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Prospective association between adherence to dietary recommendations and incident depressive symptoms in the French NutriNet-Santé cohort

  • Moufidath Adjibade (a1), Cédric Lemogne (a2) (a3) (a4), Chantal Julia (a1) (a5), Serge Hercberg (a1) (a5), Pilar Galan (a1), Karen E. Assmann (a1) and Emmanuelle Kesse-Guyot (a1)...
Abstract

A posteriori healthier dietary patterns and several nutrients have been associated with lower risks of depression in various studies; however, evidence is lacking with regard to the prospective association between adherence to nutritional recommendations (food-based and nutrient-based recommendations) and incident depression or depressive symptoms. In this study, we investigate such associations in the NutriNet Santé cohort. The study sample included 26 225 participants (aged 18–86 years) who were initially free of depressive symptoms. Adherence to nutritional recommendations was measured by four scores namely modified French Programme National Nutrition Santé-Guideline Score (mPNNS-GS), Alternative Healthy Eating Index-2010 (AHEI-2010), Probability of Adequate Nutrient Intake Dietary Score (PANDiet) and Diet Quality Index-International (DQI-I), using non-consecutive dietary record data during the first 2 years of follow-up (mean number of recording days=8, sd 2). Depressive symptoms were defined by a Center for Epidemiologic Studies Depression Scale (CES-D) score ≥17 for men and ≥23 for women. We used Cox proportional hazards models to estimate hazard ratios and 95 % CI, modelling the dietary scores as standardised continuous variables and as tertiles. Over a mean follow-up of 6 years, we identified 2166 incident cases of depressive symptoms. All dietary scores with the exception of the AHEI-2010 were significantly inversely associated with incident depressive symptoms. In the fully adjusted model, an increase of 1 sd in the mPNNS-GS, PANDiet and DQI-I was, respectively, associated with an 8 % (95 % CI 4, 13), 5 % (95 % CI 1, 9) and 9 % (95 % CI 5, 13) reduction in the risk of depressive symptoms. Overall, these findings suggest that diet in accordance with national or international guidelines could have beneficial effects with regard to mental health.

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Corresponding author
* Corresponding author: M. Adjibade, fax +33 1 48 38 89 31, email m.adjibade@eren.smbh.univ-paris13.fr
References
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1. World Health Organization (2013) Mental Health Action Plan 2013–2020. Geneva: WHO.
2. Doris, A, Ebmeier, K & Shajahan, P (1999) Depressive illness. Lancet 354, 13691375.
3. World Health Organization (2004) Global Strategy on Diet, Physical Activity and Health. Geneva: WHO.
4. Rahe, C, Unrath, M & Berger, K (2014) Dietary patterns and the risk of depression in adults: a systematic review of observational studies. Eur J Nutr 53, 9971013.
5. Lai, JS, Hiles, S, Bisquera, A, et al. (2014) A systematic review and meta-analysis of dietary patterns and depression in community-dwelling adults. Am J Clin Nutr 99, 181197.
6. Li, Y, Lv, MR, Wei, YJ, et al. (2017) Dietary patterns and depression risk: a meta-analysis. Psychiatry Res 253, 373382.
7. Hercberg, S, Chat-Yung, S & Chaulia, M (2008) The French National Nutrition and Health Program: 2001–2006–2010. Int J Public Health 53, 6877.
8. Martin, A (2001) Apports nutritionnels conseillés pour la population Française (Recommended Dietary Allowances for the French Population), 3rd ed. Paris: Tec & Doc, Lavoisier.
9. Estaquio, C, Kesse-Guyot, E, Deschamps, V, et al. (2009) Adherence to the French Programme National Nutrition Sante Guideline Score is associated with better nutrient intake and nutritional status. J Am Diet Assoc 109, 10311041.
10. Verger, EO, Mariotti, F, Holmes, BA, et al. (2012) Evaluation of a diet quality index based on the probability of adequate nutrient intake (PANDiet) using national French and US dietary surveys. PLOS ONE 7, e42155.
11. Arvaniti, F & Panagiotakos, DB (2008) Healthy indexes in public health practice and research: a review. Crit Rev Food Sci Nutr 48, 317327.
12. Psaltopoulou, T, Sergentanis, TN, Panagiotakos, DB, et al. (2013) Mediterranean diet, stroke, cognitive impairment, and depression: a meta-analysis. Ann Neurol 74, 580591.
