The Effectiveness of Cigarette Price and Smoke-Free Homes on Low-Income Smokers in the United States

Abstract

Objectives. We examined the effectiveness of state cigarette price and smoke-free homes on smoking behaviors of low-income and high-income populations in the United States.

Methods. We used the 2006–2007 Tobacco Use Supplement to the Current Population Survey. The primary outcomes were average daily cigarette consumption and successful quitting. We used multivariable regression to examine the association of cigarette price and smoke-free home policies on these outcomes.

Results. High state cigarette price (pack price ≥ $4.50) was associated with lower consumption across all income levels. Although low-income individuals were least likely to adopt smoke-free homes, those who adopted them had consumption levels and successful quit rates that were similar to those among higher-income individuals. In multivariable analysis, both policies were independently associated with lower consumption, but only smoke-free homes were associated with sustained cessation at 90 days.

Conclusions. High cigarette prices and especially smoke-free homes have the potential to reduce smoking behaviors among low-income individuals. Interventions are needed to increase adoption of smoke-free homes among low-income populations to increase cessation rates and prevent relapse.

High state cigarette prices^1–3 and clean indoor air laws^4–8 are 2 of the most effective tobacco control policies for decreasing tobacco use⁵ and increasing cessation on a population level.^4–6 These policies have been included in national surveillance surveys of tobacco use.⁹ Whether these policies are effective among lower-income as well as higher-income smokers is unclear. Some studies, including an econometric analysis,¹⁰ have suggested that price and clean air laws have a similar effect in reducing smoking behavior among lower- and higher-income smokers.^2,10,11 Others have suggested that such policies may be less effective for lower-income smokers^12–14 as they have a higher smoking prevalence,¹⁵ higher consumption rate per smoker,¹⁶ and lower rates of successful quitting^17–19 compared with higher-income smokers. Indeed, the prevalence of smoking among adults living below the federal poverty level (FPL) is almost 50% higher than the prevalence in the general population.¹⁵

Economic theory suggests that rising cigarette prices should reduce cigarette consumption more in low-income smokers compared with those with higher incomes.^{2,12,13,20–23} However, studies have shown that low-income smokers vary in their response to rising cigarette prices. Some individuals may compensate for higher prices by relying on lower-priced cigarette products (e.g., generic vs premium brands, discount vs convenience stores, or non–state-taxed products [e.g., from Indian reservations] vs taxed products).^23–29 Others who are motivated to quit may react to a price increase as an opportunity to quit smoking or reduce cigarette consumption.^3,21 One concern is that the higher prevalence of heavy smoking among low-income smokers may be evidence of impaired personal autonomy such that fewer are able to quit even with a price increase.³⁰ This in combination with the stress of coping with material or environmental constraints may pose significant challenges to smoking cessation.³¹ Another concern is that high cigarette prices can result in a significant financial burden for low-income smokers.³²

Social cognitive theory predicts that a person’s motivation to change behavior varies with the social norms of his or her environment.³³ Variability in smoking behaviors between low- and high-income smokers may result from different social norms related to smoking.³⁴ The passage of smoke-free policies in communities is one indicator of social norms related to smoking³⁵; a stronger marker is the prevalence of households with smokers who have voluntarily established a smoke-free home.⁶ Strong clean indoor air laws are associated with increased adoption of smoke-free homes among smokers and nonsmokers.^36,37 Smoke-free homes have been associated with reduced exposure to second-hand smoke among nonsmokers, and reduced smoking behaviors among smokers.^5,6,38 Lower-income adults are less likely than higher-income adults to adopt smoke-free homes,^39,40 reflecting differential smoking norms in the respective communities.

To determine whether cigarette prices and smoke-free home policies are effective among smokers of different income levels, we used the 2006–2007 Tobacco Use Supplement to the Current Population Survey (TUS-CPS), a nationally representative cross-sectional survey, to explore the association of these policies with smoking behaviors by income categories indexed on poverty status. The level of excise tax on tobacco products has differed considerably across states.⁴¹ Thus, we aggregated self-reported purchase price of cigarettes and compared across states. We examined whether average daily consumption and successful quitting differed by income levels among adults living in states with higher average cigarette prices compared with those with lower prices. We similarly assessed whether an income gradient existed in cigarette consumption and successful quitting among adults living in smoke-free homes relative to non–smoke-free homes. We examined the independent association of state cigarette price and smoke-free homes on smoking behaviors. We hypothesized that smoke-free homes would be a stronger predictor than price in reducing smoking behaviors because smokers may have access to a number of price-minimizing strategies^23,26 but lack similar strategies to minimize the effects of smoking restrictions.

