Application of Decision Analysis Techniques' in Huge Health-checkup Database to Explore the High-risk Group With Metabolic Syndrome

NCT04142593 | Completed

• 1 other identifier: 107126-E
• Study Type: observational
• Target: 100,000
• Locations: 1 country
• Sites: 1

Brief Summary

Application of Decision Analysis Techniques' in Huge Health-checkup Database to Explore the High-risk Group With Metabolic Syndrome (MetS)

Conditions

Mets

Keywords

Metabolic Syndrome（MetS）; Classification; Decision Tree; Risk Factors Assessment

Outcome Measures

Primary Outcomes (1)

• analyze the big database of health examination to find out the major decision-making analysis module of MetS

  This study plans to use decision analysis and new statistical techniques, including decision tree algorithms; random forest algorithms; multivariate linear regression combinations and hierarchical linear models, and with a large number of health databases. Analysis, through the comprehensive health check report and physiological indicator data accumulated over many years, find more key variables or physiological indicators that can be used to evaluate MetS or CVD, in order to provide government departments, medical institutions or nationals early Detect or prevent, and further reduce the overall rate of MetS in Taiwan at this stage.

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

As aging society is coming, it is estimated that the elderly people over the age of 65 in Taiwan will reach 20% by 2025. According to the estimation of Executive Yuan, the growth rate of healthcare service industry will reach at least 17%, and the annual output value will reach USD 18 billion. Therefore, this study intends to develop strategies for preventing chronic illness in the middle-aged and elderly people and find out the characteristic variables of high risk group according to different age groups to further reduce the incidence of MetS or CVD.

You may qualify if:

• In 2006-2016, the MJ Health Research Foundation's member,which continuously tested twice or more of the annual health check database , about 90,000 people.
• The person who was in charge of the taxi driver health checkup project commissioned by the New North City Transportation Bureau at Far Eastern Memorial Hospital, data period 2012-2016, about 2,000 people.

Sponsors & Collaborators

• Far Eastern Memorial Hospital: lead

Study Sites (1)

Oriental Institute of Technology / Far Eastern Memorial Hospital

New Taipei City, Pan-Chiao Dist., 22061, Taiwan

Location

Study Officials

• Ming-Shu Chen, PhD

  Oriental Institute of Technology

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: OTHER
• Target Duration: 10 Years
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 18, 2019
• First Posted: October 29, 2019
• Study Start: September 1, 2018
• Primary Completion: September 15, 2019
• Study Completion: January 1, 2022
• Last Updated: March 22, 2022

Record last verified: 2022-01

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)