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Background <p>Despite progress towards SDG2, malnutrition remains a major concern. Little is known about co-occurrence patterns of nutritional deficits, particularly in low- and middle-income countries. This study analyzes four key child nutrition indicators: hemoglobin (Hb), height-for-age z-score (HAZ), weight-for-age z-score (WAZ), and weight-for-height z-score (WHZ), to identify shared risk factors and spatio-temporal dynamics of malnutrition in sub-Saharan Africa (SSA).</p> Methods <p>Data on 205,374 children aged six to 59 months, of both sexes, from 30 countries in SSA, surveyed between 2003 and 2020, were obtained from the Demographic and Health Surveys. These data were merged with geospatial information from various sources. The generalized additive models for location, scale and shape framework was used to fit a multivariate Gaussian model to investigate co-occurrence patterns, shared risk factors and spatio-temporal variability of malnutrition indicators in SSA.</p> Results <p>The analysis reveals substantial variability in the analyzed indicators across age groups and geographic regions. In 2020, among included countries, the corresponding estimated prevalence rates were: (i) anemia: 69.6% [66.2% -72.8%]; (ii) stunting: 32.9% [32.2% -33.6%]; (iii) underweight: 14.8% [13.6% -15.9%]; (iv) wasting: 5.2% [4.5% -6.0%]; and (v) overweight: 2.5% [2.0% -3.1%]. Strong correlations were observed between WAZ and WHZ (0.70 [0.67-0.73]) and HAZ and WAZ (0.68 [0.64-0.71]), suggesting that chronic malnutrition often co-occurs with acute malnutrition. In contrast, the correlation between anthropometric indicators and the Hb level was relatively low, although geographic variability still highlights specific hotspots.</p> Conclusions <p>We provide high-resolution prevalence estimates for anemia, stunting, underweight, wasting, and overweight, alongside their pairwise correlations. The pronounced spatial heterogeneity highlights the need for localized, coordinated interventions. The findings support multi-sectoral strategies involving nutrition, health, education, and social protection programs to reduce malnutrition in SSA.</p>

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Co-occurrence patterns of malnutrition indicators among children in sub-Saharan Africa

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月9日

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  • Johannes Seiler,
  • Benjamin Müller,
  • Isabel Günther,
  • Mattias Wetscher,
  • Reto Stauffer,
  • Nikolaus Umlauf,
  • Kenneth Harttgen

摘要

Background

Despite progress towards SDG2, malnutrition remains a major concern. Little is known about co-occurrence patterns of nutritional deficits, particularly in low- and middle-income countries. This study analyzes four key child nutrition indicators: hemoglobin (Hb), height-for-age z-score (HAZ), weight-for-age z-score (WAZ), and weight-for-height z-score (WHZ), to identify shared risk factors and spatio-temporal dynamics of malnutrition in sub-Saharan Africa (SSA).

Methods

Data on 205,374 children aged six to 59 months, of both sexes, from 30 countries in SSA, surveyed between 2003 and 2020, were obtained from the Demographic and Health Surveys. These data were merged with geospatial information from various sources. The generalized additive models for location, scale and shape framework was used to fit a multivariate Gaussian model to investigate co-occurrence patterns, shared risk factors and spatio-temporal variability of malnutrition indicators in SSA.

Results

The analysis reveals substantial variability in the analyzed indicators across age groups and geographic regions. In 2020, among included countries, the corresponding estimated prevalence rates were: (i) anemia: 69.6% [66.2% -72.8%]; (ii) stunting: 32.9% [32.2% -33.6%]; (iii) underweight: 14.8% [13.6% -15.9%]; (iv) wasting: 5.2% [4.5% -6.0%]; and (v) overweight: 2.5% [2.0% -3.1%]. Strong correlations were observed between WAZ and WHZ (0.70 [0.67-0.73]) and HAZ and WAZ (0.68 [0.64-0.71]), suggesting that chronic malnutrition often co-occurs with acute malnutrition. In contrast, the correlation between anthropometric indicators and the Hb level was relatively low, although geographic variability still highlights specific hotspots.

Conclusions

We provide high-resolution prevalence estimates for anemia, stunting, underweight, wasting, and overweight, alongside their pairwise correlations. The pronounced spatial heterogeneity highlights the need for localized, coordinated interventions. The findings support multi-sectoral strategies involving nutrition, health, education, and social protection programs to reduce malnutrition in SSA.