Evidence map›Paper›PMID 25019158›Full record

ArticlePloS one2014

Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.

Yue Zhang, Li Peng, Haidong Kan, Jianming Xu, Renjie Chen, Yuan Liu, Weibing Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

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

  1. Pooled it
  2. Temperature drop and the risk of asthma: a systematic review and meta-analysis.Environmental science and pollution research international · 2017
    Pooled it
  3. Trial
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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.

Yue ZhangDepartment of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China.
Li PengShanghai Center for Urban Environmental Meteorology, Shanghai, China; Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
Haidong KanDepartment of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China; Fudan Tyndall Centre, Fudan University, Shanghai, China.
Jianming XuShanghai Center for Urban Environmental Meteorology, Shanghai, China; Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
Renjie ChenDepartment of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China.
Yuan LiuDepartment of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China.
Weibing WangDepartment of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety (Ministry of Education), Fudan University, Shanghai, China; Fudan Tyndall Centre, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is limited evidence for the impacts of meteorological changes on asthma hospital admissions in adults in Shanghai, China.

objectivesTo quantitatively evaluate the short-term effects of daily mean temperature on asthma hospital admissions.

methodsDaily hospital admissions for asthma and daily mean temperatures between January 2005 and December 2012 were analyzed. After controlling for secular and seasonal trends, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) combined with a distributed lag non-linear model were used to explore the associations between temperature and hospital admissions for asthma.

resultsDuring the study periods, there were 15,678 hospital admissions for asthma by residents of Shanghai, an average 5.6 per day. Pearson correlation analysis found a significant negative correlation (r = -0.174, P<0.001) between asthma hospitalizations and daily mean temperature (DMT). The DMT effect on asthma increased below the median DMT, with lower temperatures associated with a higher risk of hospital admission for asthma. Generally, the cold effect appeared to be relatively acute, with duration lasting several weeks, while the hot effect was short-term. The relative risk of asthma hospital admissions associated with cold temperature (the 25th percentile of temperature relative to the median temperature) was 1.20 (95% confidence interval [CI], 1.01∼1.41) at lag0-14. However, warmer temperatures were not associated with asthma hospital admissions.

conclusionsCold temperatures may trigger asthmatic attacks. Effective strategies are needed to protect populations at risk from the effects of cold.

Indexed as

Meteorological ConceptsTemperatureAdultAir PollutionAsthmaChinaHumansModels, TheoreticalNonlinear DynamicsPatient AdmissionPoisson DistributionTime Factors

Identifiers

PMID25019158
PMCPMC4097056

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.