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. 2024 Mar 20;31(3):2–12.

Tobacco and Nicotine Use Among Active Component U.S. Military Service Members: A Comparison of 2018 Estimates from the Health Related Behaviors Survey and the Periodic Health Assessment

James D Mancuso 1, Anwar E Ahmed 1, Kristen R Rossi 2
PMCID: PMC11023702  PMID: 38621256

Abstract

This study compared estimates of the prevalence of and risk factors for tobacco and nicotine use obtained from the 2018 Health Related Behaviors Survey (HRBS) and Periodic Health Assessment (PHA) survey. The HRBS and the PHA are important Department of Defense sources of data on health behavior collected from U.S. military service members. While their collection methods differ, some survey questions are similar, which provides an opportunity to compare survey estimates. Active duty service members consistently reported a much lower prevalence of all types of tobacco and nicotine use on the PHA compared to the HRBS: cigarettes (11.1% vs. 18.4%), e-cigarettes (7.3% vs. 16.2%), chewing tobacco (9.7% vs. 13.4%), any tobacco or nicotine use (25.3% vs. 37.8%), and use of 2 or more tobacco or nicotine products (5.8% vs. 17.4%). Associations between tobacco and nicotine use as well as demographic and other behavioral variables were fairly similar, including age, sex, education, race and ethnicity, rank, and alcohol use. The associations with service branch, body mass index, and sleep were inconsistent. This results of this study suggest that the PHA can provide timely information on trends in military tobacco and nicotine use over time, but much higher estimates from the confidential, voluntary HRBS reported in this study suggest that the command-directed PHA may substantially underestimate the prevalence of all types of tobacco and nicotine use.

What are the new findings?

U.S. service members consistently reported much lower prevalence of use of tobacco and nicotine on the PHA compared to the HRBS. The command-directed PHA may provide timely information on trends and risk factors for tobacco and nicotine use but substantially underestimates their use.

What is the impact on readiness and force health protection?

The use of tobacco and nicotine remains an important threat to the health and readiness of U.S. military service members. Both the HRBS and the PHA provide unique and valuable information for military policy guidance on force health protection and readiness, and they should be used in tandem.

1. BACKGROUND

The HRBS is a confidential, cross-sectional survey sponsored by the Department of Defense (DOD) for better understanding of the health behaviors of all military branches. The HRBS was most recently conducted in 2018 by the RAND Corporation (Santa Monica, CA). Despite its utility in monitoring health-related behaviors in the U.S. military over time, the HRBS is limited by a low response rate, increasing the probability of bias.1

The periodic health assessment (PHA) is an annual, standardized health assessment throughout the military services to “assess currency of individual medical readiness (IMR) requirements,” in accordance with DOD Instructions 6025.19 and 6200.06.2,3 The PHA collects some survey items similar to the HRBS, including questions on smoking and tobacco and nicotine product use.3 As the PHA must be reviewed by a health care provider, often in a direct, personal encounter,3 its data may not be reported accurately due to service member concerns about negative career consequences, or other social desirability misclassification biases.4

In 2015 the prevalence of cigarette use reported in the HRBS within the active duty population (13.8%) declined for the first time to a point lower than the general U.S. population (15.1%).5,6,7,8 In contrast, the prevalence of electronic cigarette (e-cigarette) use—also known as vaping—was higher in the U.S. military (12.4%) than in the general U.S. population (3.5%).5,9 Particularly notable was the much higher prevalence of e-cigarette use among the 17-24 year old age group in the military (22.8%) compared to the general population (5.2%). The most recently published HRBS results from 2018 indicate substantial increases in overall cigarette use (18.4%) and e-cigarette use (16.2%) compared to 2015.1

A comparison of these 2 data sources could be helpful in determining the validity and utility of both data sources both for surveillance purposes and public health guidance. Furthermore, such a comparison could obviate the need for questions in the HRBS that are already covered in the PHA, if the 2 data sources are found to provide similar information.1 This study compares estimates of prevalence and risk factors for tobacco and nicotine use among active duty U.S. service members that were self-reported in 2018 in the HRBS and the PHA.

2. METHODS

The 2018 HRBS study design included population-based stratified random sampling and non-responsive weights, which were utilized to make the analytic sample obtained from the study representative of the eligible service member population.1 Publicly available data from the 2018 HRBS, the most recent data released, were utilized to create a sampling frame of 1,357,219 active component service members (ACSMs), which was segmented into 50 strata, based on the interaction of service branch (5 categories), pay grade (5 categories), and sex. Of 199,996 invited eligible active duty service members, 17,166 responded to the survey request, with an overall weighted response rate of 9.6%.1 Sampling weights by post-stratification were used to represent the population. The low response rate of HRBS increases risk of selection bias and bias due to unobserved data. To increase representativeness, HRBS used SAS 9.4 to produce summary statistics, with confidence interval (CI) estimates computed using the Wald method.1 Missing data among respondents was addressed via imputation methods such as predictive mean matching to impute binary, ordinal, and continuous variables, and polytomous regression to impute categorical data.1

All PHAs completed (n=854,579) during calendar year 2018 by ACSMs in the Army, Navy, Air Force, Marine Corps, and Coast Guard were queried from the Defense Medical Surveillance System (DMSS).

HRBS and PHA questions assessing tobacco and nicotine use, demographic characteristics, and other exposures were reviewed. The questions that assessed tobacco and nicotine use were very similar, as shown in Table 1. Tobacco and nicotine use outcomes were assessed for 5 types of single product use within the past 30 days: cigarettes, chewing tobacco or snuff, cigars (cigars, cigarillos, or little cigars), tobacco use in a pipe or hookah, and electronic cigarettes (‘e-cigarettes’ or ‘vaping’). The use of any tobacco or nicotine product use and 2 or more forms of any single tobacco or nicotine product use were also assessed.

Table 1.

Comparison of PHA and HRBS Smoking and Tobacco Product Use Questions

Tobacco Use Classification PHA Question HRBS Question
In the past 30 days, which of the following products have you used on at least 1 day… On how many of the past 30 days did you…
Cigarettes Cigarettes? Smoke a cigarette?
Chewing tobacco Chewing tobacco, snuff or dip? Use chewing tobacco or snuff?
Cigars Cigars, cigarillos or little cigars? Smoke cigars, cigarillos, or little cigars?
Hookah/pipe Hookahs or waterpipes? Smoke tobacco in a pipe or hookah?
Pipes filled with tobacco?
E-cigarettes Electronic cigarettes, e-cigarettes, or vape pens? Use electronic cigarettes, e-cigarettes, or 'vaping'?
Any tobacco producta Cigarettes?; chewing tobacco, snuff or dip?; cigars, cigarillos or little cigars?; hookahs or waterpipes?; pipes filled with tobacco?; electronic cigarettes, e-cigarettes, or vape pens?; bidis?; snus?; dissolvable tobacco products? Smoke a cigarette?; use chewing tobacco or snuff?; smoke cigars, cigarillos, or little cigars?; smoke tobacco in a pipe or hookah? use electronic cigarettes, e-cigarettes, or 'vaping'?
Two or more tobacco products *2 or more positive responses to the cigarette, chewing tobacco, cigar, hookah / pipe, or e-cigarette classifications described above
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Abbreviations: PHA, Periodic Health Assessment; HRBS, Health Risk Behavior Survey; e-cigarette, electronic cigarette.

aPHA tobacco use categories for bidis, snus, and disosolvable tobacco products did not have a directly comparable terminology group for HRBS; thus, these items were not assessed for individual tobacco use comparison but were included for the 'any tobacco product' PHA classification.

