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.

Wildfire Exposure and Health Care Use Among People Who Use Durable Medical Equipment in Southern California.

BACKGROUND: People using electricity-dependent durable medical equipment (DME) may be vulnerable to health effects from wildfire smoke, residence near wildfires, or residence in evacuation zones. To our knowledge, no studies have examined their healthcare utilization during wildfires. METHODS: We obtained 2016-2020 counts of residential Zip Code Tabulation Area (ZCTA) level outpatient, emergency department (ED), and inpatient visits made by DME-using Kaiser Permanente Southern California members 45+. We linked counts to daily ZCTA-level wildfire particulate matter (PM) 2.5 and wildfire boundary and evacuation data from the 2018 Woolsey and 2019 Getty wildfires. We estimated the association of lagged (up to 7 days) wildfire PM 2.5 and residence near a fire or in an evacuation zone and healthcare visit frequency with negative binomial and difference-in-differences models. RESULTS: Among 236,732 DME users, 10 µg/m 3 increases in wildfire PM 2.5 concentration were associated with the reduced rate (RR = 0.96; 95% confidence interval [CI] = 0.94, 0.99) of all-cause outpatient visits 1 day after exposure and increased rate on 4 of 5 subsequent days (RR range 1.03-1.12). Woolsey Fire proximity (<20 km) was associated with reduced all-cause outpatient visits, whereas evacuation and proximity were associated with increased inpatient cardiorespiratory visits (proximity RR = 1.45; 95% CI = 0.99, 2.12, evacuation RR = 1.72; 95% CI = 1.00, 2.96). Neither Getty Fire proximity nor evacuation was associated with healthcare visit frequency. CONCLUSIONS: Our results support the hypothesis that wildfire smoke or proximity interrupts DME users' routine outpatient care, via sheltering in place. However, wildfire exposures were also associated with increased urgent healthcare utilization in this vulnerable group.

Excess Injury Mortality in Washington State During the 2021 Heat Wave.

PUBLIC HEALTH IMPLICATIONS: Under global warming scenarios, heat waves of this magnitude will become much more common. Adaptation and planning efforts are needed to protect residents of the historically temperate Pacific Northwest for a range of health outcomes. (Am J Public Health. 2023;113(6):657-660. https://doi.org/10.2105/AJPH.2023.307269).

Exposure to the early COVID-19 pandemic and early, moderate and overall preterm births in the United States: A conception cohort approach.

BACKGROUND: The United States (US) data suggest fewer-than-expected preterm births in 2020, but no study has examined the impact of exposure to the early COVID-19 pandemic at different points in gestation on preterm birth. OBJECTIVE: Our objective was to determine-among cohorts exposed to the early COVID-19 pandemic-whether observed counts of overall, early and moderately preterm birth fell outside the expected range. METHODS: We used de-identified, cross-sectional, national birth certificate data from 2014 to 2020. We used month and year of birth and gestational age to estimate month of conception for birth. We calculated the count of overall (<37 weeks gestation), early (<33 weeks gestation) and moderately (33 to <37 weeks gestation) preterm birth by month of conception. We employed time series methods to estimate expected counts of preterm birth for exposed conception cohorts and identified cohorts for whom the observed counts of preterm birth fell outside the 95% detection interval of the expected value. RESULTS: Among the 23,731,146 births in our study, the mean prevalence of preterm birth among monthly conception cohorts was 9.7 per 100 live births. Gestations conceived in July, August or December of 2019-that is exposed to the early COVID-19 pandemic in the first or third trimester-yielded approximately 3245 fewer moderately preterm and 3627 fewer overall preterm births than the expected values for moderate and overall preterm. Gestations conceived in August and October of 2019-that is exposed to the early COVID-19 pandemic in the late second to third trimester-produced approximately 498 fewer early preterm births than the expected count for early preterm. CONCLUSIONS: Exposure to the early COVID-19 pandemic may have promoted longer gestation among close-to-term pregnancies, reduced risk of later preterm delivery among gestations exposed in the first trimester or induced selective loss of gestations.

