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Review
. 2021 Aug;98(Suppl 1):31-40.
doi: 10.1007/s11524-021-00558-7. Epub 2021 Sep 1.

Data Sources for Understanding the Social Determinants of Health: Examples from Two Middle-Income Countries: the 3-D Commission

Irene Torres  1   2 , Bishnu Thapa  2   3 , Grace Robbins  2   4 , Shaffi Fazaludeen Koya  2   4 , Salma M Abdalla  5   6 , Onyebuchi A Arah  2   7 , William B Weeks  2   8 , Luxia Zhang  2   9 , Samira Asma  2   10 , Jeanette Vega Morales  2   11 , Sandro Galea  2   4 , Heidi J Larson  2   12   13 , Kyu Rhee  2   14
Affiliations
Review

Data Sources for Understanding the Social Determinants of Health: Examples from Two Middle-Income Countries: the 3-D Commission

Irene Torres et al. J Urban Health. 2021 Aug.

Abstract

The expansion in the scope, scale, and sources of data on the wider social determinants of health (SDH) in the last decades could bridge gaps in information available for decision-making. However, challenges remain in making data widely available, accessible, and useful towards improving population health. While traditional, government-supported data sources and comparable data are most often used to characterize social determinants, there are still capacity and management constraints on data availability and use. Conversely, privately held data may not be shared. This study reviews and discusses the nature, sources, and uses of data on SDH, with illustrations from two middle-income countries: Kenya and the Philippines. The review highlights opportunities presented by new data sources, including the use of big data technologies, to capture data on social determinants that can be useful to inform population health. We conducted a search between October 2010 and September 2020 for grey and scientific publications on social determinants using a search strategy in PubMed and a manual snowball search. We assessed data sources and the data environment in both Kenya and the Philippines. We found limited evidence of the use of new sources of data to study the wider SDH, as most of the studies available used traditional sources. There was also no evidence of qualitative big data being used. Kenya has more publications using new data sources, except on the labor determinant, than the Philippines. The Philippines has a more consistent distribution of the use of new data sources across the HEALTHY determinants than Kenya, where there is greater variation of the number of publications across determinants. The results suggest that both countries use limited SDH data from new data sources. This limited use could be due to a number of factors including the absence of standardized indicators of SDH, inadequate trust and acceptability of data collection methods, and limited infrastructure to pool, analyze, and translate data.

Keywords: Big data; Data sources; Kenya; Philippines; Social determinants of health.

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Figures

Fig. 1
Fig. 1
Variety of data sources on SDH in Kenya
Fig. 2
Fig. 2
Variety of data sources on SDH in the Philippines
Fig. 3
Fig. 3
Publications by determinant and type of source (each square represents a publication included in the review
See this image and copyright information in PMC

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Publication types