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Body composition analysis, anthropometric indices and lipid profile markers as predictors for prediabetes.

ABSTRACT: To compare different anthropometric indices, Body composition analysis and lipid profile markers in terms of their ability to predict prediabetes (PD).We enrolled 83 subjects with PD and 84 normoglycemic subjects who were matched for age and gender. The diagnosis of prediabetes was done according to the American Diabetes Association (ADA) criteria. All subjects were aged between 30-55 years of age and visited the outpatient department of tertiary care hospital. Anthropometric and lipid profile measurements were obtained. Analysis of body composition was done using Bodystat 1500MDD Instrument. Backward logistic regression was performed for detecting the predictors of PD. A receiver operator characteristic curve (ROC) with area under curve (AUC) was utilized for the accuracy of the predictors of PD.Comparison of anthropometric measurement and body composition analysis parameters between the two groups showed that Waist circumference (WC), Body mass index, Body Fat% were significantly higher whereas Extracellular water and Dry lean weight in percentage (ECW% and DLW%) were found to be lower in PD (p< 0.05). Higher triglyceride (TG) levels and lower high-density cholesterol (HDL-C) with high TG/HDL-C were seen in subjects with PD. Backward logistic regression analysis found the combination of Body Fat % with WC, TG, ECW% and DLW% as strong predictors of PD. In ROC analysis, ECW% (AUC = 0.703) was the most predictive measure, followed by WC (AUC = 0.702).This study demonstrated that estimation of Body Fat % combined with waist circumference, Extracellular water and Dry lean weight in percentage are valuable in screening and diagnosis of prediabetes. Plasma levels of TG in lipid profile measurements can also serve as an additional marker for prediction of prediabetes.

SUBMITTER: Nayak VKR

PROVIDER: S-EPMC6095495 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Body composition analysis, anthropometric indices and lipid profile markers as predictors for prediabetes.

Nayak Vineetha K Ramdas VKR Raghurama Nayak Kirtana K Vidyasagar Sudha S Kamath Asha A

PloS one 20180816 8

<h4>Objectives</h4>To compare different anthropometric indices, Body composition analysis and lipid profile markers in terms of their ability to predict prediabetes (PD).<h4>Methods</h4>We enrolled 83 subjects with PD and 84 normoglycemic subjects who were matched for age and gender. The diagnosis of prediabetes was done according to the American Diabetes Association (ADA) criteria. All subjects were aged between 30-55 years of age and visited the outpatient department of tertiary care hospital. ...[more]

PMID: 30114196

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Project description:Introduction:The purpose of this study was to elucidate the relationship between cold-heat patterns and body composition, anthropometric indices, blood parameters, and tongue features in Tae-Eum type subjects. We also sought to determine whether significant indicators could be used as risk factors for predicting cold-heat patterns in a clinic. Methods:This prospective, case-control pilot study was conducted at a single center. The subjects were males and females aged 19 years or older who had been analyzed as the Tae-Eum type. After screening, subject allocation was performed. The body composition, 11 anthropometric indices, blood parameters, and tongue features of the subjects were measured by well-trained practitioners. An independent t-test was conducted to compare the cold- and heat-pattern groups. Binary logistic regression was performed to determine significant differences between the two groups after adjusting for age, sex, and systolic blood pressure, with a focus on identifying significant indicators. Results:Eighty-nine participants were recruited, 39 of whom were excluded from the analysis. Ultimately, 20 cold-pattern and 30 heat-pattern subjects were included in the final analysis. We found that alanine aminotransferase and all anthropometric indices, except for neck and forehead circumference, were significant predictive factors in both groups according to the binary regression analysis. Additionally, the tongue body color in the cold-pattern group was significantly paler than that in the heat-pattern group. Conclusions:This study found that cold and heat patterns were significantly associated with body composition, anthropometric indices, blood parameters, and tongue features. We suggest that these factors could thus be used as objective indicators and predictors of cold-heat patterns. Our findings provide fundamental but also applicable data that will be useful for diagnosing and monitoring cold-heat patterns in Tae-Eum type patients.

Project description:In adolescence, health status is influenced by several factors, including dietary pattern and physical activity (PA) which are crucial elements of lifestyle in terms of prevention and treatment of metabolic and chronic diseases. The current study aimed to explore the impact of the different intensity levels of PA along with the adherence to a Mediterranean diet (MD), on body composition indices and metabolic parameters in a cohort of adolescents, thereby investigating potential predictors of health behavior in youth. This cross-sectional study was carried out among 92 participants (44 girls and 48 boys, aged 14 to 17 years), which were divided into the following three groups according to intensity levels of PA: Group A (physical inactivity), Group B (moderate PA), and Group C (vigorous-intensity PA). The Questionnaire of Adherence to the Mediterranean Diet (KIDMED test) was used to assess both diet composition and adherence to a MD. All subjects underwent anthropometric measurements, bio-impedentiometric analysis for body composition parameters, and biochemical and hormonal measurements. The majority of adolescents (60.87%) had a medium adherence to the MD, and even a better distribution of food rates was found in adolescents performing vigorous-intensity PA. A comparison of anthropometric measurements and body composition parameters among groups showed that body mass index and fat mass (FM) were significantly lower while body cell mass (BCM), free fat mass (FFM), phase angle (PhA), and total body water (TBW) were higher in Group C adolescents as compared with those of Group A. In Group C, insulin resistance (HOMA-IR) was reduced and insulin levels were inversely associated with FFM (r = -0.454 and p = 0.004) and directly correlated with FM (r = 0.331 and p = 0.003). In the same Group C, we observed elevated serum irisin levels and lower lipid profile markers as compared with Group A. Interestingly, irisin negatively correlated with both total cholesterol (r = -0.428 and p = 0.04) and LDL (r = -0.468 and p = 0.02) in Group C. Finally, a receiver operator characteristic curve (ROC) analysis revealed irisin, LDL, HDL, and body composition variables (FFM, BMC, PhA, and TBW) as the most predictive measures for vigorous-intensity PA. Our results highlight the importance of developing healthy lifestyle programs that include improving the intensity of PA among a young population as a superior strategy for ensuring a better quality of life.

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Body composition analysis, anthropometric indices and lipid profile markers as predictors for prediabetes.

Publications

Body composition analysis, anthropometric indices and lipid profile markers as predictors for prediabetes.

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