Dietary inflammatory index, cardiometabolic conditions and depression in the Seguimiento Universidad de Navarra cohort study.
Only one prospective study has analysed the relationship between the inflammatory properties of diet and risk of depression thus far. The aim of this study was to assess the association between the dietary inflammatory index (DII) and the incidence of depression. In a cohort study of 15 093 university graduates, participants completed a validated FFQ at baseline and after 10 years of follow-up. The DII was calculated based on the FFQ. Each of the twenty-eight nutrients or foods received a score based on findings from the peer-reviewed literature reporting on the relationships between diet and inflammatory biomarkers (IL-1β, IL-4, IL-6, IL-10, TNF-α and C-reactive protein). Participants were classified as having depression if they reported a new clinical diagnosis of depression by a physician, antidepressant drugs, or both. Multivariable Cox regression models were used to estimate hazard ratios (HR) of depression according to quintiles of the DII. After a median 8·5 years of follow-up, we observed 1051 incident cases of depression. The HR for participants in the highest quintile of DII (strongly pro-inflammatory) was 1·47 (95% CI 1·17, 1·85) compared with those in the bottom quintile, with a significant dose-response relationship (P trend=0·01). In the subgroup analyses, the association between DII and depression was stronger among participants >55 years and among those with cardiometabolic comorbidities (HR 2·70; 95% CI 1·22, 5·97 and HR 1·80; 95% CI 1·27, 2·57, respectively). A pro-inflammatory diet was associated with a significantly higher risk of depression in a Mediterranean population. This association was stronger among older subjects and subjects with cardiometabolic diseases.
1Nutrition Research Group,Research Institute of Biomedical and Health Sciences,University of Las Palmas de Gran Canaria,CP 35016 Las Palmas de Gran Canaria,Spain.
Almudena
A
Sánchez-Villegas
2Ciber de Fisiopatología de la Obesidad y Nutrición (CIBER OBN),Instituto de Salud Carlos III,CP 28029 Madrid,Spain.
Miguel
M
Ruíz-Canela
2Ciber de Fisiopatología de la Obesidad y Nutrición (CIBER OBN),Instituto de Salud Carlos III,CP 28029 Madrid,Spain.
Carmen
C
de la Fuente-Arrillaga
2Ciber de Fisiopatología de la Obesidad y Nutrición (CIBER OBN),Instituto de Salud Carlos III,CP 28029 Madrid,Spain.
Alfredo
A
Gea
4Cancer Prevention and Control Program,University of South Carolina,Columbia,SC 29208,USA.
Nitin
N
Shivappa
4Cancer Prevention and Control Program,University of South Carolina,Columbia,SC 29208,USA.
James R
JR
Hébert
2Ciber de Fisiopatología de la Obesidad y Nutrición (CIBER OBN),Instituto de Salud Carlos III,CP 28029 Madrid,Spain.
Miguel A
MA
Martínez-González
D000328:Adult; D015415:Biomarkers / Q000097:blood; D015992:Body Mass Index; D002097:C-Reactive Protein / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000097:blood / Q000150:complications; D015331:Cohort Studies; D003863:Depression / Q000097:blood* / Q000150:complications / Q000453:epidemiology*; D004032:Diet; D002149:Energy Intake; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D015994:Incidence; D007249:Inflammation / Q000097:blood*; D016753:Interleukin-10 / Q000097:blood; D053583:Interleukin-1beta / Q000097:blood; D015847:Interleukin-4 / Q000097:blood; D015850:Interleukin-6 / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000150:complications; D008875:Middle Aged; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012959:Socioeconomic Factors; D013030:Spain / Q000453:epidemiology; D011795:Surveys and Questionnaires; D014409:Tumor Necrosis Factor-alpha / Q000097:blood
D015415:Biomarkers; D053583:Interleukin-1beta; D015850:Interleukin-6; D014409:Tumor Necrosis Factor-alpha; D016753:Interleukin-10; D015847:Interleukin-4; D002097:C-Reactive Protein
Anti-inflammation; Cohort studies; DII dietary inflammatory index; DM2 type 2 diabetes; Depression; Diabetes; Dietary patterns; HR hazard ratio; HTA hypertension; MetS metabolic syndrome