The burden of disease attributable to indoor air pollutants in China from 2000 to 2017.

BACKGROUND: High-level exposure to indoor air pollutants (IAPs) and their corresponding adverse health effects have become a public concern in China in the past 10 years. However, neither national nor provincial level burden of disease attributable to multiple IAPs has been reported for China. This is the first study to estimate and rank the annual burden of disease and the financial costs attributable to targeted residential IAPs at the national and provincial level in China from 2000 to 2017. METHODS: We first did a systematic review and meta-analysis of 117 articles from 37 231 articles identified in major databases, and obtained exposure-response relationships for the candidate IAPs. The exposure levels to these IAPs were then collected by another systematic review of 1864 articles selected from 52 351 articles. After the systematic review, ten IAPs with significant and robust exposure-response relationships and sufficient exposure data were finally targeted: PM2·5, nitrogen dioxide, sulphur dioxide, ozone, carbon monoxide, radon, formaldehyde, benzene, toluene, and p-dichlorobenzene. The annual exposure levels in residences were then evaluated in all 31 provinces in mainland China continuously from 2000 to 2017, using the spatiotemporal Gaussian process regression model to analyse indoor originating IAPs, and the infiltration factor method to analyse outdoor originating IAPs. The disability-adjusted life-years (DALYs) attributable to the targeted IAPs were estimated at both national and provincial levels in China, using the population attributable fraction method. Financial costs were estimated by an adapted human capital approach. FINDINGS: From 2000 to 2017, annual DALYs attributable to the ten IAPs in mainland China decreased from 4620 (95% CI 4070-5040) to 3700 (3210-4090) per 100 000. Nevertheless, in 2017, IAPs still ranked third among all risk factors, and their DALYs and financial costs accounted for 14·1% (95% CI 12·3-15·6) of total DALYs and 3·45% (3·01-3·82) of the gross domestic product. Specifically, the rank of ten targeted IAPs in order of their contribution to DALYs in 2017 was PM2·5, carbon monoxide, radon, benzene, nitrogen dioxide, ozone, sulphur dioxide, formaldehyde, toluene, and p-dichlorobenzene. The DALYs attributable to IAPs were 9·50% higher than those attributable to outdoor air pollution in 2017. For the leading IAP, PM2·5, the DALYs attributable to indoor origins are 18·3% higher than those of outdoor origins. INTERPRETATION: DALYs attributed to IAPs in China have decreased by 20·0% over the past two decades. Even so, they are still much higher than those in the USA and European countries. This study can provide a basis for determining which IAPs to target in various indoor air quality standards and for estimating the health and economic benefits of various indoor air quality control approaches, which will help to reduce the adverse health effects of IAPs in China. FUNDING: The National Key Research and Development Program of China and the National Natural Science Foundation of China.

Association between light at night and the risk of child death in sub-saharan Africa: a cross-sectional analysis based on DHS data.

BACKGROUND: The high under-five mortality rate (U5MR) in Africa is a significant public health concern. Previous studies have found that satellite retrieved light at night (LAN) data with long-term and global coverage can be used as a proxy for socio-economic development and urbanization. Currently, few studies on the effects of LAN on child mortality have been conducted in Africa, a region with varying levels of urbanization between countries. OBJECTIVE: To quantify the correlation between risk of child mortality and LAN as an indicator of urbanization and economic development in Africa. METHODS: Using data from the Demographic and Health Survey (DHS) database conducted in 15 African countries out of 46 countries from 2005 to 2013, this study estimated LAN levels for children based on their year of birth and residential addresses. This study used Cox proportional hazards models to assess the association between LAN and the risk of child mortality in Africa. RESULTS: The mean U5MR was 95 per 1,000 livebirths among the 15 African countries during 2005-2013. After adjusting for covariates, each 10-unit increment in LAN was associated with a 5.3% reduction in the risk of U5MR. The effect estimates were more pronounced in areas with lower LAN. CONCLUSION: In Africa, the risk of U5MR decreased with increasing LAN, especially in areas with lower LAN. The results suggest that the development of urbanization and socio-economic conditions may be beneficial to child health, especially in regions with low LAN. The use of LAN as a proxy may offer an intriguing approach for identifying areas requiring targeted development in urbanization and socio-economic conditions.

