Evidence map›Paper›PMID 37263610›Full record

ArticleSouthern medical journal2023

Mediation Analysis of Maternal Smoking, Gestational Age, and Birth Weight on the Texas-Mexico Border.

Chinodebem Ogbutor, Stephanie M Mishaw, Zuber D Mulla

Open access · bronzeAbstract read
In one paragraph

Article in Southern medical journal, 2023. 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

3 authors at 1 institution in 1 country.

Chinodebem OgbutorFrom the Paul L. Foster School of Medicine.
Stephanie M MishawDepartment of Obstetrics and Gynecology.
Zuber D Mulla
Macalester College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPublished data on the indirect effect of maternal smoking on birth weight as mediated by gestational age in Hispanic populations are lacking. Our goal was to conduct such a mediation analysis using data from El Paso County, Texas.

methodsEl Paso County is located on the US-Mexico border. A simple mediation analysis was conducted using year 2010 El Paso County birth certificate data. The SAS macro PROCESS 3.5.3 was used to estimate the direct and indirect effects of active maternal smoking (by trimester) on birth weight (in grams) in the setting of linear regression. The single mediator was gestational age in weeks. A direct or indirect effect was deemed to be present if the 95% confidence limits (CLs) excluded 0. Analyses were adjusted for multiple variables, including maternal prepregnancy body mass index. The indirect effect was reported along with a 95% bootstrap CL.

resultsA total of 16,654 singleton births were included in the cohort. The majority of the mothers were White Hispanic (87.2%). The mean (standard deviation) birth weight was 3198.6 g (517.2). A direct effect of maternal smoking during each trimester on birth weight was detected. An indirect effect of maternal smoking on birth weight was not detected in any of the trimesters. In adjusted analyses for the third trimester, the indirect effect for every 1-U increase in the mean number of cigarettes smoked per day was -4.18 (95% bootstrap CL -10.64 to 1.99).

conclusionsIn our large, predominantly Hispanic cohort, it appears that gestational age is not a mediator of the effect of maternal smoking on birth weight. Future studies in our population should explore other possible mediators of this association.

Indexed as

Mediation AnalysisSmokingBirth WeightFemaleGestational AgeHumansMexicoPregnancyTexas

Identifiers

PMID37263610
PMCPMC10208643
OpenAlexW4378966151

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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.