Predictors of U.S. Adults’ Opinion Toward an R-Rating Policy for Movies With Cigarette Smoking

Abstract

Recently, multiple health organizations and advocacy groups have pushed for giving an R-rating for movies depicting tobacco imagery. This study examined several predictors of U.S. adults’ opinion toward an R-rating policy for movies depicting cigarette smoking. We used data from the Health Information National Trends Survey (2020 cycle), for a nationally representative sample of 3,865 US adults (aged ≥ 18). The outcome variable was opinion toward an R-rating policy (support, neutral, and oppose) for movies depicting cigarette smoking. A weighted adjusted multinomial logistic regression analysis with comparisons of support versus oppose, support versus neutral, and neutral versus oppose was performed. About 48.2% of respondents were supportive of, 31.1% were neutral toward, and 20.7% were opposed to an R-rating policy. Adults aged 50 to 64 years (adjusted odds ratio [aOR] = 2.28, p = .008) and ≥65 years (aOR = 4.54, p <.001) (vs. 18–34 years) were more likely to support the R-rating policy than oppose it. Non-Hispanic Black respondents (vs. non-Hispanic Whites) were 1.74 times more likely to support than oppose the policy (aOR = 1.74, p = .04), whereas adults with a household annual income of US$75,000 or more (vs. <$20,000) and those with moderate (vs. liberal) political viewpoints were more likely to be neutral than oppose the policy. Former and current e-cigarette users (vs. never users) were less likely to support than oppose the policy. Tailored messaging addressing the rationale behind R-rating policy should be directed towards communities based on age, race/ethnicity, household income, e-cigarette usage, and political ideologies.

Keywords

smoking R-rating movies tobacco policy youth

Introduction

For several decades, the tobacco industry has worked closely with movie studios, actors, and filmmakers to promote its products (Mekemson, 2004; Mekemson & Glantz, 2002; World Health Organization [WHO], 2009). More specifically, dating back to at least 1972, tobacco companies have sought to enhance brand exposure and sales through paid product placement in films, offering their products to be used as movie props free of charge, and incentivizing popular actors to use their products both on- and off-screen (Mekemson & Glantz, 2002). Depictions of tobacco use in popular films increased throughout the 1990s and have continued to do so in recent years (Mekemson & Glantz, 2002). For example, data suggest that the total number of tobacco scenes in top-grossing U.S. movies has increased by 57%, from 1,824 in 2010 to 2,868 in 2018 (Tynan et al., 2019). Furthermore, 51% of the top-grossing U.S. movies in 2019 depicted tobacco use (J. Polansky et al., 2020).

The continued propagation of tobacco use in popular films constitutes a significant public health problem. Tobacco depictions in movies encourage adolescents to hold more pro-tobacco attitudes and beliefs and have shown to have a dose-response relationship with adolescent smoking behavior (Charlesworth & Glantz, 2005; Heatherton & Sargent, 2009; Sargent et al., 2002; Sargent & Hanewinkel, 2015). The U.S. Surgeon General’s Report has established a causal relationship between depictions of smoking in movies and the initiation of smoking among younger individuals (U.S. Department of Health and Human Services, 2012). Some estimates suggest that approximately 90% of smokers initiate smoking due to on-screen exposure before reaching 18 years of age (Truth Initiative, 2020). If tobacco use initiation continues at its current rate, 5.6 million youths are projected to die from tobacco-related diseases (Centers for Disease Control and Prevention [CDC], 2022). In response to these alarming statistics, the World Health Organization (WHO) has urged governments to take concrete steps, such as rating films with tobacco scenes and displaying tobacco warnings before films with tobacco, to prevent children and adolescents from starting to smoke cigarettes and use other forms of tobacco (WHO, 2016).

Since 1968, the Motion Picture Association (MPA), a trade organization that currently represents the five major U.S. film studios (i.e., Universal, Paramount, Warner Bros., Disney, and Sony Pictures) and the Netflix streaming service, instituted a film rating system (Classification and Rating Administration) to help parents make informed viewing choices for their children. There are currently five MPA ratings: G (general audiences, all ages admitted), PG (parental guidance suggested, some material may not be suitable for children), PG-13 (parents strongly cautioned, some material may be inappropriate for children under 13), R (restricted, under 17 requires accompanying parent or adult guardian), and NC-17 (no one 17 and under admitted), which are specific for nudity, violence, strong language, sensuality, depictions of sexual activity, adult activities (i.e., activities that adults, but not minors, may engage in legally), and drug use (Motion Picture Association, 2020). The effectiveness of the MPA rating system in reducing youth exposure to potentially harmful content has been mixed (Nalkur et al., 2010). However, Gentile (2010) argues that “rating systems do play an important role in providing information regarding media products so that parents can make informed decisions about content appropriate for their children (p. 1). Furthermore, evidence suggests that U.S. parents overwhelmingly support content rating systems for various types of media (Kunkel et al., 1998).

