Background: Adolescence is a critical period for bone development, and peak bone mass may be reached in late adolescence. Boosting bone accumulation at this time can help preserve adult bone health and avoid osteoporosis later in life. Body mass index (BMI) has been found to have a favorable impact on bone mineral density (BMD) in previous research. However, excessive obesity is harmful to health and may lead to various systemic diseases. Therefore, finding an appropriate BMI to maintain a balance between obesity and BMD is critical for adolescents.Methods: The datasets from the National Health and Nutrition Examination Survey (NHANES) 2011–2020 were used in a cross-sectional investigation. Multivariate linear regression models were used to examine the linear connection between BMI and BMD. Fitted smoothing curves and threshold effect analysis were used to describe the nonlinear relationship. Subgroup analyses were then conducted based on gender and age.Results: This population-based study included a total of 6,143 adolescents aged 8–19 years. In a multivariate linear regression analysis, a good association between BMI and total BMD was shown [0.014 (0.013, 0.014)]. This positive association was maintained in all subgroup analyses grouped by sex and age. Furthermore, the association between BMI and BMD was nonlinear with a saturation point present, as evidenced by smoothed curve fitting. According to the threshold effect study, with an age group of two years, adolescents of different ages had different BMI saturation values with respect to BMD.Conclusions: Our study showed a significant positive and saturated association between BMI and BMD in adolescents aged 8–19 years. Maintaining BMI at saturation values may reduce other adverse effects while achieving optimal BMD.

Introduction: Inequality in socioeconomic status plays an important role in the prevalence of metabolic diseases in adolescents. The purpose of this study was to explore the association between family income and the degree of hepatic steatosis quantified by vibration-controlled transient elastography (VCTE) among U.S. adolescents.Methods: This cross-sectional study included two cycles of the National Health and Nutrition Examination Survey (NHANES) 2017-2020. Multivariate linear regression and smoothing curve fitting were used to investigate the linear and nonlinear relationship between PIR and hepatic steatosis, respectively. Subgroup analysis and interaction tests were used to test whether this relationship was stable across groups.Results: Of the 1,574 adolescent participants, 456 lived in poor households and 307 lived in wealthy households. After adjusting for all covariates, PIR (Ratio of family income to poverty) was significantly negatively associated with the degree of hepatic steatosis [-4.78 (-7.39, -2.17)], and this remained stable after converting PIR to a categorical variable. In addition, this significant negative association was more pronounced in women [-7.62 (-11.38, -3.87)], non-Hispanic blacks [-7.19 (-14.43, 0.06)], Mexican Americans [-6.80 (-13.63, 0.03)], and participants with BMI >30 cm² [-10.83 (-19.70, -1.96)].Conclusions: PIR was significantly and negatively associated with the degree of hepatic steatosis in US adolescents. Additional prospective studies are needed to confirm our findings.

We aimed to evaluate the incremental predictive value of metabolomic biomarkers for assessing the 10-year risk of type 2 diabetes when added to the clinical Cambridge Diabetes Risk Score (CDRS). We utilized 86,232 UK Biobank (UKB) participants (recruited between 13 March 2006 and 1 October 2010) for model derivation and internal validation. Additionally, we included 4383 participants from the German ESTHER cohort (recruited between 1 July 2000 and 30 June 2002 for external validation). Participants were followed up for 10 years to assess the incidence of type 2 diabetes. A total of 249 NMR-derived metabolites were quantified using nuclear magnetic resonance (NMR) spectroscopy. Metabolites were selected with LASSO regression and model performance was evaluated with Harrell's C-index. 11 metabolomic biomarkers, including glycolysis related metabolites, ketone bodies, amino acids, and lipids, were selected. In internal validation within the UKB, adding these metabolites significantly increased the C-index (95% confidence interval (95% CI)) of the clinical CDRS from 0.815 (0.800, 0.829) to 0.834 (0.820, 0.847) and the continuous net reclassification index (NRI) with 95% CI was 39.8% (34.6%, 45.0%). External validation in the ESTHER cohort showed a comparable statistically significant C-index increase from 0.770 (0.750, 0.791) to 0.798 (0.779, 0.817) and a continuous NRI of 33.8% (26.4%, 41.2%). A concise model with 4 instead of 11 metabolites yielded similar results. Adding 11 metabolites to the clinical CDRS led to a novel type 2 diabetes prediction model, we called UK Biobank Diabetes Risk Score (UKB-DRS), substantially outperformed the clinical CDRS. The concise version with 4 metabolites performed comparably. As only very few clinical information and a blood sample are needed for the UKB-DRS, and as high-throughput NMR metabolomics are becoming increasingly available at low costs, these models have considerable potential for routine clinical application in diabetes risk assessment. The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the 10.13039/501100002347 Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The UK Biobank project was established through collaboration between various entities including the Wellcome Trust, the Medical Research Council, Department of Health, Scottish Government, and the Northwest Regional Development Agency. Additional funding was provided by the Welsh Assembly Government, 10.13039/501100000274 British Heart Foundation , 10.13039/501100000289 Cancer Research UK , and Diabetes UK, with support from the National Health Service (NHS). The German Diabetes Center is funded by the German Federal Ministry of Health (Berlin, Germany) and the 10.13039/501100014690 Ministry of Culture and Science of the state North Rhine-Westphalia (Düsseldorf, Germany) and receives additional funding from the German Federal Ministry of Education and Research (BMBF) through the German Center for Diabetes Research (DZD e.V.).

Background: The weight-adjusted waist circumference index (WWI) is a novel obesity indicator that offers improved accuracy in assessing both muscle and fat mass compared to traditional measures. This study aimed to investigate the association between WWI and bone mineral density (BMD) in adults. Methods: Weighted multivariate logistic regression, subgroup analysis, interaction tests and restricted cubic spline (RCS) curves were used to explore the relationship between WWI and BMD based on data from the National Health and Nutrition Examination Survey (NHANES). Results: This study had 40,568 individuals in total. At all four measurement sites, we detected a negative linear correlation between WWI and BMD. Even when quartile factors for WWI were created, this unfavorable connection maintained. In comparison to those in the lowest quartile, those in the highest percentile of WWI showed declines in lumbar BMD of 0.08 g/cm² and femoral neck BMD of 0.03 g/cm², respectively. This adverse correlation, nevertheless, differed among several categories. Conclusions: Our findings suggest an adverse correlation between WWI and BMD among US adults. Employing WWI as a tool for osteoporosis prevention in the general population may enhance interventions.