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Occupational Medicine Advance Access originally published online on June 22, 2006
Occupational Medicine 2006 56(5):353-356; doi:10.1093/occmed/kql057
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© The Author 2006. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

SHORT REPORT

Physical fitness, absenteeism and workers' compensation in smoking and non-smoking police officers

Robert W. Boyce1, Michael A. Perko2, Glenn R. Jones3, Ann H. Hiatt4 and Edward L. Boone5

1 University of North Carolina at Wilmington, Department of Health and Applied Human Sciences, 601 South College Road, Wilmington, NC 28403, USA
2 University of Alabama, Department of Health Sciences, 209 East Annex, Tuscaloosa, AL 35487, USA
3 President, Work Physiology Associate Inc., 7111 Forger Drive, Charlotte, NC 28270, USA
4 117 Coventry Hills Lane, Troutman, NC 28166, USA
5 University of North Carolina at Wilmington, Department of Math and Statistics, 601 South College Road, Wilmington, NC 28403, USA

Correspondence to: R. W. Boyce, University of North Carolina at Wilmington, Department of Health and Applied Human Sciences, 601 South College Road, Wilmington, NC 28403, USA. Tel: +1 910 962 7824; fax: +1 901 962 7073; e-mail: boycer{at}uncw.edu


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Supplementary data
 Conflicts of interest
 References
 
Background Employers seek to minimize business costs by creating conditions of employment. Relying on the presumably negative effects of smoking on variables such as workers' compensation claims, absenteeism and physical fitness scores, they seek a rational basis for requirements that employees refrain from smoking. No research has been found on police officer smoking rates relating to physical fitness, and the resulting economic variables of workers' compensation claims and absenteeism rates.

Aims To compare police officer non-smoker and smoker physical fitness, absenteeism rates and workers' compensation claims.

Methods The sample included 514 officers of a metropolitan police department. A physical fitness test was administered. Smoking status, yearly absenteeism rates and workers' compensation claims were collected.

Results Male smokers were significantly older than non-smokers. An analysis of covariance controlling for sex and age indicated that smokers had significantly (P ≤ 0.05) lower fitness scores in sit and reach flexibility, sit-ups endurance, bench press strength and bicycle ergometer cardiovascular endurance. When neither age nor sex was controlled in males, a similar trend continued. However, in females only the sit and reach and sit-up tests demonstrated statistically significant differences. Fat percentage, step-test scores, absenteeism rates and workers' compensation claims were not statistically different.

Conclusion These data do not provide a rational basis for the requirement that officers refrain from smoking when considering body fat and the economic savings of lower absenteeism rates and workers' compensation. To some extent, smoking policies can be justified by officers' physical fitness but there are age, gender and test protocol considerations.

Keywords      Absenteeism; conditions of employment; cost; insurance; physical fitness; police; rational basis; smoking; workers' compensation


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Supplementary data
 Conflicts of interest
 References
 
Employers seek to minimize business costs by creating conditions of employment [1,2]. Relying on the presumably negative effects of smoking [3–7] on variables such as workers' compensation claims, absenteeism and physical fitness scores, they seek a rational basis for requirements that employees refrain from smoking. We found no research conducted on police officer smoking status in relation to physical fitness abilities, worker compensation claims and absenteeism rates that would provide a rational basis for department policies concerning smoking.

The purpose of this study was to compare non-smokers and smokers in a metropolitan police department. Specifically, the research questions were (i) do police officers who smoke have different descriptive characteristics (sex, age, rank and race) from those who do not smoke? (ii) Do police officers who smoke have different physical fitness scores from those who do not smoke? (iii) Do police officers who smoke have different absenteeism rates and workers' compensation claims from those who do not smoke?


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Supplementary data
 Conflicts of interest
 References
 
The sample included 514 police officers who were required to take an annual battery of five physical fitness tests [8]. Physical fitness data used in the present study were obtained from May 1988 to July 1989. The absenteeism rate was determined by the payroll sick days taken for the calendar year. Sick days accrued at the rate of one per month. The workers' compensation claims were dollars paid to the employee for accidents that occurred to the employee during working hours.

The physical fitness battery included five measurements: percent body fat, sit and reach flexibility, sit-ups, one repetition maximum bench press and the Queens College step test for those 34 years and younger and a YMCA bicycle ergometer evaluation for those 35 years and older. The unit of measure of the step test was recovery heart rate, and predicted maximum oxygen consumption for bicycle ergometer [8].

The Statistical Program for Social Science was used to analyze the data. A Chi-square and analysis procedures were used to test whether non-smokers and smokers were different on the descriptive characteristics of sex, rank, race and age. Also, one-way analysis of variance procedures were computed to determine if there were differences in age and gender among officers categorized by non-smokers and smokers. Then, a series of analysis of covariance (ANCOVA) procedures controlled for age were computed for males and females separately to determine if non-smokers and smokers differed in physical fitness scores, absenteeism rates and workers' compensation claims. Similarly, a series of ANCOVA procedures was computed comparing non-smokers and smokers controlling for sex and age.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Supplementary data
 Conflicts of interest
 References
 
Overall, 405 (79%) officers were non-smokers and 108 (21%) were smokers, 78 white and 20 black, mean age was 34.8 years. In comparing non-smokers and smokers, there were no significant differences in regard to sex, rank and race. Male officers who smoked were significantly older than non-smokers, 34.8 versus 38.7 years (n = 435), P < 0.001. However, no significant age differences were found between non-smoker and smoker females, 30.3 versus 30.4, respectively (n = 78), P = 0.95 (see Table 1).