METHODS

The Current Population Survey (CPS), a monthly survey conducted by the US Census Bureau, collects information on labor force characteristics for the noninstitutionalized population aged 15 years and older.⁴² The CPS uses a complex multistage probability sample of households selected from lists of addresses obtained from the 2000 Decennial Census of Population and Housing, and has a response rate greater than 90%.⁴² Tobacco Use Supplements (TUS) to the CPS are administered periodically.⁹ In 2006–2007, the CPS included the TUS in 3 independent monthly samples (May 2006, August 2006, and January 2007) and had a response rate of 62%.⁹ Our analysis was based on the 150 967 respondents to the 2006–2007 TUS-CPS who were aged 18 years and older, and for whom we had self-reports of both income and smoking.

The TUS-CPS used the standard national questions to probe tobacco use. Ever-smokers reported smoking more than 100 cigarettes in their lifetime. Ever-smokers were asked whether they smoked “every day, some days, or not at all.” We classified ever-smokers as current smokers and former smokers. Among current smokers, we estimated average daily cigarette consumption based on self-reports of cigarettes smoked on smoking days. We reported any previous lifetime quit attempt of at least 1 day. We classified current and former smokers who reported smoking in the previous 12 months as recent smokers.⁴³ Of the recent smokers who had made a quit attempt in the past 12 months, we determined the proportion who achieved an early marker of successful quitting, defined as a quit attempt lasting for 90 days or longer at the time of the survey.⁴⁴

Tobacco Control Policies

State cigarette prices.

Using the self-reported price per pack, we calculated the average pack price for each state and divided the range of prices into quartiles. In the lowest quartile of price (≤ $3.20; “lowest-priced states”) were the following 6 states: Georgia, Kentucky, Mississippi, Missouri, South Carolina, and West Virginia. In the highest quartile of price (≥ $4.50; “highest-priced states”) were the following 15 states: Alaska, Arizona, California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Michigan, Montana, New Jersey, New York, Rhode Island, Vermont, and Washington, plus Washington, DC. The third group (> $3.20 and < $4.50; “intermediate-priced states”) included the remaining 29 states (Alabama, Arkansas, Colorado, Delaware, Florida, Idaho, Indiana, Iowa, Kansas, Louisiana, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, South Dakota, Tennessee, Texas, Utah, Virginia, Wisconsin, and Wyoming). We used this 3-level ordinal variable as our measure of state cigarette price.

Smoking restrictions.

Participants were asked “Which statement best describes the rules about smoking inside your home: no one is allowed to smoke anywhere inside your home, smoking is allowed in some places or at some time inside your home, smoking is permitted anywhere inside your home.” We classified homes as smoke-free if individuals did not permit smoking anywhere inside their homes.

Income and Other Covariates

We used self-reported income and household size to classify respondents into the following income groups relative to the FPL: below FPL (< 100% FPL), low income (100%–199% FPL), moderate income (200%–299% FPL), and moderate to high income (≥ 300% FPL).⁴⁵

We included the following demographic measures: age group (18–24 years, 25–44 years, 45–64 years, and ≥ 65 years), gender, race/ethnicity (White, Hispanic/Latino, African American, Asian/Pacific Islander, and other), and education (< high school, high-school graduate, some college, and college graduate).

