Skip to main content

Household socio-economic determinants of food security in Limpopo Province of South Africa: a cross sectional survey



Despite the strong commitment at both national and international levels to eradicate hunger and achieve household food security, by 2030 food insecurity remains a public health problem. South Africa is amongst the countries with the highest rate of income inequality in the world and extremely high levels of absolute poverty. The Gini coefficient in South Africa is estimated at 0.68 Although South Africa may be food secure at a national level, large numbers of households within the country are food insecure approximately 52% of the rural households in Limpopo Province of South Africa were considered severely food insecure. It has been noted that the majority of households in South African informal settlements and rural areas were moderately or severely food insecure due to lack of access to food which was directly related to income. Rural areas have assets that can be explored to support households. The adult population above 18 years in South Africa make up 78% of the 5.9 million population with about 40% living in rural areas, this study explored household food insecurity in adults in rural environments. The current study aimed to explore the socioeconomic and dietary determinants of household food insecurity among the adult population in the Limpopo Province.


A cross-sectional survey design was used, and data were collected using a validated pre-tested questionnaire. The participants were recruited from households in Limpopo province. Multiple linear regression was computed to explore the influence of socioeconomic and dietary practices on food insecurity.


The study included 699 randomly selected participants of which the majority earned a monthly income ≤ 3000 ZAR, and 31.8% experiencing hunger in the past 30 days at the time of study. The dietary practices of the participants were found to be associated with household food insecurity. The study found that large family size, being female in South Africa, low household income and low rate of regular breakfast intake were significant determinants of household food insecurity (p < 0.05).


In summary, most of the households were poor and approximately one-third were food insecure. The implementation of sustainable employment policies, and food-based approaches and targeting rural household food production could significantly reduce food insecurity in the rural area.


Household food insecurity is a major public health issue in Africa, with persistent social and health impacts. Household food insecurity is referred to as the inability to afford nutritionally adequate and safe foods, or limited ability to acquire acceptable foods in socially acceptable ways [1]. The Food and Agriculture Organization of the United Nations’ (FAO) defines as: “Food security exists when all people, at all times, have physical and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life” [2, 3].

Food insecurity levels have steadily risen in Southern Africa in recent years and remain a major developmental problem in the sub-region [4]. The general household survey reports that in South Africa, food insecurity is not regarded as the ability to produce sufficient food for the nation, but as inadequate financial resources to buy food for the household [5]. South Africa as a country is food secure at the national level yet many households in rural communities still struggle with hunger and food insecurity [6, 7]. The high level of inequality and unemployment as reported by Statistics South Africa [5] may partly explain the contrasting scenarios of South Africa being food secure at national level but not at household levels. According to Drimie [8] and the World Wildlife Fund (WWF) [9], challenges affecting the South African food system include poor health conditions, a severe rate of malnutrition and long-term impacts of nutritional deficiencies in the population. Challenges of crippling poverty, high unemployment rate especially among women, corruption, and deep-rooted inequality continue to have implications on access to land, water supply, energy, food and nutritionally balanced diets.

The food security status of any population is linked to the functions of food system outcomes which are impacted by aspects such as technology, politics, economy, culture, social, and natural environment [10]. Apart from this, food systems should not only focus on farming for consumption but also need to address issues affecting the health of the population including nutrition-related chronic diseases such as cardiovascular, obesity, diabetes, and other diseases linked to the double burden of malnutrition [11]. An increase in food productivity, efficiency and profitability are of paramount importance in reducing the prevalence of hunger and improving the nutritional needs of the underprivileged population of rural communities.

Various studies have established synergies between food security, unemployment, poverty and inequality [12]. Statistics South Africa [5] provides a profile of households’ experiences of hunger in terms of sex and population group of household head as well as geographic location and settlement type. They report that that households of larger sizes (8 or more members) experienced higher proportions of hunger. The larger the household size, the higher are chances of hunger. Furthermore, a higher proportion of women in South Africa are unemployed; around 30% are male compared to 50% women. Bhorat and Goga [13] investigated the gender wage gap in South Africa using Labour Force Surveys and showed an increase in the gender wage gap over time. They investigated whether men earn more than women in any single year and whether the earnings gap increased over time and found that women who work earned far less than their male counterparts. As of 2019, 41.8 percent of households in South Africa were female-headed, which amounted to a total of 7.2 million [5]. Given that employment is one of the most important sources of earning an income and a key driver of escape from poverty and achieving food security, narrowing the poverty gap between gender is important. Census 2011 results show that 2.9 million households (20%) were involved in agriculture. Nationally, the largest percentage of agricultural households was located in Kwazulu-Natal (25%), Eastern Cape (21%) and Limpopo (16%) [5]. Therefore Limpopo has an opportunity to amplify agricultural households. The significance of these problems has been emphasised in the Sustainable Development Goals 1, 2 and 3, which aim at eradicating poverty, hunger, and promoting good health and wellbeing by 2030. This study seeks to examine food insecurity determinants taking into consideration the Sustainable Development Goals.

