Analysis of social determinants of health and individual factors found in health equity frameworks: Applications to injury research.

INTRODUCTION: This research evaluated existing health equity frameworks as they relate to social determinants of health (SDOHs) and individual factors that may impact injury outcomes and identify gaps in coverage using the Healthy People (HP) 2030 key domains. METHODS: The study used a list of health equity frameworks sourced from previous literature. SDOHs and individual factors from each framework were identified and categorized into the Healthy People 2030 domains. Five injury topic areas were used as examples for how SDOHs and individual factors can be compared to injury topic-specific health disparities to identify health equity frameworks to apply to injury research. RESULTS: The study identified 59 SDOHs and individual factors from the list of 33 health equity frameworks. The number of SDOHs and individual factors identified varied by Healthy People 2030 domain: Neighborhood and Built Environment contained 16 (27.1%) SDOHs and individual actors, Social and Community Context contained 22 (37.3%), Economic Stability contained 10 (16.9%), Healthcare Access and Quality contained 10 (16.9%), and Education Access and Quality contained one (1.7%). Twenty-three (39.0%) SDOHs/individual factors related to traumatic brain injury, thirteen (22.0%) related to motor vehicle crashes and suicide, 11 (18.6%) related to drowning and older adult falls. Eight frameworks (24.2%) covered all HP 2030 key domains and may be applicable to injury topics. CONCLUSIONS: Incorporating health equity into research is critical. Health equity frameworks can provide a way to systematically incorporate health equity into research. The findings from this study may be useful to health equity research by providing a resource to injury and other public health fields. PRACTICAL APPLICATIONS: Health equity frameworks are a practical tool to guide injury research, translation, evaluation, and program implementation. The findings from this study can be used to guide the application of health equity frameworks in injury research for specific topic areas.

Health equity guiding frameworks and indices in injury: A review of the literature.

BACKGROUND: In early 2021, CDC released the CORE Health Equity Strategy, which resolves to integrate a comprehensive health equity approach to the work of the Agency. One priority of the Injury Center's Division of Injury Prevention is to move health equity research in injury forward. The purpose of this research is to perform an initial exploration of health equity guiding frameworks and indices to better understand which of these has been applied to injury research topics. METHODS: A PubMed and CINAHL search of meta-analysis and systematic review articles was conducted from January 1998 through April 2022. Articles of any type and additional frameworks/indices were also identified from staff knowledge of the literature. Books were also considered, where accessible. The following areas were reviewed for each resource: population addressed, guiding framework/index, other health equity variables, gaps identified, and whether the articles addressed an injury topic. FINDINGS: The PubMed/CINAHL search produced 230 articles, and an additional 29 articles and 8 books were added from previous knowledge of the literature, resulting in a total of 267 resources for review. There were 60 frameworks/indices compiled that were relevant to health equity. Out of all the resources, three reported on an injury topic and used the PROGRESS-Plus framework, the WHO Social Determinants of Health Conceptual Framework, and a social-ecological framework. CONCLUSIONS: This study found there were many frameworks/indices for measuring health equity; however, there were few injury-related meta-analysis and systematic review articles. Some frameworks/indices may be more appropriate than others for measuring health equity in injury topic areas, depending on which social determinants of health (SDOHs) they address. PRACTICAL APPLICATIONS: Measuring health equity in injury and other public health research areas can help build a foundation of evidence. Moving forward, injury researchers can consider the frameworks/indices identified through this study in their health equity injury research.

Non-fatal injury data: characteristics to consider for surveillance and research.

