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Tobacco cessation behaviors among a sample of US Navy personnel

Published online by Cambridge University Press:  26 December 2018

Matthew T. Hall ,
Ryan P. Austin ,
Tai A. Do  and
Alec G. Richardson
Matthew T. Hall*
Affiliation:
Department of Aviation Medicine, Naval Hospital Jacksonville, 2080 Child Street, Jacksonville, FL 32214, USA
Ryan P. Austin
Affiliation:
Department of Aviation Medicine, Naval Hospital Jacksonville, 2080 Child Street, Jacksonville, FL 32214, USA
Tai A. Do
Affiliation:
Directorate of Public Health Services, U.S. Naval Hospital Okinawa, Okinawa, PSC 482, FPO AP 96362, Japan
Alec G. Richardson
Affiliation:
Navy Entomology Center of Excellence, Naval Air Station Jacksonville, PO Box 43, Jacksonville, FL 32212, USA
*
Author for correspondence: Matthew T. Hall, E-mail: matthew.hall2@unchealth.unc.edu
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Abstract

Introduction

The US Navy utilizes numerous resources to encourage smoking cessation. Despite these efforts, cigarette smoking among service members remains high. Electronic cigarettes (EC) have provided an additional cessation resource. Little is known regarding the utilization efficacy of these cessation resources in the US Navy.

Aims

This study sought to explore the utilization and efficacy of ECs and other smoking cessation resources.

Methods

An anonymous cross-sectional survey was conducted at a military clinic from 2015 to 2016. Participants were active duty in the US Navy and reported demographics, smoking behaviors, and utilization of cessation resources.

Results

Of the 977 participants in the study, 14.9% were current and 39.4% were former smokers. Most current smokers (83.6%) previously attempted cessation, smoked an average of 2–5 cigarettes per day (34.7%), and smoked every day of the month (26.4%). The number of daily cigarettes smoked and number of days cigarettes were smoked per month was not significantly different between cigarette-only smokers and EC dual users (p = 0.92, p = 0.75, respectively). Resources used by current and former smokers include: ‘cold turkey’ (44.6%, 57.1%, respectively), ECs (22.3%, 24.7%), nicotine patch (8.3%, 1.3%), medicine (6.6%, 3.9%), nicotine gum (5.8%, 10.4%), and quit programs (2.5%, 2.6).

Conclusion

Current and former cigarette smokers utilized similar resources to quit smoking. Electronic cigarettes are being used for cessation but do not significantly reduce the number of cigarettes smoked on a daily or monthly basis. Future studies may benefit from exploring the use of cessation resources and ECs within the military as a whole.

Keywords

cessationquitcigaretteselectronic cigarettesmilitary
Type
Original Articles
Information
Journal of Smoking Cessation , Volume 14 , Issue 3 , September 2019 , pp. 161 - 167
Creative Commons
This is a work of the U.S. Government and is not subject to copyright protection in the United States.
Copyright
Copyright © The Author(s) 2018

