Evidence map›Paper›PMID 35110245›Full record

ArticleTurkish thoracic journal2021

Analyzing the Relationship Between Air Pollution, Tobacco Use with Lung Diseases via Data Engineering Approach.

Ozgun Pinarer

Erratum issuedAbstract read
In one paragraph

Article in Turkish thoracic journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Ozgun PinarerDepartment of Computer Engineering, Galatasaray University, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objective of this study is to present the concrete impact of air pollution and tobacco use on lung disease by using a data engineering approach and acquired datasets. MATERIAL AND

methodsTo demonstrate the relationship between the air pollution and the tobacco use with the lung diseases, various relevant datasets are acquired. These datasets present not only Turkey but also worldwide situation. Datasets used in this study present the population, industrial growth, number of motor vehicles, forest area size, tobacco use rate, air pollution, number of death due to asthma, lung disease, tobacco use and air pollution. In total, 10 different datasets are gathered to prove our objective. To achieve our objective with the acquired materials, a data engineering approach is adopted. From a data engineering point of view, each dataset represents a variable for the calculation. With the data science engineering techniques used in this study, existing relations between these variables are clearly stated. Besides, with this information, a cause-consequence matching is achieved as well. In this study, covariance, correlation analyses are executed on the datasets. Moreover, multi-linear regression is performed for the forecasting.

resultsRelations between the various datasets are explored and results are divided into 3 clusters based on the relations. Among the explored relations, the most significant relation is discovered between the tobacco use rate and its effects on death rates. This relation is measured around 93-94%, which can be considered as a high risk.

conclusionResults show the concrete impacts of deforestation on air pollution, increase in tobacco use especially in easy ages causes lung disease in worldwide. These results indicate a global warning about various senses: the importance of the forest area size to balance the air quality, regulations about the number of motor vehicles, and the tobacco selling to young people are highly required.

Identifiers

PMID35110245
PMCPMC8975306

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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.