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Multilevel analysis of individual, household, and community factors influencing child growth in Nepal
BACKGROUND: Childhood malnutrition and growth faltering is a serious concern in Nepal. Studies of child growth typically focus on child and mother characteristics as key factors, largely because Demographic and Health Surveys (DHS) collect data at these levels. To control for and measure the importa...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449894/ https://www.ncbi.nlm.nih.gov/pubmed/30953501 http://dx.doi.org/10.1186/s12887-019-1469-8 |
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author | Smith, Tim Shively, Gerald |
author_facet | Smith, Tim Shively, Gerald |
author_sort | Smith, Tim |
collection | PubMed |
description | BACKGROUND: Childhood malnutrition and growth faltering is a serious concern in Nepal. Studies of child growth typically focus on child and mother characteristics as key factors, largely because Demographic and Health Surveys (DHS) collect data at these levels. To control for and measure the importance of higher-level factors this study supplements 2006 and 2011 DHS data for Nepal with data from coincident rounds of the Nepal Living Standards Surveys (NLSS). NLSS information is summarized at the district level and matched to children using district identifiers available in the DHS. METHODS: The sample consists of 7533 children aged 0 to 59 months with complete anthropometric measurements from the 2006 and 2011 NDHS. These growth metrics, specifically height-for-age and weight-for-height, are used in multilevel regression models, with different group designations as upper-level denominations and different observed characteristics as upper-level predictors. RESULTS: Characteristics of children and households explain most of the variance in height-for-age and weight-for-height, with statistically significant but relatively smaller overall contributions from community-level factors. Approximately 6% of total variance and 22% of explained variance in height-for-age z-scores occurs between districts. For weight-for-height, approximately 5% of total variance, and 35% of explained variance occurs between districts. CONCLUSIONS: The most important district-level factors for explaining variance in linear growth and weight gain are the percentage of the population belonging to marginalized groups and the distance to the nearest hospital. Traditional determinants of child growth maintain their statistical power in the hierarchical models, underscoring their overall importance for policy attention. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12887-019-1469-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6449894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64498942019-04-15 Multilevel analysis of individual, household, and community factors influencing child growth in Nepal Smith, Tim Shively, Gerald BMC Pediatr Research Article BACKGROUND: Childhood malnutrition and growth faltering is a serious concern in Nepal. Studies of child growth typically focus on child and mother characteristics as key factors, largely because Demographic and Health Surveys (DHS) collect data at these levels. To control for and measure the importance of higher-level factors this study supplements 2006 and 2011 DHS data for Nepal with data from coincident rounds of the Nepal Living Standards Surveys (NLSS). NLSS information is summarized at the district level and matched to children using district identifiers available in the DHS. METHODS: The sample consists of 7533 children aged 0 to 59 months with complete anthropometric measurements from the 2006 and 2011 NDHS. These growth metrics, specifically height-for-age and weight-for-height, are used in multilevel regression models, with different group designations as upper-level denominations and different observed characteristics as upper-level predictors. RESULTS: Characteristics of children and households explain most of the variance in height-for-age and weight-for-height, with statistically significant but relatively smaller overall contributions from community-level factors. Approximately 6% of total variance and 22% of explained variance in height-for-age z-scores occurs between districts. For weight-for-height, approximately 5% of total variance, and 35% of explained variance occurs between districts. CONCLUSIONS: The most important district-level factors for explaining variance in linear growth and weight gain are the percentage of the population belonging to marginalized groups and the distance to the nearest hospital. Traditional determinants of child growth maintain their statistical power in the hierarchical models, underscoring their overall importance for policy attention. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12887-019-1469-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-05 /pmc/articles/PMC6449894/ /pubmed/30953501 http://dx.doi.org/10.1186/s12887-019-1469-8 Text en © The Author(s). 2019 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 | Research Article Smith, Tim Shively, Gerald Multilevel analysis of individual, household, and community factors influencing child growth in Nepal |
title | Multilevel analysis of individual, household, and community factors influencing child growth in Nepal |
title_full | Multilevel analysis of individual, household, and community factors influencing child growth in Nepal |
title_fullStr | Multilevel analysis of individual, household, and community factors influencing child growth in Nepal |
title_full_unstemmed | Multilevel analysis of individual, household, and community factors influencing child growth in Nepal |
title_short | Multilevel analysis of individual, household, and community factors influencing child growth in Nepal |
title_sort | multilevel analysis of individual, household, and community factors influencing child growth in nepal |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449894/ https://www.ncbi.nlm.nih.gov/pubmed/30953501 http://dx.doi.org/10.1186/s12887-019-1469-8 |
work_keys_str_mv | AT smithtim multilevelanalysisofindividualhouseholdandcommunityfactorsinfluencingchildgrowthinnepal AT shivelygerald multilevelanalysisofindividualhouseholdandcommunityfactorsinfluencingchildgrowthinnepal |