Wildfire smoke exposure and emergency department visits for headache: A case-crossover analysis in California, 2006-2020.

OBJECTIVE: To evaluate the association of short-term exposure to overall fine particulate matter of <2.5 µm (PM2.5 ) and wildfire-specific PM2.5 with emergency department (ED) visits for headache. BACKGROUND: Studies have reported associations between PM2.5 exposure and headache risk. As climate change drives longer and more intense wildfire seasons, wildfire PM2.5 may contribute to more frequent headaches. METHODS: Our study included adult Californian members (aged ≥18 years) of a large de-identified commercial and Medicare Advantage claims database from 2006 to 2020. We identified ED visits for primary headache disorders (subtypes: tension-type headache, migraine headache, cluster headache, and "other" primary headache). Claims included member age, sex, and residential zip code. We linked daily overall and wildfire-specific PM2.5 to residential zip code and conducted a time-stratified case-crossover analysis considering 7-day average PM2.5 concentrations, first for primary headache disorders combined, and then by headache subtype. RESULTS: Among 9898 unique individuals we identified 13,623 ED encounters for primary headache disorders. Migraine was the most frequently diagnosed headache (N = 5534/13,623 [47.6%]) followed by "other" primary headache (N = 6489/13,623 [40.6%]). For all primary headache ED diagnoses, we observed an association of 7-day average wildfire PM2.5 (odds ratio [OR] 1.17, 95% confidence interval [CI] 0.95-1.44 per 10 µg/m3 increase) and by subtype we observed increased odds of ED visits associated with 7-day average wildfire PM2.5 for tension-type headache (OR 1.42, 95% CI 0.91-2.22), "other" primary headache (OR 1.40, 95% CI 0.96-2.05), and cluster headache (OR 1.29, 95% CI 0.71-2.35), although these findings were not statistically significant under traditional null hypothesis testing. Overall PM2.5 was associated with tension-type headache (OR 1.29, 95% CI 1.03-1.62), but not migraine, cluster, or "other" primary headaches. CONCLUSIONS: Although imprecise, these results suggest short-term wildfire PM2.5 exposure may be associated with ED visits for headache. Patients, healthcare providers, and systems may need to respond to increased headache-related healthcare needs in the wake of wildfires and on poor air quality days.

The local impacts of coal and oil power plant retirements on air pollution and cardiorespiratory health in California: An application of generalized synthetic control method.

BACKGROUND: This study capitalized on coal and oil facility retirements to quantify their potential effects on fine particulate matter (PM2.5) concentrations and cardiorespiratory hospitalizations in affected areas using a generalized synthetic control method. METHODS: We identified 11 coal and oil facilities in California that retired between 2006 and 2013. We classified zip code tabulation areas (ZCTA) as exposed or unexposed to a facility retirement using emissions information, distance, and a dispersion model. We calculated weekly ZCTA-specific PM2.5 concentrations based on previously estimated daily time-series PM2.5 concentrations from an ensemble model, and weekly cardiorespiratory hospitalization rates based on hospitalization data collected by the California Department of Health Care Access and Information. We estimated the average differences in weekly average PM2.5 concentrations and cardiorespiratory hospitalization rates in four weeks after each facility retirement between the exposed ZCTAs and the synthetic control using all unexposed ZCTAs (i.e., the average treatment effect among the treated [ATT]) and pooled ATTs using meta-analysis. We conducted sensitivity analyses to consider different classification schemes to distinguish exposed from unexposed ZCTAs, including aggregating outcomes with different time intervals and including a subset of facilities with reported retirement date confirmed via emission record. RESULTS: The pooled ATTs were 0.02 µg/m3 (95% confidence interval (CI): -0.25 to 0.29 µg/m3) and 0.34 per 10,000 person-weeks (95%CI: -0.08 to 0.75 per 10,000 person-weeks) following the facility closure for weekly PM2.5 and cardiorespiratory hospitalization rates, respectively. Our inferences remained the same after conducting sensitivity analyses. CONCLUSIONS: We demonstrated a novel approach to study the potential benefits associated with industrial facility retirements. The declining contribution of industrial emissions to ambient air pollution in California may explain our null findings. We encourage future research to replicate this work in regions with different industrial activities.

