We conducted the first systematic review and meta-analysis focusing on a range of biological, behavioural as well as psychosocial factors and their associations with T2DM in Africa. Consistent with other systematic reviews and meta-analyses [95, 127–129], publication outputs have increased over time [130]. The greatest number of studies were from West and East Africa. The present study showed that all body weight indicators (both BMI and central obesity defined), physical activity and psychosocial factors were significantly associated with T2DM with associations of varying strength. Obesity (defined by BMI) was found to have the strongest association with increased odds for T2DM of more than 3-fold that of any other body weight measures including waist circumference.
These general observations are consistent with some [131], but not all [132] prior meta-analyses. Findings from the present study are consistent with the study by Vazquez et al. [131] among populations from Mauritius, USA (including African Americans), Asia, and Europe. They are also mostly consistent with the study by Kodama et al. [132] among European subjects, however that study did suggest a stronger association between waist circumference and diabetes than that between obesity (defined by BMI) and T2DM. Waist circumference is a stronger indicator of intra-abdominal visceral fat than BMI, and closely linked to insulin resistance and hyperinsulinemia [133]. Interestingly, our findings of a stronger association between BMI and T2DM has also been documented in other pathophysiological studies in African using methods such as dual energy X-ray absorptiometry [134, 135]. Studies in South African women suggest that, for the same BMI, African women have less central fat, but greater peripheral fat accumulation than Caucasian women [133–135]. Sumner et al. [136] also show that increasing waist circumference results in less visceral adipose tissue among African-American and African women than Caucasian women. Although these findings were predominantly from studies among women, they may partly explain why the strength of the association between obesity (defined by BMI) and T2DM is stronger in this study than waist circumference.
The independent role of central obesity in insulin resistance in populations of African descent must not be discounted, however. For example, while detailed examination of the overall body weight indicators shows comparatively larger effect size for the relationship between combined BMI indices (BMI-OV, BMI-OV/OB, and BMI-OB) (OR = 2.59) and T2DM compared to the combined central obesity indices (WC and WHR) (OR = 2.24), a strong and independent association between central adiposity and T2DM was evident [137]. This may suggest that either WC or BMI alone could be used as risk factors for T2DM among Africans. The use of a measuring tape alone to assess WC may be appealing in a setting where resources are minimal [138]. A further issue which may have affected our findings in relation to associations between waist circumference and T2DM is the high heterogeneity (I2 = 87) of studies, which could not be explained by the moderation analysis. In addition, although meta-analyses have suggested a stronger association between BMI and diabetes in women than men [131, 139], this could not be assessed in the present study due to too few studies reporting findings separately for females and males.
Our analysis of physical activity indicates an almost two-fold increase in odds of T2DM for those who are inactive. After adjusting for publication bias, the magnitude remained the same. These findings are congruent with previous meta-analyses among populations from China, the USA, and Australia that have explored associations of medium to vigorous physical activity and T2DM [140]. While the present study focused on vigorous physical activity and T2DM, other reviews included alternative physical activity measures such as walking, leisure-time activity, resistance activity, occupational activities, low, moderate and vigorous-intensity activity [141]. These measures are important within the African context since physical activity patterns in Africa are somewhat different from industrialised countries [142]. Low to moderate activities are most prevalent within Africa [142]. Although beyond the scope of this paper, an in-depth comparative examination of these differences is required within the African context.
Psychosocial factors in this study were found to increase the odds of T2DM by more than 2-fold with a combined OR = 2.15. These findings are consistent with various meta-analytic reviews in non-African populations that explored relationships between psychosocial factors and diabetes [143]. A study by Smith et al. [97] in North Americans (includes Whites, African Americans, Hispanic and Chinese), European, Middle-Eastern and Asian populations found that anxiety increased the odds of diabetes by almost one and a half fold, while that of Ali et al. [144] among a population from the USA, Europe (the Netherlands, Finland, and Italy) and Iraq found that depression increased the odds of diabetes by almost one and a half fold. In the present study, however, the small sample size of depression (k = 4), stress (k = 2) and anxiety (k = 2) may have limited power to detect the association with T2DM. As such these findings should be treated as preliminary and interpreted with caution. Again, a fine-grained longitudinal study examining the individual psychosocial risk factors (stress, depression, and anxiety) in the African context is required given evidence of differential associations with T2DM.
