Power Outage: An Ignored Risk Factor for COPD Exacerbations

Use, limitations, and future directions of mixtures approaches to understand the health impacts of weather- and climate change-related exposures, an under-studied aspect of the exposome

The exposome concept aims to account for the comprehensive and cumulative effects of physical, chemical, biological, and psychosocial influences on biological systems. To date, limited exposome research has explicitly included climate change-related exposures. We define these exposures as those that will intensify with climate change, including direct effects like extreme heat, tropical cyclones, wildfires, downstream effects like air pollution, power outages, and limited or contaminated food and water supplies. These climate change-related exposures can occur individually or simultaneously. Here, we discuss the concept of a climate mixture, defined as three or more simultaneous climate change-related exposures, in the context of the exposome. In a motivating climate mixture example, we consider the impact of a co-occurring tropical cyclone, power outage, and flooding on respiratory hospitalizations. We identify current gaps and future directions for assessing the effect of climate mixtures on health. Mixtures methods allow us to incorporate climate mixtures into exposomics.

Association of social vulnerability factors with power outage burden in Washington state: 2018-2021

Major power outages have risen over the last two decades, largely due to more extreme weather conditions. However, there is a lack of knowledge on the distribution of power outages and its relationship to social vulnerability and co-occurring hazards. We examined the associations between localized outages and social vulnerability factors (demographic characteristics), controlling for environmental factors (weather), in Washington State between 2018-2021. We additionally analyzed the validity of PowerOutage.us data compared to federal datasets. The population included 27 counties served by 14 electric utilities. We developed a continuous measure of daily outage burden using PowerOutage.us data and operationalized social vulnerability using four factors: poverty level, unemployment, disability, and limited English proficiency. We applied zero-altered lognormal generalized additive mixed-effects models to characterize the relationship between social vulnerability and daily power outage burden, controlling for daily minimum temperature, maximum wind speed, and precipitation, from 2018 to 2021 in Washington State. We found that social vulnerability factors have non-linear relationships with outages. Wind and precipitation are consistent drivers of outage occurrence and duration. There are seasonal effects that vary by county-utility area. Both PowerOutage.us and federal datasets have missing and inaccurate outage data. This is the first study evaluating differential exposure to localized outages as related to social vulnerability that has accounted for weather and temporal correlation. There is a lack of transparency into power outage distribution for those most vulnerable to climate impacts, despite known contributions by electric utilities to climate change. For effective public health surveillance of power outages and transparency, outage data should be made available at finer spatial resolution and temporal scales and/or utilities should be required to report differential exposure to power outages for socially vulnerable populations.

NPCC4: Climate change, energy, and energy insecurity in New York City

This chapter of the New York City Panel on Climate Change 4 (NPCC4) report provides an overview of energy trends in New York City and the State of New York, as well as accompanying challenges and barriers to the energy transition-with implications for human health and wellbeing. The link between energy trends and their impact on health and wellbeing is brought to the fore by the concept of "energy insecurity," an important addition to the NPCC4 assessment.

The Joint Effects of Thunderstorms and Power Outages on Respiratory-Related Emergency Visits and Modifying and Mediating Factors of This Relationship

BACKGROUND

While limited studies have evaluated the health impacts of thunderstorms and power outages (POs) separately, few have assessed their joint effects. We aimed to investigate the individual and joint effects of both thunderstorms and POs on respiratory diseases, to identify disparities by demographics, and to examine the modifications and mediations by meteorological factors and air pollution.

METHODS

Distributed lag nonlinear models were used to examine exposures during three periods (i.e., days with both thunderstorms and POs, thunderstorms only, and POs only) in relation to emergency department visits for respiratory diseases (2005-2018) compared to controls (no thunderstorm/no PO) in New York State (NYS) while controlling for confounders. Interactions between thunderstorms and weather factors or air pollutants on health were assessed. The disparities by demographics and seasons and the mediative effects by particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) and relative humidity (RH) were also evaluated.

