Abstract
Objectives. We evaluated the impact of comprehensive statewide smoke-free indoor air laws on secondhand smoke (SHS) exposure, asthma prevalence, and asthma-related doctor visits.
Methods. We used the 2007–2011 Behavioral Risk Factor Surveillance System data sets. We employed a paired t test to determine whether comprehensive statewide smoke-free indoor air laws reduced SHS exposure. We performed weighted logistic and Poisson regressions to obtain likelihood of reporting asthma symptoms and incidence rate ratio (IRR) of doctor visits owing to severe asthma symptoms.
Results. After such laws were enacted, people in states with comprehensive smoke-free indoor air laws had a lower level of SHS exposure (P < .01), decreased odds of reporting current asthma symptoms (adjusted odds ratio [AOR] = 0.57; 95% confidence interval [CI] = 0.51, 0.63), and a decreased frequency of doctor’s visits owing to severe asthma symptoms (IRR = 0.80; 95% CI = 0.69, 0.92) than did their counterparts in fully adjusted models.
Conclusions. Comprehensive statewide smoke-free indoor air laws appear to be effective in reducing SHS exposure and improving asthma outcomes. Regulations requiring smoke-free indoor environments and public areas are beneficial, and smoke-free indoor air laws should be enforced in all states.
There is an increasing body of literature indicating that secondhand smoke (SHS) exposure has an adverse effect on health. SHS appears to be associated with a high risk of heart disease,1 acute stroke,2 and lung cancer.3 As the harmful consequences of SHS exposure have become increasingly recognized, the US federal government is urging state governments to establish policies to eliminate exposure to SHS. Accordingly, many states have enacted comprehensive statewide smoke-free indoor air laws to improve Americans’ public health by eliminating SHS exposure in 3 indoor locations: worksites, restaurants, and bars. However, not all states have comprehensive smoke-free laws that require the 3 locations to be smoke-free. In 2014, it was reported that only 26 states and the District of Columbia had comprehensive smoke-free laws, whereas 5 states had smoking bans in 2 of the 3 locations, 5 other states had smoking bans in 1 of the locations, and 14 states had no smoking restrictions, designated areas, or separate ventilation laws (Table 1).
TABLE 1—
US Smoke-Free Indoor Air Laws by State: 2014
| Regulation | State |
| Comprehensive smoke-free air laws | AZ, CO, DE, DC, HI, IL, IA, KS, ME, MD, MA, MI, MN, MT, NE, NJ, NM, NY, ND, OH, OR, RI, SD, UT, VT, WA, WI |
| Smoke-free in 2 locations | FL, IN, LA, NV, NC |
| Smoke-free in 1 location | AK, ID, NH, PA, TN |
| No smoking restrictions, designated areas, or separate ventilation law | AL, AK, CA, CT, GA, KY, MS, MO, OK, SC, TX, VA, WV, WY |
Source. Adapted from the State Tobacco Activities Tracking and Evaluation System, Office on Smoking and Health, the US Centers for Disease Control and Prevention.4
The literature indicates that smoke-free indoor air laws are an effective strategy in reducing SHS exposure.5 Implementing smoke-free laws was significantly associated with a reduction in SHS exposure for both hospitality workers in New York and bartenders in Wisconsin.6,7 A cross-sectional analysis of the 1999–2002 National Health and Nutrition Examination Survey data demonstrated that those living in counties with extensive smoke-free air law coverage were less exposed to SHS than were those residing in counties without a smoke-free air law.8 To date, however, no study has investigated whether state-level enactment of such smoke-free air laws has reduced SHS exposure across multiple states at a population level in the long term. Such a study would contribute to the literature by documenting the population-based long-term effects of state-level smoke-free air laws on SHS exposure.