Statistical Analysis

The US Census Bureau provides survey weights for the TUS-CPS to account for selection probability attributable to sampling design and survey nonresponse.⁴² We calculated variance estimates by using these replicate weights constructed with Fay’s balanced repeated replications.^42,46 We examined sample characteristics by income level, and reported weighted proportions (PROC SURVEYFREQ for categorical variables and PROC SURVEYMEANS for continuous variables; SAS version 9.2, SAS Institute, Cary, NC). We replicated known trends of smoking behaviors by age, gender, race/ethnicity, and education,^47,48 and presented age-, gender-, race/ethnicity-, and education-standardized estimates (and 95% confidence intervals [CIs]) of these behaviors by income categories (standardized to the moderate- to high-income group) to minimize confounding by these variables. For each smoking behavior, we conducted multivariable regression analyses to obtain a P value for trend across income levels (PROC SURVEYLOGISTIC for categorical outcomes and PROC SURVEYREG for linear outcomes; we adjusted models for age, gender, race/ethnicity, and education).

For each policy (i.e., state cigarette price and smoke-free home), we examined whether there was an effect on consumption and quitting, stratified by income level. We reported average daily consumption by income level across states categorized by average cigarette price, and used unadjusted linear regression to obtain P values for trend by income. We reported the proportion of successful quitters by income level across states categorized by average cigarette price, and used unadjusted logistic regression to obtain P values for trend by income. We repeated this unadjusted analysis for the smoke-free home policy.

We conducted 2 multivariable regression models to examine the independent association of state cigarette price and smoke-free home policy on consumption and quitting. In model 1, we used multivariable linear regression for the outcome of consumption, and adjusted for age, gender, race/ethnicity, education, income, state cigarette price, and smoke-free home status. In model 2, we used multivariable logistic regression for the outcome of successful quitting, and adjusted for demographics, socioeconomic status, and policy covariates. As sensitivity analysis, we compared the results obtained with the self-reported pack price with that of the average retail pack price of cigarettes⁴⁹ using the same methodology to categorize states according to price. We conducted these analyses with SAS version 9.2 (SAS Institute, Cary, NC).

RESULTS

Compared with individuals in the higher-income groups, persons who were living below the FPL were more likely to be women, to belong to racial/ethnic minorities, and to have less than a high-school education (Table 1). Individuals who lived below the FPL were 38% more likely to be ever-smokers than those in the moderate- to high-income group (standardized prevalence 51.5% vs 37.3%; Table 2). Among the 62 908 ever-smokers, those who lived below the FPL were 21% less likely to have quit smoking than those in the moderate- to high-income group (standardized quit ratio 18.1% vs 22.7%). Individuals living below the FPL were more than twice as likely to be current smokers as those in the moderate- to high-income group.

TABLE 1—

Description of the US Population by Income Status, Tobacco Use Supplement to the Current Population Survey, 2006–2007

Characteristic	Below FPL (n = 17 233), Weighted %	Low Income (n = 27 541), Weighted %	Moderate Income (n = 28 400), Weighted %	Moderate–High Income (n = 77 793), Weighted %
Age, y*
18–24	23.8	17.1	13.8	8.7
25–44	37.4	36.8	37.9	38.9
45–64	23.4	23.9	28.9	41.9
≥ 65	15.4	22.2	19.4	10.5
Gender*
Men	39.8	44.8	48.5	52.3
Women	60.2	55.2	51.5	47.7
Race/ethnicity*
White	46.1	58.7	69.8	79.1
Hispanic	25.5	21.6	13.9	7.2
African American	22.2	14.2	11.6	7.4
Asian/Pacific Islander	4.3	3.9	3.5	5.4
Other	2.0	1.6	1.2	0.9
Education*
< high school	37.9	26.2	13.5	4.5
High school	32.6	38.5	37.7	22.9
Some college	21.9	25.9	31.6	29.4
College graduate	7.5	9.4	17.1	43.3
Geographical regiona,*
Highest-priced	35.1	35.2	35.4	41.6
Intermediate-priced	52.9	54.4	54.9	50.1
Lowest-priced	11.9	10.4	9.8	8.3

Note. FPL = federal poverty level.

^aHighest-priced states: average price per pack ≥ $4.50; lowest-priced states: average price per pack ≤ $3.20; intermediate-priced states: average price per pack > $3.20 and < $4.50.

*P < .001; represents differences by income level.

