Abstract
Objectives
To identify predictors of older adults’ likelihood of quitting following engagement in a proactive tobacco quit line.
Methods
Older (>60 years) participants (N = 186) enrolled in a four-session quit line with 8-weeks of nicotine replacement therapy reported demographics, beliefs, and information about tobacco use. Point prevalence abstinence was reported at 3 and 12-months.
Results
In final models, endorsement of quitting to take control of one’s life and confidence in quitting were positively associated with 3-month cessation (OR = 1.74, 95% CI = 1.16, 2.62; OR = 1.75, 95% CI = 1.21, 2.52, respectively). At 12 months, stronger endorsement of quitting to take control of one’s life and decreased nicotine dependence were associated with higher cessation (OR = 1.51, 95% CI = 1.05, 2.17; OR = 0.84, 95% CI = 0.71,0.99, respectively).
Discussion
For tobacco cessation among older adults, programs should provide additional support to those with higher nicotine dependence, promote quitting self-efficacy, and encourage quitting as means to gain control of life and health.
Approximately 14% of the U.S. population (i.e., 34.2 million adults) smoke cigarettes, and this use constitutes the leading cause of disease and preventable death (Cornelius et al., 2020; World Health Organization, 2019). Unlike other age groups, which have shown significant declines in cigarette prevalence since the first Surgeon’s General Report in 1964, rates among U.S. adults over age 65 years have not decreased [Cornelius et al., 2020; U.S. Department of Health and Human Services (US DHHS), 2014, 2020]. The lack of declining cigarette rates among older adults is concerning, given that this age group is more likely to be impacted by tobacco related morbidity and mortality than younger smokers (Mons et al., 2015; US DHHS, 2014). Despite the widely held misperception that quitting smoking does not benefit older adults (Kerr et al., 2006; Yong et al., 2005), smoking cessation has significant short-and long-term health advantages for this age group (Doll et al., 2004; US DHHS, 2020). Smoking cessation can enhance an individual’s quality of life by improving the quality of comorbid chronic health conditions and diminishing the financial burden of cigarettes (US DHHS, 2020). At any age, smoking cessation reduces the risk of developing or dying from many types of cancer (e.g., lung, pancreatic, kidney, cervical), as well as cardiovascular disease and stroke (US DHHS, 2020). In fact, cessation at age 60 can increase the life span by approximately 3 years (Doll et al., 2004).
Tobacco quit lines have been widely used as a cost-effective, telephone-based cessation intervention (Lichtenstein et al., 2010). While quit lines are convenient, diminish logistical barriers to care, and offer access to free cessation counseling (Lichtenstein et al., 2010), older adult smokers are less aware of quit lines than younger smokers (Kaufman et al., 2010; Kulak & LaValley, 2018) and are less likely to access a quit line compared to those in mid-life (Kulak & LaValley, 2018). One reason that older adults might be less likely to access a tobacco quit line is a lack of referral or education about this resource from medical providers. Prior research has found that older adults are less likely to receive advice or discuss tobacco cessation, as well as less likely to be referred to cessation counseling or prescribed NRT compared to younger adults in healthcare settings (Huddleston et al., 2015; Jordan et al., 2017; Kerr et al., 2006). Overall, the literature suggests that beyond brief advice, older medical patients are less likely to receive substantial education and support when trying to quit.
Although personalizing messages within cessation treatment improves quit rates (Krebs et al., 2010; Noar et al., 2007), cessation intervention trials are rarely tailored to older smokers (Chen & Wu, 2015; Doolan et al., 2008; Smith et al., 2019; Zbikowski et al., 2012). Cessation trials will sometimes examine age group differences in quitting outcomes, but even fewer report outcomes exclusively among older adults (Chen & Wu, 2015; Doolan et al., 2008; Smith et al., 2019; Zbikowski et al., 2012). Among this limited research, older adult samples typically include a wide age range (50 years of age and older) and rarely do studies examine smokers exclusively over 60 years (Chen & Wu, 2015; Doolan et al., 2008; Smith et al., 2019; Zbikowski et al., 2012). Part of the difficulty in examining cessation outcomes in this population lies in the lack of a clear and universal definition of older age. However, the World Health Organization recognizes that most developed countries define older age to be 60 or 65 years (Kowal and Dowd, 2001). Thus, a substantial limitation in the current literature is that rarely do cessation studies provide a sub-group analysis specifically for older adults. In summary, although the older adult population is expected to double between 2012 and 2050 (Ortman et al., 2019), the lack of inclusion of older smokers in cessation research is a product of systematic ageism and a barrier to health equity (McAfee et al., 2021).
