Evaluation of under- and overreporting of energy intake in the 24-hour diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC)
Notice bibliographique
Résumé
OBJECTIVE: To evaluate under- and overreporting and their determinants in the EPIC 24-hour diet recall (24-HDR) measurements collected in the European Prospective Investigation into Cancer and Nutrition (EPIC). DESIGN: Cross-sectional analysis. 24-HDR measurements were obtained by means of a standardised computerised interview program (EPIC-SOFT). The ratio of reported energy intake (EI) to estimated basal metabolic rate (BMR) was used to ascertain the magnitude, impact and determinants of misreporting. Goldberg's cut-off points were used to identify participants with physiologically extreme low or high energy intake. At the aggregate level the value of 1.55 for physical activity level (PAL) was chosen as reference. At the individual level we used multivariate statistical techniques to identify factors that could explain EI/BMR variability. Analyses were performed by adjusting for weight, height, age at recall, special diet, smoking status, day of recall (weekday vs. weekend day) and physical activity. SETTING: Twenty-seven redefined centres in the 10 countries participating in the EPIC project. SUBJECTS: In total, 35 955 men and women, aged 35-74 years, participating in the nested EPIC calibration sub-studies. RESULTS: While overreporting has only a minor impact, the percentage of subjects identified as extreme underreporters was 13.8% and 10.3% in women and men, respectively. Mean EI/BMR values in men and women were 1.44 and 1.36 including all subjects, and 1.50 and 1.44 after exclusion of misreporters. After exclusion of misreporters, adjusted EI/BMR means were consistently less than 10% different from the expected value of 1.55 for PAL (except for women in Greece and in the UK), with overall differences equal to 4.0% and 7.4% for men and women, respectively. We modelled the probability of being an underreporter in association with several individual characteristics. After adjustment for age, height, special diet, smoking status, day of recall and physical activity at work, logistic regression analyses resulted in an odds ratio (OR) of being an underreporter for the highest vs. the lowest quartile of body mass index (BMI) of 3.52 (95% confidence interval (CI) 2.91-4.26) in men and 4.80 (95% CI 4.11-5.61) in women, indicating that overweight subjects are significantly more likely to underestimate energy intake than subjects in the bottom BMI category. Older people were less likely to underestimate energy intake: ORs were 0.58 (95% CI 0.45-0.77) and 0.74 (95% CI 0.63-0.88) for age (> or =65 years vs. <50 years). Special diet and day of the week showed strong effects. CONCLUSION: EI tends to be underestimated in the vast majority of the EPIC centres, although to varying degrees; at the aggregate level most centres were below the expected reference value of 1.55. Underreporting seems to be more prevalent among women than men in the EPIC calibration sample. The hypothesis that BMI (or weight) and age are causally related to underreporting seems to be confirmed in the present work. This introduces further complexity in the within-group (centre or country) and between-group calibration of dietary questionnaire measurements to deattenuate the diet-disease relationship.
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 | 0,018 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».