• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Tob Control. Author manuscript; available in PMC Jan 1, 2014.
Published in final edited form as:
PMCID: PMC3335969
NIHMSID: NIHMS331441

Effects of Tobacco-Related Media Campaigns on Young Adult Smoking: Longitudinal Data from the United States

Abstract

Objective

Young adults in the U.S. have one of the highest smoking prevalence rates of any age group, and young adulthood is a critical time period of targeting by the tobacco industry. We examined relationships between potential exposure to tobacco-related media campaigns from a variety of sponsors and 2-year smoking change measures among a longitudinal sample of U.S. adults aged 20-30 from 2001-2008.

Methods

Self-report data were collected from a longitudinal sample of 13,076 U.S. young adults from age 20-30. These data were merged with tobacco-related advertising exposure data from Nielsen Media Research. Two-year measures of change in smoking were regressed on advertising exposures.

Results

Two-year smoking uptake was unrelated to advertising exposure. The odds of quitting among all smokers and reduction among daily smokers in the two years between the prior and current survey were positively related to anti-tobacco advertising, especially potential exposure levels of 104-155 ads over the past 24 months. Tobacco company advertising (including corporate image and anti-smoking) and pharmaceutical industry advertising were unrelated to quitting or reduction.

Conclusions

Continued support for sustained, public health-based, well-funded anti-tobacco media campaigns may help reduce tobacco use among young adults.

Keywords: health promotion, mass media, smoking cessation, tobacco, young adult

INTRODUCTION

Young adults have the highest rates of smoking among all adults in the U.S.[1] While the majority of smokers initiate use prior to age 18, studies have indicated that a growing number of young adult smokers have their first cigarette at age 18 or older.[2-3] Smoking patterns among young adults show that this group is more likely to smoke only occasionally and with lower daily consumption than older smokers, suggesting that this population is likely to be in transition to either nonsmoking or heavier smoking.[2] Interest in quitting smoking is high among young adults. Studies utilizing nationally representative U.S. data found that young adults were more likely than older adults to (a) have seriously tried to quit smoking, and (b) have succeeded in quitting for six months or longer.[4] Importantly, the tobacco industry strongly targets this price- and brand-sensitive population,[1, 5] and research indicates such targeting pays off, because younger adults are more receptive than older adults to cigarette marketing.[2]

Tobacco control recommendations commonly include sustained, high-intensity media campaigns, especially combined with other interventions.[6-9] Research supports the efficacy of such campaigns for youth,[10-13] while showing clear differences in outcomes by advertising sponsor.[14] Research also has established that anti-tobacco media campaigns have been effective for adults in general and older adults.[8-9, 15-17] However, research on media campaign effects among young adults is sparse. Evidence from Massachusetts showed that among recent adult quitters, TV advertisements were the most frequently mentioned source for cessation help, and young smokers were more likely than older smokers to report such perceived benefits from TV ads.[18] In California, younger adults were also more likely than older adults to report hearing about quitline services via media sources (television, radio, and print advertising).[19] To our knowledge, no large-scale studies that examine the effectiveness of anti-tobacco media campaigns specifically among young adults have been published.

In this paper, we contribute to the research on young adult smoking behaviors and policy intervention by examining relationships between potential exposure to tobacco-related advertising and smoking behavior change among a longitudinal U.S. sample. Specifically, we examine how anti-tobacco, tobacco industry, and pharmaceutical television advertising relate to past 2-year smoking uptake, reduction, and quitting (while controlling for a variety of factors such as race/ethnicity, gender, drug use at age 18, and state-level variables of cigarette price and smoke-free air policy).

METHODS

Sample

This analysis utilizes data from the Monitoring the Future (MTF) study, sponsored by the National Institute on Drug Abuse (detailed methodology can be found elsewhere).[20] Briefly, a nationally representative sample of 2,400 U.S. high school seniors from about 130 schools is chosen each year for longitudinal follow-up. Substance users are over-sampled (in analysis, weights are used to appropriately adjust for over-sampling). Respondents are randomly divided into two groups, with one half surveyed in even years and the other in odd years. Follow-up surveys are mailed in the spring with a modest monetary incentive. Response rates for Follow-up 1 (1-2 years past high school) average 56 percent; rates for Follow-ups 2-6 average 52 percent.[20] Study ethical approval was obtained from the University of Michigan Behavioral Sciences Institutional Review Board.

Given that the MTF longitudinal follow-up sample is chosen from high school seniors, individuals who drop out of high school before their senior year are necessarily excluded (estimated to be between 13%-20% of each age cohort nationally).[20] Research has shown that smoking rates among high school dropouts are significantly higher than among students who remain in school,[21] and thus the current study likely underestimates smoking rates in the entire population. However, as shown below, there is still a considerable amount of smoking behavior among respondents.

Nielsen advertising ratings data

Nielsen Media Research provided data on mean audience exposure to all tobacco-related advertising from 1998-2008 appearing on monitored national network and cable television and for local spot, clearance, and syndication television. The current study includes ratings from the U.S. top 75 media markets (encompassing 78% of American television-viewing households).[22] Ratings were aggregated by month, year and market (a detailed methodology is available elsewhere).[23] The current study uses gross ratings points (GRPs) that provide an estimate of the percentage of households watching a television ad per media market over a specified time period.[11] If an ad receives 50 GRPs per month, that ad is estimated to have been viewed an average of 1 time in the past month by 50 percent of all media market viewers. GRPs are averages; individuals may have higher or lower exposure based on personal television viewing behavior.

