Evidence map›Paper›PMID 36538524›Full record

ArticlePloS one2022

Trends and inequities in severe maternal morbidity in Massachusetts: A closer look at the last two decades.

Hafsatou Diop, Eugene R Declercq, Chia-Ling Liu, Howard J Cabral, Xiaohui Cui, Ndidiamaka Amutah-Onukagha, Audra Meadows

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.9field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

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  9. Leveraging a Longitudinally Linked Dataset to Assess Recurrence of Severe Maternal Morbidity.Women's health issues : official publication of the Jacobs Institute of Women's Health
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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

7 authors at 4 institutions in 1 country.

Hafsatou DiopMassachusetts Department of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0002-3654-9674
Eugene R DeclercqBoston University School of Public Health, Boston, Massachusetts, United States of America.
Chia-Ling LiuEvalogic Services, Inc, Newton, Boston, Massachusetts, United States of America.
Howard J CabralBoston University School of Public Health, Boston, Massachusetts, United States of America.
Xiaohui CuiMassachusetts Department of Public Health, Boston, Massachusetts, United States of America.
Ndidiamaka Amutah-OnukaghaTufts University School of Medicine and the Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Audra MeadowsDepartment of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Diego, California, United States of America.ORCID 0000-0002-2747-0075
Boston University · USMassachusetts Department of Public Health · USTufts University · USUniversity of California San Diego · US

Funding

Reducing Racial Disparities in SMM post COVID19: Assessing the integration of maternal safety bundles and community based doulas to improve outcomes for Black womenR01MD016026 · NIMHD · TUFTS UNIVERSITY BOSTON · PI AMUTAH-ONUKAGHA, NDIDIAMAKA, DECLERCQ, EUGENE R · 2020 to 2024
$3.1M
NIMHD NIH HHS R01 MD016026
6 · The paper itself

Abstract

It is estimated that 50,000-60,000 pregnant people in the United States (US) experience severe maternal morbidity (SMM). SMM includes life-threatening conditions, such as acute myocardial infarction, acute renal failure, amniotic fluid embolism, disseminated intravascular coagulation, or sepsis. Prior research has identified both rising rates through 2014 and wide racial disparities in SMM. While reducing maternal death and SMM has been a global goal for the past several decades, limited progress has been made in the US in achieving this goal. Our objectives were to examine SMM trends from 1998-2018 to identify factors contributing to the persistent and rising rates of SMM by race/ethnicity and describe the Black non-Hispanic/White non-Hispanic rate ratio for each SMM condition. We used a population-based data system that links delivery records to their corresponding hospital discharge records to identify SMM rates (excluding transfusion) per 10, 000 deliveries and examined the trends by race/ethnicity. We then conducted stratified analyses separately for Black and White birthing people. While the rates of SMM during the same periods steadily increased for all racial/ethnic groups, Black birthing people experienced the greatest absolute increase compared to any other race/ethnic group going from 69.4 in 1998-2000 to 173.7 per 10,000 deliveries in 2016-2018. In addition, we found that Black birthing people had higher rates for every individual condition compared to White birthing people, with rate ratios ranging from a low of 1.11 for heart failure during surgery to a high of 102.4 for sickle cell anemia. Obesity was not significantly associated with SMM among Black birthing people but was associated with SMM among White birthing people [aRR 1.18 (95% CI: 1.02, 1.36)]. An unbiased understanding of how SMM has affected different race/ethnicity groups is key to improving maternal health and preventing SMM and mortality among Black birthing people. SMM needs to be addressed as both a medical and public health challenge.

Indexed as

EthnicityRacial GroupsFemaleHumansMassachusettsParturitionPregnancyUnited States

Identifiers

PMID36538524
PMCPMC9767362
OpenAlexW4312036718

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.