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Targeting Abdominal Adiposity and Cardiorespiratory Fitness in the Workplace VALE´RIE LE´VESQUE1,2, MAGGIE VALLIE`RES1, PAUL POIRIER1,3, JEAN-PIERRE DESPRE´S1,2, and NATALIE ALME´RAS1,2 1
Que´bec Heart and Lung Institute, Que´bec, QC, CANADA; 2Department of Kinesiology, Faculty of Medicine, Universite´ Laval, Que´bec, QC, CANADA; 3Faculty of Pharmacy, Universite´ Laval, Que´bec, QC, CANADA
ABSTRACT LE´VESQUE, V., M. VALLIE`RES, P. POIRIER, J.-P. DESPRE´S, and N. ALME´RAS. Targeting Abdominal Adiposity and Cardiorespiratory Fitness in the Workplace. Med. Sci. Sports Exerc., Vol. 47, No. 7, pp. 1342–1350, 2015. Purpose: The prevalence of numerous chronic metabolic diseases is increasing worldwide with considerable personal and societal consequences. The aim of our study was to test the hypothesis that assessment of waist circumference (WC) and of cardiorespiratory fitness (CRF) could be relevant clinical targets of a simple preventive approach designed to improve cardiometabolic risk (CMR) profile at the workplace. Methods: A total of 787 employees participated in a pilot project of the ‘‘Grand De´fi Entreprise.’’ This challenge involved a 3-month in-house competition to favor peer support in the adoption of healthier lifestyle habits. For that purpose, the participating companies offered a comprehensive cardiometabolic/cardiorespiratory health assessment performed at the workplace with a mobile risk assessment unit before and after the contest (nutrition/physical activity (PA) questionnaires, resting blood pressure (BP), anthropometric measurements, lipid profile, and submaximal treadmill test). Results: At baseline, more than 43% of workers were considered sedentary or moderately inactive (G3.5 hIwkj1 of physical activity). Furthermore, the proportion of subjects in the high-risk category of nutritional quality index (NQI) was high (49%). After 3 mo, NQI and PA level improved. Reductions in WC (j4.2 T 4.0 cm, P G 0.0001), in heart rate at a standardized submaximal workload (j4 T 10 bpm, P G 0.0001) as well as in resting systolic (j6 T 11 mm Hg) and diastolic (j4 T 7 mm Hg) blood pressure were also observed. Improvements in WC and CRF were associated with improvements in the CMR profile. Conclusion: Results of this study show the added value of measuring/targeting WC and CRF as a relevant approach to reduce CMR at the workplace. Results also suggest that putting in place a permissive ‘‘in-house ecosystem’’ within the company is relevant to promote the adoption of healthier lifestyle habits. Key Words: CARDIOMETABOLIC RISK, LIFESTYLE INTERVENTION, NUTRITION, PHYSICAL ACTIVITY, CARDIORESPIRATORY FITNESS, WAIST CIRCUMFERENCE
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management programs to deal with the epidemic proportions reached by these societal diseases (1). However, such programs are largely based on the evaluation of traditional risk factors and on the pharmacological management of chronic diseases rather than on upstream prevention approaches (18). In this regard, we have recently pointed out that important markers of behaviors such as waist circumference (WC, as a marker of abdominal adiposity) and cardiorespiratory fitness (CRF, as a marker of regular participation to moderate-tovigorous physical activities) are most often not considered in most workplace health assessment/management programs (18). Numerous studies have shown that abdominal obesity is an important and highly prevalent emerging risk factor for T2D and CVD (7,17). Accordingly, Blair et al. (8) have shown that a poor level of CRF, as a reliable marker of a low level of participation to vigorous physical activities, was a powerful and independent predictor of comorbidities and mortality even after controlling for well-established traditional risk factors such as smoking, dyslipidemia, hypertension, and diabetes. Unfortunately, very few cardiometabolic risk (CMR) assessment/ management programs offered to employees/workers also focus on markers of abdominal adiposity and CRF in addition to the legitimate attention, which should be given to smoking and elevated blood pressure (BP), lipids, and glucose. Furthermore, although numerous studies have shown the efficacy of regular aerobic exercise training to reduce abdominal
hronic metabolic diseases such as type 2 diabetes (T2D), hypertension, and cardiovascular disease (CVD) are highly prevalent conditions with considerable personal and societal consequences (36). Such disorders not only have a direct impact on the quality of life of employees/workers and their families but also have huge financial consequences related to absenteeism, health care costs, and loss of productivity (28). However, these costly chronic conditions are largely lifestyle diseases driven by overconsumption of energy-dense, highly refined processed foods and by our sedentary occupational and leisure time activities (34). Several companies have adopted disease
Address for correspondence: Natalie Alme´ras, PhD, Centre de recherche de l_Institut universitaire de cardiologie et de pneumologie de Que´bec, Pavilion Marguerite-D’Youville, 4th Floor, 2725 chemin Ste-Foy, Que´bec QC G1V 4G5, Canada; E-mail: [email protected]. Submitted for publication June 2014. Accepted for publication October 2014. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.acsm-msse.org). 0195-9131/15/4707-1342/0 MEDICINE & SCIENCE IN SPORTS & EXERCISEÒ Copyright Ó 2014 by the American College of Sports Medicine DOI: 10.1249/MSS.0000000000000559
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MATERIALS AND METHODS A total of 787 employees (631 men and 156 women) from five different companies, mostly union blue collar workers producing goods, were involved in a pilot project of the ‘‘Grand De´fi Entreprise’’ (Grand Corporate Challenge). The Grand De´fi Entreprise program was designed based on the key principles promoted by the American Heart Association behavior changes committee (5A’s: Access, Advise, Agree, Assist, Assure follow-up) (33). The challenge was conducted within each company and involved a 3-month friendly inhouse competition among teams of five employees to favor peer support in the adoption of healthier lifestyle habits (eat better, move more, and quit smoking). For that purpose, the participating companies offered to their employees a free and comprehensive cardiometabolic and cardiorespiratory health assessment provided by a mobile risk assessment unit at the workplace before and after the contest. Medical history, lifestyle habits (including nutritional quality and physical activity (PA) level) assessed by questionnaires, resting BP, anthropometric measurements including WC, lipid profile, and CRF assessed by a submaximal treadmill test, were performed by trained health care professionals at the workplace during working hours. All information, which was collected on iPads, was incorporated into a confidential global health report and was given to each employee at the end of the evaluation. Before the implementation of this pilot study, the comprehensive cardiometabolic risk assessment/management program had been previously presented and endorsed by both top management and workers’ unions/representatives. After the initial evaluation, the friendly in-house competition was conducted within each company during the spring period. Points were given to each team as a function of improved risk variables/ behaviors. Teams who globally improved the most their lifestyle habits had more chances to win a major prize offered by the top management. The competition was only within companies, and awards were not the same across companies, as it was left at the discretion of the employers. The ethics committee of the IUCPQ approved the study, and all subjects signed a written informed consent to participate in this study.