Merging MTF and Nielsen data

Individual respondents to the MTF surveys were assigned media-market-level measures of average potential exposure to anti-smoking ads based on their geographic location at the time of the survey and the date of survey return. A total of 39,307 individuals surveyed as high school seniors from 1991-2006 were randomly selected for follow-up. As part of the process of preparing the MTF data for merging and to establish consistent potential exposure to media market advertising, observations were retained if respondents reported living in the same state as identified in the mailing address, and if the current follow-up state was the same as reported for the previous survey (please see Appendix Figure 1 for a consort diagram of the sample selection process (available online only)). Further, to ensure that all observations had 24 months between surveys, Follow-up 1 data from respondents surveyed in the year immediately following the base-year survey were removed. The resulting sample included data from 23,294 respondents.

The sample selection process described above is biased towards young adults who are relatively stable geographically. Individuals who were included based on the requirement of residing in the same state as their mailing address were significantly more likely than excluded individuals to report lower parental education levels as a senior in high school and to be employed full-time when they responded to the survey. Included individuals were significantly less likely than excluded individuals to be white, to be attending college, and to have negative views of tobacco use (such as perceiving the harmful effects of cigarettes to have been exaggerated). Research has shown a significant and negative link between young adult cigarette smoking and non-White race/ethnicity,[20,24] but significant and positive relationships between young adult cigarette smoking and lower average parental education and non-college attendance.[20, 24-25] Thus, the retained sample has some characteristics that make them less likely to be smokers, while other characteristics are related to increased risk of smoking. Research among Massachusetts adults has shown that anti-tobacco advertising is more salient among smokers than non-smokers, but such advertising is perceived as more effective by those who are supportive of tobacco control goals.[26] Given that the retained sample for the current analysis exhibited more positive views of tobacco use than excluded individuals, it may be that anti-tobacco-related advertising would be perceived by this group as somewhat less effective.

MTF respondent data were merged with Nielsen advertising data using state and county Federal Information Processing Codes.[27] Research on the effects of tobacco-related media campaigns that involves the use of advertising ratings points has frequently utilized a 4-month depreciated sum of potential exposure as the main independent predictor.[11, 13, 28] However, other research has successfully used a straight 24-month sum.[29, 30] Given that our data were collected every other year, and given that the exact date when each respondent filled out their questionnaire could not be specified with precision, we chose to follow the precedent of a straight 24-month sum. Given that we had access to Nielsen data starting in late 1998, the first MTF data collection year able to be merged with 24-month advertising sums was 2001. A total of 20,547 individuals had survey data from 2001-2008, 76% (15,527) of which resided in the top 75 media markets and were successfully merged with Nielsen data.

Measures

Smoking Behavior Change

Five types of transition in past 30-day smoking in the two years between the current and prior survey were examined: reporting no smoking at the prior survey and any smoking at the current survey (hereafter referred to as 2-year smoking uptake); moving from no smoking to smoking one or more cigarettes per day (2-year daily smoking uptake); moving from any level of smoking to none (2-year quitting among all smokers); moving from smoking at least one cigarette per day to none (2-year quitting among daily smokers); and moving from smoking 1+ cigarettes/day to <1/day or none (2-year reduction or quitting among daily smokers).

Tobacco-Related Advertising

Based on the date each completed survey was returned, 24-month sums of advertising were created for each observation for the following three sponsor types: anti-tobacco (including state tobacco control programs and the American Legacy Foundation), pharmaceutical (including advertising for nicotine replacement therapy, bupropion, etc.), and tobacco industry (including corporate image advertising and youth smoking prevention targeting both parents and youth).1 Each 24-month sum was then divided by 100 to estimate the number of ad exposures seen by 100% of the total television viewing audience over the preceding 24-month period.

Models also explored non-linear advertising specifications via (a) mean-centering the advertising measures and then creating accompanying quadratic terms, and (b) categorizing the advertising measures. The U.S. Centers for Disease Control and Prevention (CDC) recommends 400 target ratings points per four weeks during the introductory phase of anti-tobacco campaigns and 200 target rating points per four weeks following the introductory phase.[6,31] Extrapolating these numbers to 24-month time periods yielded 10,400 ratings points at campaign introductory levels (104 ad exposures for 100% of all viewers over 24 months), and 5,200 ratings points during non-introductory campaign phases (52 ad exposures for 100% of all viewers over 24 months). While current analysis utilized GRPs (as opposed to targeted ratings points as recommended by the CDC), we chose to categorize the advertising measures using 52 ad exposure increments based on available CDC recommendations.

Control Variables

Clear differences have been found in young adult smoking and cessation activity by a variety of socio-demographic characteristics including gender, race/ethnicity, and education level.[1] Among young adults, males have consistently been shown to be more likely than females to be current smokers.[1] Among all adults, current smoking prevalence is highest for non-Hispanic Whites, followed by non-Hispanic Blacks, followed by Hispanics.[1] Reviews of the literature indicate that compared with individuals in college, both employed and unemployed young adults not in college are at particular risk for tobacco use,[32] and young adults who have obtained a college education have a significantly lower likelihood of smoking.[32-33] Differences in quit attempts based on education have been mixed, with some studies finding no differences,[33] while others have found quit rates to be lower among non-college educated young adults.[32]

Based on the above literature, gender, self-reported race/ethnicity (White, Black, Hispanic, or Other), and a dichotomous substance use indicator (all measured at modal age 18) were used as time-invariant controls. Time-varying controls included follow-up survey number (ranging from one to six, used as a proxy for age), a categorical measure of academic status, state cigarette price, an index of state smoke-free air policy, year (using individual year dummy variables), and state dummy variables to control for unmeasured state characteristics.2 The measure of academic status was coded such that 1 = currently not in school and do not have a college degree; 2 = currently in school (either with or without a college degree); 3 = not currently in school and have a college degree.

