Primary focused on the discriminative accuracy of the indices, individual characteristic and anthropometric data for Shenzhen children and adolescents aged 9–17 years were used to diagnose elevated ALAT, and we confirmed the belief that individual indices were important predictors of abnormal ALAT. An elevated ALAT activity was more common in overweight or obese students than those with a normal or relatively low BMI z-score. BMI and weight showed an approximate diagnostic performance for predicting the presence of elevated ALAT, followed by the z-score of BMI, height, and age.
Consistent findings that the proportion of elevated ALAT greatly increased with increasing degree of obesity (e.g. the percentile or z-score of BMI) and higher proportion among overweight or obese adolescents than normal-weight ones were shown in previous studies and our research, regardless of the use of diagnostic criteria for an elevated ALAT activity10, 16, 21, 35. Based on the criterion II (40 U/L for boys and girls), the percentage of elevated ALAT among Shenzhen children and adolescents of 9−17 years was 0.89% for normal-weight, 4.96% for overweight, and 20.58% for obese participants. According to the same thresholds, elevated ALAT levels were observed in nearly 6.6% of the Mexican youths (9.8% of boys and 3.8% of girls), and 2.7% of normal-BMI, 14.2% of overweight, and 28.9% of the obese children and adolescents, by using the baseline data from 1,262 participants of 8–19 years in the Mexican Health Worker Cohort Study16. Mexican youths had a slightly higher crude proportion of elevated ALAT than Shenzhen youths, without adjusting for age and gender based on the distribution of the world population. Likewise, using a sample of 1,591 youths from the 2008−2009 Korea National Health and Nutrition Examination Survey, another study conducted by Seung Park and cooperators also found a close prevalence of elevated ALAT (> 33 U/L for boys and > 25 U/L for girls) among Korean youths of 12−18 years — 5.9% (95%CI 4.9%−7.2%) for the overall study population, 15.7% (11.3%−21.5%) for overweight adolescents (85th ≤ BMI < 95th percentile), and 34.9% (25.6%−45.4%) for subjects with a BMI ≥ 95th percentile35. The odds ratios (ORs) for elevated ALAT also sharply increased with the greater levels of obesity, with an OR (95% CI) of 7.23 (4.33–12.10) for overweight and 23.62 (12.98–42.98) for obese adolescents, comparing to normal-weight adolescents (BMI < 85th percentile) in an unadjusted analysis35.
Screening for school-students, it is clearly more convenient to collect anthropometric measures than biochemical measures, but the abilities of several individual characteristics and anthropometric indices to correctly predict elevated serum ALAT in children and adolescents are questionable and need to be assessed. Determined by the univariate ROC curves, our results showed that the anthropometric parameter of BMI had the best superiority of discerning the presence of elevated ALAT (AUC = 0.789 for criterion I and 0.850 for II), weight and BMI-z displayed the second and third highest detection accuracy (from 0.747 to 0.850), and followed by height, age, and gender (from 0.490 to 0.695). As such, we believed that the single variable of height, age, or gender was not a reliable surrogate measure of an activity of elevated ALAT among Shenzhen students of 9−17 years. Further, age, gender, and height were considered as covariates together with each predictor of obesity indices (i.e. weight, BMI, or BMI-z) to predict elevated ALAT in the subsequent multivariate model analyses, although the diagnostic accuracy of the combined models did not markedly improve. On the other hand, the current study firstly investigated the association of height z-score with serum ALAT and estimated the usefulness of height-z as a predictive index of elevated ALAT among children and adolescents, showing a null discriminative power of height z-score for predicting an elevated ALAT activity.
For BMI, several studies had pointed out that BMI was able to determine the presence of elevated ALAT among adults, although the accuracy was not very high in absolute term — the AUC (95% CI) was 0.658 (0.633–0.683) for men and 0.651 (0.616–0.685) for women in the rural areas of China17 and 0.64 (0.60–0.68) for Italian general population22. Focused on adolescents, a representative study with a sample of 454 youths of 11–17 years from 2 northern Italian cities also found a similar diagnostic performance of dichotomized BMI for elevated ALAT, with an AUC of 0.64 (0.50–0.77)20. Compared to the dichotomized BMI model, the Italian adolescents study also indicated a more accurate univariate model of BMI-z (AUC = 0.71 [0.59–0.81]), and the predictive ability was increased substantially by considering gender together with BMI-z (AUC = 0.80 [0.71–0.89])20. In addition, based on the data from the National Health and Nutrition Examination Survey during 1999 to 2014, an United States study consisted of 5,019 adolescents of 12–19 years suggested a significant correlation between BMI z-score and serum ALAT levels (r = 0.29, P < 0.0001)7. Significant positive associations of ALAT with obesity indices (e.g. BMI, body fat percentage, truncal fat mass, total fat mass, WC, and WHtR) were further confirmed in Korean male adolescents24.
Several potential limitations of our research should be recognized. First, participants were only from a single city of China, and it might be therefore difficult to generalize these findings to other populations. Second, our cross-sectional study omitted to measure some important individual anthropometric parameters — hip circumference, WC, neck circumference, and the subsequent indicators of WHpR, WHtR, and A Body Shape Index, which might achieve a better diagnostic performance and to be more sensitive predictive indicates for diagnosing an elevated ALAT activity among the indigenous adolescents. For predicting the ALAT levels, WHtR and to some extent BMI were congruously shown to be the best body indices in some Asians, as compares to WC, hip circumference, WHpR, and the useless index of A Body Shape Index15, 17, 19. Third, our study did not take into account some potential confounders of ALAT elevation for non-adults such as physical exercise, drugs, and dietary choline deficiency1. Another limitation was our inability to consider the potential confounders of ethyl alcohol intake and hepatitis B virus (HBV) and C virus (HCV) infections, which were well-known risk factors for increases in ALAT7, 15, 20, 22. However, alcohol consumption and HBV and HCV infections were less prevalent in school-students of China36, 37, and we hypothesized that the obesity indices could be even more important predictors of elevated ALAT among the children and adolescents of Shenzhen, and the above potential confounders were not likely to have a substantial impact on current results.