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

Abstract

Objective:

To examine the association of financial stress with interest in quitting smoking, making a quit attempt, and quit success.

Design and participants:

The analysis used data from 4,984 smokers who participated in Waves 4 and 5 (2005-2007) of the International Tobacco Control (ITC) Four Country Survey, a prospective study of a cohort of smokers in the US, Canada, UK, and Australia.

Measurement:

The outcomes were interest in quitting at Wave 4, making a quit attempt, and quit success at Wave 5. The main predictor was financial stress at Wave 4: “ … because of a shortage of money, were you unable to pay any important bills on time, such as electricity, telephone or rent bills?” Additional sociodemographic and smoking-related covariates were also examined.

Findings:

Smokers with financial stress were more likely than others to have an interest in quitting at baseline (OR: 1.63; 95% CI: 1.22-2.19), but were less likely to have made a quit attempt at follow-up (OR: 0.74; 95% CI: 0.57-0.96). Among those who made a quit attempt, financial stress was associated with a lower probability of abstinence at follow-up (OR: 0.53; 95% CI: 0.33-0.87).

Conclusions:

Cessation treatment efforts should consider routinely assessing the financial stress of their clients and providing additional counseling and resources for smokers who experience financial stress. Social policies that provide a safety net for people who might otherwise face severe financial problems, such as not being able to pay for rent or food, may have a favorable impact on cessation rates.

Introduction

The association of common indicators of socioeconomic position (education, occupation, and income) with smoking are well-established.^1-4 Less attention has been paid to how financial stress (FS) affects smoking behavior. FS is a direct indicator of economic deprivation⁵ and often refers to not being able to pay for essentials such as food or rent due to shortage of money.^6-9 FS has also shown to be associated with smoking. Using data on Australian households, Siahpush and colleagues showed that FS was associated with a higher probability of reporting tobacco expenditure.⁶ They also found that among smoking households, FS was related to a higher percentage of total household expenditure on tobacco. Graham's analysis of a cross-sectional sample of working-class mothers in the United Kingdom (UK) revealed that the main reason for relapse after cessation was difficulty in coping with daily problems and stress, including FS.¹⁰ Dorsett and Marsh used longitudinal data from a sample of single mothers in the United Kingdom and showed that smoking was used as a coping mechanism and that financial hardship was the main barrier to cessation.¹¹ Similarly, a recent longitudinal study in Australia revealed that smokers with FS were less likely to quit, and ex-smokers with greater FS were more likely to relapse.⁷

These studies uniformly report an association between FS and higher probability of smoking or lower chances of successful cessation. However, owing to a lack of data availability, they provide no information on how FS is related to the pre-cessation stages of planning to quit and making a quit attempt. Furthermore, for the same reason, these studies do not adjust for smoking-related variables such as tobacco dependence or self-efficacy to quit that are shown to be associated with socioeconomic position and are strong predictors of the propensity to quit and/or successful cessation.^12-20 The International Tobacco Control (ITC) Four Country Survey provides suitable longitudinal data to help address these shortcomings in the literature.

The aim of this paper was to examine the association of FS with interest in quitting (at study baseline), making a quit attempt and quit success (at follow-up), while adjusting for smoking-related psychosocial, motivational, and behavioral factors as well as sociodemographic variables.

Method

Sample and design

Data came from Waves 4 (2005-2006) and 5 (2006-2007) of the ITC Four Country Study. A detailed description of the survey methodology can be found elsewhere ²¹ (also see http://www.itcproject.org). Briefly, the ITC Four Country Study is a prospective cohort study designed to evaluate the psychosocial and behavioural impact of key national-level tobacco control policies enacted in the US, Canada, UK and Australia. All aspects of the study protocol and survey measures are standardized across the four countries. Data collection is based on telephone interviews of a probability sample of smokers, with approximately 2000 smokers per country in each wave. The present analysis (maximum n = 4,984 ) included respondents who were daily or non-daily smokers at Wave 4, were in one or more of the previous waves of the study, and participated in Wave 5. The attrition rate from Wave 4 to 5 was lowest in Australia (26%) and highest in the US (36%).

The study protocol was cleared for ethics by the Institutional Review Boards or Research Ethics Boards in each of the countries: the University of Waterloo (Canada), Roswell Park Cancer Institute (US), University of Illinois-Chicago (US), University of Strathclyde (UK), and The Cancer Council Victoria (Australia).