13. Skarupski, KA, Tangney, CC, Li, H, et al. (2013) Mediterranean diet and depressive symptoms among older adults over time. J Nutr Health Aging 17, 441445.
14. Lai, JS, Oldmeadow, C, Hure, AJ, et al. (2016) Longitudinal diet quality is not associated with depressive symptoms in a cohort of middle-aged Australian women. Br J Nutr 115, 842850.
15. Sanchez-Villegas, A, Henriquez-Sanchez, P, Ruiz-Canela, M, et al. (2015) A longitudinal analysis of diet quality scores and the risk of incident depression in the SUN Project. BMC Med 13, 197.
16. Sanchez-Villegas, A, Martinez-Gonzalez, MA, Estruch, R, et al. (2013) Mediterranean dietary pattern and depression: the PREDIMED randomized trial. BMC Med 11, 208211.
17. Rienks, J, Dobson, AJ & Mishra, GD (2013) Mediterranean dietary pattern and prevalence and incidence of depressive symptoms in mid-aged women: results from a large community-based prospective study. Eur J Clin Nutr 67, 7582.
18. Adjibade, M, Assmann, KE, Andreeva, VA, et al. (2018) Prospective association between adherence to the Mediterranean diet and risk of depressive symptoms in the French SU.VI.MAX cohort. Eur J Nutr 57, 12251235.
19. Saneei, P, Hajishafiee, M, Keshteli, AH, et al. (2016) Adherence to Alternative Healthy Eating Index in relation to depression and anxiety in Iranian adults. Br J Nutr 116, 335342.
20. Loprinzi, PD & Mahoney, S (2014) Concurrent occurrence of multiple positive lifestyle behaviors and depression among adults in the United States. J Affect Disord 165, 126130.
21. Beydoun, MA, Fanelli Kuczmarski, MT, Beydoun, HA, et al. (2010) The sex-specific role of plasma folate in mediating the association of dietary quality with depressive symptoms. J Nutr 140, 338347.
22. Kuczmarski, MF, Cremer, SA, Hotchkiss, L, et al. (2010) Higher Healthy Eating Index-2005 scores associated with reduced symptoms of depression in an urban population: findings from the Healthy Aging in Neighborhoods of Diversity Across the Life Span (HANDLS) study. J Am Diet Assoc 110, 383389.
23. Meegan, AP, Perry, IJ & Phillips, CM (2017) The Association between Dietary Quality and Dietary Guideline Adherence with Mental Health Outcomes in Adults: A Cross-Sectional Analysis. Nutrients 9, E238.
24. Saneei, P, Esmaillzadeh, A, Keshteli, AH, et al. (2016) Combined healthy lifestyle is inversely associated with psychological disorders among adults. PLOS ONE 11, e0146888.
25. Collin, C, Assmann, KE, Andreeva, VA, et al. (2016) Adherence to dietary guidelines as a protective factor against chronic or recurrent depressive symptoms in the French SU.VI.MAX cohort. Prev Med 91, 335343.
26. Lai, JS, Hure, AJ, Oldmeadow, C, et al. (2017) Prospective study on the association between diet quality and depression in mid-aged women over 9 years. Eur J Nutr 56, 273281.
27. Akbaraly, TN, Sabia, S, Shipley, MJ, et al. (2013) Adherence to healthy dietary guidelines and future depressive symptoms: evidence for sex differentials in the Whitehall II study. Am J Clin Nutr 97, 419427.
28. Lai, J, Moxey, A, Nowak, G, et al. (2012) The efficacy of zinc supplementation in depression: systematic review of randomised controlled trials. J Affect Disord 136, e31e39.
29. Lim, SY, Kim, EJ, Kim, A, et al. (2016) Nutritional factors affecting mental health. Clin Nutr Res 5, 143152.
30. Hercberg, S, Castetbon, K, Czernichow, S, et al. (2010) The Nutrinet-Sante Study: a web-based prospective study on the relationship between nutrition and health and determinants of dietary patterns and nutritional status. BMC Public Health 10, 242.
31. Radloff, LS (1977) The CES-D Scale, a self-report depression scale for research in the general population. Appl Psychol Meas 1, 385401.
32. Führer, R & Rouillon, F (1989) The French version of the Center for Epidemiologic Studies-Depression Scale. Psychiatrie et Psychologie 4, 163166.
