Obesity is multifaceted and complex, driven largely by factors associated with obesogenic urban environments [1]. Within these settings, the poor seem to have a greater burden of obesitycompared with the more affluent [2]. Recent evidence demonstrates that the prevalence of obesity has doubled since 1980 and currently affects more than 604 million adults globally [3]. These data indicate a trend for obesity to continue increasing, especially in women living in low- and middle-income countries. The estimates of obesity are higher in north and southern Africa than the global prevalence of obesity [4], with a recent study demonstrating that the increase in severe obesity from 1975 to 2014 in South African women was higher than those of more affluent countries such as France and the United Kingdom [5]. These trends in obesity are worrying for African populations, particularly as obesity increases the risk of associated non-communicable chronic diseases and certain types of cancers [6], in addition to lowering life expectancy by increasing the risk of early mortality [7]. Being obese is also associated with lower health-related quality of life and functionality, and is especially important in the context of an increasing ageing population with excess fat accumulation [8].

In the sub-Saharan African region, it is black South African women who are the most vulnerable to overweight and obesity [9]. The underlying causes of the excess fat accumulation, particularly in the visceral region of ageing women are uncertain, however an increased risk of cardiometabolic diseases has been observed [10], in addition to an associated lower physical activity energy expenditure in older subjects compared with younger subjects [11] . In the South African setting where disparities are still evident, socioeconomic status (SES) may also have a role in the weight gain of African women. Data show that black South African women are generally poorer than other ethnic groups in the country and have limited access to adequate healthcare [12]. Moreover, previous cross-sectional studies conducted in South Africa [13–15] and other countries in the sub-Saharan African region [16, 17] have observed a positive association between higher body mass index (BMI) and improved SES. In addition, the contribution of SES and behaviours such as increased sitting time and physical inactivity on adiposity in high-income countries are well documented [18, 19], however evidence is limited on how these factors mediate and influence anthropometric changes in African populations. Therefore, the aims of this study were two-fold: (1) to determine whether SES correlates with anthropometry (both at baseline and at 10 year follow-up); and (2) to determine whether the interaction of SES with anthropometry is mediated by either moderate-vigorous physical activity (MVPA) or sitting time by using structural equation modelling (SEM).

The purpose of this longitudinal study was to determine the extent to which physical activity or sitting time mediate the association between SES and changes in BMI and central adiposity. The obesity trends observed in this study population are consistent with changes in adiposity in African women living in other sub-Saharan African countries [4]. This study confirms previous reports of increases in adiposity over time in African women, and shows how household asset derived SES influences these changes. We have shown that SES is associated with lower MVPA, higher sitting time, and consequently higher changes in BMI, suggesting that this cohort of African women is still experiencing some degree of economic transition. The results demonstrating the direct and indirect effects of SES and physical activity measures on changes in adiposity are the first from an African study, and could only be uncovered using structural equation modelling. Public health initiatives should be made aware of these study findings, particularly as obesity continues to increase with economic improvement in the sub-Saharan African region.

Research from South Africa [13–15] and other sub-Saharan African countries [16, 17] have shown that SES is positively associated with BMI. A country-wide demographic study in South Africa also showed that in all ethnic groups, men and women with some form of schooling have higher BMI values than those who have not attended school [29]. The findings of the present study confirm the current evidence, suggesting that adiposity increases with economic growth. In contrast, existing work from high-income countries shows that SES is inversely related with health outcomes [30, 31], while in non-African developing countries the relationship between SES and BMI does not appear to be constant [32]. In a recent study of young adult black South African women, SES was observed to have a direct effect on BMI in the urban population but not in the rural population [33]. These data support the phenomenon of within-country variation in the impact of SES on body adiposity, and can further vary according to region-specific sociodemographic context and geographic location [34]. Given the well-known nutritional and epidemiological transitions currently occurring in South Africa [35], our finding showing that SES was associated with lower change in MVPA is not surprising and is consistent with evidence from cross sectional [19, 33] and longitudinal studies [36, 37]. In rural South African populations, SES is positively associated with physical activity in adolescents [38] but not in adult women [33]. The urban-rural variation in socioeconomic status could explain the reason for the lack of association between SES and physical activity in rural dwelling women [33].

