Evidence map›Paper›PMID 25742021›Full record

ArticlePloS one2015

Identifying individual risk factors and documenting the pattern of heat-related illness through analyses of hospitalization and patterns of household cooling.

Michael T Schmeltz, Grace Sembajwe, Peter J Marcotullio, Jean A Grassman, David U Himmelstein, Stephanie Woolhandler

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Factors That Influence Climate Change-Related Mortality in the United States: An Integrative Review.International journal of environmental research and public health · 2021
    Review
  8. Article
  9. Review
  10. Article
  11. Risk and protective factors for heat-related events among older adults of Southern Quebec (Canada): The NuAge study.Canadian journal of public health = Revue canadienne de sante publique · 2016
    Article
  12. Article
  13. Economic Burden of Hospitalizations for Heat-Related Illnesses in the United States, 2001-2010.International journal of environmental research and public health · 2016
    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

6 authors.

Michael T SchmeltzSchool of Public Health, City University of New York (CUNY), New York, United States of America.
Grace SembajweSchool of Public Health, City University of New York (CUNY), New York, United States of America; Hunter College, City University of New York (CUNY), New York, United States of America.
Peter J MarcotullioHunter College, City University of New York (CUNY), New York, United States of America; CUNY Institute for Sustainable Cities, New York, United States of America.
Jean A GrassmanSchool of Public Health, City University of New York (CUNY), New York, United States of America; Health and Nutrition Sciences, Brooklyn College, City University of New York (CUNY), Brooklyn, NY, United States of America.
David U HimmelsteinSchool of Public Health, City University of New York (CUNY), New York, United States of America; Hunter College, City University of New York (CUNY), New York, United States of America.
Stephanie WoolhandlerSchool of Public Health, City University of New York (CUNY), New York, United States of America; Hunter College, City University of New York (CUNY), New York, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs climate change increases the frequency and intensity of extreme heat events researchers and public health officials must work towards understanding the causes and outcomes of heat-related morbidity and mortality. While there have been many studies on both heat-related illness (HRI), there are fewer on heat-related morbidity than on heat-related mortality.

objectiveTo identify individual and environmental risk factors for hospitalizations and document patterns of household cooling.

methodsWe performed a pooled cross-sectional analysis of secondary U.S. data, the Nationwide Inpatient Sample. Risk ratios were calculated from multivariable models to identify risk factors for hospitalizations. Hierarchical modeling was also employed to identify relationships between individual and hospital level predictors of hospitalizations. Patterns of air conditioning use were analyzed among the vulnerable populations identified.

resultsHospitalizations due to HRI increased over the study period compared to all other hospitalizations. Populations at elevated risk for HRI hospitalization were blacks, males and all age groups above the age of 40. Those living in zip-codes in the lowest income quartile and the uninsured were also at an increased risk. Hospitalizations for HRI in rural and small urban clusters were elevated, compared to urban areas.

conclusionsRisk factors for HRI include age greater than 40, male gender and hospitalization in rural areas or small urban clusters. Our analysis also revealed an increasing pattern of HRI hospitalizations over time and decreased association between common comorbidities and heat illnesses which may be indicative of underreporting.

Indexed as

HospitalizationAdolescentAdultAgedAged, 80 and overChildChild, PreschoolClimate ChangeCross-Sectional StudiesExtreme HeatFemaleHeat Stress DisordersHumansInfantInfant, NewbornMale

Identifiers

PMID25742021
PMCPMC4351173

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LicenceCC BY
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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.