Food Insecurity and Chronic Diseases: Diabetes &amp; Hypertension Among Older Adults in South Africa

doi:10.21203/rs.3.rs-4333376/v1

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Food Insecurity and Chronic Diseases: Diabetes & Hypertension Among Older Adults in South Africa

https://doi.org/10.21203/rs.3.rs-4333376/v1

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Food security is a situation where all people, at all times, have physical, social and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for a healthy and active life. In 2021, a significant number of the South African households either had food inadequacy or severe food inadequacy challenges. More than half of South African population is at risk of hunger and limited access to nutritious food.

Food insecurity is often associated with negative health outcomes, including chronic diseases such as diabetes and hypertension. A secondary data obtained from the cross sectional 2021 South African General Household Survey (GHS) was analyzed to determine the association between food insecurity (independent variable) and diabetes and hypertension (dependent variables). The data was analysed in three phases namely univariate, bivariate, and multivariate.

Stratified random sampling was employed in the primary study whereas the sample frame of this study consisted of 3,324 primary sampling units (PSUs) with a total of 33,000 dwelling units/ enumeration areas. The results of this study show that the odds of having hypertension or diabetes were considerably higher among older adults who had inadequate access to food (odds ratio (OR) 1.14, p < 0.05) compared to those who had adequate access to food. More targeted food security programs could lower the odds of diabetes and hypertension amongst older adults. The promotion and provision of free health screening services at various government health facilities could assist with the early detection of hypertension and diabetes.

South Africa is characteristically considered as a food secure country, while some households (majorly rural areas) are food insecure (1, 2). With the improvement of standards of living, the availability of food has extended and become more varied, where there has been an increase to access of services. However, there have also been considerable negative consequences regarding dietary patterns, decrease in physical activeness as well as consistent growth in diet-related chronic diseases especially among the poor. Diet and nutrition are prominent factors in the promotion and maintenance of good health throughout one’s entire life.

Food and Agricultural Organization (FAO) defines food security as a situation where all people, at all times, have physical, social and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for a healthy and active life (3). As more scientific data supports the idea that dietary changes have significant impact on health throughout life, both positively and negatively, nutrition has emerged as a key modifiable factor of chronic disease (4). Food insecurity therefore renders the achievement of healthy and active life out of bounds. If people are unhealthy because of limited access to food and dietary needs they are prone to have a variety of diseases, including chronic illnesses. Much of the developing world now follows high-fat, energy-dense diets that include sizeable amounts of animal-based foods rather than a plant-based diet (4). Consequently, the persistence of food insecurity and undernutrition in areas where chronic diseases are becoming a significant epidemic is not surprising. This is also motivated by the distribution of food that in these areas where it is evident that access to healthy and affordable food is challenging. The cycle of having enough food followed by shortage of food in food-insecure households plays a direct role in compromised dietary, weight gain and accumulation of visceral fat (5). The development of chronic diseases is positively correlated with weight gain and insufficient nutrition. Food insecurity is associated with stress which in turn plays a vigorous part in metabolic syndrome, potentiating instinctual fat accretion, chronic disease, and digestion (5, 6). The obesity epidemic and its associated comorbidities, such as diabetes, heart disease, hypertension, and stroke, are not limited to developed nations (4). One feature of food insecurity in the developed nations is that highly processed, low-quality meals are more affordable than fresh produce, which includes fruits and vegetables, lean proteins, and whole grains (7). The fast paced, advanced, and industrialized lifestyle of the developed world has rapidly established itself into the developing nations, while abandoning the original approach to securing healthy food in turn for healthier and prolonged lives. As a result, even in developed societies, food security remains a critical public concern, especially for disadvantaged groups (7). Furthermore, most of the developing world peoples still struggle to attain competent health support and services. Consequently, those diagnosed with chronic diseases such as diabetes and hypertension stand at a greater disadvantage of illness with added malnutrition from being food insecure. The term ‘food security’ describes the erratic or restricted availability of sufficient and safe food. Furthermore, there appears to be a correlation between food insecurity, risk factors for type 2 diabetes, and the management of type 1 and type 2 diabetes. Possible causes and pathophysiologic pathways are in the literature revealed on the relationship between food insecurity and diabetes (7).

In 2021 an estimated 828 million people suffered from hunger, an increase of around 46 million from the previous year (FAO Food and Agricultural Organization (FAO), International Fund for Agricultural Development (IFAD), United Nations International Children's Emergency Fund (UNICEF), World Food Programme (WFP)and World Health Organization (8). This represents roughly 8.9% of the world's population. The majority of hungry people live in developing countries, where 14.3% of the population is undernourished (9). Some studies, unfavourable settings promote unhealthy eating behaviours and diets, which ultimately lead to ill health. They are also linked to food shortage. The food environment, which includes food outlets' presence, accessibility, and placement, is a neighbourhood-level element that affects food access and may have an impact on obesity and diet quality. The terms "food desert" and "food swamp" refer to food situations that are characterized by a dearth of healthy food options and a surplus of harmful food options. According to previous research, unfavourable food settings can lead to poor health, bad diets, and food insufficiency (10, 11). Due to diminished mobility, physical functioning issues, and limited ability to drive, older persons may find it more difficult to obtain healthy meals in unfavourable food situations (12). In sub-Saharan Africa, the prevalence of hunger is particularly high, with one in four people experiencing hunger (13). South Africa produces enough food to meet its domestic needs however high levels of poverty and inequality mean that there is a challenge around access to food, particularly nutritious food (6, 14). In 2017, 21.3% of the South African households either had food inadequacy or severe food inadequacy challenges whilst 6.8 million South Africans were vulnerable to hunger (15). Studies show that more than half of South African population is at risk of hunger and limited access to nutritious food (16, 17).

