Abstract
Significant disparities exist between rural-urban U.S. populations. Besides higher smoking rates, rural Americans are less likely to be protected from SHS. Few studies focus across all regions, obscuring regional-level differences. This study compares support for SHS restrictions across all HHS regions. Data: 2014/15 TUS-CPS; respondents (n=228,967): 47,805 were rural residents and 181,162 urban. We examined bi-variates across regions and urban-rural adjusted odds ratios within each. Smoking inside the home was assessed along with attitudes toward smoking in bars, casinos, playgrounds, cars, and cars with kids. Urban respondents were significantly more supportive of all SHS policies:(e.g. smoking in bars [57.9% vs. 51.4%]; support for kids in cars [94.8% vs. 92.5%]. Greatest difference between urban-rural residents was in Mid-Atlantic (bar restrictions) and Southeast (home bans): almost 10% less supportive. Logistic regression confirmed rural residents least likely, overall, to support SHS in homes (OR=.78, 95% CI [.74, .81); in cars (OR= .87, 95% CI .79,.95), on playgrounds (OR=.88, 95% CI.83,.94) and in bars OR =.88, 95% CI .85,.92), when controlling for demographics and smoking status. South Central rural residents were significantly less likely to support SHS policies-home bans, smoking in cars with kids, on playgrounds, in bars and casinos; while Heartland rural residents were significantly more supportive of policies restricting smoking in cars, cars with kids and on playgrounds. Southeast and South Central had lowest policy score with no comprehensive state-level SHS policies. Understanding differences is important to target interventions to reduce exposure to SHS and related health disparities.
Keywords: disparities, secondhand smoke, rural, TUS-CPS, tobacco control, policy
INTRODUCTION
It is well established that significant health disparities exist between rural and urban areas of the United States [1]. Rural residents have higher rates of cancer, chronic diseases, and disability, as well as increased mortality rates and poorer overall health, which all contribute to their lower life expectancies [2–4]. Many factors have been implicated to account for these disparities, including lower socio-economic status, higher rates of health risk behaviors, lack of economic opportunities and geographic isolation. Rural residents are older, have less access to health care and are more likely to lack health insurance [5]. Adults who live in rural areas have among the highest smoking rates in the country, consume more cigarettes and use more smokeless/spit tobacco than their urban counterparts [6–9]. This high rate of tobacco use is directly linked to rural populations’ having worse health outcomes than those in urban areas and the country as a whole. However, rural regions are not homogeneous as they differ substantially by demographic, cultural, geographic and economic factors [10,11]. Yet no studies of rural/urban disparities in cigarette use have examined differences across all regions possibly obscuring marked regional-level differences. In addition, rural/urban differences in attitudinal support for tobacco control policies—specifically, different types of secondhand smoke (SHS) policies have received minimal attention [12–14].
Rural areas have historically been underserved by tobacco control programs, lack access to prevention and cessation services, and are less likely to have implemented protective tobacco control policies [11–15]. It has been reported that rural Americans are more likely to live in homes where smoking is permitted, more likely to smoke in their cars, more likely to work in settings where smoking is permitted, more apt to shop in stores where smoking is allowed, and to dine in restaurants where smoking is allowed [15,16]. Thus, taking a more in-depth, geographical perspective could highlight the connections between the underlying factors that influence support for secondhand smoke (SHS) policies and help improve adoption and implementation of SHS policies.
In trying to implement SHS policies, many reasons have been asserted as to why these restrictions are necessary, including health concerns, protecting children, reducing litter and de-normalizing smoking [17]. Bans have been imposed mostly indoors—in public places, and in such establishments as worksites, bars and casinos [18, 19]. More recently, they have also been extended to such outdoor areas as parks, playgrounds and beaches [17, 20]. In addition, bans have been extended into private spaces, such as cars and multi-unit housing, and individuals have instituted home bans [16, 21]. Outdoor smoking restrictions, as well as any restrictions in non-public settings, may be more controversial and less supported by rural residents [18]. The difference in support for SHS restrictions in rural areas may not be due to a lack of knowledge about dangers of SHS. Differences in norms, cultural and psychological factors, more negative media coverage and even less tobacco control capacity are important factors to consider [22–25]. In addition, support for smoke-free policies tends to increase after implementation and not all states have comprehensive SHS policies [26, 27].
This study examines rural-urban disparities in attitudes toward and support of SHS restrictions, including progressive policies (e.g., home bans, outdoor restrictions); smoking in bars and casinos (establishment restrictions); and restrictions to protect children in cars and on playgrounds (kid protections) across all U.S. regions. The study objective is to gauge how support for various SHS restrictions differs between rural and urban respondents both nationwide and within each of the regions of the country. We provide estimates adjusted for demographics and smoking status as well as unadjusted estimates for each region.
METHODS
Data
The study data are from the 2014/2015 Tobacco Use Supplement to the Current Population Survey (TUS-CPS), fielded in July 2014, January 2015, and May 2015. The TUS-CPS queries approximately 240,000 non-institutionalized current civilian U.S. adults 18 years and older, including 50 states and the District of Columbia, about their tobacco product use with demographics available from the core CPS. All respondents were asked about their attitudes toward smoking. Items from the TUS-CPS are either self-reported or provided by proxy. Households were selected based on the 2000 Census where the United States was subset into primary sampling units (PSUs), which were then grouped into strata within state. Of the total sample (n=228,967), 47,805 were rural residents and 181,162 were urban residents.
Measures
Demographics
Other respondent socio-demographic characteristics in this study included: sex (male, female); age (18–24; 25–44; 45–64; 65+); race/ethnicity (Hispanic, Non-Hispanic white, Non-Hispanic black or African-American, Non-Hispanic all other races); and family income (less than $20,000, between $20,000 and $49,999, and greater than $49,999).
