Summary Background Elevated blood pressure and glucose, serum cholesterol, and body mass index (BMI) are risk factors for cardiovascular diseases (CVDs); some of these factors also increase the risk of chronic kidney disease (CKD) and diabetes. We estimated CVD, CKD, and diabetes mortality attributable to these four cardio-metabolic risk factors for all countries and regions between 1980 and 2010. Methods We used data on risk factor exposure by country, age group, and sex from pooled analysis of population-based health surveys. Relative risks for cause-specific mortality were obtained from pooling of large prospective studies. We calculated the population attributable fractions (PAF) for each risk factor alone, and for the combination of all risk factors, accounting for multi-causality and for mediation of the effects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specific PAFs by the number of disease-specific deaths from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all inputs to the final estimates. Findings In 2010, high blood pressure was the leading risk factor for dying from CVDs, CKD, and diabetes in every region, causing over 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths; and cholesterol for 10%. After accounting for multi-causality, 63% (10.8 million deaths; 95% confidence interval 10.1–11.5) of deaths from these diseases were attributable to the combined effect of these four metabolic risk factors, compared with 67% (7.1 million deaths; 6.6–7.6) in 1980. The mortality burden of high BMI and glucose nearly doubled between 1980 and 2010. At the country level, age-standardised death rates attributable to these four risk factors surpassed 925 deaths per 100,000 among men in Belarus, Mongolia, and Kazakhstan, but were below 130 deaths per 100,000 for women and below 200 for men in some high-income countries like Japan, Singapore, South Korea, France, Spain, The Netherlands, Australia, and Canada. Interpretations The salient features of the cardio-metabolic epidemic at the beginning of the twenty-first century are the large role of high blood pressure and an increasing impact of obesity and diabetes. There has been a shift in the mortality burden from high-income to low- and middle-income countries.

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The aims of our meta-analysis were (i) to quantify the predictability of childhood overweight and obesity on the risk of incident asthma; and (ii) to evaluate the gender difference on this relationship. The selection criteria included prospective cohort paediatric studies which use age- and sex-specific body mass index (BMI) as a measure of childhood overweight and the primary outcome of incident asthma. A total of 1,027 studies were initially identified through online database searches, and finally 6 studies met the inclusion criteria. The combined result of reported relative risk from the 6 included studies revealed that overweight children conferred increased risks of incident asthma as compared with non-overweight children (relative risk, 1.19; 95% confidence interval [CI], 1.03-1.37). The relationship was further elevated for obesity vs. non-obesity (relative risk, 2.02; 95% CI, 1.16-3.50). A dose-responsiveness of elevated BMI on asthma incidence was observed (P for trend, 0.004). Obese boys had a significantly larger effect than obese girls (relative risk, boys: 2.47; 95% CI, 1.57-3.87; girls: 1.25; 95% CI, 0.51-3.03), with significant dose-dependent effect. Proposed mechanisms of gender difference could be through pulmonary mechanics, sleep disordered breathing and leptin. Further research might be needed to better understand the exact mechanism of gender difference on the obesity-asthma relationship.

Purpose Accurate segmentation of lung and infection in COVID‐19 computed tomography (CT) scans plays an important role in the quantitative management of patients. Most of the existing studies are based on large and private annotated datasets that are impractical to obtain from a single institution, especially when radiologists are busy fighting the coronavirus disease. Furthermore, it is hard to compare current COVID‐19 CT segmentation methods as they are developed on different datasets, trained in different settings, and evaluated with different metrics. Methods To promote the development of data‐efficient deep learning methods, in this paper, we built three benchmarks for lung and infection segmentation based on 70 annotated COVID‐19 cases, which contain current active research areas, for example, few‐shot learning, domain generalization, and knowledge transfer. For a fair comparison among different segmentation methods, we also provide standard training, validation and testing splits, evaluation metrics and, the corresponding code. Results Based on the state‐of‐the‐art network, we provide more than 40 pretrained baseline models, which not only serve as out‐of‐the‐box segmentation tools but also save computational time for researchers who are interested in COVID‐19 lung and infection segmentation. We achieve average dice similarity coefficient (DSC) scores of 97.3%, 97.7%, and 67.3% and average normalized surface dice (NSD) scores of 90.6%, 91.4%, and 70.0% for left lung, right lung, and infection, respectively. Conclusions To the best of our knowledge, this work presents the first data‐efficient learning benchmark for medical image segmentation, and the largest number of pretrained models up to now. All these resources are publicly available, and our work lays the foundation for promoting the development of deep learning methods for efficient COVID‐19 CT segmentation with limited data.

http://hyper.ahajournals.org/ Downloaded from Dong et al Effects of Air Pollution on Blood Pressure 579pollution on BP in different parts of the world are unclear but may result from spatial and temporal variability in pollution sources and composition. 17,18 Compared with short-term effects of air pollution, there is little information on the relation between chronic exposure to air pollution and prevalent hypertension. Inconsistent results have also been reported on the association between incident hypertension and air pollution. For instance, Coogan et al 19 showed in a 10-year follow-up for incident hypertension and diabetes mellitus of black women from Los Angeles that NO X (but less PM 2.5 ) borderline increased the risk of becoming hypertensive. However, Sørensen et al 20 reported that longterm exposure (1 and 5 years) to NO X was not associated with incident self-reported hypertension in a Danish cohort. We hypothesized that at the population level, long-term exposure to ambient air pollution is associated with higher BP and higher prevalence of hypertension among humans. In this study, we tested this hypothesis in the 11 Districts Chinese Study, a cross-sectional study of air pollution and adult health in a large, well-characterized population-based sample, residing in northeast China, where there are wide differences in inter-and intracity gradients and ambient pollutant levels, offering a valuable opportunity to assess the associations between exposure and response. Methods Study Cities Selection and Subject RecruitmentMore than 20 million people reside in 14 cities in Liaoning province in northeast China. To maximize the inter-and intracity gradients of the pollutants of interest and minimize the correlation between district-specific ambient pollutants, in April 2009, we selected 3 cities (Shenyang, Anshan, and Jinzhou) based on the results of air pollution measurements between 2006 and 2008. There are 5, well-identified geographic districts in Shenyang, and 3 districts in Anshan and Jinzhou, respectively. Three communities within 1 km of air-monitoring sites were randomly chosen from these districts resulting in 33 locales, and from each of these, 700 to 1000 households were randomly identified. One participant, aged 18 to 74 years, was selected from each household without replacement. Our entry criterion was that the subject should have lived at that place for at least 5 years. The design and conduct of this investigation was reviewed and approved by Human Studies Committee of China Medical University. Before data collection, a written informed consent form was obtained from each participant. Ambient Air PollutionIn each of the selected study districts, there was only 1 municipal air pollution monitoring station, which was located 1 mile from the participants' homes. Measurements of PM 10 , SO 2 , NO 2 , and O 3 concentrations from 2006 to 2008 were obtained at the stations. The measurements were subject to uniform criteria for monitoring, siting, instrumentation, and quality assurance. Thes...