Evidence map›Paper›PMID 27556031›Full record

ArticleBioMed research international2016

Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China.

Juanjuan Zhang, Jihong Dai, Li Yan, Wenlong Fu, Jing Yi, Yuzhi Chen, Chuanhe Liu, Dongqun Xu, Qiang Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BioMed research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

9 authors.

Juanjuan ZhangCenter of Respiratory Disorders, Children's Hospital, Chongqing Medical University, Chongqing 400014, China.
Jihong DaiCenter of Respiratory Disorders, Children's Hospital, Chongqing Medical University, Chongqing 400014, China; Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China.ORCID 0000-0002-7414-3659
Li YanMinistry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China.
Wenlong FuMinistry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China.
Jing YiDepartment of Medical Statistics, Chongqing Medical University, Chongqing 400046, China.
Yuzhi ChenCenter for Asthma Prevalence and Education, Capital Institute of Pediatrics, Beijing 100020, China.
Chuanhe LiuCenter for Asthma Prevalence and Education, Capital Institute of Pediatrics, Beijing 100020, China.
Dongqun XuInstitute of Environmental Health and Related Products Safety, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
Qiang WangInstitute of Environmental Health and Related Products Safety, Chinese Center for Disease Control and Prevention, Beijing 100021, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation. Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons. Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China's urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis. Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (p < 0.05). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2 was found to be the most powerful predictor variable amongst all (β = -19.572, p < 0.05). Furthermore, results had shown that hours of sunshine (β = -0.014, p < 0.05) was a significant component summary predictor variable. Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China.

Indexed as

ClimateAdolescentAir PollutantsAsthmaChildChild, PreschoolChinaDemographyFemaleHealth SurveysHumansInfantInfant, NewbornLinear ModelsMalePrevalenceAir Pollutants

Identifiers

PMID27556031
PMCPMC4983328

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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.