Abdullah N Alosaimi1, Riitta Luoto2,3, Abdul Wahed Al Serouri4, Bright I Nwaru5,6, Halima Mouniri7. 1. School of Health Sciences, University of Tampere, 33014, Tampere, Finland. Abdullah.alosaimi@uta.fi. 2. UKK Institute for Health Promotion Research, 33501, Tampere, Finland. 3. Department of Children and Families, National Health and Welfare Institute, 00271, Helsinki, Finland. 4. Community Health Department, Faculty of Medicine and Health Sciences, Sana'a University, Sana'a, Yemen. 5. School of Health Sciences, University of Tampere, 33014, Tampere, Finland. 6. Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK. 7. Averting Maternal Death and Disability Program, Department of Population and Family Health, the Mailman School of Public Health, Columbia University, New York, NY, USA.
Abstract
BACKGROUND: Reliable measurement of socioeconomic status (SES) in health research requires extensive resources and can be challenging in low-income countries. We aimed to develop a set of maternal SES indices and investigate their associations with maternal and child health outcomes in rural Yemen. METHODS: We applied factor analysis based on principal component analysis extraction to construct the SES indices by capturing household attributes for 7295 women of reproductive age. Data were collected from a sub-national household survey conducted in six rural districts in four Yemeni provinces in 2008-2009. Logistic regression models were fitted to estimate the associations between the SES indices and maternal mortality, spontaneous abortion, stillbirth, neonatal and infant mortality. RESULTS: Three SES indices (wealth, educational and housing quality) were extracted, which together explained 54 % of the total variation in SES. Factor scores were derived and categorized into tertiles. After adjusting for potential confounding factors, higher tertiles of all the indices were inversely associated with spontaneous abortion. Higher tertiles of wealth and educational indices were inversely associated with stillbirth, neonatal and infant mortality. None of the SES indices was strongly associated with maternal mortality. CONCLUSION: By subjecting a number of household attributes to factor analysis, we derived three SES indices (wealth, educational, and housing quality) that are useful for maternal and child health research in rural Yemen. The indices were worthwhile in predicting a number of maternal and child health outcomes. In low-income settings, failure to account for the multidimensionality of SES may underestimate the influence of SES on maternal and child health.
BACKGROUND: Reliable measurement of socioeconomic status (SES) in health research requires extensive resources and can be challenging in low-income countries. We aimed to develop a set of maternal SES indices and investigate their associations with maternal and child health outcomes in rural Yemen. METHODS: We applied factor analysis based on principal component analysis extraction to construct the SES indices by capturing household attributes for 7295 women of reproductive age. Data were collected from a sub-national household survey conducted in six rural districts in four Yemeni provinces in 2008-2009. Logistic regression models were fitted to estimate the associations between the SES indices and maternal mortality, spontaneous abortion, stillbirth, neonatal and infant mortality. RESULTS: Three SES indices (wealth, educational and housing quality) were extracted, which together explained 54 % of the total variation in SES. Factor scores were derived and categorized into tertiles. After adjusting for potential confounding factors, higher tertiles of all the indices were inversely associated with spontaneous abortion. Higher tertiles of wealth and educational indices were inversely associated with stillbirth, neonatal and infant mortality. None of the SES indices was strongly associated with maternal mortality. CONCLUSION: By subjecting a number of household attributes to factor analysis, we derived three SES indices (wealth, educational, and housing quality) that are useful for maternal and child health research in rural Yemen. The indices were worthwhile in predicting a number of maternal and child health outcomes. In low-income settings, failure to account for the multidimensionality of SES may underestimate the influence of SES on maternal and child health.
Entities:
Keywords:
Factor analysis; Maternal and child health; Socioeconomic status; Yemen
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