A Study of Body Dimensional Changes for 20 to 40 Years Old Adults in Taiwan.

• Main Author: 甘一婷
• Other Authors: 王明揚
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/92223774202933262480

碩士 === 國立清華大學 === 工業工程與工程管理學系 === 92 === As the result of economical, technical and medical growth, the height and weight of people in Taiwan have increased tremendously in the past thirty years. This increase may cause dimensional changes in different body segments. This study is aiming at finding out the growth trends of height, weight, and additional 26 body dimensions during this period of time. The study was carried out by analyzing the data of those comparable dimensions collected from twelve Taiwan anthropometric databases established from 1972 to 2002. Several sets of regression models were established to represent the approximate body growth trends. Year, height, weight and gender are independent variables in these models. A verification of these models by measuring those body dimensions in question from a small sample group shows that five dimensions (weight, head breadth, axillary arm circumference, hip breadth and knee height) fit the models well. This may indicate that these five dimensions hold stable linear growth trends in the past 30 years and the models can be used for predicting these body dimensions for the near future. Additionally, six body referred indexes showed that people in Taiwan tends to be better in recent years and might grow in the following years. As for those dimensions of nonlinear growth trend the results might suggest that their growth rates vary from time to time and simple linear regression is unsuitable to predict their changes. More data and further analysis is needed to identify the patterns of the variation. The established regression models for body growth trends have two contributions. First, they are helpful in predicting the sizes of the twenty eight body dimensions in near future, which can be used as valuable references when designing durable goods. Second, these regression models can be served as a handy and acceptable way of estimating anthropometric data periodically with quick and small sample body measurement.