Environmental Health Perspectives最新文献

Background: Extreme heat risk assessments often rely on epidemiologic studies that used the nearest available outdoor airport temperatures (OATs) rather than individually-experienced temperatures (IETs) and frequently lack key individual-level determinants of exposure, including occupation, housing, and air conditioning. This hampers efforts to characterize heat burden inequities and guide interventions for vulnerable populations.

Objectives: We developed an approach to estimate individual and subgroup-specific health impacts from modeled IETs before and during extreme heat events for three U.S. cities: Atlanta, Georgia (hot-humid), Detroit, Michigan (temperate), and Phoenix, Arizona (hot-dry).

Methods: IET profiles were estimated using modeled parcel-linked population microdata, housing-specific indoor temperatures from building energy models, ambient temperatures from urban-scale climate models, and time activity patterns from surveys. We linked each IET profile to daily OATs, then fit mixed-effects regressions to predict "equivalent" OATs (eOATs), based on IET, housing, and demographics. We assigned risk ratios (RRs) from existing literature on all-cause mortality, all-cause emergency department (ED) visits, and preterm births to each person-day's eOAT and estimated 5-day-extreme-heat absolute risks (ARs) by age-race-income-occupation subgroup.

Results: The eOATs, RRs, and ARs differed between people due to variability in IETs and baseline health outcome incidence rates. All-cause mortality RRs ranges were 1.00-1.16 (Atlanta), 1.01-7.08 (Detroit), and 1.00-6.38 (Phoenix). All-cause-mortality ARs ranged 0.01-32 (Atlanta), 0.01-1,100 (Detroit), and 0.01-950 (Phoenix) per 100,000 persons. ED visit ARs ranges were 0.2-270 (Atlanta) and 0.04-6,200 (Phoenix) per 100,000 persons. Heat mortality ARs were higher among older adults and, only in Detroit, in young, Black, outdoor workers (median = 6.6 per 100,000) compared to young, non-Black, higher-income, indoor workers (median = 0.3 per 100,000).

Discussion: When IETs can be estimated or directly measured, person-specific eOATs can be used to estimate the subgroup-specific heat-health burdens that would be experienced without adaptive behaviors. This approach could be adapted for other contexts to inform climate preparedness and justice policies. https://doi.org/10.1289/EHP15223.

Background: The relationship between prenatal exposure to low-level air pollution and child autism spectrum disorder (ASD) is unclear.

Objective: To examine associations of prenatal air pollution exposure with autism.

Methods: We analyzed data from 8,035 mother-child pairs from 44 United States cohorts in the Environmental influences on Child Health Outcomes (ECHO) Cohort. Fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and 8-hour-max ozone (O₃) levels were estimated at residential addresses during pregnancy. Parents rated children's autism-related traits using the Social Responsiveness Scale (SRS) (mean age 9.4 years, SD=3.6) and reported physician-diagnosed ASD. We examined associations of the three air pollutants with SRS scores (10^th, 50^th, and 90^th quantiles) using quantile regression and with ASD diagnosis using logistic regression. Models were run within census divisions, and coefficients were pooled in a meta-analysis.

Results: Average (SD) pregnancy exposures were 9.3 µg/m3 (2.7) for PM_2.5, 21.8 ppb (8.8) for NO₂, and 40.3 ppb (5.5) for O₃, with variations across census divisions. The median SRS T-score was 46 (IQR=41 to 52), and 444 children (5.5%) had an ASD diagnosis. Higher PM_2.5 was associated with higher SRS scores at the 10^th quantile (β=0.74, 95% CI: 0.09, 1.40) but not at the median or highest quantile. The association between PM_2.5 and ASD diagnosis was highly heterogeneous, with associations present in the South Central, Mountain, and Pacific census divisions. Heterogeneity was also high in the association between NO₂ and SRS at the median and only in the mid-Atlantic, West North Central, and South Atlantic census divisions. Higher O₃ was associated with higher SRS scores at the median (β per IQR increment=0.83, 95% CI: 0.05, 1.61) and highest quantile (β=2.19, 95% CI: 0.06, 4.32) in the meta-analysis. Higher O₃ also was associated with ASD.

Discussion: Associations with ASD outcomes were present even at low levels of air pollutants. https://doi.org/10.1289/EHP16675.

Background: Antimicrobial use in food-animal production selects for antimicrobial-resistant Escherichia coli (E. coli) that can be transmitted to humans via contaminated meat products. California Senate Bill 27 (SB27), which took effect on January 1, 2018, restricts the use of medically important antimicrobials in California food-animal production. Over time, SB27 could reduce the prevalence of antimicrobial-resistant E. coli on meat produced in California.

