The Environment and Headache: a Narrative Review.

PURPOSE OF REVIEW: In this narrative review, we summarize the peer-reviewed literature published between 2017 and 2022 that evaluated ambient environmental risk factors for primary headache disorders, which affect more than half of the population globally. Primary headache disorders include migraine, tension-type headache (TTH), and trigeminal and autonomic cephalalgias (TAC). RECENT FINDINGS: We identified 17 articles that met the inclusion criteria via PubMed or Google Scholar. Seven studies (41%) relied on data from US populations. The remaining studies were conducted in China, Taiwan, Germany, Ghana, Japan, the Netherlands, South Korea, and Turkey. Air pollution was the most frequently assessed environmental risk factor. Most studies were cross-sectional and focused on all-cause or migraine headaches; one study included TTH, and none included TAC. Short-term exposure to fine particulate matter (PM2.5) was not consistently associated with headache endpoints, but long-term exposure to PM2.5 was associated with migraine headache prevalence and severity across multiple studies. Elevated ambient temperature, changes in weather, oil and gas well exposure, and less natural greenspace, but not noise pollution, were also associated with headache. No studies considered water pollution, metal exposure, ultrafine particulate matter, or wildfire smoke exposure. There is a need for ongoing research focused on headache and the environment. Study designs with the greatest explanatory power may include longitudinal studies that capture the episodic nature of headache and case-crossover analysis, which control for time-invariant individual-level confounders by design. There is also a clear need for research that considers comorbid psychiatric illness and socioeconomic position as powerful modifiers of the effect of the environment on headache.

Accuracy of self-reported distance to nearest unconventional oil and gas well in Pennsylvania, Ohio, and West Virginia residents and implications for exposure assessment.

Self-reported distances to industrial sources have been used in epidemiology as proxies for exposure to environmental hazards and indicators of awareness and perception of sources. Unconventional oil and gas development (UOG) emits pollutants and has been associated with adverse health outcomes. We compared self-reported distance to the nearest UOG well to the geographic information system-calculated distance for 303 Pennsylvania, Ohio, and West Virginia residents using Cohen's Weighted Kappa. Agreement was low (Kappa = 0.18), and self-reports by Ohioans (39% accuracy) were more accurate than West Virginians (22%) or Pennsylvanians (13%, both p < 0.05). Of the demographic characteristics studied, only educational attainment was related to reporting accuracy; residents with 12-16 years of education were more accurate (31.3% of group) than those with <12 or >16 years (both 16.7%). Understanding differences between objective and subjective measures of UOG proximity could inform studies of perceived exposures or risks and may also be relevant to adverse health effects. IMPACT: We compared objective and self-reported measures of distance to the nearest UOG well for 303 Appalachian Basin residents. We found that residents' self-reported distance to the nearest UOG well had limited agreement with the true calculated distance category. Our results can be used to inform the collection and contextualize the use of self-reported data in communities exposed to UOGD. Self-reported metrics can be used in conjunction with objective assessments and can be informative regarding how potentially exposed populations perceive environmental exposures or risks and could provide insights into awareness of distance-related policies, such as setbacks.

Missing Black males among preterm births in the US, 1995 to 2019.