TABLE 2—

Standardized Estimates of Smoking and Quitting Behaviors by Income Status, Tobacco Use Supplement to the Current Population Survey, 2006–2007

Variable	Below FPL (n = 17 233), % (95% CI)	Low Income (n = 27 541), % (95% CI)	Moderate Income (n = 28 400), % (95% CI)	Moderate–High Income (n = 77 793), % (95% CI)
Smoking history
Ever smokers*	51.5 (41.8, 61.2)	45.6 (38.7, 52.5)	43.5 (38.1, 48.9)	37.3 (34.4, 40.2)
Current smoker*	33.1 (25.1, 41.1)	25.0 (19.1, 30.9)	21.5 (17.2, 25.8)	14.5 (12.4, 16.6)
Quit ratioa,*	18.1 (11.5, 24.7)	20.4 (14.5, 26.3)	21.7 (16.8, 26.6)	22.7 (20.5, 24.9)
Among current smokers
Average daily cigarette consumption, mean*	14.5 (10.9, 18.1)	14.4 (11.7, 17.1)	14.1 (11.6, 16.6)	13.3 (11.6, 15.0)
Ever made a quit attempt*	72.1 (57.6, 86.6)	73.1 (60.6, 85.6)	73.9 (62.5, 85.3)	75.4 (68.2, 82.6)
Smoke-free home*	31.7 (16.3, 47.1)	37.9 (23.5, 52.3)	40.5 (28.0, 53.0)	47.9 (40.1, 55.7)
Among recent smokersb
Quit attempt in the past 12 mo*	54.7 (33.9, 75.5)	47.7 (32.1, 63.3)	51.0 (37.1, 63.9)	51.2 (43.0, 59.4)
Successful quittingc,*	5.1 (–1.5, 11.7)	4.9 (–0.5, 10.3)	5.5 (0.0, 11.0)	6.9 (3.4, 10.4)
Smoke-free home*	34.3 (19.5, 49.1)	40.7 (26.6, 54.8)	43.4 (32.2, 54.6)	50.6 (43.2, 58.0)

Note. CI = confidence interval; FPL = federal poverty level. Percentage estimates were population weighted; standardized estimates were standardized to the moderate–high income group; standardized by age, gender, race/ethnicity, and education.

^aQuit ratio is the ratio of former smokers to ever-smokers.

^bRecent smokers were current or former smokers who reported smoking in the past 12 months.

^cSuccessful quitting defined as a quit attempt that lasted ≥ 90 days at the time of survey; ratio represents successful quitters to recent smokers.

*P < .05; P for trend by income obtained by using multivariable regression analysis adjusting for age, gender, race/ethnicity, and education.

Among the 28 489 current smokers, there was a linear trend in the standardized cigarette consumption, with individuals living below the FPL smoking on average 1 more cigarette per day than those in the moderate- to high-income group (range, 13–14 cigarettes per day; Table 2). Among the 31 111 recent smokers, 1688 had successfully quit at the time of the survey. The standardized successful quit rate for individuals living below the FPL was 5.1% compared with 6.9% among those in the moderate- to high-income group.

State Cigarette Price, Consumption, and Successful Quitting by Income

Current smokers living in states with the lowest cigarette prices smoked 22% more cigarettes per day than those living in states with the highest cigarette prices (16.3 vs 12.8; P < .001). Within each state group, the association between income level and cigarette consumption was small and was borderline significant in states with the highest prices (P trend = .054) and not significant in states with the lowest prices (P trend = 0.3; Figure 1a). Within each income level, there was a significant difference in consumption among state groups (P trend < .001). We observed little difference in successful quitting across states categorized by average cigarette price for those living below the FPL and those in the moderate- to high-income group (Figure 1b). Smokers in the middle-income groups in states with the lowest price appeared to have a lower rate of successful quitting than those within the same income bracket who were living in the intermediate- and highest-priced states. We observed increasing cessation with income within all 3 state categories.

FIGURE 1—

Effects of income level and average state-level cigarette price on (a) cigarette consumption and (b) successful quitting: Tobacco Use Supplement to the Current Population Survey, 2006–2007.

Note. FPL = federal poverty level. Below FPL (< 100% FPL); low income (100%–199% FPL); moderate income (200%–299% FPL), and moderate–high income (≥ 300% FPL).

^aP = .054 by income.

^bP < .001 by income.

^cP = .3 by income.

In sensitivity analysis, we compared the results of the self-reported price to the reported average price of all cigarettes per state. Using the retail price, income and price effects were attenuated but were qualitatively similar. For example, the difference in consumption between lowest- and highest-priced states was 18% (15.2 vs 12.5 cigarettes per day; P < .001) compared with 22% previously.

Smoke-Free Homes, Consumption, and Successful Quitting by Income

Current smokers who reported having a smoke-free home smoked 35% fewer cigarettes per day than those who did not (10.8 vs 16.5; P < .001). The prevalence of smoke-free homes was associated with income level: current smokers who were living below the FPL were less likely to have a smoke-free home compared with those in the higher-income groups (standardized prevalence 31.7% vs 47.9%; P < .001; Table 2).

Individuals living below the FPL who had a smoke-free home smoked fewer cigarettes (9.4 vs 15.4; P < .001) and had higher rates of successful quitting (7.9% vs 1.5%; P < .001) compared with individuals within the same income bracket who did not have a smoke-free home (Figures 2a and 2b). Individuals living below the FPL who had a smoke-free home had a slightly lower rate of successful quitting compared with those in the moderate- to high-income group (7.9% vs 10.9%; P < .001). For individuals without a smoke-free home, those living below the FPL had a successful quit rate of 1.6%, compared with 2.9% for those in the moderate- to high-income groups (P < .001).

FIGURE 2—

Effects of income level and smoke-free home status on (a) cigarette consumption and (b) successful quitting: Tobacco Use Supplement to the Current Population Survey, 2006–2007.

Note. FPL = federal poverty level. Below FPL (< 100% FPL); low income (100%–199% FPL); moderate income (200%–299% FPL), and moderate–high income (≥ 300% FPL).

^aP < .001 by income.

Multivariate Models of Consumption and Cessation

In model 1, we examined the association of state cigarette price and smoke-free homes on consumption. Individuals who were living in the highest-priced states consumed 2.2 (95% CI = −2.6, −1.9) fewer cigarettes daily compared with those living in the lowest-priced states, and individuals who had adopted smoke-free homes consumed 4.8 (95% CI = −4.9, −4.6) fewer cigarettes daily compared with those without, after we adjusted for covariates (table available as a supplement to the online version of this article at http://www.ajph.org).

In model 2, we examined the association of the 2 policies on successful quitting. Individuals who were living in the highest-priced states had similar odds of successfully quitting as those living in the lowest-priced states (adjusted odds ratio [AOR] = 1.0; 95% CI = 0.9, 1.0), whereas individuals who had a smoke-free home had 4.8-fold (95% CI = 4.4, 5.2) greater odds of successfully quitting compared with those without after we adjusted for covariates.

DISCUSSION

In this nationally representative sample, we investigated whether state cigarette price and smoke-free homes influenced smoking behavior for low-income as well as high-income smokers. High state cigarette price was associated with lower consumption across all income groups. Individuals who were living below the FPL who had a smoke-free home had substantially lower consumption and higher rates of successful quitting at 90 days compared with individuals within the same income bracket who did not. Although there was an income gradient in quitting among individuals with a smoke-free home, differences across income levels were much smaller than differences across smoke-free home status. These results highlight the potential importance of smoke-free homes in encouraging cessation and preventing relapse among low-income individuals.

Because estimates of smoking behaviors vary by demographic and socioeconomic status,^47,48 we standardized prevalence of smoking behaviors by these variables relative to the moderate- to high-income group. This allowed us to examine the association of smoking behaviors by income level, while minimizing the effects of confounding demographic and socioeconomic status variables. The standardized prevalence of current smoking was higher among individuals living below the FPL compared with individuals in the higher-income groups. Relative to the higher-income groups, significantly more individuals who were living below the FPL had initiated smoking and fewer had successfully quit smoking. These findings underscore a need for tobacco control efforts to focus on reducing smoking initiation and encouraging quitting behavior among low-income populations.

