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Depression, Anxiety, Emotional Eating, and Body Mass Index among Self-Reported Vegetarians and Non-Vegetarians: A Cross-Sectional Study in Peruvian Adults
Author(s)
Universidad Señor de Sipán
Carranza-Cubas, Sandra P.
Universidad Señor de Sipán
Serpa‐Barrientos, Antonio
National University of San Marcos
Universidad San Ignacio de Loyola
Date Issued
29 de mayo de 2024
Type
Article
Volume
16
Issue
11
Series/Report No.
Nutrients
Start Page
1663
End Page
1663
ISSN
2072-6643
Abstract
Background: Vegetarianism is commonly associated with various health benefits. However, the association between this dietary regimen and aspects of mental health remains ambiguous. This study compared the symptoms of depression and anxiety, emotional eating (EmE), and body mass index (BMI) in Peruvian vegetarian and non-vegetarian adults. Methods: A cross-sectional study was conducted on 768 Peruvian adults, of whom 284 (37%) were vegetarians and 484 (63%) were non-vegetarians. The Depression Patient Health Questionnaire-2 (PHQ-2), Generalized Anxiety Disorder Scale-2 (GAD-2), and an EmE questionnaire were applied; additionally, the BMI was calculated. Simple and multiple linear regression and Poisson regression models with robust variance were used to evaluate the association between depression, anxiety, EmE, and BMI with dietary patterns. Results: The vegetarians (Adjusted Prevalence Ratio [PR] = 0.24, 95% CI 0.16–0.31; p < 0.001) reported more depressive symptoms than the non-vegetarians. This trend persisted for anxiety, with an adjusted PR of 0.17 (95% CI: 0.01–0.29; p = 0.012). However, the vegetarians (adjusted PR = −0.38, 95% CI: −0.61–−0.14; p < 0.001) reported lower EmE scores compared to the non-vegetarians. Likewise, the vegetarians had a lower mean BMI than the non-vegetarians (B = −0.16, 95% CI: −0.21–−0.08; p < 0.001). Conclusions: Vegetarian diets are associated with increased symptoms of depression and anxiety, as well as lower EmE and BMI scores. Further longitudinal studies are needed to elucidate these associations and determine causality and the underlying mechanisms involved.