The purpose of this study was to examine the impact of a sport nutrition education and life-skills intervention on sport nutrition knowledge (SNK), attitudes/beliefs and dietary behaviors relevant to sport nutrition among high school (HS) soccer players. Three assessments were done over the 2-year intervention (baseline = time 1, end year 1 = time 2, end year 2 = time 3). Participants (n = 217; females = 64%; Latino = 47.5%; 14.9 ± 0.9-year; 46.5% National School Breakfast/Lunch Program) were assigned to an intervention group (IG, n = 153; 9 schools) or comparison group (CG, n = 64; 4 schools) based on geographical location. Differences over time were examined based on group, sex, socioeconomic status (SES) and race/ethnicity. The IG increased SNK scores by ~10% (time 1 = 51.6%; time 3 = 60.9%; p ≤ 0.001), with the greatest change in the female IG vs. CG and no differences in male IG vs. CG. Daily breakfast consumption was 53.7% in both groups. IG players were 3 times more likely (95%CI = 2.59, 7.77) to report trying to eat for performance (IG = 48.7% vs. CG = 30.2%). By time 3, IG players were less likely to report that ‘diet met nutritional requirements’ (31.6%) compared to CG (47.6%). For IG, the consumption of lunch (≥5-days/week) did not change (92.2–93.4%), but declined in the CG (90.6%) (p = 0.04). No other differences by sub-population (race/ethnicity, SES) were observed. Our findings indicate that HS athletes are motivated to learn and improve diet behaviors, and benefit from team-based nutrition interventions. Future interventions should consider delivery of curriculum/experiential learning during a defined training period, with messages reinforced with supports at home, school and athletic settings.

Food insecurity among U.S. older adults has more than doubled since 2001 and is higher in those who are frail. Given the growing aging population and the importance of physical functioning and adequate food intake, the increase in food insecurity is a public health concern. This study examined the association between domains of physical limitations and food security in U.S. older adults. Data were from the National Health and Nutrition Examination Survey (2007-2012) participants 60 years of age and older (n = 5969). Physical limitations were defined as some or much difficulty on 19 activities, categorized into 5 domains and an index score. Food security status was categorized as full, marginal, low, or very low, and also dichotomized into food secure and food insecure (marginal, low, or very low food security). Multinomial and logistic regression models were used to estimate odds ratios (OR) and adjusted ORs (aOR) with food security as the dependent variable and physical limitations as independent variables. Older adults with 4 or more physical limitations were more likely to report very low food security than older adults without limitations (aOR:2.62, 95% CI:1.43, 4.81). The strongest correlates of food insecurity were Instrumental Activities of Daily Living (aOR:1.49; 95% CI:1.10, 2.01), Leisure and Social Activities (aOR:1.56; 95% CI:1.37, 2.14), and General Physical Activities (aOR:1.50; 95% CI:1.08, 2.07). Physical functioning is important for food security among older adults. Interventions should incorporate assessment of physical functioning, and provide resources for food acquisition, preparation, and intake for older adults with physical limitations.

Zimbabwe has made substantial progress towards the Joint United Nations Programme on HIV/AIDS (UNAIDS) targets of 90-90-90 by 2020, with 73% of people living with HIV diagnosed, 87% of those diagnosed on antiretroviral therapy (ART) and 86% of those on ART virally suppressed. Despite this exceptional response, more effort is needed to completely achieve the UNAIDS targets. Here, we conducted a detailed spatial analysis of the geographical structure of the HIV epidemic in Zimbabwe to include geographical prioritization as a key component of their overall HIV intervention strategy. Data were obtained from Zimbabwe Demographic and Health Survey (ZDHS) conducted in 2015 as well as estimations from the Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2016 report, and other published literature. Data were used to produce high-resolution maps of HIV prevalence. Using these maps combined with the population density maps, we mapped the HIV-infected population lacking ART coverage and viral suppression. HIV maps for both sexes illustrated similar geographical variation of HIV prevalence within the country. HIV-infected populations lacking ART coverage and viral suppression were concentrated in the main cities and urban settlements such as Bulawayo, Harare, Ruwa and Chitungwiza. Our study showed extensive local variation in HIV disease burden across Zimbabwe for both women and men. The high-resolution maps generated here identified areas wherein high density of HIV-infected individuals are lacking ART coverage and viral suppression. These results suggest that there is need to tailor HIV programmes to address specific local needs to efficiently achieve epidemic control in Zimbabwe.

A novel semiparametric regression model is developed for evaluating the covariate‐specific accuracy of a continuous medical test or biomarker. Ideally, studies designed to estimate or compare medical test accuracy will use a separate, flawless gold‐standard procedure to determine the true disease status of sampled individuals. We treat this as a special case of the more complicated and increasingly common scenario in which disease status is unknown because a gold‐standard procedure does not exist or is too costly or invasive for widespread use. To compensate for missing data on disease status, covariate information is used to discriminate between diseased and healthy units. We thus model the probability of disease as a function of ‘disease covariates’. In addition, we model test/biomarker outcome data to depend on ‘test covariates’, which provides researchers the opportunity to quantify the impact of covariates on the accuracy of a medical test. We further model the distributions of test outcomes using flexible semiparametric classes. An important new theoretical result demonstrating model identifiability under mild conditions is presented. The modeling framework can be used to obtain inferences about covariate‐specific test accuracy and the probability of disease based on subject‐specific disease and test covariate information. The value of the model is illustrated using multiple simulation studies and data on the age‐adjusted ability of soluble epidermal growth factor receptor – a ubiquitous serum protein – to serve as a biomarker of lung cancer in men.SAScode for fitting the model is provided. Copyright © 2015 John Wiley & Sons, Ltd.