RESULTS

Thunderstorms and POs were independently associated with total and six subtypes of respiratory diseases in NYS [highest risk ratio (RR) = 1.12; 95% confidence interval (CI): 1.08, 1.17], but the impact was stronger when they co-occurred (highest RR = 1.44; 95% CI: 1.22, 1.70), especially during grass weed, ragweed, and tree pollen seasons. The stronger thunderstorm/PO joint effects were observed on chronic obstructive pulmonary diseases, bronchitis, and asthma (lasted 0-10 d) and were higher among residents who lived in rural areas, were uninsured, were of Hispanic ethnicity, were 6-17 or over 65 years old, and during spring and summer. The number of comorbidities was significantly higher by 0.299-0.782/case. Extreme cold/heat, high RH, PM 2.5 , and ozone concentrations significantly modified the thunderstorm-health effect on both multiplicative and additive scales. Over 35% of the thunderstorm effects were mediated by PM 2.5 and RH.

CONCLUSION

Thunderstorms accompanied by POs showed the strongest respiratory effects. There were large disparities in thunderstorm-health associations by demographics. Meteorological factors and air pollution levels modified and mediated the thunderstorm-health effects. https://doi.org/10.1289/EHP13237.

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.

A spatial analysis of power-dependent medical equipment and extreme weather risk in the southeastern United States

Extreme weather events endanger critical health infrastructure, and many individuals rely on infrastructure to meet their basic needs, such as heat, water, and medical devices. The purpose of this study is to identify spatially explicit at-risk populations for power outages due to these extreme weather events. To accomplish this, we used the HHS emPOWER Emergency Planning Dataset, which was created to help public health authorities plan for and address the needs of communities. Using Geographic Information Systems (GIS), we overlay emPOWER data with the frequency of extreme weather events, including wildfires, hurricanes, tornadoes, and ice storms. Through our analysis, we identified vulnerable areas for high rates of disasters and electricity-dependent durable medical equipment (DME) to be located in communities along the coast. We also found a higher concentration of DME in rural areas compared to urban areas. In addition, we found least privileged economic locations are disproportionately vulnerable to power outages in the southeastern United States due to their high concentration of DME individuals. These results will inform public health officials where to target interventions to ensure continuity of care for vulnerable populations during power outages at the community level.

Spatiotemporal distribution of power outages with climate events and social vulnerability in the USA

Power outages threaten public health. While outages will likely increase with climate change, an aging electrical grid, and increased energy demand, little is known about their frequency and distribution within states. Here, we characterize 2018-2020 outages, finding an average of 520 million customer-hours total without power annually across 2447 US counties (73.7% of the US population). 17,484 8+ hour outages (a medically-relevant duration with potential health consequences) and 231,174 1+ hour outages took place, with greatest prevalence in Northeastern, Southern, and Appalachian counties. Arkansas, Louisiana, and Michigan counties experience a dual burden of frequent 8+ hour outages and high social vulnerability and prevalence of electricity-dependent durable medical equipment use. 62.1% of 8+ hour outages co-occur with extreme weather/climate events, particularly heavy precipitation, anomalous heat, and tropical cyclones. Results could support future large-scale epidemiology studies, inform equitable disaster preparedness and response, and prioritize geographic areas for resource allocation and interventions.

The 2021 Texas Power Crisis: distribution, duration, and disparities

BACKGROUND

Precipitated by an unusual winter storm, the 2021 Texas Power Crisis lasted February 10 to 27 leaving millions of customers without power. Such large-scale outages can have severe health consequences, especially among vulnerable subpopulations such as those reliant on electricity to power medical equipment, but limited studies have evaluated sociodemographic disparities associated with outages.

OBJECTIVE

To characterize the 2021 Texas Power Crisis in relation to distribution, duration, preparedness, and issues of environmental justice.

METHODS

We used hourly Texas-wide county-level power outage data to estimate geographic clustering and association between outage exposure (distribution and duration) and six measures of racial, social, political, and/or medical vulnerability: Black and Hispanic populations, the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI), Medicare electricity-dependent durable medical equipment (DME) usage, nursing homes, and hospitals. To examine individual-level experience and preparedness, we used a preexisting and non-representative internet survey.

RESULTS

At the peak of the Texas Power Crisis, nearly 1/3 of customers statewide (N = 4,011,776 households/businesses) lost power. We identified multiple counties that faced a dual burden of racial/social/medical vulnerability and power outage exposure, after accounting for multiple comparisons. County-level spatial analyses indicated that counties where more Hispanic residents resided tended to endure more severe outages (OR = 1.16, 95% CI: 1.02, 1.40). We did not observe socioeconomic or medical disparities. With individual-level survey data among 1038 respondents, we found that Black respondents were more likely to report outages lasting 24+ hours and that younger individuals and those with lower educational attainment were less likely to be prepared for outages.

