Harmful Alcohol Use and Associated Socio-Structural Factors among Female Sex Workers Initiating HIV Pre-Exposure Prophylaxis in Dar es Salaam, Tanzania.
Hanne Ochieng LichtwarckMethod Rwelengera KazauraKåre MoenElia John MmbagaPublished in: International journal of environmental research and public health (2022)
Harmful alcohol use is an important risk factor for premature mortality and morbidity and associated with increased HIV risk and lower uptake of and adherence to HIV interventions. This study aimed to assess the extent of harmful alcohol use and associated socio-structural vulnerability factors among female sex workers in Dar es Salaam, Tanzania, a key population in the HIV epidemic. Data from a study of female sex workers initiating pre-exposure prophylaxis (PrEP) recruited through respondent driven sampling were used. We assessed harmful alcohol use with the Alcohol Use Disorders Identification Test (AUDIT) defined as having an AUDIT score ≥ 16. Associations between harmful alcohol use and socio-structural factors were assessed using logistic regression with marginal standardization. Of the 470 women recruited, more than one third (37.3%) had a drinking pattern suggestive of harmful alcohol use. Such use was independently associated with sex work-related mobility (aPR: 1.36, 95% CI: 1.11-1.61), arrest/incarceration (aPR: 1.55, 95% CI: 1.27-1.84) and gender-based violence (aPR: 1.31, 95% CI: 1.06-1.56). The high prevalence of harmful alcohol use and the interconnectedness with socio-structural factors indicate a need for a holistic programmatic approach to health for female sex workers. Programming should not solely direct attention to individual behavior but also include strategies aiming to address socio-structural vulnerabilities.
Keyphrases
- antiretroviral therapy
- hiv positive
- hiv testing
- hiv infected
- men who have sex with men
- human immunodeficiency virus
- hepatitis c virus
- hiv aids
- mental health
- healthcare
- public health
- south africa
- climate change
- electronic health record
- type diabetes
- coronary artery disease
- cardiovascular disease
- deep learning
- adipose tissue
- insulin resistance