期刊论文详细信息
Journal of Diabetes & Metabolic Disorders
Prevalence of metabolic syndrome in Nepalese type 2 diabetic patients according to WHO, NCEP ATP III, IDF and Harmonized criteria
Pramod Shankar Shukla3  Ram Chandra Kafle1  Shreedhar Acharya2  Naval Kishor Yadav3  Manoj Sigdel3  Dipendra Khadka4  Daya Ram Pokharel3 
[1] Department of Internal Medicine, Manipal College of Medical Sciences and Teaching Hospital, Pokhara, Nepal;Department of Planning and Research, Cambrian College of Arts and Technology, 1400 Barrydowne Road, Sudbury P3A 3 V8, ON, Canada;Department of Biochemistry, Manipal College of Medical Sciences and Teaching Hospital, Pokhara, Nepal;Department of Laboratory Medicine, Gandaki Medical College Teaching Hospital and Research Center, Prithvi Chowk, Pokhara, Nepal
关键词: Manipal Teaching Hospital;    Pokhara;    Nepal;    Type 2 diabetes mellitus;    Metabolic syndrome;    Prevalence;   
Others  :  1136046
DOI  :  10.1186/s40200-014-0104-3
 received in 2014-02-12, accepted in 2014-10-21,  发布年份 2014
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【 摘 要 】

Background

Metabolic syndrome (MetS) present in type 2 diabetic patients greatly increases the risk of strokes and cardiovascular diseases. Timely detection and mapping of MetS facilitates appropriate preventive and therapeutic approaches to minimize these risks. Our study aimed to determine the prevalence of MetS among Nepalese type 2 diabetic patients using WHO (1999), NCEP ATP III (2001), IDF (2005) and Harmonized (2009) definitions and identify the diagnostic concordance and disparity resulting from these four definitions.

Methods

Clinical and biochemical data were collected for 1061 type 2 diabetic patients at Manipal Teaching Hospital, Pokhara, Nepal. The data was analyzed in order to identify prevalence of MetS in these patients. Statistical analysis included usage of Student’s t- and Chi-square tests, kappa statistics and 95% confidence intervals.

Results

The total age adjusted prevalence rates of MetS were 80.3%, 73.9%, 69.9% and 66.8% according to Harmonized, NCEP ATP III, WHO and IDF definitions, respectively. Prevalence increased with the age and was higher in females (p <0.001) according to WHO, NCEP ATP III and Harmonized definitions. Patients of Dalit community had the highest prevalence (p<0.05) according to NCEP ATP III and Harmonized definitions while Mongoloid and Newar patients had the highest prevalence (p <0.05) according to WHO and IDF definitions, respectively. Prevalence was also highest among patient engaged in agriculture occupation. Central obesity and hypertension were respectively the most and the least prevalent components of MetS. The highest overall agreement was between Harmonized and NCEP ATP III definitions (κ =0.62, substantial) and the lowest between WHO & IDF definitions (κ=0.26, slight). The Harmonized definition had the highest sensitivity (99.9%) and negative predictive value (98.9%) while NCEP ATP III definition had the highest specificity (98.9%) and positive predictive values (99.9%) in identifying the cases of MetS.

Conclusions

The prevalence of MetS among Nepalese type 2 diabetic patients was very high suggesting that these patients were at increased risk of strokes, cardiovascular diseases and premature death. The Harmonized definition was the most sensitive while NCEP ATP III and IDF definitions were the most specific in detecting the presence of MetS in Nepalese type 2 diabetic patients.