BACKGROUND: In the US, non-Hispanic (NH) Black birthing persons show a two-fold greater risk of fetal death relative to NH white birthing persons. Since males more than females show a greater risk of fetal death, such loss in utero may affect the sex composition of live births born preterm (PTB; <37 weeks gestational age). We examine US birth data from 1995 to 2019 to determine whether the ratio of male to female preterm (i.e., PTB sex ratios) among NH Black births falls below that of NH whites and Hispanics. METHODS: We acquired data on all live births in the US from January 1995 to December 2019. We arrayed 63 million live births into 293 "conception cohort" months of which 2,475,928 NH Black, 5,746,953 NH white, and 2,511,450 Hispanic infants were PTB. We used linear regression methods to identify trend and seasonal patterns in PTB sex ratios. We also examined subgroup differences in PTB sex ratios (e.g., advanced maternal ages, twin gestations, and narrower gestational age ranges). RESULTS: The mean PTB sex ratio for NH Black births over the entire test period (1.06, 95% Confidence Interval [CI]: 1.05, 1.07) is much lower than that for NH white births (1.18, 95% CI: 1.17, 1.19). NH Black PTB sex ratios are especially low for twins and for births to mothers 35 years or older. Only NH white PTB sex ratios show a trend over the test period. CONCLUSIONS: Analysis of over 10 million PTBs reveals a persistently low male PTB frequency among NH Black conception cohorts relative to NH white cohorts. Low PTB sex ratios among NH Black births concentrate among subgroups that show an elevated risk of fetal death. PTB sex ratios may serve as an indicator of racial/ethnic and subgroup differences in fetal death, especially among male gestations.

Power outages and pediatric unintentional injury hospitalizations in New York State.

Background: In the past decade, electrical power disruptions (outages) have increased in the United States, especially those attributable to weather events. These outages have a range of health impacts but are largely unstudied in children. Here, we investigated the association between outages and unintentional injury hospitalizations, a leading cause of childhood morbidity. Methods: The study setting was New York State (NYS) from 2017 to 2020. Outage exposure was defined as ≥10%, ≥20%, and ≥50% of customers from a power operating locality without power, ascertained from NYS Department of Public Service records and stratified by rural, urban non-New York City (NYC), and NYC regions. Outcome daily block group-level pediatric injury hospitalization data was from the Statewide Planning and Research Cooperative System (SPARCS). We leveraged a case-crossover study design with logistic conditional regression. Results: We identified 23,093 unintentional injury hospitalizations in children <18 years with complete block group and exposure data. Most hospitalizations occurred in urban regions (90%), whereas outages were more likely in rural than urban areas. In urban non-NYC regions, outages ≥4 hours were associated with 30% increased odds of all-cause unintentional injury hospitalizations when ≥50% of customers were without power. Analyses by injury subtype revealed increasing point estimates as the proportion of customers exposed increased. These results, however, had wide confidence intervals. Conclusions: Outage exposure differed significantly across rural, urban non-NYC, and NYC regions across New York. Especially at the highest outage threshold, we observed an increased risk of pediatric unintentional injury hospitalizations.

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden.

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 µg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 µg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Limitations of Reporting Requirements under California's Livestock Antimicrobial Restriction Law.

BACKGROUND: Antimicrobial use in livestock production is considered a key contributor to growing antimicrobial resistance in bacteria. In 2015, California became the first state to enact restrictions on routine antimicrobial use in livestock production via Senate Bill 27 (SB27). SB27 further required the California Department of Food and Agriculture (CDFA) to collect and disseminate data on antimicrobial use in livestock production. OBJECTIVE: The goal of this report is to assess whether CDFA's data release allows us to evaluate how antimicrobial use changed after the implementation of SB27. METHODS: We combine the CDFA data with feed drug concentration ranges from the Code of Federal Regulation to evaluate the spread of plausible antimicrobial use trends. We also estimate antimicrobial consumption rates using data from the National Agricultural Statistical Service (NASS) and compare these to changes in medicated feed production reported by the CDFA. DISCUSSION: We show that CDFA's reported data are insufficient to reliably estimate whether antimicrobial usage has increased or decreased, most notably because no information is provided about the mass of antimicrobials approved for use or medicated feed drug concentrations. After incorporating additional external data on feed drug concentrations, one can at best provide uninformative bounds on the effect of SB27. We find some evidence that antimicrobial use has decreased by incorporating data on national sales of antimicrobials for food-producing animals, but the weakness of this inference underlines the need for improved data collection and dissemination, especially as other states seek to implement similar policies. We provide recommendations on how to improve reporting and data collection under SB27. https://doi.org/10.1289/EHP13702.

