Abstract
Introduction
Cigarette smoking is substantially more prevalent and rates of smoking cessation are lower in low-SES adults. Financial strain may be one explanation for this. This study assessed the association between financial strain, quit attempts, and successful smoking cessation among adult smokers in the U.S.
Methods
Longitudinal data on adult current smokers (aged ≥18 years) from Waves 1 and 2 of the nationally representative Population Assessment of Tobacco and Health Study (2013–2015) were analyzed in 2017. Negative binomial regression and logistic regression models assessed the association between financial strain and (1) quit attempts and (2) cigarette abstinence, adjusting for important confounders.
Results
Smokers with financial strain made more quit attempts than smokers without financial strain (adjusted incidence-rate ratio=1.34, 95% CI=1.07, 1.68), but financial strain was not associated with smoking abstinence at follow-up (AOR=0.86, 95% CI=0.70, 1.05). Low income was associated with less smoking abstinence at follow-up (AOR=0.66, 95% CI=0.50, 0.87 for <100% federal poverty level; AOR=0.64, 95% CI=0.48, 0.85 for 100%–199% of federal poverty level). Smokers with baseline financial strain who quit at follow-up had lower odds of financial strain at follow-up (AOR=0.57, 95% CI=0.36, 0.89).
Conclusions
Financially strained smokers made slightly more quit attempts than non-strained smokers but were no more likely to successfully quit. Low-income (less than 200% of the federal poverty level) smokers were less likely to quit than higher-income smokers, suggesting that financial strain alone may not explain the low quit rates in this population. Further efforts are needed to increase the success of quit attempts in low-income and financially strained smokers.
INTRODUCTION
Low SES is associated with a high prevalence of cigarette smoking and smoking-related diseases among U.S. adults.1,2 Low-SES smokers have lower rates of smoking cessation success,3–6 with cited barriers to cessation including life stressors, social environments, and low support in quitting.7 It is important to understand factors contributing to lower smoking cessation rates in low-SES smokers to inform the design of more effective cessation programs.
Prior studies have suggested that financial strain (i.e., difficulty meeting financial needs and obligations) may be one important barrier to quitting smoking.8–11 This is also suggested by the finding that cost is a more common trigger for quitting smoking in lower-SES smokers than higher-SES smokers.12 Financial strain can represent a more dynamic process than poverty, and may be experienced by higher-income individuals. Smoking has been associated with financial stress,13–15 and smokers with financial strain, despite reporting higher interest in quitting smoking, have been shown to try to quit less often than smokers without financial strain.8 Furthermore, smokers with financial strain who try to quit appear to be less successful8–10 and relapse more.11 When smokers with financial strain do quit, there is evidence that they experience less financial strain,16 suggesting that the association between financial strain and smoking is likely bidirectional and improvements in one can positively impact the other. However, the impact of poverty and financial strain on smoking behavior could be context specific, and much of the above evidence comes from non–U.S. settings. Studies evaluating the association between financial strain and smoking cessation and focusing solely on the U.S. general adult population are lacking. Understanding this association could help in designing smoking cessation interventions in this vulnerable group of smokers.
To address this gap in evidence, this study evaluates the association between financial strain and smoking cessation in a large, nationally representative longitudinal cohort of U.S. adults. The primary objectives are to examine (1) the association between baseline financial strain and subsequent quit attempts among cigarette smokers, (2) the association between baseline financial strain and smoking abstinence among smokers making a quit attempt, and (3) whether smoking abstinence at follow-up is associated with reduced financial strain among smokers with baseline financial strain.
METHODS
Study Population
The Population Assessment of Tobacco and Health study is a population-based, longitudinal study of U.S. adults and youth that collects detailed data on tobacco use and associated factors.17,18 Data were collected using Audio Computer-Assisted Self-Interviewing and Computer-Assisted Personal Interviewing technology, and survey questions were adapted from other large national surveys, such as the National Health and Nutrition Examination Survey.18 Baseline (Wave 1) data collection occurred from September 2013 to December 2014, and included 45,971 adult and youth respondents (weighted response rate for household screening: 54%, for the adult interviews: 74%). One-year follow-up (Wave 2) was conducted from October 2014 to October 2015 (weighted retention rate: 83%). Publicly available data from adults aged ≥18 years who had data for both timepoints were used for this study, and data were analyzed in 2017. This project was deemed exempt by the IRB at Partners Healthcare.
Measures
Financial strain was defined as an answer of yes to the question: In the past 30 days, because of a shortage of money, were you unable to pay any important bills on time, such as rent, electricity, or telephone bills? Other studies have used a similar single-item measure.8,19,20
Receipt of financial assistance was defined as answering yes to the question: In the past 12 months, have you received assistance or income from any federal, state or local programs, such as food stamps, welfare, cash aid, unemployment benefits, housing assistance, child care, or Medicaid?
The primary outcomes were (1) number of past 12-month quit attempts at follow-up, (2) follow-up cigarette abstinence among smokers who tried to quit, and (3) financial strain at follow-up. Participants reported the number of times in the past 12 months they tried to quit tobacco (for participants using cigarettes and other tobacco products) or cigarettes (for participants using cigarettes only). Cigarette abstinence at follow-up was defined as a response of no when asked about smoking a cigarette in the past 12 months or 30 days (for participants who smoked in the past 12 months), or reporting now smoking cigarettes not at all.
Baseline demographic covariates were age (18–24, 25–34, 35–44, 45–54, or ≥55 years), sex, race/ethnicity (Hispanic, non-Hispanic white, non-Hispanic black, non-Hispanic other), education (less than high school, high school diploma/GED, some college or more), insurance (uninsured/other), employment (employed, not in the labor force, unemployed), and geographic region of residence (Northeast, Midwest, South, West). Income was expressed as a percentage of federal poverty level (<100%, 100%–199%, or ≥200%).
