Metabolic Syndrome Clinical Trial
Official title:
Developing Health Care Service System Based on Participatory Big Data
"Increased health risks and diseases are believed to be caused by multilevel interactions of genetic and environmental factors (including lifestyle habits). Considering the recent advancements in genetic analysis, wearable devices, and big data analysis techniques, collecting and analyzing personal genetic information, lifelogs, and environmental data and predicting the exact health risks of individuals could be possible.
These changes enable the development of healthcare solutions that allow users to actively
engage in healthcare and provide appropriate care measures to sufficiently delay or prevent
chronic diseases, thereby minimizing the financial losses of the individuals and the society.
In particular, chronic diseases such as metabolic syndrome can be prevented or delayed
through healthy lifestyle habits. Controversy regarding the effectiveness of using wearable
devices and mobile health applications for maintaining lifestyle habits and losing weight
exists. Additionally, a study assessing the health of the participants and the disease
prevention care for the participants using the genetic data and the lifelog data by the
wearable device has not been conducted yet. Therefore, the objective is to operate a
lifestyle correction program for examinees who visited a family medicine and health checkup
center to develop a user-participation health and disease prevention care system using
genetic data and lifelog data. From adults who visited a family medicine and health checkup
center, the following should be performed: (1) collect a variety of clinical information,
including lifestyle data, physical information, metabolic parameters, genetic information,
and metagenomes, which can affect chronic diseases; (2) establish a service model that
combines lifestyle data, examination data, and genetic data and analyzes and identifies one's
health level through a smartphone application; and (3) examine the effects on the metabolic
parameters, lifestyle data, and metagenome (gut microbiome) after using the device (smart
healthcare).This pilot study aimed to provide personalized "my data" by linking clinical data
and personal lifestyle patterns of the participants who visited a family medicine and
examination center.
From adults who visited a family medicine and health check-up center, the following should be
performed:
1. Collect a variety of clinical information, including lifestyle data, physical
information, metabolic parameters, genetic information, and metagenomes, which can
affect chronic diseases
2. Establish a service model that combines lifestyle data, examination data, and genetic
data and analyzes and identifies one's health level through a smartphone application
3. Examine the effects on the metabolic parameters, lifestyle data, and metagenome (gut
microbiome) after using the device (smart healthcare) "
;
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