【 授权许可】

   
2014 Pokharel et al.; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Kassi E, Panagiota Pervanidou P, Kaltsas G, Chrousos G: Metabolic syndrome: definitions and controversies. BMC Med 2011, 9:48. BioMed Central Full Text
  • [2]Reaven G: Metabolic syndrome: pathophysiology and implications for management of cardiovascular diseases. Circulation 2002, 106:286-288.
  • [3]Lindsay RS, Howard BV: Cardiovascular risk associated with the metabolic syndrome. Curr Diab Rep 2004, 4:63-68.
  • [4]Hanley AJ, Festa A, D’Agostino RB Jr, Wagenknecht LE, Savage PJ, Tracy RP, Saad MF, Haffner SM: Metabolic and inflammation variable clusters and prediction of type 2 diabetes: factor analysis using directly measured insulin sensitivity. Diabetes 2004, 53:1773-1781.
  • [5]Alberti KG, Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998, 15:539-553.
  • [6]Executive summary of the third report of the national cholesterol education program (NCEP) JAMA 2001, 285:2486-2497.
  • [7]Alberti KG, Zimmet P, Shaw J: IDF epidemiology task force consensus group. The metabolic syndrome: a new worldwide definition. Lancet 2005, 366:1059-1062.
  • [8]Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA: Harmonizing the metabolic syndrome. A joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; World heart federation; International atherosclerosis society; and International association for the study of obesity. Circulation 2009, 120:1640-1645.
  • [9]Shaw JE, Sicree RA, Zimmet PZ: Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010, 87:4-14.
  • [10]Jayawardena R, Ranasinghe P, Byrne NM, Soares MJ, Katulanda P, Andrew P, Hills AP: Prevalence and trends of the diabetes epidemic in South Asia: a systematic review and meta-analysis. BMC Public Health 2012, 12:380. BioMed Central Full Text
  • [11]Alexander CM, Landsman PB, Teutsch SM, Haffner SM: NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes 2003, 52:1210-1214.
  • [12]Hunt KJ, Resendez RG, Williams K, Haffner SM, Stern MP: National cholesterol education program versus World Health Organization metabolic syndrome in relation to all-cause and cardiovascular mortality in the San Antonio heart study. Circulation 2004, 110:1251-1257.
  • [13]Tong PC, Kong AP, So WY, Yang X, Ho CS, Ma RC, Ozaki R, Chow CC, Lam CW, Chan JC, Cockram CS: The usefulness of the International Diabetes Federation and the National Cholesterol Education Program’s Adult Treatment Panel III definitions of the metabolic syndrome in predicting coronary heart disease in subjects with type 2 diabetes. Diabetes Care 2007, 30:1206-1211.
  • [14]Protopsaltis I, Nikolopoulos G, Dimou E, Brestas P, Kokkoris S, Korantzopoulos P, Melidonis A: Metabolic syndrome and its components as predictors of all-cause mortality and coronary heart disease in type 2 diabetic patients. Atherosclerosis 2007, 195:189-194.
  • [15]Sharma SK, Ghimire A, Radhakrishnan J, Thapa L, Shrestha NR, Paudel N, Gurung KRM, Budathoki A, Baral N, Brodie D: Prevalence of hypertension, obesity, diabetes, and metabolic syndrome in Nepal. Int J Hypertens 2011, 2011:821971.
  • [16]Shrestha R, Jha SC, Khanal M, Gyawali P, Yadav BK, Jha B: Association of cardiovascular risk factors in hypertensive subjects with metabolic syndrome defined by three different definitions. JNMA 2011, 51:157-163.
  • [17]Bhattarai S, Kohli SC, Sapkota S: Prevalence of metabolic syndrome in type 2 diabetes mellitus patients using NCEP/ATP III and IDF criteria in Nepal. Nepal J Med Sci 2012, 1:79-83.
  • [18]Tamang HK, Timilsina U, Thapa S, Singh KP, Shrestha S, Singh P, Shrestha B: Prevalence of metabolic syndrome among Nepalese type 2 diabetic patients. Nepal Med Coll J 2013, 15:50-55.
  • [19]World Health Organisation: Definition and diagnosis of diabetes mellitus and intermediate hyperglycemia: report of a WHO/IDF consultation. 2006.
  • [20]The Asia-Pacific perspective: Redefining obesity and its treatment Health Communications Australia 2000.