Participants self-reported whether they had ever received the following diagnoses from a doctor or health professional: cancer, diabetes or prediabetes, stroke, heart attack or myocardial infarction or needed bypass surgery, congestive heart failure, COPD (chronic obstructive pulmonary disease; defined as COPD, chronic bronchitis, or emphysema), or asthma.
Daily smokers self-reported the number of cigarettes they smoked per day. For nondaily smokers, cigarettes per day were calculated as the product of days smoked per month and cigarettes per day on days smoked, divided by 30. This variable was winsorized at the 99th percentile to reduce the impact of extreme outliers. Time to first cigarette (≤30 minutes of waking) was used to measure nicotine dependence.21 Participants self-reported current use of electronic cigarettes and other tobacco products (cigars, cigarillos, hookah, pipe tobacco, snus, smokeless tobacco, dissolvable tobacco). Home smoking ban was defined as reporting that smoking a tobacco product is not allowed anywhere or at any time inside my home. A 5-point scale from not at all harmful (1) to extremely harmful (5) measured perceived harms of cigarettes to health.
Participants reported how they would rate their mental health, which includes stress, depression, and problems with emotions, presented on a scale from poor (1) to excellent (5). Past-year drug use included marijuana; cocaine, crack; stimulants; Ritalin, Adderall, painkillers, sedatives, or tranquilizers that were not prescribed; or any other drugs like heroin, inhalants, solvents, or hallucinogens. Alcoholic drinks per day were calculated as the product of the number of days with one or more alcoholic drinks in the past 30 days and the average number of drinks on these days, divided by 30.
Statistical Analysis
Adults who had smoked ≥100 cigarettes in their lifetime, reported smoking every day or some days at baseline, and provided data on financial strain were included in analyses (unweighted n=8,658). The Population Assessment of Tobacco and Health study imputed missing values for sex, age, education, race, and ethnicity, by using data from the household screener or by statistical imputation. Complex survey procedures employing Fay’s variant of balanced repeated replication in Stata, version 14 were used for all analyses. Reported counts are unweighted and percentages are population weighted.
First, smokers with and without financial strain were compared using chi-square tests and adjusted Wald test statistics. For the first objective of examining the association between baseline financial strain and past 12-month quit attempts at follow-up, a multivariable negative binomial regression model controlling for the covariates above was used. Results were compared to Poisson regression and zero-inflated Poisson regression models, and given that model fit did not improve and results were similar, only the negative binomial regression model is presented. For the second objective, multivariable logistic regression assessed the association between baseline financial strain and follow-up cigarette abstinence among smokers who made a past 12-month quit attempt. For the third objective, a multivariable logistic regression model assessed whether smoking abstinence at follow-up was associated with reduced financial strain at follow-up among smokers with baseline financial strain.
Exploratory analyses further evaluated the association between baseline financial strain and follow-up cigarette abstinence. First, whether receipt of financial assistance modified the association between baseline financial strain and follow-up smoking abstinence was assessed by testing for an interaction between baseline financial strain X past 12-month receipt of financial assistance at follow-up. Then, negative binomial regression models investigated the possibility that smokers who report financial strain may have to expend more effort to achieve the same results as those who are not strained through assessing (1) the number of quit attempts among baseline smokers who reported trying to quit but continued to smoke cigarettes at follow-up, and (2) quit attempts among those who successfully quit. Smoking cessation medication use and duration of quit attempts among smokers with and without financial strain were explored in bivariate analyses, as longer duration of abstinence has been associated with smoking cessation success.22
RESULTS
Among baseline cigarette smokers, 29% (95% CI=27%, 30%) reported baseline financial strain. Smokers with and without financial strain differed significantly by sociodemographics, medical comorbidities, nicotine dependence, having a home smoking ban, cigarette harm perceptions, self-perceived mental health, electronic cigarette and other tobacco product use, and past-year drug use (Table 1).
Table 1.