each season using only two questions. Questions on leisure time PA allow classification of individuals into four categories: 1) active (Q7 hIwkj1), 2) moderately active (3.5–7 hIwkj1), 3) moderately inactive (0–3.5 hIwkj1) and, 4) sedentary (0 hIwkj1). The questionnaire was completed before the contest for the evaluation of PA level at baseline as well as after the 3-month lifestyle modification period, which was the same (spring season) for all participating companies. Physical activity journal. During the 3-month challenge, workers compiled in an electronic self-monitoring journal each period of 15 min of PA that induced an increase in heart rate (HR) for the assessment of the cumulative time devoted to weekly PA. Nutritional quality index. The quality of diet was evaluated using the validated Dietary Screening Tool for the assessment of a nutritional quality score, which can vary from 0 to 100 (5). The nutritional quality index (NQI) allows classifying individuals into three categories of risk: 1) low risk (Q75), 2) moderate risk (60–74) and, 3) high risk (G60). Hemodynamic Measurements Two BP and pulse rate measurements were taken by trained health professionals on both arms with an appropriate cuff size after the patient had been resting in the sitting position for at least 5 min. Mean BP assessed on the left arm was used for the analyses. Plasma Lipid Profile Blood samples were collected from the forearm vein into lithium heparin tubes containing EDTA (Miles Pharmaceuticals, Rexdale, Ontario, Canada) for the measurement of plasma lipid and lipoprotein levels. Cholesterol and triglyceride (TG) concentrations were determined in plasma and lipoprotein fractions using an Abaxis Piccolo Xpress Chemistry Analyzer (Thermo Fisher, Union City, NJ, USA) (30). Anthropometric Measurements Height, weight (11), and WC (27) were measured by trained health professionals according to standardized procedures; and body mass index (BMI) was calculated from weight and height. Individuals with a BMI between 18.5 and 24.9 kgImj2 are classified as having normal weight whereas individuals with a BMI ranging from 25 to 29.9 kgImj2 or Q30 kgImj2 are classified as overweight and obese, respectively (27). Body composition (fat and fat-free mass) was estimated by bioelectrical impedance (BIA) with the Tanita body composition analyzer TBF-300A (Arlington Heights, IL, USA).
Physical Activity and Nutritional Quality Physical activity index. The summary index of PA derived from the questions used in the EPIC study has been shown to be related to CVD risk (37). The validated short questionnaire estimated PA level at work and during leisure time for
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Prediction of Cardiovascular Risk To estimate the 10-yr cardiovascular risk, the Framingham risk score was calculated according to the adapted simplified model, using the weighted risk factors: age, gender, total
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adiposity and improve CMR (22), less evidence is available on the effectiveness of simple, low-cost interventions designed for the workplace and targeting abdominal adiposity and CRF. In the present pilot study, we tested the hypothesis that the assessment of WC and of CRF would be important and relevant clinical targets of a simple but comprehensive preventive approach based on peer support designed to improve the CMR profile.
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cholesterol, HDL cholesterol, smoking history, BP, and diabetes mellitus (39). Vascular age was calculated according to the definition of D’Agostino et al. (15). Submaximal Treadmill Test Cardiorespiratory fitness was assessed using a submaximal treadmill test according to a homemade protocol on a TMX 425 treadmill (Trackmaster, Newton, KS, USA) linked to a sphygmomanometer (Suntech Medical, Morrisville, NC, USA). Submaximal treadmill tests were administrated by trained kinesiologists specialized in exercise testing. The protocol began with a warm-up workload of 2.5 mph with a 0% slope followed by a standardized stage (3.5 mph, 2% slope). The third stage was adjusted in an attempt to reach 75% of the age-estimated maximal HR. If necessary, a fourth stage was performed. Participants’ HR was monitored using the Polar heart monitor system (QC, Canada) and was assessed at the standardized stage for the assessment of CRF. Estimated METs was predicted by extrapolation to age-predicted maximal HR (20). Statistical Analyses Data are presented as mean T SD in tables and as mean T SE in figures. The Shapiro-Wilk test was used to examine the distribution of each variable, and logarithmic transformations were applied to variables showing abnormal distribution. Paired t-tests were performed to compare baseline and post– 3-month intervention levels. Paired t-tests were also performed to compare baseline and after 3-mo intervention levels of anthropometric parameters and CMR markers in each subgroup, and a one-way ANOVA was performed to compare CMR profile between subgroups of changes in WC and CRF (see definition in the ‘‘Results’’ section). P G 0.05 was considered statistically significant. All statistical analyses were performed using the SAS statistical package version 9.2 (SAS Institute, Cary, NC, USA).
RESULTS Seven hundred eighty-seven workers, including 631 men and 156 women, participated in the 3-month friendly competition among teams of five workers to favor peer support in the adoption of healthier lifestyle habits. Baseline and post–3-month characteristics of employees are shown in Table 1. Among the 787 workers (mean age, 44.6 T 10 yr), 43% were overweight and 26% were obese, whereas 14.2% took hypolipidemic drugs, 11.6% took antihypertensive medications, and 3.6% reported to be treated for T2D. Furthermore, 25.4% of the workers did not know they had hypertension, although their resting BP was greater than 140/90 mm Hg. At baseline, men had higher BMI, WC, and TG levels, whereas HDL-cholesterol levels were lower compared to women (P G 0.05) (see Table, Supplemental Digital Content 1, Participants’ characteristics at baseline and post–3-month intervention period, http://links.lww.com/MSS/A456). Men also
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TABLE 1. Participants’ characteristics at baseline and after the 3-month intervention period. Baseline Sex (men/women) 631/156 Anthropometric measurements and body composition Weight, kg 82.6 T 15.9 27.5 T 4.5 BMI, kgImj2 Waist circumference, cm 96.3 T 12.6 Fat mass, kg 22.5 T 9.5 Fat-free mass, kg 60.0 T 10.1 Lipoprotein-lipid profile 4.70 T 0.87 Total cholesterol, mmolILj1 VLDL cholesterol, mmolILj1 0.83 T 0.41 j1 2.52 T 0.74 LDL cholesterol, mmolIL j1 1.29 T 0.32 HDL cholesterol, mmolIL Cholesterol/HDL cholesterol 3.84 T 1.17 j1 3.41 T 0.83 Non-HDL cholesterol, mmolIL j1 Triglycerides, mmolIL 2.00 T 1.15 5.99 T 1.24 Plasma glucose, mmolILj1 Nutritional quality index 60.6 T 12.8 Smokers/nonsmokers, n 104/682 Framingham risk score, % 5.5 T 4.6 Vascular age, yr 49.2 T 13.5
After 3 Mo
P
631/156 80.4 T 26.8 T 92.2 T 20.4 T 60.0 T
15.3 4.3 12.1 8.8 10.0
G0.0001 G0.0001 G0.0001 G0.0001 NS
4.47 T 0.81 0.71 T 0.39 2.40 T 0.66 1.32 T 0.32 3.54 T 0.94 3.14 T 0.75 1.65 T 0.99 5.83 T 1.01 69.9 T 11.8 41/731 4.5 T 3.8 46.7 T 13.1
G0.0001 G0.0001 G0.0001 G0.0001 G0.0001 G0.0001 G0.0001 G0.01 G0.0001 G0.0001 G0.0001 G0.0001
Values are presented as mean T SD. HDL cholesterol, high-density lipoprotein cholesterol; LDL cholesterol, low-density lipoprotein cholesterol; NS, not significant; VLDL cholesterol, very low-density lipoprotein cholesterol.
