Racial residential segregation shapes the relationship between early childhood lead exposure and fourth-grade standardized test scores.

Racial/ethnic disparities in academic performance may result from a confluence of adverse exposures that arise from structural racism and accrue to specific subpopulations. This study investigates childhood lead exposure, racial residential segregation, and early educational outcomes. Geocoded North Carolina birth data is linked to blood lead surveillance data and fourth-grade standardized test scores (n = 25,699). We constructed a census tract-level measure of racial isolation (RI) of the non-Hispanic Black (NHB) population. We fit generalized additive models of reading and mathematics test scores regressed on individual-level blood lead level (BLL) and neighborhood RI of NHB (RINHB). Models included an interaction term between BLL and RINHB. BLL and RINHB were associated with lower reading scores; among NHB children, an interaction was observed between BLL and RINHB. Reading scores for NHB children with BLLs of 1 to 3 µg/dL were similar across the range of RINHB values. For NHB children with BLLs of 4 µg/dL, reading scores were similar to those of NHB children with BLLs of 1 to 3 µg/dL at lower RINHB values (less racial isolation/segregation). At higher RINHB levels (greater racial isolation/segregation), children with BLLs of 4 µg/dL had lower reading scores than children with BLLs of 1 to 3 µg/dL. This pattern becomes more marked at higher BLLs. Higher BLL was associated with lower mathematics test scores among NHB and non-Hispanic White (NHW) children, but there was no evidence of an interaction. In conclusion, NHB children with high BLLs residing in high RINHB neighborhoods had worse reading scores.

The Association between Long-term PM2.5 Exposure and Risk for Pancreatic Cancer: An Application of Social Informatics.

There is a profound need to identify modifiable risk factors to screen and prevent pancreatic cancer. Air pollution, including fine particulate matter (PM2.5), is increasingly recognized as a risk factor for cancer. We conducted a case-control study using data from the electronic health record (EHR) of Duke University Health System, 15-year residential history, NASA satellite fine particulate matter (PM2.5) and neighborhood socioeconomic data. Using deterministic and probabilistic linkage algorithms, we linked residential history and EHR data to quantify long term PM2.5 exposure. Logistic regression models quantified the association between a one interquartile range (IQR) increase in PM2.5 concentration and pancreatic cancer risk. The study included 203 cases and 5027 controls (median age of 59 years, 62% female, 26% Black). Individuals with pancreatic cancer had higher average annual exposure (9.4 µg/m3) as compared to IQR increase in average annual PM2.5 was associated with greater odds of pancreatic cancer (OR=1.20; 95% CI: 1.00-1.44). These findings highlight the link between elevated PM2.5 exposure and increased pancreatic cancer risk. They may inform screening strategies for high-risk populations and guide air pollution policies to mitigate exposure.

Weekly prenatal PM2.5 and NO2 exposures in preterm, early term, and full term infants: Decrements in birth weight and critical windows of susceptibility.

BACKGROUND: Previous studies have observed associations between birth weight and prenatal air pollution exposure, but there is not consensus on timing of critical windows of susceptibility. OBJECTIVE: We estimated the difference in birth weight among preterm, early term and full term births associated with weekly exposure to PM2.5 and NO2 throughout gestation. METHODS: We included all singleton live births in the Lower Peninsula of Michigan (United States) between 2007 and 2012 occurring at or after 32 weeks gestational age (n = 497,897). Weekly ambient PM2.5 and NO2 concentrations were estimated at maternal residences using 1-km gridded data from ensemble-based models. We utilized a distributed lag nonlinear model to estimate the difference in birth weight associated with weekly exposures from the last menstrual period (week 0) through 31 weeks gestation for preterm births; through 36 weeks gestation for early term births; and through 38 weeks gestation for full term births. RESULTS: In single-pollutant models, a 5 µg/m3 increase in PM2.5 exposure was associated with a reduction in birth weight among preterm births (-37.1 g [95% confidence interval [CI]: 60.8 g, -13.5 g]); early term births (-13.5 g [95% CI: 26.2 g, -0.67 g]); and full term births (-8.23 g [95% CI: 15.8 g, -0.68 g])]. In single-pollutant models, a 10 ppb increase in NO2 exposure was associated with a -11.7 g (95% CI: 14.46 g, -8.92 g) decrement in birth weight among full term births only. In models co-adjusted for PM2.5 and NO2, PM2.5 exposure was associated with reduced birth weight among preterm births (-36.9 g [95% CI: 61.9 g, -11.8 g]) and NO2 exposure was associated with reduced birth weight among full term births (-11.8 g [95% CI: 14.7 g, -8.94 g]). The largest decrements in birth weight were associated with PM2.5 exposure between approximately 10 and 26 weeks of pregnancy; for NO2 exposure, the largest decrements in birth weight in full term births were associated with exposure between weeks 6-18. CONCLUSION: We observed the largest and most persistent adverse associations between PM2.5 exposure and birth weight in preterm infants, and between NO2 exposure and birth weight in full term infants. Exposure during the first half of pregnancy had a greater impact on birthweight.

