Insomnia Burden among Informal Caregivers of Hospitalized Lung Cancer Patients and Its Influencing Factors.

Objective: This study aimed to reveal the insomnia burden and relevant influencing factors among informal caregivers (ICs) of hospitalized patients with lung cancer. Methods: A cross-sectional study on ICs of hospitalized patients with lung cancer was conducted from December 31, 2020 to December 31, 2021. ICs' burden was assessed using the Caregiver Reaction Assessment (CRA), Hospital Anxiety and Depression Scale (HADS), and Insomnia Severity Index (ISI). Linear and logistic regression models were used to identify the influencing factors. Results: Among 289 ICs of hospitalized patients with lung cancer, 83 (28.72%), 53 (18.34%), and 14 (4.84%) ICs experienced mild, moderate, and severe insomnia, respectively. The scores concerning self-esteem, lack of family support, financial problems, disturbed schedule, and health problems were 4.32 ± 0.53, 2.24 ± 0.79, 2.84 ± 1.14, 3.63 ± 0.77, and 2.44 ± 0.95, respectively. ICs with higher Activities of Daily Living Scale (ADLS) scores were associated with a lower risk of insomnia, with an odd ratio ( OR) and 95% confidence interval ( CI) of 0.940 (0.898-0.983). Among the ICs, female gender ( OR = 2.597), alcohol consumption ( OR = 3.745), underlying medical conditions ( OR = 11.765), long-term caregiving experience ( OR = 37.037), and higher monthly expenses ( OR = 5.714) were associated with a high risk of insomnia. Conclusion: Of the hospitalized patients with lung cancer, 51.9% experienced insomnia. Patients' ADL, ICs gender, alcohol consumption, underlying medical conditions, caregiving duration, and monthly expenses were influencing factors. Therefore, prompt screening and early intervention for ICs of patients with lung cancer is necessary.

Combined Effect of Smoking and Obesity on Coronary Heart Disease Mortality in Male Veterans: A 30-year Cohort Study.

OBJECTIVE: Evidence is lacking regarding the combined effects of smoking and obesity on mortality from coronary heart disease in male veterans. This study aimed to explore the combined effect of smoking and obesity on coronary heart disease mortality in male veterans in China. METHODS: A cohort of 1,268 male veterans from 22 veteran centers in Xi'an (Shaanxi Province, China) were followed up once every 2 years from February 1, 1987 to October 30, 2016. The endpoint was death from any cause. The hazard ratio ( HR) of each risk factor and the 95% confidence interval ( CI) were calculated using a multivariate Cox proportional hazard model. RESULTS: The total follow-up was 24394.21 person-years; each subject was followed up for a mean duration of 19.24 years. By the end of the study, of the 1,268 veterans, 889 had died, 363 were alive, and 16 were lost to follow-up. Cox regression analysis results revealed that current smoking ( HR: 1.552, 95% CI: 1.074-2.243), obesity ( HR: 1.625, 95% CI: 1.024-2.581), and the combined effect of the two factors ( HR: 2.828, 95% CI: 1.520-5.262) were associated with coronary heart disease mortality. CONCLUSION: Our results suggest that obese veterans who smoke might be an important target population for coronary heart disease mortality control.

Analysis of Factors Influencing Insomnia and Construction of a Prediction Model: A Cross-sectional Survey on Rescuers.

OBJECTIVE: To determine the factors influencing insomnia and construct early insomnia warning tools for rescuers to informbest practices for early screening and intervention. METHODS: Cluster sampling was used to conduct a cross-sectional survey of 1,133 rescuers from one unit in Beijing, China. Logistic regression modeling and R software were used to analyze insomnia-related factors and construct a PRISM model, respectively. RESULTS: The positive rate of insomnia among rescuers was 2.74%. Accounting for participants' age, education, systolic pressure, smoking, per capita family monthly income, psychological resilience, and cognitive emotion regulation, logistic regression analysis revealed that, compared with families with an average monthly income less than 3,000 yuan, the odds ratio ( OR) values and the [95% confidence interval ( CI)] for participants of the following categories were as follows: average monthly family income greater than 5,000 yuan: 2.998 (1.307-6.879), smoking: 4.124 (1.954-8.706), and psychological resilience: 0.960 (0.933-0.988). The ROC curve area of the PRISM model (AUC) = 0.7650, specificity = 0.7169, and sensitivity = 0.7419. CONCLUSION: Insomnia was related to the participants' per capita family monthly income, smoking habits, and psychological resilience on rescue workers. The PRISM model's good diagnostic value advises its use to screen rescuer early sleep quality. Further, advisable interventions to optimize sleep quality and battle effectiveness include psychological resilience training and smoking cessation.