Findings of the lifestyle risk factors showed that in this African sample, associations between fruit and vegetable intake, alcohol consumption, and smoking and T2DM were not significant. However, various studies among non-African populations have shown otherwise. A meta-analysis of longitudinal studies among populations from the United States, Japan, United Kingdom, Germany, Israel, and the Scandinavian countries, showed that active smoking is associated with an increased risk of type 2 diabetes [100]. Similarly, a meta-analysis of longitudinal studies among populations from Europe, USA, Australia, Korea and Japan showed a U-shaped relationship between alcohol consumption and diabetes for both men and women, with a greater protective effect of moderate consumption observed for women [145]. The non-significant findings of the present study may be partly due to the simpler definitions used in many African studies. Assessing consumption levels based on a report of “Yes” or “No” is likely to not be precise enough to detect an effect, particularly where the association is not strong, or there is a U-shaped association [145, 146].
Studies on diet quality show that adherence to the appropriate diet can improve insulin sensitivity and glycaemic control. The current study had data on fruit only and vegetable consumption only, which are protective factors for diabetes. However, only two studies presented associations for fruit and vegetable intake combined, and no study had data on consumption of discretionary, typically ultra-processed, unhealthy foods, which are strongly related to higher body weight and diabetes[147, 148]. As such, we were unable to confirm the link between diet and T2DM among the African populations. There is a clear need for further studies (preferably longitudinal) assessing the complex association between diet and the incidence of Type 2 diabetes in Africa [149].
These findings were supported by the adjusted data synthesised by the vote-counting analyses, specifically with regards to the more significant results including all body weight indicators. Most moderation analyses were non-significant except for the combined central obesity indices which were moderated by locality (East and West Africa). However, no other moderator was significant. This implies that the risk of acquiring T2DM is independent of geographical location (urban/rural) and spoken language in Africa.
Strengths and Limitations
There are several limitations associated with this study that should be considered when interpreting the findings. First, only studies published in English were included and thus may under-represent studies predominantly from the Arabic, Portuguese and French-speaking countries in Africa. The use of only unadjusted data may constitute a limitation due to challenges posed by adjusted covariate for systematic reviews and meta-analysis [127]. However, previous systematic reviews and meta-analyses reported non-significant findings between unadjusted bivariate and those adjusted for different covariate [132, 150]. Further studies can also explore moderations using meta-regression. In this study, various diabetes definitions were used among the included studies. However, it is unlikely that these differences in definition would have had any impact on the results as the aim of this study was to determine the associations between the risk factors and T2DM, and not the optimal cut-point for each risk factor [138].
The absence of study quality assessments in this study is another potential limitation. Using a critical appraisal tool for meta-analytic studies exploring risk factors and T2DM have been rare, due to challenges posed by observational studies with diverse methodologies. It is also possible different study qualities from individual studies may affect the association between risk factors and T2DM. For example, the observed association between physical activity and diabetes in Africa may have been influenced by using different measurement approaches as well as other confounders used in individual studies. In particular, the different instruments used may constitute a limitation as in the case of psychosocial factors where no two studies used the same tool. Nevertheless, the influence of unknown residual confounders can also not be ignored in individual studies (particularly the lifestyle risk factors) as this may affect the results. There is an urgent need for quality data, particularly on lifestyle risk factors. In sum, there is urgent need of longitudinal studies with a probability sampling technique to systematically measure both risk factors and T2DM, particularly alcohol, smoking, psychosocial factors, unhealthy food, and a range of relevant risk factors in Africa.
Our study has many strengths which include the systematic nature of the review and the use of comprehensive meta-analytic methods, which have not been used to determine the strength of association between risk factors and T2DM in Africa previously. Finally, the large sample size of the study provides high power and precision in our estimates.