Motives of Tobacco Use Among Young Adults in the United States Air Force

Abstract

Purpose

Research has focused on cigarette use motives and have not included military personnel. The current study assessed tobacco use motives for different products, and differences within males and females and those with different racial identities given historical disparities in tobacco use.

Design

A cross-sectional survey about tobacco use was administered from October 2019 to February 2022.

Setting

Four Technical Training bases in the US.

Sample

Air Force Airmen who used tobacco (N = 3243).

Measures

Questions were about sociodemographic characteristics, tobacco use, and the Tobacco Motives Inventory (representing affect regulation, boredom, enhancement, and social motives).

Analysis

Linear regressions assessed associations between overall tobacco use and motives. Stratified analyses assessed associations between tobacco use and motives among males and females, and individuals from different racial backgrounds. Logistic regressions assessed differences in motives and use of different tobacco products between “some day” and “everyday” users.

Results

Overall, boredom (B = .09, SE = .01) and affect regulation (B = .05, SE = .00) motives were associated with higher tobacco use. Males and females and individuals from different racial backgrounds endorsed different motives, but all endorsed boredom as a motive for higher tobacco use. Individuals who used cigarettes, e-cigarettes, or smokeless tobacco “some days” endorsed higher social motives than everyday users, but everyday users endorsed different motives across products.

Conclusion

There are motives differentiating between “some day” and “everyday” users of tobacco products, which may need to be differentially targeted in intervention programs. Additionally, there are some overlapping motives (affect regulation, boredom) that may be beneficial to address with all tobacco users.

Keywords

tobacco use young adults military tobacco motives cigarettes e-cigarettes smokeless tobacco

Purpose

Smoking is one of the leading causes of preventable death in the United States (U.S.), accounting for roughly 480 000 deaths each year.¹ Smokers, on average, have a shorter lifespan compared to non-smokers by about 10 years.² Despite significant morbidity and mortality due to smoking, 18.2% of people ages 18 to 24-years-old still use tobacco products (eg, cigarettes, e-cigarettes, etc.),¹ and there have been notable increases in the use of some products such as electronic cigarettes (e-cigarettes) in the U.S. over the past decade.¹ Tobacco use for some products is also higher among sub-populations, such as military personnel,³ particularly e-cigarettes (15.3% among military personnel compared to 4.5% of the general U.S. population).^1,3 Given these disparities, understanding motives of tobacco products is important for designing and implementing effective tobacco control programs to combat the high rates of use.

Past studies with adult smokers have indicated that there are different motivations for using tobacco products, with commonly reported motives being social motives (ie, fitting in better), social norms, coping techniques, and to relieve boredom.^4-9 Other motives to engage in tobacco use include smoking to manage weight, to concentrate, for pleasure, and to avoid withdrawal symptoms.¹⁰ However, research has largely focused on cigarette use motives rather than other products. Although recent studies have started looking at motives for e-cigarette use (eg, believing that e-cigarettes are healthier and smell better than traditional cigarettes, flavors, peer use among young adults),¹¹ fewer studies have included products such as hookah, smokeless tobacco, and snus.

There is also very little existing literature on the motives of the use of tobacco products among those in the Armed Forces, which itself has a unique tobacco culture.^12,13 One study that has assessed tobacco use motives among military members only captured smoking of traditional cigarettes.¹⁴ This study found that those in the Air Force and Army reported that managing stress, anxiety, boredom, and sleep deprivation were motives for smoking during deployment.¹⁴ The authors did not examine motives among those not deployed. Additionally, one other study found that weight control was another motive for Air Force members using tobacco products.¹⁵ However, additional studies related to tobacco use motives among military personnel are needed.

It is also important to acknowledge that tobacco use has also differed across groups from different backgrounds. For example, although Black and African American individuals have lower rates of smoking than their White counterparts, they are more likely to die from smoking-related diseases.^16-18 There are also discrepancies in tobacco use by sex, with men using at higher rates.¹ Thus, it is important to consider how individuals from different sociodemographic backgrounds may be uniquely motivated to use tobacco.