BACKGROUND: All data systems used for non-fatal injury surveillance and research have strengths and limitations that influence their utility in understanding non-fatal injury burden. The objective of this paper was to compare characteristics of major data systems that capture non-fatal injuries in the USA. METHODS: By applying specific inclusion criteria (eg, non-fatal and non-occupational) to well-referenced injury data systems, we created a list of commonly used non-fatal injury data systems for this study. Data system characteristics were compiled for 2018: institutional support, years of data available, access, format, sample, sampling method, injury definition/coding, geographical representation, demographic variables, timeliness (lag) and further considerations for analysis. RESULTS: Eighteen data systems ultimately fit the inclusion criteria. Most data systems were supported by a federal institution, produced national estimates and were available starting in 1999 or earlier. Data source and injury case coding varied between the data systems. Redesigns of sampling frameworks and the use of International Classification of Diseases, 9th Revision, Clinical Modification/International Classification of Diseases, 10th Revision, Clinical Modification coding for some data systems can make longitudinal analyses complicated for injury surveillance and research. Few data systems could produce state-level estimates. CONCLUSION: Thoughtful consideration of strengths and limitations should be exercised when selecting a data system to answer injury-related research questions. Comparisons between estimates of various data systems should be interpreted with caution, given fundamental system differences in purpose and population capture. This research provides the scientific community with an updated starting point to assist in matching the data system to surveillance and research questions and can improve the efficiency and quality of injury analyses.

COVID-19 Vaccination Coverage Among Adults - United States, December 14, 2020-May 22, 2021.

The U.S. COVID-19 vaccination program launched on December 14, 2020. The Advisory Committee on Immunization Practices recommended prioritizing COVID-19 vaccination for specific groups of the U.S. population who were at highest risk for COVID-19 hospitalization and death, including adults aged ≥75 years*; implementation varied by state, and eligibility was gradually expanded to persons aged ≥65 years beginning in January 2021. By April 19, 2021, eligibility was expanded to all adults aged ≥18 years nationwide.† To assess patterns of COVID-19 vaccination coverage among U.S. adults, CDC analyzed data submitted on vaccinations administered during December 14, 2020-May 22, 2021, by age, sex, and community-level characteristics. By May 22, 2021, 57.0% of persons aged ≥18 years had received ≥1 COVID-19 vaccine dose; coverage was highest among persons aged ≥65 years (80.0%) and lowest among persons aged 18-29 years (38.3%). During the week beginning February 7, 2021, vaccination initiation among adults aged ≥65 years peaked at 8.2%, whereas weekly initiation among other age groups peaked later and at lower levels. During April 19-May 22, 2021, the period following expanded eligibility to all adults, weekly initiation remained <4.0% and decreased for all age groups, including persons aged 18-29 years (3.6% to 1.9%) and 30-49 years (3.5% to 1.7%); based on the current rate of weekly initiation (as of May 22), younger persons will not reach the same levels of coverage as older persons by the end of August. Across all age groups, coverage (≥1 dose) was lower among men compared with women, except among adults aged ≥65 years, and lower among persons living in counties that were less urban, had higher social vulnerabilities, or had higher percentages of social determinants of poor health. Continued efforts to improve vaccination confidence and alleviate barriers to vaccination initiation, especially among adults aged 18-49 years, could improve vaccination coverage.

Patterns in COVID-19 Vaccination Coverage, by Social Vulnerability and Urbanicity - United States, December 14, 2020-May 1, 2021.

Disparities in vaccination coverage by social vulnerability, defined as social and structural factors associated with adverse health outcomes, were noted during the first 2.5 months of the U.S. COVID-19 vaccination campaign, which began during mid-December 2020 (1). As vaccine eligibility and availability continue to expand, assuring equitable coverage for disproportionately affected communities remains a priority. CDC examined COVID-19 vaccine administration and 2018 CDC social vulnerability index (SVI) data to ascertain whether inequities in COVID-19 vaccination coverage with respect to county-level SVI have persisted, overall and by urbanicity. Vaccination coverage was defined as the number of persons aged ≥18 years (adults) who had received ≥1 dose of any Food and Drug Administration (FDA)-authorized COVID-19 vaccine divided by the total adult population in a specified SVI category.† SVI was examined overall and by its four themes (socioeconomic status, household composition and disability, racial/ethnic minority status and language, and housing type and transportation). Counties were categorized into SVI quartiles, in which quartile 1 (Q1) represented the lowest level of vulnerability and quartile 4 (Q4), the highest. Trends in vaccination coverage were assessed by SVI quartile and urbanicity, which was categorized as large central metropolitan, large fringe metropolitan (areas surrounding large cities, e.g., suburban), medium and small metropolitan, and nonmetropolitan counties.§ During December 14, 2020-May 1, 2021, disparities in vaccination coverage by SVI increased, especially in large fringe metropolitan (e.g., suburban) and nonmetropolitan counties. By May 1, 2021, vaccination coverage was lower among adults living in counties with the highest overall SVI; differences were most pronounced in large fringe metropolitan (Q4 coverage = 45.0% versus Q1 coverage = 61.7%) and nonmetropolitan (Q4 = 40.6% versus Q1 = 52.9%) counties. Vaccination coverage disparities were largest for two SVI themes: socioeconomic status (Q4 = 44.3% versus Q1 = 61.0%) and household composition and disability (Q4 = 42.0% versus Q1 = 60.1%). Outreach efforts, including expanding public health messaging tailored to local populations and increasing vaccination access, could help increase vaccination coverage in high-SVI counties.

