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.

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.

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.

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.

Assessing community-level exposure to social vulnerability and isolation: spatial patterning and urban-rural differences

BACKGROUND

Environmental health disparity research involves the use of metrics to assess exposure to community-level vulnerabilities or inequities. While numerous vulnerability indices have been developed, there is no agreement on standardization or appropriate use, they have largely been applied in urban areas, and their interpretation and utility likely vary across different geographies.

OBJECTIVE

We evaluated the spatial distribution, variability, and relationships among different metrics of social vulnerability and isolation across urban and rural settings to inform interpretation and selection of metrics for environmental disparity research.

METHODS

For all census tracts in North Carolina, we conducted a principal components analysis using 23 socioeconomic/demographic variables from the 2010 United States Census and American Community Survey. We calculated or obtained the neighborhood deprivation index (NDI), residential racial isolation index (RI), educational isolation index (EI), Gini coefficient, and social vulnerability index (SVI). Statistical analyses included Moran's I for spatial clustering, t-tests for urban-rural differences, Pearson correlation coefficients, and changes in ranking of tracts across metrics.

RESULTS

Social vulnerability metrics exhibited clear spatial patterning (Moran's I ≥ 0.30, p < 0.01). Greater educational isolation and more intense neighborhood deprivation was observed in rural areas and greater racial isolation in urban areas. Single-domain metrics were not highly correlated with each other (rho ≤ 0.36), while composite metrics (i.e., NDI, SVI, principal components analysis) were highly correlated (rho > 0.80). Composite metrics were more highly correlated with the racial isolation metric in urban (rho: 0.54-0.64) versus rural tracts (rho: 0.36-0.48). Census tract rankings changed considerably based on which metric was being applied.

SIGNIFICANCE

High correlations between composite metrics within urban and rural tracts suggests they could be used interchangeably; single domain metrics cannot. Composite metrics capture different facets of vulnerabilities in urban and rural settings, and these complexities should be examined by researchers applying metrics to areas of diverse urban and rural forms.

Polycyclic aromatic hydrocarbons are associated with later puberty in girls: A longitudinal study

The objective of this study is to explore associations between PAH exposures and puberty timing in girls. Beginning in May 2014, 734 girls age 7.2-11.8 years in Chongqing, China, were enrolled in a prospective cohort study. They were followed up every 6 months from enrollment through June 2021, at which point participants were ages 13.6-18.3 years. Metabolite concentrations of four PAHs (1-hydroxypyrene [1-OHPyr], 2-hydroxynaphthalene [2-OHNap], 2-hydroxyfluorine [2-OHFlu], and 9-hydroxyphenanthrene [9-OHPhe]) were measured in urine samples at baseline. At each follow up visit, the Tanner's Sexual Maturity Rating scale was administered. Cox proportional hazards models were used to estimate associations between four urinary PAH metabolite concentrations and four markers of puberty: menarche, breast development, pubic hair development, and axillary hair development. Geometric mean concentrations of 1-OHPyr, 2-OHNap, 2-OHFlu and 9-OHPhe in urine were 0.47 μg/L, 3.31 μg/L, 1.49 μg/L, 3.75 μg/L, respectively. There were statistically significant associations between several urinary PAH metabolite concentrations and puberty outcomes. PAH metabolite concentrations were grouped as Low (<25th percentile, referent group), Moderate (25th-75th percentile) or High (>75th). Girls with moderate levels of 1-OHPyr were at higher risk of delayed pubic hair development (hazard ratio [HR]: 0.82, 95 % confidence interval [CI]: 0.68-0.99). Delayed breast development (HR: 0.77, 95 % CI: 0.60-0.99) and pubic hair development (HR: 0.76, 95 % CI: 0.60-0.95) were associated with high 2-OHNap. High c 2-OHFlu was associated with delayed pubic hair development (HR: 0.77, 95 % CI: 0.61-0.96). Delayed breast (HR: 0.79, 95 % CI: 0.64-0.97), pubic hair (HR: 0.79, 95 % CI: 0.65-0.96) and axillary hair development (HR: 0.80, 95 % CI: 0.65-0.99) was associated with moderate 9-OHPhe. In conclusion, PAH exposure may delay puberty onset in girls.

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.

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.

