food insecurity in south africa essay

Poor South African households can’t afford nutritious food – what can be done

Senior Researcher, Associate Professor Economic Management Sciences, University of Pretoria

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Adrino Mazenda does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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Food insecurity is a feature of life for millions of South Africans. Food insecurity refers to a lack of regular access to enough safe and nutritious food for average growth and development and an active and healthy life. This may be due to unavailability of food or a lack of resources to buy it.

The extent of this was recently mapped by the Human Sciences Research Council. For example, in Gauteng province, South Africa’s economic powerhouse, 51% of households experience food insecurity. A national survey between 2021 and 2023 found Gauteng households were affected to different degrees: 14% faced severe food insecurity, 20% moderate food insecurity, and 17% mild food insecurity.

The research also found that South African households survive on nutrient-poor food groups such as cereals, condiments, sugars, oils and fats. Consumption of nutrient-rich food groups such as fruits, pulses, nuts, eggs, fish and seafood is limited.

Dietary diversity is useful for measuring food security. A diverse, nutritious and balanced diet prevents nutritional deficiencies and diseases. A fall in dietary diversity is linked to a rise in the proportion of people who are malnourished .

The HSRC findings were the most recent to point to a growing crisis of food insecurity in the country. In an earlier study, we examined the diets of people living in South Africa’s second largest city, Tshwane.

We found that due to income, and other socio-economic factors, none of the poor households in our study were getting adequate nutrients from what they were eating. Mostly they were eating cereals (grains such as wheat and maize), vegetables such as legumes, roots and tubers, and oils and fats because they couldn’t afford anything else. Most had little to no income . And most were poorly nourished.

On the basis of the findings we recommended a range of interventions. These included better implementation of existing policies aimed at opening up opportunities, such as the Expanded Public Works Programme . And we recommended campaigns be run to increase people’s awareness about nutritional foods and growing them.

The help of the private sector and NGOs is also recommended.

Mapping eating habits

The study measured what households were choosing to eat from among the various food groups. These were 775 households from food-insecure areas of Tshwane as mapped by the 2016 Statistics South Africa Community Survey . We asked which food groups had been eaten in the previous seven days by any household member at home, including food prepared at home but eaten, for example, at work (such as a packed lunch).

Twelve food choices were used : cereals, legumes, roots and tubers, vegetables, fruits, milk, eggs, meat, fats, fish, sweets and beverages.

The Principal Component Analysis was used to analyse the Tshwane study households’ consumption of these food groups. The analysis is widely used to derive dietary patterns from the daily eating patterns of households.

We then used the Simpson index to measure how nutrient rich the diets were. An index score greater than 0.5 shows a highly diversified diet. The Simpson Index was profiled on socio-economic determinants of food insecurity variables, such as age, household size, income, and food expenditure.

The average dietary diversity score was low for all the poor households in the Tshwane study.

What we found

In our survey, the households with the least diversified diets were those headed by women, people with no more than secondary education, unemployed people, and/or recipients of the social support grant. This suggests that the grants are insufficient to cover people’s food needs.

Households with low dietary diversity rarely reared animals or had food gardens.

Households chose mainly four food groups. The first group was associated with a vegetable-based diet (roots and tubers, legumes, vegetables, and fruit). The second group was associated with people who consumed sugar, honey and miscellaneous products (coffee, tea, soft drinks, and instant foods). The third group comprised people who consumed fats and proteins, eggs and milk products. The final group was associated with the consumption of cereals or staple foods.

It was not possible to identify a group of urban food insecure households that ate a mixed selection of all food groups. This suggests they all lacked adequate dietary requirements to boost nutrition. This was regardless of their socio-economic status.

We also found that households faced a number of obstacles beyond income constraints that limited their dietary diversity. These included unemployment, household size, education, and the lack of land, skills and resources to practise urban agriculture.

The City of Tshwane in Gauteng has adopted numerous strategies to alleviate food insecurity. These include the 2017 climate response strategy , meant to reduce food insecurity due to climate vulnerability, and the Expanded Public Works Programme , which provides job creation and skills development, supporting sustainable socio-economic development and poverty reduction.

But execution has been suboptimal.

Poor coordination among government departments and agencies about priorities has led to interventions being ineffective .

A list of the challenges facing the public works programme was presented by a parliamentary monitoring group. They included delays in implementation and reporting as well as non-submission of quarterly evaluation reports by some public bodies.

As a result, funding from the central government to local and provincial administrations was withheld for the 2024/25 budget.

In addition, the City of Tshwane faces financial challenges that affect its ability to get things done. This means the city cannot solve the problem of food insecurity and nutrition alone.

What’s needed is collaboration between government, the private sector and civil society. Policies could include prioritising food security and nutrition, such as subsidies for nutritious foods, regulations to improve food safety and incentives for sustainable agricultural practices.

Second, public-private partnership must be established to implement food security programmes targeting marginalised households, urban smart agriculture, and community gardens.

Third, there is a need to fund research on innovative food production technologies and sustainable agriculture practices, and share industry data on food supply chains and consumer preferences.

Fourth, there is a need to conduct community-based research on food needs and barriers to access.

Fifth, contribution of financial resources by investing in startups and enterprises focused on improving food security and nutrition outcomes.

Finally, monitoring and evaluation frameworks need to be established to assess the impact of food security policies and programmes and ensure accountability and transparency in resource allocation.

• Food insecurity
• South Africa
• Social grants

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• Nutrition and Dietetics
• Food Insecurity

Evaluating Food Insecurity in South Africa to Achieve Sustainability

• November 2021

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Child and adolescent food insecurity in South Africa: A household-level analysis of hunger

Siluleko Mkhize

1 Department of Family Medicine and Primary Care, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

Elena Libhaber

2 School of Clinical Medicine and Health Sciences Research Office, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

Ronel Sewpaul

3 Health and Wellbeing, Human and Social Capabilities Division, Human Sciences Research Council, Cape Town, South Africa

Priscilla Reddy

4 Faculty of Health Sciences, Nelson Mandela University, Port Elizabeth, South Africa

Laurel Baldwin-Ragaven

Associated data.

The final de-identified anonymised data set used in this study is provided as a “ Supporting information ” file in this manuscript ( S1 Database ). A data sharing agreement was signed with the Human Sciences Research Council (HSRC), the curator of the data collected in the 2012 ANHANES survey. Adult SANHANES data are available through registered access from the HSRC data repository at: http://curation.hsrc.ac.za/Datasets-XKAHAA.phtml . Child data are under third party rights and can be accessed upon reasonable request by contacting az.ca.crsh@plehatad .

Food insecurity impacts childhood nutritional status, physical and cognitive development, and increases lifetime risk for chronic disease. Previous South African studies have examined hunger at the sub-national level without a specific focus on children and adolescents. This study determines the national prevalence of childhood food insecurity, from birth to adolescence, and identifies factors associated with hunger within the household. Individual and household-level data were extracted from the South African National Health and Nutrition Examination Survey (SANHANES-1). Prevalence of food insecurity was assessed using the Community Childhood Hunger Identification Project (CCHIP) index. Multinomial logistic regression analyses were conducted on all households (with and without children) to determine the predictors of food insecurity, with additional analyses adjusting for child dependency and sociodemographic characteristics of household heads in households with children. Of 5 098 households surveyed, 68.6% had children and adolescents present (0–19 years). Of these households, 32.5% (95% Confidence Interval [CI]: 29.5–35.7) were experiencing hunger and 26.3% (95% CI: 23.9–28.8) were at risk of hunger. Among all the households, significant associations for experiencing hunger were the presence of children and adolescents: Adjusted Odds Ratio (AOR) = 1.68 (95% CI: 1.12–2.53); being female-headed: AOR = 1.53 (95% CI: 1.21–1.94) and informally-located; AOR = 1.6 (95% CI: 1.07–2.43). Of the racial groups, having a non-African household head, Coloured: AOR = 0.29 (95% CI: 0.19–0.44) and White/Indian/Asian: AOR = 0.12 (95% CI: 0.04–0.33) conferred lower odds of experiencing hunger; and, the household head having secondary/tertiary education conferred lower odds of experiencing hunger; AOR = 0.40 (95% CI: 0.28–0.56) as well as being at risk of hunger; AOR = 0.69 (95% CI: 0.52–0.92). Receiving social grants, pensions, or remittances more than doubled the odds of experiencing hunger; AOR = 2.15 (95% CI: 1.49–3.09). After adjusting for child dependency in households with children, having at least one older child (age 15–19 years old) did not change the odds of food insecurity. In summary, only 41% of South African households with children and adolescents were food secure. The associations between household head sociodemographics, household location and size on household food insecurity indicate a need for multi-sectoral interventions to bolster sustainable food systems for households with children and adolescents and to improve public protections for female-headed, African-headed and informally-located households dependent on social grants.

Introduction

Food insecurity has emerged as a major public health concern; and, the obligation to realise the “ right to food and basic nutrition” is enshrined in both the United Nations Charter [ 1 ] and the South African Constitution [ 2 ]. The Food and Agriculture Organization (FAO) of the United Nations states that “food security exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life” [ 3 ], emphasising that the availability of food must be beyond mere subsistence [ 4 ]. In Sub-Saharan Africa, one in four people experienced undernutrition in the year 2017. This represents about one-third of the global population estimated to have suffered from chronic hunger in the same year [ 5 ]. According to actuarial projections, Africa will be home to 90% of the world’s poorest by 2030 [ 6 ].

In 2017, 6.8 million South Africans were affected by hunger, representing a 50% decline since 2002; however, at the household-level, the burden of food insecurity remains largely unabated [ 7 ]. Moreover, a considerable but undocumented proportion of these households comprise children and adolescents who are vulnerable to food deprivation and hunger [ 4 ]. Indeed, it has been suggested that the presence of children in households may confer additional “ pressure of mouths to feed ” [ 7 , 8 ].

Throughout the world, household food insecurity is associated with malnutrition, especially stunting and wasting among children under five years old [ 9 ]. Nationally, Lake et al. [ 10 ] reported that approximately half of South African children under age five were malnourished; and, severe-acute and moderate-acute malnutrition accounts for between 4% to 25% of child mortality [ 10 , 11 ]. Such implications of food insecurity on health and nutrition have been observed not only in children under five, but among older children as well. The largest national census of South African households conducted in 2011/12, the South African National Health and Nutrition Examination Survey (SANHANES), reported that the highest prevalence of wasting among children was actually among boys and girls aged 10–14 years (5.6% and 2.5% respectively); and, underweight was most prevalent among boys and girls in the 7–9 year-old age group (8.6% and 4.0% respectively) [ 12 ]. In older children, the South African Demographic and Health Survey (SADHS) showed that 27% and 9% of adolescent girls and boys aged 15–19 years respectively, were overweight or obese [ 13 ], highlighting the double burden of malnutrition across childhood and adolescence in South Africa. Importantly, hunger has profound health consequences that not only affect physical growth and cognitive development in childhood [ 14 , 15 ], but endure throughout the life-course into adulthood [ 16 , 17 ] and extend into subsequent generations [ 18 , 19 ]. Two longitudinal cohort studies of the consequences of hunger that began in the throes of the Second World War, the Dutch Winter Famine [ 19 ] and the siege of Leningrad [ 18 , 20 ] indicate that the effects of intra-uterine exposure to food insecurity can traverse through multiple generations, predisposing to a “thrifty phenotype” among progeny. Bjerregaard, et al. [ 21 ] found that another form of malnutrition, obesity in childhood (measured at ages 7 and 13 years), significantly increased the hazards of developing type-2 diabetes in late adulthood among Danish men. Conversely, reversal of obesity in adolescence reduced the risk by 4%, a finding that may be explained, in part, by food insecurity given that obesity and type-2 diabetes are primarily diet-sensitive adverse health outcomes [ 15 ].