In order to tailor treatment to be inclusive of the needs of older smokers, it is important to explore individual characteristics that facilitate higher quit rates within this population. Of the limited research in this area, across treatment modalities, factors such as concurrent use of nicotine replacement therapy (NRT) with cessation counseling, less nicotine dependence, less time smoking, higher educational background, female gender, more concern about health, and identifying more cons and less pros of smoking, are characteristics and beliefs that improved quit success (Chen & Wu, 2015; Ferketich et al., 2012; Hall et al., 2009; Hsu et al., 2018; Ossip-Klein et al., 1997; Tait et al., 2008; van der Aalst et al., 2012). Because of the changing tobacco landscape with increases in e-cigarettes or ENDS (electronic nicotine delivery system) use (Cornelius et al., 2020; US DHHS, 2016), it is important for more current trials to explore how newer products have impacted beliefs and likelihood of quitting cigarettes in this population. Further, although quit lines are a widely available and a cost-effective resource, no study explored predictors of quitting among older smokers enrolled in this type of intervention.
Thus, this study’s primary aim is to examine individual characteristics predicting successful quitting at the 3 and 12-month follow-ups of a tobacco quit line intervention specifically within a subsample of smokers ≥60 years of age. Second, in order to compare current findings to previous studies (Chen & Wu, 2015; Doolan et al., 2008; Smith et al., 2019; Zbikowski et al., 2012), we will compare cessation outcomes among older (≥60 years) versus younger (≤59 years) adults. Based on previous research, we hypothesize that less nicotine dependence, less time spent smoking, quitting to improve one’s health, and demographic factors (i.e., gender, educational background) will be factors related to quit success in this sample (Chen & Wu, 2015; Ferketich et al., 2012; Hall et al., 2009; Hsu et al., 2018; Ossip-Klein et al., 1997; Tait et al., 2008; van der Aalst et al., 2012). Results aim to provide information about how to tailor cessation interventions, particularly tobacco quit lines, to the unique needs of older adults in order to optimize cessation success in this population.
Methods
Parent Study Overview
The parent study evaluated the effectiveness of a quit line for smoking cessation (2015–2020) among TRICARE beneficiaries. TRICARE is the Department of Defense health care system and includes U.S. military active duty and coast guard, retirees, and family members. For more detailed information please see Little et al., (2017).
Recruitment
Participants were TRICARE beneficiaries (≥18 years of age) smoking five or more cigarettes per day for ≥1 year and who were able to read and speak English to understand consent procedures. Individuals in basic military training were excluded because this period includes an enforced tobacco ban and telephone access is not easily available. Beneficiaries who were unwilling to discontinue smoking cessation products [i.e., NRT (nicotine replacement therapy), Wellbutrin, or Chantix] were excluded, along with those who were pregnant, breastfeeding, or planning to become pregnant in the next year. Participants who reported unstable heart conditions or had mailing restrictions were enrolled in behavioral treatment only and not provided NRT.
Procedures
The parent study was approved by the 59th Medical Wing Institutional Review Board of the Department of Defense.
