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The associations between individual components of metabolic syndrome (MetS) and bone health in children are complex, and data on this topic are sparse and inconsistent. We assessed the relationship between bone turnover markers and markers of the processes underlying MetS (insulin resistance and inflammation) in a group of presumably healthy children aged 9–11 years: 89 (51 girls, 38 boys) presenting without any features of MetS and 26 (10 girls, 16 boys) with central obesity and two features of MetS. Concentrations of glucose, triglycerides (TG), HDL cholesterol (HDL-C), C-reactive protein (CRP), HbA1c, total 25-hydroxyvitamin D (25(OH)D), intact-P1NP (N-terminal propeptide of type I procollagen), CTX-1 (C-terminal telopeptide of type I collagen) were assayed and insulin resistance was assessed (HOMA-IR). BMI centile, waist circumference (WC) and blood pressure were measured. The presence of MetS in girls resulted in significantly lower concentrations of CTX-1 and a trend to lower CTX-1 in boys. The concentrations of bone formation marker i-P1NP were not affected. Among the features associated with MetS, HOMA-IR appeared as the best positive predictor of MetS in girls, whereas CRP was the best positive predictor in boys. A significant influence of HOMA-IR on the decrease in CTX-1 in girls was independent of BMI centile and WC, and the OR of having CTX-1 below the median was 2.8-fold higher/1SD increased in HOMA-IR (p = 0.003). A weak relationship between CTX-1 and CRP was demonstrated in girls (r = −0.233; p = 0.070). Although TG, as a MetS component, was the best significant predictor of MetS in both sexes, there were no correlations between bone markers and TG. We suggest that dyslipidemia is not associated with the levels of bone markers in prepubertal children whereas CRP is weakly related to bone resorption in girls. In prepubertal girls, insulin resistance exerts a dominant negative impact on bone resorption, independent of BMI centile and waist circumference

There are many mobile health applications (apps) now available and some that use in some way laboratory medicine data. Among them, patient-oriented are of the lowest content quality. The aim of this study was to compare the opinions of non-laboratory medicine professionals (NLMP) with those of laboratory medicine specialists (LMS) and define the benchmarks for quality assessment of laboratory medicine apps. Twenty-five volunteers from six European countries evaluated 16 selected patient-oriented apps. Participants were 20-60 years old, 44% were females, with different educational degrees, and no professional involvement in laboratory medicine. Each participant completed a questionnaire based on the Mobile Application Rating Scale (MARS) and the System Usability Scale, as previously used for rating the app quality by LMS. The responses from the two groups were compared using the Mann-Whitney U test and Spearman correlation. The median total score of NLMP app evaluation was 2.73 out of 5 (IQR 0.95) compared to 3.78 (IQR 1.05) by the LMS. All scores were statistically significantly lower in the NLMP group (p<0.05), except for the item Information quality (p=0.1631). The suggested benchmarks for a useful appear: increasing awareness of the importance and delivering an understanding of persons' own laboratory test results; understandable terminology; easy to use; appropriate graphic design, and trustworthy information. NLMP' evaluation confirmed the low utility of currently available laboratory medicine apps. A reliable app should contain trustworthy and understandable information. The appearance of an app should be fit for purpose and easy to use.

Both vitamin D and insulin-like growth factor 1 (IGF-1) play essential roles in bone metabolism and may interact during prepubertal bone accrual. We investigated the association of low serum 25-hydroxyvitamin D (25(OH)D) (<20 ng/mL) with the circulating bone turnover markers, when compared to their interaction with IGF-1. Subjects and Methods: Serum 25(OH)D, IGF-I, P1NP (N-terminal propeptide of type I procollagen), and CTX-1 (C-terminal telopeptide of type I collagen) were measured, and the bone turnover index (BTI) was calculated in 128 healthy children, aged 9–11 years. Results: Mean 25(OH)D concentration was 21.9 ± 4.9 ng/mL, but in 30.5% of participants it was <20 ng/mL (<50 nmol/L). We observed a trend for higher P1NP (p < 0.05) and IGF-1 (p = 0.08), towards lower 25(OH)D in tertiles. Levels of P1NP in the lowest 25(OH)D tertile (<20 ng/mL) were the highest, while CTX and BTI remained unchanged. Additionally, 25(OH)D negatively correlated with IGF-1, while the correlation with P1NP was not significant. A strong positive correlation of IGF-1 with P1NP and BTI but weak with CTX was observed. Low 25(OH)D (<20 ng/mL) explained 15% of the IGF-1 variance and 6% of the P1NP variance. Conclusions: Low levels of 25(OH)D do not unfavorably alter bone turnover. It seems that serum 25(OH)D level may not be an adequate predictor of bone turnover in children.

Background: Many of the mobile applications (apps) used for delivering health interventions involve laboratory medicine data. This survey was conducted to search the online market for health apps that manage laboratory medicine data. The aim was to review them and perform a quality evaluation. Methods: Apps search criteria were "Lab results blood work", "Lab results", and "Health apps". After the stepwise exclusion process, 52 selected apps were downloaded and analyzed. For review and content analysis of the apps, a multidimensional tool for classifying and rating the quality of mobile health apps - Mobile App Rating Scale (MARS), was used. Results: Selected apps were classified into five categories according to their intended use by patients or physicians, and the type of data engaged. Spearman's correlation analysis found significant correlations between MARS individual scoring items, as with the subjective quality and number of technical aspects. Kruskal-Wallis analysis showed a significant difference in the number of technical aspects employed, MARS engagement and informational quality score items, total score, and subjective quality. The lowest values for all of these items were in the category of apps designed for patients, and the post hoc test showed that the difference was statistically significant between this and the values in all other categories. Conclusions: Apps designed for patients, are of the poorest quality, considering the total quality of the content and information they provide, estimated using the MARS tool. This estimation needs to be validated for laboratory medicine apps, and eventually modified after consideration of specific quality benchmarks.