Journal of Textile Research ›› 2023, Vol. 44 ›› Issue (07): 184-191.doi: 10.13475/j.fzxb.20220504501

• Apparel Engineering • Previous Articles     Next Articles

Body shape characteristics and classification of middle-aged and elderly women in eastern China

LIU Yongmei1,2, LIU Siyi1, YU Xiaokun1,2, XUE Huixin1, ZHANG Xianghui1,2()   

  1. 1. College of Fashion and Design, Donghua University, Shanghai 200051, China
    2. Key Laboratory of Clothing Design and Technology, Ministry of Education, Donghua University, Shanghai 200051, China
  • Received:2022-05-16 Revised:2023-02-28 Online:2023-07-15 Published:2023-08-10

RichHTML

17

PDF (PC)

115

Abstract:

Objective Nowadays, China's aging population is becoming increasingly severe, the size of middle-aged and elderly people is expanding, and so is the related clothing market. Middle-aged and elderly people put forward higher requirements for the comfort and aesthetetics of clothing, and the human body shape is closely related to the structure and shape design of clothing. Among them, the differences between middle-aged and elderly women and young women are significant in the shapes of chest, waist, abdomen and back. This research is proposed to study the body shape characteristics and classification of middle-aged and elderly women.

Method In order to further explore the body shape characteristics and distribution of middle-aged and elderly women, 207 middle-aged and elderly women aged 50-65 from eastern China were selected as research subjects, and 20 pieces of body size data were collected according Martin's measurement method. According to the national women's size standard, the collected data of body shape of middle-aged and elderly women were classified based on the difference of chest and waist and compared with the data of body shape proportion of the national standard to obtain the differences between the standard body shape of middle-aged and elderly women and the standard body shape of adult women. Further factoral analysis and correlation analysis were carried out on the collected data to acquire characteristic variables affecting the body shape of middle-aged and elderly women. Finally, based on the influence factor with the highest correlation, the body shape of middle-aged and elderly women was classified through rapid cluster analysis, and the value range of characteristic variables was calculated.

Results Compared with the national standard GB/T 1335.2—2008《Standard Sizing Systems for Garments-Women》, the proportion of Y and A types decreases while the proportion of B and C types increases, among which the proportion of B type is the highest (Tab. 2 and Tab. 3). The results of factor analysis showed that circumference factor was the main factor affecting the body shape difference of middle-aged and elderly women, the front and back waist section difference was the characteristic variable affecting the body shape of the torso, the waist ratio, the chest-waist difference, the hip-waist difference was the characteristic variable affecting the body height, slimness and fullness index (Tab. 4 and Tab. 5). Combined with factor analysis and extraction results of human characteristic variables, clustering was finally carried out from two perspectives, i.e. the difference between front and back waist section difference was taken as a clustering index, and waist, waist ratio, chest-waist difference and hip-waist difference were taken as clustering indexes. The results of K-means fast clustering showed that the human body shape was divided into humpback body, slight humpback body, normal body and chest pull-out body by using the difference of front and back waist as the benchmark. Based on waist circumference, waist ratio, chest-waist difference and hip-waist difference, human body shape was classified into X type, H type, small A type and A type. Finally, the value range of clustering indicators of each body type was obtained (Tab. 11 and Tab. 12).

Conclusion The body shape of middle-aged and elderly women shows an obvious trend of obesity, and the coverage rate for their body shape in the national standard is low, which calls for targeted clothing size standards to be established. Circumference factor is the main factor affecting the body size difference of middle-aged and old women. Through cluster analysis, the body shape of middle-aged and elderly women are divided into four categories from the aspects of trunk shape, and body height, thinness and fullness, and their body shape are subdivided more accurately, providing reference for the establishment of clothing type of middle-aged and elderly women. For future research, it is suggested to increase the sample size of the research subjects to better represent body shape of middle-aged and elderly women, so as to improve the accuracy of body type classification.