Baseline
At baseline, participants completed questionnaires about demographics, history of cigarette use and quit attempts, past use of cessation resources, current tobacco use, confidence to quit, beliefs about cessation and reasons for quitting. All participants received four proactive telephone sessions with a counselor within an 8-week period. The same counselor provided all four treatment sessions. Participants were also mailed 8 weeks of NRT patches (strength determined by smoking frequency at baseline). In four sessions of approximately 40 minutes each, counselors used motivational interviewing strategies to facilitate motivation and self-efficacy for smoking cessation ((Miller & Rollnick, 2012); Moyers et al., 2010). This collaborative style of intervention has been found to be effective for smoking cessation interventions (Heckman et al., 2010). All counselors received 100 hours of motivational interviewing training and participated in weekly supervision to maintain their skills (Moyers et al., 2010).
Three-month follow-up
At 3-months, individuals completed questionnaires about current use of use of nicotine and tobacco products. Those who relapsed or failed to quit (i.e., reported smoking even a puff of a cigarette in the last 7 days) were asked to re-engage with the intervention. Those who re-engaged were randomized using individualized block stratification to one of three arms: recycle, reduction, or choice condition. The recycle condition repeated the intervention with the same counselor with an additional 8 weeks of NRT (patch). Those in the rate reduction condition were enrolled in a three-session quit line intervention with the same counselor. These sessions focused on helping the participant to reduce the number of cigarettes smoked by 75% across the three sessions. Additionally, NRT in the form of the gum was provided for up to 16 weeks. Those randomized to the choice condition were informed about the rationale for both the recycle and rate reduction conditions and told they could choose one of the two.
Twelve-month follow-up
All participants who completed measures at baseline, regardless of re-engagement at 3-months, were contacted 9 months later for the 12-month follow-up and assess current tobacco use.
Measures
Baseline Measures
Demographics
Demographics included gender (women, men), race (White/Caucasian, individuals of non-White racial minority backgrounds), ethnicity (non-Hispanic/Latino, Hispanic/Latino), marital status (married/living as married versus widowed, divorced, separated, or never married), and highest level of education (high school diploma/GED versus some college/vocational training/associate degree or higher). Age was measured continuously, as well as categorized as older adults (aged ≥60 years) and younger adults (age range 18–59 years) depending on analysis. Military status was classified as (non-military TRICARE beneficiary and military beneficiary).
Cigarette use history
Participants reported how many years they had smoked cigarettes and completed the Fagerstrom Test for Nicotine Dependence, a six-item widely used and well-validated measure for nicotine dependence (Heatherton, et al., 1991). The six items from this measure were summed with scores ranging from (0) to (10), with higher numbers indicating more dependence.
Quitting history
Participants reported how many times they had tried to quit smoking cigarettes (for 24 hours or more) in the last 12 months. Number of previous quit attempts were classified as none, one time, two times or three or more.
Ever use of cessation resources
Participants reported ever use of NRT to help quit smoking (yes or no). Participants also reported ever use of e-cigarettes to quit smoking (yes or no). If yes, participants were asked if they were currently (yes or no) using e-cigarettes to quit. Additionally, participants reported if they had ever used any of the following alternative methods in a quit attempt (yes or no): Chantix, Zyban/Wellbutrin/Bupropion, group quit program, individual counseling or therapy to quit, internet quit smoking program, another tobacco quit line, or any other method (e.g., acupuncture, hypnosis).
Concurrent tobacco use
Other tobacco users were those who reported concurrent (in addition to cigarettes) past 30-day use of one or more of the following products: smokeless tobacco, snus, e-cigarettes, cigars, cigarillos/little cigars, pipe, hookah/water pipe, roll your own cigarettes.
Beliefs about cessation
Participants were asked, “How beneficial do you think quitting cigarettes is to your health?” based on item in previous research assessing predictors of quit outcomes (Hyland et al., 2006). Responses ranged from not at all to extremely. Responses were classified dichotomously as extremely versus all other responses.