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References

Amato, M. S., Boyle, R. G., & Levy, D. (2016). How to define e-cigarette prevalence? Finding clues in the use frequency distribution. Tobacco Control, 25(e1), e24–29. doi:10.1136/tobaccocontrol-2015-052236Google Scholar
Ames, G. M., Cunradi, C. B., & Moore, R. S. (2002). Alcohol, tobacco, and drug use among young adults prior to entering the military. Prevention Science, 3(2), 135–144.Google Scholar
Bartlett, M. S. (1937a). Properties of sufficiency and statistical tests. Proceedings of the Royal Statistical Society Series A, 160(901), 268–282.Google Scholar
Bartlett, M. S. (1937b). Some examples of statistical methods of research in agriculture and applied biology. Journal of Royal Statistical Society, 4(2), 137–170.Google Scholar
Bray, R. M., & Hourani, L. L. (2007). Substance use trends among active duty military personnel: Findings from the United States department of defense health related behavior surveys, 1980-2005. Addiction, 102(7), 1092–1101.Google Scholar
Centers for Disease Control and, Prevention, Brener, N. D., Kann, L., Shanklin, S., Kinchen, S., Eaton, D. K., Hawkins, J. et al. (2013). Methodology of the youth risk behavior surveillance system--2013. MMWR. Recommendations and Reports, 62(RR-1), 1–20.Google Scholar
Collee, A., Clarys, P., Geeraerts, P., Dugauquier, C., & Mullie, P. (2014). Body mass index, physical activity, and smoking in relation to military readiness. Military Medicine, 179(8), 901–905.Google Scholar
Cypel, Y. S., Hamlett-Berry, K., Barth, S. K., Christofferson, D. E., Davey, V. J., Eber, S. et al. (2016). Cigarette smoking and sociodemographic, military, and health characteristics of operation enduring freedom and operation Iraqi freedom veterans: 2009-2011 national health study for a New generation of US veterans. Public Health Reports, 131(5), 714–727.Google Scholar
Defense Medical Surveillance System (DMSS). Health.mil. http://www.health.mil/Military-Health-Topics/Health-Readiness/Armed-Forces-Health-Surveillance-Branch/Data-Management-and-Technical-Support/Defense-Medical-Surveillance-System. Updated Oct 2014. Accessed 26 January 2017.Google Scholar
Duncan, D. B. (1951). A significance test for difference between ranked treatments in an analysis of variance. Virginia Journal of Science, 2(3), 171–189.Google Scholar
Duncan, D. B. (1955). Multiple range and multiple F tests. Biometrics, 11(1), 1–42.Google Scholar
Haddock, C. K., Klesges, R. C., Talcott, G. W., Lando, H., & Stein, R. J. (1998). Smoking prevalence and risk factors for smoking in a population of United States Air Force basic trainees. Tobacco Control, 7(3), 232–235.Google Scholar
Haddock, C. K., Pyle, S. A., Poston, W. S., Bray, R. M., & Stein, R. J. (2007). Smoking and body weight as markers of fitness for duty among U.S. military personnel. Military Medicine, 172(5), 527–532.Google Scholar
Institute of Medicine (US) Committee on Smoking Cessation in Military and Veteran Populations; Bondurant, S., & Wedge, R. (Eds). (2009). Combating tobacco Use in military and veteran populations (Vol. 2). Washington, DC: National Academies Press.Google Scholar
Kalkhoran, S., & Glantz, S. A. (2016). E-cigarettes and smoking cessation in real-world and clinical settings: A systematic review and meta-analysis. The Lancet Respiratory Medicine, 4(2), 116–128.Google Scholar
Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion analysis of variance. Journal of the American Statistical Association, 47(260), 583–621.Google Scholar
MacIntyre, N. R., Mitchell, R. E., Oberman, A., Harlan, W. R., Graybiel, A. and Johnson, E. (1978). Longevity in military pilots: 37-year followup of the Navy's “1000 aviators”. Aviation, Space and Environmental Medicine, 49(9), 1120–1122.Google Scholar
Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two variables is stochastically larger than the other. Annals of Mathematical Statistics, 18, 50–60.Google Scholar
Meadows, S. O., Engel, C. C., Collins, R. L., Beckman, R., Cefalu, M., Hawes-Dawson, J. et al. (2018). 2015 department of Defense Health Related Behaviors Survey (HRBS). Retrieved from Santa Monica, California.Google Scholar
Navy, D. o. t. (2012). Bumed instruction 6200.12a. (BUMED-M3). Falls Church, VA: Department of the Navy.Google Scholar
Newman, D. (1939). The distribution of range in samples from a normal population, expressed in terms of an independent estimate of standard deviation. Biometrika, 31(1–2), 20–30.Google Scholar
Scheffe, H. (1953). A method of judging all contrasts in the analysis of variance. Biometricka, 40(1–2), 87–110.Google Scholar
Scheffe, H. (1959). The analysis of variance. New York: Wiley.Google Scholar
Smirnov, N. V. (1939). On the estimation of the discrepancy between empirical curves of distribution for two independent samples. Moscow University Mathematics Bulletin, 2(2), 3–16.Google Scholar
Smith, E. A., Jahnke, S. A., Poston, W. S., Williams, L. N., Haddock, C. K., Schroeder, S. A., & Malone, R. E. (2014). Is it time for a tobacco-free military? New England Journal of Medicine, 371(7), 589–591.Google Scholar
Smith, E. A., Poston, W. S., Haddock, C. K., & Malone, R. E. (2016). Installation Tobacco Control Programs in the U.S. Military. Military Medicine, 181(6), 596–601.Google Scholar
Tukey, J. W. (1949). One degree of freedom for non-additivity. Biometrics, 5(3), 232–242.Google Scholar
Tukey, J. W. (1953). The problem of multiple comparisons. Princeton, NJ: Department of Statistics, Princeton University.Google Scholar
Walley, S. C., Jenssen, B. P., & Section on Tobacco, C. (2015). Electronic nicotine delivery systems. Pediatrics, 136(5), 1018–1026.Google Scholar
York, E., Mitchell, R. E., & Graybiel, A. (1986). Cardiovascular epidemiology, exercise, and health: 40-year followup of the U.S. Navy's “1000 aviators”. Aviation, Space and Environmental Medicine, 57(6), 597–599.Google Scholar
Zar, J. H. (1999). Biostatistical analysis. Upper Saddle River, NJ: Prentice Hall.Google Scholar