Economic shocks predict increases in child wasting prevalence

The study examines whether short-term macroeconomic contractions in low- and middle-income countries increase the risk of child wasting, an acute form of malnutrition strongly associated with under-5 mortality. Against the backdrop of substantial macroeconomic volatility in LMICs and the exceptional, widespread income losses during COVID-19, the authors assess how deviations from long-run economic growth affect wasting. While extensive literature links long-run economic growth to stunting and documents mortality impacts of negative shocks, the economic determinants of wasting are less understood. Using multi-country data spanning 1990–2018, the paper tests the hypothesis that negative growth shocks raise the prevalence of mild, moderate/severe, and severe wasting, and explores potential mechanisms including child diet quality, infectious disease symptoms, and maternal nutritional status.

Prior research has largely focused on the relationship between longer-term economic growth and reductions in child stunting, with several cross-country studies documenting growth–nutrition linkages. Other work has shown that adverse macroeconomic shocks in LMICs increase infant and child mortality. However, the literature on economic determinants of acute malnutrition (wasting) is limited relative to stunting, despite wasting’s stronger association with mortality. Evidence also points to regional differences in wasting patterns (e.g., South Asia versus sub-Saharan Africa) and to seasonality, suggesting complex etiologies. The present study extends this literature by focusing on short-run growth shocks and wasting, and by probing mechanisms related to child diet diversity, infections, and maternal nutritional status.

Data: 177 Demographic and Health Surveys (DHS) from 52 LMICs, 1990–2018, including anthropometry for children 0–59 months (approximately 1.256 million children). Wasting was defined using WHO standards for weight-for-height z-scores: any wasting (WHZ < -1), moderate/severe wasting (WHZ < -2), and severe wasting (WHZ < -3). Macroeconomic indicators were annual changes in Gross Domestic Product (GDP) per capita and Gross National Income (GNI) per capita, primarily from the UN National Accounts Database; robustness checks used World Bank indicators.

Weights: A three-step weighting scheme was constructed to make the pooled analysis representative of the under-5 population across countries and rounds: (1) country-level weights based on under-5 population size (UN), (2) re-weighting within-country survey rounds to equalize round contributions, and (3) standard DHS survey weights.

Empirical strategy: Multivariate linear probability models estimated the impact of lagged (one-year) national growth shocks on child wasting. Growth shocks were operationalized as deviations of annual growth from long-run country-specific growth, interacted with a country’s mean wasting prevalence (for each wasting definition). This interaction allows effects to scale with the underlying prevalence and facilitates interpretation of the coefficient as an elasticity with respect to a 10% change in income. Models included country fixed effects and rich region-specific temporal controls: month-of-interview dummies (seasonality), child age-in-month dummies (wasting-age dynamics), and 5-year period dummies (secular trends). Child, maternal, and household covariates included asset ownership (improved flooring, electricity, TV, fridge, car/motorbike), maternal education (years), proxies for health service access and use (≥4 ANC visits, facility birth, full immunization), WASH (piped water, flush toilet), demographics (teenage birth, parity ≥4), child sex, and rural residence. Standard errors were clustered at the country level. Sensitivity analyses added national-level controls for climate (lagged rainfall, temperature) and conflict (battle-related deaths per 100,000), excluded growth outliers, and substituted World Bank macro indicators.

Mechanisms: Additional regressions assessed associations between contemporaneous growth shocks and intermediate outcomes: child diarrhea or fever-only in the past two weeks (0–59 m), low maternal BMI (<18.5; 15–49 y), and minimum dietary diversity (MDD; ≥4 of 7 food groups; children 6–35 m), including analyses of individual food groups. These models followed a similar structure with the relevant country mean of the outcome interacting with growth.

• Main elasticities (Table 1): Growth elasticities of wasting with respect to lagged GNI and GDP shocks are negative and statistically significant across wasting severity.

