Respiratory hospitalizations and wildfire smoke: a spatiotemporal analysis of an extreme firestorm in San Diego County, California

In this current wildfire crisis, acknowledge widespread suffering

With climate change causing more extreme weather events globally, climate scientists have argued that societies have three options: mitigation, adaptation or suffering. In recent years, devastating wildfires have caused significant suffering, yet the extent of this suffering has not been defined. To encapsulate this suffering, we determined impacts and effects of extreme wildfires through two systematic literature reviews. Six common themes of wildfire suffering emerged: environmental, social, physical, mental, cultural and resource suffering. These themes varied in scale: from local to regional; from individuals to communities; and from ecosystems to landscapes. We then applied these themes in the Las Maquinas (Chile) and Fort McMurray (Canada) wildfires. This highlighted several adaptation strategies that can reduce suffering, however our exploration indicates these strategies must address social and ecological factors. This analysis concludes that suffering from wildfires is diverse and widespread, and that significant engagement with adaptation strategies is needed if this is going to decrease.

Heat-related mortality in Mexico: A multi-scale spatial analysis of extreme heat effects and municipality-level vulnerability

Understanding effects of extreme heat across diverse settings is critical as social determinants play an important role in modifying heat-related risks. We apply a multi-scale analysis to understand spatial variation in the effects of heat across Mexico and explore factors that are explaining heterogeneity. Daily all-cause mortality was collected from the Mexican Secretary of Health and municipality-specific extreme heat events were estimated using population-weighted temperatures from 1998 to 2019 using Daymet and WorldPop datasets. We analyzed the association between single-day extreme heat events defined at the 99th percentile of the same-day maximum temperature and mortality, and seven heat threshold metrics based on relative and absolute scales were considered as sensitivity analyses. A time-stratified case-crossover was applied to evaluate heat impacts across 32 states in Mexico. A within-community matched design with Bayesian Hierarchical model explored effects across 2456 municipalities. A random-effects meta-regression was applied to understand which municipality-level socio-demographic characteristics such as education, age and housing predicted observed spatial heterogeneity. Extreme heat increased the odds of mortality overall, and this was consistent across extreme heat thresholds. At the state level, extreme heat events showed highest impact on mortality in Tabasco [OR: 1.23, 95% CI: 1.17, 1.30]. The municipality-level spatial analysis showed substantial differences across regions with highest effects observed along the eastern, southwestern and Sonora coasts. Municipalities with older populations, higher marginalization, lower education, and poorer housing conditions were more vulnerable to heat effects. Understanding the differential risks of extreme heat events at varying scales is important to prioritize at-risk populations in action plans and policies to reduce their burden.

Spatial Variation in the Association between Extreme Heat Events and Warm Season Pediatric Acute Care Utilization: A Small-Area Assessment of Multiple Health Conditions and Environmental Justice Implications in California (2005-2019)

BACKGROUND

The increasing frequency and severity of extreme heat events due to climate change present unique risks to children and adolescents. There is a lack of evidence regarding how heat's impacts on pediatric patients vary spatially and how structural and sociodemographic factors drive this heterogeneity.

OBJECTIVES

We examined the association between extreme heat events and pediatric acute care utilization in California for 19 distinct health conditions. We then assessed how extreme heat's consequences varied at the ZIP code level and identified environmental justice metrics that modulated children's vulnerability to extreme heat.

METHODS

This study analyzed 7.2 million unscheduled hospitalizations and emergency department visits for children < 19 years old in California between May and September from 2005 to 2019. We first utilized a time-stratified case-crossover design to generate statewide estimates for the association between extreme heat events and care utilization. We then implemented a within-community matched design coupled with a Bayesian hierarchical model to generate spatially varying effect estimates. Finally, we conducted a random effects meta-regression to examine how community-level characteristics modified heat's impacts across ZIP codes.