In South Africa, the Community Childhood Hunger Identification Project (CCHIP) index was used to estimate the prevalence of food insecurity nationally between 1999 and 2008 in three different studies: the National Food Consumption Surveys of 1999 and 2005, and the South African Social Attitudes Survey of 2008 [ 22 ]. A review of these surveys, which included children from 1–9 years old with at least one adult in the household, indicated a marked decline in household food insecurity from 52.3% in 1999 to 25.9% in 2008 [ 22 ]. These studies looked at a segment of children (those 1–9 years old), thus perhaps underestimating the true extent of child and adolescent food insecurity [ 23 , 24 ]. Much of what is known about the sociodemographic correlates of food insecurity in South Africa has been gleaned from sub-national cross-sectional studies. Food insecurity measured using the Household Food Insecurity Access Scale (HFIAS) indicated a gradient across the rural-urban continuum of South African towns, with households in rural areas reporting higher scores, and therefore more food insecurity, than peri-urban households (households located in urban-informal settlements) [ 25 ]. Households that are reliant on private food charities and government-assisted social grants are at an increased risk of food insecurity [ 26 ]. It is speculated that while social grants are regular and predictable, they are, however, not sensitive to the changing needs of a household [ 26 , 27 ]. The gender of the household head is also an important factor predicting household vulnerabilities [ 9 ], with the highest prevalence of food insecurity in South Africa reported among female-headed households [ 12 ]. In an analysis of international data, women are more likely to experience food insecurity in comparison to men, which is attributed mainly to disparities in income, education and access to social networks [ 28 ]. Even with increased employment rates among women, the income differentials between women and men has meant that poverty remains strongly gendered. Research into possible reasons for the gendered nature of food insecurity in South Africa include decades of migrant labour practices disrupting family structures, and household size [ 7 ]. Female-headed households are larger, on average, than male-headed households and include more dependent children and adolescents, as well as are less likely to have any household member working [ 11 ].

There is a paucity of nationally representative data to assess the granular detail about food insecurity across the country. The critical need to address hunger in childhood necessitates particular attention to factors affecting food insecurity in households with children and adolescents—such as the household size, household head sociodemographics and dependency status of children—so that nutrition-sensitive interventions can be developed and/or strengthened [ 29 ]. Such interventions would address the underlying determinants of child hunger and include, for example, multi-sectoral approaches to social safety netting through minimum guaranteed income and/or cash transfers; financial, educational and parenting support to female-headed households with children; and bolstering health services and sustainable agricultural practices [ 5 , 29 ]. Such multi-pronged approaches are necessary to mediate the short-term, long-term and inter-generational adverse health consequences of food insecurity on childhood health. Therefore, drawing from a large-scale population-based sample of households, the SANHANES-1, we set out to determine the prevalence of food insecurity in households with and without children as well as to assess associations between the sociodemographic characteristics of the household head and degrees of hunger.

Study design

In 2019–2020, we conducted a secondary data analysis of the SANHANES-1 (2011/12) [ 12 ]. The SANHANES-1 is a cross-sectional nationally representative sample of households that employed a multi-stage disproportionate, stratified cluster sampling approach based on the 2001 census Enumeration Areas (EAs). The first 20 households were sampled from each of the 500 EAs yielding a sample of 10 000 households. Ensuring national representativeness, the SANHANES-1 EA sampling was layered by type of locality (urban/rural; formal/informal), and province (there are nine in South Africa) as well as by “race” in formal urban areas. Using race as a variable allows investigation of ongoing health disparities that have endured post-apartheid. In this way, the SANHANES captures the sociodemographic and economic profile of the country. Additional sample selection details have been published elsewhere [ 12 ]. In our study, we used the “household” as the unit of analysis. Statistics South Africa (Stats-SA) defines a household as “a group of people who live together, eat together and share resources, or a single person who lives alone” [ 30 ]. In the SANHANES-1, household membership was attributed to persons who occupied the same dwelling and slept in the household for at least four nights a week. The household head was identified as a physically present member who was designated internally as the head of that household, and also served as the main respondent for household-level data acquisition.

Data extraction and study population

The SANHANES-1 database includes people of all ages residing in households in South Africa. For the present study, only occupied households were included ( S1 Fig ). Five separate but inter-related SANHANES-1 questionnaires were administered at the household-level by trained field workers capturing information on everyone living in that household (between 1 and 20+ people). The variables of interest for this study were extracted from each of the five questionnaires: visiting point (household) questionnaire (administered to the household head); child questionnaire (0–14 years old); child clinical examination form (0–14 years old); adult questionnaire (administered to anyone ≥ 15 years old); and the adult clinical examination form (≥ 15 years old). After extraction, these data were entered into four separate newly created databases. Children, whom we defined as aged 0–19 years old in order to include the adolescent population in our sample, and adults aged ≥20 years old were extracted from both the child (<15 years) and adult (≥15 years) individual-level datasets, respectively. This age selection aligns with global and national initiatives that target child and adolescent public health and nutrition [ 31 – 35 ]. After merging data for individuals aged 15–19 years with data from those 0–14 years old, thereby reclassifying everyone aged 0–19 years old as “children”, we then reconciled them back into their corresponding households. The final sample that we analysed included 5 098 households and their occupants, both adults and children/adolescents. S1 Fig illustrates the database management, organisation and integration of the different household and individual-level variables from the five SANHANES-1 databases.

Household composition and sociodemographic parameters

At the household-level, the parameters included were household size, the number of adults, the number of children occupying a household and child dependency status. Two variables were created to reflect household dependency status: those with children aged 0–14 years only (yes or no) and those with at least one child 15–19 years old (yes or no), who could theoretically contribute to overall household income given the legal age at which one can start working in South Africa [ 36 ]. Age, self-reported sex (male and female), self-reported race (African, Coloured, White/Indian/Asian), educational attainment (no schooling, primary, secondary, tertiary/higher degrees), marital status (married, living together/civil union, never married, widowed, separated/divorced) and the main source of income (salaries/wages, social grants/remittances/pensions, sale of products and services, no income) of all household heads were also included. Locality (urban, rural, formal and informal) was pre-assigned to the household from the EA sampling.

Household food insecurity

Food insecurity was measured using the CCHIP index, a validated tool for the assessment of food insecurity at the household-level [ 37 ]. While five of the eight questions are child-referenced, making the CCHIP a specific tool for measuring childhood food insecurity, the CCHIP was also administered to households without children, generalising the child-referenced questions to everyone in the household. A score of ≥5 affirmative responses indicate the presence of hunger, understood as “ experiencing hunger ” and recorded as such. A score of 1–4 affirmative responses indicates that the household is “ at risk of hunger ”. Lastly, a score of zero indicates that the household is “ food secure ”.

Statistical analyses

STATA software, version 16.1 (STATA Institute Inc., College Station, TX, USA) was used for database management and statistical analyses. Results are presented as frequencies and percentages for categorical variables and Median [IQR] or arithmetic Mean ± SD in the case of continuous variables. Comparisons between households with and without children were performed using Mann-Whitney U tests for continuous non-normally distributed data. Categorical variables were compared using Chi-Square tests. All analyses were weighted to offset for the over-allocation of EAs in areas where Indian, Coloured or White racial groups prevailed, to ensure that the minimum required sample size in those minority groups were obtained. All analyses were performed using svy function in STATA, incorporating sample weights and stratified cluster sampling design to provide estimates. Weighted prevalence of food security in households with children, stratified by sociodemographic characteristics of the household heads was ascertained from frequencies and percentages; however, age differences in prevalence estimates were computed from a Kruskal-Wallis test with a Bonferroni post hoc correction to adjust for multiple comparisons. To improve statistical power in the regression models, locality was dichotomised to formal vs informal; educational attainment (primary, secondary/tertiary/higher degrees and no schooling); marital status (married, never married, living together/civil unions, and widowed/separated/divorced). Weighted univariable and multivariable multinomial logistic regression analyses with robust standard errors were carried out to determine factors associated with being “at risk of hunger” and “experiencing hunger”, where the “food secure” category was used as the referent group for comparison in all households, and separately in households with and without children. In households with children, we conducted additional univariable multinomial logistic regressions to examine associations between food security and child dependency, and between food security and female-headed households. A multivariable multinomial logistic regression was carried out to adjust for all of the sociodemographic factors related to the household. Statistical significance was set at p<0.05. Multivariable multinomial logistic regression for “at risk of hunger” and “experiencing hunger” using adjusted odds ratios with their 95% confidence intervals (CI) as measures of association are presented as forest plots, which were produced using GraphPad Prism, version 7.00 for Windows (GraphPad Software, La Jolla, California USA).

Ethical considerations

The original SANHANES-1 (2011/12) received ethics approval from the Research Ethics Committee (REC) of the Human Sciences Research Council (HSRC) (REC 6/16/11/11). The present secondary analysis received ethics approval from the Human Research Ethics Committee (HREC) (Medical) of the University of the Witwatersrand, Johannesburg, South Africa (Clearance certificate number: M180775).

Household composition, living arrangements and main source of income of household heads

Table 1 shows the characteristics of South African households with and without children, and the living arrangements of the heads of households. Of the 5 098 households with complete CCHIP scores, 3 499 (68.6%) households contained children aged 0–19 years. Households with children were occupied by 9 505 adults and 9 184 children, while those without children were occupied by 3 243 adults. Households with children were 2.5 times larger than those without children (p<0.001). Forty percent of all households in South Africa contained children and were female headed. Of the households containing children, nine were child-headed. When comparing households with and without children, the proportions of African- and Coloured-headed households were not different (p = 0.417) and, no differences between urban formal and urban informal settings were found following two-by-two comparisons (p = 0.361). Furthermore, there was no statistically significant difference in the main source of income for households with and without children (p = 0.381).

Data presented as median [IQR]; arithmetic mean ± SD and n (%): unweighted (n) and weighted (%).

& Denotes p values obtained from Mann-Whitney U tests when comparing households with and without children for continuous variables (household size, number of adults and age of household head).

# Denotes p values obtained from overall Chi-Square tests when comparing households with and without children for categorical variables (gender, race, locality, and marital status).

† Denotes results from multiple 2x2 comparisons with Bonferroni correction: p<0.05 if categories share the same letter (a, b, c, d, and e) when comparing households with and without children. Specifically, for race and locality, p<0.0001 for African vs White/Indian/Asian, Coloured vs White/Indian/Asian, urban formal vs rural formal, and urban formal vs rural informal. For marital status, p = 0.001 in married vs never married and living together vs never married, p = 0.036 in Separated/divorced vs living together/civil unions and lastly p = 0.013 in never married vs widowed.

Prevalence of food insecurity in households with children

In households with children, the prevalence of experiencing hunger and being at risk of hunger was 32.5% (95% CI: 29.5–35.7) and 26.3% (95% CI: 23.9–28.8), respectively ( Fig 1 ). Table 2 shows the weighted prevalence of food insecurity stratified by the household head sociodemographic characteristics. Households in which the household head was female, older, of African race, unmarried, not having a formal education, dependent on social grants/pensions/remittances and having no income showed a higher prevalence of experiencing hunger or being at risk of hunger (p<0.001). Further analysis of the collapsed locality categories (formal vs informal) yielded the following: 37.2% of households with children were informally located; and, of these, only 28.9% were food secure. In contrast, of the 62.9% of households with children located in formal areas, 53.6% were food secure (p<0.001).

# p value from overall Chi-Square test when comparing food security status (food secure, at risk of hunger and experiencing hunger) across categorical variables (gender, race, marital status, educational attainment, source of income and locality), of which all were statistically significant.

*p<0.001 for age when comparing food secure vs at risk of hunger and food secure vs experiencing hunger (Kruskal-Wallis with Bonferroni correction). On multiple 2 by 2 analyses with Bonferroni correction, statistically significant differences within categories of sociodemographic characteristics are indicated by sharing the same letter: a, b, c, d or e, when comparing food secure vs at risk of hunger and food secure vs experiencing hunger. Specifically, p<0.01 between food secure vs. experiencing hunger except for:

⁋ Primary vs no schooling, salaries vs products/services; pensions/grants vs product/services and no income; p<0.01 between food secure vs. at risk of hunger except for:

† Coloured vs White/Indian/Asian; primary vs secondary; primary vs no schooling and secondary vs no schooling; salary vs product/services, pension/grants vs product/services, pension/grants vs no income and product /services vs no income; p<0.01 between food secure vs at risk of hunger and food secure vs experiencing hunger for married vs never married and married vs widower; p<0.01 between food secure vs experiencing hunger for married vs living together.

Factors associated with experiencing hunger and being at risk of hunger in all households with and without children

Weighted univariate multinomial logistic regression ( S1 Table ) of all the households exhibits that household heads who were female, of older age, unmarried/widowed/separated vs married were at higher risk of hunger and of experiencing hunger. However, when performing a weighted multivariable multinomial logistic regression ( Fig 2A and 2B ), age was no longer associated with experiencing hunger. Yet, female-headed households had 1.53 times increased odds of experiencing hunger as compared to male-headed households (p<0.001). In addition, having a larger household and a household with children present were also predictors of experiencing hunger; AOR = 1.06 (95% CI: 1.01–1.21); 1.68 (95% CI: 1.12–2.53) respectively. Having a household head who was either Coloured or White/Indian/Asian as opposed to African conferred lower odds of both experiencing hunger AOR = 0.29 (95% CI: 0.19–0.44) and 0.12 (95% CI: 0.04–0.33 and being at risk of hunger AOR = 0.54 (95% CI: 0.39–0.75), 0.22 (95% CI: 0.12–0.40. Furthermore, secondary/tertiary education conferred lower odds of both experiencing hunger; AOR = 0.40 (95% CI: 0.28–0.56 and being at risk of hunger; AOR = 0.69 (95% CI: 0.52–0.92. Households relying on pensions/social grants/remittances, or not having any source of income, were ~1.76 to 2.15 times more at risk of hunger and experiencing hunger than those receiving a salary/wage.

