Introduction

Obesity (body mass index greater than or equal to 30kg/m2), an indicator of excessive fat accumulation in the body tissues, is a growing global problem of public health concern [1, 2]. Obesity is an illness that requires deliberate policies and interventions to address it to prevent premature deaths among the world’s population [2]. The available data suggest that since 1975, the global burden of obesity has more than tripled [3]. The data also suggest that no country has experienced a decline in obesity prevalence over this period. Therefore, it is unsurprising that in 2000, the World Health Organisation (WHO) declared obesity a pandemic, which informed the development of a global action plan to combat it [4]. Further evidence suggests that it is more severe among women of reproductive age than men and in urban settings than rural [3].

Obesity is spreading very fast in developing countries and has reached world record levels in some of them [5]. In Africa, the obesity prevalence among women of reproductive age ranged from 6.5 to 50.7% [6]. The problem is most severe among urban women relative to rural women [7]. Similarly, a recent analysis [2] using urban data from 24 African countries, spanning almost three decades, showed that all the countries included in the study experienced a substantial increase in obesity among women of reproductive age. Indeed, a country such as Ghana recorded 65% increase in obesity during the study period [2]. Other studies also observed alarming trends in obesity among women of reproductive age in the African region [8, 9]. There is a need for deliberate policies by governments to address the problem. However, it appears there is lack of policy prioritisation regarding obesity in Africa. This may be the case because many policymakers are yet to appreciate the seriousness of the problem. Therefore, it is critical to provide policymakers and other stakeholders with evidence of the seriousness of the problem and its potential drivers.

The consequences of obesity on population health are enormous. It is associated with an increased risk of cardiovascular diseases (mainly heart disease and stroke), diabetes, musculoskeletal disorders, and some cancers, including but not limited to endometrial, breast, ovarian, prostate, liver, gallbladder, kidney, and colon [10]. An analysis of recent data suggests that obesity is linked to 13 different cancers [11]. Also, the effect of obesity on the incidence of gestational diabetes, pre-eclampsia, high risk of miscarriage/stillbirth, and congenital anomalies is well documented [12–14]. Pregnant women who are obese have higher chances of heart disease, hypertension, and type 2 diabetes [15]. The link between women obesity and future obesity in their children has also been observed [16].

Similarly, the extant literature suggests a strong link between obesity and high mortality rate. An analysis of global data shows that 2.8 million people die annually due to obesity [17], while 35.8 million disability-adjusted life years (DALYs) are attributed to elevated body mass index (BMI) [15]. The adverse effects of obesity on population health, as outlined above, calls for a more detailed analysis to understand the determinants of the problem among women of reproductive age.

Previous research suggests that social determinants of health are key drivers of the rising obesity in urban Africa [18, 19]. According to the WHO commission, "Social determinants of health (SDH) are the conditions in which people are born, grow, live, work and age, and the wider set of forces and systems shaping the conditions of daily life" [3]. The SDH includes socioeconomic status, education, literacy, neighborhood and physical environment, employment, food consumption, place of residence and social support networks, and access to health care. The literature on the effects of socioeconomic status, education, and employment status, among others, abound [20]. However, the impact varies between low- and high-income countries. While obesity is a significant issue among the rich in low-income countries, it is high among the poor in high-income countries [21].

Furthermore, obesity was more prevalent among highly educated women than those without formal education in low-income countries [22]. Women who are formally employed have increased odds of obesity compared to those who are not employed, which vary by educational attainment [23]. This could be attributed to increased income and behavioral changes related to the time allocated to physical activity. In addition, the existing literature suggests a link between urbanization, nutritional transition, and the high prevalence of obesity among women [24]. There have been increasing changes in food consumption, whereby urban dwellers now consume more processed and fast foods and sugary beverages, with consequential adverse effects on obesity outcomes [24, 25].

Although our previous analysis suggests that obesity among women of reproductive age has been rising rapidly in urban Ghana in the past decades [2], there is limited knowledge on the key SDH driving the surge. The present study intends to fill this gap by undertaking a comprehensive analysis of obesity prevalence by various SDH, and the effects of the SDH on the rising obesity in urban Ghana, drawing on existing data sources. This type of analysis is needed to provide detailed and nuanced findings for better decision-making to inform policy and program interventions to address the obesity challenges in urban Ghana. The present study examined the effects of SDH on obesity among women of reproductive age in urban Ghana using existing data.

Materials and methods

Results

Background characteristics of the study sample

Table 1 presents the characteristics of the study sample. The average age of study participants was 31 years (30.85±6.29), while the average height was 1.59m (1.59±0.06). Majority (59%) of the women had secondary school education, while only 6% had tertiary/higher education. This was similar to the partner education level where 59% had secondary education. Similarly, 52% of the women had clerical/sales/services as their main occupation. However, the dominant occupation of their partners was manual work (45%). The results also suggested that over 40% indicated they consumed fruits (42%) and vegetables (45%) for 4 or more days in the past 7 days.