In both surveys, demographic information (age, sex, race and ethnicity, branch of service, rank, education); body mass index (BMI); and health-related behaviors such as sleep (average hours of sleep in a 24-hour period over the last 30 days) and alcohol use (usual number of drinks containing alcohol on day[s] the service member drank in the last 30 days) were collected similarly. The assessment of sexually-transmitted infection (STI) risk defined by the HRBS included self-reporting of an STI (such as gonorrhea, syphilis, chlamydia, HPV, or genital herpes) within the past year. In contrast, the PHA defined STI risk by 1 or more of the following: a new sex partner in the past 3 months; more than 1 sex partner in the last 12 months; sexually active women less than 25 years of age; inconsistent use of latex condoms; men who have sex with men; sexual contact with person(s) with known STIs or risk of STI; exchanged money or drugs for sex; or injected drug use.

HRBS estimates were generated using sample weights to generate representative active component population estimates, as previously reported,8 while PHA data were reported using unweighted estimates. Relative frequency analyses were performed to describe the distribution of respondents’ demographics and health behaviors in both surveys. The prevalence estimates of tobacco or nicotine use classification groups were reported. The standard errors and CIs for weighted HRBS estimates were computed using the Taylor series method. Adjusted odds ratios (aORs) of tobacco or nicotine product use and 95% CIs were calculated using logistic regression, reported separately for the HRBS and PHA; sample weights were again used for HRBS (i.e., weighted logistic regression) but not PHA analysis. Statistical significance was set at 0.05 for all statistical tests. SAS statistical software 9.4 (SAS Institute, Cary, NC) was used in all analyses.

3. RESULTS

A total of 17,166 (9.6% weighted response among those invited) and 854,579 (64% of the active component population) respondents from the HRBS and the PHA, respectively, were included in the analysis (Table 2). PHA response distributions compared to the HRBS were lower for respondents who were: under age 25; of junior or enlisted ranks; in the Navy or Marine Corps; overweight; and with education levels of high school or less. Notably, compared with PHA respondents, HRBS respondents reported shorter sleep duration (5 hours or less per night: 30.3% vs. 11.3%) and more frequent alcohol use (3 or more times per week: 30.2% vs. 15.4%).

Table 2.

Demographic Characteristics of PHA and HRBS, Active Duty U.S. Military Respondents, 2018

PHA (n=854,579) HRBS (n=17,166)
95% CI
No. % Unweighted No. Weighted % Lower Upper
Sex
Male 705,867 82.60 11,813 83.31 82.62 83.99
Female 148,712 17.40 5,353 16.69 16.01 17.38
Age
17-24 302,449 35.40 3,642 37.77 36.45 39.10
25-34 353,314 41.30 6,467 39.93 38.77 41.08
35-44 164,001 19.20 5,311 18.33 17.68 18.98
45+ 34,812 4.10 1,746 3.97 3.72 4.23
Unknown 3 0.00 - 0.00
Service
Army 327,120 38.30 3,646 34.50 33.17 35.78
Navy 143,302 16.80 3,675 24.40 23.27 25.44
Marine Corps 82,705 9.70 2,569 13.90 13.14 14.66
Air Force 278,448 32.60 5,579 24.10 23.30 24.88
Coast Guard 23,004 2.70 1,697 3.20 2.98 3.36
Rank
E1-E4 331,398 38.80 4,444 42.40 41.10 43.70
E5-E6 265,521 31.10 4,585 29.80 28.76 30.84
E7-W5 101,576 11.90 3,125 11.30 10.79 11.85
O1-O3 94,865 11.10 2,469 10.10 9.61 10.66
O4+ 61,219 7.20 2,543 6.30 6.04 6.65
Rank group
Enlisted 698,495 81.70 12,154 83.50 82.89 84.15
Officer 156,084 18.30 5,012 16.50 15.85 17.11
STI risk
No 797,367 93.30 15,684 90.80 90.15 91.55
Yes 43,727 5.10 521 3.40 2.93 3.85
Unknown 13,485 1.60 961 5.80 5.21 6.32
Sleep
5 hours or less 96,925 11.30 4,563 30.30 29.11 31.45
5 to less than 7 hours 464,632 54.40 5,903 33.70 32.53 34.83
7-9 hours 283,229 33.10 6,342 33.60 32.45 34.70
9 hours or more 7,005 0.80 358 2.50 2.05 2.88
Unknown 2,788 0.30 - 0.00
Alcohol use
No response / none 267,419 31.30 4,380 29.00 27.79 30.15
1-2 455,415 53.30 8,416 40.80 39.68 41.99
3-4 112,974 13.20 3,124 19.20 18.31 20.18
5-6 15,274 1.80 864 7.10 6.38 7.84
7-9 2,412 0.30 186 1.70 1.36 2.13
10+ 1,085 0.10 196 2.10 1.64 2.56
BMI group
Under weight 5,591 0.70 109 0.70 0.41 0.94
Normal weight 263,262 30.80 5,825 34.90 33.68 36.10
Over weight 382,743 44.80 8,761 50.00 48.76 51.21
Obese 125,271 14.70 2,471 14.50 13.63 15.27
Unknown 77,712 9.10 - 0.00
Education
High school or less 504,935 59.09 7,990 64.40 63.39 65.42
Some college 126,468 14.80 2,625 12.80 12.19 13.46
Bachelors degree or more 208,288 24.37 6,301 21.60 20.87 22.35
Unknown 14,888 1.74 250 1.20 0.90 1.42
Race and ethnicity
Non-Hispanic White 490,454 57.39 10,666 57.60 56.41 58.86
Non-Hispanic Black 134,946 15.79 2,226 16.20 15.21 17.14
Hispanic 132,703 15.53 2,459 16.00 15.06 16.92
Non-Hispanic Other 96,476 11.29 1,747 9.50 8.83 10.14
Unknown 0 0.00 68 0.70 0.40 1.03
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Abbreviations: PHA, Periodic Health Assessment; HRBS, Health Risk Behavior Survey; CI, confidence interval; No., number; STI, sexually-transmitted infection; BMI, body mass index.

Service members consistently reported a much lower prevalence of all types of tobacco and nicotine use in the PHA than in the HRBS (Table 3a, 3b, 3c), for: cigarettes (11.1% vs. 18.4%), e-cigarettes (7.3% vs. 16.2%), cigars (2.8% vs. 10.0%), pipes or hookahs (1.5% vs. 5.2%), and chewing tobacco (9.7% vs. 13.4%). PHA estimates were also lower for any tobacco or nicotine use (25.3% vs. 37.8%) and use of 2 or more tobacco or nicotine products (5.8% vs. 17.4%).

Table 3a.