Reasons for quitting
Participants were given options as reasons for cessation: to save money, I am getting pressure from others, so that my hair and clothes won’t smell, it is difficult to find a place to smoke, to improve my overall health, to be a good role model for others, so that I can be in control of my life, to improve my overall physical fitness, because smoking may have a negative effect on my career. Participants identified if these reasons were not at all true (1) to extremely true (5) for a reason they wanted to quit (measured continuously). Reasons for quitting items were based on the Reasons for Quitting Scale, which is a scale assessing intrinsic and extrinsic motivations for quitting (Curry et al., 1990, 1997). This scale has demonstrated convergent and discriminant validity in previous samples and has been associated with cessation outcomes (Curry et al., 1990, 1997). Based on low internal consistency of items in the current sample (Cronbach’s alpha = 0.01), we treated items as individual constructs and items were subsequently assessed individually. A summary score of these reasons for quitting was also calculated. Each item was dichotomized (0 = not at all true vs. 1 = all other responses). Each reason endorsed by participants was added cumulatively into a total score with a range of 0 to 9 reasons.
Confidence to quit
Participants were asked “How confident are you that you will quit smoking someday?” and “How confident are you that you will quit smoking in the next six months?” Responses ranged from not at all (1) to extremely (5), coded continuously. These items are widely used to assess confidence in quitting and based upon the 2018–2019 Tobacco Use Supplement to the Current Population Survey (National Cancer Institute, 2020).
Intervention Characteristics
At 3 months, we compared individuals who completed a second dose of treatment versus those who did not (i.e., those who had either quit smoking at 3 months, were lost to follow-up, or refused to re-engage with the study).
Cessation Outcomes
At the 3-month and 12-month follow-ups, we collected point prevalence abstinence by asking participants, “Have you smoked a cigarette (even a puff) in the past 7 days?” Those who responded no were coded as those who quit smoking (1). Those who responded yes or did not complete follow-up measures, were coded as continued smokers (0). Using penalized imputation to classify those lost to follow-up as continued smokers is a conservative estimate of quitting commonly used in smoking cessation intervention trials (West et al., 2005).
Data Analysis
Baseline Demographic Descriptives of Older Adult Sample.
Note. GED = General Educational Development; N’s reflect individuals who completed baseline measures. No demographic characteristics retained in final models.
Descriptives of Predictor Variables.
Note. Older adult sample (N = 186); NRT = nicotine replacement therapy; predictors measured at baseline.
Results
Current Study Participants
The older adult sample in the current study are those who completed baseline screening of the parent study and are ≥60 years of age (n = 186) (Table 1). Among this sample (n = 186), at 3 months, 88% (n = 163) completed follow-up measures (Figure 1). Thus, at 3-month follow-up with penalized imputation, 72 participants out of 186 (38.7%) successfully quit and 114 participants out of 186 (61.3%) were classified as continued smokers (i.e., reported still smoking or lost to follow-up). At the 12-month follow-up, 91% (n = 169) of 186 individuals who completed baseline measures also completed 12-month procedures. Thus, with penalized imputation, at the 12-month follow-up, 36.0% (n = 67 out of 186) reporting no use (not even a puff) of cigarettes in the past seven days and 64.0% (n = 119 out of 186) were continued smokers (i.e., reported still smoking or lost to follow-up. Although underpowered to detect statistical differences, among those randomized to re-engage with the intervention, 16.7% (3 out of 18) quit at 12-months. Among those randomized to receive rate reduction, 6.3% (1 out of 16) quit at 12-months. Finally, among those randomized to receive their choice of intervention, 22.2% (2 out of 9) at 12-months. Overview of older adult participation.
Descriptive Statistics
This sample ranged from 60 to 79 years of age, with a M (SD) age of 66.5 (4.4) years. The sample was comprised of mostly White (i.e., 83.3% White/Caucasian, 11.3% Black/African American, 5.4% other racial background or multiracial), non-Hispanic (94.6%), military retirees (62.9%) and non-military TRICARE family members (36.6%). One participant reported active-duty military status. Approximately 59% of the sample identified as men and 41% as women. Of these participants, 18.3% had a high school education/GED, 49.5% had some college/Associates degree, 17.2% had a bachelor’s degree, and 13.4% attended graduate school. Most of the sample were married or living as married (69.9%), 15.6% were widowed, 11.8% were divorced, 2.2% were never married, and one person was separated.
