Misunderstandings in the misconception on the use of pack-years in analysis of smoking

Tobacco Patterns and Risk of Chronic Obstructive Pulmonary Disease: Results From a Cross-Sectional Study

INTRODUCTION

There is still uncertainty about which aspects of cigarette smoking influence the risk of Chronic Obstructive Pulmonary Disease (COPD). The aim of this study was to estimate the COPD risk as related to duration of use, intensity of use, lifetime tobacco consumption, age of smoking initiation and years of abstinence.

METHODS

We conducted an analytical cross-sectional study based on data from the EPISCAN-II study (n=9092). All participants underwent a face-to-face interview and post-bronchodilator spirometry was performed. COPD was defined as post-bronchodilator FEV1/FVC<70%. Parametric and nonparametric logistic regression models with generalized additive models were used.

RESULTS

8819 persons were included; 858 with COPD and 7961 without COPD. The COPD risk increased with smoking duration up to ≥50 years [OR 3.5 (95% CI: 2.3-5.4)], with smoking intensity up to ≥39cig/day [OR 10.1 (95% CI: 5.3-18.4)] and with lifetime tobacco consumption up to >29 pack-years [OR 3.8 (95% CI: 3.1-4.8)]. The COPD risk for those who started smoking at 22 or later was 0.9 (95% CI: 0.6-1.4). The risk of COPD decreased with increasing years of cessation. In comparison with both never smokers and current smokers, the lowest risk of COPD was found after 15-25 years of abstinence.

CONCLUSION

COPD risk increases with duration, intensity, and lifetime tobacco consumption and decreases importantly with years of abstinence. Age at smoking initiation shows no effect. After 15-25 years of cessation, COPD risk could be equal to that of a never smoker. This work suggests that the time it takes to develop COPD in a smoker is about 30 years.

Cigarette Smoking, and Blood Monocyte Count Correlate with Chronic Lung Injuries and Mortality

Background

Cigarette smoking (CS)-related monocytosis contributes to the development of chronic lung injuries via complex mechanisms. We aim to determine correlations between measures of CS and monocytes, their capacities to predict chronic lung diseases, and their associations with mortality.

Methods

A single-center retrospective study of patients undergoing surgical resection for suspected lung nodules/masses was performed. CS was quantified as cigarettes smoked per day (CPD), duration of smoking, composite pack years (CPY), current smoking status, and smoking cessation years. A multivariate logistic regression analysis was performed.

Results

Of 382 eligible patients, 88% were ever smokers. In this group, 45% were current smokers with mean CPD of 27.2±40.0. CPY and duration of smoking showed positive linear correlations with percentage monocyte count. Physiologically, CPY was associated with progressive obstruction, hyperinflation, and reduced diffusion capacity (DL_CO). Across the quartiles of smoking, there was an accumulation of radiologic and histologic abnormalities. Anthracosis and emphysema were associated with CPD, while lung cancer, respiratory bronchiolitis (RB), emphysema, and honeycombing were statistically related to duration of smoking. Analysis using consecutive CPY showed associations with lung cancer (≥10 and <30), fibrosis (≥20 and <40), RB (≥50), anthracosis and emphysema (≥10 and onwards). Percentage monocytes correlated with organizing pneumonia (OP), fibrosis, and emphysema. The greater CPY increased mortality across the groups. Significant predictors of mortality included percentage monocyte, anemia, GERD, and reduced DL_CO.

Conclusion

Indices of CS and greater monocyte numbers were associated with endpoints of chronic lung disease suggesting a participation in pathogenesis. Application of these easily available metrics may support a chronology of CS-induced chronic lung injuries. While a relative lesser amount of smoking can be associated with lung cancer and fibrosis, greater CPY increases the risk for emphysema. Monocytosis predicted lung fibrosis and mortality. Duration of smoking may serve as a better marker of monocytosis and associated chronic lung diseases.

Associations of attention problems and family context in childhood and adolescence with young adult daily smoking: General and smoking-specific family contexts

BACKGROUND

The potential heterogeneity in daily smoking across young adulthood has been relatively understudied. Relatedly, the unique and joint associations of earlier risk factors with young adults' daily smoking largely remain unknown. To address these gaps, this work identified subgroups of daily smoking trajectories during young adulthood and linked them to earlier attention problems and smoking-specific and general family context.

METHODS

Data came from the Seattle Social Development Project, a longitudinal study following a community sample (N = 808). Participants' daily smoking was measured from ages 21-33. Earlier attention problems were assessed at ages 14-16 and 18. Earlier smoking-specific and general family factors were assessed at ages 10-16 and 18.

