Associations between e-cigarette and combustible cigarette use among U.S. cancer survivors: implications for research and practice

Association between adverse childhood experiences and self-reported health-risk behaviors among cancer survivors: A population-based study

AIMS

Existing evidence shows that people who report Adverse Childhood Experiences (ACEs) are more likely to exhibit health-risk behaviors. However, limited research on this topic pertains to oncology population. We aim to address this knowledge gap by estimating the prevalence of ACEs and investigating their association with self-reported health-risk behaviors among adult cancer survivors living in the U.S.

METHODS

We conducted a secondary analysis using cross-sectional data from the 2021 Behavioral Risk Factor Surveillance System ACE module. We included 4,126 adults, aged ≥18 years, with a history of cancer. The outcome variable was self-reported health-risk behaviors, which included cigarette smoking, e-cigarette use, and binge alcohol drinking. Self-reported ACEs history was the primary independent variable, comprised of 11 questions regarding child abuse and dysfunctional households. We conducted descriptive statistics and multivariable logistic regression to describe the relationship between the ACE history and health-risk behaviors.

RESULTS

Overall, 84.2% of cancer survivors self-reported as White, 58.4% were women, and 76.6% were aged 65+ years. Nearly two-thirds of the sample (63.2%) self-reported at least one ACE (prior to age 18) and 21.7% engaged in ≥1 health-risk-behaviors, such as cigarette smoking, binge alcohol drinking, or e-cigarette use. Experiencing ≥3 ACEs was associated with 145% increased odds of reporting at least one health-risk behavior (OR = 2.45, 95% CI [1.78-3.38]) when compared to those without a history of ACEs. Besides, survivors who were younger, divorced, less educated, and had low income had higher odds of reporting at least one health-risk behavior.

CONCLUSIONS

Overall, a history of ACEs is associated with health-risk behaviors. These all can negatively impact cancer survivors' overall well-being. Early screening for ACE during oncologic visits can be a protective measure for preventing health-risk behaviors among cancer survivors.

Association between e-cigarette use and depression in US cancer survivors: a cross-sectional study

PURPOSE

Though prior studies have observed significant association between e-cigarette use and mental health outcomes including depression in the general population, the relationship between e-cigarette use and clinical depression in the cancer survivor subpopulation is unknown. The purpose of this study was to examine the cross-sectional association between e-cigarette use and self-reported clinical depression among cancer survivors.

METHODS

Pooled data from the 2017 and 2018 Behavioral Risk Factor Surveillance Survey were used. Multivariable logistic regression was used to analyze the independent association between e-cigarette use and self-reported clinical depression in a sample of 7,498 cancer survivors.

RESULTS

Among cancer survivors in this study, 22.1% reported a history of clinical diagnosis of depression. The overall prevalence rates for current and former e-cigarette use were 2.6% and 10.5%, respectively. Analysis showed 51.3% of current users, 40% of former users, and 19.1% of those who had never used e-cigarettes self-reported a history of clinical depression. In the multivariable analysis, the odds of self-reported clinical depression were significantly higher for survivors who were current users (OR = 2.85; 95% CI: 1.38-5.90) and former users (OR = 1.63; 95% CI: 1.05-2.55) compared to never e-cigarette users.

CONCLUSION

Findings from this study suggest a statistically significant association between e-cigarette use and depression in cancer survivors. Future studies should focus on examining the longitudinal association between e-cigarette use and depression in cancer survivors.

IMPLICATIONS FOR CANCER SURVIVORS

Study findings reemphasized the need for interventions to support cancer survivors with evidence-based treatments for depression as well as the need for clinicians to screen for psychological distress and/or e-cigarette use and make appropriate recommendations.

Smoking Behaviors Among Black and Hispanic Cancer Patients: A Systematic Review of the Literature

Smoking is the leading cause of preventable disease and death in the United States. The risk of smoking poses an even greater threat for racial/ethnic minorities, particularly Black and Hispanic cancer patients who face a range of existing disparities in healthcare. Despite these risks for poor health outcomes among this population, little is known about the smoking behaviors of Black and Hispanic cancer patients. The purpose of this review was to understand differences in smoking prevalence, intensity, and cessation between Black, Hispanic, and non-Hispanic White cancer patients and survivors. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach as our framework, we conducted a systematic review of the literature. Our review discusses the methods, population, and implications of 37 included articles. Conclusions reflect the need to establish intentional and systematic measurement of smoking behaviors to best understand the risks of smoking among Black and Hispanic cancer patients.