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; PM_2.5) 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 (PM_2.5) 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 PM_2.5 exposures were calculated using daily concentration estimates obtained from the US EPA Fused Air Quality Surface using Downscaling data archive. Associations between PM_2.5 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 PM_2.5 exposure was associated with SGA (OR: 1.11 [1.06, 1.18]) and lower birthweight percentile (- 0.46 [- 0.74, - 0.17]). Trimester-specific PM_2.5 was also associated with SGA and lower birthweight percentile. Among NHB women, statistically significant within-woman associations between PM_2.5, 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 PM_2.5 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 PM_2.5 levels. The within-woman comparison implemented here better controls for factors that may differ between women and potentially confound the relationship between PM_2.5 exposure and pregnancy outcomes. This adds to the evidence that PM_2.5 exposure may be causally related to SGA and birthweight percentile, even at concentrations close to or below National Ambient Air Quality Standards.

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.

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.

Characteristics of the built environment and spatial patterning of type 2 diabetes in the urban core of Durham, North Carolina

BACKGROUND

Few studies examine relationships between built environment (BE) and type 2 diabetes mellitus (T2DM) using spatial models, investigate BE domains apart from food environment or physical activity resources or conduct sensitivity analysis of methodological choices made in measuring BE. We examine geographic heterogeneity of T2DM, describe how heterogeneity in T2DM relates to BE and estimate associations of T2DM with BE.

METHODS

Individual-level electronic health records (n=41 203) from the Duke Medicine Enterprise Data Warehouse (2007-2011) were linked to BE based on census block. Data on housing damage, property disorder, territoriality, vacancy and public nuisances were used to estimate BE based on four different construction methods (CMs). We used race-stratified aspatial and spatial Bayesian models to assess geographic heterogeneity in T2DM and associations of T2DM with BE.

RESULTS

Among whites, a 1 SD increase in poor quality BE was associated with a 1.03 (95% credible interval 1.01 to 1.06) and 1.06 (95 % credible interval 1.02 to 1.11) increased risk of T2DM for poor quality BE CM1 and CM2, respectively. Among blacks/African Americans, associations between T2DM and BE overlapped with the null for all CMs. The addition of BE to white models reduced residual geographic heterogeneity in T2DM by 4%-15%, depending on CM. In black/African-American models, BE did not affect residual heterogeneity.

CONCLUSION

Associations of T2DM with BE were sensitive to CM and geographic heterogeneity in T2DM differed by race/ethnicity. Findings underscore the need to consider multiple methods of estimating BE and consider differences in relationships by race/ethnicity.

People, place and pollution: Investigating relationships between air quality perceptions, health concerns, exposure, and individual- and area-level characteristics

An extensive body of research has demonstrated that air pollution exposure is associated with adverse health outcomes. Urban air quality remains a major concern for both public health officials and the general public. In the United States, air quality public awareness campaigns are major efforts of governments at every level. Yet, our understanding of relationships between ambient air pollution exposure, public perceptions of air quality, and concerns about associated health risks is incomplete. We examined 2869 individual responses to annual air quality public awareness surveys administered between 2009 and 2012 in the Kansas City metropolitan area. Our study had three objectives: 1) examine the spatial distribution of PM_2.5 and O₃ exposures, pollution perceptions, and pollution health concerns; 2) explore relationships between individual- and area-level characteristics and PM_2.5 and O₃ exposure; 3) and examine cross-sectional associations between individual- and area-level characteristics, as well as PM_2.5 and O₃ exposures, and pollution perception and pollution health concerns. We found inverse spatial patterns between the distribution of O₃ and PM_2.5 exposure levels as well as between areas where respondents perceived air pollution as worsening and areas where residents had higher concern about the health effects of pollution exposure. We also found inverse relationships between individual- and area-level demographic and socioeconomic characteristics and O₃ and PM_2.5 exposure. Individual-level characteristics were significantly related to pollution perceptions, while both individual- and area-level characteristics were significantly related to pollution health concerns. Public awareness campaigns should be combined with education on ways the public can protect themselves and tailored explicitly for targeting vulnerable populations (e.g., elderly, and persons with respiratory problems) and areas both socioeconomically vulnerable (e.g., higher racial segregation and poverty) and experiencing higher pollution exposure (e.g., O₃ and PM_2.5).

