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BACKGROUND AND AIMS: Reduction of alcohol consumption is important for people undergoing treatment for HIV. We tested the efficacy of a brief intervention for reducing the average volume of alcohol consumed among patients on HIV antiretroviral therapy (ART). DESIGN, SETTING AND PARTICIPANTS: This study used a two-arm multi-centre randomized controlled trial with follow-up to 6 months. Recruitment occurred between May 2016 and October 2017 at six ART clinics at public hospitals in Tshwane, South Africa. Participants were people living with HIV, mean age 40.8 years [standard deviation (SD) = 9.07], 57.5% female, and on average 6.9 years (SD = 3.62) on ART. At baseline (BL), the mean number of drinks consumed over the past 30 days was 25.2 (SD = 38.3). Of 756 eligible patients, 623 were enrolled. INTERVENTION: Participants were randomly assigned to a motivational interviewing (MI)/problem-solving therapy (PST) intervention arm (four modules of MI and PST delivered over two sessions by interventionists) or a treatment as usual (TAU) comparison arm. People assessing outcomes were masked to group assignment. MEASUREMENTS: The primary outcome was the number of standard drinks (15 ml pure alcohol) consumed during the past 30 days assessed at 6-month follow-up (6MFU). FINDINGS: Of the 305 participants randomized to MI/PST, 225 (74%) completed the intervention (all modules). At 6MFU, retention was 88% for the control and 83% for the intervention arm. In support of the hypothesis, an intention-to-treat-analysis for the primary outcome at 6MFU was -0.410 (95% confidence interval = -0.670 to -0.149) units lower on log scale in the intervention group than in the control group (P = 0.002), a 34% relative reduction in the number of drinks. Sensitivity analyses were undertaken for patients who had alcohol use disorders identification test (AUDIT) scores ≥ 8 at BL (n = 299). Findings were similar to those of the whole sample. CONCLUSIONS: In South Africa, a motivational interviewing/problem-solving therapy intervention significantly reduced drinking levels in HIV-infected patients on antiretroviral therapy at 6-month follow-up.

Introduction Consumption of unhealthy foods in children contributes to high levels of childhood obesity globally. In developing countries there is paucity of empirical studies on the association. This study employed propensity-score methods to evaluate the effect of unhealthy foods on overweight among children in Malawi using observational data. Methods Data on 4625 children aged 6 to 59 months from the 2015-16 Malawi Demographic and Health Survey (MDHS) were analyzed. A multivariable logistic regression model of unhealthy foods (yes or no) on purported confounders of childhood overweight was used to obtain a child's unhealthy food propensity score. The propensity scores were then used to form matched sets of healthy and unhealthy fed children. The association between unhealthy foods and childhood overweight was assessed using the conditional logistic regression model. Results The prevalence of overweight (body mass index (BMI) z-score > 2 standard deviations) was estimated at 4.5% (3.8%, 5.3%). The proportion of children who consumed unhealthy foods was estimated at 14.6% (95% CI: 13.1%, 16.2%). Our propensity score matching achieved a balance in the distribution of the confounders between children in the healthy and unhealthy food groups. Children fed unhealthy foods were significantly more likely to be overweight than those fed healthy foods (OR = 2.5, 95% CI: (1.2, 5.2)). Conclusion The findings suggest the adverse effects of unhealthy foods on childhood overweight in Malawi. Thus, efforts to reduce unhealthy food consumption among children should be implemented and supported to address the problem of childhood overweight in Malawi and the sub-Saharan African region., Author(s): Halima S. Twabi [sup.1] , Samuel O. M Manda [sup.2] , Dylan S. Small [sup.3] Author Affiliations: (1) grid.10595.38, 0000 0001 2113 2211, Department of Mathematical Sciences, University of [...]