Secondhand smoke
Respondents were first asked about smoking rules inside the homes; responses included “No one is allowed to smoke anywhere inside your home”, “Smoking is allowed in some places or at sometimes inside your home”, or “Smoking is permitted anywhere inside your home”. If one household member reported that smoking was not allowed anywhere inside the home, then all householder members were coded as disallowing smoking inside the home. Respondents were then directed to five questions that reflected the respondent’s attitudes towards smoking inside various places, specifically: bars, casinos, playgrounds, cars where other people are present, and cars where children are present. All items were asked with the following response options: “Always be allowed”, “Be allowed under some conditions”, and “Never be allowed”. For all analyses, “Always be allowed” and “Be allowed under some conditions” were combined.
In addition, two composite attitude scores were created and standardized for comparison: protecting kids (cars where children are present and playgrounds), and smoking in establishments (casinos and bars). For each question, respondents who reported smoking should “always be allowed” or “be allowed under some conditions” were scored −1, respondents who reported smoking should “never be allowed” were scored as 1, and those who reported they did not know if smoking should be allowed were scored as 0. If respondents reported smoking should “never be allowed” in cars, then they were similarly scored as “never be allowed” in cars with kids. The scores were summed and divided by the number of questions to create a value ranging from −1 to 1.
Statewide Policies
Aggregated SHS regional policy scores were created by utilizing the American Nonsmokers’ Rights Foundation’s analysis of 100% Smokefree Air Laws for non-hospitality workplaces, restaurants, and bars as of July 1, 2015 maps [28]. First, each state was given a score of either 0 for states with no state-wide laws, 1 for states with 100% statewide SHS laws in one or two of the three places, or 3 for states with 100% statewide laws in all three locations. Next, scores were averaged across the region using the weighted respondent counts of the TUS to closely mirror the population from the analysis
Smoking status
Current smoking, conditioned on whether the respondent reported ever smoking 100 cigarettes in his/her lifetime, was determined by response to a question whether the respondent “now smoke[s] cigarettes every day, some days, or not at all.” An indicator variable distinguished current smokers from non-smokers (former and never smokers).
Geography
Households are first classified as either rural (nonmetropolitan) or urban (metropolitan) using the Census TUS-CPS public use file’s OMB county-level definition; the public use file does not provide the necessary information to classify respondents with another definition of rurality. Respondents are further classified into 10 HHS regions to allow for a comparison between rural regions and each rural region to the corresponding urban population. HHS regions cluster groups of states together. Region 1 (New England: CT, ME, MA, NH, RI, VT); Region 2 (NY,NJ); Region 3 (Mid-Atlantic: DE, DC, MD, PA, VA, WV); Region 4 (Southeast: AL, FL, GA, KY, MS, NC, SC, TN); Region 5 (East North Central: IL, IN, MI, MN, OH,WI); Region 6 (South Central: AR, LA, NM, OK, TX); Region 7 (Heartland: IA, KS, MO, NE); Region 8 (North Central Mountain: CO, MT, ND, SD, UT, WY); Region 9 (Southwest Pacific: AZ, CA, HI, NV); and Region 10 (Northwest: AK, ID, OR, WA).
Analysis
Estimates were age-adjusted to the year 2000 standard population to eliminate differences in observed estimates that result from differences in the age distribution of the populations. Chi-square tests were used to compare percentages of subpopulations that reported that smoking should never be allowed. ANOVA tests were used to compare means of the indices across rural HHS regions, using a Bonferroni adjustment to correct for multiple comparisons. Similarly, t-tests were performed to compare rural and urban respondents nationally. Multivariate logistic regression analyses nationally and for each of 10 HHS regions and six policies were performed to compare rural and urban attitudes while controlling for age, sex, race/ethnicity, income, and smoking status. Across all statistical tests corrected standard errors were calculated with the complex survey design in mind and were based on the CPS sample weight for self-report interviews and the appropriate CPS replicate weights. Associations and covariates were considered significant across all statistical tests at the p<0.05 level. The data analysis for this paper was generated using SAS® 9.4 software, 2002–2012 by SAS Institute Inc. Cary, NC, USA.
RESULTS
3.1. Demographics
Table 1 shows demographics and smoking prevalence across the 10 HHS rural regions as well as the national average of rural and urban values. When comparing rural to urban areas, the HHS regions differ significantly on all the measured demographic areas except gender. Current smoking also differs significantly with the national rural vs. urban prevalence rate being 19.5% vs. 12.3%, respectively. The national level, current rural e-cigarette use was greater among rural adults than urban adults (2.8% vs 2.1%, respectively; p<0.001). Smoking prevalence also differed across regions. The Southeast has the highest rural current smoking prevalence (21%) and the Southwest Pacific has the lowest rural smoking prevalence (14.7%).