Global warming may significantly increase childhood anemia burden in sub-Saharan Africa.

Childhood anemia constitutes a global public health problem, especially in low- and middle-income countries (LMICs). However, it remains unknown whether global warming has an impact on childhood anemia. Here, we examined the association between annual temperatures and childhood anemia prevalence in sub-Saharan Africa and then projected childhood anemia burden attributable to climate change. Each 1°C increment in annual temperature was associated with increased odds of childhood anemia (odd ratio = 1.138, 95% confidence interval: 1.134-1.142). Compared with the baseline period (1985-2014), the attributable childhood anemia cases would increase by 7,597 per 100,000 person-years under a high-emission scenario in the 2090s, which would be almost 2-fold and over 3-fold more than those projected in moderate- and low-emission scenarios. Our results reveal the vulnerabilities and inequalities of children for the excess burden of anemia due to climate warming and highlight the importance of climate mitigation and adaptation strategies in LMICs.

Association of Ambient Temperature With the Prevalence of Intimate Partner Violence Among Partnered Women in Low- and Middle-Income South Asian Countries.

Importance: Intimate partner violence (IPV), including physical, sexual, and emotional violence, constitutes a critical public health problem, particularly in low- and middle-income countries. While climate change could escalate violent events, data quantifying its possible association with IPV are scant. Objective: To evaluate the association of ambient temperature with the prevalence of IPV among partnered women in low- and middle-income countries in South Asia, and to estimate the association of future climate warming with IPV. Design, Setting, and Participants: This cross-sectional study used data from the Demographic and Health Survey and included 194 871 ever-partnered women aged 15 to 49 years from 3 South Asian countries (India, Nepal, and Pakistan). The study applied the mixed-effect multivariable logistic regression model to investigate the association of ambient temperature with IPV prevalence. The study further modeled the change in IPV prevalence under various future climate change scenarios. The data included in the analyses were collected from October 1, 2010, to April 30, 2018, and the current analyses were performed from January 2, 2022, to July 11, 2022. Exposure: Annual ambient temperature exposure for each woman, estimated based on an atmospheric reanalysis model of the global climate. Main Outcomes and Measures: The prevalence of IPV and its types (physical, sexual, and emotional violence) were assessed based on self-reported questionnaires from October 1, 2010, to April 30, 2018, and the changes in the prevalence with climate changes were estimated through the 2090s. Results: The study included 194 871 ever-partnered women aged 15 to 49 years (mean [SD] age, 35.4 [7.6] years; overall IPV prevalence, 27.0%) from 3 South Asian countries. The prevalence of physical violence was highest (23.0%), followed by emotional (12.5%), and sexual violence (9.5%). The annual temperature ranges were mostly between 20 °C and 30 °C. A significant association was found between high ambient temperature and the prevalence of IPV against women, with each 1 °C increase in the annual mean temperature associated with a mean increase in IPV prevalence of 4.49% (95% CI, 4.20%-4.78%). According to the study's projections under the unlimited emissions scenarios (SSPs [shared socioeconomic pathways], as defined by the Intergovernmental Panel on Climate Change] 5-8.5), IPV prevalence would increase by 21.0% by the end of the 21st century, while it would only moderately increase under increasingly stricter scenarios (SSP2-4.5 [9.8%] and SSP1-2.6 [5.8%]). In addition, the projected increases in the prevalence of physical (28.3%) and sexual (26.1%) violence were greater than that of emotional violence (8.9%). In the 2090s, India was estimated to experience the highest IPV prevalence increase (23.5%) among the 3 countries, compared with Nepal (14.8%) and Pakistan (5.9%). Conclusions and Relevance: This cross-sectional, multicountry study provides ample epidemiological evidence to support that high ambient temperature may be associated with the risk of IPV against women. These findings highlight the vulnerabilities and inequalities of women experiencing IPV in low- and middle-income countries in the context of global climate warming.

Evolution in disparity of PM2.5 pollution in China.