A. Factors associated with being at risk of hunger, data presented as adjusted odds ratios (AOR) and 95% Confidence intervals (95% CI). Reference categories : Presence of children (no children present) , Gender (male) , Race (African) , Marital status (married) , Educational attainment (primary) , Source of income (salaries/wages) , Locality (formal) . Factors associated with experiencing hunger, data presented as adjusted odds ratios (AOR) and 95% Confidence intervals (95% CI). Reference categories : Presence of children (no children present) , Gender (male) , Race (African) , Marital status (married) , Educational attainment (primary) , Source of income (salaries/wages) , Locality (formal) .

Female household heads and food security in households with children

Compared to male heads of households with children ( Table 3 ), female household heads were older, predominantly African, never married/widowed, have primary/secondary education or no schooling, reside in rural informal settings and have no income or rely on social grants/pensions/remittances. Lastly, male-headed households had more adults in the household while female-headed households had more children of all ages.

& Race: African vs Coloured (p = 0.001) and African vs White/Indian/Asian (p = 0.001)

# Marital status: married vs never married (p<0.001), married vs widowed (p<0.001), married vs separated/divorced (p<0.001), living together/civil union vs never married (p<0.001), living together/civil union vs widowed (p<0.001), living together/civil union vs separated/divorced (p<0.001), and never married vs widowed (p = 0.0015)

^Educational attainment: primary vs secondary (p = 0.0002), primary vs tertiary/higher degrees (p<0.001), secondary vs tertiary/higher degrees (p = 0.0001), and tertiary vs no schooling (p<0.001)

$ Source of income: salaries/wages vs social grants/pensions/remittances (p<0.001), salaries/wages vs no income (p<0.001), and social grants/pensions/remittances vs sale of products and services (p = 0.0002)

*Locality: urban formal vs urban informal (p = 0.001), urban formal vs rural informal (p<0.001), urban informal vs rural informal (p = 0.0010), and rural formal vs rural informal (p<0.001).

In the univariate analysis of the gender of the household head and food security in households with children, female-headed households had greater odds of being at risk of hunger [Odds Ratio (OR) = 1.58, (95% CI: 1.22–2.04), p<0.001] and experiencing hunger [OR = 2.35, (95% CI: 1.86–2.98), p<0.001].

Child dependency and sociodemographic characteristics of household heads, in households with children

In the univariate analysis of child dependency and food security in households with children, having at least one child who was 15 years or older increased the odds of experiencing hunger by 28% (OR = 1.28 (95% CI: 1.06–1.56), p = 0.012). Table 4 shows associations between food security and child dependency, adjusted for the sociodemographic characteristics of the household heads. Compared to households with younger children only, having at least one child aged 15–19 years old in a household was not associated with either being at risk of hunger or experiencing hunger (no significant change in adjusted odds ratio). Having a household head who was male, Coloured/White/Indian/Asian, employed and having obtained tertiary education/higher degrees conferred lower odds of experiencing hunger. Residing in informal settings increased the odds of both being at risk of hunger and experiencing hunger.

To the best of our knowledge, the present study is the first to objectively quantify the burden of food insecurity among children and adolescents in South Africa and draw associations using a large-scale, population-based sample of households with children. No studies in South Africa have disaggregated households with and without children aged 0–19 years old thus possibly underestimating the true extent of childhood food insecurity and limiting direct comparisons to the present study. Indeed, there is an observed increase in food insecurity (experiencing hunger—25.9% to 32.5%) by 6.6% between the prevalence estimate reported for 2008 by Labadarios et al. [ 22 ] and the estimate generated in the present study. This lack of improvement may be accounted for by the enduring socio-political and economic challenges sustained since the end of apartheid [ 22 , 38 ]. Drawing from a cross-sectional, population-based national sample of South African households, we have shown that the prevalence of food insecurity in households with children was nearly 60%. This is similar to the original SANHANES study where food insecurity among all households was 54% [ 12 ]. In the present study, after adjusting for household size, the sociodemographic characteristics of the household head and the main source of income, the presence of children and adolescents conferred ~1.68 increased odds of food insecurity (experiencing hunger) relative to households without children. In addition, having a female vs male household head, having an African household head compared to all other race groups, living in informal settings vs formal settings and having no income compared to relying on salaries or wages increased the odds of experiencing hunger between 53% and 300%. Secondary/tertiary/higher educational attainment of the household head reduced the odds of experiencing hunger by at least half relative to primary education. Reliance on social grants, pensions and remittances as the main source of income was associated with more than double the odds of being food insecure. When analysing food security in households with at least one adolescent aged 15–19 years, versus those with children aged 0–14 years only, before adjusting for the sociodemographics of the household head and location, the odds of being food insecure were almost 30% higher compared to households with younger children only. However, after controlling for these factors, neither child dependency nor the ability to work were associated with any category of food security.

Household head sociodemographics and household characteristics

The majority of households with children and adolescents in our sample was headed by women, had African household heads, or were living in urban or rural informal areas. Therefore, the increased vulnerability of households with children may be explained, in part, by the additive effects of these known predictors of food insecurity [ 39 ]. Previous studies in other contexts have found that the presence of children in households is independently associated with food insecurity, beyond sociodemographic characteristics and measures of socioeconomic status [ 7 , 39 – 43 ]. Additional research has demonstrated that the sex of the household head is an important factor predicting household vulnerabilities, with the highest prevalence of hunger reported among female-headed households [ 27 ], a risk that worsens with rural location [ 25 , 44 ]. Our comparative analysis of female- versus male-headed households points to the stark sociodemographic disadvantages that women heads endure in households with children, confirming previous research in South Africa on the gendered nature of poverty and food insecurity [ 27 , 45 ]. In their large-scale, population-based longitudinal analysis, the Indonesian Family Life Survey, Vaezghasemi et al. [ 46 ] further argue that although women may be conscious of healthy food options, because they are at the bottom of the family hierarchy and have low social capital, they remain defenseless against household hunger. Given South Africa’s colonial and apartheid history, racial differences still persist in the prevalence of food insecurity, with black or African households bearing the greatest burden compared to historically more advantaged minority groups in the country [ 7 , 11 , 12 , 25 ].

Previous studies have demonstrated strong positive associations between the lowest levels of educational attainment and food insecurity, which can be mitigated by higher levels of educational attainment [ 5 , 47 – 50 ]. Likewise, we found that improved levels of education (secondary and tertiary educational attainment) reduced the risk of food insecurity by at least half; yet, having no formal schooling was not associated with food insecurity. As Chakona and Shackleton also found [ 25 ], we suggest that household heads without a formal education may rely on subsistence farming or implement other skills-based practices which might act as a safety net against hunger.

The Born in Bradford cohort, a longitudinal study in the United Kingdom, showed associations between cohabitation status and food insecurity, where pregnant women not living with a partner had a two-fold increased risk of food insecurity [ 51 ]. Hanson, Sobal, and Frongillo [ 52 ] further demonstrated that marital status was associated with food insecurity among men, but not women. We found significant associations between the marital status of the household head and risk of experiencing hunger. Even after adjustments for sex, living together/civil unions and never married increased the odds of experiencing hunger by 61% and 41%, respectively.

Main source of household income, social grants and child dependency

Using self-reported main source of income to indicate a household’s economic stability, we note that there were no differences in income sources between households with and without children. However, household size was larger in households with children, including an increased number of adults. We show that not having any source of income predicts that a household will experience a three-fold increase in experiencing hunger. Furthermore, similar to Ruiters and Wildschutt [ 27 ], receiving government social grants, pensions or remittances did not alleviate hunger nor the risk of being food insecure for households with and without children. Despite a substantial social safety net wherein 16.2 million South Africans in 2013, representing nearly one third of the country’s population received different types of government grants [ 53 ], these were not protective in households with children, with a 76% increase in being at risk of food insecurity and double the odds for being food insecure. Other contexts show mixed results for government assistance programmes on alleviating food insecurity. Tarasuk, Fafard St-Germain and Mitchell. [ 54 ] have shown that in Canada, household before-tax income adjusted for family size was protective against food insecurity; however, households receiving social assistance were three times more likely to be food insecure. In contrast, Brown and Tarasuk. [ 55 ] showed a significant decline in severe food insecurity subsequent to the roll-out of the Canada Child Benefit (CCB) in households with children, a country-wide non-means-tested cash transfer programme. In Brazil, participation in the Bolsa Familia Programme [ 56 ] and in the United States receiving Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program) support [ 8 , 57 ], were not effective in preventing food insecurity. Furthermore, dietary quality for children and adolescents receiving SNAP benefits did not improve [ 58 ]. In one South African study where social grants did show improvements in household food insecurity and dietary quality, the authors note that these findings were not accompanied by concomitant improvements in anthropometric indicators of child malnutrition [ 26 ]. Even when controlling for the sociodemographic characteristics of the household head and the main source of income, the risk of experiencing hunger was increased with the presence of children in all households. This is similar to the findings of a 2017 national study comparing households with and without children under the age of 5 years, whereby households with no children were less likely to experience inadequate access to food [ 7 ]. In our sample of households with children, controlling for child dependency status (ages 0–14 versus 15–19 years old) did not lessen the odds of experiencing hunger. Regarding an older child’s potential to contribute towards household income through work eligibility, Stats-SA reported in 2012, the year of the SANHANES-1, an overall youth unemployment rate of 35.8% (age 15–34 years old) as compared to an adult unemployment rate of 15.1% [ 53 ]. After disaggregating youth unemployment by age and sex, males and females aged 15–19 years had rates of 50.2% versus 74% respectively [ 53 ], indicating that child dependency on an adult household head extends throughout adolescence in South Africa. Such continued dependence on an adult with resultant food insecurity has repercussions for the psychosocial functioning of teenagers, as it predicts future behavioural problems, directly and indirectly, through parental caregiver mental health stressors [ 59 ].

Contemporary considerations and current context

The present COVID-19 pandemic, occurring alongside household and child food and nutrition insecurity, presents a disconcerting syndemic [ 60 ] that is capable of reversing any recent mitigation of hunger at household and individual levels in the country [ 60 ]. Indeed, the COVID-19 pandemic has forced South Africa into an abrupt and prolonged lockdown threatening job and societal security [ 61 ]. Data from the National Income Dynamics Study-Coronavirus Rapid Mobile Survey (NID-CRAMS) [ 62 ], a four-wave longitudinal survey of adult South Africans, indicate that even with re-opening of the economy, lifting restrictions on movement and returning to work, 37–47% households did not have sufficient money to buy food, with 16–22% stating that they experienced hunger, during the period from May/June 2020 to February/March 2021 [ 62 ]. Overall, while hunger declined somewhat over this period, the poorest quintile suffered more hunger than before [ 62 ]. Without augmented social supports for households with children and adolescents, and an emphasis on nutrition-sensitive interventions [ 29 , 50 , 63 ], it is likely that food insecurity will pervade [ 14 ] and possibly impede the country from realising its 2030 Sustainable Development Goal of achieving zero hunger [ 31 , 60 ].

Limitations

The present study is not without limitations. The SANHANES-1 was conducted in 2011/12. Although never repeated, the data are at least nine years old and may not reflect the current status of food security in South Africa. Nonetheless, the SANHANES provides the most recent and comprehensive dataset on food security at the national and household-level using the CCHIP index that explores the context and loci within which food insecurity exists. This is in contrast with other national surveys which only record the frequency of problems satisfying food needs “in the past 12 months” [ 13 ]. Secondly, a comprehensive assessment of household socioeconomic status was beyond the scope of this research. Having considered the primary source of household income and educational status as contributing factors to household economic stability, a more robust measure of socioeconomic status using household assets could add a more granular dimension to the analysis.

Our study confirms that South African children and adolescents face a major challenge of food insecurity that is driven by a number of household head characteristics and household location. The untoward effects of food insecurity on child and adolescent health are not evanescent and have far-reaching adverse health outcomes. Therefore, this is a clarion call to bolster multi-sectoral interventions and healthy public policies, with a strong focus on the social determinants of health and poverty eradication strategies targeting these vulnerable households.

Supporting information

Acknowledgments.