Expectations of non-COVID-19 deaths during the pre-vaccine pandemic: a process-control approach.

BACKGROUND: Debate over "social distancing" as a response to the pandemic includes the claim that disrupting clinical and public health programming dependent on human-to-human contact increased non-COVID-19 deaths. This claim warrants testing because novel pathogens will continue to emerge. Tests, however, appear frustrated by lack of a convention for estimating non-COVID-19 deaths that would have occurred had clinical and public health programming during the pre-vaccine pandemic remained as efficacious as in the pre-pandemic era. Intending to hasten the emergence of such a convention, we describe and demonstrate "new-signal, prior-response expectations" suggested by research and methods at the intersection of epidemiology and process control engineering. METHODS: Using German data, we estimate pre-pandemic public health efficacy by applying Box-Jenkins methods to 271 weekly counts of all-cause deaths from December 29 2014 through March 8 2020. We devise new-signal, prior-response expectations by applying the model to weekly non-COVID-19 deaths from March 9 2020 through December 26 2020. RESULTS: The COVID-19 pandemic did not coincide with more non-COVID-19 deaths than expected from the efficacy of responses to pre-pandemic all-cause deaths. CONCLUSIONS: New-signal, prior-response estimates can contribute to evaluating the efficacy of public health programming in reducing non-COVID-19 deaths during the pre-vaccine pandemic.

Neighborhood disadvantage and dementia incidence in a cohort of Asian American and non-Latino White older adults in Northern California.

INTRODUCTION: Some evidence suggests that neighborhood socioeconomic disadvantage is associated with dementia-related outcomes. However, prior research is predominantly among non-Latino Whites. METHODS: We evaluated the association between neighborhood disadvantage (Area Deprivation Index [ADI]) and dementia incidence in Asian American (n = 18,103) and non-Latino White (n = 149,385) members of a Northern California integrated health care delivery system aged 60 to 89 at baseline. Race/ethnicity-specific Cox proportional hazards models adjusted for individual-level age, sex, socioeconomic measures, and block group population density estimated hazard ratios (HRs) for dementia. RESULTS: Among non-Latino Whites, ADI was associated with dementia incidence (most vs. least disadvantaged ADI quintile HR = 1.09, 95% confidence interval [CI] = 1.02-1.15). Among Asian Americans, associations were close to null (e.g., most vs. least disadvantaged ADI quintile HR = 1.01, 95% CI = 0.85-1.21). DISCUSSION: ADI was associated with dementia incidence among non-Latino Whites but not Asian Americans. Understanding the potentially different mechanisms driving dementia incidence in these groups could inform dementia prevention efforts.

Patterned Outcomes, Unpatterned Counterfactuals, and Spurious Results: Perinatal Health Outcomes Following COVID-19.

The epidemiologic literature estimating the indirect or secondary effects of the coronavirus disease 2019 (COVID-19) pandemic on pregnant people and gestation continues to grow. Our assessment of this scholarship, however, leads us to suspect that the methods most commonly used may lead researchers to spurious inferences. This suspicion arises because the methods do not account for temporal patterning in perinatal outcomes when deriving counterfactuals, or estimates of the outcomes had the pandemic not occurred. We illustrate the problem in 2 ways. First, using monthly data from US birth certificates, we describe temporal patterning in 5 commonly used perinatal outcomes. Notably, for all but 1 outcome, temporal patterns appear more complex than much of the emerging literature assumes. Second, using data from France, we show that using counterfactuals that ignore this complexity produces spurious results. We recommend that subsequent investigations on COVID-19 and other perturbations use widely available time-series methods to derive counterfactuals that account for strong temporal patterning in perinatal outcomes.

