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The prevalence of overweight/obesity and its association with household food insecurity among women living with HIV in rural Eswatini

BMC Public Health volume 22, Article number: 629 (2022) Cite this article

Abstract

Background

Eswatini is currently afflicted by an extremely high prevalence of HIV (27%) and malnutrition (both under-and over-nutrition). While rates of overweight/obesity in the general adult population have been documented, data on overweight/obesity and associated risk factors among women living with HIV (WLHIV) in Eswatini is limited. This study examines the prevalence of overweight/obesity and associated risk factors, with an emphasis on clarifying the association between household food insecurity and overweight/obesity for WLHIV in rural Eswatini.

Methods

This cross-sectional study was conducted among WLHIV (n = 166) in rural communities of Eswatini. Data were collected using an interviewer-administered survey questionnaire between October and November, 2017. Body Mass Index (BMI) was calculated to determine overweight and obesity among study participants. Women with BMI values of 25 kg/m2 or greater were classified as being overweight/obese. Multivariable log-binomial regression models were used to examine associations between household food insecurity and overweight/obesity in our study.

Results

Nearly a third (32.5%) of the women in our study were overweight and almost a quarter were obese (22.9%). We found significant associations between household food insecurity and overweight/obesity, with women who experienced household food insecurity the most being 0.38 times less likely to be overweight/obese compared to those who experienced household food insecurity the least (ARR: 0.38, 95% CI: 0.2–0.71). In our study sample, women who perceived themselves as being in poor health were less likely to be overweight/obese compared to those who perceived themselves as being in good health (ARR: 0.58, 95% CI: 0.39–0.86). We found significant associations between overweight/obesity and alcohol use, with the risk of overweight/obesity nearly 1.5 times higher among women who consumed alcohol compared to those who did not (ARR: 1.49, 95% CI: 1.07–2.05).

Conclusions

The high prevalence of overweight/obesity among food insecure women in poverty stricken communities may pose significant challenges for nutritional health and HIV management. With an increasing prevalence of overweight/obesity in food insecure households, there is a need to re-evaluate current strategies and develop multi-level targeted interventions that include prevention of excessive weight gain among women, particularly those living with HIV in rural Eswatini. HIV programs could include screening to identify individuals at risk for overweight/obesity in this population, and provide nutrition education for weight management for those individuals.

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Introduction

In sub-Saharan Africa (SSA), rising prevalence of overweight/obesity co-exists with increased rates of nutrition-related noncommunicable diseases (NR-NCDs) [1]. Studies have shown that people living with human immunodeficiency virus (HIV) are just as susceptible to overweight/obesity as non-infected individuals, and are significantly impacted by the adverse effects of these health conditions [2]. Yet data on overweight/obesity and associated risk factors among people living with HIV in Eswatini are limited. As developing countries undergo shifts in dietary intake from traditional diets high in grains and fiber to western influenced diets high in fats and sugars, this nutrition transition has been associated with increased rates of overweight/obesity in these regions [1, 3, 4]. The rising prevalence of NR-NCDs as a result of the nutrition transition creates additional stress to already weakened immune systems of individuals living with HIV, thereby increasing the risk of morbidity and mortality among this population [2].

Eswatini is currently impacted by these health challenges. In addition to undergoing a nutrition transition, the country has been faced with a drastic increase in prevalence of overweight (28%) and obesity (23%), particularly among women [4]. In conjunction with high rates of overweight/obesity, Eswatini suffers from an extremely high prevalence of HIV (27%) [5] and malnutrition [6]. This increased risk of overweight/obesity may be further impacted by childhood experiences of undernutrition and recurrent infections, and collectively elevate the risk of NR-NCDs such as cardiovascular diseases, type 2 diabetes mellitus, and hypertension [2, 7, 8]. While the prevalence of overweight/obesity in the general adult population has been documented, no known studies have addressed overweight/obesity among women living with HIV (WLHIV) in Eswatini.

Food insecurity (FIS) is crucial to examine when addressing issues of nutritional status and health. Studies have shown that FIS is significantly associated with malnutrition (overnutrition/undernutrition) [9, 10], HIV acquisition and treatment outcomes [11, 12], and increased risk for NR-NCDs [2, 7]. FIS has been associated with increased consumption of calorie-dense foods, which are the main cause of overweight/obesity [1, 3]. Adverse dietary changes, including shifts in dietary patterns toward increased consumption of calorie-dense foods (e.g. foods high in saturated fats, added sugars and sodium) and reduced consumption of unprocessed nutrient-dense foods (e.g. whole grains, fruits and vegetables, and dietary fiber), combined with a reduction in physical activity, is associated with increased risk of NR-NCDs [1, 3]. While a consistent positive relationship between FIS and overweight/obesity has been reported among studies in developed countries overall [13, 14], reports from studies conducted specifically in SSA have been inconsistent, with some showing a positive association between overweight/obesity and FIS [15], and others reporting inverse associations [16–18].

