Evidence map›Paper›PMID 26987520›Full record

ArticleDrug and alcohol dependence2016

Assessing 30-day quantity-frequency of U.S. adolescent cigarette smoking as a predictor of adult smoking 14 years later.

M L Saddleson, L T Kozlowski, G A Giovino, G G Homish, M C Mahoney, M L Goniewicz

Abstract read
In one paragraph

Article in Drug and alcohol dependence, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  3. Observational
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  14. Practical nursing students' discursive practices on smoking in Finland.International journal of qualitative studies on health and well-being · 2019
    Article
  15. Preventing Smoking Progression in Young Adults: the Concept of Prevescalation.Prevention science : the official journal of the Society for Prevention Research · 2019
    Article
  16. Impact of E-Cigarette Minimum Legal Sale Age Laws on Current Cigarette Smoking.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2018
    Article
  17. Observational
  18. Article
  19. 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

6 authors.

M L SaddlesonUniversity at Buffalo, State University of New York, School of Public Health and Health Professions, Department of Community Health and Health Behavior, Buffalo, NY, USA. Electronic address: mls38@buffalo.edu.
L T KozlowskiUniversity at Buffalo, State University of New York, School of Public Health and Health Professions, Department of Community Health and Health Behavior, Buffalo, NY, USA.
G A GiovinoUniversity at Buffalo, State University of New York, School of Public Health and Health Professions, Department of Community Health and Health Behavior, Buffalo, NY, USA.
G G HomishUniversity at Buffalo, State University of New York, School of Public Health and Health Professions, Department of Community Health and Health Behavior, Buffalo, NY, USA.
M C MahoneyUniversity at Buffalo, State University of New York, School of Public Health and Health Professions, Department of Community Health and Health Behavior, Buffalo, NY, USA; Roswell Park Cancer Institute, Department of Medicine and Department of Health Behavior, Buffalo, NY, USA.
M L GoniewiczRoswell Park Cancer Institute, Department of Health Behavior, Buffalo, NY, USA.

Funding

UPENN TCORS: Tobacco Product Messaging in a Complex Communication EnvironmentP50CA179546 · NCI · UNIVERSITY OF PENNSYLVANIA · PI HORNIK, ROBERT C. · 2013 to 2017
$18.7M
NCI NIH HHS P50 CA179546NCI NIH HHS P50-CA-179546-01
6 · The paper itself

Abstract

backgroundTo improve measures of monthly tobacco cigarette smoking among non-daily smokers, predictive of future non-daily monthly and daily smoking.

methodsData from United States National Longitudinal Study of Adolescent to Adult Health, tracking adolescents, ages 12-21, over 14 years were analyzed. At baseline, 6501 adolescents were assessed; 5114 individuals provided data at waves 1 and 4. Baseline past 30-day non-daily smokers were classified using quantity-frequency measures: cigarettes smoked/day by number of days smoked in the past 30 days.

resultsThree categories of past 30-day non-daily smokers emerged using cigarettes/month (low:1-5, moderate: 6-60, high: 61+) and predicted past 30-day smoking at follow-up (low: 44.5%, moderate: 60.0%, high: 77.0%, versus 74.2% daily smokers; rτ=-0.2319, p<0.001). Two categories of non-smokers plus low, moderate and high categories of non-daily smokers made up a five-category non-daily smoking index (NDSI). High NDSI (61+ cigs/mo.) and daily smokers were equally likely to be smoking 14 years later (High NDSI OR=0.97, 95% CI=0.53-1.80 [daily as reference]). Low (1-5 cigs/mo.) and moderate (6-60 cigs/mo.) NDSI were distinctly different from high NDSI, but similar to one another (OR=0.21, 95% CI=0.15-0.29 and OR=0.22, 95% CI=0.14-0.34, respectively) when estimating future monthly smoking. Among those smoking at both waves, wave 1 non-daily smokers, overall, were less likely than wave 1 daily smokers to be smoking daily 14 years later.

conclusionsNon-daily smokers smoking over three packs/month were as likely as daily smokers to be smoking 14-years later. Lower levels of non-daily smoking (at ages 12-21) predicted lower likelihood of future monthly smoking. In terms of surveillance and cessation interventions, high NDSI smokers might be treated similar to daily smokers.

Indexed as

Adolescent BehaviorAdolescentAdultFemaleHumansLongitudinal StudiesMaleOdds RatioSmokingTime FactorsUnited StatesAdolescentsFuture smokingLongitudinalNon-daily smokingTobacco cigarette smoking

Identifiers

PMID26987520
PMCPMC6119624

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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.