Exploring Food Security and Household Dietary Diversity in the Eastern Cape Province, South Africa

Abstract

Food security is one of the most severe challenges facing the majority of African countries. The objective of this study was to explore household food dietary diversity and food security in a rural area in the Eastern Cape Province, South Africa. A total of 296 household heads were randomly sampled to participate in the study. The Household Dietary Diversity Score (HDDS) and Household Food Consumption Score (HFCS) were used to identify the consumption patterns of the households and their food security status. Meanwhile, a binary model was used to identify the variables that had an impact on household food security. Findings from the Household Dietary Diversity Score (HDDS) revealed that 61 percent of the households had lower dietary diversity and were consuming at least three food groups, which mainly include pulses, milk, and cereals. The results from the Household Food Consumption Score (HFCS), however, showed that the majority of the households had adequate levels of food consumption. The binary model revealed that age, household income, access to credit, and gender are statistically significant in influencing household food security status in the study area. It can be concluded that household dietary diversity is not guaranteed by food security, as proven by the regression model. Therefore, the government should consider the impact of low income on food security and it should intensify efforts directed at helping rural households to reduce incidences of food insecurity.

Impact of Market Participation on Household Food Security among Smallholder Irrigators in KwaZulu-Natal, South Africa

“…Refs. [23,28,29] measured household food security using HDDS and dichotomized the HDDS. Therefore, this study also followed the same method, as it has been approved and deemed fit to measure household food security.…”

Prevalence and Socio-Demographic Correlates of Body Weight Categories Among South African Women of Reproductive Age: A Cross-Sectional Study

“…Since 1940, South Africa has been undergoing a nutrition transition, with an increase in the contribution of fats and a decrease in carbohydrates and fibre intake towards energy consumption ( 13 , 14 ). Thus, nutrition transition was found to be faster among the black racial groups than the white and Indian/Asian racial groups ( 19 , 20 ) and in urban rather than rural populations ( 21 ), driving an upsurge in obesity in the black population. Pertaining to provinces, for instance, Eastern Cape is the third largest province and the second poorest in South Africa, where 50% of households in the rural districts are food insecure ( 22 ).…”

“…In addition, there is a realisation from the previous studies that there are scarce analyses on the trends of underweight (23), particularly for the male populations. Disparities in the levels of underweight and obesity across African regions, for example, in Southern African countries comprising Botswana, Namibia, South Africa, and Swaziland (now Eswatini), the obesity index is highest (13,21,(29)(30)(31)(32). In the year 2008, South Africa was rated with the highest BMI, with a median score at the population level approximated at 26.9 kg/m 2 among males (in contrast to a world average of 23.8 kg/m 2 ), and 29.5 kg/m 2 among females (in contrast to a world average of 24.1 kg/m 2 ), respectively.…”

Interlinking dietary diversity, production diversity, and climate change: Non-separable farm household model approach

“…However, Jones et al (2014) and Sibhatu et al (2015) state that various approaches can be used to measure dietary diversity and emphasized to compare available quantities of particular foods, diets, and societal food behaviour. Therefore, many researchers use the food variety score-a simple count of food items consumed by households-and the dietary diversity score, an aggregated count of food groups consumed by the households (Cheteni et al 2020;Sibhatu et al 2015;Kumara et al 2016).…”

“…The agricultural production decisions and livelihood of farmers and other stakeholders are heavily influenced also by the increasing frequency of extreme climatic events such as droughts, floods, and heatwaves (Cheteni et al 2020;Das and Ghosh 2019;Birthal et al 2014), which reduce the farm-dependent consumers' choice of diversified food items. A general hypothesis derived from the multiple functions of farm households is that their production and consumption decisions are interrelated and influenced by climatic factors (Barnum and Squire 1979;Dillon et al 2015;Singh et al 1986).…”