Effects of smoking habit change on hospitalized fractures: a retrospective cohort study in a male population

The association of smoking on the increased risk of osteoporotic fracture: Results from a cross-sectional study and two-sample Mendelian randomization

INTRODUCTION

We conducted analyses of the association between smoking and osteoporosis and osteoporotic fractures using a secondary dataset analysis of the National Health and Nutrition Examination Survey (NHANES) database and the two-sample Mendelian randomization (MR) method.

METHODS

The associations between smoking and osteoporosis or osteoporotic fractures were analyzed using weighted logistic regression models for both univariate and multivariable analyses using pooled 1999-2018 NHANES data. The summary-level data of genome-wide association studies (GWAS) of smoking and osteoporosis were extracted from the IEU Open GWAS project. The inverse variance weighted method was used as the main method for the two-sample MR analysis.

RESULTS

We obtained the following main findings based on the NHANES data: smoking was associated with osteoporosis according to the analyses of 30856 participants (OR=1.21; 95% CI: 1.06-1.39, p=0.004); smoking was associated with hip osteoporotic fracture according to the analyses of 30928 participants (OR=1.47; 95% CI: 1.14-1.90, p=0.004); smoking was associated with wrist osteoporotic fracture according to the analyses of 30923 participants (OR=1.33; 95% CI: 1.18-1.49, p<0.001); and smoking was associated with spine osteoporotic fracture according to the analyses of 30910 participants (OR=1.43, 95% CI: 1.18-1.73, p<0.001). In addition, we confirmed the potential causal effect of smoking on the risk of osteoporotic fracture (OR=24.5; 95% CI: 1.11-539, p=0.043) by conducting two-sample MR analyses.

CONCLUSIONS

Smoking was associated with increased risks of both osteoporosis and osteoporotic fracture. Smoking showed a potential causal effect on the risk of osteoporotic fracture.

Association between Smoking Status and the Risk of Hip Fracture in Patients with Type 2 Diabetes: A Nationwide Population-Based Study

BACKGRUOUND

Limited longitudinal evidence exists regarding the potential association between smoking status and hip fracture among individuals with type 2 diabetes. We investigated this association using large-scale, nationwide cohort data for the Korean population.

METHODS

This nationwide cohort study included 1,414,635 adults aged 40 and older who received Korean National Health Insurance Service health examinations between 2009 and 2012. Subjects with type 2 diabetes were categorized according to their smoking status, amount smoked (pack-years), number of cigarettes smoked per day, and duration of smoking. The results are presented as hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between smoking status parameters and risk of hip fracture in multivariable Cox proportional hazard regression analysis.

RESULTS

Compared with never-smokers, an increased adjusted HR (aHR) for hip fracture was observed in current smokers (1.681; 95% CI, 1.578 to 1.791), and a comparable aHR for hip fracture was found in former smokers (1.065; 95% CI, 0.999 to 1.136). For former smokers who had smoked 20 pack-years or more, the risk was slightly higher than that for never-smokers (aHR, 1.107; 95% CI, 1.024 to 1.196). The hip fracture risk of female former smokers was similar to that of female current smokers, but the hip fracture risk in male former smokers was similar to that of male never-smokers.

CONCLUSION

Smoking is associated with an increased risk of hip fracture in patients with type 2 diabetes. Current smokers with diabetes should be encouraged to quit smoking because the risk of hip fracture is greatly reduced in former smokers.

Assessment of Osteoporosis Awareness and Osteoporosis Risk Level of Patients Admitted to a University Hospital

INTRODUCTION

We aimed to evaluate osteoporosis awareness and risk of osteoporosis in individuals by using the One-Minute Osteoporosis Risk Test and Osteoporosis Self-Assessment Tool for Asians score.

METHODOLOGY

This descriptive cross-sectional study included 591 volunteers who were admitted to the Internal Medicine outpatient clinic of the University Hospital. The One-Minute Osteoporosis Risk Test was applied through face-to-face interviews. Participants were classified as low, medium, and high osteoporosis risk groups in terms of the Osteoporosis Self-Assessment Tool for Asians scores.

RESULTS

Median score of the One-Minute Osteoporosis Risk Test was 1 (0-2) and the mean score of the Osteoporosis Self-Assessment Tool for Asians was 4.61 ± 3.80. In terms of the Osteoporosis Self-Assessment Tool for Asians score, 0.7% (n = 4) of the participants have a high risk of osteoporosis, 5.4% (n = 32) have a medium risk of osteoporosis and 93.9% (n = 555) have a low risk of osteoporosis. One-Minute Osteoporosis Risk Test scores of participants in terms of the osteoporosis risk levels were not significantly different (p = 0.432). The proportion of having information about osteoporosis in men was significantly lower than in women (21.0% vs. 33.4%, p = 0.004). The proportion of obtained information from medical staff was significantly higher in women than men (86.9% vs. 66.7%, p = 0.005). Informed participants have a significantly higher One-Minute Osteoporosis Risk Test score than non-informed participants (p = 0.004).

RESULTS

The risk of osteoporosis was found to be low in individuals admitted to the university hospital. The Osteoporosis Self-Assessment Tool for Asians score was more effective in determining the osteoporosis risk level compared to the One-Minute Osteoporosis Risk Test. Men should be given as much importance as women in informing about osteoporosis. Media tools should be used more effectively for this purpose.

Incidence and Risk Factors for Surgical Site Infection after Femoral Neck Fracture Surgery: An Observational Cohort Study of 2218 Patients

Background

Surgical site infection (SSI) was a formidable challenge for surgical management of femoral neck fractures; however, there was a lack of studies with comprehensive variables. We conducted this study to investigate the incidence and risk factors of SSI in elderly patients with femoral neck fractures.

