Evidence map›Paper›PMID 34759495›Full record

ArticleIndian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine

Constructing Practical and Realistic Asset-Based Socioeconomic Status Assessment Scale Using Principal Component Analysis for Urban Population of Puducherry, India.

Vinayagamoorthy Venugopal, Amol R Dongre, Poomathy Ponnusamy

Abstract read
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Article in Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Vinayagamoorthy VenugopalDepartment of Community Medicine, Sri Manakula Vinayagar Medical College and Hospital, Puducherry, India.
Amol R DongreDepartment of Extension Programme, Pramukhswami Medical College (PSMC), Karamsad, Gujarat, India.
Poomathy PonnusamyAssistant Programme Manager, Deputy Director of Health Service, Erode District, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocioeconomic status (SES) is a key determinant of health. However, ascertaining the SES in developing countries is really challenging. Hence, we decided to develop an asset-based simple and rational SES tool for urban population of Puducherry and compare it with Modified Kuppuswamy's (MK) scale. MATERIALS AND

methodsSequential mixed methods design was used. The list of local household assets to determine SES was created based on group interviews with stakeholders and review of literature. Then, survey was carried out among 500 urban households by trained medical interns after obtaining informed consent. EpiCollect-5, mobile-based software, was used to capture data. Principal component analysis (PCA) was carried out to construct a wealth index using SPSS version 24. The assets included in the final PCA were ranked based on their contribution to the index by linear regression.

resultsThe eigenvalue for the first principal component was 6.7 accounting for 33.6% of the variance in the original data. Finally, reduced 10-item-based SES scale was created and scoring system was formulated based on regression coefficient. The weighted kappa statistics and correlation coefficient measure of reliability between household quintiles on 20-item and 10-item reduced SES tool were 0.77 and 0.95, respectively. There was a moderate correlation between SES obtained from MK scale and newly constructed scale.

conclusionsThe newly devised SES scale is context specific, reliable, easy to administer, and quick to ascertain the SES and thus can be used for a similar context in future health research.

Indexed as

Indiaprincipal component analysissocioeconomic statusurban population

Identifiers

PMID34759495
PMCPMC8575199

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