Evidence map›Paper›PMID 26477995›Full record

ArticleJournal of epidemiology2016

Comparison of Prevalence- and Smoking Impact Ratio-Based Methods of Estimating Smoking-Attributable Fractions of Deaths.

Kyoung Ae Kong, Kyung-Hee Jung-Choi, Dohee Lim, Hye Ah Lee, Won Kyung Lee, Sun Jung Baik, Su Hyun Park, Hyesook Park

Abstract readComparative Study
In one paragraph

Article in Journal of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Smoking-attributable Mortality in Korea, 2020: A Meta-analysis of 4 Databases.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2024
    Pooled it
  2. Article
  3. Trends in smoking-attributable mortality in Spain: 1990-2018.European journal of public health · 2022
    Article
  4. Article
  5. Article
  6. 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

8 authors.

Kyoung Ae KongClinical Trial Center, Ewha Womans University Medical Center.
Kyung-Hee Jung-Choi
Dohee Lim
Hye Ah Lee
Won Kyung Lee
Sun Jung Baik
Su Hyun Park
Hyesook Park

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSmoking is a major modifiable risk factor for premature mortality. Estimating the smoking-attributable burden is important for public health policy. Typically, prevalence- or smoking impact ratio (SIR)-based methods are used to derive estimates, but there is controversy over which method is more appropriate for country-specific estimates. We compared smoking-attributable fractions (SAFs) of deaths estimated by these two methods.

methodsTo estimate SAFs in 2012, we used several different prevalence-based approaches using no lag and 10- and 20-year lags. For the SIR-based method, we obtained lung cancer mortality rates from the Korean Cancer Prevention Study (KCPS) and from the United States-based Cancer Prevention Study-II (CPS-II). The relative risks for the diseases associated with smoking were also obtained from these cohort studies.

resultsFor males, SAFs obtained using KCPS-derived SIRs were similar to those obtained using prevalence-based methods. For females, SAFs obtained using KCPS-derived SIRs were markedly greater than all prevalence-based SAFs. Differences in prevalence-based SAFs by time-lag period were minimal among males, but SAFs obtained using longer-lagged prevalence periods were significantly larger among females. SAFs obtained using CPS-II-based SIRs were lower than KCPS-based SAFs by >15 percentage points for most diseases, with the exceptions of lung cancer and chronic obstructive pulmonary disease.

conclusionsSAFs obtained using prevalence- and SIR-based methods were similar for males. However, neither prevalence-based nor SIR-based methods resulted in precise SAFs among females. The characteristics of the study population should be carefully considered when choosing a method to estimate SAF.

Indexed as

AdultAgedAged, 80 and overCause of DeathCohort StudiesFemaleHumansMaleMiddle AgedPrevalenceRepublic of KoreaRisk FactorsSmoking

Identifiers

PMID26477995
PMCPMC4773491

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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.