Long term trends in source apportioned particle number concentrations in Rochester NY.

During the past two decades, efforts have been made to further reduce particulate air pollution across New York State through various Federal and State policy implementations. Air quality has also been affected by economic drivers like the 2007-2009 recession and changing costs for different approaches to electricity generation. Prior work has focused on particulate matter with aerodynamic diameter ≤2.5 µm. However, there is also interest in the effects of ultrafine particles on health and the environment and analyses of changes in particle number concentrations (PNCs) are also of interest to assess the impacts of changing emissions. Particle number size distributions have been measured since 2005. Prior apportionments have been limited to seasonal analyses over a limited number of years because of software limitations. Thus, it has not been possible to perform trend analyses on the source-specific PNCs. Recent development have now permitted the analysis of larger data sets using Positive Matrix Factorization (PMF) including its diagnostics. Thus, this study separated and analyzed the hourly averaged size distributions from 2005 to 2019 into two data sets; October to March and April to September. Six factors were resolved for both data sets with sources identified as nucleation, traffic 1, traffic 2, fresh secondary inorganic aerosol (SIA), aged SIA, and O3-rich aerosol. The resulting source-specific PNCs were combined to provide continuous data sets and analyzed for trends. The trends were then examined with respect to the implementation of regulations and the timing of economic drivers. Nucleation was strongly reduced by the requirement of ultralow (<15 ppm) sulfur on-road diesel fuel in 2006. Secondary inorganic particles and O3-rich PNCs show strong summer peaks. Aged SIA was constant and then declined substantially in 2015 but rose in 2019. Traffic 1 and 2 have steadily declined bur rose in 2019.

Primary Treatment Modification and Treatment Tolerability Among Older Chemotherapy Recipients With Advanced Cancer.

Importance: Older adults with advanced cancer are less likely to tolerate treatment with cytotoxic chemotherapy compared with younger patients due to their aging-related conditions. Hence, oncologists sometimes opt to employ primary treatment modifications (deviation from standard of care) during the first cycle of chemotherapy. Objective: To examine the association between primary treatment modification and treatment tolerability in older adults with advanced cancer who were starting new palliative chemotherapy regimens. Design, Setting, and Participants: This cohort study was a secondary analysis of the GAP70+ (Geriatric Assessment Intervention for Reducing Toxicity in Older Patients with Advanced Cancer) trial, which was conducted between July 2014 and March 2019. The GAP70+ trial included patients aged 70 years or older who had advanced (ie, incurable) cancer, had 1 or more geriatric assessment domain impairments, and planned to start a new palliative chemotherapy regimen. Data analysis was conducted in November 2022. Exposures: Receipt of standard-of-care chemotherapy regimens vs primary treatment modification defined as any change from National Comprehensive Cancer Network guidelines or published clinical trials (eg, primary dose reduction, schedule change). Main Outcomes and Measures: Tolerability outcomes were assessed within 3 months of treatment. These outcomes included the following: (1) any grade 3 to 5 toxic effect, according to the National Cancer Institute Common Terminology Criteria for Adverse Events; (2) patient-reported functional decline, defined as the development of worse dependency in activities of daily living using scale scores; and (3) a composite adverse outcome (an end point that combined toxic effects, functional decline, and 6-month overall survival). Multivariable cluster-weighted generalized estimating equation models examined the association between primary treatment modification and outcomes adjusting for covariates. Results: This study included 609 patients with a mean (SD) age of 77.2 (5.2) years; more than half (333 [54.7%]) were men. Race and ethnicity was available for 607 patients: 39 (6.4%) were Black, 539 (88.5%) were non-Hispanic White, and 29 (4.8%) were of other race or ethnicity. Nearly half (281 [46.1%]) received a primary modified treatment regimen. The most common cancer types were gastrointestinal cancer (228 [37.4%]) and lung cancer (174 [28.6%]). In multivariable analysis, primary treatment modification was associated with a reduced risk of grade 3 to 5 toxic effects (relative risk [RR], 0.85 [95% CI, 0.77-0.94]) and functional decline (RR, 0.80 [95% CI, 0.67-0.95]). Patients who received primary treatment modification had 32.0% lower odds of having a worse composite adverse outcome (odds ratio, 0.68 [95% CI, 0.48-0.97]). Conclusions and Relevance: In this cohort study, primary treatment modification was associated with improved tolerability of chemotherapeutic regimens among older adults with advanced cancer and aging-related conditions. These findings may help optimize cancer treatment dosing in older adults with advanced cancer and aging-related conditions.