SHS exposure is a significant risk factor for asthma and its exacerbation.9 Wheeze and physician-diagnosed asthma are more prevalent among children who are exposed to in-home SHS than among those who are not exposed to SHS.10 Several studies have explored the effect of smoke-free air laws on asthma prevalence and its exacerbation.11–14 One study noted that smoke-free air laws had a positive relation to reduced asthma symptoms in children aged 3 to 15 years.11 Another study found that emergency department visits owing to asthma among both children and adults decreased 22% after the implementation of a smoke-free air law in Lexington–Fayette County, Kentucky.12 In Scotland, the passage of smoke-free legislation was associated with a reduction in the rate of hospital admissions for childhood asthma,13 and in Arizona, hospital admissions for asthma decreased after a statewide smoking ban was implemented.14
However, these studies examined the effect of smoke-free air laws on asthma prevalence only in a specific age group (e.g., children) or 1 area (e.g., county or state) without control sites and without regard to the smoking status of the affected residents. The lack of control sites and the failure to take adults’ smoking status into account in these investigations threaten the internal validity of their findings. Also, the lack of a representative sample of larger geographic regions weakens the external validity of the findings. To yield findings with robust internal and external validity, a controlled design with a representative sample of nonsmoking adults in larger geographic regions is needed.
Using a controlled design, we evaluated whether comprehensive statewide smoke-free indoor air laws were effective in reducing SHS exposure in a representative sample of nonsmoking adults in the United States. We also investigated the extent to which such laws were associated with fewer asthma attacks and doctor visits owing to severe asthma symptoms.
METHODS
We derived our conceptual framework from Betty Neuman's model,15 which posits that asthma attacks among children are influenced by age, gender, socioeconomic status (parents’ educational level and employment status), emotional stress, physical exertion, dietary pattern, family history of asthma, SHS exposure, the use of pesticides, birth weight, premature birth, and the use of indoor combustion devices that burn fossil fuels, such as fireplaces and wood or coal stoves. Several studies have also noted that home dampness and molds and exposure to pets are also significant predictors for developing asthma.16–18
Because of the availability of information in the secondary data we used and our focus on adults rather than children, we modified Betty Newmen’s model and postulated that asthma attacks among adults are mainly attributable to the following 6 groups of risk factors:
SHS exposure,
gender,
socioeconomic status as determined by educational level and employment status,
the use of indoor combustion devices,
pets and other domestic animals in the home, and
molds in the home.
We hypothesized that comprehensive statewide smoke-free indoor air laws are effective in reducing SHS exposure among adults. We also hypothesized that such laws are associated with fewer asthma attacks and doctor visits owing to severe asthma symptoms when the known covariates of asthma attacks are controlled, including gender, educational level, employment status, the use of indoor combustion devices, pets or other domestic animals in the home, and molds in the home.
Research Design
We used a quasiexperimental, interrupted time series design with control groups. Our study covered a period of 5 years (2007–2011), including the period before statewide smoke-free indoor air laws were enacted (2007), when they were enacted (2008), and after they were enacted (2009–2011). The effective dates and types of restrictions of state smoke-free indoor air laws are available in the online supplemental material at http://www.ajph.org.
To determine the impact of the legislation on SHS exposure and asthma outcomes, we employed repeated cross-state comparisons. Because Iowa, Illinois, and Maryland enacted comprehensive statewide smoke-free indoor air laws in 2008 and had available data during 2007–2011, they constituted our experimental group. Texas and West Virginia constituted the control group because they did not have any statewide smoking restrictions, designated smoking areas, or separate ventilation laws.
Data and Study Participants
We analyzed data drawn from the 2007–2011 Behavior Risk Factor Surveillance System (BRFSS) Asthma Call-Back Survey (ACBS). The BRFSS provides state-based annual data regarding risk behaviors and preventive health practices among a representative sample of noninstitutionalized US adults.
The Air Pollution and Respiratory Health Branch of the National Center for Environmental Health developed and funded the ACBS as a national survey and subset of the BRFSS. The ACBS provides in-depth information about asthma at the state level. Eligible study participants were the BRFSS respondents who reported an asthma history within the past 12 months and those who were not current cigarette smokers.