RESULTS

Extreme heat events were associated with substantial increases in acute care utilization for all causes [odds ratio ( OR ) = 1.03 ; 95% confidence interval (CI): 1.03, 1.04] and were attributable for over 30,000 excess acute care utilizations during the study period. Extreme heat events were also associated with increases in heat-related illness (OR = 1.53 ; 95% CI: 1.49, 1.58); endocrine, nutritional, and metabolic disorders (OR = 1.13 ; 95% CI: 1.1, 1.16); other signs and symptoms (OR = 1.07 ; 95% CI: 1.06, 1.08); and injury and poisoning (OR = 1.07 ; 95% CI: 1.05, 1.08). There was substantial spatial heterogeneity in extreme heat events effects, especially in coastal metropolitan areas. Communities with lower incomes and education levels, less access to insurance and air conditioning, and higher percentages of Black, Hispanic, and Pacific Islander residents were most vulnerable during extreme heat events.

CONCLUSIONS

Extreme heat events in California are associated with increased pediatric care utilization. There is significant variation in heat's consequences, and historically disadvantaged and under-resourced communities are most impacted. These findings suggest that interventions designed to improve heat resilience should be targeted to protect vulnerable children. https://doi.org/10.1289/EHP14236.

Lung function may recover after coal mine fire smoke exposure: a longitudinal cohort study

BACKGROUND AND OBJECTIVE

The 2014 Hazelwood coal mine fire exposed residents in nearby Morwell to high concentrations of particulate matter <2.5 µm (PM2.5) for approximately 6 weeks. This analysis aimed to evaluate the long-term impact on respiratory health.

METHODS

Adults from Morwell and the unexposed town of Sale completed validated respiratory questionnaires and performed spirometry, gas transfer and oscillometry 3.5-4 years (round 1) and 7.3-7.8 years (round 2) after the fire. Individual PM2.5 exposure levels were estimated using chemical transport models mapped onto participant-reported time-location data. Mixed-effects regression models were fitted to analyse associations between PM2.5 exposure and outcomes, controlling for key confounders.

RESULTS

From 519 (346 exposed) round 1 participants, 329 (217 exposed) participated in round 2. Spirometry and gas transfer in round 2 were mostly lower compared with round 1, excepting forced vital capacity (FVC) (increased) and forced expiratory volume in 1 second (minimal change). The effect of mine fire-related PM2.5 exposure changed from a negative effect in round 1 to no effect in round 2 for both pre-bronchodilator (p=0.005) and post-bronchodilator FVC (p=0.032). PM2.5 was not associated with gas transfer in either round. For post-bronchodilator reactance and area under the curve, a negative impact of PM2.5 in round 1 showed signs of recovery in round 2 (both p<0.001).

CONCLUSION

In this novel study evaluating long-term respiratory outcomes after medium-duration high concentration PM2.5 exposure, the attenuated associations between exposure and respiratory function may indicate some recovery in lung function. With increased frequency and severity of landscape fires observed globally, these results inform public health policies and planning.

The spatial distribution of heat related hospitalizations and classification of the most dangerous heat events in California at a small-scale level

Many studies have explored the impact of extreme heat on health, but few have investigated localized heat-health outcomes across a wide area. We examined fine-scale variability in vulnerable areas, considering population distribution, local weather, and landscape characteristics. Using 36 different heat event definitions, we identified the most dangerous types of heat events based on minimum, maximum, and diurnal temperatures with varying thresholds and durations. Focusing on California's diverse climate, elevation, and population distribution, we analyzed hospital admissions for various causes of admission (2004-2013). Our matching approach identified vulnerable zip codes, even with small populations, on absolute and relative scales. Bayesian Hierarchical models leveraged spatial correlation. We ranked the 36 heat event types by attributable hospital admissions per zip code and provided code, simulated data, and an interactive web app for reproducibility. Our findings showed high variation in heat-related hospitalizations in coastal cities and substantial heat burdens in the Central Valley. Diurnal heat events had the greatest impact in the Central Valley, while nighttime extreme heat events drove burdens in the southeastern desert. This spatially informed approach guides local policies, prioritizing dangerous heat events to reduce the heat-health burden. The methodology is applicable to other regions, informing early warning systems and characterizing extreme heat impacts.

