Risk Factors of Diabetes Mellitus in Rural Puducherry

Purpose: Prevalence of type 2 diabetes is increasing in India. Rural area constitutes 80% of India. Hence it is essential to understand the epidemiology for appropriate interventions. Objectives: to identify risk factors of type 2 diabetes mellitus in rural Puducherry. Methodology: Cross sectional s...

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Main Authors: Sumanth Mallikarjuna Majgi, Bala Soudarssanane M, Gautam Roy, Ashok Kumar Das
Format: Article
Language:English
Published: Light House Polyclinic Mangalore 2012-04-01
Series:Online Journal of Health & Allied Sciences
Subjects:
Online Access:http://www.ojhas.org/issue41/2012-1-4.htm
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spelling doaj-6da2b140923442edb0466008120bb8432020-11-24T22:27:15ZengLight House Polyclinic Mangalore Online Journal of Health & Allied Sciences0972-59972012-04-01111Risk Factors of Diabetes Mellitus in Rural PuducherrySumanth Mallikarjuna MajgiBala Soudarssanane MGautam RoyAshok Kumar DasPurpose: Prevalence of type 2 diabetes is increasing in India. Rural area constitutes 80% of India. Hence it is essential to understand the epidemiology for appropriate interventions. Objectives: to identify risk factors of type 2 diabetes mellitus in rural Puducherry. Methodology: Cross sectional study in two villages of Puducherry, India. 1403 subjects above 25 years from 2 villages. Study measured demographic variables, Body Mass Index (BMI), physical activity, family history of Diabetes Mellitus, smoking and alcohol consumption. Fasting blood glucose was measured for study subjects. Further, those with >126 mg/dl were subjected for Oral Glucose Tolerance Test. Univariate and multivariate analysis was done. Receiver Operating characteristic Curve was plotted to find out cut off for Diabetic Risk Score. Findings: The prevalence of type 2 Diabetes Mellitus (DM) was 5.8%. The response rate was (88%). In univariate analysis age, occupation, Socio Economic Status, BMI, physical activity, family history were significant for DM. In multivariate analysis age, BMI, family history of diabetes and occupation were significant for type 2 DM. The ‘diabetes risk score’ generated by the study using age, BMI and family history of DM, had specificity, sensitivity and accuracy of 54%, 77% and 76.2% respectively. The area under curve for scoring system was 0.784 (<0.05). Conclusions: Identified risk factors are useful for early diagnosis by using ‘diabetes risk score’ – thus uncovering the iceberg of disease. http://www.ojhas.org/issue41/2012-1-4.htmType 2 DiabetesRisk factorsDiabetes risk scoring.
collection DOAJ
language English
format Article
sources DOAJ
author Sumanth Mallikarjuna Majgi
Bala Soudarssanane M
Gautam Roy
Ashok Kumar Das
spellingShingle Sumanth Mallikarjuna Majgi
Bala Soudarssanane M
Gautam Roy
Ashok Kumar Das
Risk Factors of Diabetes Mellitus in Rural Puducherry
Online Journal of Health & Allied Sciences
Type 2 Diabetes
Risk factors
Diabetes risk scoring.
author_facet Sumanth Mallikarjuna Majgi
Bala Soudarssanane M
Gautam Roy
Ashok Kumar Das
author_sort Sumanth Mallikarjuna Majgi
title Risk Factors of Diabetes Mellitus in Rural Puducherry
title_short Risk Factors of Diabetes Mellitus in Rural Puducherry
title_full Risk Factors of Diabetes Mellitus in Rural Puducherry
title_fullStr Risk Factors of Diabetes Mellitus in Rural Puducherry
title_full_unstemmed Risk Factors of Diabetes Mellitus in Rural Puducherry
title_sort risk factors of diabetes mellitus in rural puducherry
publisher Light House Polyclinic Mangalore
series Online Journal of Health & Allied Sciences
issn 0972-5997
publishDate 2012-04-01
description Purpose: Prevalence of type 2 diabetes is increasing in India. Rural area constitutes 80% of India. Hence it is essential to understand the epidemiology for appropriate interventions. Objectives: to identify risk factors of type 2 diabetes mellitus in rural Puducherry. Methodology: Cross sectional study in two villages of Puducherry, India. 1403 subjects above 25 years from 2 villages. Study measured demographic variables, Body Mass Index (BMI), physical activity, family history of Diabetes Mellitus, smoking and alcohol consumption. Fasting blood glucose was measured for study subjects. Further, those with >126 mg/dl were subjected for Oral Glucose Tolerance Test. Univariate and multivariate analysis was done. Receiver Operating characteristic Curve was plotted to find out cut off for Diabetic Risk Score. Findings: The prevalence of type 2 Diabetes Mellitus (DM) was 5.8%. The response rate was (88%). In univariate analysis age, occupation, Socio Economic Status, BMI, physical activity, family history were significant for DM. In multivariate analysis age, BMI, family history of diabetes and occupation were significant for type 2 DM. The ‘diabetes risk score’ generated by the study using age, BMI and family history of DM, had specificity, sensitivity and accuracy of 54%, 77% and 76.2% respectively. The area under curve for scoring system was 0.784 (<0.05). Conclusions: Identified risk factors are useful for early diagnosis by using ‘diabetes risk score’ – thus uncovering the iceberg of disease.
topic Type 2 Diabetes
Risk factors
Diabetes risk scoring.
url http://www.ojhas.org/issue41/2012-1-4.htm
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