Abstract
Despite increasing recognition that community-level socioeconomic factors are critical to individual health outcomes globally, guidance on their measurement remains limited in low and middle income countries. We outline the steps needed to develop and validate a theory-based, multidimensional index of community-level socioeconomic composition using information that is often available in global settings. Census indicators describing human and social capital were analyzed using principal components analysis to construct a community socioeconomic composition index (CSCI) for 30 communities in the Southern plains of Nepal. The index was validated against subsequent child nutrition, household assets, and village infrastructure using data from 1822 children and their households. At the community-level, the CSCI was positively correlated with child height-for-age, and child weight-for-age, household assets, and community infrastructure (r = 0.54, 0.58, 0.85, 0.67, respectively). In multilevel analyses, +1SD of the CSCI was associated with +0.14SD of the household asset index (p < 0.01) after adjusting for confounders. These results suggest that an exclusively census-based strategy to measure socioeconomic composition has construct validity in this setting. This approach to measuring community-level socioeconomic composition may be feasibly reproduced in other resource-constrained settings where census data are available, potentially expanding the scope of place and health research globally.
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Notes
We use the term “community socioeconomic composition” rather than “community socioeconomic status” to clearly differentiate between the construct at the community versus individual level.
Six senior staff were asked to rank the top five best and worst VDCs with respect to infrastructural development in 2007. These responses were used to rank the VDCs using a modified Borda count method.
The PCA-based rankings of a subset of VDCs using the reduced set of infrastructural items was conducted using the same method described here. Discrepancies between the previously collected VDC data and retrospectively VDC data we collected were verified in the field and corrected as needed.
Abbreviations
- CSCI:
-
Community socioeconomic composition index
- NNIPS:
-
Nepal Nutrition Intervention Project-Sarlahi
- PCA:
-
Principal components analysis
- SES:
-
Socioeconomic status
- VDC:
-
Village Development Community
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Acknowledgments
Data collection was funded by the National Institutes of Health grants R01 HD050254 and HD 38753; the Bill and Melinda Gates Foundation, Seattle, Washington; the Micronutrients for Health Cooperative Agreement No. HRN-A-00-97-00015-00 and the Global Research Activity Cooperative Agreement No.GHS-A-00-03-00019-00 between the Johns Hopkins University and the Office of Health, Infectious Diseases and Nutrition, United States Agency for International Development, Washington, DC. Bill and Melinda Gates Foundation, Seattle, Washington; Sight and Life Research Institute; and the Doctoral Thesis Research Fund of the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health. We thank all of the field staff and supervisors who made data collection possible, and we thank Drs. Thomas Glass and Amy Tsui for their helpful critiques in conceptualizing the measurement and validation of the indices.
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Patel, S.A., Sherman, S.G., Khatry, S.K. et al. An Index of Community-Level Socioeconomic Composition for Global Health Research. Soc Indic Res 129, 639–658 (2016). https://doi.org/10.1007/s11205-015-1114-3
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DOI: https://doi.org/10.1007/s11205-015-1114-3