Disaggregation of Green Space Access, Walkability, and Behavioral Risk Factor Data for Precise Estimation of Local Population Characteristics.

BACKGROUND: Social and Environmental Determinants of Health (SEDH) provide us with a conceptual framework to gain insights into possible associations among different human behaviors and the corresponding health outcomes that take place often in and around complex built environments. Developing better built environments requires an understanding of those aspects of a community that are most likely to have a measurable impact on the target SEDH. Yet data on local characteristics at suitable spatial scales are often unavailable. We aim to address this issue by application of different data disaggregation methods. METHODS: We applied different approaches to data disaggregation to obtain small area estimates of key behavioral risk factors, as well as geospatial measures of green space access and walkability for each zip code of Allegheny County in southwestern Pennsylvania. RESULTS: Tables and maps of local characteristics revealed their overall spatial distribution along with disparities therein across the county. While the top ranked zip codes by behavioral estimates generally have higher than the county's median individual income, this does not lead them to have higher than its median green space access or walkability. CONCLUSION: We demonstrated the utility of data disaggregation for addressing complex questions involving community-specific behavioral attributes and built environments with precision and rigor, which is especially useful for a diverse population. Thus, different types of data, when comparable at a common local scale, can provide key integrative insights for researchers and policymakers.

Comparison of Census Tract-Level Chronic Disease Prevalence Estimates From 500 Cities and Local Health Claims Data.

OBJECTIVES: To compare city and census tract-level diabetes and hypertension prevalence using 500 Cities Project modeled estimates from the Centers for Disease Control and Prevention (CDC) and insurance claims data. METHODS: Insurance claims by census tract were collected from 3 local health plans for the city of Pittsburgh, Pennsylvania, for 2015-2016; conditions were defined using International Classification of Diseases, Ninth Revision (ICD-9) and Tenth Revision (ICD-10) codes. Crude prevalence estimates with 95% confidence intervals were downloaded from the CDC 500 Cities Web site to obtain modeled estimates by census tract. Confidence intervals were calculated for claims and compared with modeled estimates; nonoverlapping intervals were considered significant. Pearson correlation coefficients were generated for census tract-level comparison. RESULTS: City-level model-based and claims estimates were 9% versus 10% for diabetes and 31% versus 21% for hypertension. At the census tract level, model-based and insurance claims estimates were more concordant for diabetes (r = 0.366) than for hypertension (r = 0.220). Modeled estimates were significantly higher than claims estimates for 89% of census tracts for hypertension and 35% for diabetes. CONCLUSIONS: Modeled estimates from the 500 Cites Project were significantly higher than insurance claims estimates for hypertension but were more consistent for diabetes. Utilization of multiple data sources to understand local-level chronic disease burden requires consideration of the strengths and limitations of each.

Development of a Synthetic Population Model for Assessing Excess Risk for Cardiovascular Disease Death.

Importance: Evaluating the association of social determinants of health with chronic diseases at the population level requires access to individual-level factors associated with disease, which are rarely available for large populations. Synthetic populations are a possible alternative for this purpose. Objective: To construct and validate a synthetic population that statistically mimics the characteristics and spatial disease distribution of a real population, using real and synthetic data. Design, Setting, and Participants: This population-based decision analytical model used data for Allegheny County, Pennsylvania, collected from January 2015 to December 2016, to build a semisynthetic population based on the synthetic population used by the modeling and simulation platform FRED (A Framework for Reconstructing Epidemiological Dynamics). Disease status was assigned to this population using health insurer claims data from the 3 major insurance providers in the county or from the National Health and Nutrition Examination Survey. Biological, social, and other variables were also obtained from the National Health Interview Survey, Allegheny County, and public databases. Data analysis was performed from November 2016 to February 2020. Exposures: Risk of cardiovascular disease (CVD) death. Main Outcomes and Measures: Difference between expected and observed CVD death risk. A validated risk equation was used to estimate CVD death risk. Results: The synthetic population comprised 1 188 112 individuals with demographic characteristics similar to those of the 2010 census population in the same county. In the synthetic population, the mean (SD) age was 40.6 (23.3) years, and 622 997 were female individuals (52.4%). Mean (SD) observed 4-year rate of excess CVD death risk at the census tract level was -40 (523) per 100 000 persons. The correlation of social determinant data with difference between expected and observed CVD death risk indicated that income- and education-based social determinants were associated with risk. Estimating improved social determinants of health and biological factors associated with disease did not entirely remove the excess in CVD death rates. That is, a 20% improvement in the most significant determinants still resulted in 105 census tracts with excess CVD death risk, which represented 24% of the county population. Conclusions and Relevance: The results of this study suggest that creating a geographically explicit synthetic population from real and synthetic data is feasible and that synthetic populations are useful for modeling disease in large populations and for estimating the outcome of interventions.

A risk-based model to assess environmental justice and coronary heart disease burden from traffic-related air pollutants.

BACKGROUND: Communities need to efficiently estimate the burden from specific pollutants and identify those most at risk to make timely informed policy decisions. We developed a risk-based model to estimate the burden of black carbon (BC) and nitrogen dioxide (NO2) on coronary heart disease (CHD) across environmental justice (EJ) and non-EJ populations in Allegheny County, PA. METHODS: Exposure estimates in census tracts were modeled via land use regression and analyzed in relation to US Census data. Tracts were ranked into quartiles of exposure (Q1-Q4). A risk-based model for estimating the CHD burden attributed to BC and NO2 was developed using county health statistics, census tract level exposure estimates, and quantitative effect estimates available in the literature. RESULTS: For both pollutants, the relative occurrence of EJ tracts (> 20% poverty and/or > 30% non-white minority) in Q2 - Q4 compared to Q1 progressively increased and reached a maximum in Q4. EJ tracts were 4 to 25 times more likely to be in the highest quartile of exposure compared to the lowest quartile for BC and NO2, respectively. Pollutant-specific risk values (mean [95% CI]) for CHD mortality were higher in EJ tracts (5.49 × 10- 5 [5.05 × 10- 5 - 5.92 × 10- 5]; 5.72 × 10- 5 [5.44 × 10- 5 - 6.01 × 10- 5] for BC and NO2, respectively) compared to non-EJ tracts (3.94 × 10- 5 [3.66 × 10- 5 - 4.23 × 10- 5]; 3.49 × 10- 5 [3.27 × 10- 5 - 3.70 × 10- 5] for BC and NO2, respectively). While EJ tracts represented 28% of the county population, they accounted for about 40% of the CHD mortality attributed to each pollutant. EJ tracts are disproportionately skewed toward areas of high exposure and EJ residents bear a greater risk for air pollution-related disease compared to other county residents. CONCLUSIONS: We have combined a risk-based model with spatially resolved long-term exposure estimates to predict CHD burden from air pollution at the census tract level. It provides quantitative estimates of effects that can be used to assess possible health disparities, track temporal changes, and inform timely local community policy decisions. Such an approach can be further expanded to include other pollutants and adverse health endpoints.

Linking Opioid-Overdose Data to Human Services and Criminal Justice Data: Opportunities for Intervention.

OBJECTIVES: In Allegheny County, Pennsylvania, the incidence of opioid-related overdose deaths increased from 17.4 per 100 000 population in 2008 to 23.9 per 100 000 population in 2014. Our objectives were to describe local demographic characteristics of this epidemic, identify public human services targets for intervention, determine temporal relationships between use of public human services and overdose mortality, and provide recommendations about potentially beneficial interventions. METHODS: We used autopsy data from the Allegheny County Medical Examiner to link people who died of overdoses from 2008 through 2014 to their premortem incarcerations and use of mental health services and substance use disorder services. We calculated the frequency of use of public human services by decedents and the interval between the last use of these services and overdose death. RESULTS: Of the 1399 decedents, 957 (68.4%) had a public human service encounter before overdose death. Of these 957 decedents, 531 (55.5%) had ever been incarcerated, 616 (64.4%) had ever used a mental health service, and 702 (73.4%) had ever used a substance use disorder service. Of 211 decedents incarcerated in the year before their overdose death, 54 (25.6%) overdosed within 30 days of their last release from jail. Of 510 decedents using mental health services in the year before death, 231 (45.3%) overdosed within 30 days of their last use of the services. Of 350 decedents using substance use disorder services in the year before their overdose death, 134 (38.3%) overdosed within 30 days of their last use of the services. CONCLUSIONS: Merging data on overdose mortality with data on use of public human services can be a useful strategy to identify trends in, and factors contributing to, the opioid epidemic; to target interventions; and to stimulate collaboration to address the epidemic.