Racial and Ethnic Disparities in Phthalate Exposure and Preterm Birth: A Pooled Study of Sixteen U.S. Cohorts.

BACKGROUND: Phthalate exposures are ubiquitous during pregnancy and may contribute to racial and ethnic disparities in preterm birth. OBJECTIVES: We investigated race and ethnicity in the relationship between biomarkers of phthalate exposure and preterm birth by examining: a) how hypothetical reductions in racial and ethnic disparities in phthalate metabolites might reduce the probability of preterm birth; and b) exposure-response models stratified by race and ethnicity. METHODS: We pooled individual-level data on 6,045 pregnancies from 16 U.S. cohorts. We investigated covariate-adjusted differences in nine urinary phthalate metabolite concentrations by race and ethnicity [non-Hispanic White (White, 43%), non-Hispanic Black (Black, 13%), Hispanic/Latina (38%), and Asian/Pacific Islander (3%)]. Using g-computation, we estimated changes in the probability of preterm birth under hypothetical interventions to eliminate disparities in levels of urinary phthalate metabolites by proportionally lowering average concentrations in Black and Hispanic/Latina participants to be approximately equal to the averages in White participants. We also used race and ethnicity-stratified logistic regression to characterize associations between phthalate metabolites and preterm birth. RESULTS: In comparison with concentrations among White participants, adjusted mean phthalate metabolite concentrations were consistently higher among Black and Hispanic/Latina participants by 23%-148% and 4%-94%, respectively. Asian/Pacific Islander participants had metabolite levels that were similar to those of White participants. Hypothetical interventions to reduce disparities in metabolite mixtures were associated with lower probabilities of preterm birth for Black [13% relative reduction; 95% confidence interval (CI): -34%, 8.6%] and Hispanic/Latina (9% relative reduction; 95% CI: -19%, 0.8%) participants. Odds ratios for preterm birth in association with phthalate metabolites demonstrated heterogeneity by race and ethnicity for two individual metabolites (mono-n-butyl and monoisobutyl phthalate), with positive associations that were larger in magnitude observed among Black or Hispanic/Latina participants. CONCLUSIONS: Phthalate metabolite concentrations differed substantially by race and ethnicity. Our results show hypothetical interventions to reduce population-level racial and ethnic disparities in biomarkers of phthalate exposure could potentially reduce the probability of preterm birth. https://doi.org/10.1289/EHP12831.

Generating High Spatial Resolution Exposure Estimates from Sparse Regulatory Monitoring Data.

Random Forest algorithms have extensively been used to estimate ambient air pollutant concentrations. However, the accuracy of model-predicted estimates can suffer from extrapolation problems associated with limited measurement data to train the machine learning algorithms. In this study, we developed and evaluated two approaches, incorporating low-cost sensor data, that enhanced the extrapolating ability of random-forest models in areas with sparse monitoring data. Rochester, NY is the area of a pregnancy-cohort study. Daily PM2.5 concentrations from the NAMS/SLAMS sites were obtained and used as the response variable in the model, with satellite data, meteorological, and land-use variables included as predictors. To improve the base random-forest models, we used PM2.5 measurements from a pre-existing low-cost sensors network, and then conducted a two-step backward selection to gradually eliminate variables with potential emission heterogeneity from the base models. We then introduced the regression-enhanced random forest method into the model development. Finally, contemporaneous urinary 1-hydroxypyrene was used to evaluate the PM2.5 predictions generated from the two approaches. The two-step approach increased the average external validation R2 from 0.49 to 0.65, and decreased the RMSE from 3.56 µg/m3 to 2.96 µg/m3. For the regression-enhanced random forest models, the average R2 of the external validation was 0.54, and the RMSE was 3.40 µg/m3. We also observed significant and comparable relationships between urinary 1-hydroxypyrene levels and PM2.5 predictions from both improved models. This PM2.5 model estimation strategy could improve the extrapolating ability of random forest models in areas with sparse monitoring data.

