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Vol. 60. Issue S2.
Lung cancer: New perspectives
Pages S31-S37 (October 2024)
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Vol. 60. Issue S2.
Lung cancer: New perspectives
Pages S31-S37 (October 2024)
Original Article
Time Dependence Between Tobacco Consumption and Lung Cancer Mortality in Spain
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Carla Guerra-Torta, Esther López-Vizcaínob, María Isolina Santiago-Pérezc,
Corresponding author
, Julia Rey-Brandariza, Cristina Candal-Pedreiraa, Alberto Ruano-Ravinaa,d,e, Mónica Pérez-Ríosa,d,e
a Department of Preventive Medicine and Public Health, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
b Diffusion and Information Service, Galician Institute of Statistics, Santiago de Compostela, Spain
c Epidemiology Department, Directorate-General of Public Health, Galician Regional Health Authority, Santiago de Compostela, Spain
d Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
e Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Madrid, Spain
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Tables (2)
Table 1. Age-specific lung cancer mortality rates (per 100,000) by sex in the period 2016-2020 in Spain.
Table 2. Relative risk (RR) of lung cancer mortality for different increases in smoking prevalence at each lag l,with l =5, 10, 15, 20, 25, and 95% confidence interval.
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Special issue
This article is part of special issue:
Vol. 60. Issue S2

Lung cancer: New perspectives

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Abstract
Objectives

Lung cancer is the leading cause of cancer death and the second most common cancer in both sexes worldwide, with tobacco being its main risk factor. The aim of this study is to establish the temporal relationship between smoking prevalence and lung cancer mortality in Spain.

Methods

To model the time dependence between smoking prevalence and lung cancer mortality, a distributed lag non-linear model was applied adjusting for sex, age, year of mortality and population at risk. Smoking prevalence data from 1991-2020 were used. Considering a maximum lag of 25 years, mortality data from 2016-2020 were included. The effect of prevalence on mortality for each lag is presented in terms of relative risk (RR). To identify the lag at which smoking prevalence has the greatest effect on mortality, the RR of the different lags were compared.

Results

The optimal lag observed between smoking prevalence and lung cancer mortality in Spain was 15 years. The maximum RR was 2.9 (95%CI: 2.0-4.3) for a prevalence of 71% and a 15-year lag. The RR was 1.8 for a prevalence of 33%, an approximate median value between 1991-2020, and a 15-year lag.

Conclusions

In Spain, lung cancer mortality is affected by smoking prevalence 15 years prior. Knowing the evolution of the smoking prevalence series in a country and establishing a lag time is essential to predict how lung cancer incidence and mortality will evolve.

Keywords:
Lung cancer
Smoking
Prevalence
Nonlinear model
Spain

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