Evaluation of Parametric Statistical Methods in Predicting Factors Influencing Hepatitis B and HIV Among Female Sex Workers
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University of Ghana
Abstract
Purpose
This study evaluates parametric statistical methods, including logistic regression, Poisson
regression, and Cox proportional hazards models, to determine factors influencing Hepatitis B
Virus (HBV) and Human Immunodeficiency Virus (HIV) infections among female sex workers
(FSWs) in Ghana. The research focuses on infection prevalence and the effectiveness of the
Cox model in identifying significant predictors.
Methods
A cross-sectional survey with biological sampling and structured interviews was conducted
among 7,000 participants. Time Location Sampling ensured representativeness. The
prevalence of HBV and HIV was calculated, and a Cox proportional hazards model was used
to identify significant predictors, with hazard ratios (HR) and p-values evaluated to measure
risk associations.
Results
HBV prevalence was 6.53% (95% CI: 6.08–7.01%), and HIV prevalence was 4.53% (95% CI:
3.46–5.92%). Significant predictors for HBV included alcohol use during sex (HR = 1.34, p =
0.042) and healthcare avoidance due to stigma (HR = 1.64, p = 0.023). For HIV, older age was
strongly associated with increased risk, with hazard ratios of 1.60 (p = 0.007) for ages 25–35
and 2.20 (p = 0.001) for ages above 35. Education was a protective factor for HIV, with
secondary education reducing risk by 67% (HR = 0.33, p < 0.001) and higher education by
60% (HR = 0.40, p = 0.019). The Cox model outperformed logistic and Poisson regression,
demonstrating superior discriminatory ability. Conclusions
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The Cox proportional hazards model provided robust identification of risk factors for HBV and
HIV. Behavioural and systemic determinants like alcohol use, stigma, age, and education
significantly influenced infection risks. These findings underscore the need for targeted public
health interventions, particularly addressing alcohol-related behaviours, stigma, and health
literacy.
Description
MSc. Biostatistics
