S683 Association of Ultra-Processed Food and Unprocessed or Minimally Processed Food Consumption With Bowel Function Among US Adults
Notice bibliographique
Résumé
Introduction: Ultra-processed food (UPF) consumption has increased over the past few decades, raising concerns about potential negative impact on the gut microbiome. The pro-inflammatory microenvironment induced by UPFs may lead to disordered bowel function but may be mitigated by increasing consumption of unprocessed or minimally processed foods (UMPs). In this study, we aimed to assess the association between UPF and UMP consumption and bowel function among US adults and the outcomes for substituting UPFs with UMPs. Methods: We performed a cross-sectional study using data from the National Health and Nutrition Examination Survey (2005-2010). Dietary intake was evaluated by 2 24-hour dietary recalls. UPF and UMP intake (% of total gram/d) was derived based on the NOVA Classification. Constipation and diarrhea were defined according to Bristol Stool Form Scale. We used logistic regression to estimate the odds ratio (OR) and 95% confidence interval (CI) for constipation and diarrhea according to quartiles of UPF and UMP intake. Appropriate sample weights, stratification, and clustering were applied to account for the complex survey design. We performed substitution analysis to estimate the risk of constipation and diarrhea when replacing UPFs with an equivalent proportion of UMPs (Table 1). Results: Among 12,758 participants, there were 986 cases of constipation and 988 cases of diarrhea. The median UPF intake was 27% among total food intake in gram/d, while the median UMP intake was 66%. Participants who had greater UPF intake had higher risks of constipation (ORQ4 vs Q1, 1.87; 95% CI, 1.47-2.38) (Ptrend < 0.001) but not diarrhea (ORQ4 vs Q1, 0.95; 95% CI, 0.71-1.26) (Ptrend =0.99). Greater UMP intake was associated with a lower risk of constipation (ORQ4 vs Q1, 0.54; 95% CI, 0.43-0.69) (Ptrend < 0.001) but not diarrhea (ORQ4 vs Q1, 1.12; 95% CI, 0.85-1.48) (Ptrend =0.72). In addition, replacing 50% of UPF weight in diet with an equivalent proportion of UMPs was associated with a lower risk of constipation (OR, 0.68; 95% CI, 0.57-0.81). Conclusion: Dietary UPF intake was associated with a higher risk of constipation but not diarrhea, while UMP consumption had an inverse association with constipation. Substituting UPFs with UMPs may reduce the risk of constipation. These findings could be explained by differences in dietary constituents such as low fiber content in UPFs. Altered gut microbiota may also play a role through modulating the metabolic activities in colon. Table 1. - Odds ratio and 95% CI for constipation and diarrhea according to quartiles of UPF and UMP consumption among US adults. NHANES 2005-2010 UPF consumption (% gram/d) Quartile 1 Quartile 2 Quartile 3 Quartile 4 P trend Per 10% increase Median % gram/d (IQR) 10.3 (7.2-13.1) 20.8 (18.3-23.6) 33.1 (29.7-37.0) 54.6 (47.0-65.0) Constipation Cases/controls 222/2968 226/2963 250/2940 288/2901 Multivariable-adjusted modela 1 (reference) 1.18 (0.86-1.62) 1.59 (1.25-2.02) 1.87 (1.47-2.38) < 0.001 1.13 (1.09-1.17) Diarrhea Cases/controls 258/2932 244/2945 250/2940 236/2953 Multivariable-adjusted modela 1 (reference) 0.98 (0.75-1.28) 0.95 (0.73-1.22) 0.95 (0.71-1.26) 0.99 1.00 (0.95-1.05) UMP consumption (% gram/d) Quartile 1 Quartile 2 Quartile 3 Quartile 4 P trend Per 10% increase Median % gram/d (IQR) 37.0 (27.6-44.6) 59.2 (55.2-62.9) 72.6 (69.5-75.7) 84.8 (81.6-88.9) Constipation Cases/controls 259/2931 248/2941 238/2951 241/2949 Multivariable-adjusted modela 1 (reference) 0.87 (0.65-1.18) 0.70 (0.52-0.94) 0.54 (0.43-0.69) < 0.001 0.90 (0.86-0.93) Diarrhea Cases/controls 240/2950 242/2947 240/2949 266/2924 Multivariable-adjusted modela 1 (reference) 0.99 (0.73-1.35) 1.04 (0.80-1.36) 1.12 (0.85-1.48) 0.72 1.01 (0.96-1.06) Abbreviations: BMI, body mass index; CI, confidence interval; IQR, interquartile range; UMP, unprocessed or minimally processed food; UPF, ultra-processed food. aAdjusted for age group, sex, race/ethnicity, educational attainment, income, smoking status, BMI, weight circumference, physical activity, alcohol drinking, and total energy intake.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».