Background: There is presently no simple tool for use in large epidemiological studies to understand the food and nutrient intakes of Asian toddlers. This study aimed to assess the relative validity of a semi-quantitative food frequency questionnaire (sqFFQ) developed for multi-ethnic Singaporean toddlers aged 15-36 months. Methods: Ninety-one parents completed the sqFFQ and a 2-day weighed food record as the reference method. Intake of energy and 25 nutrients were determined for each method and compared using Pearson correlations corrected for attenuation, Bland-Altman plots, and weighted kappa according to quartiles; sqFFQ calibration was performed using multivariable linear regression. Results: Deattenuated correlations for energy and all nutrients were acceptable (r = ≥0.30, p < 0.001). The sqFFQ was highly reproducible, but significantly overestimated intake of energy and all nutrients except vitamin A. Bland-Altman plots showed wide limits of agreement for energy and all nutrients. Weighted kappa ranged from 0.12 (slight) to 0.53 (moderate). After calibration, deattenuated correlations improved for energy and 10/25 nutrients, with no change or a slight decline for the remainder, including one falling to r = 0.27. Limits of agreement narrowed for energy and all nutrients, and except for DHA, median intakes were not significantly different except for vitamin A, enabling population estimates of absolute intakes. Weighted kappa improved overall; energy and 16 nutrients now had moderate agreement (0.41-0.60), while 9 nutrients had fair agreement (0.21-0.40). Conclusions: The Singaporean toddler semi-quantitative food frequency questionnaire is suitable for ranking nutrient intakes of Singaporean toddlers in larger epidemiological studies. However, for population estimates of absolute nutrient intakes, it is recommended that a subsample within a cohort complete weighed food records for calibration purposes. Trial registration: This study was registered retrospectively on clinicaltrials.gov on 3rd May 2017 (identifier code: NCT03138330).
Background Salivary alpha-amylase (sAA) and salivary immunoglobulin A (sIgA) have been proposed as biomarkers for research on the mucosal immune system and on stress. Expression of both sAA and sIgA has been described to follow opposing diurnal patterns. This knowledge is crucial for the interpretation of studies using these biomarkers. Aim It was hypothesized that sAA and sIgA display diurnal patterns in children and that this is independent of food intake or demographic factors. Methods Whole saliva was collected from 78 healthy children (15-39 months old) in the morning and evening for two random nonconsecutive days. The samples have been analysed for sAA and sIgA. The total daily energy, fat, saturated fat, protein, carbohydrate and fibre, mineral, and vitamin consumption were analysed based on the two-day weighed food records collected by the parents. Results It was demonstrated that most young children followed the diurnal pattern when sAA increased and sIgA decreased from morning to evening. No correlation was observed between the intake of any of the nutrients and morning or evening values for both salivary proteins. The morning and evening values of sAA and sIgA did not correlate with age, sex, Asian ethnicity, and BMI of the children. Conclusion Diurnal patterns of sAA and sIgA exist in healthy young children and are not affected by their nutrient intake, sex, Asian ethnicity, and BMI. Scientists including sIgA and sAA in their research must consider the diurnal pattern that these markers exhibit and design the study accordingly.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.