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Enregistrement W2336317376 · doi:10.1097/ede.0000000000000490

Goat’s Milk, Plant-based Milk, Cow’s Milk, and Serum 25-hydroxyvitamin D Levels in Early Childhood

2016· letter· en· W2336317376 sur OpenAlexafffundabout
Grace J. Lee, Catherine S. Birken, Patricia C. Parkin, Gerald Lebovic, Yang Chen, Mary R. L’Abbé, Jonathon L. Maguire

Notice bibliographique

RevueEpidemiology · 2016
Typeletter
Langueen
DomaineEnvironmental Science
ThématiqueAgriculture Sustainability and Environmental Impact
Établissements canadiensSickKids FoundationUniversity of TorontoHospital for Sick ChildrenCanadian Institutes of Health ResearchSt. Michael's Hospital
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésBreast milkMedicineVitamin D and neurologyFortificationFood scienceCow milkSkimmed milkAnthropometryAnimal scienceEnvironmental healthBiologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

To the Editor Commercial availability and parental interest in alternative milk beverages for children have been increasing. We previously identified a relationship between higher consumption of alternative milk beverages and lower vitamin D levels in early childhood.1 Based on existing research, it is unclear whether this is true for both animal-based (goat’s milk) and plant-based (soy, almond, rice, etc.) milk beverages. Vitamin D fortification of alternative milk beverages is voluntary in both the United States and Canada.2–4 Our objective was to determine whether the relationship between alternative milk beverage consumption and children’s 25-hydroxyvitamin D is different for goat’s milk, plant-based milk beverages, and cow’s milk. In this cross-sectional study, children 1–6 years old seen for routine primary healthcare were recruited between 2008 and 2013 in Toronto, Canada (latitude 43.4°N).5 A parent-completed questionnaire based on the Canadian Community Health Survey, anthropometric and laboratory measurements were collected by trained research assistants and phlebotomists using standardized methods during the primary healthcare visit.1,5,6 We measured serum 25-hydroxyvitamin D concentration using the DiaSorin LIAISION 25-hydroxyvitmain D TOTAL chemiluminescence assay, with an interassay imprecision of 4.9 nmol/L using DEQAS (www.mountsinaiservices.com). Consumption of cow’s milk, goat’s milk, and plant-based milk beverages were measured as cups per day.1 We used multiple linear regression to test the association between each milk type consumed (goat, plant, and cow) and children’s 25-hydroxyvitamin D level, adjusted for clinically relevant covariates identified a priori (age, sex, body mass index z score, vitamin D supplementation, margarine consumption [vitamin D fortified in Canada], skin pigmentation, outdoor play time, and seasonality). 25-hydroxyvitamin D was positively skewed and was log-transformed. Residual analysis indicated a good fit. We conducted multiple imputation for missing data (no variable had >12% missing data). The R Project was used for statistical analyses. This study was approved by the Hospital for Sick Children and St. Michael’s Hospital Research Ethics Boards. Parents of children consented to study participation. Of the 4,523 recruited children, 2,711 children had laboratory testing and were included in the study. The mean age was 2.9 years (SD 1.5) and 53% were male. Vitamin D supplementation was reported in 53% of children, and median 25-hydroxyvitamin D level was 80 nmol/L (interquartile range 66–99). Each cup of plant-based milk was associated with a 3.2 nmol/L (95% CI, 0.7, 5.6) lower median 25-hydroxyvitamin D level and each cup of cow’s milk was associated with a 3.0 nmol/L (95% CI, 2.1, 3.9) higher median 25-hydroxyvitamin D level. Goat’s milk consumption was not associated with children’s serum 25-hydroxyvitamin D level although the trend was similar to cow’s milk. Comparing the relationship between volume of each milk type consumed and 25-hydroxyvitamin D level revealed similar associations for goat’s milk and cow’s milk whereas plant-based milk beverage consumption was associated with lower 25-hydroxyvitamin