Environmental Public Health Tracking Research Articles

Examining select sociodemographic characteristics of sub-county geographies for public health surveillance

BackgroundMapping health outcomes related to environmental health hazards at the county level can lead to a simplification of risks experienced by populations in that county. The Centers for Disease Control and Prevention’s National Environmental Public Health Tracking Program has developed sub-county geographies that aggregate census tracts to allow for stable, minimally suppressed data to be displayed. This helps to highlight more local variation in environmental health outcomes and risk data. However, we wanted to understand whether the aggregation method used was aggregating sociodemographically similar or dissimilar areas with one another. This analysis attempts to explore whether the distributions of select people who may be at increased risk for exposure to environmental health hazards as identified by the Tracking Program are preserved in these sub-county geographies with the census tracts used as the foundation to create them.MethodsMean values of three sociodemographic characteristics (persons aged 65 years and older, people from racial and ethnic minority groups, and population below the poverty level) for each sub-county geography in five states were calculated and placed into five break groups. Differences in break groups were determined and compared for each sub-county geography and census tract.ResultsThe sociodemographic characteristics among the census tracts and two aggregated sub-county geographies were similar. In some instances, census tracts with a low population or a highly skewed population (e.g., very high percentage of population aged 65 years and older) were aggregated with dissimilar census tracts out of necessity to meet the requirements set by the Tracking Program’s aggregation methodology. This pattern was detected in 2.41-6.59% of census tracts within the study area, depending on the sociodemographic variable and aggregation level.ConclusionsThe Tracking Program’s sub-county aggregation methodology aggregates census tracts with similar characteristics. The two new sub-county geographies can serve as a potential option for health officials and policymakers to develop targeted interventions using finer resolution health outcome and environmental hazard data compared to coarser resolution county-level data.

Environmental Public Health Tracking in England- support for Health Impact Assessments

Abstract Environmental epidemiology is a key function for the public health service with regards to investigating the public health effects of environmental hazards, monitoring the public health efforts to control the environmental risks, and providing the evidence that informs decisions making and preparedness. At the United Kingdom Health Security Agency (UKHSA), the Environmental Public Health Tracking (EPHT) Programme, initiated in 2010, has developed a number of data streams to help link environment and health data, to support Health Impact Assessment (HIA). The main aims of the EPHT programme in England are to: 1. Identify populations at risk from exposure to significant environmental and chemical hazards 2. Investigate relationships between hazard and disease 3. Inform public health policy making 4. Optimise intervention and prevention strategies 5. Generate hypotheses for further research. Such EPHT functions are based on three key components: a) by building a national EPHT program that integrates surveillance of environmental hazards, exposures and related health outcomes, to allow data linkage and assessment of environmental and health information; b) strengthening the epidemiology science, by conducting research and training of the workforce and c) developing strategies for response to immediate risks, incidents and preparing for future risks. Examples to support HIA include a) developing an air pollution exposure surveillance work programme, that has designed a pilot population vulnerability indicator; b) developing indicators for climate change impacts for public health, c) reporting regularly on the health impacts of public fluoridation water supply schemes (as mandated by Government) and d) exploring risk factors associated with elevated blood lead concentration in children, through laboratory reporting to surveillance systems. The talk will highlight some examples of practice and outline how the EPHT programme in England has supported HIA practices.

The INPHET- a global approach to Environmental Public Health Tracking

Abstract Environment and health monitoring and information systems are fundamental infrastructure for evidence provision for policy making. The International Network for Public Health and Environment Tracking (INPHET) was formed by a community of environmental public health practitioners to address common interests and activities that advance environmental public health surveillance (EPHS) and data systems, and their uses to inform public health actions. Its main goal is to address the vast inequalities across countries and communities in their ability to monitor, assess, inform and mitigate environmental and health issues. INPHET supports the relevant role of environmental epidemiology as the pillar science providing evidence for decision making and interventions aiming at reducing and preventing environmental related diseases and contributes to an overall vision for public health. As a “Community of Practice”, INPHET focuses on sharing experiences and expertise; addressing common challenges for implementing and enhancing the science of EPHS/tracking; improving understanding of the link between the environment and health; and providing the appropriate evidence that informs public policy. The network, initiated in conference meetings in 2012-13 and formally launched in Modena, Italy in 2014, has carried out several activities which aim at sharing expertise and learning from different models of environmental and health data integration and surveillance systems that directly inform policy. These include Twinning cooperation with Euro-Asian and Balkan countries and sharing of expertise with African Public Health Agencies. Some experiences are presented in this workshop and highlight the EPHS/EPHT model adopted by several national public health agencies. It promotes that such integration and uses of environmental and health data is key for EPHS, including their accessibility and usability for communities of public health researchers, practitioners and policy makers.