Analysis

Analyses were run using SURVEY commands in SAS v.9.2 (SAS Institute Inc., Cary, NC). The SURVEY commands (FREQ, MEANS, LOGISTIC) were used to model the longitudinal repeated-measures data by using Taylor linearization-based variance estimation to account for clustering by respondent, computing robust standard errors. Further, all analyses were weighted to (a) account for over-sampling of high school substance users, and (b) address the impact of attrition by post-stratifying the data such that the reweighted cigarette use distribution reproduced the original (high school senior year) distribution of use.[20] Models were first run treating advertising variables as linear, followed by use of quadratic and categorical advertising measures. In quadratic models, the linear advertising terms were mean-centered, and quadratic terms were created from the mean-centered measures.

RESULTS

After restricting the data to observations with no missing data on control variables, 22,445 weighted observations from 12,931 individuals (unweighted) remained for analysis (including data from 74 media markets and 44 states). The range of observations per respondent was one to four; 37 percent of respondents had one observation, 33 percent had two observations, 18 percent had three observations and 11 percent four observations. Each observation measured smoking status change between the current survey (time t) and the previous survey (t - 2 years). Figure 1 shows trends in mean 24-month advertising measures across time. Table 1 summarizes the observed 2-year smoking behavior changes observed for this sample,3 and Table 2 provides descriptive statistics for all measures. Two-year smoking uptake was not common: eight percent of observations reported no smoking at the prior survey and any smoking at the current survey; only three percent of observations reported 2-year daily uptake (moving from no smoking at the prior survey to daily smoking at the current survey). In contrast, almost one quarter of all smokers reported moving from either daily or non-daily smoking at the prior survey to no smoking at the current survey. Among daily smokers, 15 percent reported quitting between the prior and current surveys, and 24 percent reported reduction or quitting (moving to smoking less than one cigarette per day or not smoking at all).

Figure 1
Mean 24-Month Sums of Tobacco-Related Advertising, 2001-2008
Table 1
Two-Year Change in Past 30-Day Smoking Behavior
Table 2
Descriptives

Multivariate models predicting 2-year smoking uptake, quitting, and reduction using linear advertising predictors showed no significant results for any of the three advertising predictors. Further, 2-year smoking uptake models shown no indication of significance in multivariate quadratic models (available online only; see Appendix Table 1). However, indications of significant quadratic relationships were observed between anti-tobacco advertising and 2-year quitting among all smokers and daily smokers, as well as 2-year reduction or quitting among daily smokers, but neither pharmaceutical nor tobacco industry advertising were associated with these outcomes (see online only Appendix Table 1). Multivariate models were then run using dummies created from the categorical advertising measures. Smoking uptake remained unrelated to any type of smoking-related advertising. Further, neither pharmaceutical nor tobacco industry advertising were associated with any quitting or reduction models. However, anti-tobacco advertising was positively and significantly associated with quitting and reduction outcomes.

Table 3 shows multivariate results from models predicting 2-year quitting and reduction using both the quadratic and categorical measures of anti-tobacco advertising (for full categorical model results showing estimates for all control measures, see Appendix Table 2 (online only)). Compared with potential exposure to fewer than 52 ads over the past 24 months, potential exposure to 104-155 anti-tobacco ads was associated with significantly increased odds of 2-year quitting among all smokers. Twenty-two percent of prior smokers reported no cigarette use when past 24-month anti-tobacco advertising levels were lower than 52 compared with 28 percent when advertising levels were 104-155. The overall distribution of both the percentages of smokers reporting quitting and obtained odds ratios showed the relationship between anti-tobacco advertising and quitting among all smokers to be curvilinear.

Table 3
Predicted Odds of 2-Year Quitting Smoking or Reduction by Anti-Tobacco Advertising, 2001-2008

Among daily smokers, the odds of 2-year quitting were also significantly higher with anti-tobacco advertising levels of 104-155 compared with less than 52. Further, the odds of 2-year reduction or quitting among daily smokers significantly increased once anti-tobacco advertising reached 104-155 exposures or higher. Twenty-one percent of daily smokers reported 2-year reduction or quitting with ad exposure levels of less than 52 compared with 27 percent with advertising levels of 104-155, 24 percent when advertising levels were 156-207, and 25 percent when advertising levels were 208 or above.

DISCUSSION

Among this longitudinal sample of relatively geographically stable U.S. young adults, higher potential exposure to anti-tobacco advertising was associated with higher odds of quitting among all smokers and reduction or quitting among daily smokers. Specifically, potential exposure to 104-155 anti-tobacco ads over the past 24 months appeared to relate consistently to quitting and reduction when compared with potential exposure to less than 52 ads.

Our findings should be considered within the limitations of the current study. Due to funding restrictions, we were unable to work with advertising ratings data specifically targeting young adults, instead using gross ratings points. Analyses utilizing TRPs for young adults would help clarify results for all type of advertising: anti-tobacco, pharmaceutical, and industry. As noted in the Methods section, analyses have been adjusted for attrition using cigarette-specific post-stratification procedures; however, our results are subject to a clear selection bias given that we limited the sample for these analyses to young adults who reported residing in the same state for each 24-month time period, resulting in sample differences previously discussed. Included young adults also were limited to those residing in the top 75 media market areas; while the top 75 market areas do encompass more than 75% of American television-viewing households[22], young adults in more rural areas would be excluded. Such limitations notwithstanding, eight percent of the observations reported any late smoking uptake and 24 percent of smokers reported quitting. Thus, the observations remaining for analysis appear to have meaningful levels of change in smoking behaviors over time.