Key words: fashion design, middle-aged and elderly women, standard body, body shape characteristics, body shape classification, cluster analysis

CLC Number: 

  • TS941.2

Tab. 1

Anthropometric data"

类别 年龄/岁 体重/
kg		 身高/
cm		 颈椎
点高/cm		 腰高/
cm		 肩宽/
cm		 前胸
宽/cm		 后背
宽/cm		 乳间
距/cm		 腹臀
厚/cm
最小值 50 36.7 144.7 122.3 85.5 35.7 30.0 28.0 11.4 19.8
最大值 65 78.7 170.5 145.0 104.1 47.0 42.0 42.0 21.5 31.8
统计均值 58.6 58.4 157.5 133.6 94.5 41.4 35.8 35.5 16.2 26.4
标准误差均值 0.3 0.6 0.3 0.3 0.3 0.2 0.2 0.2 0.1 0.2
标准差 3.6 8.3 4.9 4.3 3.6 2.3 2.4 2.7 2.0 2.5
方差 13.1 68.0 24.0 18.3 12.7 5.3 5.9 7.3 3.9 6.1
偏度 -0.37 0.17 -0.04 -0.16 -0.13 0.23 0.14 0.11 0.1 -0.03
峰度 -0.48 -0.19 -0.03 0.01 -0.16 -0.12 -0.37 -0.34 -0.27 -0.33
变异系数/% 6.14 14.21 3.11 3.22 3.81 5.56 6.70 7.61 12.35 9.47
类别 前腰
节长/cm		 颈侧点
到乳点/
cm		 后腰
节长/
cm		 背长/
cm		 颈根围/
cm		 胸围/
cm		 胸下围/
cm		 腰围/
cm		 臀围/
cm		 臂根
围/cm
最小值 37.7 22.9 37.6 34.0 35.8 72.0 65.5 63.6 80.3 32.5
最大值 51.0 32.0 51.2 45.4 46.3 109.0 100.0 96.5 104.3 47.8
统计均值 44.9 27.2 44.2 39.2 40.9 90.2 80.9 78.3 91.6 39.7
标准误差均值 0.2 0.1 0.2 0.2 0.1 0.5 0.5 0.5 0.3 0.2
标准差 2.6 1.8 2.6 2.3 2.0 6.9 6.7 6.8 4.9 2.9
方差 6.8 3.1 6.6 5.2 4.0 47.7 44.9 46.7 23.9 8.3
偏度 0.01 0.25 0.11 0.21 0.2 0.38 0.47 0.21 0.3 0.23
峰度 -0.31 0 -0.36 -0.12 -0.23 -0.26 -0.32 -0.33 -0.18 -0.28
变异系数/% 5.79 6.62 5.88 5.87 4.89 7.65 8.28 8.68 5.35 7.30

Tab. 2

Distribution of middle-aged and elderly women and national standard body types"

体型
代号		 国家标准体型分布
比例/%		 中老年女性体型
分布比例/%
Y 14.8 2.9
A 44.1 26.1
B 33.7 47.8
C 6.5 21.7
总计 99.1 98.5

Tab. 3

Comparison of national standard body and standard body shape of middle-aged and elderly women cm"

体型 群体 身高 颈椎
点高		 腰高 胸围 腰围 臀围 肩宽
A 标准 160.0 136.0 98.1 84.0 68.2 90.9 39.9
中老年 157.0 133.2 94.2 91.6 76.0 90.7 41.2
B 标准 160.0 136.3 98.0 88.0 76.6 94.8 40.3
中老年 157.8 133.8 95.2 90.1 78.8 91.8 41.6
C 标准 160.0 136.5 98.2 88.0 81.9 96.0 40.5
中老年 157.5 133.9 93.7 88.8 80.8 92.3 41.5

Tab. 4

Factor analysis total variance interpretation table"

成分
编号		 初始特征值 旋转载荷平方和
总计 方差
百分比/%		 累积
贡献率/%		 总计 方差百
分比/%		 累积
贡献率/%
1 8.901 44.506 44.506 7.756 38.782 38.782
2 3.143 15.716 60.222 3.039 15.195 53.977
3 1.764 8.819 69.041 2.834 14.168 68.145
4 1.098 5.488 74.529 1.277 6.384 74.529

Tab. 5

Rotated factor analysis component matrix"