The spatial disparity of air pollutants is one of the key influential factors for environmental inequality. We quantitatively evaluated the evolution of PM2.5 spatial disparity in China during 2013-2020, and investigated the associations between PM2.5 spatial disparity and economic indicators. Differences in PM2.5 between more- and less-polluted cities declined over time, suggesting decreased absolute disparity. However, the more polluted cities in 2013 remained so in 2017 and 2020, and vice versa, indicating persistent relative disparity. PM2.5 pollution levels increased with higher GDP per capita in less-developed areas of China, but such negative effects weakened over time, while economic development tended to promote cleaner air in developed areas of China. Therefore, policies to improve air quality and promote economic development simultaneously are needed in China to reduce the disparity of air pollution and promote all people to enjoy environmental equality.

Indoor exposure levels and risk assessment of volatile organic compounds in residences, schools, and offices in China from 2000 to 2021: A systematic review.

The last two decades have witnessed rapid urbanization and economic growth accompanied by severe indoor air pollution of volatile organic compounds (VOCs) in China. However, indoor VOC pollution across China has not been well characterized and documented. This study is a systematic review of field measurements of eight target VOCs (benzene, toluene, xylenes, acetaldehyde, p-dichlorobenzene, butadiene, trichloroethylene, and tetrachloroethylene) in residences, offices, and schools in China from 2000 to 2021. The results show that indoor pollution of benzene, toluene, and xylenes has been more serious in China than in other countries. Spatiotemporal distribution shows lower indoor VOC levels in east and south-east regions and a declining trend from 2000 to 2021. Moving into a dwelling more than 1 year after decoration and improving ventilation could significantly reduce exposure to indoor VOCs. Reducing benzene exposure is urgently needed because it is associated with greater health risks (4.5 × 10-4 for lifetime cancer risk and 8.3 for hazard quotient) than any other VOCs. The present study enriches the database of indoor VOC levels and provides scientific evidence for improving national indoor air quality standards as well as estimating the attributable disease burden caused by VOCs in China.

Assessment of long-term particulate nitrate air pollution and its health risk in China.

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO3 -) concentration remains high or even increases at monitoring sites despite the total PM2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO3 - concentration across China due to the lack of a PM2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO3 -, thereby understanding the disease burden associated with long-term NO3 - exposure in China. Our results show that existing air pollution control policies are effective, but increased NO3 - of traffic emissions offset reduced NO3 - of industrial emissions. In 2018, the national mean mortality burden attributable to NO3 - was as high as 0.68 million, indicating that targeted regulations are needed to control NO3 - pollution in China.

The inequality labor loss risk from future urban warming and adaptation strategies.

Heat-induced labor loss is a major economic cost related to climate change. Here, we use hourly heat stress data modeled with a regional climate model to investigate the heat-induced labor loss in 231 Chinese cities. Results indicate that future urban heat stress is projected to cause an increase in labor losses exceeding 0.20% of the total account gross domestic product (GDP) per year by the 2050s relative to the 2010s. In this process, certain lower-paid sectors could be disproportionately impacted. The implementation of various urban adaptation strategies could offset 10% of the additional economic loss per year and help reduce the inequality-related impact on lower-paid sectors. So future urban warming can not only damage cities as a whole but can also contribute to income inequality. The implication of adaptation strategies should be considered in regard to not only cooling requirements but also environmental justice.

Indoor exposure to phthalates and its burden of disease in China.

China's profoundly rapid modernization in the past two decades has resulted in dramatic changes in indoor environmental exposures. Among these changes, exposure to phthalates has attracted increasing attention. We aimed to characterize indoor phthalate exposure and to estimate the disease burden attributable to indoor phthalate pollution from 2000 to 2017 in China. We integrated the national exposure level of indoor phthalates from literature through systematic review and Monte Carlo simulation. Dose-response relationships between phthalate exposure and health outcomes were obtained by systematic review and meta-analysis. Based on existing models for assessing probabilities of causation and a comprehensive review of available data, we calculated the disability-adjusted life years (DALYs) among the general Chinese population resulting from exposure to indoor phthalate pollution. We found that DnBP, DiBP, and DEHP were the most abundant phthalates in indoor environments of residences, offices, and schools with medians of national dust phase concentration from 74.5 µg/g to 96.3 µg/g, 39.6 µg/g to 162.5 µg/g, 634.2 µg/g to 1,394.7 µg/g, respectively. The national equivalent exposure for children to phthalates in settled dust was higher than that of adults except for DiBP and DnOP. Dose-response relationships associated with DEP, DiBP, DnBP, BBzP, and DEHP exposures were established. Between 2000 and 2017, indoor phthalate exposure in China has led to 3.32 million DALYs per year, accounting for 0.90% of total DALYs across China. The annual DALY associated with indoor phthalate pollution in China was over 2000 people per million, which is about 2~3 times of the DALY loss due to secondhand smoke (SHS) in six European countries or the sum of the DALY loss caused by indoor radon and formaldehyde in American homes. Our study indicates a considerable socioeconomic impact of indoor phthalate exposure for a modernizing human society. This suggest the need for relevant national standard and actions to reduce indoor phthalate exposure.