Urinary 1-hydroxypyrene in pregnant women in a Northeastern U.S. city: socioeconomic disparity and contributions from air pollution sources.

BACKGROUND: Maternal exposure to polycyclic aromatic hydrocarbons (PAHs), ubiquitous constituents of air pollution, has been associated with adverse birth outcomes. Yet it remains unclear whether and how socioeconomic status (SES) affects gestational PAH exposure. OBJECTIVE: To examine whether there are socioeconomic disparities in PAHs exposure among pregnant women from Rochester, NY, and if so, to what extent disproportionate proximity to air pollution sources, measured by residential distance to transportation-related sources, contributed to the exposure disparity. METHODS: We measured 1-hydroxypyrene concentrations in 726 urine samples collected from 305 pregnant women up to three samples throughout pregnancy. Residential distances to transportation-related sources were calculated based on participants' home addresses. We used linear mixed-effects models with random intercepts of participants to examine associations between 1-hydroxypyrene, SES indicators, and distance to transportation-related sources. We used structural equation modelling to assess to what extent distance to transportation-related sources contributes to the socioeconomic disparity in 1-hydroxypyrene concentrations. RESULTS: Reduced household income and maternal education level were both significant SES predictors of 1-hydroxypyrene concentrations, after the adjustment for other maternal demographic characteristics. Each interquartile range (IQR) increases in residential proximity to the airport (from 14.3 to 6.0 km), the railroad yard (from 22.3 to 6.0 km), and annual average daily traffic within 300 m (from 3796 to 99,933 vehicles/year) were associated with 15.0% (95%CI: 7.0-22.2%), 15.4% (95%CI: 6.5-23.5%), and 13.6% (95%CI: 4.7-23.3%) increases in 1-hydroxypyrene concentrations, respectively. Proximity to these sources jointly explained 10% (95%CI: 1.6-18.4%) of the 1-hydroxypyrene concentration change associated with decreases in SES as a latent variable defined by both household income and education level. IMPACT STATEMENT: Our findings suggest that efforts to address disproportionate residential proximity to transportation-related sources may reduce the socioeconomic disparity in PAH exposure.

Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey.

INTRODUCTION: Evidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles. METHODS: This was a large population-based survey during 2019-2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise. RESULTS: A total of 82 345 residents were included in the final analyses. For each 1 µg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4-8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2-3 and those with 0-1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable. CONCLUSION: Long-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions.

Phenomenology of ultrafine particle concentrations and size distribution across urban Europe.

The 2017-2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of <10 nm PNC are needed for full evaluation of the health effects of this size fraction.

Long-term exposure to particulate matter and COPD mortality: Insights from causal inference methods based on a large population cohort in southern China.

BACKGROUND: Evidence of the association between long-term exposure to particulate matter (PM) and chronic obstructive pulmonary disease (COPD) mortality from large population-based cohort study is limited and often suffers from residual confounding issues with traditional statistical methods. We hereby assessed the casual relationship between long-term PM (PM2.5, PM10 and PM10-2.5) exposure and COPD mortality in a large cohort of Chinese adults using state-of-the-art causal inference approaches. METHODS: A total of 580,757 participants in southern China were enrolled in a prospective cohort study from 2009 to 2015 and followed up until December 2020. Exposures to PM at each residential address were obtained from the Long-term Gap-free High-resolution Air Pollutant Concentration dataset. Marginal structural Cox models were used to investigate the association between COPD mortality and annual average exposure levels of PM exposure. RESULTS: During an average follow-up of 8.0 years, 2250 COPD-related deaths occurred. Under a set of causal inference assumptions, the hazard ratio (HR) for COPD mortality was estimated to be 1.046 (95 % confidence interval: 1.034-1057), 1.037 (1.028-1.047), and 1.032 (1.006-1.058) for each 1-µg/m3 increase in annual average concentrations of PM2.5, PM10, and PM10-2.5 respectively. Additionally, the detrimental effects appeared to be more pronounced among the elderly (age ≥ 65) and inactive participants. The effect estimates of PM2.5, PM10, and PM10-2.5 tend to be greater among participants who were generally exposed to PM10 concentrations below 70 µg/m3 than that among the general population. CONCLUSION: Our results support causal links between long-term PM exposure and COPD mortality, highlighting the urgency for more effective strategies to reduce PM exposure, with particular attention on protecting potentially vulnerable groups.