RESULTS

Growth mixture models produced four profiles: chronic daily smokers, increasers, decreasers, and no-daily smokers. Results from multinomial logistic regressions revealed that earlier attention problems and smoking-specific family factors may contribute to daily smoking in the early 20 s, whereas earlier general family context provided protection for trajectories of daily smoking characterized by changes in the late 20 s and early 30 s DISCUSSION: Selective prevention strategies that expand people's repertoire of healthy options to address attention problems might be helpful, considering the possibility of using tobacco as means to mitigate attention problems. Our findings also highlight the importance of nurturing earlier general family context, a relatively overlooked dimension in smoking prevention efforts, to facilitate young adult smokers' desistence from daily smoking, particularly those who have attention problems in adolescence.

Long-term associations of cigarette smoking in early mid-life with predicted brain aging from mid- to late life

BACKGROUND AND AIMS

Smoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid-life would have older than predicted brain age 16-28 years later.

DESIGN

Prospective cohort observational study, utilizing smoking pack years data from average age 40 (early mid-life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid-life) and 68 years (early old age). Early mid-life alcohol use was also evaluated.

SETTING

Population-based United States sample.

PARTICIPANTS/CASES

Participants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves.

MEASUREMENTS

Self-reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain-Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age-predicted brain age) acquired at average ages 56 (n = 493; 2002-08), 62 (n = 408; 2009-14) and 68 (n = 499; 2016-19).

FINDINGS

In structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = -0.144, P = 0.012, 95% confidence interval (CI) = -0.257, -0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = -0.166, P = 0.001, 95% CI = -0.261, -0.070) with additional influences at age 62 (β = -0.115, P = 0.005, 95% CI = -0.195, -0.036). Age 40 alcohol did not predict age 68 PBAD. Within-twin-pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD.

CONCLUSIONS

Heavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.

Joint effects of intensity and duration of cigarette smoking on the risk of head and neck cancer: A bivariate spline model approach

OBJECTIVES

This study aimed at re-evaluating the strength and shape of the dose-response relationship between the combined (or joint) effect of intensity and duration of cigarette smoking and the risk of head and neck cancer (HNC). We explored this issue considering bivariate spline models, where smoking intensity and duration were treated as interacting continuous exposures.

MATERIALS AND METHODS

We pooled individual-level data from 33 case-control studies (18,260 HNC cases and 29,844 controls) participating in the International Head and Neck Cancer Epidemiology (INHANCE) consortium. In bivariate regression spline models, exposures to cigarette smoking intensity and duration (compared with never smokers) were modeled as a linear piecewise function within a logistic regression also including potential confounders. We jointly estimated the optimal knot locations and regression parameters within the Bayesian framework.

RESULTS

For oral-cavity/pharyngeal (OCP) cancers, an odds ratio (OR) >5 was reached after 30 years in current smokers of ∼20 or more cigarettes/day. Patterns of OCP cancer risk in current smokers differed across strata of alcohol intensity. For laryngeal cancer, ORs >20 were found for current smokers of ≥20 cigarettes/day for ≥30  years. In former smokers who quit ≥10  years ago, the ORs were approximately halved for OCP cancers, and ∼1/3 for laryngeal cancer, as compared to the same levels of intensity and duration in current smokers.

CONCLUSION

Referring to bivariate spline models, this study better quantified the joint effect of intensity and duration of cigarette smoking on HNC risk, further stressing the need of smoking cessation policies.

Lung cancer health disparities

Compared with all other racial and ethnic groups in the United States, African Americans are disproportionally affected by lung cancer, both in terms of incidence and survival. It is likely that smoking, as the main etiological factor associated with lung cancer, contributes to these disparities, but the precise mechanism is still unclear. This paper seeks to explore the history of lung cancer disparities and review to the literature regarding the various factors that contribute to them.

Risk of lung cancer in relation to various metrics of smoking history: a case-control study in Montreal

Background

Few epidemiologic findings are as well established as the association between smoking and lung cancer. It is therefore somewhat surprising that there is not yet a clear consensus about the exposure-response relationships between various metrics of smoking and lung cancer risk. In part this is due to heterogeneity of how exposure-response results have been presented and the relative paucity of published results using any particular metric of exposure. The purposes of this study are: to provide new data on smoking-lung cancer associations and to explore the relative impact of different dimensions of smoking history on lung cancer risk.

