Evidence map›Paper›PMID 34873415›Full record

ArticleComputational and mathematical methods in medicine2021

Bayesian Analysis of Trends in Utilization of Maternal Healthcare Services in Pakistan during 2006-2018.

Navid Feroze, Muhammad Ajmal Ziad, Rabia Fayyaz, Yaé Ulrich Gaba

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Navid FerozeDepartment of Statistics, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan.ORCID https://orcid.org/0000-0002-9760-0939
Muhammad Ajmal ZiadDepartment of Statistics, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan.
Rabia FayyazCOMSATS University Islamabad, Islamabad, Pakistan.
Yaé Ulrich GabaQuantum Leap Africa (QLA), AIMS Rwanda Centre, Remera Sector KN 3, Kigali, Rwanda.ORCID https://orcid.org/0000-0001-8128-9704
University of Azad Jammu and Kashmir · PKAfrican Institute for Mathematical Sciences · RWCOMSATS University Islamabad · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study is aimed at investigating the time trends and disparities in access to maternal healthcare in Pakistan using Bayesian models.

methodsThe detailed analysis is based on the data from Pakistan Demographic and Health Survey (PDHS) conducted during 2006-2018. We have proposed Bayesian logistic regression models (BLRM) to investigate the trends of maternal healthcare in the country. Based on different goodness-of-fit criteria, the performance of proposed models has also been compared with repeatedly used classical logistic regression models (CLRM).

resultsThe results from the analysis suggested that BLRM perform better than CLRM. The access to antenatal healthcare increased from 61% to 86% during years 2006-18. The utilization of medication also improved from 44% in 2006 to 60% in 2018. Despite the improvements from 2006 to 2018, every three out of ten women were not protected against neonatal tetanus, neither delivered in the health facility place nor availed with the skilled health provider at the time of delivery during 2018. Similarly, two-fifth mothers did not received any skilled postnatal checkup within two days after delivery. Additionally, the likelihood of MHS provided to mothers is in favor of mothers with lower ages, lower birth orders, urban residences, higher education, higher wealth quintiles, and residents of Sindh and Punjab.

conclusionsThe gaps in utilization of MHS in different socioeconomic groups of the society have not decreased significantly during 2006-2018. Any future maternal health initiative in the country should focus to reduce the observed disparities among different socioeconomic sectors of the society.

Indexed as

AdolescentAdultBayes TheoremComputational BiologyFemaleHealthcare DisparitiesHealth Care SurveysHealth Services AccessibilityHumansInfant, NewbornLogistic ModelsLongitudinal StudiesMaternal Health ServicesMiddle AgedPakistanPregnancy

Identifiers

PMID34873415
PMCPMC8643246
OpenAlexW3216811899

What OpenQuestion holds

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LicenceCC BY
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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.