RESEARCH associated with industrialization and socio-economic development.Prevalence rates of

RESEARCH ARTICLEBMI OR IDRS-WHICH IS THE BETTER PREDICTOR OF RISK FOR DEVELOPING DIABETESMELLITUS SOUTH INDIAN STUDY1Vedapriya Dande Rajasekar, 1Mittal Anuj, 2Lavanya Krishnagopal, 3Kavita, V.,4Umamaheswari, K. and 5Balamuruganvelu. S.1Dept. of Community Medicine, Aarupadai Veedu Medical College and Hospital, Kirumampakkam, Puducherry2Dept. of Pathology, Aarupadai Veedu Medical College and Hospital, Kirumampakkam,, Puducherry3Dept. of Community Medicine, Indira Gandhi Medical College and Research Institute, Puducherry4Dept. of Physiology, Indira Gandhi Medical College and Research Institute, Puducherry5Dept. of Microbiology, Madha Medical College and Research Institute, ChennaiARTICLE INFO ABSTRACTBackground: Diabetes mellitus (DM) is an “Iceberg disease”. Worldwide there are about 150million estimated cases of diabetes and is predicted to double by 2025. The rising prevalence of DMin developing countries is closely associated with industrialization and socio-economic development.Prevalence rates of diabetes are increasing rapidly in both urban and rural India. Hence this studyhas been undertaken to find at risk individuals before onset of the disease in our service area.Aim: To assess the risk of diabetes mellitus in adults ?20 years by using Indian Diabetic Risk Score,in rural area of Pondicherry.Methods : A community based cross-sectional study conducted in a village under rural service areaof Community Medicine Department. Data collected were entered and analyzed on SPSS software.Test applied were Simple proportion, Chi square test, sensitivity and specificity.Results: A total of 379 adults aged ? 20 years participated in the study, of which 200 (52.8%) weremales and 179 (47.2%) were females. By using IDRS score 22.4% were with low risk, 48% withmoderate and 29.6% were found to have high risk score, among them 1.2%, 15.4% and 34% wereknown to have diabetes respectively. Performance of IDRS and BMI for diagnosing diabetes mellitusshowed, sensitivity and positive predictive value 56.71%, 33.92%, and 29.85%, 22.22% for IDRSand BMI respectively.Conclusion: IDRS is the better tool to detect undiagnosed diabetes when compared to BMI. It is aneasy and cost effective tool which can be applied to mass for screening high risk individuals. GTThas to be done among subjects with high risk score (IDRS>60) to detect early occurrence of diabetes.Copy Right, IJCR, 2012, Academic Journals. All rights reserved.INTRODUCTIONDiabetes mellitus (DM) is an “Iceberg disease”. Worldwidethere are about 150 million estimated cases of diabetes and ispredicted to double by 2025 1. The rising prevalence of DMin developing countries is closely associated withindustrialization and socio-economic development 2. In Indiathere are 40 million people estimated to have diabetes and it hasearned the dubious distinction as diabetic capital of the world3. The study done in the year 2000 by Indian Council ofMedical Research (ICMR) reported a prevalence of 2.3% inurban areas and 1% in rural areas, had increased to 12-19%and 4-10% respectively and it was reported to be 13.2% inother studies 4-6. Thus, prevalence rates of diabetes areincreasing rapidly in both urban and rural India. The aim of thisstudy is to use Indian Diabetic Risk Score (IDRS) developed byMohan et al to assess the risk of diabetes mellitus in adults ?20years, in rural area of Pondicherry 7.*Corresponding author: [email protected] AND METHODSStudy design and settingA community based cross-sectional study was designed toestimate the risk of Diabetes by using IDRS in selected villageof Pondicherry. The study was conducted in the field practicearea of Rural Health Training Centre (RHTC), Manapet,Department of Community Medicine, Aarupadai VeeduMedical College and Hospital, Pondicherry. There are fivevillages under RHTC, Manapet. A stratified random samplewas taken from each village. All the available adults aged 20years and above from each selected house were included, afterobtaining their oral informed consent. Adults aged <20 years,pregnant mother and those who had not given consent and notpresent at the time of interview were excluded.Study questionnaireA team of trained doctors administered a pre-designed and pretestedquestionnaire and elicited information from the studyparticipants on demographic factors (age, gender, marital status,ISSN: 0975-833XAvailable online at http://www.journalcra.comInternational Journal of Current ResearchVol. 