In 2007, the MPA announced that it would start considering tobacco use in its film rating system; however, the MPA still does not explicitly mention “tobacco” or “smoking” anywhere in its official ratings rules. This gives parents little “‘advance information” about exposure of tobacco imagery in movies so that they can decide what their children can and cannot see (J. R. Polansky et al., 2007; University of California, San Francisco, 2021). This change has not deterred depictions of tobacco use in films that receive various ratings; for example, among the top-grossing US movies in 2019, tobacco use appeared in 23% of films rated G/PG, 43% of those rated PG-13, and 76% of R-rated movies (J. Polansky et al., 2020). According to a Truth Initiative report, R-rated films continue to contain the highest number of tobacco incidents per film in 2020 with 35 incidents per film. In addition, non-MPA member film studios now account for more than half of youth-rated movies depicting tobacco use and have reported more tobacco incidents per film than MPA member studio films (Truth Initiative, 2020).

In recent years, multiple health organizations, tobacco control advocates, and politicians have called for the MPA to institute a policy that would automatically assign an R-rating to any movie with tobacco imagery unless it portrays tobacco use by a real historical figure (as in documentaries or biographical dramas) or depicts the harmful effects of tobacco use (American Lung Association, 2019; McAfee & Tynan, 2012; Tynan et al., 2019). Those advocating for such a policy have argued that, in coordination with additional interventions, it could potentially reduce smoking onset among youth by 18%, and prevent up to 1 million premature smoking-related deaths (CDC, 2022; Sargent et al., 2012; U.S. Department of Health and Human Services, 2014). Previous studies have also shown a significant association between parental restriction of R-rated movie viewing and lower adolescent smoking susceptibility and smoking onset rates (de Leeuw et al., 2011; Dalton et al., 2006; Sargent et al., 2004; Thompson & Gunther, 2007).

Given that an R-rating policy on movies with tobacco imagery might have a considerable influence on adolescents’ on-screen cigarette smoking exposure and initiation, and to effectively advocate for such a policy, it is important to examine public opinion on the support for this policy. While some public opinion studies exist to assess support for general tobacco control policies such as restrictions on tobacco advertising at point-of-sale, plain packaging, raising tobacco taxes, and other measures designed to protect children (Blake et al., 2022; Blendon & Young, 1998; Filippidis et al., 2017; Jeffery et al., 1990), few studies have explicitly assessed support for a policy designating automatic R-ratings for films depicting cigarette smoking. In a study that utilized the 2003 American Smoking and Health Survey, 40% of adults supported R-ratings for movies that included smoking; however, no differences were found by smoking status (Blake et al., 2010). Another descriptive study that used samples from the 2013 Social Climate Survey of Tobacco Control reported that about 45% of adults, 43% of parents, 30% of smokers, and 47% of nonsmokers supported R-ratings for such films (McMillen, 2020). Another study conducted among parents found approximately half supported adding smoking as a criterion within the MPA rating system; however, fewer parents (28.9%) favored a default R-rating policy (Longacre et al., 2009). More recently, Shete et al. (2021) tested the association between political ideology and support for tobacco control policies; they found that those with liberal ideology were strongly opposed or opposed to labeling movies with smoking with an R-rating compared with those with moderate ideology (Shete et al., 2021). In another recent study, close to half (47%) of U.S. adults supported a policy designating R-ratings for movies depicting cigarette smoking, and only age and race/ethnicity were identified as significant predictors of differential neutrality and opposition toward such a policy (Lama et al., 2022).

Considering that a limited number of studies have focused on examining public support for a potential tobacco control policy to automatically assign an R-rating for any film depicting smoking, this study offers a deeper analytical assessment of predictors that influence U.S. adults’ opinion toward such a policy. Thus, the aim of this study is to examine several predictors (such as socio-demographics, political viewpoint, social media, and behavioral factors) of opinions toward a default R-rating policy for movies depicting cigarette use among a nationally representative sample of U.S. adults.

