Evidence map›Paper›PMID 33209473›Full record

ArticleJournal of thoracic disease2020

Respiratory health effects of residential individual and cumulative risk factors in children living in two cities of the Pearl River Delta Region, China.

Jianqing Lin, Weiwei Lin, Zixuan Yin, Xi Fu, Dejian Mai, Shaojie Fu, Junfeng Jim Zhang, Jicheng Gong, Ning Feng, Lingyan He

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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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

10 authors.

Jianqing LinDepartment of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Weiwei LinDepartment of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Zixuan YinKey Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
Xi FuDepartment of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Dejian MaiDepartment of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Shaojie FuDepartment of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Junfeng Jim ZhangNicholas School of Environment & Duke Global Health Institute, Duke University, Durham, USA.
Jicheng GongBeijing Innovation Center for Engineering Science and Advanced Technology, State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, and Center for Environment and Health, Peking University, Beijing 100871, China.
Ning FengKey Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
Lingyan HeKey Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndoor environment is complex, with many factors potentially interacting with each other to affect health. However, previous studies have usually focused on effect of a single factor. Assessment of the combined effects of multiple factors can help with understanding the overall health risk.

methodsA cross-sectional study was conducted among 2,306 school children in Guangzhou and Shenzhen. Questionnaire data on respiratory symptoms and diseases were collected along with sociodemographic and residential environmental information. A subset of children (N=987) were measured for their lung function. A random forest algorithm was applied to screen the top-ranked indoor environmental exposure variables and to form a composite index for cumulative risk of indoor pollution (CRIP). Logistic regressions were conducted to analyze the independent effect of single indoor environmental risk factors and the combined effect of CRIP on children's respiratory health. Multiple linear regressions were used to examine the independent and combined effects of indoor environmental exposure on lung function.

resultsWe found that home dampness and molds as well as environmental tobacco smoke (ETS) were significantly and independently associated with increased prevalence of children's respiratory symptoms and diseases and with reduced lung function. A higher CRIP level was significantly associated with increased risk of cough with cold (OR =1.37, 95% CI: 1.05-1.79) and wheeze (OR =2.71, 95% CI: 1.16-6.34). A higher CRIP level was also associated with reduced lung function measured as FVC, FEV

conclusionsIn children living in the subtropical region of the Pearl River Delta, home dampness and the presence of mold as well as ETS were individual risk factors for children's respiratory health. The composite CRIP index was associated with respiratory symptoms and lung function, suggesting the utility of this index for predicting the combined effects of multiple risk factors.

Indexed as

childrencumulative riskIndoor environmentlung functionrespiratory diseases and respiratory symptoms

Identifiers

PMID33209473
PMCPMC7656417

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.