Joanna F Dipnall1, Julie A Pasco2, Denny Meyer3, Michael Berk4, Lana J Williams5, Seetal Dodd6, Felice N Jacka7. 1. IMPACT Strategic Research Centre, School of Medicine, Deakin University, Geelong, VIC, Australia; Department of Statistics, Data Science and Epidemiology, Swinburne University of Technology, Hawthorn, VIC, Australia. Electronic address: jdipnall@deakin.edu.au. 2. IMPACT Strategic Research Centre, School of Medicine, Deakin University, Geelong, VIC, Australia; NorthWest Academic Centre, Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia. Electronic address: juliep@barwonhealth.org.au. 3. Department of Statistics, Data Science and Epidemiology, Swinburne University of Technology, Hawthorn, VIC, Australia. Electronic address: dmeyer@swin.edu.au. 4. IMPACT Strategic Research Centre, School of Medicine, Deakin University, Geelong, VIC, Australia; Department of Psychiatry, The University of Melbourne, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia; Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia. Electronic address: mikebe@barwonhealth.org.au. 5. IMPACT Strategic Research Centre, School of Medicine, Deakin University, Geelong, VIC, Australia. Electronic address: lanaw@barwonhealth.org.au. 6. IMPACT Strategic Research Centre, School of Medicine, Deakin University, Geelong, VIC, Australia; Department of Psychiatry, The University of Melbourne, Melbourne, Australia; Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia. Electronic address: seetald@barwonhealth.org.au. 7. IMPACT Strategic Research Centre, School of Medicine, Deakin University, Geelong, VIC, Australia; Department of Psychiatry, The University of Melbourne, Melbourne, Australia; Centre for Adolescent Health, Murdoch Children׳s Research Institute, Melbourne, VIC, Australia; Black Dog Institute, Sydney, NSW, Australia. Electronic address: f.jacka@deakin.edu.au.
Abstract
BACKGROUND: Type 2 diabetes and depression are commonly comorbid high-prevalence chronic disorders. Diet is a key diabetes risk factor and recent research has highlighted the relevance of diet as a possible risk for factor common mental disorders. This study aimed to investigate the interrelationship among dietary patterns, diabetes and depression. METHODS: Data were integrated from the National Health and Nutrition Examination Study (2009-2010) for adults aged 18+ (n=4588, Mean age=43yr). Depressive symptoms were measured by the Patient Health Questionnaire-9 and diabetes status determined via self-report, usage of diabetic medication and/or fasting glucose levels ≥126mg/dL and a glycated hemoglobin level ≥6.5% (48mmol/mol). A 24-h dietary recall interview was given to determine intakes. Multiple logistic regression was employed, with depression the outcome, and dietary patterns and diabetes the predictors. Covariates included gender, age, marital status, education, race, adult food insecurity level, ratio of family income to poverty, and serum C-reactive protein. RESULTS: Exploratory factor analysis revealed five dietary patterns (healthy; unhealthy; sweets; 'Mexican' style; breakfast) explaining 39.8% of the total variance. The healthy dietary pattern was associated with reduced odds of depression for those with diabetes (OR 0.68, 95% CI [0.52, 0.88], p=0.006) and those without diabetes (OR 0.79, 95% CI [0.64, 0.97], p=0.029) (interaction p=0.048). The relationship between the sweets dietary pattern and depression was fully explained by diabetes status. CONCLUSION: In this study, a healthy dietary pattern was associated with a reduced likelihood of depressive symptoms, especially for those with Type 2 diabetes.
BACKGROUND: Type 2 diabetes and depression are commonly comorbid high-prevalence chronic disorders. Diet is a key diabetes risk factor and recent research has highlighted the relevance of diet as a possible risk for factor common mental disorders. This study aimed to investigate the interrelationship among dietary patterns, diabetes and depression. METHODS: Data were integrated from the National Health and Nutrition Examination Study (2009-2010) for adults aged 18+ (n=4588, Mean age=43yr). Depressive symptoms were measured by the Patient Health Questionnaire-9 and diabetes status determined via self-report, usage of diabetic medication and/or fasting glucose levels ≥126mg/dL and a glycated hemoglobin level ≥6.5% (48mmol/mol). A 24-h dietary recall interview was given to determine intakes. Multiple logistic regression was employed, with depression the outcome, and dietary patterns and diabetes the predictors. Covariates included gender, age, marital status, education, race, adult food insecurity level, ratio of family income to poverty, and serum C-reactive protein. RESULTS: Exploratory factor analysis revealed five dietary patterns (healthy; unhealthy; sweets; 'Mexican' style; breakfast) explaining 39.8% of the total variance. The healthy dietary pattern was associated with reduced odds of depression for those with diabetes (OR 0.68, 95% CI [0.52, 0.88], p=0.006) and those without diabetes (OR 0.79, 95% CI [0.64, 0.97], p=0.029) (interaction p=0.048). The relationship between the sweets dietary pattern and depression was fully explained by diabetes status. CONCLUSION: In this study, a healthy dietary pattern was associated with a reduced likelihood of depressive symptoms, especially for those with Type 2 diabetes.
Authors: G Pagliai; F Sofi; F Vannetti; S Caiani; G Pasquini; R Molino Lova; F Cecchi; S Sorbi; C Macchi Journal: J Nutr Health Aging Date: 2018 Impact factor: 4.075
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