This study is a cross-sectional study. According to the sample size estimation method of Logistic regression analysis proposed by Chen Kun et al. (9): the sample size is 510 times the number of variables. This study contains a total of 25 assessment factors, the sample size should be: 25*(5∼10) = 125∼250 cases. Considering the 10% invalid questionnaires during data collection, the total sample size needed is 139∼278 cases. Using the convenience sampling method, 261 CHF patients hospitalized in the cardiovascular medicine department of a tertiary-level hospital in Jiaxing City were selected from December 2023 to August 2024 for the study. A total of 261 questionnaires were collected, and 261 questionnaires were valid, with a validity rate of 100%, which meets the sample size requirement.

Inclusion criteria: (1) Compliance with the Guidelines for Primary Care of Chronic Heart Failure (Practice Edition-2019) (10); (2) Age ≥18 years; (3) Those who voluntarily participated in this study and signed the informed consent. Exclusion criteria: (1) those who combined with other serious diseases or complications, such as severe hepatic and renal insufficiency, active malignant tumors, etc.; (2) those who had unclear thinking and cognitive dysfunction; (3) those who suffered from psychiatric diseases. Exclusion criteria: (1) those who filled out the questionnaire incompletely; (2) those who filled out the questionnaire randomly.

The literature on the effects of insomnia in patients with chronic heart failure was searched in Chinese databases and guideline resource websites, such as the Chinese Journal Literature Database CNKI, Wanfang Database, and Wipro Full Text Database (VIP), as well as in English databases, such as PubMed, Cochrane Library, National Guideline Clearinghouse (NGC), EMBASE, EBSCO, and JBI Evidence-Based Health Care database and other English databases to search for literature on the factors affecting insomnia in patients with chronic heart failure. Two researchers independently screened the studies that met the criteria based on the inclusion criteria and exclusion criteria, and independently completed the quality evaluation of the included literature by applying the relevant quality evaluation tools to preliminarily form a questionnaire on the risk factors for insomnia in patients with chronic heart failure. The research group discusses the relevant topics of the included literature: members of the group analyze and discuss the results of the literature with their clinical practice experience, exchange opinions with each other, and if there is disagreement, vote by secret ballot so as to reach a consensus, so as to finalize the questionnaire on risk factors for insomnia in patients with chronic heart failure, which mainly includes age, gender, marital status, education, occupation, average monthly income, mode of medical payment, illness, and so on. monthly income, medical payment method, duration of illness, smoking and alcohol consumption, number of comorbidities, cardiac function class, mood, and chronic pain.

A questionnaire survey was conducted in face-to-face format. The researcher explains the purpose of the study to the patients, and after obtaining their informed consent, the researcher and the patients sign the informed consent form together. After the beginning of the survey, the researcher interpreted the content of the questionnaire using a unified guide, and it took about 15 min to fill in the questionnaire. After the completion of filling in the questionnaire, the researcher checked to make sure that there was no omission in the content of filling in the questionnaire, and then collected the questionnaire on the spot.

PSQI: compiled by foreign scholar Buysse in 1989, it is used to assess the sleep quality of patients in the last 1 month. This study employed a localized version of the PSQI scale to assess patients’ sleep quality and the Cronbach's α coefficient of the scale is 0.842, with 18 scoring entries, involving 7 dimensions of sleep quality, time to sleep, sleep duration, sleep disorders, sleep efficiency, hypnotic drugs, and daytime functioning (11). Each dimension is scored according to 0–3 points, with the total score ranging from 0 to 21 points, and the higher the score, the worse the sleep quality. In our country, PSQI > 7 indicates decreased sleep quality, and PSQI ≤ 7 indicates normal sleep quality.

This study was reviewed by the Ethics Committee of The Second Hospital of Jiaxing (approval number 2023YJ005-01), and all patients gave informed consent and participated in the study voluntarily.

Data were analyzed using SPSS 26.0 statistical software with a test level of α=0.05. General information of CHF patients and insomnia-related risk factors were statistically described using the number of cases and constitutive ratios, and the PSQI scores were described using the mean ± standard deviation (x¯±s). Independent samples t-test or one-way ANOVA was used for univariate analysis of factors affecting insomnia in CHF patients; subsequently, multivariate logistic regression analyses were performed on statistically significant and clinically relevant variables.

Insomnia was present in 174 (66.7%) of 261 CHF patients. The results of univariate analysis showed that gender, work status, family residence, occupational status, nature of occupation, residence, mood, NYHA cardiac function classification, chronic pain, monthly per capita family income, socialization range, smoking, alcohol consumption, number of comorbidities, comorbid diabetes mellitus, and healthcare payment method were all statistically significant (P < 0.05), as shown in Table 1.

Logistic regression analysis was used to explore the influencing factors of insomnia in CHF patients. Taking whether insomnia occurred as the dependent variable, all the meaningful independent variables in Table 1 were included in the Logistic regression analysis, in which the continuous variables were substituted with the original values, and the categorical variables were assigned as shown in Table 2. The results showed that the likelihood ratio test of P < 0.01 indicated that the model passed the test, and among the goodness-of-fit, the Pearson x² > 0.05 indicated that the goodness-of-fit was good. Gender, mood, NYHA cardiac function class, chronic pain, per capita monthly household income, socialization range, smoking, number of comorbidities, and healthcare payment method were associated with insomnia in patients with CHF, and the differences were statistically significant (P < 0.05), as shown in Table 3.

Gender, chronic pain, and anxiety-depression states are significant risk factors for insomnia in CHF patients. In this study, the proportion of female patients with insomnia was significantly higher than that of males, consistent with existing research (12–14). This may be related to hormonal fluctuations, psychological characteristics, and higher family and social role pressures in women. Furthermore, chronic pain frequently co-occurs with sleep disturbances and emotional issues. CHF patients, burdened by long-term treatment stress, social limitations, and family caregiving responsibilities, are more prone to anxiety and depression, creating a vicious cycle between insomnia and psychological distress (15, 16). Therefore, clinical management of CHF should prioritize comprehensive mind-body interventions, integrating physiological treatments with psychological support.

Cardiac dysfunction is a core factor affecting sleep in CHF patients. This study indicates that declining cardiac function is the primary cause of insomnia in CHF patients, with higher rates of insomnia occurring in those with poorer cardiac function. As cardiac function deteriorates, patients may develop pulmonary and systemic venous congestion, triggering symptoms such as coughing and dyspnea that severely disrupt sleep onset and maintenance. Additionally, CHF often coexists with sleep apnea, further disrupting sleep architecture. The study also indicates that the number of complications positively correlates with the severity of sleep disturbances. Insomnia may further exacerbate left ventricular remodeling and pulmonary hypertension, creating a vicious cycle. Regarding behavioral factors, smoking worsens insomnia through mechanisms including neural excitation, insufficient cerebral blood flow, airway irritation, and neurotransmitter disruption (17–21). Therefore, improving cardiac function, managing complications, and quitting smoking are key to enhancing patients' sleep quality.

Social support serves as an independent protective factor against insomnia in CHF patients (P < 0.05). Stable economic income and healthcare coverage alleviate the psychological burden of medical expenses, thereby reducing anxiety and improving sleep (22). Family care and companionship help boost patient confidence and reduce psychological stress (23). Furthermore, extensive social networks alleviate feelings of loneliness, promote positive emotions, and collectively contribute to improved sleep quality. Therefore, establishing a comprehensive support system integrating family, medical, and social resources holds significant practical importance for CHF patients.