Outcomes

Interest in quitting at Wave 4 was measured with the question “Are you planning to quit smoking: within the next month? Within the next 6 months? Sometime in the future, beyond 6 months? Or not planning to quit.” Those who were not planning to quit were distinguished from others. This grouping is consistent with our previous research. ²⁰ 22 However, other studies have distinguished smokers who plan to quit within the next six months ²³ or within the next three or four months. ^{24 25}

Respondents were characterized as having made a quit attempt in Wave 5 if they responded affirmatively to the question, “Have you made any attempts to stop smoking since we last talked with you, that is since [last survey date]?”

Quit success was defined as being a smoker at Wave 4 and reporting to be no longer smoking at Wave 5. Quit success was defined only among respondents who reported in Wave 5 to have made a quit attempt in the previous year.

Covariates

All covariates were measured at Wave 4. Financial stress was measured with the question: “In the last month, because of a shortage of money, were you unable to pay any important bills on time, such as electricity, telephone or rent bills? [Yes/No]”. This question is directly based on multi-item indices used in previous research on FS and smoking.^6-9 The financial stress question was not asked from respondents who were recruited in Wave 4 (ie Wave 4 replenishment sample).

Psychosocial covariates

Perceived stress was measured with two of the items (r = 0.56) from Cohen's four-item scale constructed for telephone interviews: “How often have you felt that you were unable to control the important things in your life?” and “How often have you felt difficulties were piling up so high that you could not overcome them?”²⁶ Response options ranged from “1 = never” to “5 = very often” on a five-point scale. The mean of the two items was used in the analyses.

“Smoking-induced deprivation”⁵ was measured with the question: “In the last year, have you spent money on cigarettes that you knew would be better spent on household essentials like food? [Yes/No]”.

The item “You spend too much money on cigarettes” was coded on a five-point scale from “1 = strongly disagree” to “5 = strongly agree”.

Self-efficacy was measured with the question “If you decided to give up smoking completely in the next 6 months, how sure are you that you would succeed?” Response options ranged from “1 = not at all sure” to “5 = extremely sure” on a five-point scale.

Motivational covariates

Interest in quitting, described above, was used as a covariate in the quit attempt but not the quit success analysis, based on previous research showing it to be an important predictor for quit attempt.²⁷ Worries about health and quality of life were measured with “How worried are you, if at all, that smoking will damage your health in the future?” and “How worried are you, if at all, that smoking will lower your quality of life in the future?” Response options ranged from “1 = not at all worried” to “4 = very worried” on a four-point scale.²⁷ These two items correlated strongly (r = 0.73). Their mean was used in the analyses.

The item “To what extent, if at all, has smoking lowered your quality of life?” was coded on a four-point scale from “1 = not at all” to “4 = a great deal”.

Behavioral covariate

Tobacco dependence was measured using the Heaviness of Smoking Index (HSI), a short form of the Fagerstrom Tolerance Questionnaire.^28-30 HSI scores ranged from 0 to 6 and were calculated by summing the points for time to first cigarette after waking (in minutes) and number of cigarettes smoked per day. Time to first cigarette was scored: <5 min = 3 points; 6–30 min = 2 points; 31-60 min = 1 point; and >60 min = 0 point. Respondents were asked: “On average, how many cigarettes do you smoke each day, including both factory-made and roll-your own cigarettes?” Cigarettes per day was scored: 1-10 = 0 point; 11-20 = 1 point; 21-30 =2 points; and >31 = 3 points. Higher HSI scores indicate greater tobacco dependence.

Sociodemographic covariates

Age was categorized as: 18-24, 25-39, 40-54, and over 55. Level of education consisted of three categories: high school diploma or lower (low); technical, trade school, community college, or some university (medium); university degree (high). Annual income was categorized into “under $30,000” (low), “$30,000-59,999” (medium), and “$60,000 and over”(high) for the US, Canadian, and Australian samples. For the UK sample, the following categories were used: “£15,000 or under”, “£15,001-30,000” and “£30,001 and over”.^{5 20 31}

Analysis

All analyses were performed in Stata 10 SE.³² Cases with missing values for any of the study variables were not included in the analyses. The variable with largest proportion of missing data (about 6%) was income. Logistic regression was employed to estimate the effect of FS and other covariates on interest in quitting, quit attempt, and quit success. Longitudinal weights were used to report point estimates (Table 1).²¹ Unweighted data were used to report bivariate associations (Table 2) and in multivariable modeling (Table 3), which adjusted for demographic and other covariates.