The South African government is also committed to promoting and protecting South Africans’ right to access adequate food. To accomplish this goal, it is fundamental to eradicate hunger and achieve household food security. The ‘Integrated Food Security and Nutrition Programme’ under the National Department of Agriculture, Forestry and Fisheries is charged to oversee its implementation [1]. This goal aligns with the goal of food security of the Food and Agriculture of the United Nations [7]. Although there is strong commitment both at national and international levels, the number of people suffering from hunger and food insecurity still represents some of the biggest challenges for a large part of the South African population and must be treated with utmost urgency [14]. The need to identify the determinants of food security is, therefore, essential.

Studies have been conducted in low-income settings to reveal the determinants of food insecurity in households in Addis Ababa [15], South Africa [16], and rural and urban households in South Africa [17], while Herforth and Harris [18] summarised studies from Low and Middle Income Countries. Most of these studies found that education levels, household size, dependency ratios, household income and the areas in which the households were situated, were major determinants of food insecurity. None of the studies investigated the dietary patterns as potential indicators of food insecurity. A recent study in Maphumulo in KwaZulu-Natal [19] found that education, receiving infrastructural support (irrigation), and participation in the “One Home One Garden” programme positively influenced the food security status of households, while household income and access to credit showed a negative correlation with food security. Another study examined linkages between agricultural skills and household food security in farming households of the Tugela Ferry irrigation scheme in the Msinga Local Municipality [20]. This study found that factors like household size, marital status, education levels, gender, total livestock units, household income, farming experience, credit use and competence levels in fertiliser measurement have the potential to reduce household food insecurity. The study concludes that provision of agricultural skills may improve household food security and that interventions could improve smallholder farming productivity. The current study aimed to explore the socioeconomic and dietary determinants of household food insecurity among the adult population in the Limpopo Province. In addition identifying households or community assets that could be solutions. The study forms part of a larger study that investigated eating patterns, cultural perspectives, household food security, nutritional status, physical activity and health risk of population in Limpopo province. The current study reports on the household food security and households’ determinants, specifically focusing on accessibility and availability.


Study design and setting

The study design was cross-sectional and aimed to explore a statistical analysis for measurement of correlation between two or more phenomena. This study was conducted in the Limpopo Province situated in the Northern part of South Africa, which has an estimated population of 5,404,868 [21]. It consists of five districts, namely Capricorn, Waterberg, Sekhukhune, Mopani and Vhembe. The target population was adults (male and female) aged 18 to 65.

Sampling approach and recruitment

A probability method was used which involved the selection of participants or sampling units from a population using random procedures. Three districts were randomly selected and used as a cluster: Vhembe, Mopani and Waterberg. From each cluster four villages were selected as a stratum using simple random sampling. In the stratum, a systematic method was used to select households. Individuals in the household whose ages ranged from 18 to 65 years were selected using convenience sampling. Only one member per household was recruited.

Data collection procedures

Data were collected using a well-designed pre-tested questionnaire divided into five sections, namely sociodemographic information (age, education level, marital status, household income and family size); dietary patterns; 24-h recall; household hunger scale (HHS); and food inventory. The dietary patterns questions and 24-h recall were used to measure patterns and consumption, while food accessibility and availability in the households were assessed using a household hunger scale adapted from a WHO standardised and validated tool used in the 1999 South African National Food Consumption Survey (NFCS) [22].

The levels of food security were grouped into three categories namely: food secure (0–1), at risk of hunger (2–3) and experiencing hunger (4–6).

