Exposure-lag response of smoking prevalence on lung cancer incidence using a distributed lag non-linear model.

ABSTRACT: The prevalence of smokers is a major driver of lung cancer incidence in a population, though the "exposure-lag" effects are ill-defined. Here we present a multi-country ecological modelling study using a 30-year smoking prevalence history to quantify the exposure-lag response. To model the temporal dependency between smoking prevalence and lung cancer incidence, we used a distributed lag non-linear model (DLNM), controlling for gender, age group, country, outcome year, and population at risk, and presented the effects as the incidence rate ratio (IRR) and cumulative incidence rate ratio (IRR_cum). The exposure-response varied by lag period, whilst the lag-response varied according to the magnitude and direction of changes in smoking prevalence in the population. For the cumulativ

SUBMITTER: Smith DR 

PROVIDER: S-EPMC8280159 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature