Evidence map›Paper›PMID 24604019›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2014

Latent classes of young adults based on use of multiple types of tobacco and nicotine products.

Darin J Erickson, Kathleen M Lenk, Jean L Forster

Open access · bronzeAbstract read
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Overview of Electronic Nicotine Delivery Systems: A Systematic Review.American journal of preventive medicine · 2017
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Latent Class Analysis to Examine Patterns of Smoking and Other Tobacco Products in Young Adult Bar Patrons.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2019
    Article
  7. Article
  8. Patterns and Profiles of Adolescent Tobacco Users: Results From the Virginia Youth Survey.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2018
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Electronic cigarettes: what are they and what do they do?Annals of the New York Academy of Sciences · 2017
    Review
  14. Using Ecological Momentary Assessment to Identify Common Smoking Situations Among Korean American Emerging Adults.Prevention science : the official journal of the Society for Prevention Research · 2016
    Article
  15. Predicting Tobacco Use across the First Year of College.American journal of health behavior · 2016
    Article
  16. Latino Cigarette Smoking Patterns by Gender in a US-National Sample.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2016
    Article
  17. Article
  18. 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

3 authors at 1 institution in 1 country.

Darin J EricksonDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN erick232@umn.edu.
Kathleen M LenkDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.
Jean L ForsterDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.
University of Minnesota · US

Funding

The Effects of Minnesota State and Local Programs on Young Adult Tobacco UseR01CA086191 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI FORSTER, JEAN · 2000 to 2013
$12.8M
NCI NIH HHS R01 CA86191
6 · The paper itself

Abstract

introductionNew tobacco and nicotine products such as snus, hookah, and electronic cigarettes have risen in popularity in recent years. Use of these products among young adults is of particular interest given that experimentation with new products is common in young adulthood.

methodsWe conducted latent class analysis among a population-based sample of young adults to identify separate classes based on use of 6 types of tobacco or nicotine products: snus, hookah, electronic cigarettes, cigarillos, snuff, and cigarettes. We then examined how identified classes differed on demographic characteristics and marijuana and alcohol use.

resultsWe identified 5 classes: the largest group (60%) was characterized as reporting no or limited use of any of the products, while the smallest group (7%) was characterized by use of many types of products (poly-users). Of the 3 middle classes, 2 were the same size (10%) and were characterized by primarily using 2 of the products: one class used snus and snuff, and the other used cigarillos and hookah; the third class (13%) was characterized by primarily cigarette smoking. Numerous differences were seen across classes, including the poly-users being less likely to be college students/graduates and more likely to be male and use marijuana and alcohol.

conclusionsWe found that young adults can be grouped into 5 subgroups based on types of tobacco/nicotine products they do and do not use. A poly-use group that uses all types of tobacco products is concerning, particularly given high levels of marijuana and alcohol use reported in this group.

Indexed as

AdultAlcohol DrinkingDemographyFemaleHumansMaleMarijuana SmokingMidwestern United StatesProspective StudiesSmokingStudentsTobacco ProductsYoung Adult

Identifiers

PMID24604019
PMCPMC4155422
OpenAlexW2163116298

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.