Prevalence of Tobacco Product Use,a HRBS Versus PHA, by Demographic Characteristics, Active Duty U.S. Military, 2018

Cigarettes E-Cigarettes Cigars
HRBS PHA HRBS PHA HRBS PHA
95% CI 95% CI 95% CI
No. %b Lower Upper No. % No. %b Lower Upper No. % No. %b Lower Upper No. %
Total 2,275 18.4 17.3 19.4 94,731 11.1 1,828 16.2 15.2 17.3 62,541 7.3 1,425 10.0 9.2 10.7 23,956 2.8
Sex
Male 1,694 19.5 18.3 20.7 84,078 11.9 1,316 17.1 15.8 18.3 55,869 7.9 1,196 11.0 10.1 11.9 22,532 3.2
Female 581 12.8 11.5 14.1 10,653 7.2 512 12.0 10.5 13.5 6,672 4.5 229 4.6 3.8 5.4 1,424 1.0
Age
17-24 680 23.1 20.9 25.4 41,471 13.7 907 27.9 25.5 30.2 37,812 12.5 364 11.7 10.0 13.4 10,633 3.5
25-34 869 17.4 16.0 18.8 35,791 10.1 597 11.3 10.2 12.5 18,994 5.4 522 9.3 8.3 10.3 8,147 2.3
35-44 609 13.2 12.0 14.3 15,719 9.6 287 6.0 5.1 6.8 5,360 3.3 408 8.3 7.4 9.2 4,098 2.5
45+ 117 6.8 5.4 8.2 1,750 5.0 37 1.9 1.2 2.6 374 1.1 131 7.5 6.0 8.9 1,078 3.1
Service
Army 469 18.0 15.9 20.2 47,810 14.6 246 13.9 11.7 16.1 23,581 7.2 262 8.6 7.1 10.1 10,353 3.2
Navy 540 20.4 18.2 22.7 14,409 10.1 350 17.4 15.1 19.7 10,327 7.2 341 12.2 10.3 14.0 3,396 2.4
Marine Corps 484 27.7 24.9 30.4 12,501 15.1 347 22.6 19.8 25.4 7,993 9.7 320 14.1 12.1 16.1 3,004 3.6
Air Force 579 11.9 10.9 13.0 18,521 6.7 706 14.9 13.7 16.0 19,264 6.9 358 7.1 6.3 7.9 6,573 2.4
Coast Guard 203 14.0 12.0 16.1 1,490 6.5 179 14.9 12.6 17.2 1,376 6.0 144 10.8 8.9 12.6 630 2.7
Rank
Enlisted 2,058 21.0 19.7 22.2 92,254 13.2 1,722 18.9 17.7 20.2 61,367 8.8 1,015 10.1 9.2 11.0 19,438 2.8
Officer 217 5.1 4.3 6.0 2,477 1.6 106 2.5 1.9 3.1 1,174 0.8 410 9.3 8.3 10.4 4,518 2.9
STI risk
No 2,054 18.3 17.2 19.4 86,441 10.8 1,605 15.7 14.6 16.8 56,138 7.0 1,293 9.9 9.1 10.7 21,601 2.7
Yes 102 23.0 17.1 28.9 7,042 16.1 103 24.8 18.5 31.2 5,575 12.7 52 11.3 6.7 15.9 2,195 5.0
Sleep
5 hours or less 857 26.4 24.1 28.6 17,556 18.1 605 21.8 19.5 24.1 9,745 10.1 439 12.6 10.9 14.4 3,943 4.1
5 to less than 7 hours 750 16.3 14.7 17.9 53,793 11.6 622 14.9 13.3 16.6 35,675 7.7 513 9.6 8.4 10.8 13,796 3.0
7-9 hours 614 13.3 11.7 14.9 22,691 8.0 549 12.4 10.9 13.9 16,643 5.9 450 8.1 7.0 9.2 6,054 2.1
9 hours or more 54 16.8 10.6 23.0 685 9.8 52 18.1 11.3 25.0 477 6.8 23 7.3 2.7 11.9 161 2.3
Alcohol usec
No response / none 389 12.3 10.4 14.1 22,580 8.4 376 13.0 11.0 15.0 19,850 7.4 158 5.0 3.7 6.3 5,069 1.9
1-2 830 13.6 12.4 14.9 44,205 9.7 629 11.2 9.9 12.5 26,784 5.9 673 9.4 8.4 10.4 12,536 2.8
3-4 636 24.1 21.8 26.4 22,136 19.6 494 20.9 18.6 23.3 12,809 11.3 384 13.5 11.6 15.3 5,166 4.6
5-6 275 40.5 35.0 46.0 4,523 29.6 209 33.0 27.6 38.5 2,418 15.8 124 14.8 11.0 18.7 883 5.8
7-9 62 36.8 26.2 47.4 827 34.3 54 35.3 24.6 45.9 454 18.8 37 23.4 13.9 33.0 182 7.5
10+ 83 51.7 40.6 62.8 460 42.4 66 43.0 31.7 54.3 226 20.8 49 28.3 18.3 38.4 120 11.1
BMI group
Under weight 16 22.8 3.2 42.3 752 13.5 11 9.8 2.7 16.8 539 9.6 8 4.3 0.6 8.0 113 2.0
Normal weight 744 19.3 17.4 21.3 30,049 11.4 702 18.3 16.3 20.3 22,790 8.7 389 8.7 7.4 10.1 6,572 2.5
Over weight 1,151 17.6 16.2 19.0 40,556 10.6 876 15.3 13.9 16.7 25,030 6.5 774 10.6 9.5 11.7 10,702 2.8
Obese 364 18.5 16.1 20.8 14,308 11.4 239 14.6 12.0 17.2 8,195 6.5 254 10.9 9.0 12.7 4,044 3.2
Education
High school or less 1,521 23.0 21.5 24.5 74,718 14.8 1,407 22.0 20.5 23.6 53,372 10.6 759 11.0 9.8 12.1 15,223 3.0
Some college 377 15.8 13.9 17.7 12,893 10.2 221 9.1 7.6 10.5 5,903 4.7 167 7.2 5.8 8.6 2,724 2.2
Bachelors degree or more 371 6.9 6.0 7.8 6,401 3.1 185 3.8 3.2 4.5 2,947 1.4 478 8.6 7.7 9.6 5,631 2.7
Race and ethnicity
Non-Hispanic White 1,436 19.8 18.4 21.3 57,752 11.8 1,120 16.9 15.5 18.4 37,279 7.6 891 10.4 9.4 11.5 13,402 2.7
Non-Hispanic Black 236 13.5 11.1 15.8 12,777 9.5 198 13.3 10.7 15.8 8,797 6.5 196 10.2 8.2 12.3 5,510 4.1
Hispanic 343 18.1 15.6 20.6 13,373 10.1 294 17.3 14.6 20.0 9,174 6.9 210 8.9 7.2 10.6 3,175 2.4
Non-Hispanic Other 252 18.2 15.1 21.3 10,829 11.2 209 14.9 12.2 17.6 7,291 7.6 122 8.8 6.7 11.0 1,869 1.9
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Abbreviations: HRBS, Health Risk Behavior Survey; PHA, Periodic Health Assessment; CI, confidence interval; No., number; STI, sexually-transmitted infection; BMI, body mass index.

aGroups are not mutually exclusive; thus, total of tobacco use types does not equal total survey respondents.

bWeighted percent.

cPHA MHA question 5b does not allow for assessment of missing data; thus, no response to this question is assumed as 0 drinks on a typical day when drinking.

Table 3b.

Prevalence of Tobacco Product Use,a HRBS Versus PHA, by Demographic Characteristics, Active Duty U.S. Military, 2018 (cont.)

