Socioeconomic, Health, and Dietary Determinants of Physical Activity in a Military Occupational Environment

MILITARY MEDICINE, 178, 5:495, 2013 Socioeconomic, Health, and Dietary Determinants of Physical Activity in a Military Occupational Environment Patrick Mullie, PhD* ; Audrey Collee, PhD* ; Peter Clarys, PhD* ABSTRACT Background: Health-related advantages of physical activity are well documented. The aim was to detect socioeconomic, health, and dietary determinants of physical activity. Methods: A cross-sectional design was used. Mailed questionnaires were sent to 5,000 Belgian military men. Dietary patterns were determined using the Mediterranean Diet Score (MDS). For physical activity, the validated International Physical Activity Questionnaire was used. Results: Participation rate was 37% (n = 1,852). Mean total metabolic equivalent task (MET-total) varied between 6,224 MET-minutes/week for the age category 20 to 29 years to 4,578 MET-minutes/week for the age category 50 to 59 years. About 58% of the participants had a body mass index (BMI) above 25.0 kg/m 2.Logistic regression indicated a strong relation between MDS and MET-vigorous. A BMI increase of 1 kg/m 2 was associated with an odds ratio of 0.95 (95% confidence interval: 0.93 0.98), meaning that each increase of 1 kg/m 2 decreased MET-vigorous with 5%. Each additional life year decreased MET-vigorous with 3%. Conclusions: The high level of physical activity and the physical activity promoting and facilitating occupational environment seem to be insufficient to prevent adiposity. Vigorous physical activity was most discriminative and negatively related with increasing BMI, age, and smoking and positively related with MDS. INTRODUCTION Health-related advantages of physical activity are well documented. In a meta-analysis of prospective cohort studies, Woodcock et al 1 found that 30 minutes daily of moderateintensity activity on 5 days a week compared with no activity was associated with a reduction in mortality of 19%, whereas 7 hours/week of moderate activity reduced the mortality by 24%. Other meta-analyses indicate an improvement of cognitive capacities associated with physical activity 2 and a beneficial weight loss effect. 3 Moreover, poor physical conditions and excess of adiposity are an important burden of direct (increased medical care) and indirect (lost workdays) costs for an occupational structure. 4 The workplace is recognized as an important setting for health promotion with structures to reach participants and with the availability of a natural or social network. 5 In the military environment, fitness and body composition standards are used to select individuals responding to the physical readiness and appropriateness associated with military services. 6 Members of an army are expected to achieve and maintain levels of physical fitness that will enable them to perform their normal duties with maximum efficiency; keep them prepared to meet any emergency that may require them to perform effectively under adverse conditions for a prolonged period of time; and to contribute to the maintenance of their health. 7 Hence, besides specific training, army men are encouraged to engage daily in sports or physical activity during the working day. Most military centers have *Faculty of Physical Education and Physiotherapy, Laboratory for Human Biometrics and Biomechanics, Vrije Universiteit Brussel Pleinstraat 2, B-1050 Brussels, Belgium. Unit of Epidemiology and Biostatistics, Queen Astrid Military Hospital, Bruynstraat 1, B-1120 Brussels, Belgium. doi: 10.7205/MILMED-D-12-00442 specific military training and sports facilities. Besides the amount of physical activity, the quality or intensity of the activity is equally related with possible health benefits. 8 Few studies have been conducted concerning the relation between physical activity and a general dietary pattern. Dietary pattern analysis, based on the concept that foods eaten combined are as important as a reductive methodology characterized by a single food or nutrient analysis, has emerged more than a decade ago as an alternative approach to study the relation between nutrition and disease. 9 The Mediterranean Diet Score (MDS), as a proxy for the Mediterranean dietary pattern, has been associated with reduction in mortality. 10 This reduction has been reported in different populations and by different research teams. 