Consistent with other studies of African women, our data shows that urban dwelling African women have a high level of physical activity [38–40]. These studies show that rural dwelling African women have higher amounts of MVPA compared with urban dwellers. The transition to urban hubs results in acquiring comparatively less energy-demanding jobs than in the rural settings [41], and this may be another reason for the greater difference in volume of physical activity observed in urban African women [33]. Women in urban settings sit for longer periods as a consequence of less physically demanding work, and this could explain the indirect positive effect between baseline sitting and change in BMI and central fat demonstrated in the present study. Interestingly, these effects were mediated by greater increases in sitting time. Previous studies of the cohort in the present study have shown that high sitting is associated with obesity and associated cardiometabolic diseases [42]. The literature indicates an increasing pattern of obesity with continuing urbanisation in African populations [4]. Public health interventions can address the problem by targeting sedentary behaviour, particularly during travel and occupation time. The recent work by Ekelund et al. for example [18], demonstrates that reduced sitting time is associated with lower risk for all-cause mortality by improving cardiovascular health.

Baseline MVPA was shown to have a direct negative effect on change in central fat, which is consistent with other studies [43], and suggests that physical activity has a protective effect against excess fat accumulation. Our findings also reveals an indirect positive effect between baseline MVPA and measures of change in adiposity, driven by the direct negative effect between baseline MVPA and change in MVPA. This suggests that change in MVPA may a potential confounder as this study population ages, possibly explained by the continuous rural-urban shift as noted in a recent of younger adult African women [33]. We agree with this explanation, however the literature also suggests that eating behaviour and other potential correlates of obesity can change during the transition period [32], emphasising the need for additional investigation of behaviour in the current study population. Further, evidence demonstrates that in spite of transitioning populations obtaining sufficient levels of weekly physical activity, obesity levels continue to increase [44]. In the current study, the prevalence of obesity and central fat increased significantly in the study population from baseline to 10-year follow-up, by 15.2% and 18% respectively, however, the weekly MVPA was high, 50 mins./day at baseline and 34.3 mins./day at follow-up. In the context of a growing population of ageing African women, it is therefore paramount for policy makers to consider incorporating other forms of behavioural modification such as lowering caloric consumption to decrease weight gain.

The SEM approach used in this study has a number of strengths, particularly in understanding the increasing risk of obesity in African women. SEM has been used widely in cross-sectional and longitudinal studies, and despite being seldom used in epidemiological research this approach has applications in path analysis [45]. Sample size is the main limitation related to the SEM approach, and as evidence recommends a minimum of 200 observations, this was not a concern [46]. In this longitudinal study, SEM enabled the measurement of direct, indirect, and total effects, in addition to interpreting the underlying pathways of increasing body composition by detecting or removing the possible mediators involved in the accumulation of fat in women over a 10-year follow-up period. In this study we have therefore observed novel and scientifically plausible pathways which previous traditional multivariable regression analyses of this study population have not uncovered [20]. In addition, this study has highlighted the direct and indirect effects in the relationship between SES and physical activity determinants of change in adiposity in African women [20, 42].

The main limitation of this study was that measurements were made only at baseline and 10 years later due to limited resources, however the 10-year follow-up period did allow us to observe the long term influence of baseline determinants and changes in appropriate variables on body anthropometry in an African population with high obesity risk. This study did not control for eating behaviour as data were not available, however this data are currently being collected with the aim of understanding the role of caloric intake in obesity in African women. In addition, future studies should collect data on other potential behavioural predictors of adiposity. The physical activity measures obtained in the present study are based on the self-reported and validated global physical activity questionnaire [25]. Despite the methodological differences, our findings are similar to studies using objectively measured physical activity [43]. Better methods such as MRI can provide more definitive data on adiposity compared with BMI, however, it is still acknowledged to be one of the simplest proxy indicators of fat and is widely used in epidemiological studies [4, 5].

In conclusion, this study demonstrates that the physical activity profile of urban African women is reasonable; however the threat of obesity is high and likely to continue increasing with advancing age. Changes in BMI and central fat can be minimised by maintaining or increasing energy expenditure through physical activity, in addition to limiting the negative impact of sedentary behaviour. The influence of other behavioural determinants should however also be considered in any future initiatives to address obesity in this vulnerable community of ageing African women.