Assessing the difference in contamination of retail meat with multidrug-resistant bacteria using for-consumer package label claims that indicate on-farm antibiotic use practices- United States, 2016-2019.

BACKGROUND: Antibiotic use in food-producing animals can select for antibiotic resistance in bacteria that can be transmitted to people through contamination of food products during meat processing. Contamination resulting in foodborne illness contributes to adverse health outcomes. Some livestock producers have implemented antibiotic use reduction strategies marketed to consumers on regulated retail meat packaging labels ("label claims"). OBJECTIVE: We investigated whether retail meat label claims were associated with isolation of multidrug-resistant organisms (MDROs, resistant to ≥3 classes of antibiotics) from U.S. meat samples. METHODS: We utilized retail meat data from the U.S. Food and Drug Administration National Antimicrobial Resistance Monitoring System (NARMS) collected during 2016-2019 for bacterial contamination of chicken breast, ground turkey, ground beef, and pork chops. We used modified Poisson regression models to compare the prevalence of MDRO contamination among meat samples with any antibiotic restriction label claims versus those without such claims (i.e., conventionally produced). RESULTS: In NARMS, 62,338 meat samples were evaluated for bacterial growth from 2016-2019. Of these, 24,446 (39%) samples had label claims that indicated antibiotic use was restricted during animal production. MDROs were isolated from 2252 (4%) meat samples, of which 71% (n = 1591) were conventionally produced, and 29% (n = 661) had antibiotic restriction label claims. Compared with conventional samples, meat with antibiotic restriction label claims had a statistically lower prevalence of MDROs (adjusted prevalence ratio: 0.66; 95% CI: 0.61, 0.73). This relationship was consistent for the outcome of any bacterial growth. IMPACT: This repeated cross-sectional analysis of a nationally representative retail meat surveillance database in the United States supports that retail meats labeled with antibiotic restriction claims were less likely to be contaminated with MDROs compared with retail meat without such claims during 2016-2019. These findings indicate the potential for the public to become exposed to bacterial pathogens via retail meat and emphasizes a possibility that consumers could reduce their exposure to environmental reservoirs of foodborne pathogens that are resistant to antibiotics.

Multiple Dimensions of Environmental Justice and Oil and Gas Development in Pennsylvania.

Background: Community socioeconomic deprivation (CSD) may be related to higher oil and natural gas development (OGD) exposure. We tested for distributive and benefit-sharing environmental injustice in Pennsylvania's Marcellus Shale by examining (1) whether OGD and waste disposal occurred disproportionately in more deprived communities and (2) discordance between the location of land leased for OGD and where oil and gas rights owners resided. Materials and Methods: Analyses took place at the county subdivision level and considered OGD wells, waste disposal, and land lease agreement locations from 2005 to 2019. Using 2005-2009 American Community Survey data, we created a CSD index relevant to community vulnerability in suburban/rural areas. Results: In adjusted regression models accounting for spatial dependence, we observed no association between the CSD index and conventional or unconventional drilled well presence. However, a higher CSD index was linearly associated with odds of a subdivision having an OGD waste disposal site and receiving a larger volume of waste. A higher percentage of oil and gas rights owners lived in the same county subdivision as leased land when the community was least versus most deprived (66% vs. 56% in same county subdivision), suggesting that individuals in more deprived communities were less likely to financially benefit from OGD exposure. Discussion and Conclusions: We observed distributive environmental injustice with respect to well waste disposal and benefit-sharing environmental injustice related to oil and rights owner's residential locations across Pennsylvania's Marcellus Shale. These results add evidence of a disparity between exposure and benefits resulting from OGD.

Homelessness Among Acute Care Patients Within a Large Health Care System in Northern California.

