Logistic Regression for Clustered Binary Data in Proband Studies with Application to Familial Aggregation of Sleep Disorders

Biometrics ◽  
1991 ◽  
Vol 47 (4) ◽  
pp. 1257 ◽  
Author(s):  
Tor D. Tosteson ◽  
Bernard Rosner ◽  
Susan Redline
Keyword(s):  
Logistic Regression ◽  
Sleep Disorders ◽  
Binary Data ◽  
Familial Aggregation ◽  
Clustered Binary Data

Estimating marginal proportions and intraclass correlations with clustered binary data

2018 ◽  
Vol 61 (3) ◽  
pp. 574-599
Author(s):  
Josep L. Carrasco ◽  
Yi Pan ◽  
Rosa Abellana
Keyword(s):  
Binary Data ◽  
Clustered Binary Data ◽  
Intraclass Correlations

scholarly journals Evaluation of Subjective Sleep Disturbances in Cancer Patients: A Cross-Sectional Study in a Radiotherapy Department

2021 ◽  
Vol 12 ◽  
Author(s):  
Jun Wang ◽  
Bei-Yun Zhou ◽  
Chen-Lu Lian ◽  
Ping Zhou ◽  
Hui-Juan Lin ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Sleep Quality ◽  
Sleep Disturbance ◽  
Sleep Disorders ◽  
Cancer Patients ◽  
Sleep Disturbances ◽  
Cancer Type ◽  
Multivariate Logistic Regression ◽  
Subjective Sleep ◽  
Radiotherapy Department

Background: The factors associated with sleep disturbances in cancer patients remains unclear. This study aimed to explore the prevalence of sleep disorders and predictors associated with sleep disturbance in cancer patients from a radiotherapy department.Methods: Patients with cancers were recruited before the start of radiotherapy from our institution between January 2019 and February 2020. Pittsburgh Sleep Quality Index (PSQI) scale was used to assess sleep quality. Descriptive statistics, Chi-square test, and multivariate logistic regression analysis were used to conduct statistical analysis.Results: A total of 330 eligible patients were included. Of them, 38.3% (n = 127) had the globe PSQI score >7, indicating that they suffered from sleep disorders. Patients with lung cancer (45.2%) were more likely to suffer from sleep disturbance, followed by cervical cancer (43.8%), nasopharyngeal carcinoma (41.7%), esophageal cancer (41.5%), breast cancer (37.7%), and colorectal cancer (30%). With regard to the PSQI components, the mean sleep duration was 8 h, 20.3% (n = 67) of them reported poor subjective sleep quality, 6.1% (n = 20) needed medication to improve sleep, and 53.6% (n = 177) suffered daytime dysfunction. Multivariate logistic regression models showed body mass index (BMI) ≥ 20 kg/m2 [odds ratio (OR) 0.599, 95% confidence interval (CI) 0.329–0.948, P = 0.031] and the receipt of surgery (OR 0.507, 95% CI 0.258–0.996, P = 0.048) were the significant favorable predictors for sleep disturbance, while age, gender, marital status, education level, comorbidity, metastasis status, diagnostic status, and cancer type were not significantly associated with sleep disturbance.Conclusions: Approximately 40% of the cancer patients suffer from sleep disturbance before the start of radiotherapy. Patients with BMI ≥ 20 kg/m2 and receiving surgery are less likely to develop sleep disturbance in comparison with others.

scholarly journals Familial aggregation of sleep disorders – a questionnaire based study

2010 ◽  
Vol 5 (2) ◽  
pp. 50-53
Author(s):  
Tulsi Adhikari ◽  
M K Sen ◽  
J. C. Suri
Keyword(s):  
Sleep Disorders ◽  
Familial Aggregation
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