Trends in Gestational Weight Gain in Louisiana, March 2019 to March 2022
Bibliographic record
Abstract
Importance: Average gestational weight gain (GWG) increased during the COVID-19 pandemic, but it is not known whether this trend has continued. Objective: To examine patterns of GWG during the COVID-19 pandemic by delivery and conception timing through the second year of the pandemic. Design, Setting, and Participants: This cohort study is a retrospective review of birth certificate and delivery records from 2019 to 2022. Electronic health records were from the largest delivery hospital in Louisiana. Participants included all individuals giving birth from March 2019 to March 2022. Data analysis was performed from October 2022 to July 2023. Exposure: Delivery date (cross-sectionally) and conception before the pandemic (March 2019 to March 2020) and during the peak pandemic (March 2020 to March 2021) and late pandemic (March 2021 to March 2022). Main Outcomes and Measures: The primary outcome was GWG (total GWG and adherence to the 2009 Institute of Medicine recommendations) analyzed using linear and log-linear regression with control for covariates. Results: Among 23 012 total deliveries (8763 Black individuals [38.1%]; 11 774 White individuals [51.2%]; mean [SD] maternal age, 28.9 [5.6] years), 3182 individuals (42.0%) exceeded the recommended weight gain in the year proceeding the pandemic, 3400 (45.4%) exceeded recommendations during the peak pandemic, and 3273 (44.0%) exceeded recommendations in the late pandemic. Compared with those who delivered before the pandemic (reference), participants had higher total GWG if they delivered peak or late pandemic (adjusted β [SE], 0.38 [0.12] kg vs 0.19 [0.12] kg; P = .007). When cohorts were defined by conception date, participants who conceived before the pandemic but delivered after the pandemic started had higher GWG compared with those whose entire pregnancy occurred before the pandemic (adjusted β [SE], 0.51 [0.16] kg). GWG was lower in the pregnancies conceived after the pandemic started and the late pandemic (adjusted β [SE], 0.29 [0.12] kg vs 0.003 [0.14] kg; P = .003) but these participants began pregnancy at a slightly higher weight. Examining mean GWG month by month suggested a small decrease for March 2020, followed by increased mean GWG for the following year. Individuals with 2 pregnancies (1289 individuals) were less likely to gain weight above the recommended guidelines compared with their prepandemic pregnancy, but this association was attenuated after adjustment. Conclusions and Relevance: In this cohort, individuals with critical time points of their pregnancy during the COVID-19 pandemic gained more weight compared with the previous year. The increased GWG leveled off as the pandemic progressed but individuals were slightly heavier beginning pregnancy.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| 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) | 0.002 | 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 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".