33. Cronbach, LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16, 297334.
34. Touvier, M, Kesse-Guyot, E, Mejean, C, et al. (2011) Comparison between an interactive web-based self-administered 24 h dietary record and an interview by a dietitian for large-scale epidemiological studies. Br J Nutr 105, 10551064.
35. Lassale, C, Castetbon, K, Laporte, F, et al. (2016) Correlations between fruit, vegetables, fish, vitamins, and fatty acids estimated by web-based nonconsecutive dietary records and respective biomarkers of nutritional status. J Acad Nutr Diet 116, 427438.
36. Lassale, C, Castetbon, K, Laporte, F, et al. (2015) Validation of a Web-based, self-administered, non-consecutive-day dietary record tool against urinary biomarkers. Br J Nutr 113, 953962.
37. Le Moullec, N, Deheeger, M., Preziosi, P, et al. (1996) Validation du manuel photos utilisé pour l’enquête alimentaire de l'étude SU.VI.MAX (Validation of the photo manual used for the dietary assessment of the SU.VI.MAX study). Cah Nutr Diet 31, 158164.
38. NutriNet-Santé, Etude (2013) Table de Composition des Aliments de l'étude NutriNet-Santé (NutriNet-Santé Study Food Composition Database). Paris: Economica.
39. Black, AE (2000) Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes Relat Metab Disord 24, 11191130.
40. Goldberg, GR, Black, AE, Jebb, SA, et al. (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 45, 569581.
41. Schofield, WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39, Suppl. 1, 541, 5–41.
42. Chiuve, SE, Fung, TT, Rimm, EB, et al. (2012) Alternative dietary indices both strongly predict risk of chronic disease. J Nutr 142, 10091018.
43. Kim, S, Haines, PS, Siega-Riz, AM, et al. (2003) The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. J Nutr 133, 34763484.
44. Vergnaud, AC, Touvier, M, Mejean, C, et al. (2011) Agreement between web-based and paper versions of a socio-demographic questionnaire in the NutriNet-Sante study. Int J Public Health 56, 407417.
45. Institut National de la Statistique et des Etudes Economiques (2016) Définition des Unités de Consommation (Consumption Units Definition). https://www.insee.fr/fr/metadonnees/definition/c1802 (accessed April 2017).
46. Lassale, C, Peneau, S, Touvier, M, et al. (2013) Validity of web-based self-reported weight and height: results of the Nutrinet-Sante study. J Med Internet Res 15, e152.
47. World Health Organization (1995) Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser 854, 1452.
48. Craig, CL, Marshall, AL, Sjostrom, M, et al. (2003) International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 35, 13811395.
49. Andridge, RR & Little, RJ (2009) The use of sample weights in hot deck imputation. J Off Stat 25, 2136.
50. Willett, W & Stampfer, MJ (1986) Total energy intake: implications for epidemiologic analyses. Am J Epidemiol 124, 1727.
51. Finkelstein, DM (1986) A proportional hazards model for interval-censored failure time data. Biometrics 42, 845854.
52. Morin, AJ, Moullec, G, Maiano, C, et al. (2011) Psychometric properties of the Center for Epidemiologic Studies Depression Scale (CES-D) in French clinical and nonclinical adults. Rev Epidemiol Sante Publique 59, 327340.
53. Mikkelsen, K, Stojanovska, L, Prakash, M, et al. (2017) The effects of vitamin B on the immune/cytokine network and their involvement in depression. Maturitas 96, 5871.
54. Grosso, G, Galvano, F, Marventano, S, et al. (2014) Omega-3 fatty acids and depression: scientific evidence and biological mechanisms. Oxid Med Cell Longev 2014, 313570.
55. Miki, T, Kochi, T, Eguchi, M, et al. (2015) Dietary intake of minerals in relation to depressive symptoms in Japanese employees: the Furukawa Nutrition and Health Study. Nutrition 31, 686690.
56. Berk, M, Williams, LJ, Jacka, FN, et al. (2013) So depression is an inflammatory disease, but where does the inflammation come from? BMC Med 11, 200211.
57. Lopresti, AL, Hood, SD & Drummond, PD (2013) A review of lifestyle factors that contribute to important pathways associated with major depression: diet, sleep and exercise. J Affect Disord 148, 1227.
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