Pipe/Hookah Chewing Tobacco Any Tobacco Use
HRBS PHA HRBS PHA HRBS PHA
95% CI 95% CI 95% CI
No. %b Lower Upper No. % No. %b Lower Upper No. % No. %b Lower Upper No. %
Total 721 5.2 4.6 5.7 12,515 1.5 1,531 13.4 12.4 14.3 83,044 9.7 5,160 37.8 36.6 39.0 216,265 25.3
Sex
Male 464 5.1 4.4 5.7 10,041 1.4 1,447 15.7 14.5 16.8 81,887 11.6 4,004 40.4 39.0 41.8 197,361 28.0
Female 257 5.6 4.6 6.6 2,474 1.7 84 2.0 1.5 2.6 1,157 0.8 1,156 24.8 23.0 26.6 18,904 12.7
Age
17-24 284 7.4 6.1 8.7 6,618 2.2 377 16.3 14.2 18.4 35,366 11.7 1,472 45.7 43.2 48.3 92,109 30.5
25-34 295 4.7 4.0 5.5 4,699 1.3 617 13.0 11.8 14.3 33,549 9.5 1,959 36.1 34.4 37.7 84,634 24.0
35-44 124 2.5 2.0 3.0 1,063 0.6 435 9.6 8.6 10.6 12,263 7.5 1,397 29.4 27.9 30.9 34,616 21.1
45+ 18 0.9 0.4 1.4 135 0.4 102 6.1 4.8 7.4 1,866 5.4 332 18.9 16.7 21.1 4,905 14.1
Service
Army 107 3.6 2.6 4.6 4,912 1.5 353 14.7 12.7 16.8 41,183 12.6 1,014 36.2 33.6 38.7 97,029 29.7
Navy 155 6.3 4.8 7.8 2,001 1.4 277 12.8 10.8 14.8 9,684 6.8 1,102 40.6 38.0 43.3 32,937 23.0
Marine Corps 121 6.7 5.1 8.3 1,322 1.6 393 19.8 17.3 22.3 14,246 17.2 1,030 49.0 46.1 51.9 28,133 34.0
Air Force 277 5.5 4.8 6.2 4,105 1.5 357 8.6 7.7 9.5 16,077 5.8 1,528 31.2 29.7 32.6 53,349 19.2
Coast Guard 61 4.2 2.8 5.6 175 0.8 151 11.8 9.9 13.8 1,854 8.1 486 35.4 32.6 38.2 4,817 20.9
Rank
Enlisted 594 5.6 5.0 6.3 11,316 1.6 1,220 14.4 13.3 15.5 74,515 10.7 4,276 41.2 39.7 42.6 199,753 28.6
Officer 127 2.9 2.2 3.5 1,199 0.8 311 8.3 7.3 9.4 8,529 5.5 884 20.8 19.3 22.3 16,512 10.6
STI risk
No 628 5.1 4.5 5.7 10,591 1.3 1,392 13.2 12.2 14.2 78,020 9.8 4,673 37.5 36.3 38.8 199,303 25.0
Yes 48 9.3 5.1 13.4 1,776 4.1 61 16.5 11.0 22.0 4,440 10.2 203 44.9 38.0 51.7 14,555 33.3
Sleep
5 hours or less 234 6.4 5.2 7.6 2,305 2.4 535 19.1 16.9 21.2 11,615 12.0 1,665 47.7 45.3 50.1 32,761 33.8
5 to less than 7 hours 252 5.4 4.4 6.5 7,083 1.5 547 12.9 11.3 14.5 47,563 10.2 1,796 36.5 34.5 38.6 123,215 26.5
7-9 hours 222 3.7 2.9 4.5 3,003 1.1 426 9.1 7.9 10.3 23,486 8.3 1,584 30.3 28.4 32.3 58,935 20.8
9 hours or more 13 6.7 2.0 11.3 124 1.8 23 8.9 3.9 14.0 369 5.3 115 35.0 27.0 43.1 1,336 19.1
Alcohol usec
No response / none 87 2.5 1.7 3.3 2,618 1.0 242 8.6 7.0 10.2 19,815 7.4 821 25.0 22.6 27.3 50,791 19.0
1-2 291 4.4 3.6 5.2 6,079 1.3 619 11.1 9.8 12.4 40,881 9.0 2,194 32.7 31.0 34.3 108,266 23.8
3-4 217 7.3 5.9 8.8 3,115 2.8 415 17.2 15.1 19.3 17,833 15.8 1,415 52.1 49.5 54.8 46,895 41.5
5-6 70 8.2 5.7 10.8 520 3.4 170 28.4 22.9 33.8 3,518 23.0 487 63.5 58.5 68.6 8,216 53.8
7-9 16 11.8 3.6 20.0 112 4.6 36 21.6 11.9 31.3 660 27.4 117 67.2 56.8 77.6 1,421 58.9
10+ 40 21.2 12.2 30.1 71 6.5 49 31.4 20.7 42.1 337 31.1 126 72.2 63.1 81.3 676 62.3
BMI group
Under weight 5 3.3 0.0 6.8 96 1.7 10 27.6 4.5 50.7 419 7.5 33 44.3 23.7 64.8 1,441 25.8
Normal weight 267 5.8 4.7 6.8 4,129 1.6 400 12.2 10.4 13.9 21,539 8.2 1,583 36.7 34.4 38.9 63,848 24.3
Over weight 352 4.8 4.0 5.5 5,239 1.4 864 13.7 12.5 15.0 39,046 10.2 2,732 38.0 36.4 39.7 96,196 25.1
Obese 97 5.2 3.7 6.7 1,859 1.5 257 14.5 11.9 17.1 12,711 10.1 812 39.5 36.4 42.5 33,339 26.6
Education
High school or less 445 6.3 5.4 7.1 9,189 1.8 935 15.9 14.5 17.3 60,910 12.1 3,136 44.4 42.7 46.2 160,107 31.7
Some college 90 3.3 2.5 4.2 1,452 1.1 220 11.1 9.3 12.9 9,985 7.9 799 32.7 30.4 35.1 28,613 22.6
Bachelors degree or more 176 3.1 2.6 3.7 1,738 0.8 366 7.6 6.7 8.6 11,331 5.4 1,182 22.2 20.8 23.6 25,453 12.2
Race and ethnicity
Non-Hispanic White 355 4.3 3.6 5.0 5,177 1.1 1,195 17.7 16.3 19.1 65,104 13.3 3,347 41.2 39.6 42.8 139,480 28.4
Non-Hispanic Black 151 8.0 6.1 9.9 4,032 3.0 67 4.3 2.9 5.6 3,856 2.9 557 29.4 26.3 32.5 27,546 20.4
Hispanic 132 5.9 4.3 7.4 2,032 1.5 134 8.6 6.6 10.6 7,139 5.4 708 34.8 31.7 37.9 26,711 20.1
Non-Hispanic Other 78 4.6 3.3 5.8 1,274 1.3 133 11.5 8.7 14.4 6,945 7.2 531 36.8 33.2 40.4 22,528 23.4
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Abbreviations: HRBS, Health Risk Behavior Survey; PHA, Periodic Health Assessment; CI, confidence interval; No., number; STI, sexually-transmitted infection; BMI, body mass index.

aGroups are not mutually exclusive; thus, total of tobacco use types does not equal total survey respondents.

bWeighted percent.

cPHA MHA question 5b does not allow for assessment of missing data; thus, no response to this question is assumed as 0 drinks on a typical day when drinking.

Table 3c.

Prevalence of Tobacco Product Use,a HRBS Versus PHA, by Demographic Characteristics, Active Duty U.S. Military, 2018 (cont.)

