Dataset Information

Cancer Screening Patterns Among Current, Former, and Never Smokers in the United States, 2010-2015.

ABSTRACT: Importance:National guidelines recommend screening for several cancer types, yet screening rates remain below target. To date, cancer screening patterns by smoking status, a major cancer risk factor, are unknown. Objective:To assess cancer screening patterns among individuals who never smoked (never smokers), formerly smoked (former smokers), and currently smoke (current smokers) in the United States. Design, Setting, and Participants:This cross-sectional study assessed data from the National Health Interview Survey years 2010, 2013, and 2015. Adult participants (aged ?18 years) who had never reported a cancer diagnosis were included in the analysis. Data were analyzed from August 1, 2018, through February 1, 2019. Exposures:Receipt of cancer screening, including colonoscopy, mammography, prostate-specific antigen testing, and Papanicolaou test per the US Preventive Services Task Force guidelines. Main Outcomes and Measures:Multivariable logistic regression defined adjusted odds ratios (AORs) and 95% CIs for undergoing cancer screening by smoking status. Among participants who received a specific screening test, AORs and 95% CIs of receiving the test within guideline-recommended intervals were also assessed. Results:Among 83?176 participants (45?851 [55.1%] women; mean [SD] age, 47 [18] years), 51?014 (61.3%) were never smokers; 17?235 (20.7%), former smokers; and 14?927 (17.9%), current smokers. Compared with never smokers, current smokers were less likely to ever have received a colonoscopy (43.8% vs 57.7%; AOR, 0.74; 95% CI, 0.68-0.82; P?

SUBMITTER: Sanford NN

PROVIDER: S-EPMC6537823 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Cancer Screening Patterns Among Current, Former, and Never Smokers in the United States, 2010-2015.

Sanford Nina N NN Sher David J DJ Butler Santino S Xu Xiaohan X Ahn Chul C D'Amico Anthony V AV Rebbeck Timothy T Aizer Ayal A AA Mahal Brandon A BA

JAMA network open 20190503 5

<h4>Importance</h4>National guidelines recommend screening for several cancer types, yet screening rates remain below target. To date, cancer screening patterns by smoking status, a major cancer risk factor, are unknown.<h4>Objective</h4>To assess cancer screening patterns among individuals who never smoked (never smokers), formerly smoked (former smokers), and currently smoke (current smokers) in the United States.<h4>Design, setting, and participants</h4>This cross-sectional study assessed dat ...[more]

PMID: 31099863

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Project description:Background DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm models which attempt to distinguish current, former and never smokers as individual classes. Derivation of a robust DNAm model that accurately distinguishes between current, former and never smokers would be particularly valuable to epidemiological research (as a more accurate smoking definition vs. self-report) and could potentially translate to clinical settings. Therefore, we appraise 4 DNAm models of ternary smoking status (that is, current, former and never smokers): methylation at cg05575921 (AHRR model), weighted scores from 13 CpGs created by Maas et al. (Maas model), weighted scores from a LASSO model of candidate smoking CpGs from the literature (candidate CpG LASSO model), and weighted scores from a LASSO model supplied with genome-wide 450K data (agnostic LASSO model). Discrimination is assessed by AUC, whilst classification accuracy is assessed by accuracy and kappa, derived from confusion matrices. Results We find that DNAm can classify ternary smoking status with reasonable accuracy, including when applied to external data. Ternary classification using only DNAm far exceeds the classification accuracy of simply assigning all classes as the most prevalent class (63.7% vs. 36.4%). Further, we develop a DNAm classifier which performs well in discriminating current from former smokers (agnostic LASSO model AUC in external validation data: 0.744). Finally, across our DNAm models, we show evidence of enrichment for biological pathways and human phenotype ontologies relevant to smoking, such as haemostasis, molybdenum cofactor synthesis, body fatness and social behaviours, providing evidence of the generalisability of our classifiers. Conclusions Our findings suggest that DNAm can classify ternary smoking status with close to 65% accuracy. Both the ternary smoking status classifiers and current versus former smoking status classifiers address the present lack of former smoker classification in epigenetic literature; essential if DNAm classifiers are to adequately relate to real-world populations. To improve performance further, additional focus on improving discrimination of current from former smokers is necessary. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01191-6.

