Evidence map›Paper›PMID 37601179›Full record

ArticleFrontiers in public health2023

Risk of secondhand smoke exposure and severity of COVID-19 infection: multicenter case-control study.

Surekha Kishore, Vandana Shah, Om Prakash Bera, U Venkatesh, Rakesh Kakkar, Pradeep Aggarwal, Pankaj Bhardwaj, C M Singh, Chetna Maliye, Suneela Garg and 4 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 39% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

14 authors at 7 institutions in 2 countries.

Surekha KishoreAll India Institute of Medical Sciences, Gorakhpur, Uttar Pradesh, India.
Vandana ShahCampaign for Tobacco-Free Kids, New Delhi, India.
Om Prakash BeraGlobal Health Advocacy Incubator, New Delhi, India.
U VenkateshDepartment of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Gorakhpur, Uttar Pradesh, India.
Rakesh KakkarDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Bathinda, Punjab, India.
Pradeep AggarwalDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.
Pankaj BhardwajDepartment of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India.
C M SinghDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Patna, Bihar, India.
Chetna MaliyeDepartment of Community Medicine, Mahatma Gandhi Institute of Medical Sciences, Sevagram, Maharashtra, India.
Suneela GargDepartment of Community Medicine, Maulana Azad Medical College and Associated Hospitals, New Delhi, India.
Geetha R MenonICMR-National Institute of Medical Statistics, New Delhi, India.
Puneet MisraCentre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India.
Shival Kishore VermaJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
COVID SHS Study Group
All India Institute of Medical Sciences · INAll India Institute of Medical Sciences Jodhpur · INAll India Institute of Medical Sciences Rishikesh · INJohns Hopkins University · USMahatma Gandhi Institute of Medical Sciences · INMaulana Azad Medical College · INNational Institute of Medical Statistics · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Exposure to secondhand smoke (SHS) is an established causal risk factor for cardiovascular disease (CVD) and chronic lung disease. Numerous studies have evaluated the role of tobacco in COVID-19 infection, severity, and mortality but missed the opportunity to assess the role of SHS. Therefore, this study was conducted to determine whether SHS is an independent risk factor for COVID-19 infection, severity, mortality, and other co-morbidities. Methodology: Multicentric case-control study was conducted across six states in India. Severe COVID-19 patients were chosen as our study cases, and mild and moderate COVID-19 as control were evaluated for exposure to SHS. The sample size was calculated using Epi-info version 7. A neighborhood-matching technique was utilized to address ecological variability and enhance comparability between cases and controls, considering age and sex as additional matching criteria. The binary logistic regression model was used to measure the association, and the results were presented using an adjusted odds ratio. The data were analyzed using SPSS version 24 (SPSS Inc., Chicago, IL, USA). Results: A total of 672 cases of severe COVID-19 and 681 controls of mild and moderate COVID-19 were recruited in this study. The adjusted odds ratio (AOR) for SHS exposure at home was 3.03 (CI 95%: 2.29-4.02) compared to mild/moderate COVID-19, while SHS exposure at the workplace had odds of 2.19 (CI 95%: 1.43-3.35). Other factors significantly related to the severity of COVID-19 were a history of COVID-19 vaccination before illness, body mass index (BMI), and attached kitchen at home. Discussion: The results of this study suggest that cumulative exposure to secondhand cigarette smoke is an independent risk factor for severe COVID-19 illness. More studies with the use of biomarkers and quantification of SHS exposure in the future are needed.

Indexed as

COVID-19Tobacco Smoke PollutionBody Mass IndexCase-Control StudiesCOVID-19 VaccinesHumansCOVID-19 VaccinesTobacco Smoke PollutionCOVID-19secondhand smokesmokingsubstance abusevaccination

Identifiers

PMID37601179
PMCPMC10435989
OpenAlexW4385665442

What OpenQuestion holds

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LicenceCC BY
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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.