NutritionNutrition

Child hunger

Author/s: Katharine Hall
Date: August 2024

Definition

This indicator shows the number and percentage of children living in households where children are reported to go hungry “sometimes”, “often” or “always” because there wasn’t enough food. 

Data


Data Source
Statistics South Africa (2003 - 2023) General Household Survey 2002 - 2022. Pretoria: Stats SA.
Analysis by Katharine Hall, Children’s Institute, UCT.
Notes
  1. Children are defined as persons aged 0 – 17 years.
  2. Population numbers have been rounded off to the nearest thousand.
  3. Sample surveys are always subject to error, and the proportions simply reflect the mid-point of a possible range. The confidence intervals (CIs) indicate the reliability of the estimate at the 95% level. This means that, if independent samples were repeatedly taken from the same population, we would expect the proportion to lie between upper and lower bounds of the CI 95% of the time. The wider the CI, the more uncertain the proportion. Where CIs overlap for different sub-populations or time periods we cannot be sure that there is a real difference in the proportion, even if the mid-point proportions differ. CIs are represented in the bar graphs by vertical lines at the top of each bar.

Section 28(1) (c) of the Bill of Rights in the Constitution gives every child the right to basic nutrition. The fulfilment of this right depends on children's access to sufficient food. There are a number of ways in which access to food can be monitored. At a global level, the Food and Agricultural Association (FAO) regularly publishes estimates of the prevalence of undernourishment, which is defined as the percentage of a population without access to sufficient dietary energy needed for an active and healthy life.1

Child hunger is emotive and subjective, and this is likely to undermine the reliability of estimates on the extent and frequency of reported hunger, but it is assumed that variation and reporting error will be reasonably consistent so that it is possible to monitor trends from year to year.

In 2022, 12% of children in South Africa (nearly 2.6 million) lived in households that reported child hunger. Nearly a third of these children (31%) were from KwaZulu-Natal. Reported child hunger rates in 2022 were 18 percentage points lower than they were in 2002 when 30% of children (5.5 million) lived in households that reported child hunger. The largest declines have been in the Eastern Cape, Limpopo, Mpumalanga and KwaZulu-Natal. One of the main contributors to the long-term decline is the expansion of the Child Support Grant which steadily increased its coverage, reaching nearly 13 million children in 2020.2

Another possible contributor to declining child hunger is the National School Nutrition Programme (NSNP), which reaches over nine million learners in approximately 20,000 schools.3 However, the NSNP only operates during term-time and does not include children who are too young to attend school.

Analysis of child hunger rates within provinces shows that child hunger rates in 2022 are highest in the Northern Cape (where 24% of children were in households that reported child hunger) and North West (19%), followed by KwaZulu-Natal (18%) and Western Cape (16%). The Western Cape is also the only province where child hunger rates have not reduced in the past two decades. Given population growth, the estimated number of children reported to be hungry in that province has increased from 275,000 in 2002 to 340,000 in 2022.

The lowest reported hunger rates were in Limpopo (4%). Despite high poverty rates, Limpopo has always reported child hunger rates below the national average, perhaps because of its highly fertile and productive land in rural areas where most of the population lives. However, there is no clear explanation for the dramatic decline in reported hunger in the Eastern Cape. Over the period 2002 – 2022, reported child hunger rates in that province fell from 48% (higher than any other province) to 7% (the second lowest), despite the fact that the Eastern Cape has the highest poverty rates in the country, with nearly half of children living below the food poverty line.

There are no differences in reported child hunger across gender or age groups. However, as with many other indicators, child hunger is high racialised: 13% of African children and 11% of Coloured children live in households that reported child hunger, compared with less than 4% of Indian and almost no White children. Differences are even more pronounced across income quintiles. While 20% of children living in the poorest 20% of households experienced hunger, less than 1% of children in quintile 5 (the richest 20%) lived in households where child hunger was reported. Of all those who did report child hunger, over half were in the poorest income quintile. For many years, reported hunger rates were higher in the rural former homelands than in urban areas, but the difference has reduced over time and in 2022 there was no significant difference between the area types. Food insecurity is prevalent in both urban and rural areas.

Children who suffer from hunger are at risk of various forms of malnutrition, including wasting, stunting, overweight and micronutrient deficiencies. The 2016 Demographic and Health Survey recorded the stunting rate among children under 5 years at 27% - a figure that has remained persistently high since the 1990s and indicates high rates of chronic undernutrition. The more recent National Food and Nutrition Security Survey conducted by the Human Sciences Research Council between 2021 and 2023 found similarly high levels of malnutrition, with the under-5 stunting estimate at 29% nationally.4 This suggests that chronic malnutrition has remained persistently high, and even worsened in the last decade.

It must be recognised that child hunger is a subjective indicator and does not capture other important aspects of food security such as dietary diversity and consumption of nutrient-rich foods, both of which are important for children’s healthy growth especially in early childhood. Children living in households that do not report hunger may still not have access to sufficient nutritious food be at risk of malnutrition. In 2022, for example, around 80% of children who lived in households with incomes below the food poverty line were not reported to have suffered hunger. Food poverty is an indicator that households lack the financial resources needed to meet minimum dietary requirements for children and other household members. Other measures of food insecurity also suggest a more serious challenge than the subjective hunger indicator. For example, in 2022, 20% of children lived in households that reported running out of food due to lack of money, while 25% lived in households that had been forced to cut the range of foods they could afford to buy.
 
