Evaluation of statistical regression models in predicting factors influencing HBV and HIV among female sex workers in Ghana: A Bio-behavioural survey.

PURPOSE

This study aims to evaluate the effectiveness of parametric statistical methods-specifically logistic regression, Poisson regression, and Cox proportional hazards models-in identifying factors influencing Hepatitis B Virus (HBV) and Human Immunodeficiency Virus (HIV) infections among female sex workers (FSWs) in Ghana. The primary focus is to assess infection prevalence and determine how well the Cox model identifies significant predictors.

METHODS

A cross-sectional survey was conducted, recruiting 7,000 female sex workers (FSWs), with 5,990 completing both biological sampling and structured interviews, 5,052 for HBV and 5,426 for HIV variables. Time-location sampling ensured a representative sample. The prevalence of HBV and HIV was calculated, and a Cox proportional hazards model was employed to identify key risk factors. Hazard ratios (HRs) and p-values were used to evaluate the strength and significance of these associations.

RESULT

The prevalence of HBV among FSWs was found to be 6.53% (95% CI: 6.08%-7.01%), while the prevalence of HIV was 4.53% (95% CI: 3.46%-5.92%). Significant predictors for HBV included alcohol consumption during sex (HR = 1.34, p = 0.042) and avoidance of healthcare due to stigma (HR = 1.64, p = 0.023). For HIV, older age was a significant risk factor, with hazard ratios of 1.60 (p = 0.007) for individuals aged 25-35 and 2.20 (p = 0.001) for those over 35 years old. Education appeared to be a protective factor: secondary education reduced HIV risk by 67% (HR = 0.33, p < 0.001), and higher education reduced risk by 60% (HR = 0.40, p = 0.019). The Cox model outperformed both logistic and Poisson regression in its ability to discriminate between risk factors and predict infection outcomes.

CONCLUSIONS

The Cox proportional hazards model proved highly effective in identifying the key risk factors for both HBV and HIV. Behavioral factors like alcohol use, social determinants such as stigma, and demographic variables such as age and education played significant roles in influencing infection risks. These findings highlight the need for tailored public health interventions that address alcohol-related behaviors, reduce stigma, and improve health literacy among FSWs.