Disparities in COVID-19 Vaccination Coverage Between Urban and Rural Counties - United States, December 14, 2020-April 10, 2021.

Approximately 60 million persons in the United States live in rural counties, representing almost one fifth (19.3%) of the population.* In September 2020, COVID-19 incidence (cases per 100,000 population) in rural counties surpassed that in urban counties (1). Rural communities often have a higher proportion of residents who lack health insurance, live with comorbidities or disabilities, are aged ≥65 years, and have limited access to health care facilities with intensive care capabilities, which places these residents at increased risk for COVID-19-associated morbidity and mortality (2,3). To better understand COVID-19 vaccination disparities across the urban-rural continuum, CDC analyzed county-level vaccine administration data among adults aged ≥18 years who received their first dose of either the Pfizer-BioNTech or Moderna COVID-19 vaccine, or a single dose of the Janssen COVID-19 vaccine (Johnson & Johnson) during December 14, 2020-April 10, 2021 in 50 U.S. jurisdictions (49 states and the District of Columbia [DC]). Adult COVID-19 vaccination coverage was lower in rural counties (38.9%) than in urban counties (45.7%) overall and among adults aged 18-64 years (29.1% rural, 37.7% urban), those aged ≥65 years (67.6% rural, 76.1% urban), women (41.7% rural, 48.4% urban), and men (35.3% rural, 41.9% urban). Vaccination coverage varied among jurisdictions: 36 jurisdictions had higher coverage in urban counties, five had higher coverage in rural counties, and five had similar coverage (i.e., within 1%) in urban and rural counties; in four jurisdictions with no rural counties, the urban-rural comparison could not be assessed. A larger proportion of persons in the most rural counties (14.6%) traveled for vaccination to nonadjacent counties (i.e., farther from their county of residence) compared with persons in the most urban counties (10.3%). As availability of COVID-19 vaccines expands, public health practitioners should continue collaborating with health care providers, pharmacies, employers, faith leaders, and other community partners to identify and address barriers to COVID-19 vaccination in rural areas (2).

In utero exposure to atrazine analytes and early menarche in the Avon Longitudinal Study of Parents and Children Cohort.

BACKGROUND: Evidence from experimental studies suggests that atrazine and its analytes alter the timing of puberty in laboratory animals. Such associations have not been investigated in humans. OBJECTIVE: To determine the association between in utero exposure to atrazine analytes and earlier menarche attainment in a nested case-control study of the population-based Avon Longitudinal Study of Parents and Children. METHODS: Cases were girls who reported menarche before 11.5 years while controls were girls who reported menarche at or after 11.5 years. Seven atrazine analyte concentrations were measured in maternal gestational urine samples (sample gestation week median (IQR): 12 (8-17)) during the period 1991-1992, for 174 cases and 195 controls using high performance liquid chromatography-tandem mass spectrometry. We evaluated the study association using multivariate logistic regression, adjusting for potential confounders. We used multiple imputation to impute missing confounder data for 29% of the study participants. RESULTS: Diaminochlorotriazine (DACT) was the most frequently detected analyte (58%>limit of detection [LOD]) followed by desethyl atrazine (6%), desethyl atrazine mercapturate (3%), atrazine mercapturate (1%), hydroxyl atrazine (1%), atrazine (1%) and desisopropyl atrazine (0.5%). Because of low detection of other analytes, only DACT was included in the exposure-outcome analyses. The adjusted odds of early menarche for girls with DACT exposures≥median was 1.13 (95% Confidence Interval [95% CI]:0.82, 1.55) and exposure

In utero exposure to organochlorine pesticides and early menarche in the Avon Longitudinal Study of Parents and Children.

