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      Child malnutrition in sub-Saharan Africa: A meta-analysis of demographic and health surveys (2006-2016)

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          Abstract

          Background

          Sub-Saharan Africa has one of the highest levels of child malnutrition globally. Therefore, a critical look at the distribution of malnutrition within its sub-regions is required to identify the worst affected areas. This study provides a meta-analysis of the prevalence of malnutrition indicators (stunting, wasting and underweight) within four sub-regions of sub-Saharan Africa.

          Methods

          Cross-sectional data from the most recent Demographic and Health Surveys (2006–2016) of 32 countries in sub-Saharan Africa were used. The countries were grouped into four sub-regions (East Africa, West Africa, Southern Africa and Central Africa), and a meta-analysis was conducted to estimate the prevalence of each malnutrition indicator within each of the sub-regions. Significant heterogeneity was detected among the various surveys (I 2 >50%), hence a random effect model was used, and sensitivity analysis was performed, to examine the effects of outliers. Stunting was defined as HAZ<-2; wasting as WHZ<-2 and underweight as WAZ<-2.

          Results

          Stunting was highest in Burundi (57.7%) and Malawi (47.1%) in East Africa; Niger (43.9%), Mali (38.3%), Sierra Leone (37.9%) and Nigeria (36.8%) in West Africa; Democratic Republic of Congo (42.7%) and Chad (39.9%) in Central Africa. Wasting was highest in Niger (18.0%), Burkina Faso (15.50%) and Mali (12.7%) in West Africa; Comoros (11.1%) and Ethiopia (8.70%) in East Africa; Namibia (6.2%) in Southern Africa; Chad (13.0%) and Sao Tome & Principle (10.5%) in Central Africa. Underweight was highest in Burundi (28.8%) and Ethiopia (25.2%) in East Africa; Niger (36.4%), Nigeria (28.7%), Burkina Faso (25.7%), Mali (25.0%) in West Africa; and Chad (28.8%) in Central Africa.

          Conclusion

          The prevalence of malnutrition was highest within countries in East Africa and West Africa compared to the WHO Millennium development goals target for 2015. Appropriate nutrition interventions need to be prioritised in East Africa and West Africa if sub-Saharan Africa is to meet the WHO global nutrition target of improving maternal, infant and young child nutrition by 2025.

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          Maternal and child undernutrition and overweight in low-income and middle-income countries

          Robert E Black, Cesar G Victora, Susan P. Walker … (2013)
          The Lancet, 382(9890), 427-451
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            Malnutrition in Sub – Saharan Africa: burden, causes and prospects

            Luchuo Bain, Paschal Kum Awah, Ngia Geraldine … (2013)
            Malnutrition is estimated to contribute to more than one third of all child deaths, although it is rarely listed as the direct cause. Contributing to more than half of deaths in children worldwide; child malnutrition was associated with 54% of deaths in children in developing countries in 2001. Poverty remains the major contributor to this ill. The vicious cycle of poverty, disease and illness aggravates this situation. Grooming undernourished children causes children to start life at mentally sub optimal levels. This becomes a serious developmental threat. Lack of education especially amongst women disadvantages children, especially as far as healthy practices like breastfeeding and child healthy foods are concerned. Adverse climatic conditions have also played significant roles like droughts, poor soils and deforestation. Sociocultural barriers are major hindrances in some communities, with female children usually being the most affected. Corruption and lack of government interest and investment are key players that must be addressed to solve this problem. A multisectorial approach is vital in tackling this problem. Improvement in government policy, fight against corruption, adopting a horizontal approach in implementing programmes at community level must be recognized. Genetically modified foods to increase food production and to survive adverse climatic conditions could be gateways in solving these problems. Socio cultural peculiarities of each community are an essential base line consideration for the implementation of any nutrition health promotion programs.
            Article 0 comments Cited 127 times – based on 0 reviews     Review now
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              Linear growth deficit continues to accumulate beyond the first 1000 days in low- and middle-income countries: global evidence from 51 national surveys.