The research assistants used a door–door recruitment approach, and willing participants were informed about the study and then interviewed. In each cluster area, the appropriate local language (Xitsonga, Sepedi, Tshivenda or Isindebele) was used. The researchers provided oversight and checked the completeness of the questionnaires.

Data analysis

The data were analyzed using a statistical package for social sciences (SPSS) version 25. Descriptive statistics such as percentile mean, standard deviation, minimum and maximum values were analysed. The Chi square test was used to determine the relationship between independent variables (sociodemographic and dietary patterns) and the outcome variable (food insecurity). Categorical variables were dummy coded before incorporated in the multiple regression and household hunger scale scores (dependent variable) were used. Multiple linear regression was computed to explore the influence of sociodemographic and dietary practices on food insecurity. Regression analysis allows the researchers to understand the strength of relationships between the above cited dependent and independent variables. Using statistical measurements like R-squared/adjusted R-squared, regression analysis can reveal how much of the total variability in the data is explained by your model. The six independent variables used in this study were selected based on previous findings, model building procedures and contexts of the current study area. The collinearity effect was also tested using a variance inflation factor for all six independent variables. The multicollinearity effect computed for each independent variable ranged between 1.011 and 1.131, which is less than the cut-off value (≥ 4). The only dependent variables in the study were household food insecurity coded from 0 to 6 with increasing number representing greater food insecurity. The dependent variables were managed in the analysis as continuous endpoint. Variables were considered statistically significant if p—values were less than 0.05.


Sociodemographic data

Among the 699 participants recruited, 79.9% were females, 59.4% had secondary levels of education and 46.2% were single. The average age of the participants was 36.3 ± 17.6 years, with 79.7% between 18 and 60 years. Less than half (46.2%) of the participants were married and 70.2% lived in a household where the breadwinner earned less than or equal to 3 000 ZAR (South African Rand) per month. On average, the household family size was 5.3 ± 2.5 persons, with the number of persons ranging from one to fifteen per household as depicted in Table 1.

Table 1 Sociodemographic characteristics of participants

Dietary practices

The findings of the current study revealed that the majority (95.7%) of the participants consumed more than two meals per day, 93.1% ate breakfast with 60.1% doing so daily. In addition, 92.1% of the participants reported that they prepared food at home and 78.9% ate meals alone. The majority (93.0%) of the participants reported that they ate fruit and vegetables, but only 16.0% did so daily. Furthermore, 39.2% reported that they ate fruit as a snack, see Table 2.

Table 2 Dietary practices of surveyed participants

Dietary patterns, accessibility, availability and consumption of food in the households were assessed using the dietary pattern questions and 24-h recall. A hunger scale and household food inventory were used to assess food availability at household level. The 24-h recall showed that the most consumed foods were mealie meal (99.4%), salt (99.4%), sugar (73.9%), tea (71.7%), bread (40.6%) and meat (33.9%).

The household food inventory revealed that most of the households had, on the day of the interview, consumed the foods listed in Table 3. The table only lists foods available in 20% or more of the households. On the whole, 10 starches were found in households with mealie meal; white meal and brown bread being the most frequently found starches. Other available starches were rice crisps, Weet-Bix (a cereal made from wheat), corn flakes (cereal made from corn), potato, sweet corn and sweet potato.

Table 3 Foods available in the households on the day of the visit

Regarding protein availability in the households, 15 protein food items were found with none of the items available in more than 20% of the households; however, fresh fish, mutton and gizzards (hearts and/or livers) were present in 10–17% of the households. Other food products containing proteins included burgers, peanut butter, Vienna sausages (thin parboiled sausages that contain a lot of water and are traditionally made of pork, beef or horse meat), canned fish, beef, cheese spread, chicken feet and heads, fish paste, fish fingers, polony and canned beans. Six milk and milk products were identified in the surveyed households with fat-free milk and milk blends available in more than 20% of the households. Milk, cheese, fresh milk and 2% less milk were also available in households.

Less than 10% of the surveyed households had vegetables, with only five different vegetables found in all surveyed households. These included mixed vegetables, cabbage, beetroot salad, carrots and spinach. Fifteen different fruits were available in the interviewed households; naartjies, pawpaw and oranges were present in more than 20% of the households. Other fruits included pears, apples, peaches, plums, mangoes, pineapples, avocados, apricots, bananas, guavas and grapes. Another 20 miscellaneous food items were also identified, namely non-diary creamers, hard sweets, toffee/fudge sweets, vetkoek (fried fat cake made from wheat flour), tea, ice cream, butter, cheese curls, custard, coffee, scones, sugar, chocolate bar/chomps, jelly, margarine, jam, NikNaks (maize-based chips), biscuits and marmalade.