Characteristics and Outcomes of Patients Discharged Directly Home From the Pediatric Intensive Care Unit.

Introduction: Patients admitted to the pediatric intensive care unit (PICU) typically transfer to an acute care floor prior to discharge (ACD). Various circumstances, including rapid clinical improvement, technology dependence, or capacity constraints, may lead to discharge directly to home from a PICU (DDH). This practice has been studied in adult intensive care units, but research is lacking for PICU patients. Methods: We aimed to describe characteristics and outcomes of patients requiring PICU admission who experienced DDH versus ACD. We conducted a retrospective cohort study of patients ≤18 years old admitted to our academic, tertiary care PICU between 1/1/15 and 12/31/20. Patients who died or were transferred to another facility were excluded. Baseline characteristics (including home ventilator dependence) and markers of illness severity, specifically the need for vasoactive infusion or new mechanical ventilation, were compared between groups. Admission diagnoses were categorized using the Pediatric Clinical Classification System (PECCS). Our primary outcome was hospital readmission within 30 days. Results: Of 4042 PICU admissions during the study period, 768 (19%) were DDH. Baseline demographic characteristics were similar, although DDH patients were more likely to have a tracheostomy (30% vs 5%, P < .01) and require a home ventilator at discharge (24% vs 1%, P < .01). DDH was associated with being less likely to have required a vasoactive infusion (7% vs 11%, P < .01), shorter median length of stay (LOS) (2.1 days vs 5.9 days, P < .01) and increased rate of readmission within 30 days of discharge (17% vs 14%, P < .05). However, repeat analysis after removing ventilator-dependent patients at discharge (n = 202) showed no difference in rates of readmission (14% vs 14%, P = .88). Conclusions: Direct discharge home from the PICU is a common practice. DDH and ACD groups had similar 30-day readmission rate when patient admissions with home ventilator dependence were excluded.

Where Is Air Quality Improving, and Who Benefits? A Study of PM2.5 and Ozone Over 15 Years.

In the United States, concentrations of criteria air pollutants have declined in recent decades. Questions remain regarding whether improvements in air quality are equitably distributed across subpopulations. We assessed spatial variability and temporal trends in concentrations of particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) and ozone (O3) across North Carolina from 2002-2016, and associations with community characteristics. Estimated daily PM2.5 and O3 concentrations at 2010 Census tracts were obtained from the Fused Air Quality Surface Using Downscaling archive and averaged to create tract-level annual PM2.5 and O3 estimates. We calculated tract-level measures of: racial isolation of non-Hispanic Black individuals, educational isolation of non-college educated individuals, the neighborhood deprivation index (NDI), and percentage of the population in urban areas. We fitted hierarchical Bayesian space-time models to estimate baseline concentrations of and time trends in PM2.5 and O3 for each tract, accounting for spatial between-tract correlation. Concentrations of PM2.5 and O3 declined by 6.4 µg/m3 and 13.5 ppb, respectively. Tracts with lower educational isolation and higher urbanicity had higher PM2.5 and more pronounced declines in PM2.5. Racial isolation was associated with higher PM2.5 but not with the rate of decline in PM2.5. Despite declines in pollutant concentrations, over time, disparities in exposure increased for racially and educationally isolated communities.

Information entropy tradeoffs for efficient uncertainty reduction in estimates of air pollution mortality.

