Evidence map›Paper›PMID 32446349›Full record

ArticleThe Lancet. Global health2020

Physical multimorbidity, health service use, and catastrophic health expenditure by socioeconomic groups in China: an analysis of population-based panel data.

Yang Zhao, Rifat Atun, Brian Oldenburg, Barbara McPake, Shenglan Tang, Stewart W Mercer, Thomas E Cowling, Grace Sum, Vicky Mengqi Qin, John Tayu Lee

Abstract read
In one paragraph

Article in The Lancet. Global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 248 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
248citing papers in PubMed, 5 pooled it
–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

248 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  14. Multimorbidity patterns among fragility fracture patients aged 50 + years in China and the US.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026
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188 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Yang ZhaoThe Nossal Institute for Global Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre on Implementation Research for Prevention and Control of Noncommunicable Diseases, Melbourne, VIC, Australia; The George Institute for Global Health at Peking University Health Science Center, Beijing, China. Electronic address: zhaoyang001@hsc.pku.edu.cn.
Rifat AtunDepartment of Global Health and Population, Harvard T H Chan School of Public Health and Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, MA, USA.
Brian OldenburgThe Nossal Institute for Global Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre on Implementation Research for Prevention and Control of Noncommunicable Diseases, Melbourne, VIC, Australia.
Barbara McPakeThe Nossal Institute for Global Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Shenglan TangDuke Global Health Institute, Duke University, Durham, NC, USA.
Stewart W MercerUsher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK.
Thomas E CowlingDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
Grace SumSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
Vicky Mengqi QinSaw Swee Hock School of Public Health, National University of Singapore, Singapore.
John Tayu LeeThe Nossal Institute for Global Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia; Public Health Policy Evaluation Unit, Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultimorbidity, the presence of two or more mental or physical chronic non-communicable diseases, is a major challenge for the health system in China, which faces unprecedented ageing of its population. Here we examined the distribution of physical multimorbidity in relation to socioeconomic status; the association between physical multimorbidity, health-care service use, and catastrophic health expenditures; and whether these associations varied by socioeconomic group and social health insurance schemes.

methodsIn this population-based, panel data analysis, we used data from three waves of the nationally representative China Health and Retirement Longitudinal Study (CHARLS) for 2011, 2013, and 2015. We included participants aged 50 years and older in 2015, who had complete follow-up for the three waves. We used 11 physical non-communicable diseases to measure physical multimorbidity and annual per-capita household consumption spending as a proxy for socioeconomic status.

findingsOf 17 708 participants in CHARLS, 11 817 were eligible for inclusion in our analysis. The median age of participants was 62 years (IQR 56-69) in 2015, and 5766 (48·8%) participants were male. 7320 (61·9%) eligible participants had physical multimorbidity in China in 2015. The prevalence of physical multimorbidity was increased with older age (odds ratio 2·93, 95% CI 2·71-3·15), among women (2·70, 2·04-3·57), within a higher socioeconomic group (for quartile 4 [highest group] 1·50, 1·24-1·82), and higher educational level (5·17, 3·02-8·83); however, physical multimorbidity was more common in poorer regions than in the more affluent regions. An additional chronic non-communicable disease was associated with an increase in the number of outpatient visits (incidence rate ratio 1·29, 95% CI 1·27-1·31), and number of days spent in hospital as an inpatient (1·38, 1·35-1·41). We saw similar effects in health service use of an additional chronic non-communicable disease in different socioeconomic groups and among those covered by different social health insurance programmes. Overall, physical multimorbidity was associated with a significantly increased likelihood of catastrophic health expenditure (for the overall population: odds ratio 1·29, 95% CI 1·26-1·32, adjusted for sociodemographic variables). The effect of physical multimorbidity on catastrophic health expenditures persisted even among the higher socioeconomic groups and across all health insurance programmes.

interpretationConcerted efforts are needed to reduce health inequalities that are due to physical multimorbidity, and its adverse economic effect in population groups in China. Social health insurance reforms must place emphasis on reducing out-of-pocket spending for patients with multimorbidity to provide greater financial risk protection.

fundingNone.

Indexed as

Health Status DisparitiesMultimorbidityNoncommunicable DiseasesSocial ClassAgedCatastrophic IllnessChinaFacilities and Services UtilizationFemaleHealth ExpendituresHumansInsurance, HealthLongitudinal StudiesMaleMiddle AgedPrevalence

Identifiers

PMID32446349
PMCPMC7241981

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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.