Previous studies, conducted in USA, have found a close association between food insecurity hypertension and diabetes (18). In 2017, the burden of diabetes stood at 17% in South Africa (19). High calorie foods which are easily accessible often lead to diet-induced inflammation which in turn is has been proven to be closely corelated with type 2 diabetes in South Africa (6, 19). Chronic illnesses are the leading cause of death in the world – about 63% of deaths have been associated with cardiovascular diseases, cancers, chronic respiratory diseases and diabetes (20). People who experience food insecurity are also more likely to have poor nutrition, which can lead to nutrient deficiencies and negative effects on physical and mental health (5, 21–23). One of the recent systematic review studies, conducted in Southern African region, found that food insecurity was mostly associated with hypertension; diabetes; anxiety; anxiety and depression and increased risk of HIV acquisition however the empirical studies themselves were conducted in broader African context, and not necessarily in South African context (24). Food insecure older adults often have limited economic and social resources which make them more vulnerable to food access barriers (25–27). At the fore, poor food environments may amplify negative effect of food insecurity and environment with diet quality and obesity among older adults has not been documented (28). The relationship between diet quality and obesity in older persons and the prior research suggests that poor food surroundings may compound the harmful effects of food insecurity (28).

Therefore, studies elsewhere have shown that food insecurity is associated with negative health outcomes, including chronic diseases such as diabetes; cardiovascular disease; and obesity (29, 30). Food insecurity is associated with various negative health consequences such as obesity, poor self-reported health status, mental and physical health problems, depression, higher cardiovascular risk, medication nonadherence hypertension, and poor diabetes self-management (30). Food insecurity among older adults and the associated adverse health outcomes turn to be more severe and often intensify the necessity for healthcare services (16, 30). Food insecurity among adults increases the odds of harmful health consequences such as mental health disorders, chronic diseases and obesity (31, 32). Moreover, gestational weight gain occurs and has twice the risk of gestational diabetes among low-income and food-insecure women (33, 34). People with diabetes find it hard to follow their diabetic-specific diet in food-insecure households and this decreases their confidence in the ability to manage their diabetes which leads to high emotional distress and accelerates disease progression (16, 19, 35).

Food insecurity has a negative impact on an individual's physical and mental health, which may lead to chronic diseases, poor nutrition, and decreased access to health care. It is essential to address food insecurity as a public health issue to improve overall health outcomes and reduce health disparities (18, 36–38). Low-income households consume fewer fruits and vegetables than below poverty-line households food poverty line (39, 40). Some studies have revealed that food insecurity is prevalent not only in the countries of the Global South but also in countries such as the United States, where a large proportion of the population experiences serious health problems resulting from food insecurity (41, 42). Furthermore, one study found that the number of older adults experiencing food insecurity in the USA, between 2007 and 2011, increased by 50% (30). This makes food insecurity a public health concern in the country (43). Food insecurity increased drastically around the world due to Covid-19 lockdowns. Economic hardship, job losses, and disruptions in food supply chains emanating from Covid-19 lockdowns gave rise to food insecurity in a number of countries around the world (44).

There is a general consensus that there is a paucity of research focusing on food insecurity among the elderly (45–47). Very little is known about the food security status of elderly people in South Africa (48). Hence the aim of this paper is to determine the nature of the relationship between food insecurity and self-reported diabetes and hypertension among older adults in South Africa. We therefore endeavour to answer a question as to what is the nature of relationship between food insecurity and self-reported diabetes and hypertension? Among older adults, little is known about the relationship between food insecurity and hypertension and diabetes however some previous studies have found that food insecurity increases the odds of chronic conditions, in general, among older people (49, 50). On the other hand, a few other studies have also found that chronic diseases may increase the odds of food insecurity particularly among low-income rural households (51, 52).

One of the recent studies conducted in Canada found that aboriginal adults who live in food-insecure household when compared with their counterparts living in food-secure households, 36% are more likely to report poor general health versus 21% living in food-secure households (22). Furthermore, increased stress, life dissatisfaction, and poor mental and general health have been found to be associated with households’ food-insecurity (53).

