Evidence map›Paper›PMID 32855505›Full record

ArticlePediatric research2020

Racial/ethnic disparities and human milk use in necrotizing enterocolitis.

Gregory P Goldstein, Vidya V Pai, Jessica Liu, Krista Sigurdson, Lelis B Vernon, Henry C Lee, Karl G Sylvester, Gary M Shaw, Jochen Profit

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Pediatric research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Factors Associated with Inequities in Donor Milk Bank Access Among Different Hospitals.Breastfeeding medicine : the official journal of the Academy of Breastfeeding Medicine · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

Gregory P GoldsteinDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Vidya V PaiDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Jessica LiuDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Krista SigurdsonDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Lelis B VernonCalifornia Perinatal Quality Care Collaborative, Stanford, USA.
Henry C LeeDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Karl G SylvesterDivision of Pediatric Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA.
Gary M ShawDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA.
Jochen ProfitDivision of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA. profit@stanford.edu.
Stanford University · USCalifornia Perinatal Quality Care Collaborative · GB

Funding

A Dashboard of Racial/Ethnic Disparity in Care Provided by NICUsR01HD083368 · NICHD · STANFORD UNIVERSITY · PI PROFIT, JOCHEN · 2016 to 2020
$3.2M
The Referral and Follow-up Patterns of High-Risk InfantsF32HD096778 · NICHD · STANFORD UNIVERSITY · PI PAI, VIDYA · 2018 to 2019
$135k
NICHD NIH HHS F32 HD096778NICHD NIH HHS R01 HD083368
6 · The paper itself

Abstract

backgroundThe impact of human milk use on racial/ethnic disparities in necrotizing enterocolitis (NEC) incidence is unknown.

methodsTrends in NEC incidence and human milk use at discharge were evaluated by race/ethnicity among 47,112 very low birth weight infants born in California from 2008 to 2017. We interrogated the association between race/ethnicity and NEC using multilevel regression analysis, and evaluated the effect of human milk use at discharge on the relationship between race/ethnicity and NEC using mediation analysis.

resultsAnnual NEC incidence declined across all racial/ethnic groups from an aggregate average of 4.8% in 2008 to 2.6% in 2017. Human milk use at discharge increased over the time period across all racial groups, and non-Hispanic (NH) black infants received the least human milk each year. In multivariable analyses, Hispanic ethnicity (odds ratio (OR) 1.27, 95% confidence interval (CI) 1.02-1.57) and Asian or Pacific Islander race (OR 1.35, 95% CI 1.01-1.80) were each associated with higher odds of NEC, while the association of NH black race with NEC was attenuated after adding human milk use at discharge to the model. Mediation analysis revealed that human milk use at discharge accounted for 22% of the total risk of NEC in non-white vs. white infants, and 44% in black vs. white infants.

conclusionsAlthough NEC incidence has declined substantially over the past decade, a sizable racial/ethnic disparity persists. Quality improvement initiatives augmenting human milk use may further reduce the incidence of NEC in vulnerable populations.

Indexed as

Milk, HumanBlack or African AmericanCaliforniaEnterocolitis, NecrotizingEthnicityFemaleHealth Status DisparitiesHispanic or LatinoHumansIncidenceInfantInfant, Low Birth WeightInfant, NewbornInfant, Newborn, DiseasesInfant, PrematureInfant, Very Low Birth Weight

Identifiers

PMID32855505
PMCPMC8087165
OpenAlexW3082532873

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.