3.E. Scientific session: Environmental Health Tracking Systems: a tool for planetary health

Abstract Planetary health offers a good framework for better understanding the interconnection between human health and environmental changes, promoting effective cross-sector actions and partnerships, and ensuring policy coherence. Effective implementation of this conceptual framework requires monitoring and reporting on indicators relevant to planetary health that capture the scope, spatial and temporal scales of changes in natural systems that affect human health and well-being. An approach in that sense are the environmental public health tracking systems (EPHT), which imply the ongoing collection, integration, analysis, and interpretation of data at the same spatiotemporal scale about environmental hazards, and related human exposure and health effects, maintaining appropriate data protection measures. It aims to provide public-health decision makers with timely, accurate and systematic data for quantifying health impacts related to environmental factors. EPHT system are proposed as an essential tool for designing and monitoring policies and actions that prevent and reduce environmental health burdens (EHB) efficiently and cost-effectively, and as an alerting system against present and future climatic and health crisis. Pursuing such goals requires the use of health information systems that enable the monitoring and assessing of environmental health in multiple dimensions, considering specificities across different geographical and cultural settings. EPHT system requires defining a rationale on how to select the dimensions and indicators to be included. Common challenges for defining those indicators are related to the availability of data recording, data standardization, and the linkage, integration and sharing of databases. In parallel, it is also important to define a decision aiding tools in which evidence and data are understandable and inform about the extent to which specific policy goals are attained, tailoring such tools to the specific settings. Present session attends to answers to those challenges by sharing experiences from different contexts and countries Key messages • EPHT systems represent an effective tool for progressing in achieving planetary health goals and as a surveillance alerting system for future health crisis. • Adjusting EH data quality recording and analysis in EPHT systems is essential for improving resources assignment, and the effectiveness of healthy policies in reducing EHB.

Particulate Matter 2.5 Pollution Impact on Comorbid Cancer and Cardiovascular Disease Mortality in the U.S.

BackgroundEvidence regarding the effect of long-term exposure to particulate matter (PM) 2.5 and comorbid cancer and cardiovascular disease (CVD) mortality is limited. ObjectivesIn this study, the author report the association between long-term exposure to PM 2.5 and CVD mortality, cancer mortality and comorbid cancer and CVD mortality in the U.S. population. MethodsThe Centers for Disease Control and Prevention (CDC) WONDER (Wide-Ranging Online Data for Epidemiologic Research) multiple-cause-of-death database was used to obtain U.S. county-level mortality and population estimates from 2016 to 2020. Data on average daily density of PM 2.5 were abstracted from the 2018 CDC’s National Environmental Public Health Tracking system. Counties were divided into quartiles with Q1 representing counties with least average daily density and Q4 representing counties with maximum average daily density of PM 2.5. Age-adjusted mortality rates were abstracted for each quartile, for the overall population and subgroups of population. ResultsThe age-adjusted mortality rates for CVD, cancer, and comorbid cancer and CVD mortality were 505.3 (range: 505.0-505.7), 210.7 (range: 210.5-210.9), and 62.0 (range: 61.8-62.1) per 100,000 person-years, respectively. CVD mortality had the highest percentage excess mortality in Q4 compared with Q1, followed by comorbid cancer and CVD. Cancer had the least percentage excess mortality. A disproportionate effect of PM 2.5 exposure was noted on vulnerable and minority groups, based on Social Vulnerability Index and race stratification, respectively. ConclusionsHigher levels of long-term PM 2.5 exposure reported increased CVD mortality, cancer mortality and comorbid cancer and CVD disease mortality, with a pronounced detrimental effect in vulnerable and minority population.

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information With Lower-Latency NASA Data.

Exposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention's National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated data sets over the contiguous U.S. (CONUS) include: daily 5-day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast, daily historical (1980-present) concentrations of speciated PM2.5 based on the modern era retrospective analysis for research and applications, version 2, and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real-time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (a) describing temporal and spatial trends in disease and potential environmental exposures, (b) identifying populations most affected, (c) generating hypotheses about associations between health and environmental exposures, and (d) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

Abstract 18866: Binge Alcohol Drinking and Myocardial Infarction Mortality in the United States

Introduction: Although moderate alcohol intake is related to decrease all cause and ischemic heart disease mortality, intake of large amounts at a time remains controversial. Some studies have shown that binge drinking (BD) could have a protective effect. Hypothesis: The aim of this study is to study life-style risk factors associated with cardiovascular mortality in the U.S. population. Methods: The CDC National Environmental Public Health Tracking Network was used to identify age-adjusted mortality rate due to myocardial infarction (MMI) per county among people ≥35 years between 2018 and 2019. County's age-adjusted prevalence of current smoking (CS), binge alcohol drinking (BD), no-leisure time physical activity (NLTPA) and obesity were also identified as potential community life-style risk factors for MMI. Multivariable regression model predicting MMI rate was used to identify relationship between county MMI rate and those 4 life-style risk factors. Results: A total of 3106 counties were included in this study. Median county age-adjusted MMI rate was 61.00 [46.30, 85.38] per 100.000. Median county age-adjusted prevalence of CS was 19.80% [17.40, 22.80], BD 17.70% [15.70, 19.90], Obesity 35.60% [32.70, 38.10], and NLTPA 26.50% [23.30, 30.68]. In a multivariable regression model, CS prevalence above 20% increased the MMI rate by 9.83 (6.82 to 12.84, p<0.001) per 100.000, NLTPA prevalence above 29% increased the MMI rate by 21.57 (18.12 to 25.02, p<0.001) per 100.000, and obesity prevalence above 36% increased the MMI rate by 8.30 (5.54 to 11.07, p<0.001) per 100.000. On the other hand, BD prevalence above 18% was not associated with a significant increase in the MMI rate. [0.67 (-2.11 to 3.44, p=0.638) per 100.000]. Conclusions: Community life-style risk-factors associated with myocardial infarction mortality include current smoking, no-leisure physical activity, and obesity. Alcohol binge drinking did not reduce myocardial infarction mortality rate.

The Impact of Air Pollutants on a Chicagoland Cohort of Patients with Acute Myeloid Leukemia