U.S. young adults have one of the highest smoking prevalence rates of any age group,[1] and research indicates that young adulthood is a critical time period of advertising and promotion targeting by the tobacco industry.[2, 5, 36] Given the clear need for cessation and prevention services among this population, it is encouraging that the current study found anti-tobacco advertising significantly increased the odds of 2-year quitting among all young adult smokers, and 2-year reduction or quitting among young adult daily smokers. While this study did not investigate long-term quitting and relapse, quitting smoking by age 30 has been found to reduce significantly the excess health risks associated with tobacco use.[6] Continued funding of anti-tobacco media campaigns at the exposure levels found in this study would likely reduce long-term health costs. Smoking uptake is relatively uncommon after age 18; in our sample, only eight percent reported any late smoking uptake, and only three percent reported late smoking daily uptake within the 2-year intervals observed. Thus, it is perhaps not surprising that advertising was not associated with these behaviors, unlike the more usual pattern of smoking uptake in adolescence which is associated with exposure to anti-smoking advertising.[11, 13]

Potential exposure to 104-155 anti-tobacco ads over the past 24 months was consistently related to 2-year quitting and reduction. While potential advertising exposure seemed to have a curvilinear relationship with the odds of 2-year quitting among all smokers, no such point of diminishing returns was observed for the odds of 2-year reduction or 2-year quitting among daily smokers. Adequate funding of tobacco control media campaigns is becoming more and more difficult given current economic realities. Research has indicated that funding reductions to state tobacco control media campaigns can have immediate effects on cognitive precursors to smoking behaviors,[37] and published reviews of health campaign efforts repeatedly call for adequately funded, sustained, integrated health communication efforts.[6, 9] While our single study cannot assume to define adequate broadcast levels for anti-tobacco media campaigns, it does indicate an important possible range of advertising frequency relative to U.S. young adult smoking cessation efforts. Whether this range of advertising frequency might be consistently found to be effective with additional U.S. populations or with international populations is unknown. However, studies have indicated that there is considerable equity across socio-demographic groups and national borders in terms of response to anti-tobacco advertising.[13-14, 31, 38]

Tobacco industry advertising was not associated with the smoking uptake or cessation-related outcomes included in these analyses. Within the U.S., tobacco company corporate image and youth smoking prevention television advertising began in the late 1990s. However, tobacco industry youth smoking prevention programs have been promoted since the early 1980s not only in the U.S. but also throughout Canada, Latin America, Europe, Australia, and Asia.[39] Research has indicated that by providing media campaigns that ostensibly aim to reduce youth smoking or improve corporate image, tobacco industries often build important ties with governments and the public, thereby legitimizing their activities.[39] In the current study, 64 percent of mean tobacco industry advertising was related to corporate image, 22 percent to parent-targeted prevention, and 14 percent to youth-targeted prevention. Previous research found that tobacco industry advertising that targeted youth showed little in the way of relationships with youth smoking-related beliefs and behaviors. However, industry advertising targeting parents was associated with decreased perceived harm of smoking and increased approval of smoking and increased current smoking among youth.[28] Given that young adults were not the target of the majority of industry advertising in the current study, and their relative independence from parental influence, the lack of findings is perhaps not surprising.

Interestingly, levels of potential exposure to pharmaceutical advertising were not associated with late uptake, quitting or reduction among our sample. These findings are similar to evidence from studies of youth.[40] However, given that pharmaceutical advertising is not meant to target youth, but rather targets adult smokers, our lack of significant effects is of interest. Pharmaceutical advertising had the highest potential exposure levels in the current study and the least variance: only one percent of observations had potential exposure levels lower than 156 ads over the past 24 months. Given that significant results for anti-tobacco advertising were most often found when comparing advertising levels of 104-155 with less than 52, it may be that pharmaceutical advertising simply did not have adequate variance within this population to show significant effects. Other possible explanations for a lack of significant findings include: (a) our analyses utilized GRPs versus TRPs measuring exposure for young adults, and (b) the possibility that young adults are less likely than older adults to make use of pharmaceutical methods of quitting, and thus advertising levels are not as salient. Support for this hypothesis is suggested by some Canadian and U.S. studies.[41, 42] Prior research examining the comparative effects of tobacco control policies and televised antismoking advertising with a large Australian adult sample found that smoking prevalence was not related to pharmaceutical advertising levels or sales of nicotine replacement therapy or other pharmaceutical products.[8]

The results of the current paper demonstrate that among this longitudinal sample of relatively geographically stable U.S. young adults, anti-tobacco media campaigns appear to be an effective method of increasing smoking cessation and/or reduction. Further, they indicate that potential exposure levels of 140-155 ads over a 24-month period may be particularly effective. The findings highlight the need for continued support for adequately funded, sustained, integrated anti-tobacco media campaigns that can combat messages encouraging tobacco use among young adults.

Acknowledgments

FUNDING The authors would like to thank Young Ku Choi for statistical methods assistance. Monitoring the Future is supported by the National Institute on Drug Abuse (DA01411 and DA016575). Additional grant support was obtained from the National Cancer Institute (CA123444) and the Robert Wood Johnson Foundation (64703). The views expressed in this article are those of the authors and do not necessarily reflect the views of the funders.