The goal of the current study was to address the gap in the literature and investigate motives for tobacco use among U.S. Air Force Airmen for different tobacco products, as well as overall tobacco use to examine motives among individuals potentially using multiple products. We expected higher endorsement of different motives to use tobacco (ie, social, self-enhancement, boredom relief, affect regulation motives) to be associated with higher levels of tobacco use. Moderation of race and sex were also assessed given the historical disparities in tobacco use among individuals from diverse backgrounds and between males and females. Examining differences in tobacco use motives and tobacco use among those of different sexes and racial identities was exploratory.

Methods

Design

Participants completed paper surveys in groups of approximately 50 Airmen from October 2019 to February 2022 as part of a parent study that aimed to better understand barriers and facilitators of tobacco use for Airmen during Technical Training, where new Air Force recruits go after Basic Military Training to learn how to perform their specific job duties. A total of 19 358 Airmen were briefed across 434 briefings. Of those, 89.5% provided written informed consent to participate. At the time of the study, participants were located at one of four major Technical Training bases in the southwest U.S. All study procedures were approved by the 59th Medical Wing Institutional Review Boards.

Sample

Participants were 17 333 Air Force Airmen (called such regardless of gender identity or sex). All Airmen were aged 18 years or older.

Measures

Demographics

Participants were asked about demographic characteristics such as sex, race, ethnicity, marital status, education level, and age.

Tobacco product use and tobacco use frequency score creation

Participants were asked “In the 30 days prior to BMT [Basic Military Training], did you use the following tobacco products” and were able to select not at all, some days, or every day for different tobacco products. The listed products included cigars, cigarettes/roll your own, e-cigarettes, cigarillos/little cigars, hookah, and dip/smokeless/snus. Each tobacco product was then assigned a frequency score (0 = Not at all, 1 = Some days, 2 = Every day), which were then summed to create a total frequency score that represented the number of products used as well as the frequency of use for each product. For example, a participant using more products every day would have a higher score than someone who used a few products some days. This methodology for quantifying tobacco use was used in a previous study.¹⁹

Tobacco use motives

Participants completed the Tobacco Motives Inventory.²⁰ Participants received instructions of “Below are some things that people have said about tobacco (eg, cigarettes, e-cigarettes/vape, dip/smokeless tobacco, hookah, cigarillos); read each one and select what you think” and were presented with 15 potential reasons for use. Answer options were on a five-point Likert scale from one (not at all true) to five (very true). Answer responses are then summed to create four subscale scores: social (range: 4-20), self-enhancement (increasing self-confidence and performance; range: 4-20), boredom relief (range: 2-10), and affect regulation motives (range: 5-25).²⁰

Analysis

Participants in the final sample were those who used tobacco (frequency score greater than zero; N = 3243). We used linear regressions (with clustered standard errors [SE] at the level of military sites) with demographic variables only in the first model and then added the motives subscale scores in the second model. We conducted analyses on the stratified samples by sex and race, separately, to determine the association between tobacco use frequency scores and motives within subgroups, and compared the effects between subgroups in order to better understand if there were differences that may contribute to differential tobacco use patterns. These analyses were conducted in Stata16. There were 16 participants with outlier tobacco use frequency scores (scores of eight or higher), and they were excluded from analysis. We also conducted a sensitivity analysis to determine if results would be different if the motive subscale score variables were assessed separately given their correlations with one another. Given that results were largely similar, we opted to retain all motive subscale scores in a singular model.

Second, we conducted logistic regression analyses that assessed if individual products (ie, cigarettes, e-cigarettes, smokeless tobacco) were associated with tobacco use motives. These analyses were conducted using IBM SPSS version 25 and included all participants (including the 16 participants with outlier frequency scores excluded in the linear regressions given the logistic regressions did not include this score). We controlled for age, sex, race, ethnicity, education, and marital status in all models given that these variables are associated with tobacco use patterns.¹

Results

Participant Characteristics

Table 1 displays participant characteristics. Participants in the final sample were 69.2% White, and 11.9% Black or African American. Additionally, 78.4% were male, 88.0% were single, and 57.9% had a high school education or GED or less education. Table 1 also displays the mean scores of each tobacco motives subscale. Table 2 displays the Pearson correlation matrix for tobacco motive subscales.

