Evidence map›Paper›PMID 36093142›Full record

ArticleFrontiers in cardiovascular medicine2022

Provincial heterogeneity in the management of care cascade for hypertension, diabetes, and dyslipidaemia in China: Analysis of nationally representative population-based survey.

Yang Zhao, Kanya Anindya, Rifat Atun, Tiara Marthias, Chunlei Han, Barbara McPake, Nadila Duolikun, Emily Hulse, Xinyue Fang, Yimin Ding and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
  3. [Metabolic Characteristics of Patients With Early-Onset Type 2 Diabetes Mellitus and a Risk Prediction Model for Microvascular Complications].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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

12 authors at 10 institutions in 5 countries.

Yang ZhaoThe George Institute for Global Health, Beijing, China.
Kanya AnindyaThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Rifat AtunDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States.
Tiara MarthiasThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Chunlei HanCollege of Public Health and Management, Binzhou Medical University, Yantai, China.
Barbara McPakeThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Nadila DuolikunThe George Institute for Global Health, Beijing, China.
Emily HulseDepartment of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, MA, United States.
Xinyue FangChinese Center for Disease Control and Prevention, Beijing, China.
Yimin DingSchool of Software, Tongji University, Shanghai, China.
Brian OldenburgBaker Heart and Diabetes Institute, Melbourne, VIC, Australia.
John Tayu LeeThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, VIC, Australia.
George Institute for Global Health · CNHarvard Global Health Institute · USAustralian National University · AUBaker Heart and Diabetes Institute · AUBinzhou University · CNChinese Center For Disease Control and Prevention · CNThe George Institute for Global Health · AUTongji University · CNUniversitas Gadjah Mada · IDUniversity of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aims to examine (1) province-level variations in the levels of cardiovascular disease (CVD) risk and behavioral risk for CVDs, (2) province-level variations in the management of cascade of care for hypertension, diabetes, and dyslipidaemia, and (3) the association of province-level economic development and individual factors with the quality of care for hypertension, diabetes, and dyslipidaemia. Methods: We used nationally representative data from the China Health and Retirement Longitudinal Study in 2015, which included 12,597 participants aged 45 years. Using a care cascade framework, we examined the quality of care provided to patients with three prevalent NCDs: hypertension, diabetes, and dyslipidaemia. The proportion of WHO CVD risk based on the World Health Organization CVD risk prediction charts, Cardiovascular Risk Score (CRS) and Behavior Risk Score (BRS) were calculated. We performed multivariable logistic regression models to determine the individual-level drivers of NCD risk variables and outcomes. To examine socio-demographic relationships with CVD risk, linear regression models were applied. Results: In total, the average CRS was 4.98 (95% CI: 4.92, 5.05), while the average BRS was 3.10 (95% confidence interval: 3.04, 3.15). The weighted mean CRS (BRS) in Fujian province ranged from 4.36 to 5.72 ( Conclusion: Our research found significant provincial heterogeneity in the CVD risk scores and the management of the cascade of care for hypertension, diabetes, and dyslipidaemia for persons aged 45 years or more. To improve the management of cascade of care and to eliminate regional and disparities in CVD care and risk factors in China, local and population-based focused interventions are necessary.

Indexed as

behavior riskcardiovascular diseasecare cascadeChinaregional disparity

Identifiers

PMID36093142
PMCPMC9458474
OpenAlexW4292835132

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.