Table 1:
2014–2015 TUS-CPS: Socio-demographic characteristics of all respondents, by region and rural/urban status, weighted
| HHS Region | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | National | ||
| Sample Size | U | 15,078 | 12,939 | 22,912 | 28,601 | 23,856 | 21,123 | 8,797 | 10,605 | 26,739 | 10,512 | 181,162 |
| R | 5,797 | 578 | 4,037 | 9,211 | 6,243 | 4,657 | 4,221 | 8,332 | 1,742 | 2,987 | 47,805 | |
| Distribution, % | ||||||||||||
| Female | U | 52.3 | 52.3 | 52.2 | 52.4 | 51.9 | 51.5 | 51.5 | 50.8 | 51.3 | 50.9 | 51.8 |
| R | 50.1 | 53.2 | 52.3 | 52.8 | 50.8 | 52.6 | 51.3 | 48.9 | 51.5 | 50.8 | 51.7 | |
| Race | ||||||||||||
| White | U | 84.8 | 71.0 | 74.4 | 74.9 | 81.5 | 78.3 | 84.6 | 91.3 | 73.9 | 84.7 | 77.4 |
| R | 96.8 | 94.4 | 91.2 | 74.1 | 95.7 | 84.3 | 95.3 | 92.2 | 78.1 | 87.5 | 86.7 | |
| Black | U | 7.7 | 16.3 | 18.5 | 20.3 | 12.8 | 14.1 | 9.7 | 3.0 | 6.2 | 3.2 | 13.1 |
| R | 0.8 | 2.6 | 7.8 | 21.8 | 1.4 | 9.5 | 1.5 | 0.5 | 1.4 | 0.3 | 8.4 | |
| Hispanic | U | 9.0 | 17.9 | 6.6 | 13.6 | 7.5 | 29.7 | 5.5 | 12.4 | 33.1 | 9.4 | 17.0 |
| R | 1.8 | 1.0 | 2.2 | 3.6 | 2.3 | 20.0 | 4.2 | 6.6 | 20.8 | 10.5 | 6.1 | |
| Other | U | 7.5 | 12.7 | 7.1 | 4.8 | 5.6 | 7.5 | 5.7 | 5.7 | 19.9 | 12.1 | 9.4 |
| R | 2.4 | 3.0 | 1.0 | 4.1 | 2.9 | 6.2 | 3.2 | 7.3 | 20.5 | 12.2 | 4.9 | |
| Age | ||||||||||||
| 18–24 | U | 12.1 | 13.0 | 12.7 | 12.0 | 12.5 | 13.8 | 12.1 | 11.4 | 13.7 | 11.5 | 12.7 |
| R | 11.1 | 9.6 | 12.7 | 11.5 | 11.3 | 13.1 | 12.4 | 11.9 | 11.7 | 12.5 | 11.8 | |
| 25–64 | U | 68.5 | 68.2 | 68.4 | 68.4 | 68.4 | 70.7 | 69.9 | 72.7 | 69.2 | 70.5 | 69.1 |
| R | 65.9 | 66.8 | 62.7 | 65.5 | 64.7 | 64.8 | 63.1 | 68.1 | 63.9 | 63.3 | 64.8 | |
| 65+ | U | 19.4 | 18.7 | 18.9 | 19.6 | 19.1 | 15.5 | 18.1 | 15.9 | 17.1 | 18.0 | 18.2 |
| R | 23.0 | 23.6 | 24.6 | 23.0 | 24.0 | 22.1 | 24.6 | 20.0 | 24.4 | 24.3 | 23.4 | |
| Income | ||||||||||||
| <$20k | U | 12.4 | 14.5 | 11.8 | 18.3 | 14.0 | 17.5 | 12.5 | 11.0 | 15.0 | 11.9 | 14.9 |
| R | 13.6 | 20.1 | 19.8 | 28.9 | 17.7 | 22.3 | 20.0 | 16.8 | 20.8 | 17.6 | 21.7 | |
| $20–$49k | U | 22.9 | 26.0 | 25.1 | 33.7 | 29.0 | 32.5 | 28.5 | 26.6 | 29.2 | 27.9 | 29.2 |
| R | 31.4 | 35.1 | 37.0 | 38.2 | 35.8 | 38.5 | 38.6 | 34.2 | 36.4 | 39.0 | 37.0 | |
| >=$50k | U | 64.7 | 59.5 | 63.1 | 48.1 | 57.0 | 50.0 | 59.0 | 62.5 | 55.8 | 60.2 | 55.9 |
| R | 55.0 | 44.8 | 43.2 | 32.9 | 46.4 | 39.3 | 41.4 | 49.0 | 42.8 | 43.5 | 41.3 | |
| Smoker | U | 10.7 | 10.4 | 12.9 | 13.5 | 14.8 | 13.3 | 15.0 | 11.3 | 8.3 | 12.2 | 12.2 |
| R | 18.0 | 18.8 | 18.7 | 20.2 | 18.4 | 18.6 | 17.4 | 17.0 | 13.6 | 16.4 | 18.5 | |
3.2. Rural/Urban National and Regional Comparisons
Table 2 describes overall (national) comparisions between urban-rural respondents and provides within-region urban-rural percent support by policy type. These comparisons allow us to better understand actual estimates of disparities between rural-urban residents across the regions. Overall, urban respondents were significantly more supportive of all SHS policies. Of all attitude questions about support for policies, banning smoking in bars was the one least supported by rural residents (the other being banning in casinos). Over all, banning smoking in bars had the most difference between urban and rural residents (57.9% vs. 51.4, respectively): a urban-rural difference of 6.5 percentage point (See Appendix Table 2a for all calculated differences). Protecting children from SHS in cars had the highest level of support among both urban and rural residentsurban residents were still more supportive than rural (94.8% vs.92.5%, respectively). This was only a 2.3 percentage point difference. When looking within regions, urban-rural differences was most evident in the Mid-Atlantic for supporting bar restrictions (56.4% vs. 46.6%, respectively) and for having a home smoking ban in the Southeast (87.1% vs. 77.2%, respectively): both having almost a 10- point difference between urban-rural residents. However, rural residents in the Heartland were more supportive of the Kids Protection scale (2.5 percent difference) and rural residents in NJ/NY were more supportive of the Establishment scale (4 percent difference).
Table 2.
