JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2017, Vol. 55 ›› Issue (6): 87-92.doi: 10.6040/j.issn.1671-7554.0.2017.350

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A prediction model for metabolic syndrome risk: a study based on the health management cohort

SUN Yuanying1,2, YANG Yachao3, QU Mingling3, CHEN Yanmin3, LI Min1,2, WANG Shukang1,2, XUE Fuzhong1,2, LIU Yunxia1,2   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Cheeloo Research Center for Biomedical Big Data, Shandong University, Jinan 250012, Shandong, China;
    3. Physical Examination Department, Weihai Municipal Hospital, Weihai 264200, Shandong, China
  • Received:2017-04-24 Online:2017-06-10 Published:2017-06-10

Abstract: Objective To construct a model to evaluate the risk of developing metabolic syndrome(MetS)within 5 years in Chinese mainland Han population based on a health management population. Methods A total of 15 872 people without MetS at baseline were included based on the Shandong Multi-center Longitudinal Cohort for Health Management. Cox proportional hazards regression model was used to build the prediction model and the discriminatory ability was evaluated with area under the receiver operating characteristic(ROC)curve(AUC)and observed/expected counts(OE ratio). Results A total of 1 591 new MetS cases(1 273 males and 318 females)were observed during the follow-up of 5 years, accounting for an incidence density of 38.57/1000 person-year. In the male model, the risk factors included age, body mass index(BMI), fasting blood-glucose(FBG), triglyceride(TG), high density lipoprotein cholesterol(HDL-C), uric acid(UA), total cholesterol and hypertension. In the female model, the risk factors included age, BMI, FBG, TC, UA and hypertension. The AUC was 0.751(95%CI: 0.742-0.759)and 0.745(95%CI: 山 东 大 学 学 报 (医 学 版)55卷6期 -孙苑潆,等.健康管理人群代谢综合征发病风险预测模型 \=- 0.734-0.756)in the male and female model, respectively. The OE ratio was 1.03 and 1.00 in the male and female model, respectively. Conclusion This study has constructed a 5-year risk model that could be informative for identifying individuals at a high risk of developing MetS in a health management population.

Key words: Health management population, Metabolic syndrome, Longitudinal cohort, Prediction model, Coxs proportional hazards regression

CLC Number: 