The impacts of homelessness on health and health care access are detrimental. Intervention and efforts to improve outcomes and increase availability of affordable housing have mainly originated from the public health sector and government. The role that large community-based health systems may play has yet to be established. This study characterizes patients self-identified as homeless in acute care facilities in a large integrated health care system in Northern California to inform the development of collaborative interventions addressing unmet needs of this vulnerable population. The authors compared sociodemographic characteristics, clinical conditions, and health care utilization of individuals who did and did not self-identify as homeless and characterized their geographical distribution in relation to Sutter hospitals and homeless resources. Between July 1, 2019 and June 30, 2020, 5% (N = 20,259) of the acute care settings patients had evidence of homelessness, among which 51.1% age <45 years, 66.4% males, and 24% non-Hispanic Black. Patients experiencing homelessness had higher emergency department utilization and lower utilization of outpatient and urgent care services. Mental health conditions were more common among patients experiencing homelessness. More than half of the hospitals had >5% of patients who identified as homeless. Some hospitals with higher proportions of patients experiencing homelessness are not located near many shelter resources. By understanding patients who self-identify as homeless, it is possible to assess the role of the health system in addressing their unmet needs. Accurate identification is the first step for the health systems to develop and deliver better solutions through collaborations with nonprofit organizations, community partners, and government agencies.

An environmental justice analysis of air pollution emissions in the United States from 1970 to 2010.

Over the last decades, air pollution emissions have decreased substantially; however, inequities in air pollution persist. We evaluate county-level racial/ethnic and socioeconomic disparities in emissions changes from six air pollution source sectors (industry [SO2], energy [SO2, NOx], agriculture [NH3], commercial [NOx], residential [particulate organic carbon], and on-road transportation [NOx]) in the contiguous United States during the 40 years following the Clean Air Act (CAA) enactment (1970-2010). We calculate relative emission changes and examine the differential changes given county demographics using hierarchical nested models. The results show racial/ethnic disparities, particularly in the industry and energy generation source sectors. We also find that median family income is a driver of variation in relative emissions changes in all sectors-counties with median family income >$75 K vs. less generally experience larger relative declines in industry, energy, transportation, residential, and commercial-related emissions. Emissions from most air pollution source sectors have, on a national level, decreased following the United States CAA. In this work, we show that the relative reductions in emissions varied across racial/ethnic and socioeconomic groups.

Distance and destination of retail meat alter multidrug resistant contamination in the United States food system.

Antibiotic-resistant infections are a global concern, especially those caused by multidrug-resistant (MDR) bacteria, defined as those resistant to more than three drug classes. The animal agriculture industry contributes to the antimicrobial resistant foodborne illness burden via contaminated retail meat. In the United States, retail meat is shipped across the country. Therefore, understanding geospatial factors that influence MDR bacterial contamination is vital to protect consumers and inform interventions. Using data available from the United States Food and Drug Administration's National Antimicrobial Resistance Monitoring System (NARMS), we describe retail meat shipping distances using processor and retailer locations and investigated this distance as a risk factor for MDR bacteria meat contamination using log-binomial regression. Meat samples collected during 2012-2014 totaled 11,243, of which 4791 (42.61%) were contaminated with bacteria and 835 (17.43%) of those bacteria were MDR. All examined geospatial factors were associated with MDR bacteria meat contamination. After adjustment for year and meat type, we found higher prevalence of MDR contamination among meat processed in the south (relative adjusted prevalence ratio [aPR] 1.35; 95% CI 1.06-1.73 when compared to the next-highest region), sold in Maryland (aPR 1.12; 95% CI 0.95-1.32 when compared to the next-highest state), and shipped from 194 to 469 miles (aPR 1.59; 95% CI 1.31-1.94 when compared to meats that traveled < 194 miles). However, sensitivity analyses revealed that New York sold the meat with the highest prevalence of MDR Salmonella contamination (4.84%). In this secondary analysis of NARMS data, both geographic location where products were sold and the shipping distance were associated with microbial contamination on retail meat.

Disparities in preterm birth following the July 1995 Chicago heat wave.

