Evidence map›Paper›PMID 38624736›Full record

ArticleEnvironmental sustainability (Singapore)2021

Environmental risk factor assessment for major respiratory disorders in metropolitan cities of India using VIIRS Suomi Aerosol data and Google Trends.

Diptarshi Mitra, Shiva Reddy Koti, Prabhakar Alok Verma, Sameer Saran

Open access · bronzeAbstract read
In one paragraph

Article in Environmental sustainability (Singapore), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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, top 83% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 1 institution in 1 country.

Diptarshi MitraGeoinformatics Department, Indian Institute of Remote Sensing (IIRS), 4 Kalidas Road, Dehradun, Uttarakhand 248001 India.ORCID 0000-0001-8867-180X
Shiva Reddy KotiGeoinformatics Department, Indian Institute of Remote Sensing (IIRS), 4 Kalidas Road, Dehradun, Uttarakhand 248001 India.
Prabhakar Alok VermaGeoinformatics Department, Indian Institute of Remote Sensing (IIRS), 4 Kalidas Road, Dehradun, Uttarakhand 248001 India.
Sameer SaranGeoinformatics Department, Indian Institute of Remote Sensing (IIRS), 4 Kalidas Road, Dehradun, Uttarakhand 248001 India.
Indian Institute of Remote Sensing · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study has investigated the association between the amount of atmospheric aerosols and the occurrences of Asthma, Chronic Obstructive Pulmonary Disease (COPD) and Lung Cancer in Delhi, Mumbai, Chennai, Kolkata and Bengaluru. Aerosol Optical Thickness (AOT) data of Visible Infrared Imaging Radiometer Suite (VIIRS) and Google Trends (GT) have been used to acquire information regarding the abundance of atmospheric aerosols and the occurrences of the respiratory diseases respectively. The result of Granger causality test between AOT and GT has shown that Delhi, Mumbai and Chennai were quite vulnerable to the three respiratory diseases whereas Bengaluru did not display so much vulnerability to these ailments. Kolkata was not so much vulnerable to Asthma but did exhibit susceptibility to the other two diseases. GT is validated by correlating with Annual Morbidity data of Delhi. The result of Granger causality test between Particulate Matter (diameter ≤ 10 μm) (PM

Indexed as

Aerosol optical thicknessAnnual morbidityGoogle trendsGranger causality testPearson’s correlation coefficientPM10VIIRS

Identifiers

PMID38624736
PMCPMC8590440
OpenAlexW3211582484

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.