指标
名称		 因子载荷系数 共同度
(公因子
方差)
成分1 成分2 成分3 成分4
年龄 0.021 -0.129 -0.159 0.827 0.726
体重 0.897 0.256 0.196 -0.013 0.909
身高 0.105 0.908 0.350 -0.055 0.960
颈椎点高 0.154 0.902 0.360 -0.016 0.967
腰高 0.145 0.958 -0.105 -0.072 0.955
肩宽 0.533 0.325 0.125 0.332 0.515
前胸宽 0.670 0.169 0.068 0.166 0.510
后背宽 0.665 0.176 0.201 0.208 0.556
腹臀厚 0.837 0.006 -0.011 -0.026 0.509
前腰节长 0.292 0.130 0.861 -0.090 0.702
颈侧点到乳点 0.656 0.124 0.159 0.434 0.852
后腰节长 0.187 0.123 0.871 -0.160 0.659
背长 0.049 0.177 0.889 0.095 0.834
颈根围 0.670 0.288 0.082 -0.113 0.833
胸围 0.930 0.014 0.110 0.081 0.552
胸下围 0.916 -0.012 0.109 0.082 0.885
腰围 0.896 -0.025 0.256 0.012 0.858
臀围 0.814 0.195 0.140 -0.068 0.868
臂根围 0.680 0.139 0.120 -0.177 0.725
乳间距 0.620 -0.126 -0.004 0.331 0.528

Tab. 6

Correlation indices for variables in factors"

因子类别 变量名称 R ˉ j 2指数
围度因子 体重 0.506
肩宽 0.217
前胸宽 0.270
后背宽 0.295
腰臀厚 0.366
颈侧点到乳点 0.294
颈根围 0.265
胸围 0.498
胸下围 0.478
腰围 0.472
臀围 0.393
臂根围 0.253
乳间距 0.207
高度因子 身高 0.822
颈椎点高 0.831
腰高 0.725
躯干长度因子 前腰节长 0.578
后腰节长 0.576
背长 0.474
年龄因子 年龄 1

Tab. 7

Derived variables and calculation formulae of overall shape of human body"

形态指标 派生变量 计算公式
体
质
指
标		 体质指数 BMI BMI=体重/身高2
高瘦指数 身胸比 身胸比=身高/胸围
身腰比 身腰比=身高/腰围
身臀比 身臀比=身高/臀围
丰满指数 胸腰差 胸腰差=胸围-腰围
臀腰差 臀腰差=臀围-腰围
胸凸量 胸凸量=上胸围-下胸围
躯干形态指标 前后腰节差 前后腰节差=
前腰节长-后腰节长

Tab. 8

Correlations between variables of physical fitness indicators and BMI"

指标 BMI 个案数
皮尔逊相关性 Sig.(双尾)
身胸比 -0.849 0.000 207
身腰比 -0.863 0.000 207
身臀比 -0.839 0.000 207
胸腰差 -0.187 0.007 207
臀腰差 -0.494 0.000 207
胸凸量 0.032 0.643 207

Fig. 1

SSE-K curves for clustering with two criteria. (a) Clustering by front and back waist section difference; (b) Clustering by waist, body-waist ratio, hip-waist difference and chest-waist difference "

Tab. 9

Body shape classification based on front and back waist seciton difference"

体型
分类		 样本
频数		 样本
占比/%		 (平均值±
标准差)/cm		 最终聚类
中心/cm		 各类别
相关性
驼背体 47 24.64 -1.51±0.73 -1.35 F=473.26
p=0.00
微驼背体 60 28.99 0.17±0.39 -0.31
正常体 49 23.67 1.24±0.27 0.35
挺胸体 51 24.64 2.74±0.79 1.28

Tab. 10

Value range of front and back waist section difference of four body shapes"

体型分类 初始取值
范围/cm		 均值/
cm		 二次调整
取值范围/cm
驼背体 -2.24~-0.78 -1.51 -2.35~-0.67
微驼背体 -0.22~0.56 0.17 -0.67~0.70
正常体 0.97~1.51 1.24 0.70~1.99
挺胸体 1.95~3.53 2.74 1.99~3.49

Tab. 11

Body shape classification based on waist,body-waist ratio, hip-waist difference and chest-waist difference"

体型
分类		 样本
频数		 样本
占比/%		 腰围/cm 身腰比 胸腰差/cm 臀腰差/cm
平均值±
标准差		 最终聚类
中心		 平均值±
标准差		 最终聚类
中心		 平均值±
标准差		 最终聚类
中心		 平均值±
标准差		 最终聚类
中心
X型 44 21.26 69.69±3.73 -1.16 2.26±0.12 1.26 15.19±2.78 0.97 18.75±2.64 1.15
H型 79 38.16 76.19±3.04 -0.33 2.07±0.08 -0.28 11.07±3.15 -0.08 14.07±2.54 0.24
小A型 67 32.37 83.87±3.59 0.65 1.88±0.07 -0.72 10.59±3.30 -0.20 10.00±3.06 -0.57
A型 17 8.21 94.29±5.48 1.98 1.68±0.10 -1.73 6.02±3.71 -1.35 3.25±4.10 -1.87
各特征类别
相关性		 F 254.76 248.96 38.90 150.88
p 0.00 0.00 0.00 0.00