Methods

Based on a large lung cancer case-control study (1203 cases and 1513 controls) conducted in Montreal in 1996–2000, we estimated the lifetime prevalence of smoking and odds ratios in relation to several smoking metrics, both categorical and continuous based on multivariable unconditional logistic regression.

Results

Odds ratios (ORs) for ever vs never smoking were 7.82 among males and 11.76 among females. ORs increased sharply with every metric of smoking examined, more so for duration than for daily intensity. In models using continuous smoking variables, all metrics had strong effects on OR and mutual adjustment among smoking metrics did not noticeably attenuate the OR estimates, indicating that each metric carries some independent risk-related information. Among all the models tested, the one based on a smoking index that integrates several smoking dimensions, provided the best fitting model. Similar patterns were observed for the different histologic types of lung cancer.

Conclusions

This study provides many estimates of exposure-response relationships between smoking and lung cancer; these can be used in future meta-analyses. Irrespective of the histologic type of lung cancer and the smoking metric examined, high levels of smoking led to high levels of risk, for both men and women.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5144-5) contains supplementary material, which is available to authorized users.

Substance use through adolescence into early adulthood after childhood-diagnosed ADHD: findings from the MTA longitudinal study

BACKGROUND

Inconsistent findings exist regarding long-term substance use (SU) risk for children diagnosed with attention-deficit/hyperactivity disorder (ADHD). The observational follow-up of the Multimodal Treatment Study of Children with ADHD (MTA) provides an opportunity to assess long-term outcomes in a large, diverse sample.

METHODS

Five hundred forty-seven children, mean age 8.5, diagnosed with DSM-IV combined-type ADHD and 258 classmates without ADHD (local normative comparison group; LNCG) completed the Substance Use Questionnaire up to eight times from mean age 10 to mean age 25.

RESULTS

In adulthood, weekly marijuana use (32.8% ADHD vs. 21.3% LNCG) and daily cigarette smoking (35.9% vs. 17.5%) were more prevalent in the ADHD group than the LNCG. The cumulative record also revealed more early substance users in adolescence for ADHD (57.9%) than LNCG (41.9%), including younger first use of alcohol, cigarettes, marijuana, and illicit drugs. Alcohol and nonmarijuana illicit drug use escalated slightly faster in the ADHD group in early adolescence. Early SU predicted quicker SU escalation and more SU in adulthood for both groups.

CONCLUSIONS

Frequent SU for young adults with childhood ADHD is accompanied by greater initial exposure at a young age and slightly faster progression. Early SU prevention and screening is critical before escalation to intractable levels.

Early Life Exposures and Adult Cancer Risk

Very little is known about the influence of early life exposures on adult cancer risk. The purpose of this narrative review was to summarize the epidemiologic evidence relating early life tobacco use, obesity, diet, and physical activity to adult cancer risk; describe relevant theoretical frameworks and methodological strategies for studying early life exposures; and discuss policies and research initiatives focused on early life. Our findings suggest that in utero exposures may indirectly influence cancer risk by modifying biological pathways associated with carcinogenesis; however, more research is needed to firmly establish these associations. Initiation of exposures during childhood and adolescence may impact cancer risk by increasing duration and lifetime exposure to carcinogens and/or by acting during critical developmental periods. To expand the evidence base, we encourage the use of life course frameworks, causal inference methods such as Mendelian randomization, and statistical approaches such as group-based trajectory modeling in future studies. Further, we emphasize the need for objective exposure biomarkers and valid surrogate endpoints to reduce misclassification. With the exception of tobacco use, there is insufficient evidence to support the development of new cancer prevention policies; however, we highlight existing policies that may reduce the burden of these modifiable risk factors in early life.

Greater Coronary Heart Disease Risk With Lower Intensity and Longer Duration Smoking Compared With Higher Intensity and Shorter Duration Smoking: Congruent Results Across Diverse Cohorts

INTRODUCTION

Relative risks (RRs) for coronary heart disease (CHD) by cigarettes/day exhibit a concave pattern, implying the RR increase with each additional cigarette/day consumed decreases with greater intensity. Interpreting this pattern faces limitations, since cigarettes/day alone does not fully characterize smoking-related exposure. A more complete understanding of smoking and CHD risk requires a more comprehensive representation of smoking.

METHODS

Using Poisson regression, we applied a RR model in pack-years and cigarettes/day to analyze two diverse cohorts, the US Agricultural Health Study, with 4396 CHD events and 1 425 976 person-years of follow-up, and the Finnish Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study, with 5979 CHD events and 486 643 person-years.