Background Outcomes in acute myeloid leukemia (AML) can be impacted by cytogenetic/molecular features along with environmental factors such as previous exposure to cytotoxic therapy and county-level income. Our group previously identified structural racism, defined as systemic disadvantage experienced by certain groups of people, as a mediator of disparities within a cohort of 822 patients (pts) diagnosed with AML in the Chicagoland area even when accounting for genetic features of disease (Abraham et al, Blood 2022). Air pollution disproportionately impacts racial-ethnic minorities and has been demonstrated to impact DNA methylation patterns in pts which in turn influence disease biology (Tessum et al, Sci Advances 2021; Rider et al, Clin Epigenetics 2019). With that in mind we aimed to investigate the impact of air pollutant exposures that have been associated with both leukemia development/mortality and with air pollution disparities in historically redlined cities. Methods Adult AML (non-APL) pts diagnosed between 2012 and 2018 at six academic cancer centers in the Chicago area were included. Pts' census tracts were joined with measures of pollution obtained from the Center for Disease Control National Environmental Public Health Tracking Network and the 2014 National Air Toxics Assessment: 1,3-butadiene, benzene, diesel particulate matter (PM), polycyclic aromatic hydrocarbons and polycyclic organic matter (PAHPOM), and PM 2.5 µm (2014 averaged daily census tract measures). Pollutant exposures by racial/ethnic groups were determined using a Kruskall-Wallis rank sum test and pairwise Wilcoxon rank sum tests. Univariate logistic regressions for each pollutant were performed for 2010 European Leukemia Net (ELN) AML criteria and TP53 mutation status. Survival among pts in the most and least polluted census block quartiles for each pollutant was compared using Kaplan-Meier survival analysis. Results Our multi-center database contained 789 pts with AML with census tract data, allowing for air pollutant data collection. Median age of diagnosis was 62 years old. In addition, 59.9% of pts were non-Hispanic White (NHW), 15.3% were non-Hispanic Black (NHB), and 15% of pts were Hispanic. Additional characteristics are summarized in Table 1. There was significantly higher median exposure to 1,3-butadiene, benzene, diesel PM, PAHPOM, and PM2.5 in NHB and Hispanic pts when compared to NHW pts. Hispanic pts had significantly median higher exposure to 1,3-butadiene and benzene when compared to NHB pts while NHB pts had significantly higher median exposure to PM2.5 ( Table 2). With univariate analysis, no pollutant exposure was found to be significantly associated with ELN 2010 risk category or with TP53 mutation status. We also compared median OS (mOS) from AML diagnosis between the quartile with the lowest exposure (Q1) and quartile with the highest exposure (Q4). For 1,3-butadiene mOS was 2.52 years (Q1) vs. 2.96 years (Q4) (p=0.75), for benzene it was 2.65 years vs 3.0 years (p=0.38), for diesel PM it was 2.56 years vs 2.96 years (p=0.56), for PAHPOM it was 2.76 years vs. 2.96 years (p=0.31), and for PM2.5 it was 2.92 years vs. 2.70 years (p=0.32). Conclusions We analyzed the impact of 1,3-butadiene, benzene, diesel PM, PAHPOM, and PM2.5 on outcomes in pts with AML in the Chicagoland area. While there were significant differences in median exposure to pollutants by race/ethnicity, there was no significant association between pollutant exposure and ELN 2010 risk category or TP53 mutation analysis. We also analyzed overall survival between Q1 and Q4 of exposure for each pollutant and found no significant difference. While pollutant exposure disproportionately impacts racial-ethnic minorities, individual pollutants did not appear to be a major driver of outcomes in AML. Limitations include the source of our air pollutant data, where misclassification of pollutants may exist and impact the ability to detect true associations.

Per- and Polyfluoroalkyl Substances (PFAS) in Community Water Systems (CWS) and the Risk of Thyroid Cancer: An Ecological Study.

Thyroid cancer incidence has been steadily increasing over the past decade in the United States (US). A discussion exists regarding the potential contribution of exposure to endocrine-disrupting chemicals, encompassing certain per- and poly-fluoroalkyl substances (PFASs). This ecological study evaluated the potential correlation between PFAS levels in drinking water and thyroid cancer incidence in the US. Data on age-adjusted thyroid cancer incidence rate (per 100,000 persons) by county were obtained from the Centers for Disease Control and Prevention (CDC) for US counties with available data in 2015-2019. Data on PFAS concentrations in the drinking water of selected community water systems (CWSs) were obtained from the CDC National Environmental Public Health Tracking Network in 2013-2015. The correlation between PFASs in CWSs and thyroid cancer incidence was calculated using Spearman correlation. A statistically significant correlation was found between perfluorooctanoic acid (PFOA) (r = 0.031; p = 0.043), perfluorononanoic acid (PFNA) (r = 0.058; p ≤ 0.001), and thyroid cancer incidence. The results suggest a potential link between certain PFAS exposures and thyroid cancer risk. However, due to the nature of an ecological study, no conclusions can be drawn at the individual level or causality. More research is needed, particularly on an individual level to allow for more detailed exposure assessment.

