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Cholesterol testing among men and women with disability: the role of morbidity

Overview of attention for article published in Clinical Epidemiology, September 2016
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Title
Cholesterol testing among men and women with disability: the role of morbidity
Published in
Clinical Epidemiology, September 2016
DOI 10.2147/clep.s108761
Pubmed ID
Authors

Aisha K Lofters, Sara Jt Guilcher, Lauren Webster, Richard H Glazier, Susan B Jaglal, Ahmed M Bayoumi

Abstract

Despite more frequent use of health services by people living with disability, the quality of preventive care received may be suboptimal. In this retrospective cohort study, we used administrative data to examine the relationship between cholesterol testing and levels of disability and morbidity among women and men in Ontario, Canada. We linked multiple provincial-level databases in this study. In stratified analyses for women and men, we used multivariable logistic regression to examine differences in cholesterol testing, and we tested for an interaction effect between disability and morbidity. In a secondary analysis, we tested for a three-way interaction between sex, disability, and morbidity on the entire cohort. There was an interaction between morbidity and disability for both women and men. Women and men with no chronic conditions appeared to be least likely to be up-to-date on cholesterol testing, and among this group, those with moderate disability were more likely to be up-to-date on cholesterol testing than those with no disability (adjusted odds ratio [AOR] =1.51; 95% confidence interval [CI] 1.20-1.90 for women; AOR =1.16; 95% CI 1.00-1.34 for men). Among women and men who had one chronic condition, having severe disability put them at significant disadvantage versus those with no disability. Only 58.5% of men with no disability and no chronic conditions were up-to-date on cholesterol testing. An intermediate level of health care need (reflected in this study as level of disability and level of morbidity) may provide a benefit for cholesterol testing, and conversely, health care needs that are too few or too great may negatively affect testing. Public health and practice-based interventions need to be explored to address these findings.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 14%
Researcher 2 14%
Student > Doctoral Student 1 7%
Student > Ph. D. Student 1 7%
Other 1 7%
Other 0 0%
Unknown 7 50%
Readers by discipline Count As %
Medicine and Dentistry 3 21%
Nursing and Health Professions 1 7%
Arts and Humanities 1 7%
Psychology 1 7%
Agricultural and Biological Sciences 1 7%
Other 0 0%
Unknown 7 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 September 2016.
All research outputs
#18,345,259
of 23,577,654 outputs
Outputs from Clinical Epidemiology
#558
of 742 outputs
Outputs of similar age
#246,884
of 339,606 outputs
Outputs of similar age from Clinical Epidemiology
#14
of 23 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 742 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 339,606 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.