Search

Background African ancestry individuals with comparable overall anthropometric measures to Europeans have lower abdominal adiposity. To explore the genetic underpinning of different adiposity patterns, we investigated whether genetic risk scores for well-studied adiposity phenotypes like body mass index (BMI) and waist circumference (WC) also predict other, less commonly measured adiposity measures in 2420 African American individuals from the Jackson Heart Study. Methods Polygenic risk scores (PRS) were calculated using GWAS-significant variants extracted from published studies mostly representing European ancestry populations for BMI, waist-hip ratio (WHR) adjusted for BMI (WHRBMIadj), waist circumference adjusted for BMI (WCBMIadj), and body fat percentage (BF%). Associations between each PRS and adiposity measures including BF%, subcutaneous adiposity tissue (SAT), visceral adiposity tissue (VAT) and VAT:SAT ratio (VSR) were examined using multivariable linear regression, with or without BMI adjustment. Results In non-BMI adjusted models, all phenotype-PRS were found to be positive predictors of BF%, SAT and VAT. WHR-PRS was a positive predictor of VSR, but BF% and BMI-PRS were negative predictors of VSR. After adjusting for BMI, WHR-PRS remained a positive predictor of BF%, VAT and VSR but not SAT. WC-PRS was a positive predictor of SAT and VAT; BF%-PRS was a positive predictor of BF% and SAT only. Conclusion These analyses suggest that genetically driven increases in BF% strongly associate with subcutaneous rather than visceral adiposity and BF% is strongly associated with BMI but not central adiposity-associated genetic variants. How common genetic variants may contribute to observed differences in adiposity patterns between African and European ancestry individuals requires further study.

Subject to a high burden of diarrheal diseases, Afghanistan is also susceptible to climate change. This study investigated the spatiotemporal distribution of diarrheal disease in the country and how associated it is with climate variables. Using monthly aggregated new cases of acute diarrhea reported between 2010 and 2016 and monthly averaged climate data at the district level, we fitted a hierarchical Bayesian spatiotemporal statistical model. We found aridity and mean daily temperature were positively associated with diarrhea incidence; every 1°C increase in mean daily temperature and 0.01-unit change in the aridity index were associated with a 0.70% (CI: 0.67%, 0.73%) increase and a 4.79% (CI: 4.30%, 5.26%) increase in the risk of diarrhea, respectively. Average annual temperature, on the other hand, was negatively associated, with a 3.7% (CI: 3.74%, 3.68) decrease in risk for every degree Celsius increase in annual average temperature. Temporally, most districts exhibited similar seasonal trends, with incidence peaking in summer, except for the eastern region where differences in climate patterns and population density may be associated with high rates of diarrhea throughout the year. The results from this study highlight the significant role of climate in shaping diarrheal patterns in Afghanistan, allowing policymakers to account for potential impacts of climate change in their public health assessments.

This study reviewed trends in the incidence of common communicable diseases among children under five years in Afghanistan between 2005 and 2013, a period of expansion of public health services. New visits to outpatient clinics constituted the denominator for calculating proportions. In 2013, almost three-quarters of all new visits of children to public health services were for an infectious disease, with respiratory infections the most common. Because of inconsistent data collection for some infections early in the period, the trend for infectious diseases as a whole cannot be estimated. However, there was a statistically significant downward trend in the proportion of new visits that were diagnosed as one of the 11 leading communicable diseases from 74.5% in 2005 to 62.1% in 2013 (P0.001). There was no difference in communicable disease patterns between provinces, but a higher per capita consultation rate was associated with a higher proportion of the leading infections (P = 0.008). Recent improvements in maternal health, hygiene, and preventive services may have had an impact in reducing the burden of infections.اتجاهات معدلات حدوث الأمراض المعدية بين الأطفال في أفغانستان في وقت توسيع الخدمات الصحية.محمد ياسر أنور، جلبرت بورنهام.تستعرض هذه الدراسة اتجاهات معدلات حدوث الأمراض السارية الشائعة بن الأطفال دون سن الخامسة في أفغانستان في الفرة بن 2005 و 2013. وتم اتخاذ عدد الزيارات الجديدة لعيادات المرضى الخارجن ليكون المقام عند حساب النِّسَب. وفي عام 2013 كان ما يقرب من ثلاثة أرباع إجمالي الزيارات الجديدة التي قام بها الأطفال للخدمات الصحية في القطاع العام بسبب الأمراض المعدية، وكانت الأمراض التنفسية هي الأكثر شيوعاً. وبسبب عدم التناسق في جمع البيانات حول بعض الأمراض المعدية في وقت مبكر فإن اتجاه الأمراض المعدية عى وجه الإجمال يتعذر تقديرها. إلا أنه كان هناك اتجاه متناقص ذو أهمية إحصائية لنسب الزيارات الجديدة التي يتم تشخيصها عى أنها أحد الأمراض الأحد عر السارية الرئيسية، فبعد أن كانت % 74.5 عام 2005 أصبحت %62.1 عام 2013 (0.001p). ولم يكن هناك فرق في أناط الأمراض السارية بن الولايات، ولكن معدل الاستشارات لكل نسمة ترافق بنسبة أعى مع العدوى الرئيسية (0.008 = p). إن جوانب التحسن التي طرأت مؤخراً عى صحة الأمهات وعى النظافة الشخصية وعى الخدمات الوقائية قد يكون لها تأثر في خفض عبء العدوى.Tendances de l’incidence des maladies infectieuses chez les enfants en Afghanistan à l’heure de l’élargissement des services de santé publique.La présente étude a étudié les tendances de l’incidence des maladies transmissibles les plus répandues chez les enfants de moins de cinq ans en Afghanistan entre 2005 et 2013. Les premières consultations en soins ambulatoires ont constitué le dénominateur pour calculer les pourcentages. En 2013, près de trois quarts de toutes les premières consultations d’enfants dans les services de santé publique avaient pour cause une maladie infectieuse, les infections respiratoires étant les plus fréquentes. Du fait d’une collecte des données incohérente pour certaines infections au début de la période d’étude, les tendances pour les maladies infectieuses dans leur ensemble ne peuvent être estimées. Pour autant, une tendance à la baisse statistiquement significative a été observée en ce qui concerne le nombre de premières visites pour lesquelles le diagnostic établi était l’une des 11 maladies transmissibles les plus répandues (74,5 % en 2005 contre 62,1 % en 2013, soit p0,0001). Aucune différence en termes de caractéristiques des maladies transmissibles n’a été établie entre les provinces, mais un taux de consultation plus élevé par habitant a été associé avec un pourcentage plus élevé pour les infections principales (p = 0,008). Les récentes améliorations en matière de santé maternelle, d’hygiène et de services de prévention ont pu avoir une influence sur la réduction de la charge des infections.

Background Malaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region. Methods This study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models. Results Two models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts. Conclusion Results indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level. Electronic supplementary material The online version of this article (doi:10.1186/s12936-016-1602-1) contains supplementary material, which is available to authorized users.