Objective To profile the prevalence of the three body mass index (BMI) categories by sociodemographic characteristics, and to calculate the percentage transitioning (or not) from one BMI category to another, to inform South African health policy for the control of obesity and noncommunicable diseases. Methods We used data from the National Income Dynamics Study, including sociodemographic characteristics and BMI measurements collected in 2008, 2010, 2012, 2014 and 2017. For each data collection wave and each population group, we calculated mean BMI and prevalence by category. We also calculated the percentage making an upwards transition (e.g. from overweight to obese), a downwards transition or remaining within a particular category. We used a multinomial logistic regression model to estimate transition likelihood. Findings Between 2008 and 2017, mean BMI increased by 2.3 kg/[m.sup.2]. We calculated an increased prevalence of obesity from 19.7% (3686/18 679) to 23.6% (3412/14 463), with the largest increases in prevalence for those aged 19-24 years and those with at least high school education. The percentages of upwards transitions to overweight or obese categories increased sharply between the ages of 19 and 50 years. Once overweight or obese, the likelihood of transitioning to a normal BMI is low, particularly for women, those of higher age groups, and those with a higher income and a higher level of education. Conclusion In the development of national strategies to control obesity and noncommunicable diseases, our results will allow limited public health resources to be focused on the relevant population groups. Objectif Etablir la prevalence des trois categories d'indice de masse corporelle (IMC) en fonction des caracteristiques sociodemographiques, et calculer le pourcentage de transition (ou d'absence de transition) d'une categorie d'IMC a l'autre, afin de renseigner les politiques de sante sud-africaines visant a lutter contre l'obesite et les maladies non transmissibles. Methodes Nous avons exploite les donnees provenant de l'Enquete nationale sur la dynamique des revenus (NIDS), notamment les caracteristiques sociodemographiques et les mesures de l'IMC recoltees en 2008, 2010, 2012, 2014 et 2017. Pour chaque vague de collecte de donnees et chaque groupe de population, nous avons calcule l'IMC moyen et la prevalence par categorie. Nous avons egalement determine le pourcentage de passages vers la categorie superieure (en surpoids a obese par exemple), de passages vers la categorie inferieure et de maintien au sein d'une categorie specifique. Enfin, nous avons employe un modele de regression logistique multinomiale pour estimer la probabilite de transition. Resultats Entre 2008 et 2017, l'IMC moyen a augmente de 2,3 kg/[m.sup.2]. Nous avons observe une prevalence accrue pour l'obesite, passee de 19,7% (3686/18 679) a 23,6% (3412/14 463). Cette hausse touche principalement les 19-24 ans et ceux possedant au moins un diplome d'etudes secondaires. Le pourcentage de passage a la categorie superieure, vers le surpoids ou l'obesite, a fortement augmente chez les personnes agees de 19 a 50 ans. Une fois en surpoids ou obese, la probabilite de repasser a un IMC normal est faible, surtout chez les femmes, les personnes plus agees, ceux dont les revenus sont plus importants et dont le niveau d'education est plus eleve. Conclusion Dans le cadre du developpement de strategies nationales destinees a lutter contre l'obesite et les maladies non transmissibles, nos resultats permettront d'affecter des ressources de sante publique limitees aux groupes de population les plus touches. Objetivo Describir la prevalencia de las tres categorias del indice de masa corporal (IMC) por caracteristicas sociodemograficas y calcular el porcentaje que pasa (o no) de una categoria del IMC a otra con el fin de fundamentar la politica sanitaria de Sudafrica para controlar la obesidad y las enfermedades no transmisibles. Metodos Se usaron los datos del Estudio nacional de la dinamica de los ingresos (NIDS, por sus siglas en ingles), incluidas las caracteristicas sociodemograficas y las mediciones del IMC que se obtuvieron en 2008, 2010, 2012, 2014 y 2017. Se calculo el IMC medio y la prevalencia por categoria para cada fase de recopilacion de datos y cada grupo de poblacion. Tambien se calculo el porcentaje que hace una transicion ascendente (por ejemplo, del sobrepeso a la obesidad), una transicion descendente o que permanece dentro de una categoria en particular. En este contexto, se aplico un modelo de regresion logistica polinomial para estimar la probabilidad de la transicion. Resultados Entre 2008 y 2017, el IMC medio aumento en 2,3 kg/[m.sup.2]. Se calculo un aumento de la prevalencia de la obesidad del 19,7 % (3686/18 679) al 23,6 % (3412/14 463), siendo los mayores aumentos de la prevalencia para las personas de 19 a 24 anos de edad y las que habian cursado al menos estudios secundarios. Los porcentajes de transiciones ascendentes a las categorias de sobrepeso u obesidad aumentaron de manera considerable entre los 19 y los 50 anos de edad. Cuando se tiene sobrepeso o se es obeso, la probabilidad de pasar a un IMC normal es baja, en especial en el caso de las mujeres, las de los grupos de edad avanzada y las que tienen mayores ingresos y un nivel de educacion mas alto. Conclusion Los resultados obtenidos permitiran destinar los recursos limitados de la salud publica a los grupos de poblacion correspondientes en la elaboracion de estrategias nacionales para controlar la obesidad y las enfermedades no transmisibles. [phrase omitted], Introduction The mean body mass index (BMI) of the African population is increasing, (1) resulting in a steady rise of the prevalence of people being overweight or obese across Africa, [...]

In sub-Saharan Africa (SSA), adolescent girls and young women (AGYW) have the highest risk of acquiring HIV. This has led to several studies aimed at identifying risk factors for HIV in AGYM. However, a combination of the purported risk variables in a multivariate risk model could be more useful in determining HIV risk in AGYW than one at a time. The purpose of this study was to develop and validate an HIV risk prediction model for AGYW. We analyzed HIV-related HERStory survey data on 4,399 AGYW from South Africa. We identified 16 purported risk variables from the data set. The HIV acquisition risk scores were computed by combining coefficients of a multivariate logistic regression model of HIV positivity. The performance of the final model at discriminating between HIV positive and HIV negative was assessed using the area under the receiver-operating characteristic curve (AUROC). The optimal cut-point of the prediction model was determined using the Youden index. We also used other measures of discriminative abilities such as predictive values, sensitivity, and specificity. The estimated HIV prevalence was 12.4% (11.7% − 14.0) %. The score of the derived risk prediction model had a mean and standard deviation of 2.36 and 0.64 respectively and ranged from 0.37 to 4.59. The prediction model's sensitivity was 16. 7% and a specificity of 98.5%. The model's positive predictive value was 68.2% and a negative predictive value of 85.8%. The prediction model's optimal cut-point was 2.43 with sensitivity of 71% and specificity of 60%. Our model performed well at predicting HIV positivity with training AUC of 0.78 and a testing AUC of 0.76. A combination of the identified risk factors provided good discrimination and calibration at predicting HIV positivity in AGYW. This model could provide a simple and low-cost strategy for screening AGYW in primary healthcare clinics and community-based settings. In this way, health service providers could easily identify and link AGYW to HIV PrEP services. [ABSTRACT FROM AUTHOR]