Table 1.

Participant Characteristics of the Final Sample.

Characteristic	N (%)
Sex
Female	700 (21.6%)
Male	2542 (78.4%)
Race
Black/African American	386 (11.9%)
White	2244 (69.2%)
Other racial identity not listed	614 (18.9%)
Ethnicity
Hispanic	544 (17.5%)
Non-hispanic	2570 (82.5%)
Education
High school graduate/GED or less	1885 (57.9%)
Some college or more	1370 (42.1%)
Marital status
Not married	2853 (88.0%)
Married/Living as married	390 (12.0%)
	M (SD)
Age	21.10 (3.66)
Tobacco motives inventory subscale scores
Social	7.86 (3.58)
Enhancement	6.66 (3.19)
Boredom	4.76 (2.57)
Affect regulation	12.38 (5.45)

Note. SD = standard deviation.

Table 2.

Correlation Matrix of Tobacco Motives Inventory Subscales.

	Social	Enhancement	Boredom	Affect Regulation
Social	1.00	—	—	—
Enhancement	.62	1.00	—	—
Boredom	.53	.50	1.00	—
Affect regulation	.60	.73	.57	1.00

In the linear regression with just demographic characteristics, older age, being female, and identifying as Hispanic were associated with lower tobacco use frequency scores. Identifying as White or another racial identity besides White or Black were associated with higher tobacco use frequency scores compared to individuals with Black racial identities (see Table 3).

Table 3.

Linear Regression Results Assessing Association Between Tobacco Use Frequency Scores and Tobacco Motives Subscale Scores.

	Model 1	Model 2
	B (SE)	B (SE)
Age	−.02 (.00)*	.01 (.00)
Female^a	−.31 (.02)*	−.22 (.02)*
Race^b
White	.45 (.04)*	.20 (.09)
Other racial identity	.35 (.06)*	.16 (.10)
Ethnicity^c	−.20 (.03)*	−.04 (.03)
High school diploma/GED or less^d	.06 (.09)	.03 (.07)
Married^e	.09 (.03)	.01 (.04)
Tobacco motives inventory
Social	—	−.03 (.01)
Enhancement	—	.03 (.01)
Boredom	—	.09 (.01)*
Affect regulation	—	.05 (.00)*

Note. * = P < .05; SE = standard error.

^aReference group is males.

^bReference group is individuals reporting Black racial identity.

^cReference group is non-Hispanic individuals.

^dReference group was individuals with some college or higher levels of education.

^eReference group is unmarried individuals.

Tobacco Use Motives and Tobacco Use

Overall tobacco use

The average tobacco frequency score was 2.07. In the linear regression with motive subscales, boredom (B = .09, SE = .01, P < .05) and affect regulation (B = .05, SE = .00, P < .05) subscales were associated with higher tobacco use frequency scores.

In a stratified analysis, we examined associations between tobacco use frequency scores and motives subscale scores by sex. For males, there were significant associations (P < .05) between tobacco use frequency scores and enhancement (B = .04, SE = .01), boredom (B = .10, SE = .01), and affect regulation (B = .05, SE = .00) motives. The association with the social motive was non-significant (P > .05). Among females, there were significant associations between tobacco use frequency scores and boredom (B = .07, SE = .01) and affect regulation (B = .06, SE = .01) motives. The associations between social and enhancement motives were non-significant (P > .05). Males and females were significantly different in their endorsement of enhancement (P = .04) and boredom (P < .001) motives, with men reporting higher scores for both motive subscales (see Figure 1).

Figure 1.

