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Development of two socioeconomic indices for Saudi Arabia

BACKGROUND: Health and socioeconomic status (SES) are linked in studies worldwide. Measures of SES exist for many countries, however not for Saudi Arabia (SA). We describe two indices of area-based SES for SA. METHODS: Routine census data has been used to construct two indices of SES at the geograph...

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Autores principales: AlOmar, Reem S., Parslow, Roger C., Law, Graham R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019717/
https://www.ncbi.nlm.nih.gov/pubmed/29940925
http://dx.doi.org/10.1186/s12889-018-5723-z
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author AlOmar, Reem S.
Parslow, Roger C.
Law, Graham R.
author_facet AlOmar, Reem S.
Parslow, Roger C.
Law, Graham R.
author_sort AlOmar, Reem S.
collection PubMed
description BACKGROUND: Health and socioeconomic status (SES) are linked in studies worldwide. Measures of SES exist for many countries, however not for Saudi Arabia (SA). We describe two indices of area-based SES for SA. METHODS: Routine census data has been used to construct two indices of SES at the geographically-delimited administrative region of Governorates in SA (n = 118). The data used included indicators of educational status, employment status, car and material ownership. A continuous measure of SES was constructed using exploratory factor analysis (EFA) and a categorical measure of SES using latent class analysis (LCA). Both indices were mapped by Governorates. RESULTS: The EFA identified three factors: The first explained 51.58% of the common variance within the interrelated factors, the second 15.14%, and the third 14.26%. These proportions were used in the formulation of the standard index. The scores were fixed to range from 100 for the affluent Governorate and 0 for the deprived. The LCA found a 4 class model as the best model fit. Class 1 was termed “affluent” and included 11.01% of Governorates, class 2 “upper middle class” (44.91%), class 3 “lower middle class” (33.05%) and class 4 “deprived” (11.01%). The populated urbanised Governorates were found to be the most affluent whereas the smaller rural Governorates were the most deprived. CONCLUSION: This is the first description of measures of SES in SA at a geographical level. Two measures have been successfully constructed and mapped. The maps show similar patterns suggesting validity. Both indices support the common perception of SES in SA. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12889-018-5723-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-60197172018-07-06 Development of two socioeconomic indices for Saudi Arabia AlOmar, Reem S. Parslow, Roger C. Law, Graham R. BMC Public Health Research Article BACKGROUND: Health and socioeconomic status (SES) are linked in studies worldwide. Measures of SES exist for many countries, however not for Saudi Arabia (SA). We describe two indices of area-based SES for SA. METHODS: Routine census data has been used to construct two indices of SES at the geographically-delimited administrative region of Governorates in SA (n = 118). The data used included indicators of educational status, employment status, car and material ownership. A continuous measure of SES was constructed using exploratory factor analysis (EFA) and a categorical measure of SES using latent class analysis (LCA). Both indices were mapped by Governorates. RESULTS: The EFA identified three factors: The first explained 51.58% of the common variance within the interrelated factors, the second 15.14%, and the third 14.26%. These proportions were used in the formulation of the standard index. The scores were fixed to range from 100 for the affluent Governorate and 0 for the deprived. The LCA found a 4 class model as the best model fit. Class 1 was termed “affluent” and included 11.01% of Governorates, class 2 “upper middle class” (44.91%), class 3 “lower middle class” (33.05%) and class 4 “deprived” (11.01%). The populated urbanised Governorates were found to be the most affluent whereas the smaller rural Governorates were the most deprived. CONCLUSION: This is the first description of measures of SES in SA at a geographical level. Two measures have been successfully constructed and mapped. The maps show similar patterns suggesting validity. Both indices support the common perception of SES in SA. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12889-018-5723-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-26 /pmc/articles/PMC6019717/ /pubmed/29940925 http://dx.doi.org/10.1186/s12889-018-5723-z Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
AlOmar, Reem S.
Parslow, Roger C.
Law, Graham R.
Development of two socioeconomic indices for Saudi Arabia
title Development of two socioeconomic indices for Saudi Arabia
title_full Development of two socioeconomic indices for Saudi Arabia
title_fullStr Development of two socioeconomic indices for Saudi Arabia
title_full_unstemmed Development of two socioeconomic indices for Saudi Arabia
title_short Development of two socioeconomic indices for Saudi Arabia
title_sort development of two socioeconomic indices for saudi arabia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019717/
https://www.ncbi.nlm.nih.gov/pubmed/29940925
http://dx.doi.org/10.1186/s12889-018-5723-z
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