Socio-Demographic Determinants of HIV Infection Status among Patients Attending Public Hospitals in Akwa Ibom North-West Senatorial District, Nigeria
DOI:
https://doi.org/10.5281/zenodo.21294313Keywords:
HIV infection status, socio-demographic characteristics, logistic regression, adjusted odds ratio (AOR), Akwa Ibom North-West Senatorial District, patients, hospitals.Abstract
This study investigated the influence of socio-demographic characteristics on the HIV infection status of patients attending public hospitals in Akwa Ibom North-West Senatorial District, Nigeria. Data were obtained from patients attending four randomly selected public hospitals between 2021 and 2025. The study covered eight public hospitals across the senatorial district, from which four hospitals were selected using simple random sampling. A total of 2,611 patient records were analysed, comprising 1,581 (60.6%) HIV-negative and 1,030 (39.4%) HIV-positive patients. The explanatory variables included family history of HIV infection, sex, marital status, educational level, employment status, place of residence, age, CD4 count, and growth phase, while HIV infection status served as the binary response variable. Descriptive statistics and multiple binary logistic regression were used for data analysis.The results showed that family history of HIV infection was the strongest predictor of HIV-positive status (AOR = 93.31, 95% CI: 35.28–246.80, p < 0.001). Male patients had significantly higher odds of HIV infection than females (AOR = 1.774, 95% CI: 1.491–2.110, p < 0.001). Compared with the reference categories, patients with primary (AOR = 1.748, p = 0.006) and secondary education (AOR = 2.089, p = 0.001), government-employed patients (AOR = 1.260, p = 0.036), and patients aged 11–20 years (AOR = 2.187, p = 0.038), 21–30 years (AOR = 3.134, p = 0.003), 31–40 years (AOR = 3.495, p = 0.001), 41–50 years (AOR = 4.625, p < 0.001), and 51–60 years (AOR = 4.034, p = 0.001) had significantly higher odds of testing HIV-positive. Conversely, urban residence was associated with significantly lower odds of HIV infection than rural residence (AOR = 0.818, 95% CI: 0.688–0.973, p = 0.023). The logistic regression model demonstrated an adequate fit to the data (Hosmer–Lemeshow χ² = 10.661, df = 8, p = 0.222) and an overall classification accuracy of 68.9%. The study concludes that family history of HIV infection, sex, marital status, educational level, employment status, residence, and age are significant determinants of HIV infection status among patients attending public hospitals in Akwa Ibom North-West Senatorial District. The findings underscore the need for targeted HIV prevention, screening, and public health interventions focusing on socio-demographic groups at greater risk of HIV infection.
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Copyright (c) 2026 Unyime Patrick Udoudo (Translator); Eduma E. Essien, Emmanuel John Ekpenyong (Author)

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