Results from Stratified Linear Regressions of Tobacco Motives Subscale Scores between Males and Females. Notes. Figure depicts coefficients and standard errors from stratified models examining differences in tobacco motive subscale scores between males and females. P-values corresponding to statistically significant differences are displayed. Analyses controlled for age, sex, race, ethnicity, education, and marital status.

We also used stratified analyses to assess associations between tobacco use frequency scores and motives subscale scores by race. For Black individuals, social motives were associated with lower tobacco use frequency scores (B = −.05, SE = .01), while boredom (B = .07, SE = .01) and affect regulation (B = .07, SE = .01) motives were associated with higher frequency scores. Among White individuals, boredom (B = .09, SE = .01) and affect regulation (B = .05, SE = .00) were associated with higher frequency scores. Among individuals with other racial identities, boredom (B = .10, SE = .02) and affect regulation (B = .04, SE = .00) were associated with higher frequency scores. Black and White participants were not significantly different in their endorsement of different motives (P > .05). However, Black participants and those from other racial identities were significantly different in their endorsement of social (P < .001) and affect regulation (P < .001) motives, which are displayed in Figure 2. White participants and those from other racial identities were significantly different in their endorsement of affect regulation motives (P = .03), with White participants having higher scores for affect regulation (see Figure 2).

Figure 2.

Results from Stratified Linear Regressions of Tobacco Motives Subscale Scores between Racial Groups. Notes. Figure depicts coefficients and standard errors from stratified models examining differences in tobacco motive subscale scores between individuals reporting Black, White, and other racial backgrounds. P-values corresponding to statistically significant differences are displayed. Analyses controlled for age, sex, race, ethnicity, education, and marital status.

Cigarettes

Table 4 displays mean motive subscale scores for “some days” and “everyday” cigarette users. Participants who used cigarettes “some days” were more likely to endorse social motives (OR = .93, 95% confidence interval [CI]: [.87, .998], P = .04) than those who smoked “everyday.” Participants who smoked “everyday” were more likely to have higher scores on the affect regulation (OR = 1.09, 95% CI: [1.03, 1.15], P = .001) subscale than individuals who used cigarettes on “some days.” The association between the boredom and enhancement motives subscales and cigarette use were not significant (P > .05; see Table 5).

Table 4.

Mean Motive Subscale Scores Across Tobacco Products.

	Social		Enhancement		Boredom		Regulation
	Some days	Everyday	Some days	Everyday	Some days	Everyday	Some days	Everyday
	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)
Cigarettes	8.79 (3.86)	8.82 (4.09)	7.53 (3.44)	8.15 (3.94)	5.35 (2.64)	6.04 (2.73)	14.24 (5.48)	16.06 (5.42)
E-cigarettes	7.47 (3.36)	8.86 (3.84)	6.13 (2.77)	7.79 (3.59)	4.36 (2.43)	5.85 (2.57)	11.34 (4.97)	14.96 (5.31)
Smokeless	8.52 (3.75)	8.87 (3.89)	7.65 (3.37)	8.93 (3.73)	5.32 (2.48)	6.37 (2.64)	13.70 (5.27)	15.77 (5.53)
Cigars	8.50 (3.72)	9.04 (4.34)	7.15 (3.51)	8.25 (3.58)	4.92 (2.69)	5.96 (2.60)	12.85 (5.67)	14.91 (5.48)
Cigarillos	8.37 (3.76)	7.86 (4.25)	7.11 (3.40)	8.00 (3.99)	5.12 (2.64)	5.14 (2.77)	13.12 (5.53)	14.48 (6.03)
Hookah	7.33 (3.75)	7.07 (4.27)	5.99 (3.13)	6.25 (2.44)	4.29 (2.65)	5.94 (3.23)	10.84 (5.84)	13.53 (5.45)

Table 5.

Regression Results Assessing Association Between Product Use and Motives.