Associations between Cigarette Smoking and Health-Related Quality of Life in Adult Survivors of Adolescent and Young Adult Cancer

This cross-sectional, secondary data analysis examines the association between cigarette smoking and self-reported health-related quality of life (HRQoL) in adult survivors of Adolescent and Young Adult Cancer. Pooled data for survivors of Adolescent and Young Adult Cancer (N = 1495) were drawn from the 2016 and 2017 Behavioral Risk Factor Surveillance Survey. Binary logistic regression models were utilized to examine independent associations between each of the four HRQoL domains (i.e., self-related general health, activity limitation days, poor physical, and mental health days) and cigarette smoking. Of the 1495 Adolescent and Young Adult Onset Cancer Survivors (AYAO-CS) in this study, approximately 30% reported currently smoking cigarettes. Relative to never smokers, the odds of reporting fair/poor general health were significantly higher for current and former smokers: (OR = 3.95, 95% CI: 2.08-7.50) and (OR = 2.51, 95% CI: 1.46-4.32), respectively. Likewise, current smokers were significantly more likely to report frequent days of poor physical health (OR = 2.79, 95% CI: 1.38-5.65). The study findings suggest a significant cross-sectional association between cigarette smoking and poor health-related quality of life in adult survivors of adolescent and young adult cancer. These findings, although cross-sectional, underscore the need for prospective studies to examine the longitudinal association between HRQoL and cigarette smoking among cancer survivors. Findings also help establish both the need for smoking cessation programs and the importance of effective strategies for addressing HRQoL issues among cancer survivors.

Trends in frequency of e-cigarette use among cancer patients and survivors in the United States, 2014-2018

INTRODUCTION

Electronic cigarettes (e-cigarettes) have become increasingly popular in the United States, including among cancer survivors; however, the majority of prior studies do not report frequency of active e-cigarette usage.

METHODS

Using data from the National Health Interview Survey (2014-2018), frequency of active e-cigarette usage was estimated among cancer survivors reporting history of e-cigarette usage. Multivariable logistic regression analyses defined adjusted odds of active e-cigarette usage (either every day and some days vs. not at all) by year of survey and baseline demographic characteristics.

RESULTS

Among 1529 cancer survivors who reported ever using e-cigarettes, 1172 (76.7%) were not active users, while 145 (9.5%) and 212 (13.9%) actively used e-cigarettes every day or some days, respectively. Later year of survey was negatively associated with active e-cigarette usage (p < 0.001) as was Black race (as compared to white race, AOR 0.47, p = 0.02). Age 45-54 was positively associated with active usage (as compared to 18-34 years, AOR 1.58, p = 0.02). Notably, individuals who were former or current traditional cigarette smokers had greater odds of reporting active e-cigarette use (27.0%, AOR 4.39, p < 0.001, 23.4%, AOR 3.28, p = 0.002, respectively) as compared to never traditional cigarette smokers (7.6%).

CONCLUSIONS

The majority of cancer survivors who have ever used e-cigarettes do not appear to be actively using them. Rather, our findings suggest that the reported increasing popularity of e-cigarettes may be driven by a growing absolute proportion of individuals trying e-cigarettes over time. Those who were current or former traditional cigarette smokers were more likely to actively use e-cigarettes. Our findings can help inform current policies on e-cigarettes and contextualize studies on long-term effects of e-cigarettes among survivors of cancer.

E-cigarette and cigarette use among cancer survivors versus general population: a case-control study in Korea

PURPOSE

Although successful smoking cessation after cancer diagnosis is important, research on e-cigarette use and smoking behavior among cancer survivors (CS) is limited. This study compared cigarette and e-cigarette use among CS and non-cancer populations in Korea.

