Impact of maternal metabolic abnormalities in pregnancy on human milk and subsequent infant metabolic development: methodology and design
Bibliographic record
Abstract
BACKGROUND: Childhood obesity is on the rise and is a major risk factor for type 2 diabetes later in life. Recent evidence indicates that abnormalities that increase risk for diabetes may be initiated early in infancy. Since the offspring of women with diabetes have an increased long-term risk for obesity and type 2 diabetes, the impact of maternal metabolic abnormalities on early nutrition and infant metabolic trajectories is of considerable interest. Human breast milk, the preferred food during infancy, contains not only nutrients but also an array of bioactive substances including metabolic hormones. Nonetheless, only a few studies have reported concentrations of metabolic hormones in human milk specifically from women with metabolic abnormalities. We aim to investigate the impact of maternal metabolic abnormalities in pregnancy on human milk hormones and subsequently on infant development over the first year of life. The objective of this report is to present the methodology and design of this study. METHODS/DESIGN: The current investigation is a prospective study conducted within ongoing cohort studies of women and their offspring. Pregnant women attending outpatient obstetrics clinics in Toronto, Canada were recruited. Between April 2009 and July 2010, a total of 216 pregnant women underwent a baseline oral glucose tolerance test and provided medical and lifestyle history. Follow-up visits and telephone interviews are conducted and expected to be completed in October 2011. Upon delivery, infant birth anthropometry measurements and human breast milk samples are collected. At 3 and 12 months postpartum, mothers and infants are invited for follow-up assessments. Interim telephone interviews are conducted during the first year of offspring life to characterize infant feeding and supplementation behaviors. DISCUSSION: An improved understanding of the link between maternal metabolic abnormalities in pregnancy and early infant nutrition may assist in the development of optimal prevention and intervention strategies and in the protection of nutritionally vulnerable offspring who are at risk for obesity and diabetes later in life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".