| Peer-Reviewed

Health Information Risk Analysis Based on BMI Fluctuation

Received: 1 December 2020     Accepted: 9 December 2020     Published: 22 December 2020
Views:       Downloads:
Abstract

Obesity is a factor that lowers productivity in companies. In recent years there has been a focus on health management in the management of human resources, including obesity. Actually, as living habits change after people graduate from university and become company employees, a situation arises in which it is easy for obesity to occur from a lack of activity and the accumulation of stress. People therefore need to establish risk management for obesity while they are still university students. However, the concept of obesity as a human resource and the magnitude of that risk are not clear in university students. Since the cutoff value for obesity is not established, if health information on risk due to the degree of obesity were understood, it would perhaps contribute to the facilitation of health management in university students. In this study we assessed the level of health risk based on BMI fluctuations, calculated mean values for health information items for each unit of BMI for BMI values from 14 to 34, and analyzed fluctuations in health information items by analyzing changing trends in each item based on BMI fluctuation. The results showed that blood pressure and maximum oxygen uptake increased risks together with fluctuations in BMI. With this, it is thought that a new cutoff point for obesity risk can be established.

Published in American Journal of Sports Science (Volume 8, Issue 4)
DOI 10.11648/j.ajss.20200804.15
Page(s) 105-110
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Obesity, Health Information, BMI Fluctuation, Cutoff Value

References
[1] T. Furugouri, “Economics of obesity,” Kadokawa Gakugei Shuppan, 2010.
[2] Ministry of Health, Labour and Welfare. “National Health and Nutrition,” https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/kenkou_iryou/kenkou/eiyou/h29-houkoku.html, (accessed 2019. 12).
[3] National Center for Health Statistics (NCHS), “overweight and obesity,” https://www.cdc.gov/obesity/, (accessed 2019. 12).
[4] A. Matsumoto, “Fundamental Properties of Aldehyde Dehydrogenase 2 (ALDH2) and the Importance of the ALDH2 Polymorphism,” Japanese Journal of Hygiene, Vol. 71, No. 1, pp. 55-68, 2016.
[5] M. Asakawa, “Lifestyle Characteristics of Obese people in Terms of Health Checkup Questions,” Journal of Japan Society for the Study of Obesity, Vol. 18, p. 171, 2012.
[6] K. Hayakawa, K. Fujii, K. Kasuya, T. Kondoh and N. Tanaka, “The Estimation for Proper Physical Fitness of Company Employees Derived from Body Composition Balance,” Production Management, 23 (2), pp. 97-102, 2016.
[7] K. Hayakawa, K. Fujii, K. Kasuya, and N. Tanaka, “Productivity of Defense Education Judged from Optimum Validity of Physical Fitness in Defense Employees,” Production Management, 24 (1), pp. 69-74, 2017.
[8] Y. Matsuura and M. Kim, “Analysis of Physical growth by fitting the polynomial to the longitudinal growth distance data of individual – age 6 to 17,” Research Monograph issued by Growth and Development Research institute of Health and Sports Sciences, University of Tsukuba, pp. 1-153, 1991.
[9] R. H. Largo, Th. Gasser, A. Prader, W. Stuetzle, and P. J. Huber, “Analysis of the adolescent growth spurt using smoothing spline functions,” Annals of Human Biology, Volume 5, pp. 421-434, 1978.
[10] K. Fujii, and Y. Matsuura, “Analysis of the growth velocity curve for height by the Wavelet Interpolation Method in children classified by maturity rate,” American Journal of Human Biology, Vol. 11, pp. 13-30, 1999.
[11] K. Fujii, and S. Demura, “Confirmation of Delayed Menarche Based on Regression Evaluation of Age at Menarche for Age at MPV of Height in Female Ball Game Players,” Environmental Health and Preventive Medicine, Vol. 10, pp. 48-54, 2005.
[12] K. Fujii, and Y. Yamamoto, “The analysis of the growth velocity curve in height based upon the maturity rate,” Japan Journal of Physical Fitness and Sports Medicine, Vol. 44, pp. 431-438, 1996.
[13] A. Quetelet, “Sur I’ home et le development de ses faculties,” Essai de physique sociale, Bachelier, Pairs, Vol. 2, 1835.
[14] A. Keys, F. Fidanza, M. J. Karvonen, N. Kimura, and H. L. Taylor, “Indices of relative weight and obesity,” J Chronic Dis, 25, p329-343, 1972.
[15] Y. Matsuzawa and I. Yasuo, “Definition and diagnostic criteria of metabolic syndrome,” Journal of the Japanese Society of Internal Medicine, 94, pp. 794-809, 2005.
[16] K. Fujii, “Essential causal relation of BMI and fat that contributes to female trunk circumference information,” AIT The Review of Business Administration and Computer Science, 12 (1), pp. 19-32, 2017.
[17] T. Kuroki, “Kenko, Rouka, Jumyou (Health, Ageing, lifespan)” Chuokoron-Shinsha, 2007.
[18] Y. Takeyama, K. Fujii, Y. Naito, T. Sakai, and K. Hayakawa, “Risk Analysis of Body Balance by Youth Severe Obesity,” Production Management, 25 (2), pp. 143-148, 2018.
[19] T. Hirohara and K. Hattori, “Blood Pressure and Related Factors in Male High School Students,” Bull. Inst. education, Ibaraki University, Vol. 21, pp. 225-233, 2002.
[20] M. Iwata, K. Takakura, H. Noguchi, S. Matsui, and Y. Yamamoto, “Comparison of blood pressure and lifestyle in the university student of sugitani campus divided according to BMI,” Clinical Study of Campus Life, No. 13, pp. 23-26, 2019.
[21] R. Tsuji, Y. Kodaira, T. Oota, and T. Yahata, “Energy metabolism and autonomic regulatory function in lean female students,” Journal of Japan Health Medicine Association. 13 (1), pp. 11-17, 2004.
[22] S. Demura, “Health sports science lecture,” Tokyo: Kyorin-shoin, 2012.
Cite This Article
  • APA Style