Two or More Tobacco Products
HRBS PHA
95% CI
No. %b Lower Upper No. %
Total 1,886 17.4 16.3 18.5 49,768 5.8
Sex
Male 1,511 19.1 17.8 20.3 46,610 6.6
Female 375 9.0 7.7 10.2 3,158 2.1
Age
17-24 731 25.7 23.3 28.0 29,548 9.8
25-34 716 15.1 13.7 16.5 15,563 4.4
35-44 380 8.3 7.3 9.2 4,293 2.6
45+ 59 3.6 2.5 4.6 364 1.0
Service
Army 329 16.1 13.9 18.2 24,625 7.5
Navy 417 20.2 17.8 22.6 6,205 4.3
Marine Corps 426 26.0 23.2 28.8 8,376 10.1
Air Force 535 11.9 10.8 12.9 9,878 3.5
Coast Guard 179 14.1 11.8 16.3 684 3.0
Rank
Enlisted 1,660 19.7 18.4 20.9 47,952 6.9
Officer 226 5.7 4.8 6.6 1,816 1.2
STI risk
No 1,660 16.9 15.7 18.0 44,444 5.6
Yes 108 26.2 19.8 32.7 4,801 11.0
Sleep
5 hours or less 698 24.9 22.6 27.3 9,409 9.7
5 to less than 7 hours 644 15.8 14.1 17.4 28,731 6.2
7-9 hours 507 12.3 10.7 13.8 11,267 4.0
9 hours or more 37 16.1 9.6 22.6 359 5.1
Alcohol usec
No response / none 297 11.0 9.1 12.8 14,158 5.3
1-2 663 12.6 11.3 13.9 20,145 4.4
3-4 544 23.0 20.6 25.4 11,775 10.4
5-6 241 38.1 32.6 43.6 2,782 18.2
7-9 57 41.1 30.0 52.3 573 23.8
10+ 84 58.0 47.5 68.5 335 30.9
BMI group
Under weight 15 21.0 1.5 40.5 363 6.5
Normal weight 636 18.4 16.4 20.3 16,663 6.3
Over weight 947 16.9 15.5 18.4 20,587 5.4
Obese 288 16.4 13.9 18.9 6,770 5.4
Education
High school or less 1,337 22.6 21.0 24.1 42,163 8.4
Some college 223 11.4 9.5 13.3 4,298 3.4
Bachelors degree or more 311 6.2 5.3 7.0 3,009 1.4
Race and ethnicity
Non-Hispanic White 1,190 18.8 17.3 20.2 32,382 6.6
Non-Hispanic Black 210 13.6 11.1 16.1 6,057 4.5
Hispanic 285 17.2 14.5 19.8 6,495 4.9
Non-Hispanic Other 195 16.0 12.8 19.1 4,834 5.0
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Abbreviations: HRBS, Health Risk Behavior Survey; PHA, Periodic Health Assessment; CI, confidence interval; No., number; STI, sexually-transmitted infection; BMI, body mass index.

aGroups are not mutually exclusive; thus, total of tobacco use types does not equal total survey respondents.

bWeighted percent.

cPHA MHA question 5b does not allow for assessment of missing data; thus, no response to this question is assumed as 0 drinks on a typical day when drinking.

Tobacco and nicotine use associations with demographic and behavioral variables were mostly similar between the 2 data sources. Prevalence for all types of tobacco and nicotine use was highest in youngest service members and decreased with age; of note, prevalence among 17 to 24-year-olds was much higher in the HRBS for both cigarette use (23.1% vs. 13.7%) and e-cigarette use (27.9% vs. 12.5%). Prevalence of all types of tobacco or nicotine use was higher among men than women, except for pipe and hookah use, which was higher among women. Service members who were enlisted, at increased STI risk, used more alcohol, or had lower education levels had generally a higher prevalence of all types of tobacco or nicotine use.

Non-Hispanic Black service members had the lowest prevalence of cigarette, e-cigarette, and chewing tobacco use but highest prevalence of pipe or hookah use (8.0%) and high levels of cigar use (10.2%). Hispanic service members had the highest prevalence of e-cigarette (17.3%) use and high levels of cigarette use (18.1%). These findings were generally consistent between the data sources.

Some associations between demographic and behavioral factors and tobacco or nicotine use were inconsistent between the 2 data sources. Among the services, Marines had the highest use of all types of tobacco or nicotine, but otherwise associations between services varied by type of product used and the data source. For example, prevalence of cigarette use among Navy service members (20.4%) was higher than among Army service members (18.0%) according to HRBS data, but the relationship was reversed for the PHA—estimated prevalence in the Navy (10.1%) was lower than in the Army (14.6%). Associations of hours of sleep per night were also inconsistent with some types of tobacco or nicotine use. Much of the apparent “underweight” BMI heterogeneity between the 2 data sources was likely due to the small numbers of HRBS respondents, leading to unstable estimates.

Table 4a, 4b, 4c shows the relationship between each demographic and behavioral factor and the different types of tobacco or nicotine use after adjusting for all other factors, which resulted in generally similar associations as seen in Table 3a, 3b, 3c. HRBS data demonstrated statistically significant decreases in adjusted odds of any tobacco or nicotine use among service members who were female, older, officers, with higher education levels, had more hours of sleep per night, of a race or ethnicity other than Non-Hispanic White, and with lower alcohol use levels. The findings from PHA data were similar, but with even stronger negative associations between any use and female sex, service, officer rank, and increased education level. In contrast, negative associations of slightly lower magnitude were seen in the PHA data for increasing age, while positive associations of slightly lower magnitude were seen for alcohol use.

Table 4a.

Adjusted Odds Ratios (95% CI) for Tobacco Use by Product in the Active Duty U.S. Military, HRBS Versus PHA, 2018

