Warning: mkdir(): Permission denied in /home/virtual/lib/view_data.php on line 81

Warning: fopen(upload/ip_log/ip_log_2024-11.txt): failed to open stream: No such file or directory in /home/virtual/lib/view_data.php on line 83

Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 84
Analysis of Body Composition, Dietary Behaviors and Life style of 30~50 year old Women Living in Seoul


Your browser does not support the NLM PubReader view.

Go to this page to see a list of supporting browsers.

Analysis of Body Composition, Dietary Behaviors and Life style of 30~50 year old Women Living in Seoul

Article information

Korean J Community Nutr. 2012;17(4):440-449
Publication date (electronic) : 2012 August 31
doi : https://doi.org/10.5720/kjcn.2012.17.4.440
Jae Ok Koo, Seoyun Park1
Department of Home Economics Korea National Open University, Seoul, Korea.
1Department of Food & Nutrition, Catholic University, Bucheon, Korea.
Corresponding author: Jae Ok Koo, Department of Home Economic, Korea National Open University, Dongsungdong 169, Seoul 110-791, Korea. Tel: (02) 3668-4643, Fax: (02) 3668-4188, cokoo@knou.ac.kr
Received 2012 June 27; Revised 2012 August 07; Accepted 2012 August 27.

Abstract

This study was carried out to investigate the distribution of body composition, and to analyze its relationship to dietary behaviors and life style. The study subjects were divided into 3 age groups; 30' years (n = 78) 40' years (n = 71) and 50' years (n = 44). The data was collected by physical measurement (Inbody 230) and questionnaires. The rate of disease and general characteristics were higher in the 50 year old group than in the other groups. Average amount of body water, protein, mineral and body fat were 29.0 kg (50.4%), 7.7 kg (13.4%), 2.8 kg (4.8%), 18.7 kg (31.5%), respectively. The rate of menopause was significantly different with increasing age. Menopause was 1.3%, 9.1%, 79.6% by age respectively. Body fat percent was significantly increased and body water decreased with age (p < 0.01). The fat composition was higher and the mineral content was lower in 50' year old group. Dietary behavior scores of 30' year old group was significant lower than in the other two groups (p < 0.001). The means of salty eating, skipping meals, fruit intake and food habits total point were significantly higher in the 50 year old group than in the other groups. There were significant positive correlations between age, BMI, waist hip ratio respectively (p < 0.01). There were significant negative correlations between age and body water, body mineral, skeletal muscle (p < 0.01, p < 0.05, p < 0.01). The results of this study suggested that nutritional management and education for adult women differ by age group.

Keywords: women; dietary behavior; life style

Notes

This research was supported by grants from Korea National Open University 2011 the last half year