PURPOSE: To evaluate if changes in preterm birth (PTB, <37 weeks of gestation) incidence differed between non-Hispanic (NH) Black and NH white births following the July 1995 Chicago heat wave-among the most severe U.S. heat waves since 1950. METHODS: We used an ecologic study design. We obtained birth data from January 1990-December 1996 from the National Vital Statistics File to calculate the mean monthly PTB incidence in Chicago's Cook County, Illinois. Births between July 1995 and February 1996 were potentially exposed to the heat wave in utero. We generated time series models for NH Black and NH white births, which incorporated synthetic controls of Cook County based on unexposed counties. We ran a secondary analysis considering socioeconomic status (SES). RESULTS: From 1990-1996, the mean monthly PTB incidence among NH Black births was 18.6% compared to 7.8% among NH white births. The mean monthly PTB incidence among NH Black births from August 1995-January 1996 was 16.7% higher than expected (three additional PTBs per 100 live births per month [95% confidence interval (CI): 1, 5]). A similar increase occurred among low-SES NH Black births. No increase appeared among NH white births. CONCLUSIONS: Severe heat waves may increase racial disparities in PTB incidence.

Methods in Public Health Environmental Justice Research: a Scoping Review from 2018 to 2021.

PURPOSE OF REVIEW: The volume of public health environmental justice (EJ) research produced by academic institutions increased through 2022. However, the methods used for evaluating EJ in exposure science and epidemiologic studies have not been catalogued. Here, we completed a scoping review of EJ studies published in 19 environmental science and epidemiologic journals from 2018 to 2021 to summarize research types, frameworks, and methods. RECENT FINDINGS: We identified 402 articles that included populations with health disparities as a part of EJ research question and met other inclusion criteria. Most studies (60%) evaluated EJ questions related to socioeconomic status (SES) or race/ethnicity. EJ studies took place in 69 countries, led by the US (n = 246 [61%]). Only 50% of studies explicitly described a theoretical EJ framework in the background, methods, or discussion and just 10% explicitly stated a framework in all three sections. Among exposure studies, the most common area-level exposure was air pollution (40%), whereas chemicals predominated personal exposure studies (35%). Overall, the most common method used for exposure-only EJ analyses was main effect regression modeling (50%); for epidemiologic studies the most common method was effect modification (58%), where an analysis evaluated a health disparity variable as an effect modifier. Based on the results of this scoping review, current methods in public health EJ studies could be bolstered by integrating expertise from other fields (e.g., sociology), conducting community-based participatory research and intervention studies, and using more rigorous, theory-based, and solution-oriented statistical research methods.

The role of insurance status in the association between short-term temperature exposure and myocardial infarction hospitalizations in New York State.

Myocardial infarction (MI) is a leading cause of morbidity and mortality in the United States and its risk increases with extreme temperatures. Climate change causes variability in weather patterns, including extreme temperature events that disproportionately affect socioeconomically disadvantaged communities. Many studies on the health effects of extreme temperatures have considered community-level socioeconomic disadvantage. Objectives: To evaluate effect modification of the relationship between short-term ambient temperature and MI, by individual-level insurance status (insured vs. uninsured). Methods: We identified MI hospitalizations and insurance status across New York State (NYS) hospitals from 1995 to 2015 in the New York Department of Health Statewide Planning and Research Cooperative System database, using International Classification of Diseases codes. We linked short-term ambient temperature (averaging the 6 hours preceding the event [MI hospitalization]) or nonevent control period in patient residential zip codes. We employed a time-stratified case-crossover study design for both insured and uninsured strata, and then compared the group-specific rate ratios. Results: Over the study period, there were 1,095,051 primary MI admissions, 966,475 (88%) among insured patients. During extremely cold temperatures (<5.8 °C) insured patients experienced reduced rates of MI; this was not observed among the uninsured counterparts. At warmer temperatures starting at the 65th percentile (15.7 °C), uninsured patients had higher rates than insured patients (e.g., for a 6-hour pre-event average temperature increase from the median to the 75th percentile, the rate of MI increased was 2.0% [0.0%-4.0%] higher in uninsured group). Conclusions: Uninsured individuals may face disproportionate rates of MI hospitalization during extreme temperatures.

