Abstract: Objective To explore the current status of depression in elderly hypertensive patients and to analyze the influencing factors of different latent profiles. Methods A total of 1 000 hypertensive patients admitted to the Fourth Affiliated Hospital of Nanjing Medical University during the time period of January to December 2023 were selected as the subjects of this study, and a general information questionnaire and a geriatric depression scale were used to conduct the questionnaire survey. Latent profile analysis was conducted to characterize the depression status of elderly hypertensive patients, and the influencing factors of the latent profiles of depression status were explored by univariate analysis. Results A total of 908 valid questionnaires were collected, yielding an effective response rate of 90.80%. The mean depression score of elderly hypertensive patients was （6.25±2.25） points. The depression status of elderly hypertensive patients was categorized into three latent profiles：high depression group, high loneliness with moderate depression group, and low depression group. The average probabilities of elderly hypertensive patients belonging to each latent profile was 0.966, 0.956, and 0.967, respectively. The analysis of influencing factors revealed that there were statistically significant differences in the depression status groups of elderly hypertensive patients in terms of age, marital status, living arrangement, monthly income, visual function, auditory function, and self-care ability （χ²=6.938-38.434, P<0.05 or P<0.01）. Conclusions The depression status subgroups of elderly hypertensive patients are heterogeneous. Clinical staff should identify the characteristics of different categories of patients, and actively adopt countermeasures for highly depressed elderly hypertensive patients, which is conducive to reducing the occurrence of depression and has a positive effect on the maintenance of their mental health.

Key words: Elderly, Hypertension, Depression, Latent profile, Influencing factor