  • GNI shocks: A 10% reduction predicts increases of approximately 7.1% (any wasting, WHZ < -1), 14.4% (moderate/severe wasting, WHZ < -2), and 22.2% (severe wasting, WHZ < -3). 95% CIs: (-0.114, -0.028), (-0.213, -0.076), (-0.325, -0.118) for the elasticities.
  • GDP shocks: A 10% reduction predicts increases of approximately 8.8% (any wasting), 17.8% (moderate/severe), and 29.1% (severe). 95% CIs: (-0.162, -0.013), (-0.312, -0.044), (-0.526, -0.056).
  • Elasticity magnitudes rise with wasting severity; GDP-based elasticities tend to be larger in absolute value but less precisely estimated than GNI-based ones.

• Predicted COVID-19 impact (Table 2): Applying the GDP elasticity for moderate/severe wasting (-0.178) to IMF 2020 GDP growth estimates (relative to 2010–2019 averages) suggests about 9.37 million additional preschool children could have become wasted in 2021 due to 2020 economic contractions. India accounts for a large share of the projected increase given its sizable GDP shock (-14.9% in 2020), high pre-COVID wasting prevalence (20.8%), and large under-5 population (~117 million).

• Mechanisms (Table 3 and supplements):

  • Diet quality: For GNI shocks, a 10% negative shock is associated with a 19.4 percentage-point lower probability that children 6–35 months achieve minimum dietary diversity (statistically significant at 5%). GDP-based estimates are directionally similar but imprecise and not statistically significant overall; consumption of flesh foods shows a significant decline with negative shocks.
  • Morbidity: GDP shocks are associated with higher diarrhea and fever-only prevalence at the 10% significance level; these associations are not robust for GNI shocks. Associations between growth shocks and low maternal BMI are imprecise and not statistically different from zero.

• Heterogeneity and robustness: Results are robust to extensive specification checks, inclusion of climate and conflict controls, exclusion of growth outliers, and alternative macro data sources (with World Bank GNI measures yielding larger absolute elasticities). There is suggestive evidence that urban children are more sensitive to growth shocks; for GDP shocks, girls may be somewhat more sensitive than boys.

The findings confirm that short-run macroeconomic contractions substantially elevate risks of child wasting in LMICs, addressing a key gap in the literature that has emphasized stunting and mortality. The elasticities indicate that even moderate income declines can yield meaningful increases in mild, moderate/severe, and severe wasting. These results help explain prior evidence linking adverse macro shocks to higher child mortality and underscore the heightened risk during COVID-19: aggregate income losses alone, even absent direct health system disruptions, likely worsened wasting burdens. Indications that dietary diversity declines during negative shocks suggest household food access and diet quality are plausible channels, while morbidity-related mechanisms are less consistently supported across macro measures. Urban children’s greater sensitivity aligns with evidence that non-farm livelihoods are more exposed to macro downturns than farm-based ones. The large projected impact in India highlights the importance of country-specific dynamics in global estimates and the need for targeted responses.

This study provides cross-country evidence that negative macroeconomic shocks significantly increase child wasting across severity thresholds, with larger effects for more severe wasting. By quantifying elasticities using DHS data linked to national accounts, it contributes a novel, policy-relevant perspective on the short-run nutrition consequences of income contractions. In the context of COVID-19, the results imply substantial increases in wasting, concentrated in large, high-prevalence countries. Policy implications include coupling the protection of health systems with nutrition-sensitive social protection to safeguard household incomes and diet quality, particularly for urban populations and other vulnerable groups. Future research should further characterize heterogeneity in impacts across countries and subpopulations, integrate health system disruption data, and leverage higher-frequency nutrition and economic monitoring to refine real-time risk assessments and policy targeting.

• Limited number of country-year shock episodes relative to child sample size restricts exploration of heterogeneity across shocks and countries.
• Macroeconomic shocks arise from diverse causes; impacts may vary across socioeconomic groups depending on economic structure and social protection, potentially attenuating estimated average effects.
• National income measures (GDP/GNI) are imperfect proxies for household welfare; household income losses may exceed average national income declines during crises.
• Extraordinary policy responses during COVID-19 (social protection, income support) may have mitigated household-level impacts, making historically derived elasticities potential upper bounds for pandemic-period effects.
• The analysis focuses on economic channels; it does not quantify concurrent health system disruptions (e.g., reduced ANC, immunization, treatment of severe acute malnutrition), which also affect wasting and mortality.