Prevalence of hunger among participants

The prevalence of hunger was assessed using a hunger scale, and the findings revealed that more than two-thirds of the households surveyed were food insecure and 31.8% experienced hunger. This finding is higher than the national and provincial rates of 26.0% and 30.8%, respectively. The households were asked whether any adults had gone hungry in the previous month because there was not enough food. They were also asked whether any child in the household had gone hungry in the previous month. Nearly all the households included at least one adult, and among these 82% had never experienced problems satisfying adult food needs in the previous month, 4% seldom experienced problems, 11% sometimes experienced problems, 2% often experienced problems, and 1% always experienced problems. However, 32.6% of the households in the present study were found to be food secure as depicted in Fig. 1. Figure 1 juxtaposes the findings in this study with those conducted in South Africa using similar instruments at various time points as well as highlighting ones done in the same area, namely Limpopo Province.

Fig. 1
figure 1

Food insecurity status comparison with previous studies [23, 26]

Bivariate associations/correlations of sociodemographic data, dietary patterns and food security

Female participants were more likely to be food insecure than male participants (p = 0.019). When considering those who experiencing hunger as illustrated in Table 4, a higher proportion of 35% (195 out of 557 females) compared to 19% (27 out of 140 males) is observed. Conversely, more men at 40.7% compared to women at 30% were food secure, when analyzing the data within the groups.

Table 4 The association between sociodemographic variables and food insecurity

Household food insecurity was also significantly associated with large family size and low household income (Table 4).

The dietary practices of the participants were also found to be associated with household food insecurity (Table 5). A detailed analysis showed that lower number of meals eaten per day (p = 0.000) and a low rate of regular breakfast intake (p = 0.000) were determinants of household food insecurity. While, most participants ate breakfast, the frequency or number of times per week revealed that more than 50% do not eat breakfast frequently.

Table 5 The association between dietary patterns and food insecurity

Multiple linear regression was computed to explore the influence of sociodemographic and dietary practices on food insecurity. Multicollinearity was verified for highly correlated variables. The analysis revealed that being female (vs. male, β: 0.119, p = 0.002), and having or being part of a household size of ≤ 6 persons (vs. ≥ 6 persons, β: 0.132, p = 0.001) were positively correlated with food insecurity. Income level ≤ 3 000 ZAR (vs. ≥ 3000 ZAR, β: − 0.967, p = 0.001) and daily eating of breakfast (vs. sometimes, β: − 0.298, p = 0.000) were negatively correlated with food security (see Table 6). The model explains the 14% variance in food insecurity.

Table 6 Results of multiple linear regression on sociodemographic characteristics and dietary practices associated with food insecurity

Discussion and conclusion

The present study was conducted to identify the potential determinants of household food insecurity. For a household to be food secure, food needs to be available, accessible, and consumed, and there should be a stable food supply [24]. The findings show that more than a third (35.6%) of the study participants reported to be at risk of hunger and 31.8% already experienced hunger, which was higher than the result of the national and provincial rates of 26.0% and 30.8% respectively—experiencing hunger according to South African National Health and Nutrition Examination Survey (SANHANES) 2013 [25]. However, the present findings revealed a significant decline from the 1999 and 2005 national surveys which reported that 52.3% and 52.0% respectively, of households experiencing hunger [17, 22]. This study used the same tool for measuring food security as that used in the NFCS of 2005. SANHANES 2013 and our study findings for households experiencing hunger in Limpopo province are similar; 30.8% vs 31.8%. Perhaps this reduction in number of people experiencing hunger might be an indication that intervention strategies such as grants and poverty relief strategies put in place by the South African government has indeed improved the livelihood of her people [26,27,28]. The South Africa Demographic Health Survey conducted in 2016 reported the percent distribution of households by the frequency of problems satisfying food needs of de jure adults in the previous 12 months [29].

