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The association of depression and diabetes across methods, measures, and study contexts

Overview of attention for article published in Clinical Diabetes and Endocrinology, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

news
1 news outlet
twitter
4 tweeters

Citations

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14 Dimensions

Readers on

mendeley
48 Mendeley
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Title
The association of depression and diabetes across methods, measures, and study contexts
Published in
Clinical Diabetes and Endocrinology, January 2018
DOI 10.1186/s40842-017-0052-1
Pubmed ID
Authors

Jaimie C. Hunter, Brenda M. DeVellis, Joanne M. Jordan, M. Sue Kirkman, Laura A. Linnan, Christine Rini, Edwin B. Fisher

Abstract

Empirical research has revealed a positive relationship between type 2 diabetes mellitus and depression, but questions remain regarding timing of depression measurement, types of instruments used to measure depression, and whether "depression" is defined as clinical depression or depressive symptoms. The present study sought to establish the robustness of the depression-diabetes relationship across depression definition, severity of depressive symptoms, recent depression, and lifetime depression in a nationally representative dataset and a large rural dataset. The present examination, conducted between 2014 and 2015, used two large secondary datasets: the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2008 (n = 3072) and the Arthritis, Coping, and Emotion Study (ACES) from 2002 to 2006 (n = 2300). Depressive symptoms in NHANES were measured using the Patient Health Questionnaire 9-item survey (PHQ-9). ACES used the Center for Epidemiologic Studies-Depression Scale (CES-D) to measure depressive symptoms and the Composite International Diagnostic Interview (CIDI) to measure diagnosable depression. Diabetes was modelled as the dichotomous outcome variable (presence vs. absence of diabetes). Logistic regression was used for all analyses, most of which were cross-sectional. Analyses controlled for age, ethnicity, sex, education, and body mass index, and NHANES analyses used sample weights to account for the complex survey design. Additional analyses using NHANES data focused on the addition of health behavior variables and inflammation to the model. NHANES. Every one-point increase in depressive symptoms was associated with a 5% increase in odds of having diabetes [OR: 1.05 (CI: 1.03, 1.07)]. These findings persisted after controlling for health behaviors and inflammation. ACES. For every one-point increase in depressive symptom score, odds of having diabetes increased by 2% [OR: 1.02 (CI: 1.01, 1.03)]. Recent (past 12 months) depression [OR: 1.49, (CI: 1.03, 2.13)] and lifetime depression [OR: 1.40 (CI: 1.09, 1.81)] were also significantly associated with having diabetes. This study provides evidence for the robustness of the relationship between depression or depressive symptoms and diabetes and demonstrates that depression occurring over the lifetime can be associated with diabetes just as robustly as that which occurs more proximal to the time of study measurement.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 17%
Student > Master 7 15%
Student > Ph. D. Student 4 8%
Student > Doctoral Student 4 8%
Student > Postgraduate 3 6%
Other 9 19%
Unknown 13 27%
Readers by discipline Count As %
Medicine and Dentistry 14 29%
Psychology 8 17%
Nursing and Health Professions 3 6%
Agricultural and Biological Sciences 3 6%
Social Sciences 2 4%
Other 7 15%
Unknown 11 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 August 2019.
All research outputs
#1,629,211
of 15,659,679 outputs
Outputs from Clinical Diabetes and Endocrinology
#7
of 54 outputs
Outputs of similar age
#59,011
of 406,415 outputs
Outputs of similar age from Clinical Diabetes and Endocrinology
#3
of 6 outputs
Altmetric has tracked 15,659,679 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 54 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done well, scoring higher than 87% 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 406,415 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.