Measures
The dependent variables were current asthma symptoms and the number of doctor visits owing to severe asthma symptoms. We measured current asthma symptoms as a binary variable (yes vs no). We measured the numbers of doctor visits owing to severe asthma symptoms as a count variable.
To measure SHS exposure, the key predictor, we used fine particulate matter (PM2.5, which is < 2.5 µm in diameter) data obtained from the US Environmental Protection Agency instead of the BRFSS-ACBS because BRFSS-ACBS has a lot (> 15%) of missing values on the questionnaire item that measures SHS exposure. It is recommended that this specific variable be deleted when 15% or more of the cases have missing data.19 Many studies have used PM2.5 to measure SHS exposure. For example, 1 study assessed the magnitude of SHS exposure in outdoor dining areas by measuring the concentrations of particulate pollution (PM2.5).20 We calculated annual average SHS exposure by dividing the sum of daily PM2.5 concentrations by the total number of observations during the year.
The Environmental Protection Agency provides additional information on daily PM2.5 concentration on exceptional event dates. Because of the undue influence of exceptional events on the SHS level, we excluded daily PM2.5 concentrations on exceptional event dates in our computations. Table 2 shows the mean PM2.5 concentration by state from 2007 to 2011.
TABLE 2—
Mean PM2.5 (μg/m3) Concentration: 2007–2011
| States With Comprehensive Smoke-Free Indoor Air Laws |
States Without Comprehensive Smoke-Free Indoor Air Laws |
||||
| Year | IL | IA | MD | TX | WV |
| 2007 | 13.4 | 12.1 | 13.5 | 10.5 | 15.1 |
| 2008 | 11.7 | 10.8 | 12.2 | 10.0 | 12.9 |
| 2009 | 11.3 | 10.6 | 10.4 | 9.3 | 11.3 |
| 2010 | 12.1 | 11.4 | 11.0 | 9.2 | 12.5 |
| 2011 | 11.9 | 10.4 | 10.7 | 10.0 | 11.1 |
We measured gender as a binary variable (female or male), current employment status as a categorical variable (full time, part time, or not employed), education level as a categorical variable (did not graduate from high school, graduated from high school, attended college or technical school, and graduated from college or technical school), and the use of indoor combustion devices, pets or other domestic animals in the home, and molds in the home as binary indicators (yes vs no).
We created 2 dummy variables for this study: 1 that indicates pre–post enactment of smoke-free indoor air laws (i.e., 2007–2008 vs 2009–2011) and another that indicates the presence of smoke-free indoor air laws (i.e., states with smoke-free indoor air laws vs states without smoke-free indoor air laws). We examined interaction effects between the 2 dummy variables to capture the impact of smoke-free indoor air laws on outcome variables, adjusting for the pre- and postenactment of such laws.
Statistical Analysis
To test the first hypothesis, that comprehensive statewide smoke-free indoor air laws are effective in reducing SHS exposure, we performed the paired t test at the .05 level by examining changes in mean SHS exposure before and after the legislation was enacted. We computed the mean difference in SHS exposure between 2007 and 2011 in the experimental and control groups.
To test the second hypothesis, that such laws are associated with fewer asthma symptoms or doctor visits owing to severe asthma symptoms, we used the χ2 test for the categorical outcome (presence of current asthma symptoms) and the count response outcome (number of doctor visits owing to severe asthma symptoms). We used logistic regression analysis to examine the adjusted odds ratios (AORs) of the presence of such smoke-free indoor air laws in predicting current asthma symptoms. We conducted Poisson regression to examine whether the presence of such laws can predict the number of doctor visits owing to severe asthma symptoms. We calculated the incidence rate ratio (IRR), the exponential of an estimated Poisson parameter estimate, to report the number of doctor visits. We conducted all statistical analyses using SAS version 9.3 (SAS Institute, Cary, NC) and weighted all statistical analyses by ACBS final weights, which adjusted the BRFSS weights, because ACBS is a subset of the BRFSS.