Increasing WIC Farmers' Market Nutrition Program Redemption Rates: Results and Policy Recommendations.

BACKGROUND: WIC Farmers' Market Nutrition Program (FMNP) aims to increase consumption of fresh produce among Special Supplemental Nutrition Program for Women, Infants and Children (WIC) participants while supporting local farmers. Area stakeholders are addressing the existing barriers to FMNP use that keep participation low. OBJECTIVES: Increase FMNP check redemption by participants in a Pittsburgh WIC office. METHODS: Quasiexperimental design including cooking demonstrations, tours of FMs, and community garden visits. Program participation and check redemption rates were tracked. RESULTS: The redemption rate of FMNP checks among research participants and nonparticipants was 46.5% and 39.0% (P < .001), respectively. Lessons learned point to needed changes on the local, state, and federal levels. CONCLUSIONS: Barriers to the use of WIC FMNP checks were consistent with the literature. Allowing mobile markets to accept FMNP checks may address barriers to FM shopping while supporting the local farmer. Our stakeholder group continues to recommend multilevel policy changes to improve the redemption rate.

Environmental lead and childhood blood lead levels in US children: NHANES, 1999-2006.

Although blood lead levels in the United States have fallen dramatically since 1980, there remain subgroups of children with high blood lead levels. We assessed the relationship between environmental lead sources and blood lead levels in children ages 1 to 5 years from the National Health and Nutrition Examination Survey (NHANES), 1999-2006. Modeled ambient air lead levels and industrial lead releases at the census-tract level were assigned to each child's residence with adjustment for confounding factors. Of 3,223 children, 272 (8.4%) had blood lead levels ≥ 5 ug/dL. Industrial releases (2,252 vs 1,696 lbs/mi2) and ambient air lead levels (2.28 vs 1.75 ng/m3) were greater in exposed versus unexposed children. For every 10,000 lb/mi2 increase in inverse distance squared weighted exposure, there was a 1.13% increase (95% CI: 0.45%, 1.81%) in blood lead (p = .001).

Perinatal outcomes and unconventional natural gas operations in Southwest Pennsylvania.

Unconventional gas drilling (UGD) has enabled extraordinarily rapid growth in the extraction of natural gas. Despite frequently expressed public concern, human health studies have not kept pace. We investigated the association of proximity to UGD in the Marcellus Shale formation and perinatal outcomes in a retrospective cohort study of 15,451 live births in Southwest Pennsylvania from 2007-2010. Mothers were categorized into exposure quartiles based on inverse distance weighted (IDW) well count; least exposed mothers (first quartile) had an IDW well count less than 0.87 wells per mile, while the most exposed (fourth quartile) had 6.00 wells or greater per mile. Multivariate linear (birth weight) or logistical (small for gestational age (SGA) and prematurity) regression analyses, accounting for differences in maternal and child risk factors, were performed. There was no significant association of proximity and density of UGD with prematurity. Comparison of the most to least exposed, however, revealed lower birth weight (3323 ± 558 vs 3344 ± 544 g) and a higher incidence of SGA (6.5 vs 4.8%, respectively; odds ratio: 1.34; 95% confidence interval: 1.10-1.63). While the clinical significance of the differences in birth weight among the exposure groups is unclear, the present findings further emphasize the need for larger studies, in regio-specific fashion, with more precise characterization of exposure over an extended period of time to evaluate the potential public health significance of UGD.

The association of respiratory hospitalization rates in WV counties, total, underground, and surface coal production and sociodemographic covariates.

BACKGROUND: Exposures associated with coal mining have long been linked to occupational disease. More recently, investigators have suggested that this industry may affect community health. METHODS: We explored associations between age-adjusted, county-level respiratory disease hospitalization rates (RHRs) in West Virginia and total, surface, and underground coal production, taking into account relevant sociodemographic and behavioral covariates. RHRs were calculated for 2005 to 2009, and analyses were performed to assess the effect of coal production after adjusting for sociodemographic factors. RESULTS: After controlling for percent below poverty, percent urban, and smoking, neither total nor underground tonnage was associated with RHR. Surface coal production, however, was significantly related with RHR (P < 0.05). CONCLUSIONS: Surface coal production makes a small but significant contribution to RHR in West Virginia after accounting for other important sociodemographic and behavioral determinants of health.

