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Use of primary care data to predict those most vulnerable to cold weather: a case-crossover analysis

Overview of attention for article published in British Journal of General Practice, January 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
6 news outlets
blogs
2 blogs
twitter
29 tweeters
facebook
1 Facebook page

Readers on

mendeley
3 Mendeley
Title
Use of primary care data to predict those most vulnerable to cold weather: a case-crossover analysis
Published in
British Journal of General Practice, January 2018
DOI 10.3399/bjgp18x694829
Pubmed ID
Authors

Peter Tammes, Claudio Sartini, Ian Preston, Alastair D Hay, Daniel Lasserson, Richard W Morris

Abstract

The National Institute for Health and Care Excellence (NICE) recommends that GPs use routinely available data to identify patients most at risk of death and ill health from living in cold homes. To investigate whether sociodemographic characteristics, clinical factors, and house energy efficiency characteristics could predict cold-related mortality. A case-crossover analysis was conducted on 34 777 patients aged ≥65 years from the Clinical Practice Research Datalink who died between April 2012 and March 2014. The average temperature of date of death and 3 days previously were calculated from Met Office data. The average 3-day temperature for the 28th day before/after date of death were calculated, and comparisons were made between these temperatures and those experienced around the date of death. Conditional logistic regression was applied to estimate the odds ratio (OR) of death associated with temperature and interactions between temperature and sociodemographic characteristics, clinical factors, and house energy efficiency characteristics, expressed as relative odds ratios (RORs). Lower 3-day temperature was associated with higher risk of death (OR 1.011 per 1°C fall; 95% CI = 1.007 to 1.015; P<0.001). No modifying effects were observed for sociodemographic characteristics, clinical factors, and house energy efficiency characteristics. Analysis of winter deaths for causes typically associated with excess winter mortality (N = 7710) showed some evidence of a weaker effect of lower 3-day temperature for females (ROR 0.980 per 1°C, 95% CI = 0.959 to 1.002, P = 0.082), and a stronger effect for patients living in northern England (ROR 1.040 per 1°C, 95% CI = 1.013 to 1.066, P = 0.002). It is unlikely that GPs can identify older patients at highest risk of cold-related death using routinely available data, and NICE may need to refine its guidance.

Twitter Demographics

The data shown below were collected from the profiles of 29 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 33%
Student > Bachelor 1 33%
Unspecified 1 33%
Readers by discipline Count As %
Unspecified 1 33%
Biochemistry, Genetics and Molecular Biology 1 33%
Earth and Planetary Sciences 1 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 74. 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 06 April 2018.
All research outputs
#153,426
of 9,684,510 outputs
Outputs from British Journal of General Practice
#63
of 2,209 outputs
Outputs of similar age
#8,260
of 249,948 outputs
Outputs of similar age from British Journal of General Practice
#7
of 99 outputs
Altmetric has tracked 9,684,510 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,209 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one has done particularly well, scoring higher than 97% 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 249,948 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 96% of its contemporaries.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.