Fat Mass Index (FMI) And Percentage of Body Fat (%BF) As Anthropometric Tools In Predicting Risk of Metabolic Syndrome Among Malay Adolescents

• Main Authors: Wee, Bee Suan, Lim, Jing Ying
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2019
• Subjects: Q Science (General); RA0421 Public health. Hygiene. Preventive Medicine
• Online Access: http://eprints.unisza.edu.my/2516/1/FH03-FSK-19-32157.pdf; http://eprints.unisza.edu.my/2516/2/FH03-FSK-19-32158.pdf; http://eprints.unisza.edu.my/2516/
• Institution: Universiti Sultan Zainal Abidin

Body mass index (BMI) alone cannot distinguish lean body mass (LBM) from fat mass (FM). Hence, it highlights the needs of measuring body composition as high level of adiposity is associated with metabolic syndrome (MS). This study aimed to develop two cut-off values for fat mass index (FMI) and body fat percentage (%BF) in predicting MS and to investigate the association between these indicators with MS. Subjects comprised 238 Malay adolescents (21% male, 79% female) aged 18 to 19 years old. Anthropometric comprised weight, height and waist circumference. Body composition was measured using bioelectrical impedance analysis (BIA) techniques and blood pressure was also measured. FMI was determined by dividing subject’s FM (kg) by the square of height (m2 ). Fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-c), lowdensity lipoprotein cholesterol (LDL-c) were determined from an overnight fasting blood sample. MS was diagnosed based on IDF (2007) definition for adolescents aged 16-year-old and above. Receiver Operating Characteristics (ROC) curve analysis revealed that the optimal cut-off value for FMI and %BF were 9.04 kg/m2 with AUC of [0.898 (95% CI: 0.801, 0.995)] and 30.71% with AUC of [0.875 (95% CI: 0.752, 0.997)]. Binary Logistic Regression showed that both FMI (p<0.01) and %BF (p<0.05) were significantly associated with MS. Adolescents with FMI higher than cut-off value had 31. 846 (95% CI: 3.428, 295.848) odds of having MS and those with % BF higher than cut-off value had 13.585 (95% CI: 1.486, 124.160) of having MS. In conclusion, FMI and %BF possess good discriminatory ability in predicting MS among adolescents. Significant association exists between FMI and %BF with MS. Urgent action such as intervention programme is needed to reduce the body adiposity level among Malay adolescents.