Multidrug Resistance of Escherichia coli From Outpatient Uncomplicated Urinary Tract Infections in a Large United States Integrated Healthcare Organization.

Background: Urinary tract infections (UTIs) cause significant disease and economic burden. Uncomplicated UTIs (uUTIs) occur in otherwise healthy individuals without underlying structural abnormalities, with uropathogenic Escherichia coli (UPEC) accounting for 80% of cases. With recent transitions in healthcare toward virtual visits, data on multidrug resistance (MDR) (resistant to ≥3 antibiotic classes) by care setting are needed to inform empiric treatment decision making. Methods: We evaluated UPEC resistance over time by care setting (in-person vs virtual), in adults who received outpatient care for uUTI at Kaiser Permanente Southern California between January 2016 and December 2021. Results: We included 174 185 individuals who had ≥1 UPEC uUTI (233 974 isolates) (92% female, 46% Hispanic, mean age 52 years [standard deviation 20]). Overall, prevalence of UPEC MDR decreased during the study period (13% to 12%) both in virtual and in-person settings (P for trend <.001). Resistance to penicillins overall (29%), coresistance to penicillins and trimethoprim-sulfamethoxazole (TMP-SMX) (12%), and MDR involving the 2 plus ≥1 antibiotic class were common (10%). Resistance to 1, 2, 3, and 4 antibiotic classes was found in 19%, 18%, 8%, and 4% of isolates, respectively; 1% were resistant to ≥5 antibiotic classes, and 50% were resistant to none. Similar resistance patterns were observed over time and by care setting. Conclusions: We observed a slight decrease in both class-specific antimicrobial resistance and MDR of UPEC overall, most commonly involving penicillins and TMP-SMX. Resistance patterns were consistent over time and similar in both in-person and virtual settings. Virtual healthcare may expand access to UTI care.

A novel indicator of selection in utero.

Background and objectives: Selection in utero predicts that population stressors raise the standard for how quickly fetuses must grow to avoid spontaneous abortion. Tests of this prediction must use indirect indicators of fetal loss in birth cohorts because vital statistics systems typically register fetal deaths at the 20th week of gestation or later, well after most have occurred. We argue that tests of selection in utero would make greater progress if researchers adopted an indicator of selection against slow-growing fetuses that followed from theory, allowed sex-specific tests and used readily available data. We propose such an indicator and assess its validity as a dependent variable by comparing its values among monthly birth cohorts before, and during, the first 10 months of the COVID-19 pandemic in Sweden. Methodology: We apply Box-Jenkins methods to 50 pre-pandemic birth cohorts (i.e., December 2016 through January 2020) and use the resulting transfer functions to predict counterfactual values in our suggested indicator for selection for ten subsequent birth cohorts beginning in February 2020. We then plot all 60 residual values as well as their 95% detection interval. If birth cohorts in gestation at the onset of the pandemic lost more slow-growing fetuses than expected from history, more than one of the last 10 (i.e. pandemic-exposed) residuals would fall below the detection interval. Results: Four of the last 10 residuals of our indicator for males and for females fell below the 95% detection interval. Conclusions and implications: Consistent with selection in utero, Swedish birth cohorts in gestation at the outset of the COVID-19 pandemic included fewer than expected infants who grew slowly in utero.

Aircraft and road traffic noise, insulin resistance, and diabetes: The role of neighborhood socioeconomic status in San Diego County.

