A scalable climate health justice assessment model. (May 2015)
- Record Type:
- Journal Article
- Title:
- A scalable climate health justice assessment model. (May 2015)
- Main Title:
- A scalable climate health justice assessment model
- Authors:
- McDonald, Yolanda J.
Grineski, Sara E.
Collins, Timothy W.
Kim, Young-An - Abstract:
- 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 heatAbstract: 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. Highlights: Introduces climate health justice model to assess climate change-related diseases. Model is transferable, adaptable, and suitable for comparative purposes. Model application reveals social and spatial health disparities in Texas. Model emphasizes reduction of disparities to achieve climate health justice. … (more)
- Is Part Of:
- Social science & medicine. Volume 133(2015)
- Journal:
- Social science & medicine
- Issue:
- Volume 133(2015)
- Issue Display:
- Volume 133, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 133
- Issue:
- 2015
- Issue Sort Value:
- 2015-0133-2015-0000
- Page Start:
- 242
- Page End:
- 252
- Publication Date:
- 2015-05
- Subjects:
- Texas, United states -- Disease mapping -- Climate change -- Climate gap -- Climate health justice -- Heath disparities -- Health inequalities -- Health surveillance
Social medicine -- Periodicals
Medical anthropology -- Periodicals
Public health -- Periodicals
Psychology -- Periodicals
Medicine -- Periodicals
Medicine -- Periodicals
Médecine sociale -- Périodiques
Anthropologie médicale -- Périodiques
Santé publique -- Périodiques
Psychologie -- Périodiques
Médecine -- Périodiques
Electronic journals
362.105 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02779536 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.socscimed.2014.10.032 ↗
- Languages:
- English
- ISSNs:
- 0277-9536
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8318.157000
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