Objective Whether HMG-CoA-reductase inhibition, the main mechanism of statins, plays a role in the pathogenesis of osteoporosis, is not entirely known so far. Consequently, this study was set out to investigate the relationship of different kinds and dosages of statins with osteoporosis, hypothesising that the inhibition of the synthesis of cholesterol could influence sex-hormones and therefore the diagnosis of osteoporosis. Methods Medical claims data of all Austrians from 2006 to 2007 was used to identify all patients treated with statins to compute their daily defined dose averages of six different types of statins. We applied multiple logistic regression to analyse the dose-dependent risks of being diagnosed with osteoporosis for each statin individually. Results In the general study population, statin treatment was associated with an overrepresentation of diagnosed osteoporosis compared with controls (OR: 3.62, 95% CI 3.55 to 3.69, p<0.01). There was a highly non-trivial dependence of statin dosage with the ORs of osteoporosis. Osteoporosis was underrepresented in low-dose statin treatment (0–10 mg per day), including lovastatin (OR: 0.39, CI 0.18 to 0.84, p<0.05), pravastatin (OR: 0.68, 95% CI 0.52 to 0.89, p<0.01), simvastatin (OR: 0.70, 95% CI 0.56 to 0.86, p<0.01) and rosuvastatin (OR: 0.69, 95% CI 0.55 to 0.87, p<0.01). However, the exceeding of the 40 mg threshold for simvastatin (OR: 1.64, 95% CI 1.31 to 2.07, p<0.01), and the exceeding of a 20 mg threshold for atorvastatin (OR: 1.78, 95% CI 1.41 to 2.23, p<0.01) and for rosuvastatin (OR: 2.04, 95% CI 1.31 to 3.18, p<0.01) was related to an overrepresentation of osteoporosis. Conclusion Our results show that the diagnosis of osteoporosis in statin-treated patients is dose-dependent. Thus, osteoporosis is underrepresented in low-dose and overrepresented in high-dose statin treatment, demonstrating the importance of future studies’ taking dose-dependency into account when investigating the relationship between statins and osteoporosis.

Objectives: Diabetic patients are often diagnosed with several comorbidities. The aim of the present study was to investigate the relationship between different combinations of risk factors and complications in diabetic patients. Research design and methods: We used a longitudinal, population-wide dataset of patients with hospital diagnoses and identified all patients (n = 195,575) receiving a diagnosis of diabetes in the observation period from 2003–2014. We defined nine ICD-10-codes as risk factors and 16 ICD-10 codes as complications. Using a computational algorithm, cohort patients were assigned to clusters based on the risk factors they were diagnosed with. The clusters were defined so that the patients assigned to them developed similar complications. Complication risk was quantified in terms of relative risk (RR) compared with healthy control patients. Results: We identified five clusters associated with an increased risk of complications. A combined diagnosis of arterial hypertension (aHTN) and dyslipidemia was shared by all clusters and expressed a baseline of increased risk. Additional diagnosis of (1) smoking, (2) depression, (3) liver disease, or (4) obesity made up the other four clusters and further increased the risk of complications. Cluster 9 (aHTN, dyslipidemia and depression) represented diabetic patients at high risk of angina pectoris “AP” (RR: 7.35, CI: 6.74–8.01), kidney disease (RR: 3.18, CI: 3.04–3.32), polyneuropathy (RR: 4.80, CI: 4.23–5.45), and stroke (RR: 4.32, CI: 3.95–4.71), whereas cluster 10 (aHTN, dyslipidemia and smoking) identified patients with the highest risk of AP (RR: 10.10, CI: 9.28–10.98), atherosclerosis (RR: 4.07, CI: 3.84–4.31), and loss of extremities (RR: 4.21, CI: 1.5–11.84) compared to the controls. Conclusions: A comorbidity of aHTN and dyslipidemia was shown to be associated with diabetic complications across all risk-clusters. This effect was amplified by a combination with either depression, smoking, obesity, or non-specific liver disease.

