Evidence map›Paper›PMID 41257817›Full record

ArticleBMC health services research2025

Decomposition of socioeconomic inequalities of hypertension care utilization: Bangladesh experience.

Farah Ishaq, Israt Jahan Kakoly

Abstract read
In one paragraph

Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Farah IshaqUniversity of Dhaka, Dhaka, Bangladesh. farah.ishaq_ihe@du.ac.bd.
Israt Jahan KakolyUniversity of Dhaka, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper investigates the socioeconomic determinants of the utilization of screening services and prescribed medication for hypertension in Bangladesh, aiming to address the significant burden of non-communicable diseases (NCDs) in the country. Drawing upon Andersen's theoretical framework of healthcare behavior, the analysis employs probit regression and concentration index methodologies on data from the 2017-18 Bangladesh Health and Demographic Survey. Results indicate that age, marital status, body mass index (BMI), smoking habit, and wealth status positively influence the utilization of screening services and treatment for hypertension. However, contradictory findings for education and employment suggest a nuanced relationship, possibly influenced by access to healthcare resources and time constraints. Concentration curve analysis reveals pro-rich inequality in both screening and treatment utilization, with the concentration index for screening services being statistically significant. Decomposition analysis further elucidates the contributions of specific factors to socioeconomic inequality, highlighting the importance of educational attainment and age in healthcare access. These findings underscore the need for targeted interventions aimed at addressing socioeconomic disparities in hypertension management, including efforts to improve access to healthcare resources, raise awareness, and mitigate barriers to healthcare access among marginalized populations. Addressing these disparities is crucial for promoting equitable healthcare delivery and reducing the burden of hypertension and related NCDs in Bangladesh.

Indexed as

Healthcare DisparitiesHypertensionPatient Acceptance of Health CareAdultAgedAge FactorsBangladeshFemaleHealth Services AccessibilityHumansMaleMass ScreeningMiddle AgedSocioeconomic FactorsYoung Adult

Identifiers

PMID41257817
PMCPMC12629048

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.