IEICE TRANSACTIONS on Information
Health Checkup Data Analysis Focusing on Body Mass Index
Summary :
This paper analyzes the relationship between the changes of Body Mass Index (BMI) and those of the other health checkup data in one year. We divide all data of the subjects into 13 groups by their BMI changes. We calculate these variations in each group and classify the variations into gender, age, and BMI. As the result by gender, men were more influenced by the changes of BMI than women at Hb-A1c, AC, GPT, GTP, and TG. As the result of classification by age, they were influenced by the changes of BMI at Hb-A1c, GPT, and DTP by age. As the result of classification by BMI, inspection values such as GOT, GPT, and GTP decreased according to the decrement of BMI. Next we show the result on gender-age, gender-BMI, and age-BMI clusters. Our results showed that subjects should reduce BMI values in order to improve lifestyle-related diseases. Several inspection values would be improved according to decrement of BMI. Conversely, it may be difficult for subjects with under 18 of BMI to manage them by BMI. We show a possibility that we could prevent the lifestyle disease by controlling BMI.
- Publication
- IEICE TRANSACTIONS on Information Vol.E100-D No.8 pp.1634-1641
- Publication Date
- 2017/08/01
- Publicized
- 2017/05/19
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016LOP0009
- Type of Manuscript
- Special Section PAPER (Special Section on Multiple-Valued Logic and VLSI Computing)
- Category
- Soft Computing
Authors
Mizuki HIGUCHI
University of Hyogo
Kenichi SORACHI
Sorachi Naikain
Yutaka HATA
University of Hyogo
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Mizuki HIGUCHI, Kenichi SORACHI, Yutaka HATA, "Health Checkup Data Analysis Focusing on Body Mass Index" in IEICE TRANSACTIONS on Information,
vol. E100-D, no. 8, pp. 1634-1641, August 2017, doi: 10.1587/transinf.2016LOP0009.
Abstract: This paper analyzes the relationship between the changes of Body Mass Index (BMI) and those of the other health checkup data in one year. We divide all data of the subjects into 13 groups by their BMI changes. We calculate these variations in each group and classify the variations into gender, age, and BMI. As the result by gender, men were more influenced by the changes of BMI than women at Hb-A1c, AC, GPT, GTP, and TG. As the result of classification by age, they were influenced by the changes of BMI at Hb-A1c, GPT, and DTP by age. As the result of classification by BMI, inspection values such as GOT, GPT, and GTP decreased according to the decrement of BMI. Next we show the result on gender-age, gender-BMI, and age-BMI clusters. Our results showed that subjects should reduce BMI values in order to improve lifestyle-related diseases. Several inspection values would be improved according to decrement of BMI. Conversely, it may be difficult for subjects with under 18 of BMI to manage them by BMI. We show a possibility that we could prevent the lifestyle disease by controlling BMI.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016LOP0009/_p
Copy
@ARTICLE{e100-d_8_1634,
author={Mizuki HIGUCHI, Kenichi SORACHI, Yutaka HATA, },
journal={IEICE TRANSACTIONS on Information},
title={Health Checkup Data Analysis Focusing on Body Mass Index},
year={2017},
volume={E100-D},
number={8},
pages={1634-1641},
abstract={This paper analyzes the relationship between the changes of Body Mass Index (BMI) and those of the other health checkup data in one year. We divide all data of the subjects into 13 groups by their BMI changes. We calculate these variations in each group and classify the variations into gender, age, and BMI. As the result by gender, men were more influenced by the changes of BMI than women at Hb-A1c, AC, GPT, GTP, and TG. As the result of classification by age, they were influenced by the changes of BMI at Hb-A1c, GPT, and DTP by age. As the result of classification by BMI, inspection values such as GOT, GPT, and GTP decreased according to the decrement of BMI. Next we show the result on gender-age, gender-BMI, and age-BMI clusters. Our results showed that subjects should reduce BMI values in order to improve lifestyle-related diseases. Several inspection values would be improved according to decrement of BMI. Conversely, it may be difficult for subjects with under 18 of BMI to manage them by BMI. We show a possibility that we could prevent the lifestyle disease by controlling BMI.},
keywords={},
doi={10.1587/transinf.2016LOP0009},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - Health Checkup Data Analysis Focusing on Body Mass Index
T2 - IEICE TRANSACTIONS on Information
SP - 1634
EP - 1641
AU - Mizuki HIGUCHI
AU - Kenichi SORACHI
AU - Yutaka HATA
PY - 2017
DO - 10.1587/transinf.2016LOP0009
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2017
AB - This paper analyzes the relationship between the changes of Body Mass Index (BMI) and those of the other health checkup data in one year. We divide all data of the subjects into 13 groups by their BMI changes. We calculate these variations in each group and classify the variations into gender, age, and BMI. As the result by gender, men were more influenced by the changes of BMI than women at Hb-A1c, AC, GPT, GTP, and TG. As the result of classification by age, they were influenced by the changes of BMI at Hb-A1c, GPT, and DTP by age. As the result of classification by BMI, inspection values such as GOT, GPT, and GTP decreased according to the decrement of BMI. Next we show the result on gender-age, gender-BMI, and age-BMI clusters. Our results showed that subjects should reduce BMI values in order to improve lifestyle-related diseases. Several inspection values would be improved according to decrement of BMI. Conversely, it may be difficult for subjects with under 18 of BMI to manage them by BMI. We show a possibility that we could prevent the lifestyle disease by controlling BMI.
ER -
English