The current findings revealed that female participants were more affected by food insecurity than males. These findings agreed with the results of a study conducted by Matheson and McIntyre [30], which reported that female household members were found to be more sensitive to food insecurity than their male counterparts. According to Herforth and Harris, the pathway from women's empowerment to improved nutrition is influenced by a number of factors, including social norms, knowledge, skills and how decision-making power is shared within households [18]. The pathway generally consists of three interrelated components: women's use of income for food and non-food expenditures, the ability of women to care for themselves and their families, and women's energy expenditure. Evidence suggests that empowering women improves nutrition for mothers, their children, and other household members.

The present findings also indicated that the rate of regular breakfast intake was low in the food insecure group, which is consistent with the findings of Chun et al. who conducted a study among Korean adults with the main aim of verifying the association between food insecurity and health behaviors [4]. Most studies in South Africa have focused on breakfast in children and adolescents [31, 32]. The study by Seedat and Pillay [32] demonstrated that most of their participants consumed breakfast; however, only a small proportion consumed it daily. In this study, breakfast was consumed, but less frequently per week probably due to food unavailability. Breakfast is an important part of the diet which contributes significantly towards daily nutrient intake and is linked to improved intake of energy, protein, iron, vitamin A and vitamin C, if consumed frequently. The consumption of breakfast leads to positive health behaviour, improved stress management, feeling energetic, and making fewer unhealthy snack choices. Skipping breakfast results in fatigue and suboptimal concentration levels, as well as an increased risk of developing obesity. Reasons for skipping meals, in general, often include being in a hurry, lack of appetite, inability to cook, fasting/religion, and not being hungry. However, in poor households with diminished purchasing power, it could be a function of not having sufficient resources to afford breakfast.

The current study also found that a lower number of meals eaten per day and having eating partner(s) at home or being parents, were determinants of household food insecurity. Reducing number of meals eaten per day could be coping strategies used by households to respond to food security as reported by an earlier study conducted in the Limpopo Province in 2016 [33].

The majority of households included in the study had a monthly income of less than or equal to 3000 ZAR. These results clearly indicate that the majority of the participants lived in poor households and lived below the poverty line of approximately one United States Dollar (15 ZAR) per person per day according to the World Bank. This poses an increased risk of poverty and limits the purchasing power of the household, thus leading to food inaccessibility as reported in this study. These findings are consistent with a previous study where it was reported that on average, a household in the Limpopo Province had an income of 2953 ZAR per month [7]. Low household income was found to be significantly associated with household food insecurity in the study area. Household income is a significant determinant of access to food, which in turn is a major determinant of the nutritional status of the household members [34,35,36,37].

The average family size per household was five persons. A larger household size implies more people to feed which might easily lead to food insecurity. The current findings established an association between household size and food insecurity, similarly to previous findings in South Africa and Ethiopia, which reported that larger household size tends to be food insecure compared to smaller household size [15, 17]. The determinants which were significantly linked to food insecurity are depicted in Fig. 2.

Fig. 2
figure 2

Determinants of food insecurity with a significant association

These determinants were related to the status of women in the society. Women in this study are mostly unemployed, earn less money and have or live with large families. This is in line with the high rural women unemployment rates reported by Statistics South Africa [5].

The limitations of the current study recognized the possibility of misclassification of individuals as food insecure when food security survey tools are used to assess food security in households where some household members are food insecure. In addition, the data was self-reported which means that social prestige may have affected the extent to which participants might have responded to food-related behaviours. There were also more female participants than males.


The findings revealed that more than one-third of all households surveyed were poor, with 31.7% already experiencing hunger. Being female with a low household income, eating a small number of meals per day, with a low rate of regular breakfast intake, and having an eating partner at home or being parents, were found to be risk factors of household food insecurity. Recommendations based on the key findings of the study include policy strengthening of sustainable development activities for reduction of unemployment, creating employment opportunities at local and promoting income-generating activities for women to ensure that households can have improved ability to purchase food. These measures can improve household food security and advance livelihoods.

Data availability

The data used to support the findings of this study are available from the corresponding author, upon request.



Food and Agriculture Organisation


Household Hunger Scale


National Food Consumption Survey


South African National Health and Nutrition Examination Survey


Statistical package for social sciences


World Wildlife Fund


South African rand


  1. Battersby J. Urban food insecurity in Cape Town, South Africa: an alternative approach to food access. Dev South Afr. 2011;28(4):545–61.