Implementing effective policy to protect human health from the adverse effects of air pollution, such as premature mortality, requires reducing the uncertainty in health outcomes models. Here we present a novel method to reduce mortality uncertainty by increasing the amount of input data of air pollution and health outcomes, and then quantifying tradeoffs associated with the different data gained. We first present a study of long-term mortality from fine particulate matter (PM2.5) based on simulated data, followed by a real-world application of short-term PM2.5-related mortality in an urban area. We employ information yield curves to identify which variables more effectively reduce mortality uncertainty when increasing information. Our methodology can be used to explore how specific pollution scenarios will impact mortality and thus improve decision-making. The proposed framework is general and can be applied to any real case-scenario where knowledge in pollution, demographics, or health outcomes can be augmented through data acquisition or model improvements to generate more robust risk assessments.

Disparities in air quality downscaler model uncertainty across socioeconomic and demographic indicators in North Carolina.

Studies increasingly use output from the Environmental Protection Agency's Fused Air Quality Surface Downscaler ("downscaler") model, which provides spatial predictions of daily concentrations of fine particulate matter (PM2.5) and ozone (O3) at the census tract level, to study the health and societal impacts of exposure to air pollution. Downscaler outputs have been used to show that lower income and higher minority neighborhoods are exposed to higher levels of PM2.5 and lower levels of O3. However, the uncertainty of the downscaler estimates remains poorly characterized, and it is not known if all subpopulations are benefiting equally from reliable predictions. We examined how the percent errors (PEs) of daily concentrations of PM2.5 and O3 between 2002 and 2016 at the 2010 census tract centroids across North Carolina were associated with measures of racial and educational isolation, neighborhood disadvantage, and urbanicity. Results suggest that there were socioeconomic and demographic disparities in surface concentrations of PM2.5 and O3, as well as their prediction uncertainties. Neighborhoods characterized by less reliable downscaler predictions (i.e., higher PEPM2.5 and PEO3) exhibited greater levels of aerial deprivation as well as educational isolation, and were often non-urban areas (i.e., suburban, or rural). Between 2002 and 2016, predicted PM2.5 and O3 levels decreased and O3 predictions became more reliable. However, the predictive uncertainty for PM2.5 has increased since 2010. Substantial spatial variability was observed in the temporal changes in the predictive uncertainties; educational isolation and neighborhood deprivation levels were associated with smaller increases in predictive uncertainty of PM2.5. In contrast, racial isolation was associated with a greater decline in the reliability of PM2.5 predictions between 2002 and 2016; it was associated with a greater improvement in the predictive reliability of O3 within the same time frame.

A longitudinal study of exposure to fine particulate matter during pregnancy, small-for-gestational age births, and birthweight percentile for gestational age in a statewide birth cohort.

BACKGROUND: Previous studies observed associations between prenatal exposure to fine particulate matter (≤ 2.5 µm; PM2.5) and small-for-gestational-age (SGA) birth and lower birthweight percentile for gestational age. Few, if any, studies examine prenatal air pollution exposure and these pregnancy outcomes in neonates born to the same women. Here, we assess whether prenatal exposure to ambient fine particulate matter (PM2.5) is associated with small-for-gestational-age (SGA) birth or birthweight percentile for gestational age in a longitudinal setting. METHODS: Detailed birth record data were used to identify women who had singleton live births at least twice in North Carolina during 2002-2006 (n = 53,414 women, n = 109,929 births). Prenatal PM2.5 exposures were calculated using daily concentration estimates obtained from the US EPA Fused Air Quality Surface using Downscaling data archive. Associations between PM2.5 exposure and birthweight percentile and odds of SGA birth were calculated using linear and generalized mixed models, comparing successive pregnancies to the same woman. Odds ratios and associations were also estimated in models that did not account for siblings born to the same mother. RESULTS: Among NHW women, pregnancy-long PM2.5 exposure was associated with SGA (OR: 1.11 [1.06, 1.18]) and lower birthweight percentile (- 0.46 [- 0.74, - 0.17]). Trimester-specific PM2.5 was also associated with SGA and lower birthweight percentile. Among NHB women, statistically significant within-woman associations between PM2.5, SGA, and birthweight percentile were not observed. However, in models that did not account for births to the same mother, statistically significant associations were observed between some PM2.5 exposure windows and higher odds of SGA and lower birthweight percentile among NHB women. CONCLUSIONS: Findings suggest that a woman is at greater risk of delivering an SGA or low birthweight percentile neonate when she has been exposed to higher PM2.5 levels. The within-woman comparison implemented here better controls for factors that may differ between women and potentially confound the relationship between PM2.5 exposure and pregnancy outcomes. This adds to the evidence that PM2.5 exposure may be causally related to SGA and birthweight percentile, even at concentrations close to or below National Ambient Air Quality Standards.

