The Joint Association Between Multiple Dietary Patterns and Depressive Symptoms in Adults Aged 55 and Over in Northern China.

Background: Depression is a common psychiatric disorder in older adults that affects their health-related quality of life. Two percent of adults over the age of 55 suffer from major depression, and the prevalence of depression increases with age. Even in the absence of major depressive disorder, 10-15% of older adults have clinically significant depressive symptoms. Objectives: Epidemiological studies on the association between different gender eating patterns and depression show inconsistent associations. Our study examined whether different gender eating patterns are related to depression. We consider eating patterns individually and as a joint exposure to predefined eating patterns. Methods: Principal component analysis (PCA) was performed on the data of the 24-h diet recall dietary intake, and the dietary pattern was determined. Linear regression models are used to explore the relationship between different diets and depression of men and women; weighted quantile sum (WQS) regression, quantile g calculation (qgcomp) and Bayesian kernel machine regression (BKMR) are performed as Secondary analysis. Results: In the dietary patterns model, we found that the vegetable and fruit-based diet has a significant inhibitory effect in women, and the egg-milk-based diet has a significant inhibitory effect in men. We found that when all dietary factors are above the 55th percentile, there is a significant positive correlation between multiple dietary patterns and depression risk. We also determined a positive correlation between meat and obesity risk and a negative correlation between egg and milk and vegetables and fruits. Conclusions: In the study population, after controlling for other baseline indicators and predictors of dietary pattern exposure, a fruit and vegetable-based diet was associated with a slightly healthier and lower risk of depression, while a meat-based dietary pattern associated with a higher risk of depression, and this association effect varies between genders.