This study utilized data to classify and characterize the body types of plus-size adult men aged in their 30s and 40s. Diversity is an important factor in the era of inclusive design, and discussion about size diversity to include the plus size should be accommodated. Data from 493 adult men classified as obese (with a World Health Organization criterion ≥25 BMI) were used for the analysis. The results of the study are as follows. Six independent factors were extracted using factor analysis for cluster analysis, which were then classified into five types. Type 1 (29.01%) was identified as body type I with the smallest degree of obesity. Type 2 (15.4%) was identified as body type Y with wide shoulders and a thin waist. Type 3 (14.2%) was the largest body volume (body type O), while the fourth (19.27%) identified as body type H has a large height and upper body. Lastly, type 5 (22.11%) has a long lower body and a slim abdomen, referred to as body type X. This study presents a basis for the development of various clothing sizes utilizing the body shape characteristics of plus-size men in their 30s and 40s. Follow-up research is needed to develop patterns for plus size men and to design various products.

The apparel industry has recently been recognizing the important target market of middle-aged women. The aim of this study was to examine the anthropometric characteristics of US women of 46 to 65 years of age and identify distinctive body shape characteristics of US middle-aged women. A total of 1915 middle-aged women whose ages ranged from 46 to 65 were selected from the SizeUSA database. The age range was divided into two groups: 46-55 and 56-65. Twenty-four body measurements important for apparel development were chosen. Four factors—Girth Factor, Height Factor, Hip Drop Factor, and Bust Drop Factor—accounted for the US middle-aged women’s body measurements. The body shapes were classified into four body shapes, which were Y-Shape in the overweight range, S-Shape in the overweight range, H-Shape in the overweight range, and the A-Shape in obese range. H-Shape, which was the least-defined waist in relation to the bust and hips with a short height, existed more in older middle-aged women than in younger middle-aged women. Y-Shape, S-Shape, and A-Shape existed more in the group of younger middle-aged women than in the group of older middle-aged women. In addition, compared with the younger middle-aged women, older middle-aged women had narrower shoulders, a larger waist, thinner legs, and a longer distance between side neck to bust point. The findings from the current study may be applied in the apparel industry for developing clothing sizing systems for US middle-aged women.

This study was conducted to investigate the anthropometric data, nutrient intakes and serum profiles in premenopausal and postmenopausal women living in Gyeonggi-do Province, Republic of Korea. The subjects were 49 premenopausal women and 63 postmenopausal women who are not taking any hormone or cardiovascular drugs. Anthropometric measurements were taken by a trained practitioner and the data for dietary intakes were obtained by a 24-hour recall method. Serum samples were collected and analyzed for the total cholesterol, triglyceride (TG) and lipoprotein fractions. The mean age of the premenopausal women was 45.17±3.28 years and that of the postmenopausal women was 62.52±4.14 years. The height and weight were 157.86±4.35 ㎝, 58.75±6.01 ㎏ in premenopausal women and 156.42±3.62 ㎝, 57.63±5.38 ㎏ in postmenopausal women, respectively. WHR (waist hip ratio) in postmenopausal women was significantly higher than that of premenopausal women (p<0.05). There were no differences between the pre-and postmenopausal women in the intakes of energy, protein, fat, Ca, Fe, vitamin A, vitamin B1, vitamin B2, niacin, vitamin C and vitamin E. However carbohydrate and Na intakes in postmenopausal women were significantly higher than those of premenopausal women. In postmenopausal women, Ca intake was below and Na intake was extremely high considering KDRIs (Dietary Reference Intakes for Koreans). Serum triglyceride in postmenopausal women was positively correlated with age, BMI (body mass index) and WHR. Serum total cholesterol and triglyceride in postmenopausal women showed significantly negative correlations with fiber intake. These results suggest that it is necessary to help postmenopausal women maintain a healthy body weight. Postmenopausal women needs to increase Ca (calcium) intakes and diet quality by decreasing the intakes of Na (sodium). In addition, an adequate intakes of fiber is recommended for postmenopausal women to prevent cardiovascular disease.

The purpose of this study was to investigate the effect and correlation of anthropometric data, eating behaviors, and nutrient intake on the bone mineral density(BMD) of female college students. 349 female college students were surveyed and their age, height, and weight were an average of 20.5 years, 163.2 ㎝ and 54.0 ㎏, respectively. Their average BMI was 20.2, with 66% falling in the normal range, 21.8% classified as underweight, 8.0% as overweight, and obese individuals comprised 3.4% of the sample by BMI classification. Calcaneal BMD was measured and the average T-score was 0.117. The results of BMD measurements were normal in 268 people(76.8%), osteopenia was found in 71 individuals(20.3%), and osteoporosis in 10(2.9%), respectively. There was a significant difference in bone mineral density according to height(p<0.05) and BMI (p<0.01). There were significant differences between BMD and eating behavior, regularity of eating behaviors(p<0.05), instant food intake(p<0.05), eating out(p<0.05) and nutritional supplement intake(p<0.05). In addition, normal the group with normal BMD had a more desirable eating behavior compared to the osteopenia and osteoporosis afflicted groups. BMD had a significant difference according to the nutrient intake of calcium(p<0.05), vitamin A(p<0.05), and vitamin C(p<0.05). In conclusion, BMD showed a good correlation with height(p<0.01), BMI(p<0.01), body composition including total body water(p<0.05), FFM(p<0.05), body protein(p<0.05) and intake of calcium(p<0.05), iron(p<0.05), vitamin A(p<0.05), and vitamin C(p<0.05). Therefore, an education plan and training on balanced diets proper body weight control, and desirable eating behaviors for female college students will be needed.

In this study, the representative hand shapes for the adult Koreans were analyzed by factor analysis and cluster analyses. The analyses were conducted on the anthropometric data of 58 hand dimensions from 325 subjects having nonhomogeneous demographics. Maximum hand circumference, first phalanx length of index finger, and ratio between the two measures were the independent variables for the cluster analyses. The results of the study showed that Korean hand shapes can be divided into 2 clusters irrespective of their size for each of the male and female group. There were slight differences in component ratio of hand shapes with respect to the occupation and the age, but their differences were not statistically significant. The representative Korean hand shapes and their anthrpometric dimensions could be used to design and establish proper sizing system for various hand operating devices.

The mask-face interface design should consider the face shape to improve the half mask respirator's fit ratio. This study tried to design the mask-face interface using recent Korean face data. By using the data of 1536 men's 3D face scanning (Size Korea data), head clay mock-up was made and mask-face interface line was extracted from this head mock-up. Using this interface line, the half-mask prototype was made. According to the quantitative fitting test, the proposed mask was found to be well fitted (average fit-ratio > 100). The proposed method had two advantages. 1) The method could use massive head-related anthropometric data like Size Korea data. 2) The qualitative fit test (observation) could be conducted very quickly by fitting the prototype to the head mock-up. However, this method also had several limitations. 1) The head clay mock-up could be different according to the mock-up maker. 2) The average values of the head-related anthropometric data were used to make the head mock-up. Small and large size head mock-ups should be made and tested.