The authors acknowledge Dr Innocent Maposa for his assistance with data analysis.

Funding Statement

SM received funding from the South African National Research Foundation (NRF): Freestanding, Innovation and Scarce Skills Development Fund Masters and Doctoral Scholarships (Reference: SFH170525233408 and MND190719457401) to support his postgraduate studies enabling him to pursue this research. SM received additional funding from the Carnegie Corporation of New York, in the form of a grant (G-17-55194) to complete his degree.

Data Availability

• PLoS One. 2022; 17(12): e0278191.

Decision Letter 0

26 Apr 2021

PONE-D-20-39991

Childhood food insecurity in South Africa: A household-level analysis of hunger

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Reviewer #2: No

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Reviewer #2: Yes

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Reviewer #1: Since the previous research studies related to food insecurity lack a specific focus on households with children, so I found the study worth reading. A comparative analysis of different household characteristics between households with and without children is made. Various descriptive and inferential statistical methods have been used by the authors to analyze the data. The findings of the study are quite interesting and believable. The language and draft of the paper is also excellent.

Reviewer #2: Generally, I found this manuscript to be well written. However, the relevance to current circumstances is questionable and the findings are not adequately explored.

I provide specific comments below, if you choose to make revisions.

The SANHANES-1 dataset has been used for many publications in the academic literature. The introduction needs to better summarise previous research and identify the gap in the literature that this study seeks to fill. Please reference Shisana and colleagues 2013 report at the very least. An early blog post by Parker in 2013 on the data may also be relevant.

Lines 92 – 20 years of age seems like an arbitrary cut-off for the definition of a child.

Lines 96 & 419 refers to improvements between 2002 and 2017. Source and further information is needed.

Line 138 introduces the concept of nutrition-sensitive interventions without any definition, background or references. Consider adding a paragraph summarising nutrition-sensitive interventions generally and in South Africa and how sociodemographic correlates can inform the design of these interventions to improve childhood health.

Lines 140-140 The sentence spanning these lines is repeating information from earlier in the introduction. Rephrase.

Lines 198-199 The sentence spanning these lines is superfluous. This is rudimentary data manipulation and is expressed in the previous sentence.

Lines 273-275 This is unclear. What were the differences?

Lines 287, 290, 305, 312 Identifying factors as being directly ‘protective for experiencing hunger’ is misleading. Many of these factors are likely causally related to asset endowment and/or income. They are not protective of but negatively related to. However, this term is appropriate when discussing social grants – that are designed to be protective against extreme poverty and food insecurity.

Lines 312-313 The sentence spanning these lines seems more emotive than the rest of the results section.

A theme throughout the manuscript is this purported influence of having children on food insecurity. This appears twice in the introduction, is expressed as a poignant point in the results section and in discussion it is suggested that there is a mounting body of evidence on the topic. The evidence as presented in this manuscript is weak in supporting the assertion “children below age 18 years in households is independently associated with food insecurity, beyond sociodemographic characteristics and measures of socioeconomic status”.

The most interesting finding in this manuscript is that “social grants and pensions, or remittances, did not alleviate hunger or the risk of being food insecure.” This needs to be analysed and discussed further.

The link between this manuscript and the COVID-19 pandemic is tenuous. The authors have done very little to link the dated dataset to present day.

Inconsistency in p value presentation.

Original sources need to be cited.

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Reviewer #1:  Yes:  Muhammad Azeem

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Submitted filename: Review Report PLoS.docx

Author response to Decision Letter 0

25 Jun 2021

See attached "Response to Reviewers" file

Submitted filename: Response to Reviewers_2021_06_24.docx

Decision Letter 1

23 Jul 2021

PONE-D-20-39991R1

Please submit your revised manuscript by 2nd September 2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at gro.solp@enosolp . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

3. Has the statistical analysis been performed appropriately and rigorously?

4. Have the authors made all data underlying the findings in their manuscript fully available?

5. Is the manuscript presented in an intelligible fashion and written in standard English?

6. Review Comments to the Author

Reviewer #2: The revisions to the manuscript show improvement. Background detail on nutrition sensitive interventions has been provided adequately, the link with this study and the COVID-19 pandemic is better supported and some revisions have been made to improve the scientific writing. However, there are still substantial deficiencies in the interpretation of the literature and the interpretation of results. In general I find that the language used in the manuscript suggests that causality has not been appropriately interpreted. In addition, my initial points still stand on 1) the purported influence of having children on food insecurity and 2) social grants and pensions, or remittances.

The classification of children being under 0-19 is problematic. In the introduction, the authors emphasise the implications of household food insecurity among children, where the implications of undernutrition for wasting and stunting are most relevant for young children, less so for adolescence. Given the age threshold, this background information is irrelevant to the present study. Further, the cited studies do not justify the threshold used in this study. The present study does not assess BMI or other anthropometric measurements. Rather than appropriating this threshold for anthropometry it is more relevant to set a threshold based on child dependency, where in this analysis, some ‘children’ will be an important source of labour for the household and may even support other “mouths to feed”. Most critically, the talking point remains in the discussion about the “pressure of mouths to feed”. The authors acknowledge that “the majority of households with children in our sample were headed by women… vulnerability of households with children may be explained, in part, by the additive effects”. Yet, the authors still attempt to add potential Type I errors to a supposed “mounting body of evidence”. Revisit the analysis in order to 1) better account for the gender of household head and child association and 2) assess the sensitivity of your results to age - using thresholds more relevant to dependency on a carer.

The authors need to be cognisant of the causality of the association between social grants (etc) and food insecurity. These data were not collected as part of a randomised control trial designed to assess the effectiveness of social grants. A mistaken view of causality pervades the language of the manuscript. Furthermore, the introduction of the manuscript contains the following: “Households that are reliant on private food charities and government assisted social grants are at an three-fold increased risk of food insecurity”. This is based on mistaken causality and a misuse of a descriptive study (Ruiters and Wildschutt 2010). The study that the authors cite, in my opinion, contained ill-informed suggestions of reallocating social grants from food insecurity prevention to lump-sum expenditures and that “Food baskets could be provided to families in exchange for work” – that is demeaning. This is only one example of an inadequate interpretation of the literature.

Reviewer #3: The manuscript looks okay but with minor revision.

L141-143: Any reason found in the literature for this. It will be nice if you add few reasons as being found in the literature. If there is none, it may be stated.

L202-204:Was the ethical clearance obtained for the use of the secondary data or this was the ethical clearance obtained for the collection of the primary data? If the latter holds, please re-phrase to indicate that.

L207: Household-level or Household level? Please check the entire manuscript and be consistent with one.

L227: Is it arithmetic or geometric mean? Please indicate?

Please check for other comments that were inserted directly in the manuscript.

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Reviewer #3:  Yes:  Alamu Emmanuel Oladeji(PhD, FIFST, MNIFST)

Submitted filename: PONE-D-20-39991_R1_reviewerEA.pdf

Author response to Decision Letter 1

16 Jan 2022

The Response to Reviewers document has been uploaded and labelled as such.

Submitted filename: Response to Reviewers_06_Jan_2022.docx

Decision Letter 2

28 Mar 2022

PONE-D-20-39991R2Childhood food insecurity in South Africa: A household-level analysis of hungerPLOS ONE

Dear Dr. Baldwin-Ragaven

Please submit your revised manuscript by 12th May 2022. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at  gro.solp@enosolp . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

Reviewer #3: All comments have been addressed

Reviewer #2: Partly

Reviewer #2: Some of these revisions have, indeed, improved this manuscript - particularly in incorporating Table 3 and Table 4. Unfortunately, my underlying concerns remain.

Reviewer #3: Thanks to the authors for responding to all comments satisfactorily. However, please check L-187, a reference is missing, and please add the reference.

Reviewer #3:  Yes:  Alamu, Emmanuel Oladeji(Ph.D., FIFST, MNIFST)

Author response to Decision Letter 2

16 May 2022

Kindly see attached "Response to Reviewers" file.

Submitted filename: RESPONSE TO REVIEWERS_2022_05_12.docx

Decision Letter 3

PONE-D-20-39991R3Childhood food insecurity in South Africa: A household-level analysis of hungerPLOS ONE

Dear Dr. Baldwin-Ragaven,

Please submit your revised manuscript by 2nd October 2022. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at  gro.solp@enosolp . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Section Editor

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Reviewer #4: (No Response)

Reviewer #5: (No Response)

Reviewer #6: (No Response)

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #5: No

Reviewer #6: Yes

Reviewer #3: Excellent effort to respond to all the comments has improved the manuscript tremendously. Please see the minor edits and comments inserted in the manuscript for your consideration.

Reviewer #4: Summary

Thank you for the opportunity I have to provide a review for this important article on Childhood food insecurity in South Africa. The authors have done a good job of identifying the extent of childhood hunger and factors which contribute to it.

• The title clearly depicts the research that was carried out with focus on the outcome, however the period or time of investigation is missing

• Each author’s contribution was clearly stated, and corresponding author’s contact is clear.

• The abstract is unstructured, and it allowed for a good read. It is a good summary of the workdone.

• The introduction revealed the intent of the study and raise curiosity as to what could be the finding of the study.

• However, the authors used very old references-I think they could use more recent references. I could not relate well with when the study weas conducted because I could not find anywhere it was mentioned. I could have missed it.

• The objectives were well stated: The authors wanted to determine the prevalence of food insecurity in households with and without children as well as to assess associations between the sociodemographic characteristics of the household head and degrees of hunger.

Methods and Materials

• The methods were well explained, and it is repeatable.

• The SANHANES-1 database was used for this study, however the question is when was the data extracted or when was this study conducted?

• Ethical consideration should have been the last in method. Authors can consider making the changes if they want.

• Well written results and clearly stated

• In lines 354-6 – larger household as a predictor of experiencing hunger seems not to be related. LCL of 1.00 shows that if repeated a researcher can get AOR of 1.00. I think 4 digits LCL should be used if not it should not be reported because it is an unlikely association.

• The discussion is well written and provides the necessary reasoning behind the results of the study

• It is was nice that they provided sub-headings which made an easy understanding of the discussion.

• The limitation of the study was clearly stated which eventually clarifies some of my earlier questions on when this study was conducted. But I think the authors should clearly state the year of study in the title.

• Provides answers to the objectives of the study

• The recommendations made by the authors may not be relevant since the authors agreed that this is a very old data, but the only data available for this kind of secondary data analysis.

Recommendation

• Accept with minor revision

Reviewer #5: It is an article with clear objective and met it if the method of analysis used was correct.

But I doubt on the selection of method for analysis. Is it difficult to dichotomize the outcome variable? If so, why you did not use another method of data analysis? Because, multinomial logistic regression is usually not preferred except when the the outcome variable is difficult to dichotomize or the categories of the outcome variable is worth as it is or multinomial.

Reviewer #6: Review of the Paper “Childhood food insecurity in South Africa: A household-level analysis of hunger”

� The title is better to be “prevalence of food in security and associated factors among households in South Africa” Or “Childhood and adolescent food insecurity in south Africa”

� The gap to be filled by this study should be clearly stated, such as the variables added other than other similar studies, method change or modification etc.

� The AOR better to precede the CI like AOR=1.68[1.12-2.53] with 95%CI.

� Instead of saying lower odds of experiencing hunger, I recommend to say there was a preventive/protective risk for hunger for those AOR<1

� Please minimize the key words

� The table titles don’t contain time period

� In the discussion part the implication of the study should be stated after comparing and contrasting.

� The conclusion is better to declare that food insecurity (experiencing hunger), at risk of hunger and food secured were low, medium or high.

Regardless of these minor corrections the paper is very interesting and informative. It is well organized; better to be published.

Thank you!!!

Reviewer #3:  Yes:  Alamu Emmanuel Oladeji (PhD, IFST, MNIFST)

Reviewer #4:  Yes:  ADEBAYO PETER ADEWUYI

Reviewer #6:  Yes:  Wondimnew Desalegn Addis Lecturer of Epidemiology at Debre Tabor University, Ethiopia.

Submitted filename: PONE-D-20-39991_R3_EA.pdf

Submitted filename: Peter_Review_39991.docx

Author response to Decision Letter 3

Please see attached "Response to Reviewers" PDF document where we have addressed all reviewers' concerns. Thank you.

Submitted filename: Response to Reviewers_01 October 2022.pdf

Decision Letter 4

14 Nov 2022

Child and adolescent food insecurity in South Africa: A household-level analysis of hunger

PONE-D-20-39991R4

Dear Dr. Baldwin-Ragaven, 

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Additional Editor Comments (optional):

Reviewer #6: All comments have been addressed

Reviewer #3: The authors have done an excellent job by responding carefully to all the comments and this has improved the quality of the paper. However, I have minor edits for consideration by the authors.

