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Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach

Overview of attention for article published in Environmental Health, November 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

news
1 news outlet
policy
2 policy sources
twitter
3 tweeters

Citations

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58 Dimensions

Readers on

mendeley
135 Mendeley
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Title
Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach
Published in
Environmental Health, November 2015
DOI 10.1186/s12940-015-0071-2
Pubmed ID
Authors

Joel D. Schwartz, Mihye Lee, Patrick L. Kinney, Suijia Yang, David Mills, Marcus C. Sarofim, Russell Jones, Richard Streeter, Alexis St. Juliana, Jennifer Peers, Radley M. Horton

Abstract

A warming climate will affect future temperature-attributable premature deaths. This analysis is the first to project these deaths at a near national scale for the United States using city and month-specific temperature-mortality relationships. We used Poisson regressions to model temperature-attributable premature mortality as a function of daily average temperature in 209 U.S. cities by month. We used climate data to group cities into clusters and applied an Empirical Bayes adjustment to improve model stability and calculate cluster-based month-specific temperature-mortality functions. Using data from two climate models, we calculated future daily average temperatures in each city under Representative Concentration Pathway 6.0. Holding population constant at 2010 levels, we combined the temperature data and cluster-based temperature-mortality functions to project city-specific temperature-attributable premature deaths for multiple future years which correspond to a single reporting year. Results within the reporting periods are then averaged to account for potential climate variability and reported as a change from a 1990 baseline in the future reporting years of 2030, 2050 and 2100. We found temperature-mortality relationships that vary by location and time of year. In general, the largest mortality response during hotter months (April - September) was in July in cities with cooler average conditions. The largest mortality response during colder months (October-March) was at the beginning (October) and end (March) of the period. Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990. However, the magnitude and sign of the change varied by cluster and city. We found increasing future premature deaths across the 209 modeled U.S. cities using two climate model projections, based on constant temperature-mortality relationships from 1997 to 2006 without any future adaptation. However, results varied by location, with some locations showing net reductions in premature temperature-attributable deaths with climate change.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 135 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 20%
Researcher 22 16%
Student > Master 22 16%
Student > Bachelor 13 10%
Other 8 6%
Other 23 17%
Unknown 20 15%
Readers by discipline Count As %
Medicine and Dentistry 17 13%
Earth and Planetary Sciences 16 12%
Environmental Science 15 11%
Engineering 10 7%
Nursing and Health Professions 9 7%
Other 35 26%
Unknown 33 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 15 January 2020.
All research outputs
#1,731,482
of 22,832,057 outputs
Outputs from Environmental Health
#338
of 1,490 outputs
Outputs of similar age
#27,462
of 285,322 outputs
Outputs of similar age from Environmental Health
#3
of 16 outputs
Altmetric has tracked 22,832,057 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,490 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.3. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 285,322 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.