Long-Term Fine Particulate Matter Concentrations and Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2: Differential Relationships by Socioeconomic Status Among Pregnant Individuals in New York City.

We aimed to determine whether long-term ambient concentrations of fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5)) were associated with increased risk of testing positive for coronavirus disease 2019 (COVID-19) among pregnant individuals who were universally screened at delivery and whether socioeconomic status (SES) modified this relationship. We used obstetrical data collected from New-York Presbyterian Hospital/Columbia University Irving Medical Center in New York, New York, between March and December 2020, including data on Medicaid use (a proxy for low SES) and COVID-19 test results. We linked estimated 2018-2019 PM2.5 concentrations (300-m resolution) with census-tract-level population density, household size, income, and mobility (as measured by mobile-device use) on the basis of residential address. Analyses included 3,318 individuals; 5% tested positive for COVID-19 at delivery, 8% tested positive during pregnancy, and 48% used Medicaid. Average long-term PM2.5 concentrations were 7.4 (standard deviation, 0.8) µg/m3. In adjusted multilevel logistic regression models, we saw no association between PM2.5 and ever testing positive for COVID-19; however, odds were elevated among those using Medicaid (per 1-µg/m3 increase, odds ratio = 1.6, 95% confidence interval: 1.0, 2.5). Further, while only 22% of those testing positive showed symptoms, 69% of symptomatic individuals used Medicaid. SES, including unmeasured occupational exposures or increased susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to concurrent social and environmental exposures, may explain the increased odds of testing positive for COVID-19 being confined to vulnerable pregnant individuals using Medicaid.

Changes in preterm birth and caesarean deliveries in the United States during the SARS-CoV-2 pandemic.

BACKGROUND: Preliminary studies suggest that the SARS-CoV-2 pandemic and associated social, economic and clinical disruptions have affected pregnancy decision-making and outcomes. Whilst a few US-based studies have examined regional changes in birth outcomes during the pandemic's first months, much remains unknown of how the pandemic impacted perinatal health indicators at the national-level throughout 2020, including during the 'second wave' of infections that occurred later in the year. OBJECTIVES: To describe changes in monthly rates of perinatal health indicators during the 2020 pandemic for the entire US. METHODS: For the years 2015 to 2020, we obtained national monthly rates (per 100 births) for four perinatal indicators: preterm (<37 weeks' gestation), early preterm (<34 weeks' gestation), late preterm (34-36 weeks' gestation) and caesarean delivery. We used an interrupted time-series approach to compare the outcomes observed after the pandemic began (March 2020) to those expected had the pandemic not occurred for March through December of 2020. RESULTS: Observed rates of preterm birth fell below expectation across several months of the 2020 pandemic. These declines were largest in magnitude in early and late 2020, with a 5%-6% relative difference between observed and expected occurring in March and November. For example, in March 2020, the observed preterm birth rate of 9.8 per 100 live births fell below the 95% prediction interval (PI) of the rate predicted from history, which was 10.5 preterm births per 100 live births (95% PI 10.2, 10.7). We detected no changes from expectation in the rate of caesarean deliveries. CONCLUSIONS: Our findings provide nationwide evidence of unexpected reductions in preterm delivery during the 2020 SARS-CoV-2 pandemic in the US. Observed declines below expectation were differed by both timing of delivery and birth month, suggesting that several mechanisms, which require further study, may explain these patterns.

Anomalously warm weather and acute care visits in patients with multiple sclerosis: A retrospective study of privately insured individuals in the US.