  • R589
[1] 中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2013年版)[J]. 中华内分泌代谢杂志, 2014, 30(10): 26-89. Chinese Diabetes Society. China guideline for type 2 diabetes[J]. Chin J Endocrinol Metab, 2014, 30(10): 26-89.
[2] Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey[J]. JAMA, 2002, 287(3): 356-359.
[3] Beltrán-Sánchez H, Harhay MO, Harhay MM, et al. Prevalence and trends of metabolic syndrome in the adult U.S. population, 1999-2010[J]. J Am Coll Cardiol, 2013, 62(8): 697-703.
[4] Gu D, Reynolds K, Wu X, et al. Prevalence of the metabolic syndrome and overweight among adults in China[J]. Lancet, 2005, 365(9468): 1398-1405.
[5] Villegas R, Xiang YB, Yang G, et al. Prevalence and determinants of metabolic syndrome according to three definitions in middle-aged Chinese men[J]. Metab Syndr Relat Disord, 2009, 7(1): 37-45.
[6] Li G, de Courten M, Jiao S, et al. Prevalence and characteristics of the metabolic syndrome among adults in Beijing, China[J]. Asia Pac J Clin Nutr, 2010, 19(1): 98-102.
[7] Xiao J, Wu CL, Gao YX, et al. Prevalence of metabolic syndrome and its risk factors among rural adults in Nantong, China[J]. Sci Rep, 2016, 6: 38089. doi: 10.1038/srep38089.
[8] Kassi E, Pervanidou P, Kaltsas G, et al. Metabolic syndrome: definitions and controversies[J]. BMC Med, 2011, 9: 48. doi: 10.1186/1741-7015-9-48.
[9] Ford ES. The metabolic syndrome and mortality from cardiovascular disease and all-causes: findings from the National Health and Nutrition Examination Survey II Mortality Study[J]. Atherosclerosis, 2004, 173(2): 309-314.
[10] Grundy SM, Cleeman JI, Daniels SR, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement[J]. Circulation, 2005, 112(17): 2735-2752.
[11] Wilson PW, D'Agostino RB, Parise H, et al. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus[J]. Circulation, 2005, 112(20): 3066-3072.
[12] Yang XH, Tao QS, Sun F, et al. Setting up a risk prediction model on metabolic syndrome among 35-74 year-olds based on the Taiwan MJ Health-checkup Database[J]. Chin J Epidemiol, 2013, 34(9): 874-878.
[13] Hsiao FC, Wu CZ, Hsieh CH, et al. Chinese metabolic syndrome risk score[J]. South Med J, 2009, 102(2): 159-164.
[14] 中华医学会糖尿病学分会代谢综合征研究协作组. 中华医学会糖尿病学分会关于代谢综合征的建议[J]. 中华糖尿病杂志, 2004, 12(3): 156-161. Metabolic syndrome research collaboration group from Chinese Diabetes Society. Suggestions on metabolic syndrome from Chinese Diabetes Society[J]. Chin J Diabetes, 2004, 12(3): 156-161.
[15] Kaur J. A comprehensive review on metabolic syndrome[J]. Cardiol Res Pract, 2014, 2014:943162. doi:10.1155/2014/943162.
[16] Jiang B, Li B, Wang Y, et al. The nine-year changes of the incidence and characteristics of metabolic syndrome in China: longitudinal comparisons of the two cross-sectional surveys in a newly formed urban community[J]. Cardiovasc Diabetol, 2016, 15:84. doi: 10.1186/s12933-016-0402-9.
[17] Lu J, Wang L, Li M, et al. Metabolic syndrome among adults in China - the 2010 China noncommunicable disease surveillance[J]. J Clin Endocrinol Metab, 2017, 102(2): 507-515.
[18] Sheu WH, Chuang SY, Lee WJ, et al. Predictors of incident diabetes, metabolic syndrome in middle-aged adults: a 10-year follow-up study from Kinmen, Taiwan[J]. Diabetes Res Clin Pract, 2006, 74(2): 162-168.
[19] Yu S, Guo X, Yang H, et al. An update on the prevalence of metabolic syndrome and its associated factors in rural northeast China[J]. BMC Public Health, 2014, 14: 877. doi: 10.1186/1471-2458-14-877.
[20] Tao LX, Li X, Zhu HP, et al. Association of hematological parameters with metabolic syndrome in Beijing adult population: a longitudinal study[J]. Endocrine, 2014, 46(3): 485-495.
[21] Regitz-Zagrosek V, Lehmkuhl E, Weickert MO. Gender differences in the metabolic syndrome and their role for cardiovascular disease[J]. Clin Res Cardiol, 2006, 95(3): 136-147.
[22] Zhou P, Meng Z, Liu M, et al. The associations between leukocyte, erythrocyte or platelet, and metabolic syndrome in different genders of Chinese[J]. Medicine, 2016, 95(44): e5189. doi: 10.1097/MD.0000000000005189
[23] Hwang LC, Bai CH, Chen CJ, et al. Gender difference on the development of metabolic syndrome: a population-based study in Taiwan[J]. Eur J Epidemiol, 2007, 22(12): 899-906.
[24] Park YW, Zhu S, Palaniappan L, et al. The metabolic syndrome: Prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988-1994[J]. Arch Intern Med, 2003, 163(4): 427-436.
[25] Li JB, Wang X, Zhang JX, et al. Metabolic Syndrome: prevalence and risk factors in southern China[J]. J Int Med Res, 2010, 38(3): 1142-1148.
[26] Wang F, Wu S, Song Y, et al. Waist circumference, body mass index and waist to hip ratio for prediction of the metabolic syndrome in Chinese[J]. Nutr Metab Cardiovasc Dis, 2009, 19(8): 542-547.
[27] Zhou XH, Song XX, Ji LN. The components of metabolic syndrome analyzed by factor analysis[J]. J Diabetes, 2005, 13(6): 434-436.
[28] Dai X, Yuan J, Yao P, et al. Association between serum uric acid and the metabolic syndrome among a middle- and old-age Chinese population[J]. Eur J Epidemiol, 2013, 28(8): 669-676.
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