References

1. Aloia JF, Vaswani A, Flaster E, Ma R. Relationship of body water compartments to age, race, and fat-free mass. J Lab Clin Med 1998. 132(6)483–490.
2. Biospace. User's manual (Inbody 230) 2008. Seoul: Biospace Co., Ltd;
3. Chang HS. A study on weight control behavior, eating habits and health-related life habits according to obesity degree by body fat percentage among middle-aged women in Gunsan city. Korean J Community Nutr 2010. 15(2)227–239.
4. Choi M, Kim MH. A study on bone mineral density, dietary habits and nutritional status of adult women in the three age groups. Korean J Food Cult 2007. 22(6)833–840.
5. Trémollieres FA, Pouilles JM, Ribot CA. Relative influence of age and menopause on total age and regional body composition changes in postmenopausal women. Am J Obstet Gynecol 1996. 175(6)1594–1600.
6. Gallagher JC, Riggs BL, Jerpbak CM, Arnaud CD. The effect of age on serum immunoreactive parathyroid hormone in normal and osteoporotic women. J Lab Clin Med 1980. 95(3)373–385.
7. Haroun D, Taylor SJC, Viner RM, Hayward RS, Darch TS, Eaton S, Cole TJ, Wells JCK. Validation of bioelectrical impedance analysis in adolescents across different ethnic groups. Obesity 2010. 181252–1259.
8. Hwang IC, Jo YN, Kim KK. The usefulness of waist to hip ratio estimated by bioelectric impedance analysis in diagnosing metabolic syndrome based on NCEP-ATP III guideline. Korean J Obes 2009. 18(3)79–86.
9. Jung IK. A study on the nutrient intakes and factors related to dietary behavior of women by age groups in Incheon. Korean J Community Nutr 2005. 10(1)46–58.
10. Koo JO, Park S. Analysis of BMI, body composition, weight control, dietary behaviors of adult women. Korean J Community Nutr 2011. 16(4)454–465.
11. Kim JH, Kim SH. A study on energy metabolism of Korean healthy women with age. Korean J Nutr 1989. 22(6)531–538.
12. Korean National Statistical Office. The statistics of life table 2010 2010. cited 2012 June 20. Available from www.kosis.kr.
13. Korea Centers for Disease Control and Prevention & Korea Health Industry Development Institute. Korea national health & nutrition examination survey 2008. cited 2011 March 1. Available from http://knhanes.cdc.go.kr/.
14. Korea Centers for Disease Control and Prevention & Korea Health Industry Development Institute. Korea national health & nutrition examination survey 2010. cited 2012 March 29. Available from http://knhanes.cdc.go.kr/.
15. Ley CJ, Lees B, Stevenson JC. Sex-and menopause-associated changes in body-fat distribution. Am J Clin Nutr 1992. 55(5)950–954.
16. Lee HJ, Choi MR, Koo JO. A study of body image, weight control and dietary habits with different BMI in female high school students. Korean J Community Nutr 2005. 10(6)805–813.
17. Lee HS, Kwun IS, Kwon CS. Nutritional risks analysis based on the food intake frequency and health-related behaviors of the older residents (50 years and over) in Andong area (1). J Korean Soc Food Sci Nutr 2008. 37(8)998–1008.
18. Meeuwsen S, Horgan GW, Elia M. The relationship between BMI and percent body fat, measured by bioelectrical impedance, in a large adult sample is curvilinear and influenced by age and sex. Clin Nutr 2010. 29(5)560–566.
19. Moon HK, Kim EG. Comparing validity of using body mass index, waist to hip ratio, and waist circumference to cardiovascular risk factors of middle aged Koreans. J Korean Diet Assoc 2005. 11(3)365–374.
20. Ock SM, Ju SY, Choi WS, Park HM, Jung KI, Song CJ. Association of sleep hours with obesity in adult women. Korean J Obes 2008. 17(3)110–116.
21. Oh HJ, Cho DH, Chung HY, Han KO, Yoon HK, Han IK. Effects of obesity on BMD in pre & peri-menopausal Korean women. Korean J Obes 2000. 9(2)122–127.
22. Park JC, Kweon HJ, Oh YK, Do HJ, Oh SW, Lym YL, Choi JK, Joh HK, Cho DY. Association of the metabolic syndrome and bone mineral density in postmenopausal women. Korean J Fam Med 2010. 31(1)9–15.
23. Park SY. Nutritional status of anemic adolescent females, screening tools and the effect of nutrition education on improvement of iron status 2002. Graduate school of Catholic University; MS thesis.
24. Sakurai M, Takamura T, Miura K, Kaneko S, Nakagawa H. Middle-aged Japanese women are resistant to obesity-related metabolic abnormalities. Metabolism 2009. 58(4)456–459.
25. Sharpe JK, Byrneb NM, Stedmana TJ, Hillsb AP. Bioelectric impedance is a better indicator of obesity in men with schizophrenia than body mass index. Psychiatry Res 2008. 159(1-2)121–126.
26. Woo J, Kwok T, Lau E, Li M, Yu LM. Body composition in Chinese subjects: relationship with age and disease. Arch Gerontol Geriatr 1997. 26(1)23–32.
27. Woo SI, Cho SS. The influence of diet, body fat, menstrual function, and activity upon the bone density of female gymnasts. Korean J Nutr 1999. 32(1)50–63.

Article information Continued

Copyright © 2012 The Korean Society of Community Nutrition

Fig. 1

Fig. 1

Body composition of the subjects by age.

Means with different superscripts (a > b) within a row are significantly different at p = 0.05 by Duncan's multiple range test.

Table 1

General characteristics of the subjects

Table 1

1) N (%)

Table 2

Anthropometric characteristics and body composition of the subjects by age

Table 2

1) Mean ± SD

2) Significance as determined by GLM test

3) Means with different superscripts (a > b) within a row are significantly different from each at p = 0.05 by Duncan's multiple range test

4) ***: p < 0.001 by χ2-test

Table 3

Weight control in experience of each group by age

Table 3

1) N (%)

2) Significance as determined by χ2-test

***: p < 0.001

Table 4

Food habits of the subjects by age

Table 4

1) Mean ± SD

2) Means with different superscripts (a > b) within a row are significantly different from each at p = 0.05 by Duncan's multiple range test

*: p < 0.05, **: p < 0.01 by GLM test

cf. 4) yes = 3 point, sometimes = 2 point, no = 1point, 5) often = 3point, sometimes = 2point, rarely = 1point, The highest score, the better it is for the health, perfect score = 30

Table 5

Dietary behaviors of the subjects by age

Table 5

1) N (%)

2) Significance as determined p < 0.05 by χ2-test

Table 6

Sleep, exercise, watching TV and using computer of the subjects by age

Table 6

1) Mean ± SD

2) Significance as determined by GLM test

3) Means with different superscripts (a > b) within a row are significantly different at p = 0.05 by Duncan's multiple range test

4) N (%)

5) Significance as determined by χ2-test

***: p < 0.001

Table 7

Correlation coefficients between body composition and TV watching, using computer, food habits

Table 7

1) Significance as determined by Pearson's correlation coefficient (r)

*: p < 0.05, **: p < 0.01, ***: p < 0.001