4, Issue, 10, pp.149-151, October, 2012INTERNATIONAL JOURNALOF CURRENT RESEARCHArticle History:Received 18th July, 2012Received in revised form14thAugust, 2012Accepted 17th September, 2012Published online 23rd October, 2012xxxxxxxxxxxxxxxKey words:Risk factors,rural community,diabetes mellitus,IDRSlevel of education), socioeconomic factors (household incomeand occupation), family history of diabetes, lifestyle factor likesedentary life style and details on physical activity. Standardtechniques were used to measure height, weight and waistcircumference. By using modified B G Prasad classification(calculated based on CPI of April 2011) socio-economic statusSES was assessed 8 and grade of physical activity wasassessed by using our previous study9. Mohan et al. hasdeveloped Indian diabetes risk score (IDRS) which was used todetect high -risk cases. 10. The parameters for IDRS scorecomprises of two modifiable (waist circumference & physicalactivity) and two non-modifiable risk factors (age & familyhistory) for diabetes. If age <35 years score is = 0, if 35-49years score is=20, if >50 years score= 30, waist circumference<80 cm for female and <90cm for male score = 0, >80-89 cmfor female and >90-99 cm male score=10, >90 cm for femaleand >100 cm for male score=20, physical activities vigorousexercise or strenuous work score=0, moderate exercise workhome=10, mild exercise work/ home = 20, no exercise andsedentary work-home =30, family history of diabetes, no familyhistory = 0, family history present either parent = 10, bothparents =20. After addition of all four parameters, the score isinterpreted as risk score greater than 60 very high risk, 30-50moderate risk and less than 30 low risk.Statistical data analysisThe data collected were entered and analyzed Simpleproportions (%) Chi square test, sensitivity and specificity)using SPSS 11.5 (SPSS Inc., Chicago, IL, USA).RESULTS A total of 379 adults aged ? 20 years participated in the study,of which 200 (52.8%) were males and 179 (47.2%) werefemales. More than fifty percent were found to be illiterates(56%). Nearly 45.1% of individuals were sedentary workersand only 15.3% were found as heavy workers. Maximumnumbers (63.8%) of participants belong to upper and uppermiddle class, while only 4.2% belong to lower class accordingto Modified B.G. Prasad’s classification. There is significantassociation of diabetes with age, female gender, illiterates andsedentary workers (table 1). According to IDRS score 22.4%were with low risk score, 48% with moderate and 29.6% werefound to have high risk score, among them 1.2%, 15.4% and34% were known to have diabetes respectively.(table2).Performance of IDRS and BMI for diagnosing diabetes mellitusshowed, sensitivity and positive predictive value 56.71%,33.92%, and 29.85%, 22.22% for IDRS and BMI respectively.DISCUSSIONDeveloping country like India, predicted to be the future capitalfor diabetes, needs a simple and cost-effective tool to screenand detect high risk individuals prior to onset of disease. Onesuch tool was developed by Mohan et al (2005) 7 at Chennaiis IDRS (Indian Diabetic Risk Score). American DiabetesAssociation has also recommended this IDRS score 11. Hencewe had applied IDRS to detect at risk individuals. According toour study 30% of the individuals were under high risk group,whereas it was 43% and 19% in similar study done by Mohanet al (2005) 7 at Chennai and Sanjay Kumar Gupta et al(2010) 12 done at Chunampett and Annechikuppam of TamilNadu. In the present study we found that 17.7% were knowndiabetes, whereas it was 6% in a study done by Sanjay KumarGupta et al (2010) 12 and 4.9% in a study done by Anil.JPurty et al (2009) 13.Table 1. Socio-demographic risk variables for diabetes mellitusS.NoVariablesKnown case of DMChi