Characteristics of Baseline Smokers With and Without Financial Straina
| Baseline characteristic | No financial strain (n=6,061) |
Financial strain (n=2,597) |
p-value | ||
|---|---|---|---|---|---|
|
| |||||
| N | Weighted % (95% CI) |
N | Weighted % (95% CI) |
||
| Age,b years | <0.001 | ||||
| 18–24 | 1,254 | 14 (13, 15) | 494 | 13 (11, 14) | |
| 25–34 | 1,314 | 24 (22, 25) | 649 | 27 (25, 28) | |
| 35–44 | 1,014 | 18 (16, 19) | 569 | 23 (21, 25) | |
| 45–54 | 1,104 | 19 (18, 20) | 527 | 22 (21, 24) | |
| ≥55 | 1,374 | 26 (24, 27) | 358 | 15 (14-17) | |
| Female sex | 2,847 | 43 (42, 45) | 1,404 | 50 (48, 52) | <0.001 |
| Race/ethnicity | <0.001 | ||||
| Non-Hispanic white | 4,231 | 73 (72, 74) | 1,528 | 63 (60, 65) | |
| Hispanic | 725 | 10 (9.5, 11) | 344 | 12 (11, 13) | |
| Non-Hispanic black | 699 | 11 (10, 12) | 512 | 19 (17, 21) | |
| Non-Hispanic other | 406 | 6 (5, 6) | 213 | 6 (5, 8) | |
| Educationb | <0.001 | ||||
| Less than HS | 927 | 15 (14, 16) | 509 | 18 (17, 20) | |
| HS/GED | 2,197 | 39 (37, 40) | 921 | 39 (37, 41) | |
| Some college or more | 2,919 | 47 (45, 48) | 1,165 | 43 (41, 45) | |
| Employment statusb | <0.001 | ||||
| Employed | 3,799 | 64 (63, 66) | 1,509 | 60 (57, 62) | |
| Not in the labor force | 1,499 | 25 (23, 26) | 592 | 22 (21, 24) | |
| Unemployed | 731 | 11 (10, 12) | 481 | 18 (17, 20) | |
| Region | 0.3 | ||||
| Northeast | 876 | 17 (15, 19) | 379 | 18 (16, 20) | |
| Midwest | 1,711 | 25 (24, 27) | 715 | 24 (21, 27) | |
| South | 2,353 | 39 (37, 41) | 1,054 | 41 (38, 44) | |
| West | 1,121 | 18 (17, 20) | 449 | 17 (16, 19) | |
| Uninsuredb | 1,408 | 23 (22, 24) | 781 | 31 (29, 33) | <0.001 |
| Medical comorbidities | <0.001 | ||||
| 0 | 3,352 | 54 (52, 55) | 1,249 | 47 (45, 50) | |
| 1 | 1,391 | 23 (22, 25) | 669 | 26 (24, 29) | |
| ≥2 | 1,318 | 23 (21, 24) | 679 | 26 (24, 28) | |
| Federal poverty levelb | <0.001 | ||||
| <100% | 1,932 | 31 (30, 33) | 1,361 | 51 (49, 54) | |
| 100%–199% | 1,520 | 27 (26, 28) | 705 | 29 (27, 31) | |
| ≥200% | 2,126 | 42 (40, 44) | 432 | 20 (18, 22) | |
| Cigarettes per dayb | 5,929 | 13.4 (0.2) | 2,554 | 14.2 (0.3) | 0.01 |
| Current electronic cigarette use | 1,295 | 21 (19, 22) | 610 | 23 (21, 25) | 0.04 |
| Current other tobacco product useb | 1,820 | 30 (28, 31) | 859 | 33 (30, 35) | 0.02 |
| Time to first cigarette ≤30 minutesb | 3,516 | 59 (57, 60) | 1,697 | 67 (64, 69) | <0.001 |
| Smoking ban in the homeb | 3,320 | 56 (54, 58) | 1,150 | 45 (42, 48) | <0.001 |
| Perceived harm of cigarettesb,c | 6,050 | 4.0 (0.01) | 2,596 | 4.2 (0.02) | <0.001 |
| Self-perceived mental healthb,d | 6,057 | 3.4 (0.02) | 2,593 | 3.0 (0.03) | <0.001 |
| Past-year drug useb | 2,101 | 34 (33, 35) | 1,304 | 49 (47, 52) | <0.001 |
| Alcoholic drinks per dayb | 5,955 | 0.9 (0.03) | 2,553 | 0.8 (0.05) | 0.7 |
Notes: Boldface indicates statistical significance (p<0.05). All Ns are unweighted; all percentages and 95% CIs are population weighted.
Excludes 626 current smokers with missing data on financial strain.
Data missing for covariates were as follows: 1 for age, 20 for education, 47 for employment, 44 for insurance, 582 for poverty level, 175 for cigarettes per day, 14 for electronic cigarette use, 333 for other tobacco product use, 23 for smoking ban in the home, 12 for perceived harm of cigarettes, 8 for self-perceived mental health, 242 for drug use, and 150 for alcohol use.
5-point scale from not at all harmful (1) to extremely harmful (5).
5-point scale from poor (1) to excellent (5).
HS, high school; GED, General Education Development test.
More smokers with baseline financial strain tried to quit at least once in the past 12 months compared with smokers without financial strain (45% vs 40%, p=0.0002). In a multivariable negative binomial regression model, smokers with baseline financial strain had a significantly higher rate of past 12-month quit attempts at follow-up compared with smokers without financial strain (p=0.01). Specifically, smokers with baseline financial strain had 2.1 (SE=0.3) predicted quit attempts compared with 1.6 (SE=0.1) for smokers without financial strain. Other factors associated with increased quit attempts are shown in Table 2.
Table 2.
Predictors of Past 12-month Quit Attempts Among Baseline Smokers (n=7,213)a
| Variables | aIRR (95% CI) |
|---|---|
| Financial strain at baseline | 1.34 (1.07-1.68)* |
| Age, years | |
| 18–24 | 0.86 (0.57, 1.29) |
| 25–34 | 0.70 (0.46, 1.05) |
| 35–44 | 0.79 (0.56, 1.13) |
| 45–54 | 0.91 (0.63, 1.30) |
| ≥55 | ref |
| Female sex | 1.00 (0.83, 1.20) |
| Race/ethnicity | |
| Non-Hispanic white | ref |
| Hispanic | 1.26 (0.98, 1.63) |
| Non-Hispanic black | 1.55 (1.10, 2.20)* |
| Non-Hispanic other | 1.00 (0.77, 1.29) |
| Education | |
| Less than HS | 1.01 (0.77, 1.32) |
| HS/GED | 0.84 (0.70, 1.01) |
| Some college or more | ref |
| Employment status | |
| Employed | ref |
| Not in the labor force | 1.38 (1.08, 1.75)** |
| Unemployed | 0.90 (0.70, 1.14) |
| Region | |
| Northeast | ref |
| Midwest | 1.19 (0.76, 1.84) |
| South | 1.02 (0.81, 1.28) |
| West | 0.75 (0.60, 0.93)** |
| Uninsured | 0.94 (0.77, 1.15) |
| Medical comorbidities | |
| 0 | ref |
| 1 | 1.14 (0.87, 1.49) |
| ≥2 | 1.38 (1.04, 1.82)* |
| Federal poverty level | |
| <100% | 0.99 (0.75, 1.32) |
| 100%–199% | 0.99 (0.76, 1.28) |
| ≥200% | ref |
| Cigarettes per day | 0.99 (0.982, 0.999)* |
| Electronic cigarette use | 1.15 (0.94, 1.41) |
| Other tobacco product use | 1.20 (0.98, 1.48) |
| Time to first cigarette ≤30 minutes | 0.76 (0.56, 1.03) |
| Smoking ban in the home | 1.28 (0.99, 1.65) |
| Perceived harm of cigarettesb | 1.34 (1.20, 1.50)*** |
| Self-perceived mental healthc | 0.86 (0.78, 0.96)** |
| Past-year drug use | 1.14 (0.92, 1.42) |
| Alcoholic drinks per day | 1.00 (0.95, 1.04) |
Notes: Boldface indicates statistical significance
p<0.05;
p<0.01;
p<0.001.
