Evidence map›Paper›PMID 38166087›Full record

ArticlePloS one2024

From the local disparities to national realities: Mapping and multilevel modeling of catastrophic health expenditure in Bangladesh using HIES 2016.

Md Muhitul Alam, Md Israt Rayhan, Mohaimen Mansur

Abstract read
In one paragraph

Article in PloS one, 2024. 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

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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

3 authors.

Md Muhitul AlamInstitute of Statistical Research and Training (ISRT), University of Dhaka, Dhaka, Bangladesh.ORCID 0009-0008-2307-8712
Md Israt RayhanInstitute of Statistical Research and Training (ISRT), University of Dhaka, Dhaka, Bangladesh.ORCID 0000-0002-0451-3976
Mohaimen MansurInstitute of Statistical Research and Training (ISRT), University of Dhaka, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In developing nations, catastrophic health expenditures have become an all-too-common occurrence, threatening to push households into impoverishment and poverty. By analyzing the Household Income and Expenditure Survey 2016, which features a sample of 46,080 households, this study provides a comprehensive district-by-district analysis of the variation in household catastrophic health expenditures and related factors. The study utilizes a multilevel logistic regression model, which considers both fixed and random effects to identify factors associated with catastrophic health expenditure. The findings of the study indicate that districts located in the eastern and southern regions are at a significantly higher risk of experiencing catastrophic health expenditures. A potential explanation for this trend may be attributed to the high prevalence of chronic diseases in these districts, as well as their economic conditions. The presence of chronic diseases (AOR 5.45 with 95% CI: 5.14, 5.77), presence of old age person (AOR 1.50 with 95% CI: 1.39, 1.61), place of residence (AOR 1.40 with 95% CI: 1.14, 1.73) are found to be highly associated factors. Additionally, the study reveals that the thresholds used to define catastrophic health expenditures exhibit substantial variation across different regions, and differ remarkably from the threshold established by the WHO. On average, the thresholds are 23.12% of nonfood expenditure and 12.14% of total expenditure. In light of these findings, this study offers important insights for policymakers and stakeholders working towards achieving universal health coverage and sustainable development goals in Bangladesh.

Indexed as

Family CharacteristicsHealth ExpendituresBangladeshCatastrophic IllnessChronic DiseaseFinancing, PersonalHumans

Identifiers

PMID38166087
PMCPMC10760898

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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.