General Practice and Primary Care - Research Publications
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ItemMetabolic Score for Visceral Fat (METS-VF) Estimation - A Novel Cost-Effective Obesity Indicator for Visceral Adipose Tissue Estimation(DOVE MEDICAL PRESS LTD, 2020)BACKGROUND: Visceral adipose tissue (VAT) assessment is limited in clinical practice due to expensive, time consuming and limited availability of MRI and DXA machines. We explored the utility of a recently developed Metabolic Score for Visceral Fat (METS-VF) to assess VAT in south Asian individuals with morbid obesity. PATIENTS AND METHODS: Individuals with BMI ≥35 kg/m2 aged between 30 and 60 years were randomly selected from a database of individuals with morbid obesity, attending a multi-disciplinary bariatric clinic in a tertiary care teaching hospital in southern India. Body composition was assessed by using a Hologic Discovery A dual-energy X-ray absorptiometry (DXA) machine. METS-VF was used to estimate VAT by using a previously published algorithm. RESULTS: The mean age and body mass index of the study subjects (N=350) were 38.2 years and 40.1 kg/m2. The MET-VF score performed satisfactorily (AUC of 0.78 (95% CI 0.72-0.85)) for predicting an increased visceral adipose tissue (VAT area ≥ 163 cm2) as detected by DXA. A METS-VF value of 7.3 was found to have a good sensitivity and reasonable specificity in predicting elevated VAT in this population. CONCLUSION: This is the first study to validate the utility of METS-VF as a surrogate measure of visceral adiposity in south Indian individuals with morbid obesity. Given the simplicity, easy availability, reliability and inexpensive nature of this obesity indicator, it may find its widespread use in lower middle-income countries.
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ItemObesity indicators that best predict type 2 diabetes in an Indian population: insights from the Kerala Diabetes Prevention Program(CAMBRIDGE UNIV PRESS, 2020)Obesity indicators are known to predict the presence of type 2 diabetes mellitus (T2DM); however, evidence for which indicator best identifies undiagnosed T2DM in the Indian population is still very limited. In the present study we examined the utility of different obesity indicators to identify the presence of undiagnosed T2DM and determined their appropriate cut point for each obesity measure. Individuals were recruited from the large-scale population-based Kerala Diabetes Prevention Program. Oral glucose tolerance tests was performed to diagnose T2DM. Receiver operating characteristic (ROC) curve analyses were used to compare the association of different obesity indicators with T2DM and to determine the optimal cut points for identifying T2DM. A total of 357 new cases of T2DM and 1352 individuals without diabetes were identified. The mean age of the study participants was 46⋅4 (sd 7⋅4) years and 62 % were men. Waist circumference (WC), waist:hip ratio (WHR), waist:height ratio (WHtR), BMI, body fat percentage and fat per square of height were found to be significantly higher (P < 0⋅001) among those with diabetes compared with individuals without diabetes. In addition, ROC for WHR (0⋅67; 95 % 0⋅59, 0⋅75), WHtR (0⋅66; 95 % 0⋅57, 0⋅75) and WC (0⋅64; 95 % 0⋅55, 0⋅73) were shown to better identify patients with T2DM. The proposed cut points with an optimal sensitivity and specificity for WHR, WHtR and WC were 0⋅96, 0⋅56 and 86 cm for men and 0⋅88, 0⋅54 and 83 cm for women, respectively. The present study has shown that WHR, WHtR and WC are better than other anthropometric measures for detecting T2DM in the Indian population. Their utility in clinical practice may better stratify at-risk patients in this population than BMI, which is widely used at present.
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ItemPrevalence of normal weight obesity and its associated cardio-metabolic risk factors - Results from the baseline data of the Kerala Diabetes Prevention Program (KDPP)(PUBLIC LIBRARY SCIENCE, 2020-08-25)BACKGROUND: Cardiometabolic disorders are frequently observed among those who have obesity as measured by body mass index (BMI). However, there is limited data available on the cardiometabolic profile of those who are non-obese by BMI but with a high body fat percentage (BFP), a phenotype frequently observed in the Indian population. We examined the prevalence of individuals with normal weight obesity (NWO) and the cardiometabolic profile of NWO individuals at high risk for type 2 diabetes(T2D) in a south Asian population. MATERIAL AND METHODS: In the Kerala Diabetes Prevention Program, individuals aged between 30 to 60 years were screened using the Indian Diabetes Risk Score(IDRS) in 60 rural communities in the Indian state of Kerala. We used data from the baseline survey of this trial for this analysis which included 1147 eligible high diabetes risk individuals(IDRS >60). NWO was defined as BMI within the normal range and a high BFP (as per Asia-pacific ethnicity based cut-off); Non-obese (NO) as normal BMI and BFP and overtly obese (OB) as BMI ≥25 kg/m2 irrespective of the BFP. Data on demographic, clinical and biochemical characteristics were collected using standardized questionnaires and protocols. Body fat percentage was assessed using TANITA body composition analyser (model SC330), based on bioelectrical impedance. RESULTS: The mean age of participants was 47.3 ± 7.5 years and 46% were women. The proportion with NWO was 32% (n = 364; 95% CI: 29.1 to 34.5%), NO was 17% (n = 200) and OB was 51% (n = 583). Among those with NWO, 19.7% had T2D, compared to 18.7% of those who were OB (p value = 0.45) and 8% with NO (p value = 0.003). Among those with NWO, mean systolic and diastolic blood pressure were 129 ± 20; 78 ± 12 mmHg, compared to 127 ± 17; 78±11 mmHg among those with OB (p value = 0.12;0.94) and 120 ± 16; 71±10 mmHg among with NO (p value<0.001; 0.001), respectively. A similar pattern of association was observed for LDL cholesterol and triglycerides. After adjusting for other risk factors, the odds of having diabetes (OR:2.72[95% CI:1.46-5.08]) and dyslipidemia (2.37[1.55-3.64]) was significantly more in individuals with NWO as compared to non-obese individuals. CONCLUSIONS: Almost one-third of this South Asian population, at high risk for T2D, had normal weight obesity. The significantly higher cardiometabolic risk associated with increased adiposity even in lower BMI individuals has important implications for recognition in clinical practice.