Deepa Pandit-Agrawal1, Anuradha Khadilkar2, Shashi Chiplonkar1, Vaman Khadilkar3, Vivek Patwardhan1. 1. Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, 32, Sassoon Road, Pune, 411 001, India. 2. Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, 32, Sassoon Road, Pune, 411 001, India. anuradhavkhadilkar@gmail.com. 3. Jehangir Hospital, Pune, India.
Abstract
OBJECTIVES: To develop and to evaluate efficacy of screening score for early detection of cardio-metabolic risk (CMR) in adults. METHODS: Cross-sectional data on anthropometry, lipids, sugar levels, diet, and physical activity were collected on 720 adults (361 men, 35-50 year) using standardized techniques. Screening score was developed using regression analysis-cluster of risk conditions (blood pressure, lipids, and sugar levels) was dependent variable against age, sex, waist, diet, and physical activity as independent variables. Odd ratios were added to obtain final score and receiver-operating characteristic (ROC) curves were constructed to identify cut-off value of CMR score. RESULTS: Mean age and BMI were 42.7 ± 9.4 years and 25.7 ± 5.0 kg/m2. Analysis showed age, male sex, waist, lack of fruits, green leafy vegetables, and lack of physical activity were independent predictors for increased CMR (p < 0.05). Total score ranged from 0 to 20. Area under the curve for ROC was 0.728 [95% (CI) 0.67-0.78]. Criterion value >8 had sensitivity (76%) and specificity (56%) for screening cases with CMR. CONCLUSIONS: Screening score is a pragmatic way of identifying individuals with CMR without performing biochemical tests. Cost-effective community screening programs may be planned.
OBJECTIVES: To develop and to evaluate efficacy of screening score for early detection of cardio-metabolic risk (CMR) in adults. METHODS: Cross-sectional data on anthropometry, lipids, sugar levels, diet, and physical activity were collected on 720 adults (361 men, 35-50 year) using standardized techniques. Screening score was developed using regression analysis-cluster of risk conditions (blood pressure, lipids, and sugar levels) was dependent variable against age, sex, waist, diet, and physical activity as independent variables. Odd ratios were added to obtain final score and receiver-operating characteristic (ROC) curves were constructed to identify cut-off value of CMR score. RESULTS: Mean age and BMI were 42.7 ± 9.4 years and 25.7 ± 5.0 kg/m2. Analysis showed age, male sex, waist, lack of fruits, green leafy vegetables, and lack of physical activity were independent predictors for increased CMR (p < 0.05). Total score ranged from 0 to 20. Area under the curve for ROC was 0.728 [95% (CI) 0.67-0.78]. Criterion value >8 had sensitivity (76%) and specificity (56%) for screening cases with CMR. CONCLUSIONS: Screening score is a pragmatic way of identifying individuals with CMR without performing biochemical tests. Cost-effective community screening programs may be planned.
Entities:
Keywords:
Adults; Cardio-metabolic risk; Early detection; India; Screening
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