SIGNIFICANCE

Power outages can be deadly, and medically vulnerable, socioeconomically vulnerable, and marginalized groups may be disproportionately impacted or less prepared. Climate and energy policy must equitably address power outages, future grid improvements, and disaster preparedness and management.

How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state?

Background

Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State.

Methods

We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees.

Results

Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9-15.6%), population density (3.3-16.1%), per capita income (2.3-10.7%), and the density of public infrastructure (0.8-8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3-27.9%) and those with limited English (2.2-8.1%), the percent of sandy soil (6.5-11.8%), and average soil temperature (3.0-15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status.

Conclusion

Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization.

The independent and synergistic impacts of power outages and floods on hospital admissions for multiple diseases

Highly destructive disasters such as floods and power outages (PO) are becoming more commonplace in the U.S. Few studies examine the effects of floods and PO on health, and no studies examine the synergistic effects of PO and floods, which are increasingly co-occurring events. We examined the independent and synergistic impacts of PO and floods on cardiovascular diseases, chronic respiratory diseases, respiratory infections, and food-/water-borne diseases (FWBD) in New York State (NYS) from 2002 to 2018. We obtained hospitalization data from the NYS discharge database, PO data from the NYS Department of Public Service, and floods events from NOAA. Distributed lag nonlinear models were used to evaluate the PO/floods-health association while controlling for time-varying confounders. We identified significant increased health risks associated with both the independent effects from PO and floods, and their synergistic effects. Generally, the Rate Ratios (RRs) for the co-occurrence of PO and floods were the highest, followed by PO alone, and then floods alone, especially when PO coverage is >75th percentile of its distribution (1.72% PO coverage). For PO and floods combined, immediate effects (lag 0) were observed for chronic respiratory diseases (RR:1.58, 95%CI: 1.24, 2.00) and FWBD (RR:3.02, 95%CI: 1.60, 5.69), but delayed effects were found for cardiovascular diseases (lag 3, RR:1.13, 95%CI: 1.03, 1.24) and respiratory infections (lag 6, RR:1.85, 95%CI: 1.35, 2.53). The risk association was slightly stronger among females, whites, older adults, and uninsured people but not statistically significant. Improving power system resiliency could be a very effective way to alleviate the burden on hospitals during co-occurring floods. We conclude that PO and floods have independently and jointly led to increased hospitalization for multiple diseases, and more research is needed to confirm our findings.

Climate Change and Infections on the Move in North America

Climate change is increasingly recognized for its impacts on human health, including how biotic and abiotic factors are driving shifts in infectious disease. Changes in ecological conditions and processes due to temperature and precipitation fluctuations and intensified disturbance regimes are affecting infectious pathogen transmission, habitat, hosts, and the characteristics of pathogens themselves. Understanding the relationships between climate change and infectious diseases can help clinicians broaden the scope of differential diagnoses when interviewing, diagnosing, and treating patients presenting with infections lacking obvious agents or transmission pathways. Here, we highlight key examples of how the mechanisms of climate change affect infectious diseases associated with water, fire, land, insects, and human transmission pathways in the hope of expanding the analytical framework for infectious disease diagnoses. Increased awareness of these relationships can help prepare both clinical physicians and epidemiologists for continued impacts of climate change on infectious disease in the future.

The individual and synergistic impacts of windstorms and power outages on injury ED visits in New York State

BACKGROUND

There is little work in assessing the impact of storm events combined with power outage (PO). In this study, we evaluated the individual and synergistic impacts of wind events and PO on overall and subtypes of injuries in New York State (NYS) and by demographics.

METHODS

The emergency department (ED) visit data were obtained from the NYS Department of Health from November-April 2005-2013 to identify injury cases, length of stay and care costs. Wind event was defined according to high wind, strong wind or thunderstorm wind defined by NOAA. PO occurrence was defined when PO coverage exceeded the 50th percentile of its distribution. By comparing non-event days, we used distributed lag nonlinear models to evaluate the impacts of wind events, PO, and their combined effect on injuries during the cold season over a 0-3-day lag period, while controlling for time-varying confounders. The differences in critical care indicators between event and non-event days were also evaluated.