Methods

Data Source, Sample, and Study Setting

The current study utilized data from the Health Information National Trends Survey (HINTS), a nationally representative, cross-sectional, probability-based survey of U.S. adults conducted every few years by the National Cancer Institute since 2003. The survey employs a random sampling strategy, focusing on civilian noninstitutionalized adults aged ≥18 years, to collect information on the use of, access to, needs for, and trends in health-related information, knowledge, perceptions, and behaviors among adults in the United States (National Cancer Institute [NIH], 2020; Nelson et al., 2004). For this study, we specifically used data from cycle 4 of the HINTS 5, which included a single-mode, self-administered, mail-in survey and was fielded between February and June 2020 with a response rate of 37%. Our analytical sample comprised 3,865 noninstitutionalized adults (≥18 years) living in the United States during the survey period. Since we utilized de-identified, publicly available secondary data, the study was exempt from obtaining Institutional Review Board approval. Additional details about the survey methodology and design are available at https://hints.cancer.gov/.

Outcome Variable

The study’s outcome variable was respondents’ opinions toward a default R-rating policy for movies depicting cigarette use. It was assessed using a single item: “To what extent would you support or oppose the following measures related to cigarettes? . . . Just like with violence and sex, movies with cigarette smoking should be rated ‘R’ to protect children and youth from seeing cigarette smoking in movies” The original response categories included strongly oppose, oppose, neither support nor oppose, support, and strongly support. However, due to the small cell counts for certain subcategories and for analysis purposes, we recoded the responses into three categories: “support (support, strongly support), neutral (neither support nor oppose), and oppose (strongly oppose, oppose).”

Explanatory Variables

Several factors, such as socio-demographic, behavioral, social media use, and political viewpoints, were utilized as explanatory variables in this study and investigated as potential predictors of opinion toward the R-rating policy for movies with cigarette smoking.

Socio-demographic factors included age (18–34, 35–49, 50–64, and ≥65 years), biological sex (male, female), race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Asian or other minorities), residential location was determined based on metropolitan statistical area (MSA, non-MSA, drawn from the U.S. Department of Agriculture’s 2013 Rural-Urban Continuum Codes), education (less than high school, high school graduate, some college, and college graduate or more), annual household income (less than US$20,000, US$20,000 to <US$35,000, US$35,000 to <US$50,000, US$50,000 to <US$75,000, and US$75,000 or more), marital status (married or living as married, divorced/widowed/separated, and single/never married), and number of children under age 18 living in respondents’ households (recategorized as none, one, and ≥ two).

Behavioral factors included smoking status (current, former, and never), and e-cigarette use (current, former, and never). Smoking status was measured using two items: (a) Have you smoked at least 100 cigarettes in your entire life? (yes, no), and (b) How often do you now smoke cigarettes? (every day, some days, not at all). Similarly, e-cigarette use was measured using two items: (a) Have you ever used an e-cigarette, even one or two times? (yes, no), and (b) Do you now use an e-cigarette every day, some days, or not at all? For each two subsequent smoking status and e-cigarette use questions, if respondents answered “yes” to the first question and “every day or some days” to the second question, they were categorized as “current”; if they answered “yes” to the first question and “not at all” to the second question, they were categorized as “former,” and if they answered “no” to the first question, they were categorized as “never.”

Finally, each respondent’s political viewpoint was assessed using the item: “Thinking about politics these days, how would you describe your own political viewpoint?” The original response categories included: “very liberal,” “liberal,” “somewhat liberal,” “moderate,” “somewhat conservative,” “conservative,” and “very conservative.” Due to the small cell counts for certain subcategories and for analysis purposes, we recoded the responses into three categories: “liberal” (very liberal, liberal, somewhat liberal), “moderate,” and “conservative” (very conservative/ conservative/ somewhat conservative). Furthermore, given that “social media” can be used as a platform for tobacco-specific communication designed to increase policy support (Oghenetega et al., 2022), we included this variable in our analysis. We assessed each respondent’s social media use using the item: “In the last 12 months, have you used the internet to visit a social networking site, such as Facebook or LinkedIn?” The response categories were “yes” and “no.”