Triggering of ST-elevation myocardial infarction by ultrafine particles in New York: Changes following Tier 3 vehicle introduction.

BACKGROUND: Previously, we found increased rates of ST-elevation myocardial infarction (STEMI) associated with increased ultrafine particle (UFP; <100 nm) concentrations in the previous few hours in Rochester, New York. Relative rates were higher after air quality policies and a recession reduced pollutant concentrations (2014-2016 versus 2005-2013), suggesting PM composition had changed and the same PM mass concentration had become more toxic. Tier 3 light duty vehicles, which should produce less primary organic aerosols and oxidizable gaseous compounds, likely making PM less toxic, were introduced in 2017. Thus, we hypothesized we would observe a lower relative STEMI rate in 2017-2019 than 2014-2016. METHODS: Using STEMI events treated at the University of Rochester Medical Center (2014-2019), UFP and other pollutants measured in Rochester, a case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increased UFP and other pollutants in the previous hours and days in the 2014-2016 and 2017-2019 periods. RESULTS: An increased rate of STEMI was associated with each 3111 particles/cm3 increase in UFP concentration in the previous hour in 2014-2016 (lag hour 0: OR = 1.22; 95% CI = 1.06, 1.39), but not in 2017-2019 (OR = 0.94; 95% CI = 0.80, 1.10). There were similar patterns for black carbon, UFP11-50nm, and UFP51-100nm. In contrast, increased rates of STEMI were associated with each 0.6 ppb increase in SO2 concentration in the previous 120 h in both periods (2014-2016: OR = 1.26, 95% CI = 1.03, 1.55; 2017-2019: OR = 1.21, 95% CI = 0.87, 1.68). CONCLUSIONS: Greater rates of STEMI were associated with short term increases in concentrations of UFP and other motor vehicle related pollutants before Tier 3 introduction (2014-2016), but not afterwards (2017-2019). This change may be due to changes in PM composition after Tier 3 introduction, as well as to increased exposure misclassification and greater underestimation of effects from 2017 to 2019.

Assessment of absolute risk of life-threatening cardiac events in long QT syndrome patients.

Background: Risk stratification in long QT syndrome (LQTS) patients is important for optimizing patient care and informing clinical decision making. We developed a risk prediction algorithm with prediction of 5-year absolute risk of the first life-threatening arrhythmic event [defined as aborted cardiac arrest, sudden cardiac death, or appropriate implantable cardioverter defibrillator (ICD) shock] in LQTS patients, accounting for individual risk factors and their changes over time. Methods: Rochester-based LQTS Registry included the phenotypic cohort consisting of 1,509 LQTS patients with a QTc ≥ 470 ms, and the genotypic cohort including 1,288 patients with single LQT1, LQT2, or LQT3 mutation. We developed two separate risk prediction models which included pre-specified time-dependent covariates of beta-blocker use, syncope (never, syncope while off beta blockers, and syncope while on beta blockers), and sex by age < and ≥13 years, baseline QTc, and genotype (for the genotypic cohort only). Follow-up started from enrollment in the registry and was censored at patients' 50s birthday, date of death due to reasons other than sudden cardiac death, or last contact, whichever occurred first. The predictive models were externally validated in an independent cohort of 1,481 LQTS patients from Pavia, Italy. Results: In Rochester dataset, there were 77 endpoints in the phenotypic cohort during a median follow-up of 9.0 years, and 47 endpoints in the genotypic cohort during a median follow-up of 9.8 years. The time-dependent extension of Harrell's generalized C-statistics for the phenotypic model and genotypic model were 0.784 (95% CI: 0.740-0.827) and 0.785 (95% CI: 0.721-0.849), respectively, in the Rochester cohort. The C-statistics obtained from external validation in the Pavia cohort were 0.700 (95% CI: 0.610-0.790) and 0.711 (95% CI: 0.631-0.792) for the two models, respectively. Based on the above models, an online risk calculator estimating a 5-year risk of life-threatening arrhythmic events was developed. Conclusion: This study developed two risk prediction algorithms for phenotype and genotype positive LQTS patients separately. The estimated 5-year absolute risk can be used to quantify a LQTS patient's risk of developing life-threatening arrhythmic events and thus assisting in clinical decision making regarding prophylactic ICD therapy.