10 The first aim of the present work was to investigate if a physical activity promoting environment is associated with higher levels of physical activity and a lower prevalence of adiposity. A second aim was to determine the relation between physical activity, dietary pattern, socioeconomic position (educational level), and some health indicators (smoking and BMI). METHODS In February 2007, air and ground components of the Belgian army totaled 33,053 men. After stratification for military rank and age, 5,000 men were selected representative for the total army structure. Stratification in Belgian army consists of officers (from lieutenant to general); noncommissioned officers (from sergeant to warrant officer); and soldiers (corporal and other personnel with no command authority). The selection consisted of 598 officers; 2,103 noncommissioned officers and 2,299 soldiers. Physical activity was estimated using a validated Dutch and French translation of the International Physical Activity MILITARY MEDICINE, Vol. 178, May 2013 495

Questionnaire (IPAQ) 11 sent to the participants. The IPAQ short form is an instrument designed for physical activity surveillance among adults at population level. IPAQ registers physical activity across different domains as leisuretime activity, domestic and gardening activity, and work- and transport-related activity. Weighting each type of activity by its energy requirements defined in metabolic equivalent task (MET) yields a score in MET-minutes for three levels of activity: walking, moderate activity, and vigorous activity. Total MET minutes for an individual is the sum of the three scores for each level. Weekly minutes of walking, moderateintensity and vigorous-intensity activity were calculated separately by multiplying the number of days a week by the duration on an average day. Reported minutes per week in each category were weighted by a metabolic equivalent. The summary indicator was used to categorize a population into 3 levels of physical activity: low, moderate, and high levels of physical activity. These categories were based on standard scoring criteria (http://www.ipaq.ki.se): Low: meets neither moderate nor high criteria. Moderate: Meets any of the following three criteria: (1) 3 days of vigorous activity of at least 20 minutes/ day; (2) 5 days of moderate-intensity activity or walking of >30 minutes/day for >10 minutes at a time; or (3) 5 days of any combination of walking, moderate intensity, or vigorous-intensity activities achieving at least 600 MET-minutes/week. High: Meets either of two criteria: (1) vigorousintensity activity on >3 days/week and accumulating at least 1,500 MET-minutes/week; or (2) >5 days of any combination of walking, moderate-intensity, or vigorous-intensity activities achieving at least 3,000 MET minutes/week. Nutritional habits were estimated using a semiquantitative food frequency questionnaire, including 150 food items. For each food item, the following categories of consumption frequency during the past year were used: never, 1 to 3timesamonth,onceaweek,2to4timesaweek,5to 6timesaweek,onceadayandmorethanonceaday. Portion sizes were predefined using household measures (teaspoon, glass, cup, etc.). The validity of the food frequency questionnaire was tested on a sample of 100 men representative of the participants to the present study. 6 The food frequency questionnaire was tested on repeatability and validated against a 4-days food record. The MDS was computed as described previously. 10 Briefly, a value of 0 or 1 was assigned to each of 9 indicated components with the use of the median as the cutoff. For beneficial components (vegetables, legumes, fruits and nuts, cereal, and fish), persons whose consumption was below the median were assigned a value of 0, and persons whose consumption was at or above the median were assigned a value of 1. For components presumed to be detrimental (meat, poultry, and dairy products), persons whose consumption was below the median were assigned a value of 1, and persons whose consumption was at or above the median were assigned a value of 0. For ethanol, a value of 1 was assigned to men consuming between 10 and 50 g per day. Finally, for fat intake, the ratio of monounsaturated lipids to saturated lipids was used. Thus, the total MDS ranged from 0 (minimal adherence to the traditional Mediterranean diet) to 9 (maximal adherence). The following health-related and lifestyle characteristics were registered with a questionnaire used in previous research 12 : age (20 29 years, 30 39 years, 40 49 years, and 50 59 years), military rank as proxy for socioeconomic status, body mass index (BMI) classified according to the World Health Organization in normal weight, 18.5 BMI < 25.0 kg/m 2, overweight, 