Reviewer #6: Unless some minor errors like ediorial issues, it is nice work and Well done! for me now it is Ok to be published. Go ahead please. Thank you so much!

Reviewer #3:  Yes:  Alamu Emmanuel Oladeji

Reviewer #6:  Yes:  Wondimnew Desalegn Addis , Debre Tabor University, College of Health Sciences, Department of Public Health/Epidemiology,

Submitted filename: PONE-D-20-39991_R4EA.pdf

Acceptance letter

Dear Dr. Baldwin-Ragaven:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Causes of food insecurity in Southern Africa : an assessment

Journal title, journal issn, volume title, description, collections.

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FAO / FOOD SECURITY REPORT

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STORY: FAO / SOFI REPORT TRT: 04:15 SOURCE: FAO RESTRICTIONS: PLEASE CREDIT FAO ON SCREEN LANGUAGE: ENGLISH / NATS DATELINE: 18 JULY 2024, ROME, ITALY / FILE

AUGUST 2022, JANAKPUR MADHESH PROVINCE, NEPAL

1.Pan left, weekly market

8 APRIL 2024, GAZA STRIP

2. Med shot, livestock keeper putting animal feed into a container

2 JULY 2024, KAPOETA, SOUTH SUDAN

3. Wide shot, women gathering water

FILE – FAO, ROME, ITALY

4. Wide shot, FAO Headquarters 5. Close up, FAO logo

18 JULY 2024, ROME, ITALY

6. SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “Sadly, this year, the SOFI is showing that the numbers have not changed from the previous years, basically, which were already years where we have seen already the increase because of COVID 19. So what we are reporting this year is that we have between 713 million and 757 million people which are chronically undernourished, people facing hunger. This is one out of 11 people in the world are facing hunger. But the other issue which is really important of this SOFI is the disparities. For example, the region which is doing the worst is the African region, where we have one in five people facing hunger this year.”

6 MARCH 2024, DOLOW, GEDO, SOMALIA

7. Aerial shot, Internally Displaced Persons (IDPs) camp

1-5 OCTOBER 2023, KAPOETA SOUTH COUNTY, SOUTH SUDAN

8. Wide shot, woman preparing a meal

11-15 JULY 2022, TIMOR-LESTE

9. Med shot, farmers planting velvet beans 10. Close up, corn in a bag

16 JUNE 2018, CHIQUIMULA MUNICIPALITY, GUATEMALA

11. Med shot, personnel serving milk in a school feeding program 12. Wide shot, children having lunch

13. SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “South America has very developed social protection programs that allows them to target interventions so they can effectively move out of hunger in a very fast way because it is efficient. In the case of Africa, we have not observed that. We have observed that they still don't have the institutionality to deliver a good targeted social protection program. But on the other hand, is a region that has been affected the most by conflicts and by climate and, of course, by [economic] slowdowns and downturns. It is a region that today is showing the bigger number of countries in food crises because of these three key drivers and conflict being the first in this sense.”

2 MAY 2024, ASSOMADA, SANTIAGO, CABO VERDE

14. Pan right, fruits and vegetables being sold in a food market

26-29 APRIL 2022, PRACHUAP KHIRI KHAN PROVINCE, THAILAND

15. Close up, fish being sold in a fish market 16. Med shot, customer buying fish

18 MAY 2024, COLOMBIA

17. Tilt down, woman feeding children

18. Wide shot, meals being distributed in a school

2019, ARARAT PROVINCE, ARMENIA

19. Wide shot, children eating lunch at the school canteen

20. SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “Today we have 2.8 billion people that don't have access to the minimum cost of a healthy diet. The number is extremely high, it has not improved relative to the previous years, and that tells us that we need to do a lot here. We need to change this paradigm, why countries have prices which are so high that don't allow people to consume, and also why income is a problem.”

20 JUNE 2024, KHAN YUNIS, GAZA

21. Pan right, farmer walking by his destroyed house 22. Med shot, destroyed house

09 – 14 APRIL 2023, BORANA, ETHIOPIA

23. Wide shot, wind blowing on a dry riverbed

23 MAY 2022, NETRAKONA PROVINCE, BANGLADESH

24. Aerial shot, river overflowing

4 JULY 2024, TEREKEKA, SOUTH SUDAN

25. Tracking shot, FAO boat on the Nile

26. Med shot, FAO staff talking with farmers

4-6 APRIL 2024, GAZA STRIP

27. Close up, animal fodder being poured into a bag 28. Med shot, FAO staff helping a farmer carry a fodder bag

18 JULY 2024, ROME ITALY

29. SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “We need to change how we finance hunger in the world. And that's why we need to find ways in which we can accelerate the financing. But we need several things to happen. First, we need to coordinate better. Donors and different agencies provide funding with different objectives in mind, and that needs to be improved. We need to increase coordination as well as we need to increase targeting. Second, we need to be more risk takers. We are too risk adverse in the way we allocate the resources. Sometimes it is necessary to take some risk. For example, to sacrifice a little bit of growth to be able to assure that you have better lower poverty and therefore less hunger in the world. And third, we need to increase the different ways in which we get financing.”

AUGUST 2023, CHOLUTECA, HONDURAS

30. Aerial shot, FAO staff checking a water storage pond

31. Wide shot, FAO staff meeting farmers hit by floods

29 APRIL, SANTA CRUZ, SANTIAGO, CABO VERDE

32. Wide shot, FAO-China South-South Cooperation project experts walking in a cultivated field

33. Pull focus, from FAO logo on a veterinarian coverall to livestock keepers vaccinating a goat

Around 733 million people faced hunger in 2023, equivalent to one in eleven people globally and one in five in Africa, according to the latest State of Food Security and Nutrition in the World (SOFI) report published on Wednesday by five United Nations specialized agencies.

The annual report launched this year in the context of the G20 Global Alliance against Hunger and Poverty Task Force First Ministerial Meeting in Brazil, warns the world is falling significantly short of achieving the Sustainable Development Goal (SDG) 2, Zero Hunger, by 2030. The report shows that the world has been set back 15 years, with levels of undernourishment comparable to those in 2008-2009.

Maximo Torero, Chief Economist at the Food and Agriculture Organization of the United Nations (FAO), explains that, despite some progress in specific areas, an alarming number of people continue to face food insecurity and malnutrition as global hunger levels have plateaued for three consecutive years, with between 713 and 757 million people undernourished—approximately 152 million more than in 2019 when considering the mid-range (733 million).

SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “Sadly, this year, the SOFI is showing that the numbers have not changed from the previous years, basically, which were already years where we have seen already the increase because of COVID 19. So, what we are reporting this year is that we have between 713 million and 757 million people which are chronically undernourished, people facing hunger. This is one out of 11 people in the world are facing hunger. But the other issue which is really important of this SOFI is the disparities. For example, the region which is doing the worst is the African region, where we have one in five people facing hunger this year.”

Regional trends vary significantly: hunger continues to rise in Africa, remains stable in Asia—still representing a significant challenge—and shows progress in Latin America. However, from 2022 to 2023, hunger increased in Western Asia, the Caribbean, and most African sub regions.

SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “South America has very developed social protection programs that allows them to target interventions so they can effectively move out of hunger in a very fast way because it is efficient. In the case of Africa, we have not observed that. We have observed that they still don't have the institutionality to deliver a good targeted social protection program. But on the other hand, is a region that has been affected the most by conflicts and by climate and, of course, by [economic] slowdowns and downturns. It is a region that today is showing the bigger number of countries in food crises because of these three key drivers and conflict being the first in this sense.”

If current trends continue, about 582 million people will be chronically undernourished in 2030, half of them in Africa, the report warns. This projection closely resembles the levels seen in 2015 when the Sustainable Development Goals were adopted, marking a concerning stagnation in progress.

The report highlights that access to adequate food remains elusive for billions. In 2023, around 2.33 billion people globally faced moderate or severe food insecurity, a number that hasn't changed significantly since the sharp upturn in 2020, in the mist of the COVID-19 pandemic. Among those, over 864 million people experienced severe food insecurity, going without food for an entire day or more at times. This number has remained stubbornly high since 2020 and while Latin America shows improvement, broader challenges persist, especially in Africa where 58 percent of the population is moderately or severely food insecure.

The lack of economic access to healthy diets also remains a critical issue, affecting over one-third of the global population. With new food price data and methodological improvements, the publication reveals that last year, over 2.8 billion people were unable to afford a healthy diet. This disparity is most pronounced in low-income countries, where 71.5 percent of the population cannot afford a healthy diet, compared to 6.3 percent in high-income countries.

SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “Today we have 2.8 billion people that don't have access to the minimum cost of a healthy diet. The number is extremely high, it has not improved relative to the previous years, and that tells us that we need to do a lot here. We need to change this paradigm, why countries have prices which are so high that don't allow people to consume, and also why income is a problem.”

While progress has been made in increasing exclusive breastfeeding rates among infants to 48 percent, achieving global nutrition targets will be a challenge. Low birthweight prevalence has stagnated around 15 percent, and stunting among children under five, while declining to 22.3 percent, still exceeds targets. Additionally, the prevalence of wasting among children has not seen significant improvement while anemia in women aged 15 to 49 years has increased.

Similarly, new estimates of adult obesity show a steady increase over the last decade, from 12.1 percent (2012) to 15.8 percent (2022). Projections indicate that by 2030, the world will have more than 1.2 billion obese adults. The double burden of malnutrition – the co-existence of undernutrition together with overweight and obesity – has also surged globally across all age groups. Thinness and underweight have declined in the last two decades, while obesity has risen sharply.

These trends underscore the complex challenges of malnutrition and the urgent need for targeted interventions as the world is not on track to reach any of the seven global nutrition targets by 2030, the five agencies indicate.

Food insecurity and malnutrition are worsening due to a combination of factors, including persisting food price inflation that continues to erode economic gains for many people in many countries, the report notes. Major drivers like conflict, climate change, and economic downturns are becoming more frequent and severe. These issues, along with underlying factors such as unaffordable healthy diets and persistent inequality, are now happening simultaneously, amplifying their individual effects.

This year’s report’s theme “Financing to end hunger, food insecurity and all forms of malnutrition’’, emphasizes that achieving SDG 2 Zero Hunger requires a multi-faceted approach, including transforming and strengthening agrifood systems, addressing inequalities, and ensuring affordable and accessible healthy diets for all. Crucially, it calls for increased and more cost-effective financing, with a clear and standardized definition of financing for food security and nutrition.

SOUNDBITE (English), Maximo Torero, FAO Chief Economist: “We need to change how we finance hunger in the world. And that's why we need to find ways in which we can accelerate the financing. But we need several things to happen. First, we need to coordinate better. Donors and different agencies provide funding with different objectives in mind, and that needs to be improved. We need to increase coordination as well as we need to increase targeting. Second, we need to be more risk takers. We are too risk adverse in the way we allocate the resources. Sometimes it is necessary to take some risk. For example, to sacrifice a little bit of growth to be able to assure that you have better lower poverty and therefore less hunger in the world. And third, we need to increase the different ways in which we get financing.”

Countries most in need of increased financing face significant challenges in accessing it. Among the 119 low- and middle-income countries analyzed, approximately 63 percent have limited or moderate access to financing. Additionally, the majority of these countries (74 percent) are impacted by one or more major factors contributing to food insecurity and malnutrition. Coordinated efforts to harmonize data, increase risk tolerance, and enhance transparency are vital to bridge this gap and strengthen global food security and nutrition frameworks.

The State of Food Security and Nutrition in the World is an annual report jointly prepared by the Food and Agriculture Organization of the United Nations (FAO), the International Fund for Agricultural Development (IFAD), the United Nations Children’s Fund (UNICEF), the World Food Programme (WFP) and the World Health Organization (WHO).

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Why do farmers not irrigate all the areas equipped for irrigation lessons from southern africa.

1. Introduction

2.1. data collection and analysis, 2.2. literature screening and analysis flowchart, 3. results and discussion, 3.1. irrigation potential, 3.2. dam storage potential, 3.3. gender and irrigation development, 3.4. policy frameworks on irrigation development, 4. causes for not irrigating all the land equipped for irrigation, 5. recommendations.

