| Title |
Combined effects of sleep quality and depression on quality of life in patients with type 2 diabetes
|
|---|---|
| Published in |
BMC Primary Care, April 2016
|
| DOI | 10.1186/s12875-016-0435-x |
| Pubmed ID | |
| Authors |
Pan Zhang, Peian Lou, Guiqiu Chang, Peipei Chen, Lei Zhang, Ting Li, Cheng Qiao |
| Abstract |
Poor sleep quality and depression negatively impact the health-related quality of life of patients with type 2 diabetes, but the combined effect of the two factors is unknown. This study aimed to assess the interactive effects of poor sleep quality and depression on the quality of life in patients with type 2 diabetes. Patients with type 2 diabetes (n = 944) completed the Diabetes Specificity Quality of Life scale (DSQL) and questionnaires on sleep quality and depression. The products of poor sleep quality and depression were added to the logistic regression model to evaluate their multiplicative interactions, which were expressed as the relative excess risk of interaction (RERI), the attributable proportion (AP) of interaction, and the synergy index (S). Poor sleep quality and depressive symptoms both increased DSQL scores. The co-presence of poor sleep quality and depressive symptoms significantly reduced DSQL scores by a factor of 3.96 on biological interaction measures. The relative excess risk of interaction was 1.08. The combined effect of poor sleep quality and depressive symptoms was observed only in women. Patients with both depressive symptoms and poor sleep quality are at an increased risk of reduction in diabetes-related quality of life, and this risk is particularly high for women due to the interaction effect. Clinicians should screen for and treat sleep difficulties and depressive symptoms in patients with type 2 diabetes. |
X Demographics
The data shown below were collected from the profiles of 8 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 | 2 | 25% |
| Australia | 1 | 13% |
| Unknown | 5 | 63% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Practitioners (doctors, other healthcare professionals) | 2 | 25% |
| Scientists | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 129 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 26 | 20% |
| Student > Bachelor | 24 | 19% |
| Researcher | 10 | 8% |
| Other | 8 | 6% |
| Lecturer | 7 | 5% |
| Other | 19 | 15% |
| Unknown | 35 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 26 | 20% |
| Medicine and Dentistry | 22 | 17% |
| Psychology | 12 | 9% |
| Agricultural and Biological Sciences | 6 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 4% |
| Other | 12 | 9% |
| Unknown | 46 | 36% |
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 13 April 2016.
All research outputs
#7,301,532
of 25,371,288 outputs
Outputs from BMC Primary Care
#955
of 2,359 outputs
Outputs of similar age
#97,827
of 315,549 outputs
Outputs of similar age from BMC Primary Care
#16
of 26 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 2,359 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 59% 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 315,549 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.