Study design and data source

This is a cross-sectional study that analysed secondary data obtained from the 2021 South African General Household Survey (GHS). The GHS is a nationally representative household-based survey that has collected data annually on the population since its inception in 2002 with the objective of examining progress in the development of various sectors in the country (8). Development indicators that are examined in the GHS include social development and health, education, housing, food security, agriculture, and the access of households to service delivery and other facilities and these are examined in all private households as well as among individuals who reside in hostels due to labour migration across all the nine South African provinces (8). The sampling design employed by the GHS was a stratified two-stage design which involved the use of a Master Sample Frame which was developed specifically at a household level and is based on information that was collected during the 2011 Census year (8). This sample frame consisted of 3,324 primary sampling units (PSUs) with a total of 33,000 dwelling units/ enumeration areas being randomly selected (8). Dwelling units that consisted of individuals who resided in old age homes, hospitals, prisons, student accommodation and military institutions were excluded from participation. The GHS consists of two surveys namely the Household survey and the Person survey.

Population and sample size

The population of interest in this study were adults (both male and female) who were aged 50 + and were household heads. The variables that were of interest for this study population were obtained in both the household and person survey. Thus, both surveys were used. The total weighted sample (N) of individuals who participated in the person survey was 60,482,490 and the total weighted sample (N) of individuals who participated in the household survey was 17,946,571. The two datasets were not analysed separately but were merged using the unique person identifiers of the individuals namely “uqnr” which refers to the “unique number” and “personnr” which refers to the “person number” and are included in both surveys. The merge yielded a weighted match of 17,946,571 individuals who participated in both the household and person surveys. For this current study, analysis was only restricted to adults aged 50 + and thus the analytical sample was reduced to N = 2,964,539 adults aged 50 + for whom complete information was collected.

Study Variables

Dependent variable

The two dependent variables in this study were self-reported diabetes and hypertension. The two dependent variables were defined by asking respondents whether a doctor/nurse/other healthcare worker at a clinic/hospital/private practice had ever told a respondent that he/she has/had any of these chronic conditions. The response categories of the two chronic conditions were dichotomous and given that we were interested in adults 50 + who indicated that they were diabetic or hypertensive, the response categories for these two dependent variables were coded as 0 for those who responded “no” and 1 for those who responded “yes”.

Independent variables

The main independent variable in this study was food security. The GHS household survey includes a set of questions that assess household’s access to food and these questions are asked based on the Household Food Insecurity Access Scale (HFIAS) (8, 47, 54). The four questions that were asked in the GHS were as follows:

During the last 12 months, was there a time when you or others in your household ate only a few kinds of foods because of a lack of money or other resources?

During the last 12 months, was there a time when you or others in your household had to skip a meal because there was not enough money or other resources to get food?

During the last 12 months, was there a time when you or others in your household ate less than you thought you should because of a lack of money or other resources?

During the last 12 months, was there a time when your household ran out of food because of a lack of money or other resources?

Questions 2 and 3 were combined to form the composite question “During the last 12 months, was there a time when you or others in your household cut the size of meals or skip meals because there was a lack of money or other resources to get food”. These two questions were collapsed into one given how these questions appear elsewhere (55, 56). Although the GHS used questions obtained from the HFIAS, measurement of food security was not measured using the HFIAS scale given that the follow up questions for each of these questions did not ask the frequency of how often this occurred but only asked if this happened for 5 or more days in the past 30 days, with responses captured as a dichotomous outcome. Given this circumstance, household food security was measured by employing the tool used in the Community Childhood Hunger Identification Project (CCHIP) which has been used in previous studies (55, 57). To create a composite food security variable, total food security scores were computed using the three questions. Respondents who answered “No” to all three questions were assigned a score of 0 and classified as having “adequate access to food”. In addition, respondents who answered “Yes” to only one of these three questions were assigned a score of 1 and classified as having “inadequate access to food”. Lastly, respondents who answered yes to two or three of these questions were assigned a score of 2 or 3 and were classified as having “severely inadequate access to food’.

The control variables in this study were: (i) Sex (Male, Female); (ii) Age (50–54 years, 55–59 years, 60–64 years, 65–69 years, 70–74 years, 75–79 years, 80 + years); (iii) Population group (Black African, Coloured, Indian/Asian, White); (iv) Place of residence (Urban, Rural); (v) Province (Western Cape, Eastern Cape, Northern Cape, Free State, KwaZulu-Natal, North West, Gauteng, Mpumalanga, Limpopo); (vi) Marital status (Never married, Married/living together, Divorced/separated, Widowed); (vii) Level of education (No schooling, Primary, Secondary, Tertiary/Higher); (viii) Employment status (Employed, Unemployed, Not economically active); (viiii) Recipient of Social grant (Yes); (ix) Recipient of special COVID-19 social relief of distress grant (Yes, No); (x) Number of household members (1,2,3,4,5,6,7,8+); (xi) Frequency of food insufficiency for adults 18 years and older in household in the past 12 months (Never, Seldom, Sometimes, Often/Always).

Data Analysis

The data was analysed in three phases namely univariate, bivariate, and multivariate. At the univariate level, descriptive statistics were computed by showing the levels of diabetes and hypertension, the level of diabetes and hypertension by food security status as well as the levels of overall food security status through a series of graphs. In addition, a frequency table was generated to show the percentage distribution of the sociodemographic characteristics of the respondents. At the bivariate level, a chi-square test of association contingency table was used to test for an association between the respondents’ sociodemographic characteristics and their chronic disease status (whether they were hypertensive or diabetic). Lastly at a multivariate level, a binary logistic regression model was employed to predict the association between the respondents’ sociodemographic characteristics and the two dependent variables, while controlling for other covariates. This regression model was employed given that the dependent variable was categorical and had response categories that were dichotomous.