	OR (95% CI)	P
Cigarettes
Social	.93 (.87, .998)	.04
Enhancement	1.07 (1.01, 1.12)	.84
Boredom	1.13 (1.05, 1.21)	.001
Regulation	1.07 (1.03, 1.11)	<.0001
E-cigarettes
Social	.96 (.92, .99)	.007
Enhancement	1.01 (.93, 1.09)	.42
Boredom	1.09 (.995, 1.19)	.06
Regulation	1.09 (1.03, 1.15)	.001
Smokeless
Social	.89 (.83, .96)	.002
Enhancement	1.10 (1.01, 1.19)	.03
Boredom	1.17 (1.07, 1.29)	.001
Regulation	1.04 (.98, 1.10)	.23

Note. Models controlled for age, sex, education, race, ethnicity, and marital status.

E-cigarettes

Table 4 displays mean motive subscale scores for “some day” and “everyday” e-cigarette users, while Table 5 displays logistic regression results. Participants who used e-cigarettes “everyday” were more likely to have higher scores on the boredom (OR = 1.15, 95% CI: [1.11, 1.20], P < .0001) and affect regulation (OR = 1.11, 95% CI: [1.08, 1.14], P < .0001) subscales than participants who used e-cigarettes on “some days.” Participants who used e-cigarettes “some days” were more likely to have higher scores on the social (OR = .96, 95% CI: [.92, .99], P = .007) motive subscale than those who used e-cigarettes “everyday.”

Smokeless tobacco

Table 4 displays mean motive subscale scores for “some day” and “everyday” smokeless tobacco users, while Table 5 displays logistic regression results. Participants who used smokeless tobacco “every day” were more likely to have higher scores on the enhancement (OR = 1.10, 95% CI: [1.01, 1.19], P = .03) and boredom (OR = 1.17, 95% CI: [1.07, 1.29], P = .001) subscales than participants who used smokeless tobacco on “some days.” Participants who used smokeless tobacco “some days” were more likely to have higher scores on the social (OR = .89, 95% CI: [.83, .96], P = .002) motive subscale than participants who used smokeless tobacco “everyday.” The association between the affect regulation motives subscale and smokeless tobacco use was not significant (P > .05).

Cigars, cigarillos, and hookah

Infrequent endorsement of “everyday” use of cigars, cigarillos, and hookah precluded comparisons of tobacco use motives based on frequency of use. The means and standard deviations for use of each product are displayed in Table 4.

Discussion

The current study found that “some day” users of cigarettes, e-cigarettes, and smokeless tobacco were more likely to have higher scores related to social motives than those who used these products everyday. Everyday users of e-cigarettes endorsed affect regulation and boredom motives. Everyday cigarette users also endorsed affect regulation motives, while everyday smokeless tobacco users endorsed enhancement and boredom motives. Many of these motives for tobacco use are similar to those reported within civilian populations, including boredom, social, and coping or affect regulation motives.^4-9 These results indicate that there are motives that distinguish those who use tobacco products every day from more infrequent use, and these individuals may need different prevention strategies to reduce risk. Additionally, evaluating motives to use tobacco products may be informative to identify individuals who may be at risk for everyday use. More research is needed to determine if assessing these motives for use is an effective screening tool to predict individuals’ risk for escalating product use by endorsing similar motives for use, or if these motives change over time as use progresses.

Conversely, there was overlap in the motives that distinguished between “some days” and “everyday” users across tobacco products. Thus, an intervention that targets these motives across products may be effective in reducing use, eliminating the need for product-specific intervention tailoring. These results are in line with a recent randomized controlled trial our team conducted with young adults who recently enlisted in the US Air Force. We found that a Brief Tobacco Intervention (BTI) that targeted the five most commonly used tobacco products among Airmen (eg, cigarettes, e-cigarettes, cigarillos/little cigars, large cigars and smokeless tobacco) was effective in reducing tobacco use among 18-20 year-olds at a 3-month follow-up.²¹ More research is needed to determine if a tailored intervention or a universal tobacco control program is more effective at reducing tobacco use.