Long-term trends of ultrafine and fine particle number concentrations in New York State: Apportioning between emissions and dispersion.

In the past several decades, a variety of efforts have been made in the United States to improve air quality, and ambient particulate matter (PM) concentrations have been used as a metric to evaluate the efficacy of environmental policies. However, ambient PM concentrations result from a combination of source emission rates and meteorological conditions, which also change over time. Dispersion normalization was recently developed to reduce the influence of atmospheric dispersion and proved an effective approach that enhanced diel/seasonal patterns and thus provides improved source apportionment results for speciated PM mass and particle number concentration (PNC) measurements. In this work, dispersion normalization was incorporated in long-term trend analysis of 11-500 nm PNCs derived from particle number size distributions (PNSDs) measured in Rochester, NY from 2005 to 2019. Before dispersion normalization, a consistent reduction was observed across the measured size range during 2005-2012, while after 2012, the decreasing trends slowed down for accumulation mode PNCs (100-500 nm) and reversed for ultrafine particles (UFPs, 11-100 nm). Through dispersion normalization, we showed that these changes were driven by both emission rates and dispersion. Thus, it is important for future studies to assess the effects of the changing meteorological conditions when evaluating policy effectiveness on controlling PM concentrations. Before and after dispersion normalization, an evident increase in nucleation mode particles was observed during 2015-2019. This increase was possibly enabled by a cleaner atmosphere and will pose new challenges for future source apportionment and accountability studies.

Inflammation, Attention, and Processing Speed in Patients With Breast Cancer Before and After Chemotherapy.

BACKGROUND: Inflammation may contribute to cognitive difficulties in patients with breast cancer. We tested 2 hypotheses: inflammation is elevated in patients with breast cancer vs noncancer control participants and inflammation in patients is associated with worse attention and processing speed over the course of chemotherapy. METHODS: Serum cytokines (interleukin [IL]-4, 6, 8, 10; tumor necrosis factor [TNF]-α) and soluble receptors [sTNFRI, II]) were measured in 519 females with breast cancer before and after chemotherapy and 338 females without cancer serving as control participants. Attention and processing speed were measured by Rapid Visual Processing (RVP), Backward Counting (BCT), and Trail Making-A (TMT-A) tests. Linear regression models examined patient vs control cytokines and receptor levels, adjusting for covariates. Linear regression models also examined relationships between patient cytokines and receptor levels and test performance, adjusting for age, body mass index, anxiety, depression, cognitive reserve, and chemotherapy duration. Statistical tests were 2-sided (α = .05). RESULTS: sTNFRI and sTNFRII increased over time in patients relative to controls, whereas IL-4, IL-6, and IL-10 decreased. Prechemotherapy, higher IL-8 associated with worse BCT (ß = 0.610, SE = 0.241, P = .01); higher IL-4 (ß = -1.098, SE = 0.516, P = .03) and IL-10 (ß = -0.835, SE = 0.414, P = .04) associated with better TMT-A. Postchemotherapy, higher IL-8 (ß = 0.841, SE = 0.260, P = .001), sTNFRI (ß = 6.638, SE = 2.208, P = .003), and sTNFRII (ß = 0.913, SE = 0.455, P = .045) associated with worse BCT; higher sTNFRII also associated with worse RVP (ß = -1.316, SE = 0.587, P = .03). At prechemotherapy, higher IL-4 predicted RVP improvement over time (ß = 0.820, SE = 0.336, P = .02); higher sTNFRI predicted worse BCT over time (ß = 5.566, SE = 2.367, P = .02). Longitudinally, increases in IL-4 associated with BCT improvement (ß = -0.564, SE = 0.253, P = .03). CONCLUSIONS: Generally, worse attention and processing speed were associated with higher inflammatory cytokines and receptors and lower anti-inflammatory cytokines in patients; future confirmatory studies are needed.

