Risk of lung cancer among women in relation to lifetime history of tobacco smoking: a population-based case-control study in France (the WELCA study).

BACKGROUND: This study aims to provide new insights on the role of smoking patterns and cigarette dependence in female lung cancer, and to examine differences by histological subtype. METHODS: We conducted a population-based case-control study in the great Paris area among women including 716 incident cases diagnosed between 2014 and 2017 and 757 age-matched controls. Detailed data on smoking history was collected during in-person interviews to assess intensity and duration of tobacco smoking, time since cessation, smoking habits (depth of smoke inhalation, use of filter, type of tobacco, and type of cigarettes) and Fagerström test for cigarette dependence. The comprehensive smoking index (CSI), a score modelling the combined effects of intensity, duration and time since quitting smoking was determined for each subject. Multivariable logistic regression models were fitted to calculate odds ratios (ORs) and their confidence intervals (95%CI) of lung cancer associated with smoking variables. RESULTS: Lung cancer risk increased linearly with intensity and duration of tobacco smoking while it decreased with time since cessation, to reach the risk in never-smokers after 20 years of abstinence. The combined effect of intensity and duration of tobacco smoking was more than multiplicative (p-interaction 0.012). The OR in the highest vs the lowest quartile of CSI was 12.64 (95%CI 8.50; 18.80) (p-trend < 0.001). The risk of small cell or squamous cell carcinomas increased with the CSI more sharply than the risk of adenocarcinomas. Deep smoke inhalation, dark vs blond tobacco, conventional vs light cigarettes, and unfiltered vs filtered cigarettes, as well as having mixed smoking habits, were found to be independent risk factors. Having high cigarette addiction behaviours also increased the risk after adjusting for CSI. CONCLUSION: This study provides additional insights on the effects of tobacco smoking patterns on lung cancer risk among women.

Contribution of cognitive performance and cognitive decline to associations between socioeconomic factors and dementia: A cohort study.

BACKGROUND: Socioeconomic disadvantage is a risk factor for dementia, but longitudinal studies suggest that it does not affect the rate of cognitive decline. Our objective is to understand the manner in which socioeconomic disadvantage shapes dementia risk by examining its associations with midlife cognitive performance and cognitive decline from midlife to old age, including cognitive decline trajectories in those with dementia. METHODS AND FINDINGS: Data are drawn from the Whitehall II study (N = 10,308 at study recruitment in 1985), with cognitive function assessed at 4 waves (1997, 2002, 2007, and 2012). Sociodemographic, behavioural, and cardiometabolic risk factors from 1985 and chronic conditions until the end of follow-up in 2015 (N dementia/total = 320/9,938) allowed the use of inverse probability weighting to take into account data missing because of loss to follow-up between the study recruitment in 1985 and the introduction of cognitive tests to the study in 1997. Generalized estimating equations and Cox regression were used to assess associations of socioeconomic markers (height, education, and midlife occupation categorized as low, intermediate, and high to represent hierarchy in the socioeconomic marker) with cognitive performance, cognitive decline, and dementia (N dementia/total = 195/7,499). In those with dementia, we examined whether retrospective trajectories of cognitive decline (backward timescale) over 18 years prior to diagnosis differed as a function of socioeconomic markers. Socioeconomic disadvantage was associated with poorer cognitive performance (all p < 0.001). Using point estimates for the effect of age, the differences between the high and low socioeconomic groups corresponded to an age effect of 4, 15, and 26 years, for height, education, and midlife occupation, respectively. There was no evidence of faster cognitive decline in socioeconomically disadvantaged groups. Low occupation, but not height or education, was associated with risk of dementia (hazard ratio [HR] = 2.03 [95% confidence interval (CI) 1.23-3.36]) in an analysis adjusted for sociodemographic factors; the excess risk was unchanged after adjustment for cognitive decline but was completely attenuated after adjustment for cognitive performance. In further analyses restricted to those with dementia, retrospective cognitive trajectories over 18 years prior to dementia diagnosis showed faster cognitive decline in the high education (p = 0.006) and occupation (p = 0.001) groups such that large differences in cognitive performance in midlife were attenuated at dementia diagnosis. A major limitation of our study is the use of electronic health records rather than comprehensive dementia ascertainment. CONCLUSIONS: Our results support the passive or threshold cognitive reserve hypothesis, in that high cognitive reserve is associated with lower risk for dementia because of its association with cognitive performance, which provides a buffer against clinical expression of dementia.