    Article  Google Scholar 

  2. Gross R, Schoeneberger H, Pfeifer H, Preuss HJ. The four dimensions of food and nutrition security: definitions and concepts. SCN News. 2000;20(20):20–5.

    Google Scholar 

  3. Barrett CB. Measuring food insecurity. Science. 2010;327(5967):825–8.

    Article  CAS  PubMed  Google Scholar 

  4. Chun IA, Ryu SY, Park J, Ro HK, Han MA. Associations between food insecurity and healthy behaviors among Korean adults. Nurs Res Pract. 2015;9(4):425–32.

    Google Scholar 

  5. Statistics South Africa. Community survey 2016. Pretoria: Statistics South Africa; 2016.

    Google Scholar 

  6. Altman M, Hart TG, Jacobs PT. Household food security status in South Africa. Agrekon. 2009;48(4):345–61.

    Article  Google Scholar 

  7. De Cock N, D’Haese M, Vink N, Van Rooyen CJ, Staelens L, Schönfeldt HC, D’Haese L. Food security in rural areas of Limpopo province, South Africa. Food Secur. 2013;5(2):269–82.

    Article  Google Scholar 

  8. Drimie S. 12 Chapter Aligning policy to address food insecurity. In: Taylor V, Fukuda-Parr S, editors. Food security in South Africa: human rights and entitlements perspectives. Cape town: UCT press; 2015.

    Google Scholar 

  9. World Wildlife Fund. Food: Agri-food Systems: facts and futures. 2019. Accessed 17 Sept 2019.

  10. Ghale Y, Pyakuryal KN, Devkota D, Pant KP, Timsina NP. Citizen participation in food security policy formulations in Nepal: a case of agriculture development strategy. 20, No. 18. Nepal J Participatory Dev. 2018. p. 136.

  11. Popkin BM, Corvalan C, Grummer-Strawn LM. Dynamics of the double burden of malnutrition and the changing nutrition reality. Lancet. 2020;395(10217):65–74.

    Article  PubMed  Google Scholar 

  12. Wight V, Kaushal N, Waldfogel J, Garfinkel I. Understanding the link between poverty and food insecurity among children: does the definition of poverty matter? J Child Poverty. 2014;20(1):1–20.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bhorat H, Goga S, Stanwix B.. Skills-biased labour demand and the pursuit of inclusive growth in South Africa (No. 2014/130). 2014. WIDER Working Paper.

  14. Food and agricultural organisation of the United Nations. Transforming food and agriculture to achieve the SDGS: 20 Interconnected Actions to Guide Decision-Makers. 2018. Rome.

  15. Gebre GG. Determinants of food insecurity among households in Addis Ababa City, Ethiopia. Interdiscip Descr Complex Syst. 2012;10(2):159–73.

    Article  Google Scholar 

  16. Grobler W. Food security of social grant recipients in a low income neighborhood in South Africa. 2013. Accessed June 2016.

  17. Labadarios D, Steyn N, Maunder E, MacIntyre U, Swart R, Gericke G, et al. The national food consumption survey (NFCS)-children aged 1–9 years, South Africa, 1999. South Afr J Clin Nutr. 2002;14(2):98.

    Google Scholar 

  18. Herforth A, Harris J. Understanding and applying primary pathways and principles. 2014.

  19. Ngema PZ, Sibanda M, Musemwa L. Household food security status and its determinants in Maphumulo local municipality, South Africa. Sustainability. 2018;10:3307.

    Article  Google Scholar 

  20. Maziya M, Mudhara M, Chitja J. What factors determine household food security among smallholder farmers? Insights from Msinga, KwaZulu-Natal, South Africa. Agrekon. 2017;56(1):40–52.

    Article  Google Scholar 

  21. Statistics South Africa. Mid-Year Population Estimates. 2011. Pretoria.

  22. Labadarios D, Steyn N, Maunder E, MacIntryre U, Gericke, G, Swart R, et al. The National Food Consumption Survey (NFCS): South Africa, 1999. Public Health Nutrition. 2005. 8, no. 5 (August): 533–543.

  23. Ballard T, Coates J, Swindale A, Deitchler M. Household hunger scale: indicator definition and measurement guide. Washington, DC: Food and Nutrition Technical, Assistance II Project, FHI 360; 2011.