Do US ambient air lead levels have a significant impact on childhood blood lead levels: results of a national study.

INTRODUCTION: Although lead paint and leaded gasoline have not been used in the US for thirty years, thousands of US children continue to have blood lead levels (BLLs) of concern. METHODS: We investigated the potential association of modeled air lead levels and BLLs ≥ 10 µ g/dL using a large CDC database with BLLs on children aged 0-3 years. Percent of children with BLLs ≥ 10 µ g/dL (2000-2007) by county and proportion of pre-50 housing and SES variables were merged with the US EPA's National Air Toxics Assessment (NATA) modeled air lead data. RESULTS: The proportion with BLL ≥ 10 µ g/dL was 1.24% in the highest air lead counties, and the proportion with BLL ≥ 10 µ g/dL was 0.36% in the lowest air lead counties, resulting in a crude prevalence ratio of 3.4. Further analysis using multivariate negative binomial regression revealed that NATA lead was a significant predictor of % BLL ≥ 10 µ g/dL after controlling for percent pre-l950 housing, percent rural, and percent black. A geospatial regression revealed that air lead, percent older housing, and poverty were all significant predictors of % BLL ≥ 10 µ g/dL. CONCLUSIONS: More emphasis should be given to potential sources of ambient air lead near residential areas.

Can 8-hydroxy-2'-deoxyguanosine be used to assess oxidative stress caused by particulate matter air pollution in the general population?

OBJECTIVES: Assess the association between 8-hydroxy-2'-deoxyguanosine (8OHdG) levels and particulate matter air pollution in non-occupational exposure groups from peer-reviewed literature. METHODS: Ovid Medline and PubMed were used to search for all peer-reviewed articles published between 1946 and May 2013. Keywords included particulate matter, air pollution, deoxyguanosine, 8-hydroxy-2'-deoxyguanosine, and known abbreviations. Seven English, non-occupational exposure, human subject studies were evaluated. RESULTS: Of the two studies involving children one found significant positive associations between exposure to particulate matter air pollution and 8OHdG. Investigations into non-occupationally exposed adults were mixed. The lone double-blind crossover study found no relationship between diesel exhaust exposure and 8OHdG. Two out of three panel studies and one cohort study found significant associations between 8OHdG and classes of particles and for various lags. CONCLUSIONS: Analyses accounting for particle composition and lags between exposure and physiological responses had the strongest significant associations. Results are not conclusive due to the inconsistency in study designs, small sample sizes, and differences in exposure assessment techniques. Consistent methodology with representative populations including women and other non-occupationally exposed groups are recommended.

Trends in acute myocardial infarction hospitalization rates for US States in the CDC tracking network.

OBJECTIVES: We examined temporal trends, spatial variation, and gender differences in rates of hospitalization due to acute myocardial infarction. METHODS: We used data from the Centers for Disease Control National Environmental Public Health Tracking Network to evaluate temporal trends, geographic variation, and gender differences in 20 Environmental Public Health Tracking Network states from 2000 to 2008. A longitudinal linear mixed effects model was fitted to the acute myocardial infarction hospitalization rates for the states and counties within each state to examine the overall temporal trend. RESULTS: There was a significant overall decrease in age-adjusted acute myocardial infarction hospitalization rates between 2000 and 2008, with most states showing over a 20% decline during the period. The ratio of male/female rates for acute myocardial infarction hospitalization rates remained relatively consistent over time, approximately two-fold higher in men compared to women. A large geographic variability was found for age-adjusted acute myocardial infarction hospitalization rates, with the highest rates found in the Northeastern states. Results of two ecological analyses revealed that the NE region remained significantly associated with increased AMI hospitalization rates after adjustment for socio-demographic factors. CONCLUSIONS: This investigation is one of the first to explore geographic differences in AMI age adjusted hospital rates in individuals 35+ years of age for 2000-2008. We showed a decreasing trend in AMI hospitalization rates in men and women. A large geographic variability in rates was found with particularly higher rates in the New England/Mid-Atlantic region of the US and lower rates in the mountain and Pacific states of the tracking network. It appeared that over time this disparity in rates became less notable.

