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Record W2588652569 · doi:10.1371/journal.pone.0171573

Factors associated with the utilization of institutional delivery services in Bangladesh

2017· article· en· W2588652569 on OpenAlexaff
Sanni Yaya, Ghose Bishwajit, Michael Ekholuenetale

Bibliographic record

VenuePLoS ONE · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHealth facilityEnvironmental healthLogistic regressionService delivery frameworkMedicineMillennium Development GoalsRural areaHealth careDeveloping countryReproductive healthDemographyService (business)Health servicesBusinessEconomic growthPopulation

Abstract

fetched live from OpenAlex

INTRODUCTION: Bangladesh has made remarkable progress towards reducing its maternal mortality rate (MMR) over the last two decades and is one of the few countries on track to achieving the MMR-related Millennium Development Goals (MDG-5A). However, the provision of universal access to reproductive healthcare (MDG-5B) and the utilization of maternal healthcare services (MHS) such as institutional delivery, which are crucial to the reduction of maternal mortality, are far behind the internationally agreed-upon target. Effective policymaking to promote the utilization of MHS can be greatly facilitated by the identification of the factors that hinder service uptake. In this study, we therefore aim to measure the prevalence of institutional delivery services and explore the factors associated with their utilization in Bangladesh. METHODS: Data for this study were extracted from the 2011 Bangladesh Demographic and Health Survey (BDHS, 2011); participants were 7,313 women between the ages of 15 and 49 years, selected from both urban and rural households. Data were analyzed using Chi-square analysis, and conditional logistic regression. RESULTS: According to the findings, fewer than one in three women reported delivering at a health facility. The multivariable regression analysis showed that participants from rural areas were 46.9% less likely to have institutional deliveries compared to urban dwellers (OR = 0.531; p<0.001; 95%CI: 0.467-0.604), and participants aged between 30 and 49 years had a 23.6% higher prevalence of institutional delivery service utilization compared to those aged 15 to 29 years (OR = 1.236; p = 0.006; 95%CI: 1.062-1.437). Moreover, participants with higher educational attainment were about twice as likely to deliver at a standard health facility when compared to those without formal education (OR = 2.081; p<0.001; 95%CI: 1.650-2.624), and similarly, husbands with higher educational attainment exhibited an approximately 71% higher service utilization of institutional delivery facilities compared to those without formal education (OR = 1.709; p<0.001; 95%CI: 1.412-2.069). Wealth status was also a significant predictor of institutional delivery service use, with participants belonging to the highest economic stratum being more likely to receive skilled care compared to the lowest economic stratum (OR = 2.507; p<0.001; 95%CI: 2.118-2.968). In addition, results indicated that households of average economic class had a 27% higher level of institutional delivery service utilization compared to those of lower economic status (OR = 1.272; p = 0.011; 95%CI: 1.057-1.531). Furthermore, institutional health service use was 18% higher among participants who were aware of community clinical services compared to those who were hardly aware of these services (OR = 0.816; p = 0.012; 95%CI: 0.696-0.957). Lastly, the odds of utilizing delivery services was 1.553 times more likely for participants who use family planning compared to those who do not (p<0.001; 95%CI: 1.374-1.754), and 3.639 times more likely for those who receive antenatal care compared to those who do not (p<0.001; 95%CI: 3.074-4.308). These were found to be significant predictors of the choice of delivery services. DISCUSSION: Our results suggest that efforts towards reducing national maternal mortality in Bangladesh could be aided by investments into education, poverty reduction and the strengthening of reproductive healthcare services through community clinics, with particular focus on rural areas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.101

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.094
GPT teacher head0.275
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations131
Published2017
Admission routes1
Has abstractyes

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