-
Co-occurrence Network Analysis of Keywords in Geriatric Frailty
-
Young Ji Kim, Soong Nang Jang, Jung Lim Lee
-
J Korean Acad Community Health Nurs. 2018;29(4):429-439. Published online December 31, 2018
-
DOI: https://doi.org/10.12799/jkachn.2018.29.4.429
-
-
1,202
View
-
7
Download
-
3
Citations
-
 Abstract
 PDF
- PURPOSE
The aim of this study is to identify core keyword of frailty research in the past 35 years to understand the structure of knowledge of frailty.
METHODS
10,367 frailty articles published between 1981 and April 2016 were retrieved from Web of Science. Keywords from these articles were extracted using Bibexcel and social network analysis was conducted with the occurrence network using NetMiner program.
RESULTS
The top five keywords with a high frequency of occurrence include ‘disability’, ‘nursing home’, ‘sarcopenia’, ‘exercise’, and ‘dementia’. Keywords were classified by subheadings of MeSH and the majority of them were included under the healthcare and physical dimensions. The degree centralities of the keywords were arranged in the order of ‘long term care’ (0.55), ‘gait’ (0.42), ‘physical activity’ (0.42), ‘quality of life’ (0.42), and ‘physical performance’ (0.38). The betweenness centralities of the keywords were listed in the order of depression’ (0.32), ‘quality of life’ (0.28), ‘home care’ (0.28), ‘geriatric assessment’ (0.28), and ‘fall’ (0.27). The cluster analysis shows that the frailty research field is divided into seven clusters: aging, sarcopenia, inflammation, mortality, frailty index, older people, and physical activity.
CONCLUSION
After reviewing previous research in the 35 years, it has been found that only physical frailty and frailty related to medicine have been emphasized. Further research in psychological, cognitive, social, and environmental frailty is needed to understand frailty in a multifaceted and integrative manner.
-
Citations
Citations to this article as recorded by  - A content analysis of research on technology use for teaching mathematics to students with disabilities: word networks and topic modeling
Mikyung Shin, Min Wook Ok, Sam Choo, Gahangir Hossain, Diane P. Bryant, Eunyoung Kang
International Journal of STEM Education.2023;[Epub] CrossRef - Artificial intelligence in customer relationship management: literature review and future research directions
Cristina Ledro, Anna Nosella, Andrea Vinelli
Journal of Business & Industrial Marketing.2022; 37(13): 48. CrossRef - Mining the sociome for Health Informatics: Analysis of therapeutic lifestyle adherence of diabetic patients in Twitter
Gael Pérez-Rodríguez, Martín Pérez-Pérez, Florentino Fdez-Riverola, Anália Lourenço
Future Generation Computer Systems.2020; 110: 214. CrossRef
-
The Prevalence and Associated Factors of the Metabolic Syndrome in Pre-menopausal Housewives: An Analysis of the 2010~2015 Korean National Health and Nutrition Examination Survey
-
Chul Gyu Kim, Young Ji Kim
-
J Korean Acad Community Health Nurs. 2018;29(1):108-119. Published online March 31, 2018
-
DOI: https://doi.org/10.12799/jkachn.2018.29.1.108
-
-
865
View
-
9
Download
-
4
Citations
-
Abstract
PDF
- PURPOSE
The purpose of this study is to estimate the prevalence of the metabolic syndrome in pre-menopausal housewives and to explore controllable and uncontrollable factors regarding metabolic syndrome.
METHODS
The study population of this cross-sectional survey was from the Korean Health and Nutrition Examination Survey (KHANES) 2010 through 2015, including the fifth and sixth population-based studies. The criteria for metabolic syndrome include waist circumference, blood pressure, fasting plasma glucose, triglyceride, high-density lipoprotein (HDL) based on Korean Clinical Practice Guideline for Metabolic Syndrome by the Korean Academy of Family Medicine 2015.
RESULTS
Among the 2,498 subjects, 247 subjects had metabolic syndrome and the prevalence was estimated to be 9.9%. The number of subjects who met the criterion of HDL was 936 (36.2%), which was the most prevalent among the criteria for metabolic syndrome. Statistically significant (p < .05) factors include age, livinghood benefit group, perceived health status, obesity, family history of DM, sleeping time, awareness of stress,leukocyte, and erythrocyte count. The odds ratio of obesity in the BMI ≥25 group was 12.59 times as high as that of the BMI < 25 group (p < .001) for metabolic syndrome.
CONCLUSION
The prevalence of metabolic syndrome in pre-menopausal housewives in the survey was not low, and it is necessary to develop and apply comprehensive health habit management programs to improve controllable factors including exercise and food intake.
-
Citations
Citations to this article as recorded by - Effect of Household Type on the Prevalence of Metabolic Syndrome in Korea: Using Propensity Score Matching
Jisu Park, Ilsu Park
Healthcare.2022; 10(10): 1894. CrossRef - Comparison of metabolic syndrome and related factors in married pre-menopausal white- and blue-collar woman
Seungmi Park, Chul-Gyu Kim, Youngji Kim
Archives of Environmental & Occupational Health.2022; 77(9): 744. CrossRef - Sociodemographic and Health Characteristics Associated with Metabolic Syndrome in Men and Women Aged ≥50 Years
Goeun Chung, Hye-Sun Jung, Hye-Jin Kim
Metabolic Syndrome and Related Disorders.2021; 19(3): 159. CrossRef - Mental Health Status of Adults with Cardiovascular or Metabolic Diseases by Gender
Yeunhee Kwak, Yoonjung Kim, Soo Jin Kwon, Haekyung Chung
International Journal of Environmental Research and Public Health.2021; 18(2): 514. CrossRef
|
KACHN