25.0 BMI < 30.0 kg/m 2 and obesity, BMI ³ 30.0 kg/m 2, actual smoking (yes or no); and educational level (low for vocational education, moderate for secondary level, and high for high school level or university, i.e., bachelor or master level) are presented in Table I. Descriptive statistics were expressed as mean and 95% confidence interval (95% CI). A binary logistic regression was executed to estimate the effect of age, BMI, smoking, education, and MDS on high versus lowest levels of physical activity. In a multivariate linear regression, the residuals of MET-walking, MET-moderate, MET-vigorous, and MET-total showed a non-normal distribution. Instead of transforming the data logarithmically, a logistic regression was preferred. MET-walking, MET-moderate, METvigorous, and MET-total were coded as following: below the median = 0 and above the median = 1. All variables were introduced at the same time in the model. Plots of the residuals versus the predicted values were examined to ascertain that basic model assumptions were met. A two-sided 0.05 level of significance was defined. SPSS 19.0 (SPSS, Chicago, IL) statistics software was used. This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Bioethical Committee of the University of Leuven. Written informed consent was obtained from all subjects. RESULTS Table I presents the demographic and lifestyle characteristics of the subjects. In total, 1,852 subjects were included in the study, which represents 37% of the 5,000 preselected men. The most prevalent age category was 40 to 49 years, 76% were nonsmokers. About 58% had a BMI ³ 25.0 kg/m 2, whereas 42.6% had a low level of education. Responders to the mailing tended to be older than nonresponders (74.3% were older than 40 years compared to 61.4% for the nonresponders) ( p < 0.001). Moreover, soldiers were less incline to participate to the study ( p < 0.001). 496 MILITARY MEDICINE, Vol. 178, May 2013

TABLE I. Characteristics of the 1,852 Belgian Army Men Characteristics Categorization n % n % Total 1,852 100.0 3,148 100.0 Age (in Years) 20 29 119 6.4* 461 14.6* 30 39 358 19.3* 753 23.9* 40 49 1,064 57.5* 1,439 45.7* 50 59 311 16.8* 495 15.7* Military Rank Officers 217 11.7* 381 12.1* Noncommissioned Officers 936 50.5* 1,167 37.1* Soldiers 699 37.7* 1,600 50.8* BMI Normal (<25.0) 744 40.2 Overweight (³25.0 <30.0) 836 45.1 Obesity (³30.0) 244 13.2 Missing 28 1.5 Physical Activity Low 365 20.7 Moderate 383 21.7 High 1,016 57.6 Missing 88 4.8 Actual Smoking 447 24.1 Educational Level Low 789 42.6 Moderate 811 43.8 High 252 13.6 MDS Low (0 3) 694 38.3 Moderate (4 6) 803 52.5 High (7 9) 108 9.2 *p < 0.001. Responders Nonresponders Analysis of the IPAQ indicated that 57.6% (n = 1,016) of the participants had a high level of physical activity, 21.7% a moderate level and 20.7% a low level (Table I). Less than 10% reached a high MDS (a score between 7 and 9). The majority had a moderate score between 4 and 6, whereas 38.3% had a MDS below 4. Table II presents the median and 95% CI of MET in function of variables used in the logistic regression model. Median MET-total varied between 6,224 MET-minutes/week for the age category 20 to 29 years to 4,578 MET-minutes/ week for the age category 50 to 59 years. MET-walk increased with increasing age and BMI categories and decreased with increasing educational level. In contrast, MET-moderate and MET-vigorous decreased with increasing age categories, BMI categories, and educational level. MET-moderate and MET-vigorous were associated with a high MDS. Table III presents the odds ratios (OR) of the multivariable logistic models with 95% CI. MET-walk, MET-moderate, MET-vigorous, and MET-total were dichotomized in below and above the median. After adjustment for other variables, TABLE II. Stratified Distribution of Physical Activity Expressed in MET-Minutes/Week MET-Walk MET-Moderate MET-Vigorous MET-Total MET in Minutes/Week n Mean 95% CI Mean 95% CI Mean 95% CI Mean 95% CI Age (in Years) 20 29 104 909 607 1,211 1,603 1,162 2,044 3,712 2,845 4,579 6,224 5,087 7,360 30 39 325 961 783 1,140 1,268 1,027 1,509 3,177 2,738 3,615 5,406 4,758 6,054 40 49 934 1,152 1,039 1,265 1,354 1,221 1,487 2,844 2,584 3,104 5,350 5,000 5,700 50 59 263 1,264 1,042 1,487 1,192 962 1,422 2,121 1,724 2,518 4,578 3,994 5,161 BMI Normal (<25.0) 661 1,079 950 1,208 1,273 1,125 1,420 2,999 2,684 3,314 5,350 4,931 5,769 Overweight 729 1,083 957 1,208 1,352 1,199 1,506 2,909 2,629 3,189 5,344 4,953 5,725 (³25.0 <30.0) Obesity (³30.0) 214 1,278 1,040 1,516 1,331 1,028 1,635 2,170 1,688 2,653 4,780 4,043 5,517 