Abstract

New forms of data for understanding low- and middle-income countries’ health inequalities: the case of Tanzania

Highlights

  • HEALTH INEQUALITIES AS A GLOBAL PROBLEM lies on Demographic and Health Surveys, which Many low- and middle-income countries (LMICs) are are typically expensive, complex, infrequent and insufficiently powered to provide data suitable for planning local health services

  • Characterised by high levels of socioeconomic inequality and uneven access to clinical and preventive services, leading to unacceptably wide differences in health outcomes between rich and poor [1]. This is often exacerbated by weak systems of governance, which hinder the efficient and fair distribution of resources. Tackling such inequalities is one of the Sustainable Development Goals proposed by the United Nations (SDG #10), and is echoed in the World Health Organization’s (WHO) campaign to promote Universal Health Coverage as a fundamental human right [2]

  • While the association between socioeconomic status (SES) and health has been relatively well-studied in high income countries, much less is known about how these factors interact in LMICs or how changing local contexts influence patterns of health inequality in these settings

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Summary

Edinburgh Research Explorer

New forms of data for understanding low- and middle-income countries’ health inequalities: the case of Tanzania. Citation for published version: Frank, JW, Pagliari, C, Geubbels, E & Mtenga, S 2018, 'New forms of data for understanding low- and middle-income countries’ health inequalities: the case of Tanzania', Journal of Global Health, vol 8, no. Characterised by high levels of socioeconomic inequality and uneven access to clinical and preventive services, leading to unacceptably wide differences in health outcomes between rich and poor [1]. This is often exacerbated by weak systems of governance, which hinder the efficient and fair distribution of resources. Obtaining a better understanding of this is vital for informing effective, targeted, responsive, and equitable health and social services [3]

UTILISING INFORMATION FOR HEALTH SYSTEMS STRENGTHENING
DIFFICULTIES WITH EVALUATING HEALTH INEQUALITIES IN LMICs
TANZANIA AS A CASE IN POINT
Two key sources of health and SES data in the past
Findings
FUTURE DIRECTIONS
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