A review of 19 studies by Franklin et al. (2012) examining the relationship between FIS and obesity suggest a strong positive association between FIS and excessive weight gain among women in the United States, even after adjusting for a wide range of socio-demographic characteristics [19]. This review is supported by several studies showing increased weight gain among food insecure individuals in developed countries. Among other factors, these studies suggest that this association may be due to increased poverty, sedentary lifestyle, and unhealthy food environments that facilitate access to calorie-dense foods [20–23]. Nkambule et al. (2021) reviewed 22 studies from countries in SSA. The purpose of the review was to assess associations between FIS and key metabolic risk factors among food-insecure individuals in the region. While findings from this review indicated positive associations between FIS and overweight, in the studies they reviewed, the authors observed a plethora of inconsistencies among previous studies, and noted the need for further research of the association between FIS and overweight in this region [24].

Socioeconomic status (SES) was frequently reported as a significant mediator of the observed associations between FIS and overweight/obesity. While some studies in SSA have reported positive correlations between overweight/obesity and high SES [25], others have reported similar associations among individuals of low SES [26]. Increased wealth and disposable income have a direct influence on food choices/dietary intake and are associated with increased consumption of calorie-dense foods, which in turn leads to increases in weight gain in the context of SSA [27]. Initially, in developing countries, this type of dietary shift and excessive weight gain was correlated with individuals of high SES [26]. However, recent findings from studies conducted in developing countries have been conflicting. Even though a majority of studies have found positive associations between high SES and overweight/obesity [26, 28], some have reported similar findings among individuals of low SES [29–31], and others found no significant associations between these groups, particularly among women [32, 33].

While the prevalence of overweight/obesity in the general adult population has been documented, no known studies have addressed overweight/obesity among WLHIV in Eswatini, who are currently the country’s most vulnerable to HIV infection and poor health [34–36].

Our study seeks to investigate the prevalence of overweight/obesity and associated risk factors, with a specific focus on clarifying the critical association between household food insecurity and overweight/obesity for WLHIV in rural communities of Eswatini. To our knowledge, this is the first study to investigate the prevalence of overweight/obesity and its association with food insecurity among WLHIV in rural Eswatini. This study provides scientific data that may help inform policies and intervention strategies aimed at preventing excessive weight gain and addressing issues of food insecurity among WLHIV, particularly those in resource limited settings.

Methods

Study design and setting

Data from this study were obtained from a cross-sectional study investigating barriers to antiretroviral therapy (ART) adherence among WLHIV in Eswatini [37]. The study was conducted in four rural communities located in the Lubombo and Shiselweni regions between October and November, 2017. This analysis examines the prevalence of overweight/obesity and associated risk factors, with an emphasis on clarifying the association between household food insecurity and overweight/obesity for WLHIV in rural Eswatini.

Participants recruitment

Participants’ recruitment was conducted in collaboration with local health facilities and community health workers or expert clients. Study participants were recruited using targeted community techniques with both venue recruitment (attending community outreach activities and support group meetings) and invitation notices that were posted in public locations (e.g. health facilities, community centers, constituency buildings, churches, and neighborhood care points) within the respective communities. Women who were interested were invited to participate in a survey. Women were eligible to participate in the study if they were between ages 20–49 years, and had been on ART for at least one month at the time of the surveys. Participants were compensated with a 100 Rands for travel expenses and for time taken to participate in the study.

Sample size

Based on previous literature, we estimated that approximately 60% of women living with HIV in our target communities would be overweight or obese. Using an alpha of 0.05 and a statistical power of 80%, 103 participants were determined to be the minimum sample required to effectively assess associations between food insecurity and overweight/obesity among women living with HIV in our study sample.

Data collection

Data were collected through an interviewer-administered survey questionnaire. Study participants were interviewed in their native language of siSwati by trained research assistants. The surveys were conducted in a central location within respective rural communities, such as local constituency buildings, churches, and neighborhood care points. The survey questionnaire included the following items: 1) Household Food Insecurity Access Scale [38], 2) CASE Adherence Index [39], and 3) a structured questionnaire including demographic information and anthropometric measurements (age, weight, height). Weight was measured in kilograms (kg) using a digital bathroom scale, and height was measured in meters (m) using a stadiometer. Weight measurements were taken with participants wearing light clothing and barefoot.

Outcome

Overweight and obesity were determined by using body mass index (BMI), calculated by dividing weight in kilograms by height in meters squared (kg/m2). BMI was categorized as underweight (< 18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), and obesity (≥ 30 kg/m2) [40]. The outcome was modeled as a dichotomous variable normal (18.5–24.9 kg/m2) versus overweight/obese (≥ 25 kg/m2).

