Evidence map›Paper›PMID 25459205›Full record

ArticleSocial science & medicine (1982)2015

A scalable climate health justice assessment model.

Yolanda J McDonald, Sara E Grineski, Timothy W Collins, Young-An Kim

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 23% of its field
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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Economic Burden of Hospitalizations for Heat-Related Illnesses in the United States, 2001-2010.International journal of environmental research and public health · 2016
    Article
  8. 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

4 authors at 3 institutions in 1 country.

Yolanda J McDonaldCollege of GeoSciences, Department of Geography, Texas A&M University, MS 3147, College Station, TX 77843, USA. Electronic address: ymcdonald77@tamu.edu.
Sara E GrineskiDepartment of Sociology and Anthropology, The University of Texas at El Paso, USA.
Timothy W CollinsDepartment of Sociology and Anthropology, The University of Texas at El Paso, USA.
Young-An KimSchool of Social Ecology, Department of Criminology, Law and Society, University of California, Irvine, USA.
The University of Texas at El Paso · USTexas A&M University · USUniversity of California, Irvine · US

Funding

RESEARCH TRAINING COREP20MD002287 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI PROVENCIO-VASQUEZ, ELIAS · 2007 to 2012
$7.6M
NIMHD NIH HHS P20 MD002287
6 · The paper itself

Abstract

This paper introduces a scalable "climate health justice" model for assessing and projecting incidence, treatment costs, and sociospatial disparities for diseases with well-documented climate change linkages. The model is designed to employ low-cost secondary data, and it is rooted in a perspective that merges normative environmental justice concerns with theoretical grounding in health inequalities. Since the model employs International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) disease codes, it is transferable to other contexts, appropriate for use across spatial scales, and suitable for comparative analyses. We demonstrate the utility of the model through analysis of 2008-2010 hospitalization discharge data at state and county levels in Texas (USA). We identified several disease categories (i.e., cardiovascular, gastrointestinal, heat-related, and respiratory) associated with climate change, and then selected corresponding ICD-9 codes with the highest hospitalization counts for further analyses. Selected diseases include ischemic heart disease, diarrhea, heat exhaustion/cramps/stroke/syncope, and asthma. Cardiovascular disease ranked first among the general categories of diseases for age-adjusted hospital admission rate (5286.37 per 100,000). In terms of specific selected diseases (per 100,000 population), asthma ranked first (517.51), followed by ischemic heart disease (195.20), diarrhea (75.35), and heat exhaustion/cramps/stroke/syncope (7.81). Charges associated with the selected diseases over the 3-year period amounted to US$5.6 billion. Blacks were disproportionately burdened by the selected diseases in comparison to non-Hispanic whites, while Hispanics were not. Spatial distributions of the selected disease rates revealed geographic zones of disproportionate risk. Based upon a downscaled regional climate-change projection model, we estimate a >5% increase in the incidence and treatment costs of asthma attributable to climate change between the baseline and 2040-2050 in Texas. Additionally, the inequalities described here will be accentuated, with blacks facing amplified health disparities in the future. These predicted trends raise both intergenerational and distributional climate health justice concerns.

Indexed as

Climate ChangeHealth Status DisparitiesSocial JusticeAsthmaBlack or African AmericanHealth Care CostsHealthcare DisparitiesHealth Impact AssessmentHospitalizationHumansInternational Classification of DiseasesModels, TheoreticalMorbidityPublic Health SurveillanceStrokeTexasClimate changeClimate gapClimate health justiceDisease mappingHealth inequalitiesHealth surveillanceHeath disparitiesTexas, United states

Identifiers

PMID25459205
PMCPMC4402103
OpenAlexW1983736152

What OpenQuestion holds

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Registered trials

None linked

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.