A mouse model of wildfire smoke-induced health effects: sex differences in acute and sustained effects of inhalation exposures

Due to climate change, wildfires have increased in intensity and duration. While wildfires threaten lives directly, the smoke has more far-reaching adverse health impacts. During an extreme 2017 wildfire event, residents of Seeley Lake, Montana were exposed to unusually high levels of wood smoke (WS) causing sustained effects on lung function (decreased FEV1/FVC). Objective: The present study utilized an animal model of WS exposure to research cellular and molecular mechanisms of the resulting health effects. Methods: Mice were exposed to inhaled WS utilizing locally harvested wood to recapitulate community exposures. WS was generated at a rate resulting in a 5 mg/m3 PM2.5 exposure for five days. Results: This exposure resulted in a similar 0.28 mg/m2 particle deposition (lung surface area) in mice that was calculated for human exposure. As with the community observations, there was a significant effect on lung function, increased resistance, and decreased compliance, that was more pronounced in males at an extended (2 months) timepoint and males were more affected than females: ex vivo assays illustrated changes to alveolar macrophage functions (increased TNFα secretion and decreased efferocytosis). Female mice had significantly elevated IL-33 levels in lungs, however, pretreatment of male mice with IL-33 resulted in an abrogation of the observed WS effects, suggesting a dose-dependent role of IL-33. Additionally, there were greater immunotoxic effects in male mice. Discussion: These findings replicated the outcomes in humans and suggest that IL-33 is involved in a mechanism of the adverse effects of WS exposures that inform on potential sex differences.

Spatial Heterogeneity of the Respiratory Health Impacts of Wildfire Smoke PM2.5 in California

Wildfire smoke fine particles (PM2.5) are a growing public health threat as wildfire events become more common and intense under climate change, especially in the Western United States. Studies assessing the association between wildfire PM2.5 exposure and health typically summarize the effects over the study area. However, health responses to wildfire PM2.5 may vary spatially. We evaluated spatially-varying respiratory acute care utilization risks associated with short-term exposure to wildfire PM2.5 and explored community characteristics possibly driving spatial heterogeneity. Using ensemble-modeled daily wildfire PM2.5, we defined a wildfire smoke day to have wildfire-specific PM2.5 concentration ≥15 μg/m3. We included daily respiratory emergency department visits and unplanned hospitalizations in 1,396 California ZIP Code Tabulation Areas (ZCTAs) and 15 census-derived community characteristics. Employing a case-crossover design and conditional logistic regression, we observed increased odds of respiratory acute care utilization on wildfire smoke days at the state level (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.05, 1.07). Across air basins, ORs ranged from 0.88 to 1.57, with the highest effect estimate in San Diego. A within-community matching design and spatial Bayesian hierarchical model also revealed spatial heterogeneity in ZCTA-level rate differences. For example, communities with a higher percentage of Black or Pacific Islander residents had stronger wildfire PM2.5-outcome relationships, while more air conditioning and tree canopy attenuated associations. We found an important heterogeneity in wildfire smoke-related health impacts across air basins, counties, and ZCTAs, and we identified characteristics of vulnerable communities, providing evidence to guide policy development and resource allocation.

Data Linkages for Wildfire Exposures and Human Health Studies: A Scoping Review

Wildfires are increasing in frequency and intensity, with significant consequences that impact human health. A scoping review was conducted to: (a) understand wildfire-related health effects, (b) identify and describe environmental exposure and health outcome data sources used to research the impacts of wildfire exposures on health, and (c) identify gaps and opportunities to leverage exposure and health data to advance research. A literature search was conducted in PubMed and a sample of 83 articles met inclusion criteria. A majority of studies focused on respiratory and cardiovascular outcomes. Hospital administrative data was the most common health data source, followed by government data sources and health surveys. Wildfire smoke, specifically fine particulate matter (PM2.5), was the most common exposure measure and was predominantly estimated from monitoring networks and satellite data. Health data were not available in real-time, and they lacked spatial and temporal coverage to study health outcomes with longer latency periods. Exposure data were often available in real-time and provided better temporal and spatial coverage but did not capture the complex mixture of hazardous wildfire smoke pollutants nor exposures associated with non-air pathways such as soil, household dust, food, and water. This scoping review of the specific health and exposure data sources used to underpin these studies provides a framework for the research community to understand: (a) the use and value of various environmental and health data sources, and (b) the opportunities for improving data collection, integration, and accessibility to help inform our understanding of wildfires and other environmental exposures.