Evidence linking traffic noise to insulin resistance and diabetes is limited and unanswered questions remain regarding the potential effect modification by neighborhood socioeconomic status (nSES). We aimed to assess socioeconomic inequalities in noise exposure, whether road and aircraft noise exposures were associated with insulin resistance or diabetes, and whether nSES modified these relationships. Among the Community of Mine Study in San Diego County, road and aircraft noise exposure at enrollment was calculated based on the static (participant's administrative boundary, and circular buffer around participant homes), and dynamic (mobility data by global positioning system, GPS) spatio-temporal aggregation methods. Associations of noise with insulin resistance (HOMA-IR) or type 2 diabetes (T2DM) were quantified using generalized estimating equation models adjusted for sex, age, ethnicity, individual income, and air pollution (nitrogen dioxide) exposure. Additive interaction between noise and nSES was assessed. Among 573 participants (mean age 58.7 y), participants living in low nSES were exposed to higher levels of aircraft and road noise using noise level at the census tract, circular buffer, or Kernel Density Estimation (KDE) of GPS data. Participants exposed to road noise greater or equal to the median (53 dB(A)) at the census tract and living in low nSES had an increased level of insulin resistance (ß = 0.15, 95%CI: -0.04, 0.34) and higher odds of T2DM (Odds Ratio = 2.34, 95%CI: 1.12, 4.90). A positive additive interaction was found as participants living in low nSES had higher odds of T2DM. The impact of noise exposure on insulin resistance and T2DM differs substantially by nSES. Public health benefits of reducing exposure to road or aircraft noise would be larger in individuals living in low nSES.

Can traffic-related air pollution trigger myocardial infarction within a few hours of exposure? Identifying hourly hazard periods.

INTRODUCTION: Traffic-related air pollution can trigger myocardial infarction (MI). However, the hourly hazard period of exposure to nitrogen dioxide (NO2), a common traffic tracer, for incident MI has not been fully evaluated. Thus, the current hourly US national air quality standard (100 ppb) is based on limited hourly-level effect estimates, which may not adequately protect cardiovascular health. OBJECTIVES: We characterized the hourly hazard period of NO2 exposure for MI in New York state (NYS), USA, from 2000 to 2015. METHODS: For nine cities in NYS, we obtained data on MI hospitalizations from the NYS Department of Health Statewide Planning and Research Cooperative System and hourly NO2 concentrations from the US Environmental Protection Agency's Air Quality System database. We used city-wide exposures and a case-crossover study design with distributed lag non-linear terms to assess the relationship between hourly NO2 concentrations over 24 h and MI, adjusting for hourly temperature and relative humidity. RESULTS: The mean NO2 concentration was 23.2 ppb (standard deviation: 12.6 ppb). In the six hours preceding MI, we found linearly increased risk with increasing NO2 concentrations. At lag hour 0, a 10 ppb increase in NO2 was associated with 0.2 % increased risk of MI (Rate Ratio [RR]: 1.002; 95 % Confidence Interval [CI]: 1.000, 1.004). We estimated a cumulative RR of 1.015 (95 % CI: 1.008, 1.021) for all 24 lag hours per 10 ppb increase in NO2. Lag hours 2-3 had consistently elevated risk ratios in sensitivity analyses. CONCLUSIONS: We found robust associations between hourly NO2 exposure and MI risk at concentrations far lower than current hourly NO2 national standards. Risk of MI was most elevated in the six hours after exposure, consistent with prior studies and experimental work evaluating physiologic responses after acute traffic exposure. Our findings suggest that current hourly standards may be insufficient to protect cardiovascular health.

Temperature and socioeconomic vulnerability: associations with cardiac event-induced posttraumatic stress symptoms.