Tab. 12

Value ranges of waist, body-waist ratio, hip-waist difference and chest-waist difference for four body shapes"

类别 腰围/cm 身腰比 胸腰差/cm 臀腰差/cm
初始取值
范围		 均值 二次调整
取值范围		 初始取值
范围		 均值 二次调整取
值范围		 初始取值
范围		 均值 二次调整取
值范围		 初始取值
范围		 均值 二次调整取
值范围/cm
X型 65.96~73.42 69.69 66.4~73.0 2.14~2.38 2.26 2.17~2.36 12.41~17.97 15.19 13.1~17.3 16.11~21.39 18.75 16.4~21.1
H型 73.15~79.23 76.19 73.0~80.0 1.99~2.15 2.07 1.98~2.17 7.92~14.22 11.07 10.8~13.1 11.53~16.61 14.07 12.0~16.4
小A型 80.28~87.46 83.87 80.0~89.0 1.81~1.95 1.88 1.78~1.98 7.29~13.89 10.59 8.3~10.8 6.94~13.06 10.00 6.6~12.0
A型 88.81~99.77 94.29 89.0~99.5 1.58~1.78 1.68 1.58~1.78 2.31~9.73 6.02 3.7~8.3 -0.85~7.35 3.25 -0.1~6.6
[1] 项鑫, 王乙. 中国人口老龄化现状、特点、原因及对策[J]. 中国老年学杂志, 2021, 41(18): 4149-4152.
XIANG Xin, WANG Yi. Current situation, characteristics, causes and countermeasures of population aging in China[J]. Chinese Journal of Gerontology, 2021, 41(18): 4149-4152.
[2] 陈明艳. 成年女性体型特征及其服装样板设计[J]. 纺织学报, 2005, 26(3): 121-124.
CHEN Mingyan. Body characteristics of the mature female and the design of template for suit-dress[J]. Journal of Textile Reasearch, 2005, 26(3): 121-124.
[3] 吴巧英, 袁观洛. 中老年女性与青年女性体型比较研究[J]. 东华大学学报(自然科学版), 2004, 20(1): 66-71.
WU Qiaoying, YUAN Guanluo. Comparison on characteristics of body form between middle-aged women and young women[J]. Journal of Donghua Univer-sity (Natural Science), 2004, 20(1): 66- 71.
[4] 陈晓玲, 彭小琴, 黄家剑. 湖南女大学生体型特征与分类研究[J]. 针织工业, 2021(8): 72-77.
CHEN Xiaoling, PENG Xiaoqin, HUANG Jiajian. Body shape characteristics and classification of female college students in Hunan province[J]. Knitting Industries, 2021(8): 72-77.
[5] 汪海仙, 尚笑梅. 人体体型分类方法研究综述[J]. 现代丝绸科学与技术, 2019, 34(3): 37-40.
WANG Haixian, SHANG Xiaomei. A review of research on human body classification methods[J]. Modern Silk Science & Technology, 2019, 34(3): 37-40.
[6] 杨玫. 关中地区中老年体型特征及服装结构设计研究[D]. 西安: 西安工程大学, 2016: 31.
YANG mei. The research on clothing structure design and body characteristics of the middle-aged in Guan Zhong region[D]. Xi'an: Xi'an Polytechnic University, 2016: 31.
[7] 于晓坤, 胡帆, 朱达辉, 等. 上海地区中老年女性体型研究[J]. 北京服装学院学报(自然科学版), 2016, 36(4): 9-17.
YU Xiaokun, HU Fan, ZHU Dahui, et al. Research on body shape of the middle and old aged women in Shanghai area[J]. Journal of Beijing Institute of Fashion Technology (Natural Science Edition), 2016, 36(4): 9-17.
[8] 邢英梅, 王竹君, 阚燕, 等. 基于因子分析和分层聚类的成年女性体型特征识别[J]. 河南工程学院学报(自然科学版), 2019, 31(2): 8-12.
XING Yingmei, WANG Zhujun, KAN Yan, et al. Feature identification of female's body type based on factor analysis and hierarchical clustering[J]. Journal of Henan University of Engineering(Natural Science Edition), 2019, 31(2): 8-12.
[9] 杨蕾, 马凯. 北京地区中年女性体型细分研究[J]. 北京服装学院学报(自然科学版), 2021, 41(2): 35-40.
YANG Lei, MA Kai. Body shape classification of middle-aged women in Beijing[J]. Journal of Beijing Institute of Fashion Technology(Natural Science Edition), 2021, 41(2): 35-40.
[10] 金娟凤, 孙洁, 倪世明, 等. 基于三维人体测量的青年女性臀部体型细分[J]. 纺织学报, 2013, 34(9): 108-112.
JIN Juanfeng, SUN Jie, NI Shiming, et al. Research on subdividing of young female's hip shapes based on 3-D body measurement[J]. Journal of Textile Research, 2013, 34(9): 108-112.