Exploring spatial heterogeneity in synergistic effects of compound climate hazards: Extreme heat and wildfire smoke on cardiorespiratory hospitalizations in California

Extreme heat and wildfire smoke events are increasingly co-occurring in the context of climate change, especially in California. Extreme heat and wildfire smoke may have synergistic effects on population health that vary over space. We leveraged high-resolution satellite and monitoring data to quantify spatially varying compound exposures to extreme heat and wildfire smoke in California (2006-2019) at ZIP Code Tabulation Area (ZCTA) level. We found synergistic effects between extreme heat and wildfire smoke on daily cardiorespiratory hospitalizations at the state level. We also found spatial heterogeneity in such synergistic effects across ZCTAs. Communities with lower education attainment, lower health insurance coverage, lower income, lower proportion of automobile ownership, lower tree canopy coverage, higher population density, and higher proportions of racial/ethnic minorities experienced higher synergistic effects. This study highlights the need to incorporate compound hazards and environmental justice considerations into evidence-based policy development to protect populations from increasingly prevalent compound hazards.

Prescribed fires, smoke exposure, and hospital utilization among heart failure patients

BACKGROUND

Prescribed fires often have ecological benefits, but their environmental health risks have been infrequently studied. We investigated associations between residing near a prescribed fire, wildfire smoke exposure, and heart failure (HF) patients' hospital utilization.

METHODS

We used electronic health records from January 2014 to December 2016 in a North Carolina hospital-based cohort to determine HF diagnoses, primary residence, and hospital utilization. Using a cross-sectional study design, we associated the prescribed fire occurrences within 1, 2, and 5 km of the patients' primary residence with the number of hospital visits and 7- and 30-day readmissions. To compare prescribed fire associations with those observed for wildfire smoke, we also associated zip code-level smoke density data designed to capture wildfire smoke emissions with hospital utilization amongst HF patients. Quasi-Poisson regression models were used for the number of hospital visits, while zero-inflated Poisson regression models were used for readmissions. All models were adjusted for age, sex, race, and neighborhood socioeconomic status and included an offset for follow-up time. The results are the percent change and the 95% confidence interval (CI).

RESULTS

Associations between prescribed fire occurrences and hospital visits were generally null, with the few associations observed being with prescribed fires within 5 and 2 km of the primary residence in the negative direction but not the more restrictive 1 km radius. However, exposure to medium or heavy smoke (primarily from wildfires) at the zip code level was associated with both 7-day (8.5% increase; 95% CI = 1.5%, 16.0%) and 30-day readmissions (5.4%; 95% CI = 2.3%, 8.5%), and to a lesser degree, hospital visits (1.5%; 95% CI: 0.0%, 3.0%) matching previous studies.

CONCLUSIONS

Area-level smoke exposure driven by wildfires is positively associated with hospital utilization but not proximity to prescribed fires.

Wildfire smoke knows no borders: Differential vulnerability to smoke effects on cardio-respiratory health in the San Diego-Tijuana region