METHODS

This study analyzed the 2013-2018 National Health and Nutrition Survey data to investigate e-cigarette use and smoking behavior among Korean CS. The data were categorized into 1260 CS and 5040 non-cancer populations using the propensity score matching method. A multiple logistic regression was conducted among CS who previously used cigarettes or e-cigarettes to evaluate factors influencing successful cessation.

RESULTS

Regarding conventional smoking, the proportion of ex-smokers was higher (25.2% versus 19.9%) than current smokers (6.7% versus 10.6%) in the CS group than in the propensity matched non-cancer population (PMNCP) (p < 0.001). However, ever use of e-cigarettes did not differ between them (2.4% versus 2.7%, p = 0.529). Successful cessation, defined as not using either cigarettes or e-cigarettes, correlated with problem drinking (OR 0.442, 95% CI 0.207-0.940), depression (OR 0.276, 95% CI 0.087-0.872), and cancer sites. CS of stomach, liver, colorectal, and lung cancer maintained higher successful smoking cessation rates than PMNCP.

CONCLUSIONS

Korean CS had a higher cessation rate than PMNCP regarding conventional smoking; however, there was no difference in e-cigarette use.

IMPLICATIONS FOR CANCER SURVIVORS

In Korea, some CS continue to use e-cigarettes, and physicians should focus on helping them quit. Individualized and timely interventions should be provided for both cigarette and e-cigarette users, considering factors influencing successful cessation.

Assessing Electronic Nicotine Delivery Systems Use at NCI-Designated Cancer Centers in the Cancer Moonshot-funded Cancer Center Cessation Initiative

Assessing tobacco product use and delivering tobacco dependence treatment is an essential part of cancer care; however, little is known about electronic nicotine delivery systems (ENDS) or e-cigarette use assessment in cancer treatment settings. Given the importance of tailoring tobacco treatment, it is critical to understand how ENDS use is assessed in the electronic health record (EHR) in cancer care settings. Two questionnaires were completed by tobacco treatment program leads at 42 NCI-Designated Cancer Centers in the Cancer Center Cessation Initiative (January 1 to June 30 and July 1 to December 31, 2019). Items assessed how often smoking status and ENDS use were recorded in the EHR. An open-ended item recorded the text and response categories of each center's ENDS assessment question. All 42 centers assessed smoking status at both time periods. Twenty-five centers (59.5%) assessed ENDS use in the first half of 2019, increasing to 30 (71.4%) in the last half of 2019. By the end of 2019, 17 centers assessed smoking status at every patient visit while six assessed ENDS use at every visit. A checkbox/drop-down menu rather than scripted text was used at 30 centers (73.2%) for assessing smoking status and at 18 centers (42.9%) for assessing ENDS use. Our findings underscore the gap in systematic ENDS use screening in cancer treatment settings. Requiring ENDS use measures in the EHR as part of quality measures and providing scripted text scripts to providers may increase rates of ENDS use assessment at more cancer centers. PREVENTION RELEVANCE: This study identifies a gap in the systematic assessment of ENDS use among patients seen at 42 NCI-Designated cancer centers. Requiring the systematic assessment of both ENDS use and use of other tobacco products can inform evidence-based treatment of tobacco dependence and lead to improved cancer treatment outcomes.

The characteristics of patients who quit smoking in the year following a cancer diagnosis

PURPOSE

Continued tobacco smoking following a cancer diagnosis is associated with adverse outcomes. Our study aims to identify the demographic and clinical characteristics of survivors who quit smoking within a year of diagnosis.

METHODS

We conducted a secondary analysis of the Measuring Your Health (MY-Health) study, a community-based survey cohort of 5506 cancer patients registered across four Surveillance, Epidemiology, and End Results (SEER) cancer registries. Using surveys completed 6-13 months after diagnosis, we identified 868 participants who reported smoking around the time of cancer diagnosis and compared their current smoking status. We employed logistic regression models to predict current smoking status, adjusting for clinical and demographic variables.

RESULTS

The overall smoking cessation rate was 35% (n = 306). Survivors with non-small cell lung cancer were three times more likely to quit smoking compared to patients with non-smoking-related cancers (aOR = 3.23, 95% CI = 2.20-4.74). Participants with advanced stage cancer reported higher odds of quitting compared to those with localized cancer (aOR = 1.42, 95% CI = 1.02-1.96). Other characteristics that predicted quitting included being married, higher education level, and female sex (aOR = 2.01, 95% CI = 1.46-2.77; aOR = 1.74, 95% CI = 1.27-2.39; aOR = 1.54, 95% CI = 1.11-2.13, respectively).