showed a higher estimated METs and a lower submaximal HR than women (P G 0.05) (see Table, Supplemental Digital Content 1, Participants’ characteristics at baseline and post–3month intervention period, http://links.lww.com/MSS/A456). After the 3-month intervention, participants decreased their BMI (¸ = j0.7 T 1.0 kgImj2, P G 0.0001), fat mass (¸ = j2.1 T 2.9 kg, P G 0.0001) and WC (¸ = j4.2 T 4.0 cm, P G 0.0001); whereas no change in fat-free mass was observed. VLDL cholesterol, LDL cholesterol, and TG levels, as well as the total cholesterol/HDL cholesterol ratio decreased; whereas HDL cholesterol concentrations increased (P G 0.0001). Men showed a greater reduction in their WC and TG levels than women and a greater increase in their HDL-cholesterol levels than their female counterparts (P G 0.05) (see Table, Supplemental Digital Content 1, Participants’ characteristics at baseline and post–3-month intervention period, http://links.lww.com/MSS/A456). The intervention also resulted in a significant 15% improvement in the NQI (P G 0.0001) assessed by questionnaire. The proportion of workers classified in the high-risk category of NQI was reduced by more than 60%, whereas the proportion in the low- and moderate-risk categories increased by 133% and 24%, respectively (Fig. 1A). Prevalence of workers considered sedentary (0 hIwkj1) and moderately inactive (90–3.5 hIwkj1) decreased by approximately 65% and 9%, respectively, whereas those considered moderately active (3.5–7 hIwkj1) and active (Q7 hIwkj1) increased by approximately 7% and 29%, respectively (data not shown). Analyses of the PA journal showed that workers performed a mean of 5.5 h of PA per week during the 3-month follow-up. PA level assessed by questionnaire increased in each subgroup compared to baseline values except for workers who were already active at baseline (Fig. 1B). More than 60% of smokers ceased smoking during the 3-month competition (Table 1). Workers who quit smoking did not gain weight and have significantly reduced their waist circumference
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FIGURE 1—A, Proportion of employees across various categories of nutritional quality index before and after the 3-month intervention. B, Reported physical activity level before and after the 3-month intervention according to the baseline PA status. ‡Significantly different from baseline; P G 0.0001.
(¸ = j3.4 T 3.6 cm, P G 0.0001). Active smokers and those who quit smoking similarly benefited from the program (see Table, Supplemental Digital Content 2, Impact of smoking cessation on participants’ cardiometabolic risk profile, http://links.lww.com/MSS/A457). After 3 months of healthier lifestyle habits, participants also significantly decreased their resting systolic (¸ = j6 T 11 mm Hg) and diastolic (¸ = j4 T 7 mm Hg) BP, as well as their resting HR (¸ = j2 T 10 bpm) (Fig. 2A) (P G 0.0001 for all). Ten participants began to take antihypertensive drugs during this 3-month period, whereas eight subjects stopped taking their antihypertensive drugs because their BP was substantially reduced. Cardiorespiratory fitness was also improved as reflected by reductions in submaximal HR (¸ = j4 T 10 bpm) and submaximal systolic (¸ = j6 T 17 mm Hg) and diastolic
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FIGURE 2—Systolic and diastolic BP and HR before and after the 3-month intervention (A) in the resting state and (B) measured at a standardized submaximal exercise (ex) workload (3.5 mph, 2% slope). ‡P G 0.0001.
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(¸ = j3 T 12 mm Hg) BP measured at a standardized treadmill workload (Fig. 2B) (P G 0.0001 for all variables). To investigate the respective contributions of changes in WC and CRF to the improvement of CMR profile, workers were classified into four subgroups according to change in WC (Gj1 or Qj1 cm) and the median of change in submaximal HR (Gj4 or Qj4 bpm): subgroup 1 (n = 287), reduction in WC and reduction in submaximal HR; subgroup 2 (n = 309), reduction in WC and increase in submaximal HR; subgroup 3 (n = 69), increase in WC and reduction in submaximal HR; and subgroup 4 (n = 72): increase in WC and increase in submaximal HR (Fig. 3). Figures 4 and 5 illustrate changes in CMR profile according to these four subgroups. Compared to workers in the other subgroups, workers who decreased both their WC (¸ = j5.7 T 3.5 cm) and submaximal HR (¸ = j12 T 6 bpm) showed the most important improvements in
CLINICAL SCIENCES FIGURE 3—Mean changes in WC and submaximal HR according to subgroups of employees classified based on the response of these two variables. Subgroup 1 (abdominal fat loss and improvement in fitness): reduction in WC and reduction in submaximal HR; subgroup 2 (abdominal fat loss and no improvement in fitness): reduction in WC and increase in submaximal HR; subgroup 3 (no abdominal fat loss and improvement in fitness): increase in WC and reduction in submaximal HR; and subgroup 4 (no abdominal fat loss and no improvement in fitness): increase in WC and increase in submaximal HR.
BMI (¸ = j1.0 T 1.0 kgImj2), TG (¸ = j0.53 T 0.99 mmolIL), and HDL cholesterol levels (¸ = 0.06 T 0.17 mmolIL) as well as in their NQI (¸ = 10.9 T 11.1) (P G 0.0001 for all variables). They also significantly decreased their non-HDL cholesterol (¸ = j0.32 T 0.49 mmolIL), their resting systolic (¸ = j6 T 11 mm Hg) and diastolic (¸ = j4 T 7 mm Hg) BP, their systolic (¸ = j12 T 16 mm Hg) and diastolic (¸ = j4 T 11 mm Hg) BP measured at a standardized submaximal treadmill workload (data not shown), their Framingham risk score (¸ = j1.4 T 3.4), their vascular age (¸ = j3.2 T 5.6), and improved their estimated METs (¸ = 1.43 T 2.70 METs) (P G 0.0001 for all variables). Workers who only reduced their WC improved their NQI (¸ = 9.0 T 11.1), but showed a small decrease in their CRF as expressed by changes in estimated METs reduction (¸ = j0.51 T 2.68 METs) (P G 0.01). However, they significantly reduced their BMI (¸ = j0.8 T 1.0 kgImj2) as well as their TG (¸ = j0.34 T 0.89 mmolIL) and non-HDL cholesterol levels (¸ = j0.29 T 0.54 mmolIL). They also lowered their resting systolic (¸ = j5 T 10 mm Hg) and diastolic (¸ = j4 T 6 mm Hg) BP, their Framingham risk score (¸ = j0.9 T 2.9), and their vascular age (¸ = j2.1 T 5.4) (P G 0.0001 for all variables). In the third subgroup, workers reduced their submaximal HR (¸ = j11 T 6 bpm) and increased their estimated METs (¸ = 1.28 T 2.62 METs) (P G 0.01 for all variables), whereas no change was observed in their WC (¸ = 0.6 T 1.5 cm, NS). An increase in NQI was also observed (¸ = 5.2 T 9.3) but to a lesser extent than in the two first subgroups. This subgroup also significantly reduced their resting systolic (¸ = j7 T 10 mm Hg) and diastolic (¸ = j3 T 5 mm Hg) BP, their systolic (¸ = j8 T 15 mm Hg) and diastolic (¸ = j6 T 12 mm Hg) BP
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measured at a standardized submaximal treadmill workload (data not shown) as well as their vascular age (¸ = j2.3 T 4.2), whereas no change was noted regarding the BMI nor for the lipid profile. Finally, workers who did not reduce neither their WC (¸ = 0.9 T 1.8 cm) nor their submaximal HR (¸ = 4 T 7 bpm) nevertheless improved their NQI (¸ = 5.6 T 9.1) and reduced their resting systolic (¸ = j5 T 10 mm Hg) and diastolic (¸ = j3 T 7 mm Hg) BP. This subgroup showed no significant change in the BMI, lipid profile, estimated METs, Framingham risk score, or in vascular age. However, workers in this subgroup were less abdominally obese (lower WC) and were more fit (higher CRF) at baseline than the other subgroups (see Table, Supplemental Digital Content 3, Participants’ characteristics at baseline according to the four subgroups of subjects classified on the basis of WC and CRF, http://links.lww.com/MSS/A458).