BACKGROUND: As the global climate changes in response to anthropogenic greenhouse gas emissions, weather and temperature are expected to become increasingly variable. Although heat sensitivity is a recognized clinical feature of multiple sclerosis (MS), a chronic demyelinating disorder of the central nervous system, few studies have examined the implications of climate change for patients with this disease. METHODS AND FINDINGS: We conducted a retrospective cohort study of individuals with MS ages 18-64 years in a nationwide United States patient-level commercial and Medicare Advantage claims database from 2003 to 2017. We defined anomalously warm weather as any month in which local average temperatures exceeded the long-term average by ≥1.5°C. We estimated the association between anomalously warm weather and MS-related inpatient, outpatient, and emergency department visits using generalized log-linear models. From 75,395,334 individuals, we identified 106,225 with MS. The majority were women (76.6%) aged 36-55 years (59.0%). Anomalously warm weather was associated with increased risk for emergency department visits (risk ratio [RR] = 1.043, 95% CI: 1.025-1.063) and inpatient visits (RR = 1.032, 95% CI: 1.010-1.054). There was limited evidence of an association between anomalously warm weather and MS-related outpatient visits (RR = 1.010, 95% CI: 1.005-1.015). Estimates were similar for men and women, strongest among older individuals, and exhibited substantial variation by season, region, and climate zone. Limitations of the present study include the absence of key individual-level measures of socioeconomic position (i.e., race/ethnicity, occupational status, and housing quality) that may determine where individuals live-and therefore the extent of their exposure to anomalously warm weather-as well as their propensity to seek treatment for neurologic symptoms. CONCLUSIONS: Our findings suggest that as global temperatures rise, individuals with MS may represent a particularly susceptible subpopulation, a finding with implications for both healthcare providers and systems.

A Warning About Using Predicted Values From Regression Models for Epidemiologic Inquiry.

In many settings, researchers may not have direct access to data on 1 or more variables needed for an analysis and instead may use regression-based estimates of those variables. Using such estimates in place of original data, however, introduces complications and can result in uninterpretable analyses. In simulations and observational data, we illustrate the issues that arise when an average treatment effect is estimated from data where the outcome of interest is predicted from an auxiliary model. We show that bias in any direction can result, under both the null and alternative hypotheses.

Trends from 2008 to 2018 in Electricity-dependent Durable Medical Equipment Rentals and Sociodemographic Disparities.

BACKGROUND: Duration and number of power outages have increased over time, partly fueled by climate change, putting users of electricity-dependent durable medical equipment (hereafter, "durable medical equipment") at particular risk of adverse health outcomes. Given health disparities in the United States, we assessed trends in durable medical equipment rental prevalence and individual- and area-level sociodemographic inequalities. METHODS: Using Kaiser Permanente South California electronic health record data, we identified durable medical equipment renters. We calculated annual prevalence of equipment rental and fit hierarchical generalized linear models with ZIP code random intercepts, stratified by rental of breast pumps or other equipment. RESULTS: 243,559 KPSC members rented durable medical equipment between 2008 and 2018. Rental prevalence increased over time across age, sex, racial-ethnic, and Medicaid categories, most by >100%. In adjusted analyses, Medicaid use was associated with increased prevalence and 108 (95% confidence interval [CI] = 99, 117) additional days of equipment rental during the study period. ZIP code-level sociodemographics were associated with increased prevalence of equipment rentals, for example, a 1 SD increase in percent unemployed and

Climate Justice and California's Methane Superemitters: Environmental Equity Assessment of Community Proximity and Exposure Intensity.

Methane superemitters emit non-methane copollutants that are harmful to human health. Yet, no prior studies have assessed disparities in exposure to methane superemitters with respect to race/ethnicity, socioeconomic status, and civic engagement. To do so, we obtained the location, category (e.g., landfill, refinery), and emission rate of California methane superemitters from Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) flights conducted between 2016 and 2018. We identified block groups within 2 km of superemitters (exposed) and 5-10 km away (unexposed) using dasymetric mapping and assigned level of exposure among block groups within 2 km (measured via number of superemitter categories and total methane emissions). Analyses included 483 superemitters. The majority were dairy/manure (n = 213) and oil/gas production sites (n = 127). Results from fully adjusted logistic mixed models indicate environmental injustice in methane superemitter locations. For example, for every 10% increase in non-Hispanic Black residents, the odds of exposure increased by 10% (95% confidence interval (CI): 1.04, 1.17). We observed similar disparities for Hispanics and Native Americans but not with indicators of socioeconomic status. Among block groups located within 2 km, increasing proportions of non-White populations and lower voter turnout were associated with higher superemitter emission intensity. Previously unrecognized racial/ethnic disparities in exposure to California methane superemitters should be considered in policies to tackle methane emissions.

