Trends in the Prevalence of Fetal Macrosomia in the United States, 2004 to 2022
Bibliographic record
Abstract
Globally, the prevalence of macrosomia varies widely, and the trends in macrosomia prevalence are controversial. We aim to analyze temporal changes in fetal macrosomia prevalence from 2004 to 2022.This study included 72,879,544 singleton deliveries from the U.S. National Vital Statistics System Natality Files. We used Joinpoint regression to assess annual trends in fetal macrosomia (birth weight: 4,000 g), further classified into Grade 1 (4,000-4,499 g), Grade 2 (4,500-4,999 g), and Grade 3 (5,000 g).The overall prevalence of fetal macrosomia declined overall from 8.85% (95% CIs: 8.83, 8.88) in 2004 to 7.42% (95% CIs: 7.40, 7.45) in 2022, representing an average annual relative decrease of 0.89% (95% CIs: -1.17%, -0.61%). The temporal trend was nonlinear: a sharp decrease from 2004-2007 (APC: -3.63; 95% CIs: -4.92, -2.32), a modest increase during 2007-2015 (APC: 0.79; 95% CIs: 0.41, 1.16), and a steady decline from 2015-2022 (APC: -1.59; 95% CIs: -1.98, -1.20). Subgroup analyses revealed consistent declines, with more pronounced reductions among women aged > 30 years, those with a college education, primiparous women, and Asian/Pacific Islander mothers. When stratified by severity, the prevalence of Grade 1 macrosomia decreased from 7.53% to 6.42% (AAPC: -0.80; 95% CIs: -1.06, -0.53), Grade 2 decreased from 1.13% to 0.84% (AAPC:-1.50; 95% CIs: -1.94, -1.06), and Grade 3 from 0.20% to 0.16% (AAPC: -0.85; 95% CIs: -1.42, -0.27).The prevalence of fetal macrosomia has varied over time, showing an overall downward trend over the past 20 years, with two periods of rapid decline (2004-2007 and 2015-2022) and one period of moderate increase (2007-2015). The changes observed were significant for Grade 1 and Grade 2 macrosomia, while Grade 3 macrosomia also showed a downward trend, but without distinct segment slopes. · The overall prevalence of fetal macrosomia in the United States declined from 8.85% in 2004 to 7.42% in 2022, with a non-linear trend marked by two periods of decline and one of moderate increase.. · The trend was more pronounced among women aged >30 years, with college education, primiparous women, and Asian/Pacific Islander mothers.. · Severity-stratified analyses revealed significant declines in Grade 1 and Grade 2, while Grade 3 demonstrated a modest decrease without distinct Joinpoint segments..
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".