On average, this sample smoked for 44.0 years (SD = 11.5) and had a Fagerstrom Test of Nicotine Dependence score of 4.5 (SD = 2.2) out of 10, indicating a moderate level of dependence (Heatherton & Kozlowski, 1992). Most participants reported that they had tried NRT (76.3%) or an alternative cessation aid (71.7%; i.e., cessation medication, psychotherapy, quit lines, or any other method) and almost half (47.3%; n = 88) had ever tried e-cigarettes to help them quit smoking. Of these individuals (n = 88), 10 (5.4% of the sample) were currently using these products for cigarette cessation. About 9% (n = 16) of individuals were using an alternative tobacco or nicotine containing product concurrently with cigarettes at baseline. Of these 16 individuals, 13 (7.0% of sample) were using e-cigarettes. Because a small number (n = 3) of individuals were poly users of tobacco products (i.e., concurrently using cigarettes and at least two other products in the past month), dual and poly users were combined in subsequent analyses.
Most participants (94.5%) believed that quitting smoking was extremely beneficial for one’s health. Mean endorsements of reasons for quitting ranged; because it will have a negative effect on career was the lowest endorsed reason for quitting (M = 1.9, SD = 0.5) and to improve one’s health was the highest endorsed reason (M = 5.0, SD = 0.3). When reasons for quitting were added cumulatively for each individual, on average participants endorsed 7.0 (SD = 1.7) out of nine. Participants responded with a M score of 4.2 (SD = 1.0) and 4.2 (SD = 0.9) to confidence in quitting some day and confidence in quitting in the next 6 months, respectively.
Predictors of 3-Month Cessation
Univariate Associations with Baseline Predictors and Cessation Outcomes Among Older Adults.
Note. * Referents for dichotomous and ordinal predictors; ‡ continuous predictor; † p < .05; Outcome coded as continued smoking = 0, quit = 1; Bolded predictors were retained in either of the final models.
Predictors of 12-Month Cessation
Among older adults who had not quit smoking and were subsequently randomized to receive a second dose of treatment (i.e., re-engaged with the intervention; n = 43), 18 participants (15.8%) were randomized to the recycle condition, 16 (14.0%) were randomized to the rate reduction condition and 9 (7.9%) were randomized to the choice condition. In a univariate logistic regression model, those who quit smoking or did not receive another round of treatment were significantly more likely to be quit at 12 months (OR = 0.22; 95% CI = 0.09, 0.55; p = .001; n = 186). In additional unadjusted logistic regression models, multiple predictors were significantly associated with 12-month cessation at the p < .10 level (Table 3). In the final multivariable model, each increased score in endorsing to take control of one’s life as a reason for quitting was associated with a 51% increased likelihood of being quit (OR = 1.51; 95% CI = 1.05, 2.17; n = 171) and each point decrease in nicotine dependence scores was associated with 19% higher odds of being quit at 12-months (OR = 0.84; 95% CI = 0.71, 0.99; n = 171). Additionally, not receiving a second dose of treatment at 3 months compared to reengagement with treatment was associated with a 4.17 times increased likelihood of being quit at 12 months (OR = 0.24; 95% CI = .09, .63, n = 171).
Age Group Comparisons of Outcomes
In the entire adult sample, age group [<59 years (0) vs. ≥ 60 years (1)] was not significantly associated with cessation at 3 months (OR=1.11; CI = 0.78–1.59; p = .556; n = 614) or 12 months (OR = 0.89; 95% CI = .62–1.27; p = .517; n = 614). When assessing age comparisons within older age [60-69 years (0) (n=130) versus ≥ 70 years of age (1) (n = 41)], older age group was not significantly associated with either cessation at 3-months (OR = 0.63; 95% CI = 0.31–1.29; p = .634) or 12-months (OR = 0.59; 95% CI = 0.29–1.21; p = .592).
