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May 24, 20260 citationsOpen Access

Drivers of socioeconomic inequalities of child hunger during COVID-19 in South Africa: evidence from NIDS-CRAM Waves 1-5

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HCHuman Sciences Research Council

Key Points

  • This research aims to analyze the socioeconomic factors contributing to child hunger in South Africa during the COVID-19 pandemic.
  • Utilized National Income Dynamics Study-Coronavirus Rapid Mobile Survey (NIDS-CRAM Waves 1-5) data.
  • Determined child hunger using a composite index and conducted logistic regression analysis.
  • Employed the decomposable Erreygers' concentration index to assess socioeconomic inequalities.
  • Child hunger rates varied across five waves, with wave 1 reporting 19% hunger and wave 2 at 13.76%.
  • The highest hunger burden was found among urban children compared to rural children.
  • Significant determinants included access to utilities, education, gender, household size, and age of respondents.

Abstract

Background: Child hunger has long-term and short-term consequences, as starving children are at risk of many forms of malnutrition, including wasting, stunting, obesity and micronutrient defciencies. The purpose of this paper is to show that the child hunger and socio-economic inequality in South Africa increased during her COVID-19 pandemic due to various lockdown regulations that have afected the economic status of the population. Methods: This paper uses the National Income Dynamics Study-Coronavirus Rapid Mobile Survey (NIDS-CRAM WAVES 1-5) collected in South Africa during the intense COVID-19 pandemic of 2020 to assess the socioeconomic impacts of child hunger rated inequalities. First, child hunger was determined by a composite index calculated by the authors. Descriptive statistics were then shown for the investigated variables in a multiple logistic regression model to identify significant risk factors of child hunger. Additionally, the decomposable Erreygers' concentration index was used to measure socioeconomic inequalities on child hunger in South Africa during the Covid-19 pandemic. Results: The overall burden of child hunger rates varied among the five waves (1-5). With proportions of adult respondents indicated that a child had gone hungry in the past 7 days: wave 1 (19.00%), wave 2 (13.76%), wave 3 (18.60%), wave 4 (15, 68%), wave 5 (15.30%). Child hunger burden was highest in the first wave and lowest in the second wave. The hunger burden was highest among children living in urban areas than among children living in rural areas. Access to electricity, access to water, respondent education, respondent gender, household size, and respondent age were significant determinants of adult reported child hunger. All the concentrated indices of the adult reported child hunger across households were negative in waves 1-5, suggesting that children from poor households were hungry. The intensity of the pro-poor inequalities also increased during the study period. To better understand what drove socioeconomic inequalities, in this study we analyzed the decomposed Erreygers Normalized Concentration Indices (ENCI). Across all five waves, results showed that race, socioeconomic status and type of housing were important factors in determining the burden of hunger among children in South Africa. This study described the burden of adult reported child hunger and associated socioeconomic inequalities during the Covid-19 pandemic. The increasing prevalence of adult reported child hunger, especially among urban children, and the observed poverty inequality necessitate multisectoral pandemic shock interventions now and in the future, especially for urban households.

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Human Sciences Research Council (2026) studied this question.

synapsesocial.com/papers/6a12965848a0ea16656730a7https://doi.org/10.14749/32364558
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Impact of COVID-19 on household hunger and socio-economic inequality in South Africa: a comparative analysis using NIDS-CRAM (2020-2021) and NFNSS 2022 data2026
  2. 2Child and adolescent food insecurity in South Africa: a household-level analysis of hunger2026
  3. 3Income-related health inequalities associated with the coronavirus pandemic in South Africa: a decomposition analysis2026
  4. 4Vulnerability to hunger during the Covid-19 pandemic: proactive food assistance policy actions2025
  5. 5The COVID-19 pandemic reveals an unprecedented rise in hunger: South African government was ill-prepared to meet the challenge2025