Methods

This was a retrospective study of patients who presented with femoral neck fractures and underwent surgery in our institution between January 2016 and April 2020. All data were collected from a previously validated database. Patients were divided into SSI and non-SSI groups. Univariate and multivariate logistic regression analyses were conducted to identify the risk factors for SSI.

Results

A total of 2218 patients with femoral neck fractures were enrolled in the study, of whom 22 (1%) developed SSI, including 15 (0.7%) superficial and 7 (0.3%) deep SSIs. After multivariable adjustment for confounding factors, patients with and without SSI significantly differ in terms of gender, prolonged time to surgery, CHE < 5 U/L, and injury mechanism.

Conclusions

Our results were helpful for stratification of SSI risk and improved management of hip fracture. Clinicians should be alert to patients with these factors and improve modifiable factors such as preoperative waiting time.

Smoking and fracture risk in men: a meta-analysis of cohort studies, using both frequentist and Bayesian approaches

Past studies indicate that men are more likely to smoke and be at higher risk of smoking-related conditions than women. Our research aimed, through meta-analysis, to assess the association between smoking and fracture risk in men. The following databases were searched, including MEDLINE, EMBASE, Scopus, PsycINFO, ISI Web of Science, Google Scholar, WorldCat, and Open Grey, for identifying related studies. A random-effects model was used to pool the confounder-adjusted relative risk (R.R.). Frequentist and Bayesian hierarchical random-effects models were used for the analysis. The heterogeneity and publication bias were evaluated in this study. Twenty-seven studies met the inclusion criteria. Overall, smoking is associated with a significantly increased risk of fracture in both the frequentist approach (R.R., 1.37; 95% confidence interval: 1.22, 1.53) and the Bayesian approach (R.R., 1.36; 95% credible interval: 1.22, 1.54). Significant heterogeneity was observed in the meta-analysis (Higgin's I² = 83%) and Cochran's Q statistic (p < 0.01). A significant association was also observed in multiple pre-specified sensitivity and subgroup analyses. Similar results were observed in the group containing a large sample size (≥ 10,000 participants), and the group has a small sample size (< 10,000 participants); the pooled R.R was 1.23 (95% confidence interval, 1.07–1.41) and 1.56 (95% confidence interval, 1.37–1.78), respectively. With the Bayesian method, the effect size was 1.23 (95% credible interval, 1.05, 1.45) for the large sample size group and 1.57 (95% credible interval, 1.35, 1.82) for the small sample size group. Smoking is associated with a significant increase in fracture risk for men. Thus, smoking cessation would also greatly reduce fracture risk in all smokers, particularly in men.

Prediction model for the risk of osteoporosis incorporating factors of disease history and living habits in physical examination of population in Chongqing, Southwest China: based on artificial neural network

Background

Osteoporosis is a gradually recognized health problem with risks related to disease history and living habits. This study aims to establish the optimal prediction model by comparing the performance of four prediction models that incorporated disease history and living habits in predicting the risk of Osteoporosis in Chongqing adults.

Methods

We conduct a cross-sectional survey with convenience sampling in this study. We use a questionnaire From January 2019 to December 2019 to collect data on disease history and adults’ living habits who got dual-energy X-ray absorptiometry. We established the prediction models of osteoporosis in three steps. Firstly, we performed feature selection to identify risk factors related to osteoporosis. Secondly, the qualified participants were randomly divided into a training set and a test set in the ratio of 7:3. Then the prediction models of osteoporosis were established based on Artificial Neural Network (ANN), Deep Belief Network (DBN), Support Vector Machine (SVM) and combinatorial heuristic method (Genetic Algorithm - Decision Tree (GA-DT)). Finally, we compared the prediction models’ performance through accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) to select the optimal prediction model.

Results

The univariate logistic model found that taking calcium tablet (odds ratio [OR] = 0.431), SBP (OR = 1.010), fracture (OR = 1.796), coronary heart disease (OR = 4.299), drinking alcohol (OR = 1.835), physical exercise (OR = 0.747) and other factors were related to the risk of osteoporosis. The AUCs of the training set and test set of the prediction models based on ANN, DBN, SVM and GA-DT were 0.901, 0.762; 0.622, 0.618; 0.698, 0.627; 0.744, 0.724, respectively. After evaluating four prediction models’ performance, we selected a three-layer back propagation neural network (BPNN) with 18, 4, and 1 neuron in the input layer, hidden and output layers respectively, as the optimal prediction model. When the probability was greater than 0.330, osteoporosis would occur.

Conclusions

Compared with DBN, SVM and GA-DT, the established ANN model had the best prediction ability and can be used to predict the risk of osteoporosis in physical examination of the Chongqing population. The model needs to be further improved through large sample research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11002-5.

Smoking and the patient with a complex lower limb injury

Smoking is known to increase the risk of peri-operative complications in Orthoplastic surgery by impairing bone and wound healing. The effects of nicotine replacement therapies (NRTs) and electronic cigarettes (e-cigarettes) has been less well established. Previous reviews have examined the relationship between smoking and bone and wound healing separately. This review provides surgeons with a comprehensive and contemporaneous account of how smoking in all forms interacts with all aspects of complex lower limb trauma. We provide a guide for surgeons to refer to during the consent process to enable them to tailor information towards smokers in such a way that the patient may understand the risks involved with their surgical treatment. We update the literature with recently discovered methods of monitoring and treating the troublesome complications that occur more commonly in smokers effected by trauma.