495 Radon and Fracking Exposures and Lymphoma Risk in a Canine Model of non-Hodgkin Lymphoma

OBJECTIVES/GOALS: The objective of this study was to determine whether residential radon and proximity to horizontal oil and drilling (fracking) are risk factors for the development of multicentric lymphoma in pet dogs, a spontaneous, immunocompetent model for non-occupational risk for NHL in humans. METHODS/STUDY POPULATION: Two case-control populations of dogs with multicentric lymphoma were utilized, with a focus on two dog breeds at high risk for lymphoma. Control dogs were matched for age, breed, and sex. Home addresses were collected for 54 Golden retrievers with lymphoma and 108 Golden retriever controls, and for 56 boxer dogs with lymphoma and 84 unaffected boxer controls. Counties of residence were matched to radon zones and percentage of home radon tests that exceeded the actionable level of 4 pCi/L, available by county through the EPA and the CDC National Environmental Public Health Tracking Network from 2008 to 2017. Locations of horizontal oil and gas wells were obtained from the Enverus Database, and distances from dog homes to the closest well, and well density by county, were calculated for each case and control. RESULTS/ANTICIPATED RESULTS: We found no significant differences in radon zones, county level radon measurements, or residential proximity to active fracking wells between dogs with lymphoma and unaffected controls in either the Golden Retriever or boxer populations. DISCUSSION/SIGNIFICANCE: Canine multicentric lymphoma resembles human NHL and is a valuable model of non-occupational environmental risk for NHL in people. Although we did not find geographic associations between radon and fracking wells, follow-up studies will measure household radon, as well as household air, water, and dog urine for potentially genotoxic chemicals.

Temporal Variation in Indoor Radon Concentrations Using Environmental Public Health Tracking Data.

Indoor radon is the second leading cause of lung cancer in the United States (US) after smoking and the number one for lung cancer in non-smokers. Understanding how indoor radon varies during the year reveals the best time to test to avoid underestimating exposure. This study looks at the temporal variation in 13 years of radon concentrations in buildings located in 46 US states and the District of Columbia (DC). In the dataset, radon concentration varies from 3.7 Bq m -3 (Becquerels per cubic meter) to 52,958.1 Bq m -3 , with an overall mean of 181.4 Bq m -3 . About 35.4% of tests have a radon concentration level equal to or greater than the US Environmental Protection Agency (US EPA) action level 4.0 pCi L -1 (148 Bq m -3 ). 3 Temporal variation in radon concentrations was assessed using the overall monthly mean radon concentration. The highest concentrations were found in January (203.8 Bq m -3 ) and the lowest in July (129.5 Bq m -3 ). Higher monthly mean indoor radon concentrations were found in January, February, and October, and lower in July, August, and June. This result is consistent with findings from other studies and suggests continuing to encourage radon testing throughout the year with an emphasis on testing during the colder months.

Feasibility of visualizing cancer incidence data at sub-county level: Findings from 21 National Program of Cancer Registries

Monitoring cancer incidence data by geography is useful for planning public health activities. However, due to anticipated confidentiality and statistical reliability issues, data on cancer incidence and mortality are more often displayed at a national, state, or county level, rather than at more local levels. To address this gap in displaying cancer data at the local level, the CDC's National Environmental Public Health Tracking Program and 21 National Program of Cancer Registries worked together on a pilot project to examine the feasibility of displaying sub-county-level incidence of selected cancer types diagnosed during 2007–2016. The results from this project are important steps for building sub-county cancer displays into data visualizations and using the data in a way that provides meaningful insights. The availability of sub-county cancer data may allow researchers to better examine cancer data at a local level which may help guide public health decisions regarding community-based interventions and screening services.

A Multistate Study on Housing Factors Influential to Heat-Related Illness in the United States.

As climate change increases the frequency and intensity of devastating and unpredictable extreme heat events, developments to the built environment should consider instigating practices that minimize the likelihood of indoor overheating during hot weather. Heatwaves are the leading cause of death among weather-related causes worldwide, including in developed and developing countries. In this empirical study, a four-step approach was used to collect, extract and analyze data from twenty-seven states in the United States. Three housing characteristic categories (i.e., general housing conditions, living conditions, and housing thermal inertia) and eight variables were extracted from the American Housing Survey database, ResStock database and CDC's National Environmental Public Health Tracking Network. Multivariable regression models were used to understand the influential variables, a multicollinearity test was used to determine the dependence of those variables, and then a logistic model was used to verify the results. Three variables-housing age (HA), housing crowding ratio (HCR), and roof condition (RC)-were found to be correlated with the risk of heat-related illness (HRI) indexes. Then, a logistic regression model was generated using the three variables to predict the risk of heat-related emergency department visits (EDV) and heat-related mortality (MORD) on a state level. The results indicate that the proposed logistic regression model correctly predicted 100% of the high-risk states for MORD for the eight states tested. Overall, this analysis provides additional evidence about the housing character variables that influence HRI. The outcomes also reinforce the concept of the built environment determined health and demonstrate that the built environment, especially housing, should be considered in techniques for mitigating climate change-exacerbated health conditions.

