DOI QR코드

DOI QR Code

Fasting Blood Sugars and Their Association with Serum Lipids, and Obesity Indices in Manufacturing Workers

제조업 근로자의 공복 시 혈당과 혈청지질 및 비만지표와의 관련성

  • Park, Sung-Kyeong (Department of Beauty Art & Skin Care, Daejeon Health Science College) ;
  • Cho, Young-Chae (Department of Preventive Medicine and Public Health, Chungnam National University School of Medicine and Research Institute for Medical Sciences)
  • 박승경 (대전보건대학 피부미용과) ;
  • 조영채 (충남대학교 의학전문대학원 예방의학교실)
  • Received : 2017.01.19
  • Accepted : 2017.04.07
  • Published : 2017.04.30

Abstract

The purpose of this study was to investigate the relationship between the fasting blood sugar and serum lipid levels (TC, TG, HDL-C, LDL-C) and obesity indices (BMI, body fat rates, waist circumference, waist to hip ratio). The study sample consists of 1,473 manufacturing workers aged from 30 to 59 years, who underwent a health check-up at a university hospital during the period from Jan. to Dec. 2015. A data analysis was conducted to classify the subjects into the normal and abnormal groups according to their fasting blood sugar levels depending on the average values of the serum lipids and obesity indices. Multiple regression analyzes adjusted for sex and age were conducted for the factors affecting the fasting blood sugar level. As a result, the Serum TC, TG, LDL-C, BMI and waist circumference were found to be significantly higher in the abnormal fasting blood sugar level group than in the normal one, but the HDL-C was significantly lower in the abnormal group than in the normal one The fasting blood sugar level had a significant positive correlation with the TC, TG, LDL-C, BMI and waist circumference. The TC, TG, BMI and body fat were the significant factors affecting the fasting blood sugar. The above results suggest that the fasting blood sugar and serum lipid levels (TC, TG, HDL-C, LDL-C), obesity indices (BMI, body fat rates, waist circumference, waist to hip ratio) of manufacturing workers are significantly associated with each other.

본 연구는 제조업 근로자들의 공복 시 혈당과 혈청지질치(TC, TG, HDL-C, LDL-C) 및 비만지표(BMI, 체지방률, 허리둘레, 허리둘레와 엉덩이둘레의 비)와의 관련성을 검토할 목적으로 시도하였다. 연구는 2015년 1월부터 12월까지의 기간에 한 대학병원 건강검진센터에서 종합건강검진을 받았던 30~59세의 근로자 1,473명을 대상으로 하였다. 자료의 분석은 조사대상자의 공복 시 혈당을 정상군과 비정상군으로 구분하여 혈청지질치 및 비만지표의 평균치를 비교하였고, 성과 연령을 조정한 다중 회귀분석을 통해 공복시 혈당에 영향을 미치는 관련요인을 검토하였다. 연구결과, 조사대상자의 TC, TG, LDL-C, BMI 및 허리둘레는 공복 시 혈당이 정상인 군보다 비정상인 군에서 유의하게 높았고, HDL-C는 공복 시 혈당이 정상군보다 비정상군에서 유의하게 낮았다. 조사대상자의 공복시 혈당치는 TC, TG, LDL-C, BMI 및 허리둘레와 유의한 양의 상관관계를 보였다. 공복 시 혈당에 영향을 미치는 요인으로는 TC, TG, BMI 및 체지방률이 유의한 변수로 선정되었다. 이상과 같은 결과는 제조업 근로자들의 공복시 혈당은 TC, TG, LDL-C와 같은 혈청지질치 및 BMI, 체지방률과 같은 비만지표와 유의한 관련성이 있음을 시사한다.

