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ObjectiveTo develop public health adaptation strategies and to project the impacts of climate change on human health, indicators of vulnerability and preparedness along with accurate surveillance data on climate-sensitive health outcomes are needed. We researched and developed environmental health indicators for inputs into human health vulnerability assessments for climate change and to propose public health preventative actions.Data sourcesWe conducted a review of the scientific literature to identify outcomes and actions that were related to climate change. Data sources included governmental and nongovernmental agencies and the published literature.Data extractionSources were identified and assessed for completeness, usability, and accuracy. Priority was then given to identifying longitudinal data sets that were applicable at the state and community level.Data synthesisWe present a list of surveillance indicators for practitioners and policy makers that include climate-sensitive health outcomes and environmental and vulnerability indicators, as well as mitigation, adaptation, and policy indicators of climate change.ConclusionsA review of environmental health indicators for climate change shows that data exist for many of these measures, but more evaluation of their sensitivity and usefulness is needed. Further attention is necessary to increase data quality and availability and to develop new surveillance databases, especially for climate-sensitive morbidity.

This study describes and demonstrates different techniques for surface fitting daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 m (PM 2.5 ) for the purpose of integrating respiratory health and environmental data for the Centers for Disease Control and Prevention (CDC) pilot study of Health and Environment Linked for Information Exchange (HELIX)-Atlanta. It presents a methodology for estimating daily spatial surfaces of ground-level PM 2.5 concentrations using the B-Spline and inverse distance weighting (IDW) surface-fitting techniques, leveraging National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectrometer (MODIS) data to complement U.S. Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM 2.5 from the EPA database for the year 2003 as well as PM 2.5 estimates derived from NASA's satellite data. Hazard data have been processed to derive the surrogate PM 2.5 exposure estimates. This paper shows that merging MODIS remote sensing data with surface observations of PM 2.5 not only provides a more complete daily representation of PM 2.5 than either dataset alone would allow, but it also reduces the errors in the PM 2.5 -estimated surfaces. The results of this study also show that IMPLICATIONSThe described method of estimating concentrations of PM 2.5 by merging NASA MODIS remote sensing data with surface observations provides a more complete daily representation of PM 2.5 than either dataset alone, and it reduces the errors in the PM 2.5 -estimated surfaces with respect to observations. These new data products have the potential to serve as a tool for environmental public health surveillance to monitor trends and as an early warning system for prevention of human exposure to potential hazards. Such continuous spatial surfaces of environmental hazards as those developed in this study would enable linking environmental hazards to health outcomes on the grid-aggregated level as well as the individual level at the geographic locations of patients' residences.

Purpose Receipt of radiation therapy (RT) is a key quality indicator in breast cancer treatment. Prior analyses using population-based tumor registry data have demonstrated substantial underuse of RT for breast cancer, but the validity of such findings remains debated. To address this controversy, we evaluated accuracy of registry RT coding compared to the gold standard of Medicare claims. Methods and Materials Using SEER-Medicare data, we identified 73,077 patients age ≥ 66 diagnosed with breast cancer from 2001-2007. Underascertainment (1-sensitivity), sensitivity, specificity, kappa, and chi-square were calculated for RT receipt determined by registry data vs. claims. Multivariate logistic regression characterized patient, treatment, and geographic factors associated with underascertainment of RT. Findings in the SEER-Medicare registries were compared to three non-SEER registries (Florida, New York, and Texas). Results In the SEER-Medicare registries, 41.6% (n=30,386) of patients received RT according to registry coding versus 49.3% (n=36,047) according to Medicare claims (P<0.001). Underascertainment of RT was more likely if patients resided in a newer SEER registry (OR 1.70, 95%CI 1.60-1.80;P<0.001), rural county (OR 1.34, 95%CI 1.21-1.48;P<0.001) or if RT was delayed (OR 1.006/day, 95%CI 1.006-1.007,P<0.001). Underascertainment of RT receipt in SEER registries was 18.7% (95% CI 18.6-18.8%), compared to 44.3% (95% CI 44.0-44.5%) in non-SEER registries. Discussion Population-based tumor registries are highly variable in ascertainment of RT receipt and should be augmented with other data sources when evaluating quality of breast cancer care. Future work should identify opportunities for the radiation oncology community to partner with registries to improve accuracy of treatment data.