Going Beyond the Rural-Urban and Regional Divide: Investigating Health Inequities in Bangladesh at Varying Spatial Scales
*Names in bold indicate Presenter
It is now widely accepted that rural-urban divide matters in persisting health inequities. For instance, in Bangladesh about 70 percent of women in urban areas have access to medically trained provider for antenatal care coverage while only about 47 percent of women in rural areas are likely to have access. Theories of social determinants of health suggest that social characteristics such as race, ethnicity, and income can produce differences in these inequities and health outcomes. Only about 26 percent women with no education had access to antenatal care coverage while coverage was about 88 percent for women with secondary or higher education. While less than 30 percent women in the lowest wealth quintile accessed a medically trained provider, more than 80 percent in the top wealth quintile had antenatal care coverage. Evidence also suggests that there is a strong persistence of regional inequality. Again, in Bangladesh a mother in Khulna division is more likely to have better access than a mother in the Sylhet region. But then why Sylhet, which is suppose to be the worst performing region have clusters of communities which have better access to services and perform well while Khulna which is one of the best performing region have underserved population groups?
While there exists ample literature on health and place and community based characteristics and inequities, literature is scarce on the issue of spatial scale. At what spatial scale do these inequities manifest themselves? In other words, at what level does population groups remain underserved and remain similar? Are they more similar at the village level, union-level, thana level? At what scale do these inequities start disappearing as population groups become dissimilar?
This paper explores the issue of health inequities at different spatial scale by testing multiple variables at different geographic units such as i) village level ii)union iii) thana iv) district. I employ spatial regression techniques to test relation among different variables using appropriate weights scheme.
Implications: Preliminary results indicate that inequities and spatial variability manifests at more local scale. Just as the one size fits all approach does not work, classifying health inequities based on mere rural-urban or regional landscape is not enough. Attention needs to be paid to how population is partitioned in order for inequities to manifest or disappear, thus in turn target health interventions effectively.