Exposure

Data on household food insecurity was collected using the Household Food Insecurity Access Scale(HFIAS) [38]. Participants were asked to provide information on their household food status in the month before the survey. Women were interviewed on all three domains of the HFIAS: 1) anxiety and uncertainty about the household food supply, 2) insufficient food intake, and 3) insufficient quality of food. Due to high prevalence of household food insecurity in the sampled communities, we observed an insignificant variation in the household food insecurity variable, as only 1.2% of the women were from food secure households. Therefore, food security data was used to assess two of the three HFIAS domains (i.e. insufficient food intake and insufficient quality of food) which were combined to create the food insufficiency variable. Women were classified as food insufficient if their answer to one or more of the food insufficiency questions was “yes”. Household food insufficiency was modeled as a dichotomous variable, women that were food sufficient versus women that were food insufficient. Given the high prevalence of food insecurity in our study population, we again observed an insignificant variation in the household food insufficiency variable, as only 8.4% of the women were found to be food insufficient.

Due to the extremely high rates of food insecurity observed in these communities, we decided to create a Household Food Insecurity Index variable, which is a comprehensive measurement adapted to capture the severity of food insecurity as it applies to our study population. The Household Food Insecurity Index consisted of three categories: 1) women who were from households that were food insufficient, 2) women who skipped taking medication due to hunger, and 3) those who missed doses due to hunger-related side effects from taking their medication. Next, composite scores were generated and calculated for each participant in our sample. Study participants received a composite score of 0, 1, 2, or 3 with 0 being the least food insecure and 3 the most. Cronbach’s alpha was used to determine the reliability of all items included in the household food insecurity index, and showed a reliability coefficient of 0.80, which is regarded as acceptable [41–44].

Potential confounders

As part of the survey questionnaire, participants were also asked “In the past month, have you ever skipped taking your pills because of any of the following reasons: hunger, hunger-related side effects, poor treatment, forgetfulness, stress, clinic too far, no money for transport, etc.”. In the same questionnaire, participants were also asked to estimate travel time, transportation costs, and mode of transportation used to travel to and from the clinic or facility where they received health services. Travel time and transportation costs were modeled as continuous variables while mode of transport was modeled as a dichotomous variable, walking versus bus. Survey questionnaires were pilot tested prior to conducting this study.

Data analysis

Data were analyzed using Stata version 17 (College Station, TX: StataCorp LP). Data analyses were conducted at the descriptive, bivariate, and multivariable levels. Continuous variables are presented as means with standard deviations, and categorical variables are presented as frequencies and percentages. The majority of categorical variables were normally distributed. For continuous variables, the Kolmogorov-Smornov and Shapiro–Wilk tests were conducted to determine whether data was normally distributed. Travel time was not normally distributed, therefore data were transformed to its natural logarithm. Differences in socio-demographic characteristics between women who were overweight/obese versus those who were normal weight were assessed using Pearson’s chi-squared test of significance for categorical variables, and the t-test for continuous variables. Variables that were significantly associated with overweight/obesity at a significance level of 25% were selected and included in multivariable regression models.

The variable “Household Food Insecurity Index” was used as the main exposure variable, having a wider distribution and demonstrating a better fit for the model. Multivariable log-binomial regression models were used to assess the relationship between overweight/obesity and household food insecurity, while controlling for potential confounders in the model. Variables were considered statistically significant when p < 0.05.

Results

The study population consists of 166 women living with HIV in rural communities of Eswatini (Table 1). Of the 166 participants, 44.6% were normal weight, 32.5% were overweight, and 22.9% were obese. A majority of the participants were married/living with a partner (56.6%), with participants mean age of 37 years. Of the 166 participants, 23.5% had no formal education, while 76.5% attended some primary and/or high school education. A striking 54.8% of the participants were unemployed, with 45.2% of the participants reporting being employed full-time or limited to seasonal or part-time employment at local clothing factories and sugarcane fields. Of the 166 women, 51.2% occasionally obtained food and/or financial support from family members (including husbands, partners, and relatives), neighbors, friends, and community members, while 48.8% reported not receiving any form of support.

Table 1 Demographic characteristics of study participants, n = 166a
Full size table

Table 2 presents measures of associations between overweight/obesity and socio-demographic factors. Overweight/obesity was significantly higher among women who reported being in good health compared to those who reported being in poor health (64.7%, p = 0.000). We found significant associations between overweight/obesity and household food insecurity, with prevalence rates being significantly higher among women who experienced food insecurity the least compared to those who experienced it the most (85.7% versus 44.8%, p = 0.003). Similarly, the prevalence of overweight/obesity was higher among women who traveled for shorter periods of time to and from the clinic compared to those who traveled for longer periods of time (54.4%, p = 0.04).

Table 2 Measures of association between overweight/obesity and associated risk factors
Full size table

Similarly, in multivariable adjusted regression models (Table 3), we found significant associations between household food insecurity and overweight/obesity. Women who experienced household food insecurity the most were 0.38 times less likely to be overweight/obese compared to those who experienced household food insecurity the least (ARR: 0.38, 95% CI: 0.2–0.71). In our study population, the risk of overweight/obesity was significantly associated with perceptions of health status. Women who perceived themselves as being in poor health were 42% less likely to be overweight/obese compared to those who perceived themselves as being in good health (ARR: 0.58, 95% CI: 0.39–0.86). We found significant associations between overweight/obesity and alcohol use, with the risk of overweight/obesity nearly 1.5 times higher among women who consumed alcohol compared to those who did not (ARR: 1.49, 95% CI: 1.07–2.05). In addition, women who felt supported by family members were 27% less likely to be overweight/obese as those who did not feel supported by their families (ARR: 0.73, 95% CI: 0.53–0.99).

