In this comparative study of EE and obesity we observed that while body composition differed dramatically between women living in rural Nigeria and Chicago, the levels of AEE were indistinguishable. As in previous reports (7
), the Nigerian women were significantly shorter, weighed less and had less body fat than their US counterparts. After adjustment for body size and composition, TEE was higher in the Nigerian than the US cohort by 0.53 MJ.d−1
), more than half of which was due to a higher REE; neither AEE nor PAL differed significantly between the cohorts. Mean EE levels were not influenced by parity or season of measurement in either cohort. Unlike many previous studies of EE and adiposity, most of which were smaller in size or based on indirect measurement, there was no meaningful association between measures of EE and BMI or percent body fat in either the Nigerian or the US cohort. Since DLW is insensitive to variation in patterns of activity, it remains possible that intensity, duration or other characteristics of EE may contribute to adiposity differences between these cohorts of women. However, neither PAL nor AEE, as currently conceptualized and measured, appear to be important.
The concept of the epidemiologic or nutrition transition has been widely used to provide a framework for the process of modernization of lifestyle. Although relatively little data exist on physical activity levels using objective measurement, lower EE in more industrialized societies is generally accepted as one of the driving factors in the increase of overweight and obesity in those societies (8
). It seems apparent that as societies become more mechanized the EE associated with occupational activity and the chores of daily living would decrease markedly, and indirect evidence exists does support this notion (8
). It is then reasonable to make the assumption that overall AEE, and by extension TEE, would also be decreased in more industrialized societies. Much of the research in developing countries, however, suggests that this scenario may not accurately reflect reality. Although most of the extant studies did not utilize the DLW technique, there is substantial experience measuring EE in developing countries in order to ascertain energy intake requirements (26
). A comprehensive review of these data concluded that there was no evidence to suggest systematically higher EE in developing countries (27
). The findings presented from this study of women in Nigeria and the US are obviously consistent with this general conclusion. In contrast, Esparza et al (28
) reported dramatically lower TEE and AEE, ie, on the order of 2.1 MJ.d−1
), and much higher adiposity among adult Pima Indians living in southern Arizona compared to Pima Indians living in the rural mountainous region in northern Mexico. Pima Indians living a more traditional lifestyle in Mexico were clearly expending more energy than a related population in the US, and this increased EE could have made an important contribution to the differences in obesity prevalence. Life in tropical regions may of course be different from that of northern Mexico. Ferro-Luzzi has suggested that individuals in environments of marginal energy supplies may take advantage of compensatory inactivity in order to conserve energy (29
Although the difference in mean BMI between the Nigerian and US women was comparable to that between the two Pima Indian populations, the difference in TEE was only about 25% of that observed in the Pima Indian study. The major difference between the cohorts of women was in REE, with only a 0.20 MJ.d−1
) difference in AEE. In contrast to the present findings on REE, we previously reported no significant difference in REE adjusted for body composition between adults of both sexes in Nigeria and the US (30
). A similar absolute difference in REE between the samples was present in the earlier data, however the sample size of the earlier study was not large enough to render this difference of 0.27 MJ.d−1 (65 kcal.d−1) significant. The explanation for lower REE among the US women is not obvious. These are two populations that are genetically-related, broadly speaking; population-specific allelic markers suggest that on average they share roughly 80% of their genetic material (31
). It is possible that isotope dilution provided a less than optimal estimate of total body water, from which FFM and FM were estimated, which would be more pronounced in the much more obese US cohort. More likely, however, is that there is a slight, but significant, difference in the composition of the FFM component of the two cohorts. Recently Gallagher et al reported that lower REE among African-American than white adults might, in part, be due to a lower total volume of high metabolically active organs (32
). The reverse may be happening here: the US women in the present study are much taller and heavier, with higher FFM, that their Nigerian counterparts. The relative proportion of low metabolically active tissue, ie, skeletal muscle and bone, may therefore be higher among the US women, contributing to a lower overall REE. Regardless of the etiology of the higher average REE of the Nigerian women, it is unlikely to play a significant role in the difference in obesity rates. In a large prospective cohort of Nigerian adults, we previously reported finding no association between REE and weight gain (33
). With the exception of two influential studies among adult Pima Indians (4
), there have been no reports supporting REE as a determinant of weight change (35
Physical activity has been defined and measured differently in different studies, complicating generalizable statements about their potential relationship. The use of DLW for measuring TEE combined with measurement of REE lends itself to defining physical activity as either the physical activity level (PAL) or AEE in MJ/d, neither of which were found to be related to adiposity in our study. The absence of a relationship between adiposity and PAL, however, is not entirely unexpected since it is now recognized that PAL is highly confounded by body weight and only reflects differences in physical activity when the groups or persons being compared are of similar weight (36
Our finding of no relationship between adiposity and AEE in both the Nigerian and the US cohorts is inconsistent with findings from many other studies, including our own; in general, of course, the reported observation is cross-sectional data is an inverse association between BMI and AEE (38
). On the other hand, our findings are not completely unprecedented. In a combined analysis of 22 studies, Westerterp and Goran reported no association between AEE and body fat in women while in men the correlation was −0.35 (40
). Our previous studies have also indicated a weaker relationship between AEE and adiposity in women than men (25
). Neither inclusion of parity nor season of measurement improved the correlations appreciably, suggesting that factors other than EE are influencing adiposity in women living in rural Nigeria and in suburban US.
By default, a difference in energy intake between the cohorts is likely to be the most important determinant of differences in obesity prevalence. We have been unable to accurately assess dietary intake in our Nigerian participants because of an absence of a comprehensive macronutrient database. Careful measurement of quantity and composition of food in high vs. low risk settings represents an important additional challenge for the epidemiology of obesity.
Analysis of the body size-AEE relationship depends critically on the method of adjustment of the EE variables. As can be observed in , there is a linear increase in mean expenditure by BMI classification for all EE variables except PAL; this increase is particularly striking for the Nigerian cohort. It may be that the accepted adjustments for body composition are simply not adequate and this becomes obvious when comparing two populations with such different body sizes and composition. Specifically, AEE is a product of the time spent in physical activity, the intensity of the physical activities, and the weight of the subject performing those physical activities (41
). Thus a simple linear adjustment for weight may be insufficient. However, despite attempts to generate better models incorporating non-linear terms we could not improve on the basic adjustment procedures displayed above.
Weinsier and coworkers (43
) compared different measures of physical activity, including intensity and duration in addition to PAL, AEE, and concluded that these measures represent different domains and have different relationships with body weight and adiposity. It may therefore be inappropriate to equate any single measure with the term physical activity. For example, we found that the values for AEE were not significantly different despite a 44% greater weight in the US cohort as well as an 11% greater percent body fat. Because the energy costs of a given activity increase proportionally with weight (41
), our findings would suggest that the time spent in physical activities in the US cohort was less. Unfortunately, we do not have any reliable measures of the time domains of physical activity. It is worth noting that Weinsier et al (44
) and Levine et al (45
) identified differences in some of these domains between lean and obese samples in which AEE was similar. Finally, it should also be noted that the 6% lower AEE in the US would, if extended over a period of years, lead to substantial excess in calories stores. However, this interpretation is unwarranted given the lack of statistical significance in the two-group comparison and the absence of within-group associations.
While alternative explanations of our results may be plausible, the most parsimonious interpretation suggest that our expectation of high EE in developing countries may, in fact, be erroneous. While we did observe higher adjusted TEE among the Nigerian cohort of women, this was driven primarily by increased REE; AEE did not differ significantly between the cohorts. A better understanding of energy intake and time domains in physical activity in both populations will be necessary to form a complete picture of energy balance.