Determination of the relationship between dietary inflammatory index and depression status in female students.
Ezgi ArslanTuğçe ÖzlüEmre Batuhan KengerBilge Meral KocPublished in: Nutrition and health (2022)
Background: The relationship between diet, inflammation and mental health has been receiving increasing interest. However, limited data are available on the inflammatory role of diet in university students, among whom depression is commonly observed. Aim: The aim of our study is to investigate the relationship between dietary inflammatory index (DII) and depression among female students of nutrition and dietetics department, whom we assume to be conscious about health. Methods: DII scores were determined by averaging the 3-day dietary records. Depression status of the students was determined by using Beck Depression Inventory (BDI). Results: Our study was conducted with 122 female university students. The mean total BDI score of the students in the first tertile (more anti-inflammatory effect) was found significantly lower than those of the students in the second and third tertiles ( p = 0.001). In addition, there were no significant difference between the depression scores of the students and their grade level ( p = 0.114) and place of residence ( p = 0.866). We found a positive association between DII and depressive symptoms (Model 1, B = 0.512, %95 CI: 0.236-0.789, p = 0.000). This relationship was also found when adjusting for age, weight, body mass index, smoking status, and presence of chronic disease (Model 2, B = 0.496, %95 CI: 0.217-0.776, p = 0.006; Model 3, B = 0.493, %95 CI: 0.210-0.777, p = 0.024. Conclusion: Supporting that the inflammatory burden of diet is associated with mental health, our findings are of significance for the development of anti-inflammatory nutritional approaches among students who are prone to depression.
Keyphrases
- depressive symptoms
- mental health
- high school
- sleep quality
- body mass index
- physical activity
- oxidative stress
- weight loss
- public health
- machine learning
- risk assessment
- climate change
- weight gain
- mass spectrometry
- deep learning
- risk factors
- health information
- smoking cessation
- liquid chromatography
- tandem mass spectrometry