INTRODUCTION: Epidemiologic data supporting the role of organochlorine pesticides in pubertal development are limited. METHODS: Using a nested case-control design, serum collected during pregnancy from mothers of 218 girls who reported menarche before 11.5years of age (cases) and 230 girls who reported menarche at or after 11.5years of age (controls) was analyzed for 9 organochlorines and metabolites. We analyzed the association between in utero organochlorine concentrations and early menarche using multivariate logistic regression controlling for mother's age at menarche, or mother's prenatal BMI. RESULTS: We did not observe an association between in utero exposure to HCB, ß-HCH, ϒ-HCH, p,p'-DDT, p,p'-DDE, oxychlordane or trans-nonachlor and early menarche. CONCLUSIONS: This study is the first to examine the association between in utero exposure to HCB, ß-HCH, ϒ-HCH, oxychlordane or trans-nonachlor and early menarche. In utero exposure to organochlorine pesticides does not appear to have a role in the timing of menarche in this study.

Long-Term Exposure to Ozone and Life Expectancy in the United States, 2002 to 2008.

Long-term exposure to ground-level ozone is associated with increased risk of morbidity and mortality. The association remains uncertain between long-term exposure to ozone and life expectancy. We assessed the associations between seasonal mean daily 8-hour maximum (8-hr max) ozone concentrations measured during the ozone monitoring seasons and life expectancy at birth in 3109 counties of the conterminous U.S. during 2002 to 2008. We used latent class growth analysis to identify latent classes of counties that had distinct mean levels and rates of change in ozone concentrations over the 7-year period and used linear regression analysis to determine differences in life expectancy by ozone levels. We identified 3 classes of counties with distinct seasonal mean daily 8-hr max ozone concentrations and rates of change. When compared with the counties with the lowest ozone concentrations, the counties with the highest ozone concentrations had 1.7- and 1.4-year lower mean life expectancy in males and females (both P < 0.0001), respectively. The associations remained statistically significant after controlling for potential confounding effects of seasonal mean PM2.5 concentrations and other selected environmental, demographic, socio-economic, and health-related factors (both P < 0.0001). A 5 ppb higher ozone concentration was associated with 0.25 year lower life expectancy in males (95% CI: -0.30 to -0.19) and 0.21 year in females (95% CI: -0.25 to -0.17). We identified 3 classes of counties with distinct mean levels and rates of change in ozone concentrations. Our findings suggest that long-term exposure to a higher ozone concentration may be associated with a lower life expectancy.

Geographic Variation in the Association between Ambient Fine Particulate Matter (PM2.5) and Term Low Birth Weight in the United States.

BACKGROUND: Studies on the association between prenatal exposure to fine particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) and term low birth weight (LBW) have resulted in inconsistent findings. Most studies were conducted in snapshots of small geographic areas and no national study exists. OBJECTIVES: We investigated geographic variation in the associations between ambient PM2.5 during pregnancy and term LBW in the contiguous United States. METHODS: A total of 3,389,450 term singleton births in 2002 (37-44 weeks gestational age and birth weight of 1,000-5,500 g) were linked to daily PM2.5 via imputed birth days. We generated average daily PM2.5 during the entire pregnancy and each trimester. Multi-level logistic regression models with county-level random effects were used to evaluate the associations between term LBW and PM2.5 during pregnancy. RESULTS: Without adjusting for covariates, the odds of term LBW increased 2% [odds ratio (OR) = 1.02; 95% CI: 1.00, 1.03] for every 5-µg/m(3) increase in PM2.5 exposure during the second trimester only, which remained unchanged after adjusting for county-level poverty (OR = 1.02; 95% CI: 1.01, 1.04). The odds did change to null after adjusting for individual-level predictors (OR = 1.00; 95% CI: 0.99, 1.02). Multi-level analyses, stratified by census division, revealed significant positive associations of term LBW and PM2.5 exposure (during the entire pregnancy or a specific trimester) in three census divisions of the United States: Middle Atlantic, East North Central, and West North Central, and significant negative association in the Mountain division. CONCLUSIONS: Our study provided additional evidence on the associations between PM2.5 exposure during pregnancy and term LBW from a national perspective. The magnitude and direction of the estimated associations between PM2.5 exposure and term LBW varied by geographic locations in the United States.