SquaredfP valueYes No Total n=379(%)1 Age <35 6 (5.08) 112 (94.92) 118(31.1) 62.73 2 <.000135-49 7 (5.98) 110 (94.92) 117(30.9)>50 54 (37.50) 90 (62.50) 144(38)2 Gender Female 45 (25.14) 134 (74.86) 179(47.2) 12.02 1 0.0005Male 22 (11.00) 178 (89.00) 200(52.8)3 Education Illiterate 43 (25.15) 128 (74.85) 212(56) 13.13 2 0.0014Primary & Middle 20 (13.33) 130 (86.67) 57(15)Secondary & above 4 (6.90) 54 (93.10) 110(29)4 Occupational Sedentary 50 (23.58) 162 (76.42) 171(45.1)) 11.8 2 0.0027Moderate 7 (12.28) 50 (87.72) 150(39.6)Heavy 10 (9.09) 100 (90.91) 58(15.3)5 SES I class (Upper class) 13 (12.62) 90 (87.38) 103(27.2) 10.45 4 0.03II class (Upper middle) 25 (17.99) 114 (82.01) 139(36.7)III class (Middle) 21 (28.00) 54 (72.00) 75(19.8)IV class (Lower middle) 4 (8.70) 42 (91.30) 46(12.1)V class (Lower) 4 (25.00) 12 (75.00) 16(4.2)Table 2. Performance of BMI& IDRS for diagnosing Diabetes MellitusS. No BMI/KDM(%) (95% CI) IDRS/KDM(%) (95%CI)1 Sensitivity 29.85 (19.59-42.43) 56.71 (44.08-68.57)2 Specificity 77.56 (72.44-82.98) 76.28 (71.09-80.08)3 Positive predictive value 22.22 (14.41-3245) 33.92 (25.41-43.55)4 Negative predictive value 84.73 (78.85-87.69) 89.13 (84.62-92.48)5 False Positive 77.77 (67.54-85.58) 66.07 (56.44-74.58)6 False Negative 16.26 (12.30-21.14) 10.86 (07.12-15.37)Table 3. Level of risk of diabetic case with IDRSLevel of risk Risk Score No. of persons (%) Diabetic cases (%)Low risk <30 85(22.42) 1 (1.2)Moderate risk 30-50 182(48.02%) 28(15.38)High risk >60 112(29.55) 38(33.92)150 International Journal of Current Research, Vol. 4, Issue, 10, pp. 149-151, October, 2012Sensitivity and specificity for IDRS (High risk score >60) was56.7% and 76.3% respectively In this study, whereas in thestudy done by Mohan et al at (2005) 7 Chennai it was 62.2%and 73.7% respectively and it was 94.68 and 44.87% in a studyby S Nandeshwar1 et al (2010) 14 . The IDRS score whenapplied for known diabetes we found 33.92% had high risksore, whereas in the study by S.Nandeshwar1 et al (2010) 14it was 51.6% and study by Sanjay Kumar Gupta et al (2010)12 it was only 6%. Many such type of studies by usingdiabetes risk score with different criteria were used to detectundiagnosed diabetes in developed countries 15-18. Thedifference in results is due to studies done at differentgeographical settings.ConclusionWe conclude from our study that IDRS is the better tool todetect undiagnosed diabetes when compared to BMI. It is alsoan easy and cost effective tool to be applied for mass forscreening of high risk individuals. GTT has to be done amongsubjects with high risk score (IDRS>60) to detect theoccurrence of diabetes early.LimitationSurvey was carried out during the working hours (9.00am2.00pm), hence in this study the proportion of older people andhomemakers are more.REFERENCESAnil J Purty, DR Vedapriya, Joy Bazoy, Sanjay Kumar Gupta,, J Cherian, Mohan Vishwanathan. Prevalence of diagnoseddiabetes in an urban area of Pudhucherry, India-Time forprevention. Int J Diab Dev Ctries/ Januay-March 2009/Volume 29/Issue 1.Ahuja MM, Sivaji L, Garg VK, Mitroo P. Prevalence ofdiabetes in northern India (Delhi area). Horm Metab Res1974;4:321-4.Available from: AmericanDiabetes Association for identifying high risk individuals.last accessed on 2008 JunChow CK, Raju PK, Raju R, Reddy KS, Cardona M,Celermajer DS, et al. The prevalence and management ofdiabetes in rural India. Diabetes Care 2006;29:1717-8.Glümer C, Carstensen B, Sandbaek A, Lauritzen T, JørgensenT, Borch-Johnsen K, et al. 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Belgium: InternationalDiabetes Federation; 2006;15-103.Spijkerman AM, Yuyun MF, Griffin SJ, Dekker JM, Nijpels G,Wareham NJ. The performance of a risk score as ascreening test for undiagnosed hyperglycemia in ethnicminority groups: Data from the 1999 health survey forEngland. Diabetes Care 2004;27:116-22.The Textbook of Community Medicine With Recent Advancesby Suryakantha A H 2nd edition 2010 pg. 679-680WHO (2003), Tech. Rep. Ser., N 916.151 International Journal of Current Research, Vol. 4, Issue, 10, pp. 149-151, October, 2012*******


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