Comparison of body mass index and fat mass index to classify body composition in adolescents-The EVA4YOU study.

The objectives of this study were to develop age- and sex-specific reference percentiles for fat mass index (FMI) and fat-free mass index (FFMI) in adolescents aged 14 to 19 years and to determine differences in overweight/obesity classification by FMI and body mass index (BMI). The EVA4YOU study is a single-center cross-sectional study conducted in western Austria. Cardiovascular risks including anthropometric measurements and bioelectrical impedance analysis were assessed in adolescents (mean age 17 years). FMI and FFMI were calculated as the ratio of fat mass (FM) and fat-free mass (FFM) to the square of height and compared to study population-specific BMI percentiles. One thousand four hundred twenty-two adolescents were included in the analysis. Girls had a significantly higher mean FM and FMI and a significantly lower mean FFM, FFMI (p < 0.001, each), and mean BMI (p = 0.020) than boys. Body composition classification by FMI and BMI percentiles shows a concordance for the < 75th and > 97th percentile, but a significant difference in percentile rank classifications between these two cut-off values (all p < 0.05). Based on FMI, 15.5% (221/1422) of the whole population and 29.4% (92/313) of those between the 75th and 97th percentiles are classified one category higher or lower than those assigned by BMI. CONCLUSION:  Classification of normal or pathologic body composition based on BMI and FMI shows good accordance in the clearly normal or pathologic range. In an intermediate range, FMI reclassifies categories based on BMI in more than a quarter of adolescents. Cut-off values to differentiate normal from pathologic FMI values on a biological basis are needed. TRIAL REGISTRATION: The study is registered at www. CLINICALTRIALS: gov  (Identifier: NCT04598685; Date of registration: October 22, 2020). WHAT IS KNOWN: • Chronic non-communicable diseases (NCDs) are the leading cause of morbidity and mortality globally, with major risk factors including unhealthy diets, harmful behaviors, and obesity. Obesity in children and adolescents is a key risk factor for later NCDs, which is commonly measured by Body Mass Index (BMI). • BMI can be misleading as it doesn't distinguish between fat mass (FM) and fat-free mass (FFM), leading to potential misclassification of obesity in children. Previous studies have already suggested the use of the Fat Mass Index (FMI) and Fat-Free Mass Index (FFMI) as a more accurate measures of body composition. WHAT IS NEW: • This study adds the first age- and sex-specific reference values for FMI and FFMI in Austrian adolescents using bioelectrical impedance analysis (BIA) as a safe and secure measurement method of a large representative cohort. • We found percentile misclassification between BMI and FMI when categorizing for obesity, especially in intermediate categories of body composition. Furthermore, when comparing the new reference values for FMI and FFMI to existing ones from the US, UK, and Germany we could show a good alignment within the European cohorts and major differences with American values, indicating and confirming the difference of FMI and FFMI for different populations of different ethnical background, living on different continents.

Determinants of non-alcoholic fatty liver disease in young people: Maternal, neonatal, and adolescent factors.

AIM: To assess the impact of maternal, neonatal, and adolescent factors on the development of non-alcoholic fatty liver disease (NAFLD) in a cohort of 14- to 19-year-old adolescents. METHODS: This study is part of the Early Vascular Ageing in the YOUth study, a single-center cross-sectional study conducted in western Austria. Maternal and neonatal factors were extracted from the mother-child booklet, adolescent factors were evaluated by a face-to-face interview, physical examination, and fasting blood analyses. Liver fat content was assessed by controlled attenuation parameter (CAP) using signals acquired by FibroScan® (Echosense, Paris, France). The association of maternal, neonatal, and adolescent factors with CAP values was analyzed using linear regression models. RESULTS: In total, 595 adolescents (27.2% male) aged 17.0 ± 1.3 years were included. 4.9% (n = 29) showed manifest NAFLD with CAP values above the 90th percentile. Male sex (p < 0.001), adolescent triglyceride levels (p = 0.021), Homeostatic Model Assessment for Insulin Resistance index and BMI z-score (p < 0.001, each) showed a significant association with liver fat content in the multivariable analysis. Maternal pre-pregnancy BMI was associated with CAP values after adjustment for sex, age, and birth weight for gestational age (p < 0.001), but this association was predominantly mediated by adolescent BMI (indirect effect b = 1.18, 95% CI [0.69, 1.77]). CONCLUSION: Components of the metabolic syndrome were the most important predictors of adolescent liver fat content. Therefore, prevention of NAFLD should focus on lifestyle modification in childhood and adolescence.

Determinants of Diet Quality in Adolescents: Results from the Prospective Population-Based EVA-Tyrol and EVA4YOU Cohorts.

(1) Background: Unhealthy dietary behaviors are estimated to be one of the leading causes of death globally and are often shaped at a young age. Here, we investigated adolescent diet quality and its predictors, including nutrition knowledge, in two large Central European cohorts. (2) Methods: In 3056 participants of the EVA-Tyrol and EVA4YOU prospective population-based cohort studies aged 14 to 19 years, diet quality was assessed using the AHEI-2010 and DASH scores, and nutrition knowledge was assessed using the questionnaire from Turconi et al. Associations were examined utilizing multivariable linear regression. (3) Results: The mean overall AHEI-2010 score was 42%, and the DASH score was 45%. Female participants (60.6%) had a significantly higher diet quality according to the AHEI-2010 and DASH score. AHEI-2010 and DASH scores were significantly associated (p < 0.001) with sex, school type, smoking, and total daily energy intake. The DASH score was additionally significantly associated (p < 0.001) with age, socioeconomic status, and physical activity. Participants with better nutrition knowledge were more likely to be older, to attend a general high school, to live in a high-income household, to be non-smokers, and to have a higher diet quality according to the AHEI-2010 and DASH score. (4) Conclusions: Predictors of better diet quality included female sex, physical activity, educational level, and nutrition knowledge. These results may aid focused interventions to improve diet quality in adolescents.