Table 3 Results of multivariable analysis of the association between overweight/obesity and household food insecurity among women living with HIV in rural Eswatini
Full size table

Discussion

This study examined the prevalence of overweight/obesity and its association with household food insecurity among WLHIV in rural Eswatini. We found significantly higher rates of overweight/obesity among women reporting the lowest levels of food insecurity in our study, suggesting an inverse association between food insecurity and weight gain. Other studies in the region have reported similar findings, where lower rates of overweight/obesity were found among food insecure individuals [17, 18]. In a study conducted among women in Kenya, food insecurity was found to be a significant predictor of overweight/obesity, with higher rates observed among women in urban areas as opposed to those in rural areas [18].

Among studies in sub-Saharan Africa, household food insecurity has been adversely associated with an increased prevalence of multiple metabolic risk factors including overweight, obesity, dyslipidemia, and hypertension [24]. The impact of food insecurity on food choices, dietary intake, and nutritional status has long been recognized [21, 45, 46]. Potential mechanisms explaining the association between food insecurity and increased rates of overweight/obesity in our study may include the following: 1) an increase in consumption of diets comprised of high calorie foods in rural households (e.g. processed grains, fats/oil, and sugars) [1, 24, 27], 2) chronic periods of inadequate dietary intake/hunger combined with compensatory overconsumption of high calorie foods, potentially triggering the thrifty phenotype phenomenon among our study population [47], and 3) changes in dietary patterns as a result of nutrition transition with increased access to and availability of processed/calorie dense foods in these communities [1, 48].

Nearly a third of the women in our study were overweight and almost a quarter were obese. While the prevalence of overweight is comparable to those reported in previous studies, the rates of obesity in our study were slightly higher than those reported among women in the general population of Eswatini [4]. The high rates of overweight/obesity observed among women living with HIV in our study are alarming, particularly due to their association with increased risk of NR-NCDs [2, 9, 10, 24]. Furthermore, our findings show significantly higher rates of overweight/obesity among women who perceived themselves as being in good health. In many SSA cultures, weight gain is traditionally associated with perceptions of wealth and good health. Overweight/obesity is culturally accepted, often deemed desirable, and typically perceived as ‘normal’ (especially among women) [49–51].

In some African countries where HIV/AIDS is highly prevalent, a larger body size is viewed as a sign of good health and thereby associated with being free of HIV infection. In a study conducted among women in South Africa, being overweight/obese was preferred by a more than a third of the women and regarded as indicative of health, while a thinner frame was often associated with a higher likelihood of that person having HIV/AIDS [52]. In another study conducted among female community health workers in South Africa, being overweight was preferred and often associated with dignity, respect, confidence, beauty, and wealth [51]. Similarly in Eswatini, being overweight is often perceived as a sign of wealth and life success [53], though it is unclear whether people are actively gaining weight as a way to achieve societal acceptance and appear healthy (particularly in regard to HIV status). Studies have shown that culture/traditional beliefs are crucial to examine when addressing issues of health and practices related to food and eating patterns, as well as attitudes and perceptions about body weight and disease [49, 51]. Given that cultural body size preferences have been shown to influence nutritional health and disease outcomes, there is a need to investigate this association further in the context of the Eswatini.

We found significant associations between alcohol use and an increased risk of overweight/obesity. Alcohol use has been documented as a widely used means of coping with a range of stressors including economic stress, marital problems, and lack of social support [54–56]. Empirical evidence indicates that the more severe and chronic the stressor, the greater the alcohol consumption [54–56]. In Eswatini, 59% of those who drink regularly consume a homemade traditional brew, commonly known as umcombotsi [57]. Umcombotsi is an inexpensive (approximately $0.25 USD per liter) alcoholic beverage typically served at local drinking spots (shebeens) throughout rural communities of Eswatini. In our previous study of barriers to ART adherence, women reported excess alcohol use as a common strategy for coping with stress and hunger [12]. The current study findings are parallel to other studies that have documented associations between alcohol consumption and overweight/obesity among countries in SSA [58]. High levels of food insecurity and stress combined with easily available alcohol create enormous problems in communities already burdened by poverty and chronic diseases.

