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Relative Risk of Dietary Patterns and Other Obesity Factors in Korean Males above 40 Years of Age

한국 40세 이상 남성의 식이패턴과 비만 요인들의 상대적 위험도

  • Received : 2013.04.15
  • Accepted : 2013.11.01
  • Published : 2013.11.30

Abstract

A debate over the association between dietary patterns and obesity is not settled in the literature. Some studies suggest that there are significant differences in the mean body mass index (BMI) across dietary patterns, while others refute the result. Therefore, we extended this line of study to examine whether the influence of dietary pattern is strong enough to affect the incidence of obesity based on the criterion, BMI=25. We identified 3 dietary patterns using a cluster analysis of food intake data obtained from the food frequency survey conducted as a part of Korean genome epidemiologic study: 'variety', 'unrefined grain', and 'rice' dietary patterns. A Cox Hazard regression result showed that the all the dietary pattern variable parameters were not significant. Hence, it was concluded that the dietary patterns do not affect the incidence of obesity under the control of variables, such as age, energy intake, and etc.

본 연구에서는 식이패턴의 차이가 BMI 25 이상의 비만 발병에 영향을 미치는지 구명하였다. 한국인유전체역학조사사업으로 일환으로 수행된 안성-안산 코호트 연구의 식품섭취빈도 자료에 대해 군집분석을 수행하여 3개의 식이패턴 군집을 도출하였다. 3개의 식이패턴은 '다양성', '잡곡', 그리고 '쌀밥' 식이패턴이다. 식이패턴, 나이, 열량섭취량, 소득, 교육수준, 흡연여부, 음주량, 고강도 활동 시간, 직업 변수들을 비만 발병률에 대한 Cox Hazard Model을 회귀분석 실시한 결과 식이패턴변수는 비만 발병에 영향을 미치지 않는 것으로 나타났다. 오히려 식이패턴보다는 나이, 섭취 열량, 소득, 고강도 활동시간, 직업 요인들이 비만 발병에 유의성 있는 영향을 미치는 것으로 나타났다.

Keywords

References

  1. Sassi F, Devaux M, Cecchini M, Rusticelli E. 2009. The Obesity epidemic: analysis of past and projected future trend in selected OECD countries. OECD Health Working Papers 45. OECD.
  2. Kant AK. 2004. Dietary patterns and health outcomes. J Am Diet Assoc 104: 615-635. https://doi.org/10.1016/j.jada.2004.01.010
  3. Togo P, Osler M, Sørensen TIA, Heitmann BL. 2001. Food intake patterns and body mass index in observational studies. Int J Obes 25: 1741-1751. https://doi.org/10.1038/sj.ijo.0801819
  4. Baglietto L, Krishnan K, Severi G, Hodge A, Brinkman M, English DR, McLean C, Hopper JL, Giles GG. 2011. Dietary patterns and risk of breast cancer. Br J Cancer 104:524-531. https://doi.org/10.1038/sj.bjc.6606044
  5. Newby PK, Muller D, Hallfrisch J, Qiao N, Andres R, Tucker KL. 2003. Dietary Patterns and changes in body mass index and waist circumference in adults. Am J Clin Nutr 77: 1417-1425. https://doi.org/10.1093/ajcn/77.6.1417
  6. Schulze MB, Fung TT, Manson JE, Willett WC, Hu FB. 2006. Dietary patterns and changes in body weight in women. Obesity 14: 1444-1453. https://doi.org/10.1038/oby.2006.164
  7. McNaughton SA, Ball K, Mishra GD, Crawford DA. 2008. Dietary patterns of adolescents and risk of obesity and hypertension. J Nutr 138: 364-370. https://doi.org/10.1093/jn/138.2.364
  8. Anderson AL, Harris TB, Houston DK, Tylavsky FA, Lee JS, Sellmeyer DE, Sahyoun NR. 2010. Relationship of dietary patterns with body composition in older adults differ by gender and PPAR-$\gamma$ Pro12Ala genotype. Eur J Nutr 49: 385-394. https://doi.org/10.1007/s00394-010-0096-9
  9. Esmaillzadeh A, Azadbakht L. 2008. Major dietary patterns in relation to general obesity and central adiposity among Iranian women. J Nutr 138: 358-363. https://doi.org/10.1093/jn/138.2.358
  10. Lee SM, Oh AR, Ahn HS. 2008. Major dietary patterns and their associations with socio-demographic, psychological and physical factors among generally healthy Korean middle-aged women. Korean J Community Nutr 13: 439-452.
  11. Song YJ, Paik HY, Joung H. 2009. A comparison of cluster and factor analysis to derive dietary patterns in Korean adults using data from the 2005 Korea National Health and Nutrition Examination Survey. Korean J Community Nutr 14: 722-733.
  12. Ministry of Health and Welfare. National Health Statistics 2009. Available from https://knhanes.cdc.go.kr/knhanes/sub01/sub01_05.jsp. Accessed June 12, 2011.
  13. Baik I, Lee M, Jun NR, Lee JY, Shin C. 2013. A healthy pattern consisting of a variety of food choices is inversely associated with the development of metabloic syndrome. Nutr Res Pract 7: 233-241. https://doi.org/10.4162/nrp.2013.7.3.233
  14. Ahn Y, Park YJ, Park SJ, Min H, Kwak HK, Oh KS, Park C. 2007. Dietary patterns and prevalence odds ratio in middle-aged adults of rural and mid-size city in Korean genome epidemiology study. Korean J Nutr 40: 259-269.
  15. SPSS. 2009. IBM SPSS Statistics version 20. Chicago, IL, USA.
  16. Deddens JA, Petersen MR. 2008. Approaches for estimating prevalence ratios. Occup Environ Med 65: 501-506. https://doi.org/10.1136/oem.2007.034777
  17. Schmidt CO, Kohlmann T. 2008. When to use the odds ratio or the relative risk? Int J Public Health 53: 165-167. https://doi.org/10.1007/s00038-008-7068-3
  18. Kaplan, EL, Meier P. 1958. Nonparametric estimation from incomplete observations. J Am Stat Assoc 53: 643-653.
  19. Kwock CK, Lee JM, Kim EM, Lee MA. 2011. Diet and lifestyle factors affecting obesity: A Korea National Health and Nutrition Survey Analysis. J Food Sci Nutr 16: 117-126. https://doi.org/10.3746/jfn.2011.16.2.117
  20. Bodnar LM, Siega-Riz AM, Cogswell ME. 2004. High prepregnancy BMI increases the risk of postpartum anemia. Obes Res 12: 941-948. https://doi.org/10.1038/oby.2004.115

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