Smoking Yes 370 1,417 1,206 1,627 1,628 1,371 1,885 3,025 2,541 3,506 6,090 5,359 6,780 No 1,256 1,028 939 1,118 1,238 1,131 1,345 2,797 2,591 3,003 5,063 4,789 5,337 Educational Low 663 1,176 1,039 1,313 1,543 1,369 1,717 3,136 2,791 3,481 5,855 5,397 6,313 Level Moderate 729 1,180 1,045 1,314 1,291 1,143 1,440 2,878 2,598 3,157 5,348 4,950 5,747 High 234 751 617 885 824 638 1,010 1,945 1,669 2,222 3,521 3,114 3,927 MDS Low (0 3) 587 1,196 1,052 1,339 1,347 1,173 1,521 2,644 2,322 2,966 5,187 4,728 5,645 Moderate (4 6) 852 1,049 937 1,161 1,285 1,149 1,421 2,752 2,510 2,994 5,086 4,747 5,415 High (7 9) 152 1,054 789 1,320 1,291 991 1,592 3,543 2,844 4,241 5,888 5,021 6,755 MILITARY MEDICINE, Vol. 178, May 2013 497

TABLE III. Logistic Regressions With Total and Subscores of Physical Activity as Dichotomic-Dependent Variables and Demographic and Lifestyle Characteristics as Predictors (Mutually Adjusted OR) MET-Walk MET-Moderate MET-Vigorous MET-Total Characteristics Categorization OR 95% CI OR 95% CI OR 95% CI OR 95% CI Age in Years 1.02* 1.01 1.04 0.99 0.98 1.00 0.97* 0.95 0.98 0.98* 0.97 0.99 BMI in kg/m 2 1.04* 1.01 1.07 0.98 0.95 1.01 0.95* 0.93 0.98 0.96* 0.94 0.99 Smoking Yes Versus No 1.20 0.94 1.53 1.00 0.78 1.28 0.83 0.65 1.06 0.92 0.72 1.18 Educational Level Low, Moderate, High 0.98 0.85 1.14 0.73* 0.63 0.85 0.85* 0.73 0.98 0.70* 0.60 0.81 MDS Score from 0 to 9 0.99 0.94 1.05 1.02 0.96 1.08 1.11* 1.05 1.18 1.06 1.00 1.12 MET-tot = sum of MET-walk, MET-moderate, and MET-vigorous. Operationalization of MET-variables: below median score 0 and above median score 1. *OR (adjusted for age, BMI, smoking, education, and MDS) within a column were statistically significant ( p < 0.05). MET-walk was associated with increasing age, BMI, and smoking. MET-moderate was inversely associated with educational level with an OR = 0.73 (95%CI: 0.63 0.85). METvigorous decreased with age, BMI, smoking, and educational level. MET-vigorous was positively related to MDS, with an OR of 1.11 (95% CI: 1.05 1.18) for each MDS-point. An increase in BMI of 1 kg/m 2 was associated with an OR of 0.95 (95% CI: 0.93 0.98), meaning that each increase of one BMI unit decreased the probability of MET-vigorous with 5%. Each life year was associated with a 3% decrease in MET-vigorous. Smokers had an OR for MET-vigorous of 0.83 (95% CI: 0.65 1.06) compared to nonsmokers. DISCUSSION The aim of the present study was to estimate levels of physical activity in a military occupational environment in relation to the prevalence of adiposity. Furthermore, we tried to explore the relation between physical activity and dietary pattern as characterized by MDS. According to the IPAQ classification, the majority of this military sample has a high level of physical activity (57.8%); whereas 21.7% had a moderate and only 20.7% had a low physical activity level. However, this physical activity promoting environment is not associated with lower prevalence of adiposity. The mean total physical activity level as reported in this military situation was 5,292 MET/minutes/week (95% CI: 5,025 5,559). Compared to values obtained on a representative sample of the Belgian population, using the same questionnaire, this is high. Mean and 95% CI MET-total in the Belgian Health Interview Survey was 4,227 METminutes/week (95% CI: 3,894 4,560). 13 A higher level of physical activity in this military sample was found for all age categories when comparing with the Belgian population, with respectively a mean MET-minutes/week of 4,563, 4,341, 4,382, and 2,866; for the present study, this was 6,224, 5,406, 5,350, and 4,578. Army men are encouraged to engage daily in sports or physical activity during the working day. This physical activity promoting environment results in higher levels of activity compared with a nonmilitary population. This high level of physical activity does not result in a healthy BMI about 58% of the military participants had a BMI of 25.0 kg/m 2 or more. The prevalence in this military sample was higher compared to the above mentioned Belgian survey in which 50% of male subjects aged between 20 and 55 years had a BMI of 25.0 kg/m 2 or more. For the age categories in years of 20 to 29, 30 to 39, 40 to 49, and 50 to 59 this was, respectively, 28.8%, 49.6%, 59.2%, and 64.6%; for the present study, this was 35.9%, 53.8%, 59.7%, and 72.7%. Army men are encouraged to engage daily in sports or physical activity during the working day. This physical activity promoting environment results in higher levels of activity compared with a nonmilitary population. The majority of the participants had a moderate MDS and only 9% scored high. This is comparable with the results of Trichopoulou et al 14 reporting only 8% of a Greek population reaching a high MDS. A high MDS has been associated with a healthy lifestyle. 