Veeradej Pisprasert MD1, Sornwichate Rattanachaiwong MD1, Pranithi Hongsprabhas MD1, Panita Limpawattana MD2, Pisaln Mairiang MD3, Sirirat Anutrakulchai MD4
Affiliation : 1 Division of Clinical Nutrition, Department of Internal Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand 2 Division of Geriatric Medicine, Department of Internal Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand 3 Division of Gastroenterology, Department of Internal Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand 4 Division of Nephrology, Department of Internal Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
Objective : Metabolic syndrome [MetS] is a deleterious complication related to obesity. Body mass index [BMI] is a practical
parameter indicating obesity and associated conditions. However, the usefulness of BMI is limited since it does not truly
reflect the amount of body fat a person has. This study aims to determine the performance of the fat mass index [FMI] and
percent fat mass [PFM] in detecting MetS, and to identify the optimal cutoff points of these parameters among the elderly
Thai population.
Materials and Methods : Participants were subjects aged above 50 years who attended the Healthy Ageing Khon Kaen
University Campus Project between March 2012 and April 2015. Baseline characteristics, anthropometric measures, body
composition as measured by bioelectrical analysis [BIA], and metabolic profiles were collected. MetS was identified using
the criteria of the International Diabetes Foundation [IDF].
Results : There were 201 men and 385 women recruited for the present study. The prevalence of metabolic syndrome was
approximately 40%. FMI and PFM were correlated with the prevalence of metabolic syndrome, particularly in women. The
area under the ROC curve [AUC] of FMI to predict metabolic syndrome was 0.89 in men and 0.84 in women, while the AUC
of PFM was 0.84 for men and 0.82 for women. We propose an FMI of 9.0 kg/m2 or a PMF of 36.6% for women and an FMI
of 5.8 kg/m2 or PFM of 23.1% for men as cutoff points to indicate MetS.
Conclusion : PFI and FMI are alternative reliable parameters in predicting MetS that can be measured using unsophisticated
techniques.
Keywords : Body mass index, Fat mass index, Metabolic syndrome, Percent fat mass, Waist circumference
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