Toll-like Receptor 4 Pathway Polymorphisms Interact with Pollution to Influence Asthma Diagnosis and Severity

Asthma is a common chronic lung disease, the incidence and severity of which may be influenced by gene-environment interactions. Our objective was to examine associations between single nucleotide polymorphisms (SNPs) and combinations of SNPs in the toll-like receptor 4 (TLR4) pathway, residential distance to roadway as a proxy for traffic-related air pollution exposure, and asthma diagnosis and exacerbations. We obtained individual-level data on genotype, residential address, and asthma diagnosis and exacerbations from the Environmental Polymorphisms Registry. Subjects (n = 2,704) were divided into three groups (hyper-responders, hypo-responders, and neither) based on SNP combinations in genes along the TLR4 pathway. We geocoded subjects and calculated distance, classified as <250 m or ≥250 m, between residence and nearest major road. Relationships between genotype, distance to road, and odds of asthma diagnosis and exacerbations were examined using logistic regression. Odds of an asthma diagnosis among hyper-responders <250 m from a major road was 2.37(0.97, 6.01) compared to the reference group (p < 0.10). Hypo-responders ≥250 m from the nearest road had lower odds of activity limitations (0.46 [0.21, 0.95]) and sleeplessness (0.36 [0.12, 0.91]) compared to neither-responders (p < 0.05). Specific genotype combinations when combined with an individual's proximity to roadways, possibly due to traffic-related air pollution exposure, may affect the likelihood of asthma diagnosis and exacerbations.

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.

Airborne Fine Particles and Risk of Hospital Admissions for Understudied Populations: Effects by Urbanicity and Short-Term Cumulative Exposures in 708 U.S. Counties

BACKGROUND

Evidence of health risks associated with ambient airborne fine particles in nonurban populations is extremely limited.

OBJECTIVE

We estimated the risk of hospitalization associated with short-term exposures to particulate matter with an aerodynamic diameter < 2.5 μm (PM_2.5) in urban and nonurban counties with population ≥ 50,000.

METHODS

We utilized a database of daily cardiovascular- and respiratory-related hospitalization rates constructed from Medicare National Claims History files (2002-2006), including 28 million Medicare beneficiaries in 708 counties. Daily PM_2.5 exposures were estimated using the Community Multiscale Air Quality (CMAQ) downscaler. We used time-series analysis of hospitalization rates and PM_2.5 to evaluate associations between PM_2.5 levels and hospitalization risk in single-pollutant models.

RESULTS

We observed an association between cardiovascular hospitalizations and same-day PM_2.5 with higher risk in urban counties: 0.35% [95% posterior interval (PI): -0.71%, 1.41%] and 0.98% (95% PI: 0.73%, 1.23%) increases in hospitalization risk per 10-μg/m³ increment in PM_2.5 were observed in the least-urban and most-urban counties, respectively. The largest association for respiratory hospitalizations, a 2.57% (95% PI: 0.87%, 4.30%) increase per 10-μg/m³ increase in PM_2.5, was observed in the least-urban counties; in the most-urban counties, a 1.13% (0.73%, 1.54%) increase was observed. Effect estimates for cardiovascular hospitalizations were highest for smaller lag times, whereas effect estimates for respiratory hospitalizations increased as more days of exposure were included.

CONCLUSION

In nonurban counties with population ≥ 50,000, exposure to PM_2.5 is associated with increased risk for respiratory hospitalizations; in urban counties, exposure is associated with increased risk of cardiovascular hospitalizations. Effect estimates based on a single day of exposure may underestimate true effects for respiratory hospitalizations.

Particulate Air Pollution from Wildfires in the Western US under Climate Change

Wildfire can impose a direct impact on human health under climate change. While the potential impacts of climate change on wildfires and resulting air pollution have been studied, it is not known who will be most affected by the growing threat of wildfires. Identifying communities that will be most affected will inform development of fire management strategies and disaster preparedness programs. We estimate levels of fine particulate matter (PM2.5) directly attributable to wildfires in 561 western US counties during fire seasons for the present-day (2004-2009) and future (2046-2051), using a fire prediction model and GEOS-Chem, a 3-D global chemical transport model. Future estimates are obtained under a scenario of moderately increasing greenhouse gases by mid-century. We create a new term "Smoke Wave," defined as ≥2 consecutive days with high wildfire-specific PM2.5, to describe episodes of high air pollution from wildfires. We develop an interactive map to demonstrate the counties likely to suffer from future high wildfire pollution events. For 2004-2009, on days exceeding regulatory PM2.5 standards, wildfires contributed an average of 71.3% of total PM2.5. Under future climate change, we estimate that more than 82 million individuals will experience a 57% and 31% increase in the frequency and intensity, respectively, of Smoke Waves. Northern California, Western Oregon and the Great Plains are likely to suffer the highest exposure to widlfire smoke in the future. Results point to the potential health impacts of increasing wildfire activity on large numbers of people in a warming climate and the need to establish or modify US wildfire management and evacuation programs in high-risk regions. The study also adds to the growing literature arguing that extreme events in a changing climate could have significant consequences for human health.