Summary: Background: Testosterone plays an important role in the regulation of glucose metabolism. While earlier studies have shown that it has a protective effect in males, unfavorable effects of testosterone on glucose metabolism have been reported in females; however, whether there is a sex-specific relationship between testosterone and glucose metabolism in patients with prediabetes has not been investigated in detail hitherto. Methods: This cross-sectional analysis investigated 423 males and 287 females with diagnosed prediabetes. Detailed assessment of their metabolic profiles was performed, including a 2‑h oral glucose tolerance test (OGTT), HbA1c levels, calculation of insulin resistance with homeostatic model assessment for insulin resistance (HOMA-IR), assessment of lipid metabolism, anthropometric parameters and the fatty liver index (FLI). By using Spearman’s correlation test, we investigated the sex-specific relationship between testosterone and metabolism in the prediabetic individuals. Results: In the present study, prediabetic females (mean age 58.6 years, confidence interval [CI: 57.6 y; 59.5 y]) were characterized by lower fasting plasma glucose levels (104.2 mg/dl [CI: 103.0 mg/dl; 105.4 mg/dl] vs. 106.9 mg/dl [CI: 106.0 mg/dl; 107.8 mg/dl]) and a lower FLI (49.5 [CI: 45.7; 53.2] vs. 58.8 [CI: 55.8; 61.8]), but presented with a higher risk of developing manifest type 2 diabetes in the next 10 years (FINDRISK score: 17.6 [CI: 17.1; 18.1] vs. 16.1 [CI: 15.7; 16.5]) when compared to prediabetic males (mean age: 58.04 years [CI: 57.0 y; 59.1 y]). Testosterone was negatively related to insulin resistance (HOMA-IR: Spearman’s ρ: −0.33, p < 0.01), 2‑h stimulated glucose levels during the OGTT (ρ = −0.18, p < 0.01), HbA1c levels (ρ = −0.13, p < 0.05), FLI and BMI in prediabetic males; however, no relationship between testosterone and metabolic parameters could be found in prediabetic females. Conclusion: The increase of testosterone levels in males was related to a more favorable glucose metabolism, including lower HbA1c, lower stimulated glucose levels and higher insulin sensitivity; however, in prediabetic females, testosterone was not related to glucose metabolism.

Objectives Despite the paucity of evidence verifying its efficacy and safety, traditional Chinese medicine (TCM) is expanding in popularity and political support. Decisions to include TCM diagnoses in the International Classification of Diseases 11th Revision and campaigns to integrate TCM into national healthcare systems have occurred while public perception and usage of TCM, especially in Europe, remains undetermined. Accordingly, this study investigates TCM’s popularity, usage and perceived scientific support, as well as its relationship to homeopathy and vaccinations. Design/Setting We performed a cross-sectional survey of the Austrian population. Participants were either recruited on the street (in-person) or online (web-link) via a popular Austrian newspaper. Participants 1382 individuals completed our survey. The sample was poststratified according to data derived from Austria’s Federal Statistical Office. Outcome measures Associations between sociodemographic factors, opinion towards TCM and usage of complementary medicine (CAM) were investigated using a Bayesian graphical model. Results Within our poststratified sample, TCM was broadly known (89.9% of women, 90.6% of men), with 58.9% of women and 39.5% of men using TCM between 2016 and 2019. Moreover, 66.4% of women and 49.7% of men agreed with TCM being supported by science. We found a positive relationship between perceived scientific support for TCM and trust in TCM-certified medical doctors (ρ=0.59, 95% CI 0.46 to 0.73). Moreover, perceived scientific support for TCM was negatively correlated with proclivity to get vaccinated (ρ=−0.26, 95% CI −0.43 to –0.08). Additionally, our network model yielded associations between TCM-related, homeopathy-related and vaccination-related variables. Conclusions TCM is widely known within the Austrian general population and used by a substantial proportion. However, a disparity exists between the commonly held public perception that TCM is scientific and findings from evidence-based studies. Emphasis should be placed on supporting the distribution of unbiased, science-driven information.

Combining mouse experiments with big data analysis of the Austrian population, we investigated the association between high-dose statin treatment and bone quality. The bone microarchitecture of the femur and vertebral body L4 was measured in male and ovariectomized female mice on a high-fat diet containing simvastatin (1.2 g/kg). A sex-specific matched big data analysis of Austrian health insurance claims using multiple logistic regression models was conducted (simvastatin 60-80 mg/day vs. controls; males: n = 138,666; females: n = 155,055). High-dose simvastatin impaired bone quality in male and ovariectomized mice. In the trabecular femur, simvastatin reduced bone volume (µm³: ♂, 213 ± 15 vs. 131 ± 7, p < 0.0001; ♀, 66 ± 7 vs. 44 ± 5, p = 0.02) and trabecular number (1/mm: ♂, 1.88 ± 0.09 vs. 1.27 ± 0.06, p < 0.0001; ♀, 0.60 ± 0.05 vs. 0.43 ± 0.04, p = 0.01). In the cortical femur, bone volume (mm³: ♂, 1.44 ± 0.03 vs. 1.34 ± 0.03, p = 0.009; ♀, 1.33 ± 0.03 vs. 1.12 ± 0.03, p = 0.0002) and cortical thickness were impaired (µm: ♂, 211 ± 4 vs. 189 ± 4, p = 0.0004; ♀, 193 ± 3 vs. 169 ± 3, p < 0.0001). Similar impairments were found in vertebral body L4. Simvastatin-induced changes in weight or glucose metabolism were excluded as mediators of deteriorations in bone quality. Results from mice were supported by a matched cohort analysis showing an association between high-dose simvastatin and increased risk of osteoporosis in patients (♂, OR: 5.91, CI: 3.17-10.99, p < 0.001; ♀, OR: 4.16, CI: 2.92-5.92, p < 0.001). High-dose simvastatin dramatically reduces bone quality in obese male and ovariectomized female mice, suggesting that direct drug action accounts for the association between high dosage and increased risk of osteoporosis as observed in comparable human cohorts. The underlying pathophysiological mechanisms behind this relationship are presently unknown and require further investigation.