Progression of severity in coronavirus disease 2019 patients before treatment and a self-assessment scale to predict disease severity.

OBJECTIVES: This study aims to further investigate the association of COVID-19 disease severity with numerous patient characteristics, and to develop a convenient severity prediction scale for use in self-assessment at home or in preliminary screening in community healthcare settings. SETTING AND PARTICIPANTS: Data from 45,450 patients infected with COVID-19 from January 1 to February 27, 2020 were extracted from the municipal Notifiable Disease Report System in Wuhan, China. PRIMARY AND SECONDARY OUTCOME MEASURES: We categorized COVID-19 disease severity, based on The Chinese Diagnosis and Treatment Protocol for COVID-19, as "nonsevere" (which grouped asymptomatic, mild, and ordinary disease) versus "severe" (grouping severe and critical illness). RESULTS: Twelve scale items-age, gender, illness duration, dyspnea, shortness of breath (clinical evidence of altered breathing), hypertension, pulmonary disease, diabetes, cardio/cerebrovascular disease, number of comorbidities, neutrophil percentage, and lymphocyte percentage-were identified and showed good predictive ability (area under the curve = 0·72). After excluding the community healthcare laboratory parameters, the remaining model (the final self-assessment scale) showed similar area under the curve (= 0·71). CONCLUSIONS: Our COVID-19 severity self-assessment scale can be used by patients in the community to predict their risk of developing severe illness and the need for further medical assistance. The tool is also practical for use in preliminary screening in community healthcare settings. Our study constructed a COVID-19 severity self-assessment scale that can be used by patients in the community to predict their risk of developing severe illness and the need for further medical assistance.

High spatial resolution land-use regression model for urban ultrafine particle exposure assessment in Shanghai, China.

BACKGROUND: Little is currently known about long-term health effects of ambient ultrafine particles (UFPs) due to the lack of exposure assessment metrics suitable for use in large population-based studies. Land use regression (LUR) models have been used increasingly for modeling small-scale spatial variation in UFPs concentrations in European and American, but have never been applied in developing countries with heavy air pollution. OBJECTIVE: This study developed a land-use regression (LUR) model for UFP exposure assessment in Shanghai, a typic mega city of China, where dense population resides. METHOD: A 30-minute measurement of particle number concentrations of UFPs was collected at each visit at 144 fixed sites, and each was visited three times in each season of winter, spring, and summer. The annual adjusted average was calculated and regressed against pre-selected geographic information system-derived predictor variables using a stepwise variable selection method. RESULT: The final LUR model explained 69% of the spatial variability in UFP with a root mean square error of 6008 particles cm-3. The 10-fold cross validation R2 reached 0.68, revealing the robustness of the model. The final predictors included traffic-related NOx emissions, number of restaurants, building footprint area, and distance to the nearest national road. These predictors were within a relatively small buffer size, ranging from 50 m to 100 m, indicating great spatial variations of UFP particle number concentration and the need of high-resolution models for UFP exposure assessment in urban areas. CONCLUSION: We concluded that based on a purpose-designed short-term monitoring network, LUR model can be applied to predict UFPs spatial surface in a mega city of China. Majority of the spatial variability in the annual mean of ambient UFP was explained in the model comprised primarily of traffic-, building-, and restaurant-related predictors.

Indoor exposure levels of ammonia in residences, schools, and offices in China from 1980 to 2019: A systematic review.