Data on past 12-month quit attempts missing for 113 participants.
5-point scale from not at all harmful (1) to extremely harmful (5).
5-point scale from poor (1) to excellent (5).
aIRR, adjusted incidence-rate ratio; HS, high school; GED, General Education Development test.
Of smokers with baseline financial strain who made at least one quit attempt, 15% reported cigarette abstinence at follow-up compared with 20% of smokers without financial strain (p=0.0007). This association was no longer statistically significant in a multivariable logistic regression model (AOR=0.86, 95% CI=0.70, 1.05, p=0.13; Table 3). Living below the federal poverty level was associated with significantly less smoking abstinence among smokers who tried to quit (AOR=0.66, 95% CI=0.50, 0.87).
Table 3.
Predictors of Cigarette Abstinence at Wave 2 Among Smokers Who Tried to Quit (n=3,108)a
| Variables | AOR (95% CI) |
|---|---|
| Financial strain at baseline | 0.86 (0.70, 1.05) |
| Age, years | |
| 18–24 | 1.02 (0.63, 1.66) |
| 25–34 | 1.00 (0.64, 1.54) |
| 35–44 | 0.80 (0.51, 1.25) |
| 45–54 | 0.78 (0.47, 1.28) |
| ≥55 | ref |
| Female sex | 1.07 (0.82, 1.40) |
| Race/ethnicity | |
| Non-Hispanic white | ref |
| Hispanic | 1.03 (0.73, 1.45) |
| Non-Hispanic black | 0.70 (0.51, 0.98)* |
| Non-Hispanic other | 0.86 (0.51, 1.45) |
| Education | |
| Less than HS | 0.81 (0.53, 1.23) |
| HS/GED | 1.05 (0.80, 1.36) |
| Some college or more | ref |
| Employment status | |
| Employed | ref |
| Not in the labor force | 0.89 (0.66, 1.21) |
| Unemployed | 0.73 (0.51, 1.06) |
| Region | |
| Northeast | ref |
| Midwest | 1.21 (0.87, 1.69) |
| South | 1.50 (1.09, 2.06)* |
| West | 1.14 (0.78, 1.66) |
| Uninsured | 0.92 (0.68, 1.26) |
| Medical comorbidities | |
| 0 | ref |
| 1 | 0.89 (0.67, 1.17) |
| ≥2 | 0.84 (0.63, 1.12) |
| Federal poverty level | |
| <100% | 0.66 (0.50, 0.87)** |
| 100%–199% | 0.64 (0.48, 0.85)** |
| ≥200% | ref |
| Cigarettes per day | 0.96 (0.95, 0.98)*** |
| Electronic cigarette use | 1.00 (0.77, 1.30) |
| Other tobacco product use | 1.08 (0.83, 1.41) |
| Time to first cigarette ≤30 minutes | 0.81 (0.64, 1.03) |
| Smoking ban in the home | 1.23 (0.97, 1.54) |
| Perceived harm of cigarettesb | 0.94 (0.82, 1.08) |
| Self-perceived mental healthc | 1.11 (1.04, 1.24)* |
| Past-year drug use | 1.03 (0.81, 1.30) |
| Alcoholic drinks per day | 0.98 (0.91, 1.05) |
Notes: Boldface indicates statistical significance
p<0.05;
p<0.01;
p<0.001.
Data on cigarette abstinence at Wave 2 missing for 1 participant.
5-point scale from not at all harmful (1) to extremely harmful (5).
5-point scale from poor (1) to excellent (5).
HS, high school; GED, General Education Development test.
Of smokers with baseline financial strain, 51% reported financial strain at follow-up. In a multivariable logistic regression model (Table 4), cigarette abstinence at follow-up was associated with less financial strain at follow-up among smokers with baseline financial strain (AOR=0.57, 95% CI=0.36, 0.89, p=0.01).
Table 4.
