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BACKGROUND: Quantitative evidence of direct links between dietary intake during pregnancy and maternal and infant outcomes in the preterm population is lacking in the literature. However, studies are starting to investigate relationships between them, and data shows that many of the adverse effects of poor maternal diet are linked to inflammatory response and dysbiosis of the microbiome in both the mother and her offspring. OBJECTIVE: Our objective with this study was to analyze the relationships between sociodemographic factors, maternal diet, pH of breast milk, and infant inflammation. We aimed to assess the dietary pattern of our population of mothers who delivered preterm in comparison to other populations, as well as explore the possibility of using pH of mother’s own milk in future research. METHODS: We reviewed the Electronic Medical Records (EMRs) of participants to gather clinical and demographic characteristics (infants n = 53; mothers n = 45). Maternal participants also completed the Dietary Screener Questionnaire (DSQ). Spearman’s rank correlation and raw unadjusted linear regression analyses were used to investigate relationships between maternal diet and characteristics, mother’s own milk pH, and infant urinary intestinal fatty acid binding protein (I-FABP). Kruskal Wallis analysis was used to analyze between group differences of maternal comorbidities. RESULTS: None of our maternal participants met the guidelines for dietary recommendations by the United States Department of Agriculture (USDA) for pregnant women. This follows the trend in national data for women who are pregnant. The greatest number of women met the recommendation for fiber intake (n = 12). Maternal intake of fiber and whole grains was negatively correlated with pH of mother’s own milk (p <0.5). We did not find any significant correlations between maternal characteristics and maternal diet or pH of mother’s own milk. However, meeting the guidelines for added sugars differed by race (p = 0.03). We found no statistically significant correlations between urinary I-FABP and pH of mother’s own milk or maternal dietary intake. Urinary I-FABP values differed by infant sex (p = 0.03) and infant feeding status (> 50% formula or donor milk vs. < 50% formula or donor milk, p = 0.03). Analysis by groups showed statistically significant differences (p = 0.04). Preeclamptic participants had a higher intake of whole grains (0.97 oz) than women without preeclampsia (0.69 oz). Mothers with gestational diabetes had a lower intake of sugar (14.4 tsp) compared to women without diabetes (17.9 tsp) (p = 0.01). We found no other statistically significant results between groups for maternal diet, milk pH, or urinary I-FABP. CONCLUSION: Our findings suggest that additional research on mother’s own milk pH may be warranted, and that continued education on the importance of a healthy diet and its benefits during pregnancy is needed. Areas of planned future research include fat intake calculations and inflammatory measures of the maternal dietary data.

Plusieurs études à ce jour démontrent que la consommation d’aliments ultra-transformés (AUT) serait associée à une alimentation de faible qualité et à une augmentation du risque de maladies chroniques non-transmissibles (MCNT) et d’obésité. Actuellement, pour les adultes canadiens, il n’existe encore aucun questionnaire permettant de discriminer rapidement entre différents profils de consommateurs d’AUT. Ce mémoire présente donc un projet pilote de développement et de validation initiale d’un Outil pour mesurer la consommation de Produits Ultra-Transformés (le OUTPUT). Pour ce faire, les catégories d’AUT contribuant à 0,5% et plus de l’apport énergétique total des adultes canadiens ont été identifiées d’après les données de consommation nationale (ESCC) de 2015. Ces catégories ont été représentées par des photos d’AUT vendus en épicerie et en restauration rapide. Celles-ci constituaient les deux questionnaires alimentaires simplifiés développés (rappel de 24 heures et questionnaire de fréquence). La validité apparente et de contenu du OUTPUT a été évaluée par un comité d’experts, avec la méthode Delphi. Deux tours d’enquête ont été nécessaires pour observer un consensus (fixé à 80% et plus) quant aux dimensions évaluées. La validité apparente de l’outil a ensuite été évaluée par 11 membres de la communauté de l’UdeM. Les données recueillies à travers cette étude pilote ont permis d’émettre des recommandations pour l’étude future de développement et de validation de l’outil. Une fois validé, celui-ci permettra aux nutritionnistes, aux chercheurs en épidémiologie et aux décideurs politiques une meilleure identification, gestion et prévention des MCNT et d’obésité, en lien avec la consommation d’AUT. / Several studies to date have shown that ultra-processed food consumption (UPF) is associated with low diet quality and increased risk of non-communicable diseases (NCDs) and obesity. Currently, there is no rapid screener to estimate UPF consumption based on Canadian dietary patterns. This research presents a pilot study that addresses the early stages of the development and validation of a screener to this purpose (the OUTPUT). Ultra-processed food categories contributing to 0.5% or more of the total energy intake for Canadian adults (18 years and older) were identified based on 2015 national consumption data (CCHS). Thus, two simplified dietary screeners were developed (a 24-hour recall and a food frequency questionnaire). The face and content validity of the OUTPUT was evaluated by an expert advisory committee, through the Delphi method. Two rounds were required to observe an agreement (set at 80% or more) regarding the different metrics that were assessed. The face validity of the screener was then evaluated by 11 participants from the UdeM community. The data collected through this pilot study made it possible to provide recommendations for the future study in which the development and validation of the tool will take place. Once validated, this tool will enable nutritionists, epidemiology researchers, and policymakers to better identify, manage and prevent NCDs and obesity.