Evidence map›Paper›PMID 31574887›Full record

ArticleMedicine2019

Catastrophic health expenditure and impoverishment for type 2 diabetes mellitus patients in a multiethnic province in China using a Blinder-Oaxaca decomposition: A cross-sectional study.

Xian Sun, Tippawan Liabsuetrakul, Xiaomin Xie, Ping Liu

Abstract readEvaluation Study
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

4 authors.

Xian SunDepartment of Epidemiology and Health Statistics, Faculty of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia, China.
Tippawan LiabsuetrakulEpidemiology Unit, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Xiaomin XieEndocrinology Department, First People's Hospital of Yinchuan.
Ping LiuEndocrinology Department, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to compare the catastrophic health expenditure (CHE) and impoverishment of type 2 diabetes mellitus (T2DM) patients between 2 ethnic groups and explore the contribution of associated factors to ethnic differences in CHE and impoverishment in Ningxia Hui Autonomous Region, China.A cross-sectional study was conducted in 2 public hospitals from October 2016 to June 2017. Data were collected by interviewing eligible Hui and Han T2DM inpatients and reviewing the hospital electronic records. Both CHE and impoverishment were measured by headcount and gap. The contributions of associated factors to ethnic differences were analyzed by the Blinder-Oaxaca decomposition technique.Both the CHE and impoverishment of Hui patients before and after reimbursement were significantly higher than those of Han patients. The ethnic differences in CHE and impoverishment headcount after reimbursement were 11.9% and 9.8%, respectively. The different distributions of associated factors between Hui and Han patients contributed to 60.5% and 35.7% of ethnic differences in CHE and impoverishment, respectively. Household income, occupation, and region were significant contributing factors.Hui T2DM patients suffered greater CHE and impoverishment than Han patients regardless of reimbursements from health insurance. Differences in socioeconomic status between Hui and Han patients were the main factors behind the ethnic differences.

Indexed as

AgedCatastrophic IllnessChinaCross-Sectional StudiesDiabetes Mellitus, Type 2EthnicityFemaleHealth ExpendituresHumansInsurance, HealthMaleMiddle AgedPovertySocioeconomic Factors

Identifiers

PMID31574887
PMCPMC6775392

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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.