Predictors of Financial Strain at Follow-up Among Smokers With Financial Strain at Baseline Who Tried to Quit (n=983)a
| Variables | AOR (95% CI) |
|---|---|
| Cigarette abstinence at Wave 2 | 0.57 (0.36, 0.89)* |
| Age, years | |
| 18–24 | 0.43 (0.23, 0.80)** |
| 25–34 | 0.61 (0.36, 1.04) |
| 35–44 | 0.79 (0.44, 1.44) |
| 45–54 | 0.85 (0.49, 1.48) |
| ≥55 | ref |
| Female sex | 1.37 (0.99, 1.89) |
| Race/ethnicity | |
| Non-Hispanic white | ref |
| Hispanic | 0.97 (0.61, 1.56) |
| Non-Hispanic black | 0.75 (0.48, 1.17) |
| Non-Hispanic other | 1.08 (0.53, 2.20) |
| Education | |
| Less than HS | 0.86 (0.55, 1.33) |
| HS/GED | 1.16 (0.82, 1.65) |
| Some college or more | ref |
| Employment status | |
| Employed | ref |
| Not in the labor force | 0.80 (0.52, 1.21) |
| Unemployed | 0.91 (0.59, 1.41) |
| Region | |
| Northeast | ref |
| Midwest | 1.49 (0.87, 2.55) |
| South | 1.41 (0.86, 2.30) |
| West | 1.25 (0.76, 2.05) |
| Uninsured | 1.03 (0.69, 1.52) |
| Medical comorbidities | |
| 0 | ref |
| 1 | 1.00 (0.68, 1.49) |
| ≥2 | 1.32 (0.90, 1.93) |
| Federal poverty level | |
| <100% | 1.59 (1.04, 2.45)* |
| 100%–199% | 1.29 (0.86, 1.94) |
| ≥200% | ref |
| Cigarettes per day | 1.00 (0.98, 1.01) |
| Electronic cigarette use | 1.14 (0.80, 1.62) |
| Other tobacco product use | 1.08 (0.74, 1.59) |
| Time to first cigarette ≤30 minutes | 1.11 (0.79, 1.58) |
| Smoking ban in the home | 1.30 (0.95, 1.77) |
| Perceived harm of cigarettesb | 1.14 (0.96, 1.36) |
| Self-perceived mental healthc | 0.92 (0.81, 1.04) |
| Past-year drug use | 1.59 (1.11, 2.27)* |
| Alcoholic drinks per day | 1.01 (0.94, 1.09) |
Notes: Boldface indicates statistical significance
p<0.05;
p<0.01;
p<0.001.
Data on financial strain at follow-up missing for 322 participants.
5-point scale from not at all harmful (1) to extremely harmful (5).
5-point scale from poor (1) to excellent (5).
HS, high school; GED, General Education Development test
Among smokers with financial strain at baseline, 43% reported receiving financial assistance at follow-up, compared with 24% of smokers without baseline financial strain. In a model testing for interaction between baseline financial strain X past 12-month receipt of financial assistance at follow-up, the main effect of financial strain was associated with follow-up cigarette abstinence (AOR=0.77, 95% CI=0.587, 0.998). Receipt of financial assistance among those with financial strain was not associated with statistically significant cigarette abstinence (AOR=1.43, 95% CI=0.94, 2.19, p-value for interaction=0.18; data not shown in tables). Baseline smokers with financial strain who tried to quit cigarettes but continued smoking at follow-up had a nonsignificantly higher number of quit attempts compared with those without baseline financial strain (adjusted incidence-rate ratio=1.26, 95% CI=0.99, 1.62). Baseline smokers with and without financial strain who successfully quit did not differ in the number of quit attempts (adjusted incidence-rate ratio=0.97, 95% CI=0.76, 1.24). Use of stop-smoking medications was similar among smokers with and without financial strain who tried to quit (21% vs 23%, p=0.22). Finally, among smokers who tried to quit but were still smoking at follow-up, the mean duration of the last quit attempt was similar among those with and without baseline financial strain (42 days vs 54 days, p=0.17). Smokers with baseline financial strain who reported trying to quit and achieving cigarette abstinence at follow-up had quit for less time compared with smokers without financial strain (123 days vs 170 days, p=0.006).
DISCUSSION
In this large, nationally representative sample of U.S. adults, smokers with financial strain made more quit attempts over 1 year, but they were no more successful in quitting than smokers without financial strain. Furthermore, low income was associated with reduced quitting. This suggests that factors other than financial strain may impact whether low-income smokers who try to quit are successful.
These results differ from a prior longitudinal study using the International Tobacco Control Four Country Survey, which found that smokers with financial strain at baseline were less likely to make a quit attempt after 1 year, and those who tried to quit were less successful.8 One potential explanation for this difference is that, in addition to the U.S., the International Tobacco Control study pooled data from three other countries (Canada, Australia, and the United Kingdom), where the smoking behaviors may differ from U.S. smokers. Furthermore, International Tobacco Control study data were collected 8 years prior to the Population Assessment of Tobacco and Health data. In the U.S., past-year quit attempts have increased among adult smokers from 2005 to 2015.23 Although the between-groups difference in quit attempts in this study (2.1 versus 1.6) was small, it nevertheless suggests that financially strained smokers in the U.S. are actively attempting to quit to a greater extent than non-strained smokers. The results of the current study also differed from another study that showed an association between financial strain and reduced smoking cessation in the context of a smoking cessation intervention.9 One explanation may be that the results obtained from the subpopulation of smokers included in such a clinical trial may not be as relevant in real-world scenarios that are captured by this observational study. Factors, such as study design (access to smoking cessation treatment) and study population (participant readiness/motivation to quit), may not be transportable to all settings, highlighting the importance of conducting observational studies as well.