Cigarettes E-Cigarettes Cigars
HRBS PHA HRBS PHA HRBS PHA
Sex
Male Ref Ref Ref Ref Ref Ref
Female 0.77 (0.65, 0.90) 0.74 (0.72, 0.75) 0.72 (0.60, 0.87) 0.58 (0.56, 0.59) 0.44 (0.35, 0.55) 0.30 (0.28, 0.31)
Age
17-24 Ref Ref Ref Ref Ref Ref
25-34 0.94 (0.78, 1.14) 0.96 (0.94, 0.97) 0.40 (0.33, 0.49) 0.50 (0.49, 0.51) 0.74 (0.58, 0.93) 0.58 (0.56,0.60)
35-44 0.85 (0.69, 1.04) 1.14 (1.12, 1.17) 0.23 (0.18, 0.30) 0.37 (0.36, 0.38) 0.63 (0.49, 0.81) 0.59 (0.56, 0.62)
45+ 0.63 (0.46, 0.85) 0.88 (0.83, 0.93) 0.11 (0.07, 0.18) 0.20 (0.18, 0.23) 0.55 (0.39, 0.76) 0.70 (0.65, 0.75)
Service
Army Ref Ref Ref Ref Ref Ref
Navy 0.99 (0.79, 1.24) 0.68 (0.66, 0.69) 1.05 (0.80, 1.38) 1.16 (1.12, 1.19) 1.34 (1.01, 1.78) 0.85 (0.81, 0.89)
Marine Corps 1.19 (0.94, 1.50) 0.88 (0.86, 0.90) 0.96 (0.73, 1.26) 0.96 (0.93, 0.99) 1.32 (0.99, 1.77) 1.09 (1.04, 1.14)
Air Force 0.69 (0.57, 0.83) 0.48 (0.47, 0.49) 1.21 (0.98, 1.51) 1.15 (1.13, 1.18) 0.88 (0.69, 1.12) 0.92 (0.89, 0.95)
Coast Guard 0.69 (0.54, 0.88) 0.38 (0.36, 0.40) 1.23 (0.93, 1.63) 1.00 (0.94, 1.07) 1.31 (0.98, 1.77) 1.11 (1.01, 1.21)
Rank
Enlisted Ref Ref Ref Ref Ref Ref
Officer 0.44 (0.34, 0.56) 0.21 (0.20, 0.23) 0.28 (0.20, 0.40) 0.22 (0.20, 0.24) 1.15 (0.90, 1.46) 1.33 (1.25, 1.41)
STI risk
No Ref Ref Ref Ref Ref Ref
Yes 1.22 (0.85, 1.75) 1.46 (1.41, 1.50) 1.47 (1.01, 2.14) 1.50 (1.45, 1.55) 1.15 (0.68, 1.94) 1.64 (1.57, 1.73)
Sleep
5 hours or less 1.56 (1.30, 1.86) 1.44 (1.41, 1.47) 1.31 (1.07, 1.62) 1.32 (1.28, 1.35) 1.28 (1.02, 1.60) 1.30 (1.25, 1.35)
5 to less than 7 hours Ref Ref Ref Ref Ref Ref
7-9 hours 0.88 (0.73, 1.07) 0.79 (0.77, 0.80) 0.79 (0.63, 0.97) 0.73 (0.71, 0.74) 0.89 (0.72, 1.11) 0.76 (0.74, 0.79)
9 hours or more 0.96 (0.59, 1.57) 0.85 (0.78, 0.92) 0.89 (0.55, 1.45) 0.68 (0.62, 0.76) 0.57 (0.29, 1.12) 0.79 (0.67, 0.94)
Alcohol usea
No response / none Ref Ref Ref Ref Ref Ref
1-2 1.36 (1.10, 1.68) 1.64 (1.61, 1.67) 1.23 (0.97, 1.56) 1.26 (1.23, 1.28) 2.10 (1.54, 2.86) 1.70 (1.64, 1.76)
3-4 2.39 (1.90, 3.00) 2.68 (2.62, 2.74) 2.16 (1.68, 2.79) 1.83 (1.78, 1.87) 2.74 (1.96, 3.82) 2.40 (2.30, 2.50)
5-6 3.91 (2.88, 5.30) 3.67 (3.52, 3.83) 3.09 (2.22, 4.29) 2.11 (2.00, 2.22) 2.76 (1.79, 4.24) 2.61 (2.41, 2.83)
7-9 3.30 (1.95, 5.60) 3.93 (3.57, 4.33) 3.27 (1.76, 6.08) 2.24 (2.00, 2.52) 3.78 (1.98, 7.23) 3.01 (2.54, 3.58)
10+ 5.77 (3.46, 9.61) 5.09 (4.43, 5.84) 4.19 (2.44, 7.20) 2.08 (1.75, 2.47) 5.43 (3.00, 9.84) 4.22 (3.38, 5.26)
BMI group
Under weight 1.14 (0.48, 2.67) 1.17 (1.08, 1.27) 0.38 (0.12, 1.22) 1.08 (0.99, 1.19) 0.42 (0.13, 1.32) 0.85 (0.70, 1.03)
Normal weight Ref Ref Ref Ref Ref Ref
Over weight 0.86 (0.72, 1.03) 0.85 (0.84, 0.87) 1.00 (0.82, 1.21) 0.84 (0.82, 0.86) 1.22 (0.97, 1.52) 1.07 (1.04, 1.11)
Obese 0.86 (0.69, 1.09) 0.87 (0.85, 0.89) 0.98 (0.73, 1.31) 0.89 (0.86, 0.91) 1.21 (0.91, 1.62) 1.25 (1.20, 1.30)
Education
High school or less Ref Ref Ref Ref Ref Ref
Some college 0.82 (0.68, 0.99) 0.68 (0.66, 0.69) 0.74 (0.58, 0.93) 0.64 (0.62, 0.66) 0.82 (0.64, 1.05) 0.89 (0.85, 0.93)
Bachelors degree or more 0.51 (0.41, 0.64) 0.38 (0.37, 0.40) 0.65 (0.49, 0.85) 0.43 (0.41, 0.45) 0.98 (0.76, 1.25) 0.99 (0.93, 1.05)
Race and ethnicity
Non-Hispanic White Ref Ref Ref Ref Ref Ref
Non-Hispanic Black 0.58 (0.45, 0.74) 0.61 (0.60, 0.63) 0.71 (0.54, 0.94) 0.75 (0.73, 0.77) 1.17 (0.89, 1.56) 1.69 (1.63, 1.75)
Hispanic 0.73 (0.59, 0.90) 0.68 (0.66, 0.69) 0.81 (0.64, 1.03) 0.74 (0.72, 0.76) 0.80 (0.63, 1.03) 0.90 (0.86, 0.94)
Non-Hispanic Other 0.88 (0.69, 1.14) 0.97 (0.95, 1.00) 0.89 (0.68, 1.17) 1.02 (0.99, 1.05) 0.89 (0.65, 1.22) 0.77 (0.73, 0.82)
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Abbreviations: CI, confidence interval; HRBS, Health Risk Behavior Survey; PHA, Periodic Health Assessment; e-cigarette, electronic cigarette; STI, sexually-transmitted infection; BMI, body mass index.

aPHA MHA question 5b does not allow for assessment of missing data; thus, no response to this question is assumed as 0 drinks on a typical day when drinking.

Note: These analyses used weighted (HRBS) and unweighted (PHA) logistic regression.

Table 4b.

Adjusted Odds Ratios (95% CI) for Tobacco Use by Product in the Active Duty U.S. Military, HRBS Versus PHA, 2018 (cont.)

