Fruit and Vegetable Intake and Mental Health in Adults: A Systematic Review
Notice bibliographique
Résumé
The role of a properly balanced diet in the prevention and treatment of mental disorders has been suggested, while vegetables and fruits have a high content of nutrients that may be of importance in the case of depressive disorders. The aim of the study was to conduct a systematic review of the observational studies analyzing association between fruit and vegetable intake and mental health in adults. The search adhered to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and the review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD42019138148). A search for peer-reviewed observational studies published until June 2019 was performed in PubMed and Web of Science databases, followed by an additional manual search for publications conducted via analyzing the references of the found studies. With respect to the intake of fruit and/or vegetable, studies that assessed the intake of fruits and/or vegetables, or their processed products (e.g., juices), as a measure expressed in grams or as the number of portions were included. Those studies that assessed the general dietary patterns were not included in the present analysis. With respect to mental health, studies that assessed all the aspects of mental health in both healthy participants and subjects with physical health problems were included, but those conducted in groups of patients with intellectual disabilities, dementia, and eating disorders were excluded. To assess bias, the Newcastle-Ottawa Scale (NOS) was applied. A total of 5911 studies were independently extracted by 2 researchers and verified if they met the inclusion criteria using a 2-stage procedure (based on the title, based on the abstract). After reviewing the full text, a total of 61 studies were selected. A narrative synthesis of the findings from the included studies was performed, which was structured around the type of outcome. The studies included mainly focused on depression and depressive symptoms, but also other characteristics ranging from general and mental well-being, quality of life, sleep quality, life satisfaction, flourishing, mood, self-efficacy, curiosity, creativity, optimism, self-esteem, stress, nervousness, or happiness, to anxiety, minor psychiatric disorders, distress, or attempted suicide, were analyzed. The most prominent results indicated that high total intake of fruits and vegetables, and some of their specific subgroups including berries, citrus, and green leafy vegetables, may promote higher levels of optimism and self-efficacy, as well as reduce the level of psychological distress, ambiguity, and cancer fatalism, and protect against depressive symptoms. However, it must be indicated that the studies included were conducted using various methodologies and in different populations, so their results were not always sufficiently comparable, which is a limitation. Taken together, it can be concluded that fruits and/or vegetables, and some of their specific subgroups, as well as processed fruits and vegetables, seems to have a positive influence on mental health, as stated in the vast majority of the included studies. Therefore, the general recommendation to consume at least 5 portions of fruit and vegetables a day may be beneficial also for mental health.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,008 |
| Bibliométrie | 0,010 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».