Evidence map›Paper›PMID 33907731›Full record

ArticleGlobal epidemiology2019

Measuring Smoking Prevalence in a Middle Income Nation: An Examination of the 100 Cigarettes Lifetime Screen.

David Levy, Luis Zavala-Arciniega, Luz Myriam Reynales-Shigematsu, Nancy L Fleischer, Zhe Yuan, Yameng Li, Luz Maria Sanchez Romero, Yan Kwan Lau, Rafael Meza, James F Thrasher

Abstract read
In one paragraph

Article in Global epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
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  4. Higher prevalence of thyroid-specific autoantibodies (TPOAb and TgAb) is related to a higher prevalence of fractures in females: results from NHANES 2007-2010.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
    Article
  5. Article
  6. Observational
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  9. Risk factors of latent tuberculosis among chronic kidney disease with routine haemodialysis patients.Journal of clinical tuberculosis and other mycobacterial diseases · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Erectile Dysfunction in Cirrhosis: Its Prevalence and Risk Factors.Journal of clinical and experimental hepatology
    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

10 authors.

David LevyLombardi Comprehensive Cancer Center Georgetown University.
Luis Zavala-ArciniegaTobacco Research Department, National Institute of Public Health, Cuernavaca, Mexico.
Luz Myriam Reynales-ShigematsuTobacco Research Department, National Institute of Public Health, Cuernavaca, Mexico.
Nancy L FleischerDepartment of Epidemiology, University of Michigan School Public Health, Ann Arbor, MI, United States of America of.
Zhe YuanLombardi Comprehensive Cancer Center Georgetown University.
Yameng LiLombardi Comprehensive Cancer Center Georgetown University.
Luz Maria Sanchez RomeroLombardi Comprehensive Cancer Center Georgetown University.
Yan Kwan LauDepartment of Epidemiology, University of Michigan School Public Health, Ann Arbor, MI, United States of America of.
Rafael MezaDepartment of Epidemiology, University of Michigan School Public Health, Ann Arbor, MI, United States of America of.
James F ThrasherTobacco Research Department, National Institute of Public Health, Cuernavaca, Mexico.

Funding

Comparative Modeling of Lung Cancer Prevention and Control PoliciesU01CA199284 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DE KONING, HARRY J, HOLFORD, THEODORE R · 2015 to 2019
$8.4M
Electronic cigarettes in Latin America: Evaluation of impacts and policy optionsR01TW010652 · FIC · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI BARNOYA, JOAQUIN, THRASHER, JAMES · 2018 to 2021
$1.6M
FIC NIH HHS R01 TW010652NCI NIH HHS U01 CA199284
6 · The paper itself

Abstract

introductionPublic health surveillance of smoking prevalence is essential in gauging the magnitude of the problem, identifying groups most affected, and evaluating polices. However, little attention has focused on how prevalence is measured, particularly in low-and middle-income countries, where smoking patterns may not mirror those in high-income countries and where the burden of tobacco use is rapidly growing. Mexico provides a unique opportunity to gauge how the questions used to define established smokers can affect prevalence estimates. This study assesses how using the 100-cigarette lifetime question to define smoking status affects estimates of smoking prevalence.

methodsWe consider data from four nationally representative surveys in Mexico, from 2002 to 2016. These surveys ask about current smoking even for adults who do not indicate having smoked 100 cigarettes in their lifetime. We compare estimates of daily and nondaily smoking prevalence by age and gender with and without the 100-cigarette screen.

resultsThe relative difference in prevalence estimates with and without the screen was greater for nondaily than daily smoking and for females than males. The difference was especially pronounced for nondaily smokers aged 15-24, where there was a 50%-75% relative difference in estimates, albeit smaller discrepancies (20-49% relative difference) were also found among older smokers. In recent years, the relative difference was greatest at lower levels of educational attainment.

conclusionsWith the growth in nondaily smoking, using the 100-cigarettes screen to define smoking status can have important implications regarding size of smoking population. Further research is warranted in other countries.

Indexed as

dailymeasurementnondailySmoking prevalencesomeday

Identifiers

PMID33907731
PMCPMC8075165

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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.