Key results
Household income was related to both BMI and WC in an East German adult population. A substantial part of the age-adjusted associations of income with obesity measures was attributable to confounding by other SES indicators. Adjusted for these variables, the associations of interest varied by gender, age, and education.
Among women, BMI and WC decreased across categories representing the range from risk of poverty to affluence. The inverse associations tended to be more pronounced at non-working age than at working age. Conversely, among working-age men, BMI and WC increased with increasing income. Among older men, risk of poverty was related to higher values of the obesity measures. The aforementioned associations were mostly stronger among highly educated participants compared to those with medium/low education.
The differences in mean BMI and WC between persons at risk of poverty and higher income groups were generally small.
Limitations
Although our investigation was based on a large data set, in our subgroups of interest, the extreme income categories representing risk of poverty and affluence partly comprised only few persons. As a result, the precision of our estimates was generally low as indicated by wide CI. In addition, biased estimates due to special characteristics of the few participants reporting extreme incomes are possible. Because of insufficient study size, we could also not stratify by working status directly but had to use prime working age as a surrogate in the main analyses, which might have masked important heterogeneity in the associations of interest.
Only about a third of the invited Leipzig residents participated in the LIFE-Adult baseline examination. As it is typical for studies on volunteers, this low participation was likely associated with a selection of individuals with higher SES and better health [36]. The associations between income and body fat measures might have been underestimated if the low-income persons in LIFE-Adult were less affected by overweight than their counterparts in the general population [37, 38].
Several sources of error in measurement of income are of concern. Income was assessed only at one point in time, although it can change considerably in the short term [7]. Further, income is a sensitive indicator with respect to participants’ willingness to disclose this information accurately [7]. It also may indeed be difficult to spontaneously provide accurate information on a complex quantity such as household income. Misreporting of the household’s composition might have additionally affected the level of equivalised income. Self-reported NEI should therefore be regarded only a rough estimate of the true long-term exposure. Misclassification of participants with respect to their actual NEI may have distorted our estimates of associations with obesity measures to an extent that we cannot judge. However, there are no indications that income was measured with greater error than in other studies in the general population [7, 39, 40].
Furthermore, it should be borne in mind that BMI and WC do not directly capture body fat, whose excess defines obesity. However, the accuracy of these simple indices was found to be sufficient for ranking participants’ body fatness and investigating its relations with health risks in large epidemiological studies [41].
Finally, we used cross-sectional data to reveal the relationship between income and body fatness in our population. Therefore, we cannot infer on the direction of the observed associations. We discuss the distinct interpretations following from this limitation in the next section.
Interpretation of the results
The association between income and obesity found in social epidemiological research can be interpreted in two directions: (1) the causation hypothesis posits that low income causes obesity, whereas (2) the perspective of reverse causality views obesity as a cause of low income.
Reverse causality
A recent systematic review on the relative importance of causation and reverse causality in explaining the link between income and obesity found more consistent evidence for reverse causality, although the relationship is likely to be bidirectional [42]. The main argument for reverse causality is stigmatisation. Because of negative stereotypes, obese people face various weight penalties in the labour market in western societies [43]. This may particularly hold for women [44]. In contrast, in men, wages were found to be highest in the range from upper normal weight to obesity, probably reflecting the positive aura of physical strength in males [45].
Our data are consistent with this gender-specific link between income and obesity. However, reverse causality may be of minor importance in explaining the observations, at least among persons of non-working age. In this population group, income largely represents benefits from the public pension scheme, which depend mainly on wages over the life course. Their working life, in turn, these persons had largely spent in a socialist society where weight stigma is unlikely to have played an important role in employment. Nevertheless, we cannot rule out that reverse causality might have contributed to the inverse income-body size association in working-age women and the positive gradient in working-age men.
Causation hypothesis
Numerous studies aimed at evaluating income as a possible cause of obesity. In line with our observations, inverse associations were commonly found among women in high-income countries, including Germany [16,17,18,19,20,21,22, 46]. For men, the available data are contradictory: often no association was found [16, 17, 19, 21, 22], observed associations were frequently positive instead of negative [16, 46], yet in German general populations also negative [18, 20]. There is little evidence for gender differences in the relations of income to traits hypothesised to mediate an effect on body fatness. Studies among European and German adults showed that socioeconomic deprived groups consume less vegetables, fruit, and fibre than the better-off [47, 48]. Low-income persons were also less often engaged in sports activity than higher income groups in Germany [49]. However, neither the socioeconomic inequalities in dietary intakes nor in physical activity differed by gender. In contrast, a higher vulnerability to chronic stressors could explain why an inverse SES-obesity association is seen more consistently in women than in men [14, 50]. Moreover, gender differences in physical characteristics that are socially valued may underlie the observations in our study. For women, thinness represents the ideal of physical beauty and is materially more viable for those with higher SES, whereas for men, a larger body size is likely to be valued a symbol of physical dominance and prowess [16, 44].