Exposure to fine particles in wildfire smoke is deleterious for human health and can increase cases of cardio-respiratory illnesses and related hospitalizations. Neighborhood-level risk factors can increase susceptibility to environmental hazards, such as air pollution from smoke, and the same exposure can lead to different health effects across populations. While the San Diego-Tijuana border can be exposed to the same wildfire smoke event, socio-demographic differences may drive differential effects on population health. We used the October 2007 wildfires, one the most devastating wildfire events in Southern California that brought smoke to the entire region, as a natural experiment to understand the differential effect of wildfire smoke on both sides of the border. We applied synthetic control methods to evaluate the effects of wildfire smoke on cardio-respiratory hospitalizations in the Municipality of Tijuana and San Diego County separately. During the study period (October 11th- October 26th, 2007), 2009 hospital admissions for cardio-respiratory diseases occurred in San Diego County while 37 hospital admissions were reported in the Municipality of Tijuana. The number of cases in Tijuana was much lower than San Diego, and a precise effect of wildfire smoke was detected in San Diego but not in Tijuana. However, social drivers can increase susceptibility to environmental hazards; the poverty rate in Tijuana is more than three times that of San Diego. Socio-demographics are important in modulating the effects of wildfire smoke and can be potentially useful in developing a concerted regional effort to protect populations on both sides of the border from the adverse health effects of wildfire smoke.

Wildfires: Implications for nurses

Wildfire smoke can travel hundreds of miles from its source, resulting in poor air quality. Exposure to poor air quality has been associated with health risks. Nurses should be knowledgeable about such risks to provide appropriate care and education in affected communities.

Hot and cold flavors of southern California's Santa Ana winds: their causes, trends, and links with wildfire

Santa Ana winds (SAWs) are associated with anomalous temperatures in coastal Southern California (SoCal). As dry air flows over SoCal's coastal ranges on its way from the elevated Great Basin down to sea level, all SAWs warm adiabatically. Many but not all SAWs produce coastal heat events. The strongest regionally averaged SAWs tend to be cold. In fact, some of the hottest and coldest observed temperatures in coastal SoCal are linked to SAWs. We show that hot and cold SAWs are produced by distinct synoptic dynamics. High-amplitude anticyclonic flow around a blocking high pressure aloft anchored at the California coast produces hot SAWs. Cold SAWs result from anticyclonic Rossby wave breaking over the northwestern U.S. Hot SAWs are preceded by warming in the Great Basin and dry conditions across the Southwestern U.S. Precipitation over the Southwest, including SoCal, and snow accumulation in the Great Basin usually precede cold SAWs. Both SAW flavors, but especially the hot SAWs, yield low relative humidity at the coast. Although cold SAWs tend to be associated with the strongest winds, hot SAWs tend to last longer and preferentially favor wildfire growth. Historically, out of large (> 100 acres) SAW-spread wildfires, 90% were associated with hot SAWs, accounting for 95% of burned area. As health impacts of SAW-driven coastal fall, winter and spring heat waves and impacts of smoke from wildfires have been recently identified, our results have implications for designing early warning systems. The long-term warming trend in coastal temperatures associated with SAWs is focused on January-March, when hot and cold SAW frequency and temperature intensity have been increasing and decreasing, respectively, over our 71-year record.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00382-021-05802-z.

Spatial variation in the joint effect of extreme heat events and ozone on respiratory hospitalizations in California

Extreme heat and ozone are co-occurring exposures that independently and synergistically increase the risk of respiratory disease. To our knowledge, no joint warning systems consider both risks; understanding their interactive effect can warrant use of comprehensive warning systems to reduce their burden. We examined heterogeneity in joint effects (on the additive scale) between heat and ozone at small geographical scales. A within-community matched design with a Bayesian hierarchical model was applied to study this association at the zip code level. Spatially varying relative risks due to interaction (RERI) were quantified to consider joint effects. Determinants of the spatial variability of effects were assessed using a random effects metaregression to consider the role of demographic/neighborhood characteristics that are known effect modifiers. A total of 817,354 unscheduled respiratory hospitalizations occurred in California from 2004 to 2013 in the May to September period. RERIs revealed no additive interaction when considering overall joint effects. However, when considering the zip code level, certain areas observed strong joint effects. A lower median income, higher percentage of unemployed residents, and exposure to other air pollutants within a zip code drove stronger joint effects; a higher percentage of commuters who walk/bicycle, a marker for neighborhood wealth, showed decreased effects. Results indicate the importance of going beyond average measures to consider spatial variation in the health burden of these exposures and predictors of joint effects. This information can be used to inform early warning systems that consider both heat and ozone to protect populations from these deleterious effects in identified areas.