Data management

The 2021 GHS was downloaded from the Statistics South Africa data repository (particularly NESSTAR) and was analyzed using STATA version 15.

Ethical Considerations

The GHS survey was conducted anonymously, and respondents were assigned unique person identifiers. As such, the names and other personal information of the respondents were not revealed in the datasets.

Figure 1 shows that out of the total sample of adults aged 50 + who had visited a healthcare professional, over 50% of the adults (51.6%, n = 1,531,147) reported that they had hypertension while 48.3% indicated that they did not have hypertension. Furthermore, close to 20% of the adults (18.5%, n = 547,886) reported that they had diabetes while 81.5% did not have diabetes.

Figure 2 shows that most of the adults who reported being hypertensive had inadequate access to food as they constituted 53.6% of the sampled population. This was followed by 51.3% who had adequate access to food and close to 50% who had severely inadequate access to food (48.1%). Conversely, there were slight percentage differences in the distribution of diabetic adults who had severely inadequate access to food (18.5%) and those who had inadequate access to food (18.1%).

Table 1

Sociodemographic characteristics of respondents aged 50 + in South Africa
Sociodemographic characteristics	Total (N = 2,964,539), n (%)
Sex
Male	1,155,570 (39.0)
Female	1,808,969 (61.0)
Age
50–54 years	145,646 (4.9)
55–59 years	193,383 (6.5)
60–64 years	814,932 (27.5)
65–69 years	684,979 (23.1)
70–74 years	503,788 (17.0)
75–79 years	319,623 (10.8)
80 + years	302,188 (10.2)
Population group
Black African	2,485,923 (83.9)
Coloured	288,444 (9.7)
Indian/Asian	71,758 (2.4)
White	118,414 (4.0)
Place of residence
Urban	1,610,145 (54.3)
Rural	1,354,394 (45.7)
Province
Western Cape	262,981 (8.9)
Eastern Cape	473,504 (16.0)
Northern Cape	76,082 (2.6)
Free State	188,585 (6.4)
KwaZulu-Natal	572,578 (19.3)
North West	227,765 (7.7)
Gauteng	562,996 (19.0)
Mpumalanga	260,327 (8.8)
Limpopo	339,721 (11.5)
Marital status
Never married	536,061 (18.1)
Married/living together	897,316 (30.3)
Divorced/separated	179,633 (6.1)
Widowed	1,351,529 (45.6)
Level of education
No schooling	569,806 (19.2)
Primary	1,189,221 (40.1)
Secondary	1,144,767 (38.6)
Tertiary/Higher	60,745 (2.0)
Employment status
Employed	198,849 (6.7)
Unemployed	94,777 (3.2)
Not economically active	2,670,913 (90.1)
Recipient of social grant
Yes	2,964,539 (100.0)
Recipient of special COVID-19 social relief of distress grant
Yes	167,046 (5.6)
No	2,797,493 (94.4)
Number of household members
1	463,957 (15.7)
2	556,745 (18.8)
3	465,841 (15.7)
4	371,706 (12.6)
5	374,470 (12.6)
6	247,047 (8.3)
7	213,666 (7.2)
8+	271,106 (9.1)
Frequency of food insufficiency for adults 18 years and older in household in past 12 months
Never	2,394,679 (80.8)
Seldom	266,906 (9.0)
Sometimes	248,998 (8.4)
Often/Always	53,956 (1.8)

Table 1 shows the sociodemographic characteristics of the respondents aged 50 + in South Africa. Overall, the percentage distributions show that majority of the respondents were female (61.0%), who were between the age groups 60–64 years (27.5%). Most of the respondents were Black African (83.9%), resided in urban settings (54.3%) and are widowed (45.6%). The results showed that there were only percentage differences in the proportion of respondents who resided in the KwaZulu-Natal (19.3%) and Gauteng (19.0%) provinces. Furthermore, more than 40% of the participants had a primary school qualification (40.1%), were not economically active (90.1%) and all the respondents were recipients of a social grant (100.0%). More than 80% of the respondents reported that adults aged 18 years and older in their households did not experience any food insufficiency in the past 12 months and only 5.6% of the respondents were recipients of the special COVID-19 social relief of distress grant. There were no differences in the percentage distribution of respondents who reported having a family size of 1 or 3 household members (15.7% respectively) and those who had a family size of 4 or 5 household members (12.6% respectively).

