Abstract
BACKGROUND: Per capita allocation of overall development assistance has been shown to be biased towards countries with lower population size, meaning funders tend to provide proportionally less development assistance to countries with large populations. Individuals that happen to be part of large populations therefore tend to receive less assistance. However, no study has investigated whether this is also true regarding development assistance for health. We examined whether this so-called 'small-country bias' exists in the health aid sector. METHODS: We analysed the effect of a country's population size on the receipt of development assistance for health per capita (in 2015 US$) among 143 countries over the period 1990-2014. Explanatory variables shown to be associated with receipt of development assistance for health were included: gross domestic product per capita, burden of disease, under-5 mortality rate, maternal mortality ratio, vaccination coverage (diphtheria, tetanus and pertussis) and fertility rate. We used the within-between regression analysis, popularised by Mundluck, as well as a number of robustness tests, including ordinary least squares, random-effects and fixed-effects regressions. RESULTS: Our results suggest there exists significant negative effect of population size on the amount of development assistance for health per capita countries received. According to the within-between estimator, a 1% larger population size is associated with a 0.4% lower per capita development assistance for health between countries (-0.37, 95% CI -0.45 to -0.28), and 2.3% lower per capita development assistance for health within countries (-2.29, 95% CI -3.86 to -0.72). CONCLUSIONS: Our findings support the hypothesis that small-country bias exists within international health aid, as has been previously documented for aid in general. In a rapidly changing landscape of global health and development, the inclusion of population size in allocation decisions should be challenged on the basis of equitable access to healthcare and health aid effectiveness.