RESULTS

Overall injuries ED visits (16,628,812) significantly increased during the wind events (highest Risk Ratio (RR): 1.05; 95% CI: 1.02-1.08), and were highest when wind events cooccurred with PO (highest RR: 1.14; 95% CI: 1.10-1.18), but not during PO alone (RR: 1.00; 95%CI: 0.96-1.04). The increase was also observed with all subgroups through Day 2 after the event. Greater risks exist for older adults (≥65 years) and those on Medicaid. After the joint occurrences of wind events and PO, average visits are 0.2 days longer, and cost 13% more, compared to no wind/no PO days.

CONCLUSION

There is a significant increase in ED visits, length of stay and cost of injuries during wind events, especially when they coupled with PO and especially among older cases and Medicaid holders. Our findings may be used for planning disaster preparedness and recovery efforts.

Association of Power Outage With Mortality and Hospitalizations Among Florida Nursing Home Residents After Hurricane Irma

Importance

Exposure to hurricanes is associated with increased mortality and morbidity in nursing home (NH) residents, but the factors contributing to these outcomes are less understood. One hypothesized pathway could be power outages from hurricanes that expose NH residents to excess ambient heat.

Objective

To determine the association of power loss from Hurricane Irma with hospitalization and mortality in NH residents in Florida.

Design Setting and Participants

This retrospective cohort study of NH residents residing in Florida when Hurricane Irma landed on September 10, 2017, assessed mortality at 7 and 30 days after the storm and hospitalization at 30 days after the storm. The analysis was conducted from May 2, 2021, to June 28, 2021. All NH residents residing in Florida at landfall were eligible (N = 67 273). We excluded those younger than 65 years, missing power status information, or who were evacuated (13 178 [19.6%]).

Exposure

We used state-administered surveys to determine NH power outage status. Exposed residents experienced a power outage poststorm, whereas unexposed residents did not experience a power outage poststorm.

Main Outcomes and Measures

We used Medicare claims to assess mortality and hospitalization after Hurricane Irma landfall using generalized linear models with robust standard errors.

Results

In the aftermath of Hurricane Irma, 27 892 residents (18 510 women [66.4%]; 3906 [14.0%] Black, 1651 [5.9%] Hispanic, and 21 756 [78.0%] White individuals) in 299 NHs were exposed to power loss and 26 203 residents (17 620 women [67.2%]; 4175 [15.9%] Black, 1030 [3.9%] Hispanic, and 20 477 [78.1%] White individuals) in 292 NHs were unexposed. Nursing homes that lost power were similar in size, quality star rating, and type of ownership compared with NHs that did not lose power. Power loss was associated with an increased adjusted odds of mortality among all residents within 7 days (odds ratio [OR],1.25; 95% CI,1.05-1.48) and 30 days (OR, 1.12; 95% CI,1.02-1.23) poststorm and hospitalization within 30 days, although only among residents aged 65 to 74 years (OR, 1.16; 95% CI, 1.03-1.33).

Conclusions and Relevance

In this cohort study, power loss was associated with higher odds of mortality in all affected NH residents and hospitalization in some residents. The benefits and costs of policies that require NHs to have emergency alternate power sources should be assessed.

Power outage mediates the associations between major storms and hospital admission of chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide with continuous rise. Limited studies indicate that COPD was associated with major storms and related power outages (PO). However, significant gaps remain in understanding what PO's role is on the pathway of major storms-COPD. This study aimed to examine how PO mediates the major storms-COPD associations.

METHODS

In this time-series study, we extracted all hospital admissions with COPD as the principal diagnosis in New York, 2001-2013. Using distributed lag nonlinear models, the hospitalization rate during major storms and PO was compared to non-major storms and non-PO periods to determine the risk ratios (RRs) for COPD at each of 0-6 lag days respectively after controlling for time-varying confounders and concentration of fine particulate matter (PM2.5). We then used Granger mediation analysis for time series to assess the mediation effect of PO on the major storms-COPD associations.

RESULTS

The RRs of COPD hospitalization following major storms, which mainly included flooding, thunder, hurricane, snow, ice, and wind, were 1.23 to 1.49 across lag 0-6 days. The risk was strongest at lag3 and lasted significantly for 4 days. Compared with non-outage periods, the PO period was associated with 1.23 to 1.61 higher risk of COPD admissions across lag 0-6 days. The risk lasted significantly for 2 days and was strongest at lag2. Snow, hurricane and wind were the top three contributors of PO among the major storms. PO mediated as much as 49.6 to 65.0% of the major storms-COPD associations.

