| Title |
Sasang constitutional types for the risk prediction of metabolic syndrome: a 14-year longitudinal prospective cohort study
|
|---|---|
| Published in |
BMC Complementary Medicine and Therapies, September 2017
|
| DOI | 10.1186/s12906-017-1936-4 |
| Pubmed ID | |
| Authors |
Sunghee Lee, Seung Ku Lee, Jong Yeol Kim, Namhan Cho, Chol Shin |
| Abstract |
To examine whether the use of Sasang constitutional (SC) types, such as Tae-yang (TY), Tae-eum (TE), So-yang (SY), and So-eum (SE) types, increases the accuracy of risk prediction for metabolic syndrome. From 2001 to 2014, 3529 individuals aged 40 to 69 years participated in a longitudinal prospective cohort. The Cox proportional hazard model was utilized to predict the risk of developing metabolic syndrome. During the 14 year follow-up, 1591 incident events of metabolic syndrome were observed. Individuals with TE type had higher body mass indexes and waist circumferences than individuals with SY and SE types. The risk of developing metabolic syndrome was the highest among individuals with the TE type, followed by the SY type and the SE type. When the prediction risk models for incident metabolic syndrome were compared, the area under the curve for the model using SC types was significantly increased to 0.8173. Significant predictors for incident metabolic syndrome were different according to the SC types. For individuals with the TE type, the significant predictors were age, sex, body mass index (BMI), education, smoking, drinking, fasting glucose level, high-density lipoprotein (HDL) cholesterol level, systolic and diastolic blood pressure, and triglyceride level. For Individuals with the SE type, the predictors were sex, smoking, fasting glucose, HDL cholesterol level, systolic and diastolic blood pressure, and triglyceride level, while the predictors in individuals with the SY type were age, sex, BMI, smoking, drinking, total cholesterol level, fasting glucose level, HDL cholesterol level, systolic and diastolic blood pressure, and triglyceride level. In this prospective cohort study among 3529 individuals, we observed that utilizing the SC types significantly increased the accuracy of the risk prediction for the development of metabolic syndrome. |
X Demographics
The data shown below were collected from the profiles of 3 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 States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 19% |
| Student > Master | 3 | 14% |
| Researcher | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Lecturer | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 8 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 19% |
| Medicine and Dentistry | 3 | 14% |
| Nursing and Health Professions | 2 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 8 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 09 September 2017.
All research outputs
#14,574,585
of 23,342,092 outputs
Outputs from BMC Complementary Medicine and Therapies
#1,716
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Outputs of similar age
#176,761
of 317,178 outputs
Outputs of similar age from BMC Complementary Medicine and Therapies
#40
of 100 outputs
Altmetric has tracked 23,342,092 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,682 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.