To our knowledge, this is the first study to investigate the prevalence of overweight/obesity and its association with household food insecurity among WLHIV in Eswatini. In addition, our study generated important data regarding variations in prevalence by socio-demographic factors, thereby providing us with a suggestive evidence of potential risk factors of overweight/obesity in this population. Our study may be limited due to minimal sample size, which may have led to an underestimation of the reported prevalence rates and degree of association between household food insecurity and overweight/obesity. In addition, this study relies on self-reported data which may be susceptible to human error and may be influenced by recall bias. In order to minimize this potential limitation, we used an objective measurement of BMI that was computed from weight and height of participants that were directly measured rather than reported. Despite the limitations, this study provides important information on the prevalence of overweight/obesity and associated risk factors among WLHIV in Eswatini, who are currently one of Eswatini’s most vulnerable sub-populations to infections and poor health outcomes. In addition, our study generated important data regarding variations in overweight/obesity prevalence by food insecurity status, thereby providing us with a glimpse of potential risk factors of overweight/obesity in this population.

Conclusions

The prevalence of overweight/obesity among women in poverty stricken communities may pose significant challenges for nutritional health and HIV management. The direct impact of food insecurity on dietary intake and poor health outcomes has long been recognized. Food insecurity not only impacts the ability to consume adequate nutrients, it also increases a person’s risk of poor nutritional health and susceptibility to infections including HIV. In Eswatini, there has been a drastic increase in overweight and obesity rates over the past years, with women more overweight/obese than men [59]. Overweight and obesity have been found to be significant predictors of numerous NR-NCDs including type 2 diabetes mellitus, hypertension, cardiovascular disease, and certain cancers [1, 60, 61]. The increasing rates of overweight/obesity among WLHIV in rural households are disconcerting as they suggest an increased risk of NR-NCDs and further exacerbating challenges experienced by women in these communities [60, 61]. With an increasing prevalence of overweight and obesity in food insecure households, there is a need to re-evaluate current strategies and develop multi-level targeted interventions that include prevention of excessive weight gain among women, particularly those living with HIV.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the Figshare repository, https://doi.org/10.6084/m9.figshare.12174273

Abbreviations

SSA:

Sub-Saharan Africa

NR-NCDs:

Nutrition-Related Noncommunicable Diseases

HIV:

Human Immunodeficiency Virus

WLHIV:

Women Living with HIV

FIS:

Food Insecurity

ART:

Antiretroviral Therapy

BMI:

Body Mass Index

Kg:

Kilograms

M:

Meters

HFIAS:

Household Food Insecurity Access Scale

ARR:

Adjusted Risk Ratios

CI:

Confidence Interval

References

  1. Steyn NP, Mchiza ZJ. Obesity and the nutrition transition in Sub-Saharan Africa. Ann N Y Acad Sci. 2014;1311(1):88–101.

    CAS  PubMed  Google Scholar 

  2. Lake JE. The Fat of the Matter: Obesity and Visceral Adiposity in Treated HIV Infection. Curr HIV/AIDS Rep. 2017;14(6):211–9.

    PubMed  PubMed Central  Google Scholar 

  3. Amuna P, Zotor FB. Epidemiological and nutrition transition in developing countries: impact on human health and development: The epidemiological and nutrition transition in developing countries: evolving trends and their impact in public health and human development. Proc Nutr Soc. 2008;67(1):82–90.

    PubMed  Google Scholar 

  4. Neupane S, Prakash KC, Doku DT. Overweight and obesity among women analysis of demographic and health survey data from 32 Sub-Saharan African Countries. BMC Public Health. 2016;16:1–9.

    Google Scholar 

  5. AVERT. HIV and AIDS in Eswatini. 2019. Available from: https://www.avert.org/professionals/hiv-around-world/sub-saharan-africa/swaziland Accessed February 25, 2022.

  6. Central Statistical Office and UNICEF. Swaziland Multiple Indicator Cluster Survey 2014. Available from: http://www.swazistats.org.sz/images/reports/Multiple%20Indicator%20Cluster%20Survey%202014.pdf. Accessed January 3, 2022.

  7. Peer N. The converging burdens of infectious and non-communicable diseases in rural-to-urban migrant Sub-Saharan African populations: a focus on HIV/AIDS, tuberculosis and cardio-metabolic diseases. Trop Dis Travel Med Vaccines. 2015;1:6.

    PubMed  PubMed Central  Google Scholar 

  8. Heidari-Beni M. Early Life Nutrition and Non Communicable Disease. Adv Exp Med Biol. 2019;1121:33–40.

    PubMed  Google Scholar 

  9. Musumari P, Techasrivichien T, Suguimoto P, Ndarabu A, Mboyo A, Ngasia B, et al. Undernutrition, Food Insecurity, and Antiretroviral Outcomes: An Overview of Evidence from sub-Saharan Africa. Health HIV Infected People Food Nutr Lifestyle Antiretrovir Drugs. 2015;2:181–201.

    Google Scholar 

  10. Rogers BG, Kegler MC, Berg CJ, Haardörfer R, Frederick GT. Understanding the Food Insecurity and Obesity Relationship by Examining Potential Mediators: An Exploratory Analysis. J Hunger Environ Nutr. 2016;11(2):195–209.