    Google Scholar 

  24. Piniel A, Swart EC. Factors contributing to severe acute malnutrition among the under five children in Francistown-Botswana. 2016. Accessed Aug 2018.

  25. Shisana O, Labadorias D, Rehle T, Simbayi L, Zuma K, Dhansay A. South Africa national health and nutrition examination survey (SANHANES-1). Cape town: HSRC Press; 2013.

    Google Scholar 

  26. Woldesenbet SA, Jackson D, Goga AE, Crowley S, Doherty T, Mogashoa MM, et al. Missed opportunities for early infant HIV diagnosis: results of a national study in South Africa. J Acquir Immune Defic Syndr. 2015;68(3):e26–32.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Barnes H, Hall K, Sambu W, Wright G, Zembe-Mkabile, W. Review of research evidence on child poverty in South Africa. 2017. Ci.Uct.Ac.Za. Accessed Mar 2020.

  28. Misselhorn A, Hendriks HL. A systematic review of sub-national food insecurity research in South Africa: missed opportunities for policy insights. PLoS ONE. 2017.

    Article  PubMed  PubMed Central  Google Scholar 

  29. National Department of Health (NDoH), Statistics South Africa (Stats SA), South African Medical Research Council (SAMRC), and ICF. South Africa Demographic and Health Survey 2016. 2019. Pretoria and Rockville: NDoH, Stats SA, SAMRC, and ICF.

  30. Matheson J, Mcintyre L. Women respondents report higher household food insecurity than do men in similar canadian households. Public Health Nutr. 2005;17:40–8.

    Article  Google Scholar 

  31. Sedibe MH, Feeley AB, Voorend C, Griffith PL, Doak CM, Norris SA. Narratives of urban female adolescents in South Africa: dietary and physical activity practices in an obesogenic environment. S Afr J Clin Nutr. 2014;27(3):114–9.

    Google Scholar 

  32. Seedat R, Pillay K. Breakfast consumption and its relationship to sociodemographic and lifestyle factors of undergraduate students in the school of health sciences at the university of KwaZulu-Natal. South Afr J Clin Nutr. 2020;33(3):79–85.

    Article  Google Scholar 

  33. Phooko-Rabodiba D, Tambe B, Nesamvuni C, Mbhenyane X. Socioeconomic determinants influencing nutritional status of children in Sekhukhune district of Limpopo Province in South Africa. J Nutri Health. 2019;5(1):7.

    Google Scholar 

  34. Nathalie DC. A comparative overview of commonly used food security indicators, case study in the Limpopo Province, South Africa. Universiteit Gent. 2012:12–16.

  35. Psaki S, Bhutta BA, Ahmed T, Ahmed S, Bessong P, Islam M, et al. Household food access and child malnutrition: results from the eight-country MAL-ED study. Popul Health Metrics. 2012;10:1.

    Article  Google Scholar 

  36. Arthur SS, Nyide B, Soura AB, Kahn K, Weston M, Sankoh O. Tackling malnutrition: a systematic review of 15-year research evidence from INDEPTH health and demographic surveillance systems. Glob Health Action. 2015;8(1):28298.

    Article  PubMed  Google Scholar 

  37. Dil Farzana F, Rahman AS, Sultana S, Raihan MJ, Haque MA, Waid JL, et al. Coping strategies related to food insecurity at the household level in Bangladesh. PLoS ONE. 2017;12(4):e0171411.

    Article  Google Scholar 

Download references


We acknowledge all participants and the field workers.


This project was funded by the University of Venda.

Author information

Authors and Affiliations



XG conceptualised the study. TA, NS, HV, TC, LF, MM and XG collected and analyzed the data, wrote the draft and approved final versions. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xikombiso Gertrude Mbhenyane.

Ethics declarations

Ethics approval and consent to participate

The research proposal was approved by the Ethics committee of the University of Venda (SHS/08/NUT/003) before data collection commenced. Permissions and consents were obtained from local authorities and the participants, respectively.

Consent for publication

Participants were informed that data will be shared widely while kept anonymous.

Competing interests

The authors declare that there are no financial competing interest regarding the publication of this paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tambe, B.A., Mabapa, N.S., Mbhatsani, H.V. et al. Household socio-economic determinants of food security in Limpopo Province of South Africa: a cross sectional survey. Agric & Food Secur 12, 19 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: