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The Cancer Intervention and Surveillance Modeling Network (CISNET) Lung Working Group age-period-cohort methodology to study smoking patterns can be applied to tackle important issues in tobacco control and public health. This paper summarizes the analyses of smoking patterns in the U.S. by race/ethnicity, educational attainment, and family income and for each of the 50 U.S. states using the CISNET Lung Working Group age-period-cohort approach. We describe how decision makers, policy advocates, and researchers can use the sociodemographic analyses in this supplement to project state smoking trends and develop effective state-level tobacco control strategies. The all-cause mortality RR estimates associated with smoking for U.S. race/ethnicity and education groups are also discussed in the context of research that measures and evaluates health disparities. Finally, the application of the CISNET Lung Working Group age-period-cohort methodology to Brazil is reviewed with a view to how the same types of analyses can be applied to other low- and middle-income countries. [ABSTRACT FROM AUTHOR]

Smoking prevalence has decreased considerably in Brazil from 34.8% in 1989 to 12.6% in 2019 owing to the implementation of strong tobacco control policies. However, recent data show that the downward trend may be stagnating. Detailed analyses of historical smoking patterns by birth cohort could guide tobacco control decision making in Brazil. Using the 2008 Global Adult Tobacco Survey and the 2013 and 2019 National Health Surveys, historical smoking patterns in Brazil were estimated, supplemented with data from the 2006‒2019 Surveillance System of Risk Factors for Chronic Diseases by Telephone Interviews. Age‒period‒cohort models with constrained natural splines were applied to estimate the annual probabilities of smoking initiation and cessation, current smoker prevalence, and mean cigarettes smoked per day by age, gender, and birth cohort. Analysis was conducted in 2021‒2022. Current smoker prevalence has declined considerably since the 1950 and 1955 birth cohorts for males and females, respectively, reflecting decreased smoking initiation and increased smoking-cessation probabilities over time. Among female cohorts born on or after 2000, smoking initiation may be increasing even as their smoking cessation has increased considerably. Mean cigarettes smoked per day has remained relatively constant across period and cohorts, showing only a minor decrease among males. These detailed cohort-specific smoking parameters can be used to inform models that evaluate the impact of tobacco use and policies on long-term health outcomes and guide public health decision making in Brazil. Stagnant mean cigarettes smoked per day, increasing female smoking initiation, and limited improvement in male cessation among recent cohorts present challenges to tobacco control. [ABSTRACT FROM AUTHOR]

Introduction: Experts recommend integrating smoking-cessation treatments within U.S. mental health settings, but the population health benefits of doing so have not been estimated. This study simulates the impact of widespread cessation treatment for patients with depression under best-case treatment and maximum potential cessation scenarios.Methods: Cessation interventions were simulated for U.S. adult smokers seeing a health professional for depression from 2020 to 2100. Interventions included (1) Any Treatment (behavioral counseling, pharmacological, combination) and (2) Pharmacological Treatment (including counseling), combined with increased mental health service utilization each. These were compared with a maximum potential cessation scenario where all patients with major depression quit smoking. Analyses were conducted in 2016-2020.Results: Widespread uptake of Any Treatment among patients with depression would avert 32,000 deaths and result in 138,000 life-years gained by 2100; Any Treatment combined with 100% mental health service utilization would result in 53,000 and 231,000, respectively. Pharmacological Treatment would avert 125,000 deaths, with 540,000 life-years gained. Pharmacological Treatment combined with 100% mental health service utilization would result in 203,000 deaths averted and 887,000 life-years gained. Health gains under best-case treatment scenarios represent modest fractions of those projected under maximum potential cessation scenarios at current mental health service utilization levels (835,000 deaths averted, 3.73 million life-years gained) and at 100% utilization (1.11 million deaths averted, 5.07 million life years gained).Conclusions: Providing smoking-cessation treatment to patients with depression and increasing mental health service utilization would reduce the toll of tobacco on this population. These gains would be considerably larger if cessation treatments were more effective. [ABSTRACT FROM AUTHOR]