In this study, we relied on the self-reported cigarette price rather than the aggregate retail price for the state. The strength of this approach is that it factored in price-minimizing behaviors of low-income groups. In sensitivity analysis, models incorporating the retail price showed similar but attenuated effects. Consistent with previous studies,^10,50–52 low-income individuals were responsive to cigarette price increases. In the highest-priced states, cigarette consumption did not vary substantially between smokers living below the FPL and smokers with high incomes. However, low-income smokers who lived in the highest-priced states consumed significantly fewer cigarettes daily than smokers from the same income group who were living in the lowest-priced states. These results suggest that a cigarette price increase may be an effective public health intervention to reduce consumption among low-income smokers. However, one consequence of raising cigarette prices is the disproportionate increase in financial burden among low-income smokers.³² To minimize this possibility, revenue from cigarette excise taxes should be directed toward cessation programs that help low-income smokers quit as well as programs that alleviate their financial burden.³²

Some studies have demonstrated that high cigarette prices are associated with increased quit attempts^3,53,54; however, others have found that, despite major price increases in the past 2 decades, neither quit attempts nor successful quitting in the United States has increased.⁵⁵ In adjusted multivariable analysis, we found that high state cigarette price was not associated with successful quitting at 90 days, after we adjusted for covariates and a smoke-free home policy. This lack of a statistically significant effect of price on successful quitting in our adjusted models may have occurred because we were underpowered to detect moderate effect sizes. However, these results suggest that smoke-free homes may be a more important intervention than price to encourage successful quitting.

As demonstrated in previous studies,^39,40 we observed a significant increase in adoption of smoke-free homes with higher income levels. We observed this trend despite standardizing for demographic and socioeconomic variables that may be associated with the adoption of smoke-free homes. Several factors are associated with individuals’ decisions to adopt smoke-free homes including income status, educational attainment, presence of current smokers in the household, level of consumption of the smoker, and absence of young children in the household.^40,56 Current smokers who have high consumption and live with others smokers in the household are less likely to adopt smoke-free homes than those without these characteristics.⁶ Parents with older children are less likely to adopt smoke-free homes than parents of infants.⁴⁰ The low prevalence of smoke-free homes among low-income households, even after standardization for age, gender, race/ethnicity, and education, highlights the need to target social norms surrounding smoking among low-income individuals.

As with higher income levels, we found that individuals living below the FPL who had a smoke-free home had substantially lower consumption and higher quit rates than those who did not have them. The adoption of smoke-free homes may have lessened 90-day relapse among individuals who made a quit attempt. A smoke-free home may disrupt established smoking patterns such that individuals may smoke less or delay their first cigarette of the day because of the inconvenience of having to go outside to smoke.⁶ This may encourage smoking reduction or cessation attempts.⁶ Among those who have quit, a smoke-free home may prevent relapse because of the absence of environmental cues to initiate smoking (e.g., other smokers in the household).⁶ Our results underscore the need for interventions to encourage the adoption of smoke-free homes among low-income populations to increase cessation and prevent relapse. Such interventions may include public health interventions to increase regulation of secondhand smoke in public housing,^57,58 or educational interventions to increase adoption of these restrictions among low-income populations.^57–59

Our study had several limitations. We were unable to infer causality or temporal associations from our cross-sectional analysis. We relied on self-reports of income, cigarette price, home smoking restrictions, and smoking behaviors, resulting in a potential for misclassification bias. Although we anticipate this bias to be nondifferential, it is possible that income level influenced self-reports of price, smoking, and quitting. The small sample size of the lowest income group precluded us from conducting subgroup analyses. By standardizing to common demographic variables, we may have minimized confounding in the estimates of smoking behaviors, but at the expense of increasing variance in our estimates. By limiting successful quitting to 90 days, we increased the proportion of quitters who were labeled as successful, thereby increasing the power in our analysis. However, it is well known that up to half of these quitters will eventually relapse, possibly introducing bias.⁴⁴ We were unable to assess compensating behaviors (e.g., change in inhalation patterns) related to decreases in consumption among low- or high-income smokers.

The strength of the study is in the use of large survey data to examine the effects of 2 tobacco control policies on reducing smoking behaviors among low-income populations. Our study provides evidence that, within a certain price range, raising cigarette prices may be an effective strategy to reduce consumption among low-income smokers. To minimize the financial burden among low-income smokers, any price increase should be accompanied with programs that help low-income smokers quit. Our study also highlights opportunities for public health interventions to increase adoption of smoke-free homes among low-income populations as a strategy to reduce consumption and increase cessation.