| Title |
Vulnerability to renal, heat and respiratory hospitalizations during extreme heat among U.S. elderly
|
|---|---|
| Published in |
Climatic Change, March 2016
|
| DOI | 10.1007/s10584-016-1638-9 |
| Pubmed ID | |
| Authors |
Carina J. Gronlund, Antonella Zanobetti, Gregory A. Wellenius, Joel D. Schwartz, Marie S. O’Neill |
| Abstract |
Extreme heat (EH) is a growing concern with climate change, and protecting human health requires knowledge of vulnerability factors. We evaluated whether associations between EH (maximum temperature > 97th percentile) and hospitalization for renal, heat and respiratory diseases among people ≥ 65 years differed by individual and area-level characteristics. We used Medicare billing records, airport weather data, U.S. Census data and satellite land cover imagery in 109 US cities, May-September, 1992-2006, in a time-stratified case-crossover design. Interaction terms between EH and individual (> 78 years, black race, sex) and home ZIP-code (percentages of non-green space, high school education, housing built before 1940) characteristics were incorporated in a single model. Next, we pooled city-specific effect estimates or regressed them on quartiles of air conditioning prevalence (ACP) in a multivariate random effects meta-analysis. EH and combined renal/heat/respiratory hospitalization associations were stronger among blacks, the very old, in ZIP codes with lower educational attainment or older housing and in cities with lower ACP. For example, for EH versus non-heat days, we found a 15% (95% CI 11%-19%) increase in renal/heat/respiratory hospitalizations among individuals in ZIP codes with higher percent of older homes in contrast to a 9% (95% CI 6%-12%) increase in hospitalizations in ZIP codes with lower percent older homes. Vulnerability to EH-associated hospitalization may be influenced by age, educational attainment, housing age and ACP. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 194 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 194 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 35 | 18% |
| Student > Ph. D. Student | 31 | 16% |
| Student > Master | 22 | 11% |
| Student > Doctoral Student | 10 | 5% |
| Professor | 8 | 4% |
| Other | 27 | 14% |
| Unknown | 61 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 33 | 17% |
| Social Sciences | 18 | 9% |
| Medicine and Dentistry | 15 | 8% |
| Earth and Planetary Sciences | 10 | 5% |
| Engineering | 10 | 5% |
| Other | 34 | 18% |
| Unknown | 74 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 January 2020.
All research outputs
#6,649,027
of 25,109,675 outputs
Outputs from Climatic Change
#3,572
of 6,002 outputs
Outputs of similar age
#85,358
of 305,240 outputs
Outputs of similar age from Climatic Change
#43
of 65 outputs
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