Appendix

Appendix Table 1

Two-Year Smoking Behavior Change by Tobacco-Related Advertising: Linear and Quadratic Advertising Predictors, 2001-2008

2-Year Smoking Uptakea2-Year Daily Smoking Uptakeb
ORCIpORCIp

Anti-tobacco ads
 Linear model1.0000.988-1.0120.96100.9880.968-1.0080.2399
 Quadratic model
  Linear term1.0000.986-1.0140.99130.9880.965-1.0110.2983
  Quadratic term1.0000.999-1.0010.83971.0000.998-1.002.09353
Pharmaceutical ads
 Linear model0.9930.946-1.0420.77100.9750.904-1.0510.5041
 Quadratic model
  Linear term0.9990.948-1.0530.96920.9820.904-1.0660.6587
  Quadratic term1.0000.995-1.0050.99261.0000.992-1.0080.9693
Tobacco industry ads
 Linear model1.0230.983-1.0650.25811.0330.969-1.1020.3225
 Quadratic model
  Linear term1.0090.955-1.0650.75621.0170.932-1.1090.7093
  Quadratic term1.0010.999-1.0030.42761.0010.997-1.0050.5919

2-Year Quitting Among All Smokersc2-Year Quitting Among Daily Smokersd2-Year Reduction or Quitting Among Daily Smokerse
ORCIpORCIpORCIp

Anti-tobacco ads
 Linear model0.9950.984-1.0070.43960.9990.983-1.0150.89591.0120.998-1.0260.0969
 Quadratic model
  Linear term1.0040.989-1.0180.61851.0090.988-1.0300.40471.0231.005-1.0410.0131
  Quadratic term0.9990.998-1.0000.04200.9990.998-1.0000.10090.9990.998-1.0000.0430
Pharmaceutical ads
 Linear model1.0310.982-1.0820.22011.0280.961-1.1000.42401.0150.957-1.0750.6241
 Quadratic model
  Linear term1.0290.977-1.0840.28351.0280.956-1.1050.45391.0130.951-1.0780.6900
  Quadratic term0.9970.992-1.0020.28820.9980.991-1.0060.62910.9970.991-1.0040.3820
Tobacco industry ads
 Linear model1.0030.967-1.0420.86041.0050.953-1.0590.86311.0070.963-1.0520.7724
 Quadratic model
  Linear term0.9960.948-1.0450.86170.9800.917-1.0470.54380.9920.936-1.0510.7773
  Quadratic term1.0000.998-1.0020.98851.0010.998-1.0040.40671.0000.998-1.0030.7591

Notes: In these analyses, advertising measures are gross ratings points (GRPs) and have been re-scaled by units of 10. Thus, estimates should be understood as inferring the change in odds of the outcome for every 10-unit increase in advertising. Controlling for self-reported race/ethnicity, gender, base-year drug use, academic status, state-level policy variables of cigarette price and smoke-free air index, level of follow-up survey, year and state fixed effects.

aMoving from no past-30-day smoking at the prior survey to any smoking in the past 30 days at the current survey.
bMoving from no past-30-day smoking at the prior survey to smoking 1+ cigarettes/day in the past 30 days at the current survey.
cMoving from any smoking in past 30 days at the prior survey to none at all at the current survey.
dMoving from daily smoking in past 30 days at the prior survey to none at all at the current survey.
eMoving from daily smoking in past 30 days at the prior survey to <1 cigarette/day or none at all at the current survey.

Appendix Table 2

Predicted Odds of 2-Year Quitting Smoking or Reduction by Tobacco-Related Advertising, 2001-2008

2-Year Quitting Among All Smokersa2-Year Quitting Among Daily SmokersbReduction or Quitting Among Daily Smokersc
ORCIpORCIpORCIp

