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Developing a Health Risk Evaluation Method for Triple H

Author

Listed:
  • Chien-Chih Wang

    (Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei 24301, Taiwan)

  • Cheng-Ding Chang

    (Department of Industrial Engineering and Management, Yuan Ze University, Chung-Li 32003, Taiwan)

  • Bernard C. Jiang

    (Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan)

Abstract

The development of a health evaluation system from human-related data is an important issue in preventive medicine. Previously, most studies have focused on disease assessment and prevention in patients. However, even if certain risk factors are all within normal ranges, individuals may not necessarily be completely healthy. This study focused on healthy individuals to develop a new index to assess health risks; this index can be used for the prevention of multiple diseases in healthy people. The kernel density technique was proposed to estimate the distribution of common risk factors and to develop a health risk index. A dataset of hypertension, hyperlipidemia, and hyperglycemia (Triple H) data from the National Health Insurance Research Database in Taiwan was used to demonstrate the proposed analytical process. The results of risk factor changes after six weeks of exercise were used to calculate the health risk index. The results showed that the subjects experienced a 7.29% reduction in their health risk index after the exercise intervention. This finding demonstrates the potential impact of an important reference index on quantifying the effect of maintenance in healthy people.

Suggested Citation

  • Chien-Chih Wang & Cheng-Ding Chang & Bernard C. Jiang, 2019. "Developing a Health Risk Evaluation Method for Triple H," IJERPH, MDPI, vol. 16(7), pages 1-12, April.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1168-:d:218893
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    References listed on IDEAS

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    1. Liberatore, Matthew J. & Nydick, Robert L., 2008. "The analytic hierarchy process in medical and health care decision making: A literature review," European Journal of Operational Research, Elsevier, vol. 189(1), pages 194-207, August.
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