Table 1.

Sample Characteristics (weighted)

Variablesa	US n=1033	Can. n=1192	UK n=1161	Austr. n=1284
Interest in quitting	71.58	75.60	66.64	74.06
Made a quit attempt	32.49	36.55	35.86	41.12
Quit success	27.40	29.64	40.19	31.67
Financial stress	15.94	12.64	6.07	13.45
Perceived stress (mean)	2.42	2.22	2.25	2.29
Spent money on cigarettes instead of food	28.13	32.02	18.37	24.19
Spending too much money on cigarettes (mean)	3.99	3.97	3.78	4.02
Self-efficacy to quit (mean)	2.62	2.57	2.26	2.39
Worried smoking will damage health (mean)	2.62	2.63	2.53	2.56
Smoking has lowered quality of life (mean)	1.98	1.96	1.72	1.81
HSI (mean)	2.53	2.65	2.47	2.53
Female	45.90	46.24	46.89	44.96
Age
18-24	12.51	13.54	14.21	14.85
25-39	29.82	31.07	32.19	35.94
40-54	37.88	38.72	33.63	34.45
55+	19.79	16.67	19.98	14.77
Education
Low	38.30	44.88	57.60	63.22
Medium	44.09	40.13	27.79	21.65
High	17.61	14.98	14.61	15.13
Income
Low	39.14	28.11	25.49	25.61
Medium	36.67	39.02	39.48	35.87
High	24.19	32.87	35.03	38.53

Note: All numbers are percentages unless otherwise specified.

^aAll variables were measured at Wave 4 except “quit attempt” and “quit success”, which were measured at Wave 5.

Table 2.

Characteristics of smokers with financial stress (n=4670)

	Financial Stress
Variablesa	Yes	No	Pb
Interest in quitting			<0.001
Yes	82.68	68.73
No	17.32	31.27
Made a quit attemptC			0.272
Yes	42.76	46.23
No	57.24	53.77
Quit success			0.013
Yes	22.31	33.49
No	77.69	66.51
Perceived stress (mean)	2.94	2.22	<0.001
Spent money on cigarettes instead of food			<0.001
Yes	48.53	21.57
No	51.47	78.43
Spending too much money on cigarettes (mean)	4.13	3.89	<0.001
Self-efficacy to quit (mean)	2.52	2.39	0.0218
Worried smoking will damage health (mean)	2.81	2.53	<0.001
Smoking has lowered quality of life (mean)	2.23	1.80	<0.001
HSI (mean)	2.69	2.59	0.1516
Sex			0.149
Female	59.22	55.88
Male	40.78	44.12
Age			<0.001
18-24	12.04	6.84
25-39	36.70	26.14
40-54	36.89	42.22
55+	14.37	24.80
Education			0.601
Low	50.88	51.47
Medium	34.05	32.15
High	15.07	16.38
Income			<0.001
Low	49.71	30.01
Medium	34.56	37.66
High	15.73	32.33

Note: All numbers are percentages unless otherwise specified.

^aAll variables were measured at Wave 4 except “quit attempt” and “quit success”, which were measured at Wave 5.

^bP-values correspond to the association of FS and the variables in the table.

^CQuit attempt in this table is computed for respondents who reported to have an interest in quitting smoking.

Table 3.

Adjusted odds ratios (OR) and 95% confidence intervals (CI) from the effect of financial stress and other covariates on the odds of having an intention to quit, making a subsequent quit attempt, and its success

	Interest in quitting n=4415		Quit attempt n=3220		Quit success n=1199
Covariates	OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)	P
Financial stress		0.001		0.025		0.012
Yes	1.63 (1.22-2.19)		0.74 (0.57-0.96)		0.53 (0.33-0.87)
No	1.00		1.00		1.00
Perceived stress	1.03 (0.95-1.11)	0.459	0.97 (0.89-1.04)	0.384	1.01 (0.89-1.15)	0.823
Spent money on cigarettes instead of food		0.951		0.131		0.928
Yes	0.99 (0.81-1.21)		1.16 (0.96-1.41)		0.99 (0.72-1.35)
No	1.00		1.00		1.00
Spending too much money on cigarettes	1.31 (1.21-1.42)	<0.001	0.96 (0.89-1.04)	0.351	0.97 (0.85-1.10)	0.638
Self-efficacy to quit	1.29 (1.20-1.37)	<0.001	1.07 (1.00-1.14)	0.065	1.07 (0.96-1.20)	0.242
Interest in quitting		--		<0.001		--
Yes	--		3.51 (2.82-4.37)		--
No	--		1.00		--
Worried smoking will damage health	3.05 (2.73-3.40)	<0.001	1.28 (1.15-1.42)	<0.001	0.99 (0.84-1.17)	0.921
Smoking has lowered quality of life	1.18 (1.05-1.33)	0.007	1.22 (1.10-1.36)	<0.001	0.89 (0.75-1.06)	0.203
HSI	0.81 (0.77-0.85)	<0.001	0.82 (0.78-0.87)	<0.001	0.86 (0.79-0.94)	0.001
Sex		0.083		0.794		0.138
Female	1.15 (0.98-1.35)		0.98 (0.83-1.15)		0.82 (0.63-1.07)
Male	1.00		1.00		1.00
Age		<0.001		<0.001		0.776
18-24	1.00		1.00		1.00
25-39	1.38 (0.98-1.95)		0.58 (0.42-0.81)		0.78 (0.48-1.25)
40-54	0.76 (0.55-1.05)		0.56 (0.41-0.78)		0.81 (0.51-1.29)
55+	0.61 (0.43-0.86)		0.85 (0.60-1.21)		0.84 (0.51-1.39)
Education		0.015		0.144		0.493
Low	1.00		1.00		1.00
Medium	1.30 (1.09-1.56)		1.20 (1.00-1.43)		1.16 (0.86-1.55)
High	1.05 (0.83-1.32)		1.07 (0.86-1.34)		1.21 (0.84-1.73)
Income		0.006		0.122		0.756
Low	1.00		1.00		1.00
Medium	1.22 (1.01-1.48)		0.83 (0.68-1.00)		1.10 (0.79-1.53)
High	1.41 (1.14-1.75)		0.94 (0.76-1.17)		0.99 (0.70-1.41)
Country		<0.001		<0.001		0.015
US	1.00		1.00		1.00
Canada	1.41 (1.13-1.77)		0.97 (0.77-1.22)		0.92 (0.61-1.36)
UK	1.00 (0.80-1.25)		1.14 (0.90-1.45)		1.63 (1.10-2.41)
Australia	1.42 (1.13-1.78)		1.46 (1.16-1.83)		1.22 (0.83-1.78)

Results

Table 1 provides weighted characteristics of the sample by country. About 12% of the total Wave 4 sample experienced FS. The UK had the lowest (6%) and the US had the highest (13%) percentage of smokers who reported FS. Canada had the highest (76%) and the UK had the lowest (64%) percentage of smokers who had an interest in quitting. Percentage of smokers who made a quit attempt was highest in Australia (42%) and lowest in the US (33%). Successful cessation rate was highest in the UK (37%) and lowest in the US (26%).

Table 2 shows the characteristics of smokers with FS and the bivariate associations of FS with the outcomes and other variables. Country data were pooled as there was no evidence of interaction between FS and country in their association with the outcomes. About 83% of smokers with FS and 69% without FS had an interest in quitting. At the bivariate level, there was no association between FS and quit attempts. Among smokers who attempted to quit, 20% of those with FS and 31% of those without FS were successful. Smokers with financial stress were more likely to be younger and have lower income than other smokers.

Table 3 shows adjusted odds ratios for the association of covariates with interest in quitting in the same wave, and quit attempt and quit success at the next wave. The odds of having an interest in quitting were 71% (p < 0.004) higher in smokers with FS than others. Other factors that were associated with a higher probability of interest in quitting were: spending too much money on cigarettes, higher self-efficacy, being worried about the effect of cigarettes on health and quality of life, reporting that smoking has lowered one's quality of life, lower levels of nicotine dependence, being female, being under 40 years old, not having low education, and higher income. The probability of interest in quitting was highest in Australia and lowest in the UK. We note that when interest in quitting was defined as planning to quit within the next six months (as compared to beyond six months or no plan at all), financial stress did not have an association with interest in quitting. Furthermore, among those who had an interest in quitting, there was no evidence of an association between financial stress and whether a respondent had an interest in quitting within the next six months or sometime in the future.