The current study also found that individuals who use more tobacco products more frequently (as represented by the frequency score) were significantly more likely to endorse higher scores on the boredom and affect regulation motive subscales. This indicates that each of these motives may be important to address in prevention and intervention programs in the future to prevent escalation of use or using more products. This is important given that dual and polytobacco use is common among military personnel who use tobacco.¹⁹ While enforced tobacco bans have been shown to be effective at reducing the number and frequency of tobacco product use over time,¹⁹ this does not address the root causes of why individuals use tobacco. By understanding the motives associated with increased tobacco use, it is possible to implement programs that provide alternative resources to meet the needs of the Airmen. For example, programs may be able to target using tobacco for affect regulation by teaching other regulation skills that are empirically supported, such as mindfulness.²² More research is needed to determine if assessing tobacco use motives and tailoring interventions to the unique needs of the individual based on their reported motives is effective at decreasing tobacco use.

There were also important considerations within the subgroup analyses assessing effects among males and females, and individuals from different racial identities. Boredom and affect regulation continued to be significantly associated with higher tobacco use frequency scores for all groups. Males also reported that enhancement motives were associated with increased tobacco use, while Black individuals also reported that social motives were associated with lower tobacco use. These results indicate that tobacco control programs should focus on addressing affect regulation and boredom motives, particularly among Airmen, since these motives are significantly associated with higher tobacco use. Further research is needed to determine if having targeted programs that address enhancement motives among males, or bolster social motives among Black individuals, provides any added intervention effects above and beyond addressing affect regulation and boredom motives in universally delivered programs.

Strengths and Limitations

The current study expanded the literature by assessing tobacco use motives among Air Force personnel when past studies have focused on civilian motives. Limitations included our inability to assess for experiences with discrimination that may influence tobacco use motives among minority individuals (eg, people of color, females). Previous studies have shown that experiences with discrimination increase likelihood of ever using e-cigarettes or using them more often.²³ Thus, future studies will need to examine the impact of discriminatory experiences on e-cigarette use motives to better understand how we can help alleviate the health burden of these experiences. Additionally, some of the subgroups had smaller sample sizes (ie, individuals who reported Native American or Alaskan Native or Native Hawaiian or Pacific islander identities) and were represented as a singular group (“other racial identity”) to preserve statistical power. These groups do not comprise a large portion of the military and thus are also underrepresented in the current study, but it will be important for future research to examine tobacco use motives among individuals from these identities to ensure they are provided with adequate and appropriate tobacco interventions and further reduce health disparities.

So What?

What is already known on this topic?

Past studies show motives for using tobacco include social motives, social norms, coping techniques, to relieve boredom, to manage weight, to concentrate, for pleasure, and to avoid withdrawal symptoms.

What does this article add?

Boredom and affect regulation motives were associated with greater tobacco use, with differences between individuals with different reported sexes or racial identities.

Individual tobacco product use motives were different based on “everyday” or “some day” use status.

What are the implications for health promotion practice or research?

Results indicate that some tobacco use motives may be similar enough to broadly target across different groups of people within the military.

More research is needed to determine if having targeted programs that address different motives within subgroups provides any added intervention effects above and beyond addressing shared product motives in universally delivered programs.

Footnotes

Author Contributions

Kinsey Pebley assisted with data analysis, wrote the original draft and reviewed and edited the manuscript. Asal Pilehvari conducted data analyses and revised the manuscript. Rebecca Krukowski assisted with writing and revisions to the draft. James Morris assisted with writing and revisions to the draft. Melissa Little secured funding, facilitated data collection, and assisted with writing and revisions to the draft.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institutes of Health (NIH/R01 DA043468).

Informed Consent

All participants provided written informed consent, and all study procedures were approved by the 59^th Medical Wing Institutional Review Boards (FWH20170129H).

Disclaimer

The opinions expressed on this document are solely those of the authors and do not represent an endorsement by or the views of the United States Air Force, the Department of Defense, the United States Government or the National Institutes of Health.

ORCID iDs

Kinsey Pebley

Rebecca A. Krukowski

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