Many South Africans, even poor ones, have a high body mass (Case and Deaton 2005). This has led to an increase in the prevalence of hypertension and strokes in contexts where one might not have expected to see this (Kahn and Tollman 1999). Understanding some of the correlates of high body mass would therefore be useful. Indeed the rapid increase in obesity around the world has become the focus of attention not only of health researchers. Increasing numbers of economists have also started to explore the economic correlates of the increase in body weight. In US based studies (e.g. Chou, Grossman and Saffer 2002) a negative relationship between income and obesity has been observed. On the other and it seems clear that across countries obesity is positively correlated with income. This suggests that the relationship may be non-monotonic: increasing with income at low levels, but decreasing at higher levels.
South Africa offers an interesting setting for studying some of the these effects. Firstly it has high levels of inequality. This means that there is a section of the population (largely the White sub-population) that has incomes and standards of living comparable to those found in developed societies. Within the Black South African majority there is also a wide range of incomes which will give us some power to analyse these relationships. Secondly, obesity is becoming a demonstrable problem, even in communities in which poverty seems to be widespread.
In this paper we will be concerned with two substantive issues. Firstly we will show that among Black South Africans body mass increases more or less monotonically with income. Furthermore it seems that body mass also increases with education and employment. This is consistent with the idea that more successful individuals have greater weight. Indeed we will show that Black South Africans seem to aspire to greater body weight even in ranges where they would be classified as overweight. The picture for White South Africans, however, is quite different, with high income individuals more likely to be of lower body weight.
Secondly, we will show that there is a strong gender component to these relationships. Black women acquire body weight at a more rapid rate with increases in income than do their men. White women, on the other hand, shed it more aggressively. These “stylised facts” suggest that the images that these women have of themselves and that, perhaps, their partners have of them, are also implicated in the patterns that we observe.
In order to make these points we will also be concerned with a methodological issue. There are three publicly available data sets which have anthropometric information. Two of these are relatively small surveys that also have good socio-economic information. The third is the Demographic and Health Survey which only has asset information. A considerable part of this paper will be devoted to examining how good an estimate one can get from such asset proxies. We will show that on the whole the assets perform reasonably well — but that once one allows for the facts that assets may have independent effects on the outcome of interest, the issue becomes considerably more murky. In the process, however, we will discover some points which, after the event, are fairly obvious, such as that car ownership seems to be implicated in the increase in obesity!
The structure of this paper is as follows. In the next section we will review some of the literature and, in particular, some of the literature dealing with proxy variables. In section 3 we describe our three data sets and present a number of descriptive analyses. Section 4 provides a detailed discussion of the performance of the asset proxies on these data sets. Having satisfied ourselves that these variables will not fundamentally distort the relationships, we use them in Section 5 to examine the relationship between body mass and a variety of economic and individual attributes. Section 6 concludes.
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The Weight of Success: The Body Mass Index and Economic Well-being in South Africa