Indoor ammonia (NH3 ) pollution has been paid more and more attention in view of its health risk. However, few studies have investigated the exposure level in the non-occupational environment in China. This study systematically reviewed the indoor ammonia exposure level in different regions, the equivalent exposure concentration of different populations, and the factors that influence indoor air ammonia in residences, offices, and schools in China. The literature published in 1980-2019 from main databases was searched and detailed screened, and finally, 56 related studies were selected. The results illustrated that the median concentration of indoor air ammonia in residences, offices, and school buildings was 0.21 mg/m3 , 0.26 mg/m3 , and 0.15 mg/m3 . There were 46.4%, 71.4%, and 40% of these samples exceeding the NH3  standard, respectively. The national concentrations and the equivalent exposure levels of adults and children were calculated and found to be higher than 0.20 mg/m3 . The concentration of ammonia varied greatly in different climate zones and economic development regions. Higher concentrations were found in the severe cold zone and the regions with higher economic level. This review reveals a high exposure risk of indoor air ammonia and the crucial impact of human emission, indoor air temperature, new concrete, and economic level, suggesting further investigation on indoor air ammonia evaluation and health effects.

Population ageing and deaths attributable to ambient PM2·5 pollution: a global analysis of economic cost.

BACKGROUND: The health impacts of ambient air pollution impose large costs on society. Although all people are exposed to air pollution, the older population (ie, those aged ≥60 years) tends to be disproportionally affected. As a result, there is growing concern about the health impacts of air pollution as many countries undergo rapid population ageing. We investigated the spatial and temporal variation in the economic cost of deaths attributable to ambient air pollution and its interaction with population ageing from 2000 to 2016 at global and regional levels. METHODS: In this global analysis, we developed an age-adjusted measure of the value of a statistical life-year (VSLY) to estimate the economic cost of deaths attributable to ambient PM2·5 pollution using Global Burden of Diseases, Injuries, and Risk Factors Study 2017 data and country-level socioeconomic information. First, we estimated the global age-specific and cause-specific mortality and years of life lost (YLLs) attributable to PM2·5 pollution using the global exposure mortality model and global estimates of exposure at 0·1°â€ˆ× 0·1° (about 11 km × 11 km at the equator) resolution. Second, for each year between 2000 and 2016, we translated the YLLs within each age group into a health-related cost using a country-specific, age-adjusted measure of VSLY. Third, we decomposed the major driving factors that contributed to the temporal change in health costs related to PM2·5. Finally, we did a sensitivity test to analyse the variability of the estimated health costs to four alternative valuation measures. We identified the uncertainty intervals (UIs) from 1000 draws of the parameters and concentration-response functions by age, cause, country, and year. All economic values are reported in 2011 purchasing power parity-adjusted US dollars. All simulations were done with R, version 3.6.0. FINDINGS: Globally, in 2016, PM2·5 was estimated to have caused 8·42 million (95% UI 6·50-10·52) attributable deaths, which was associated with 163·68 million (116·03-219·44) YLLs. In 2016, the global economic cost of deaths attributable to ambient PM2·5 pollution for the older population was US$2·40 trillion (1·89-2·93) accounting for 59% (59-60) of the cost for the total population ($4·09 trillion [3·19-5·05]). The economic cost per capita for the older population was $2739 (2160-3345) in 2016, which was 10 times that of the younger population (ie, those aged <60 years). By assessing the factors that contributed to economic costs, we found that increases in these factors changed the total economic cost by 77% for gross domestic product (GDP) per capita, 21% for population ageing, 16% for population growth, -41% for age-specific mortality, and -0·4% for PM2·5 exposure. INTERPRETATION: The economic cost of ambient PM2·5 borne by the older population almost doubled between 2000 and 2016, driven primarily by GDP growth, population ageing, and population growth. Compared with younger people, air pollution leads to disproportionately higher health costs among older people, even after accounting for their relatively shorter life expectancy and increased disability. As the world's population is ageing, the disproportionate health cost attributable to ambient PM2·5 pollution potentially widens the health inequities for older people. Countries with severe air pollution and rapid ageing rates need to take immediate actions to improve air quality. In addition, strategies aimed at enhancing health-care services, especially targeting the older population, could be beneficial for reducing the health costs of ambient air pollution. FUNDING: National Natural Science Foundation of China, China Postdoctoral Science Foundation, and Qiushi Foundation.

On-field test and data calibration of a low-cost sensor for fine particles exposure assessment.