Pipe/Hookah Chewing Tobacco Any Tobacco Use
HRBS PHA HRBS PHA HRBS PHA
Sex
Male Ref Ref Ref Ref Ref Ref
Female 1.14 (0.88, 1.47) 1.09 (1.04, 1.14) 0.14 (0.10, 0.19) 0.09 (0.08, 0.09) 0.58 (0.51, 0.66) 0.47 (0.46, 0.48)
Age
17-24 Ref Ref Ref Ref Ref Ref
25-34 0.62 (0.47, 0.83) 0.59 (0.57, 0.62) 0.87 (0.70, 1.09) 0.92 (0.90, 0.94) 0.75 (0.64, 0.87) 0.85 (0.84, 0.86)
35-44 0.33 (0.23, 0.46) 0.30 (0.27, 0.32) 0.65 (0.51, 0.83) 0.75 (0.72, 0.77) 0.62 (0.53, 0.74) 0.84 (0.83, 0.86)
45+ 0.15 (0.08, 0.28) 0.21 (0.18, 0.26) 0.45 (0.32, 0.64) 0.59 (0.55, 0.62) 0.46 (0.37, 0.57) 0.69 (0.67, 0.72)
Service
Army Ref Ref Ref Ref Ref Ref
Navy 1.60 (1.07, 2.40) 1.02 (0.96, 1.08) 0.72 (0.55, 0.94) 0.54 (0.52, 0.55) 0.98 (0.82, 1.17) 0.73 (0.72, 0.74)
Marine Corps 1.48 (0.96, 2.27) 0.94 (0.88, 1.01) 0.93 (0.72, 1.21) 1.23 (1.20, 1.26) 1.13 (0.93, 1.36) 1.01 (0.99, 1.02)
Air Force 1.79 (1.27, 2.54) 1.25 (1.20, 1.31) 0.56 (0.45, 0.69) 0.46 (0.45, 0.47) 0.83 (0.72, 0.96) 0.63 (0.62, 0.64)
Coast Guard 1.53 (0.91, 2.57) 0.69 (0.58, 0.82) 0.69 (0.52, 0.90) 0.51 (0.48, 0.54) 0.85 (0.71, 1.03) 0.55 (0.53, 0.57)
Rank
Enlisted Ref Ref Ref Ref Ref Ref
Officer 0.88 (0.63, 1.22) 0.85 (0.77, 0.94) 1.00 (0.77, 1.30) 0.81 (0.78, 0.84) 0.64 (0.54, 0.75) 0.54 (0.52, 0.55)
STI risk
No Ref Ref Ref Ref Ref Ref
Yes 1.37 (0.75, 2.47) 2.22 (2.10, 2.35) 1.68 (1.05, 2.67) 1.05 (1.01, 1.09) 1.31 (0.95, 1.80) 1.38 (1.35, 1.42)
Sleep
5 hours or less 1.03 (0.76, 1.40) 1.41 (1.34, 1.49) 1.49 (1.21, 1.85) 1.17 (1.14, 1.20) 1.44 (1.25, 1.67) 1.32 (1.30, 1.34)
5 to less than 7 hours Ref Ref Ref Ref Ref Ref
7-9 hours 0.67 (0.49, 0.91) 0.75 (0.72, 0.79) 0.74 (0.59, 0.91) 0.87 (0.85, 0.89) 0.81 (0.71, 0.94) 0.81 (0.80, 0.82)
9 hours or more 1.07 (0.48, 2.39) 1.00 (0.83, 1.20) 0.61 (0.31, 1.22) 0.59 (0.52, 0.66) 0.95 (0.64, 1.39) 0.70 (0.65, 0.75)
Alcohol usea
No response / none Ref Ref Ref Ref Ref Ref
1-2 2.31 (1.55, 3.44) 1.90 (1.81, 2.00) 1.44 (1.11, 1.87) 1.55 (1.52, 1.58) 1.76 (1.51, 2.06) 1.83 (1.81, 1.86)
3-4 3.58 (2.36, 5.42) 3.25 (3.07, 3.44) 2.08 (1.59, 2.73) 2.16 (2.11, 2.22) 3.48 (2.92, 4.15) 3.13 (3.08, 3.19)
5-6 4.08 (2.48, 6.70) 3.49 (3.14, 3.88) 2.89 (2.01, 4.16) 2.71 (2.59, 2.84) 4.32 (3.30, 5.65) 4.08 (3.93, 4.24)
7-9 4.89 (1.87, 12.79) 4.27 (3.44, 5.31) 1.79 (0.92, 3.50) 3.05 (2.75, 3.39) 4.34 (2.55, 7.38) 4.28 (3.90, 4.70)
10+ 12.24 (6.31, 23.75) 6.01 (4.57, 7.91) 2.97 (1.73, 5.11) 3.24 (2.79, 3.78) 5.74 (3.47, 9.48) 4.57 (3.97, 5.27)
BMI group
Under weight 0.44 (0.11, 1.82) 1.06 (0.86, 1.31) 3.29 (1.19, 9.05) 0.96 (0.87, 1.07) 1.33 (0.62, 2.85) 1.09 (1.02, 1.16)
Normal weight Ref Ref Ref Ref Ref Ref
Over weight 0.92 (0.69, 1.22) 0.97 (0.93, 1.02) 1.02 (0.83, 1.26) 1.19 (1.16, 1.21) 1.04 (0.91, 1.19) 0.99 (0.97, 1.00)
Obese 0.97 (0.66, 1.42) 1.04 (0.98, 1.10) 1.22 (0.90, 1.66) 1.36 (1.33, 1.39) 1.08 (0.90, 1.30) 1.07 (1.05, 1.09)
Education
High school or less Ref Ref Ref Ref Ref Ref
Some college 0.83 (0.59, 1.17) 0.88 (0.82, 0.93) 0.79 (0.62, 1.00) 0.74 (0.72, 0.76) 0.77 (0.66, 0.90) 0.67 (0.66, 0.69)
Bachelors degree or more 1.01 (0.74, 1.38) 0.86 (0.78, 0.93) 0.56 (0.43, 0.73) 0.51 (0.49, 0.53) 0.62 (0.53, 0.73) 0.44 (0.43, 0.45)
Race and ethnicity
Non-Hispanic White Ref Ref Ref Ref Ref Ref
Non-Hispanic Black 2.34 (1.68, 3.25) 2.69 (2.57, 2.82) 0.19 (0.13, 0.28) 0.18 (0.17, 0.18) 0.56 (0.46, 0.67) 0.55 (0.54, 0.56)
Hispanic 1.25 (0.88, 1.78) 1.32 (1.25, 1.39) 0.37 (0.27, 0.49) 0.32 (0.31, 0.33) 0.60 (0.51, 0.71) 0.52 (0.51, 0.52)
Non-Hispanic Other 1.12 (0.78, 1.61) 1.26 (1.17, 1.34) 0.63 (0.47, 0.86) 0.57 (0.55, 0.58) 0.83 (0.69, 1.00) 0.79 (0.78, 0.80)
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Abbreviations: CI, confidence interval; HRBS, Health Risk Behavior Survey; PHA, Periodic Health Assessment; e-cigarette, electronic cigarette; STI, sexually-transmitted infection; BMI, body mass index.

aPHA MHA question 5b does not allow for assessment of missing data; thus, no response to this question is assumed as 0 drinks on a typical day when drinking.

Note: These analyses used weighted (HRBS) and unweighted (PHA) logistic regression.

Table 4c.

Adjusted Odds Ratios (95% CI) for Tobacco Use by Product in the Active Duty U.S. Military, HRBS Versus PHA, 2018 (cont.)

Two or More Tobacco Products
HRBS PHA
Sex
Male Ref Ref
Female 0.48 (0.39, 0.58) 0.38 (0.36, 0.39)
Age
17-24 Ref Ref
25-34 0.62 (0.51, 0.76) 0.56 (0.54, 0.57)
35-44 0.36 (0.29, 0.45) 0.39 (0.37, 0.40)
45+ 0.20 (0.14, 0.30) 0.21 (0.19, 0.24)
Service
Army Ref Ref
Navy 1.13 (0.89, 1.45) 0.66 (0.64, 0.68)
Marine Corps 1.07 (0.83, 1.38) 1.02 (0.99, 1.05)
Air Force 0.80 (0.65, 0.99) 0.57 (0.55, 0.58)
Coast Guard 0.93 (0.71, 1.22) 0.45 (0.42, 0.49)
Rank
Enlisted Ref Ref
Officer 0.64 (0.50, 0.83) 0.47 (0.44, 0.51)
STI risk
No Ref Ref
Yes 1.65 (1.13, 2.42) 1.76 (1.70, 1.83)
Sleep
5 hours or less 1.50 (1.24, 1.83) 1.50 (1.46, 1.54)
5 to less than 7 hours Ref Ref
7-9 hours 0.80 (0.65, 0.99) 0.68 (0.66, 0.69)
9 hours or more 0.88 (0.51, 1.52) 0.73 (0.65, 0.82)
Alcohol usea
No response / none Ref Ref
1-2 1.53 (1.20, 1.94) 1.36 (1.33, 1.40)
3-4 2.67 (2.08, 3.44) 2.23 (2.16, 2.29)
5-6 4.16 (3.02, 5.74) 3.05 (2.90, 3.21)
7-9 4.09 (2.31, 7.26) 3.54 (3.17, 3.94)
10+ 8.51 (5.17, 14.02) 4.14 (3.56, 4.82)
BMI group
Under weight 1.01 (0.41, 2.49) 1.02 (0.91, 1.14)
Normal weight Ref Ref
Over weight 0.98 (0.81, 1.18) 0.91 (0.89, 0.93)
Obese 0.95 (0.72, 1.24) 1.02 (0.98, 1.05)
Education
High school or less Ref Ref
Some college 0.75 (0.59, 0.95) 0.62 (0.60, 0.64)
Bachelors degree or more 0.55 (0.44, 0.70) 0.41 (0.39, 0.44)
Race and ethnicity
Non-Hispanic White Ref Ref
Non-Hispanic Black 0.68 (0.52, 0.89) 0.57 (0.56, 0.59)
Hispanic 0.73 (0.58, 0.92) 0.59 (0.57, 0.61)
Non-Hispanic Other 0.84 (0.63, 1.11) 0.83 (0.80, 0.86)
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Abbreviations: CI, confidence interval; HRBS, Health Risk Behavior Survey; PHA, Periodic Health Assessment; e-cigarette, electronic cigarette; STI, sexually-transmitted infection; BMI, body mass index.

aPHA MHA question 5b does not allow for assessment of missing data; thus, no response to this question is assumed as 0 drinks on a typical day when drinking.

Note: These analyses used weighted (HRBS) and unweighted (PHA) logistic regression.

