The prevalence of obesity among children and adolescents is progressively increasing around the world. One of the important consequences of obesity is the development of insulin resistance (IR). Insulin resistance is a state in which normal concentrations of insulin produce a subnormal biologic response. This condition has a multifactorial pathogenesis and is associated with hyperlipidemia, hyperglycemia, high blood pressure and ovarian hyperandrogenism. Those are early state of adult diseases such as type 2 diabetes mellitus, hypertension, polycystic-ovary syndrome, cardiovascular disease and MS [22–24]. Although metabolic syndrome has been referred to as the insulin resistance syndrome, the ATPIII criteria do not include either fasting insulin level or the homeostasis model of insulin resistance (HOMA-IR) . There has been debate about the extent to which the metabolic syndrome defines the risk of CVD associated with insulin resistance beyond the risk associated with classic CVD risk factors (obesity, HDL, triglycerides, and blood pressure) . Therefore, it would be useful to understand the extent to which the presence of the syndrome is associated with insulin resistance.
In line with previous population-based studies [26, 27], we found that insulin resistance and MS were significantly associated. HOMA-IR levels were directly related to the number of MS components and the risk of MS increased with rising HOMA-IR percentiles. As the number of MS related components increased, mean BMI, WC, SBP, DBP, FAT%, TG showed a gradually significant increase. Similarly, the mean insulin and HOMA-IR values increased with the number of MS components. From another point of view, we show the ORs of suffering MS according to IR categories. We use the group with HOMA-IR values below the 20th percentile as a reference, and we find that the odds of developing MS (adjusted for gender, age and tanner stage) increase as a function of IR. Participants in the highest quintile of HOMA-IR were about 60 times more likely to be classified with metabolic syndrome than those in the lowest quintile. Although the data are cross-sectional, it is not possible to identify the direction of causality among metabolic syndrome and HOMA-IR,and the relationship between insulin resistance and metabolic syndrome might be different in other samples. Nevertheless, the key implications are that youths with high insulin and HOMA-IR levels have a much greater risk of being classified with metabolic syndrome. Therefore, evaluation of insulin resistance as a pathological or physiological disease as well as early intervention will help control and reduce the currency of relevant diseases.
The correlation between HOMA-IR and M-clamp had been validated in diverse adult populations. Furthermore, two studies have described the pediatric information on its validation about clamps [8, 9]. Although it is more difficult to define HOMA-IR cut-off points for diagnosis of insulin resistance in youths than that in adults due to lack of longitudinal evidence in youths for risk prediction of cardiovascular outcomes, there were a few studies on HOMA-IR utility in pediatric populations [28, 29] and some methods for defining cutoff values of HOMA-IR. In most studies, cut-off points for diagnosis of insulin resistance have been defined based on HOMA-IR distribution in reference population. Values based on the 95th percentile [30–32], lower boundary of the top quintile [33, 34] ortertile  of HOMA-IR obtained from population studies or non-obese subjects with no metabolic disorders have been used previously. In other studies, presence of pediatric MS, as a risk for future CVD, also has been considered for defining cut-off values of HOMA-IR by using ROC statistical method. Youden index and the distance from the top left corner of the ROC curve are two methods commonly used in previous work to determine the best HOMA-IR cut-off [33, 36–38]. In our study, the present HOMA-IR cutoff point corresponding to the 95th percentile of our healthy reference children was 3.0 for whole referent and 2.6 for children in prepubertal stage and 3.2 in pubertal period, respectively. The optimal point for diagnosis of MS was 2.3 in total referent, 1.7 in prepubertal stage and 2.6 in pubertal period in ROC curve analysis.
Although HOMA-IR is wildly used in population-based studies, many factors involved in the inconsistencies of HOMA-IR should be stressed. Firstly, it is expected to be different in prepubertal and pubertal children as we show in this study. A transient insulin resistance develops in children during puberty. This insulin resistance emerging during pubertal maturation is accepted as a physiological condition rather than pathologic [39, 40]. Some cross-sectional studies have shown that insulin resistance increases with the onset of puberty, makes a peak at Tanner stage 3 and recedes to prepubertal levels at the end of puberty [41–43]. Longitudinal studies have found a 30% decrease in insulin sensitivity between Tanner stages I and V . However, this decrease was found to return to normal at the end of puberty . In our study, while no difference for gender was detected in HOMA-IR cut-off values, it was higher in the pubertal period than that in the prepubertal period. A similar result was found in the different age phases; the HOMA-IR threshold is rapidly increased when children reach the age of 10 years, when most commence puberty. Therefore, it is important that, in the evaluation of insulin resistance in children and adolescents, different threshold values should be used according to puberty stage or age. Secondly, Different cut-off points might be selected to optimize sensitivity versus specificity depending on the study purpose. We defined a HOMA cutoff point for diagnosis of MS of 1.7 in prepubertal stage yielding a sensitivity of 86% and a specificity of 67% in the ROC curve. In pubertal population, the HOMA cutoff point of 2.6 produced a sensitivity of 78% and a specificity of 67%. A screening test requires high sensitivity and moderate specificity, whereas a diagnostic test requires a much higher specificity. In our study, the 95th percentile of HOMA-IR for normalsubjects in prepubertal stage was 2.6 and the sensitivity and the specificity of this point in the ROC analysis are were 54% and 85% respectively. The 95th percentile of HOMA-IR for pubertal adolescents of 3.2 leaded to a sensitivity of 64% and a specificity of 80%. Due to the fact that our sample size was large, we are able to propose precise cut-off limits based on the results of this study. This may be useful for different purposes, such as early intervention or early diagnose of insulin resistance in clinic. Thirdly, HOMA-IR is a function of both insulin and glucose, and glucose is included in the unified criteria of MS. However, insulin assays have not yet to be standardized and assessment methods differ between laboratories [46, 47]. This makes comparison with different studies difficult.