Racial isolation and exposure to airborne particulate matter and ozone in understudied US populations: Environmental justice applications of downscaled numerical model output

BACKGROUND

Researchers and policymakers are increasingly focused on combined exposures to social and environmental stressors, especially given how often these stressors tend to co-locate. Such exposures are equally relevant in urban and rural areas and may accrue disproportionately to particular communities or specific subpopulations.

OBJECTIVES

To estimate relationships between racial isolation (RI), a measure of the extent to which minority racial/ethnic group members are exposed to only one another, and long-term particulate matter with an aerodynamic diameter of <2.5μ (PM2.5) and ozone (O3) levels in urban and nonurban areas of the eastern two-thirds of the US.

METHODS

Long-term (5year average) census tract-level PM2.5 and O3 concentrations were calculated using output from a downscaler model (2002-2006). The downscaler uses a linear regression with additive and multiplicative bias coefficients to relate ambient monitoring data with gridded output from the Community Multi-scale Air Quality (CMAQ) model. A local, spatial measure of RI was calculated at the tract level, and tracts were classified by urbanicity, RI, and geographic region. We examined differences in estimated pollutant exposures by RI, urbanicity, and demographic subgroup (e.g., race/ethnicity, education, socioeconomic status, age), and used linear models to estimate associations between RI and air pollution levels in urban, suburban, and rural tracts.

RESULTS

High RI tracts (≥80th percentile) had higher average PM2.5 levels in each category of urbanicity compared to low RI tracts (<20th percentile), with the exception of the rural West. Patterns in O3 levels by urbanicity and RI differed by region. Linear models indicated that PM2.5 concentrations were significantly and positively associated with RI. The largest association between PM2.5 and RI was observed in the rural Midwest, where a one quintile increase in RI was associated with a 0.90μg/m(3) (95% confidence interval: 0.83, 0.99μg/m(3)) increase in PM2.5 concentration. Associations between O3 and RI in the Northeast, Midwest and West were positive and highest in suburban and rural tracts, even after controlling for potential confounders such as percentage in poverty.

CONCLUSION

RI is associated with higher 5year estimated PM2.5 concentrations in urban, suburban, and rural census tracts, adding to evidence that segregation is broadly associated with disparate air pollution exposures. Disproportionate burdens to adverse exposures such as air pollution may be a pathway to racial/ethnic disparities in health.

Air pollution and mortality in São Paulo, Brazil: Effects of multiple pollutants and analysis of susceptible populations

Health impacts of air pollution may differ depending on sex, education, socioeconomic status (SES), location at time of death, and other factors. In São Paulo, Brazil, questions remain regarding roles of individual and community characteristics. We estimate susceptibility to air pollution based on individual characteristics, residential SES, and location at time of death (May 1996-December 2010). Exposures for particulate matter with an aerodynamic diameter ≤ 10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were estimated using ambient monitors. Time-stratified case-crossover analysis was used with individual-level health data. Increased risk of non-accidental, cardiovascular, and respiratory mortality were associated with all pollutants (P < 0.05), except O3 and cardiovascular mortality. For non-accidental mortality, effect estimates for those with > 11 years education were lower than estimates for those with 0 years education for NO2, SO2, and CO (1.66% (95% confidence interval: 0.23%, 3.08%); 1.51% (0.51%, 2.51%); and 2.82% (0.23%, 5.35%), respectively). PM10 cardiovascular mortality effects were (3.74% (0.044%, 7.30%)) lower for the high education group (> 11 years) compared with the no education group. Positive, significant associations between pollutants and mortality were observed for in-hospital deaths, but evidence of differences in air pollution-related mortality risk by location at time of death was not strong.

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.

Air Quality in Lanzhou, a Major Industrial City in China: Characteristics of Air Pollution and Review of Existing Evidence from Air Pollution and Health Studies

Air pollution contributes substantially to global health burdens; however, less is known about pollution patterns in China and whether they differ from those elsewhere. We evaluated temporal and spatial heterogeneity of air pollution in Lanzhou, an urban Chinese city (April 2009-December 2012), and conducted a systematic review of literature on air pollution and health in Lanzhou. Average levels were 141.5, 42.3, and 47.2 µg/m³ for particulate matter with an aerodynamic diameter ≤10 µm (PM₁₀), NO₂, and SO₂, respectively. Findings suggest some seasonality, particularly for SO₂, with higher concentrations during colder months relative to warmer months, although a longer time frame of data is needed to evaluate seasonality fully. Correlation coefficients generally declined with distance between monitors, while coefficients of divergence increased with distance. However, these trends were not statistically significant. PM₁₀ levels exceeded Chinese and other health-based standards and guidelines. The review identified 13 studies on outdoor air pollution and health. Although limited, the studies indicate that air pollution is associated with increased risk of health outcomes in Lanzhou. These studies and the high air pollution levels suggest potentially serious health consequences. Findings can provide guidance to future epidemiological studies, monitor placement programs, and air quality policies.

