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Record W7011142042

Longitudinal analysis of dietary patterns of Quebec youth

2018· dissertation· en· W7011142042 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typedissertation
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsnot available
Fundersnot available
KeywordsObesityContext (archaeology)CohortLongitudinal studyDescriptive statisticsChildhood obesityNational Longitudinal SurveysCohort studyOverweight
DOInot available

Abstract

fetched live from OpenAlex

In Canada, the problem of obesity in children and adolescents is particularly alarming, as it is advancing at a more rapid pace than among adults. The role played by the immediate environment in shaping the dietary behavior of youth is increasingly important, particularly in the context of obesity prevention. Due to the ease with which cross-sectional studies can be undertaken, there are numerous such studies showing the relationship between children and their dietary intake, especially how they are not meeting their nutrition recommendations. Little research has examined the changes in dietary intake in children as they age. This study examines the changes in eating patterns of children between the ages 8-10 years and 15-17 years and to describe potential determinants of dietary changes as children grow older including, initial BMI and sex of the child, maternal obesity, paternal obesity and supper with family as potential factors associated with this change. The study used a secondary data set which was collected using a longitudinal cohort design- the Quebec Adiposity and Lifestyle Investigation in Youth (QUALITY) cohort. An essential eligibility criterion included Caucasian children with at least one obese biological parent. Participants 8-10 through 15-17 years of age had their dietary assessments by means of three 24-hour recalls at two time-points approximately 7 years apart. Data were entered and verified using the CANDAT10 software which uses the Canadian Nutrient File (CNF), version 2010 as a database. Key nutrients and food groupings were examined using IBM SPSS Statistic 22.0 © 2012 Software. Descriptive analyses were performed to understand sample characteristics. Paired t-tests were used to the compare the changes in servings of fruits, vegetables, grains, meat and alternatives, and dairy and alternatives consumed at two time-points. Participants were stratified by gender and by their obesity status to learn more about the evolution of diet as the child grows older. The participants (n = 365), were on average 9.5±0.9y, 54.5% were male, the mean BMI z-score of the cohort was 0.61±1.0 at baseline. Dietary intakes were normalized to 1000 kcal consumed. Overall the number of fruit and dairy servings decreased from 1.5±0.9 to 1.3±1.0 (p=0.004) and 1.1±0.5 to 1.0±0.5 (p<0.001) respectively per day over time. In contrast servings of grains and meats and alternatives increased. These changes in food choices led to increases in protein (p<0.01), and a decrease in calcium (p<0.01), owing to the decreased dairy consumption. The girls showed no decline in fruit intake while the boys declined substantially showing a significant difference (p<0.01) between the sexes. The mean change score for the five food groups examined was not influenced by baseline bodyweight of children. No significant differences were observed in the mean change score of servings for food groups examined, between the healthy weight group and the overweight/obese group. However, on comparing the mean change score, the healthy weight group reported greater increases in energy intake than the overweight/obese group (p<0.01). The children of mothers who were obese reduced their fruit intake over time (p<0.01). But on comparing mean change scores, maternal obesity status had no significant associations on the change in food group consumption or energy intake of the individuals in the study. The children having a non-obese father reported greater increases in their energy intake over time as compared to those children with an obese father (p<0.01). The findings from this study suggest that initiatives to increase fruit, vegetable and dairy intake with increasing age should be included in programs and interventions aimed to improve diet quality of individuals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.266
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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