While FS and subsequent quit attempts were not associated at the bivariate level, after controlling for interest in quitting and the respondents' reports on whether smoking had lowered their quality of life at the baseline (Wave 4), the data provided considerably more evidence for an association. In the multivariate analysis, the odds of making a quit attempt by the next wave were 26% (p = 0.023) lower in smokers with FS than others. Interest in quitting, being worried about the effect of cigarettes on health and quality of life, reporting that smoking has lowered one's quality of life, lower nicotine dependence, being under 25 years old, and not having low income were independently associated with a higher probability of making a subsequent quit attempt. The probability of a subsequent quit attempt was highest in Australia and lowest in the US.

Among those who tried to quit smoking, the odds of a successful attempt were 48% (p = 0.012) lower in smokers with financial stress than others. Lower nicotine addiction was independently associated with a higher probability of quit success. The probability of quit success was highest in the UK and lowest in Canada.

There was no interaction between FS and country in any of the regression models.

Whether a person had an interest in quitting, made a quit attempt, or had quit smoking in Wave 4 was not associated with being lost to follow-up in Wave 5, with p-values of 0.797, 0.640, and 0.701, respectively. Lower age and education in Wave 4 were associated with being lost to follow-up in Wave 5 with p values of <0.001 and 0.006, respectively. None of the other covariates were associated with attrition. The exact impact of attrition on results cannot be assessed. However, by including the correlates of attrition (ie age and education) in the multivariate analyses, we have partially controlled for bias.

Supplementary analyses showed that there was no evidence of an association between financial stress and three variables in the ITC dataset that pertain to the use of services or products to help cessation: use of “stop-smoking medications” (p = 0.665), doctors' “help or referral to another service” as an aid to cessation (p = 0.791), or use of telephone quitlines (p = 0.667) in wave 5. Consequently, including these variables in the quit attempt and quit success analyses resulted in negligible change in the effect of financial stress. For example, when these three variables were included separately in the quit success regression model (Table 3), the odds ratio for the effect of financial stress changed from 0.5338 (p = 0.012) to 0.5343 (p = 0.012), 0.5083 (p = 0.007), and 0.5336 (p = 0.012), respectively.

In further supplementary analyses, we included health (“In general, how would you describe your health? Is it … 1. Poor, 2. Fair, 3. Good, 4. Very good, or 5. Excellent”) in the models. This variable was not associated with interest in quitting (p = 0.204), quit attempt (p = 0.599), or quit success (p = 0.312). Consequently, the inclusion of health in the regression models did not make an appreciable change in the effect of financial stress. For example, after health was included in the quit success model, the odds ratio for financial stress changed from 0.534 (p = 0.012) to 0.533 (p = 0.012). Thus, we did not include health in the analyses.

Discussion

The study findings revealed that while smokers with financial stress were more likely than others to have an interest in quitting, they were marginally less likely to make a quit attempt and considerably less likely to stay quit. These results held across all four countries. To our knowledge, this was the first study to examine the association of FS with interest in quitting and subsequent quit attempt. The result of the cessation analysis was consistent with previous studies.^6-11

A major strength of this paper was its use of a unique international longitudinal dataset devoted to collecting information on tobacco control and cessation. In addition to allowing us to examine the association of FS with interest in quitting, and also subsequent quit attempt and its success, the ITC Four Country Survey data made it possible to adjust for factors that are known to be important predictors of quitting motivation or behavior.

A possible weakness of the study was that it used a self-reported measurement of smoking status, which may have resulted in underreporting of smoking. However, previous research has shown that questionnaire-based surveys of the general population provide a reliable estimate of smoking status when cotinine validated, without systematic differentials in underreporting by socio-economic groups.^{33 34} The amount of misclassification (proportion of self-reported non-smokers with increased cotinine levels indicative of active smoking) is very low (for example, 0.9%³⁵ and 1.4%³⁶) in most community-based studies³⁷, but much higher in clinical trials and intervention studies³⁷, especially among young adults.³⁸ Under-reporting of smoking is not a major concern in the present study, as our aim was not to provide accurate estimates of smoking intention, attempt, or quit success rates, but to examine the association of these outcomes with FS.