RESULTS
Table 3 outlines the descriptive statistics of the study sample. The majority of the study sample were women, were employed full time or unemployed, and had a high school diploma or higher. From 2007 to 2011, current asthma symptoms decreased slightly in the experimental group, whereas they increased slightly in the control group. Overall, the number of doctor visits owing to severe asthma symptoms was lower in the experimental group than in the control group.
TABLE 3—
Descriptive Statistics of Study Sample by Treatment: United States, 2007–2011
| Experimental Group, No. (%) or Mean ±SD |
Control Group, No. (%) or Mean ±SD |
|||||||||
| Variable | 2007 (n = 287) | 2008 (n = 310) | 2009 (n = 264) | 2010 (n = 259) | 2011 (n = 223) | 2007 (n = 196) | 2008 (n = 236) | 2009 (n = 286) | 2010 (n = 319) | 2011 (n = 277) |
| Gender | ||||||||||
| Male | 90 (31.4) | 76 (24.5) | 68 (25.8) | 64 (24.7) | 56 (25.1) | 40 (20.4) | 59 (25.0) | 59 (20.6) | 68 (21.3) | 57 (20.6) |
| Female | 197 (68.6) | 234 (75.5) | 196 (74.2) | 195 (75.3) | 167 (74.9) | 156 (79.6) | 177 (75.0) | 227 (79.4) | 251 (78.7) | 220 (79.4) |
| Employment status | ||||||||||
| Full time | 130 (45.3) | 124 (40.0) | 105 (39.8) | 107 (41.3) | 78 (35.0) | 60 (30.6) | 81 (34.3) | 98 (34.3) | 100 (31.4) | 69 (24.9) |
| Part time | 34 (11.9) | 47 (15.2) | 29 (11.0) | 25 (9.7) | 23 (10.3) | 13 (6.6) | 21 (8.9) | 36 (12.6) | 33 (10.3) | 29 (10.5) |
| Not employed | 123 (42.8) | 139 (44.8) | 130 (49.2) | 127 (49.0) | 122 (54.7) | 123 (62.8) | 134 (56.8) | 152 (53.2) | 186 (58.3) | 179 (64.6) |
| Educational level | ||||||||||
| Did not graduate from high school | 19 (6.6) | 20 (6.5) | 19 (7.2) | 14 (5.5) | 8 (3.6) | 30 (15.3) | 27 (11.5) | 22 (7.7) | 41 (12.9) | 26 (9.4) |
| Graduated from high school | 86 (30.0) | 73 (23.5) | 63 (23.9) | 76 (29.3) | 52 (23.3) | 58 (29.6) | 65 (27.5) | 64 (22.4) | 77 (24.1) | 65 (23.5) |
| Attended college or technical school | 71 (24.7) | 82 (26.5) | 68 (25.7) | 70 (27.0) | 80 (35.9) | 49 (25.0) | 68 (28.8) | 80 (28.0) | 95 (29.8) | 89 (32.1) |
| Graduated from college or technical school | 111 (38.7) | 135 (43.5) | 114 (43.2) | 99 (38.2) | 83 (37.2) | 59 (30.0) | 76 (32.2) | 120 (41.9) | 106 (33.2) | 97 (35.0) |