Introduction: Simulation models can improve measurement and understanding of mental health conditions in the population. Major depressive episodes are a common and leading cause of disability but are subject to substantial recall bias in survey assessments. This study illustrates the application of a simulation model to quantify the full burden of major depressive episodes on population health in the U.S.Methods: A compartmental model of major depressive episodes that explicitly simulates individuals' under-reporting of past episodes was developed and calibrated to 2005-2017 National Surveys on Drug Use and Health data. Parameters for incidence of a first major depressive episode and the probability of under-reporting past episodes were estimated. Analysis was conducted from 2017 to 2019.Results: The model estimated that 30.1% of women (95% range: 29.0%-32.5%) and 17.4% of men (95% range: 16.7%-18.8%) have lifetime histories of a major depressive episode after adjusting for recall error. Among all adults, 13.1% of women (95% range: 8.1%-16.5%) and 6.6% of men (95% range: 4.0%-8.3%) failed to report a past major depressive episode. Under-reporting of a major depressive episode history in adults aged >65 years was estimated to be 70%.Conclusions: Simulation models can address knowledge gaps in disease epidemiology and prevention and improve surveillance efforts. This model quantifies the under-reporting of major depressive episodes and provides parameter estimates for future research. After adjusting for under-reporting, 23.9% of adults have a lifetime history of major depressive episodes, which is much higher than based on self-report alone (14.0%). Far more adults would benefit from depression prevention strategies than what survey estimates suggest. [ABSTRACT FROM AUTHOR]

Introduction: There is concern that youth e-cigarette use may serve as a gateway to cigarette smoking, and that nicotine exposure may harm brain development. It is therefore important to know how much nonsmoking youth perceive being exposed to nicotine through e-cigarettes.Methods: Data on smoking and vaping from the 2016 Monitoring the Future survey of eighth, tenth, and 12th grade students were analyzed in 2017. The weighted percentage distributions of self-reported e-cigarette mist last inhaled were calculated according to ever-smoking status and past 30-day smoking frequency. Chi-square tests of the association between smoking status and use of e-cigarettes perceived to contain nicotine, marijuana or hash oil, or just flavoring were performed. Never smokers and regular smokers were compared regarding the type of e-cigarette mist they believe they last used.Results: A significant relationship exists between smoking behavior and reportedly vaping nicotine (p<0.01) or just flavors (p<0.01). With increasing smoking intensity, an increasing proportion of students report they are vaping nicotine; a decreasing proportion report just flavors. Among 12th graders, prevalence of vaping nicotine is lowest among never smokers and non-current smokers (14.3% and 18.1%) and highest among current and frequent smokers (61.3% and 60.9%, p<0.01). Substantially larger proportions of never smokers and 30-day nonsmokers report vaping just flavors (76.0% and 69.6%) compared with regular or frequent smokers (31.0% and 29.3%, p<0.01).Conclusions: Most nonsmoking students perceive limited nicotine exposure from vaping. Future research should evaluate the accuracy of self-reported e-cigarette nicotine content and monitor students who are consciously using nicotine-based e-cigarettes. [ABSTRACT FROM AUTHOR]

Introduction: People with serious mental illness experience substantially reduced life expectancy, likely due in part to their higher smoking rates relative to the general population. However, the extent to which smoking affects their life expectancy, independent of mental illness, is unknown. This study quantifies the potential contribution of smoking to reduced life expectancy among individuals with serious psychological distress (SPD), a measure that screens for serious mental illness in national surveys.Methods: A cohort of 328,110 U.S. adults was examined using the 1997-2009 National Health Interview Surveys linked to the 2011 National Death Index. Cox models were used to estimate mortality hazard ratios for current smoking, former smoking, and SPD and construct life tables by smoking and SPD status. The smoking-attributable fraction of deaths by SPD status was calculated. Analyses were conducted in 2015.Results: Among those with SPD, being a current smoker doubles the risk of death. Current smokers with SPD lose 14.9 years of life relative to never smokers without SPD. Among never smokers, having SPD reduces life expectancy by 5.3 years. Thus, smoking may account for up to two thirds of the difference in life expectancy between smokers with SPD and never smokers without SPD. One third of deaths among those with SPD can be attributed to smoking.Conclusions: The life expectancy difference between current smokers with SPD and never smokers without SPD is primarily due to smoking. Aiding individuals with serious mental illness to avoid smoking will translate into sizeable gains in life expectancy. [ABSTRACT FROM AUTHOR]