The finding that financial strain was associated with quit attempts but not abstinence suggests that making a quit attempt and maintaining abstinence are distinct processes.24 Although analyses controlled for baseline variables associated with smoking relapse, such as nicotine dependence,25 factors arising during individual quit attempts may be important in determining whether the attempt is ultimately successful. For example, physical factors, such as cravings, and emotional factors, such as depressive symptoms, may arise or worsen during a quit attempt, particularly in smokers who are financially strained and have higher levels of nicotine dependence and worse self-perceived mental health at baseline. Further research should address these potential issues within the context of quit attempts made by smokers with financial strain, as interventions focused on medication use and behavioral support may help reduce relapse in this population. Support should extend for more than 1 month after a smoker’s quit date, as the mean duration of participants’ longest quit attempt exceeded 1 month in this study. Furthermore, because lower income was associated with less quitting among smokers who tried to quit in this study, effective smoking cessation interventions in this population may need to focus on factors other than financial strain that are associated with low income and smoking, such as stress,26 social aspects of smoking,27 social support,28 and less knowledge about the health consequences of smoking,29 or factors associated with relapse, such as emotional symptoms.30 Providers should be aware that many low-SES smokers are making multiple attempts to quit per year and ensure close follow-up for these motivated smokers to help anticipate and manage relapses and other difficulties that arise on the path to complete cigarette abstinence.
Consistent with a previous study, smokers with financial strain who were abstinent from cigarettes at follow-up had lower odds of reporting financial strain at follow-up in this study.16 Although one limitation is that the exact timing of reduced financial strain and cigarette abstinence cannot be fully ascertained from this study, one potential implication is that smoking cessation among financially strained smokers can have both health and economic benefits by helping them escape a cycle in which limited financial resources are directed toward cigarettes to cope with the stresses associated with financial hardship. Even though receiving financial assistance was not associated with smoking cessation in smokers with financial strain in this study, one intervention strategy to explore is incorporating smoking cessation treatment into financial assistance programs (e.g., through assistance in obtaining nicotine replacement therapy and counseling). Thus, financial assistance programs could serve as a teachable moment on the financial impact of smoking and financial benefits of quitting, complementing the associated health benefits. Additionally, smoking behaviors should be explored in the context of other strategies to reduce financial strain, such as interventions incorporating financial incentives for smoking cessation in vulnerable populations31–34 and guaranteed minimum income programs.
Limitations
This study is subject to several limitations. First, all data, including smoking status and abstinence, were obtained by self-report and are subject to reporting bias. However, other population-based surveys have found that self-report was associated with accurate nicotine and tobacco use status as obtained by biomarkers.35,36 Second, participants reported past 12-month quit attempts at follow-up, which may be subject to recall bias. Third, financial strain was based on one question about ability to pay bills on time and may not have captured all the ways people can experience financial strain. Similarly, the one-question measure of financial assistance did not differentiate between sources of financial assistance and may not have captured all sources of assistance. Fourth, participants who used cigarettes and other tobacco products were asked about attempts to quit tobacco rather than cigarettes specifically, and some quit attempts may have referred to non-cigarette tobacco products. However, limiting the population to cigarette smokers who did not use other tobacco products in a sensitivity analysis did not alter the main findings. Fifth, reasons for smoking abstinence and relapse are complex and were not captured by the questions in this survey. Further research should explore other potentially addressable barriers to smoking cessation in vulnerable populations. Finally, all data were from U.S. adults and may not be generalizable to other countries.
CONCLUSIONS
U.S. adult smokers with financial strain make more attempts to quit over 1 year, but are no more successful in quitting than smokers without financial strain. Smokers with financial strain who are successful in quitting are less likely to experience financial strain at follow-up. Low income remains associated with reduced quitting, which highlights the importance of identifying other factors that may hamper successful smoking cessation in this population. Targeted efforts are needed to help low-SES smokers quit and thereby reduce disparities in tobacco use and tobacco-related morbidity and mortality in this vulnerable population.
Acknowledgments
Dr. Kalkhoran’s work on this project was supported by The Carney Family Foundation. Dr. Baggett’s role was supported by award K23DA034008 to Dr. Baggett from the National Institute on Drug Abuse at NIH and by a Massachusetts General Hospital Transformative Scholars Program Award. Dr. Berkowitz’s role in the research reported in this publication was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of NIH under Award Number K23DK109200. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH. The funding sources had no role in study design; collection, analysis and interpretation of data; writing the report; or the decision to submit the report for publication.
Dr. Baggett receives royalty payments from UpToDate for authorship of a topic review on homelessness and health. Dr. Rigotti receives royalties from UpToDate for authorship of reviews on smoking cessation topics. She also has a research grant from Pfizer and has consulted (without pay) for the company.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
No other financial disclosures were reported by the authors of this paper.
