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Summary Many developed countries use environmental public health tracking to gain a better understanding of the link between environmental hazards and public health. To respond to complicated environmental health issues, the National Institute of Environmental Health (NIEH), Chinese Center for Disease Control and Prevention (China CDC), has begun to build a Chinese Environmental Public Health Tracking (CEPHT) system. On behalf of the CEPHT, authors provide insight into the CEPHT's development, current status, and future plans. In the initial stage of CEPHT, an indicator framework linking environment and public health that included a list of publicly available data sources regarding environmental hazards, public health outcomes, and risk factors in China was developed. An analysis of data availability, along with a comparison between CEPHT's indicator system and other tracking networks, revealed the existence of barriers and gaps in data integration that affect China's ability to track environmental public health. The lack of access to data, combined with inadequate data quality, has led to difficulties linking environmental hazards to their effects on public health. Current CEPHT efforts will help integrate environmental factors and exposure data with public health outcomes. For the near future, CEPHT plans to focus on increasing collaboration among data tracking agencies, improving data quality, and expanding proper data sharing. https://doi.org/10.1289/EHP4319, Introduction China has faced greater environmental challenges than many other countries (Liu and Diamond 2005) and has experienced a remarkable transition in cause-specific mortality over the past three decades (Zhou [...]

Abstract Extreme heat events have recently become more frequent and represent an increasing risk of damage to public health. However, the existing prediction of heatwave related health effects has limited representativeness and verification. Our study addressed the prediction of heatstroke occurrences based on three years' data of typical cities of hot temperature in China, and examined the importance ranks of model parameters including meteorological and socioeconomic status (SES) factors. The results show that meteorological factors contributed the most to model estimation of the parameters evaluated, and SES parameters, such as the search index, were also important indicators of heatstroke prediction. The model had a satisfying performance compared to traditional linear regression models. The model established in our study can be further applied to extreme weather-related impact research and reduce economic loss due to public health expenses. Graphical abstract Unlabelled Image Highlights • Using heatstroke as indicator of heat related health impact and improved representativeness • Conducted non-conventional random forest prediction model on heatstroke in China • Obtained satisfying results compared to traditional linear regression model • Included search index as SES, and have important contributions in model prediction [ABSTRACT FROM AUTHOR]

It is critical to estimate the exposure to indoor air pollution of residents spending most of their time in such microenvironments. However, the understanding regarding PM 2.5 exposure in residential indoor environments is very limited. In this study, we collected participants' basic information and time-activity patterns, as well as details of other factors related to indoor air pollution exposure, through questionnaires presented to a large population in 37 counties of China. Continuous monitoring of ambient PM 2.5 concentrations was performed using an environmental fixed-site monitoring network. Residential indoor PM 2.5 concentrations were predicted using a mass balance model based on the data obtained. Evaluation of continuous daily average residential indoor PM 2.5 exposure doses for large populations during winter revealed concentrations ranged from 67 to 195 μg/m 3 . Finally, differences in residential indoor PM 2.5 exposure between northern and southern China were investigated. The results suggested that residential indoor PM 2.5 concentrations in northern China, associated with heating, were higher than in the south. The established model could be important for improved understanding of human exposure to indoor PM 2.5 air pollution., (Copyright © 2018 Elsevier Ltd. All rights reserved.)