DISCUSSION In a cohort of 787 workers involved in a 3-month lifestyle modification program focusing on increased PA level, healthy eating, and smoking cessation, a high prevalence of physical inactivity as well as a low NQI was observed at baseline. Moreover, 13% of the population were active smokers. After the 3-month lifestyle modification, PA level and NQI increased and 60% of smokers ceased smoking. Our results showed significant improvements in adiposity variables as reflected by reductions in BMI, WC, and fat mass. The intervention also resulted in significant improvements in the plasma lipid profile and CRF. As revealed by our subgroup analysis, the magnitude of the response to the program varied depending on whether or not participants reduced their waistline or improved their CRF. Results showed that the subgroup of workers who reduced their WC and while also improving their CRF were those who improved the most their CMR profile. Furthermore, the subgroup who had the most deteriorated CMR profile at baseline was the one who benefited the most from this worksite intervention (see Table, Supplemental Digital Content 3, Participants’ characteristics at baseline according to the four subgroups of subjects classified on the basis of waist circumference and CRF, http://links.lww.com/MSS/A458), a finding which is fully consistent with our previous lifestyle interventions (14). In the current health care system, legitimate attention is given to the management of traditional CVD risk factors, such as dyslipidemia and hypertension. However, it is now recognized that there are risk factors that tend to cluster in patients, making them more susceptible to develop CVD. Therefore, it is essential to consider a comprehensive approach in the evaluation and management of CMR. Several imaging studies using measurements of abdominal adiposity have shown that excess visceral adipose tissue (VAT) is a driving factor behind the metabolic abnormalities observed in sedentary overweight/ obese patients, independent of total body fat (16,19). Lifestyle intervention studies have documented their beneficial effects on VAT mobilization and on improving the CMR profile,
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CLINICAL SCIENCES FIGURE 4—Adiposity and lipid profile changes according to the four subgroups of subjects classified on the basis of waist circumference and cardiorespiratory fitness changes. Subgroup 1, reduction in WC and reduction in submaximal HR; subgroup 2, reduction in WC and increase in submaximal HR; subgroup 3, increase in WC and reduction in submaximal HR; and subgroup 4, increase in WC and increase in submaximal HR. ‡Significantly different from baseline, P G 0.0001. 1, 2, and 3, Significantly different from the corresponding subgroups.
even in the absence of weight loss (31). Accordingly, results of the present study show that subgroups who reduced their WC (a relevant marker of abdominal adiposity) significantly improved their CMR profile, even in the absence of improved CRF. On the other hand, it is also well documented that a high CRF is associated with a lower risk of metabolic syndrome, coronary artery disease (CAD), and all-cause mortality (9). A large longitudinal study demonstrated that a low CRF in young adults was associated with the development of T2D, hypertension, metabolic syndrome, and CVD (12). While improving CRF is associated with beneficial effects on numerous cardiovascular risk factors, a high level of CRF also seems to provide additional protection from CVD mortality independent from these risk factors (8). Lifestyle modification programs, which are aimed at increasing PA, have shown to be effective to improve the CMR profile and CRF (6,9). In the present study, to classify the CRF response of our participants, we have selected to use the median of changes in HR measured at a standardized submaximal workload (3.5 mph, 2%
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slope), which corresponds to a decrease of 4 bpm. We have previously reported that such reduction in submaximal HR was quite sensitive to detect an improvement in CRF, as it was associated with significant improvements in several CMR factors in response to a 1-yr lifestyle intervention study (10,26). The present pilot project provides further evidences that a cheap, rapid, and inexpensive measurement of HR at a standardized submaximal workload is useful to assess and target CRF in clinical practice. Therefore, we believe that the results of the present pilot study support the notion that reducing WC and improving CRF through increased PA level and improved NQI are important clinical targets, in addition to the management of traditional cardiovascular risk factors. However, these important markers of behaviors are not often considered in most health evaluation and behavioral counseling is not consistently provided to patients (35). Furthermore, in the present study, 22% of the participants reported that they did not have a family physician, whereas 29% reported that they did not benefit from a regular
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CLINICAL SCIENCES FIGURE 5—Blood pressure (BP), estimated cardiovascular risk, estimated METs, and nutritional quality index changes according to the four subgroups of subjects classified on the basis of WC and CRF changes. Subgroup 1, reduction in WC and reduction in submaximal HR; subgroup 2, reduction in WC and increase in submaximal HR; subgroup 3, increase in WC and reduction in submaximal HR; and subgroup 4, increase in WC and increase in submaximal HR. †Significantly different from baseline, P G 0.01. ‡Significantly different from baseline, P G 0.0001. 1, 2, and 3, Significantly different from the corresponding subgroups.
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proof-of-concept study and was not designed to isolate the contribution of these variables. All subgroups examined seemed to benefit from the intervention. Although the magnitude of the response to the program was related to some of the baseline participants’ characteristics, all subgroups showed improvements in their CMR profile. Another and obviously important issue to address will be the long-term efficacy of such a lifestyle intervention approach. Since this pilot study was conducted over a 3-month period, long-term compliance and benefits remain unaddressed issues. As a final point, we consider that changes in outcome variables considered in the present study are clinically relevant. For instance, we report a robust reduction in resting and submaximal exercise BP, which is predictive of a decreased risk of CHD and stroke (13). The significant reduction in the proportion of subjects with hypertriglyceridemic waist from 35% to 23% suggests a reduction in the number of workers characterized by the high-risk visceral obesity phenotype (24). Finally, regarding the increase in HDL cholesterol, although Mendelian randomization studies have questioned its relevance as an isolated endpoint (21), we believe that an increased HDL-cholesterol concentration resulting from a lifestyle modification program is rather an integrated marker of improved insulin sensitivity and loss of visceral/ectopic fat resulting from regular exercise (4). In conclusion, results of the Grand De´fi Entreprise pilot study suggest that CRF and WC may represent important additional targets in the evaluation and prevention of CVD in the workplace. These two variables represent important clinical markers of behaviours, which should be further considered in health evaluation and management programs. Although each of these two factors independently contributed to the improvement in the CMR profile found in the present study, the combination of reduced WC and improved CRF generated the most substantial cardiometabolic benefits. Thus, the workplace has the potential to become an epicenter for CMR assessment and for the promotion of healthier lifestyle habits (eat better, move more, and quit smoking), through friendly in-house competition and peer support.