• The reliance on rainfed agriculture increases vulnerability to food insecurity as crops are grown only during the rainy season. However, abundant groundwater resources can be drawn for irrigation during the dry winter or intra-seasonal drought periods. The main challenge of rainfed agriculture is that there is total crop failure when there is drought. Therefore, conjunctive water use in irrigation increases crop productivity, creates employment, reduces poverty, and enhances food and nutritional security.
• The current institutions must be strengthened through investment and supported by appropriate governance frameworks that guide and monitor the sector. Agricultural institutions should be established at both the national and regional levels, considering southern Africa’s transboundary nature of water resources. Currently, there are transboundary watercourse institutions that govern the transboundary water resources including the Zambezi Watercourse Commission (ZAMCOM), Limpopo Watercourse Commission (LIMCOM), and Orange-Senqu River Commission (ORASECOM), among others. The establishment of these institutions is quite important, but they need to be strengthened and work on developing policies that reduce the possibility of water conflicts but promote regional integration.
• The irrigation sector must gain the necessary skills to operate and maintain the irrigation technologies. As a result, some of the land equipped for irrigation is not being irrigated. The failure to fully exploit the irrigation potential and the underutilisation of the existing infrastructure in southern Africa is testimony to the scarce skills in the sector. There is, therefore, a need to develop the capacity in irrigation by establishing agricultural colleges to equip the farmers with the necessary skills including management and farm operation skills. This will go a long way toward transforming the irrigation sector into a fully operational and viable system as smallholder farmers take ownership of irrigation schemes. Training in agricultural skills is important in this era where 4IR and artificial intelligence (AI) are revolutionising agriculture.
• The 4IR coupled with the integration of novel technologies including AI, remote sensing, geographic information systems (GIS), blockchain, the Internet of Things (IoT), big data platforms, and drones, among other technologies, are transforming agriculture by facilitating smart irrigation and enhancing irrigation scheduling [ 84 ]. These intelligent technologies are being used to monitor soil moisture, predict weather conditions, adjust irrigation, and optimise irrigation scheduling, thus enhancing water use efficiency and crop-water productivity [ 36 ]. However, smart technologies require investment to fully realise the irrigation potential. This is important as climate change depletes freshwater resources and increases water scarcity.
• Therefore, the other critical area needing redress is more support and investment in woman-dominated irrigated areas. The lack of support for women in agriculture is resulting in women practicing agriculture on a part-time basis to supplement the income from their spouses who work in urban and mining areas. The policy should prioritise supporting women in agriculture as they dominate the agriculture sector. However, more investment and use of smart technologies will attract the youth to the sector which is currently dominated by women and the elderly [ 33 ].
• Equally critical is the need to address the co-operative nature of the existing irrigation schemes as most are lying idle due to the infighting of members and a lack of a sense of ownership of the irrigation infrastructure [ 31 ]. As a result, most of the irrigation schemes are abandoned, leaving the infrastructure to deteriorate [ 66 ]. Studies have shown that irrigation schemes have generally failed, calling for policymakers to come up with novel approaches to empower smallholder irrigation and revitalise irrigation schemes [ 31 , 33 ].
• As most irrigation schemes are being underutilised or have been abandoned completely, there is a need to formulate a strategy to revitalise the idle schemes [ 85 ]. The revitalisation efforts must include all stakeholders including farmers and extension officers. The revitalisation should be accompanied by improved institutions and investment opportunities. This is meant to recommend the appropriate irrigation technologies most suitable for smallholder irrigation schemes, including drip and micro-irrigation methods.

6. Conclusions

Author contributions, conflicts of interest.

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Nhamo, L.; Mpandeli, S.; Liphadzi, S.; Dirwai, T.L.; Mugiyo, H.; Senzanje, A.; Lankford, B.A.; Mabhaudhi, T. Why Do Farmers Not Irrigate All the Areas Equipped for Irrigation? Lessons from Southern Africa. Agriculture 2024 , 14 , 1218. https://doi.org/10.3390/agriculture14081218

Nhamo L, Mpandeli S, Liphadzi S, Dirwai TL, Mugiyo H, Senzanje A, Lankford BA, Mabhaudhi T. Why Do Farmers Not Irrigate All the Areas Equipped for Irrigation? Lessons from Southern Africa. Agriculture . 2024; 14(8):1218. https://doi.org/10.3390/agriculture14081218

Nhamo, Luxon, Sylvester Mpandeli, Stanley Liphadzi, Tinashe Lindel Dirwai, Hillary Mugiyo, Aidan Senzanje, Bruce A Lankford, and Tafadzwanashe Mabhaudhi. 2024. "Why Do Farmers Not Irrigate All the Areas Equipped for Irrigation? Lessons from Southern Africa" Agriculture 14, no. 8: 1218. https://doi.org/10.3390/agriculture14081218

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Food insecurity has long been an issue in South Africa, with 11% of the population (6.5 million people) suffering from hunger in 2019, according to Statistics South Africa . 

As of late, it has become a considerably topical issue, with President Cyril Ramaphosa having referred to food insecurity in parliament proceedings as well as his weekly newsletters at least twice in the last month. 

It’s not hard to see why it has increasingly become a topic of discussion in the country. This year has seen the rate of hunger in South Africa increase significantly due to a number of factors, resulting in an economic decline and many citizens going to bed hungry. 

In his recently presented economic recovery plan, the president announced a number of ways to rebuild the economy and slowly eradicate food insecurity in the country over the next five years. However 61% of South Africans interviewed by Ask Afrika have little confidence in the president’s plan. 

Access to sufficient food is also crucial for pregnant women and growing children. An estimated 27% of children under the age of 5 in South Africa are stunted. This means that they experienced a lack of nutrients in the womb that can result in lifelong challenges.

Children who are stunted are more likely to face learning difficulties and grow to be a lot shorter than children who are not stunted. They’re also highly likely to experience health issues in their adulthood, including diabetes and obesity. 

A lot of work needs to be done in order to decrease the rate of hunger in the country and overcome the lack of food for its citizens.

But in order to tackle the issue, it is important to note what has caused an incline in food insecurity this year in the first place. 

1. The COVID-19 pandemic

The pandemic itself is not the cause of the state of food insecurity in South Africa, but rather the measures put in place by the government to manage the spread of the virus. 

South Africa experienced one of the strictest lockdowns in the world between March and July this year. Most of the economy was forced to shut down as non-essential services were told to close during the period. 

While important to control the spread of the pandemic, this resulted in one of the biggest economic declines South Africa has seen in nearly a century, and saw 2.2 million people lose their jobs. This loss of income has seriously impacted the rate of household food security across the country. 

The Coronavirus Rapid Mobile Survey published in July this year , showed that 47% of the adults surveyed ran out of money to buy food for their household in April. In the previous seven days before being surveyed, 21% of adults said that at least one person in their household went hungry, and 15% said that a child had gone hungry in the same period. 

With the United Nations predicting that that the number of households living below the poverty line in South Africa will increase due to the pandemic, the lack of income to secure food in a growing number of households is a rising issue of concern . 

2. Environmental factors

Droughts have long been a threat to South Africa’s agriculture and food production. 

Last year’s droughts were the cause of decreased grain, wheat, and fruit production in several parts of the country and the prolonged dry seasons caused farmers to wait longer to plant their crops, or miss the planting season entirely. 

This month Independent Online South Africa reported that droughts in KwaZulu-Natal (KZN) could result in a serious food security crisis, especially since the province is the main provider of South Africa’s agricultural produce.

KZN Premier Sihle Zikalala warned of the crisis while speaking at the launch of the Provincial Multi-Planting Season last Friday. 

“Unless immediate action is taken, it is increasingly clear that the impending worst food emergency could have a long-term severe impact on thousands of children and adults already impoverished in KwaZulu-Natal,” he said.

Another huge environmental issue are dust clouds that have been plaguing the Free State province, where most of the country’s maize is grown. A report in The Conversation has revealed that these dust clouds continue to affect the growth of crops and could eventually result in a food crisis if not handled well. 

3. Farm attacks

In recent months, there has been an increase in fear and outrage among farmers over invasions and attacks occurring on their land. 

The president has condemned these violent crimes and has called it a threat to food security in the country. 

Last week  at a press conference , Minister of the Presidency, Jackson Mthembu reiterated the president’s sentiments and declared that the government as a whole recognises the issue as a threat to national food security.

“The farming community is an integral part of our economy, and crime on farms poses a threat not only to the personal safety of farmers and farmworkers but also to the country’s food security,” he said. 

The government is in talks of what measures to take to protect farmers in the country. 

Although South Africa is experiencing an increase in hunger, it is still one of Africa’s most food secure countries . Millions of people on the continent struggle with access to food as a result of poverty and other factors. To help make sure that the continent sees an end to food insecurity, take action here . 

Defeat Poverty

3 Things That Have Increased Food Insecurity in South Africa This Year

Oct. 27, 2020

• Comment & Opinion

South Africa’s university students face a crisis: nearly a third go hungry

There is a common perception that students represent the elite, and so cannot possibly suffer from hunger. But this is a myth. In fact, the available evidence suggests that students are more likely to be food insecure – they are not able to access adequate nutritious food on a daily basis – than others in the general population.

I reviewed a number of studies conducted at several South African universities over the past five years. These show that, on average, nearly a third of students at the country’s universities live with food insecurity. The actual numbers might be even higher since some students may be ashamed to admit that they’re poor and hungry.

Official statistics estimate that 26% of the country’s broader population is food insecure. One obvious reason why students are more vulnerable to food insecurity is that they have effectively left home but they are not yet employed, so they have low or zero income and depend on family support, bursaries or loans.

There are several underlying drivers of hunger among students. These include the fact that they come from poor families – poverty stands at 55% nationally – as well as the fact that living costs are high .

But the strongest predictor of food insecurity among students is race – an unsavoury legacy of apartheid. For instance , 24% of white students but 79% of black African students at the University of the Free State were found to be food insecure in 2013.

Even though South Africa’s democracy is now 23 years old, there are still no signs of improvement in several key indicators of inequality, including the racial distribution of hunger.

Food insecurity among students isn’t confined to South Africa. Studies at several US campuses have found that between 14% and 59% of students are food insecure. The national prevalence is 14.5%. As in South Africa, black students in the US are disproportionately at risk.

How students cope

The consequences of food insecurity for students can be very serious. Being hungry can impair academic performance or even lead to students dropping out. It can also cause mental health problems such as anxiety, depression and even thoughts of suicide.

Hunger reduces the ability to concentrate on studying, to write fluently, or to perform well in exams. Researchers have suggested that not having access to enough nutritionally adequate and safe food could be one of the reasons why almost half of South African university students never graduate.

Students respond to food insecurity and hunger by finding alternative sources of food, like eating with friends or relatives. They also ration their consumption by eating cheaper food, only drinking fluids or fasting. They borrow money or seek work so they can afford more or better food. But taking on work reduces their time and energy for studying.

Interventions

The National Student Financial Aid Scheme (NSFAS) disburses loans to pay for fees, accommodation and living expenses for poor students. It also provides food vouchers. But it often disburses the funds as well as the vouchers late. In addition, the vouchers aren’t enough to ensure students can feed themselves.

Universities, NGOs and students themselves are trying to help. Many universities have introduced food banks, food gardens, meal vouchers and free breakfasts or hot lunches. The University of the Free State launched a “No Student Hungry” campaign . NGOs such as Stop Hunger Now and Gift of the Givers are feeding thousands of university students. One student at the University of the Western Cape set up a Facebook page called “ Fairy Godmother ”, where struggling students write candidly about their financial needs and invite others to contribute donations.

These initiatives provide essential support to hungry students, but they tend to be uncoordinated and under-funded. They often depend on the generosity of university staff and the resources of each university – which only reproduces preexisting inequalities between wealthier and poorer universities.

Besides, academics and university staff should not be responsible for feeding their students. Ultimately, this is a government responsibility. The right to food is in South Africa’s Constitution, but it isn’t being upheld for South Africa’s students.

Hunger on South Africa’s campuses is an invisible crisis that should be prioritised at the highest policy level. Efficient management at NSFAS is urgently needed to disburse funds to students on time.

The government’s commitment to free higher education for poor and working class students must include not only fees but basic needs, especially food. This might require a new vision for financing higher education in South Africa: one that takes students’ daily realities of hunger and deprivation into account.

This article is based on the author’s keynote address at the National Colloquium on Access to Food for Students in South African Tertiary Institutions on 14 August 2018.

Stephen Devereux , Research Fellow, Institute of Development Studies, University of Sussex

This article was originally published on The Conversation . Read the original article .

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Addressing food insecurity for poor South African households

by Adrino Mazenda, The Conversation

Food insecurity is a feature of life for millions of South Africans. Food insecurity refers to a lack of regular access to enough safe and nutritious food for average growth and development and an active and healthy life. This may be due to unavailability of food or a lack of resources to buy it.

