Breastfeeding-injury link: are concerns warranted?
Bibliographic record
Abstract
OBJECTIVE: Recreational and elite athletes report avoiding breastfeeding when returning to physical activity following childbirth due to a perceived increased risk of injury; yet, there are no empirical data to support this relationship. We aimed to examine the complex interaction of breastfeeding and physical activity and its potential impact on musculoskeletal injury. METHODS: Individuals (≥18 years) who participated in physical activity during their first year following childbirth were recruited to complete an online questionnaire that covered maternal demographics, reproductive history, health outcomes (preconception to postpartum), breastfeeding habits, physical activity characteristics and musculoskeletal conditions and complaints. RESULTS: 590 people completed the survey (age at delivery 33.0±3.5, months postpartum 27.9±26.7) and identified that 22% (n=129) reported a musculoskeletal injury in the first year after childbirth. The proportion of individuals exclusively breastfeeding for a minimum of 6 months following delivery was not different between injured and non-injured groups (OR 0.97, 95% CI 0.65 to 1.45). However, a previous or current history of an eating disorder increased the risk of postpartum injury (OR 2.76, 95% CI 1.54 to 4.94). A 50% decrease in weekly metabolic equivalent of task minutes from preconception to trimester 1 or trimester 2 was associated with an 89% increased risk of postpartum injury (OR 1.89, 95% CI 1.25 to 2.86; p=0.002). CONCLUSION: In this retrospective study, breastfeeding did not increase the risk of musculoskeletal injury during the postpartum period. Maintaining preconception physical activity during pregnancy may reduce the risk of postpartum injury.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".