Statistical Analysis

We first explored the data, checked for data missingness, and any potential patterns in missing data among study variables by employing the MI procedure in the SAS software program. Our assessment revealed that there were no patterns in missingness and the missing observations for both predictor and outcome variables were completely at random (MCAR). Therefore, data were analyzed under the assumption of MCAR. We computed unweighted frequencies and weighted proportions for the entire sample of survey respondents and then by the three subgroups of opinion toward the R-rating policy. In testing for equal proportions in two-way analyses, we used the Wald Chi-square test. Univariate and multivariable multinomial logistic regressions were conducted to investigate predictors of opinion toward policy giving R-rating to movies with cigarette smoking. Three pairs of comparisons from the regression models were presented using different groups for the outcome variable to serve the aims of the study. Opinion toward an R-rating policy was assessed in three different ways: support versus oppose, support versus neutral, and neutral versus oppose. The rationale behind using multinomial logistic regression model was that the outcome variable had three levels of subcategories and their order in the study was of minimum interest. Our fully adjusted model included the entire pool of potential predictors. In this process, possible multicollinearities between the potential predictors were checked during model fitting; there were no threats of multicollinearity observed among model variables. The final computed results included odds ratios (ORs), their 95% CIs, and associated p-values. During all steps of data analysis, we accounted for final person weights and jack-knife replicate weights, provided with the HINTS data, to estimate national-level values and a more accurate variance of estimates. The analyses were conducted using the SAS statistical software (version SAS 9.4; SAS Institute Inc.) and the significance threshold level was set at p < .05.

Results

Overall, in our sample of 3,865 adults, 48.2% were supportive of, 31.1% were neutral toward, and 20.7% were opposed to an R-rating policy for films depicting smoking. Furthermore, the sample comprised 51.0% female, 63.3% non-Hispanic White, 54.8% married or living as married, 13.8% current smokers, and 6.4% current e-cigarette users (Table 1).

Table 1.

Descriptive Statistics of the Overall Sample and Opinion Toward Policy Giving R-Rating to Movies With Cigarette Smoking Among U.S. Adults.

Characteristics	Movies with cigarette smoking should be rated R to protect children and youth
	Total (n = 3,865)	Support (n = 1,957, 48.2%)	Neutral (n = 1,098, 31.1%)	Oppose (n = 695, 20.7%)
	Frequency (Weighted %)^b	Frequency (Weighted %)^b	Frequency (Weighted %)^b	Frequency (Weighted %)^b	p-value^a
Age groups (in years)
18–34	484 (26.2)	166 (20.2)	160 (27.6)	156 (40.3)	<.001
35–49	703 (25.5)	319 (24.9)	224 (25.5)	150 (26.1)
50–64	1142 (27.7)	568 (28.5)	351 (30.5)	205 (22.3)
≥65	1409 (20.6)	865 (26.4)	333 (16.4)	161 (11.3)
Sex
Male	1487 (49.0)	731 (47.9)	427 (49.6)	302 (51.6)	.60
Female	2052 (51.0)	1079 (52.1)	591 (50.4)	341 (48.4)
Race/Ethnicity
Non-Hispanic White	2133 (63.3)	1026 (60.0)	672 (69.0)	411 (64.6)	.04
Non-Hispanic Black	481 (11.1)	268 (12.7)	135 (10.7)	68 (7.9)
Hispanic	596 (17.0)	335 (18.3)	147 (13.8)	101 (17.4)
Non-Hispanic Asian or other minorities	280 (8.6)	154 (9.0)	74 (6.5)	48 (10.1)
MSA residency status
MSA	3435 (87.8)	1756 (89.2)	963 (86.1)	619 (86.8)	.32
Non-MSA	430 (12.2)	201 (10.8)	135 (13.9)	76 (13.2)
Education
Less than high school	273 (8.0)	153 (7.9)	57 (8.4)	50 (7.1)	.20
High school graduate	705 (22.5)	374 (24.2)	197 (20.5)	112 (20.7)
Some college	1081 (39.2)	539 (39.6)	337 (40.8)	184 (35.7)
College graduate or more	1663 (30.3)	833 (28.3)	482 (30.3)	330 (36.5)
Annual household income
Less than US$20,000	624 (15.2)	336 (15.4)	152 (12.3)	120 (19.1)	.45
US$20,000 to < US$35,000	451 (11.4)	230 (11.2)	141 (11.4)	66 (10.8)
US$35,000 to < US$50,000	460 (12.7)	248 (13.2)	127 (11.7)	77 (12.7)
US$50,000 to < US$75,000	592 (18.3)	308 (18.9)	173 (18.2)	103 (17.3)
US$75,000 or More	1321 (42.4)	640 (41.3)	406 (46.4)	265 (40.1)
Marital status
Married or living as married	1978 (54.8)	1042 (58.6)	565 (54.3)	343 (48.2)	.02
Divorced/Widowed/Separated	1098 (14.4)	590 (15.6)	300 (13.5)	171 (12.0)
Single/Never married	645 (30.8)	268 (25.8)	204 (32.2)	160 (39.8)
Number of children under the age of 18 living in the household
None	2676 (65.8)	1379 (65.0)	799 (68.5)	449 (63.9)	.66
One	390 (16.1)	193 (16.5)	113 (15.0)	75 (16.1)
≥ Two	489 (18.1)	241 (18.5)	130 (16.5)	113 (20.0)
Social media use
Yes	2508 (74.3)	1250 (73.0)	733 (76.2)	493 (76.7)	.21
No	1243 (25.7)	656 (27.0)	339 (23.8)	189 (23.3)
Smoking status
Current	436 (13.8)	185 (12.8)	139 (15.2)	103 (14.8)	.66
Former	935 (23.0)	482 (22.1)	275 (25.1)	160 (21.9)
Never	2422 (63.2)	1263 (65.1)	672 (59.7)	426 (63.3)
E-cigarette use
Current	114 (6.4)	32 (3.6)	36 (7.4)	43 (11.4)	<.001
Former	382 (12.7)	142 (9.2)	123 (13.4)	108 (20.2)
Never	3314 (80.9)	1767 (87.2)	929 (79.2)	540 (68.4)
Political viewpoint
Liberal	1058 (29.5)	510 (29.0)	292 (26.5)	238 (34.7)	.17
Moderate	1200 (37.0)	641 (36.0)	363 (41.9)	181 (32.5)
Conservative	1223 (33.5)	646 (35.0)	333 (31.6)	219 (32.8)