Anti-tobacco ads
 Less than 52(ref)(ref)(ref)
 52 to 1031.1510.912-1.4520.23611.1770.840-1.6480.34311.1780.887-1.5650.258
 104 to 1551.4011.072-1.8300.01341.5451.041-2.2930.03091.591.147-2.2040.0054
 156 to 2071.2070.896-1.6260.21521.3490.873-2.0840.17791.4320.991-2.0680.0556
 208 or greater1.2220.898-1.6620.20131.4090.902-2.2020.13171.6591.143-2.4080.0077
Pharmaceutical ads
 Less than 208(ref)(ref)(ref)
 208 to 2591.0120.834-1.2290.90150.9050.679-1.2070.49840.9580.753-1.2200.7305
 260 or greater0.9470.679-1.3190.74630.9440.586-1.5220.81421.0260.689-1.5270.8999
Tobacco industry ads
 Less than 104(ref)(ref)(ref)
 104 to 1551.0560.811-1.3740.68640.7940.558-1.1300.20060.8720.638-1.1900.3871
 156 to 2071.0920.762-1.5640.63150.670.407-1.1020.11440.7190.467-1.1050.1326
 208 or greater1.4440.843-2.4740.1810.7660.364-1.6120.48290.80.422-1.5180.4944
Surveyd0.9880.946-1.0320.59741.0190.959-1.0840.53930.9740.925-1.0270.3281
Race/ethnicity
 White(ref)(ref)(ref)
 African American1.2230.867-1.7240.25121.0930.686-1.7410.70960.7910.497-1.2590.3228
 Hispanic1.5641.216-2.0120.00051.2960.862-1.9490.21191.541.084-2.1880.016
 Other or missing data1.0080.785-1.2950.94960.8270.574-1.1930.30990.9380.695-1.2650.6745
Male0.8590.757-0.9740.0180.8160.683-0.9750.02540.8380.719-0.9770.0239
Academic status
 Not in school, no degree(ref)(ref)(ref)
 In school1.6441.425-1.896<.00011.3181.076-1.6140.00751.6971.431-2.012<.0001
 Not in school, with degree2.0081.705-2.364<.00011.3961.097-1.7760.00672.0541.669-2.529<.0001
Cigarette pricee0.9990.995-1.0040.7961.0020.995-1.0080.56641.0051.000-1.0110.0649
Smoke-free air indexf1.0050.999-1.0110.12260.9970.988-1.0070.5820.9960.988-1.0040.3415
Survey callendar year
 2001(ref)(ref)(ref)
 20021.010.736-1.3890.94530.840.532-1.3280.45580.810.550-1.1880.2785
 20031.540.884-2.6750.12760.900.410-1.9690.78940.810.417-1.5790.5385
 20041.380.775-2.4460.27560.700.313-1.5690.38740.580.290-1.1500.1183
 20051.200.699-2.0610.50730.730.341-1.5750.42640.680.357-1.3000.2440
 20061.310.781-2.1800.30900.960.462-1.9770.90230.970.528-1.7920.9299
 20071.570.929-2.6530.09181.090.522-2.2860.81370.930.497-1.7340.8148
 20081.510.800-2.8410.20420.890.364-2.1880.80250.870.405-1.8670.7194
State
 AL0.170.029-0.9510.04380.040.003-0.3910.00640.050.006-0.4560.0074
 AZ0.180.035-0.8880.03540.050.006-0.3360.00250.090.013-0.5810.0117
 AR0.130.023-0.7950.0270<0.001<0.001-<0.001<.00010.030.003-0.3750.0059
 CA0.250.055-1.1400.07340.080.013-0.4460.00430.110.019-0.6240.0128
 CO0.220.046-1.0380.05580.060.009-0.3600.00220.110.019-0.6680.0161
 CT0.180.033-0.9790.04720.060.008-0.4700.00720.060.008-0.4310.0053
 DE0.290.019-4.5430.37980.130.005-3.0580.20270.090.003-2.0790.1308
 DC0.220.030-1.5160.12280.090.006-1.4490.08980.150.013-1.6900.1246
 FL0.250.054-1.1430.07360.090.014-0.5080.00690.150.025-0.8430.0315
 GA0.250.049-1.2680.09400.110.015-0.7190.02160.120.017-0.7600.0248
 ID0.230.044-1.2050.08200.060.008-0.4360.00580.060.008-0.4370.0056
 IL0.200.043-0.8980.03580.080.013-0.4500.00450.090.016-0.5360.0078
 IN0.230.048-1.0510.05790.070.011-0.3860.00270.070.012-0.4020.0029
 IA0.420.086-2.0610.28610.220.036-1.3620.10360.280.045-1.7670.1767
 KS0.290.060-1.3670.11670.120.019-0.7360.02200.160.027-0.9970.0496
 KY0.300.061-1.4650.13650.130.021-0.7830.02610.150.024-0.9140.0396
 LA0.120.015-0.8780.0369<0.001<0.001-<0.001<.00010.030.004-0.3010.0024
 MD0.180.039-0.8790.03390.070.011-0.4450.00490.100.016-0.5780.0105
 MA0.220.046-1.0800.06220.080.012-0.5100.00790.080.013-0.5040.0072
 MI0.190.042-0.9070.03710.080.014-0.4990.00650.110.018-0.6230.0130
 MN0.240.052-1.1010.06620.090.014-0.5050.00670.120.020-0.6730.0164
 MS0.200.016-2.4850.2117<0.001<0.001-<0.001<.0001<0.001<0.001-<0.001<.0001
 MO0.090.019-0.4550.00340.060.009-0.3640.00240.120.020-0.7100.0196
 NE0.270.051-1.3660.11240.080.012-0.5990.01350.090.013-0.5850.0121
 NV0.320.043-2.4400.27400.080.005-1.3150.07670.050.003-0.8650.0392
 NJ0.250.051-1.1830.08000.080.012-0.5140.00800.060.009-0.3650.0024
 NM0.220.045-1.0750.06140.050.007-0.3460.00260.100.015-0.6360.0149
 NY0.140.030-0.6930.01560.050.008-0.3260.00170.050.009-0.3280.0015
 NC0.170.036-0.8500.03070.060.009-0.4160.00420.100.016-0.5990.0120
 OH0.190.042-0.8440.02920.080.014-0.4380.00370.090.016-0.5090.0063
 OK0.320.068-1.5100.14990.180.030-1.1160.06560.250.042-1.4670.1244
 OR0.760.142-4.0170.74310.400.050-3.1740.38390.360.046-2.9020.3399
 PA0.170.036-0.7580.02040.070.011-0.3780.00240.080.014-0.4610.0046
 RI0.150.028-0.7920.02540.060.008-0.4210.00470.070.010-0.4400.0050
 SC0.260.053-1.2700.09600.100.015-0.6080.01290.130.022-0.8090.0286
 TN0.250.054-1.1570.07620.090.016-0.5630.00960.120.020-0.6830.0171
 TX0.230.051-1.0380.05590.090.015-0.4880.00570.130.023-0.7250.0201
 UT0.210.039-1.1500.07210.070.009-0.4910.00770.070.010-0.4570.0058
 VT0.420.053-3.2760.40630.210.020-2.1320.18590.150.016-1.4940.1064
 VA0.240.052-1.0990.06590.090.016-0.5360.00790.130.022-0.7320.0210
 WA0.210.042-0.9880.04830.060.010-0.3890.00310.080.013-0.4850.0060
 WV0.150.021-1.0060.05070.060.006-0.5660.01410.180.020-1.5880.1218
 WI0.250.054-1.1650.07750.100.017-0.5960.01140.100.017-0.5920.0110
 WY(ref)(ref)(ref)

Notes: In these analyses, advertising measures are gross ratings points (GRPs) and have been re-scaled by units of 10. Thus, estimates should be understood as inferring the change in odds of the outcome for every 10-unit increase in advertising.

aMoving from any smoking in past 30 days at the prior survey to none at all at the current survey; N (wtd) = 6,365.
bMoving from daily smoking in past 30 days at the prior survey to none at all at the current survey; N (wtd) = 4,476.
cMoving from daily smoking in past 30 days at the prior survey to <1 cigarette/day or none at all at the current survey; N (wtd) = 4,476.
d1=First follow-up…6=sixth follow-up; used as a proxy for age.
eState-level price in cents per pack of cigarettes obtained using data from first 6 months of the year, generics excluded, and adjusted for the CPI82-84.
fState-level scale measuring the strictness of state smoke-free air laws.

