children can be stunted and wasted concomitantly. Similarly, they can be stunted and overweight. These conditions are associated with greater susceptibility to mortality or chronic diseases, respectively. This work presents an adaptation of Waterlow’s classification (AWC), which discriminates six nutritional conditions. Additionally, it provides a command routine in Stata, which processes the z-scores of the anthropometric indices height-for-age and weight-for-height and presents the respective prevalence of the nutritional conditions. METHODS: Data from two household surveys were used to demonstrate the application of AWC, which were conducted in 1992 (n = 1229) and 2015 (n = 987), with probabilistic samples of children (< 5 years) in Alagoas, Northeast Brazil. AWC is based on a cross-classification scheme, involving the categories obtained with height-for-age (z < − 2; z ≥ − 2) and weight-for-height (z < − 2; − 2 to 2; z > 2). RESULTS: The prevalence obtained with AWC in 1992 and 2015 was, respectively: eutrophy (71.0/80.2), stunting (20.8/2.7), wasting (0.8/2.1), concurrent stunting and wasting (0.5/0.0), overweight (4.8/14.4) and short stature with overweight (2.0/0.5). The prevalence of wasting, concurrent wasting and stunting, and for short stature with overweight was never higher than 2.3%. Possibly these values should be much higher in countries where there is a high prevalence of undernutrition. In total, 472 children had low height-for-age. By the usual anthropometric classification, they would be classified as chronic undernourished. However, 39 (8.3%) of them were also overweight and seven (1.5%) had concurrent stunting and wasting, a condition at extreme risk of mortality, which is perhaps the explanation for its low prevalence in cross-sectional studies. CONCLUSION: In addition to identifying wasted, stunted and overweight children, AWC also identified children with two other conditions, which are generally neglected in most nutritional surveys. Each of these nutritional conditions have different characteristics (aetiology, preventive, and therapeutic approach, damage to the patient’s health, and priority level in public policy). Such aspects justify their identification in the distinct scenarios where nutritional surveys are developed. |
format | Online Article Text |
id | pubmed-7014708 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70147082020-02-20 Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification Ferreira, Haroldo da Silva BMC Pediatr Technical Advance BACKGROUND: The methodology currently used for nutritional assessment of populations classifies children according to four conditions: eutrophy, wasting, stunting, and overweight. However, children can be stunted and wasted concomitantly. Similarly, they can be stunted and overweight. These conditions are associated with greater susceptibility to mortality or chronic diseases, respectively. This work presents an adaptation of Waterlow’s classification (AWC), which discriminates six nutritional conditions. Additionally, it provides a command routine in Stata, which processes the z-scores of the anthropometric indices height-for-age and weight-for-height and presents the respective prevalence of the nutritional conditions. METHODS: Data from two household surveys were used to demonstrate the application of AWC, which were conducted in 1992 (n = 1229) and 2015 (n = 987), with probabilistic samples of children (< 5 years) in Alagoas, Northeast Brazil. AWC is based on a cross-classification scheme, involving the categories obtained with height-for-age (z < − 2; z ≥ − 2) and weight-for-height (z < − 2; − 2 to 2; z > 2). RESULTS: The prevalence obtained with AWC in 1992 and 2015 was, respectively: eutrophy (71.0/80.2), stunting (20.8/2.7), wasting (0.8/2.1), concurrent stunting and wasting (0.5/0.0), overweight (4.8/14.4) and short stature with overweight (2.0/0.5). The prevalence of wasting, concurrent wasting and stunting, and for short stature with overweight was never higher than 2.3%. Possibly these values should be much higher in countries where there is a high prevalence of undernutrition. In total, 472 children had low height-for-age. By the usual anthropometric classification, they would be classified as chronic undernourished. However, 39 (8.3%) of them were also overweight and seven (1.5%) had concurrent stunting and wasting, a condition at extreme risk of mortality, which is perhaps the explanation for its low prevalence in cross-sectional studies. CONCLUSION: In addition to identifying wasted, stunted and overweight children, AWC also identified children with two other conditions, which are generally neglected in most nutritional surveys. Each of these nutritional conditions have different characteristics (aetiology, preventive, and therapeutic approach, damage to the patient’s health, and priority level in public policy). Such aspects justify their identification in the distinct scenarios where nutritional surveys are developed. BioMed Central 2020-02-11 /pmc/articles/PMC7014708/ /pubmed/32046666 http://dx.doi.org/10.1186/s12887-020-1940-6 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Technical Advance Ferreira, Haroldo da Silva Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification |
title | Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification |
title_full | Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification |
title_fullStr | Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification |
title_full_unstemmed | Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification |
title_short | Anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of Waterlow’s classification |
title_sort | anthropometric assessment of children’s nutritional status: a new approach based on an adaptation of waterlow’s classification |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014708/ https://www.ncbi.nlm.nih.gov/pubmed/32046666 http://dx.doi.org/10.1186/s12887-020-1940-6 |
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