Note. MSA = metropolitan statistical area.

Wald Chi-Square Test. ^bFrequencies represent sample frequencies; proportions are population-level estimates that were generated by adjusting for complex survey features of the HINTS data (N = 253.8 million).

The results of the adjusted multinomial logistic regression analyses are shown in Table 2. Our analysis showed that compared with adults aged 18 to 34 years, those aged 50 to 64 years, adjusted (a)OR = 2.28, 95% CI = 1.25–4.16, p = .008, and ≥65 years (aOR = 4.54, 95% CI = 2.41–8.55, p <.001) were more likely to support the R-rating policy than oppose it. In addition, those aged ≥65 years (vs. 18–34 years) were also more likely to support (aOR = 2.46, 95% CI = 1.43–4.24, p = .002) than be neutral to the policy. Non-Hispanic Blacks (vs. Non-Hispanic Whites) were more likely to support than oppose the policy (aOR = 1.74, 95% CI = 1.02–2.96, p = .04), whereas Non-Hispanic Asian or other minorities (vs. Non-Hispanic Whites) were 1.85 times more likely to support than be neutral to the policy (aOR = 1.85, 95% CI = 1.04–3.28, p = .03). Adults with household annual income of US$75, 000 or more (aOR = 2.21, 95% CI = 1.13–4.31, p = .02) (vs. less than US$20,000) and those with moderate (aOR = 1.75, 95% CI = 1.05–2.91, p = .03) (vs. liberal) political viewpoint were more likely to be neutral than oppose the policy. Former (aOR = 0.56, 95% CI = 0.32–0.97, p = .03) and current (aOR = 0.30, 95% CI = 0.09–0.94, p = .03) e-cigarette users (vs. never users) were less likely to support than oppose the policy (Table 2).

Table 2.

Adjusted Multinomial Logistic Regression Analysis Examining Predictors of Opinion Toward Policy Giving R-Rating to Movies With Cigarette Smoking Among U.S. Adults (n=3,865, HINTS 5, Cycle 4, 2020, the United States).

