Evidence map›Paper›PMID 34844998›Full record

ArticleBMJ global health2021

Inequity of healthcare access and use and catastrophic health spending in slum communities: a retrospective, cross-sectional survey in four countries.

Improving Health in Slums Collaborative

Abstract read
In one paragraph

Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

1 author.

Improving Health in Slums Collaborative

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTracking the progress of universal health coverage (UHC) is typically at a country level. However, country-averages may mask significant small-scale variation in indicators of access and use, which would have important implications for policy choice to achieve UHC.

methodsWe conducted a retrospective cross-sectional household and individual-level survey in seven slum sites across Nigeria, Kenya, Bangladesh and Pakistan. We estimated the adjusted association between household capacity to pay and report healthcare need, use and spending. Catastrophic health expenditure was estimated by five different methods.

resultsWe surveyed 7002 households and 6856 adults. Gini coefficients were wide, ranging from 0.32 to 0.48 across the seven sites. The total spend of the top 10% of households was 4-47 times more per month than the bottom 10%. Households with the highest budgets were: more likely to report needing care (highest vs lowest third of distribution of budgets: +1 to +31 percentage points (pp) across sites), to spend more on healthcare (2.0 to 6.4 times higher), have more inpatient and outpatient visits per year in five sites (1.0 to 3.0 times more frequently), spend more on drugs per visit (1.1 to 2.2 times higher) and were more likely to consult with a doctor (1.0 to 2.4 times higher odds). Better-off households were generally more likely to experience catastrophic health expenditure when calculated according to four methods (-1 to +12 pp), but much less likely using a normative method (-60 to -80 pp).

conclusionsSlums have a very high degree of inequality of household budget that translates into inequities in the access to and use of healthcare. Evaluation of UHC and healthcare access interventions targeting these areas should consider distributional effects, although the standard measures may be unreliable.

Indexed as

Financing, PersonalPoverty AreasAdultCross-Sectional StudiesHealth Services AccessibilityHumansRetrospective Studiescross-sectional surveyhealth economicshealth policyhealth systems evaluation

Identifiers

PMID34844998
PMCPMC8633995

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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.