Understanding the links between education and smoking (2022)


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Social Science Research

Volume 48,

November 2014

, Pages 20-34


This study extends the theoretical and empirical literature on the relationship between education and smoking by focusing on the life course links between experiences from adolescence and health outcomes in adulthood. Differences in smoking by completed education are apparent at ages 12–18, long before that education is acquired. I use characteristics from the teenage years, including social networks, future expectations, and school experiences measured before the start of smoking regularly to predict smoking in adulthood. Results show that school policies, peers, and youths’ mortality expectations predict smoking in adulthood but that college aspirations and analytical skills do not. I also show that smoking status at age 16 predicts both completed education and adult smoking, controlling for an extensive set of covariates. Overall, educational inequalities in smoking are better understood as a bundling of advantageous statuses that develops in childhood, rather than the effect of education producing better health.


Across nearly every dimension of health, those with more education experience better outcomes, adopt healthier behaviors, and live longer. These large and robust effects of education on health endure even when income, wealth, and previous health status are controlled (Smith, 2007, Grossman and Kaestner, 1997, Preston and Elo, 1995, Williams and Collins, 1995, Kitagawa and Hauser, 1973). Using quasi-natural experiments such as policy changes and expansions in school availability or structural modeling strategies, studies show that at least part of the relationship between education and health-related outcomes can be isolated from confounding factors and considered causal (Chandola et al., 2006, Grossman, 2006, Lleras-Muney, 2005).

Differences in cigarette smoking by education represent one of the deadliest of such inequalities. Smoking is the leading behavioral cause of death in the U.S., with smoking-related illnesses accounting for nearly one out of every five deaths each year. Smoking, however, takes its toll primary on individuals with less education. In 2009, about a quarter of those with high school or less completed were current smokers compared to 20% of those with an associate degree, 11% of those with an undergraduate degree, and 5.6% of those with a graduate degree (Centers for Disease Control and Prevention CDC, 2012, CDC, 2010). Educational inequalities in smoking are an important public health concern, and a sobering example of the many advantages experienced by those with more schooling.

But is this association between education and smoking casual? If it is, and we understood which aspects of schooling caused individuals not to smoke, then educational policy could have massive health dividends. From a public health perspective this is especially promising because, while Americans are divided on issues of health infrastructure, support, and regulation, we are remarkably unified in our support of educational opportunities (Brint, 2011). Moreover, if increasing individuals’ education causes them to smoke less, then this would only add to the many social and economic benefits that are linked to educational attainment. In contrast, if the relationship between education and smoking is non-causal, then the observed gradients are instead explained by unobserved factors that predict both statuses, making the disparities more difficult to address.

Understanding the causal links between education and smoking is complicated by an important problem that is often ignored in the existing literature. At the population level, educational inequalities in smoking are produced primarily by differences in smoking initiation—whether someone ever smokes regularly—rather than quitting (Maralani, 2013). Smoking initiation, however, occurs early in life. Nearly all adult smokers started smoking regularly before age 20, often in mid-adolescence (Chassin et al., 1996, Chen and Kandel, 1995, Lanz, 2003). Among adults who smoke daily, 71% had smoked daily by age 18 (Elders et al., 1994). Thus, the mechanisms linking education and smoking in adulthood have been operating from a much earlier point in the life course. Smoking regularly begins before many of the key educational transitions, such as high school graduation, college entry, and college completion, which serve as natural breaking points in the path through school. Even advanced statistical methods that adjust for unmeasured factors do not address the basic problem that, from a life course perspective, completed education generally comes after the transition to regular smoking.

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This issue of timing underlying the relationship between education and smoking in adulthood is important not just conceptually and methodologically but also theoretically. The existing literature identifies many potential mechanisms that might link education and smoking; however, these are described as operating in adulthood (Cutler and Lleras-Muney, 2010, Link, 2008, Ross and Wu, 1995). But if the causal links between smoking and education in adulthood are in fact explained by characteristics and choices made in adolescence, then our existing theoretical framework must be reformulated to account for the links across the life course between characteristics in adolescence and smoking in adulthood. To give a concrete example, if adults with a college degree are less likely to smoke because they have better analytical or self-efficacy skills, or higher social integration, then they must have acquired these skills and resources in early adolescence, prior to modal ages of smoking initiation. The college degree may serve as a proxy for having gained these resources at an earlier point in school, but the college schooling itself did not provide the relevant resources. This is the theoretical and empirical problem that remains unexamined in the current literature.