Associations between short-term exposure of PM2.5 constituents and hospital admissions of cardiovascular diseases among 18 major Chinese cities

Previous studies showed different risk effects on exposure of fine particulate matter (PM2.5) mass for cardiovascular disease (CVD) globally, which is likely due to different constituents of PM2.5. This study aimed to investigate the association between short-term exposure of PM2.5 constituents and hospital admissions of CVD. Daily counts of city-specific hospital admissions for CVD in 18 cities in China between 2014 and 2017 were extracted from the national Urban Employee Basic Medical Insurance database and the Beijing Municipal Commission of Health and Family Planning Information Center database. Directly measured PM2.5 constituents, including ions and polycyclic aromatic hydrocarbons, were collected by the Chinese Environmental Public Health Tracking system. We used the time-stratified case-crossover design to estimate the association between PM2.5 constituents and hospital admissions of CVD. Concentrations of ions accounted for the majority of the detected constituents. Excess risk (ER) of average ions concentrations for CVD was highest as 2.30% (95% CI: 1.62–2.99%) for NH4+, whose major sources are residential and agricultural emissions. This was followed by 1.85% (1.30–2.41%) for NO3- (generally from vehicles), 0.95% (0.28–1.63%) for SO42- (often from fossil fuel burning) respectively. The association for ions were generally consistent with ischemic heart disease (IHD) and ischemic stroke, e.g., NH4+ was associated with IHD (2.50%; 1.52–3.48%) and ischemic stroke (1.77%; 0.65–2.9%). For polycyclic aromatic hydrocarbons (PAHs), mainly from coal and vehicle-related oil combustion, the constituents were all associated with ischemic stroke but not for IHD. The ER for ischemic stroke was highest at 1.69% (0.99–2.39%) for indeno (123-cd) pyrene. Thus, in terms of the subtypes of CVD, the risks of hospital admissions varied with exposure to different PM2.5 constituents. Exposed to NH4+ had the highest risk to IHD and ischemic stroke, whereas PAHs were predominately associated with ischemic stroke only.

Interventions to reduce lead (Pb) exposure and value of a broad environmental health monitoring capacity

Background and aims In recent years, reports of lead (Pb) contamination have dramatically increased in Georgia. In 2018, 41% of the children who participated in the Multiple Indicator Cluster Surveys (MICS), a nationally representative among 2 to 7 years old children (n=1578), had blood Pb levels (BLL) above 5 microgram/dL. The National Centre for Disease Control and Public Health of Georgia (NCDC&PH) implemented written and verbal advice on how to reduce Pb exposure, and a state program of clinical follow-up was implemented. A significant reduction of BLL in children over a relatively short period has been documented. We aimed to identify the most relevant sources of Pb exposure contributing to elevated blood Pb in MICS children. Methods In collaboration with UK Health Security Agency, British Geological Survey, and Georgian agencies, NCDC&PH conducted a Pb isotope ratio study in 36 purposefully selected children from MICS. Environmental samples collected for each included household included dust, soil, paint, spices, milk, drinking water, and toys. Pb isotope ratio analyses were conducted on both blood and environmental samples. Analyses included household level and group level ranking of environmental sources as an explanation of exposure to Pb represented by BILL. Results Preliminary results indicate that drinking water and milk are not among Pb exposure sources of concern, while the precise ranking of other Pb sources varies between children and regions of Georgia. Conclusions It is expected that these data will support the design of more detailed public health interventions to reduce exposure to key sources of Pb, thus leading to further reduction of Pb-induced health effects in Georgia. In addition, this experience will clarify elements of ongoing monitoring of environmental factors such as an Environmental Public Health Tracking system, to support the national capacity to manage the risks to public health. Keywords Lead, intervention, health surveillance

Social vulnerability, medical care access and asthma related emergency department visits and hospitalization: An observational study