This study was partly supported by an unrestricted grant from Pfizer as well as by the Foundation of the Institut universitaire de cardiologie et de pneumologie de Que´bec. The project is the result of a consortium between the Grand De´fi Entreprise Inc. and the Institut universitaire de cardiologie et de pneumologie de Que´bec. Dr. Paul Poirier is a senior clinical scientist from the Fonds de recherche du Que´bec – Sante´ (FRQ-S). Vale´rie Le´vesque is supported by the training program in obesity, Canadian Institutes of Health Research (CIHR), Universite´ Laval. Dr. Jean-Pierre Despre´s is the Scientific Director of the International Chair on Cardiometabolic Risk, which is based at Universite´ Laval. Results of the present study do not constitute endorsement by the American College of Sports Medicine (ACSM). Conflicts of Interest and Source of Funding: This study was partly supported by an unrestricted grant from Pfizer as well as by the Foundation of the Institut universitaire de cardiologie et de pneumologie de Que´bec. The project is the result of a consortium between the Grand De´fi Entreprise Inc. and the Institut universitaire de cardiologie et de pneumologie de Que´bec. All authors declare that there are no conflicts of interest.
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yearly health examination. Although our pilot project only included a 3-month intervention, we hope that our results provide encouraging evidence that it is indeed possible to assess nutritional quality and PA in clinical practice. Furthermore, targeting abdominal obesity and CRF can be achieved at low cost and little time by measuring WC and using a submaximal exercise test. Previous studies have shown that the 5 A’s, the key elements of a health behavior change counseling, produce significant changes in health behavior such as smoking cessation, improvement in nutritional quality and PA habits, as well as successful weight management (23,29,38). Indeed, subjects who received 5 A’s counselling techniques were found to have higher level of motivation and intentions to change their behaviors. Considering that the workplace has a large influence on workers’ health, growing evidence supports that it could become a privileged environment to promote healthy lifestyle habits (1,3). For this purpose, a recent position paper from the American Heart Association has stated that conducting health screenings in the workplace is a promising strategy for the early detection of established CVD risk factors as putting in place health programs seems to positively influence workers’ health (2). Several workplace lifestyle intervention programs have shown that nutritional and PA programs are effective to improve nutritional quality, fitness, and weight management (32) as well as to improve quality of life and reduce behavioral symptoms (such depression, anxiety, etc.) (25). We have also recently shown that an increase in both nutritional quality and PA levels optimally reduced VAT in initially sedentary viscerally obese men (26). Results of the present study showed that workers who both reduced their WC and their submaximal HR through increased PA level and improved nutritional habits were those who showed the most substantial improvements in their CMR profile. These results highlight the importance of targeting both CRF and WC through regular PA/exercise and improving nutritional quality to improve the CMR profile. To facilitate the adoption of these healthy behaviors, companies should also provide permissive physical and social environments. Furthermore, we believe that support tools (website, diary recording, physical activities, and nutritional targets) and peer support within the company are also important factors to promote PA, healthy eating, and smoking cessation as well as to maintain a high level of motivation among employees. Our pilot study documented the feasibility and efficacy of improving CMR profile through a simple 3-month lifestyle modification intervention performed at the workplace. However, the present study was not randomized, and patients who agreed to participate in the study were motivated to change their lifestyle. Nevertheless, a fairly high percentage of workers who were approached (63.5%) volunteered to participate in this lifestyle modification program. Obviously, several confounding factors (sex, age, socioeconomic status, employee status, smoking or not, initial health, and risk factor status) could have possibly modulated participant’s response to the intervention. The present pilot project was a
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21. Holmes MV, Asselbergs FW, Palmer TM, et al. Mendelian randomization of blood lipids for coronary heart disease. Eur Heart J. 2015;36(9):539–50. 22. Ismail I, Keating SE, Baker MKJohnson NA. A systematic review and meta-analysis of the effect of aerobic vs. resistance exercise training on visceral fat. Obes Rev. 2012;13(1):68–91. 23. Kahn EB, Ramsey LT, Brownson RC, et al. The effectiveness of interventions to increase physical activity. A systematic review. Am J Prevent Med. 2002;22(4 Suppl):73–107. 24. Lemieux I, Pascot A, Couillard C, et al. Hypertriglyceridemic waist: a marker of the atherogenic metabolic triad (hyperinsulinemia; hyperapolipoprotein B; small, dense LDL) in men? Circulation. 2000;102(2): 179–84. 25. Milani RV, Lavie CJ. Impact of worksite wellness intervention on cardiac risk factors and one-year health care costs. Am J Cardiol. 2009;104(10):1389–92. 26. Nazare JA, Smith J, Borel AL, et al. Changes in both global diet quality and physical activity level synergistically reduce visceral adiposity in men with features of metabolic syndrome. J Nutr. 2013; 143(7):1074–83. 27. National Heart, Lung, and Blood Institute (NHLBI) Obesity Education Initiative Expert Panel on the Identification, Evaluation, and Treatment of Obesity in Adults. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report. National Institutes of Health. Obes Res. 1998;6(2 Suppl):51S–209. 28. Ni Mhurchu C, Aston LM, Jebb SA. Effects of worksite health promotion interventions on employee diets: a systematic review. BMC Public Health. 2010;10:62. 29. Ockene IS, Hebert JR, Ockene JK, et al. Effect of physician-delivered nutrition counseling training and an office-support program on saturated fat intake, weight, and serum lipid measurements in a hyperlipidemic population: Worcester Area Trial for Counseling in Hyperlipidemia (WATCH). Arch Intern Med. 1999;159(7):725–31. 30. Robertson B LC, Chapman JF. Performance of the Abaxis Piccolo Analyzer for lipid measurements. Abaxis website [Internet]. Available from: http://www.abaxis.com/pdf/Piccolo%20Lipid%20Measurements% 20Performance.pdf. 31. Ross R, Janssen I, Dawson J, et al. Exercise-induced reduction in obesity and insulin resistance in women: a randomized controlled trial. Obes Res. 2004;12(5):789–98. 32. Schroer S, Haupt J, Pieper C. Evidence-based lifestyle interventions in the workplace—an overview. Occup Med. 2014;64(1):8–12. 33. Spring B, Ockene JK, Gidding SS, et al. Better population health through behavior change in adults: a call to action. Circulation. 2013; 128(19):2169–76. 34. Task Force on Community Preventive Services. A recommendation to improve employee weight status through worksite health promotion programs targeting nutrition, physical activity, or both. Am J Prev Med. 2009;37(4):358–9. 35. Vuori IM, Lavie CJ, Blair SN. Physical activity promotion in the health care system. Mayo Clin Proc. 2013;88(12):1446–61. 36. Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. Lancet. 2011;378(9793):815–25. 37. Wareham NJ, Jakes RW, Rennie KL, et al. Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Public Health Nutr. 2003;6(4):407–13. 38. Whitlock EP, Orleans CT, Pender N, Allan J. Evaluating primary care behavioral counseling interventions: an evidence-based approach. Am J Prevent Med. 2002;22(4):267–84. 39. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837–47.
