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Record W7132950245

Variations in the Measurement of Early-infant Feeding Practices and Effects on Associations in Epidemiological Research

2025· dissertation· W7132950245 on OpenAlexfundno aff
Miranda Grace Loutet

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsnot available
FundersHospital for Sick ChildrenChild Health Research FoundationWorld Health Organization
KeywordsBreastfeedingEpidemiologyObservational studyRecall biasMetric (unit)Public healthCohort studyLongitudinal studyConfounding
DOInot available

Abstract

fetched live from OpenAlex

Rates of exclusive breastfeeding to 6 months of age remain low globally and little progress has been made over the past decade in some countries like Bangladesh. As such, research efforts should continue to focus on modifiable risk factors to promote breastfeeding. To date, such factors have been identified through studies that adopted varied methods for measuring breastfeeding practices. Therefore, in my doctoral thesis, I aimed to compare methods of measuring breastfeeding practices (referred to as metrics), highlighting the implications on population-level surveillance and epidemiological studies. Furthermore, I aimed to estimate the association between mode of delivery – a potentially modifiable factor of public health importance – and breastfeeding using accurate measurement approaches. I used data from the Synbiotics for the Early Prevention of Severe Infections in Infants (SEPSiS) Observational Cohort Study conducted in Dhaka, Bangladesh. Infant feeding in the past 24 hours and 7 days were collected longitudinally during routine visits from baseline (0-4 days of age) to 6 months of age, with an additional since-birth recall at 6-months (metrics derived using different recalls). In the first study, I compared effects of different metrics on estimates of population-level prevalence and individual-level classification of early-infant feeding practices and found that single cross-sectional and long retrospective recall lead to inaccurate estimates compared to longitudinal data. In the second study, I estimated the modifying effect of different metrics on associations between maternal and perinatal characteristics and early-infant feeding practices and found that the effect of the metric was unpredictable and, in some cases, the use of biased metrics attenuated the association. In the third study, I estimated the association between mode of delivery and early-infant feeding practices and found that infants born by C-section were less likely to initiate breastfeeding early compared to those born vaginally, although the mechanism was not distinctively through immediate skin-to-skin contact and there was no evidence of a difference in the duration of exclusive breastfeeding. Overall, these results generate new evidence on methods to ascertain data on early-infant feeding practices and can provide government and non-governmental organizations with evidence to prioritize and fund breastfeeding promotion policies and programmes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.409
metaresearch head score (Gemma)0.612
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.728

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4090.612
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0050.013
Science and technology studies0.0020.007
Scholarly communication0.0060.004
Open science0.0040.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.215
GPT teacher head0.499
Teacher spread0.284 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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
Published2025
Admission routes1
Has abstractyes

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