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      Factors associated with HIV testing among pregnant women in Rwanda: A nationwide cross-sectional survey

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          Abstract

          Human immunodeficiency virus (HIV) testing during pregnancy is crucial for the prevention of mother-to-child transmission of HIV, through aiding prompt treatment, care, and support. However, few studies have explored HIV testing among pregnant women in Rwanda. This study, therefore, aimed to determine the prevalence and associated factors of HIV testing among pregnant women in Rwanda. We used secondary data from the 2020 Rwanda Demographic and Health Survey (RDHS), comprising 870 pregnant women. Multistage stratified sampling was used by the RDHS team to select participants. We conducted bivariable and multivariable logistic regression to explore factors associated with HIV testing using SPSS (version 25). Of the 870 pregnant women, 94.0% had tested for HIV during their current pregnancy. Younger age (24–34 years), not working, large household size, multiple sex partners, as well as secondary, primary, and no education were associated with higher odds of HIV testing compared to their respective counterparts. However, being unmarried, belonging to the western region, having not visited a health facility, and not having comprehensive HIV knowledge were associated with lower odds of HIV testing. A high proportion of pregnant women had tested for HIV. The study revealed that individual-level factors had the greatest influence on HIV testing in pregnancy, with a few household-level factors showing significance. There is a need for maternal health stakeholders to design and develop HIV testing programs that are region-sensitive. These programs should target older, more educated, working, and unmarried women with limited HIV knowledge.

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          Purposeful selection of variables in logistic regression

          Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS) data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.
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            Confounding and collinearity in regression analysis: a cautionary tale and an alternative procedure, illustrated by studies of British voting behaviour

            Many ecological- and individual-level analyses of voting behaviour use multiple regressions with a considerable number of independent variables but few discussions of their results pay any attention to the potential impact of inter-relationships among those independent variables—do they confound the regression parameters and hence their interpretation? Three empirical examples are deployed to address that question, with results which suggest considerable problems. Inter-relationships between variables, even if not approaching high collinearity, can have a substantial impact on regression model results and how they are interpreted in the light of prior expectations. Confounded relationships could be the norm and interpretations open to doubt, unless considerable care is applied in the analyses and an extended principal components method for doing that is introduced and exemplified.
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              Women and HIV in Sub-Saharan Africa

              Thirty years since the discovery of HIV, the HIV pandemic in sub-Saharan Africa accounts for more than two thirds of the world’s HIV infections. Southern Africa remains the region most severely affected by the epidemic. Women continue to bear the brunt of the epidemic with young women infected almost ten years earlier compared to their male counterparts. Epidemiological evidence suggests unacceptably high HIV prevalence and incidence rates among women. A multitude of factors increase women’s vulnerability to HIV acquisition, including, biological, behavioral, socioeconomic, cultural and structural risks. There is no magic bullet and behavior alone is unlikely to change the course of the epidemic. Considerable progress has been made in biomedical, behavioral and structural strategies for HIV prevention with attendant challenges of developing appropriate HIV prevention packages which take into consideration the socioeconomic and cultural context of women in society at large.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Editor
                Journal
                PLOS Glob Public Health
                PLOS Glob Public Health
                plos
                PLOS Global Public Health
                Public Library of Science (San Francisco, CA USA )
                2767-3375
                18 January 2024
                2024
                : 4
                : 1
                : e0002728
                Affiliations
                [1 ] School of Nursing and Midwifery, Aga Khan University, Kampala, Uganda
                [2 ] Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, SAR- China
                [3 ] Mbarara Regional Referral Hospital, Mbarara, Uganda
                [4 ] Programmes Department, Relief International, Khartoum, Sudan
                [5 ] Key Laboratory of Environmental Medicine Engineering, School of Public Health, Southeast University, Nanjing, Jiangsu Province, China
                University of Montreal School of Public Health: Universite de Montreal Ecole de Sante Publique, CANADA
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-3255-3876
                Article
                PGPH-D-23-00992
                10.1371/journal.pgph.0002728
                10795989
                38236821
                f6d60d77-8ed3-43ef-9623-c4f1aa179c23
                © 2024 Nuwabaine et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 May 2023
                : 27 November 2023
                Page count
                Figures: 0, Tables: 2, Pages: 15
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Viral Pathogens
                Immunodeficiency Viruses
                HIV
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Viral Pathogens
                Immunodeficiency Viruses
                HIV
                Biology and Life Sciences
                Organisms
                Viruses
                Viral Pathogens
                Immunodeficiency Viruses
                HIV
                Biology and Life Sciences
                Organisms
                Viruses
                Immunodeficiency Viruses
                HIV
                Biology and life sciences
                Organisms
                Viruses
                RNA viruses
                Retroviruses
                Lentivirus
                HIV
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Viral Pathogens
                Retroviruses
                Lentivirus
                HIV
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Viral Pathogens
                Retroviruses
                Lentivirus
                HIV
                Biology and Life Sciences
                Organisms
                Viruses
                Viral Pathogens
                Retroviruses
                Lentivirus
                HIV
                Medicine and Health Sciences
                Diagnostic Medicine
                Virus Testing
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
                Medicine and Health Sciences
                Health Care
                Health Care Facilities
                People and Places
                Geographical Locations
                Africa
                Rwanda
                Medicine and health sciences
                Public and occupational health
                Preventive medicine
                HIV prevention
                Social Sciences
                Sociology
                Education
                Educational Attainment
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Antenatal Care
                Custom metadata
                The data set used is openly available upon permission from the MEASURE DHS website (URL: https://www.dhsprogram.com/data/available-datasets.cfm). However, authors are not authorized to share this data set with the public but anyone interested in the data set can seek it with written permission from the MEASURE DHS website (URL: https://www.dhsprogram.com/data/available-datasets.cfm).

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