ArticleBMC public health2023
Risk factors combine in a complex manner in assessment for macrosomia.
Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Defining Low Milk Supply: A Data-Driven Diagnostic Framework and Risk Factor Analysis for Breastfeeding Women.Nutrients · 2025Article
- Prevalence of Large-for-Gestational Age and Macrosomia Among Livebirths in 23 Low- and Middle-Income Countries Between 2000 and 2021: An Individual Participant Data Analysis.BJOG : an international journal of obstetrics and gynaecology · 2025Article
- Unilateral diaphragmatic paralysis and complete brachial plexus injury in a complex birth injury: A rare case report mimicking Tarlov cyst and review of literature.Clinical case reports · 2024Article
- Prevalence and determinants of fetal macrosomia in Bangladesh.Frontiers in pediatrics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMacrosomia is a serious public health concern. This study aimed to examine the combined effects of various risk factors on macrosomia.
methodsThe China Labor and Delivery Survey was a multicenter cross-sectional study that included 96 hospitals. Logistic regression analysis was performed to examine the combined effects of the risk factors for macrosomia. The population attributable risk percentage (PAR%) was calculated for the risk factors.
resultsA total of 64,735 live births, including 3,739 neonates with macrosomia, were used for the analysis. The weighted prevalence of macrosomia was 5.8%. Pre-pregnancy overweight/obesity, diabetes, and gestational hypertension have a synergistic effect on increasing the rate of macrosomia in mothers aged < 36 years. The highest odds ratio (36.15, 95% CI: 34.38-38.02) was observed in female fetuses whose mothers had both gestational hypertension and diabetes. However, in mothers aged ≥ 36 years, the synergistic effect of gestational hypertension and other factors did not exist, and the risk for macrosomia was reduced by 70% in female fetuses of mothers with both gestational hypertension and overweight/obesity. Pre-pregnancy risk factors (pre-pregnancy overweight/obesity and advanced maternal age) contributed the most to macrosomia (23.36% of the PAR%), and the single largest risk factor was pre-pregnancy overweight/obesity (17.43% of the PAR%).
conclusionMacrosomia was related to several common, modifiable risk factors. Some factors have combined effects on macrosomia (e.g., pre-pregnancy overweight/obesity and diabetes), whereas gestational hypertension varies by maternal age. Strategies based on pre-pregnancy risk factors should be given more attention to reduce the burden of macrosomia.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.