Evidence map›Paper›PMID 36328381›Full record

ArticleBMJ global health2022

Multimorbidity and out-of-pocket expenditure for medicines in China and India.

Dennis Tuan Vu La, Yang Zhao, Perianayagam Arokiasamy, Rifat Atun, Stewart Mercer, Tiara Marthias, Barbara McPake, Sanghamitra Pati, Raffaele Palladino, John Tayu Lee

Abstract read
In one paragraph

Article in BMJ global health, 2022. 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

10 authors.

Dennis Tuan Vu LaNossal Institute for Global Health, University of Melbourne, Melbourne, Victoria, Australia dennis.la@unimelb.edu.au.ORCID 0000-0003-1996-1453
Yang ZhaoGeorge Institute for Global Health, Peking University Health Science Cente, Beijing, China.
Perianayagam ArokiasamyDepartment of Development Studies, International Institute for Population Sciences (IIPS), Mumbai, India.
Rifat AtunSchool of Public Health, Harvard University, Boston, Massachusetts, USA.ORCID 0000-0002-1531-5983
Stewart MercerCentre for Population Health Sciences, University of Edinburgh, Edinburgh, UK.
Tiara MarthiasNossal Institute for Global Health, University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0001-8226-9473
Barbara McPakeNossal Institute for Global Health, University of Melbourne, Melbourne, Victoria, Australia.
Sanghamitra PatiRMRC, ICMR, Bhubaneswar, India.
Raffaele PalladinoDepartment of Primary Care and Public Health, Imperial College, London, UK.
John Tayu LeeNossal Institute for Global Health, University of Melbourne, Melbourne, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionUsing nationally representative survey data from China and India, this study examined (1) the distribution and patterns of multimorbidity in relation to socioeconomic status and (2) association between multimorbidity and out-of-pocket expenditure (OOPE) for medicines by socioeconomic groups.

methodsSecondary data analysis of adult population aged 45 years and older from WHO Study on Global Ageing and Adult Health (SAGE) India 2015 (n=7397) and China Health and Retirement Longitudinal Study (CHARLS) 2015 (n=11 570). Log-linear, two-parts, zero-inflated and quantile regression models were performed to assess the association between multimorbidity and OOPE for medicines in both countries. Quantile regression was adopted to assess the observed relationship across OOPE distributions.

resultsBased on 14 (11 self-reported) and 9 (8 self-reported) long-term conditions in the CHARLS and SAGE datasets, respectively, the prevalence of multimorbidity in the adult population aged 45 and older was found to be 63.4% in China and 42.2% in India. Of those with any long-term health condition, 38.6% in China and 20.9% in India had complex multimorbidity. Multimorbidity was significantly associated with higher OOPE for medicines in both countries (p<0.05); an additional physical long-term condition was associated with a 18.8% increase in OOPE for medicine in China (p<0.05) and a 20.9% increase in India (p<0.05). Liver disease was associated with highest increase in OOPE for medicines in China (61.6%) and stroke in India (131.6%). Diabetes had the second largest increase (China: 58.4%, India: 91.6%) in OOPE for medicines in both countries.

conclusionMultimorbidity was associated with substantially higher OOPE for medicines in China and India compared with those without multimorbidity. Our findings provide supporting evidence of the need to improve financial protection for populations with an increased burden of chronic diseases in low-income and middle-income countries.

Indexed as

Health ExpendituresMultimorbidityAdultChinaCross-Sectional StudiesHumansIndiaLongitudinal Studieshealth policy

Identifiers

PMID36328381
PMCPMC9639066

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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.