[11] 方方, 王子英. K-means聚类分析在人体体型分类中的应用[J]. 东华大学学报(自然科学版), 2014, 40(5): 593-598.
FANG Fang, WANG Ziying. Application of K-means clustering analysis in the body shape classification[J]. Journal of Donghua University (Natural Science), 2014, 40(5): 593-598.
[12] 韩凌波. K-均值算法中聚类个数优化问题研究[J]. 四川理工学院学报(自然科学版), 2012, 25(2): 77-80.
HAN Lingbo. Optimization study on class number of K-means algorithm[J]. Journal of Sichuan University of Science & Engineering (Natural Science Edition), 2012, 25(2): 77-80.
[1] CHEN Jia, YANG Congcong, LIU Junping, HE Ruhan, LIANG Jinxing. Cross-domain generation for transferring hand-drawn sketches to garment images [J]. Journal of Textile Research, 2023, 44(01): 171-178.
[2] ZHONG Zejun, ZHANG Beibei, XU Kaiyi, WANG Ruowen, GU Bingfei. Research on breast shape of young females using characteristic parameters [J]. Journal of Textile Research, 2022, 43(10): 148-154.
[3] WANG Fenfen, WANG Gehui, HUANG Tianyi, ZHANG Xianghui, WANG Yongrong. Female leg shape classification based on frontal and lateral morphological characteristics [J]. Journal of Textile Research, 2022, 43(09): 188-194.
[4] WANG Di, KE Ying, WANG Hongfu. Parametric fashion design based on Voronoi graphics [J]. Journal of Textile Research, 2021, 42(12): 131-137.
[5] ZHOU Jie, LI Jian, MA Qiurui, HUANG Xiaojie. Recognition of special template based on improved analytic hierarchy process [J]. Journal of Textile Research, 2019, 40(05): 124-130.
[6] . Design and application of three-dimensional parametric technology in construction of new forms of modern clothing [J]. Journal of Textile Research, 2018, 39(12): 118-123.
[7] . Integrating of soft intelligent textile and functional fiber [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(05): 160-169.
[8] . Young female body shape classification and prototype patterns based on wavelet coefficient [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(12): 119-123.
[9] . Optimization design of multi-light source for foreign fiber detection based on clustering neural network [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(10): 104-112.
[10] . Classification of body shape based on longitudinal section curve [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(06): 86-91.
[11] . Innovative application of men's plus fours in Chinese modern fashion design [J]. Journal of Textile Research, 2015, 36(04): 124-127.
[12] . Evaluation and analysis of perceptual images of clothing fabrics [J]. Journal of Textile Research, 2015, 36(03): 99-104.
[13] . Female Body Shape Classification Based on the optimal segmentation method for orderly samples [J]. JOURNAL OF TEXTILE RESEARCH, 2014, 35(9): 114-0.
[14] . Female body shape prediction based on random forest [J]. JOURNAL OF TEXTILE RESEARCH, 2014, 35(5): 113-0.
[15] Juan-Feng JIN Jie SUN. Research on subdividing of young female’s hip shapes based on 3-D body measurement [J]. JOURNAL OF TEXTILE RESEARCH, 2013, 34(9): 108-0.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备14006648号
Copyright 2021 © Editorial office of Journal of Textile Research
Supported by Beijing Magtech Co.Ltd