References
- 1.U.S. DHHS. The health consequences of smoking—50 years of progress: a report of the Surgeon General. Atlanta, GA: U.S. DHHS, CDC, National Center for Chronic Disease Prevention and Health Promotion Office on Smoking and Health; 2014. Published. [Google Scholar]
- 2.Jamal A, King BA, Neff LJ, Whitmill J, Babb SD, Graffunder CM. Current cigarette smoking among adults – United States, 2005–2015. MMWR Morb Mortal Wkly Rep. 2016;65(44):1205–1211. doi: 10.15585/mmwr.mm6544a2. https://doi.org/10.15585/mmwr.mm6544a2. [DOI] [PubMed] [Google Scholar]
- 3.Kotz D, West R. Explaining the social gradient in smoking cessation: it’s not in the trying, but in the succeeding. Tob Control. 2009;18(1):43–46. doi: 10.1136/tc.2008.025981. https://doi.org/10.1136/tc.2008.025981. [DOI] [PubMed] [Google Scholar]
- 4.Hiscock R, Judge K, Bauld L. Social inequalities in quitting smoking: what factors mediate the relationship between socioeconomic position and smoking cessation? J Public Health (Oxf) 2011;33(1):39–47. doi: 10.1093/pubmed/fdq097. https://doi.org/10.1093/pubmed/fdq097. [DOI] [PubMed] [Google Scholar]
- 5.Reid JL, Hammond D, Boudreau C, Fong GT, Siahpush M. Socioeconomic disparities in quit intentions, quit attempts, and smoking abstinence among smokers in four western countries: Findings from the International Tobacco Control Four Country Survey. Nicotine Tob Res. 2010;12(suppl 1):S20–33. doi: 10.1093/ntr/ntq051. https://doi.org/10.1093/ntr/ntq051. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Fernandez E, Schiaffino A, Borrell C, et al. Social class, education, and smoking cessation: Long-term follow-up of patients treated at a smoking cessation unit. Nicotine Tob Res. 2006;8(1):29–36. doi: 10.1080/14622200500264432. https://doi.org/10.1080/14622200500264432. [DOI] [PubMed] [Google Scholar]
- 7.Twyman L, Bonevski B, Paul C, Bryant J. Perceived barriers to smoking cessation in selected vulnerable groups: a systematic review of the qualitative and quantitative literature. BMJ Open. 2014;4(12):e006414. doi: 10.1136/bmjopen-2014-006414. https://doi.org/10.1136/bmjopen-2014-006414. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Siahpush M, Yong HH, Borland R, Reid JL, Hammond D. Smokers with financial stress are more likely to want to quit but less likely to try or succeed: findings from the International Tobacco Control (ITC) Four Country Survey. Addiction. 2009;104(8):1382–1390. doi: 10.1111/j.1360-0443.2009.02599.x. https://doi.org/10.1111/j.1360-0443.2009.02599.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kendzor DE, Businelle MS, Costello TJ, et al. Financial strain and smoking cessation among racially/ethnically diverse smokers. Am J Public Health. 2010;100(4):702–706. doi: 10.2105/AJPH.2009.172676. https://doi.org/10.2105/AJPH.2009.172676. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Reitzel LR, Langdon KJ, Nguyen NT, Zvolensky MJ. Financial strain and smoking cessation among men and women within a self-guided quit attempt. Addict Behav. 2015;47:66–69. doi: 10.1016/j.addbeh.2015.03.026. https://doi.org/10.1016/j.addbeh.2015.03.026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Siahpush M, Carlin JB. Financial stress, smoking cessation and relapse: results from a prospective study of an Australian national sample. Addiction. 2006;101(1):121–127. doi: 10.1111/j.1360-0443.2005.01292.x. https://doi.org/10.1111/j.1360-0443.2005.01292.x. [DOI] [PubMed] [Google Scholar]
- 12.Vangeli E, West R. Sociodemographic differences in triggers to quit smoking: findings from a national survey. Tob Control. 2008;17(6):410–415. doi: 10.1136/tc.2008.025650. https://doi.org/10.1136/tc.2008.025650. [DOI] [PubMed] [Google Scholar]
- 13.Guillaumier A, Twyman L, Paul C, Siahpush M, Palazzi K, Bonevski B. Financial stress and smoking within a large sample of socially disadvantaged Australians. Int J Environ Res Public Health. 2017;14(3):231. doi: 10.3390/ijerph14030231. https://doi.org/10.3390/ijerph14030231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Siahpush M, Borland R, Scollo M. Smoking and financial stress. Tob Control. 2003;12(1):60–66. doi: 10.1136/tc.12.1.60. https://doi.org/10.1136/tc.12.1.60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Pyle SA, Haddock CK, Poston WS, Bray RM, Williams J. Tobacco use and perceived financial strain among junior enlisted in the U.S. military in 2002. Prev Med. 2007;45(6):460–463. doi: 10.1016/j.ypmed.2007.05.012. https://doi.org/10.1016/j.ypmed.2007.05.012. [DOI] [PubMed] [Google Scholar]
- 16.Siahpush M, Spittal M, Singh GK. Association of smoking cessation with financial stress and material well-being: results from a prospective study of a population-based national survey. Am J Public Health. 2007;97(12):2281–2287. doi: 10.2105/AJPH.2006.103580. https://doi.org/10.2105/AJPH.2006.103580. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.U.S. DHHS, NIH, National Institute on Drug Abuse, Food and Drug Administration, Center for Tobacco Products. Population Assessment of Tobacco and Health (PATH) Study [United States] Public-Use Files. Inter-university Consortium for Political and Social Research (ICPSR); 2017. [distributor]; [Google Scholar]