Maternal exposure to ambient PM2.5 and term birth weight: A systematic review and meta-analysis of effect estimates.

Effect estimates of prenatal exposure to ambient PM2.5 on change in grams (ß) of birth weight among term births (≥37 weeks of gestation; term birth weight, TBW) vary widely across studies. We present the first systematic review and meta-analysis of evidence regarding these associations. Sixty-two studies met the eligibility criteria for this review, and 31 studies were included in the meta-analysis. Random-effects meta-analysis was used to assess the quantitative relationships. Subgroup analyses were performed to gain insight into heterogeneity derived from exposure assessment methods (grouped by land use regression [LUR]-models, aerosol optical depth [AOD]-based models, interpolation/dispersion/Bayesian models, and data from monitoring stations), study regions, and concentrations of PM2.5 exposure. The overall pooled estimate involving 23,925,941 newborns showed that TBW was negatively associated with PM2.5 exposure (per 10 µg/m3 increment) during the entire pregnancy (ß = -16.54 g), but with high heterogeneity (I2 = 95.6%). The effect estimate in the LUR-models subgroup (ß = -16.77 g) was the closest to the overall estimate and with less heterogeneity (I2 = 18.3%) than in the other subgroups of AOD-based models (ß = -41.58 g; I2 = 95.6%), interpolation/dispersion models (ß = -10.78 g; I2 = 86.6%), and data from monitoring stations (ß = -11.53 g; I2 = 97.3%). Even PM2.5 exposure levels of lower than 10 µg/m3 (the WHO air quality guideline value) had adverse effects on TBW. The LUR-models subgroup was the only subgroup that obtained similar significant of negative associations during the three trimesters as the overall trimester-specific analyses. In conclusion, TBW was negatively associated with maternal PM2.5 exposures during the entire pregnancy and each trimester. More studies based on relatively standardized exposure assessment methods need to be conducted to further understand the precise susceptible exposure time windows and potential mechanisms.

Effectiveness of Implantable Cardioverter-Defibrillators to Reduce Mortality in Patients With Long QT Syndrome.

BACKGROUND: The effectiveness of implantable cardioverter-defibrillators (ICDs) on reducing mortality has not been well studied in patients with long QT syndrome (LQTS). OBJECTIVES: This study aimed to assess the survival benefits of ICDs in the overall LQTS population and in subgroups defined by ICD indications. METHODS: This study included 3,035 patients (597 with ICD) from the Rochester LQTS Registry with a QTc ≥470 milliseconds or confirmed LQTS mutation. Using multivariable Cox proportional hazards models, the risk of all-cause mortality, all-cause mortality before age 50 years, and sudden cardiac death (SCD) were estimated as functions of time-dependent ICD therapy. Indication subgroups examined included patients with: 1) nonfatal cardiac arrest; 2) syncope while on beta-blockers; and 3) a QTc ≥500 milliseconds and syncope while off beta-blockers. RESULTS: During the 118,837 person-years of follow-up, 389 patients died (137 before age 50 years, and 116 experienced SCD). In the entire population, patients with ICDs had a lower risk of death (HR: 0.54; 95% CI: 0.34-0.86), death before age 50 years (HR: 0.29; 95% CI: 0.14-0.61), and SCD (HR: 0.22; 95% CI: 0.09-0.55) than patients without ICDs did. Patients with ICDs also had a lower risk of mortality among the 3 indication subgroups (HR: 0.14; 95% CI: 0.06-0.34; HR: 0.27; 95% CI: 0.10-0.72; and HR: 0.42; 95% CI: 0.19-0.96, respectively). CONCLUSIONS: ICD therapy was associated with a lower risk of all-cause mortality, all-cause mortality before age 50 years, and SCD in the LQTS population, as wells as with a lower risk of all-cause mortality in indication subgroups. This study provides evidence supporting ICD implantation in patients with high-risk LQTS.

