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The World Health Organization sets up the Ambient Air Quality Guidelines mainly based on short-term and long-term health effects of air pollution. Previous studies, however, have generally revealed a non-threshold concentration-response relationship between air pollution and health, making it difficult to determine a concentration, below which no obvious health effects can be observed. Here we proposed a novel approach based on the concept of “number needed to treat”, specifically, we calculated the reduction in air pollution concentrations needed to avoid one death corresponding to different hypothetical concentration standards; the one with the smallest value would be the most practical concentration standard. As an example, we applied this approach to the daily standard of ambient PM2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) in four Chinese cities. The calculation was based on the association between daily mortality and ambient PM2.5, which was examined by a generalized additive model with adjustment of important covariates. Significant associations were observed between PM2.5 and mortality. Our analyses suggested that it is appropriate to have 50 μg/m3 as the daily standard of ambient PM2.5 for the study area, compared to the current standard of which were directly adopted from the national standard of 75 μg/m3. This novel approach should be considered when planning and/or revising the ambient air quality guidelines/standards.

Maternal blood glucose level is associated with fetal growth, therefore, its role in the associations between air pollution and birth weight deserves investigation. We examined the mediation effect of maternal blood glucose on the associations between maternal air pollution exposure and birth weight. A total of 10,904 pregnant women in Foshan, China during 2015–2019 were recruited. Oral glucose tolerance test (OGTT) was administered to each participant after late trimester 2. Air pollution data at the monitoring stations in residential districts was used to estimate exposures of each participant during trimester 1 and trimester 2. Mixed-effects linear models were used to estimate the associations between air pollution and birth weight. After controlling for ten covariates, the direct effect of PM2.5 and SO2 (each 10 μg/m3 increment) on birth weight was −15.7 g (95% CI: −29.4, −4.8 g) and −83.6 g (95% CI: −134.8, −33.0 g) during trimester 1. The indirect effect of PM2.5 and SO2 (each 10 μg/m3 increment) on birth weight by increasing maternal fasting glucose level was 6.6 g (95% CI: 4.6, 9.1 g) and 22.0 g (95% CI: 4.1, 44.0 g) during trimester 1. Our findings suggest that air pollution might affect the birth weight through direct and indirect pathway, and the indirect effect might be mediated by maternal blood glucose.

Little evidence exists about the effects of long-term exposure to ambient air pollution on metabolic syndrome (MetS). This study aimed to determine the association between long-term ambient air pollution and MetS in China. A total of 15,477 adults who participated in the 33 Communities Chinese Health Study (33CCHS) in 2009 were evaluated. MetS was defined based on the recommendation by the Joint Interim Societies. Exposure to air pollutants was assessed using data from monitoring stations and a spatial statistical model (including particles with diameters ≤ 1.0 µm (PM1), ≤ 2.5 µm (PM2.5), and ≤ 10 µm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3)). Two-level logistic regression analyses were utilized to assess the associations between air pollutants and MetS. The prevalence of MetS was 30.37%. The adjusted odds ratio of MetS per 10 µg/m3 increase in PM1, PM2.5, PM10, SO2, NO2, and O3 were 1.12 (95% CI = 1.00–1.24), 1.09 (95% CI = 1.00–1.18), 1.13 (95% CI = 1.08–1.19), 1.10 (95% CI = 1.02–1.18), 1.33 (95% CI = 1.12–1.57), and 1.10 (95% CI = 1.01–1.18), respectively. Stratified analyses indicated that the above associations were stronger in participants with the demographic variables of males

The medical home model has been gaining attention from the health care community as a strategy for improved outcomes for management of chronic disease, including diabetes. The purpose of this study was to compare referrals for diabetes education among patients receiving care from a medical home model versus a traditional practice.Data were obtained from a large, university-affiliated primary care patient data registry. All patients (age 18-96 years) with a diagnosis of prediabetes or diabetes and seen by a physician at least twice during 2011 to 2013 were selected for inclusion. Multivariate regression models measuring the association between medical home status and referral to diabetes education were computed before and after adjusting for covariates.A significantly (P.001) higher percentage of patients in a medical home than without a medical home (23.9% vs 13.5%) received a referral for diabetes education. After adjusting for covariates, medical home patients were 2.7 times more likely to receive a referral for diabetes education (odds ratio, 2.70; 95% confidence interval, 1.69-4.35).Patients in a medical home model were more likely to receive referrals for diabetes education than patients in a standard university-affiliated family medicine practice. Future longitudinal designs that match characteristics of patients with a medical home with those of patients without one will provide strong evidence to determine whether referral to diabetes education is a result of the medical home model of care independent of confounding factors.