This study extends the existing literature on the well-documented association between education and smoking on three fronts. The first is to refocus the theoretical discussion of the potential mechanisms linking education and smoking on adolescence rather than adulthood. The second is to estimate an empirical model of the relationship between education and smoking that accounts for the appropriate timing of the theoretically relevant mechanisms across the life course. The approach uses personal, family, and school-related characteristics of individuals when they were in 7–9th grade to predict whether they smoked regularly as adults. I control for a large number of potentially confounding factors such as psychosocial characteristics, family background, health characteristics, and future expectations, all measured before the transition to smoking regularly. The third contribution is to formulate a joint model of smoking and completed education in adulthood that considers the bundling of these outcomes, and how their joint distribution relates to personal, family, school, and smoking-related characteristics in adolescence, net of future expectations.

Section snippets


The question of whether education has a causal effect on smoking has been primarily debated in the economics literature. Of central concern has been the issue of whether unobserved traits such as time preferences (how much one values her wellbeing in the present versus the future) or future expectations determine both education and smoking status. Farrell and Fuchs (1982) proposed this as the primary explanation for the observed association and showed that years of school completed predicted

Potential mechanisms between schooling and smoking status

The path through formal schooling is a complex and multidimensional process that occurs over many years and domains. Educational attainment involves various curricular offerings and choices, peer contexts, adult role models, institutional policies, learning skills such as reading, writing, and analytical thinking, and making key transitions. These components inform the process of schooling, and combine with individuals’ personal, family, and school characteristics and choices to result in—or

Analytical approach

The analyses describe the relationship between education and smoking from adolescence to adulthood. First, I demonstrate the links between smoking initiation and later educational attainment by showing the age trajectories of smoking initiation by completed education. Next, I consider the relationship between the personal, family, and school-related characteristics of adolescents who are not smokers in 7–9th grade and the probability of being a current smoker in adulthood. Finally, I examine

A life course perspective on smoking and education

Educational inequalities in smoking regularly are distinctly present in adolescence, long before that education is actually acquired. Fig. 1 shows the discrete-time hazard of starting to smoke regularly from age 10 to 29, by the final level of education obtained by Add Health respondents at Wave IV (N=180,812 person years).7 The model only controls for age, gender, and race-ethnicity, and is estimated separately for each education group

Discussion and conclusion

Age patterns of starting to smoke regularly show a distinct gradient by completed education from ages 12 to 18, long before that education is acquired. The mechanisms that produce the robust correlation between education and smoking in adulthood are rooted early in the life course. Although our existing theories for the mechanisms linking education and health are conceptualized as operating in adulthood, in case of smoking in adulthood, this is not the case. The causal mechanisms must be


I’m grateful to the Robert Wood Johnson Foundation Health & Society Scholars program for its financial support and to program affiliates for their input. I owe many thanks to Gail Slap, Doug McKee, Sam Preston, Richard Breen, Olav Sorenson, Peter Bearman, Berkay Ozcan, and several anonymous reviewers for their valuable comments and advice, and to Candas Pinar, Matt Lawrence, Lucas Wiesendanger, Sam Stabler, Luke Wagner, and Alexandra Brodsky for providing superb research assistance.


References (61)

  • M.B.M. Van Den Bree et al.Predictors of smoking development in a population-based sample of adolescents: a prospective study

    J. Adolesc. Health


  • S. Tenn et al.The role of education in the production of health: an empirical analysis of smoking behavior

    J. Health Econ.


  • S.S. Smith et al.The epidemiology of tobacco use, dependence, and cessation in the United States

    Tobacco Use Cessation


  • W. SanderSchooling and smoking

    Econ. Educ. Rev.


  • F.C. PampelDiffusion, cohort change, and social patterns of smoking

    Soc. Sci. Res.


  • V. MaralaniEducational inequalities in smoking: the role of initiation versus quitting

    Soc. Sci. Med.


  • L.K. Jacobsen et al.Effects of smoking and smoking abstinence on cognition in adolescent tobacco smokers

    Biol. Psychiat.


  • F. Grimard et al.Education and smoking: were Vietnam war draft avoiders also more likely to avoid smoking?

    J. Health Econ.


  • E.A. Gilpin et al.Demographic differences in patterns in the incidence of smoking cessation: United States 1950–1990

    Ann. Epidemiol.


