Maternal Body Mass Index and Breastmilk Energy, Fat, and Protein Content: A Systematic Review and Regression Analysis of Simulated Data (OR30-06-19)
Bibliographic record
Abstract
Given increased incidence of maternal postpartum obesity and limited understanding of the degree to which maternal body composition is related to energy and macronutrient content of breastmilk, we conducted a systematic review to assess the associations between maternal body mass index (BMI) and breastmilk energy, fat, and/or total protein content. A protocol was registered prior to the completion of this systematic review (PROSPERO 2018 CRD42018098808). The electronic databases MEDLINE, Embase, CINAHL, and Web of Science were searched. The three outcomes of interest were breastmilk energy (kcal/dL), fat (g/dL), and total protein (g/dL) from mothers of term-born infants. Articles that reported maternal BMI or weight and height, collected breastmilk, and measured energy, fat, or protein concentration in breastmilk one to six months postpartum were eligible. If breastmilk was collected at multiple timepoints, the measures closest to three months postpartum were used. A simulated dataset was generated in Stata 14 based on respective sample sizes and means and variance of maternal BMI and breastmilk energy, fat, and protein content of the included studies, assuming normality of each of these variables based on the literature. Linear regressions were performed to examine associations between maternal BMI (kg/m2) and breastmilk energy and individual macronutrients. A total of 2,012 articles were identified from the search and reference lists of included studies. After full-text screening by two reviewers, 39 articles were included with breastmilk samples from 2,837 mothers. Based on the simulated data, maternal BMI was not significantly associated with breastmilk energy concentration (β = −0.0044, 95% CI [−0.14, 0.14], P > 0.9). However, BMI was positively associated with breastmilk fat concentration (β = 0.015, 95% CI [0.0022, 0.027] P = 0.02) and was negatively associated with total protein concentration (β = −0.0068, 95% CI [−0.011, −0.0027], P = 0.001). Thus, every 1 kg/m2 increase in BMI is associated with a 0.0022 g/dL increase in fat and a 0.011 g/dL decrease in total protein concentration. Statistically significant associations were found between maternal BMI and breastmilk fat and protein content. However, the effect size was small suggesting that these differences may not be clinically meaningful. N/A.
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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 | 0.025 | 0.093 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.021 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".