Discussion
This study explored a variety of individual characteristics as predictors of quitting outcomes at 3 and 12 months among older adults enrolled in a proactive tobacco quit line study. The current sample had been smoking for an average of 44 years and reported moderate nicotine dependence (M = 4.5 on Fagerstrom Test of Nicotine Dependence) (Heatherton & Kozlowski, 1992). Although these were individuals who had smoked for many years, this sample on average was highly motivated to quit. In the past year, they had tried to quit nearly twice (M = 1.8 times) and had high scores in confidence in quitting some day and the next 6 months (M = 4.2, M = 4.2, respectively, out of 5). About 58% of this sample had made at least one quit attempt in the past year, which is higher than older adult smokers in the general population (47.2%) (Babb et al., 2017). The majority had used NRT (76.3%) or some type of alternative aid (71.7%) to quit cigarettes before this study. Although only about 9% of this sample were concurrently using one or more alternative tobacco or nicotine containing product with cigarettes at baseline, notably the overwhelming majority of these individuals (13 out of 16) were using e-cigarettes specifically.
In terms of ENDS product use, about half had ever used e-cigarettes to aid in a quit attempt (47.3%), which was higher than a previous study finding only 16% of adults of all ages enrolled in quit lines had ever used e-cigarettes to quit tobacco (Vickerman et al., 2013). However, the higher proportion using e-cigarettes in the current study is not surprising, given that the Vickerman and colleagues (2013) study was conducted 8 years ago, and ENDS products have increased in popularity since then (Cornelius et al., 2020; US DHHS, 2016). Among our sample, 7.0% were current users of e-cigarettes, of which 10 (5.4% of sample) were currently using these products specifically for cigarette cessation. Comparatively, Vickerman and colleagues (2021), found that about 15% of adults of all ages enrolled in tobacco quit lines in 2018 were concurrently using ENDS products, although it is unclear what percentage of these individuals were using these products specifically for cigarette cessation (Vickerman et al., 2021). In regard to older smokers specifically, there is limited research observing e-cigarette use patterns. In a nationally representative sample of older smokers (≥65 years), most (60%) had tried e-cigarettes; although, it is unclear what percentage of these individuals tried e-cigarettes specifically for cigarette cessation (Goldberg et al., 2018). Among older smokers, those who were seriously considering cigarette cessation held more positive beliefs about e-cigarettes than those not interested in cigarette cessation (Goldberg et al., 2018). Specifically, these older adults more strongly agreed that e-cigarettes help individuals quit and that e-cigarette flavors can facilitate quit success (Goldberg et al., 2018). Similarly, in qualitative explorations, older individuals were commonly interested in e-cigarettes as a cigarette cessation aid and reported the convenience of using this product in locations forbidding cigarette smoking (Cataldo et al., 2015). This literature suggests that older adult cigarette smokers hold positive beliefs about e-cigarettes and perhaps use these products to help quit cigarettes. It is also important to mention that our sample included 62.9% retired military personnel. Compared to civilians, military and veteran populations have historically had higher rates of tobacco use (Agaku et al., 2014; Creamer et al., 2019; Department of Defense, 2013; Little et al., 2015a; Meadows et al., 2021), including a higher prevalence of e-cigarette use (Cooper et al., 2019; King et al., 2014; Little et al., 2015b, 2020; Meadows et al., 2021). Perhaps a high likelihood of having tried these products at least once to help quit cigarettes in our sample was influenced by a higher exposure to e-cigarette advertisements (Fahey et al., 2020) and peer use (Cooper et al., 2019; Department of Defense, 2013; Little et al., 2015a, 2015b, 2020), common in military and veteran populations. Additionally, in our sample, ever using e-cigarettes for cigarette cessation was also not associated with success in quitting. This finding is dissimilar from Vickerman and colleagues (2013), in which ever use of e-cigarettes for cigarette cessation was associated with poorer quit outcomes among adults in a tobacco quit line (Vickerman et al., 2013). However, ever using a cessation resources to help quit smoking in the current study was associated with a higher likelihood of continuing to smoke at 3 months. Perhaps those who had tried to quit prior to this study and had used other resources were individuals who have had more difficulty sustaining cessation. Because of the small sample size of current ENDS product users in this sample (n = 13), we were unable to explore how current e-cigarette use and/or current e-cigarette use specifically for cigarette cessation predicted quit outcomes. However, findings do indicate it might be common for older adult smokers to try ENDS products for tobacco cessation at least once. Yet, concurrent use of e-cigarettes, motivated by any reason of use, during the time of accessing a tobacco quit line might be less common.