D than both cow’s milk and goat’s milk (Figure).FIGURE: Adjusted association between milk consumption and children’s serum 25-hydroxyvitamin D levels, by milk type.In summary, we identified a dose-dependent association between plant-based milk beverage consumption and lower 25-hydroxyvitamin D level in early childhood. This association was in the opposite direction to the relationship between consumption of animal-based milks and 25-hydroxyvitamin D. One explanation for the lower 25-hydroxyvitamin D levels among children who consume plant-based milk beverages may be a difference in the biological potency of vitamin D2, found in plant-based milk, relative to vitamin D3, found in animal-based milk. There has been considerable debate about whether vitamin D2 is as effective as vitamin D3 in raising serum 25-hydroxyvitamin D concentration.7,8 Another explanation may be differences in regulatory requirements for vitamin D fortification of animal- and plant-based milk. Future investigations are needed to elucidate the differences between the effects of plant-based milk beverage consumption and animal-based milk consumption on children’s 25-hydroxyvitamin D levels. ACKNOWLEDGMENTS We thank Azar Azad, PhD, Tonya D’Amour, Julie DeGroot, MSc, Sharmilaa Kandasamy, Kanthi Kavikondala, Tarandeep Malhi, Magda Melo, MSc, Subitha Rajakumaran, Juela Sejdo, and Laurie Thompson for administrative and technical support for TARGetKids!. The following clinical site investigators participated in the TARGetKids! Collaboration: Tony Barozzino, MD, Gary Bloch, MD, Ashna Bowry, MD, Douglas Campbell, MD, Sohail Cheema, MD, Brian Chisamore, MD, Karoon Danayan, MD, Anh Do, MD, Michael Evans, MD, Mark Feldman, MD, Sloane Freeman, MD, Moshe Ipp, MD, Sheila Jacobson, MD, Tara Kiran, MD, Holly Knowles, MD, Eddy Lau, MD, Fok-Han Leung, MD, Muhammad Mamdani, PharmD, MA, MPH, Julia Morinis, MD, MSc, Sharon Naymark, MD, Patricia Neelands, MD, Michael Peer, MD, Marty Perlmutar, MD, Michelle Porepa, MD, Noor Ramji, MD, Alana Rosenthal, MD, Janet Saunderson, MD, Michael Sgro, MD, Susan Shepherd, MD, Carolyn Taylor, MD, Sheila Wijayasinghe, MD, Ethel Ying, MD, and Elizabeth Young, MD. Grace J. Lee Department of Nutritional Sciences University of Toronto Toronto, ON, Canada Department of Pediatrics St. Michael’s Hospital Toronto, ON, Canada Li Ka Shing Knowledge Institute of St. Michael’s Hospital Toronto, ON, Canada Catherine S. Birken Patricia C. Parkin Division of Paediatric Medicine and the Paediatric Outcomes Research Team The Hospital for Sick Children Toronto, ON, Canada Department of Paediatrics University of Toronto Toronto, ON, Canada Child Health Evaluative Sciences The Hospital for Sick Children Research Institute Toronto, ON, Canada Gerald Lebovic Li Ka Shing Knowledge Institute of St. Michael’s Hospital Toronto, ON, Canada Institute of Health Policy Management and Evaluation University of Toronto Toronto, ON, Canada Yang Chen Li Ka Shing Knowledge Institute of St. Michael’s Hospital Toronto, ON, Canada Mary R. L’Abbe Jonathon L. Maguire Department of Nutritional Sciences University of Toronto Toronto, ON, Canada Jonathon L. Maguire Department of Pediatrics St. Michael’s Hospital Toronto, ON, Canada Li Ka Shing Knowledge Institute of St. Michael’s Hospital Toronto, ON, Canada Division of Paediatric Medicine and the Paediatric Outcomes Research Team The Hospital for Sick Children Toronto, ON, Canada Department of Paediatrics University of Toronto Toronto, ON, Canada Child Health Evaluative Sciences The Hospital for Sick Children Research Institute Toronto, ON, Canada Institute of Health Policy Management and Evaluation University of Toronto Toronto, ON, Canada [email protected] for the TARGet Kids! Collaboration

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,295
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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.

Tête enseignante Opus0,021
Tête enseignante GPT0,240
Écart entre enseignants0,219 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2016
Routes d'admission3
Résumé présentoui

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