Hyperlocalized Measures of Air Pollution and Preeclampsia in Oakland, California.

Exposure to nitrogen dioxide (NO2), black carbon (BC), and ultrafine particles (UFPs) during pregnancy may increase the risk of preeclampsia, but previous studies have not assessed hyperlocalized differences in pollutant levels, which may cause exposure misclassification. We used data from Google Street View cars with mobile air monitors that repeatedly sampled NO2, BC, and UFPs every 30 m in Downtown and West Oakland neighborhoods during 2015-2017. Data were linked to electronic health records of pregnant women in the 2014-2016 Sutter Health population, who resided within 120 m of monitoring data (N = 1095), to identify preeclampsia cases. We used G-computation with log-binomial regression to estimate risk differences (RDs) associated with a hypothetical intervention reducing pollutant levels to the 25th percentile observed in our sample on preeclampsia risk, overall and stratified by race/ethnicity. Prevalence of preeclampsia was 6.8%. Median (interquartile range) levels of NO2, BC, and UFPs were 10.8 ppb (9.0, 13.0), 0.34 µg/m3 (0.27, 0.42), and 29.2 # × 103/cm3 (26.6, 32.6), respectively. Changes in the risk of preeclampsia achievable by limiting each pollutant to the 25th percentile were NO2 RD = -1.5 per 100 women (95% confidence interval (CI): -2.5, -0.5); BC RD = -1.0 (95% CI: -2.2, 0.02); and UFP RD = -0.5 (95% CI: -1.8, 0.7). Estimated effects were the largest for non-Latina Black mothers: NO2 RD = -2.8 (95% CI: -5.2, -0.3) and BC RD = -3.0 (95% CI: -6.4, 0.4).

Air pollution, methane super-emitters, and oil and gas wells in Northern California: the relationship with migraine headache prevalence and exacerbation.

BACKGROUND: Migraine-an episodic disorder characterized by severe headache that can lead to disability-affects over 1 billion people worldwide. Prior studies have found that short-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone increases risk of migraine-related emergency department (ED) visits. Our objective was to characterize the association between long-term exposure to sources of harmful emissions and common air pollutants with both migraine headache and, among patients with migraine, headache severity. METHODS: From the Sutter Health electronic health record database, we identified 89,575 prevalent migraine cases between 2014 and 2018 using a migraine probability algorithm (MPA) score and 270,564 frequency-matched controls. Sutter Health delivers care to 3.5 million patients annually in Northern California. Exposures included 2015 annual average block group-level PM2.5 and NO2 concentrations, inverse-distance weighted (IDW) methane emissions from 60 super-emitters located within 10 km of participant residence between 2016 and 2018, and IDW active oil and gas wells in 2015 within 10 km of each participant. We used logistic and negative binomial mixed models to evaluate the association between environmental exposures and (1) migraine case status; and (2) migraine severity (i.e., MPA score > 100, triptan prescriptions, neurology visits, urgent care migraine visits, and ED migraine visits per person-year). Models controlled for age, sex, race/ethnicity, Medicaid use, primary care visits, and block group-level population density and poverty. RESULTS: In adjusted analyses, for each 5 ppb increase in NO2, we observed 2% increased odds of migraine case status (95% CI: 1.00, 1.05) and for each 100,000 kg/hour increase in IDW methane emissions, the odds of case status also increased (OR = 1.04, 95% CI: 1.00, 1.08). We found no association between PM2.5 or oil and gas wells and migraine case status. PM2.5 was linearly associated with neurology visits, migraine-specific urgent care visits, and MPA score > 100, but not triptans or ED visits. NO2 was associated with migraine-specific urgent care and ED visits, but not other severity measures. We observed limited or null associations between continuous measures of methane emissions and proximity to oil and gas wells and migraine severity. CONCLUSIONS: Our findings illustrate the potential role of long-term exposure to multiple ambient air pollutants for prevalent migraine and migraine severity.