    Yuki Takeyama, Katsunori Fujii. (2020). Health Information Risk Analysis Based on BMI Fluctuation. American Journal of Sports Science, 8(4), 105-110. https://doi.org/10.11648/j.ajss.20200804.15

    Copy | Download

    ACS Style

    Yuki Takeyama; Katsunori Fujii. Health Information Risk Analysis Based on BMI Fluctuation. Am. J. Sports Sci. 2020, 8(4), 105-110. doi: 10.11648/j.ajss.20200804.15

    Copy | Download

    AMA Style

    Yuki Takeyama, Katsunori Fujii. Health Information Risk Analysis Based on BMI Fluctuation. Am J Sports Sci. 2020;8(4):105-110. doi: 10.11648/j.ajss.20200804.15

    Copy | Download

  • @article{10.11648/j.ajss.20200804.15,
      author = {Yuki Takeyama and Katsunori Fujii},
      title = {Health Information Risk Analysis Based on BMI Fluctuation},
      journal = {American Journal of Sports Science},
      volume = {8},
      number = {4},
      pages = {105-110},
      doi = {10.11648/j.ajss.20200804.15},
      url = {https://doi.org/10.11648/j.ajss.20200804.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajss.20200804.15},
      abstract = {Obesity is a factor that lowers productivity in companies. In recent years there has been a focus on health management in the management of human resources, including obesity. Actually, as living habits change after people graduate from university and become company employees, a situation arises in which it is easy for obesity to occur from a lack of activity and the accumulation of stress. People therefore need to establish risk management for obesity while they are still university students. However, the concept of obesity as a human resource and the magnitude of that risk are not clear in university students. Since the cutoff value for obesity is not established, if health information on risk due to the degree of obesity were understood, it would perhaps contribute to the facilitation of health management in university students. In this study we assessed the level of health risk based on BMI fluctuations, calculated mean values for health information items for each unit of BMI for BMI values from 14 to 34, and analyzed fluctuations in health information items by analyzing changing trends in each item based on BMI fluctuation. The results showed that blood pressure and maximum oxygen uptake increased risks together with fluctuations in BMI. With this, it is thought that a new cutoff point for obesity risk can be established.},
     year = {2020}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Health Information Risk Analysis Based on BMI Fluctuation
    AU  - Yuki Takeyama
    AU  - Katsunori Fujii
    Y1  - 2020/12/22
    PY  - 2020
    N1  - https://doi.org/10.11648/j.ajss.20200804.15
    DO  - 10.11648/j.ajss.20200804.15
    T2  - American Journal of Sports Science
    JF  - American Journal of Sports Science
    JO  - American Journal of Sports Science
    SP  - 105
    EP  - 110
    PB  - Science Publishing Group
    SN  - 2330-8540
    UR  - https://doi.org/10.11648/j.ajss.20200804.15
    AB  - Obesity is a factor that lowers productivity in companies. In recent years there has been a focus on health management in the management of human resources, including obesity. Actually, as living habits change after people graduate from university and become company employees, a situation arises in which it is easy for obesity to occur from a lack of activity and the accumulation of stress. People therefore need to establish risk management for obesity while they are still university students. However, the concept of obesity as a human resource and the magnitude of that risk are not clear in university students. Since the cutoff value for obesity is not established, if health information on risk due to the degree of obesity were understood, it would perhaps contribute to the facilitation of health management in university students. In this study we assessed the level of health risk based on BMI fluctuations, calculated mean values for health information items for each unit of BMI for BMI values from 14 to 34, and analyzed fluctuations in health information items by analyzing changing trends in each item based on BMI fluctuation. The results showed that blood pressure and maximum oxygen uptake increased risks together with fluctuations in BMI. With this, it is thought that a new cutoff point for obesity risk can be established.
    VL  - 8
    IS  - 4
    ER  - 

    Copy | Download

Author Information
  • Graduate School of Business Administration and Computer Science, Aichi Institute of Technology, Aichi-prefecture, Japan

  • Graduate School of Business Administration and Computer Science, Aichi Institute of Technology, Aichi-prefecture, Japan

  • Sections