The international comparisons described here demonstrate site-specific negative associations at both the individual and group level between activity captured by accelerometry and measures adiposity. While the individual-level associations are small in magnitude, there is moderate consistency across groups with statistically significant associations being found among men, with the exception of South Africa, among the women, however, associations did not achieve significance. Quantitatively these associations were small in magnitude, as one might expect for measurements of a fairly short time sample for habitual physical activity. It should be noted, however, that four days of activity monitoring has been shown to be sufficient to capture typical patterns among adults . The strengths of the observed associations are similar to those previously reported using data nationally representative for the United States [26, 27].
In general ecological associations should be interpreted as a permissive construct, i.e., if they are absent then the hypothesis being tested is unlikely to be true. In this study, therefore, group level associations support the hypothesis of a pathway from activity to obesity: mean physical activity was lowest in the groups with the highest mean BMIs.
While ecological comparisons may provide a quantitative view of associations between adiposity and measures of physical activity in the broadest sense, it is the non-quantifiable factors that provide the context for those associations. According to self-report, there were relatively minor differences between men or women across the five sites with regard to amount of time spent in travel or in recreational activities. There were, however, stark differences in reported work-related MVPA, with both men and women in Ghana reporting much higher median levels than any of the other sites. For women in METS, there is an almost two-fold difference in measured MVPA and three-fold differences in self-reported MVPA between the least active and the most active cohorts and part of this difference is likely due to types of primary employment within each site. The very low MVPA levels and, possibly, the very high mean BMI observed among the US women may well be related to the fact that they report the lowest levels of manual labor with most of their employment taking place in the healthcare, service representative and education fields (76% of the cohort are engaged in these occupations). In contrast, among Ghanaian women who have both the highest measured MVPA and lowest mean BMI, 90% report being involved in manual labor, primarily trading (40%) and agriculture (21%). Among the other three cohorts of women, the measured MVPA differed very little and the levels of adiposity also were not dramatically different. In both South Africa and Jamaica, the women were overwhelmingly engaged in routine service occupations and trading (>50% in each site), while among the Seychellois, there was a much higher proportion of clerical and professional occupations reported (~48%).
The straightforward explanation that differences in activity and adiposity may be primarily due to differences in occupation, however, does not hold true for the men. Jamaican men have the lowest levels of MVPA, the lowest overall physical activity as measured by counts per minute and the second lowest work-related self-reported MVPA, and yet they are very lean. Moreover, among Jamaican men at least one-third of the cohort was reportedly engaged in the construction industry. In contrast, men in the US have higher objectively measured MVPA, higher work-related MVPA, with a comparable proportion in manual labor occupations, yet are much more obese. Among the male cohorts, there are instances where the data are consistent across domains, i.e., Ghanaian men are lean and have relatively high levels of both objectively measured MVPA and self-reported MVPA; about one-quarter of the cohort works as subsistence farmers. The interplay between physical activity, adiposity, occupation and environment is clearly complex and undoubtedly influenced by other unexplored contextual factors.
Although associations between physical activity and BMI were observed in this study as well as in others [28, 29], the design prevents any assumption of causality. Other studies conducted over the last 5 to 10 years provide a body of data which suggests that reduction in physical activity has a minor or non-existent role in the etiology of the contemporary obesity epidemic [1, 2, 27, 30, 31]. Moreover, reverse causality must also be postulated. Persons with greater body mass may have consequently reduced walking and other activities requiring use of large muscle groups, which is the principal domain captured by accelerometry [32, 33]. Examples of weak to non-existent associations include our previous study of a smaller sample of women from southwest Nigeria and metropolitan Chicago – with measurement of physical activity-related energy expenditure using doubly labeled water; we did not find either individual-level or group-level negative associations between energy expended in activity and BMI or adiposity [27, 34, 35]. A recent meta-analysis of data from cultures with low levels of mechanization likewise recorded similar amounts of energy expended as observed in industrialized societies . Likewise, recent studies of the Hadza people of Tanzania, who subsist by foraging and hunting , and the Tsimane, forager-horticulturalists of Amazonian Bolivia , reported little difference between energy expenditure or physical activity levels by degree of modernization or income. Compared to women in high-income populations, Hadza women had no excess expenditure in daily activity, as assessed by doubly labeled water, yet had lower BMIs . Physical activity levels determined through direct observation and accelerometry in a subsample among the Tsimane showed little variation regardless of degree of “modernization” . Additionally, levels of physical activity were found to be comparable between Europeans and urban Cameroonians when measured using individually calibrated, combined heart rate and motion sensors [37–39], although rural Cameroonians and rural Kenyans recorded higher activity than their urban counterparts .
Although the technology and design sophistication for studies of energy expenditure in free-living individuals has been improving rapidly, to our knowledge, all studies reported to date either included small sample sizes (e.g., N = 19 among the Hadza  and N = 16 urban Cameroonians , or comparisons based on independent studies which did not share a standardized protocol . It also must be appreciated that the different methodologies employed, e.g., doubly labeled water, accelerometry, heart rate monitoring, direct observation or others, measure very different domains of human metabolism and activity; although correlated, physical activity energy expenditure is a different component of physical activity than body movement measured by accelerometry. In addition, the imbalance in energy intake and expenditure can be small in the short run, but result in large life-time excess weight gain, thereby challenging the precision of our measurement tools [40–42].
The need for objective measurement of physical activity in the effort to understand the relationship between movement or physical activity energy expenditure and excess weight gain is obvious when one considers that most previous data were obtained using questionnaires and surveys, which have very limited precision . According to the World Health Organization’s STEPwise Approach to Chronic Disease Risk Factor Surveillance Program, over 83% of men and 75% of women in 22 African countries met the organization’s physical activity recommendations . Although the countries included and the metrics used are not identical, overall in our five cohorts only 56% of the men and 25% of the women recorded 30 minutes/day or more of MVPA in 1-minute bouts on at least 4 days of the measurement period; a much smaller percentage recorded the 30 minutes/day of MVPA in 10-minute bouts (39% and 14% for men and women, respectively). The countries surveyed as part of the STEPwise program may not be directly compared to ours because only the Seychelles was included in both studies. In the Seychelles, however, we found only 12% of our cohort met the recommended ≥30 minutes/day of MVPA in 10-minute bouts where as the STEPwise figure was >81% . Using the WHO’s survey data to understand the association between activity and obesity would not be useful, at least among African populations.