Evidence map›Paper›PMID 32257169›Full record

ArticleJournal of global health2020

Effective coverage for hypertension treatment among middle-aged adults and the older population in China, 2011 to 2013: A nationwide longitudinal study.

Yang Zhao, Ajay Singh Mahal, Shenglan Tang, Tilahun Nigatu Haregu, Brian Oldenburg

Abstract read
In one paragraph

Article in Journal of global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Yang ZhaoThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, Australia.
Ajay Singh MahalThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, Australia.
Shenglan TangDuke Global Health Institute, Duke University, Durham, North Carolina, USA.
Tilahun Nigatu HareguThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, Australia.
Brian OldenburgThe Nossal Institute for Global Health, The University of Melbourne, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

methodsWe used the baseline survey and first follow-up surveys of the China Health and Retirement Longitudinal Study of middle-aged and older populations conducted between 2011 and 2013. Correlates of effective coverage and treatment coverage for hypertension were analysed using multivariate logistic regression models, after controlling for demographic characteristics.

resultsIn 2011, 38.40% of 13 702 individuals surveyed were identified with hypertension. Overall, the effective treatment coverage among the middle-aged and older population in China from 2011 to 2013 was only 22.40% compared to the treatment coverage of 55.86%. Variations in effective coverage among patients enrolled in the three public health insurance schemes ranged from 22.60% to 29.31%.

conclusionsThe level of effective coverage for hypertension treatment in China was still very low, and that health insurance schemes play a significant role in improving treatment coverage and effective coverage for hypertension treatment. In the implementation of China's health system reform, health equity and health care equality should be emphasised and enhanced by offering more equitable benefits packages across social health insurance schemes.

Indexed as

AdultAgedAged, 80 and overAntihypertensive AgentsChinaFemaleHealthcare DisparitiesHealth Care ReformHealth ExpendituresHealth ServicesHealth Services AccessibilityHealthy AgingHumansHypertensionInsurance CoverageInsurance, HealthAntihypertensive Agents

Identifiers

PMID32257169
PMCPMC7101209

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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.