Distribution of Risk Factors by Poverty

Socioeconomic position is an important distal risk determinant for many health outcomes. While it was not possible (owing to limitations of data and other factors) to directly map socioeconomic position to the burden of disease, it was considered possible to map some risk factors by absolute poverty, which is one measure of socioeconomic position. The proportions of the population living on <US$ 1, on US$ 1–2 and on >US$ 2 per day were estimated for each of the 14 subregions using World Bank estimates of poverty by country. The counterfactual scenario was no absolute poverty in the world (no one living on <US$ 2 per day). The prevalences of risk factors for each subregion were obtained from the relevant risk factor chapters in this publication. The associations of absolute poverty with eight risk factors (child and maternal underweight, unsafe water and sanitation, unsafe sex, indoor air pollution, outdoor air pollution, tobacco use, alcohol use and over- weight [women only]) were determined by an indirect method, using asset scores calculated from demographic and health survey (DHS) data and income from living standards measurement surveys (LSMS) data. First, the joint association of the asset score or income variable with the risk factor was determined for each subregion. Second, the percentage estimates of poverty by subregion were overlaid on the ranked asset scores and income variables (e.g. if 20% of people in a subregion were estimated to be living on <US$ 1 per day, then the prevalence of each factor among these poor people was assumed to be that observed for the 20% of people with lowest asset scores). Third, the crude relative risks of each risk factor by level of poverty were estimated based on this overlay. We also undertook selective literature reviews for some risk factors. Approximately one fifth of the world’s population live on <US$ 1 per day and almost half on <US$ 2 per day. Of the 14 subregions, three (EUR-A, AMR-A and WPR-A) had negligible levels of absolute poverty and were excluded from all subsequent analyses. We estimate that 9% of people in EMR-B were living on < US$ 2 per day (2% on < US$ 1 per day), but the estimates for this subregion were based on sparse data. The estimates for the remaining 10 subregions ranged from 18% (3%) for EUR-B to 85% (42%) for SEAR-D and 78% (56%) for AFR-D. Childhood malnutrition, unimproved water and sanitation and indoor air pollution were strongly associated with absolute poverty. The asso- ciations of poverty with one indicator of unsafe sex (unprotected sex with a non-marital partner) and tobacco and alcohol consumption were weaker and variable across subregions. Our analyses and literature reviews were consistent with the proposition that tobacco and alcohol consumption, adverse lipid profiles, hypertension and overweight initially affect the non-poor in developing countries. If the worldwide prevalence of childhood malnutrition among all children living on <US$ 2 per day were changed to that of children living on >US$2 per day (i.e. counterfactual scenario 1), 37% of the cases worldwide of underweight would be prevented (assuming a causal relationship). The equivalent percentage reduction from shifting all poor children to exactly US$ 2 per day (counterfactual scenario 2) was 23%. For inadequate water and sanitation these percentage reductions were 51% and 36%, respectively. Both poverty and risk factor data were available or were used for only some countries within each subregion, and thus extrapolations had to be made from those countries with data. Second, some subregions had no data at all for some risk factors (e.g. unsafe sex), thus limiting the number of subregions for which we could conduct analyses. Third, all results were based on survey data with their associated errors. Another notable limitation with our analyses was the assumption that the ranking by asset score was comparable to the unobserved ranking by income poverty. Nevertheless, our findings confirm that there are currently severe inequalities in the distribution of childhood malnutrition, inadequate water and sanitation and indoor air pollution by income poverty worldwide, with these risks concentrated among the poorest sectors of society.