Maternal and neonatal outcomes among pregnant women with eating disorders.
Pregnant women with eating disorders face significantly higher risks of preterm delivery, low birth weight infants, and maternal complications in large US cohort study.
This population-level study demonstrates that eating disorders during pregnancy are becoming more prevalent and are associated with measurable increases in adverse maternal and neonatal outcomes. The large sample size provides robust evidence that eating disorders represent a significant perinatal risk factor that warrants clinical attention.
With eating disorder prevalence rising among pregnant women, clinicians need evidence-based awareness of associated risks to guide screening, monitoring, and counseling practices. This data supports the clinical importance of identifying and managing eating disorders as part of comprehensive prenatal care.
| Study Type | Retrospective Cohort Study |
| Population | 4,337,612 delivery admissions in the US, with 1,262 involving eating disorder diagnosis, 2016-2021 |
| Intervention | Presence of maternal eating disorder (ICD-10 F50.x codes) |
| Comparator | Pregnancies without eating disorder diagnosis |
| Primary Outcome | Maternal and neonatal perinatal outcomes |
| Key Finding | Eating disorder prevalence increased from 23.9 to 37.6 per 100,000 deliveries, with increased adverse outcomes |
| Journal | Journal of Perinatal Medicine |
| Year | 2024 |
Pregnant women with eating disorders require enhanced monitoring and multidisciplinary care given their elevated risk profile for both maternal and fetal complications. The increasing prevalence suggests this will become a more common clinical scenario requiring systematic approaches to identification and management.
The abstract does not specify which types of eating disorders carry the highest risk, the mechanisms underlying these associations, or whether treatment of eating disorders during pregnancy can mitigate these risks. The study cannot establish causation or determine optimal intervention strategies.
ICD-10 coding may underestimate eating disorder prevalence due to underdiagnosis or coding practices, potentially selecting for more severe cases. The study design cannot account for eating disorder severity, duration, or active treatment status, which likely influence outcomes significantly.
Eating disorders represent an underrecognized but significant perinatal risk factor with measurable impacts on maternal and fetal outcomes. Healthcare systems should consider systematic screening approaches and ensure multidisciplinary resources are available for affected pregnancies.
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FAQ
How common are eating disorders during pregnancy?
Based on this large US cohort study, eating disorders affect approximately 29 per 100,000 delivery admissions. The prevalence is increasing significantly, rising from 23.9 to 37.6 per 100,000 deliveries between 2016 and 2021.
What are the main risks to the baby when the mother has an eating disorder?
Infants born to mothers with eating disorders face significantly higher risks of preterm delivery and low birth weight. These complications can lead to long-term developmental issues and require specialized neonatal care.
What maternal complications are associated with eating disorders during pregnancy?
Pregnant women with eating disorders experience increased rates of various maternal complications during delivery and the postpartum period. The study identified multiple adverse maternal outcomes that require enhanced monitoring and clinical management.
Should pregnant women with a history of eating disorders receive special prenatal care?
Yes, given the significantly increased risks demonstrated in this study, pregnant women with eating disorders should receive specialized prenatal monitoring. Enhanced surveillance can help identify and manage complications early to improve both maternal and neonatal outcomes.
How reliable is this research for clinical decision-making?
This is a robust population-based cohort study analyzing over 4.3 million delivery admissions using standardized diagnostic codes. The large sample size and multivariable analysis adjusting for confounding factors provides strong evidence for clinical practice guidelines.