Table 2

Sociodemographic characteristics by type of chronic disease
	Diabetes			Hypertension
Sociodemographic characteristics	Yes, (%)	No, (%)	p-value	Yes, (%)	No, (%)	p-value
Sex
Male	31.4	43	0.000	31.1	51.1	0.000
Female	68.6	57	0.000	68.9	48.8	0.000
Age
50–54 years	1.5	5	0.002	3.1	5.7	0.000
55–59 years	6.4	6.2		5.5	7
60–64 years	22	25.7		22.9	27.3
65–69 years	22.5	25		23.3	25.8
70–74 years	20.3	16.8		18.8	15.9
75–79 years	13.6	10.1		12.3	9
80 + years	13.8	11.1		14	9.1
Population group
Black African	85.4	90.8	0.000	89.9	89.7	0.696
Coloured	10	6.3		6.8	7.1
Indian/Asian	3.4	1		1.7	1.2
White	1.3	1.9		1.6	1.9
Place of residence
Urban	48.9	43.5	0.030	48.2	40.6	0.000
Rural	51.1	56.5	0.030	51.8	59.4	0.000
Province
Western Cape	10.4	4.9	0.000	6.3	5.5	0.000
Eastern Cape	21.8	22.3		24.8	19.4
Northern Cape	3	4.6		5	3.6
Free State	7	5.8		7.2	4.8
KwaZulu-Natal	29.2	17.7		19.1	20.5
North-West	4.4	7.1		7	6.3
Gauteng	9.1	12.6		12.4	11.6
Mpumalanga	7	8.6		8.1	8.6
Limpopo	8	16.2		10.2	19.6
Marital Status
Never married	14.6	17.4	0.000	17.3	16.5	0.001
Married/living together	25	32.2		25.5	36.5
Divorced/separated	5.3	5.5		4.6	6.4
Widowed	55.1	44.9		52.6	40.6
Level of education
No schooling	20.8	21.8	0.739	19.5	23.9	0.005
Primary	44.3	42.1		45.7	39.3
Secondary	33	34.5		33.4	35.1
Tertiary/Higher	1.9	1.5		1.5	1.7
Employment status
Employed	4.2	6	0.181	4.3	7.1	0.000
Unemployed	2.3	3.2		1.8	4.3
Not economically active	93.4	90.8		93.8	88.6
Recipient of special COVID-19 social relief of distress grant
Yes	2.1	5.9	0.001	2.8	7.8	0.000
No	97.9	94.1	0.001	97.2	92.2	0.000
Number of household members
1	13.3	15.6	0.465	14.9	15.5	0.359
2	19.3	17		18.6	16.2
3	18.6	15.2		16.8	14.8
4	13.1	13.2		12.7	13.7
5	11.4	13		12.8	12.7
6	8	8.7		7.7	9.6
7	6.8	7.4		7	7.7
8+	9.3	9.8		9.6	9.8
Frequency of food insufficiency for adults 18 years and older in household in past 12 months
Never	81.4	81.4	0.933	81.3	81.6	0.571
Seldom	9.7	9.4		9.3	9.6
Sometimes	7.8	7.9		8.4	7.3
Often/Always	1.1	1.2		1	1.4

Table 2 shows that majority of Black African (85.4%) female respondents (68.6%) who resided in rural settings (51.1%) in the KwaZulu-Natal province (29.2%) reported that they had diabetes. Furthermore, over 50% of respondents who were widowed (55.1%), had a primary education qualification (44.3%) and were not economically active (93.4%) indicated that they had diabetes. Close to 100% of respondents who were not recipients of a special COVID-19 social relief of distress grant (97.9%) who resided in a household that constituted an average family size of 2 family members (19.3%) and reported no food insufficiency for all adults aged 18 years and older in their households in the past 12 months, indicated that they had diabetes. There were slight differences in the percentage distribution of adults aged 60–64 years (22.0%) and 65–69 years (22.5%) who reported that they had diabetes. Similarly, slight percentage differences were observed in the distribution of adults aged 75–79 years and 80 + who reported that they had diabetes.

Similarly, to the previous results, the results showed that most of the respondents who reported that they had hypertension were Black African (89.9%) females (68.9%) aged 65–69 years (23.3%) who resided in rural areas (51.8%) in the Eastern Cape province (24.8%). Over 50% of the respondents who were hypertensive were widowed (52.6%), had a primary school qualification (45.7%) and were not economically active (93.8%). Similarly, close to 100% of the respondents who reported being hypertensive were not recipients of the special COVID-19 social relief of distress grant (97.2%), reported no food insufficiency for adults 18 years and older in their households in the past 12 months (81.3%) and had a family size of two household member (18.6%). Of note, there were slight percentage differences in the distribution of hypertensive adults who had a family size of 4 household members (12.7%) and 5 household members (12.8%).