2014–2015 TUS-CPS: Smoking Home Ban and Attitudes by HHS Region and rural-urban status, age adjusted weighted
| HHS Region | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | National | ||
| Attitudes, % Smoking should never be allowed in: | ||||||||||||
| Cars | U | 74.8 | 76.7 | 71.0 | 75.9 | 66.4 | 77.9 | 66.2 | 73.1 | 79.5 | 70.9 | 74.1 |
| R | 68.2 | 71.0 | 65.8 | 71.2 | 64.7 | 74.4 | 71.1 | 66.7 | 73.1 | 65.6 | 69.1 | |
| Cars with kids | U | 95.9 | 95.7 | 94.0 | 95.0 | 92.8 | 95.4 | 91.2 | 95.0 | 96.5 | 94.8 | 94.8 |
| R | 95.8 | 92.6 | 92.1 | 92.2 | 91.0 | 92.7 | 93.8 | 92.6 | 96.4 | 93.2 | 92.5 | |
| Casinos | U | 62.4 | 62.3 | 55.4 | 53.0 | 55.2 | 50.7 | 50.8 | 58.8 | 57.1 | 58.7 | 55.7 |
| R | 63.4 | 67.3 | 49.2 | 47.4 | 52.8 | 44.7 | 50.6 | 58.5 | 59.0 | 52.0 | 51.4 | |
| Bars | U | 69.5 | 65.7 | 56.4 | 53.1 | 57.0 | 51.2 | 51.3 | 60.3 | 61.9 | 63.6 | 57.9 |
| R | 66.8 | 68.9 | 46.6 | 45.8 | 53.8 | 44.0 | 51.1 | 60.1 | 60.8 | 54.6 | 51.4 | |
| Playgrounds | U | 90.3 | 90.7 | 86.5 | 87.8 | 85.1 | 89.2 | 82.9 | 89.4 | 92.0 | 87.5 | 88.4 |
| R | 90.2 | 91.3 | 84.4 | 84.0 | 83.7 | 83.2 | 85.2 | 85.7 | 88.5 | 84.2 | 84.8 | |
| Home | U | 89.6 | 86.3 | 86.9 | 87.1 | 84.2 | 88.9 | 86.3 | 91.1 | 92.7 | 92.8 | 88.2 |
| R | 84.9 | 78.9 | 78.6 | 77.2 | 81.0 | 84.2 | 83.1 | 88.4 | 90.3 | 89.7 | 81.7 | |
| Attitude Scores | ||||||||||||
| Kids | U | 0.9 | 0.9 | 0.8 | 0.8 | 0.8 | 0.8 | 0.7 | 0.8 | 0.9 | 0.8 | 0.8 |
| R | 0.9 | 0.8 | 0.8 | 0.8 | 0.7 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | |
| %‡ | 0.0 | 1.1 | 1.7 | 3.3 | 1.5 | 4.4 | −2.5 | 3.0 | 1.7 | 2.5 | 2.9 | |
| Entertain Est. | U | 0.3 | 0.3 | 0.1 | 0.1 | 0.1 | 0.0 | 0.0 | 0.2 | 0.2 | 0.2 | 0.1 |
| R | 0.3 | 0.4 | 0.0 | −0.1 | 0.1 | −0.1 | 0.0 | 0.2 | 0.2 | 0.1 | 0.0 | |
| %‡ | 0.8 | −4 | 7.8 | 6.2 | 2.7 | 6.4 | 0.2 | 0.2 | −0.4 | 7.7 | 5.3 | |
| Smoke-free Air Law Score† | 1.4 | 3.0 | 2.0 | 0.5 | 2.7 | 0.2 | 2.1 | 1.9 | 1.3 | 2.6 | - | |
Note: attitude scores range between −1 and 1. Differences have been converted to percentages as follows: [(Urban – Rural)/2] *100.
Source: Analysis of 100% Smokefree Air Laws for non-hospitality workplaces, restaurants, and bars as reported by American Nonsmokers’ Rights Foundation’s on July 1, 2015
3.3. Multivariate
Table 3 provided detailed findings from the multivariate logistic regressions. Odds ratios (OR) display the odds of rural respondents supporting an SHS policies when compared to urban residents within the same region. These analyses confirm that overall (nationally) rural residents were significantly less likely to have a SHS restriction in their homes (OR=.78, 95% CI [.74, .81); or be supportive of policy restictions in cars (OR= .87, 95% CI .79,.95), on playgrounds (OR=.88, 95% CI.83,.94) and in bars OR =.88, 95% CI .85,.92), when controlling for demographics and smoking status. Rural residents were significantly less likely to have a home ban: this was true in 6 of 10 regions. Residents in the South Central region were significantly less likely to support SHS policiess than their urban neighbors: less likely to have a home ban (OR=0.83, 95% CI [.72, .94]); less likely to support banning smoking in cars with kids (OR=0.75, CI [.56, 1]); on playgrounds (OR=0.68, 95% CI [.56, .83]); in bars (OR=. 83, 95% CI [.76, .91]); and in casinos (OR=0.86, 95% CI [.78, .95]). Also, rural residents were significantly less likely to support banning smoking in bars in the Mid-Atlantic, (OR=. 78, 95% CI [.67, .92]), Southeast (OR= .87, 95% CI [.80, .95]) and Northwest (OR=. 74, 95% CI [.62, .89]). Only NY/NJ’s rural residents were more supportive of the SHS policies banning smoking in bars (OR=1.36, 95% CI [1.06, 1.75]).