BackgroundThe Social Vulnerability Index (SVI) is a publicly available dataset to identify communities in greatest need of resources. ObjectiveTo examine the utility of using the county-level SVI as predictors of asthma-related outcomes. MethodsWe used the American Community Survey-derived SVI and the National Environmental Public Health Tracking Network – Query Tool to retrieve data for all counties with available SVI data and at least one matched outcome of interest. Then, we tested SVI as a predictor for emergency department visits (EDV) and hospitalizations, with investigating disparities in primary care physician (PCP) density and emergency department physicians (EDP) density. Linear and logistic regression models were used. ResultsCompared to counties of the lowest SVI quartile, counties of mid-low, mid-high, and highest SVI quartiles had 1%, 4%, and 5% higher odds of asthma-related EDV per 10,000 population, respectively, and 4%, 21%, and 24% higher odds of asthma-related hospitalization per 10,000 population, respectively. Moreover, the data showed an apparent resources mismatch between the EDP densities per 10,000 populations and the SVI quartiles, and the effect of the county level SVI on the asthma-related EDV and hospitalization is not strongly affected by PCP or EDP densities. ConclusionThe counties with the highest SVI -and the most vulnerable to asthma hazards- have a lower coverage of PCP and EDP. Interventions directed to address persistent social vulnerability would offer the opportunity of primary prevention with less exhaustion for the medical resources.

Full-coverage 1 km daily ambient PM<sub>2.5</sub> and O<sub>3</sub> concentrations of China in 2005–2017 based on a multi-variable random forest model

Abstract. The health risks of fine particulate matter (PM2.5) and ambient ozone (O3) have been widely recognized in recent years. An accurate estimate of PM2.5 and O3 exposures is important for supporting health risk analysis and environmental policy-making. The aim of our study was to construct random forest models with high-performance and estimate daily average PM2.5 concentration and O3 daily maximum of 8 h average concentration (O3-8 hmax) of China in 2005–2017 at a spatial resolution of 1 km × 1 km. The model variables included meteorological variables, satellite data, chemical transport model output, geographic variables and socioeconomic variables. Random forest model based on 10-fold cross-validation was established, and spatial and temporal validations were performed to evaluate the model performance. According to our sample-based division method, the daily, monthly and yearly estimations of PM2.5 from test datasets gave average model-fitting R2 values of 0.85, 0.88 and 0.90, respectively; these R2 values were 0.77, 0.77 and 0.69 for O3-8 hmax, respectively. The meteorological variables and their lagged values can significantly affect both PM2.5 and O3-8 hmax estimations. During 2005–2017, PM2.5 concentration exhibited an overall downward trend, while ambient O3 concentration experienced an upward trend. Whilst the spatial patterns of PM2.5 and O3-8 hmax barely changed between 2005 and 2017, the temporal trend had spatial characteristics. The dataset is accessible to the public at https://doi.org/10.5281/zenodo.4009308 (Ma et al., 2021a), and the shared dataset of Chinese Environmental Public Health Tracking (CEPHT, 2022) is available at https://cepht.niehs.cn:8282/developSDS3.html.

The association between air pollution and childhood asthma: United States, 2010–2015

Objective The current population-based study examines the association between county-level ambient air pollution and childhood asthma. Methods Data from the nationally representative 2010–2015 National Health Interview Survey were linked to nationwide fine particulate matter (PM2.5) air pollution data at the county-level from the National Environmental Public Health Tracking Network which utilizes air quality monitoring stations and modeled PM2.5 measurements (Downscaler model data) and adjusted by county-level socioeconomic characteristics data from the 2010–2015 American Community Survey. Multilevel modeling techniques were used to assess the association between PM2.5 annual concentrations (quartiles < 8.11, 8.11–9.50, 9.51–10.59, ≥ 10.60 µg/m3) and current childhood asthma along with two asthma outcomes (episode in the past year, emergency room (ER) visit due to asthma). Results From 2010 to 2015, there were significant declines in PM2.5 concentrations and asthma outcomes. In unadjusted models, children living in areas with higher PM2.5 concentrations were more likely to have current asthma, ≥1 asthma episode in the past year, and ≥1 ER visit due to asthma compared with children living in areas with the lowest quartile (< 8.11 µg/m3). After adjusting for characteristics at the county, geographic, and child and family-level, significant associations remained for asthma episode, and ER visit among children living in areas with PM2.5 annual concentrations between 9.51 and 10.59 µg/m3 (3rd quartile) compared with children living in areas with the lowest quartile. Conclusions This study adds to the limited literature by incorporating nationally representative county-, child-, and family-level data to provide a multi-level analysis of the associations between air pollution and childhood asthma in the U.S.

