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84-0.89, p less then 0.001). CONCLUSION Achieving targets for HIV epidemic control will require increasing ART retention and reducing the disparity in retention for those with same-day ART.BACKGROUND Men living with HIV (MLHIV) have a high burden of human papillomavirus (HPV)-related cancer. Understanding serological dynamics of HPV in men can guide decisions on introducing HPV vaccination and monitoring impact. We determined HPV seroprevalence and evaluated factors associated with HPV seroconversion among MLHIV in Johannesburg, South Africa. METHODS We enrolled 304 sexually active MLHIV ≥18 years and collected socio-behavioral data, blood samples (CD4+ counts, HIV-1 plasma viral load [PVL] and HPV serology), genital and anal swabs (HPV DNA and HPV Viral Load [VL]) at enrolment and 6-monthly for up to 18 months. Antibodies to 15 HPV types were measured using HPV pseudovirions. Generalised estimating equations were used to evaluate correlates of HPV seroconversion. RESULTS Median age at enrolment was 38 years (IQR22-59), 25% reported >1 sexual partner in the past 3 months and 5% reported ever having sex with other men. Most participants (65%) were on antiretroviral therapy (ART), with median CD4+ count of 445 cells/µL (IQR328-567). Seroprevalence for any-HPV type was 66% (199/303). Baseline seropositivity for any bivalent (16/18), quadrivalent (6/11/16/18) and nonavalent (6/11/16/18/31/33/45/52/58) vaccine-types were 19%, 37% and 60% respectively. At 18 months, type-specific seroconversion among 59 men whose genital samples were HPV-DNA positive but seronegative for the same type at enrolment was 22% (13/59). Type-specific seroconversion was higher among men with detectable HIV-PVL (adjusted odds-ratio [aOR]=2.78, 95%CI1.12-6.77) and high HPV-VL (aOR=3.32, 95%CI1.42-7.74). CONCLUSION Seropositivity and exposure to nonavalent HPV types were high among MLHIV. HPV vaccination of boys before they become sexually active could reduce the burden of HPV infection among this at-risk population.BACKGROUND People with HIV (PWH) may have lower daily activity levels compared to persons without HIV. We sought to determine the impact of initiating a supervised exercise program on the daily step count of sedentary PWH and uninfected controls. METHODS PWH and controls, aged 50-75 were enrolled in a 24-week supervised exercise program. All individuals were given a pedometer and instructed in regular use. A linear mixed model taking into account random effects was used to model daily step count. RESULTS Of 69 participants that began the study, 55 completed and 38 (21 PWH, 17 controls) had complete pedometer data. Baseline daily step count on non-supervised exercise day was (estimated geometric mean, 95% CI) 3543 [1306, 9099] for PWH and 4182 [1632, 10187] for controls. Both groups increased daily steps on supervised (43% [20, 69]%, p less then 0.001) but not unsupervised exercise days (-12% [-24, 1]%, p=0.071). Compared with controls, PWH had 26% ([-47, 4]%, p=0.08) fewer daily steps on days with supervised exercise and 35% ([-53, -10]%, p=0.011) fewer daily steps on days without supervised exercise. Higher BMI (per 1 unit) and smoking were associated with fewer daily steps (-5% [-9, -1]%; -49% [-67, -23]%; p≤0.012). Days with precipitation (-8% [-13, -3]%, p=0.002) or below freezing (-10% [-15, - 4]%, p less then 0.001) were associated with fewer steps. CONCLUSION Supervised exercise increased daily step counts in sedentary individuals, but at the expense of fewer steps on non-supervised exercise days.BACKGROUND HIV disclosure benefits people living with HIV (PLWH), their partners, and HIV programs. However, data on the prevalence of disclosure and associated correlates have come largely from patients already in HIV care, potentially overestimating disclosure rates and precluding examination of the impact of disclosure on HIV care outcomes. SETTING We used data from an implementation study conducted in Maputo City and Inhambane Province, Mozambique. Adults were enrolled at HIV testing clinics following diagnosis and traced in the community 1 and 12 months later when they reported on disclosure and other outcomes. METHODS We examined patterns of participant disclosure to their social networks (N=1573) and sexual partners (N=1024) at both follow-up assessments, and used relative risk regression to identify correlates of non-disclosure. RESULTS Disclosure to one's social network and sexual partners was reported by 77.8% and 57.7% of participants, respectively, at 1 month, and 92.9% and 72.4% of participants, respectively, at 12 months. At both time points, living in Inhambane Province, being single or not living with a partner, having high levels of anticipated stigma and not initiating HIV treatment were associated with increased risks of non-disclosure to social networks. Non-disclosure to sexual partners at both follow-up assessments was associated with being female, living in Inhambane Province and in a household without other PLWH, and reporting that post-test counselling addressed disclosure. CONCLUSION Although reported disclosure to social networks was high, disclosure to sexual partners was sub-optimal. Effective and acceptable approaches to support partner disclosure, particularly for women, are needed.BACKGROUND Stress has a negative impact on fertility by suppressing the secretion of fertility hormones. Although it is known that stress reduces the probability of conception and affects fertility negatively, scales that are now widely used to evaluate fertility preparedness include negative items. Positive statements are crucial to relieving stress in women. Using positive items in assessments of fertility preparedness in women may help reduce related stress. PURPOSE This study was designed to develop the Fertility Preparedness Scale for women receiving fertility treatments. METHODS A methodological study was conducted in four fertility clinics between December 2015 and March 2016. Two hundred thirty women who had been diagnosed with primary or secondary infertility were enrolled as participants. selleck chemical A personal information form and the Fertility Preparedness Scale were used to collect data. RESULTS The Cronbach's alpha was .84 for the total scale and .76-.79 for the subscales. Factor analysis extracted three subscales that explained 52.
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