4. DISCUSSION

Service members consistently reported much lower prevalence for all types, and combinations, of tobacco or nicotine use in the PHA compared to the HRBS. As reported elsewhere, HRBS data trends from 2015 to 2018 indicate increased prevalence of cigarette use (13.8% to 18.4%) and e-cigarette use (12.4% to 16.2%) in the U.S. military.5,1 Highest prevalence for both types of tobacco or nicotine use was among 17-24 year olds, whose cigarette use increased from 19.3% to 23.1%, and e-cigarette use rose from 22.8% to 27.9%.5 Factors demonstrating generally strong associations with most or all types of increased tobacco and nicotine use included younger age, male sex, enlisted rank, lower education level, greater amounts of alcohol use, increased STI risk, and Marine Corps service. While associations between tobacco or nicotine use and demographic and behavioral variables were mostly similar in the 2 surveys, there were some inconsistent associations with branch of service.

The HRBS-obtained prevalence of cigarette use in the U.S. military was lower in 2015 than the prevalence in the general U.S. population reported by the U.S. Centers for Disease Control and Prevention (CDC),5,9 but HRBS-obtained prevalence then increased in 2018 to exceed the U.S. population (18.4% vs. 13.7%, respectively).10 In contrast, the 2018 prevalence of cigarette use in the U.S. military estimated from PHA data (11.1%) was lower than U.S. population prevalence. As the methods employed in obtaining HRBS data were more similar to those used by the CDC for civilian data than in PHA data capture, HRBS data were preferentially utilized for the remainder of military and civilian comparisons. The prevalence of e-cigarette use also remained much higher in the U.S. military than in the U.S. population (16.2% compared to 3.2%),10 as in 2015.5 “Any smoking” was higher among service members than in the U.S. population (37.8% vs. 19.7%), as was use of 2 or more tobacco or nicotine products (17.4% vs. 3.7%).9

Among 17-24 year olds in the U.S. military there was a much higher prevalence (23.1%) of cigarette use found than in the U.S. 18-24 year old population (7.8%).10 The U.S. military also had a much higher prevalence of e-cigarette use in the 17-24 age group (27.9% vs. 7.6% in the U.S. population). Any smoking was higher among 17-24 year old service members than in the U.S. population (45.7% vs. 17.1%), as was use of 2 or more tobacco or nicotine products (25.7% vs. 4.1%). The prevalence of e-cigarette use among U.S. high school students (20.8%) in 2018 was closer to the prevalence among the youngest U.S. service members (27.9%), compared to the U.S. population of the same age (7.6%), but U.S. high school student cigarette use (8.1%) was much lower than cigarette use by youngest U.S. service members (18.4%).11

The findings in this study are generally similar to the findings of the 2015 HRBS, but the differences between the military and civilian populations are of greater magnitude.5 The 7.3% prevalence estimate of e-cigarette use among ACSMs from the PHA data in this study was similar to the 9% prevalence among active and reserve service members previously reported, also using 2018-2019 PHA data.12 Similar to this study, in 2018 the prevalence of e-cigarette use among U.S. Air Force recruits increased to 15.3%, although prevalence of cigarette and other tobacco or nicotine product use decreased in that study but increased in this study.13 This study also found similar factors associated with higher prevalence of tobacco or nicotine use, as reported in previous military studies, including younger age, male sex, enlisted rank, lower education levels, greater alcohol use, and Army or Marine Corps service.5,14 Similar associations have also been found among the general U.S. population.1010

The most important strengths of this study are the large sample sizes, multiple data sources to assess the burden of tobacco and nicotine use in the U.S. military, and the comparability between the 2 sources due to similar survey questions. The stratified random survey design of the HRBS is also a contributing strength, as it provides estimates representative of the entire U.S. military population.

This work also has several important limitations. Tobacco and nicotine use have been highly dynamic in both the U.S. general and military populations in recent years, and trends have likely changed since 2018; the release of the 2024 HRBS should allow further assessment of these trends. The weighted response rate for the 2018 HRBS was low (9.6%), which could introduce selection bias into these estimates if participating service members differed from those not participating11; this type of volunteer bias in survey literature generally leads to healthier participants, however, so tobacco and nicotine use estimates obtained through HRBS data utilization would have been expected to underestimate prevalence, not overestimate it.1515 Likewise, the 64% of service members for whom PHA data were available may have differed from those for whom data were unavailable, but because how those service members differed is unknown, the impact of this difference on prevalence estimates is unknown.

A more important source of PHA underestimation is introduction of misclassification bias if participants did not provide accurate information on their tobacco and nicotine use, which could occur due to social desirability bias, perceived stigma of tobacco and nicotine use, or other perceived negative consequences of divulging tobacco and nicotine use behaviors to other military personnel during a required military exam documented on an official form.16 The much lower prevalence for all types of tobacco and nicotine use in PHA data compared to the HRBS suggests this misclassification may lead to substantial bias and underestimates of the burden of tobacco and nicotine use.

Some misclassification may be non-differential; for example, the smaller aORs for age and alcohol use using PHA data compared to HRBS data suggest bias towards the null and possible non-differential misclassification. The more extreme aORs in the PHA data for other variables such as Naval service, sex, rank, and education compared to HRBS data do suggest possible differential misclassification, which could occur if service members who were female, officers, higher educated, and serving in the Navy were more affected by social desirability, stigma, or perceived negative consequences due to reporting tobacco and nicotine use.4 The assessment of other health behaviors such as alcohol use, drug use, and sexual practices may also be biased (particularly in the PHA) due to perceived stigma and potential for negative career consequences.17 The magnitude of this misclassification bias may be associated with the amount of stigma and potential consequences perceived for each behavior, so further research should consider and study their possible associations.

Tobacco and nicotine use remain an important threat to the health of U.S. military service members, resulting not only in short- and long-term health consequences, but also billions of dollars in health care and lost productivity costs,8 decreased fitness,18 and higher rates of premature discharge.19 Military tobacco and nicotine control policies and interventions must be guided by accurate and timely surveillance to ensure interventions are effective and responsive to dynamic societal, cultural, and economic forces that affect tobacco and nicotine use.

This study suggests that the PHA can provide timely information on trends in military tobacco and nicotine use over time, but much higher estimates in this study obtained from the confidential, voluntary HRBS also suggest that the command-directed PHA, which is part of a service member’s permanent record, may substantially underestimate the prevalence of all types of tobacco and nicotine use. Additionally, the more extreme differences between some types of service members suggest that this misclassification may be differential. This issue could potentially result in biased, and thereby invalid, associations with these demographic and behavioral risk factors, such as service members who are female, officers, higher educated, or serve in the Navy.

These differences also suggest that HRBS tobacco and nicotine use questions should not be discontinued, as some have suggested,1 since its data may be more valid than the PHA. The HRBS, on the other hand, suffers from a lack of timeliness, as it is only performed every 3 to 6 years, with its data lagging several years. Both data sources provide uniquely valuable information to guide military force health protection and readiness policy, and they should be used in tandem. Further research is needed to assess the validity of PHA data, not only for tobacco and nicotine use but other important health behaviors and outcomes as well.

AUTHOR AFFILIATIONS

Uniformed Services University Department of Preventive Medicine and Biostatistics: Dr. Mancuso and Dr. Ahmed; Armed Forces Health Surveillance Division: Ms. Rossi

DISCLAIMERS

The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, assertions, opinions, nor policies of the Uniformed Services University of the Health Sciences, the Defense Health Agency, or the Department of Defense.

ACKNOWLEDGMENTS

The authors would like to thank Ms. Jessica H. Murray, MPH for the PHA data analysis presented in this report.

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