Evidence map›Paper›PMID 35597940›Full record

ArticlePopulation health metrics2022

US county-level estimation for maternal and infant health-related behavior indicators using pregnancy risk assessment monitoring system data, 2016-2018.

Yan Wang, Heather Tevendale, Hua Lu, Shanna Cox, Susan A Carlson, Rui Li, Holly Shulman, Brian Morrow, Philip A Hastings, Wanda D Barfield

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

Article in Population health metrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 91% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

10 authors at 2 institutions in 1 country.

Yan WangDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA. XXM4@cdc.gov.ORCID 0000-0003-0245-6872
Heather TevendaleDivision of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Hua LuDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Shanna CoxDivision of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Susan A CarlsonDivision of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Rui LiHealth Resources and Services Administration, Rockville, MD, 20857, USA.
Holly ShulmanDivision of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Brian MorrowDivision of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Philip A HastingsFar Harbor LLC, Austin, TX, 78701, USA.
Wanda D BarfieldDivision of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA.
Centers for Disease Control and Prevention · USHealth Resources and Services Administration · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a critical need for maternal and child health data at the local level (for example, county), yet most counties lack sustainable resources or capabilities to collect local-level data. In such case, model-based small area estimation (SAE) could be a feasible approach. SAE for maternal or infant health-related behaviors at small areas has never been conducted or evaluated.

methodsWe applied multilevel regression with post-stratification approach to produce county-level estimates using Pregnancy Risk Assessment Monitoring System (PRAMS) data, 2016-2018 (n = 65,803 from 23 states) for 2 key outcomes, breastfeeding at 8 weeks and infant non-supine sleeping position.

resultsAmong the 1,471 counties, the median model estimate of breastfeeding at 8 weeks was 59.8% (ranged from 34.9 to 87.4%), and the median of infant non-supine sleeping position was 16.6% (ranged from 10.3 to 39.0%). Strong correlations were found between model estimates and direct estimates for both indicators at the state level. Model estimates for both indicators were close to direct estimates in magnitude for Philadelphia County, Pennsylvania.

conclusionOur findings support this approach being potentially applied to other maternal and infant health and behavioral indicators in PRAMS to facilitate public health decision-making at the local level.

Indexed as

Health BehaviorPopulation SurveillanceChildFamilyFemaleHumansInfantPregnancyRisk AssessmentInfant non-supine sleeping positionMaternal breastfeedingMultilevel regressionPregnancy risk assessment monitoring systemSmall area estimation

Identifiers

PMID35597940
PMCPMC9124401
OpenAlexW4281262154

What OpenQuestion 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 OpenQuestion graph.