RESULTS

In both cohorts, the concave RR pattern with cigarettes/day was consistent with cigarettes/day modifying a linear RR association for CHD by pack-years within categories of cigarettes/day, indicating that strength of the pack-years association depended on cigarettes/day (p < .01). For example, at 50 pack-years (365 000 total cigarettes), estimated RRs of CHD were 2.1 for accrual at 20 cigarettes/day and 1.5 for accrual at 50 cigarettes/day.

CONCLUSIONS

RRs for CHD increased with pack-years with smoking intensities affecting the strength of association. For equal pack-years, smoking fewer cigarettes/day for longer duration was more deleterious than smoking more cigarettes/day for shorter duration. We have now observed inverse smoking intensity effects in multiple cohorts with differing smoking patterns and other characteristics, suggesting a common underlying phenomenon.

IMPLICATIONS

Risk of CHD increases with pack-years of smoking, but accrual intensity strongly influences the strength of the association, such that smoking fewer cigarettes/day for longer duration is more deleterious than smoking more cigarettes/day for shorter duration. This observation offers clues to better understanding biological mechanisms, and reinforces the importance of cessation rather than smoking less to reduce CHD risk.

Synergistic and Non-synergistic Associations for Cigarette Smoking and Non-tobacco Risk Factors for Cardiovascular Disease Incidence in the Atherosclerosis Risk In Communities (ARIC) Study

INTRODUCTION

Cigarette smoking, various metabolic and lipid-related factors and hypertension are well-recognized cardiovascular disease (CVD) risk factors. Since smoking affects many of these factors, use of a single imprecise smoking metric, for example, ever or never smoked, may allow residual confounding and explain inconsistencies in current assessments of interactions.

METHODS

Using a comprehensive model in pack-years and cigarettes/day for the complex smoking-related relative risk (RR) of CVD to reduce residual confounding, we evaluated interactions with non-tobacco risk factors, including additive (non-synergistic) and multiplicative (synergistic) forms. Data were from the prospective Atherosclerosis Risk in Communities (ARIC) Study from four areas of the United States recruited in 1987-1989 with follow-up through 2008. Analyses included 14 127 participants, 207 693 person-years and 2857 CVD events.

RESULTS

Analyses revealed distinct interactions with smoking: including statistical consistency with additive (body mass index [BMI], waist to hip ratio [WHR], diabetes mellitus [DM], glucose, insulin, high density lipoproteins [HDL] and HDL(2)); and multiplicative (hypertension, total cholesterol [TC], low density lipoproteins [LDLs], apolipoprotein B [apoB], TC to HDL ratio and HDL(3)) associations, as well as indeterminate (apolipoprotein A-I [apoA-I] and triglycerides) associations.

CONCLUSIONS

The forms of the interactions were revealing but require confirmation. Improved understanding of joint associations may help clarify the public health burden of smoking for CVD, links between etiologic factors and biological mechanisms, and the consequences of joint exposures, whereby synergistic associations highlight joint effects and non-synergistic associations suggest distinct contributions.

IMPLICATIONS

Joint associations for cigarette smoking and non-tobacco risk factors were distinct, revealing synergistic/multiplicative (hypertension, TC, LDL, apoB, TC/HDL, HDL(3)), non-synergistic/additive (BMI, WHR, DM, glucose, insulin, HDL, HDL(2)) and indeterminate (apoA-I and TRIG) associations. If confirmed, these results may help better define the public health burden of smoking on CVD risk and identify links between etiologic factors and biologic mechanisms, where synergistic associations highlight joint impacts and non-synergistic associations suggest distinct contributions from each factor.

Risk of Cardiovascular Disease from Cumulative Cigarette Use and the Impact of Smoking Intensity

BACKGROUND

Relative risks (RRs) for cardiovascular disease (CVD) by smoking rate exhibit a concave pattern, with RRs in low rate smokers exceeding a linear extrapolation from higher rate smokers. However, cigarettes/day does not by itself fully characterize smoking-related risks. A reexamination of the concave pattern using a comprehensive representation of smoking may enhance insights.

METHODS

Data were from the Atherosclerosis Risk in Communities (ARIC) Study, a prospective cohort enrolled in four areas of the US in 1987-1989. Follow-up was through 2008. Analyses included 14,233 participants, 245,915 person-years, and 3,411 CVD events.