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  		Table 1. Sex, rank, race and age comparisons of non-smoker and smoker officers

 
ANCOVA procedures controlling for sex and age resulted in smokers having significantly lower scores in sit and reach flexibility (F = 6.49, n = 504, P = 0.01), sit-ups endurance (F = 19.15, n = 503, P = 0.001), bench press strength (F = 4.61, n = 498, P = 0.03) and bike cardiovascular endurance (F = 10.27, n = 218, P = 0.002). No significant differences were found in fat percentage (F = 0.009, n = 507, P = 0.92), step-test cardiovascular endurance (F = 1.08, n = 267, P = 0.18), absenteeism rate, (F = 0.43, n = 512, P = 0.52) and workers' compensation claims (F = 1.075, n = 512, P = 0.30). Similar trends were found when analyzing men controlling for their age (see Table 2). When neither age nor sex was controlled in males, the same trend continued; however, sit and reach and bench press were only marginally significant (P < 0.06).


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  		Table 2. Physical fitness, absenteeism and workers' compensation comparisons of non-smoker and smoker officers

 
There were no statistically significant differences for females in three of the five physical fitness parameters. Only the sit and reach and sit-up tests demonstrated statistically significant differences (see Table 2).

There was no significant difference in body fat for males and females when controlling for age and sex together and when there was no age control (see Table 2). However, when controlling for age only, significant differences were observed. The percent fat for male smokers was only 1–2% more than the non-smokers, and the female smokers had ~1% less fat than the non-smokers.

The economic variables of absenteeism rates, and workers' compensation claims for males or females when controlling for age showed no significant differences between non-smokers and smokers (P ≤ 0.05). It is worth mentioning that when controlling for age in men only, absenteeism rates' P value was close to the P ≤ 0.05 level of significance (P = 0.06).


   Discussion
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 Abstract
 Introduction
 Methods
 Results
 Discussion
Supplementary data
 Conflicts of interest
 References
 
Our study found differences in body fat and most physical fitness parameters between smokers and non-smokers. This is consistent with the literature which overwhelmingly supports this finding [5]. There were no significant differences in absenteeism or worker's compensation, which is consistent with some previous work [9,10]. We found that male smokers were significantly older than male non-smokers. However, all other studied descriptive characteristics showed no significant differences.

A rational basis was not established for smoking policies affecting conditions of employment of police officers based upon body fat, obesity and the economic savings of lower absenteeism rates and workers' compensation claims. To some extent, a rational basis can be established for smoking policies based upon physical fitness of these police officers. However, there are age, gender and test protocol considerations, which may complicate the justification for these policies.


   Supplementary data
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Supplementary data
Conflicts of interest
 References
 
Please note that a longer version of this article is available as supplementary data at Occupational Medicine Online.


   Conflicts of interest
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Supplementary data
 Conflicts of interest
References
 
None declared.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Supplementary data
 Conflicts of interest
 References
 

  1. Wysocki B Jr. Companies get tough with smokers, obese to trim costs. Wall Street J (serial online) 2004;Oct 12; Sect.B;1. ProQuest® (cited 2005 Aug 26).

  2. Janofsky M. Ban on employees who smoke faces challenges of bias. New York Times (serial online) 1994;Apr 28; Sect.A;1(col.1). LexisNexisTM Academic–Document (cited 2005 Aug 26).

  3. U.S. Department of Health and Human Services. Smoking and Health: A Report of the Surgeon General. Washington, DC: Superintendent of Documents, 1986.

  4. Kaufman KR, Brodine S, Shaffer R. Military training-related injuries surveillance, research and prevention. Am J Prev Med 2000;18:54–63.[ISI][Medline]

  5. Lee CD, Blair SN. Cardiovascular fitness and smoking-related and total cancer mortality in men. Med Sci Sports Exerc 2002;34:735–739.

  6. Robbins AS, Chao MS, Fonseca VP et al. Predictors of low fitness in a cohort of active-duty U.S. Air Force members. Am J Prev Med 2001;20:90–96.[ISI][Medline]

  7. Ault RW, Ekelund RB Jr, Jackson JD et al. Smoking and absenteeism. Appl Econ 1991;23:743–754.

  8. Jones GR, Boyce RW. Charlotte Police Department Physical Fitness Program Stand Operating Procedures. Charlotte, NC: Charlotte Police Department, 1990.

  9. Parks KR. Smoking as a moderator of the relationship between affective state and absence from work. J Appl Physiol 1983;68:689–708.

  10. Resenfeld O, Tenebaum G, Ruskins ST. Behavioral modifications following a physical activity program in the Israeli pharmaceutical industry. Aust J Sci Med Sport 1990;22:93–96.


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