Exploring the HIV continuum of care among young black MSM

<div><p>Background</p><p>HIV disproportionately impacts young, black men who have sex with men (YBMSM) who experience disparities across the HIV care continuum. A more nuanced understanding of facilitators and barriers to engagement in care, missed visits, antiretroviral uptake, adherence and viral suppression could improve care and intervention design.</p><p>Methods</p><p>A randomized controlled trial of an online intervention, healthMpowerment, enrolled 465 YBMSM (18–30 years); 193 identified as HIV-positive. Bivariable and multivariable analyses of baseline data explored predictors of: engagement in care, missed visits, antiretroviral uptake, self-reported adherence, and viral suppression.</p><p>Results</p><p>Mean age was 24.9 years; most identified as gay (71.0%) and were receiving HIV care (89.1%). Among those in care, 52.1% reported no missed visits in the past 12 months, 41 (24.6%) reported one missed visit, and 39 (23.4%) reported two or more. Having insurance (prevalence odds ratio [POR] 4.5; 95% CI: 1.3, 15.8) and provider self-efficacy (POR 20.1; 95% CI: 6.1, 64.1) were associated with being in care. Those with a college degree (POR 9.1; 95% CI: 1.9, 45.2) and no recent marijuana (POR 2.6; 95% CI: 1.2, 5.6) or methamphetamine use (POR 5.4; 95% CI: 1.0, 28.5) were less likely to miss visits. Most (n = 153, 84.1%) had been prescribed antiretroviral therapy. A majority of participants (70.8%) reported ≥90% adherence; those with depressive symptoms had 4.7 times the odds of reporting adherence <90% (95% CI: 1.65, 13.37). Of participants who reported viral load testing in the past six months, 65% (n = 102) reported an undetectable viral load. Disclosure to sex partners was associated with viral suppression (POR 6.0; 95% CI: 1.6, 22.4).</p><p>Conclusions</p><p>Multi-level facilitators and barriers to engagement across the continuum of care were identified in this sample of YBMSM. Understanding the distinct needs of YBMSM at each stage of the continuum and addressing them through tailored approaches is critical for long term success in care.</p></div

Bivariable and multivariable analysis for antiretroviral therapy uptake.

<p>Bivariable and multivariable analysis for antiretroviral therapy uptake.</p

Bivariable and multivariable analysis for engagement in care and no missed visits.

<p>Bivariable and multivariable analysis for engagement in care and no missed visits.</p

Descriptive statistics of HIV-positive HMP participants at study entry.

<p>Descriptive statistics of HIV-positive HMP participants at study entry.</p

Bivariable and multivariable analysis for self-reported antiretroviral adherence and viral suppression.

<p>Bivariable and multivariable analysis for self-reported antiretroviral adherence and viral suppression.</p

The Epidemiology of Chronic Kidney Disease in Northern Tanzania: A Population-Based Survey

<div><p>Background</p><p>In sub-Saharan Africa, kidney failure has a high morbidity and mortality. Despite this, population-based estimates of prevalence, potential etiologies, and awareness are not available.</p><p>Methods</p><p>Between January and June 2014, we conducted a household survey of randomly-selected adults in Northern Tanzania. To estimate prevalence we screened for CKD, which was defined as an estimated glomerular filtration rate ≤ 60 ml/min/1.73m2 and/or persistent albuminuria. We also screened for human immunodeficiency virus (HIV), diabetes, hypertension, obesity, and lifestyle practices including alcohol, tobacco, and traditional medicine use. Awareness was defined as a self-reported disease history and subsequently testing positive. We used population-based age- and gender-weights in estimating prevalence, and we used generalized linear models to explore potential risk factors associated with CKD, including living in an urban environment.</p><p>Results</p><p>We enrolled 481 adults from 346 households with a median age of 45 years. The community-based prevalence of CKD was 7.0% (95% CI 3.8-12.3), and awareness was low at 10.5% (4.7-22.0). The urban prevalence of CKD was 15.2% (9.6-23.3) while the rural prevalence was 2.0% (0.5-6.9). Half of the cases of CKD (49.1%) were not associated with any of the measured risk factors of hypertension, diabetes, or HIV. Living in an urban environment had the strongest crude (5.40; 95% CI 2.05-14.2) and adjusted prevalence risk ratio (4.80; 1.70-13.6) for CKD, and the majority (79%) of this increased risk was not explained by demographics, traditional medicine use, socioeconomic status, or co-morbid non-communicable diseases (NCDs).</p><p>Conclusions</p><p>We observed a high burden of CKD in Northern Tanzania that was associated with low awareness. Although demographic, lifestyle practices including traditional medicine use, socioeconomic factors, and NCDs accounted for some of the excess CKD risk observed with urban residence, much of the increased urban prevalence remained unexplained and will further study as demographic shifts reshape sub-Saharan Africa.</p></div

Characteristics of NYC public schools reporting and not reporting substantial ILI in spring 2009.

a<p>Participating schools compared to nonparticipating schools.</p>b<p>Chi-square test.</p>§<p>Satterthwaite T-test of Mean Difference, two-sided exact <b>Pr>|t|</b>.</p>*<p>A federal program that provides financial assistance to Local Education Agencies and schools with high numbers or high percentages of poor children.</p>†<p>The percentage of public schools where ≥75% of students are eligible for free or reduced price lunch.</p>¶<p>Proportion of each ethnic group in schools.</p

Forest plot.

<p>The crude and fully-adjusted (model 4) prevalence risk ratios for CKD by each variable relative to the reference group for each variable.</p

Venn diagram.

<p>The proportion of CKD associated with HIV, hypertension, and diabetes.</p

Characteristics of the Survey Sample.

<p>§ Other tribal ethnicities represented in our groups include Luguru, Kilindi, Kurya, Mziguwa, Mnyisanzu, Rangi, Jita, Nyambo, and Kaguru</p><p># Includes housewives and students</p><p>† Professional includes any salaried position (e.g. nurse, teacher, government employee, etc.) and retired persons</p><p>* Heart Disease includes coronary disease, heart failure, or structural diseases</p><p>Characteristics of the Survey Sample.</p