    Google Scholar 

  11. Weiser SD, Young SL, Cohen CR, Kushel MB, Tsai AC, Tien PC, et al. Conceptual framework for understanding the bidirectional links between food insecurity and HIV/AIDS. Am J Clin Nutr. 2011;94(6):1729S-1739S.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Becker N, Cordeiro LS, Poudel KC, Sibiya TE, Sayer AG, Sibeko LN. Individual, household, and community level barriers to ART adherence among women in rural Eswatini. Plos One. 2020;15(4):e0231952.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Sirotin N, Hoover DR, Shi Q, Anastos K, Weiser SD. Food insecurity with hunger is associated with obesity among HIV-infected and at risk women in Bronx, NY. PloS One. 2014;9(8):e105957.

    PubMed  PubMed Central  Google Scholar 

  14. Vedovato GM, Surkan PJ, Jones-Smith J, Steeves EA, Han E, Trude AC, et al. Food insecurity, overweight and obesity among low-income African-American families in Baltimore City: associations with food-related perceptions. Public Health Nutr. 2016;19(8):1405–16.

    PubMed  Google Scholar 

  15. Chaput J-P, Gilbert J-A, Tremblay A. Relationship between food insecurity and body composition in Ugandans living in urban Kampala. J Am Diet Assoc. 2007;107(11):1978–82.

    PubMed  Google Scholar 

  16. Hunter-Adams J, Battersby J, Oni T. Food insecurity in relation to obesity in peri-urban Cape Town, South Africa: Implications for diet-related non-communicable disease. Appetite. 2019;137:244–9.

    PubMed  Google Scholar 

  17. Widen EM, Collins SM, Khan H, Biribawa C, Acidri D, Achoko W, et al. Food insecurity, but not HIV-infection status, is associated with adverse changes in body composition during lactation in Ugandan women of mixed HIV status. Am J Clin Nutr. 2017;105(2):361–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Keino S, Plasqui G, van den Borne B. Household food insecurity access a predictor of overweight and underweight among Kenyan women. Agric Food Secur. 2014;3(1):2. https://doi.org/10.1186/2048-7010-3-2.

    Article  Google Scholar 

  19. Franklin B, Jones A, Love D, Puckett S, Macklin J, White-Means S. Exploring mediators of food insecurity and obesity: a review of recent literature. J Community Health. 2012;37(1):253–64.

    PubMed  PubMed Central  Google Scholar 

  20. Morales ME, Berkowitz SA. The Relationship Between Food Insecurity, Dietary Patterns, and Obesity. Curr Nutr Rep. 2016;5(1):54–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Smith TM, Colón-Ramos U, Pinard CA, Yaroch AL. Household food insecurity as a determinant of overweight and obesity among low-income Hispanic subgroups: Data from the 2011–2012 California Health Interview Survey. Appetite. 2016;97:37–42.

    PubMed  Google Scholar 

  22. Farrell P, Negin J, Awoke M, Thow AM, Taua M, Faumuina T, et al. Associations between sociodemographic and behaviour factors, and dietary risk factors for overweight and obesity, in Samoan women. Appetite. 2019;134:155–61.

    PubMed  Google Scholar 

  23. Ryan-Ibarra S, Sanchez-Vaznaugh EV, Leung C, Induni M. The relationship between food insecurity and overweight/obesity differs by birthplace and length of US residence. Public Health Nutr. 2017;20(4):671–7.

    PubMed  Google Scholar 

  24. Nkambule SJ, Moodley I, Kuupiel D, Mashamba-Thompson TP. Association between food insecurity and key metabolic risk factors for diet-sensitive non-communicable diseases in sub-Saharan Africa: a systematic review and meta-analysis. Sci Rep. 2021;11:5178.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Moore S, Hall JN, Harper S, Lynch JW. Global and National Socioeconomic Disparities in Obesity, Overweight, and Underweight Status. J Obes. 2010;2010:514674.

    PubMed  PubMed Central  Google Scholar 

  26. Dinsa GD, Goryakin Y, Fumagalli E, Suhrcke M. Obesity and socioeconomic status in developing countries: a systematic review. Obes Rev Off J Int Assoc Study Obes. 2012;13(11):1067–79.

    CAS  Google Scholar 

  27. Farrell P, Thow AM, Abimbola S, Faruqui N, Negin J. How food insecurity could lead to obesity in LMICs: When not enough is too much: a realist review of how food insecurity could lead to obesity in low- and middle-income countries. Health Promot Int. 2018;33(5):812–26.

    PubMed  Google Scholar 

  28. F Mashinya, M Alberts, I Cook, S Ntuli. 2018 Determinants of body mass index by gender in the Dikgale Health and Demographic Surveillance System site, South Africa. Glob Health Action

  29. Bhurosy T, Jeewon R. Overweight and obesity epidemic in developing countries: a problem with diet, physical activity, or socioeconomic status? Scientific World Journal. 2014;2014:964236.

    PubMed  PubMed Central  Google Scholar 

  30. Monteiro CA, Moura EC, Conde WL, Popkin BM. Socioeconomic status and obesity in adult populations of developing countries: a review. Bull World Health Organ. 2004;82(12):940–6.