RESULTS

The concave RRs with cigarettes/day were consistent with cigarettes/day modifying a linear RR association of pack-years with CVD (i.e., strength of the pack-years association depended on cigarettes/day, indicating that the manner of pack-years accrual impacted risk). Smoking fewer cigarettes/day for longer duration was more deleterious than smoking more cigarettes/day for shorter duration (P < 0.01). For 50 pack-years (365,000 cigarettes), estimated RRs of CVD were 2.1 for accrual at 20 cigarettes/day and 1.6 for accrual at 50 cigarettes/day. Years since smoking cessation did not alter the diminishing strength of association with increasing cigarettes/day. Analyses that accounted for competing risks did not affect findings.

CONCLUSION

Pack-years remained the primary determinant of smoking-related CVD risk; however, accrual influenced RRs. For equal pack-years, smoking fewer cigarettes/day for longer duration was more deleterious than smoking more cigarettes/day for shorter duration. This observation provides clues to better understanding the biological mechanisms, and reinforces the importance of cessation rather than smoking less to reduce CVD risk.

The Effects of Viral Load Burden on Pregnancy Loss among HIV-Infected Women in the United States

Background. To evaluate the effects of HIV viral load, measured cross-sectionally and cumulatively, on the risk of miscarriage or stillbirth (pregnancy loss) among HIV-infected women enrolled in the Women's Interagency HIV Study between 1994 and 2013. Methods. We assessed three exposures: most recent viral load measure before the pregnancy ended, log₁₀ copy-years viremia from initiation of antiretroviral therapy (ART) to conception, and log₁₀ copy-years viremia in the two years before conception. Results. The risk of pregnancy loss for those with log₁₀ viral load >4.00 before pregnancy ended was 1.59 (95% confidence interval (CI): 0.99, 2.56) times as high as the risk for women whose log₁₀ viral load was ≤1.60. There was not a meaningful impact of log₁₀ copy-years viremia since ART or log₁₀ copy-years viremia in the two years before conception on pregnancy loss (adjusted risk ratios (aRRs): 0.80 (95% CI: 0.69, 0.92) and 1.00 (95% CI: 0.90, 1.11), resp.). Conclusions. Cumulative viral load burden does not appear to be an informative measure for pregnancy loss risk, but the extent of HIV replication during pregnancy, as represented by plasma HIV RNA viral load, predicted loss versus live birth in this ethnically diverse cohort of HIV-infected US women.

Rethinking cumulative exposure in epidemiology, again

The use of cumulative exposure, the product of intensity and duration, has enjoyed great popularity in epidemiology of chronic diseases despite numerous known caveats in its interpretation. We briefly review the history of use of cumulative exposure in epidemiology and propose an alternative method for relating time-integrated exposures to health risks. We argue, as others before us have, that cumulative exposure metrics obscures the interplay of exposure intensity and duration. We propose to use a computationally simple alternative in which duration and intensity of exposure are modelled as a main effect and their interaction, cumulative exposure, only be added if there is evidence of deviation from this additive model. We also consider the Lubin-Caporaso model of interplay of exposure intensity and duration. The impact of measurement error in intensity on model selection was also examined. The value of this conceptualization is demonstrated using a simulation study and further illustrated in the context of respiratory health and occupational exposure to latex dust. We demonstrate why cumulative exposure has been so popular because the cumulative exposure metric per se gives a robust answer to the existence of an association, regardless of the underlying true mechanism of disease. Treating cumulative exposure as the interaction of main effects of exposure duration and intensity enables epidemiologists to derive more information about mechanism of disease then fitting cumulative exposure metric by itself, and without the need to collect additional data. We propose that the practice of fitting duration, intensity and cumulative exposure separately to epidemiologic data should lead to conceptualization of cumulative exposure as interaction of main effects of duration and intensity of exposure.

Invited commentary: is it time to retire the "pack-years" variable? Maybe not!

Cumulative exposure--the product of intensity and duration for a constant exposure rate or its integral over time if variable--has been widely used in epidemiologic analyses of extended exposures, for example, the "pack-years" variable for tobacco smoking. Although the effects of intensity and duration are known to differ for exposures like smoking and ionizing radiation and simple cumulative exposure does not explicitly allow for modification by other time-related variables, such as age at exposure or time since exposure, the cumulative exposure variable has the merit of simplicity and has been shown to be one of the best predictors for many exposure-response relationships. This commentary discusses recent refinements of the pack-years variable, as discussed in this issue of the Journal by Vlaanderen et al. (Am J Epidemiol. 2014;179(3):290-298), in the broader context of general exposure-time-response relationships.