Stillbirth as left truncation for early neonatal death in California, 1989-2015: a time-series study.

BACKGROUND: Some scholars posit that attempts to avert stillbirth among extremely preterm gestations may result in a live birth but an early neonatal death. The literature, however, reports no empirical test of this potential form of left truncation. We examine whether annual cohorts delivered at extremely preterm gestational ages show an inverse correlation between their incidence of stillbirth and early neonatal death. METHODS: We retrieved live birth and infant death information from the California Linked Birth and Infant Death Cohort Files for years 1989 to 2015. We defined the extremely preterm period as delivery from 22 to < 28 weeks of gestation and early neonatal death as infant death at less than 7 days of life. We calculated proportions of stillbirth and early neonatal death separately by cohort year, race/ethnicity, and sex. Our correlational analysis controlled for well-documented declines in neonatal mortality over time. RESULTS: California reported 89,276 extremely preterm deliveries (live births and stillbirths) to Hispanic, non-Hispanic (NH) Black, and NH white mothers from 1989 to 2015. Findings indicate an inverse correlation between stillbirth and early neonatal death in the same cohort year (coefficient: -0.27, 95% CI of - 0.11; - 0.42). Results remain robust to alternative specifications and falsification tests. CONCLUSIONS: Findings support the notion that cohorts with an elevated risk of stillbirth also show a reduced risk of early neonatal death among extremely preterm deliveries. Results add to the evidence base that selection in utero may influence the survival characteristics of live-born cohorts.

Outpatient Urinary Tract Infections in an Era of Virtual Healthcare: Trends From 2008 to 2017.

BACKGROUND: Urinary tract infections (UTIs) occur commonly, but recent data on UTI rates are scarce. It is unknown how the growth of virtual healthcare delivery affects outpatient UTI management and trends in the United States. METHODS: From 1 January 2008 to 31 December 2017, UTIs from outpatient settings (office, emergency, and virtual visits) were identified from electronic health records at Kaiser Permanente Southern California using multiple UTI definitions. Annual rates estimated by Poisson regression were stratified by sex, care setting, age, and race/ethnicity. Annual trends were estimated by linear or piecewise Poisson regression. RESULTS: UTIs occurred in 1 065 955 individuals. Rates per 1000 person-years were 53.7 (95% confidence interval [CI], 50.6-57.0) by diagnosis code with antibiotic and 25.8 (95% CI, 24.7-26.9) by positive culture. Compared to office and emergency visits, UTIs were increasingly diagnosed in virtual visits, where rates by diagnosis code with antibiotic increased annually by 21.2% (95% CI, 16.5%-26.2%) in females and 29.3% (95% CI, 23.7%-35.3%) in males. Only 32% of virtual care diagnoses had a culture order. Overall, UTI rates were highest and increased the most in older adults. Rates were also higher in Hispanic and white females and black and white males. CONCLUSIONS: Outpatient UTI rates increased from 2008 to 2017, especially in virtual care and among older adults. Virtual care is important for expanding access to health services, but strategies are needed in all outpatient care settings to ensure accurate UTI diagnosis and reduce inappropriate antibiotic treatment.

Non-COVID-19 deaths after social distancing in Norway.

Lay persons and policy makers have speculated on how national differences in the imposition of social distancing to reduce SARS CoV-2 (severe acute respiratory syndrome coronavirus 2) infection has affected non-COVID-19 deaths. No rigorous estimation of the effect appears in the scholarly literature. We use time-series methods to compare non-COVID-19 deaths in Norway during its 9 weeks of mandated social distancing to those expected from history as well as from non-COVID-19 deaths in relatively less restricted Sweden. We estimate that 430 fewer Norwegians than expected died from causes other than COVID-19. We argue that failing to account for averted non-COVID-19 deaths will lead to an underestimate of the benefits of social distancing policies.