    PubMed  Google Scholar 

  31. Jones-Smith JC, Gordon-Larsen P, Siddiqi A, Popkin BM. Is the burden of overweight shifting to the poor across the globe? Time trends among women in 39 low- and middle-income countries (1991-2008). Int J Obes 2005. 2012;36(8):1114–20.

    CAS  Google Scholar 

  32. Mowafi M, Khadr Z, Kawachi I, Subramanian SV, Hill A, Bennett GG. Socioeconomic status and obesity in Cairo, Egypt: a heavy burden for all. J Epidemiol Glob Health. 2014;4(1):13–21.

    PubMed  Google Scholar 

  33. Alaba O, Chola L. Socioeconomic inequalities in adult obesity prevalence in South Africa: a decomposition analysis. Int J Environ Res Public Health. 2014;11(3):3387–406.

    PubMed  PubMed Central  Google Scholar 

  34. Ramjee G, Daniels B. Women and HIV in sub-Saharan Africa. AIDS Res Ther. 2013;10(1):1.

    Google Scholar 

  35. Reza A, Breiding MJ, Gulaid J, Mercy JA, Blanton C, Mthethwa Z, et al. Sexual violence and its health consequences for female children in Swaziland: a cluster survey study. The Lancet. 2009;373(9679):1966–72.

    Google Scholar 

  36. PEPFAR: US President Emergency Plan For AIDS Relief. Swaziland Country Operational Plan (COP) 2017 Strategic Direction Summary. 2017. Available from: https://www.pepfar.gov/documents/organization/273039.pdf. Accessed June 3, 2021.

  37. Becker N, Poudel KC, Cordeiro LS, Sayer AG, Sibiya TE, Sibeko LN. A quantitative analysis of food insecurity and other barriers associated with ART nonadherence among women in rural communities of Eswatini. Plos one. 2021;16(8):e0256277.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Coates J, Swindale A, Bilinsky P. Household Food Insecurity Access Scale (HFIAS) for Measurement of Household Food Access: Indicator Guide. Washington, D.C.: Food and Nutrition Technical Assistance Project; 2007.

    Google Scholar 

  39. Mannheimer S, Mukherjee R, Hirschhorn L, Dougherty J, Celano S, Ciccarone D, et al. The CASE adherence index: A novel method for measuring adherence to antiretroviral therapy. AIDS Care. 2006;18(7):853–61.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. CDC. All About Adult BMI. Centers for Disease Control and Prevention. Available from: https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html. Accessed October 5, 2021.

  41. Punch KF, Oancea A. Introduction to research methods in education. Sage; 2014.

  42. Na M, Gross AL, Wu LSF, Caswell BL, Talegawkar SA, Palmer AC. Internal validity of the Food Access Survey Tool in assessing household food insecurity in rural Zambia. Food Secur. 2016;8(3):679–88.

    Google Scholar 

  43. Sethi V, Maitra C, Avula R, Unisa S, Bhalla S. Internal validity and reliability of experience-based household food insecurity scales in Indian settings. Agric Food Secur. 2017;6(1):1–17.

    Google Scholar 

  44. Mohammadi F, Omidvar N, Houshiar-Rad A, Khoshfetrat M-R, Abdollahi M, Mehrabi Y. Validity of an adapted Household Food Insecurity Access Scale in urban households in Iran. Public Health Nutr. 2012;15(1):149–57.

    PubMed  Google Scholar 

  45. Mello JA, Gans KM, Risica PM, Kirtania U, Strolla LO, Fournier L. How is food insecurity associated with dietary behaviors? An analysis with low income, ethnically diverse participants in a nutrition intervention study. J Am Diet Assoc. 2010;110(12):1906–11.

    PubMed  PubMed Central  Google Scholar 

  46. Morales ME, Berkowitz SA. The Relationship Between Food Insecurity, Dietary Patterns, and Obesity. Curr Nutr Rep. 2016;5(1):54–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Smith CJ, Ryckman KK. Epigenetic and developmental influences on the risk of obesity, diabetes, and metabolic syndrome. Diabetes Metab Syndr Obes Targets Ther. 2015;29(8):295–302.

    Google Scholar 

  48. Cobb LK, Appel LJ, Franco M, Jones-Smith JC, Nur A, Anderson CAM. The relationship of the local food environment with obesity: A systematic review of methods, study quality, and results. Obesity. 2015;23(7):1331–44.

    PubMed  Google Scholar 

  49. Micklesfield LK, Lambert EV, Hume DJ, Chantler S, Pienaar PR, Dickie K, et al. Socio-cultural, environmental and behavioural determinants of obesity in black South African women. Cardiovasc J Afr. 2013;24(9):369–75.

    PubMed  PubMed Central  Google Scholar 

  50. Okop KJ, Mukumbang FC, Mathole T, Levitt N, Puoane T. Perceptions of body size, obesity threat and the willingness to lose weight among black South African adults: a qualitative study. BMC Public Health. 2016;16:365.