CONCLUSIONS

This is one of the first studies to examine smoking cessation trends in a community-based, US cancer cohort during the year after diagnosis. Survivors with lung cancer and advanced cancer were significantly more likely to quit smoking.

IMPLICATIONS FOR CANCER SURVIVORS

Practitioners may use this knowledge to target interventions and address substantial disparities in cessation rates among survivors with early stage and non-lung cancers.

Associations among marijuana use, health-related quality of life, exercise, depression and sleep in cancer survivors

AIMS

To assess associations among cannabis use, health-related quality of life, exercise, depression and sleep among a nationally representative sample of US adults living with cancer.

DESIGN

A cross-sectional correlational study.

METHODS

We used survey data from the 2016-2018 Behavioral Risk Factor Surveillance System. Analyses were considered for sample weights and the complex designs. Logistic regression was performed to assess associations among cannabis use (0, 1-19, vs. 20-30 [frequent] days), health-related quality of life (0-13 vs. ≥14 mentally or physically unhealthy days in the past 30 days; 0-13 vs. ≥14 functionally limited days), exercise, depression, and sleep after accounting for covariates. Reason for cannabis use (medical vs. non-medical) was also assessed.

RESULTS

Frequent users had significantly more physically unhealthy days (adjusted odds ratio [OR]: 1.79, 95% CI: 1.28-2.51, p < .01) and reported ≥ 14 mentally unhealthy days (adjusted OR: 2.43, 95% CI: 1.78-3.32, p < .001) and depression (adjusted OR: 2.65, 95% CI: 1.97-3.57, p < .001) compared with non-users. A positive relationship between frequency of cannabis use and depression existed only among non-medical cannabis users.

CONCLUSION

Cancer survivors using cannabis frequently (20 days+ in the past month) had poorer mental health-related quality of life. The reason for cannabis use as well as frequency of use may be important considerations in predicting depression.

IMPACT

This is the first study that evaluates the associations among cannabis use, the purpose of cannabis use, HRQoL, exercise, depression and sleep in a nationally representative sample of US adults living with cancer. Frequent cannabis users are likely vulnerable to poorer mental health-related quality of life and depression, and non-medical cannabis use in frequent users was associated with depression. Given expanding medical cannabis legalization, these findings warrant further attention so that this information can be used by people living with cancer in decision-making for symptom self-management.

Association between E-cigarette use and chronic obstructive pulmonary disease in non-asthmatic adults in the USA

BACKGROUND

Concern about the health impacts of e-cigarette use is growing; however, limited research exists regarding potential long-term health effects of this behavior. This study explored the relationship between e-cigarette use and COPD in a sample of US adults.

METHODS

A secondary data analysis using data from the 2018 Behavioral Risk Factor Surveillance Survey in the USA was computed to examine associations between e-cigarette use and COPD controlling for conventional cigarette smoking status, past month leisure physical activity and demographic characteristics including age, sex, education, race, marital status and body mass index.

RESULTS

Significant associations between e-cigarette use and COPD among former combustible cigarette smokers and those who reported never using combustible cigarettes were found. Compared with never e-cigarette users, the odds of having COPD were significantly greater for daily e-cigarette users (OR = 1.53; 95% CI: 1.11-2.03), occasional users (OR = 1.43, 95% CI: 1.13-1.80) and former users (OR = 1.46 95% CI: 1.28-1.67).

CONCLUSIONS

Findings from this study indicate a potential link between e-cigarette use and COPD. Further research to explore the potential effects of e-cigarette on COPD is recommended.

