Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).     

Effects of second-hand smoking on lung functions in athlete and non-athlete school-aged children – observational study

BackgroundSecond-hand smoking or environmental tobacco smoke is a critical health risk. Children are the most vulnerable to second-hand smoking because of their small bronchial ducts, less developed immunity, and low-physical activity.ObjectivesThe purpose of this study was to ascertain the effects of second-hand smoking on lung functions in athlete and non-athlete school-aged children.MethodsThis observational study included forty-six school-aged children, their age was 8–15 years, assigned to three groups; 2 study groups and 1 control group (n=15). The study groups comprised of 16 football players, and of 15 cyclists. Lung functions were evaluated recording forced vital capacity, forced expiratory volume in 1 sec and peak expiratory flow using digital spirometer.ResultsAll measures were recorded in definite values and the children were also classified into second-hand smoking (SH), or non-exposed to tobacco smoking (NE). The findings presented a significant increase (p<0.05) of the study groups in forced vital capacity, forced expiratory volume in 1 sec and peak expiratory flow solely for the non-exposed children. However, there were non-significant differences between the cyclists and football players or between the passive smoking children and non-exposed children in any of the two study groups (p>0.05).ConclusionThe outcomes of this study suggest beneficial influences of the sports activity on the lung functions, without different influences of the cyclists and football players on the lung functions.     

Prejudice and the Plate: Effects of Weight Bias in Nutrition Judgments

As millions of people turn to social media for health information, better understanding the factors that guide health-related judgments and perceptions in this context is imperative. We report on two Web experiments (n > 400 total) examining the power of society’s widespread weight bias and related stereotypes to influence nutrition judgments in social media spaces. In Experiment 1, meals were judged as lower in nutritional quality when the person who recommended them (the source) was depicted as obese rather than of normal weight, an effect mediated by stereotypic beliefs about the source as a generally unhealthy person. Experiment 2 replicated this effect, which—notably—remained significant when controlling for objective nutritional information (calories and fat content). Results highlight spillover effects of weight bias that extend beyond person perception to color impressions of objects (here, food) that are associated with stigmatized attributes. Implications for everyday nutrition judgments and public health are considered.