Little is known about how U.S. smoking patterns of initiation, cessation, and intensity vary by birth cohort across education levels or how these patterns may be driven by other demographic characteristics. Smoking data for adults aged ≥25 years was obtained from the National Health Interview Surveys 1966–2018. Age-period-cohort models were developed to estimate the probabilities of smoking initiation, cessation, intensity, and prevalence by age, cohort, calendar year, and gender for education levels: ≤8th grade, 9th–11th grade, high school graduate or GED, some college, and college degree or above. Further analyses were conducted to identify the demographic factors (race/ethnicity and birthplace) that may explain the smoking patterns by education. Analyses were conducted in 2020–2021. Smoking disparities by education have increased by birth cohort. In recent cohorts, initiation probabilities were highest among individuals with 9th–11th-grade education and lowest among individuals with at least a college degree. Cessation probabilities were higher among those with higher education. Current smoking prevalence decreased over time across all education groups, with important differences by gender. However, it decreased more rapidly among individuals with ≤8th grade education, resulting in this group having the second lowest prevalence in recent cohorts. This may be driven by the increasing proportion of non-U.S. born Hispanics in this group. Although smoking is decreasing by cohort across all education groups, disparities in smoking behaviors by education have widened in recent cohorts. Demographic changes for the ≤8th-grade education group need special consideration in analyses of tobacco use by education. [ABSTRACT FROM AUTHOR]

Introduction: Youth e-cigarette use has been rising, however U.S. prevalence data are generally reported without disaggregating by individuals' use of other tobacco products. It is not clear how the proportion of youth e-cigarette users naïve to all combustible tobacco is changing.Methods: Annual prevalence estimates of ever and current (defined as past 30-day use) tobacco use prevalence by school type are reported using the 2014-2019 National Youth Tobacco Surveys (NYTS) with mutually exclusive categories of e-cigarette, smokeless tobacco, and/or combustible tobacco product use. T-tests were used to compare annual estimates with the preceding year. The annual percent change (APC) for each category from 2014 to 2018 were analyzed using JoinPoint regression. Data for 2019 were reported separately due to the change in survey format from paper to electronic.Results: Current use of only e-cigarettes among HS students who never used combustible tobacco increased significantly from 2014 to 2018 (APC = +42.4%, 95% CI: 0.7, 101.3); by 2019, prevalence peaked at 9.2% (95% CI: 8.2, 10.2) among never combustible users and 8.3% (95% CI: 7.3, 9.3) among former combustible users. This coincided with significant declines in use of only combustible tobacco (APC = -14.5%, 95% CI: -18.3, -10.5).Conclusions: Use of only e-cigarettes among US youth with no history of combustible tobacco use has increased substantially over time, even as combustible tobacco use continues to decline. Of the 17.5% (95% CI: 15.7, 19.0) of HS students who currently used only e-cigarettes (but not other tobacco) in 2019, more than half have no history of combustible tobacco use. [ABSTRACT FROM AUTHOR]

The impact of cigarette smoking on mortality is well studied, with estimates of the relative mortality risks for the overall population widely available. However, age-specific mortality estimates for different sociodemographic groups in the U.S. are lacking. Using the 1987–2018 National Health Interview Survey Linked Mortality Files through 2019, all-cause mortality relative risks (RRs) were estimated for current smokers or recent quitters and long-term quitters compared with those for never smokers. Stratified Cox proportional hazards regression models were used to estimate RRs by age, gender, race/ethnicity, and educational attainment. RRs were also assessed for current smokers or recent quitters by smoking intensity and for long-term quitters by years since quitting. The analysis was conducted in 2021–2022. All-cause mortality RRs among current smokers or recent quitters were generally highest for non-Hispanic White individuals than for never smokers, followed by non-Hispanic Black individuals, and were lowest for Hispanic individuals. RRs varied greatly by educational attainment; generally, higher-education groups had greater RRs associated with smoking than lower-education groups. Conversely, the RRs by years since quitting among long-term quitters did not show clear differences across race/ethnicity and education groups. Age-specific RR patterns varied greatly across racial/ethnic and education groups as well as by gender. Age-specific all-cause mortality rates associated with smoking vary considerably by sociodemographic factors. Among high-education groups, lower underlying mortality rates for never smokers result in correspondingly high RR estimates for current smoking. These estimates can be incorporated in modeling analyses to assess tobacco control interventions' impact on smoking-related health disparities between different sociodemographic groups. [ABSTRACT FROM AUTHOR]