1 FAO, IFAD, UNICEF, WFP & WHO (2019) The State of Food Security and Nutrition in the World 2019. Safeguarding against economic slowdowns. Rome: FAO.
2 Statistics South Africa. General Household Survey series. Analysis by K Hall, Children's Institute.
3 National Treasury. Estimates of National Expenditure, Vote 14 Basic Education. Pretoria: National Treasury. 2019.
4 Simelane T, Mutanga SS, Hongoro C, Parker W, Mjimba V, Zuma K, . . . Marinda E. National Food and Nutrition Security Survey: National Report. Pretoria: Human Sciences Research Council. 2023.

The General Household Survey asks: “In the past 12 months, did any child in this household go hungry because there wasn’t enough food?” Those children living in households where the respondent answered “sometimes”, “often” or “always” are included as children experiencing hunger. "Not applicable” and unspecified responses were excluded from the analysis, and the distribution of valid responses was applied to the total child population.

The ‘hunger’ question in the General Household Survey provides notoriously weak data. Child hunger is emotive, subjective and estimates of frequency unreliable – particularly since the presence and frequency of ‘child hunger’ is reported by one adult in the household. It is assumed, however, that reporting error will be similar in each year of data collection, so that it is possible to report trends even if proportions for a single year are questionable. For this indicator the 5-point scale is collapsed into a dichotomous (yes/no) variable.

The numbers are derived from the General Household Survey, a multi-purpose annual survey conducted by the national statistical agency, Statistics South Africa, to collect information on a range of topics from households in the country’s nine provinces.

The GHS uses a Master Sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys that have design requirements that are reasonably compatible with the GHS. The sample is drawn from Census enumeration areas using a stratified two-stage design with probability proportional to size sampling of PSUs in teh first stage, and sampling of dwelling units with systematic sampling in the second stage. The resulting sample consists of just over 20,000 households with around 70,000 individuals, and should be representative of all households in South Africa. It is also designed to be representative at provincial level and within provinces at metro/non-metro levels and three geography types (urban areas, rural areas under traditional authority, and farms).

The sample consists of households and does not cover other collective institutionalised living-quarters such as boarding schools, orphanages, students’ hostels, old-age homes, hospitals, prisons, military barracks and workers’ hostels. These exclusions probably do not have a noticeable impact on the findings in respect of children.

Changes in sample frame and stratification
Since 2014 the GHS has been based on the 2013 master sample that that is, in turn, based on information collected during the 2011 Population Census. The previous master sample for the GHS was used for the first time in 2008, and the one before that in 2004. These again differed from the master sample used in the first two years of the GHS: 2002 and 2003. Thus there have been four different sampling frames during history of the annual GHS, with the changes occurring in 2004, 2008 and 2013. In addition, there have been changes in the method of stratification over the years. These changes could compromise comparability across iterations of the survey to some extent, although it is common practice to use the GHS for longitudinal monitoring and many of the official trend analyses are drawn from this survey.

Weights
Person and household weights are provided by Stats SA and are applied in Children Count analyses to give population estimates on the indicators. The GHS weights are derived from Stats SA’s mid-year population estimates for the relevant year. The population estimates are based on a model that is revised from time to time when it is possible to calibrate the population model to Census data and larger population surveys such as the Community Survey.

In 2017, Stats SA revised its demographic model to produce a new series of mid-year population estimates and the GHS data were re-released with the revised population weights. All the Children Count indicators were re-analysed retrospectively, using the revised weights provided by Stats SA, based on the 2013 model. The estimates are therefore comparable over all years. The revised weights particularly affected estimates for the years 2002 – 2007.

The 2017 model drew on the 2011 census, along with vital registration, antenatal and other administrative data, but was a “smoothed” model that did not mimic the unusual shape of the age distribution found in the census. The results of the 2011 census were initially distrusted because it seemed to over-count children in the 0 – 4 age group and under-count children in the 4 – 14-year group. It is now thought that the fertility rates recorded in the 2011 population census may have been an accurate reflection of demopraphic trends, with an unexplained upswing in fertility around 2009 after which fertility rates declined again gradually. Similar patterns were found in the vital registration data as more births were reported retrospectively to the Department of Home Affairs, and in administrative data from schools, compiled by the Department of Basic Education. In effect, this means that there may be more children in South Africa than appear from the analyses presented in these analyses, where we have applied weights based on a model that it is now known to be inaccurate.

Stats SA has subsequently developed a new population model - the 2022 series, which provides revised mid-year population estimates back to 2002 and projected to 2032. However, the GHS series has not yet been reweighted.The population estimates in Children Count are therefore based on weights derived from outdated population model (2017). It is not yet clear when and how the population model will be revised again following the 2022 Census, as there are concerns around census under-count and plausibility of its findings.

Disaggregation
Statistics South Africa suggests caution when attempting to interpret data generated at low level disaggregation. The population estimates are benchmarked at the national level in terms of age, sex and population group while at provincial level, benchmarking is by population group only. This could mean that estimates derived from any further disaggregation of the provincial data below the population group may not be robust enough.

Reporting error
Error may be present due to the methodology used, i.e. the questionnaire is administered to only one respondent in the household who is expected to provide information about all other members of the household. Not all respondents will have accurate information about all children in the household. In instances where the respondent did not or could not provide an answer, this was recorded as “unspecified” (no response) or “don’t know” (the respondent stated that they didn’t know the answer).

For more information on the methods of the General Household Survey, see the metadata for the respective survey years, available on Nesstar  or DataFirst