Reliability of HR-pQCT Derived Cortical Bone Structural Parameters When Using Uncorrected Instead of Corrected Automatically Generated Endocortical Contours in a Cross-Sectional Study: The Maastricht Study.

Most HR-pQCT studies examining cortical bone use an automatically generated endocortical contour (AUTO), which is manually corrected if it visually deviates from the apparent endocortical margin (semi-automatic method, S-AUTO). This technique may be prone to operator-related variability and is time consuming. We examined whether the AUTO instead of the S-AUTO method can be used for cortical bone analysis. Fifty scans of the distal radius and tibia from participants of The Maastricht Study were evaluated with AUTO, and subsequently with S-AUTO by three independent operators. AUTO cortical bone parameters were compared to the average parameters obtained by the three operators (S-AUTOmean). All differences in mean cortical bone parameters between AUTO and S-AUTOmean were < 5%, except for lower AUTO cortical porosity of the radius (- 16%) and tibia (- 6%), and cortical pore volume (Ct.Po.V) of the radius (- 7%). The ICC of S-AUTOmean and AUTO was > 0.90 for all parameters, except for cortical pore diameter of the radius (0.79) and tibia (0.74) and Ct.Po.V of the tibia (0.89), without systematic errors on the Bland-Altman plots. The precision errors (RMS-CV%) of the radius parameters between S-AUTOmean and AUTO were comparable to those between the individual operators, whereas the tibia RMS-CV% between S-AUTOmean and AUTO were higher than those of the individual operators. Comparison of the three operators revealed clear inter-operator variability. This study suggests that the AUTO method can be used for cortical bone analysis in a cross-sectional study, but that the absolute values-particularly of the porosity-related parameters-will be lower.

Replacement Effects of Sedentary Time on Metabolic Outcomes: The Maastricht Study.

INTRODUCTION: Sedentary time has been associated with detrimental health effects, so in some countries, guidelines to reduce sedentary time have been developed. As reducing sedentary time inevitably results in more nonsedentary time, effects of this reduction may depend on the activity with which it is replaced. PURPOSE: This study aimed to examine associations of theoretical reallocations of sedentary time to standing or stepping with cardiometabolic outcomes and type 2 diabetes. METHODS: We included 2213 participants (51% men, mean ± SD age = 60.0 ± 8.1 yr) of the Maastricht Study who were asked to wear an accelerometer 24 h·d for a week. We calculated daily sedentary, standing, and stepping time. An isotemporal substitution modeling approach was applied to examine effects on waist circumference; body mass index; cholesterol, triacylglycerol, glucose, and insulin levels; metabolic syndrome; and type 2 diabetes. RESULTS: Replacement of sedentary time (30 min·d) with stepping was associated with lower odds for metabolic syndrome (odds ratio [OR] = 0.72, 95% confidence interval [CI] = 0.66-0.78) and type 2 diabetes (OR = 0.79, 95% CI = 0.72-0.87), more favorable waist circumference (B = -1.42, 95% CI = -1.78 to -1.06), and body mass index (B = -0.48, 95% CI = -0.62 to -0.35) and improved cholesterol, triacylglycerol, glucose, and insulin levels. Replacing sedentary time with standing was associated with lower odds for metabolic syndrome and type 2 diabetes and favorable outcomes in waist circumference, cholesterol, triacylglycerol, and insulin levels. CONCLUSION: Theoretical replacements of sedentary time with nonsedentary time (both standing and stepping) were associated with lower odds for metabolic syndrome, type 2 diabetes, and beneficial metabolic outcomes. These results could be important for the general population, including those who cannot meet physical activity guidelines. Consideration should be given to developing recommendations for daily reallocating sedentary time.

Increased fracture risk in patients with type 2 diabetes mellitus: an overview of the underlying mechanisms and the usefulness of imaging modalities and fracture risk assessment tools.

Type 2 diabetes mellitus has recently been linked to an increased fracture risk. Since bone mass seems to be normal to elevated in patient with type 2 diabetes, the increased fracture risk is thought to be due to both an increased falling frequency and decreased bone quality. The increased falling frequency is mainly a result of complications of the disease such as a retinopathy and polyneuropathy. Bone quality is affected through changes in bone shape, bone micro-architecture, and in material properties such as bone mineralization and the quality of collagen. Commonly used methods for predicting fracture risk such as dual energy X-ray absorptiometry and fracture risk assessment tools are helpful in patients with type 2 diabetes mellitus, but underestimate the absolute fracture risk for a given score. New imaging modalities such as high resolution peripheral quantitative computed tomography are promising for giving insight in the complex etiology underlying the fragility of the diabetic bone, as they can give more insight into the microarchitecture and geometry of the bone. We present an overview of the contributing mechanisms to the increased fracture risk and the usefulness of imaging modalities and risk assessment tools in predicting fracture risk in patients with type 2 diabetes.