Table 3:
2014–2015 TUS-CPS: Region-specific logistic regression adjusted odds ratios‡ and 95% confidence intervals: smoking bans and attitudes, age adjusted weighted
| Smoking is not allowed in the home | Smoking should never be allowed in cars | Smoking should never be allowed in cars with kids | Smoking should never be allowed in playgrounds | Smoking should never be allowed in bars | Smoking should never be allowed in casinos | |
|---|---|---|---|---|---|---|
| Rural, n | 21,387 | 24,288 | 31,852 | 18,406 | 18,543 | 29,127 |
| Urban, n | 82,552 | 90,417 | 115,873 | 107,625 | 70,727 | 67,839 |
| Rural HHS Region, Odds Ratios and Confidence Intervals‡ | ||||||
| National | 0.78 (0.74, 0.81) | 1.00 (0.95, 1.04) | 0.87 (0.79, 0.95) | 0.88 (0.83, 0.94) | 0.88 (0.85, 0.92) | 0.97 (0.93, 1.01) |
| By HHS Region: | ||||||
| 1 | 0.78 (0.64, 0.96) | 0.94 (0.83, 1.07) | 1.31 (1.05, 1.65) | 1.18 (1.00, 1.40) | 1.02 (0.92, 1.14) | 1.23 (1.11, 1.35) |
| 2 | 0.87 (0.65, 1.17) | 1.09 (0.80, 1.50) | 0.86 (0.44, 1.70) | 1.41 (1.03, 1.93) | 1.36 (1.06, 1.75) | 1.53 (1.27, 1.84) |
| 3 | 0.73 (0.62, 0.86) | 0.98 (0.85, 1.14) | 0.94 (0.73, 1.20) | 1.00 (0.86, 1.17) | 0.78 (0.67, 0.92) | 0.90 (0.79, 1.03) |
| 4 | 0.65 (0.59, 0.71) | 0.98 (0.88, 1.09) | 0.78 (0.63, 0.98) | 0.87 (0.75, 1.00) | 0.87 (0.80, 0.95) | 0.94 (0.86, 1.02) |
| 5 | 0.89 (0.80, 0.99) | 1.13 (1.04, 1.22) | 0.95 (0.83, 1.09) | 1.05 (0.93, 1.18) | 0.98 (0.88, 1.09) | 1.01 (0.91, 1.12) |
| 6 | 0.83 (0.72, 0.94) | 0.99 (0.86, 1.13) | 0.75 (0.56, 1.00) | 0.68 (0.56, 0.83) | 0.83 (0.76, 0.91) | 0.86 (0.78, 0.95) |
| 7 | 0.84 (0.71, 1.00) | 1.52 (1.33, 1.75) | 1.68 (1.38, 2.05) | 1.30 (1.11, 1.53) | 1.12 (0.97, 1.29) | 1.10 (0.98, 1.25) |
| 8 | 0.84 (0.72, 0.99) | 0.83 (0.72, 0.96) | 0.75 (0.57, 0.99) | 0.79 (0.69, 0.90) | 1.10 (0.98, 1.24) | 1.09 (0.94, 1.27) |
| 9 | 1.10 (0.73, 1.66) | 0.88 (0.73, 1.05) | 1.18 (0.81, 1.72) | 0.79 (0.61, 1.02) | 1.09 (0.91, 1.31) | 1.27 (1.04, 1.56) |
| 10 | 0.80 (0.61, 1.03) | 0.81 (0.68, 0.96) | 0.80 (0.59, 1.08) | 0.82 (0.69, 0.98) | 0.74 (0.62, 0.89) | 0.82 (0.69, 0.96) |
Odds ratios (OR) display the odds of rural respondents supporting SHS policies when compared to urban residents within the same HHS region. Results represents eleven logistic regressions (10 regions plus national) per smoking ban or attitude. Logistic regressions adjust for age, sex, race/ethnicity, rural-urban status, income, and smoking status.
Figure 1 offers an illustrative map of rural/urban odds ratios of SHS attitudes. As enumerated in the legend, lighter shades indicated less rural support of the smoking ban when compared to urban. Through this pictorial lens, it becomes more apparent that rural North Central Mountain residents are less supportive of smoking bans (cars, kids, playgrounds, and homes) when comared to urban, while their rural neighbors in Heartland are significantly more supportive of smoking bans for three of four policies (cars, kids, playgrounds).
Figure 1. 2014–2015 TUS-CPS: Regional adjusted odds ratios‡: smoking bans and attitudes, age adjusted weighted.
Lighter shades indicate more urban support of the smoking ban when compared to rural.
‡ Odds ratios (OR) display the odds of rural respondents supporting SHS policies when compared to urban residents within the same HHS region. Models adjusted for age, sex, race/ethnicity, rural-urban status, education status, and smoking status.
*Asterisks denotes Wald Chi-Square test statistic was < .05 and thus statistically significant.
DISCUSSION
To our knowledge, this study is the first to examine national and regional rural/urban differences in support for SHS policies across all regions of the U.S. Our findings show that, overall, rural areas are significantly less supportive of all SHS policies examined, consistent with other studies [7,11,12, 22]. However, the picture becomes more nuanced when we look at rural/urban differences within regions and support for the different types of SHS policies/approaches. For example, Mid-Atlantic has the greatest rural/urban bivariate disparity, registering the lowest level of support for all SHS policies except home bans when compared to national rural values; the South East and South Central had lowest levels of rural support for SHS policies, even after controlling for various factors. These findings are interesting in light of Roberts et al. (2017), who found that rural residents from Census’s South Atlantic region had the highest amounts of rural/urban disparities in cigarette use, and Meit et al. (2014), found a similar relationship for all of Census’s Southern and Midwest regions [2,11]. They are also consistent with previous research that demonstrated a causal relationship between stronger policies (including SHS policies) and lower prevalence rates [25]. SHS policy development is especially challenging in Southeast and South Central: no states in these two regions have state-level, comprehensive SHS policies [28]. Lessons learned from successful efforts in these challenging environments do highlight that strong coalitions, long-standing tobacco control expertise along with a strong legal team, were essential ingredients for success [29, 30]. In addition, it is likely that local areas once they have adopted a policy can influence and help the diffusion and adoption of this policy to their neighbors; especially at the local-level [31].