Project description:Although obesity has been directly linked to the development of many cancers, many epidemiological studies have found that body mass index (BMI)--a surrogate marker of obesity--is inversely associated with the risk of lung cancer. These studies are difficult to interpret because of potential confounding by cigarette smoking, a major risk factor for lung cancer that is associated with lower BMI.We prospectively examined the association between BMI and the risk of lung cancer among 448?732 men and women aged 50-71 years who were recruited during 1995-1996 for the National Institutes of Health-AARP Diet and Health Study. BMI was calculated based on the participant's self-reported height and weight on the baseline questionnaire. We identified 9437 incident lung carcinomas (including 415 in never smokers) during a mean follow-up of 9.7 years through 2006. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for lung cancer risk factors, including smoking status. To address potential bias due to preexisting undiagnosed disease, we excluded potentially unhealthy participants in sensitivity analyses. All statistical tests were two-sided.The crude incidence rate of lung cancer over the study follow-up period was 233 per 100?000 person-years among men and 192 per 100?000 person-years among women. BMI was inversely associated with the risk of lung cancer among both men and women (BMI ?35 vs 22.5-24.99 kg/m(2): HR = 0.81, 95% CI = 0.70 to 0.94 and HR = 0.73, 95% CI = 0.61 to 0.87, respectively). The inverse association was restricted to current and former smokers and was stronger after adjustment for smoking. Among smokers, the inverse association persisted even after finely stratifying on smoking status, time since quitting smoking, and number of cigarettes smoked per day. Sensitivity analyses did not support the possibility that the inverse association was due to prevalent undiagnosed disease.Our results suggest that a higher BMI is associated with a reduced risk of lung cancer in current and former smokers. Our inability to attribute the inverse association between BMI and the risk of lung cancer to residual confounding by smoking or to bias suggests the need for considering other explanations.

Project description:IntroductionDepression is strongly associated with daily smoking. Yet, little is known about the association between depression and non-daily smoking. The aim of this study was to investigate the prevalence of past-year depression and changes in past-year depression over time among non-daily smokers, compared to daily smokers and never-smokers, overall and stratified by age, gender, income, nicotine dependence, and cigarettes per day.MethodsData were drawn from the National Household Survey on Drug Use (NSDUH), an annual cross-sectional study of persons aged 12 and over (total study population N = 496 805). The prevalence of past-year depression was examined annually among non-daily smokers, daily smokers, and never-smokers from 2005 to 2013 using linear trend analyses.ResultsPast-year depression was common among 10.10% of non-daily smokers, common among 10.78% of daily smokers, and 5.51% of never-smokers in 2013. The prevalence of depression increased from 2005 to 2013 among non-daily smokers (9.06% vs. 10.10%; p = .034) while there was no significant change in depression over time among daily smokers. Increases in depression among non-daily smokers occurred for both men and women and appear most pronounced youth, those smoking fewer cigarettes, and those without nicotine dependence.ConclusionsThe prevalence of depression among non-daily smokers was equivalent to daily smokers and nearly twice that among nonsmokers. Depression appears to be increasing over time in non-daily smokers especially among youth, those who smoke less, and those without nicotine dependence. More work on the mental health of non-daily smokers is needed as this is an increasing and understudied group.ImplicationsThis is the first study to investigate changes in the prevalence of depression among non-daily smokers compared to daily smokers and never-smokers over the past decade in a nationally representative sample of the United States. The results suggest an increase in depression among non-daily smokers over time that did not similarly occur for daily smokers. Further, there were several subgroups of non-daily smokers among whom depression has increased more rapidly. This study suggests the need for more information about the relationship between depression and non-daily smoking including the impact of depression on quit attempts and outcomes.

Dataset Information

Cancer Screening Patterns Among Current, Former, and Never Smokers in the United States, 2010-2015.

Publications

Cancer Screening Patterns Among Current, Former, and Never Smokers in the United States, 2010-2015.

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