Trabecular bone score (TBS) is a gray-level textural index of bone microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry (DXA) images. TBS is a bone mineral density (BMD)-independent predictor of fracture risk. The objective of this metaanalysis was to determine whether TBS predicted fracture risk independently of FRAX probability and to examine their combined performance by adjusting the FRAX probability for TBS. We utilized individual-level data from 17,809 men and women in 14 prospective population-based cohorts. Baseline evaluation included TBS and the FRAX risk variables, and outcomes during follow-up (mean 6.7 years) comprised major osteoporotic fractures. The association between TBS, FRAX probabilities, and the risk of fracture was examined using an extension of the Poisson regression model in each cohort and for each sex and expressed as the gradient of risk (GR; hazard ratio per 1 SD change in risk variable in direction of increased risk). FRAX probabilities were adjusted for TBS using an adjustment factor derived from an independent cohort (the Manitoba Bone Density Cohort). Overall, the GR of TBS for major osteoporotic fracture was 1.44 (95% confidence interval [CI] 1.35-1.53) when adjusted for age and time since baseline and was similar in men and women (p > 0.10). When additionally adjusted for FRAX 10-year probability of major osteoporotic fracture, TBS remained a significant, independent predictor for fracture (GR ¼ 1.32, 95% CI 1.24-1.41). The adjustment of FRAX probability for TBS resulted in a small increase in the GR (1.76, 95% CI 1.65-1.87 versus 1.70, 95% CI 1.60-1.81). A smaller change in GR for hip fracture was observed (FRAX hip fracture probability GR 2.25 vs. 2.22). TBS is a significant predictor of fracture risk independently of FRAX. The findings support the use of TBS as a potential adjustment for FRAX probability, though the impact of the adjustment remains to be determined in the context of clinical assessment guidelines.

BackgroundNonadherence with medication is a complex and multidimensional health care problem. The causes may be related to the patient, treatment, and/or health care provider. As a consequence, substantial numbers of patients do not benefit optimally from pharmacotherapy, resulting in increased morbidity and mortality as well as increased societal costs. Several interventions may contribute to improved adherence. However, most interventions have only a modest effect. Thus, despite the many efforts made, there has been little progress made as yet in tackling the problem of nonadherence.MethodsThis paper summarizes the definitions and taxonomy of adherence with medication, as well as types and causes of nonadherence. In addition, interventions aimed at improvement of adherence are discussed.ConclusionThere is not just one solution for the nonadherence problem that fits all patients. Most interventions to improve adherence are aimed at all patients regardless of whether they are adherent or not. Recently, a number of tailored interventions have been described in the literature. Modern techniques are useful. Electronic pill boxes combined with Short Message Service reminders are specifically designed to improve unintentional adherence and have resulted in an increase in refill adherence in diabetic patients with suboptimal adherence. Tailored Internet interventions are a possibility for influencing patient drug-taking behavior and show promising results. Tailored counseling interventions targeted at the underlying causes of nonadherence seem an attractive method for supporting patients with their use of drugs. However, despite the plausible theoretical framework, data on long-term health effects of the various interventions are not available. To improve adherence effectively, there is a need for a tailored approach based on the type and cause of nonadherence and the specific needs of the patient.

Daily-life accelerometry contributes substantially to the identification of individuals at risk of falls, and can predict falls in 6 months with good accuracy.

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Social jetlag represents the discrepancy between circadian and social clocks, which is measured as the difference in hours in midpoint of sleep between work days and free days. Previous studies have shown social jetlag to be associated with body mass index (BMI), glycated hemoglobin levels, heart rate, depressive symptoms, smoking, mental distress and alcohol use. The objective of our current study was to investigate, in a group of 145 apparently healthy participants (67 men and 78 women, aged 18-55 years, BMI 18-35 kg/m(2)), the prevalence of social jetlag and its association with adverse endocrine, behavioral and cardiovascular risk profiles as measured in vivo. participants with ≥2 h social jetlag had higher 5-h cortisol levels, slept less during the week, were more often physically inactive and had an increased resting heart rate, compared with participants who had ≤1 h social jetlag. We therefore concluded that social jetlag is associated with an adverse endocrine, behavioral and cardiovascular risk profile in apparently healthy participants. These adverse profiles put healthy participants at risk for development of metabolic diseases and mental disorders, including diabetes and depression, in the near future.