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Targeting Abdominal Adiposity and Cardiorespiratory Fitness in the Workplace VALE´RIE LE´VESQUE1,2, MAGGIE VALLIE`RES1, PAUL POIRIER1,3, JEAN-PIERRE DESPRE´S1,2, and NATALIE ALME´RAS1,2 1
Que´bec Heart and Lung Institute, Que´bec, QC, CANADA; 2Department of Kinesiology, Faculty of Medicine, Universite´ Laval, Que´bec, QC, CANADA; 3Faculty of Pharmacy, Universite´ Laval, Que´bec, QC, CANADA
ABSTRACT LE´VESQUE, V., M. VALLIE`RES, P. POIRIER, J.-P. DESPRE´S, and N. ALME´RAS. Targeting Abdominal Adiposity and Cardiorespiratory Fitness in the Workplace. Med. Sci. Sports Exerc., Vol. 47, No. 7, pp. 1342–1350, 2015. Purpose: The prevalence of numerous chronic metabolic diseases is increasing worldwide with considerable personal and societal consequences. The aim of our study was to test the hypothesis that assessment of waist circumference (WC) and of cardiorespiratory fitness (CRF) could be relevant clinical targets of a simple preventive approach designed to improve cardiometabolic risk (CMR) profile at the workplace. Methods: A total of 787 employees participated in a pilot project of the ‘‘Grand De´fi Entreprise.’’ This challenge involved a 3-month in-house competition to favor peer support in the adoption of healthier lifestyle habits. For that purpose, the participating companies offered a comprehensive cardiometabolic/cardiorespiratory health assessment performed at the workplace with a mobile risk assessment unit before and after the contest (nutrition/physical activity (PA) questionnaires, resting blood pressure (BP), anthropometric measurements, lipid profile, and submaximal treadmill test). Results: At baseline, more than 43% of workers were considered sedentary or moderately inactive (G3.5 hIwkj1 of physical activity). Furthermore, the proportion of subjects in the high-risk category of nutritional quality index (NQI) was high (49%). After 3 mo, NQI and PA level improved. Reductions in WC (j4.2 T 4.0 cm, P G 0.0001), in heart rate at a standardized submaximal workload (j4 T 10 bpm, P G 0.0001) as well as in resting systolic (j6 T 11 mm Hg) and diastolic (j4 T 7 mm Hg) blood pressure were also observed. Improvements in WC and CRF were associated with improvements in the CMR profile. Conclusion: Results of this study show the added value of measuring/targeting WC and CRF as a relevant approach to reduce CMR at the workplace. Results also suggest that putting in place a permissive ‘‘in-house ecosystem’’ within the company is relevant to promote the adoption of healthier lifestyle habits. Key Words: CARDIOMETABOLIC RISK, LIFESTYLE INTERVENTION, NUTRITION, PHYSICAL ACTIVITY, CARDIORESPIRATORY FITNESS, WAIST CIRCUMFERENCE
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management programs to deal with the epidemic proportions reached by these societal diseases (1). However, such programs are largely based on the evaluation of traditional risk factors and on the pharmacological management of chronic diseases rather than on upstream prevention approaches (18). In this regard, we have recently pointed out that important markers of behaviors such as waist circumference (WC, as a marker of abdominal adiposity) and cardiorespiratory fitness (CRF, as a marker of regular participation to moderate-tovigorous physical activities) are most often not considered in most workplace health assessment/management programs (18). Numerous studies have shown that abdominal obesity is an important and highly prevalent emerging risk factor for T2D and CVD (7,17). Accordingly, Blair et al. (8) have shown that a poor level of CRF, as a reliable marker of a low level of participation to vigorous physical activities, was a powerful and independent predictor of comorbidities and mortality even after controlling for well-established traditional risk factors such as smoking, dyslipidemia, hypertension, and diabetes. Unfortunately, very few cardiometabolic risk (CMR) assessment/ management programs offered to employees/workers also focus on markers of abdominal adiposity and CRF in addition to the legitimate attention, which should be given to smoking and elevated blood pressure (BP), lipids, and glucose. Furthermore, although numerous studies have shown the efficacy of regular aerobic exercise training to reduce abdominal
hronic metabolic diseases such as type 2 diabetes (T2D), hypertension, and cardiovascular disease (CVD) are highly prevalent conditions with considerable personal and societal consequences (36). Such disorders not only have a direct impact on the quality of life of employees/workers and their families but also have huge financial consequences related to absenteeism, health care costs, and loss of productivity (28). However, these costly chronic conditions are largely lifestyle diseases driven by overconsumption of energy-dense, highly refined processed foods and by our sedentary occupational and leisure time activities (34). Several companies have adopted disease
Address for correspondence: Natalie Alme´ras, PhD, Centre de recherche de l_Institut universitaire de cardiologie et de pneumologie de Que´bec, Pavilion Marguerite-D’Youville, 4th Floor, 2725 chemin Ste-Foy, Que´bec QC G1V 4G5, Canada; E-mail: [email protected]. Submitted for publication June 2014. Accepted for publication October 2014. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.acsm-msse.org). 0195-9131/15/4707-1342/0 MEDICINE & SCIENCE IN SPORTS & EXERCISEÒ Copyright Ó 2014 by the American College of Sports Medicine DOI: 10.1249/MSS.0000000000000559
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MATERIALS AND METHODS A total of 787 employees (631 men and 156 women) from five different companies, mostly union blue collar workers producing goods, were involved in a pilot project of the ‘‘Grand De´fi Entreprise’’ (Grand Corporate Challenge). The Grand De´fi Entreprise program was designed based on the key principles promoted by the American Heart Association behavior changes committee (5A’s: Access, Advise, Agree, Assist, Assure follow-up) (33). The challenge was conducted within each company and involved a 3-month friendly inhouse competition among teams of five employees to favor peer support in the adoption of healthier lifestyle habits (eat better, move more, and quit smoking). For that purpose, the participating companies offered to their employees a free and comprehensive cardiometabolic and cardiorespiratory health assessment provided by a mobile risk assessment unit at the workplace before and after the contest. Medical history, lifestyle habits (including nutritional quality and physical activity (PA) level) assessed by questionnaires, resting BP, anthropometric measurements including WC, lipid profile, and CRF assessed by a submaximal treadmill test, were performed by trained health care professionals at the workplace during working hours. All information, which was collected on iPads, was incorporated into a confidential global health report and was given to each employee at the end of the evaluation. Before the implementation of this pilot study, the comprehensive cardiometabolic risk assessment/management program had been previously presented and endorsed by both top management and workers’ unions/representatives. After the initial evaluation, the friendly in-house competition was conducted within each company during the spring period. Points were given to each team as a function of improved risk variables/ behaviors. Teams who globally improved the most their lifestyle habits had more chances to win a major prize offered by the top management. The competition was only within companies, and awards were not the same across companies, as it was left at the discretion of the employers. The ethics committee of the IUCPQ approved the study, and all subjects signed a written informed consent to participate in this study.