The extent of this was recently mapped by the Human Sciences Research Council. For example, in Gauteng province, South Africa's economic powerhouse, 51% of households experience food insecurity. A national survey between 2021 and 2023 found Gauteng households were affected to different degrees: 14% faced severe food insecurity, 20% moderate food insecurity, and 17% mild food insecurity.

The research also found that South African households survive on nutrient-poor food groups such as cereals, condiments, sugars, oils and fats. Consumption of nutrient-rich food groups such as fruits, pulses, nuts, eggs, fish and seafood is limited.

Dietary diversity is useful for measuring food security. A diverse, nutritious and balanced diet prevents nutritional deficiencies and diseases. A fall in dietary diversity is linked to a rise in the proportion of people who are malnourished .

The HSRC findings were the most recent to point to a growing crisis of food insecurity in the country. In an earlier study, we examined the diets of people living in South Africa's second largest city, Tshwane.

We found that due to income, and other socio- economic factors , none of the poor households in our study were getting adequate nutrients from what they were eating. Mostly they were eating cereals (grains such as wheat and maize), vegetables such as legumes, roots and tubers, and oils and fats because they couldn't afford anything else. Most had little to no income . And most were poorly nourished.

On the basis of the findings we recommended a range of interventions. These included better implementation of existing policies aimed at opening up opportunities, such as the Expanded Public Works Program . And we recommended campaigns be run to increase people's awareness about nutritional foods and growing them.

The help of the private sector and NGOs is also recommended.

Mapping eating habits

The study measured what households were choosing to eat from among the various food groups. These were 775 households from food-insecure areas of Tshwane as mapped by the 2016 Statistics South Africa Community Survey . We asked which food groups had been eaten in the previous seven days by any household member at home, including food prepared at home but eaten, for example, at work (such as a packed lunch).

Twelve food choices were used : cereals, legumes, roots and tubers, vegetables, fruits, milk, eggs, meat, fats, fish, sweets and beverages.

The Principal Component Analysis was used to analyze the Tshwane study households' consumption of these food groups. The analysis is widely used to derive dietary patterns from the daily eating patterns of households.

We then used the Simpson index to measure how nutrient rich the diets were. An index score greater than 0.5 shows a highly diversified diet. The Simpson Index was profiled on socio-economic determinants of food insecurity variables, such as age, household size, income, and food expenditure.

The average dietary diversity score was low for all the poor households in the Tshwane study.

What we found

In our survey, the households with the least diversified diets were those headed by women, people with no more than secondary education, unemployed people, and/or recipients of the social support grant. This suggests that the grants are insufficient to cover people's food needs.

Households with low dietary diversity rarely reared animals or had food gardens.

Households chose mainly four food groups. The first group was associated with a vegetable-based diet (roots and tubers, legumes, vegetables, and fruit). The second group was associated with people who consumed sugar, honey and miscellaneous products (coffee, tea, soft drinks, and instant foods). The third group comprised people who consumed fats and proteins, eggs and milk products. The final group was associated with the consumption of cereals or staple foods.

It was not possible to identify a group of urban food insecure households that ate a mixed selection of all food groups. This suggests they all lacked adequate dietary requirements to boost nutrition. This was regardless of their socio-economic status.

We also found that households faced a number of obstacles beyond income constraints that limited their dietary diversity. These included unemployment, household size, education, and the lack of land, skills and resources to practice urban agriculture.

The City of Tshwane in Gauteng has adopted numerous strategies to alleviate food insecurity. These include the 2017 climate response strategy , meant to reduce food insecurity due to climate vulnerability, and the Expanded Public Works Program , which provides job creation and skills development, supporting sustainable socio-economic development and poverty reduction.

But execution has been suboptimal.

Poor coordination among government departments and agencies about priorities has led to interventions being ineffective .

A list of the challenges facing the public works program was presented by a parliamentary monitoring group. They included delays in implementation and reporting as well as non-submission of quarterly evaluation reports by some public bodies.

As a result, funding from the central government to local and provincial administrations was withheld for the 2024/25 budget.

In addition, the City of Tshwane faces financial challenges that affect its ability to get things done. This means the city cannot solve the problem of food insecurity and nutrition alone.

What's needed is collaboration between government, the private sector and civil society. Policies could include prioritizing food security and nutrition, such as subsidies for nutritious foods, regulations to improve food safety and incentives for sustainable agricultural practices.

Second, public–private partnerships must be established to implement food security programs targeting marginalized households, urban smart agriculture, and community gardens.

Third, there is a need to fund research on innovative food production technologies and sustainable agricultural practices, and share industry data on food supply chains and consumer preferences.

Fourth, there is a need to conduct community-based research on food needs and barriers to access.

Fifth, contribution of financial resources by investing in startups and enterprises focused on improving food security and nutrition outcomes.

Finally, monitoring and evaluation frameworks need to be established to assess the impact of food security policies and programs and ensure accountability and transparency in resource allocation.

Provided by The Conversation

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Sweet Potato Flour as a Solution to Food Insecurity

One Solution to Food Insecurity

Root and tuber crops, such as sweet potatoes , are important for food security. As a drought-tolerant crop, sweet potatoes are resilient in warm climates like those in sub-Saharan Africa. They are a staple food globally, especially in developing countries, providing affordable and accessible nutrition. Sweet potatoes hold great economic value in South Africa. However, after harvest, there is a limited time to determine when they are good to eat. They are harvested once a year and are ripe for a limited period.

InnoFoodAfrica

InnoFoodAfrica is a cross-continental project that aims to enhance food and nutrition security in Africa. As part of this project, researchers at the University of Pretoria, South Africa, have found a way to make orange-fleshed sweet potato last longer by making flour out of it. A Doctor of Philosophy (PhD) Food Science candidate, Daddy Kgonothi, has been central in the development of this flour. The goal of the invention was to address micronutrient deficiencies among young children and pregnant women.

Sweet potato has a short shelf life of only two to three weeks. The flour, which is made from the same crop, has a shelf life of a whole year. Sweet potato contains beta-carotene , which is converted into vitamin A in the body. Vitamin A deficiency is one of the leading causes of micronutrient deficiencies in children younger than 6 and among pregnant women. Sweet potato also contains a high level of fiber and antioxidants. This protects the body from free radical damage and promotes a healthy gut and brain.

Flour is also a good source of iron, zinc and phosphorus. When sweet potato is made into flour, it lasts longer, which can lead to more people getting their hands on the product. It is also versatile and can be used in many recipes, such as bread. This way, the flour can be a solution to deficiencies.

The Impacts of the Sweet Potato Flour

The flour is one solution to food insecurity in not only South Africa but also large parts of Africa. The development of the flour was finalized in 2022. It allows people to enjoy the nutrients and benefits of the crop all year long. Not only is the flour helping enhance general food insecurity in South Africa and the rest of Africa, but it is especially helping pregnant women and children eat more nutritious food.

– Sigrid Nyhammer

Sigrid is based in London, UK and focuses on Good News for The Borgen Project.

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South africa: poor households in south africa cannot afford nutritious food – what can be done.

Food insecurity is a feature of life for millions of South Africans. Food insecurity refers to the lack of regular access to sufficient and healthy food for normal growth and development and an active and healthy life. This may be due to the unavailability of food or the lack of resources to purchase it.

The Human Sciences Research Council recently assessed the extent of this phenomenon. For example, in Gauteng province, the economic hub of South Africa, 51% of households are food insecure. A national survey conducted between 2021 and 2023 found that households in Gauteng were affected to varying degrees: 14% faced severe food insecurity, 20% moderate food insecurity, and 17% mild food insecurity.

The study also found that South African households survive on nutrient-poor food groups such as cereals, condiments, sugars, oils and fats. Consumption of nutrient-rich foods such as fruits, legumes, nuts, eggs, fish and seafood is limited.

Dietary diversity is useful for measuring food security. A varied, nutritious and balanced diet prevents nutritional deficiencies and diseases. A decrease in dietary diversity is linked to an increase in the proportion of people suffering from malnutrition.

The HSRC findings are the latest to highlight a growing food insecurity crisis in the country. In a previous study, we looked at the diets of residents of Tshwane, South Africa’s second largest city.

We found that due to their income and other socio-economic factors, none of the poor households in our study were getting enough nutrients from their diets. Most of them relied on cereals (wheat and maize), vegetables (legumes, roots and tubers) and oils and fats because they could not afford anything else. Most of them had little or no income and were malnourished.

Based on the findings, we recommended a series of interventions, including better implementation of existing policies aimed at opening up new opportunities, such as the Expanded Public Works Programme. We also recommended conducting campaigns to increase awareness of nutritious foods and their cultivation.

Assistance from the private sector and NGOs is also recommended.

Mapping eating habits

The study measured household food choices across different food groups. This included 775 households from food insecure areas of Tshwane, as mapped by Statistics South Africa’s 2016 community survey. We asked which food groups had been consumed in the previous seven days by a household member at home, including foods prepared at home but consumed, for example, at work (such as a packed lunch).

Twelve food choices were used: cereals, legumes, roots and tubers, vegetables, fruits, milk, eggs, meat, fats, fish, sweets and beverages.

Principal component analysis was used to analyse the consumption of these food groups by households in the Tshwane study. The analysis is widely used to infer dietary patterns from households’ daily eating habits.

We then used the Simpson index to measure the nutritional richness of diets. An index score greater than 0.5 indicates a highly diversified diet. The Simpson index was profiled according to socioeconomic determinants of food insecurity variables, such as age, household size, income, and food expenditure.

The average dietary diversity score was low for all poor households in the Tshwane study.

What we found

In our survey, households with the least diversified diets were those headed by women, those with less than secondary education, the unemployed and/or those receiving social assistance. This suggests that assistance is not sufficient to cover people’s food needs.

Households with low dietary diversity rarely raised animals or had vegetable gardens.

Households chose mainly four food groups. The first group was associated with a vegetable-based diet (roots and tubers, legumes, vegetables and fruits). The second group was associated with people consuming sugar, honey and miscellaneous products (coffee, tea, soft drinks and instant foods). The third group included people consuming fats and proteins, eggs and dairy products. The last group was associated with the consumption of cereals or staple foods.

It was not possible to identify a cluster of food-insecure urban households that consumed a mix of all food groups. This suggests that not all of these households had adequate nutritional needs to improve their nutrition, regardless of their socio-economic status.

We also found that households faced a number of barriers, in addition to income constraints, that limited their dietary diversity. These included unemployment, household size, education, and lack of land, skills and resources to practice urban agriculture.

The City of Tshwane in Gauteng has adopted many strategies to mitigate food insecurity. These include the 2017 Climate Change Response Strategy, aimed at reducing food insecurity due to climate vulnerability, and the Expanded Public Works Programme, which provides for job creation and skills development, thereby supporting sustainable socio-economic development and poverty reduction.

But the execution was not optimal.

Lack of coordination between government departments and agencies on priorities has led to ineffective interventions.

A parliamentary monitoring group has listed challenges facing the public works programme. These include delays in implementation and reporting, as well as the non-submission of quarterly evaluation reports by some public bodies.

As a result, central government funding to local and provincial governments has been withheld for the 2024/25 budget.

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In addition, the City of Tshwane is facing financial challenges that are hampering its ability to deliver its projects. This means that the city cannot address the issue of food insecurity and nutrition alone.

Collaboration between government, the private sector and civil society is needed. Policies could include prioritizing food security and nutrition, for example by subsidizing nutritious foods, regulating food safety and encouraging sustainable agricultural practices.

Second, a public-private partnership must be established to implement food security programs targeting marginalized households, smart urban agriculture and community gardens.

Third, there is a need to fund research into innovative food production technologies and sustainable agricultural practices, and to share industry data on food supply chains and consumer preferences.

Fourth, there is a need for community-based research on food needs and barriers to food access.

Fifth, providing financial resources by investing in startups and businesses focused on improving food security and nutritional outcomes.

Finally, monitoring and evaluation frameworks must be established to assess the impact of food security policies and programmes and ensure accountability and transparency in resource allocation.

Adrino Mazenda, Principal Investigator, Associate Professor in Economic Management Sciences, University of Pretoria

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T he International Monetary Fund recently estimated the monetary value of ecosystem services — especially carbon sequestration — provided by one whale to be about $2  million over its lifetime. 

This underlines the significance of ecosystem restoration, biodiversity, wildlife conservation and ecotourism in Africa and elsewhere. These elements are crucial in the continent’s efforts to adapt to and mitigate climate change. They are also integrally connected to the problems of food and water insecurity and poverty, the solutions to which sometimes threaten biodiversity preservation efforts.

Mainstream economics’ growth models were, until the late 1980s with the adoption of the sustainable use paradigm, dominated by efforts to quantify the economic value of factors of production — entrepreneurship, labour and capital, without accounting for the negative externalities from production that were offloaded on the natural environment. 