The effect of air pollution on the transcriptomics of the immune response to respiratory infection.

Combustion related particulate matter air pollution (PM) is associated with an increased risk of respiratory infections in adults. The exact mechanism underlying this association has not been determined. We hypothesized that increased concentrations of combustion related PM would result in dysregulation of the innate immune system. This epidemiological study includes 111 adult patients hospitalized with respiratory infections who underwent transcriptional analysis of their peripheral blood. We examined the association between gene expression at the time of hospitalization and ambient measurements of particulate air pollutants in the 28 days prior to hospitalization. For each pollutant and time lag, gene-specific linear models adjusting for infection type were fit using LIMMA (Linear Models For Microarray Data), and pathway/gene set analyses were performed using the CAMERA (Correlation Adjusted Mean Rank) program. Comparing patients with viral and/or bacterial infection, the expression patterns associated with air pollution exposure differed. Adjusting for the type of infection, increased concentrations of Delta-C (a marker of biomass smoke) and other PM were associated with upregulation of iron homeostasis and protein folding. Increased concentrations of black carbon (BC) were associated with upregulation of viral related gene pathways and downregulation of pathways related to antigen presentation. The pollutant/pathway associations differed by lag time and by type of infection. This study suggests that the effect of air pollution on the pathogenesis of respiratory infection may be pollutant, timing, and infection specific.

Prehospital time intervals and management of ischemic stroke patients.

OBJECTIVE: Quantify prehospital time intervals, describe prehospital stroke management, and estimate potential time saved if certain procedures were performed en route to the emergency department (ED). METHODS: Acute ischemic stroke patients who arrived via emergency medical services (EMS) between 2012 and 2016 were identified. We determined the following prehospital time intervals: chute, response, on-scene, transport, and total prehospital times. Proportions of patients receiving the following were determined: Cincinnati Prehospital Stroke Scale (CPSS) assessment, prenotification, glucose assessment, vascular access, and 12-lead electrocardiography (ECG). For glucose assessment, ECG acquisition, and vascular access, the location (on-scene vs. en route) in which they were performed was described. Difference in on-scene times among patients who had these three interventions performed on-scene vs. en route was assessed. RESULTS: Data from 870 patients were analyzed. Median total prehospital time was 39 min and comprised the following: chute time: 1 min; response time: 9 min; on-scene time: 15 min; and transport time: 14 min. CPSS was assessed in 64.7% of patients and prenotification was provided for 52.0% of patients. Glucose assessment, vascular access initiation, and ECG acquisition was performed on 84.1%, 72.6%, and 67.2% of patients, respectively. 59.0% of glucose assessments, 51.2% of vascular access initiations, and 49.8% of ECGs were performed on-scene. On-scene time was 9 min shorter among patients who had glucose assessments, vascular access initiations, and ECG acquisitions all performed en route vs. on-scene. CONCLUSIONS: On-scene time comprised 38.5% of total prehospital time. Limiting on-scene performance of glucose assessments, vascular access initiations, and ECG acquisitions may decrease prehospital time.

Sex-Specific Platelet Activation Through Protease-Activated Receptors Reverses in Myocardial Infarction.

OBJECTIVE: The platelet phenotype in certain patients and clinical contexts may differ from healthy conditions. We evaluated platelet activation through specific receptors in healthy men and women, comparing this to patients presenting with ST-segment-elevation myocardial infarction and non-ST-segment-elevation myocardial infarction. Approach and Results: We identified independent predictors of platelet activation through certain receptors and a murine MI model further explored these findings. Platelets from healthy women and female mice are more reactive through PARs (protease-activated receptors) compared with platelets from men and male mice. Multivariate regression analyses revealed male sex and non-ST-segment-elevation myocardial infarction as independent predictors of enhanced PAR1 activation in human platelets. Platelet PAR1 signaling decreased in women and increased in men during MI which was the opposite of what was observed during healthy conditions. Similarly, in mice, thrombin-mediated platelet activation was greater in healthy females compared with males, and lesser in females compared with males at the time of MI. CONCLUSIONS: Sex-specific signaling in platelets seems to be a cross-species phenomenon. The divergent platelet phenotype in males and females at the time of MI suggests a sex-specific antiplatelet drug regimen should be prospectively evaluated.

