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1.
Malaysian Journal of Nutrition ; : 455-466, 2018.
Article in English | WPRIM | ID: wpr-751212

ABSTRACT

@#Introduction: Finger millet (FM) or Eleusine coracana L. is considered as a healthier cereal option, especially based on its higher dietary fibre, phytochemical and mineral contents. FM is also recommended for individuals with diabetes, as it is believed to elicit a lower glycaemic response. Methods: The glycaemic response of FM diet was evaluated and compared with white rice (WR) diets using a continuous glucose monitoring system (CGMS™) iPro 2™ among 14 healthy male and female volunteers aged 25-45 years with normal Body Mass Index (≥22.9kg/m2) in a crossover trial. They were recruited from Madras Diabetes Research Foundation volunteers registry. The participants consumed randomised iso-caloric FM or WR based diets for five consecutive days and 24 h interstitial glucose concentrations were recorded. Results: The FM diet had significantly higher dietary fibre than WR (29.9 g vs 15.8 g/1000 kcal, p<0.01) but the other macronutrients were similar. The 5-day average incremental area under the curve (IAUC) of FM diet [Mean (95% CI) = 73.6 (62.1-85.1) mg*min/dl] was not significantly different from that for WR diet [Mean (95% CI) = 78.3(67.9-88.7) mg*min/dl]. Conclusion: Both finger millet and white rice diets showed similar 24 h glycaemic responses, despite the former having higher amounts of dietary fibre. The result suggests that use of FM flour-based food preparations and decorticated FM grains to replace WR in the Indian diets offer no significant benefit with regards to 24 h glycaemic response. Studies of longer duration with larger sample size are needed to verify our findings.

2.
Article in English | IMSEAR | ID: sea-86841

ABSTRACT

BACKGROUND AND OBJECTIVE: Although Asian Indians have been shown to have increased body fat compared to Europeans, there have been very few studies in Asian Indians validating the various methods available for body fat measurement. The aim of this study was to test the validity of body fat measured by two commercial impedance analyzers (leg-to-leg and hand-held) as well as by skinfolds with Dual Energy X-ray Absorptiometry (DEXA) as the reference method in a population based study in southern India. METHODS: Body fat percentage (BF%) was measured in 162 South Indian urban men (n=76) and women (n=86) randomly selected from the "Chennai Urban Rural Epidemiology Study" (CURES), an ongoing population based study of a representative population of Chennai. The mean age of the subjects was 45.1 +/- 9.0 years and the body mass index ranged from 16.4 - 34.4 kg/m2. Percentage body fat was measured using DEXA, segmental impedance (leg-to-leg: BF%IMP-LEG; and hand-held BF%IMP-HAND) using the manufacturer's software and skinfolds using the prediction equation from the literature (BF%SKFD). RESULTS: Body fat (%) determined by the leg-to-leg method (BF%IMP-LEG 35.10 +/- 7.26) and the skinfolds (BF%SKFD 35.77 +/- 6.06) did not differ significantly from the reference method DEXA (BF%DEXA 35.82 +/- 8.33), but the hand-held impedance method (BF%IMP-HAND 31.38 +/- 6.24) showed significant difference (p < 0.001). The bias for estimation of body fat (%) for the bioimpedance leg-to-leg, hand-held and skinfolds were 0.73 +/- 5.70, 4.45 +/- 4.83 and 0.06 +/- 5.86 respectively. All the three methods showed a fairly good correlation with DEXA (BF%IMP-LEG: r = 0.741, p<0.001; BF%IMP-HAND: r = 0.817, p< 0.001; BF%SKFD: r 0.710, p< 0.001). CONCLUSION: The study shows that in urban south Indians, measurement of body fat by the leg-to-leg impedance and the skinfold method have better agreement (lower bias) with DEXA than the hand-held impedance. However, all three methods (skinfolds, the leg-to-leg bioelectric impedance and hand-held impedance) show a fairly good correlation with DEXA.