Table 3

Unadjusted and adjusted logistic regression analysis of predictors of diabetes and hypertension among adults 50 years and older in South Africa
	Diabetes		Hypertension
Characteristics	Unadjusted OR (95% CI)	Adjusted OR (95% CI)	Unadjusted OR (95% CI)	Adjusted OR (95% CI)
Food security status
Adequate access to food	Ref	Ref	Ref	Ref
Inadequate access to food	1.06 (1.04–1.07) *	1.04 (1.02–1.05) *	1.31 (1.30–1.32) *	1.18 (1.17–1.19) *
Severely inadequate access to food	1.03 (1.02–1.04) *	1.01 (0.99–1.02)	0.91 (0.90–0.92) *	0.78 (0.77–0.79) *
Sex
Male	Ref	Ref	Ref	Ref
Female	1.65 (1.64–1.66) *	1.69 (1.68–1.71) *	2.32 (2.31–2.33) *	2.59 (2.57–2.60) *
Age
50–54 years	Ref	Ref	Ref	Ref
55–59 years	3.78 (3.69–3.88) *	2.89 (2.81–2.96) *	1.50 (1.48–1.52) *	1.29 (1.27–1.31) *
60–64 years	2.94 (2.87-3.00) *	1.85 (1.81–1.90) *	1.52 (1.50–1.53) *	0.81 (0.80–0.82) *
65–69 years	3.24 (3.17–3.31) *	2.03 (1.99–2.09) *	1.55 (1.53–1.57) *	0.85 (0.83–0.86) *
70–74 years	4.47 (4.37–4.57) *	2.63 (2.56–2.70) *	2.06 (2.04–2.09) *	1.09 (1.07–1.10) *
75–79 years	4.15 (4.05–4.24) *	2.49 (2.43–2.55) *	2.25 (2.22–2.27) *	1.20 (1.18–1.22)
80 + years	4.91 (4.80–5.03) *	3.09 (3.01–3.17) *	2.93 (2.89–2.96) *	1.65 (1.63–1.68) *
Population group
Black African	Ref	Ref	Ref	Ref
Coloured	1.78 (1.76–1.80) *	1.18 (1.17–1.20) *	0.86 (0.85–0.86) *	0.52 (0.51–0.52) *
Indian/Asian	3.36 (3.31–3.41) *	2.23 (2.19–2.27) *	1.12 (1.11–1.14) *	1.04 (1.02–1.06) *
White	1.23 (1.21–1.24) *	0.84 (0.83–0.86) *	0.97 (0.95–0.98) *	0.66 (0.65–0.67) *
Place of residence
Urban	Ref	Ref	Ref	Ref
Rural	0.81 (0.81–0.82) *	0.94 (0.94–0.95) *	0.74 (0.73–0.74) *	0.74 (0.73–0.74) *
Province
Western Cape	Ref	Ref	Ref	Ref
Eastern Cape	0.44 (0.43–0.44) *	0.49 (0.49–0.50) *	1.11 (1.10–1.12) *	0.86 (0.85–0.87) *
Northern Cape	0.29 (0.28–0.30) *	0.29 (0.28–0.29) *	1.22 (1.20–1.24) *	1.19 (1.17–1.21) *
Free State	0.48 (0.48–0.49) *	0.54 (0.53–0.55) *	1.28 (1.26–1.29) *	0.88 (0.87–0.89) *
KwaZulu-Natal	0.82 (0.82–0.83) *	0.90 (0.89–0.92) *	0.87 (0.87–0.88) *	0.66 (0.66–0.67) *
North-West	0.30 (0.29–0.30) *	0.38 (0.37–0.39) *	1.02 (1.00-1.03) *	0.94 (0.93–0.96) *
Gauteng	0.37 (0.37–0.38) *	0.44 (0.43–0.45) *	1.05 (1.04–1.06) *	0.77 (0.76–0.78) *
Mpumalanga	0.39 (0.38–0.39) *	0.42 (0.42–0.43) *	0.95 (0.94–0.96) *	0.74 (0.73–0.76) *
Limpopo	0.22 (0.22–0.22) *	0.24 (0.24–0.25) *	0.47 (0.46–0.47) *	0.37 (0.37–0.38) *
Marital status
Never married	Ref	Ref	Ref	Ref
Married/living together	0.94 (0.93–0.95) *	1.31 (1.29–1.32) *	0.68 (0.68–0.69) *	1.35 (1.34–1.36) *
Divorced/separated	1.59 (1.57–1.61) *	2.09 (2.06–2.12) *	0.80 (0.79–0.80) *	0.98 (0.97-1.00)
Widowed	1.39 (1.38–1.40) *	1.18 (1.17–1.19) *	1.23 (1.22–1.23) *	1.10 (1.09–1.11) *
Level of education
No schooling	Ref	Ref	Ref	Ref
Primary	1.05 (1.04–1.06) *	0.97 (0.96–0.98) *	1.39 (1.38–1.40) *	1.43 (1.42–1.44) *
Secondary	0.87 (0.86–0.87) *	0.81 (0.80–0.82) *	1.06 (1.06–1.07) *	1.14 (1.13–1.15) *
Tertiary/higher	1.46 (1.43–1.48) *	1.26 (1.23–1.29) *	0.89 (0.88–0.91) *	1.05 (1.03–1.07) *
Employment status
Employed	Ref	Ref	Ref	Ref
Unemployed	0.77 (0.75–0.79) *	1.17 (1.14–1.21) *	0.68 (0.67–0.69) *	0.97 (0.95–0.99) *
Not economically active	1.43 (1.41–1.45) *	1.21 (1.19–1.23) *	1.69 (1.68–1.71) *	1.29 (1.27–1.30) *
Recipient of special COVID-19 social relief of distress grant
Yes	Ref	Ref	Ref	Ref
No	2.74 (2.69–2.79) *	2.04 (1.99–2.08) *	2.78 (2.75–2.81) *	2.50 (2.46–2.54) *
Number of household members
1	Ref	Ref	Ref	Ref
2	1.16 (1.15–1.17) *	1.16 (1.14–1.17) *	1.13 (1.12–1.13) *	1.06 (1.05–1.07) *
3	1.26 (1.25–1.28) *	1.15 (1.14–1.17) *	1.12 (1.11–1.13) *	1.02 (1.02–1.03) *
4	1.12 (1.11–1.14) *	0.99 (0.98-1.00)	0.94 (0.93–0.95) *	0.78 (0.78–0.79) *
5	0.80 (0.79–0.81) *	0.74 (0.73–0.75) *	0.98 (0.97–0.99) *	0.90 (0.90–0.91) *
6	0.89 (0.88–0.90) *	0.81 (0.80–0.82) *	0.98 (0.97–0.99) *	0.94 (0.93–0.95) *
7	1.00 (0.99–1.01)	0.99 (0.98–1.01) *	0.97 (0.96–0.98) *	0.85 (0.84–0.86) *
8+	0.96 (0.95–0.97) *	0.84 (0.83–0.85) *	0.90 (0.89–0.91) *	0.84 (0.84–0.85) *
Frequency of food insufficiency for adults 18 years and older in household in past 12 months
Never	Ref	Ref	Ref	Ref
Seldom	1.01 (0.99–1.02)	1.03 (1.02–1.04) *	0.81 (0.80–0.82) *	0.83 (0.82–0.84) *
Sometimes	1.15 (1.14–1.16) *	1.07 (1.05–1.08) *	1.28 (1.27–1.29) *	1.48 (1.47–1.50) *
Often/Always	0.73 (0.71–0.75) *	0.69 (0.67–0.71) *	0.89 (0.87–0.90) *	0.93 (0.91–0.95) *

