文章基本信息

标题：A Meta-Analysis of Influencing Dietary Interventions on the Metabolic Syndrome Risk Factors Utilizing Big Data
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作者：Ok-kyeong Yu ; Youn-Soo Cha ; Chan-Yong Jin 等
期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2016
卷号：10
期号：9
页码：19-26
DOI：10.14257/ijseia.2016.10.9.03
出版社：SERSC
摘要：Meta-analysis is a statistical integration method that delivers an opportunity to overview the entire result of integrating and analyzing many quantitative research results. Meta-analysis is sometimes expressed as an analysis of another analysis. Commonly, factors of metabolic syndrome can be defined as abdominal obesity, high triglycerides, low high density lipoprotein cholesterol, elevated blood pressure, and elevated fasting glucose. This study will find meaningful mediator variables for criterion variables that affect before and after the metabolic syndrome studies, on the basis of the results of a meta-analysis. We reviewed a total of 15 studies related to metabolic syndrome published in Korea between 1998 and 2016, where a cause and effect relationship is established between variables that are specified in the conceptual model of this study. The result of this meta-analysis, the path between pre and post in the fasting blood glucose showed the biggest effect size (r = -.669). Therefore, the effect of the dietary intervention for the fasting blood glucose shows an explanatory power of 45%. The second biggest effect size (r = -.302) was found in the path between pre and post in the systolic blood pressure. The third biggest effect size (r = -.264) was reported in the path between pre and post in the triglyceride. Also, one of the smallest effect size (r = -.114) was obtained in the path between pre and post in the diastolic blood pressure. Thus, we present the theoretical and practical implications of these results.
关键词：Big data; Meta-analysis; Metabolic syndrome; Diet therapy; Obesity