Latent profile analysis of depression in non-hospitalized elderly patients with hypertension and its influencing factors

Hypertension is a common chronic disease in the elderly, which seriously affects people's physical and mental health, leading to anxiety, depression and other symptoms. To analyze the types of depression that may occur in elderly patients with non-hospitalized hypertension and explore its influencing factors can reduce the level of depression and improve the quality of life. Based on the data of the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), latent profile analysis (LPA) was used to establish the potential profile model of elderly hypertensive patients with depression, and multiple logistic regression analysis was employed to explore the influencing factors of patients with depression. 3514 elderly patients with hypertension could be divided into three potential characteristics of depression: low-level (13.9 %), medium-level (51.9 %) and high-level (34.2 %). Multiple logistic regression showed that anxiety, IADL, age, exercise, economic level, hearing difficulty, self-reported health and visual function predicted the depression of the medium-level in the comparison between the low-level and the medium-level; taking low levels as a reference, anxiety, IADL, co-residence of interviewee, age, exercise, self-reported health marital status and visual function can predict the depression of high-level; anxiety, exercise, self-reported health and marital status predicted the depression of the high-level in the comparison between the medium-level and the high-level. (1) This study is a cross-sectional study; (2) due to data limitations, other influencing factors may be ignored. Depression in elderly patients with hypertension was divided into three potential profiles, which had obvious classification characteristics.