OR = Odds ratios; CI = Confidence Interval; Ref = Reference category; *p < 0.005 or 0.05

Table 3 shows the unadjusted and adjusted binary logistic regression results of the adults’ sociodemographic characteristics that are associated with being diabetic and hypertensive. The results showed that all the sociodemographic characteristics were significantly associated with being diabetic or hypertensive at both the unadjusted and adjusted levels, given that the p-values were less than 0.005 (p < 0.005). In interpreting some of the selected adjusted multivariate results for adults who were diabetic, the results showed that the odds of being diabetic were considerably higher among adults who had inadequate access to food (odds ratio (OR) 1.04, p < 0.05) compared to those who had adequate access to food. The odds of being diabetic were 1.69 times higher among female adults (Odds ratio (OR) 1.69, p < 0.05), considerably higher among those in the age groups 80+ (odds ratio (OR) 3.09, p < 0.05) and among those who were Indian (odds ratio (OR) 2.23, p < 0.05) in relation to those who were aged 50–54 years and those who were Black African, although these odds were observed to be high in all the age groups and population groups. Furthermore, the odds of being diabetic were relatively higher among adults who were divorced/separated (odds ratio (OR) 2.09, p < 0.05), were in tertiary or higher education (odds ratio (OR) 1.26, p < 0.05), not economically active (odds ratio (OR) 1.21,p < 0.05), not recipients of special COVID-19 social relief of distress grant (odds ratio (OR) 2.04, p < 0.05), lived in a household constituting of 2 family member (odds ratio (OR) 1.16, p < 0.05) and sometimes experienced food insufficiency for adults aged 18 years and older in their households in the past 12 months (odds ratio (OR) 1.07, p < 0.05). Contrary to these findings, the odds of being diabetic were considerably lower among adults who resided in rural areas (odds ratio (OR) 0.94, p < 0.05), and lived in the Limpopo province (odds ratio (OR) 0.24, p < 0.05).

In terms of hypertension, the odds of being hypertensive were higher among adults who had inadequate access to food (odds ratio (OR) 1.18, p < 0.05), female adults (odds ratio (OR) 2.59, p < 0.05), and those who were 80+ (odds ratio (OR) 1.65, p < 0.05), though these odds were observed to be higher across all age groups. Similarly, the odds of being hypertensive were found to be higher among the Indian population group (odds ratio (OR) 1.04, p < 0.05), those who were living in the Northern Cape (OR) 1.19, p,0.05), those who were married/living together (OR) 1.35, p < 0.05), and those who had a primary school qualification (OR) 1.43, p < 0.05). In addition, the odds of being hypertensive were higher among adults who were not economically active (OR) 1.29, p < 0.05), were not recipients of the special COVID-19 social relief of distress grant (OR) 2.50, p < 0.05), lived in a household constituting of 2 family members (OR) 1.06, p < 0.05), and sometimes experienced food insufficiency for adults aged 18 years and older in their households in the past 12 months (odds ratio (OR) 1.48, p < 0.05). Conversely, the odds of being hypertensive were lower among adults who resided in rural areas (OR) 0.74, p < 0.05).

The results of this study suggest that most adults suffer from hypertension and diabetes. Previous studies have made similar findings(49, 58, 59). Most older adults who have hypertension and diabetes are females (71.9%), compared to males (28.1%).

