Objective To explore the network characteristics of insomnia symptoms in patients with hypertension and their influencing factors. Methods A total of 577 patients with hypertension were selected as the research subjects, and the general data inventory, insomnia severity index (ISI), Generalized Anxiety Disorder⁃7 Items (GAD⁃7), Patient Health Questionnaire⁃9 Items (PHQ⁃9), and Connor⁃Davidson Resilience Scale (CD⁃RISC) were adopted to perform investigation on them. The R language 4.2.3 software was employed to construct Gaussian partial correlation network model of hypertensive patients with insomnia symptoms to analyze characteristics of insomnia symptoms. The multiple linear regression model was used to analyze the influencing factors for insomnia of patients with hypertension. Results A total of 446 patients suffered from insomnia among 577 patients with hypertension, with the incidence rate of insomnia being 77.3% and the incidence rate of severe early awakening being the highest. The results of Gaussian partial correlation network model analysis revealed that there were extensive correlations between various insomnia symptoms, therein “the influence on quality of life” had the greatest correlation with “level of worry about sleep”; moreover, the core symptom in this network was “level of worry about sleep”, while the bridge symptom was “dissatisfaction with sleep”. The results of multiple linear regression analysis revealed that gender, educational level, personal monthly income, smoking history, exercise frequency, maintain blood pressure grading during hospitalization, anxiety degree, depression degree, and psychological resilience were the influencing factors for severity of insomnia symptoms in patients with hypertension (P<0.05). Conclusion Severity of insomnia symptoms in patients with hypertension is affected by gender, educational level, personal monthly income, smoking history, exercise frequency, maintain blood pressure grading during hospitalization, anxiety degree, depression degree, and psychological resilience. Insomnia symptoms form an interactive network with “level of worry about sleep” at the core and “dissatisfaction with sleep” as the bridge. In clinical practice, it is important to attach great importance to targeted intervention for the negative emotions of patients with hypertension. By combining cognitive behavioral therapy, the psychological resilience of patients can be enhanced, thereby improving their sleep quality.

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