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Measures of Maternal Socioeconomic Status in Yemen and Association with Maternal and Child Health Outcomes

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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.

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Acknowledgments

The authors acknowledge the local midwives and healthcare workers for taken part in the study survey and contacted the interviews. Thanks are due to staff at the governorate health offices. Also the authors acknowledge UNICEF Yemen office for granting us permission to use the HBMNC 2008–2009 survey data for this study. Financial assistance for the survey came from the UNICEF Yemen office and Ministry of health, Yemen.

Authors’ Contribution

This article was designed, analyzed and written by Alosaimi Abdullah under the supervision of Riitta Luoto and Bright Nwaru. Alserouri Abdelwahed, and Halima Mouniri did the surveys in the provinces. All authors commented and approved the final version of the manuscript.

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Authors and Affiliations

  1. School of Health Sciences, University of Tampere, 33014, Tampere, Finland

    Abdullah N. Alosaimi & Bright I. Nwaru

  2. UKK Institute for Health Promotion Research, 33501, Tampere, Finland

    Riitta Luoto

  3. Department of Children and Families, National Health and Welfare Institute, 00271, Helsinki, Finland

    Riitta Luoto

  4. Community Health Department, Faculty of Medicine and Health Sciences, Sana’a University, Sana’a, Yemen

    Abdul Wahed Al Serouri

  5. Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK

    Bright I. Nwaru

  6. Averting Maternal Death and Disability Program, Department of Population and Family Health, the Mailman School of Public Health, Columbia University, New York, NY, USA

    Halima Mouniri

Authors
  1. Abdullah N. Alosaimi
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  2. Riitta Luoto
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  3. Abdul Wahed Al Serouri
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  4. Bright I. Nwaru
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  5. Halima Mouniri
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Corresponding author

Correspondence to Abdullah N. Alosaimi.

Appendices

Appendix 1

See Table 5.

Table 5 Operational definition and categorization of variables used for constructing the SES indices
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Appendix 2

See Table 6.

Table 6 Correlations between the variables used in the factor analysis for constructing the SES indices: Pearson correlation coefficients and their significant levels are presented
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Appendix 3

See Table 7.

Table 7 PCA results showing the three extracted components, their loaded variables, their eigenvalues and the percentage of variance in SES explained by each component
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Alosaimi, A.N., Luoto, R., Al Serouri, A.W. et al. Measures of Maternal Socioeconomic Status in Yemen and Association with Maternal and Child Health Outcomes. Matern Child Health J 20, 386–397 (2016). https://doi.org/10.1007/s10995-015-1837-4

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  • DOI: https://doi.org/10.1007/s10995-015-1837-4

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