Decoding Depression in Elderly Hypertensive Patients: A Latent Profile Analysis
Hypertension, a prevalent condition in the elderly, often intertwines with mental health issues like depression. A recent study, using data from the 2018 Chinese Longitudinal Healthy Longevity Survey, investigates depression types in elderly hypertensive patients. Latent profile analysis (LPA) was used to categorize depression into three levels: low, medium, and high. This categorization helps in understanding the varying degrees of depression among these patients.
The study identified that 13.9% of patients had low-level depression, 51.9% medium-level, and 34.2% high-level. Factors like anxiety, instrumental activities of daily living (IADL), age, exercise, economic status, hearing and visual function, and self-reported health were significant in predicting depression levels. These findings emphasize the complex interplay of physical and mental health in elderly hypertensive patients.
Despite its cross-sectional nature and potential data limitations, the study offers valuable insights. It highlights the need for holistic healthcare approaches, considering both physical and mental health aspects, especially in managing hypertension in the elderly. Such approaches could significantly improve their quality of life.
Article Information
Latent profile analysis of depression in non-hospitalized elderly patients with hypertension and its influencing factors
Journal of Affective Disorders. Linghui Kong et al.
Abstract
Background: 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.
Methods: 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.
Results: 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.
Limitations: (1) This study is a cross-sectional study; (2) due to data limitations, other influencing factors may be ignored.
Conclusion: Depression in elderly patients with hypertension was divided into three potential profiles, which had obvious classification characteristics.
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