Inappropriate sleep duration and poor sleep quality are associated with risk of stroke, but their interactive effect on stroke is unknown. We explored the interactive effect of sleep quality and duration on stroke risk. A prospective cohort study was conducted with 41,786 adults. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. Sleep duration was measured by average hours of sleep per night. Cox regression models were used to calculate the association of sleep duration and quality with stroke. The delta method and a non-conditional logistic regression model were used and the relative excess risk due to interaction (RERI), the attributable proportion (AP), and the synergy index (S) were calculated. Compared with sleep duration 6–8 h/day, the risk ratio of stroke was 1.63 (1.23–2.11) times for sleep duration <6 h/day and 1.40 (1.08–1.75) times for >8 h/day. The stroke risk ratio was 2.37 (1.52–3.41) times in subjects with poor sleep quality compared with those with good sleep quality. Women who slept <6 h/day had higher stroke risk than men who slept <6 h/day. Men who slept >8 h/day had higher stroke risk than women who slept >8 h/day. Men with poor sleep quality had higher stroke risk than women with poor sleep quality. Stroke was associated with short/long sleep duration and poor sleep quality in subjects aged >46 years, compared with those aged 18–45 years. Stroke occurred more frequently in subjects with poor sleep quality combined with short sleep duration (odds ratio: 6.75; 95% confidence interval (CI): 2.45–14.12). RERI, AP, and S values (and their 95% CIs) were 5.54 (3.75–8.12), 0.72 (0.56–0.80), and 5.69 (4.23–9.90) for the poor sleep quality interact with short sleep duration. In persons with poor sleep quality accompanied by long sleep duration, RERI, AP, and S (95% CI) were 1.12 (1.01–1.27), 0.35 (0.26–0.51), and 2.05 (1.57–2.96), respectively. Subjective sleep disturbances are related with risk of stroke in Chinese adults. There are additive interactions between short/long sleep duration and poor sleep quality that affect risk of stroke.

Background “Overlap syndrome” refers to obstructive sleep apnea (OSA) combined with chronic obstructive pulmonary disease (COPD), and has poorer outcomes than either condition alone. We aimed to evaluate the prevalence and possible predictors of overlap syndrome and its association with clinical outcomes in patients with COPD. Methods We assessed the modified Medical Research Council dyspnea scale (mMRC), Epworth sleepiness scale (ESS), COPD assessment test (CAT), Hospital Anxiety and Depression Scale (HADS), Charlson Comorbidity Index (CCI), and STOP-Bang questionnaire (SBQ) and performed spirometry and full overnight polysomnography in all patients. An apnea–hypopnea index (AHI) ≥ 5 events per hour was considered to indicate OSA. Risk factors for OSA in COPD patients were identified by univariate and multivariate logistic regression analyses. Results A total of 556 patients (66%) had an AHI ≥ 5 events per hour. There were no significant differences in age, sex ratio, mMRC score, smoking index, number of acute exacerbations and hospitalizations in the last year, and prevalence of cor pulmonale between the two groups (all p > 0.05). Body mass index (BMI), neck circumference, CAT score, CCI, ESS, HADS, and SBQ scores, forced expiratory volume (FEV)1, FEV1% pred, FEV1/forced vital capacity ratio, and prevalence of hypertension, coronary heart disease, and diabetes were all significantly higher and the prevalence of severe COPD was significantly lower in the COPD-OSA group compared with the COPD group (p < 0.05). BMI, neck circumference, ESS, CAT, CCI, HADS, hypertension, and diabetes were independent risk factors for OSA in COPD patients (p < 0.05). SBQ could be used for OSA screening in patients with COPD. Patients with severe COPD had a lower risk of OSA compared with patients with mild or moderate COPD (β =  − 0.459, odds ratio = 0.632, 95% confidence interval 0.401–0.997, p = 0.048). Conclusion Patients with overlap syndrome had a poorer quality of life, more daytime sleepiness, and a higher prevalence of hypertension and diabetes than patients with COPD alone. BMI, neck circumference, ESS, CAT, CCI, HADS, hypertension, and diabetes were independent risk factors for OSA in patients with COPD. The risk of OSA was lower in patients with severe, compared with mild or moderate COPD.

ObjectivesDiabetes and smoking are known independent risk factors for stroke; however, their interaction concerning stroke is less clear. We aimed to explore such interaction and its influence on stroke in Chinese adults.DesignCross-sectional study.SettingCommunity-based investigation in Xuzhou, China.ParticipantsA total of 39 887 Chinese adults who fulfilled the inclusion criteria were included.MethodsParticipants were selected using a multistage stratified cluster method, and completed self-reported questionnaires on stroke and smoking. Type 2 diabetes mellitus (DM2) was assessed by fasting blood glucose or use of antidiabetic medication. Interaction, relative excess risk owing to interaction (RERI), attributable proportion (AP) and synergy index (S) were evaluated using a logistic regression model.ResultsAfter adjustment for age, sex, marital status, educational level, occupation, physical activity, body mass index, hypertension, family history of stroke, alcohol use and blood lipids, the relationships between DM2 and stroke, and between smoking and stroke, were still significant: ORs were 2.75 (95% CI 2.03 to 3.73) and 1.70 (95% CI 1.38 to 2.10), respectively. In subjects with DM2 who smoked, the RERI, AP and S values (and 95% CIs) were 1.80 (1.24 to 3.83), 0.52 (0.37 to 0.73) and 1.50 (1.18 to 1.84), respectively.ConclusionsThe results suggest there are additive interactions between DM2 and smoking and that these affect stroke in Chinese adults.

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Background Alexithymia is a common psychological disorder. However, few studies have investigated its prevalence and predictors in patients with chronic obstructive pulmonary disease (COPD). Therefore, we aimed to determine the prevalence and predictors of alexithymia in Chinese patients. Methods This cross-sectional study included 842 COPD patients to assess the prevalence and predictors of alexithymia using the 20-item Toronto Alexithymia Scale (TAS-20). We used the Hospital Anxiety and Depression Scale (HADS) to assess anxiety and depression, the modified British Medical Research Council dyspnea Rating Scale (mMRC) to assess dyspnea, St. George's Respiratory Questionnaire (SGRQ) to assess quality of life, and the age-adjusted Charlson comorbidity index (ACCI) to assess comorbidities. Alexithymia-related predictors were identified using univariate and multivariate logistic regression analyses. Results The prevalence of alexithymia in COPD patients was 23.6% (199/842). Multivariate analysis showed that age [odds ratio (OR) 0.886; 95% confidence interval (CI) 0.794–0.998], body mass index (OR 0.879; 95% CI 0.781–0.989), HADS-anxiety (OR 1.238; 95% CI 1.097–1.396), HADS-depression (OR 1.178; 95% CI 1.034–1.340), mMRC (OR 1.297; 95% CI 1.274–1.320), SGRQ (OR 1.627; 95% CI 1.401–1.890), ACCI (OR 1.165; 95% CI 1.051–1.280), and GOLD grade (OR 1.296; 95% CI 1.256–1.337) were independent predictors for alexithymia in patients with COPD. Conclusions The prevalence of alexithymia was high in Chinese COPD patients. Anxiety, depression, dyspnea, quality of life, comorbidities, and disease severity are independent risk factors, and age and BMI are predictive factors for alexithymia in COPD patients.