Evidence map›Paper›PMID 38829734›Full record

ArticleEnvironmental health perspectives2024

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

Shao Lin, Quan Qi, Han Liu, Xinlei Deng, Ian Trees, Xiaojun Yuan, Mary P Gallant

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Environmental health perspectives, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Assessing bias in measuring power outage exposure with simulations.Environmental epidemiology (Philadelphia, Pa.) · 2025
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shao LinDepartment of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Albany, New York, USA.ORCID 0000-0002-5535-7504
Quan QiDepartment of Economics, University at Albany, State University of New York, Albany, New York, USA.
Han LiuPopulation Studies and Training Center, Brown University, Providence, Rhode Island, USA.
Xinlei DengEpidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, North Carolina, USA.
Ian TreesEpidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Rockville, Maryland, USA.
Xiaojun YuanDepartment of Information Sciences and Technology, College of Emergency Preparedness, Homeland Security and Cybersecurity, University at Albany, State University of New York, Albany, New York, USA.
Mary P GallantZuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, Massachusetts, USA.

Funding

Weather extremes, natural disasters, and health outcomes among vulnerable older adults: New improvements on exposure assessment, disparity identification, and risk communication strategiesR01AG070949 · NIA · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI LIN, SHAO · 2022 to 2025
$1.6M
Assess and Model the Health Effects, Population, and Infrastructural Vulnerabilities of Power OutageR15ES028000 · NIEHS · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI LIN, SHAO · 2018 to 2018
$444k
NIA NIH HHS R01 AG070949NIEHS NIH HHS R15 ES028000
6 · The paper itself

Abstract

backgroundWhile 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.

methodsDistributed 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

resultsThunderstorms 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,

conclusionThunderstorms 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.

Indexed as

Air PollutantsAir PollutionEmergency Service, HospitalEnvironmental ExposureParticulate MatterRespiratory Tract DiseasesWeatherAdolescentAdultAgedChildFemaleHumansMaleMiddle AgedNew YorkAir PollutantsParticulate Matter

Identifiers

PMID38829734
PMCPMC11166412

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.