Ethnicity and anthropometric deficits in children: a cross-sectional analysis of national survey data from 18 countries in sub-Saharan Africa

Background Anthropometric deficits persist in sub-Saharan Africa (SSA) despite sustained improvements in nutrition, disease burden and living conditions. The UN Sustainable Development Goals advocate for disaggregation of health indicators by ethnic group. However, few studies have assessed how ethnicity is associated with anthropometric deficits across SSA. Methods Data were extracted from 37 georeferenced Demographic and Health Surveys carried out during 2006-2019 across SSA that recorded anthropometric data for children aged <5 years. In a cross-sectional analysis, the odds of stunting (low height-for-age), wasting (low weight-for-height) and underweight (low weight-for-age) were modelled in relation to ethnic group using a generalised linear hierarchical mixed-effects model, controlling for survey design and environmental, socioeconomic, and clinical variables. Findings The study population comprised 138,312 children spanning 45 ethnic groups across 18 countries. In pairwise comparisons between ethnic groups, height-for-age Z scores differed by at least 0.5 standard deviations in 56% of comparisons, weight-for-height Z scores in 39% of comparisons and weight-for-age Z scores in 34% of comparisons. Compared to a reference group of Fula children (the largest ethnic group), ethnic group membership was associated with both increases and decreases in growth faltering, ranging from a 69% reduction to a 32% increase in odds of stunting (Igbo: adjusted odds ratio (aOR) 0.31, 95% confidence intervals (CI) 0.27-0.35, p<0.0001; Hausa: aOR 1.32, 95% CI 1.21-1.44, p<0.0001); a 13% to 87% reduction in odds of wasting (Mandinka: aOR 0.87, 95% CI 0.76-0.99, p=0.034; Bamileke: aOR 0.13, 95% CI 0.05-0.32, p<0.0001) and an 85% reduction to 13% increase in odds of underweight (Bamileke: aOR 0.15, 95% CI 0.08-0.29, p<0.0001; Hausa: aOR 1.13, 95% CI 1.03-1.24, p=0.010). Interpretation Major ethnic disparities in stunting, wasting and underweight were observed across 18 countries in SSA. Understanding and accounting for these differences is essential to support progress monitoring and targeting of nutrition interventions in children. Funding UK Medical Research Council, Novo Nordisk Foundation Evidence before this study We searched PubMed with no date restrictions for studies published in English, using the following search terms: (“child*”, “five” OR “infant”) AND (“child growth”, “stunting”, “stunted”, “growth failure”, “growth faltering”, “height” OR “anthropometric”) AND (“ethnic*”). We identified 288 studies (196 from the database search and 92 from reference lists). Of 93 studies full text studies screened, 37 were relevant. Two multi-country studies measured the association between ethnicity and growth outcomes. An analysis of 13 national surveys from Latin America during 2006-2020 found a 97% higher prevalence of stunting among indigenous than European or mixed ancestry participants. In a 2014 systematic review, 20% of height means in 55 countries or ethnic groups differed by ≥0.5 standard deviations (SD) from the WHO Multicentre Growth Reference Study mean, suggesting some differences. A further 35 local studies measured ethnicity as a potential risk factor for child growth outcomes in Australia, Brazil, China, Guatemala, Hawaii, India, Iran, Lithuania, Malaysia, Nepal, Peru, South Africa, Thailand, Trinidad and Tobago, the UK and the USA, with a range of associations observed. We identified additional multi-country, population-based cohorts designed to support the development of international growth standards, but these did not specifically measure inequalities between ethnic groups. Added value of this study To our knowledge, this is the first systematic, multi-country analysis of ethnicity and anthropometric deficits in sub-Saharan Africa. By analysing data for 138,312 children spanning 45 ethnic groups in 18 countries, measured in 37 Demographic and Health Surveys, we found ethnicity to be a primary risk factor for anthropometric deficits after adjusting for socioeconomic, environmental and child-level characteristics. The strength of this association exceeded that for other factors known to affect children’s growth, such as household wealth, history of diarrhoea and access to improved water and sanitation. Anthropometric z-scores differed by ≥0.5 SD (a clinically relevant threshold) in 34%-56% of pairwise comparisons between ethnic groups. Implications of all the available evidence Child growth faltering persists as a major cause of morbidity and mortality in sub-Saharan Africa[1][1] but our study shows that this burden is unequally distributed among ethnic groups. Research is needed to understand these differences, in order to target interventions and effectively track progress towards Sustainable Development Goal 2. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement LST is a Skills Development Fellow (N011570) jointly funded by the UK Medical Research Council and the UK Department for International Development under the MRC/DFID Concordat agreement (http://www.mrc.ac.uk/). LST receives support from the Novo Nordisk Foundation (number 0069116). The authors alone are responsible for the views expressed in this Article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated. This study was funded by UK Medical Research Council, Novo Nordisk Foundation ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All health data used in this analysis are available to download free of charge by registered users from the Demographic and Health Surveys Program. Registration, data, and full dataset access instructions are available online at http://dhsprogram.com. Code to replicate data extraction and curation is available at: https://github.com/harry-gibson/DHS-To-Database. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All health data used in this analysis are available to download free of charge by registered users from the Demographic and Health Surveys Program. Registration, data, and full dataset access instructions are available online at . Remotely sensed data are available to download from the cited sources. Code to replicate data extraction and curation is available at: . [1]: #ref-1