At 3 months, 38.7% of participants had quit cigarettes and 36.0% had quit at 12 months. Both of these rates are higher compared to quit rates obtained in the general population of adults using tobacco quit lines with free NRT (21% quit success) (Stead et al., 2013) but comparable to the average quit rate (36.7%) obtained from multi-modal randomized clinical trials (i.e., behavioral interventions and pharmacotherapy combined) of older adults (Chen & Wu, 2015). Thus, tobacco quit lines, offer an effective and logistically practical cessation treatment, and can be used to address the high rates of continued cigarette use among U.S. older adults. Clearly, more work is needed to translate the effects observed in research into practice.
Results from final models suggest the most important predictors for quit success included more strongly wanting to quit to take control of one’s life, greater quitting self-efficacy, and a lower level of nicotine dependence. Current findings are supported by a recent study of older (50+ years) smokers in the general population, in which higher self-efficacy and quit confidence were cross-sectionally related with motivation to quit (Smith et al., 2021). Wanting to take control of one’s life as a reason for quitting was assessed through the endorsement of a single statement; thus, it would be helpful if future researchers could develop more psychometrically sound measures of this construct. Despite the limitations in the measurement of this construct, the association between wanting to quit to be in control of one’s life and subsequent cessation in this study warrants future research. Notably, the three significant predictors of successful quitting in this study (e.g., wanting to be in control of one’s life, quitting self-efficacy, and nicotine dependence) all involve constructs of independence and control, which research has shown to decline with age (Infurna et al., 2013; Lachman et al., 2011). Older individuals are more likely to experience uncontrollable age-related constraints on physical health and mobility, as well as to be exposed to ageist beliefs (e.g., that older adults are helpless; Lachman et al., 2011). Importantly, a stronger sense of control, or self-efficacy, in older age is associated with better health outcomes (e.g., longer survival times, improved mental health; Infurna et al., 2011; Infurna et al., 2013; Lachman et al., 2011; Nicolaisen et al., 2018; Turiano et al., 2014). Future cessation studies for older adults might consider assessing and promoting perceived control over cessation and other health goals. Perhaps acquiring agency through self-directed goals can be a strong motivator for older adults in tobacco quit lines, as well as can help improve overall health and wellbeing. Facilitating self-directed and person-centered approaches to attaining cessation goals might help older adults feel more in control of their health.
The current sample of older adults (N = 186) was a subpopulation of the larger parent study (N =614); and thus, was not powered to test the efficacy of the three treatment conditions in relations to quit outcomes. Receiving a second dose of treatment at 3 months was associated with a lower likelihood of quitting at 12 months in our population. However, at the individual level, it is not likely that a second dose of treatment was detrimental for quit success. Results indicate that those who successfully quit at 3 months were also much more likely to be quit at 12 months. In fact, in additional analyses, we did find that those who quit at 3 months were 20 times more likely to be quit at 12 months, compared to those who continued to smoke at 3 months (OR = 19.93, 95% CI = 9.26,42.88). In general, long-term quit success was most likely to be achieved within the first 3 months of treatment. Therefore, findings indicate that it is difficult to interpret the effect of a second dose of treatment within the current sample, given the strong relationship between 3-month and 12-month cigarette abstinence.
