In the present population- and DXA-based study, which evaluated the diagnostic performance of BMI at 1.5 and 3 years of age for predicting excessive FM at 14 years of age, both AUCs and 95% CIs calculated from ROC curve analysis were greater than 0.5. The statistical analysis confirmed that these AUCs significantly differed from 0.5, indicating that BMI values calculated using MCH Handbook data have potential ability to distinguish between the presence and absence of excessive FM at 14 years of age. In general, AUC is an effective way to summarize the overall diagnostic accuracy of a diagnostic test [20]. An AUC of 0.5 suggests no discrimination, 0.7–0.8 is considered acceptable, 0.8–0.9 is considered excellent, and above 0.9 is outstanding [20]. The present AUC results, as well as the respective 95% CIs, indicate that BMI at 3 years of age is an acceptable practice to predict excessive FM in the future. On the other hand, the lower limit of 95% CIs at 1.5 years of age was near 0.5, suggesting that the diagnostic performance of BMI at 1.5 years of age is inferior to that of BMI at 3 years of age.

The present study also obtained cutoff values of BMI with the best tradeoff between true-positive (sensitivity) and true-negative (specificity). Unfortunately, neither sensitivity nor specificity of the BMI cutoff points at 1.5 and 3 years of age were remarkably high. To screen for FMI at 14 years of age > 95th percentile, cutoff values for BMI at 3 years of age were 16.6 kg/m2 for girls and 16.4 kg/m2 for boys, corresponding approximately to the 83rd and 71st percentiles of BMI in girls and boys, respectively. On the other hand, international (International Obesity Task Force) BMI cutoffs for being overweight at 3 years of age, which link a BMI of 25.0 kg/m2 (corresponding to the 89th and 91st percentiles of BMI in girls and boys, respectively, at 18 years of age) are 17.6 kg/m2 for girls and 17.9 kg/m2 for boys [14]. The BMI cutoff values at 3 years of age for predicting excessive FM at 14 years of age were much lower than those used to identify an overweight individual at 3 years of age. Cutoff values for predicting excessive FM at 14 years of age should not be used to discriminate overweight children from normal children at 3 years of age.

To our knowledge, no other study has used ROC curves to assess the utility of BMI in early childhood for predicting adiposity in adolescence, and no study has attempted to identify a cutoff point for BMI in early childhood that might predict adolescent adiposity. Few studies with correlation analysis have examined the association between body weight recorded in MCH Handbook and DXA-based whole-body FM in later childhood [5, 6]. However, the correlational analysis used in those previous studies cannot describe the nature and extent of any misclassifications [7]. A categorical analysis, which enables to quantify diagnostic accuracy of BMI values for distinguishing subjects into clinically relevant categories (subjects with excess vs. normal FM) with true-positive and false-positive rates, is required [7]. For this purpose, the present study used categorical analyses such as ROC curves, and AUCs were used to quantify the diagnostic accuracy of BMI at birth and 1.5 and 3 years of age.

Both the point on the ROC curve closest to the upper left-hand corner (0, 1) and the Youden index are methods commonly used to establish the “optimal” cutoff point with the best tradeoff between sensitivity and specificity. However, the inconsistency in the cutoff points (i.e., the point closest to (0, 1) or the Youden index) was highlighted by our findings. To screen for FMI at 14 years of age > 95th percentile, the cutoff value closest to the upper left-hand corner was 16.4 kg/m2 in boys, while the value obtained by the Youden index was 17.5 kg/m2. Some inconsistency has been reported in “optimal” cutoff points obtained using these two criteria based on ROC curves [19]. In general, a good cutoff point is one which produces both high sensitivity and high specificity [21]. To minimize the misclassification of true-positives, we recommend that others proceed cautiously when establishing a BMI cutoff point in early childhood for clinical prediction of adolescent adiposity. Further validation studies using larger populations, and those spanning different countries, are required.

This study has several strengths. First, DXA is a safe and simple technique that can be used to determine FM of the whole body in individuals of all ages [22]. The measurement precision is extremely high with DXA [22]. A multicenter study using Hologic QDR 4500 devices reported an inter-instrumental variation of 5.6% (coefficient of variation) for FM [23]. DXA is increasingly being used as a criterion method for body composition assessment and has achieved “reference” status for soft tissue assessment of FM [24]. Second, in the present single-center study, a single radiological technologist performed all scans and scan analyses using the same DXA instrument. Accordingly, our study is free from inter-center variation.

The present study also has some limitations. First, the sample size for the ROC analysis with BMI at 3 years of age to screen for FMI > 95th percentile at 14 years of age was relatively small (9 girls and 10 boys with FMI > 95th percentile). ROC curves created using a smaller sample size are less smooth, which makes it difficult to determine precise cutoff points [25]. However, results for FMI > 95th percentile were consistent with those for FMI > 90th and 85th percentiles, which have a larger number of subjects than FMI > 95th percentile. Second, participants were selected from just a few cities in Japan and thus may be not entirely representative of the entire Japanese population. In other words, we may have introduced some sampling bias. However, according to standard growth charts of Japanese children based on national surveys, mean height/weight measurements of girls and boys at 14 years of age were 155.8 cm/49.3 kg and 162.6 cm/52.5 kg, respectively [26]. Thus, there were no remarkable differences in anthropometric variables between the present population and the general population in Japan. Third, fat accumulation is strongly related to sexual maturity, especially in girls at 14 years of age. However, the growth and developmental status of the participants were not taken into account or considered in the present study.

In the present population- and DXA-based study, ROC curve analysis demonstrated the quantitative accuracy of BMI at 1.5 and 3 years of age for predicting excessive adiposity at 14 years of age, supporting the idea that BMI values calculated using MCH Handbook data have potential ability to distinguish between individuals with and without excessive fat in adolescence. Future studies should investigate which of the childhood BMI cutoff points is most appropriate for predicting adolescent adiposity.

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