Objectives: We aimed to assess whether the implementation of SB27 was associated with significant decreases in resistance to medically important antimicrobials among E. coli strains contaminating raw chicken produced in California.

Methods: We purchased raw chicken products in Southern California, including those produced in and outside of California, from 2017 to 2021 and cultured them for E. coli. Susceptibility to 19 antimicrobials was determined using the disk diffusion method. Changes in antimicrobial susceptibility over the course of the study were evaluated using the Mann-Kendall test.

Results: We observed significant decreases in resistance to multiple classes of antimicrobials in E. coli isolated from retail chicken meat from 2017 to 2021. Resistance to penicillins had a relative decrease of 14-18% annually in E. coli from chicken raised in California but not from chicken raised outside California, potentially indicating that SB27 was effective. Resistance to multiple other classes of antimicrobials saw an absolute decrease of up to 8% in chicken produced both inside and outside California.

Discussion: Our findings suggest that the downward trends in antimicrobial resistance among E. coli populations from California-produced chicken products reflect national trends. It is possible that the California SB27 legislation helped motivate industry-wide decreases in antimicrobial use among broiler chicken producers. Alternatively, the changes observed in California may have been driven by industry-wide trends independent of SB27. The lack of publicly available data regarding actual antimicrobial use in California and non-California broiler chicken production limits our ability to make stronger conclusions about our observations. https://doi.org/10.1289/EHP16115.

Background: Environmental epidemiology studies increasingly integrate "big" geospatial and health datasets to examine associations between environmental factors and health outcomes. Using such datasets - and linking between them - presents a number of complexities with regard to study design and analytic approaches. These complexities are often magnified with the integration of additional contextual data representing other neighborhood characteristics, including socioeconomic factors. Guidance regarding the design of environmental health studies that leverage "big" geospatial and health outcome data is limited and fragmented.

Objective: Drawing on methodological literature and case studies, this commentary outlines common challenges related to geospatial and health data linkages, posing a series of guiding questions and considerations for investigators conducting environmental health studies, particularly analyses with an etiological focus.

Discussion: Recommendations include: 1) using a target trial approach to guide causal analysis, 2) aligning measures with hypothesized causal mechanisms, 3) exploring opportunities to "groundtruth" and validate data, and 4) prioritizing interdisciplinary science. The goal of the commentary is to consolidate insights from multiple disciplines - including exposure science, epidemiology, and sociology - to provide a foundation for etiologic research focused on advancing environmental health for all populations. https://doi.org/10.1289/EHP15756.

Background: While numerous studies have examined associations between prenatal air pollution exposure and fetal growth measures, investigations assessing longitudinal growth trajectories across multiple time points during mid-to-late pregnancy remain limited.

Objectives: The aim of this study is to explore the effects of prenatal exposure to air pollution during pregnancy on fetal growth trajectories.

Methods: From a prospective birth cohort in Wuhan, China recruited from 2013 to 2016, we included a total of 4283 eligible pregnant women. At 16, 24, 31, and 38 weeks of gestation, we collected ultrasound measurements, including biparietal diameter (BPD), abdominal circumference (AC), femur length (FL), and estimated fetal weight (EFW). Exposure to air pollution during pregnancy was estimated for the participants' residential addresses using a spatial interpolation method. Associations between air pollutants and fetal growth parameters across four exposure windows were examined using multiple informant models. A group-based trajectory modelling (GBTM) combined with multinomial logistic regression model were used to explore the effect of air pollution exposure on fetal growth trajectories.

Results: Four trajectory groups for AC, FL, and EFW, and three trajectory groups for BPD were selected based on GBTM. Compared with the reference trajectory group, exposure to higher PM_2.5 during weeks 1-16 was significantly associated with lower odds of "fast growth group" for AC(OR=0.68, 95% CI: 0.55, 0.84) and EFW(OR=0.71, 95% CI: 0.56, 0.91). Exposures to PM_2.5, PM₁₀, NO₂, SO₂, and CO during 1-16 weeks were negatively associated with AC, FL, and EFW at 16 weeks, as well as BPD, FL, and EFW at 24 weeks. While similar negative associations were observed between air pollution exposure during 25-38 weeks and AC and EFW at 38 weeks.