each season using only two questions. Questions on leisure time PA allow classification of individuals into four categories: 1) active (Q7 hIwkj1), 2) moderately active (3.5–7 hIwkj1), 3) moderately inactive (0–3.5 hIwkj1) and, 4) sedentary (0 hIwkj1). The questionnaire was completed before the contest for the evaluation of PA level at baseline as well as after the 3-month lifestyle modification period, which was the same (spring season) for all participating companies. Physical activity journal. During the 3-month challenge, workers compiled in an electronic self-monitoring journal each period of 15 min of PA that induced an increase in heart rate (HR) for the assessment of the cumulative time devoted to weekly PA. Nutritional quality index. The quality of diet was evaluated using the validated Dietary Screening Tool for the assessment of a nutritional quality score, which can vary from 0 to 100 (5). The nutritional quality index (NQI) allows classifying individuals into three categories of risk: 1) low risk (Q75), 2) moderate risk (60–74) and, 3) high risk (G60). Hemodynamic Measurements Two BP and pulse rate measurements were taken by trained health professionals on both arms with an appropriate cuff size after the patient had been resting in the sitting position for at least 5 min. Mean BP assessed on the left arm was used for the analyses. Plasma Lipid Profile Blood samples were collected from the forearm vein into lithium heparin tubes containing EDTA (Miles Pharmaceuticals, Rexdale, Ontario, Canada) for the measurement of plasma lipid and lipoprotein levels. Cholesterol and triglyceride (TG) concentrations were determined in plasma and lipoprotein fractions using an Abaxis Piccolo Xpress Chemistry Analyzer (Thermo Fisher, Union City, NJ, USA) (30). Anthropometric Measurements Height, weight (11), and WC (27) were measured by trained health professionals according to standardized procedures; and body mass index (BMI) was calculated from weight and height. Individuals with a BMI between 18.5 and 24.9 kgImj2 are classified as having normal weight whereas individuals with a BMI ranging from 25 to 29.9 kgImj2 or Q30 kgImj2 are classified as overweight and obese, respectively (27). Body composition (fat and fat-free mass) was estimated by bioelectrical impedance (BIA) with the Tanita body composition analyzer TBF-300A (Arlington Heights, IL, USA).
Physical Activity and Nutritional Quality Physical activity index. The summary index of PA derived from the questions used in the EPIC study has been shown to be related to CVD risk (37). The validated short questionnaire estimated PA level at work and during leisure time for
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Prediction of Cardiovascular Risk To estimate the 10-yr cardiovascular risk, the Framingham risk score was calculated according to the adapted simplified model, using the weighted risk factors: age, gender, total
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adiposity and improve CMR (22), less evidence is available on the effectiveness of simple, low-cost interventions designed for the workplace and targeting abdominal adiposity and CRF. In the present pilot study, we tested the hypothesis that the assessment of WC and of CRF would be important and relevant clinical targets of a simple but comprehensive preventive approach based on peer support designed to improve the CMR profile.
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cholesterol, HDL cholesterol, smoking history, BP, and diabetes mellitus (39). Vascular age was calculated according to the definition of D’Agostino et al. (15). Submaximal Treadmill Test Cardiorespiratory fitness was assessed using a submaximal treadmill test according to a homemade protocol on a TMX 425 treadmill (Trackmaster, Newton, KS, USA) linked to a sphygmomanometer (Suntech Medical, Morrisville, NC, USA). Submaximal treadmill tests were administrated by trained kinesiologists specialized in exercise testing. The protocol began with a warm-up workload of 2.5 mph with a 0% slope followed by a standardized stage (3.5 mph, 2% slope). The third stage was adjusted in an attempt to reach 75% of the age-estimated maximal HR. If necessary, a fourth stage was performed. Participants’ HR was monitored using the Polar heart monitor system (QC, Canada) and was assessed at the standardized stage for the assessment of CRF. Estimated METs was predicted by extrapolation to age-predicted maximal HR (20). Statistical Analyses Data are presented as mean T SD in tables and as mean T SE in figures. The Shapiro-Wilk test was used to examine the distribution of each variable, and logarithmic transformations were applied to variables showing abnormal distribution. Paired t-tests were performed to compare baseline and post– 3-month intervention levels. Paired t-tests were also performed to compare baseline and after 3-mo intervention levels of anthropometric parameters and CMR markers in each subgroup, and a one-way ANOVA was performed to compare CMR profile between subgroups of changes in WC and CRF (see definition in the ‘‘Results’’ section). P G 0.05 was considered statistically significant. All statistical analyses were performed using the SAS statistical package version 9.2 (SAS Institute, Cary, NC, USA).
RESULTS Seven hundred eighty-seven workers, including 631 men and 156 women, participated in the 3-month friendly competition among teams of five workers to favor peer support in the adoption of healthier lifestyle habits. Baseline and post–3-month characteristics of employees are shown in Table 1. Among the 787 workers (mean age, 44.6 T 10 yr), 43% were overweight and 26% were obese, whereas 14.2% took hypolipidemic drugs, 11.6% took antihypertensive medications, and 3.6% reported to be treated for T2D. Furthermore, 25.4% of the workers did not know they had hypertension, although their resting BP was greater than 140/90 mm Hg. At baseline, men had higher BMI, WC, and TG levels, whereas HDL-cholesterol levels were lower compared to women (P G 0.05) (see Table, Supplemental Digital Content 1, Participants’ characteristics at baseline and post–3-month intervention period, http://links.lww.com/MSS/A456). Men also
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TABLE 1. Participants’ characteristics at baseline and after the 3-month intervention period. Baseline Sex (men/women) 631/156 Anthropometric measurements and body composition Weight, kg 82.6 T 15.9 27.5 T 4.5 BMI, kgImj2 Waist circumference, cm 96.3 T 12.6 Fat mass, kg 22.5 T 9.5 Fat-free mass, kg 60.0 T 10.1 Lipoprotein-lipid profile 4.70 T 0.87 Total cholesterol, mmolILj1 VLDL cholesterol, mmolILj1 0.83 T 0.41 j1 2.52 T 0.74 LDL cholesterol, mmolIL j1 1.29 T 0.32 HDL cholesterol, mmolIL Cholesterol/HDL cholesterol 3.84 T 1.17 j1 3.41 T 0.83 Non-HDL cholesterol, mmolIL j1 Triglycerides, mmolIL 2.00 T 1.15 5.99 T 1.24 Plasma glucose, mmolILj1 Nutritional quality index 60.6 T 12.8 Smokers/nonsmokers, n 104/682 Framingham risk score, % 5.5 T 4.6 Vascular age, yr 49.2 T 13.5
After 3 Mo
P
631/156 80.4 T 26.8 T 92.2 T 20.4 T 60.0 T
15.3 4.3 12.1 8.8 10.0
G0.0001 G0.0001 G0.0001 G0.0001 NS
4.47 T 0.81 0.71 T 0.39 2.40 T 0.66 1.32 T 0.32 3.54 T 0.94 3.14 T 0.75 1.65 T 0.99 5.83 T 1.01 69.9 T 11.8 41/731 4.5 T 3.8 46.7 T 13.1
G0.0001 G0.0001 G0.0001 G0.0001 G0.0001 G0.0001 G0.0001 G0.01 G0.0001 G0.0001 G0.0001 G0.0001
Values are presented as mean T SD. HDL cholesterol, high-density lipoprotein cholesterol; LDL cholesterol, low-density lipoprotein cholesterol; NS, not significant; VLDL cholesterol, very low-density lipoprotein cholesterol.
