Effect of modeling a multilevel structure on the Indian population to identify the factors influencing HIV infection

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dc.contributor.authorMenon, Nidhi
dc.contributor.authorBhaskarapillai, Binukumar
dc.contributor.authorRichardson, Alice
dc.date.accessioned2020-04-28T09:54:54Z
dc.date.issued2019
dc.date.updated2019-11-25T08:01:01Z
dc.description.abstractMany studies have addressed the factors associated with HIV in the Indian population. Some of these studies have used sampling weights for the risk estimation of factors associated with HIV, but few studies have adjusted for the multilevel structure of survey data. The National Family Health Survey 3 collected data across India between 2005 and 2006. 38,715 females and 66,212 males with complete information were analyzed. To account for the correlations within clusters, a three-level model was employed. Bivariate and multivariable mixed effect logistic regression analysis were performed to identify factors associated with HIV. Intracluster correlation coefficients were used to assess the relatedness of each pair of variables within clusters. Variables pertaining to no knowledge of contraceptive methods, age at first marriage, wealth index and noncoverage of PSUs by Anganwadis were significant risk factors for HIV when the multileveled model was used for analysis. This study has identified the risk profile for HIV infection using an appropriate modeling strategy and has highlighted the consequences of ignoring the structure of the data. It offers a methodological guide towards an applied approach to the identification of future risk and the need to customize intervention to address HIV infection in the Indian population.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2470-9360en_AU
dc.identifier.urihttp://hdl.handle.net/1885/203448
dc.language.isoen_AUen_AU
dc.publisherTaylor & Francisen_AU
dc.rights© 2019 International Biometric Society – Chinese Regionen_AU
dc.sourceBiostatistics & Epidemiologyen_AU
dc.subjectHIV infection; logistic regression; multilevel modeling; multistage samplingen_AU
dc.titleEffect of modeling a multilevel structure on the Indian population to identify the factors influencing HIV infectionen_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.issue1en_AU
local.bibliographicCitation.lastpage139en_AU
local.bibliographicCitation.startpage126en_AU
local.contributor.affiliationMenon, Nidhi, College of Health and Medicine, ANUen_AU
local.contributor.affiliationBhaskarapillai, Binukumar, National Institute of Mental Health and Neuro Sciences (NIMHANS)en_AU
local.contributor.affiliationRichardson, Alice, College of Health and Medicine, ANUen_AU
local.contributor.authoremailnidhi.menon@anu.edu.auen_AU
local.contributor.authoremailalice.richardson@anu.edu.auen_AU
local.contributor.authoruidMenon, Nidhi, u6192898en_AU
local.contributor.authoruidRichardson, Alice, u3767151en_AU
local.description.embargo2037-12-31
local.description.notesImported from ARIESen_AU
local.identifier.absfor111711 - Health Information Systems (incl. Surveillance)en_AU
local.identifier.absseo920503 - Health Related to Specific Ethnic Groupsen_AU
local.identifier.ariespublicationu5786633xPUB1103en_AU
local.identifier.citationvolume3en_AU
local.identifier.doi10.1080/24709360.2019.1671096en_AU
local.identifier.scopusID2-s2.0-85073197449
local.identifier.uidSubmittedByu5786633en_AU
local.publisher.urlhttps://www.tandfonline.com/en_AU
local.type.statusPublished Versionen_AU

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