Discussion: Our study provided evidence of negative associations between air pollution exposure during 1-16 weeks gestation and fast growth trajectory group. In addition, we observed distinct lagged associations between air pollution and fetal growth, with early-pregnancy exposure negatively related to early and mid-gestational growth, and mid-to-late pregnancy exposure negatively related to growth in the late window. These results underscore the importance of identifying critical windows of susceptibility during pregnancy and support early intervention strategies to mitigate adverse fetal developmental outcomes. https://doi.org/10.1289/EHP15204.

Background: Long-term exposure to arsenic (As) can cause many health effects and As metabolism is key in the detoxification and elimination of As. We hypothesize that hepatic steatosis might affect As metabolism efficiency. We evaluated the association of As exposure and As metabolism biomarkers with hepatic steatosis.

Methods: In this cross-sectional analysis, we analyzed data from 3,577 participants in the Multi-Ethnic Study of Atherosclerosis (MESA), an ethnically diverse US adult population, with urinary metals and liver CT scan data available. We measured total As and As species in urine, and summarized As methylation biomarkers as inorganic (iAs%), monomethylarsonic acid (MMA%), and dimethylarsinic acid (DMA%). The ratio of liver-to-spleen (L/S) Hounsfield units (HU) < 1.0 and liver attenuation < 40 HU were used to assess the presence and severity of liver fat content. We used logistic regression to estimate the odds ratio (OR) (95%CI) of steatosis per higher interquartile range (IQR) of log-transformed total urinary As levels (ΣAs, μg/L), and per 5% higher in log-transformed As species (iAs%, MMA%, DMA%).

Results: The adjusted ORs (95%CI) for L/S < 1.0 were 1.09 (0.91, 1.30) per higher IQR of ΣAs, and 0.80 (0.68, 0.95), 0.69 (0.61, 0.77), and 1.24 (1.15, 1.34) per 5% higher iAs%, MMA%, and DMA%, respectively. The corresponding ORs (95% CI) for HU < 40 were 0.99 (0.75, 1.30) per higher IQR of increase ΣAs, and 0.70 (0.50, 0.91), 0.65 (0.55, 0.78), and 1.31 (1.16, 1.48) per 5% higher iAs%, MMA%, and DMA%, respectively. The associations were consistent by self-reported race/ethnicity and sex.

Conclusions: Arsenic methylation capacity, but not exposure, was associated with the prevalence of hepatic steatosis. Studies are needed to examine the longitudinal association between the progression of hepatic steatosis with As metabolism biomarkers and As-related disease. https://doi.org/10.1289/EHP16728.

Introduction: Disparities in exposure to and harm associated with pesticides are established. However, high resolution spatial data on exposure to pesticides are lacking.

Purpose: To describe the development of a pesticide metric for Washington State and to evaluate the associations between pesticide exposure and sociodemographic characteristics of census tracts.

Methods: We used the US cropland dataset to quantify the location and size of agricultural land. These data were overlayed with state- and county-level estimated annual agricultural pesticide use to estimate pesticide exposure at the census tract level. Sociodemographic characteristics of census tracts were from the US Centers for Disease Control and Prevention's Social Vulnerability Index (SVI). Generalized additive models evaluated the associations between pesticide exposure and each of the SVI variables.

Results: The median exposure to pesticides was 1.5 lbs/sq mi. Significant associations were observed between exposure to pesticides and higher percentage of population below poverty, populations unemployed, populations 65 and older, non-Hispanic white populations, those with limited English language proficiency, mobile homes, and group quarters.

Conclusions: The results inform public health and policy efforts to identify areas and populations that are most vulnerable to pesticide exposure and improve the health and wellbeing of farmworkers and populations residing near agricultural areas. https://doi.org/10.1289/EHP15686.

Background: The evidence linking long-term exposure to air pollution and development of chronic obstructive pulmonary disease (COPD) is still controversial. Furthermore, most studies have investigated associations with particulate matter (PM) and nitrogen dioxide (NO₂), disregarding their emission source and other relevant air pollutants, such as ultrafine particles (UFP) and elemental carbon (EC).

Objectives: This study aimed to assess associations between long-term residential exposure to PM_2.5, NO₂, UFP, and EC and risk of COPD, distinguishing the effects of air pollution from local traffic and other sources.

Methods: We pooled data from two large Danish cohorts - the Diet, Cancer, and Health cohort and the Danish National Health Survey. For all participants (N = 159,769), we estimated long-term air pollution exposure to total, local traffic, and other contributions, based on complete address histories. We used Cox proportional hazards models to estimate associations between 10-year time-weighted averaged air pollution and incident COPD, adjusting for demographic, socioeconomic, and lifestyle factors, including smoking.We evaluated possible modification of these associations by sex, smoking status, and previous asthma diagnosis.