Ozone, Fine Particulate Matter, and Chronic Lower Respiratory Disease Mortality in the United States.

RATIONALE: Short-term effects of air pollution exposure on respiratory disease mortality are well established. However, few studies have examined the effects of long-term exposure, and among those that have, results are inconsistent. OBJECTIVES: To evaluate long-term association between ambient ozone, fine particulate matter (PM2.5, particles with an aerodynamic diameter of 2.5 µm or less), and chronic lower respiratory disease (CLRD) mortality in the contiguous United States. METHODS: We fit Bayesian hierarchical spatial Poisson models, adjusting for five county-level covariates (percentage of adults aged ≥65 years, poverty, lifetime smoking, obesity, and temperature), with random effects at state and county levels to account for spatial heterogeneity and spatial dependence. MEASUREMENTS AND MAIN RESULTS: We derived county-level average daily concentration levels for ambient ozone and PM2.5 for 2001-2008 from the U.S. Environmental Protection Agency's down-scaled estimates and obtained 2007-2008 CLRD deaths from the National Center for Health Statistics. Exposure to ambient ozone was associated with an increased rate of CLRD deaths, with a rate ratio of 1.05 (95% credible interval, 1.01-1.09) per 5-ppb increase in ozone; the association between ambient PM2.5 and CLRD mortality was positive but statistically insignificant (rate ratio, 1.07; 95% credible interval, 0.99-1.14). CONCLUSIONS: This study links air pollution exposure data with CLRD mortality for all 3,109 contiguous U.S. counties. Ambient ozone may be associated with an increased rate of death from CLRD in the contiguous United States. Although we adjusted for selected county-level covariates and unobserved influences through Bayesian hierarchical spatial modeling, the possibility of ecologic bias remains.

Data to action: using environmental public health tracking to inform decision making.

CONTEXT: Public health surveillance includes dissemination of data and information to those who need it to take action to prevent or control disease. The concept of data to action is explicit in the mission of the Centers for Disease Control and Prevention's (CDC's) National Environmental Public Health Tracking Program (Tracking Program). The CDC has built a National Environmental Public Health Tracking Network (Tracking Network) to integrate health and environmental data to drive public health action (PHA) to improve communities' health. OBJECTIVE: To assess the utility of the Tracking Program and Tracking Network in environmental public health practice and policy making. DESIGN: We analyzed information on how Tracking (all program components hereafter referred to generally as "Tracking") has been used to drive PHAs within funded states and cities (grantees). Two case studies are presented to highlight Tracking's utility. SETTING: Analyses included all grantees funded between 2005 and 2013. PARTICIPANTS: Twenty-seven states, 3 cities, and the District of Columbia ever received funding. MAIN OUTCOME MEASURES: We categorized each PHA reported to determine how grantees became involved, their role, the problems addressed, and the overall action. RESULTS: Tracking grantees reported 178 PHAs from 2006 to 2013. The most common overall action was "provided information in response to concern" (n = 42), followed by "improved a public health program, intervention, or response plan" (n = 35). Tracking's role was most often either to enhance surveillance (24%) or to analyze data (23%). In 47% of PHAs, the underlying problem was a concern about possible elevated rates of a health outcome, a potential exposure, or a potential association between a hazard and a health outcome. PHAs were started by a request for assistance (48%), in response to an emergency (8%), and though routine work by Tracking programs (43%). CONCLUSION: Our review shows that the data, expertise, technical infrastructure, and other resources of the Tracking Program and Tracking Network are driving state and local PHAs.

A decade of environmental public health tracking (2002-2012): progress and challenges.