U.S. smoking prevalence varies greatly by race/ethnicity. However, little is known about how smoking initiation, cessation, and intensity vary by birth cohort and race/ethnicity. Adult smoking data were obtained from the 1978–2018 National Health Interview Surveys. Age‒period‒cohort models with constrained natural splines were developed to estimate historical smoking patterns among non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic Asian and Pacific Islander, and non-Hispanic American Indian and Alaskan Native individuals. Annual smoking prevalence and probabilities of smoking initiation, cessation, and intensity by age, year, gender, and race/ethnicity were estimated for the 1900 to 2000 birth cohorts. Analysis was conducted in 2020–2021. Smoking initiation probabilities were highest for the American Indian and Alaskan Native population, second highest among the non-Hispanic White population, and lowest among Asian and Pacific Islander and Hispanic populations across birth cohorts. Historically, initiation probabilities among non-Hispanic Black populations were comparable with those among non-Hispanic White populations but have decreased since the 1970 birth cohort. Cessation probabilities were lowest among American Indian and Alaskan Native and non-Hispanic Black populations and highest among non-Hispanic White and Asian and Pacific Islander populations across cohorts and ages. Initiation and cessation probabilities produce observed patterns of smoking where prevalence among American Indian and Alaskan Native populations is highest across all ages and cohorts. Across cohorts, smoking prevalence among non-Hispanic Black populations, particularly males, is lower than among non-Hispanic White populations at younger ages but higher at older ages. There are important and persistent racial/ethnic differences in smoking prevalence, initiation, cessation, and intensity across U.S. birth cohorts. Targeted interventions should address widening smoking disparities by race/ethnicity, particularly for American Indian and Alaskan Native and non-Hispanic Black populations. [ABSTRACT FROM AUTHOR]

Smoking rates across U.S. states have declined at different rates over time because some states have progressive tobacco control policies, whereas others have yet to adopt them. Therefore, each state has its own unique historical experience of smoking initiation, cessation, and prevalence. This study characterizes smoking histories for each U.S. state by birth cohort. Using 1965–2018 National Health Interview Survey and 1992–2019 Tobacco Use Supplement to the Current Population Survey data, statistical methods applied an age‒period‒cohort modeling framework to reconstruct population-level smoking histories for each state. Smoking initiation, cessation, and intensity by age, gender, and cohort were estimated for each state. These were used to construct state-specific trends in the prevalence of current, former, and never smoking as well as the mean smoking duration and pack years. Analysis was conducted from 2017 to 2022. California and Kentucky, respectively, are exemplar states of more and less aggressive tobacco control. Initiation probabilities were consistently lower in California than in Kentucky, and cessation probabilities were higher. Hence, the smoking prevalence derived from these parameters is higher in Kentucky. The intensity of cigarette smoking was higher in Kentucky than in California, yielding considerably higher estimated pack years when used with the other parameters. Summaries of smoking trends are given for all states. Smoking initiation, cessation, and intensity trends vary substantially across states, resulting in major differences in estimated smoking prevalence, duration, and pack years. Some states show improvements in smoking metrics over time with more recent birth cohorts, but others have shown very little. [ABSTRACT FROM AUTHOR]

In the U.S., low-income individuals generally smoke more than high-income individuals. However, detailed information about how smoking patterns differ by income, especially differences by birth cohort, is lacking. Using the National Health Interview Survey 1983–2018 data, individual family income was calculated as a ratio of the federal poverty level. Missing income data from 1983 to 1996 were imputed using sequential regression multivariate imputation. Age‒period‒cohort models with constrained natural splines were used to estimate annual probabilities of smoking initiation and cessation and smoking prevalence and intensity by gender and birth cohort (1900–2000) for 5 income groups: <100%, 100%–199%, 200%–299%, 300%–399%, and ≥400% of the federal poverty level. Analysis was conducted in 2020–2021. Across all income groups, smoking prevalence and initiation probabilities are decreasing by birth cohort, whereas cessation probabilities are increasing. However, relative differences between low- and high-income groups are increasing markedly, such that there were greater declines in prevalence among those in high-income groups in more recent cohorts. Smoking initiation probabilities are lowest in the ≥400% federal poverty level group for males across birth cohorts, whereas for females, this income group has the highest initiation probabilities in older cohorts but the lowest in recent cohorts. People living below the federal poverty level have the lowest cessation probabilities across cohorts. Smoking prevalence has been decreasing in all income groups; however, disparities in smoking by family income are widening in recent birth cohorts. Future studies evaluating smoking disparities should account for cohort differences. Intervention strategies should focus on reducing initiation and improving quit success among low-income groups. [ABSTRACT FROM AUTHOR]

Highlights: [•] We have developed a present day ecosystem model for the Taputeranga MR. [•] We have historically reconstructed the ecosystem state prior to commercial fishing. [•] We have run future simulations to predict ecosystem response to marine protection. [•] The keystone role of lobster has changed since historical times due to fishing. [•] The Taputeranga MR is predicted to return the ecosystem to a more historical state. [Copyright &y& Elsevier]