Bayesian variable selection for understanding mixtures in environmental exposures.

Social and environmental stressors are crucial factors in child development. However, there exists a multitude of measurable social and environmental factors-the effects of which may be cumulative, interactive, or null. Using a comprehensive cohort of children in North Carolina, we study the impact of social and environmental variables on 4th end-of-grade exam scores in reading and mathematics. To identify the essential factors that predict these educational outcomes, we design new tools for Bayesian linear variable selection using decision analysis. We extract a predictive optimal subset of explanatory variables by coupling a loss function with a novel model-based penalization scheme, which leads to coherent Bayesian decision analysis and empirically improves variable selection, estimation, and prediction on simulated data. The Bayesian linear model propagates uncertainty quantification to all predictive evaluations, which is important for interpretable and robust model comparisons. These predictive comparisons are conducted out-of-sample with a customized approximation algorithm that avoids computationally intensive model refitting. We apply our variable selection techniques to identify the joint collection of social and environmental stressors-and their interactions-that offer clear and quantifiable improvements in prediction of reading and mathematics exam scores.

Effects of accumulated environmental, social and host exposures on early childhood educational outcomes.

BACKGROUND: Persistent disparities in academic performance may result from a confluence of adverse exposures accruing disproportionately to specific subpopulations. OBJECTIVE: Our overarching objective was to investigate how multiple exposures experienced over time affect early childhood educational outcomes. We were specifically interested in whether there were: racial/ethnic disparities in prevalence of adverse exposures; racial/ethnic disparities in associations observed between adverse exposures and early childhood educational outcomes; and interactions between exposures, suggesting that one exposure augments susceptibility to adverse effects of another exposure. METHODS: We link geocoded North Carolina birth data for non-Hispanic white (NHW) and non-Hispanic black (NHB) children to blood lead surveillance data and 4th grade end-of-grade (EOG) standardized test scores (n = 65,151). We construct a local, spatial index of racial isolation (RI) of NHB at the block group level. We fit race-stratified multi-level models of reading and mathematics EOG scores regressed on birthweight percentile for gestational age, blood lead level, maternal smoking, economic disadvantage, and RI, adjusting for maternal- and child-level covariates and median household income. RESULTS: There were marked racial/ethnic disparities in prevalence of adverse exposures. Specifically, NHB children were more likely than NHW children to be economically disadvantaged (80% vs. 40%), live in block groups with the highest quintile of RI (46% vs. 5%), have higher blood lead levels (4.6 vs. 3.7 µg/dL), and lower birthweight percentile for gestational age (mean: 39th percentile vs. 51st percentile). NHB children were less likely to have mothers who reported smoking during pregnancy (11% and 22%). We observed associations between key adverse exposures and reading and math EOG scores in 4th grade. Higher birthweight percentile for gestational age was associated with higher EOG scores, while economic disadvantage, maternal smoking, and elevated blood lead levels were associated with lower EOG scores. Associations observed for NHB and NHW children were generally not statistically different from one another, with the exception of neighborhood RI. NHB children residing in block groups in the highest RI quintile had reading and math scores 1.54 (0.74, 2.34) and 1.12 (0.38, 1.87) points lower, respectively, compared to those in the lowest RI quintile; statistically significant decrements in EOG scores associated with RI were not observed for NHW children. We did not find evidence of multiplicative interactions between exposures for NHB or NHW children. DISCUSSION: Key adverse host, environmental, and social exposures accrue disproportionately to NHB children. Decrements in test scores associated with key adverse exposures were often but not always larger for NHB children, but were not significantly different from those estimated for NHW children. While we did not observe interactive effects, NHB children on average experience more deleterious combined exposures, resulting in larger decrements to test scores compared to NHW children.