Subject(s)
Absorptiometry, Photon , Anthropometry/methods , Body Composition , Electric Impedance , Female , Humans , Male , Middle Aged , Skinfold Thickness
3.
Article in English | IMSEAR | ID: sea-85661

ABSTRACT

The report of World Health Organization (WHO) shows that India tops the world with the largest number of diabetic subjects. This increase is attributed to the rapid epidemiological transition accompanied by urbanization, which is occurring in India. There is very little data regarding the influence of affluence on the prevalence of diabetes and its complications particularly retinopathy in the Indian population. Furthermore, there are very few studies comparing the urban/rural prevalence of diabetes and its complications. The Chennai Urban Rural Epidemiology Study (CURES) is designed to answer the above questions. CURES is initially planned as a cross-sectional study to evolve later into a longitudinal study. Subjects for the urban component of the CURES have been recruited from within the corporation limits of Chennai City. Chennai (formerly Madras), the largest city in Southern India and the fourth largest in India has been divided into 10 zones and 155 wards. 46 wards were selected by a systematic random sampling method to represent the whole of Chennai. Twenty thousand and one individuals were recruited for the study, this number being derived based on a sample size calculation. The study has three phases. Phase one is a door to door survey which includes a questionnaire, anthropometric, fasting capillary blood glucose and blood pressure measurements. Phase two focussed on the prevalence of diabetic complications particularly retinopathy using standardized techniques like retinal photography etc. Diabetic subjects identified in phase one and age and sex matched non-diabetic subjects will participate in these studies. Phase three will include more detailed studies like clinical, biochemical and vascular studies on a sub-sample of the study subjects selected on a stratified basis from phase one. CURES is perhaps one of the largest systematic population based studies to be done in India in the field of diabetes and its complications like retinopathy, nephropathy and neuropathy.


Subject(s)
Adult , Anthropometry , Blood Glucose , Diabetes Mellitus/epidemiology , Female , Humans , India/epidemiology , Male , Population Surveillance , Prevalence , Surveys and Questionnaires , Risk Factors , Rural Health
4.
Article in English | IMSEAR | ID: sea-89693

ABSTRACT

OBJECTIVES: Lipoprotein(a) [LP(a)] has been reported to be an independent risk factor for coronary artery disease (CAD). However, its relationship with other vascular complications is not clear. The aim of the study was to determine the relation of lipoprotein(a) with micro- and macrovascular complications seen in type 2 diabetic patients. METHODS: We studied 725 type 2 diabetic patients with and without diabetic complications at the MV Diabetes Specialities Centre, Chennai. The mean age of the study group was 54 +/- 10 years and 70% were males. Diabetic complications viz retinopathy, proteinuria, peripheral vascular disease and coronary artery disease were diagnosed using standardized definitions. Lipoprotein(a) levels were measured using enzyme linked immunosorbant assay (ELISA). Since the frequency distribution of Lp(a) was skewed Lp(a) values were log transformed and geometric mean was used for statistical analysis. RESULTS: The mean Lp(a) level of patients with any vascular complication was significantly higher compared to the subjects without any complications. Multiple logistic regression analysis revealed that lipoprotein(a) had as independent association with CAD (Odds Ratio -1.16, p=0.04) and proteinuria (Odds Ratio -1.69, p < 0.001). The association of Lp(a) with retinopathy and PVD turned out to be non-significant when CAD and proteinuria was introduced as cofactors in the regression model. CONCLUSION: Lp(a) concentrations are found to be higher in those with CAD and proteinuria. There appears to be no association between Lp(a) and retinopathy or PVD in South Indian type 2 diabetic patients.


Subject(s)
Adult , Cholesterol/blood , Coronary Disease/blood , Diabetes Mellitus, Type 2/blood , Diabetic Angiopathies/blood , Female , Humans , India , Lipoprotein(a)/blood , Logistic Models , Male , Middle Aged , Peripheral Vascular Diseases/blood , Risk Factors
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