BACKGROUND: The creation of the Centers for Disease Control and Prevention Environmental Public Health Tracking Program spawned an invigorating and challenging approach toward implementing the nation's first population-based, environmental disease tracking surveillance system. More than 10 years have passed since its creation and an abundance of peer-reviewed articles have been published spanning a broad variety of public health topics related primarily to the goal of reducing diseases of environmental origin. OBJECTIVE: To evaluate peer-reviewed literature related to Environmental Public Health Tracking during 2002-2012, recognize major milestones and challenges, and offer recommendations. DESIGN: A narrative overview was conducted using titles and abstracts of peer-reviewed articles, key word searches, and science-based search engine databases. MAIN OUTCOMES: Eighty published articles related to "health tracking" were identified and categorized according to 4 crossed-central themes. The Science and Research theme accounted for the majority of published articles, followed by Policy and Practice, Collaborations Among Health and Environmental Programs, and Network Development. CONCLUSIONS: Overall, progress was reported in the areas of data linkage, data sharing, surveillance methods, and network development. Ongoing challenges included formulating better ways to establish the connections between health and the environment, such as using biomonitoring, public water systems, and private well water data. Recommendations for future efforts include use of data to inform policy and practice and use of electronic health records data for environmental health surveillance.

Statistical air quality predictions for public health surveillance: evaluation and generation of county level metrics of PM2.5 for the environmental public health tracking network.

BACKGROUND: The Centers for Disease Control and Prevention (CDC) developed county level metrics for the Environmental Public Health Tracking Network (Tracking Network) to characterize potential population exposure to airborne particles with an aerodynamic diameter of 2.5 µm or less (PM(2.5)). These metrics are based on Federal Reference Method (FRM) air monitor data in the Environmental Protection Agency (EPA) Air Quality System (AQS); however, monitor data are limited in space and time. In order to understand air quality in all areas and on days without monitor data, the CDC collaborated with the EPA in the development of hierarchical Bayesian (HB) based predictions of PM(2.5) concentrations. This paper describes the generation and evaluation of HB-based county level estimates of PM(2.5). METHODS: We used three geo-imputation approaches to convert grid-level predictions to county level estimates. We used Pearson (r) and Kendall Tau-B (τ) correlation coefficients to assess the consistency of the relationship, and examined the direct differences (by county) between HB-based estimates and AQS-based concentrations at the daily level. We further compared the annual averages using Tukey mean-difference plots. RESULTS: During the year 2005, fewer than 20% of the counties in the conterminous United States (U.S.) had PM(2.5) monitoring and 32% of the conterminous U.S. population resided in counties with no AQS monitors. County level estimates resulting from population-weighted centroid containment approach were correlated more strongly with monitor-based concentrations (r = 0.9; τ = 0.8) than were estimates from other geo-imputation approaches. The median daily difference was -0.2 µg/m(3) with an interquartile range (IQR) of 1.9 µg/m(3) and the median relative daily difference was -2.2% with an IQR of 17.2%. Under-prediction was more prevalent at higher concentrations and for counties in the western U.S. CONCLUSIONS: While the relationship between county level HB-based estimates and AQS-based concentrations is generally good, there are clear variations in the strength of this relationship for different regions of the U.S. and at various concentrations of PM(2.5). This evaluation suggests that population-weighted county centroid containment method is an appropriate geo-imputation approach, and using the HB-based PM(2.5) estimates to augment gaps in AQS data provides a more spatially and temporally consistent basis for calculating the metrics deployed on the Tracking Network.

Public health surveillance in the United States: evolution and challenges.

In its landmark 1988 report, a committee of the Institute of Medicine highlighted assessment as one of the three core functions of public health along with policy development and assurance. The committee recommended that every public health agency regularly and systematically collect, assemble, analyze, and make available information on the health of the community, including statistics on health status, community health needs, and epidemiologic and other studies of health problems. Public health surveillance, often called the cornerstone of public health practice, is an essential element of the assessment function.

U.S. census unit population exposures to ambient air pollutants.