Clinical and Economic Impact of Wound Care Using a Polyurethane Foam Multilayer Dressing.

OBJECTIVE: To study the impact of a newly introduced dressing on efficiency and quality of care in routine clinical practice in a Spanish community setting. DESIGN AND SETTING: An ambispective multicenter observational study was conducted in 24 primary care centers and 6 nursing homes in 4 different Spanish regions. The study was carried out between November 2017 and March 2019. PATIENTS AND INTERVENTION: A total of 128 wounds in 94 patients (primary care, n = 79; nursing home, n = 15) were analyzed before and 4 weeks after switching to the study dressing. OUTCOME MEASURES: Frequency of dressing changes; secondary outcomes were change in the mean wound area and weekly cost and patient and provider satisfaction. MAIN RESULTS: The mean number of dressing changes was significantly reduced with the study dressing from 3.14 ± 1.77 changes per week to 1.66 ± 0.87 (P < .001), a 47.1% reduction in frequency. Wound area significantly reduced from 9.90 ± 19.62 cm to 7.10 ± 24.33 cm. In addition, a 58.7% reduction in weekly costs was achieved with the intervention. Patients and providers agreed that their satisfaction with wound care improved. CONCLUSIONS: The use of the study dressing in routine clinical practice could lead to a major improvement in both efficiency and quality of wound care. Its use could reduce wound care-related costs through improvements in healing and a reduced frequency of dressing changes. It also enhanced the wound care experience from the perspective of both patients and providers.

Geosocial Factors Associated With Adherence to Statin Medications.

BACKGROUND: Individual patient characteristics, social determinants, and geographic access may be associated with patients engaging in appropriate health behaviors. OBJECTIVE: To assess the relationship between statin adherence, geographic accessibility to pharmacies, and neighborhood sociodemographic characteristics in Michigan. METHODS: The proportion of days covered (PDC) was calculated from pharmacy claims of a large insurer of adults who had prescriptions for statins between July 2009 and June 2010. A PDC ≥0.80 was defined as adherent. The predictor of interest was a ZIP code tabulation area (ZCTA)-level measure of geographic accessibility to pharmacies, measured using a method that integrates availability and access into a single index. We fit unadjusted models as well as adjusted models controlling for age, sex, and ZCTA-level measures of socioeconomic status (SES), racial isolation (RI) of non-Hispanic blacks, and urbanicity. RESULTS: More than 174 000 patients' claims data were analyzed. In adjusted models, pharmacy access was not associated with adherence (0.99; 95% CI: 0.96, 1.03). Greater RI (0.87; 95% CI: 0.85, 0.88) and urban status (0.93; 95% CI: 0.89, 0.96) were associated with lower odds of adherence. Individuals in ZCTAs with higher SES had higher odds of adherence, as were men and older age groups. CONCLUSION AND RELEVANCE: Adherence to statin prescriptions was lower for patients living in areas characterized as being racially segregated or lower income. Initiating interventions to enhance adherence, informed by understanding the social and systematic barriers patients face when refilling medication, is an important public health initiative that pharmacists practicing in these areas may undertake.

Residential Racial Isolation and Spatial Patterning of Hypertension in Durham, North Carolina.

INTRODUCTION: Neighborhood characteristics such as racial segregation may be associated with hypertension, but studies have not examined these relationships using spatial models appropriate for geographically patterned health outcomes. The objectives of our study were to 1) evaluate the geographic heterogeneity of hypertension; 2) describe whether and how patient-level risk factors and racial isolation relate to geographic heterogeneity in hypertension; and 3) examine cross-sectional associations of hypertension with racial isolation. METHODS: We obtained electronic health records from the Duke Medicine Enterprise Data Warehouse for 2007-2011. We linked patient data with data on racial isolation determined by census block of residence. We constructed a local spatial index of racial isolation for non-Hispanic black patients; the index is scaled from 0 to 1, with 1 indicating complete isolation. We used aspatial and spatial Bayesian models to assess spatial variation in hypertension and estimate associations with racial isolation. RESULTS: Racial isolation ranged from 0 (no isolation) to 1 (completely isolated). A 0.20-unit increase in racial isolation was associated with 1.06 (95% credible interval, 1.03-1.10) and 1.11 (95% credible interval, 1.07-1.16) increased odds of hypertension among non-Hispanic black and non-Hispanic white patients, respectively. Across Durham, census block-level odds of hypertension ranged from 0.62 to 1.88 among non-Hispanic black patients and from 0.32 to 2.41 among non-Hispanic white patients. Compared with spatial models that included patient age and sex, residual heterogeneity in spatial models that included age, sex, and block-level racial isolation was 33% lower for non-Hispanic black patients and 20% lower for non-Hispanic white patients. CONCLUSION: Racial isolation of non-Hispanic black patients was associated with increased odds of hypertension among both non-Hispanic black and non-Hispanic white patients. Further research is needed to identify latent spatially patterned factors contributing to hypertension.