We measured financial stress by assessing difficulty paying bills such as “electricity, telephone or rent”. We did not have a separate question concerning difficulty paying mortgage by homeowners. In order to assess the impact of this exclusion, we performed supplementary analyses using an Australian national dataset known as Household Income and Labour Dynamics in Australia (2001).⁷ In this dataset there are two separate financial stress items about difficulty paying “electricity, gas and telephone bills on time” and paying “mortgage or rent on time”. Among home owners who smoked (n = 1,218), there were only 1.8% who did not have difficulty paying “electricity, gas or telephone bills” but did have difficulty making mortgage payments. This indicates that asking owners a question about bills, as we have in this research, will capture the overwhelming majority of those who experience financial stress as is measured here.

While cessation was assessed at wave 5, financial stress in the past month was assessed at wave 4. Thus, the effect of long-term or sustained financial stress on cessation and the other study outcomes was possibly underestimated, as the impact of any temporary financial stress may not be observed over a year.

While smokers in the UK had the smallest proportion who had an interest in quitting, they had the highest quit success compared to the other countries. The low motivation of the UK smokers to quit may be because of the fact that more of them lack a knowledge of some health hazards of smoking and toxic constituents in smoke. UK smokers have the lowest proportion who believes that smoking causes stroke or lung cancer. They also have a considerably lower proportion of smokers who believe that tobacco smoke contains cyanide, mercury, arsenic, or carbon monoxide.³¹ The higher rates of quit success in the UK can be attributed to the fact that it is the only country to have introduced a national smoking cessation treatment service.³⁹ Every Health Authority in the UK offers treatment to dependent smokers who want to quit through the National Health Service. Treatment is free to all users, although partial payment can be required for pharmacotherapies.⁴⁰

The observed age effect that younger smokers are generally more likely to want to quit but less likely to make a quit attempt or succeed are consistent with other population-based studies. ^{7 20 27} The direction of this effect can be understood with reference to previous studies indicating that older smokers: are less likely to accept evidence that smoking is detrimental to health⁴¹; have a less clear understanding of the etiological role of smoking in their illness, which reduces the likelihood of cessation⁴²; commonly believe that “the damage is done” and there is little to be gained from quitting⁴³; are more likely to believe that it is actually harmful to stop smoking or that nicotine replacement therapy could be harmful⁴⁴; and report many positive associations with smoking, which prevents a quit attempt.⁴³

The fact that smokers with FS were more likely than others to have an interest in quitting was not because they reported spending too much of their food (or other household essentials) money on cigarettes. The experience of FS, as defined in this research, is unique in that it produces a tangible threat to a person's material conditions of life. For example, not being able to pay rent poses the real threat of eviction and possible homelessness. It is perhaps this unique property of FS that leads a smoker to be seriously concerned about the financial consequences of smoking and thus have an interest in quitting smoking.

Previous research has shown that smokers with lower levels of education and income are less likely to have an interest in quitting.²⁰ It is interesting that while there is a close association between FS and lower socioeconomic status, they are correlated with interest in quitting in opposite directions. Lower socioeconomic smokers, compared to their higher socioeconomic counterparts, are not as motivated to quit smoking, perhaps because of their lower knowledge of the harms of smoking.³¹ However, smokers with FS who realize the possible financial consequences of smoking are likely to be motivated to quit, regardless of their socioeconomic position.

Although more motivated to quit, smokers with FS were less likely to try to quit and stay quit. The effect on trying only becomes clear when controlling for other predictors of quitting, again probably because of the fact that factors correlated with FS affect quitting activity in different ways. It is important to note that in the cessation analysis, among all the individual predictors including psychological stress, only FS and nicotine dependence had an effect. The reason psychological stress was not associated with quit success, but FS was, could be related to the way these concepts were measured in the present research. While psychological stress referred to having difficulties coping with problems of life in “general”, FS pertained to “specific” and consequential stressful experiences, such as the inability to pay rent. Previous research has shown that smokers who relapse often report that specific stressful experiences triggered their return to smoking.⁴⁵

Smokers with FS can especially benefit from quitting and not spending money on cigarettes. Recent research has shown that long-term cessation can lower the likelihood of experiencing financial stress and enhance material well-being.^{8 9} Smokers with FS thus are caught in a vicious cycle. Compared to others, they are less likely to quit, which means they are more likely to experience even more FS, which in turn makes it even harder to quit. Cessation treatment efforts should consider routinely assessing the FS status of their clients and providing additional counseling and resources for smokers who experience FS. At a broader level, the findings indicate that social policies that provide a safety net for people who might otherwise face severe financial problems, such as not being able to pay for rent or food, could have a favorable impact on cessation rates.