Interpregnancy Weight Change and Adverse Birth Outcomes: Cohort Study Using Brazil's Routine Register‐Based Linked Data
Bibliographic record
Abstract
The effects of interpregnancy weight change (IPWC) on the risk of adverse birth outcomes in subsequent pregnancies are still not fully understood. Existing studies present conflicting results regarding the association between IPWC and preterm birth, while evidence of its relationship with low birth weight (LBW) or macrosomia is limited, particularly in low- and middle-income countries. This population-based longitudinal study used Brazil's routine register-based linked data from 2008 to 2015 to evaluate the association between IPWC and adverse birth outcomes in a subsequent pregnancy. Preterm birth, LBW, and macrosomia were compared across categories of IPWC between pregnancies (including changes in BMI unit, changes in BMI category, and percentage of weight change). Logistic and multinomial logistic regressions were used to estimate the association between IPWC and adverse birth outcomes. We analysed 15,570 live births from 7785 multiparous women. Women who reduced their BMI between pregnancies had an increased chance of delivering preterm neonates (OR 1.27; 95% CI 1.01-1.60) and those who increased their BMI by ≥ 4 units between pregnancies had an increased chance of macrosomia (OR 1.60; 95% CI 1.21-2.12) compared to those who maintained their BMI. Similar results were observed when IPWC was defined as changes in BMI categories and percentage changes in weight. The results of this study show that IPCW were associated with changes in both the newborn's maturity and size in a subsequent pregnancy. These findings support the need to develop experimental studies on the effects of maternal weight management within and between pregnancies to improve outcomes for both mothers and babies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".