Residential Racial Isolation and Spatial Patterning of Type 2 Diabetes Mellitus in Durham, North Carolina.

Neighborhood characteristics such as racial segregation may be associated with type 2 diabetes mellitus, but studies have not examined these relationships using spatial models appropriate for geographically patterned health outcomes. We constructed a local, spatial index of racial isolation (RI) for black residents in a defined area, measuring the extent to which they are exposed only to one another, to estimate associations of diabetes with RI and examine how RI relates to spatial patterning in diabetes. We obtained electronic health records from 2007-2011 from the Duke Medicine Enterprise Data Warehouse. Patient data were linked to RI based on census block of residence. We used aspatial and spatial Bayesian models to assess spatial variation in diabetes and relationships with RI. Compared with spatial models with patient age and sex, residual geographic heterogeneity in diabetes in spatial models that also included RI was 29% and 24% lower for non-Hispanic white and black residents, respectively. A 0.20-unit increase in RI was associated with an increased risk of diabetes for white (risk ratio = 1.24, 95% credible interval: 1.17, 1.31) and black (risk ratio = 1.07, 95% credible interval: 1.05, 1.10) residents. Improved understanding of neighborhood characteristics associated with diabetes can inform development of policy interventions.

The impact of temperature on mortality in a subtropical city: effects of cold, heat, and heat waves in São Paulo, Brazil.

Understanding how weather impacts health is critical, especially under a changing climate; however, relatively few studies have investigated subtropical regions. We examined how mortality in São Paulo, Brazil, is affected by cold, heat, and heat waves over 14.5 years (1996-2010). We used over-dispersed generalized linear modeling to estimate heat- and cold-related mortality, and Bayesian hierarchical modeling to estimate overall effects and modification by heat wave characteristics (intensity, duration, and timing in season). Stratified analyses were performed by cause of death and individual characteristics (sex, age, education, marital status, and place of death). Cold effects on mortality appeared higher than heat effects in this subtropical city with moderate climatic conditions. Heat was associated with respiratory mortality and cold with cardiovascular mortality. Risk of total mortality was 6.1% (95% confidence interval 4.7, 7.6%) higher at the 99th percentile of temperature than the 90th percentile (heat effect) and 8.6% (6.2, 11.1%) higher at the 1st compared to the 10th percentile (cold effect). Risks were higher for females and those with no education for heat effect, and males for cold effect. Older persons, widows, and non-hospital deaths had higher mortality risks for heat and cold. Mortality during heat waves was higher than on non-heat wave days for total, cardiovascular, and respiratory mortality. Our findings indicate that mortality in São Paulo is associated with both cold and heat and that some subpopulations are more vulnerable.

A systematic review of the physical health impacts from non-occupational exposure to wildfire smoke.