Our findings also highlight the rural/urban disparity in support for various types of SHS policies and approaches. It has been suggested that outdoor smoking restrictions—as well as restrictions in non-public settings, such as private dwellings/homes—may be more controversial and less supported by rural residents [16, 20]. We found that the situation differs by region. It is interesting to note that while home bans are supported by a majority of both rural and urban respondents, significantly fewer rural residents were likely to have initiated a home ban, possibly reflecting cultural or normative differences in instituting such a ban in private dwellings. Again, we see Mid-Atlantic and Southeast as the regions in which home bans are least likely.
In NY/NJ, however, there were fewer differences between rural and urban areas. In fact, rural residents of the NY/NJ, New England and the Heartland were even more supportive than their urban peers of policies banning smoking in playgrounds, bars and casinos. However, it should be noted that NY/NJ has the smallest number of rural respondents on the TUS-CPS, and is among the most urban in the country and had the strongest regional SHS policy score [32]. Research has demonstrated a positive relationship between county population density and strength of tobacco control [11,13]. In addition, evidence exists of an association between favorable attitudes and stronger and more comprehensive SHS policies [27].
There are a number of possible explanations for rural/urban and regional disparities for different types of SHS policies. Research has identified special characteristics of rural areas—contextual factors—related to geography (i.e., isolation, access to services, few media outlets, chronic poverty and a declining economy and population), which are known to influence tobacco control resources, infrastructure for tobacco control implementation, media coverage and policy advocacy efforts [33,34]. Isolation is an important factor that requires further study since more isolated rural populations are not getting the same intensity of tobacco control interventions as delivered in urban areas [11]. Compositional factors related to characteristics of the people residing in rural areas (i.e., political affiliations, norms, education, cultural, socio-economic and psycho-behavioral factors) are also important [33–35]. Rural areas may equate smoke-free policies as being more of an “urban” issue or as coming from urban media outlets and something that is antithetical to rural values [36]. Thus, research that delves into rural norms and culture is required to better understand different rural regions and existing beliefs that may not support tobacco control efforts.
Moreover, not much is known concerning the tobacco industry’s targeting of rural populations, and specifically undermining rural second-hand smoke policy development. For example, Altria’s website contains statements about various types of SHS policy that seem to reflect some of the rural/urban disparities we found in our analyses. Altria statements indicate that “complete bans go too far” and smoking should be “permitted outdoors except maybe around children”, “owners of restaurants and bars should have the opportunity and flexibility to determine their own smoking policy” and “owners of private residences and other private places should determine the smoking policy for that particular location” [37]. The tobacco industry may also influence the media coverage in rural areas [37–40]. For example, focusing media coverage on problems of youth smoking instead of covering smoke-free ordinances meant fewer chances to highlight benefits of smoke-free policies [39].
Our results have important implications for tobacco control and efforts to reduce health disparities. While states have differing success with implementing smoke-free policies, their rural populations have differing attitudes and support for SHS policies. While strong SHS policies, once in place, do lead to increased support for these policies, we still need additional research in rural areas to better understand how to foster tobacco policy development in rural areas. Urban and rural areas suffer from many of the same issues, but programs and approaches designed for urban areas often do not translate well to rural areas [41]. Further, research is needed to better identify approaches required to help rural communities, including working with community members and policy makers, building capacity and infrastructure and promoting cooperation and collaboration [11, 41–42].
There are some limitations to our analysis. This study relied on the HHS-designated regions, which cluster groups of states together. This approach was established to facilitate HHS programs and funding that are conducted through regional offices. The regional clustering does not reflect individual states’ policy environments which can influence attitudes and support for SHS policies. However, sample size limitations at the state level restricted rural/urban comparisons. As is, we have a large representative sample and the current findings present a novel perspective on the rural/urban divide through attention to regional differences. Also, since “Census does not actually define rural”, our study relied on OMB’s county-level definition of rural; analyses using alternative definitions may produce somewhat different results. This definition is commonly used by government and researchers and is a conservative measure of rurality. [43]
CONCLUSIONS
Few studies have compared rural/urban disparities in cigarette use across diverse geographic regions, and none have looked at rural/urban disparities in support for secondhand smoke restrictions in the 10 HHS regions. The results indicate that overall, respondents in rural regions are significantly less supportive of secondhand smoke policies as compared to respondents in urban regions and that significant differences exist between these regions. There is a critical need to improve rural America’s tobacco control policy, regulation and cessation efforts, and understanding the variation among diverse rural areas is an important step towards achieving this goal [37, 44].
ACKNOWLEDGEMENTS
The study research was funded by NCI grant 1R21CA205589. FAS and MEW led the study conceptualization and secured the research funding. ET and DC conducted the analysis and produced the tables and figure. FAS, ET, DC, MEW and ND were responsible for the interpretation of data. FAS drafted the manuscript with assistance on the Methods section from ET and DC. MEW, EAM, ND, MR and KG reviewed the manuscript and were responsible for providing comments and making critical revisions. KG was responsible for administrative, technical, and material support. All authors gave final approval to the manuscript.