Prevalence and Factors Associated with Electronic Cigarette Use Among Young Adult Cancer Survivors Using Behavioral Risk Factor Surveillance System, 2016-2018

Purpose: This study describes the prevalence trends of electronic cigarette (e-cigarette) use in young adult cancer survivors and compares these to the prevalence among young adults without a cancer history. It also examines the association between conventional cigarette use, binge drinking, depression, and other sociodemographic factors, and e-cigarette use in young adult cancer survivors. Methods: Cross-sectional analyses, using the Behavioral Risk Factor Surveillance System, 2016-2018, were done. Multivariable logistic regression was used to examine the associations between conventional cigarette use, binge drinking, and depression as well as other factors associated with e-cigarette use in young adult cancer survivors. Results: Lifetime e-cigarette use increased from 40.1% in 2016 to 47.4% in 2018. Former smokers were 5.47 times (95% confidence interval [CI]: 3.48-8.61) more likely to be lifetime e-cigarette users and 1.9 times (95% CI: 1.12-3.23) more likely to be current e-cigarette users compared to never smokers. Current smokers were over sixteen folds more likely (adjusted odds ratio: 16.50, 95% CI: 11.59-23.57) to be lifetime e-cigarette users and 2.1 times (95% CI: 1.24-3.57) more likely to be current e-cigarette users relative to never smokers. Furthermore, binge drinking and depression were associated with higher odds of lifetime e-cigarette use, while increasing age was associated with lower odds of e-cigarette use. Compared to females, males were significantly more likely to be current users of e-cigarettes relative to former users. Conclusion: Conventional cigarette use, binge drinking, depression, age, and gender were found to be associated with e-cigarette use among young adult cancer survivors. Policies targeted at e-cigarette control among young adult cancer survivors need to be multipronged, simultaneously addressing other harmful practices such as binge drinking and the use of conventional cigarettes.

The effect of different tobacco tar levels on DNA damage in cigarette smoking subjects

Objective

To explore the genetic damage caused by different tar levels in the human body.

Methods

The subjects were divided into high, medium and low (12 mg, 8 mg, 5 mg) tar groups according to the tar levels. Nonsmoking populations served as a control group. 2 ml of peripheral blood was collected on the 10th day after morning fasting. Oxidative and genetic toxicological damage indicators were analysed with enzyme-linked immunosorbent assay, cytokinesis-block micronucleus assay in human lymphocyte and single cell gel electrophoresis.

Results

The distribution of hOGG1 concentration was significantly different within all groups, P < 0.01. The concentrations of cotinine, 8-OHdG and Rap-2b were significantly differences between control and medium tar group, control and high tar group, low and medium tar group and low and high tar group, respectively, P < 0.05. The level of PAH-DNA adducts was not significantly changed in the middle tar group and high tar group, P > 0.05. The level of CRP was significantly changed between control and high tar group, low and high tar group and medium and high tar group, respectively, P < 0.0001. The rate of comet tailing was significantly different between all groups. The rate of micronucleus cells was not significantly different between all groups.

Conclusions

The increase of tar content could increase the DNA damage to a certain extent, so the intake of tar content should be monitored.

Implementation of the Smoking Treatment and Recovery (STAR) program: healthy cancer survivorship through integrated tobacco control

PURPOSE

It is well-established that persistent tobacco use among patients with cancer results in numerous adverse outcomes. However, the assessment and treatment of tobacco use with evidence-based methods have been lacking in cancer care. Our cancer center has established its first tobacco treatment program, a multidisciplinary, evidence-based, clinical program for hematology/oncology patients.

METHODS

We describe the development and implementation of the program, emphasizing lessons learned in treating nicotine addiction among patients who are at very high risk for continuing to use tobacco throughout the survivorship phase.

RESULTS

We developed a system to assess tobacco use at each outpatient visit, from those recently diagnosed to long-term survivors. For patients who have smoked in the past month, the protocol offers standard behavioral and pharmacological treatments, delivered by tobacco treatment specialists and nurse practitioners over four in-person and/or telephone-based sessions. Partnerships with the Psychosocial Oncology and Cancer Survivorship Programs have provided integrated and comprehensive care for patients during and after their cancer treatment.

CONCLUSIONS

The systematic efforts to reach and engage current smokers have laid the groundwork for maximizing the program's future effectiveness and impact. Our initial results demonstrate not only the complexities but also the feasibility of developing a new tobacco treatment program in the oncology setting.

IMPLICATIONS FOR CANCER SURVIVORS

The implications for cancer survivors are the significant improvements in treatment outcomes that occur with tobacco abstinence.