| Molds in the home | ||||||||||
| No | 244 (85.0) | 271 (87.4) | 224 (84.9) | 221 (85.3) | 199 (89.2) | 168 (85.7) | 215 (91.1) | 260 (90.9) | 275 (86.2) | 248 (89.5) |
| Yes | 43 (15.0) | 39 (12.6) | 40 (15.2) | 38 (14.7) | 24 (10.8) | 28 (14.3) | 21 (8.9) | 26 (9.1) | 44 (13.8) | 29 (10.5) |
| Pets or domestic animals in the home | ||||||||||
| No | 124 (43.5) | 148 (47.7) | 131 (49.6) | 130 (50.2) | 107 (48.0) | 95 (48.5) | 121 (51.3) | 126 (44.1) | 134 (42.0) | 115 (41.5) |
| Yes | 162 (56.5) | 162 (52.3) | 133 (50.4) | 129 (49.8) | 116 (52.0) | 101 (51.5) | 115 (48.7) | 160 (55.9) | 185 (58.0) | 162 (58.5) |
| Use of indoor combustion devices | ||||||||||
| No | 269 (93.7) | 297 (95.8) | 248 (93.9) | 242 (93.4) | 212 (95.1) | 175 (89.3) | 215 (91.1) | 256 (89.5) | 297 (93.1) | 259 (93.5) |
| Yes | 18 (6.3) | 13 (4.2) | 16 (6.1) | 17 (6.6) | 11 (4.9) | 21 (10.7) | 21 (8.9) | 30 (10.5) | 22 (6.9) | 18 (6.5) |
| Secondhand smoke exposure | 13.13 ±0.58 | 10.76 ±0.40 | 10.72 ±0.37 | 11.41 ±0.43 | 11.04 ±0.66 | 12.26 ±2.24 | 9.97 ±0.95 | 9.87 ±0.92 | 9.85 ±1.32 | 10.22 ±0.44 |
| Current asthma | ||||||||||
| No | 107 (37.3) | 119 (38.4) | 124 (47.0) | 109 (42.0) | 93 (41.7) | 68 (34.7) | 92 (39.0) | 103 (36.0) | 113 (35.4) | 97 (35.0) |
| Yes | 180 (62.7) | 191 (61.6) | 140 (53.0) | 150 (58.0) | 130 (58.3) | 128 (65.3) | 144 (61.0) | 183 (64.0) | 206 (64.6) | 180 (65.0) |
| No. of doctor visits | 1.25 ±2.64 | 1.32 ±2.28 | 1.02 ±1.50 | 1.48 ±3.73 | 1.04 ±2.09 | 1.69 ±2.92 | 1.22 ±2.37 | 1.61 ±3.97 | 1.22 ±2.30 | 1.27 ±1.82 |
The mean difference in SHS exposure in the experimental group between 2007 and 2011 was significant at the .05 level, whereas that in the control group was not significant (P = .42), supporting our first hypothesis.
Current Asthma Prevalence
Table 4 shows the results of the logistic regression analysis of asthma symptoms on covariates, including the 2 dummy variables (pre–post enactment of smoke-free indoor air laws, reflecting within-state changes, and the presence of such laws, reflecting between-state changes) and their interaction effect. As expected, SHS exposure was associated with increased odds of reporting current asthma symptoms, controlling for other covariates (AOR = 1.07; 95% CI = 1.05, 1.10).