Current income is considered a more reliable indicator of actual SES in the main earning years than at older ages [7]. Hence, the relation of income to body fatness is expected to be stronger at working age than at non-working age, a hypothesis that has been rarely investigated. Income inequality in obesity was reported to be both smaller and larger among women aged over 55 than in the middle-aged in European and German populations, respectively [17, 21]. In our women, the differences in body fat measures between the poor and the affluent tended to be larger among those of non-working age. Long-term income may have been captured more validly in retired women whose income mainly consists of stable pension benefits, which in turn reflect incomes over the life course [40]. Alternatively, the presence of employed women in the high-income groups among women aged over 65 may explain the unexpected observation. Still working women may be much more committed to the slimness ideal than non-working women. A sensitivity analysis did not point to heterogeneity in the income-BMI association between actually retired and employed women. In agreement with proposed mechanisms, the gradient in body fat measures across income categories was reversed and more pronounced among working-age men than among older men. Moreover, it was restricted to the employed when stratifying by employment directly.
We had hypothesised that education protects against the obesogenic effects of income inequality through cognitive skills and social capital. However, NEI was predominantly stronger related to body fat measures among highly educated participants, except in working-age women. The evidence for education as a modifier of the income-obesity relation is scarce. The inverse relation in South-Korean women was found to be stronger among the highly educated [30], which partly agrees with our findings. The stronger associations among highly educated persons may reflect a synergistic interaction between income and education with respect to the obesity-related pathways. On the other hand, self-reported income may be more valid for highly educated participants, although there is a lack of evidence on the relation between SES and the accuracy of income reporting [40]. In addition, the less educated population was probably less willing to participate in LIFE-Adult [36]. As a result, the observed dependencies of body fat measures from income may reflect the true situation less valid (are underestimated) in the less educated compared to the higher educated participants. Moreover, NEI varied more across income categories in highly educated persons, which may also have led to larger differences in obesity measures.
BMI and WC were strongly correlated in our population, indicating that both body fat surrogates measure approximately the same, which was later confirmed by their associations with income. Comparable correlations between BMI and WC were reported in the American general population [51]. In addition, both BMI and WC were highly correlated with direct measurements of body fat mass, body fat percentage, and subcutaneous adipose tissue, irrespective of age, gender, and ethnicity [23, 41]. In other social epidemiological studies, however, the association of income with obesity partly varied by the definition of the latter. Among British males, income was inversely related to WC but not to BMI [25]. Likewise, income was stronger related to WC than to BMI among Swedish women [26]. Confounding by other SES indicators may partly explain differences in the associations of income with WC compared to BMI. After adjustment for age only, we observed a decrease in WC with increasing income but no differences in BMI among working-age men, which agrees with the finding in British men. Consistent with our observation, education largely explained the income inequality in WC among the British men [25].
After adjustment for other SES indicators, the differences in mean BMI and WC between societally relevant income groups were rather small, ranging from 1 to 2 kg/m2 for BMI and 2 to 4 cm for WC. Hence, our data do not suggest that income disparities are a major driver of body fat accumulation in an East German population of middle and older age. Income inequality in obesity was low in magnitude in other European countries, too [17, 25]. Among German women, however, income turned out to be the strongest determinant of obesity relative to education and occupation [19]. Methodological limitations may have led to an underestimation of the true associations between income and body fat indices in the Leipzig population. On the other hand, even low income may be sufficient to meet the needs for healthy food, which is available at affordable prices in common supermarkets, at middle and older age in Germany. Also of importance, an obese phenotype develops in the long term and is probably significantly determined by early-life SES [44]. In our older population that had spent critical life periods in an egalitarian system, current income as a reflection of material conditions over the life course may not be a crucial factor for the distribution of obesity. Chronically overconsumption of calories has been primarily attributed to the psychosocial impact of living in a more hierarchical society [52].