Background Most studies examining the short-term effects of temperature on health were based on the daily scale, few were at the hourly level. Revealing the relationship between unfavorable temperatures on an hourly basis and health is conducive to the development of more accurate extreme temperature early warning systems and reasonable dispatch of ambulances. Methods Hourly data on temperature, air pollution (including PM2.5, O3, SO2 and NO2) and emergency ambulance calls (EACs) for all-cause, cardiovascular and respiratory diseases from January 16, 2014 to December 31, 2016 were obtained from Luoyang, China. A distributed lag non-linear model (DLNM) was used to assess the association between hourly temperature and ambulance calls after adjusting for potential confounding factors. The fractions of EACs attributable to non-optimum temperatures were also estimated. Results Hourly temperature was associated with increased ambulance calls with a varying lag pattern. Extreme hot temperature (>32.1 °C) was positively associated with all-cause, cardiovascular diseases at lag 0–30 h and lag 0–9 h, while no significant effects were found for respiratory morbidity. Extreme cold temperature ( Conclusions Extreme hot temperature may lead to increased ambulance calls within a few hours, while extreme cold temperature may not increase ambulance calls until more than 2 days later. Effective measures, such as forming hourly temperature warning standards, optimizing ambulance services at extreme temperatures, etc., should be taken to reduce the unfavorable temperature - associated EACs burden.

Exposure to chemicals may affect liver enzyme to increase the risk of liver diseases. Perfluoroalkyl acids (PFAAs) are one kind of persistent organic pollutants with hepatotoxic effect in organism. However, data is scarce to characterize the hepatotoxic effects of specific structural PFAA isomers in general population. To address this data gap, we evaluated the association between serum PFAAs concentration and liver function biomarkers in the Isomers of C8 Health Project in China. High performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was used to measure 18 serum PFAAs, except for linear and branched isomers of PFOA/PFOS, nine perfluorinated carboxylic acids (PFCAs) and two perfluorinated sulfonic acids (PFSAs) were also included, in 1605 adult residents of Shenyang, China. Values for nine serum liver function biomarkers were determined by full-automatic blood biochemical analyzer. Linear regression was used to evaluate associations between PFAAs and continuous liver function biomarkers and logistic regression to assess markers dichotomized per clinical reference intervals. Results indicated that serum PFAAs concentrations were associated with liver biomarker levels suggestive of hepatotoxicity, especially for liver cell injury. For example, a 1 ln-unit increase in total- perfluorooctanoic acid (PFOA) exposure was associated with a 7.4% [95% confidence interval (CI): 3.9%, 11.0%] higher alanine aminotransferase (ALT) level in serum. Interestingly, we observed association between branched PFAA isomers and liver biomarkers. For example, one ln-unit increase in branched perfluorooctane sulfonate (PFOS) isomers exposure was associated with a 4.3% increase in ALT level (95% CI: 1.2%, 7.4%) and a 33.0% increased odds of having abnormal ALT (95% CI: 5.0%, 67.0%). Also, we found that PFNA had positive association with ALT [(6.2%, 95% CI: 3.1%, 9.4%) and AST levels (2.5%, 95% CI: 0.5%, 4.5%)]. Logistic regression results showed that PFPeA, PFHxA, PFNA, PFDoDA, PFTrDA and PFTeDA had statistically association with abnormal prealbumin. Conclusively, our results support previous studies showing association between PFAAs exposure and liver function biomarkers. We found new evidence that branched PFAAs isomer exposure is associated with the risk of clinically relevant hepatocellular dysfunction.

Little evidence exists about the effects of long-term exposure to ambient air pollution on metabolic syndrome (MetS). This study aimed to determine the association between long-term ambient air pollution and MetS in China. A total of 15,477 adults who participated in the 33 Communities Chinese Health Study (33CCHS) in 2009 were evaluated. MetS was defined based on the recommendation by the Joint Interim Societies. Exposure to air pollutants was assessed using data from monitoring stations and a spatial statistical model (including particles with diameters ≤ 1.0 µm (PM

Background Recent studies suggest that ambient air pollution exposure during pregnancy is associated with stillbirth occurrence. However, the results on the associations between ambient air pollutants and stillbirths are inconsistent and little is known about the gestational timing of sensitive periods for the effects of ambient air pollutants exposure on stillbirth. Objective This study aimed to examine whether exposure to high levels of ambient air pollutants in a Chinese population is associated with an increased risk of stillbirth, and determine the gestational period when the fetus is most susceptible. Methods We conducted a population-based cohort study in Wuhan, China, involving 95,354 births between June 10, 2011 and June 9, 2013. The exposure assessments were based on the daily mean concentrations of air pollutants obtained from the exposure monitor nearest to the pregnant women’s residence. Logistic regression analyses were performed to determine the associations between stillbirths and exposure to each of the air pollutants at different pregnancy periods with adjustment for confounding factors. Results Stillbirth increased with a 10 μg/m3 increase in particulate matter 2.5 (PM2.5) in each stage of pregnancy, and a significant association between carbon monoxide (CO) exposure and stillbirth was found during the third trimester (adjusted odds ratio (aOR): 1.01, 95% confidence interval (CI): 1.00–1.01) and in the entire pregnancy (aOR: 1.18, 95% CI: 1.04–1.34). Furthermore, an increased risk of stillbirth in the third trimester was associated with a 10 μg/m3 increase in PM10 (aOR: 1.08, 95% CI: 1.04–1.11), nitrogen dioxide (NO2) (aOR: 1.13, 95% CI: 1.07–1.21) and sulfur dioxide (SO2) (aOR: 1.26, 95% CI: 1.16–1.35). However, no positive association was observed between ozone exposure and stillbirth. In the two-pollutant models, PM2.5 and CO exposures were found to be consistently associated with stillbirth. Conclusions Our study revealed that exposure to high levels of PM2.5, PM10, SO2, NO2 and CO increases the risk of stillbirth and the most susceptible gestational period to ambient air pollution exposure was in the third trimester. Further toxicological and prospective cohort studies with improved exposure assessments are needed to confirm the causal link between air pollutants and stillbirth.

