Predictors of High HIV+ Prevalence in Mozambique: A Complex Samples Logistic Regression Modeling and Spatial Mapping Approaches

Authors

• Jerry John Nutor, University of California - San Francisco
• Precious Adade Duodu, East Surrey Hospital
• Pascal Agbadi, Kwame Nkrumah University of Science and Technology
• Henry Ofori Duah, Marquette UniversityFollow
• Kelechi Elizabeth Oladimeji, University of Fort Hare
• Kaboni W. Gondwe, University of Wisconsin - Milwaukee

Document Type

Article

Publication Date

6-2020

Publisher

Public Library of Science (PLoS)

Source Publication

PLoS One

Source ISSN

1932-6203

Abstract

Introduction The burden of HIV infection in southern Africa is a public health concern with an increasing number of new infections. This study sought to investigate the predictors of HIV prevalence in Mozambique through a complex samples logistic regression and spatial mapping approach using nationally representative data. Methods We conducted a secondary data analysis using the 2015 Mozambique Demographic and Health Survey and AIDS Indicator Survey. The analysis performed in four stages while incorporating population survey sampling weights did the following: i) created a complex sample plan file in SPSS, ii) performed the weighted estimate of HIV prevalence, iii) performed complex sample chi-square test of independence, and then iv) performed complex sample logistic regression modeling. Results Out of 11,270 participants, 1,469 (13.0%) tested positive for HIV. The prevalence of HIV infection was higher in females (15.1%) than males (10.2%). We found that urban dwellers were more likely to be HIV-positive compared to rural dwellers (AOR: 1.70; CI: 1.27, 2.27). We observed provincial variations in HIV prevalence, with Maputo Cidade (17.4%), Maputo Provincia (22.6%), Gaza (25.2%) recording higher prevalence above the national estimate. Other independent predictors of HIV infection in Mozambique included age, education level, marital status, total lifetime sexual partners, and having had an STI in the last 12 months. Conclusions The study revealed associations between high-risk sexual behavior and HIV infection. Results from our spatial mapping approach can help health policy makers to better allocate resources for cost-effective HIV/AIDS interventions. Pre-Exposure Prophylaxis (PrEP) campaigns among high-risk groups should be pursued to lower the reservoir of HIV among high-risk groups.

Comments

Published version. PLOS One, Vol. 15, No. 6 (2020). DOI. © 2020 John Nutor 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.

Henry Duah was affiliated with FOCOS Orthopaedic Hospital, Accra, Ghana at the time of publication.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Nutor, Jerry John; Duodu, Precious Adade; Agbadi, Pascal; Duah, Henry Ofori; Oladimeji, Kelechi Elizabeth; and Gondwe, Kaboni W., "Predictors of High HIV+ Prevalence in Mozambique: A Complex Samples Logistic Regression Modeling and Spatial Mapping Approaches" (2020). College of Nursing Faculty Research and Publications. 1202.
https://epublications.marquette.edu/nursing_fac/1202