Appendix Figure 1

An external file that holds a picture, illustration, etc.
Object name is nihms331441f2.jpg
Sample Flow Diagram

Notes: n indicates unweighted unique respondents.

Footnotes

1Tobacco industry documents have shown that corporations such as Philip Morris view both types of advertising (youth smoking prevention and corporate image) to be part of coordinated public relations efforts.[7] Thus, we include both in the current analyses.

2State fixed effects were considered to be more important to include than media-market fixed effects due to the specific focus on anti-tobacco advertising, consisting of advertising from both state tobacco control programs and the American Legacy Foundation.

3Detailed information on time trends for cigarette smoking among young adults can be found in Johnston et al.[20].

COMPETING INTERESTS The authors have no competing financial interests related to the findings of this paper.

References

1. National Cancer Institute. Cancer trends progress report – 2009/2010 update. Bethesda, MD: National Cancer Institute, National Institutes of Health, Department of Health and Human; [17 Sep 2010]. Services 2010. http://progressreport.cancer.gov.
2. Biener L, Albers AB. Young adults: vulnerable new targets of tobacco marketing. Am J Public Health. 2004;94(2):326–330. [PMC free article] [PubMed]
3. Substance Abuse and Mental Health Services Administration. Results from the 2007 National Survey on Drug Use and Health: national findings (Office of Applied Studies, NSDUH Series H-34, DHHS Publication No SMA 08-4343) Rockville, MD: SAMHSA; 2008.
4. Messer K, Trinidad DR, Al-Delaimy WK, et al. Smoking cessation rates in the United States: a comparison of young adult and older smokers. Am J Public Health. 2008;98(2):317–322. [PMC free article] [PubMed]
5. White VM, White MM, Freeman K, Gilpin EA, Pierce JP. Cigarette promotional offers: who takes advantage? Am J Prev Med. 2006;30(3):225–231. [PubMed]
6. Centers for Disease Control and Prevention. Best practices for comprehensive tobacco control programs—2007. Atlanta, GA: United States Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2007.
7. National Cancer Institute. The role of the media in promoting and reducing tobacco use. Tobacco Control Monograph No 19 (NIH Pub No 07-6242) Bethesda, MD: U.S. Department of Health and Human Services, National Institutes of Health, National Cancer Institute; 2008.
8. Wakefield MA, Durkin S, Spittal MJ, et al. Impact of tobacco control policies and mass media campaigns on monthly adult smoking prevalence. Am J Public Health. 2008;98(8):1443–1450. [PMC free article] [PubMed]
9. Wakefield MA, Loken B, Hornik RC. Use of mass media campaigns to change health behavior. Lancet. 2010 doi: 10.1016/S0140-6736(10)60809-4. published online October 7. [PubMed] [Cross Ref]
10. Davis KC, Farrelly MC, Messeri P, et al. The impact of national smoking prevention campaigns on tobacco-related beliefs, intentions to smoke and smoking initiation: results from a longitudinal survey of youth in the United States. Int J Environ Res Public Health. 2009;6(2):722–740. [PMC free article] [PubMed]
11. Emery S, Wakefield MA, Terry-McElrath Y, et al. Televised state-sponsored anti-tobacco advertising and youth smoking beliefs and behavior in the United States, 1999-2000. Arch Pediatr Adolesc Med. 2005;159:639–645. [PubMed]
12. Soldz S, Cui XJ. Pathways through adolescent smoking: a 7-year longitudinal grouping analysis. Health Psychol. 2002;21(5):495–504. [PubMed]
13. Terry-McElrath YM, Wakefield MA, Emery S, et al. State anti-smoking advertising and smoking outcomes by gender and race/ethnicity. Ethn Health. 2007;12(4):339–362. [PubMed]
14. Wakefield M, Szczypka G, Terry-McElrath Y, et al. Mixed messages on tobacco: comparative exposure to public health, tobacco company and pharmaceutical company sponsored tobacco-related television campaigns in the United States, 1999-2003. Addiction. 2005;100(12):1875–1883. [PubMed]
15. Borland R, Balmford J. Understanding how mass media campaigns impact on smokers. Tob Control. 2003;12:ii45–ii52. [PMC free article] [PubMed]
16. Messer K, Pierce JP, Zhu SH, et al. The California Tobacco Control Program’s effect on adult smokers: (1) smoking cessation. Tob Control. 2007;16:85–90. [PMC free article] [PubMed]
17. Vallone DM, Duke JC, Mowery PD, et al. The impact of EX (R): results from a pilot smoking-cessation media campaign. Am J Prev Med. 2010;38(3):S312–S318. [PubMed]
18. Biener L, Reimer RL, Wakefield M, et al. Impact of smoking cessation aids and mass media among recent quitters. Am J Prev Med. 2006;30(3):217–224. [PubMed]
19. Cummins SE, Hebert KK, Anderson CM, et al. Reaching young adult smokers through quitlines. Am J Public Health. 2007;97(8):1402–1405. [PMC free article] [PubMed]
20. Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the Future national survey results on drug use, 1975-2008. Volume II: college students and adults ages 19-50 (NIH Publication No 09-7403) Bethesda, MD: National Institute on Drug Abuse; 2009.
