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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Interrelationships among common symptoms in the elderly and their effects on health-related quality of life: a cross-sectional study in rural Korea
|
|---|---|
| Published in |
Health and Quality of Life Outcomes, October 2016
|
| DOI | 10.1186/s12955-016-0549-9 |
| Pubmed ID | |
| Authors |
Sujeong Mun, Kihyun Park, Younghwa Baek, Siwoo Lee, Jong-hyang Yoo |
| Abstract |
Because the world population is aging, it has become increasingly important to focus on and meet the healthcare needs of elderly individuals. This study aims to evaluate the relationships among common symptoms experienced by the elderly, including fatigue, pain, sleep disturbance, indigestion, and depression/anger/anxiety, and to assess how these symptoms affect health-related quality of life (HRQoL) in the elderly population after adjusting for sociodemographic characteristics and diagnosed diseases. In a cross-sectional study conducted in 2014 in a rural area of Korea, we extracted data on 1328 elderly individuals aged 60 years or older. Their HRQoL was assessed using the EuroQol Five-Dimension (EQ-5D) questionnaire. The pairwise associations between each symptom and the influence of the symptoms on HRQoL were measured using logistic regression and multiple regression analysis. Each symptom was positively correlated with the other symptoms. The strongest association was observed between fatigue and pain (adjusted odds ratio = 8.127), and the weakest correlation was observed between sleep and indigestion (adjusted odds ratio = 2.521). Of the individuals experiencing symptoms other than sleep disturbance, those who reported comorbid symptoms tended to report higher symptom severity and a higher prevalence of symptoms persisting for ≥ 3 days compared with individuals who reported only one symptom. The number of symptoms was significantly correlated with the EQ-5D index (Spearman correlation coefficient = -0.370, p < 0.01) and the EQ Visual Analog Scale (EQ VAS) scores (Spearman correlation coefficient = -0.226, p < 0.01). Fatigue, pain, and sleep disturbance showed negative effects on all dimensions of EQ-5D. In multiple regression analysis, fatigue (β = -0.073, p < 0.01), pain (β = -0.140, p < 0.01), sleep disturbance (β = -0.061, p < 0.05), and depression/anger/anxiety (β = -0.065, p < 0.05) showed significant independent effects on the EQ-5D index when we adjusted for socioeconomic characteristics and diagnosed diseases. Fatigue, pain, sleep disturbance, and depression/anger/anxiety were correlated with one another, and they presented significant independent effects on the HRQoL of elderly individuals. Thus, multidisciplinary healthcare programs are required to address these common symptoms. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 74 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 10 | 14% |
| Student > Ph. D. Student | 9 | 12% |
| Researcher | 7 | 9% |
| Student > Master | 7 | 9% |
| Student > Bachelor | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 27 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 22% |
| Nursing and Health Professions | 5 | 7% |
| Social Sciences | 4 | 5% |
| Psychology | 3 | 4% |
| Sports and Recreations | 3 | 4% |
| Other | 10 | 14% |
| Unknown | 33 | 45% |
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 14 October 2016.
All research outputs
#17,820,151
of 22,893,031 outputs
Outputs from Health and Quality of Life Outcomes
#1,469
of 2,160 outputs
Outputs of similar age
#228,050
of 319,475 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#21
of 40 outputs
Altmetric has tracked 22,893,031 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 2,160 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 22nd percentile – i.e., 22% 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 319,475 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.