Neurodegenerative hospital admissions and long-term exposure to ambient fine particle air pollution.

PURPOSE: Long-term exposure to ambient fine particle (PM2.5) concentrations has been associated with an increased rate or risk of neurodegenerative conditions, but individual PM sources have not been previously examined in relation to neurodegenerative diseases. METHODS: Using the Statewide Planning and Research Cooperative System database, we studied 63,287 hospital admissions with a primary diagnosis of either Alzheimer's disease, dementia, or Parkinson's disease for New York State residents living within 15 miles from six PM2.5 monitoring sites. In addition to PM2.5 concentrations, we studied seven specific PM2.5 sources: secondary sulfate, secondary nitrate, biomass burning, diesel, spark-ignition emissions, pyrolyzed organic rich, and road dust. We estimated the rate of neurodegenerative hospital admissions associated with increased concentration of PM2.5 and individual PM2.5 sources average concentrations in the previous 0-29, 0-179, and 0-364 days. RESULTS: Increases in ambient PM2.5 concentrations were not consistently associated with increased hospital admissions rates. Increased source-specific PM2.5 concentrations were associated with both increased (e.g., secondary sulfates and diesel emissions) and decreased rates (e.g., secondary nitrate and spark-ignition vehicular emissions) of neurodegenerative admissions. CONCLUSIONS: We did not observe clear associations between overall ambient PM2.5 concentrations or source-apportioned ambient PM2.5 contributions and rates of neurologic disease hospitalizations.

Temporal changes in short-term associations between cardiorespiratory emergency department visits and PM2.5 in Los Angeles, 2005 to 2016.

BACKGROUND: Emissions control programs targeting certain air pollution sources may alter PM2.5 composition, as well as the risk of adverse health outcomes associated with PM2.5. OBJECTIVES: We examined temporal changes in the risk of emergency department (ED) visits for cardiovascular diseases (CVDs) and asthma associated with short-term increases in ambient PM2.5 concentrations in Los Angeles, California. METHODS: Poisson log-linear models with unconstrained distributed exposure lags were used to estimate the risk of CVD and asthma ED visits associated with short-term increases in daily PM2.5 concentrations, controlling for temporal and meteorological confounders. The models were run separately for three predefined time periods, which were selected based on the implementation of multiple emissions control programs (EARLY: 2005-2008; MIDDLE: 2009-2012; LATE: 2013-2016). Two-pollutant models with individual PM2.5 components and the remaining PM2.5 mass were also considered to assess the influence of changes in PM2.5 composition on changes in the risk of CVD and asthma ED visits associated with PM2.5 over time. RESULTS: The relative risk of CVD ED visits associated with a 10 µg/m3 increase in 4-day PM2.5 concentration (lag 0-3) was higher in the LATE period (rate ratio = 1.020, 95% confidence interval = [1.010, 1.030]) compared to the EARLY period (1.003, [0.996, 1.010]). In contrast, for asthma, relative risk estimates were largest in the EARLY period (1.018, [1.006, 1.029]), but smaller in the following periods. Similar temporal differences in relative risk estimates for CVD and asthma were observed among different age and season groups. No single component was identified as an obvious contributor to the changing risk estimates over time, and some components exhibited different temporal patterns in risk estimates from PM2.5 total mass, such as a decreased risk of CVD ED visits associated with sulfate over time. CONCLUSIONS: Temporal changes in the risk of CVD and asthma ED visits associated with short-term increases in ambient PM2.5 concentrations were observed. These changes could be related to changes in PM2.5 composition (e.g., an increasing fraction of organic carbon and a decreasing fraction of sulfate in PM2.5). Other factors such as improvements in healthcare and differential exposure misclassification might also contribute to the changes.