Smoking and Cessation Behaviors Among Young Adults of Various Educational Backgrounds

HealthPartners Research Foundation, Minneapolis, MN 55440, USA.
American Journal of Public Health (Impact Factor: 4.55). 09/2007; 97(8):1421-6. DOI: 10.2105/AJPH.2006.098491
Source: PubMed


We sought to determine whether the educational backgrounds of young adult smokers (aged 18 to 24 years) affect their cessation attitudes or behaviors in ways that could be used to improve smoking interventions.
We surveyed 5580 members of the HealthPartners health plan and conducted a follow-up survey 12 months later of current and former smokers. Respondents were divided into subgroups according to educational level.
Higher levels of education were associated with lower smoking rates (16% among students in 4-year colleges, 31% among those in technical or 2-year colleges, and 48% among those with a high school education or less) as well as less frequent or heavy smoking. However, number of quit attempts in the past year, level of interest in quitting, and smoking relapse rates did not vary according to educational level. Seventy-three percent of those who had attempted to quit had not used some form of assistance.
Rates of smoking among young adults, especially those at low educational levels, are relatively high. However, most members of this age group are interested in quitting, regardless of educational background.

Download full-text


Available from: Raymond G Boyle, Nov 07, 2014
1 Follower
17 Reads
  • Source
    • "In NSW, the most common aid used in quit attempts is NRT (approximately 33%), followed by bupropion (13.2%), with very small proportions of smokers reporting that they used behavioural aids such as telephone helplines [4,8]. Despite the increasing availability and marketing of pharmacological and behavioural interventions, population studies consistently show that the largest proportion of smokers who permanently quit smoking do so without any form of assistance [3,6,8-12]. That is, the most common method used by people who have successfully stopped smoking remains unassisted cessation (cold turkey or reducing before quitting). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Increasing rates of smoking cessation is one of the most effective measures available to improve population health. To advance the goal of increasing successful cessation at the population level, it is imperative that we understand more about smokers' use of cessation methods, as well as the helpfulness of those methods in real-world experiences of quitting. In this survey of recent quitters, we simultaneously examined rates of use and perceived helpfulness of various cessation methods. Recent quitters (within 12 months; n = 1097) completed a telephone survey including questions relating to 13 cessation methods. Indices of use and perceived helpfulness for each method were plotted in a quadrant analysis. Socio-demographic differences were explored using bivariate and multivariate analyses. From the quadrant analysis, cold turkey, NRT and gradual reduction before quitting had high use and helpfulness; GP advice had high use and lower helpfulness. Prescribed medication and online programs had low use but high helpfulness. Remaining methods had low use and helpfulness. Younger quitters were more likely to use unassisted methods such as cold turkey; older or less educated quitters were more likely to use assisted methods such as prescribed medication or advice from a general practitioner. The majority of recent quitters quit cold turkey or cut down before quitting, and reported that these methods were helpful. Efforts to influence population smoking prevalence should attempt to provide support and motivation for smokers choosing these methods, in addition to assessing the effectiveness and accessibility of other methods for smokers who need or choose them.
    BMC Public Health 07/2011; 11(1):592. DOI:10.1186/1471-2458-11-592 · 2.26 Impact Factor
  • Source
    • "Gilpin and Pierce [13], in their more extensive study of the whole US population from 1950 to 1990, also showed an increasing incidence of smoking cessation, but also noted that the age group which had higher quit rates varied over the years, for example, middle aged smokers (35–50), had a higher quit rate that younger smokers in 1960–1965. Solberg et al. [14] studied the educational background of young adult smokers (age 18–24 years) in the US, and concluded that the level of interest in quitting, number of quit attempts, and relapse rates did not depend on educational level, although higher educational level was associated with a lower proportion of smokers. Macy et al. [15], studying a similar group, showed that 33% of long-term quitters who had quit for over 1 year, had relapsed by 5 years. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The greatest risk factor for lung cancer is smoking, the second largest factor being raised radon levels at home. Initiatives to stop smoking and reduce domestic radon levels have met with some success, but in both cases a significant proportion of those affected have not taken action. The two risk factors combine, so that those who smoke and live in a house with high radon levels are at higher risk than if exposed to only one of the two threats. There is the potential for combined public health campaigns to better target those affected. Using postal questionnaires, we collected demographic information of those in Northamptonshire, UK, a radon Affected Area, who participated in Smoking Cessation Programmes, and compared these to a recent study by our group of those who had taken action to reduce radon. The comparison suggests that these two groups are significantly different, and in some cases differ from the general population. In addition, those who continue to quit smoking at 1 year were more likely to have children under 18 at home, and live with a parent or partner compared to those who had relapsed after the previous assessment at 4 weeks. There is merit in extending Smoking Cessation Programmes to include advice on reducing the risks from radon.
    Health Policy 12/2009; DOI:10.1016/j.healthpol.2009.07.011 · 1.91 Impact Factor
  • Source
Show more