Evidence map›Paper›PMID 35906603›Full record

ArticleBMC health services research2022

What fragile factors hinder the pace of China's alleviation efforts of the poverty-stricken population? A study from the perspective of impoverishment caused by medical expenses.

Jiahui Wang, Xinye Qi, Linghan Shan, Kexin Wang, Xiao Tan, Zheng Kang, Ning Ning, Libo Liang, Lijun Gao, Mingli Jiao and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 10 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

14 authors at 2 institutions in 1 country.

Jiahui Wang *Centre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Xinye Qi *Centre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Linghan Shan *Centre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Kexin WangCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Xiao TanShenzhen Hospital of Guangzhou University of traditional Chinese Medicine (Futian), 6001 Beihuan Avenue, Futian District, Shenzhen, Guangdong Province, China.
Zheng KangCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Ning NingCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Libo LiangCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Lijun GaoCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Mingli JiaoCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Yu CuiCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Yanhua HaoCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China.
Qunhong WuCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China. wuqunhong@163.com.
Ye LiCentre of Health Policy & Management, Health Management College, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150086, Heilongjiang, China. liye8459@163.com.
Harbin Medical University · CNGuangzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveChina has made remarkable achievements in poverty alleviation. However, with the change in economic development and age structure, the population stricken by poverty due to medical expenses and disability accounted for 42.3 and 14.4% of the total poverty-stricken population, respectively. Accordingly, it is crucial to accurately pinpoint the characteristics of people who are about to become poor due to illness. In this study, we analyzed the incidence of impoverishment by medical expense at the provincial, family, and different medical insurance scheme levels to identify the precise groups that are vulnerable to medical-related poverty.

methodData were extracted from the Fifth National Health Service Survey in China in 2013 through a multi-stage, stratified, and random sampling method, leaving 93,570 households (273,626 people) for the final sample. The method recommended by World Health Organization (WHO) was adopted to calculate impoverishment by medical expense, and logistic regression was adopted to evaluate its determinants.

resultsThe poverty and impoverishment rate in China were 16.2 and 6.3% respectively. The poverty rate in western region was much higher than that of central and eastern regions. The rate of impoverishment by medical expense (IME) was higher in the western region (7.2%) than that in the central (6.5%) and eastern (5.1%) regions. The New Cooperative Medical Scheme (NCMS) was associated with the highest rate (9.1%) of IME cases. The top three diseases associated with IME were malignant tumor, congenital heart disease, and mental disease. Households with non-communicable disease members or hospitalized members had a higher risk on IME. NCMS-enrolled, poorer households were more likely to suffer from IME.

conclusionThe joint roles of economic development, health service utilization, and welfare policies result in medical impoverishment for different regions. Poverty and health service utilization are indicative of households with high incidence of medical impoverishment. Chronic diseases lead to medical impoverishment. The inequity existing in different medical insurance schemes leads to different degrees of risk of IME. A combined strategy to precise target multiple vulnerabilities of poor population would be more effective.

Indexed as

Health ExpendituresState MedicineChinaHumansInsurance, HealthPovertyRural PopulationChinaFinancial protectionMedical impoverishmentPoverty alleviation

Identifiers

PMID35906603
PMCPMC9336080
OpenAlexW4288515163

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.