BACKGROUND: Climate change is likely to increase the threat of wildfires, and little is known about how wildfires affect health in exposed communities. A better understanding of the impacts of the resulting air pollution has important public health implications for the present day and the future. METHOD: We performed a systematic search to identify peer-reviewed scientific studies published since 1986 regarding impacts of wildfire smoke on health in exposed communities. We reviewed and synthesized the state of science of this issue including methods to estimate exposure, and identified limitations in current research. RESULTS: We identified 61 epidemiological studies linking wildfire and human health in communities. The U.S. and Australia were the most frequently studied countries (18 studies on the U.S., 15 on Australia). Geographic scales ranged from a single small city (population about 55,000) to the entire globe. Most studies focused on areas close to fire events. Exposure was most commonly assessed with stationary air pollutant monitors (35 of 61 studies). Other methods included using satellite remote sensing and measurements from air samples collected during fires. Most studies compared risk of health outcomes between 1) periods with no fire events and periods during or after fire events, or 2) regions affected by wildfire smoke and unaffected regions. Daily pollution levels during or after wildfire in most studies exceeded U.S. EPA regulations. Levels of PM10, the most frequently studied pollutant, were 1.2 to 10 times higher due to wildfire smoke compared to non-fire periods and/or locations. Respiratory disease was the most frequently studied health condition, and had the most consistent results. Over 90% of these 45 studies reported that wildfire smoke was significantly associated with risk of respiratory morbidity. CONCLUSION: Exposure measurement is a key challenge in current literature on wildfire and human health. A limitation is the difficulty of estimating pollution specific to wildfires. New methods are needed to separate air pollution levels of wildfires from those from ambient sources, such as transportation. The majority of studies found that wildfire smoke was associated with increased risk of respiratory and cardiovascular diseases. Children, the elderly and those with underlying chronic diseases appear to be susceptible. More studies on mortality and cardiovascular morbidity are needed. Further exploration with new methods could help ascertain the public health impacts of wildfires under climate change and guide mitigation policies.

Prepubertal exposure to polycyclic aromatic hydrocarbons are associated with early pubertal development onset in boys: A longitudinal study.

OBJECTIVE: To investigate the effects of polycyclic aromatic hydrocarbons(PAHs) on puberty in boys. METHODS: 695 subjects were selected from four primary schools in Chongqing, China. 675 urine samples from these boys were collected four PAH metabolites: 1-hydroxypyrene, 2-hydroxynaphthoic, 2-hydroxyfluorene, and 9-hydroxyphenanthrene. Pubertal development of 695 boys was assessed at follow-up visits starting in December 2015 and occurring every six months thereafter until now, data used in this article ending in June 2021. A total of 12 follow-up visits were performed. Cox proportional hazards regression models were used to analyze the relationship between PAH metabolite concentrations and indicators of pubertal timing. RESULTS: The mean age at puberty onset of testicular volume, facial hair, pubic hair, first ejaculation, and axillary hair in boys was 11.66, 12.43, 12.51, 12.72 and 13.70 years, respectively. Cox proportional hazards regression models showed that boys with moderate level of 1-OHPyr exposure was associated with earlier testicular development (hazard ratio [HR] = 1.276, 95% confidence interval [CI]: 1.006-1.619), with moderate level of 2-OHNap were at higher risk of early testicular development (HR = 1.273, 95% CI: 1.002-1.617) and early axillary hair development (HR = 1.355, 95% CI: 1.040-1.764), with moderate level of 2-OHFlu was associated with earlier pubic hair development (HR = 1.256, 95% CI: 1.001-1.577), with high level of 9-OHPhe were at higher risk of early fisrt ejaculation (HR = 1.333, 95% CI: 1.005-1.767) and early facial hair development (HR = 1.393, 95% CI: 1.059-1.831). CONCLUSION: Prepubertal exposure to PAHs may be associated with earlier pubertal development in boys.

Uncertainty Reduction and Environmental Justice in Air Pollution Epidemiology: The Importance of Minority Representation.

Ambient air pollution is an increasing threat to society, with rising numbers of adverse outcomes and exposure inequalities worldwide. Reducing uncertainty in health outcomes models and exposure disparity studies is therefore essential to develop policies effective in protecting the most affected places and populations. This study uses the concept of information entropy to study tradeoffs in mortality uncertainty reduction from increasing input data of air pollution versus health outcomes. We study a case scenario for short-term mortality from particulate matter (PM2.5) in North Carolina for 2001-2016, employing a case-crossover design with inputs from an individual-level mortality data set and high-resolution gridded data sets of PM2.5 and weather covariates. We find a significant association between mortality and PM2.5, and the information tradeoffs indicate that a 10% increase in mortality information reduces model uncertainty three times more than increased resolution of the air pollution model from 12 to 1 km. We also find that Non-Hispanic Black (NHB) residents tend to live in relatively more polluted census tracts, and that the mean PM2.5 for NHB cases in the mortality model is significantly higher than that of Non-Hispanic White cases. The distinct distribution of PM2.5 for NHB cases results in a relatively higher information value, and therefore faster uncertainty reduction, for new NHB cases introduced into the mortality model. This newfound influence of exposure disparities in the rate of uncertainty reduction highlights the importance of minority representation in environmental research as a quantitative advantage to produce more confident estimates of the true effects of environmental pollution.