  • P. Farrell et al.Schooling and health: the cigarette connection

    J. Health Econ.


  • D. de WalqueDoes education affect smoking behaviors?: evidence using the vietnam draft as an instrument for college education

    J. Human Resour.


    (Video) Dave Chappelle Explained: Why Smart People Smoke

  • Rebecca de Leeuw et al.Relative risks of exposure to different smoking models on the development of nicotine dependence during adolescence: a five-wave longitudinal study

    J. Adolesc. Health


  • D.M. Cutler et al.Understanding differences in health behaviors by education

    J. Health Econ.


  • A. Case et al.The lasting consequences of childhood health and circumstance

    J. Health Econ.


  • C. Alexander et al.Peers, schools, and adolescent cigarette smoking

    J. Adolesc. Health


  • P.D. Allison

    Event History Analysis: Regression for Longitudinal Event Data


  • S. Bowles et al.

    Does school raise earnings by making people smarter?

  • N. Breslau et al.

    Smoking cessation in young adults: age at initiation of cigarette smoking and other suspected influences

    Am. J. Public Health


  • Brint, S., 2011. The Educational Lottery, November 15, 2011. <http://lareviewofbooks.org/article.php?id=277> (accessed...
  • Center for Disease Control, 1994. Surveillance for Selected Tobacco-Use Behaviors – United States, 1900–1994. Morbidity...
  • Centers for Disease Control and Prevention, 2010. Vital Signs: Current Cigarette Smoking Among Adults Aged ⩾18 Years –...
  • Centers for Disease Control and Prevention, 2012. Health Effects of Cigarette Smoking....
  • T. Chandola et al.

    Pathways between education and health: a causal modelling approach

    J. Roy. Stat. Soc.


  • Chantala, K., 2006. Guidelines for Analyzing Add Health Data....
  • Chantala, K., Kalsbeek, W.D., Andraca, E., 2004. Non-Response in Wave III of the Add Health Study....
  • Chantala, K., Tabor, J., 2010. Strategies to Perform a Design-Based Analysis Using the Add Health Data....
  • L. Chassin et al.

    The natural history of cigarette smoking from adolescence to adulthood: demographic predictors of continuity and change

    Health Psychol.


  • K. Chen et al.

    The natural history of drug use from adolescence to the mid-thirties in a general population sample

    Am. J. Public Health


  • J. Currie et al.

    Mother’s education and the intergenerational transmission of human capital: evidence from college openings

    Q. J. Econ.


  • Cutler, D.M., Glaeser, E., 2005. What Explains Differences in Smoking, Drinking, and Other Health Related Behaviors?...
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    What is the relationship between smoking and education? ›

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    Youth smoking can biologically reduce learning productivity. It can also reduce youths' expected returns to education and lower their motivation to go to school, where smoking is forbidden. Using rich household survey data from rural China, this study investigates the effect of youth smoking on educational outcomes.

    What education level is most likely to smoke? ›

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    Their effect is mediated through poor school achievement. As smoking often continues in adulthood and poor school performance typically leads to lower education, schoolwork disengagement and difficulties in adolescence constitute potential pathways to inequalities in health.

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    More than half of college students (53.4%) have smoked a cigarette, 38.1% did so in the past year, and 28.5% were current (past 30-day) cigarette smokers. Among current smokers, 32.0% smoke less than 1 cigarette per day, 43.6% smoke 1 to 10 cigarettes per day, and only 12.8% smoke 1 or more pack per day.

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    Quitting smoking is one of the most important actions people who smoke can take to reduce their risk for cardiovascular disease. Quitting smoking1: reduces the risk of disease and death from cardiovascular disease. reduces markers of inflammation and hypercoagulability.

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    Smoking behavior is complex. Learning models suggest that smoking behavior is maintained by operant conditioning, including positive and negative reinforcement, and classical conditioning, through the repeated pairing of smoking to various physical and emotional states (Wilker, 1973).

    Is smoking a positive or negative reinforcement? ›

    Smoking reinforcement motivations can be broadly classified as either negative (terminating/avoiding negative outcomes; e.g., “Cigarettes help me deal with anxiety or worry”) or positive (producing positive outcomes; e.g., “I smoke to get a sense of euphoria”) (Pomerleau, Fagerstrom et al., 2003).

    Why do people still smoke? ›

    Nicotine is highly addictive. The addictive effect of nicotine is the main reason why tobacco is widely used. Many smokers continue to smoke in order to avoid the pain of withdrawal symptoms. Smokers also adjust their behavior (inhaling more deeply, for example) to keep a certain level of nicotine in the body.

    Is smoking good for student? ›

    College students who smoke have higher rates of respiratory infections and asthma as well as a higher incidence of bacterial meningitis, especially among freshman living in dorms.” Having a serious health complication in college could prevent students from being able to do their best in school.

    Does smoking affect school grades? ›

    Students who smoke cigarettes or drink alcohol are more likely to have bad grades, according to results of the 2011 Connecticut Youth Risk Behavior Survey. The survey shows that only 8.4 percent of students who acknowledged smoking cigarettes in the past 30 days routinely received As in school.