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Table 1. Characteristics of the sample (n = 1204).

https://doi.org/10.1371/journal.pgph.0001442.t001

Table 2 shows the prevalence of obesity by various SDH. The results showed that 40% (95% confidence interval (CI) = 25.4, 57.0) of women who had higher education were obese, compared to only 14.4% (95% CI = 8.6, 23.0) of those with no formal education. Also, 36.7% (95% CI = 25.6, 49.3) of women whose partners had higher education were obese. The prevalence of obesity was 28.8% (95% CI = 24.1, 34.0) among women living in rich households compared to 5.7% (95% CI = 2.4, 13.0) of those in poor households. Further, 33.4% (95% CI = 18.5, 19.3) of women who occupied managerial positions were obese. Conversely, only 1.8% (95% CI = 0.4, 7.8) of those whose occupation was agriculture suffered from obesity. Women whose partners held managerial positions suffered more from obesity than those whose partners were agricultural workers (33.6 vs. 7.2%). All the above results were statistically significant.

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Table 2. Prevalence of obesity by social determinants of health (n = 1204).

https://doi.org/10.1371/journal.pgph.0001442.t002

Table 3 presents the effects of SDH on obesity among women. The results showed that compared to women in the poor households, those in the rich households were 3.4 times (95% CI = 1.31, 8.97) more likely to suffer from obesity. Women whose main occupation was agriculture were 81% (aOR = 0.19; 95% CI = 0.034, 0.99) less likely to suffer from obesity than those with no occupation. Similarly, women whose partners’ occupation was agriculture worker had 71% (aOR = 0.39; 95% CI = 0.15, 0.99) reduced odds of becoming obese compared to those whose partners were manual workers. Partners attaining primary education had a moderate protective effect on obesity among women (aOR = 0.34; 95%CI = 0.11, 1.08). Compared to women who did not listen to radio at all, those who listened to radio less than once a week or at least once a week had increased odds of obesity (aOR = 2.64, 95% CI = 1.26, 5.54). A biological variable such as women’s age was associated with increased odds of obesity (aOR = 1.09; 95% CI = 1.06, 1.13).

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Table 3. Multivariable logistic regression analysis of the association between social determinants of health and women obesity (n = 1204).

https://doi.org/10.1371/journal.pgph.0001442.t003

Discussion

The extant literature shows that social determinants of health (SDH), as captured in the WHO commission on SDH framework, play a critical role in determining obesity and health outcomes [3, 20–23]. In this study, we presented a comprehensive analysis of obesity prevalence by various SDH and their effects on the rising obesity in urban Ghana, using existing data. The results suggest that obesity was three times higher among women with high education relative to those without education (40% vs 14.4%). This is also the case with partner education, where women whose partners were highly educated suffer more from obesity. The findings reflect the results of previous research. Several studies have documented the relationship between the level of education and the high prevalence of obesity [22, 23, 30, 31]. High education appears to place women at an elevated risk of obesity. The negative effect of education on obesity may be because this subgroup is likely to have a higher income, with a consequential impact on lifestyle changes. For example, the extant literature reveals that high-income earners in LMICs practice sedentary lifestyles and consume unhealthy diets [24, 30]. It is essential to point out that while education is a risk factor for obesity in LMICs, it is indeed a protective factor in high-come settings [21]. Thus, the highly educated in high-income countries are less prone to obesity than the less educated.

The analysis of the women’s occupation data reveals that women holding managerial positions had a substantially higher prevalence of obesity than other occupations. The high prevalence may be because of prolonged sitting hours, reduced walkability, increased intake of convenient, highly processed foods, and greater reliance on cars as the primary means of transport [30, 32]. For example, long hours at the office can make it challenging to squeeze in time for exercise [33]. The finding in the present study is consistent with the extant literature. A study undertaken among Korean women showed that obesity prevalence was significantly higher among managers than non-managers [32].

Further, our results suggest that women who engage in agriculture suffer less from obesity compared to the other occupations. This could be attributed to the high physical activity associated with this occupation. This finding is consistent with the multivariable logistic regression results, which revealed that women who engaged in agriculture had an 81% reduced odds of becoming obese than those in other occupations. The low risk associated with agriculture may be linked to agricultural workers consuming their produce rather than relying on high-energy food such as fast food and sugar-sweetened beverages [32].

Similarly, the findings show that the prevalence of obesity among women living in rich households is over five times higher than those in poor households (28.8% vs 5.7%). It implies that wealth is a risk factor for women’s obesity, while poverty is a protective factor. This finding has been corroborated by the multivariable analysis, where women in rich households were over three times more likely to suffer from obesity than those in poor households. The endemicity of obesity in rich households may be due to access to high-energy food and a lack of physical activity. This finding is consistent with the existing literature, whereby several studies have shown that women in rich households suffer more from obesity than those in poor households [34–37]. However, a previous comparative analysis showed some differences between low-and high incomes countries. Indeed, while obesity is a major public health issue among the rich in low-income countries, it is the case among the poor in high-income countries [21]. It may mean that the rich in the high-income countries are more concerned about their weight and therefore live healthy lifestyles.

Conclusions

The study examined the effects of the various social determinants of health on obesity among women of reproductive age in urban Ghana. The results suggest that the different SDH substantially influence women’s obesity. Higher education increases the risk of obesity among women. Women occupying managerial positions are also likely to suffer from obesity. Similarly, living in rich households increases the risk of obesity among women. Interventions to address the rising obesity in urban Ghana should have specific packages targeted at these sub-groups. These may include promoting physical activity, and healthy eating behaviours, which the extant evidence suggests are hardly practised by these sub-groups.

Acknowledgments

We wish to express our profound gratitude to The DHS Program, USA for providing us access to the data. We also wish to acknowledge institutions of respective countries that played critical roles in the data collection process.