Hepatic Steatosis is Negatively Associated with Bone Mineral Density in Children.

OBJECTIVE: To evaluate the relationship between hepatic steatosis and bone mineral density (BMD) in children. In addition, to assess 25-hydroxyvitamin D levels in the relationship between hepatic steatosis and BMD. STUDY DESIGN: A community-based sample of 235 children was assessed for hepatic steatosis, BMD, and serum 25-hydroxyvitamin D. Hepatic steatosis was measured by liver magnetic resonance imaging proton density fat fraction (MRI-PDFF). BMD was measured by whole-body dual-energy x-ray absorptiometry. RESULTS: The mean age of the study population was 12.5 years (SD 2.5 years). Liver MRI-PDFF ranged from 1.1% to 40.1% with a mean of 9.3% (SD 8.5%). Across this broad spectrum of hepatic fat content, there was a significant negative relationship between liver MRI-PDFF and BMD z score (R = -0.421, P < .001). Across the states of sufficiency, insufficiency, and deficiency, there was a significant negative association between 25-hydroxyvitamin D and liver MRI-PDFF (P < .05); however, there was no significant association between vitamin D status and BMD z score (P = .94). Finally, children with clinically low BMD z scores were found to have higher alanine aminotransferase (P < .05) and gamma-glutamyl transferase (P < .05) levels compared with children with normal BMD z scores. CONCLUSIONS: Across the full range of liver MRI-PDFF, there was a strong negative relationship between hepatic steatosis and BMD z score. Given the prevalence of nonalcoholic fatty liver disease and the critical importance of childhood bone mineralization in protecting against osteoporosis, clinicians should prioritize supporting bone development in children with nonalcoholic fatty liver disease.

Which Sleep Health Characteristics Predict All-Cause Mortality in Older Men? An Application of Flexible Multivariable Approaches.

Study Objectives: Sleep is multidimensional, with domains including duration, timing, continuity, regularity, rhythmicity, quality, and sleepiness/alertness. Individual sleep characteristics representing these domains are known to predict health outcomes. However, most studies consider sleep characteristics in isolation, resulting in an incomplete understanding of which sleep characteristics are the strongest predictors of health outcomes. We applied three multivariable approaches to robustly determine which sleep characteristics increase mortality risk in the osteoporotic fractures in men sleep study. Methods: In total, 2,887 men (mean 76.3 years) completed relevant assessments and were followed for up to 11 years. One actigraphy or self-reported sleep characteristic was selected to represent each of seven sleep domains. Multivariable Cox models, survival trees, and random survival forests were applied to determine which sleep characteristics increase mortality risk. Results: Rhythmicity (actigraphy pseudo-F statistic) and continuity (actigraphy minutes awake after sleep onset) were the most robust sleep predictors across models. In a multivariable Cox model, lower rhythmicity (hazard ratio, HR [95%CI] =1.12 [1.04, 1.22]) and lower continuity (1.16 [1.08, 1.24]) were the strongest sleep predictors. In the random survival forest, rhythmicity and continuity were the most important individual sleep characteristics (ranked as the sixth and eighth most important among 43 possible sleep and non-sleep predictors); moreover, the predictive importance of all sleep information considered simultaneously followed only age, cognition, and cardiovascular disease. Conclusions: Research within a multidimensional sleep health framework can jumpstart future research on causal pathways linking sleep and health, new interventions that target specific sleep health profiles, and improved sleep screening for adverse health outcomes.