Comparison of exposure estimation methods for air pollutants: ambient monitoring data and regional air quality simulation

Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM(2.5)) and ozone (O(3)) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM(2.5) and O(3), respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O(3) (annual normalized mean bias=4.30%), while modeled PM(2.5) had an annual normalized mean bias of -2.09%, although bias varied seasonally, from 32% in November to -27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors.

Spatial heterogeneity of PM10 and O3 in São Paulo, Brazil, and implications for human health studies

Developing exposure estimates is a challenging aspect of investigating the health effects of air pollution. Pollutant levels recorded at centrally located ambient air quality monitors in a community are commonly used as proxies for population exposures. However, if ample intraurban spatial variation in pollutants exists, city-wide averages of concentrations may introduce exposure misclassification. We assessed spatial heterogeneity of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) and ozone (O3) and evaluated implications for epidemiological studies in São Paulo, Brazil, using daily (24-hr) and daytime (12-hr) averages and 1-hr daily maximums of pollutant levels recorded at the regulatory monitoring network. Monitor locations were also analyzed with respect to a socioeconomic status index developed by the municipal government. Hourly PM10 and O3 data for the Sāo Paulo Municipality and Metropolitan Region (1999-2006) were used to evaluate heterogeneity by comparing distance between monitors with pollutants' correlations and coefficients of divergence (CODs). Both pollutants showed high correlations across monitoring sites (median = 0.8 for daily averages). CODs across sites averaged 0.20. Distance was a good predictor of CODs for PM10 (p < 0.01) but not O3, whereas distance was a good predictor of correlations for O3 (p < 0.01) but not PM10. High COD values and low temporal correlation indicate a spatially heterogeneous distribution of PM10. Ozone levels were highly correlated (r > or = 0.75), but high CODs suggest that averaging over O3 levels may obscure important spatial variations. Of municipal districts in the highest of five socioeconomic groups, 40% have > or = 1 monitor, whereas districts in the lowest two groups, representing half the population, have no monitors. Results suggest that there is a potential for exposure misclassification based on the available monitoring network and that spatial heterogeneity depends on pollutant metric (e.g., daily average vs. daily 1-hr maximum). A denser monitoring network or alternative exposure methods may be needed for epidemiological research. Findings demonstrate the importance of considering spatial heterogeneity and differential exposure misclassification by subpopulation.

Platelet-derived growth factor in idiopathic pulmonary fibrosis

Fibrosis is a complex process involving an inflammatory reaction, fibroblast proliferation, and abnormal accumulation of interstitial collagens. Mononuclear cells are usually present in lung fibrosis. Activated monocytes and macrophages in culture have been shown to produce several growth factors including platelet-derived growth factor (PDGF). PDGF is a potent mitogen and chemoattractant for fibroblasts and smooth muscle cells and a stimulator of collagen synthesis. We have studied the expression of c-sis/PDGF-2 mRNA in lung tissues derived from five patients with idiopathic pulmonary fibrosis (IPF) and from four control individuals without IPF. Northern blot analysis of specimens obtained from four patients with IPF revealed the expression of the c-sis/PDGF-2 protooncogene. A control lung tissue without IPF did not express the c-sis protooncogene. In situ hybridization extended these studies demonstrating the expression of the c-sis mRNA in the five specimens with IPF but not in the four control specimens without IPF. The expression of c-sis mRNA was localized primarily in the epithelial cells. Invading alveolar macrophages also expressed c-sis mRNA. The expression of c-sis mRNA was accompanied by the expression of PDGF-like proteins in lung specimens with IPF but not in control lung specimens. These findings demonstrate the in vivo expression of the c-sis/PDGF-2 protooncogene and the production of PDGF-like proteins in the epithelial cells and macrophages of the fibrotic tissue. This localized and sustained production of PDGF-like mitogen may constitute an important contributing factor in the abnormal fibroblast proliferation and collagen production, events associated with pulmonary fibrosis.