Results: Long-term exposures to PM_2.5, NO₂, UFP, and EC were associated with higher risk of COPD. The highest hazard ratio (HR) per interquartile range of total contributions was observed for PM_2.5 (HR: 1.11 [95% confidence interval: 1.05, 1.17]), followed by NO₂ (1.08 [1.04, 1.13]), UFP (1.05 [0.99, 1.11]), and EC (1.02 [1.00, 1.05]), after full adjustment. PM_2.5 from other sources than local traffic was more strongly associated with COPD than PM_2.5 from local traffic, while for UFP and EC, the contributions from local traffic seemed most harmful. Effect modification analyses showed stronger associations among women, never smokers, and those with an asthma diagnosis.

Discussion: Our findings suggest that air pollution from local traffic and other sources contribute to COPD risk, with variations depending on the pollutant type. Further research is needed to validate these findings across different populations and geographical settings. https://doi.org/10.1289/EHP16554.

Background: Temperature-related risks on non-accidental morbidity or mortality have been well documented. However, limited studies have investigated the injury morbidity risk and burden attributed to ambient temperature.

Objective: The current study aimed to assess the injury morbidity risk and burden attributed to ambient temperature in China.

Methods: A time-stratified case-crossover study was conducted in 31 provincial-level administrations across mainland China, and 11.5 million injury-related emergency department visits recorded in National Injury Surveillance System (NISS) during 2006-2021 were included in the study. An injury case refers to a patient who takes the first visit to the outpatient or emergency department in NISS due to an injury. Daily meteorological data were collected from the fifth generation of European ReAnalysis-Land. A two-stage approach, including a conditional logistic regression and a multilevel meta-analysis, was applied to estimate the temperature-injury association, which were then applied to assess the morbidity burden attributable to temperature.

Results: We observed that injury risk increased 1.2% (95%CI: 1.0%-1.4%) for a 1 °C increase in daily mean temperature with higher risk for males, children aged 0-4, and residents in tropical and subtropical zone. We also found that animal injury, violence and attack, and injury in agricultural area were more susceptible to temperature. Compared to the 2020s, we projected 5.7 times increase of injury cases and 10.4 times of attributable fraction due to temperature change driven by global warming in the 2090s under SSP5-8.5 scenario in China. Our findings might be informative for injury prevention in the context of climate change in China.

Conclusion: Our findings identify susceptible populations, regions and mechanism-specific injuries when exposure to ambient temperature, which could be informative for injury prevention in the context of climate change in China. https://doi.org/10.1289/EHP16878.

Background: Persistent organic pollutants (POPs) are toxic chemicals that bioaccumulate and were used in pesticides and industrial products/processes. POP-exposed occupations and environmental exposure to POPs have been associated with amyotrophic lateral sclerosis (ALS), but no study has evaluated the association with ALS when measuring POPs in samples collected before ALS onset.

Objectives: This study examined the relationship between pre-disease POP exposure and ALS risk.

Methods: We conducted a nested case-control study pooling three Finnish cohorts (n=56,862). During a median follow-up of 27 years, 97 incident ALS cases were identified (mean age at ALS=68). Within each cohort, two controls per case were selected by individual matching for age, sex, municipality, and serum freeze-thaw cycles. Thirteen polychlorinated biphenyls (PCB) and nine organochlorine pesticides (OCP) were determined in serum samples collected at baseline and stored at -20C. We considered these POPs both in groups (similar congener, isomer, metabolite groups) and separately. Odds ratios and 95% confidence intervals were estimated using a conditional logistic model in a two-stage approach, further adjusting for smoking, occupation, marital status, BMI, and serum cholesterol level in primary models.

Results: In the main model hexachlorobenzene (HCB) showed a positive association with ALS occurrence. In contrast, Σnon-dioxin-like (NDL) PCB and ΣDDT were significantly inversely associated with ALS incidence. Most other POP groups were non-significantly inversely associated with ALS risk. In co-pollutant models, the only notable changes were that Σdioxin-like PCB and ΣHCH showed large non-significant, elevated, ORs, suggesting some negative co-pollutant confounding. There were some suggestions of stronger findings when limiting to some subgroups.

Discussion: We found little evidence that POPs were associated with ALS, but we identified a suggestive positive association with HCB and HCH. ΣNDL PCB and ΣDDT were inversely associated with ALS. This could suggest protective mechanisms or uncontrolled confounding by neuroprotective factors (e.g. fish oils). https://doi.org/10.1289/EHP16539.