TABLE 4—
Weighted Results of Logistic Regression and Poisson Regression: 2007–2011
| Variable | Logistic Regression Predicting Asthma Symptoms, AOR (95% CI) | Poisson Regression Predicting the No. of Doctor Visits Owing to Severe Asthma Symptoms, IRR (95% CI) |
| Secondhand smoke exposure | 1.07* (1.05, 1.10) | 1.04* (1.01, 1.07) |
| Gender | ||
| Male (Ref) | 1.00 | 1.00 |
| Female | 1.63* (1.50, 1.76) | 1.42* (1.30, 1.56) |
| Employment status | ||
| Full time (Ref) | 1.00 | 1.00 |
| Part time | 1.27* (1.06, 1.53) | 1.05 (0.90, 1.18) |
| Not employed | 1.54* (1.49, 1.61) | 1.51* (1.39, 1.64) |
| Educational level | ||
| Did not graduate from high school (Ref) | 1.00 | 1.00 |
| Graduated from high school | 1.11 (0.97, 1.28) | 1.04 (0.91, 1.19) |
| Attended college or technical school | 1.32* (1.19, 1.47) | 1.11 (0.98, 1.26) |
| Graduated from college or technical school | 1.04 (0.92, 1.17) | 0.90 (0.86, 1.12) |
| Molds in the home | ||
| No | 0.68* (0.64, 0.71) | 0.86* (0.78, 0.95) |
| Yes (Ref) | 1.00 | 1.00 |
| Pets or domestic animals in the home | ||
| No | 1.19* (1.14, 1.26) | 1.04 (0.97, 1.11) |
| Yes (Ref) | 1.00 | 1.00 |
| Use of indoor combustion devices | ||
| No | 0.82* (0.74, 0.90) | 1.03 (0.92, 1.20) |
| Yes (Ref) | 1.00 | 1.00 |
| Enactment of laws | ||
| Pre (Ref) | 1.00 | 1.00 |
| Post | 1.32* (1.28, 1.36) | 0.98 (0.89, 1.09) |
| Presence of laws | ||
| No (Ref) | 1.00 | 1.00 |
| Yes | 0.86* (0.81, 0.92) | 0.94 (0.84, 1.05) |
| Presence of laws pre–post enactment | 0.57* (0.51, 0.63) | 0.80* (0.69, 0.92) |
Note. AOR = adjusted odds ratio; CI = confidence interval; IRR = incidence rate ratio. We ran both regressions with all the variables shown in the table included in each model.
*P < .01.
Women were more likely than men to report current asthma symptoms (AOR = 1.63; 95% CI = 1.50, 1.76). Those who were employed part time (AOR = 1.27; 95% CI = 1.06, 1.53) and who did not work (AOR = 1.54; 95% CI = 1.49, 1.61) were more likely than those who were employed full time to report current asthma symptoms in the adjusted logistic model. Attending college or technical school was associated with increased odds of reporting current asthma symptoms compared with not graduating from high school, controlling for other covariates (AOR = 1.32; 95% CI = 1.19, 1.47). The absence of molds in the home (AOR = 0.68; 95% CI = 0.64, 0.71) and not using indoor combustion devices (AOR = 0.82; 95% CI = 0.74, 0.90) were associated with decreased odds of reporting current asthma symptoms.
Interestingly, the absence of pets or other domestic animals (AOR = 1.19; 95% CI = 1.14, 1.26) was associated with increased odds of reporting current asthma symptoms, which is in line with the findings of previous studies.23,24 Although it is inconclusive, published findings show that early exposure to pets or other domestic animals is associated with a lower prevalence of asthma or asthma-like symptoms.23,24 A study explains that many of the children exposed to cats at home can develop an immune response that does not include immunoglobulin E, an antibody that plays a major role in allergic asthma.25
The presence of smoke-free indoor air laws (AOR = 0.86; 95% CI = 0.81, 0.92) was associated with decreased odds of reporting current asthma symptoms. When the interaction was considered, it was found that, after the enactment of smoke-free indoor air laws, nonsmoking adults in states with such laws showed decreased odds of reporting current asthma symptoms (AOR = 0.57; 95% CI = 0.51, 0.63) compared with those living in states without such laws in the fully adjusted models.
Number of Doctor Visits Owing to Asthma Attacks
Table 4 also shows the results of the Poisson regression analysis of the number of doctor visits owing to severe asthma symptoms on covariates including the 2 dummy variables of pre–post enactment of smoke-free indoor air laws (reflecting within-state changes) and the presence of such laws (reflecting between-state changes). We also examined the interaction effect between 2 dummy variables.