              Edward A. Frongillo, Piet L. J. M. Leroy, Marie Ruel … (2014)
              Growth faltering is usually assessed using height-for-age Z-scores (HAZs), which have been used for comparisons of children of different age and sex composition across populations. Because the SD (denominator) for calculating HAZ increases with age, the usefulness of HAZs to assess changes in height over time (across ages) is uncertain. We posited that population-level changes in height as populations age should be assessed using absolute height-for-age differences (HADs) and not HAZs. We used data from 51 nationwide surveys from low- and middle-income countries and graphed mean HAZs and HADs by age. We also calculated annual changes in HAZs and HADs and percentage of total height deficit accumulated annually from birth to age 60 mo using both approaches. Mean HAZ started at -0.4 Z-scores and dropped dramatically up to 24 mo, after which it stabilized and had no additional deterioration. Mean HAD started at -0.8 cm, with the most pronounced faltering occurring between 6 and 18 mo, similar to HAZ. However, in sharp contrast to HAZ, HAD curves had continued increases in the deficit of linear growth from 18 to 60 mo, with no indication of a leveling off. Globally, 70% of the absolute deficit accumulated in height (HAD) at 60 mo was found to be due to faltering during the first "1000 days" (conception to 24 mo), but 30% was due to continued increases in deficit from age 2 to 5 y. The use of HAZ masks these changes because of age-related changes in SD. Therefore, HAD, rather than HAZ, should be used to describe and compare changes in height as children age because detecting any deficit compared with expected changes in height as children grow is important and only HAD does this accurately at all ages. Our findings support the current global programmatic momentum to focus on the first 1000 d. Research is needed to better understand the dynamics and timing of linear growth faltering using indices and indicators that accurately reflect changes over ages and to identify cost-effective ways to prevent growth faltering and its consequences throughout the lifecycle. © 2014 American Society for Nutrition.
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                Author and article information

                Contributors
                Frank Wieringa: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 11 May 2017
                Publication date Collection: 2017
                Volume: 12
                Issue: 5
                Electronic Location Identifier: e0177338
                Affiliations
                [1 ]School of Science and Health, Western Sydney University, Penrith, New South Wales, Australia
                [2 ]School of Social Sciences and Psychology, Western Sydney University, Penrith, New South Wales, Australia
                [3 ]School of Public Health and Community Medicine, University of New South Wales, Sydney, New South Wales, Australia
                Institut de recherche pour le developpement, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: BJA KEA.

                • Formal analysis: BJA.

                • Methodology: BJA.

                • Writing – original draft: BJA.

                • Writing – review & editing: BJA KEA DM AMR JJH.

                Author information
                http://orcid.org/0000-0002-6410-4154
                Article
                Publisher ID: PONE-D-16-51511
                DOI: 10.1371/journal.pone.0177338
                PMC ID: 5426674
                PubMed ID: 28494007
                SO-VID: 9cc9df94-5f21-4bae-9640-7247f78ad55e
                Copyright © © 2017 Akombi et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 1 January 2017
                Date accepted : 26 April 2017
                Page count
                Figures: 4, Tables: 1, Pages: 11
                Funding
                Professor Andre M. Renzaho is supported by an ARC Future Fellowship (FT110100345). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Biology and Life Sciences
                Subject: Nutrition
                Subject: Malnutrition
                Subject: Medicine and Health Sciences
                Subject: Nutrition
                Subject: Malnutrition
                Subject: Biology and Life Sciences
                Subject: Nutrition
                Subject: Medicine and Health Sciences
                Subject: Nutrition
                Subject: People and Places
                Subject: Geographical Locations
                Subject: Africa
                Subject: People and Places
                Subject: Population Groupings
                Subject: Age Groups
                Subject: Children
                Subject: People and Places
                Subject: Population Groupings
                Subject: Families
                Subject: Children
                Subject: Biology and Life Sciences
                Subject: Population Biology
                Subject: Population Metrics
                Subject: Population Growth
                Subject: Medicine and Health Sciences
                Subject: Pediatrics
                Subject: Child Health
                Subject: Medicine and Health Sciences
                Subject: Public and Occupational Health
                Subject: Child Health
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Anthropometry
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Anthropometry
                Subject: Research and Analysis Methods
                Subject: Mathematical and Statistical Techniques
                Subject: Statistical Methods
                Subject: Meta-Analysis
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Statistics (Mathematics)
                Subject: Statistical Methods
                Subject: Meta-Analysis
                Custom metadata
                Data Availability Data are from the DHS Program [ http://dhsprogram.com/data/data-collection.cfm]. Data from the following countries were used: Burundi (2010), Comoros (2012), Ethiopia (2014), Kenya (2014), Malawi (2010), Mozambique (2011), Rwanda (2015), Uganda (2011), Tanzania (2016), Zambia (2014), Zimbabwe (2011), Burkina Faso (2010), Cote de Ivoire (2012), Gambia (2013), Ghana (2014), Guinea (2012), Liberia (2013), Mali (2013), Niger (2012), Nigeria (2013), Senegal (2011), Sierra Leone (2013), Togo (2014), Lesotho (2014), Namibia (2013), Swaziland (2007), Cameroun (2011), Chad (2014), Congo DR (2014), Equatorial Guinea (2011), Gabon (2012), Sao Tome & Principle (2009).

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                ScienceOpen disciplines: Uncategorized

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