Intermediate- and long-term associations between air pollution and ambient temperature and glycated hemoglobin levels in women of child bearing age.

BACKGROUND: Air pollution has been linked to obesity while higher ambient temperatures typically reduce metabolic demand in a compensatory manner. Both relationships may impact glucose metabolism, thus we examined the association between intermediate- and long-term exposure to fine particulate matter (PM2.5) and ambient temperature and glycated hemoglobin(HbA1c), a longer-term marker of glucose control. METHODS: We assessed 3-month, 6-month, and 12-month average air pollution and ambient temperature at 1-km2 spatial resolution via satellite remote sensing models (2013-2019), and assessed HbA1c at four, six, and eight years postpartum in women enrolled in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City. PM2.5 and ambient temperature were matched to participants' addresses and confirmed by GPS tracker. Using linear mixed-effects models, we examined the association between 3-month, 6-month, and 12-month average PM2.5 and ambient temperature with repeated log-transformed HbA1c values. All models included a random intercept for each woman and were adjusted for calendar year, season, and individual-level confounders (age, marital status, smoking, alcohol consumption level, and education level). RESULTS: We analyzed 1,265 HbA1c measurements of 484 women. Per 1 µg/m3 increase in 3-month and 6-month PM2.5, HbA1c levels increased by 0.28% (95% confidence interval (95 %CI): 0.14, 0.42%) and 0.28% (95 %CI: 0.04, 0.52%) respectively. No association was seen for 12-month average PM2.5. Per 1 °C increase in ambient temperature, HbA1c levels decreased by 0.63% (95 %CI: -1.06, -0.21%) and 0.61% (95 %CI: -1.08, -0.13%), while the 12-month average again is not associated with HbA1c. CONCLUSIONS: Intermediate-term exposure to PM2.5 and ambient temperature are associated with opposing changes in HbA1c levels, in this region of high PM2.5 and moderate temperature fluctuation. These effects, measurable in mid-adult life, may portend future risk of type 2 diabetes and possible heart disease.

MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: a systematic review and meta-analysis.

Based on studies focusing on positron emission tomography (PET)-computed tomography (CT) combined with magnetic resonance imaging (MRI) in the diagnosis of glioma, we conducted a systematic review and meta-analysis evaluating the pros and cons and the accuracy of different examinations. PubMed and Cochrane Library were searched. The search was conducted until April 2017. Two reviewers independently conducted the literature search according to the criteria set initially. Based on the exclusion criteria, 15 articles are included in this study. Of all studies that used MRI examination, there are five involving 18F-fluorodeoxyglucose-PET, five involving 11C-methionine-PET, five involving 18F-fluoro-ethyl-tyrosine-PET, and three involving 18F-fluorothymidine-PET. Due to the limitations such as lack of data, small sample size, and unrepresentative studies, we use a non-quantitative methodology. MRI examination can provide the anatomy information of glioma more clearly. PET-CT examinations based on tumor metabolism using different tracers have more advantages in determining the degree of glioma malignancy and boundaries. However, information provided by PET-CT of different tracers is not the same. With respect to the novel hybrid MRI/PET examination equipment proposed in recent years, the combination of MRI and PET-CT can definitively improve the diagnostic accuracy of glioma.

A county-level estimate of PM2.5 related chronic mortality risk in China based on multi-model exposure data.

BACKGROUND: Ambient fine particulate matter (PM2.5) pollution is currently a serious environmental problem in China, but evidence of health effects with higher resolution and spatial coverage is insufficient. OBJECTIVE: This study aims to provide a better overall understanding of long-term mortality effects of PM2.5 pollution in China and a county-level spatial map for estimating PM2.5 related premature deaths of the entire country. METHOD: Using four sets of satellite-derived PM2.5 concentration data and the integrated exposure-response model which has been employed by the Global Burden of Disease (GBD) to estimate global mortality of ambient and household air pollution in 2010, we estimated PM2.5 related premature mortality for five endpoints across China in 2010. RESULT: Premature deaths attributed to PM2.5 nationwide amounted to 1.27million in total, and 119,167, 83,976, 390,266, 670,906 for adult chronic obstructive pulmonary disease, lung cancer, ischemic heart disease, and stroke, respectively; 3995 deaths for acute lower respiratory infections were estimated in children under the age of 5. About half of the premature deaths were from counties with annual average PM2.5 concentrations above 63.61µg/m3, which cover 16.97% of the Chinese territory. These counties were largely located in the Beijing-Tianjin-Hebei region and the North China Plain. High population density and high pollution areas exhibited the highest health risks attributed to air pollution. On a per capita basis, the highest values were mostly located in heavily polluted industrial regions. CONCLUSION: PM2.5-attributable health risk is closely associated with high population density and high levels of pollution in China. Further estimates using long-term historical exposure data and concentration-response (C-R) relationships should be completed in the future to investigate longer-term trends in the effects of PM2.5.

Differences in health-related behaviors between middle school, high school, and college students in Jiangsu province, China.

BACKGROUND AND OBJECTIVES: Increasing rates of obesity among Chinese adolescents has become a major public health concern in recent years. Studies have shown that factors such as food choices, physical activity, and screen time play important roles in fostering obesity. We examined a number of biological and social determinants that influence these factors. To determine whether dietary behavior, physical activity, and screen time varied among students in different stages of their education. METHODS AND STUDY DESIGN: Students in 13 cities across Jiangsu Province completed an anonymous survey assessing demographics and various health-related behaviors in a controlled setting. The survey population ranged from middle school students to undergraduates. 55,361 surveys were returned, and 46,611 (84.2%) were usable for the analysis. Multiple linear regression models were used to investigate the relationship between four behavioral factors (dietary behavior, screen time, physical activity, and moderate exercise) and seven predictors (gender, age, BMI, mother's education, nearsightedness, allowance, and geographic region). RESULTS: Baseline characteristics of the survey population analyzed by education level (middle school, high school, college and beyond) showed moderate differences in demographics among the three groups. Physical activity, moderate exercise, and dietary behavior decreased with educational level, while screen time increased. All predictors in the four considered regression models were statistically significant. CONCLUSIONS: This unique, large-scale survey of Chinese students in a region of contrasting economic development revealed numerous relationships between health-related diet and physical-activity, region, and education level. These findings can inform the development of measures to counteract the rise of obesity in China.