SHS exposure was associated with an increased frequency of doctor visits owing to severe asthma symptoms (IRR = 1.04; 95% CI = 1.01, 1.07), adjusting for other covariates. Women and the unemployed were 1.42 times and 1.51 times, respectively, more likely to visit a doctor owing to severe asthma attacks than were men (IRR = 1.42; 95% CI = 1.30, 1.56) and the employed (IRR = 1.51; 95% CI = 1.39, 1.64). The absence of molds at home (IRR = 0.86; 95% CI = 0.78, 0.95) was associated with a decreased frequency of doctor visits owing to severe asthma attacks.
When we considered the interaction, after the enactment of smoke-free indoor air laws, nonsmoking adults showed a decreased frequency of doctor visits owing to severe asthma symptoms (IRR = 0.80; 95% CI = 0.69, 0.92) compared with those living in places without such laws in the fully adjusted models.
DISCUSSION
This research was one of the first investigations of the effects of comprehensive smoke-free indoor air laws on SHS exposure, asthma prevalence, and its exacerbation at the population level using a controlled design with nationally representative samples of nonsmoking adults in the United States. An estimated 88 million nonsmokers in the United States are exposed to SHS.26 In view of the large number of people who are still exposed to SHS, implementing an effective regulatory policy to eliminate SHS exposure is warranted.
We found a significant reduction in the level of SHS exposure among states with comprehensive smoke-free indoor air laws after the legislation was enacted. This finding adds to the evidence that enacting smoke-free indoor air laws is an effective strategy in reducing SHS exposure.5–8 Especially because designated smoking rooms and ventilation systems are not effective in reducing SHS exposure,27,28 it is critically important to implement a comprehensive smoking ban in all indoor areas to protect nonsmokers from exposure to SHS.
The major finding of our study is that nonsmoking adults in the states that enacted smoke-free indoor air laws showed decreased odds of reporting current asthma symptoms and fewer doctor visits owing to severe asthma symptoms than did nonsmoking adults in states without such laws.
Asthma is one of the major health concerns in the United States. It has been estimated that approximately 18.7 million adults aged 18 years or older and 7 million children aged 0 to 17 years were reported as having asthma symptoms in 2010.29 Asthma is a costly disease because of its economic burden. The total per person annual cost of asthma is estimated to be $4912 (direct cost: $3180, indirect cost: $1732).30 We have demonstrated the efficacy of the enactment of comprehensive smoke-free indoor air laws in reducing asthma symptoms and the number of doctor visits owing to severe asthma symptoms in a fully adjusted model. Several previous studies support our findings although their samples were not representative of the entire nation. These findings converge on the importance of SHS exposure control at the population level in reducing asthma prevalence and incidence. Mandating comprehensive statewide smoke-free indoor air laws may contribute significantly to better asthma outcomes.
Our findings suggest the benefits of enacting legislation or a similar regulatory approach requiring a smoke-free indoor environment for all enclosed areas as well as public areas. For states with a public smoking ban in place, adequate implementation and enforcement of the laws are necessary to protect people from the hazards of SHS exposure. Regardless of such laws, because of the detrimental effect of SHS exposure, the implementation of educational strategies appears to be imperative for minimizing SHS exposure in any enclosed space, including private vehicles and rooms, as recommended by the World Health Organization.31
This study has limitations. First, we considered only 5 years of data to assess the effect of enacting smoke-free indoor air laws. This period might not be long enough to capture the effects on asthma outcomes. Second, the BRFSS-ACBS data set relied on self-reports of the number of doctor visits owing to severe asthma symptoms. Thus, recall bias might have confounded the findings.
Despite these limitations, our results contribute to the literature by providing strong evidence of the impact of comprehensive statewide smoke-free indoor air laws on SHS exposure and asthma prevalence and related doctor visits. Policymakers and lawmakers should make extra efforts to strengthen smoke-free environments and enforce comprehensive statewide smoke-free indoor air laws in all states of the nation. Health practitioners and educators should actively employ evidence-based educational strategies to help people avoid SHS exposure in any enclosed space.
Human Participant Protection
This study was exempted from institutional review board approval at the authors’ institutions because the data is publically available.
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