10 Increasing MDS of a population can be seen as a measure for prevention of chronic diseases. Univariate analysis revealed that MET-total was negatively related to age, BMI, educational level, and positively to smoking and MDS. However, a changing pattern of METwalk, MET-moderate, and MET-vigorous was observed over age, BMI, smoking, educational level, and MDS. When analyzing in function of the intensity of physical activity, it was found that especially MET-vigorous had the most discriminative power. In multivariate analysis, MET-vigorous was associated with being young, a lower BMI, not smoking, a lower educational level, and a higher MDS. An explanation for the inverse association of MET with educational level can be that officers have more administrative and sedentary duties in an army compared with noncommissioned officers and soldiers. Especially, the decrease of MET-vigorous, and the increase of MET-moderate, and MET-walking as a function of age and BMI may be an indication that the quantity of physical activity is sufficient with insufficient quality to reach the intensity threshold to reach optimal health benefits. 8 Logistic regression confirmed the discriminative power of MET vigorous and revealed that an increase in one BMI unit decreased the probability of MET vigorous with 5%, whereas an increase of one life years decreased the probability of 498 MILITARY MEDICINE, Vol. 178, May 2013

MET vigorous with 3%. This emphasizes the essential role of BMI in the ability to perform high-intensity physical activity. Our results are in line with the recent publication of Holtermann et al, 15 where a higher level of occupational physical activity was related with an increased BMI in the Copenhagen City Heart Study (n = 7,819). As in our sample, these authors found equally an increasing prevalence of smoking with increasing occupational physical activity. To our knowledge, this was the first study carried out, that found an association of physical activity level with a more general dietary pattern. In this study we used the MDS, because of the strong negative association of this score with total mortality, as reported in different populations by different research teams. 10 Only MET-vigorous was associated with higher score for MDS. A limitation of this study is the low response of 37%, but information could be gathered concerning nonresponders. The responders to this study were older than nonresponders. Socioeconomic position, as measured by military rank, was comparable between responders and nonresponders. However, the main purpose of this study was not to provide exact estimations of prevalence but to detect differences in socioeconomic position, health behavior factors, and dietary pattern between low and high levels of physical activity. A second limitation could be the social desirability with a high physical readiness expectation for the military environment, which may result in an overestimation of physical activity. It is well-known that a high degree of muscularity may result in a misclassification based on BMI only. 16,17 However, earlier research using a combined approach of bioelectrical impedance estimated body fat percentage and BMI found that 80% of Belgian army recruits were classified correctly using BMI as an indicator for adiposity. Moreover, it is well showed that as a function of age, fat mass is increasing to the detriment of muscle mass. Because of the overrepresentation of age groups of 40 years and more in our sample, it may be expected that a high BMI is more because of a high adiposity. In conclusion, the military environment seems to impose a considerable occupational physical activity level. The latter does not result in a healthy weight status as estimated by BMI. Only the vigorous physical activities were found to be related with a healthier diet as indicated by MDS. Future research should focus on the possible role, barriers, motivators, the optimal level, and quantity of physical activity necessary for prevention of obesity in occupational settings. Interestingly, Nelson et al found in 71 healthy military volunteers that the chief benefit of physical activity reported was an improvement in physical performance, whereas the leading barrier to physical activity was the physical exertion involved. 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