APPENDIX
Table A1:
2014–2015 TUS-CPS: Socio-demographic Characteristics of all respondents, Standard Errors, by region and rural/urban status, weighted
| HHS Region | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Characteristic | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | National | |
| Female | Urban | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.2 | 0.2 | 0.1 | 0.1 | 0.0 |
| Rural | 0.4 | 1.4 | 0.5 | 0.3 | 0.3 | 0.4 | 0.5 | 0.5 | 1.0 | 0.5 | 0.2 | |
| Race | ||||||||||||
| White | Urban | 0.4 | 0.5 | 0.4 | 0.3 | 0.3 | 0.3 | 0.4 | 0.4 | 0.3 | 0.5 | 0.1 |
| Rural | 0.3 | 1.4 | 1.1 | 0.9 | 0.4 | 1.1 | 0.4 | 1.1 | 2.8 | 1.0 | 0.4 | |
| Black | Urban | 0.1 | 0.2 | 0.2 | 0.2 | 0.1 | 0.2 | 0.3 | 0.2 | 0.1 | 0.1 | 0.1 |
| Rural | 0.2 | 0.7 | 1.1 | 0.8 | 0.2 | 0.8 | 0.2 | 0.1 | 0.5 | 0.1 | 0.3 | |
| Other | Urban | 0.4 | 0.5 | 0.3 | 0.2 | 0.2 | 0.3 | 0.3 | 0.3 | 0.3 | 0.5 | 0.0 |
| Rural | 0.3 | 1.0 | 0.2 | 0.5 | 0.3 | 0.7 | 0.4 | 1.0 | 2.8 | 1.0 | 0.2 | |
| Hispanic | Urban | 0.4 | 0.5 | 0.3 | 0.3 | 0.3 | 0.6 | 0.3 | 0.6 | 0.5 | 0.6 | 0.1 |
| Rural | 0.4 | 0.7 | 0.4 | 0.5 | 0.3 | 2.0 | 0.6 | 0.7 | 5.1 | 1.5 | 0.5 | |
| Age | ||||||||||||
| 18–24 | Urban | 0.4 | 0.3 | 0.3 | 0.2 | 0.2 | 0.2 | 0.4 | 0.4 | 0.2 | 0.3 | 0.0 |
| Rural | 0.6 | 2.1 | 0.7 | 0.4 | 0.4 | 0.7 | 0.6 | 0.5 | 1.0 | 0.6 | 0.2 | |
| 25–64 | Urban | 0.4 | 0.4 | 0.4 | 0.3 | 0.3 | 0.3 | 0.6 | 0.6 | 0.3 | 0.5 | 0.0 |
| Rural | 0.7 | 1.5 | 0.8 | 0.5 | 0.6 | 0.8 | 0.6 | 1.0 | 1.6 | 1.1 | 0.2 | |
| 65+ | Urban | 0.3 | 0.3 | 0.3 | 0.2 | 0.2 | 0.3 | 0.4 | 0.5 | 0.2 | 0.4 | 0.0 |
| Rural | 0.7 | 2.3 | 0.8 | 0.5 | 0.6 | 0.9 | 0.6 | 0.8 | 1.1 | 1.2 | 0.2 | |
| Age | ||||||||||||
| <$20k | Urban | 0.5 | 0.4 | 0.3 | 0.3 | 0.3 | 0.4 | 0.5 | 0.5 | 0.3 | 0.5 | 0.1 |
| Rural | 0.7 | 1.2 | 1.0 | 0.7 | 0.8 | 0.9 | 0.9 | 0.9 | 2.1 | 1.0 | 0.3 | |
| $20k to $49k | Urban | 0.6 | 0.5 | 0.5 | 0.4 | 0.4 | 0.5 | 0.7 | 0.7 | 0.4 | 0.7 | 0.2 |
| Rural | 0.9 | 3.3 | 1.3 | 0.9 | 0.8 | 1.0 | 1.1 | 1.0 | 2.1 | 1.8 | 0.4 | |
| >=$50k | Urban | 0.8 | 0.6 | 0.5 | 0.5 | 0.5 | 0.6 | 0.8 | 0.9 | 0.5 | 0.9 | 0.2 |
| Rural | 1.1 | 3.7 | 1.3 | 0.7 | 0.9 | 1.2 | 1.1 | 1.1 | 3.1 | 1.5 | 0.4 | |
| Smoker | Urban | 0.3 | 0.2 | 0.3 | 0.2 | 0.2 | 0.3 | 0.5 | 0.4 | 0.2 | 0.4 | 0.1 |
| Rural | 0.6 | 1.8 | 0.9 | 0.5 | 0.5 | 0.8 | 0.6 | 0.5 | 0.6 | 0.8 | 0.2 | |
Table A2:
2014–2015 TUS-CPS: Region-Specific Urban-Rural Differences in Smoking Home ban and Attitudes, age adjusted weighted
| Smoking Restriction or Attitude | HHS Region | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Nation | |
| Cars | 6.5 | 5.6 | 5.2 | 4.7 | 1.6 | 3.4 | −5.0 | 6.3 | 6.3 | 5.3 | 5.0 |
| Cars with kids | 0.1 | 3.0 | 1.9 | 2.8 | 1.8 | 2.7 | −2.6 | 2.4 | 0.1 | 1.6 | 2.3 |
| Casinos | −1.1 | −5.0 | 6.1 | 5.5 | 2.4 | 6.0 | 0.2 | 0.2 | −2.0 | 6.8 | 4.3 |
| Bars | 2.7 | −3.3 | 9.9 | 7.2 | 3.1 | 7.2 | 0.1 | 0.1 | 1.1 | 8.9 | 6.5 |
| Playgrounds | 0.1 | −0.6 | 2.0 | 3.9 | 1.4 | 6.0 | −2.2 | 3.7 | 3.5 | 3.2 | 3.6 |
| Home | 4.6 | 7.3 | 8.2 | 9.9 | 3.3 | 4.7 | 3.1 | 2.6 | 2.4 | 3.1 | 6.5 |
Table A3:
2014–2015 TUS-CPS: Smoking Home ban and Attitudes 95% confidence level lower bounds by HHS Region and rural-urban status, age adjusted weighted
| HHS Region | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Average | ||
| Attitudes, % Smoking should never be allowed in: | ||||||||||||
