Evidence map›Paper›PMID 38010484›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2023

Association Between Air Pollution and Coronary Heart Disease Hospitalizations in Lanzhou City, 2013-2020: a Time Series Analysis.

Miaoxin Liu, Jingze Yu, Anning Zhu, Jianglong Ling, Rentong Chen, Yaoyi Zhang, Ye Ruan

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. 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

7 authors.

Miaoxin LiuSchool of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
Jingze YuSchool of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
Anning ZhuSchool of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
Jianglong LingSchool of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
Rentong ChenSchool of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
Yaoyi ZhangSchool of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
Ye RuanSchool of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China. ruany1203@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronary heart disease (CHD) is one of the most serious public health problems. However, few studies have focused on the effects of exposure to particulate matter and gaseous air pollutants on CHD. This study aimed to explore the relationship between air pollutants and the number of hospitalized patients with CHD in Lanzhou, and we collected daily data on the number of hospitalized patients with CHD, daily air pollutants, and meteorological factors from 2013 to 2020. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson regression model was applied to evaluate the relationship between air pollutants and the number of hospitalized patients with CHD. The results indicated that the hysteresis effect of all pollutants except O

Indexed as

Air PollutantsAir PollutionCoronary DiseaseAgedChinaEnvironmental ExposureFemaleHospitalizationHumansTime FactorsAir PollutantsAir pollutantsCoronary heart diseaseHospitalizationLagged effectShort-term exposure

Identifiers

PMID38010484
PMCPMC10728394

What OpenQuestion holds

Textmetadata
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.