Estimation of short-term effects of air pollution on stroke hospital admissions in Wuhan, China.

BACKGROUND AND OBJECTIVE: High concentrations of air pollutants have been linked to increased incidence of stroke in North America and Europe but not yet assessed in mainland China. The aim of this study is to evaluate the association between stroke hospitalization and short-term elevation of air pollutants in Wuhan, China. METHODS: Daily mean NO2, SO2 and PM10 levels, temperature and humidity were obtained from 2006 through 2008. Data on stroke hospitalizations (ICD 10: I60-I69) at four hospitals in Wuhan were obtained for the same period. A time-stratified case-crossover design was performed by season (April-September and October-March) to assess effects of pollutants on stroke hospital admissions. RESULTS: Pollution levels were higher in October-March with averages of 136.1 µg/m(3) for PM10, 63.6 µg/m(3) for NO2 and 71.0 µg/m(3) for SO2 than in April-September when averages were 102.0 µg/m(3), 41.7 µg/m(3) and 41.7 µg/m(3), respectively (p<.001). During the cold season, every 10 µg/m(3) increase in NO2 was associated with a 2.9% (95%C.I. 1.2%-4.6%) increase in stroke admissions on the same day. Every 10 ug/m(3) increase in PM10 daily concentration was significantly associated with an approximate 1% (95% C.I. 0.1%-1.4%) increase in stroke hospitalization. A two-pollutant model indicated that NO2 was associated with stroke admissions when controlling for PM10. During the warm season, no significant associations were noted for any of the pollutants. CONCLUSIONS: Exposure to NO2 is significantly associated with stroke hospitalizations during the cold season in Wuhan, China when pollution levels are 50% greater than in the warm season. Larger and multi-center studies in Chinese cities are warranted to validate our findings.

The relationship of ambient ozone and PM(2.5) levels and asthma emergency department visits: possible influence of gender and ethnicity.

ABSTRACT An investigation of the relationship of air pollution and emergency department (ED) visits for asthma was an opportunity to assess environmental risks for asthma exacerbations in an urban population. A total of 6,979 individuals with a primary discharge diagnosis of asthma presented to 1 of 6 EDs in the Pittsburgh, Pennsylvania, area between 2002 and 2005. Using a case-crossover methodology, which controls for the effects of subject-specific covariates such as gender and race, a 2.5% increase was observed in asthma ED visits for each 10 ppb increase in the 1-hour maximum ozone level on day 2 (odds ratio [OR] = 1.025, p < .05). Particulate matter with an aerodynamic diameter ≤2.5 µm (PM(2.5)) had an effect both on the total population on day 1 after exposure (1.036, p < .05), and on African Americans on days 1, 2, and 3. PM(2.5) had no significant effect on Caucasian Americans alone. The disparity in risk estimates by race may reflect differences in residential characteristics, exposure to ambient air pollution, or a differential effect of pollution by race.

Changes over time in audiometric thresholds in a group of automobile stamping and assembly workers with a hearing conservation program.

Noise induced hearing loss (NIHL) is among the 10 leading occupational diseases, afflicting between 7.4 and 10.2 million people who work in noise above 85 dBA. Although mandatory hearing conservation programs (HCPs) have been in effect since 1972, this problem persists, as hearing protectors are not consistently used by workers, or may not attenuate to manufacturer's estimates in real world conditions. In this study, information from noise and hearing protection use measurements taken at an automobile assembly plant were used to construct average lifetime noise exposure and hearing protection compliance estimates for use in modeling to predict both total hearing loss and onset of two accepted definitions of hearing loss. There were 301 males and females in this cohort; their mean age was 42.6 (7.2) years, and mean tenure was 14.3 (3.5) years. Average length of follow-up was 14.0 years. There were 16 members of this cohort who had hearing loss at the speech frequencies (defined as an average hearing level > or = 25 dB at 500, 1000, and 2000 Hz). In cross-sectional multivariate analyses, years of employment, male gender, and proportion of time wearing hearing protection were the factors most associated with hearing loss at the average of 2000, 3000, and 4000 Hz (p < 0.0001) controlling for age, transfer status (as a surrogate for previous noise exposure), race, and lifetime average noise exposure. The most consistent predictor of hearing loss in both univariate and multivariate analyses was percentage of time having used hearing protection during the workers' tenure.