Evidence map›Paper›PMID 23262360›Full record

ArticlePreventive medicine2013

Home matters: work and household predictors of smoking and cessation among blue-collar workers.

C A Okechukwu, L M Dutra, J Bacic, A El Ayadi, K M Emmons

Abstract read
In one paragraph

Article in Preventive medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

C A OkechukwuHarvard University School of Public Health, Department of Society, Human Development and Health, 677 Huntington Avenue, Boston, MA 02115, USA. cokechuk@hsph.harvard.edu
L M Dutra
J Bacic
A El Ayadi
K M Emmons
Public Health Department · INBoston University · USHarvard University · US

Funding

NIMHD NIH HHS L60 MD003645
6 · The paper itself

Abstract

objectiveThis study examined the joint influence of work- and household-related variables on smoking behavior among a population representative sample of blue-collar workers with live-in partners.

methodsThe study used data on 1389 blue-collar workers from the Tobacco Use Supplement to the United States Current Population Survey 2002 to 2003 longitudinal overlap sample. Unadjusted and adjusted logistical regression analyses, which employed sampling and replicate weights to account for sampling design, were run to estimate independent and joint effects of the predictors.

resultsIn adjusted analyses, partner smoking (OR=4.97, 95%CI=3.02-8.18) and complete and partial home smoking policy (OR=0.16, 95%CI=0.09-0.29 and OR=0.39, 95%CI=0.23-0.68, respectively) were significant predictors of smoking status, but worksite smoking policies and presence of a young child under 5 in the household were not (p>0.05). Baseline complete home smoking ban was a significant predictor of subsequent cessation (OR=3.49, 95%CI=1.19-10.23), while partner smoking status, workplace smoking policy, and the presence of a young child in the home did not predict cessation (p>0.05).

conclusionHousehold-related variables were significant predictors of smoking status and cessation among blue-collar workers. Current efforts to decrease smoking in this group, which are mostly focused on work-related risk factors, should consider how to incorporate household risk factors.

Indexed as

AdultEmploymentFemaleHealth SurveysHumansInterpersonal RelationsLogistic ModelsLongitudinal StudiesMaleMiddle AgedPredictive Value of TestsResidence CharacteristicsSmokingSmoking CessationUnited StatesWorkplace

Identifiers

PMID23262360
PMCPMC3552033
OpenAlexW2038547429

What OpenQuestion holds

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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.