Background: Posttraumatic stress symptoms (PTSS) are common after acute coronary syndrome (ACS) and predict increased morbidity and mortality. Climate change contributes to worse mental and cardiovascular health outcomes, thus, PTSS represent a potential mechanism linking climate change to adverse cardiovascular outcomes. Because people living in areas with lower socioeconomic status (SES) experience greater climate vulnerability, have worse cardiovascular health, and may be more susceptible to PTSS, any effect of temperature on PTSS could be amplified in this population. Methods: Spatial regression models were estimated to test the association of temperature and temperature variability (within-day variability, directed change over time, and absolute change over time), census tract-level SES, and their interaction with PTSS 1 month post-hospital discharge in a longitudinal cohort study comprising 956 patients evaluated for ACS at an urban U.S. academic medical center between November 2013-May 2017. PTSS were self-reported in relation to the ACS event that brought the patient to the hospital. Census tract-level was computed as a composite score from the CDC Social Vulnerability Index, with higher values indicating lower SES. Results: No temperature or temperature variability metrics were associated with PTSS. Lower census tract-level SES was associated with greater PTSS at 1 month. There was a marginally significant interaction of SES with ACS status, such that we only observed evidence of an association among those with ACS. Conclusion: Temperature exposures were not associated with acute CVD-induced PTSS, which could be a result of a small sample size, mismatched timescale, or lack of a true effect. Conversely, lower census tract-level SES was associated with developing worse PTSS 1 month after evaluation for an ACS. This association appeared stronger in individuals with a true ACS. Early interventions to prevent PTSS could promote better mental and CVD outcomes in this at-risk population.

Impact of California's Senate Bill 27 on Antimicrobial-Resistant Escherichia coli Urinary Tract Infection in Humans: Protocol for a Study of Methods and Baseline Data.

BACKGROUND: Overuse of antibiotics contributes to antimicrobial resistance (AMR) and is a growing threat to human health worldwide. Previous work suggests a link between antimicrobial use in poultry and human AMR extraintestinal pathogenic Escherichia coli (E coli) urinary tract infections (UTIs). However, few US-based studies exist, and none have comprehensively assessed both foodborne and environmental pathways using advanced molecular and spatial epidemiologic methods in a quasi-experimental design. Recently, California enacted Senate Bill 27 (SB27), which changed previous policy to require a veterinarian's prescription for the use of antibiotic drugs, and which banned antibiotic use for disease prevention in livestock. This provided an opportunity to evaluate whether SB27 will result in a reduction in antimicrobial-resistant infections in humans. OBJECTIVE: We describe in detail the methods implemented to achieve the overarching objective of this study to evaluate the impact of SB27 on downstream antibiotic resistance rates in human UTIs. METHODS: A summary of the overall approach and the partnerships between Columbia University, George Washington University (GWU), Johns Hopkins Bloomberg School of Public Health, Kaiser Permanente Southern California (KPSC) Research and Evaluation, the Natural Resources Defense Council, Sanger Institute at Stanford University, Sutter Health Center for Health Systems Research, the University of Cambridge, and the University of Oxford is presented. The collection, quality control testing, and shipment of retail meat and clinical samples are described. Retail meat (chicken, beef, turkey, and pork) was purchased from stores throughout Southern California from 2017 to 2021. After processing at KPSC, it was shipped to GWU for testing. From 2016 to 2021, after clinical specimens were processed for routine clinical purposes and immediately before discarding, those with isolated colonies of E coli, Campylobacter, and Salmonella from KPSC members were collected and processed to be shipped for testing at GWU. Detailed methods of the isolation and testing as well as the whole-genome sequencing of the meat and clinical samples at GWU are described. KPSC electronic health record data were used to track UTI cases and AMR patterns among the cultured specimens. Similarly, Sutter Health electronic health record data were used to track UTI cases in its Northern California patient population. RESULTS: From 2017 to 2021, overall, 12,616 retail meat samples were purchased from 472 unique stores across Southern California. In addition, 31,643 positive clinical cultures were collected from KPSC members during the same study period. CONCLUSIONS: Here, we presented data collection methods for the study, which was conducted to evaluate the impact of SB27 on downstream antibiotic resistance rates in human UTI. To date, it is one of the largest studies of its kind to be conducted. The data collected during this study will be used as the foundation for future analyses specific to the various objectives of this large body of work. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45109.