Evidence map›Paper›PMID 31118033›Full record

ArticleInternational journal for equity in health2019

Incidence, socio-economic inequalities and determinants of catastrophic health expenditure and impoverishment for diabetes care in South Africa: a study at two public hospitals in Tshwane.

Chipo Mutyambizi, Milena Pavlova, Charles Hongoro, Frederik Booysen, Wim Groot

Open access · goldAbstract read
In one paragraph

Article in International journal for equity in health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
4.9field-weighted citation impact, top 5% of its field
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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 54 citations in OpenAlex.

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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

5 authors at 3 institutions in 3 countries.

Chipo MutyambiziResearch Use and Impact Assessment, Human Sciences Research Council, HSRC Building, 134 Pretorius Street, Pretoria, 0002, South Africa. CMutyambizi@hsrc.ac.za.ORCID 0000-0003-4749-7280
Milena PavlovaDepartment of Health Services Research, CAPHRI, Maastricht University Medical Centre, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands.
Charles HongoroResearch Use and Impact Assessment, Human Sciences Research Council, HSRC Building, 134 Pretorius Street, Pretoria, 0002, South Africa.
Frederik BooysenSchool of Economic and Business Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Wim GrootDepartment of Health Services Research, CAPHRI, Maastricht University Medical Centre, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands.
Human Sciences Research Council · ZAMaastricht University Medical Centre · NLUniversity of the Witwatersrand · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDirect out of pocket (OOP) payments for healthcare may cause financial hardship. For diabetic patients who require frequent visits to health centres, this is of concern as OOP payments may limit access to healthcare. This study assesses the incidence, socio-economic inequalities and determinants of catastrophic health expenditure and impoverishment amongst diabetic patients in South Africa.

methodsData were taken from a cross-sectional survey conducted in 2017 at two public hospitals in Tshwane, South Africa (N = 396). Healthcare costs and transport costs related to diabetes care were classified as catastrophic if they exceeded the 10% threshold of household's capacity to pay (WHO standard method) or if they exceeded a variable threshold of total household expenditure (Ataguba method). Erreygers concentration indices (CIs) were used to assess socio-economic inequalities. A multivariate logistic regression was applied to identify the determinants of catastrophic health expenditure and impoverishment.

resultsTransport costs contributed to over 50% of total healthcare costs. The incidence of catastrophic health expenditure was 25% when measured at a 10% threshold of capacity to pay and 13% when measured at a variable threshold of total household expenditure. Depending on the method used, the incidence of impoverishment varied from 2 to 4% and the concentration index for catastrophic health expenditure varied from - 0.2299 to - 0.1026. When measured at a 10% threshold of capacity to pay factors associated with catastrophic health expenditure were being female (Odds Ratio 1.73; Standard Error 0.51), being within the 3rd (0.49; 0.20), 4th (0.31; 0.15) and 5th wealth quintile (0.30; 0.17). When measured using a variable threshold of total household expenditure factors associated with catastrophic health expenditure were not having children (3.35; 1.82) and the 4th wealth quintile (0.32; 0.21).

conclusionFinancial protection of diabetic patients in public hospitals is limited. This observation suggests that health financing interventions amongst diabetic patients should target the poor and poor women in particular. There is also a need for targeted interventions to improve access to healthcare facilities for diabetic patients and to reduce the financial impact of transport costs when seeking healthcare. This is particularly important for the achievement of universal health coverage in South Africa.

Indexed as

AdultAgedCatastrophic IllnessCross-Sectional StudiesDiabetes MellitusFemaleHealth ExpendituresHospitals, PublicHumansIncidenceMaleMiddle AgedPovertySocioeconomic FactorsSouth AfricaCatastrophic health expenditureDiabetesImpoverishmentInequalitySouth Africa

Identifiers

PMID31118033
PMCPMC6530010
OpenAlexW2947667858

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.