BACKGROUND: Accurate individual exposure assessment is crucial for evaluating the health effects of particulate matter (PM). Various portable monitors built upon low-cost optical sensors have emerged. However, the main challenge for their application is to guarantee accuracy of measurements. OBJECTIVE: To assess the performance of a newly developed PM sensor, and to develop methods for post-hoc data calibration to optimize its data quality. METHOD: We conducted a series of laboratory experiments and field evaluations to quantify the reproducibility within Plantower PM sensors 7003 (PMS 7003) and the consistency between sensors and two established PM2.5 measurement methods [tapered element oscillating microbalances (TEOM) and gravimetric method (GM)]. Post-hoc data calibration methods for sensors were based on a multiple linear regression model (MLRM) and a random forest model (RFM). Ratios of raw and calibrated readings over the data of reference methods were calculated to examine the improvement after calibration. RESULTS: Strong correlations (≥0.82) and relatively small relative standard deviations (16-21%) between sensors were found during the laboratory and the field sampling. Compared with the reference methods, moderate to strong coefficients of determination (0.56-0.83) were observed; however, significant deviations were presented. After calibration, the ratios of PMS measurements over that of two reference methods both became convergent. CONCLUSIONS: Our study validated low-cost optical PM sensors under a wide range of PM2.5 concentrations (8-167 µg/m3). Our findings indicated potential applicability of PM sensors in PM2.5 exposure assessment, and confirmed a need of calibration. Linear calibration methods may be sufficient for ambient monitoring using TEOM as a reference, while nonlinear calibration methods may be more appropriate for indoor monitoring using GM as a reference.

Necessity of personal sampling for exposure assessment on specific constituents of PM2.5: Results of a panel study in Shanghai, China.

Many epidemiological studies have evaluated the health risks of ambient fine particulate matter (PM2.5). However, few studies have investigated the potential exposure misclassification caused by using ambient PM2.5 concentrations as proxy for individual exposure to PM2.5 in regions with high-level of air pollution. This study aimed to compare the differences between personal and ambient PM2.5 constituent concentrations, and to predict the personal exposure of sixteen PM2.5 constituents. We collected 141 72-h personal exposure filter samples from a panel of 36 healthy non-smoking college students in Shanghai, China. We then used the liner mixed effects models to predict personal constituent-specific exposure using ambient observations and several possible influencing factors including time-activity patterns, temporal variables, and meteorological conditions. The final model of each component was further evaluated by determination coefficient (R2) and root mean square error (RMSE) from leave-one-out-cross-validation (LOOCV). We observed ambient concentrations were higher than personal concentrations for all PM2.5 components except for Mn, Fe, Ca, and V. Especially, ambient NH4+, As, and NO3- concentrations were 3.65, 5.65 and 7.33-fold higher than their corresponding personal concentrations, respectively. The ambient level was the strongest predictor of their corresponding personal PM2.5 components with the highest marginal R2 (RM2: 0.081 ~ 0.901), meteorological conditions (RM2: 0.000 ~ 0.357), time-activity pattern (RM2: 0.000 ~ 0.083) and temporal indicators (RM2: 0.031 ~ 0.562) were also important predictors. Our final models predicted at least 50% of the variance of all personal PM2.5 constituents and even over 90% for K, Pb, and SO42-. LOOCV analysis showed that R2 and RMSE ranged from 0.251 to 0.907 and 0.000 to 0.092 µg/m3, respectively. Our results showed that ambient concentration of most PM2.5 constituents along with time-activity patterns, temporal variables, and meteorological conditions, could adequately predict personal exposure concentration. Prediction models of individual PM2.5 constituent may help to improve the accuracy of exposure measurement in future epidemiological studies.

A systematic assessment of carcinogenicity of chemicals in hydraulic-fracturing fluids and flowback water.