Characteristics	Movies with cigarette smoking should be rated R to protect children and youth
	Support vs. oppose		Support vs. neutral		Neutral vs. oppose
	aOR (95% CI)	p-value	aOR (95% CI)	p-value	aOR (95% CI)	p-value
Age groups (in years) (ref: 18–34)
35–49	1.60 [0.95, 2.70]	.08	1.26 [0.80, 1.97]	.31	1.28 [0.74, 2.18]	.37
50–64	2.28 [1.25, 4.16]	.008	1.39 [0.82, 2.36]	.22	1.64 [0.91, 2.95]	.097
≥65	4.54 [2.41, 8.55]	<.001	2.46 [1.43, 4.24]	.002	1.85 [0.97, 3.49]	.06
Sex (ref: male)
Female	1.06 [0.76, 1.48]	.73	0.95 [0.69, 1.29]	.73	1.12 [0.74, 1.69]	.58
Race/Ethnicity (ref: non-Hispanic White)
Non-Hispanic Black	1.74 [1.02, 2.96]	.04	1.23 [0.74, 2.05]	.41	1.41 [0.83, 2.38]	.20
Hispanic	1.53 [0.95, 2.45]	.07	1.637 [0.95, 2.83]	.07	0.93 [0.55, 1.59]	.79
Non-Hispanic Asian or other minorities	1.09 [0.61, 1.96]	.77	1.85 [1.04, 3.28]	.03	0.59 [0.29, 1.20]	.14
MSA residency status (ref: MSA)
Non-MSA	0.82 [0.49, 1.35]	.42	0.69 [0.44, 1.12]	.13	1.17 [0.62, 2.20]	.62
Education (ref: less than high school)
High school graduate	0.61 [0.18, 2.03]	.41	0.86 [0.28, 2.62]	.79	0.71 [0.21, 2.35]	.56
Some college	0.58 [0.18, 1.91]	.36	0.78 [0.24, 2.57]	.68	0.75 [0.20, 2.73]	.65
College graduate or more	0.32 [0.08, 1.21]	.09	0.74 [0.22, 2.53]	.62	0.43 [0.13, 1.47]	.17
Annual household income (ref: less than US$20,000)
US$20,000 to <US$35,000	0.97 [0.46, 2.04]	.93	0.69 [0.42, 1.16]	.16	1.39 [0.65, 3.02]	.39
US$35,000 to <US$50,000	1.32 [0.68, 2.57]	.41	0.84 [0.47, 1.51]	.56	1.57 [0.79, 3.08]	.19
US$50,000 to <US$75,000	1.46 [0.64, 3.31]	.36	0.84 [0.44, 1.59]	.58	1.75 [0.79, 3.88]	.17
US$75,000 or More	1.59 [0.82, 3.06]	.16	0.72 [0.38, 1.34]	.29	2.21 [1.13, 4.31]	.02
Marital status (ref: single/never married)
Married or living as married	1.24 [0.69, 2.22]	.47	1.21 [0.69, 2.08]	.50	1.03 (0.60, 1.74)	.93
Divorced/Widowed/Separated	0.97 [0.53, 1.76]	.91	1.22 [0.69, 2.17]	.48	0.79 [0.41, 1.53]	.48
Number of children under the age of 18 living in the household (ref: none)
One	1.05 [0.59, 1.85]	.85	1.25 [0.74, 2.09]	.40	0.85 [0.49, 1.46]	.54
≥Two	1.03 [0.63, 1.68]	.90	1.44 [0.93, 2.23]	.10	0.72 [0.43, 1.21]	.21
Social media use (ref: no)
Yes	1.25 [0.79, 1.97]	.32	1.12 [0.80, 1.55]	.51	1.13 [0.66, 1.91]	.66
Smoking status (ref: never)
Current	1.34 [0.66, 2.73]	.41	0.98 [0.51, 1.86]	.94	1.38 [0.65, 2.93]	.40
Former	0.80 [0.46, 1.39]	.43	0.82 [0.48, 1.39]	.45	0.98 [0.47, 2.07]	.96
E-cigarette use (ref: never)
Current	0.30 [0.09, 0.94]	.03	0.56 [0.14, 2.16]	.39	0.53 [0.21, 1.37]	.18
Former	0.56 [0.32, 0.97]	.03	0.78 [0.43, 1.45]	.43	0.71 [0.41, 1.25]	.23
Political viewpoint (ref: liberal)
Moderate	1.19 [0.70, 2.05]	.50	0.69 [0.45, 1.04]	.07	1.75 [1.05, 2.91]	.03
Conservative	0.91 [0.53, 1.57]	.73	0.88 [0.53, 1.48]	.63	1.03 [0.59, 1.79]	.90

Note. aOR = adjusted odds ratio; CI = confidence interval; Ref = reference; MSA = metropolitan statistical area.