Developing an air pollution exposure surveillance system in England; a new national vulnerability indicator

BACKGROUND AND AIM: Air pollution is a serious public health issue and stakeholders (in particular local authorities (LA)) require more detailed information to protect those at risk. Public Health England was tasked to develop enhanced surveillance for air pollution, as part of the Environmental Public Health Tracking programme, and this may include surveillance of hazards (such as air pollution), exposures (concentrations of PM2.5 and NO2) and susceptibility (pre-existing demographic, social and health conditions). AIMS: 1) To scope and develop feasibility of air pollution exposure surveillance for stakeholders in England, 2) To design, pilot and trial potential new indicators to represent human vulnerabilities to air pollution, to help identify areas with populations who are sensitive, i.e. by age or socio-economic status (SES). METHODS: Following extensive consultation with stakeholders, vulnerability indicator development was conducted in two stages: 1) choice of exposure data and susceptibility indicator, and 2) linkage of the exposure and susceptibility indicators to produce population vulnerability that can be provided in a useful output format, e.g. map, rating index or indicator. We interviewed pilot LA’s to gain feedback on local application. RESULTS:We focused on susceptibility to ambient air pollution: age, SES and location, and related these to air pollution (PM2.5 and NO2) concentrations. We combined the exposure data and susceptibility to derive the vulnerabilities indicator plotted in a GIS. LA’s interpreted the maps for their areas and fed back how the indicator supported local decision-making processes. CONCLUSIONS:An air pollution exposure surveillance system is piloted for England. LAs welcomed the novel public health application and new datasets. The indicator shows where exposure needs to be tackled to reduce health effects including morbidity associated with exposure to outdoor air pollution. Next, the indicator needs to track the impact of interventions where changes in air pollution occur. KEYWORDS: Air pollution, Environmental disparities, Policy and Practice, methodological study design, exposures, multi-pollutants.

The Growing Relation between Environment and Public Health

Introduction: Environmental health is deteriorating worldwide. Evidence shows that exposure to air, water and soil pollution has caused many deaths worldwide, a trend that is increasing day by day. Health consequences from exposure to environmental pollutants range from cancer, lung disease, heart disease and a series health problems which often lead to death. The majority of pollution related deaths happens mostly in low and middle-income countries. Environmental and pollution health related issues are not getting the attention they deserve in Albania. The main purpose of this article is to identify the relationship between environmental problems and public health consequences, by analysing public policies, case studies and instruments for measuring environmental health indicators. The article also presents suggestions regarding development of Environmental Medicine in Albania, and Public Health Tracking methods. Methods: Qualitative method is thoughtfully used in this article. Specifically, literature review methodology is used to identify environmental indicators that directly affect public health, adequate policies and instruments for the protection of public health, as well as environmental health at the international and national level. Qualitative method is used to reveal and evaluate the topic through multiple facets covering relevant contextual conditions. This method helps identifying the link between public and environment health indicators in a real-life situation, and to understand the relationship between these indicators in the Albanian context. Results and Discussion: Albania lacks a specific measurement system of Environmental Public Health Tracking, as well an established methodology for linking environmental and public health. Potential capacities for measuring environmental and health indicators are limited at the national level, thus, the public health policies do not clearly and fully integrate environmental health indicators for the protection of public health. Vocational training in health and environment is being practiced through various disciplines, but there is a need for specialized environmental medicine health professionals, with adequate competences in the field. Conclusions: The correlation between environment and public health is gaining attention nationally and globally. As in other countries, the need for Environmental Medicine professionals is growing also in Albania. Strong correlations between of environmental pollution indicators (air, water, land pollution) and public health indicators (such as infant and general mortality, morbidity rates, respiratory diseases, etc.) have increased in the last years. Use of instruments (such as EPHT), a fully integrated university curricula and a specific discipline of Environmental Medicine should be made a priority not only nationally, but also globally as environmental problems such as climate change do not recognize national borders. In order to manage the rising cases, states need to be resilient, and build appropriate research based policies and action plans to prevent the occurrence of environmental related public health consequences. Doi: 10.28991/SciMedJ-2021-0302-3 Full Text: PDF