BACKGROUND: Thousands of chemicals exist in hydraulic-fracturing (HF) fluids and wastewater from unconventional oil gas development. The carcinogenicity of these chemicals in HF fluids and wastewater has never been systematically evaluated. OBJECTIVES: In this study, we assessed the carcinogenicity of 1,173 HF-related chemicals in the HF chemical data from the US Environmental Protection Agency (EPA). METHODS: We linked the HF chemical data with the agent classification data from the International Agency for Research on Cancer (IARC) at the World Health Organization (WHO) (N = 998 chemicals) to evaluate human carcinogenic risk of the chemicals and with the Carcinogenic Potency Database (CPDB) from Toxnet (N = 1,534 chemicals) to evaluate potential carcinogenicity of the chemicals. RESULTS: The Chemical Abstract Service Registry Numbers (CASRNs) for chemicals were used for data linkage. Among 1,173 chemicals, 1,039 were identified only in HF fluids, 97 only in wastewater, and 37 in both. Compared with IARC, we found information of 104 chemicals, and 48 of them may have potentially carcinogenic risk to human, among which 14 are definitely carcinogenic, 7 probably carcinogenic, and 27 possibly carcinogenic. Using the CPDB data, it suggests that 66 chemicals are potentially carcinogenic based on rats and mouse models. CONCLUSIONS: Conclusions Our evaluation suggests that exposure to some chemicals in HF fluids and wastewater may increase cancer risk, and the identified chemicals could be selected as the priority list for drinking water exposure assessment or cancer-related health studies.

How urban characteristics affect vulnerability to heat and cold: a multi-country analysis.

BACKGROUND: The health burden associated with temperature is expected to increase due to a warming climate. Populations living in cities are likely to be particularly at risk, but the role of urban characteristics in modifying the direct effects of temperature on health is still unclear. In this contribution, we used a multi-country dataset to study effect modification of temperature-mortality relationships by a range of city-specific indicators. METHODS: We collected ambient temperature and mortality daily time-series data for 340 cities in 22 countries, in periods between 1985 and 2014. Standardized measures of demographic, socio-economic, infrastructural and environmental indicators were derived from the Organisation for Economic Co-operation and Development (OECD) Regional and Metropolitan Database. We used distributed lag non-linear and multivariate meta-regression models to estimate fractions of mortality attributable to heat and cold (AF%) in each city, and to evaluate the effect modification of each indicator across cities. RESULTS: Heat- and cold-related deaths amounted to 0.54% (95% confidence interval: 0.49 to 0.58%) and 6.05% (5.59 to 6.36%) of total deaths, respectively. Several city indicators modify the effect of heat, with a higher mortality impact associated with increases in population density, fine particles (PM2.5), gross domestic product (GDP) and Gini index (a measure of income inequality), whereas higher levels of green spaces were linked with a decreased effect of heat. CONCLUSIONS: This represents the largest study to date assessing the effect modification of temperature-mortality relationships. Evidence from this study can inform public-health interventions and urban planning under various climate-change and urban-development scenarios.

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

Associations between birth outcomes and maternal PM2.5 exposure in Shanghai: A comparison of three exposure assessment approaches.

BACKGROUND: Few studies have estimated effects of maternal PM2.5 exposure on birth outcomes in China due to the lack of historical air pollution data. OBJECTIVES: We estimated the associations between maternal PM2.5 exposure and birth outcomes using gap-filled satellite estimates in Shanghai, China. METHODS: We obtained birth registration records of 132,783 singleton live births during 2011-2014 in Shanghai. PM2.5 exposures were assessed from satellite-derived estimates or central-site measurements. Linear and logistic regressions were used to estimate associations with term birth weight and term low birth weight (LBW), respectively. Logistic and discrete-time survival models were used to estimate associations with preterm birth. Effect modification by maternal age and parental education levels was investigated. RESULTS: A 10 µg/m3 increase in gap-filled satellite-based whole-pregnancy PM2.5 exposure was associated with a -12.85 g (95% CI: -18.44, -7.27) change in term birth weight, increased risk of preterm birth (OR 1.27, 95% CI: 1.20, 1.36), and increased risk of term LBW (OR 1.22, 95% CI: 1.06, 1.41). Sensitivity analyses during 2013-2014, when ground PM2.5 measurements were available, showed that the health associations using gap-filled satellite PM2.5 concentrations were higher than those obtained using satellite PM2.5 concentrations without accounting for missingness. The health associations using gap-filled satellite PM2.5 had similar magnitudes to those using central-site measurements, but with narrower confidence intervals. CONCLUSIONS: The magnitude of associations between maternal PM2.5 exposure and adverse birth outcomes in Shanghai was higher than previous findings. One reason could be reduced exposure error of the gap-filled high-resolution satellite PM2.5 estimates.