Background and Aims: A growing body of research suggests an association between residential exposure to traffic emissions and a variety of health outcomes, including respiratory and cardiovascular disease and premature mortality. In the U.S., an estimated 30.3 million people live within 500 feet (150 m) of an interstate or highway, and this population is disproportionately low-income and minority. Currently, no national and few state policies exist that address this important environmental health issue. Thus, the U.S. Centers for Disease Control and Prevention conducted a systematic review and meta-analysis of observational studies to better understand the health burden associated with residential proximity to traffic. Methods: We searched 15 electronic databases for original peer-reviewed articles, abstracts, and dissertations published during 1980–2008. Each reference was independently screened, abstracted, and reviewed for quality by two people. Separate meta-analyses were conducted for each health outcome with enough unique studies. We calculated weighted pooled effect estimates using a random effects model to address variability in study design, assessed study heterogeneity, conducted subgroup analyses, and assessed publication bias. Results: Over 14,500 references were screened, of which 149 met the inclusion criteria (84 respiratory and allergic diseases, 22 cancer, 10 cardiovascular diseases, 9 reproductive outcomes, 8 mortality, and 16 other). Preliminary analysis of 10 case-control studies suggests that residential proximity to traffic is associated with childhood leukemia (odds ratio=1.5, 95% confidence interval=1.1–2.1); however, the effect estimate varied by study quality and evidence of publication bias was observed. Analysis of other outcomes will be completed by summer 2011. Conclusions: Roughly 10% of the U.S. population lives near heavy traffic, which may contribute to substantial disease burden, including childhood leukemia. Findings from this review will inform the development of national, state, and local policies to reduce traffic emission exposures and improve population health through zoning and infrastructure changes.
In 2006, we began a three-year project funded by the NASA Integrated Decisions Support program to develop a three-dimensional air quality system (3D-AQS). The focus of 3D-AQS is on the integration of aerosol-related NASA Earth Science Data into key air quality decision support systems used for air quality management, forecasting, and public health tracking. These will include the U.S. Environmental Protection Agency (EPA)'s Air Quality System/AirQuest and AIRNow, Infusing satellite Data into Environmental Applications (IDEA) product, U.S. Air Quality weblog (Smog Blog) and the Regional East Atmospheric Lidar Mesonet (REALM). The project will result in greater accessibility of satellite and lidar datasets that, when used in conjunction with the ground-based particulate matter monitors, will enable monitoring across horizontal and vertical dimensions. Monitoring in multiple dimensions will enhance the air quality community's ability to monitor and forecast the geospatial extent and transboundary transport of air pollutants, particularly fine particulate matter. This paper describes the concept of this multisensor system and gives current examples of the types of products that will result from it.
This review presents epidemiologic evidence of adverse health effects associated with residential proximity to traffic. Of the 29 peer-reviewed studies that met the authors' defined criteria, 25 reported statistically significant associations with at least one adverse health effect across a broad range of exposure metrics and diverse geographical locations. Specific pollutants contributing to the associated health effects could not, however, be identified, and uncertainties existed because of the lack of individual exposure assessments that could rule out confounding by other factors. Improved exposure assessments and future studies should be considered for better identification of contributing pollutants and mechanisms of action. In the meantime, additional policies, additional regulations, and improved land use and urban planning can better protect the public and limit exposure, especially for vulnerable populations such as pregnant women, children, and the elderly.
Initiated in February 2004, the Public Health Air Surveillance Evaluation (PHASE) Project is a multi-disciplinary collaboration between the Centers for Disease Control and Prevention (CDC), the U.S Environmental Protection Agency (EPA), and three Environmental Public Health Tracking Network (EPHTN) state agencies. The objective of this project is to develop, evaluate, and demonstrate the advantages and limitations of different methods of generating air quality characterization data that could be systematically and routinely available to link with public health surveillance data as part of the Environmental Public Health Tracking Network.
For nearly 2 decades, the Community Health Status Indicators tool reliably supplied communities with standardized, local health data and the capacity for peer-community comparisons. At the same time, it created a large community of users who shared learning in addressing local health needs. The tool survived a transition from the Health Resources and Services Administration to the Centers for Disease Control and Prevention before being shuttered in 2017. While new community data tools have come online, nothing has replaced Community Health Status Indicators, and many stakeholders continue to clamor for something new that will enable local health needs assessments, peer comparisons, and creation of a community of solutions. The National Committee on Vital and Health Statistics heard from many stakeholders that they still need a replacement data source. (Am J Public Health. 2021;111(10):1865-1873. https://doi.org/10.2105/AJPH.2021.306437).
Compared with people in other developed countries, Americans live shorter lives, have more disease and disability, and lag on most population health measures. Recent research suggests that this poor comparative performance is primarily driven by profound local place-based disparities. Several initiatives successfully used sub-county life expectancy estimates to identify geographic disparities, generate widespread interest, and catalyze multisector actions. To explore the feasibility of scaling these efforts, the Centers for Disease Control and Prevention and the Council of State and Territorial Epidemiologists initiated a multiphase project - the Sub-County Assessment of Life Expectancy. Phase I participants reviewed the literature, assessed and identified appropriate tools, calculated locally relevant estimates, and developed methodological guidance. Phase I results suggest that most state and local health departments will be able to calculate actionable sub-county life expectancy estimates despite varying resources, expertise, and population sizes, densities, and geographies. To accelerate widespread scaling, we describe several successful case examples, identify user-friendly validated tools, and provide practical tips that resulted from lessons learned.