- 18.Hyland A, Ambrose BK, Conway KP, et al. Design and methods of the Population Assessment of Tobacco and Health (PATH) Study. Tob Control. 2017;26(4):371–378. doi: 10.1136/tobaccocontrol-2016-052934. https://doi.org/10.1136/tobaccocontrol-2016-052934. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Siahpush M, Borland R, Yong HH, Cummings KM, Fong GT. Tobacco expenditure, smoking-induced deprivation, and financial stress: Results from the International Tobacco Control (ITC) four country survey. Drug Alcohol Rev. 2012;31(5):664–671. doi: 10.1111/j.1465-3362.2012.00432.x. https://doi.org/10.1111/j.1465-3362.2012.00432.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Siahpush M, Tibbits M, Soliman GA, et al. Neighbourhood exposure to point-of-sale price promotions for cigarettes is associated with financial stress among smokers: results from a population-based study. Tob Control. 2017;26(6):703–708. doi: 10.1136/tobaccocontrol-2016-053339. https://doi.org/10.1136/tobaccocontrol-2016-053339. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Baker TB, Piper ME, McCarthy DE, et al. Time to first cigarette in the morning as an index of ability to quit smoking: Implications for nicotine dependence. Nicotine Tob Res. 2007;9(suppl 4):S555–570. doi: 10.1080/14622200701673480. https://doi.org/10.1080/14622200701673480. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Gilpin EA, Pierce JP, Farkas AJ. Duration of smoking abstinence and success in quitting. J Natl Cancer Inst. 1997;89(8):572–576. doi: 10.1093/jnci/89.8.572. https://doi.org/10.1093/jnci/89.8.572. [DOI] [PubMed] [Google Scholar]
- 23.Babb S, Malarcher A, Schauer G, Asman K, Jamal A. Quitting smoking among adults – United States, 2000–2015. MMWR Morb Mortal Wkly Rep. 2017;65(52):1457–1464. doi: 10.15585/mmwr.mm6552a1. https://doi.org/10.15585/mmwr.mm6552a1. [DOI] [PubMed] [Google Scholar]
- 24.Vangeli E, Stapleton J, Smit ES, Borland R, West R. Predictors of attempts to stop smoking and their success in adult general population samples: a systematic review. Addiction. 2011;106(12):2110–2121. doi: 10.1111/j.1360-0443.2011.03565.x. https://doi.org/10.1111/j.1360-0443.2011.03565.x. [DOI] [PubMed] [Google Scholar]
- 25.Zhou X, Nonnemaker J, Sherrill B, Gilsenan AW, Coste F, West R. Attempts to quit smoking and relapse: factors associated with success or failure from the ATTEMPT cohort study. Addict Behav. 2009;34(4):365–373. doi: 10.1016/j.addbeh.2008.11.013. https://doi.org/10.1016/j.addbeh.2008.11.013. [DOI] [PubMed] [Google Scholar]
- 26.Bock BC, Papandonatos GD, de Dios MA, et al. Tobacco cessation among low-income smokers: motivational enhancement and nicotine patch treatment. Nicotine Tob Res. 2014;16(4):413–422. doi: 10.1093/ntr/ntt166. https://doi.org/10.1093/ntr/ntt166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Hitchman SC, Fong GT, Zanna MP, Thrasher JF, Chung-Hall J, Siahpush M. Socioeconomic status and smokers’ number of smoking friends: findings from the International Tobacco Control (ITC) Four Country Survey. Drug Alcohol Depend. 2014;143:158–166. doi: 10.1016/j.drugalcdep.2014.07.019. https://doi.org/10.1016/j.drugalcdep.2014.07.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Businelle MS, Kendzor DE, Reitzel LR, et al. Mechanisms linking socioeconomic status to smoking cessation: A structural equation modeling approach. Health Psychol. 2010;29(3):262–273. doi: 10.1037/a0019285. https://doi.org/10.1037/a0019285. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Siahpush M, McNeill A, Hammond D, Fong GT. Socioeconomic and country variations in knowledge of health risks of tobacco smoking and toxic constituents of smoke: results from the 2002 International Tobacco Control (ITC) Four Country Survey. Tob Control. 2006;15(suppl 3):iii65–70. doi: 10.1136/tc.2005.013276. https://doi.org/10.1136/tc.2005.013276. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Pisinger C, Aadahl M, Toft U, Jorgensen T. Motives to quit smoking and reasons to relapse differ by socioeconomic status. Prev Med. 2011;52(1):48–52. doi: 10.1016/j.ypmed.2010.10.007. https://doi.org/10.1016/j.ypmed.2010.10.007. [DOI] [PubMed] [Google Scholar]
- 31.Kendzor DE, Businelle MS, Poonawalla IB, et al. Financial incentives for abstinence among socioeconomically disadvantaged individuals in smoking cessation treatment. Am J Public Health. 2015;105(6):1198–1205. doi: 10.2105/AJPH.2014.302102. https://doi.org/10.2105/AJPH.2014.302102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Etter JF, Schmid F. Effects of large financial incentives for long-term smoking cessation: a randomized trial. J Am Coll Cardiol. 2016;68(8):777–785. doi: 10.1016/j.jacc.2016.04.066. https://doi.org/10.1016/j.jacc.2016.04.066. [DOI] [PubMed] [Google Scholar]
- 33.Lasser KE, Quintiliani LM, Truong V, et al. Effect of patient navigation and financial incentives on smoking cessation among primary care patients at an urban safety-net hospital: a randomized clinical trial. JAMA Intern Med. 2017;177(12):1798–1807. doi: 10.1001/jamainternmed.2017.4372. https://doi.org/10.1001/jamainternmed.2017.4372. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Baggett TP, Chang Y, Yaqubi A, McGlave C, Higgins ST, Rigotti NA. Financial incentives for smoking abstinence in homeless smokers: A pilot randomized controlled trial. Nicotine Tob Res. doi: 10.1093/ntr/ntx178. In press. Online August 18, 2017. https://doi.org/10.1093/ntr/ntx178. [DOI] [PMC free article] [PubMed]
- 35.Caraballo RS, Giovino GA, Pechacek TF, Mowery PD. Factors associated with discrepancies between self-reports on cigarette smoking and measured serum cotinine levels among persons aged 17 years or older: Third National Health and Nutrition Examination Survey, 1988–1994. Am J Epidemiol. 2001;153(8):807–814. doi: 10.1093/aje/153.8.807. https://doi.org/10.1093/aje/153.8.807. [DOI] [PubMed] [Google Scholar]
- 36.Yeager DS, Krosnick JA. The validity of self-reported nicotine product use in the 2001–2008 National Health and Nutrition Examination Survey. Med Care. 2010;48(12):1128–1132. doi: 10.1097/MLR.0b013e3181ef9948. https://doi.org/10.1097/MLR.0b013e3181ef9948. [DOI] [PubMed] [Google Scholar]