In secondary analyses, this study found no difference in 3-month and 12-month quit success between older (≥60 years of age) and younger (<59 years) smokers. This finding is inconsistent with prior research in which older adult smokers had higher quit rate success than those younger (Doolan et al., 2008). Further, Chen and Wu (2015) found that among older adults, increasing age was associated with increased quit success. However, to our knowledge, no study explored age group differences in quit success among adults in tobacco quit lines with free NRT. Thus, future research is needed to assess age group differences specifically in the effectiveness of this type of intervention. Our study indicates that older adults experience comparable quit success as those younger when engaging in a tobacco quit line.
Limitations
Although anxiety and depressive symptoms have been associated with quit outcomes among older adults in the literature (Ferketich et al., 2012; Tait et al., 2008), this study did not assess mental health symptoms. In addition, poor health factors have been associated with a higher likelihood of cessation among older adults (Choi & DiNitto, 2015; Cohen-Mansfield, 2016; Donzé et al., 2007; Sachs-Ericsson et al., 2009; Shahab et al., 2015; Whitson et al., 2006). However, the current study did not assess specific health information regarding chronic illness. Second, this subsample of older adults was not large enough to analyze quit outcome differences between treatment conditions. Further, our sample was not large enough to explore relationships between patterns of ENDS use and quit outcomes. Future studies should assess large samples of older adults in order to better capture how ENDS products might impact quit outcomes among those trying to quit cigarettes in tobacco quit lines. Because our sample included TRICARE beneficiaries, generalizability might be limited to civilians. However, 36.6% of our sample were civilians (i.e., family members of those in the military). Although 62.9% of our sample was retired from their military career, information about current employment status in this sample is unknown. Based on research indicating involuntary retirement is associated with an increase in smoking (Henkens et al., 2008), further research on the impact of retirement on quitting outcomes in this age group will be important. Although it is important to identify modifiable factors that improve cessation specifically within this high priority age population of smokers, future studies should consider how younger age groups are differentially impacted by key factors in order to compare with older age groups. Finally, future studies should explore individual characteristics associated with tobacco quit line outcomes among larger, more diverse samples of older adults.
Conclusion
Despite the aging U.S. population (Ortman et al., 2019), the lack of declining cigarette rates in older age (Cornelius et al., 2020), and this population’s higher risk for tobacco morbidity and mortality (Mons et al., 2015; US DHHS, 2014), older adults are underrepresented in cessation research (Chen & Wu, 2015). Aimed at addressing this gap, this study expanded upon the literature by exploring individual characteristics associated with long-term quit success in a tobacco quit line among a sample exclusively of older adults. Findings provide important considerations for how to tailor cessation programs for older adults. First, promoting quitting self-efficacy and perceived control in cessation and health goals might be particularly important for older adults trying to quit cigarettes, given that this age group is more likely to experience a decline in perceived control over life’s circumstances. Secondly, older smokers with higher nicotine dependence might need additional support during cessation programs. Although a subsample of these older adults was highly motivated to quit and re-enrolled for a second dose of treatment, they were not abstinent from cigarettes at the 1-year follow-up. Normalizing a long history of cigarette use and quit attempts and facilitating discussions about reasons for unsuccessful quit attempts in the past could be important topics for quit line counselors to broach with older adults. Future tobacco quit line studies should assess patterns of ENDS use and the concurrent use of other tobacco products in relationship to quit success in larger gender and racially/ethnically diverse samples of exclusively older adults.
Footnotes
Acknowledgments
The authors gratefully acknowledge the support of Wilford Hall Ambulatory Surgical Center, Joint Base San Antonio, Lackland Air Force Base. The views expressed are those of the authors and do not reflect the official views or policy of the Department of Defense or its Components.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a grant from the National Heart, Lung, and Blood Institute (R01 123978) and was a collaborative endeavor between the United States Air Force and the University of Virginia.
Informed Consent
The voluntary, fully informed consent of the subjects used in this research was obtained as required by 32 CFR 219 and DODI 3216.02_AFI 40-402.