  • [21]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 1972, 18:499-502.
  • [22]Keyfitz N: Sampling variance of standardized mortality rates. Human Biol 1966, 38:309-317.
  • [23]Agresti A, Coull BA: Approximate is better than “exact” for interval estimation of binomial proportions. Am Stat 1998, 52:119-126.
  • [24]Central Bureau of Statistics, Government of Nepal: National Population and Housing Census 2011 (A national report). Kathmandu; 2012.
  • [25]Landis JR, Koch GG: The measurement of observer agreement for categorical data. Biometrics 1977, 33:159-174.
  • [26]Deepa M, Farooq S, Datta M, Deepa R, Mohan V: Prevalence of metabolic syndrome using WHO, ATP III and IDF definitions in Asian Indians: the Chennai Urban Rural Epidemiology Study (CURES-34). Diabetes Metab Res Rev 2007, 23:127-134.
  • [27]Motala AA, Esterhuizen T, Pirie FJ, Omar MAK: The prevalence of metabolic syndrome and determination of the optimal waist circumference cut-off points in a rural South African community. Diabetes Care 2011, 34:1032-1037.
  • [28]Katulanda P, Ranasinghe P, Jayawardana R, Sheriff R, Matthews DR: Metabolic syndrome among Sri Lankan adults: prevalence, patterns and correlates. Diabetol Metab Syndr 2012, 4:24. BioMed Central Full Text
  • [29]Ogbera OA: Prevalence and gender distribution of the metabolic syndrome. Diabetol Metab Syndr 2010, 2:1. BioMed Central Full Text
  • [30]Tan MC, Ng OC, Wong TW, Joseph A, Chan YM, Hejar AR: Prevalence of metabolic syndrome in type 2 diabetic patients: a comparative study using WHO, NCEP ATP III, IDF and Harmonized definitions. Health 2013, 5:1689-1696.
  • [31]Kengne AP, Limen SN, Sobngwi E, Djouogo CFT, Nouedoui C: Metabolic syndrome in type 2 diabetes: comparative prevalence according to two sets of diagnostic criteria in sub-Saharan Africans. Diabetol Metab Syndr 2012, 4:22. BioMed Central Full Text
  • [32]Cameron AJ, Magliano DJ, Zimmet PZ, Welborn T, Shaw JE: The metabolic syndrome in Australia: prevalence using four definitions. Diabetes Res Clin Pract 2007, 77:471-478.
  • [33]Niroula BP: Caste/ethnic composition of Nepal. CNAS J 1998, 25:15-56.
  • [34]Ardern CI, Katzmarzyk PT: Geographic and demographic variation in the prevalence of the metabolic syndrome in Canada. Can J Diabetes 2007, 31:34-46.
  • [35]Santos AC, Ebrahim S, Barros H: Gender, socio-economic status and metabolic syndrome in middle-aged and old adults. BMC Public Health 2008, 8:62. BioMed Central Full Text
  • [36]Sánchez-Chaparro MA, Calvo-Bonacho E, González-Quintela A, Fernández-Labandera C, Cabrera M, Sáinz JC, Fernández-Meseguer A, Banegas JR, Ruilope LM, Valdivielso P, Román-García J: Occupation-related differences in the prevalence of metabolic syndrome. Diabetes Care 2008, 31:1884-1885.
  • [37]de Simone G, Devereux RB, Chinali M, Best LG, Lee ET, Galloway JM, Resnick HE: Prognostic impact of metabolic syndrome by different definitions in a population with high prevalence of obesity and diabetes: The strong heart study. Diabetes Care 2007, 30:1851-1856.
  • [38]Enas EA, Mohan V, Deepa M, Farooq S, Pazhoor S, Chennikkara H: Metabolic Syndrome among Asian Indians: A population with high rates of diabetes and premature heart disease. J Cardiometab Syndr 2007, 2:267-275.
  • [39]Ahmed A, Khan TE, Yasmeen T, Awan S, Islam N: Metabolic syndrome in type 2 diabetes: comparison of WHO, modified ATPIII & IDF criteria. J Pak Med Assoc 2012, 62:574-579.
  • [40]Yadav D, Mahajan S, Subramanian SK, Bisen PS, Chung CH, Prasad GBKS: Prevalence of metabolic syndrome in type 2 diabetes mellitus using NCEP-ATPIII, IDF and WHO definition and its agreement in Gwalior Chambal Region of Central India. Global J Health Sci 2013, 5:144-155.
  • [41]Laakso M: Cardiovascular disease in type 2 diabetes from population to man to mechanisms. Diabetes Care 2010, 33:442-449.
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