Segregation and Childhood Blood Lead Levels in North Carolina.

BACKGROUND AND OBJECTIVES: Using a local measure of racial residential segregation, estimate the association between racial residential segregation and childhood blood lead levels between the early 1990s and 2015 in North Carolina. METHODS: This population-based observational study uses individual-level blood lead testing records obtained from the NC Department of Health and Human Services for 320 916 children aged <7 years who were tested between 1992 and 1996 or 2013 and 2015. NC childhood blood lead levels were georeferenced to the census tract. Neighborhood racial residential segregation, assessed using a local, spatial measure of the racial isolation of non-Hispanic Blacks (RINHB), was calculated at the census tract level. RESULTS: From 1990 to 2015, RINHB increased in 50% of 2195 NC census tracts, although the degree of change varied by geographic region. In 1992 to 1996 blood lead testing data, a 1-standard-deviation increase in tract-level RINHB was associated with a 2.86% (95% confidence interval: 0.96%-4.81%) and 2.44% (1.34%-3.56%) increase in BLL among non-Hispanic Black and non-Hispanic White children, respectively. In 2013 to 2015 blood lead testing data, this association was attenuated but persisted with a 1-standard-deviation increase in tract-level RINHB associated with a 1.59% (0.50%-2.70%) and 0.76% (0.08%-1.45%) increase in BLL among non-Hispanic Black and non-Hispanic White children, respectively. In the supplemental information, we show the change in racial residential segregation across the entire United States, demonstrating that RINHB increased in 69% of 72 899 US census tracts. CONCLUSIONS: Racially isolated neighborhoods are associated with higher childhood lead levels, demonstrating the disproportionate environmental burdens borne by segregated communities and warranting attention to providing whole child health care.

Long-term air pollution exposure and markers of cardiometabolic health in the National Longitudinal Study of Adolescent to Adult Health (Add Health).

BACKGROUND: Air pollution exposure is associated with cardiovascular morbidity and mortality. Although exposure to air pollution early in life may represent a critical window for development of cardiovascular disease risk factors, few studies have examined associations of long-term air pollution exposure with markers of cardiovascular and metabolic health in young adults. OBJECTIVES: By combining health data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) with air pollution data from the Fused Air Quality Surface using Downscaling (FAQSD) archive, we: (1) calculated multi-year estimates of exposure to ozone (O3) and particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) for Add Health participants; and (2) estimated associations between air pollution exposures and multiple markers of cardiometabolic health. METHODS: Add Health is a nationally representative longitudinal cohort study of over 20,000 adolescents aged 12-19 in the United States (US) in 1994-95 (Wave I). Participants have been followed through adolescence and into adulthood with five in-home interviews. Estimated daily concentrations of O3 and PM2.5 at census tracts were obtained from the FAQSD archive and used to generate tract-level annual averages of O3 and PM2.5 concentrations. We estimated associations between average O3 and PM2.5 exposures from 2002 to 2007 and markers of cardiometabolic health measured at Wave IV (2008-09), including hypertension, hyperlipidemia, body mass index (BMI), diabetes, C-reactive protein, and metabolic syndrome. RESULTS: The final sample size was 11,259 individual participants. The average age of participants at Wave IV was 28.4 years (range: 24-34 years). In models adjusting for age, race/ethnicity, and sex, long-term O3 exposure (2002-07) was associated with elevated odds of hypertension, with an odds ratio (OR) of 1.015 (95% confidence interval [CI]: 1.011, 1.029); obesity (1.022 [1.004, 1.040]); diabetes (1.032 [1.009,1.054]); and metabolic syndrome (1.028 [1.014, 1.041]); PM2.5 exposure (2002-07) was associated with elevated odds of hypertension (1.022 [1.001, 1.045]). CONCLUSION: Findings suggest that long-term ambient air pollution exposure, particularly O3 exposure, is associated with cardiometabolic health in early adulthood.