    Why is smoking bad for college students? ›

    Tobacco use negatively impacts our physical and mental health. This is particularly true for college students, who are already facing major health challenges such as stress. Tobacco use has also been connected to poor academic performance, high-risk drinking behavior, illicit drug use and high-risk sexual behavior.

    Is smoking good for memory? ›

    Smokers' working memory ability and cognitive efficiency are significantly lower than non-smokers, so people should pay attention to smoking and memory impairment [26]. However, some researchers find that working memory and ability of the short-term smokers were improved compared to that of the non-smokers [27].

    Do smart people smoke? ›

    Background: Although previous studies indicate that people with lower intelligence quotient (IQ) scores are more likely to become cigarette smokers, IQ scores of siblings discordant for smoking and of adolescents who began smoking between ages 18-21 years have not been studied systematically.

    How does smoking affect your mental health? ›

    It's a common belief that smoking helps you relax. But smoking actually increases anxiety and tension. Smokers are also more likely than non-smokers to develop depression over time.

    Which group of college students has the highest smoking rates? ›

    2 Eight in 10 college smokers started smoking before age 18. They report smoking on twice as many days and smoke nearly four times as many cigarettes as those who began smoking at an older age. 3 White students have the highest smoking rates, followed by Hispanic, Asian, and African American students.

    Which of the following is a risk factor for smoking in adolescence? ›

    Risk factors for smoking in adolescence include lower socioeconomic status, family stress, psychological distress (especially depressive symptoms), exposure to physical or sexual abuse, and parents who smoke. Closeness to parents and participation in extracurricular activities appear to be protective [1].

    Why smoking should be banned on college campuses? ›

    The trend in tobacco and smoke-free college campuses is a step towards decreasing the use of these dangerous, habit forming products. Research also shows that there are no safe levels of secondhand smoke, therefore, preventing exposure is a key component to a healthy campus community.

    Are college students less likely to smoke? ›

    Education level is one of the strongest correlates of nonsmoking, and college students are less likely to smoke than similar-aged young adults who are not attending college.

    What is a college smoker? ›

    In our modern world, it is a device that smokes meat to make great barbecue. In olden times in was an event where people from various schools or colleges would get together and sing songs, listen to speeches and smoke.

    Why do college students use e cigarettes? ›

    In addition, 77 percent of the survey participants who had vaped within the past month reported using e-cigarettes because they are less toxic than tobacco cigarettes. “Using e-cigs because they are less toxic could appeal to users and make the product more enjoyable for the user,” Saddleson said.

    How can we prevent teenage smoking? ›

    Help your teen make a plan
    1. Know your reasons. Ask your teen to think about why he or she wants to stop smoking. ...
    2. Set a quit date. Help your teen choose a date to stop smoking.
    3. Avoid temptation. ...
    4. Be prepared for cravings. ...
    5. Consider stop-smoking products. ...
    6. Seek support.

    How does smoking affect the teenage brain? ›

    The adolescent brain is particularly sensitive to the effects of nicotine. Studies in human subjects indicate that smoking during adolescence increases the risk of developing psychiatric disorders and cognitive impairment in later life.

    What are the effects of a teenager smoking? ›

    Exposure to nicotine can have lasting effects on adolescent brain develop- ment. Cigarette smoking also causes children and teens to be short of breath and to have less stamina, both of which can affect athletic performance and other physically active pursuits. reduced lung growth; and early cardiovascular damage.

    Why do poor people smoke? ›

    More people are smoking in poorer communities. It is easy to blame people in poverty for making bad choices. But it's more complicated than that. Tobacco companies target these communities to encourage the habit, and the stresses of living in poverty and sometimes hopelessness also cause people to turn to cigarettes.

    Which of the following describes the relationship between smoking and mortality in the United States? ›

    Which of the following describes the relationship between smoking and mortality in the United States? Nearly 1 in 5 adult deaths are related to tobacco.

    Is advertising cigarettes on TV illegal? ›

    A ban on cigarette advertisements on TV and radio (specifically those stations broadcasting on FCC-regulated airwaves) went into effect in 1971. Since tobacco ads were no longer on the airwaves, there was no longer an obligation to air anti-tobacco advertising and those ads went off the air, too.

    Which age group is most targeted by tobacco advertisers? ›

    Results: The most advertised brands of cigarettes were Marlboro, according to 33.6% of adults and 41.8% of teenagers, and Camel, according to 13.7% of adults and 28.5% of teenagers--named most often by 12- to 13-year-olds (34.2%).


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