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Background. The Gaussian graphical model (GGM) is a new approach that has recently gained attention for identifying dietary patterns. It examines the connections between different food groups and how they are consumed together. The aim of our study was to investigate the link between dietary networks derived from GGM and the odds of major depressive disorder (MDD). Methods. Two hundred drug-free patients with MDD and 200 healthy individuals were enrolled in this age- and sex-matched case-control study. The mean age of the participants was 45.4 years and 67.5% were female. The Beck Depression Inventory-II questionnaire was used for screening depression in the control group. Dietary intake was assessed using a 168-item food frequency questionnaire A GGM was applied to identify dietary networks. The GGM-derived networks were scored, categorized into tertiles, and their association with MDD was determined using a multivariable logistic regression model controlling for energy intake, marital status, job status, income, living status, education, drug use, smoking status, physical activity level, family history of major depressive disorders, comorbidities, and BMI. Results. GGM identified four dietary networks: healthy, prudent, western, and mixed. Nonleafy vegetables in healthy, grains in prudent, and red meat in western dietary networks were identified as hubs, indicating their important position in the identified network. High adherence to a healthy dietary network was associated with decreased odds of MDD (OR: 0.54, 95% CI: 0.31, 0.92; p value = 0.02), whereas, participants at the highest tertile of the western dietary network had greater odds of MDD (OR: 1.80, 95% CI: 1.05, 3.08; p value = 0.03). Neither prudent nor mixed networks were associated with MDD. Conclusions. Healthy and western dietary networks were associated with lower and higher odds of MDD, respectively. Recommendations for reducing the odds of MDD can be focused on increasing nonleafy vegetables and decreasing red meat consumption. |
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