BACKGROUND: Progress has been made recently in estimating ambient PM(2.5) (particulate matter with aerodynamic diameter < 2.5 µm) and ozone concentrations using various data sources and advanced modeling techniques, which resulted in gridded surfaces. However, epidemiologic and health impact studies often require population exposures to ambient air pollutants to be presented at an appropriate census geographic unit (CGU), where health data are usually available to maintain confidentiality of individual health data. We aim to generate estimates of population exposures to ambient PM(2.5) and ozone for U.S. CGUs. METHODS: We converted 2001-2006 gridded data, generated by the U.S. Environmental Protection Agency (EPA) for CDC's (Centers for Disease Control and Prevention) Environmental Public Health Tracking Network (EPHTN), to census block group (BG) based on spatial proximities between BG and its four nearest grids. We used a bottom-up (fine to coarse) strategy to generate population exposure estimates for larger CGUs by aggregating BG estimates weighted by population distribution. RESULTS: The BG daily estimates were comparable to monitoring data. On average, the estimates deviated by 2 µg/m(3) (for PM(2.5)) and 3 ppb (for ozone) from their corresponding observed values. Population exposures to ambient PM(2.5) and ozone varied greatly across the U.S. In 2006, estimates for daily potential population exposure to ambient PM(2.5) in west coast states, the northwest and a few areas in the east and estimates for daily potential population exposure to ambient ozone in most of California and a few areas in the east/southeast exceeded the National Ambient Air Quality Standards (NAAQS) for at least 7 days. CONCLUSIONS: These estimates may be useful in assessing health impacts through linkage studies and in communicating with the public and policy makers for potential intervention.

Methods for characterizing fine particulate matter using ground observations and remotely sensed data: potential use for environmental public health surveillance.

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 microm (PM2.5) 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 PM2.5 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 PM2.5 from the EPA database for the year 2003 as well as PM2.5 estimates derived from NASA's satellite data. Hazard data have been processed to derive the surrogate PM2.5 exposure estimates. This paper shows that merging MODIS remote sensing data with surface observations of PM,2. not only provides a more complete daily representation of PM,2. than either dataset alone would allow, but it also reduces the errors in the PM2.5-estimated surfaces. The results of this study also show that although the IDW technique can introduce some numerical artifacts that could be due to its interpolating nature, which assumes that the maxima and minima can occur only at the observation points, the daily IDW PM2.5 surfaces had smaller errors in general, with respect to observations, than those of the B-Spline surfaces. Finally, the methods discussed in this paper establish a foundation for environmental public health linkage and association studies for which determining the concentrations of an environmental hazard such as PM2.5 with high accuracy is critical.

Summary and findings of the EPA and CDC symposium on air pollution exposure and health.

The U.S. Environmental Protection Agency (EPA) and the U.S. Centers for Disease Control (CDC) co-organized a symposium on "Air Pollution Exposure and Health" at Research Triangle Park, North Carolina on September 19-20, 2006. The symposium brought together health and environmental scientists to discuss the state of the science and the cross-jurisdictional and methodological challenges in conducting air pollution epidemiology, environmental public health tracking and accountability research. The symposium was held over 2 days and consisted of technical presentations and breakout group discussions on each of the three principal themes of this meeting: (1) monitoring and exposure modeling information, (2) health effects data and (3) linkage of air quality and health data for research, tracking and accountability. This paper summarizes the symposium presentations and the conclusions and recommendations developed during the meeting. The accompanying two papers, which appear in this issue of the Journal, provide more in-depth discussion of issues pertinent to obtaining and analyzing air pollution exposure and health information. The symposium succeeded in identifying areas where there are critical gaps of knowledge in existing air pollution exposure and health information and in discovering institutional or programmatic barriers, which impede accessing and linking disparate data sets. Several suggestions and recommendations emerged from this meeting, directed toward (1) improving the utility of air monitoring data for exposure quantification, (2) improving access to and the quality of health data, (3) studying emerging air quality and health issues, (4) exploring improved or novel methods for linking data and (5) developing partnerships, building capacity and facilitating interdisciplinary communication. The meeting was successful in promoting an interdisciplinary dialogue around these issues and in formulating strategies to support these recommended activities. Finally, this symposium subsequently led to strengthening and initiating new partnerships or interactions between the EPA, CDC, States, academia and the research community at large.