Discussion

The empirical evidence to advocate for a policy of assigning movies with smoking an R-rating is growing across the United States and worldwide. This study sought to expand the literature on this issue by assessing the extent to which U.S. adults are supportive, neutral, or opposed to a default R-rating policy for movies with cigarette smoking; it also explored various predictors of support, neutrality, and opposition toward such a policy. Our findings indicate that almost half (48.2%) of U.S. adults support a R-rating policy for movies depicting cigarette use, which is relatively close to the upper limit (40.0%–48.2%) of what has been reported in other studies (Blake et al., 2010; Lama et al., 2022; McMillen, 2020; Oghenetega et al., 2022). We also found that there is more neutrality than opposition (31.1% vs. 20.7%) to such a policy, which could be due to a lack of public understanding regarding the link between depictions of cigarette smoking in movies and subsequent youth smoking initiation. Efforts to raise awareness of the policy’s potential value are particularly important to garner broad public support for an R-rating policy for movies with smoking, which may influence both MPA and non-MPA member film studios consideration of R-ratings (Fillon, 2023).

This study identified age, race/ethnicity, and household annual income as significant sociodemographic predictors of U.S. adults’ opinions regarding a default R-rating policy for films depicting cigarette use. Compared with younger adults (18–34 years old), we found greater public support than opposition for the R-rating policy among adults aged above ≥50 years. In addition, those aged ≥65 years (vs. 18–34 years old) were also more likely to be supportive than neutral to this policy. A potential explanation for such findings could be due to the greater awareness and concern about the negative impacts of youth tobacco use among older adults than their younger counterparts. Findings from a systematic review also reported that older adults are generally more supportive of restrictive policies around tobacco, alcohol, and an unhealthy diet (Diepeveen et al., 2013).

In this study, those with an annual household income of ≥US$75,000 were more likely to be neutral (vs. opposed) about having an R-rating policy than those with a less than US$20,000 annual household income. The reason for such a finding could be that those with higher incomes may feel less personally affected by tobacco control policies, whether socially or economically, as there is a lower prevalence of tobacco use in this segment of the population. Compared with Non-Hispanic Whites, non-Hispanic Black adults in our study were more supportive (vs. opposed) and adults from non-Hispanic Asian origin or other minority groups were more neutral (vs. opposed) of R-rating policy. The disproportionate impact of tobacco-related health issues that Black or other racial minority communities have experienced over the years, coupled with aggressive marketing strategies from the tobacco industry (Lee et al., 2015) and the cultural norms and values that place a strong emphasis on family and community well-being (Smith et al., 2019), could be potential reasons for higher support for an R-rating policy in these subgroups.

In the published studies that have assessed support for or opposition to tobacco control policy measures, smoking status has been an important predictor of opposition (Blake et al., 2022; Gentzke et al., 2020; Jeffery et al., 1990; Schmidt et al., 2018). In our study, being a former or current smoker was not a significant predictor of opinions toward the R-rating policy. However, people who were former and current e-cigarette users (vs. never users) were less likely to support than oppose the R-rating policy for movies with cigarette smoking. Several factors may explain our findings. First, people who are former or current e-cigarette users may perceive e-cigarettes as a less harmful alternative to traditional cigarettes (Malt et al., 2020), or might be less aware of or less concerned about the health risks associated with cigarette smoking. As a result, they might be less likely to support restrictive policies for smoking in movies compared with cigarette smokers who may have a different perspective on the health risks associated with smoking. Second, e-cigarette users and cigarette smokers may identify with different social groups or subcultures. Social identity can influence individuals' attitudes and behaviors, including their stance on policies related to smoking in movies. Third, e-cigarette users may be of the view that restricting smoking or tobacco scenes in movies with an R-rating infringes upon their personal liberties, hinders creative expression in movies, and contributes to the stigmatization of smokers or tobacco users (Stuber et al., 2008). Finally, it is plausible that some respondents may be dual tobacco users (2.3% of current dual users and 4.5% of former dual users of cigarette and e-cigarette—data not shown in tables), and therefore they choose to provide less support toward such a policy. It is important to note that the survey item in this study assessed public opinion regarding an R-rating policy for movies with cigarette smoking and did not focus on e-cigarette smoking. Thus, it would be interesting to investigate in future how various characteristics would influence public opinion toward policies restricting young people’s exposure to cigarette smoking, e-cigarette smoking, and other forms of tobacco products portrayals in films and other media platforms (e.g., television and online streaming), particularly those with a substantial youth audience (Fillon, 2023).