    PubMed  PubMed Central  Google Scholar 

  51. Puoane T, Fourie J, Shapiro M, Rosling L, Tshaka N, Oelefse A. Big is beautiful An exploration with urban black community health workers in a South African Township. South Afr J Clin Nutr. 2005;18:6–15.

    Google Scholar 

  52. Matoti-Mvalo T, Puoane T. Perceptions of body size and its association with HIV/AIDS. South Afr J Clin Nutr. 2011;24(1):40–5.

    Google Scholar 

  53. Kgaphola M, Viljoen A. Food habits of rural Swazi households: 1939–1999 Part 1: Technological influences on Swazi food habits. J Fam Ecol Consum Sci Tydskr Vir Gesinsekologie En Verbruikerswetenskappe 2010;28.

  54. Mulia N, Ye Y, Zemore SE, Greenfield TK. Social disadvantage, stress, and alcohol use among Black, Hispanic, and White Americans: Findings from the 2005 US National Alcohol Survey. J Stud Alcohol Drugs. 2008;69(6):824–33.

    PubMed  PubMed Central  Google Scholar 

  55. Veenstra MY, Lemmens PH, Friesema IH, Tan FE, Garretsen HF, Knottnerus JA, et al. Coping style mediates impact of stress on alcohol use: a prospective population-based study. Addiction. 2007;102(12):1890–8.

    PubMed  Google Scholar 

  56. Liu S, Wang M, Zhan Y, Shi J. Daily work stress and alcohol use: Testing the cross-level moderation effects of neuroticism and job involvement. Pers Psychol. 2009;62(3):575–97.

    Google Scholar 

  57. World Health Organization. Global status report on alcohol and health 2018. Available from: https://apps.who.int/iris/bitstream/handle/10665/274603/9789241565639-eng.pdf. Accessed March 6, 2019.

  58. Agbeko MP, Akwasi K-K, Andrews DA, Gifty OB. Predictors of Overweight and Obesity Among Women in Ghana. Open Obes J. 2013;5(1).

  59. The Ministry of Health E. Noncommunicable Disease Risk Factor Surveillance Report. Available from: https://www.who.int/ncds/surveillance/steps/Swaziland_2014_STEPS_Report.pdf. Accessed April 5, 2019.

  60. Gbadamosi MA, Tlou B. Modifiable risk factors associated with non-communicable diseases among adult outpatients in Manzini, Swaziland: a cross-sectional study. BMC Public Health. 2020;20(1):1–12.

    Google Scholar 

  61. Gbadamosi MA, Tlou B. Prevalence of abnormal glucose metabolism among adults attending an outpatient department at a tertiary referral hospital in Swaziland: a cross-sectional study. BMC Public Health. 2020;20(1):392.

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank the women who participated in this study, the local research assistants for their invaluable assistance in collecting data, and collaborative partners (Eswatini Ministry of Health, University of Eswatini, and the Eswatini National AIDS Program) and staff of participating health facilities for their assistance in the implementation of this study. We would like to extend our gratitude to the Graduate School and the School of Public Health and Health Sciences at the University of Massachusetts Amherst and the Center for Research on Families for their assistance.

Funding

The study received financial assistance from the University of Massachusetts (UMass) to help support data collection in Eswatini: the UMass Graduate School (Dissertation Research and Fieldwork Grants), the UMass School of Public Health and Health Sciences (Dean’s International Travel Research Award and PhD Summer Fellowship), and the UMass Centre for Research on Families (Dissertation Research Award). The funders had no role in study design, data collection and analysis, interpretation of data, and in writing the manuscript. This publication was supported by grant T32 MH19105 from the National Institutes of Mental Health of the U.S. Public Health Service.

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Authors and Affiliations

  1. Department of Nutrition, University of Massachusetts, Amherst, USA

    Nozipho Becker & Lindiwe N. Sibeko

  2. Department of Food and Nutrition Sciences, University of Eswatini, Luyengo, Kingdom of Eswatini

    Nozipho Becker & Andile Mkhonta

  3. Center for AIDS Prevention Studies, Division of Prevention Science, University of California, San Francisco, USA

    Nozipho Becker

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  1. Nozipho Becker
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  3. Lindiwe N. Sibeko
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Contributions

NB contributed to the conception or design of the study, material preparation, data collection, analysis, and writing of the manuscript. AM contributed in study set-up and drafted sections of the manuscript. Supervision was provided by LNS who also substantively reviewed the different sections of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Nozipho Becker.

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Ethics approval and consent to participate

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by University of Massachusetts Amherst Institutional Review Board and the Eswatini National Health Research Review Board. Permission to conduct the study was also obtained from the Eswatini Ministry of Health and participating health facilities. Written informed consent was obtained from all individual participants included in the study.

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The authors declare that they have no competing interests.

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Becker, N., Mkhonta, A. & Sibeko, L.N. The prevalence of overweight/obesity and its association with household food insecurity among women living with HIV in rural Eswatini. BMC Public Health 22, 629 (2022). https://doi.org/10.1186/s12889-022-13036-9

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