Evidence map›Paper›PMID 35206960›Full record

ArticleHealthcare (Basel, Switzerland)2022

Long-Term Trends of Asthma Mortality in China from 2000 to 2019: A Joinpoint Regression and Age-Period-Cohort Analysis.

Guimin Huang, Junting Liu, Tao Li, Dongqing Hou, Wenqian Liu, Yixuan Xie, Tong Zhang, Yijing Cheng

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. 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

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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.

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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

8 authors.

Guimin HuangChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.ORCID 0000-0003-3477-0612
Junting LiuChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.
Tao LiChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.ORCID 0000-0002-6096-8772
Dongqing HouChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.ORCID 0000-0003-1099-6481
Wenqian LiuChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.
Yixuan XieChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.
Tong ZhangChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.
Yijing ChengChild Health Big Data Research Center, Capital Institute of Pediatrics, Beijing 100020, China.ORCID 0000-0002-8294-1781

Funding

National Natural Science Foundation of China 72004142Research Foundation of Capital Institute of Pediatrics LCPY-2021-07
6 · The paper itself

Abstract

backgroundTrends of asthma mortality vary widely all over the world, while the trends in China over the past 15 years are unknown. The aim of this study was to assess the trends of asthma mortality in China.

methodsAsthma deaths and demographic characteristics were collected from National Death Cause Datasets of Disease Surveillance System between 2004 and 2019. The data were analyzed with joinpoint regression analysis and age-period-cohort (APC) analysis for the mortality rate due to asthma in China.

resultsAsthma mortality declined from 2.4 (95% confidence interval (CI): 2.3-2.5) per 100,000 in 2004 to 1.6 (95% CI: 1.5-1.7) per 100,000 in 2019. Age-adjusted asthma mortality rates decreased for men and women in urban and rural areas from 2004 through 2019. The decreasing trend of the mortality rate has slowed down substantially during 2007 and 2009. After that, the decreasing trend has stabilized. The asthma mortality rates generally have a positive relationship with the age of the population when controlling for period and cohort. The period trend decreased and then increased when controlling for age and cohort.

conclusionsWe should pay more attention to asthma management plans or treatment for aging people who are facing higher risk of asthma death.

Indexed as

age-period-cohort (APC) analysisasthmajoinpoint regression analysismortality

Identifiers

PMID35206960
PMCPMC8871574

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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.