Objective A mixed methods study is being conducted on the statewide Early Notification of Community Based Epidemics (ESSENCE) system in Missouri to identify factors that can improve the timeliness and identification of outbreaks. This research will provide stakeholders with guidance on how best to implement and improve ESSENCE usage statewide, and by sharing this research input can be solicited on the utility of the applied framework as well as future implications from this body of work. Introduction In spite of the noted benefits of syndromic surveillance, and more than a decade after it started gaining support, the primary use for syndromic surveillance appears to be largely for seasonal and jurisdictional disease monitoring, event response and situational awareness as opposed to its intended purpose of early event detection. (1-4) Research assessing the user characteristics and standards applied at local public health agencies (LPHA’s) for syndromic surveillance are scarce, and in national surveys epidemiologists frequently tend to utilize their own syndromic surveillance systems as opposed to a national system such as Biosense. While the National Syndromic Surveillance Program (NSSP) has addressed many operational concerns from stakeholders, and is in the process of providing access to the cloud based Biosense platform-along with ESSENCE as a key tool, there is still a paucity of research that exists as to what can be done to improve the utilization of syndromic surveillance systems for its primary purpose of early event detection. Methods This research proposes to evaluate the use of ESSENCE within Missouri and the surrounding areas, to comprehensively identify its strengths and limitations, through an assessment of the user experience. This research will evaluate three key areas: 1) the quality of the data received by the syndromic surveillance system, 2) the characteristics of the individuals and organizations utilizing the system (end-users), 3) the influence and extent of syndromic surveillance data on public health actions. ESSENCE data will be evaluated directly with special attention to the top three data quality attributes across the literature, completeness, accuracy and timeliness. (5) A survey will also be administered to ESSENCE system users and public health leadership at LPHA’s, to gain insight into perspectives, perceptions and general practices, as well as how they interact with data from ESSENCE. Results The data for this research is primarily being collected throughout the fall of 2016, so the hope is to bring preliminary data to this conference as a means to validate some of the findings, solicit input on the proposed framework and share this research in a timely manner for the NSSP roll out of Biosense and ESSENCE. Conclusions Through a thorough evaluation, the application and utility of ESSENCE for early event detection will be better understood, along with the identification of factors that can be targeted in the future (and across syndromic surveillance platforms) for improvement in the timely identification of outbreaks.

Background: Epidemiological studies have reported significant association between ambient fine particulate matter air pollution (PM2.5) and mortality, however, few studies have investigated the relationship of mortality with PM2.5 and associated mortality burden in China, especially in a multicity setting. Methods: We investigated the PM2.5-mortality association in six cities of the Pearl River Delta region from 2013 to 2015. We used generalized additive Poisson models incorporating penalized smoothing splines to control for temporal trend, temperature, and relative humidity. We applied meta-analyses using random-effects models to pool the effect estimates in the six cities. We also examined these associations in stratified analyses by sex, age group, education level and location of death. We further estimated the mortality burden (attributable fraction and attributable mortality) due to ambient PM2.5 exposures. Results: During the study period, a total of 316,305 deaths were recorded in the study area. The analysis revealed a significant association between PM2.5 and mortality. Specifically, a 10 μg/m3 increase in 4-day averaged (lag03) PM2.5 concentration corresponded to a 1.76% (95% confidence interval (CI): 1.47%, 2.06%) increase in total mortality, 2.19% (95% CI: 1.80%, 2.59%) in cardiovascular mortality, and 1.68% (95% CI: 1.00%, 2.37%) in respiratory mortality. The results were generally robust to model specifications and adjustment of gaseous air pollutants. We estimated that 0.56% (95% CI: 0.47%, 0.66%) and 3.79% (95% CI: 3.14%, 4.45%) of all-cause mortalities were attributable to PM2.5 using China's and WHO's air quality standards as the reference, corresponding to 1661 (95% CI: 1379, 1946) and 11,176 (95% CI: 9261, 13,120) attributable premature mortalities, respectively. Conclusion: This analysis adds to the growing body of evidence linking PM2.5 with daily mortality, and mortality burdens, particularly in one Chinese region with high levels of air pollution. Keywords: Air pollution, Fine particles, Mortality burden, Mortality, China