Evidence map›Paper›PMID 26825988›Full record

ArticleJournal of health, population, and nutrition2015

Caesarean delivery and its correlates in Northern Region of Bangladesh: application of logistic regression and cox proportional hazard model.

Mostafizur Rahman, Asma Ahmad Shariff, Aziz Shafie, Rahmah Saaid, Rohayatimah Md Tahir

Abstract readComparative StudyMulticenter Study
In one paragraph

Article in Journal of health, population, and nutrition, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Mostafizur RahmanUniversity of Rajshahi, Rajshahi, Bangladesh. mos_pshd@yahoo.com.
Asma Ahmad ShariffCentre for Foundation Studies in Science, University of Malaya, Kuala Lumpur, Malaysia. asma@um.edu.my.
Aziz ShafieDepartment of Geography, Faculty of Arts and Social Sciences, University of Malaya, Kuala Lumpur, Malaysia. azizs@um.edu.my.
Rahmah SaaidDepartment of Obstetrics and Gynaecology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
Rohayatimah Md TahirCentre for Foundation Studies in Science, University of Malaya, Kuala Lumpur, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCaesarean delivery (C-section) rates have been increasing dramatically in the past decades around the world. This increase has been attributed to multiple factors such as maternal, socio-demographic and institutional factors and is a burning issue of global aspect like in many developed and developing countries. Therefore, this study examines the relationship between mode of delivery and time to event with provider characteristics (i.e., covariates) respectively.

methodsThe study is based on a total of 1142 delivery cases from four private and four public hospitals maternity wards. Logistic regression and Cox proportional hazard models were the statistical tools of the present study.

resultsThe logistic regression of multivariate analysis indicated that the risk of having a previous C-section, prolonged labour, higher educational level, mother age 25 years and above, lower order of birth, length of baby more than 45 cm and irregular intake of balanced diet were significantly predict for C-section. With regard to survival time, using the Cox model, fetal distress, previous C-section, mother's age, age at marriage and order of birth were also the most independent risk factors for C-section. By the forward stepwise selection, the study reveals that the most common factors were previous C-section, mother's age and order of birth in both analysis. As shown in the above results, the study suggests that these factors may influence the health-seeking behaviour of women.

conclusionsFindings suggest that program and policies need to address the increase rate of caesarean delivery in Northern region of Bangladesh. Also, for determinant of risk factors, the result of Akaike Information Criterion (AIC) indicated that logistic model is an efficient model.

Indexed as

Cesarean SectionPatient Acceptance of Health CarePractice Patterns, Physicians'AdultBangladeshCesarean Section, RepeatCross-Sectional StudiesDeveloping CountriesDystociaEducational StatusFemaleHospitals, PrivateHospitals, PublicHumansLogistic ModelsMaternal Age

Identifiers

PMID26825988
PMCPMC5025997

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Registered trials

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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.