CONCLUSIONS

Both major storms and PO were associated with increased hospital admission of COPD. PO mediated almost half of the major storms-COPD hospitalization associations. Preparation of surrogate electric system before major storms is essential to reduce major storms-COPD hospitalization.

[Knowledge gained from a 31-h power outage in Berlin Köpenick-medical problems and challenges]

On 19 February 2019 the severance of a 110kW cable caused an extensive electrical power cut in the Treptow-Köpenick district of Berlin. Subsequently, ca. 30,000 households were without electricity and ca. 70,000 people were affected. The power cut lasted more than 24h and all those involved were faced with a multitude of challenges. An operational command post was set up in which medical problems had to be continuously identified and re-evaluated. These included the identification of patients particularly at risk, such as home-ventilated patients and patients with artificial hearts. Furthermore, individual nursing homes had to be evacuated. During the procedure it was necessary to evacuate an intensive care ward or intermediate care ward with 23 patients due to the loss of power supply in the affected area. Hospitals must be prepared for such scenarios within the framework of preliminary planning. Furthermore, preliminary planning containing the special needs of vulnerable groups must be carried out on the part of the responsible authorities.

The immediate effects of winter storms and power outages on multiple health outcomes and the time windows of vulnerability

BACKGROUND

While most prior research has focused on extreme heat, few assessed the immediate health effects of winter storms and associated power outages (PO), although severe storms have become more frequent. This study evaluates the joint and independent health effects of winter storms and PO, snow versus ice-storm, effects by time window (peak timing, winter/transitional months) and the impacts on critical care indicators including numbers of comorbidity, procedure, length of stay and cost.

METHODS

We use distributed lag nonlinear models to assess the impacts of winter storm/PO on hospitalizations due to cardiovascular, lower respiratory diseases (LRD), respiratory infections, food/water-borne diseases (FWBD) and injuries in New York State on 0-6 lag days following storm/PO compared with non-storm/non-PO periods (references), while controlling for time-varying factors and PM2.5. The storm-related hospitalizations are described by time window. We also calculate changes in critical care indicators between the storm/PO and control periods.

RESULTS

We found the joint effects of storm/PO are the strongest (risk ratios (RR) range: 1.01-1.90), followed by that of storm alone (1.02-1.39), but not during PO alone. Ice storms have stronger impacts (RRs: 1.04-3.15) than snowstorms (RRs: 1.03-2.21). The storm/PO-health associations, which occur immediately, and some last a whole week, are stronger in FWBD, October/November, and peak between 3:00-8:00 p.m. Comorbidity and medical costs significantly increase after storm/PO.

CONCLUSION

Winter storms increase multiple diseases, comorbidity and medical costs, especially when accompanied by PO or ice storms. Early warnings and prevention may be critical in the transitional months and afternoon rush hours.

Power Outages and Community Health: a Narrative Review

PURPOSE OF REVIEW

Power outages, a common and underappreciated consequence of natural disasters, are increasing in number and severity due to climate change and aging electricity grids. This narrative review synthesizes the literature on power outages and health in communities.

RECENT FINDINGS

We searched Google Scholar and PubMed for English language studies with titles or abstracts containing "power outage" or "blackout." We limited papers to those that explicitly mentioned power outages or blackouts as the exposure of interest for health outcomes among individuals living in the community. We also used the reference list of these studies to identify additional studies. The final sample included 50 articles published between 2004 and 2020, with 17 (34%) appearing between 2016 and 2020. Exposure assessment remains basic and inconsistent, with 43 (86%) of studies evaluating single, large-scale power outages. Few studies used spatial and temporal control groups to assess changes in health outcomes attributable to power outages. Recent research linked data from electricity providers on power outages in space and time and included factors such as number of customers affected and duration to estimate exposure. The existing literature suggests that power outages have important health consequences ranging from carbon monoxide poisoning, temperature-related illness, gastrointestinal illness, and mortality to all-cause, cardiovascular, respiratory, and renal disease hospitalizations, especially for individuals relying on electricity-dependent medical equipment. Nonetheless the studies are limited, and more work is needed to better define and capture the relevant exposures and outcomes. Studies should consider modifying factors such as socioeconomic and other vulnerabilities as well as how community resiliency can minimize the adverse impacts of widespread major power outages.