CONTEXT: Visceral adipose tissue (VAT) is a strong predictor of carbohydrate metabolism disorders. Abdominal bioelectrical impedance analysis (A-BIA) is a simple method for the measurement of VAT and is a promising tool in screening and follow-up of abdominal obesity. However the role of A-BIA in dieting individuals has not been evaluated adequately in longitudinal follow-up studies. OBJECTIVE: The aim of this study is to determine the role of A-BIA in identifying the changes in metabolic predictors after diet and/or exercise therapy. DESIGN: All patients who sought weight loss treatment underwent baseline assessment and were prescribed a program of diet. After a mean follow-up of 3.2 months, data were analyzed. SUBJECTS AND METHODS: Ultimately, 103 participants who reported adhering to the diet, enrolled to the study. We tested associations between changes in body composition measures and changes in laboratory measures using correlations and multivariate linear regression analysis. RESULTS: Mean loss of body weight was 3.4±2.8 kg. All but waist-to-hip ratio, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol levels changed significantly (p<0.001). Decreases in body weight, body mass index (BMI), and VAT level significantly correlated with decreases in fasting blood glucose, fasting insulin level, and HOMA-IR score (r=0.230-0.371). In multiple linear regression analysis changes in BMI and VAT significantly correlated with change in HOMA-IR score (F(7.93)=2.283, p=0.034, R2=0.147). CONCLUSION: Decreases in BMI and VAT, as determined by A-BIA, were predictors of changes in metabolic laboratory measures. A-BIA is useful for follow-up of patients receiving diet therapy for weight loss.
CONTEXT: Visceral adipose tissue (VAT) is a strong predictor of carbohydrate metabolism disorders. Abdominal bioelectrical impedance analysis (A-BIA) is a simple method for the measurement of VAT and is a promising tool in screening and follow-up of abdominal obesity. However the role of A-BIA in dieting individuals has not been evaluated adequately in longitudinal follow-up studies. OBJECTIVE: The aim of this study is to determine the role of A-BIA in identifying the changes in metabolic predictors after diet and/or exercise therapy. DESIGN: All patients who sought weight loss treatment underwent baseline assessment and were prescribed a program of diet. After a mean follow-up of 3.2 months, data were analyzed. SUBJECTS AND METHODS: Ultimately, 103 participants who reported adhering to the diet, enrolled to the study. We tested associations between changes in body composition measures and changes in laboratory measures using correlations and multivariate linear regression analysis. RESULTS: Mean loss of body weight was 3.4±2.8 kg. All but waist-to-hip ratio, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol levels changed significantly (p<0.001). Decreases in body weight, body mass index (BMI), and VAT level significantly correlated with decreases in fasting blood glucose, fasting insulin level, and HOMA-IR score (r=0.230-0.371). In multiple linear regression analysis changes in BMI and VAT significantly correlated with change in HOMA-IR score (F(7.93)=2.283, p=0.034, R2=0.147). CONCLUSION: Decreases in BMI and VAT, as determined by A-BIA, were predictors of changes in metabolic laboratory measures. A-BIA is useful for follow-up of patients receiving diet therapy for weight loss.
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