Political ideology is considered an important predictor of attitudes and opinions associated with tobacco control policies (Cohen, 2000). This study found that compared with liberals, those with moderate political viewpoints were more likely to be neutral than opposed to the R-rating policy. Prior research has shown that people who espouse liberal ideology or believe that the government has a role in promoting healthy lifestyles have lower smoking rates (Fox et al., 2017) and are generally supportive of tobacco control policies (Cohen et al., 2001; Shete et al., 2021). However, those who express conservative ideology are more resistant to smoking behavior change and anti-tobacco policies (Filippidis et al., 2017), as they may prioritize individual freedom and limited government intervention. Thus, the ideological divide between the role of government to intervene to protect the health of its citizens and the rights of individuals to make their own choices is pivotal to the debate on developing and implementing public health policies. With the increase in political polarization associated with other public health issues and policies (Blendon et al., 2021; Shete et al., 2021), it has become increasingly important to consider differing political viewpoints when educating the public about the harms of tobacco and anti-tobacco policies (Blendon et al., 2021; Shete et al., 2021). As research on political ideology and tobacco control is still developing, it would be useful to conduct qualitative or mixed-methods research with the general public, policymakers, and government legislatures to explore in-depth the role of political ideology and how it relates to support for tobacco control policies, including R-rating policy in the U.S. population (Cohen, 2000).

This study has some inherent limitations. First, it used HINTS data, which is cross-sectional in nature and uses self-reported measures; this increases the chances of recall bias. Second, the response of “neither support nor oppose,” which we considered in this study as a “neutral” response to assess public opinion toward an R-rating policy for movies with smoking, could reflect a number of things, including uncertainty, limited knowledge, a lack of understanding, conflict of interest, or political or social pressure. There is a need for robust longitudinal and qualitative or mixed-methods studies in the future that allow researchers to identify patterns and reasons behind public attitudes, beliefs, and behaviors toward R-rating policy. Furthermore, future research should consider exploring disparities in public opinion to identify if certain population subgroups are more resistant to policy changes or have specific concerns and needs. Such information can guide proactive R-rating policy development and implementation ensuring that tobacco control efforts remain effective and responsive to evolving public sentiment.

Conclusion

Our study suggests that there is a modest public support among U.S. adults for a default R-rating policy for movies depicting cigarette smoking. In addition, several factors such as socio-demographic (age, race/ethnicity, and household annual income), behavioral (e-cigarette use), and political viewpoint are significant predictors of U.S. adults’ opinions regarding an R-rating policy. Based on our findings, we recommend several action items for tobacco control advocates and stakeholders regarding R-rating policy development and implementation. First, there is a need to raise awareness and carry out educational campaigns targeting not only the general public, but also parents, scriptwriters, filmmakers, and producers on the impact of smoking portrayals in movies. It is vital to emphasize the potential benefits of R-rating and other anti-tobacco policies to all these stakeholders. Second, tailored messaging and outreach initiatives should be developed, specifically addressing the rationale behind R-ratings for films depicting smoking. These efforts should be directed toward communities based on age, race/ethnicity, household income, e-cigarette use, and political ideologies. Third, it is crucial to encourage and advocate for all film studios (including MPA and non-MPA affiliated film studios as well as other independent film studios) to explicitly consider including “smoking or tobacco” as a criterion in the movie rating process. This is particularly important considering its potential influence on younger audiences. Collaboration among public health agencies, filmmakers, rating boards, advocacy groups, and policymakers is essential in establishing guidelines and recommendations concerning smoking depiction in films and assigning movie ratings. These collaborations can facilitate public health campaigns aimed at counteracting any normalization of smoking behaviors and empowering individuals to make informed decisions about their movie viewing choices.

Supplemental Material

sj-docx-1-heb-10.1177_10901981241239933 – Supplemental material for Predictors of U.S. Adults’ Opinion Toward an R-Rating Policy for Movies With Cigarette Smoking

Supplemental material, sj-docx-1-heb-10.1177_10901981241239933 for Predictors of U.S. Adults’ Opinion Toward an R-Rating Policy for Movies With Cigarette Smoking by Nikhil Ahuja, Asos Mahmood, Satish Kedia and Patrick J. Dillon in Health Education & Behavior

Footnotes

Data Availability Statement

Data used for this paper are publicly available at

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Nikhil Ahuja

Supplemental Material

Supplemental material for this article is available online.

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