The aim of this paper was to investigate the association between food insecurity and self-reported diabetes and hypertension among older adults in South Africa and thereby ascertaining whether food insecurity could be exacerbating specific chronic health conditions i.e. hypertension and diabetes among older adults. Whilst many previous studies were conducted in other parts of the world and in Africa in general, this study focused in South Africa. The unique contribution of this study is the inclusion of older adults who aren’t covered by old age social grants i.e. 50–59 and the results show that there’s an urgent need to focus on this age group. The results suggest that older adults besieged by food insecurity challenges are more likely to suffer from hypertension and diabetes. These findings are in line with findings from the previous studies which found that elderly people have multiple chronic diseases (58–60).

The results of this study show that the odds of having hypertension or diabetes were considerably higher among older adults who had inadequate access to food (odds ratio (OR) 1.14, p < 0.05) compared to those who had adequate access to food. Hence there is a positive correlation between food insecurity; hypertension and diabetes. Other studies have also found that food insecurity exacerbates the odds of chronic diseases such as diabetes and hypertension (18, 35). Older adults are the vulnerable group in society and the limited access to food may increase their stress levels which may expose them to hypertension. Food insecurity intersects with diabetes at both the causal and management of the disease dimensions (53). Food variety play an important role in the management of diabetes because of special diets one must adhere to in order to successfully manage its progression. In instances where there is absence or limited access to food, clearly it is impossible to achieve the latter.

The results further suggest that being widowed and having a low level of education, such as primary education, increases the odds of hypertension and diabetes. Being widowed status suggest lack of support from a spouse which can be a serious challenge especially at advanced age. A male provider role is a global phenomenon hence most women depend on men for their livelihood. Whilst low education status means lower ability to fend for oneself. Black African are mostly affected by hypertension and diabetes compared to all other race groups in South Africa. Other studies have also found that low education level and being widowed are some of the factors which influence food insecurity among older adults in Sub-Saharan Africa (61, 62).

The results also showed that older adult women have more odds of suffering from hypertension and diabetes than men. The likelihood of having a hypertension and diabetes were more than twice higher among female adults (odds ratio (OR) 2.07, p < 0.05), and considerably higher among those in the age groups 80+ (odds ratio (OR) 2.69, p < 0.05). Previous studies have shown that women older adults are more prone, than older men, to suffer social ills such as poverty and ill-health due to relative depravation of women during their life courses (63).

Social grants, and specifically special COVID-19 social relief of distress grant, appear to play a significant moderating role in respect of hypertension and diabetes. To an extent that hypertension and diabetes maybe an indirect by-product of food insecurity, availability of critical social grant such as special COVID-19 grants may be pacifying food insecurity, and by deduction hypertension and diabetes, in these poor households. Hence, in this study, not being a recipient of special social relief COVID-19 grant was associated with hypertension and diabetes. Contrary to the findings from previous studies (40, 61, 64) which found that food insecurity is more prevalent in rural areas than urban areas, the results of this study show that the odds of food insecurity and having hypertension and diabetes were considerably lower among adults who resided in rural areas (odds ratio (OR) 0.88, p < 0.05), and lived in the Limpopo province (odds ratio (OR) 0.20, p < 0.05).

Diabetes and hypertension are at worrying levels amongst alder adults in South Africa. Our findings indicated that hypertension and. diabetes are more associated with food insecure older adults ,50 years and above, at household level in South Africa. The promotion and provision of free health screening services at various government health facilities could assist with the early detection of hypertension and diabetes among older adults. Government and civil society food provisioning initiatives, and the related social security measures, must target indigent older adults more. In as much as these study findings suggest that food insecurity is less prevalent in rural than in urban areas, it is important that the role of subsistence farming, and specifically home gardens, in alleviating food insecurity be more explored to enhance access to nutritious and quality foods. Furthermore, social security grant plays a moderating role in relation to food insecurity, an obvious deduction is that the means of purchasing food elevates the odds of food insecurity among older adults. Older adults who are above fifty years old yet below the minimum sixty years requirement maybe exposing this category of older adults to a heightened risk of food insecurity. The latter category of older adults is generally unemployable, considering their advancement in age and yet do not qualify for the old age grant. It is important that future studies be conducted on old age grant coverage and to determine what factors lead to lesser-than-desired coverage of older adults who are sixty years and older. The current means-test in South Africa which measures the qualifying income criteria, and/or threshold, for the old income grant may excluding vulnerable older adults. Similar empirical investigations must be conducted in relation to special social relief grant.

Human Ethics & Consent to Participant

Not Applicable. This is a secondary in which data collected by Statistics South Africa (a government agency with legislative mandate to collect country-level statistics on behalf of South African government) was used. No primary data collection was conducted for this research article.

Funding Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Author Contribution

Mgwaba, MT wrote conceptualisation of the manuscript; data analysis and conclusions.Masuku, MM wrote introduction; literature review and edited the manuscript

Data Availability

http://superweb.statssa.gov.za/webapi/jsf/tableView/tableView.xhtml

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No competing interests reported.

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Food Insecurity and Chronic Diseases: Diabetes & Hypertension Among Older Adults in South Africa

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