21. Kopstein A. Tobacco use in America: findings from the 1999 National Household Survey on Drug Abuse (Analytic Series: A-15, DHHS Publication No SMA 02-3622) Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies; 2001.
22. Nielsen Media Research. DMA market and demographic rank: September 2001. New York: Nielsen Media Research; 2002.
23. Szczypka G, Emery S, Wakefield M, Chaloupka F. ImpacTeen Research Paper Series No 29. Chicago, IL: University of Illinois at Chicago; 2003. [17 Sep 2010]. The adaptation and use of Nielsen Media Research commercial ratings data to measure potential exposure to televised smoking-related advertisements. www.impacteen.org/generalarea_PDFs/Nielsenpaper_051403.pdf.
24. Lawrence D, Fagan P, Backinger CL, Gibson JT, Hartman A. Cigarette smoking patterns among young adults aged 18-24 years in the United States. Nicotine Tob Res. 2007;9(6):687–697. [PubMed]
25. Soteriades ES, DiFranza JR. Parent’s socioeconomic status, adolescents’ disposable income, and adolescents’ smoking status in Massachusetts. Am J Public Health. 2003;93(7):1155–1160. [PMC free article] [PubMed]
26. Biener L, McCallum-Keeler G, Nyman AL. Adults’ response to Massachusetts anti-tobacco television advertisements: impact of viewer and advertisement characteristics. Tob Control. 2000;9:401–407. [PMC free article] [PubMed]
27. American National Standards Institute. U.S. Census Bureau, Geography Division, Geographic Standards and Criteria Branch; 2008. [17 Sep 2010]. Codes for the identification of the states, the District of Columbia, Puerto Rico, and the insular areas of the United States (INCITS 38:200x) www.census.gov/geo/www/ansi/statetables.html.
28. Wakefield M, Terry-McElrath YM, Emery S, et al. Impact of televised tobacco industry smoking prevention advertising on youth smoking-related beliefs, intentions and behavior. Am J Public Health. 2006;96(12):2154–2160. [PMC free article] [PubMed]
29. Durkin SJ, Biener L, Wakefield MA. Effects of different types of antismoking ads on reducing disparities in smoking cessation among socioeconomic groups. Am J Public Health. 2009;99(12):2217–2223. [PMC free article] [PubMed]
30. Farrelly MC, Davis KC, Haviland L, Messeri P, Healton CG. Evidence of a dose-response relationship between “truth” antismoking ads and youth smoking prevalence. Am J Public Health. 2005;95(3):425–431. [PMC free article] [PubMed]
31. Schar E, Gutierrez K, Murphy-Hoefer R, Nelson D. Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2006. [17 Sep 2010]. Tobacco use prevention media campaigns: lessons learned from youth in nine countries. www.cdc.gov/tobacco/youth/report/pdfs/youthMedia.pdf.
32. Green MP, McCausland KL, Xiao H, et al. A closer look at smoking among young adults: where tobacco control should focus its attention. Am J Public Health. 2007;97(8):1427–1433. [PMC free article] [PubMed]
33. Solberg LI, Asche SE, Boyle R, et al. Smoking and cessation behaviors among young adults of various educational backgrounds. Am J Public Health. 2007;97(8):1421–1426. [PMC free article] [PubMed]
34. Orzechowski W, Walker R. The tax burden on tobacco. Arlington, VA: Orzechowski and Walker; 2003.
35. ImpacTeen. Tobacco control policy and prevalence data: 1991-2008 codebook and definitions. Chicago, IL: University of Illinois at Chicago; 2009. [10 May 2011]. http://www.impacteen.org/statetobaccodata/Codebook.pdf.
36. Ling PM, Glantz SA. Why and how the tobacco industry sells cigarettes to young adults: evidence from industry documents. Am J Public Health. 2002;92(6):908–916. [PMC free article] [PubMed]
37. Niederdeppe J, Farrelly MC, Hersey JC, et al. Consequences of dramatic reductions in state tobacco control funds: Florida, 1998-2000. Tob Control. 2008;17(3):205–210. [PubMed]
38. Mullin S. Comparative performance of anti-smoking advertisements in seven low- and middle-income countries using a standard pre-testing protocol. Poverty and Lung Health: 40th World Lung Conference in Cancun; Mexico. Dec 3-7, 2009; [17 Sep 2010]. www.worldlungfoundation.org/ht/d/sp/i/6514/pid/6514.
39. Sebrie EM, Glantz SA. Tobacco industry “youth smoking prevention” programs to undermine meaningful tobacco control in Latin America. Am J Public Health. 2007;97(8):1357–1367. [PMC free article] [PubMed]
40. Durkin S, Wakefield M, Spittal M. Looking for boomerang effects: a pre-post experimental study of the effects of exposure of youth to television advertising for nicotine replacement therapy and Zyban® Addict Behav. 2006;31(12):2158–2168. [PubMed]
41. Ismailov RM, Leatherdale ST. Smoking cessation aids and strategies among former smokers in Canada. Addict Behav. 2010;35:282–285. [PubMed]
42. Lillard DR, Plassmann V, Kenkel D, Mathois A. Who kicks the habit and how they do it: socioeconomic differences across methods of quitting smoking in the USA. Soc Sci Med. 2007;64:2504–2519. [PMC free article] [PubMed]

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

  • PubMed
    PubMed
    PubMed citations for these articles

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...