Keywords

References

  1. Department of Health and Human Services, Centers for Disease Control and Prevention. 2011 National Health Statistics-National Health and Nutrition Examination Survey 5th, 2012.
  2. Elasy T. Diabetes and C-reactive protein. Clin diabetes, 25(1), pp. 1-2, 2007. DOI: https://doi.org/10.2337/diaclin.25.1.1
  3. Unwin N. Shaw J, Zimmet, Alberti KG. Impaired glucose tolerance and impaired fasting glycaemia: the current status on definition and intervention. Diabet Med, 19, pp. 708-723, 2002. DOI: https://doi.org/10.1046/j.1464-5491.2002.00835.x
  4. Thomas GN, Schooling CM, McGhee SM, Ho S-Y, Cheung BMY, Wat NM, Janus ED, Lam TH. Identification of factors differentially associated with isolated impaired fasting glucose and isolated post-load impaired glucose tolerance: the Hong Kong Cardiovascular Risk Factor Study, Eur J Endocrinol, 155, pp. 623-632, 2006. DOI: https://doi.org/10.1530/eje.1.02250
  5. American Heart Association. Cholesterol level. Available from http://www.amhrt.org/presenter.jhtml? identifier=4500.
  6. Thomas GN, Ho S-Y, Lam KSL, Janus ED, Hedley AJ, Lam TH. Impact of obesity and body fat distribution on cardiovascular risk factors in Hong Kong Chinese. Obes Res, 12, pp. 1805-1813, 2004. DOI: https://doi.org/10.1038/oby.2004.224
  7. Thomas GN, Critchley JAJH. Tomlinson B, Anderson PJ, Lee ZSK, Chan JCN. Obesity, independent of insulin resistance, is a major determinant of blood pressure in normoglycaemic Hong Kong Chinese. Metabolism, 49;1523-1528, 2000. DOI: https://doi.org/10.1053/meta.2000.18512
  8. Hartz AJ, Rupley DC, Kalkohoff RD. Relationship of obesity to diabetes: influence of obesity level and body fat distribution. Prev Med, 12, pp. 351-357, 1983. DOI: https://doi.org/10.1016/0091-7435(83)90244-X
  9. Chan JCN, Cockram CS. Diabetes in the Chinese population and its implications for health care. Diabetes Care, 20, pp. 1785-1790, 1997. DOI: https://doi.org/10.2337/diacare.20.11.1785
  10. Chong IK, Kim SW, Park YJ, et al. Comparison of Clinical Characteristics of Impaired Fasting Glucose with Impaired Glucose Tolerance in Yonchon County. Diabetes & Metabolism Journal, 24(1), pp. 71-77, 2000.
  11. Macdiarmid J. The global challenge of obesity and the international obesity task force.1998, Available from http://www.iuns.org/features/obesity/obesity_copy(1).htm
  12. Fujioka S, Matzuzawa Y, Tokunaga K, Tarui S. Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity. Metabolism 36, pp. 54-59, 1987. DOI: https://doi.org/10.1016/0026-0495(87)90063-1
  13. Matsuzawa Y. Pathophysiology and molecular mechanisms of visceral fat syndrome: the Japanese experience. Diabetes Metab Rev, 13, pp. 3-13, 1997. DOI: https://doi.org/10.1002/(SICI)1099-0895(199703) 13:1<3::AID-DMR178>3.0.CO;2-N
  14. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care, 26(11), pp. 3160-3167, 2003. DOI: https://doi.org/10.2337/diacare.26.11.3160
  15. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low density lipoprotein cholesterol in plasma without use of the preparative ultracentrifuge. Clin Chem, 18, pp. 499, 1972.
  16. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999-2000. JAMA, 288(14), pp. 1723-1727, 2002. DOI: https://doi.org/10.1001/jama.288.14.1723
  17. Kereiakes DJ, Willerson JT. Metabolic syndrome epidemic. Circulation, 108, pp. 1552-1553, 2003. DOI: https://doi.org/10.1161/01.CIR.0000093203.00632.2B
  18. Mokdad AH, Ford ES, Bowman BA, Dietz WH, Vinicor F, Bales VS, et al. Prevalence of obesity, diabetes, and obesity related health risk factors, 2001. JAMA, 289(1), pp. 76-79, 2003. DOI: https://doi.org/10.1001/jama.289.1.76
  19. Park HS., Kim PN. Lifestyle Factors Associated with Visceral fat Accumulation by CT Scan in Korean Obese Adults. Korean J Obes, 11(4), pp. 337-348, 2002.
  20. Kang JH., Kim KA., Cho YG., Chun JY., Kim OH. Effect of Visceral Obesity for Patients with Type 2 Diabetes Mellitus. Korean J Obes, 15(4), pp. 175-187, 2006.
  21. Reaven GM. Banting lenture. role of insulin resistance in human disease. Diabete, 37, pp. 1595-1607, 1998. DOI: https://doi.org/10.2337/diab.37.12.1595
  22. Kwon HS., Kim DM., Kim BW., Kim YK., Kim IJ., Kim TH et al. Updates on the metabolic syndrome, Bio Wave, 9(2), pp. 1-13, 2007.
  23. Kim KS. The influencing factors associated with glycemic control among adult diabetes patients. Journal of the Korea Academia-Industrial cooperation Society, 16(5), pp. 3284-3292, 2015. DOI: http://doi.org/10.5762/KAIS.2015.16.5.3284
  24. Uusitupa M, Loutheranta A, Lindstrom J, Valle T, Sundvall J, Eriksson J, Tuomilehto J. The Finnish Diabetes Prevention Study. Br J Nutr, (Suppl. 1), pp. S137-S142, 2000. DOI: https://doi.org/10.1017/s0007114500001070
  25. Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, Zimmet P, Son HY. Epidemic obesity and type 2 diabetes in Asia. Lancet, 369(9558), pp. 273-274, 2007.
  26. Yoon HS, Bae SY, Cho YC. Relationship between obesity indices and serum lipid levels in adults using data from health examination. Journal of the Korea Academia-Industrial cooperation Society, 16(2), pp. 1145-1152, 2015. DOI: http://dx.doi.org/10.5762/KAIS.2015.16.2.1145