Natural ecosystems were seen as resources to be exploited for production, the environmental costs of which were externalised through the system of national accounts (SNA), which still counts GDP today absent of ecological and social costs.

While efforts have been made by economists and biologists to quantify environmental value and subsequently any damage to ecosystems, the SNA still treats the environment as a secondary priority, not integral to how economies are built and sustained. 

For example, the valuation of ecosystems often occurs in the aftermath of an oil spill or major industrial environmental disaster. Even then, damage to the natural environment is often considered merely part of the cost of doing business .

This thinking remains pervasive, despite the increased attention paid to nature and the effect of climate change entering the corporate zeitgeist. Consider, for example, the effect on the environment of soy farming or cattle ranching in Brazil and its contribution to the destruction of the Amazon rainforest, or how the destruction of mangrove forests contributes to the reduction in water quality and increased flood risks.

But if a blue whale can be reliably valued at about $2  million in terms of carbon absorbed over its lifetime, and the estimated global population or “stock” of blue whales at the time was almost $1  trillion, then there is an argument for resource economics and pursuing sustainability and biodiversity preservation considering the climate crisis. 

If we are to meet net zero carbon emissions by 2050, the Paris Agreement and sustainable development goals , businesses and countries need to pay significant attention to the economic value and risks connected to nature, in addition to the implementation and achievement of the goals of the Global Biodiversity Framework . Or we risk having them as some la-la land dream sequence.

One may ask what whales and biodiversity have to do with Africa. All these things are easy for the Global North to worry about because their basic needs are met. After all, Africa has serious issues limiting development, from crippling national debt to food, water and energy insecurity and loss and damage caused by climate change. 

Africa is disproportionately affected by climate change. The continent experiences severe droughts, floods and other extreme weather events, exacerbating socio-economic problems.

Rising temperatures and unpredictable rainfall threaten agricultural productivity, leading to food insecurity and displacement of people. Climate-driven migration may also fuel conflict. Pollution caused by commercial, agricultural and industrial activities further limits accessibility to clean and safe drinking water, and contaminated water sources damage vulnerable ecosystems that individuals depend on for their livelihoods. 

This further increases the natural environment’s fragility and reduces countries’ already limited fiscal capacity to fund climate adaptation strategies.

While Africa faces some of the worst effects of climate change and lacks the fiscal capacity to respond, the continent’s rich biodiversity and ecosystems are vital for the global carbon cycle — even as they are degraded by climate change fuelled by human activities. 

The Congo Basin , for instance, is crucial for regulating the global climate, despite being highly vulnerable to deforestation.

Africa has forests and other marine and terrestrial ecosystems that are essential to realising net zero emissions. These are assets, the value of which needs to be credibly quantified to encourage their conservation, even as other problems remain.

In addition to the Congo Basin being one of the “lungs of the Earth”, the continent has some of the world’s most effective ocean carbon capture ecosystems. 

The continent is also home to wetland , grassland , dryland and other ecosystems of plants and animals, all critical for carbon storage. These ecosystems have the potential to absorb and store significant amounts of carbon dioxide and support the natural achievement of net zero.

Yet, the spectre of climate change looms large over Africa’s natural carbon sinks, with increased temperatures contributing to desertification, erosion and ocean acidification. Human activities, including overfishing, illegal timber and wildlife trades and usage of certain fertilisers and industrial activities, further reduce the continent’s ability to act as a carbon sink.

Preserving and protecting Africa’s carbon sinks are critical to the global future. But we must also be cautious of the slow and steady creep of potential green colonialism — the ignorant do-gooding in the name of the global good, which preys on power imbalances and results in false solutions that are dangerous distractions.

Mass tree planting of a single species is considered a great solution to natural carbon storage. But, without adequate planning, understanding of the land and consultation with the local residents, these efforts create “ green deserts ” — a monoculture of trees with limited ecosystem and biodiversity value.

Green deserts are a manifestation of climate colonialism and greenwashing that must be avoided. Instead, promoting ecosystem restoration through integrating and indigenous knowledge systems and practices is critical, because people have coexisted with the land for generations and possess knowledge and insights on maintaining them.

International cooperation and support are critical for successfully quantifying the value of Africa’s biodiversity and achieving net zero while promoting sustainable development on the continent. 

Moreover, people’s inclusion provides an opportunity for job creation through activities such as ecotourism, creating benefits for the local residents and a stake in the ownership of an asset that has been demonstrated to have tangible value.

Given the challenging fiscal conditions faced by many African countries, debt-for-nature swops offer a promising approach to harness the economic value of their biodiversity and ecosystems while achieving fiscal sustainability. 

These arrangements involve debt forgiveness in return for commitments to environmental conservation. 

By alleviating financial pressures and supporting sustainable practices, debt-for-nature swops provide a viable method to combine debt relief with ecological and biodiversity preservation.

Given the economic value of blue whales and other natural assets highlights that the factors of production that are measured and given value can no longer simply be capital, non-environmental assets, labour and entrepreneurship. 

Biodiversity and nature must factor into the equation. 

Africa’s unique challenges and opportunities make it a critical player in the global effort to achieve net zero and build a sustainable future. 

Through global collaboration, avoiding green deserts and green colonialism, while promoting investments in the continent’s natural capital, there is an opportunity for a climate-resilient, prosperous and sustainable Africa.

Vincent Obisie-Orlu is a researcher in the natural resource governance programme at Good Governance Africa.

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UNDRR (2022). Climate Change Triggers Mounting Food Insecurity, Poverty and Displacement in Africa. https://www.preventionweb.net

has been cited by the following article:

TITLE: Leveraging Indigenous Knowledge for Effective Environmental Governance in West Africa

KEYWORDS: African Indigenous Knowledge Systems , Sustainable Development Goals , Climate Change

JOURNAL NAME: Beijing Law Review , Vol.13 No.4 , December 26, 2022

ABSTRACT: Effective environmental governance is key to achieving Sustainable Development Goals. Environmental sustainability programs in developing countries across West Africa are anchored on western scientific knowledge. This has led to a tendency to marginalize the application of indigenous knowledge in environmental protection in West Africa. Yet, no knowledge system develops in isolation as they cross-fertilize and benefit from each other. Indigenous knowledge systems are as old as the traditional societies having been passed from one generation to another. They are those voluminous, diverse, and highly localized sources of wisdom that are neither specific nor universal. Indigenous knowledge systems such as using animal dung as manure, sighting of the new moon before planting, rain-making rituals, and planting of trees to serve as shades have helped to conserve the wetlands and the forests of most societies in West Africa and are effective in promoting environmental sustainability. Hence, the reason they are considered as important as scientific knowledge which must be integrated through multiple evidence base approaches for effective environmental governance. This article using doctrinal research methodology aims at examining how traditional societies in West Africa can leverage indigenous knowledge to achieve effective environmental governance, mitigate climate change, and promote sustainable development. The article recommends that mainstreaming indigenous knowledge systems into environmental legislation, policy and institutional frameworks will not only help in mitigating environmental issues such as climate change but will help developing countries in West Africa meet the SDG goals and their commitments in the Paris Agreement. The article concludes that the integration of such unique knowledge systems into other evidence or scientific based knowledge systems could be one of the best ways to ensure effective and participatory environmental governance in West Africa.

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South Africa: Poor South African Households Can't Afford Nutritious Food - What Can Be Done

Food insecurity is a feature of life for millions of South Africans. Food insecurity refers to a lack of regular access to enough safe and nutritious food for average growth and development and an active and healthy life. This may be due to unavailability of food or a lack of resources to buy it.

The extent of this was recently mapped by the Human Sciences Research Council. For example, in Gauteng province, South Africa's economic powerhouse, 51% of households experience food insecurity. A national survey between 2021 and 2023 found Gauteng households were affected to different degrees: 14% faced severe food insecurity, 20% moderate food insecurity, and 17% mild food insecurity.

The research also found that South African households survive on nutrient-poor food groups such as cereals, condiments, sugars, oils and fats. Consumption of nutrient-rich food groups such as fruits, pulses, nuts, eggs, fish and seafood is limited.

Dietary diversity is useful for measuring food security. A diverse, nutritious and balanced diet prevents nutritional deficiencies and diseases. A fall in dietary diversity is linked to a rise in the proportion of people who are malnourished .

The HSRC findings were the most recent to point to a growing crisis of food insecurity in the country. In an earlier study, we examined the diets of people living in South Africa's second largest city, Tshwane.

We found that due to income, and other socio-economic factors, none of the poor households in our study were getting adequate nutrients from what they were eating. Mostly they were eating cereals (grains such as wheat and maize), vegetables such as legumes, roots and tubers, and oils and fats because they couldn't afford anything else. Most had little to no income . And most were poorly nourished.

On the basis of the findings we recommended a range of interventions. These included better implementation of existing policies aimed at opening up opportunities, such as the Expanded Public Works Programme . And we recommended campaigns be run to increase people's awareness about nutritional foods and growing them.

The help of the private sector and NGOs is also recommended.

Mapping eating habits

The study measured what households were choosing to eat from among the various food groups. These were 775 households from food-insecure areas of Tshwane as mapped by the 2016 Statistics South Africa Community Survey . We asked which food groups had been eaten in the previous seven days by any household member at home, including food prepared at home but eaten, for example, at work (such as a packed lunch).

Twelve food choices were used : cereals, legumes, roots and tubers, vegetables, fruits, milk, eggs, meat, fats, fish, sweets and beverages.

The Principal Component Analysis was used to analyse the Tshwane study households' consumption of these food groups. The analysis is widely used to derive dietary patterns from the daily eating patterns of households.

We then used the Simpson index to measure how nutrient rich the diets were. An index score greater than 0.5 shows a highly diversified diet. The Simpson Index was profiled on socio-economic determinants of food insecurity variables, such as age, household size, income, and food expenditure.

The average dietary diversity score was low for all the poor households in the Tshwane study.

What we found

In our survey, the households with the least diversified diets were those headed by women, people with no more than secondary education, unemployed people, and/or recipients of the social support grant. This suggests that the grants are insufficient to cover people's food needs.

Households with low dietary diversity rarely reared animals or had food gardens.

Households chose mainly four food groups. The first group was associated with a vegetable-based diet (roots and tubers, legumes, vegetables, and fruit). The second group was associated with people who consumed sugar, honey and miscellaneous products (coffee, tea, soft drinks, and instant foods). The third group comprised people who consumed fats and proteins, eggs and milk products. The final group was associated with the consumption of cereals or staple foods.

It was not possible to identify a group of urban food insecure households that ate a mixed selection of all food groups. This suggests they all lacked adequate dietary requirements to boost nutrition. This was regardless of their socio-economic status.

We also found that households faced a number of obstacles beyond income constraints that limited their dietary diversity. These included unemployment, household size, education, and the lack of land, skills and resources to practise urban agriculture.

The City of Tshwane in Gauteng has adopted numerous strategies to alleviate food insecurity. These include the 2017 climate response strategy , meant to reduce food insecurity due to climate vulnerability, and the Expanded Public Works Programme , which provides job creation and skills development, supporting sustainable socio-economic development and poverty reduction.

But execution has been suboptimal.

Poor coordination among government departments and agencies about priorities has led to interventions being ineffective .

A list of the challenges facing the public works programme was presented by a parliamentary monitoring group. They included delays in implementation and reporting as well as non-submission of quarterly evaluation reports by some public bodies.

As a result, funding from the central government to local and provincial administrations was withheld for the 2024/25 budget.

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In addition, the City of Tshwane faces financial challenges that affect its ability to get things done. This means the city cannot solve the problem of food insecurity and nutrition alone.

What's needed is collaboration between government, the private sector and civil society. Policies could include prioritising food security and nutrition, such as subsidies for nutritious foods, regulations to improve food safety and incentives for sustainable agricultural practices.

Second, public-private partnership must be established to implement food security programmes targeting marginalised households, urban smart agriculture, and community gardens.

Third, there is a need to fund research on innovative food production technologies and sustainable agriculture practices, and share industry data on food supply chains and consumer preferences.

Fourth, there is a need to conduct community-based research on food needs and barriers to access.

Fifth, contribution of financial resources by investing in startups and enterprises focused on improving food security and nutrition outcomes.

Finally, monitoring and evaluation frameworks need to be established to assess the impact of food security policies and programmes and ensure accountability and transparency in resource allocation.

Adrino Mazenda , Senior Researcher, Associate Professor Economic Management Sciences, University of Pretoria

This article is republished from The Conversation Africa under a Creative Commons license. Read the original article .

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