Factors associated with problem drinking among women employed in food and recreational facilities in northern Tanzania.

BACKGROUND: There is growing evidence that alcohol consumption is associated with increased risk of HIV infection. To determine factors associated with problem drinking, we analyzed data collected in two prospective cohorts of at-risk female food and recreational facility workers in northern Tanzania. METHODS: We enrolled HIV seronegative women aged 18-44 years and employed in the towns of Geita, Kahama, Moshi, and Shinyanga. At enrolment, women were interviewed to obtain information about alcohol use, using CAGE and AUDIT screening scales, and risk factors for HIV infection. Blood and genital samples were collected for detection of HIV and sexually transmitted infections (STIs). We characterized alcohol use, concordance, and agreement of the scales, and examined the associations between characteristics of participants and problem drinking as defined by both scales using logistic regression. Lastly, we assessed problem drinking as a risk factor for recent sexual behavior and prevalent STIs. RESULTS: Among enrollees, 68% women reported ever drinking alcohol; of these 76% reported drinking alcohol in the past 12 months. The prevalence of problem drinking was 20% using CAGE and 13% using AUDIT. Overall concordance between the scales was 75.0% with a Kappa statistic of 0.58. After adjusting for age, independent factors associated with problem drinking, on both scales, were marital status, occupation, facility type, increasing number of lifetime sexual partners, and transactional sex in the past 12 months. In addition, women who were problem drinkers on either scale were more likely to report having ≥ 1 sexual partner (CAGE: aOR = 1.56, 95% confidence interval, CI: 1.10-2.23; AUDIT: aOR = 2.00, 95% CI: 1.34-3.00) and transactional sex (CAGE: aOR = 1.79, 95% CI: 1.26-2.56; AUDIT: aOR = 1.51, 95% CI: 1.04-2.18), in the past 3 months. CONCLUSION: These findings suggest that interventions to reduce problem drinking in this population may reduce high-risk sexual behaviors and contribute in lowering the risk of HIV infection

Chlamydia trachomatis variant not detected by plasmid based nucleic acid amplification tests: molecular characterisation and failure of single dose azithromycin

OBJECTIVE: To characterise a Chlamydia trachomatis variant strain from a patient with non-gonococcal urethritis (NGU) whose first void urine (FVU) displayed discrepant Ctrachomatis test results and describe the clinical response to treatment. METHODS: The FVU specimen was assayed with an immune based Chlamydia Rapid Test (CRT) and various nucleic acid amplification tests (NAATs) to establish C trachomatis infection. Sequencing of the major outer membrane protein gene (omp1 also known as ompA) was undertaken to identify the serovar of the variant strain. Polymerase chain reaction (PCR) analysis was also conducted to determine whether the strain harboured deletions in the cryptic plasmid or was plasmid free. RESULTS: The FVU specimen was strongly reactive in CRT but negative with the plasmid based Amplicor PCR (Roche) and ProbeTec ET (Becton-Dickinson) assays. However, NAATs for 16S RNA (Aptima Combo 2, GenProbe), omp1 (RealArt CT PCR, Artus and in-house NAATs) or the outer membrane complex B protein gene (omcB) established C trachomatis infection. Sequencing of omp1 showed that the variant belonged to serovar I. PCR analysis indicated that the variant was plasmid free. The patient did not respond to single dose azithromycin treatment but subsequently responded to a course of doxycycline. CONCLUSIONS: A pathogenic plasmid free C trachomatis variant was identified. Clinicians should be alerted to the possibility of undetected C trachomatis infection caused by such variants and the potential of azithromycin failure in patients with recurrent chlamydial NGU. The occurrence of this variant is rare and should not form the basis for judgment of the performance or usefulness of plasmid based NAATs for C trachomatis detection

CAGE and AUDIT alcohol screening questions.

<p>¹ A possible score of 4 on the CAGE scale.</p><p>² A possible score of 40 on the AUDIT scale.</p><p>³ Computed using these open-ended questions: (i) On average, how many days do you drink an alcohol-containing beverage in a week? (ii) On average, how many drinks containing alcohol do you have on a typical day when you are drinking?</p

Associations of problem drinking with reported sexual behaviors in the past 3 months and sexually transmitted infections at the time of enrollment in a cohort of women working in food and recreational facilities in northern Tanzania.

<p>¹ A score of ≥2 out of a possible 4 on the CAGE scale.</p><p>² A score of ≥8 out of a possible 40 on the AUDIT scale.</p><p>³ The following potential confounders were considered: age, education, marital status, enrolment site, SES, age at first sex, facility type, occupation, age at first sex, lifetime partners, transactional sex in past 12, and forced sex ever. Age was retained in all models. Variables which changed the age-adjusted OR for the association of problem drinking with each outcome by >10% were retained.</p

Associations between problem drinking (based on CAGE and AUDIT) and long-term sexual behavior, socio-demographic and economic factors at the time of enrollment in a cohort of women working in food and recreational facilities in northern Tanzania.

<p>¹ A score of ≥2 out of a possible 4 on the CAGE scale.</p><p>² A score of ≥8 out of a possible 40 on the AUDIT scale.</p><p>³ Adjusted for independent predictors of problem drinking: age group (a priori confounder), marital status, enrolment site, facility type, lifetime sexual partners, transactional sex in past 12 months, and forced sex ever (variables shown in bold).</p><p>⁴ Adjusted for independent predictors of problem drinking: age group (a priori confounder), marital status, occupation, lifetime sexual partners, transactional sex in past 12 months, and forced sex ever (variables shown in bold).</p><p>⁵ Asset index based on household characteristics and assets using principal component analysis.</p><p>⁶ Adjusted for all factors listed in footnote 4, except occupation.</p><p>⁷ Informal food sellers at makeshift facilities.</p><p>⁸ Traditionally brewed alcohol vendors.</p><p>⁹ Adjusted for all factors listed in footnote 3, except facility type.</p