| Cars | Urban | 74.8 | 76.7 | 71.0 | 75.9 | 66.4 | 77.9 | 66.2 | 73.1 | 79.5 | 70.9 | 74.1 |
| Rural | 68.2 | 71.0 | 65.8 | 71.2 | 64.7 | 74.4 | 71.1 | 66.7 | 73.1 | 65.6 | 69.1 | |
| Cars with kids | Urban | 95.9 | 95.7 | 94.0 | 95.0 | 92.8 | 95.4 | 91.2 | 95.0 | 96.5 | 94.8 | 94.8 |
| Rural | 95.8 | 92.6 | 92.1 | 92.2 | 91.0 | 92.7 | 93.8 | 92.6 | 96.4 | 93.2 | 92.5 | |
| Casinos | Urban | 62.4 | 62.3 | 55.4 | 53.0 | 55.2 | 50.7 | 50.8 | 58.8 | 57.1 | 58.7 | 55.7 |
| Rural | 63.4 | 67.3 | 49.2 | 47.4 | 52.8 | 44.7 | 50.6 | 58.5 | 59.0 | 52.0 | 51.4 | |
| Bars | Urban | 69.5 | 65.7 | 56.4 | 53.1 | 57.0 | 51.2 | 51.3 | 60.3 | 61.9 | 63.6 | 57.9 |
| Rural | 66.8 | 68.9 | 46.6 | 45.8 | 53.8 | 44.0 | 51.1 | 60.1 | 60.8 | 54.6 | 51.4 | |
| Playgrounds | Urban | 90.3 | 90.7 | 86.5 | 87.8 | 85.1 | 89.2 | 82.9 | 89.4 | 92.0 | 87.5 | 88.4 |
| Rural | 90.2 | 91.3 | 84.4 | 84.0 | 83.7 | 83.2 | 85.2 | 85.7 | 88.5 | 84.2 | 84.8 | |
| Home | Urban | 89.6 | 86.3 | 86.9 | 87.1 | 84.2 | 88.9 | 86.3 | 91.1 | 92.7 | 92.8 | 88.2 |
| Rural | 84.9 | 78.9 | 78.6 | 77.2 | 81.0 | 84.2 | 83.1 | 88.4 | 90.3 | 89.7 | 81.7 | |
| Attitude Scores | ||||||||||||
| Kids | Urban | 0.9 | 0.9 | 0.8 | 0.8 | 0.8 | 0.8 | 0.7 | 0.8 | 0.9 | 0.8 | 0.8 |
| Rural | 0.9 | 0.8 | 0.8 | 0.8 | 0.7 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | |
| Entertainment Est. | Urban | 0.3 | 0.3 | 0.1 | 0.1 | 0.1 | 0.0 | 0.0 | 0.2 | 0.2 | 0.2 | 0.1 |
| Rural | 0.3 | 0.4 | 0.0 | −0.1 | 0.1 | −0.1 | 0.0 | 0.2 | 0.2 | 0.1 | 0.0 | |
Table A4:
2014–2015 TUS-CPS: Smoking Home Ban and Attitudes 95% confidence level upper bounds by HHS Region and rural/urban status, age adjusted weighted
| HHS Region | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Average | ||
| Attitudes, % Smoking should never be allowed in: | ||||||||||||
| Cars | Urban | 74.8 | 76.7 | 71.1 | 75.9 | 66.4 | 77.9 | 66.2 | 73.2 | 79.5 | 71.0 | 74.1 |
| Rural | 68.3 | 71.2 | 65.8 | 71.3 | 64.8 | 74.5 | 71.2 | 66.8 | 73.3 | 65.7 | 69.1 | |
| Cars with kids | Urban | 96.0 | 95.7 | 94.0 | 95.0 | 92.8 | 95.4 | 91.2 | 95.0 | 96.5 | 94.8 | 94.8 |
| Rural | 95.9 | 92.7 | 92.1 | 92.2 | 91.1 | 92.7 | 93.8 | 92.6 | 96.5 | 93.3 | 92.6 | |
| Casinos | Urban | 62.5 | 62.3 | 55.4 | 53.0 | 55.3 | 50.7 | 50.9 | 58.8 | 57.2 | 58.8 | 55.7 |
| Rural | 63.5 | 67.4 | 49.4 | 47.5 | 52.9 | 44.8 | 50.7 | 58.6 | 59.1 | 52.1 | 51.4 | |
| Bars | Urban | 69.6 | 65.7 | 56.5 | 53.1 | 57.0 | 51.2 | 51.3 | 60.4 | 61.9 | 63.6 | 57.9 |
| Rural | 66.9 | 69.1 | 46.7 | 45.9 | 53.9 | 44.1 | 51.3 | 60.2 | 60.9 | 54.7 | 51.4 | |
| Playgrounds | Urban | 90.3 | 90.8 | 86.5 | 87.9 | 85.1 | 89.2 | 83.0 | 89.4 | 92.0 | 87.6 | 88.4 |
| Rural | 90.3 | 91.4 | 84.5 | 84.0 | 83.8 | 83.2 | 85.3 | 85.8 | 88.6 | 84.3 | 84.8 | |
| Home | Urban | 89.6 | 86.3 | 86.9 | 87.1 | 84.3 | 88.9 | 86.3 | 91.1 | 92.8 | 92.8 | 88.2 |
| Rural | 85.0 | 79.0 | 78.7 | 77.2 | 81.0 | 84.2 | 83.2 | 88.5 | 90.4 | 89.7 | 81.7 | |
| Attitude Scores | ||||||||||||
| Kids | Urban | 0.9 | 0.9 | 0.8 | 0.8 | 0.8 | 0.8 | 0.7 | 0.8 | 0.9 | 0.8 | 0.8 |
| Rural | 0.9 | 0.8 | 0.8 | 0.8 | 0.7 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | |
| Entertainment Est. | Urban | 0.3 | 0.3 | 0.1 | 0.1 | 0.1 | 0.0 | 0.0 | 0.2 | 0.2 | 0.2 | 0.1 |
| Rural | 0.3 | 0.4 | 0.0 | −0.1 | 0.1 | −0.1 | 0.0 | 0.2 | 0.2 | 0.1 | 0.0 | |
Footnotes
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