showed a higher estimated METs and a lower submaximal HR than women (P G 0.05) (see Table, Supplemental Digital Content 1, Participants’ characteristics at baseline and post–3month intervention period, http://links.lww.com/MSS/A456). After the 3-month intervention, participants decreased their BMI (¸ = j0.7 T 1.0 kgImj2, P G 0.0001), fat mass (¸ = j2.1 T 2.9 kg, P G 0.0001) and WC (¸ = j4.2 T 4.0 cm, P G 0.0001); whereas no change in fat-free mass was observed. VLDL cholesterol, LDL cholesterol, and TG levels, as well as the total cholesterol/HDL cholesterol ratio decreased; whereas HDL cholesterol concentrations increased (P G 0.0001). Men showed a greater reduction in their WC and TG levels than women and a greater increase in their HDL-cholesterol levels than their female counterparts (P G 0.05) (see Table, Supplemental Digital Content 1, Participants’ characteristics at baseline and post–3-month intervention period, http://links.lww.com/MSS/A456). The intervention also resulted in a significant 15% improvement in the NQI (P G 0.0001) assessed by questionnaire. The proportion of workers classified in the high-risk category of NQI was reduced by more than 60%, whereas the proportion in the low- and moderate-risk categories increased by 133% and 24%, respectively (Fig. 1A). Prevalence of workers considered sedentary (0 hIwkj1) and moderately inactive (90–3.5 hIwkj1) decreased by approximately 65% and 9%, respectively, whereas those considered moderately active (3.5–7 hIwkj1) and active (Q7 hIwkj1) increased by approximately 7% and 29%, respectively (data not shown). Analyses of the PA journal showed that workers performed a mean of 5.5 h of PA per week during the 3-month follow-up. PA level assessed by questionnaire increased in each subgroup compared to baseline values except for workers who were already active at baseline (Fig. 1B). More than 60% of smokers ceased smoking during the 3-month competition (Table 1). Workers who quit smoking did not gain weight and have significantly reduced their waist circumference
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FIGURE 1—A, Proportion of employees across various categories of nutritional quality index before and after the 3-month intervention. B, Reported physical activity level before and after the 3-month intervention according to the baseline PA status. ‡Significantly different from baseline; P G 0.0001.
(¸ = j3.4 T 3.6 cm, P G 0.0001). Active smokers and those who quit smoking similarly benefited from the program (see Table, Supplemental Digital Content 2, Impact of smoking cessation on participants’ cardiometabolic risk profile, http://links.lww.com/MSS/A457). After 3 months of healthier lifestyle habits, participants also significantly decreased their resting systolic (¸ = j6 T 11 mm Hg) and diastolic (¸ = j4 T 7 mm Hg) BP, as well as their resting HR (¸ = j2 T 10 bpm) (Fig. 2A) (P G 0.0001 for all). Ten participants began to take antihypertensive drugs during this 3-month period, whereas eight subjects stopped taking their antihypertensive drugs because their BP was substantially reduced. Cardiorespiratory fitness was also improved as reflected by reductions in submaximal HR (¸ = j4 T 10 bpm) and submaximal systolic (¸ = j6 T 17 mm Hg) and diastolic
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FIGURE 2—Systolic and diastolic BP and HR before and after the 3-month intervention (A) in the resting state and (B) measured at a standardized submaximal exercise (ex) workload (3.5 mph, 2% slope). ‡P G 0.0001.
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(¸ = j3 T 12 mm Hg) BP measured at a standardized treadmill workload (Fig. 2B) (P G 0.0001 for all variables). To investigate the respective contributions of changes in WC and CRF to the improvement of CMR profile, workers were classified into four subgroups according to change in WC (Gj1 or Qj1 cm) and the median of change in submaximal HR (Gj4 or Qj4 bpm): subgroup 1 (n = 287), reduction in WC and reduction in submaximal HR; subgroup 2 (n = 309), reduction in WC and increase in submaximal HR; subgroup 3 (n = 69), increase in WC and reduction in submaximal HR; and subgroup 4 (n = 72): increase in WC and increase in submaximal HR (Fig. 3). Figures 4 and 5 illustrate changes in CMR profile according to these four subgroups. Compared to workers in the other subgroups, workers who decreased both their WC (¸ = j5.7 T 3.5 cm) and submaximal HR (¸ = j12 T 6 bpm) showed the most important improvements in
CLINICAL SCIENCES FIGURE 3—Mean changes in WC and submaximal HR according to subgroups of employees classified based on the response of these two variables. Subgroup 1 (abdominal fat loss and improvement in fitness): reduction in WC and reduction in submaximal HR; subgroup 2 (abdominal fat loss and no improvement in fitness): reduction in WC and increase in submaximal HR; subgroup 3 (no abdominal fat loss and improvement in fitness): increase in WC and reduction in submaximal HR; and subgroup 4 (no abdominal fat loss and no improvement in fitness): increase in WC and increase in submaximal HR.
BMI (¸ = j1.0 T 1.0 kgImj2), TG (¸ = j0.53 T 0.99 mmolIL), and HDL cholesterol levels (¸ = 0.06 T 0.17 mmolIL) as well as in their NQI (¸ = 10.9 T 11.1) (P G 0.0001 for all variables). They also significantly decreased their non-HDL cholesterol (¸ = j0.32 T 0.49 mmolIL), their resting systolic (¸ = j6 T 11 mm Hg) and diastolic (¸ = j4 T 7 mm Hg) BP, their systolic (¸ = j12 T 16 mm Hg) and diastolic (¸ = j4 T 11 mm Hg) BP measured at a standardized submaximal treadmill workload (data not shown), their Framingham risk score (¸ = j1.4 T 3.4), their vascular age (¸ = j3.2 T 5.6), and improved their estimated METs (¸ = 1.43 T 2.70 METs) (P G 0.0001 for all variables). Workers who only reduced their WC improved their NQI (¸ = 9.0 T 11.1), but showed a small decrease in their CRF as expressed by changes in estimated METs reduction (¸ = j0.51 T 2.68 METs) (P G 0.01). However, they significantly reduced their BMI (¸ = j0.8 T 1.0 kgImj2) as well as their TG (¸ = j0.34 T 0.89 mmolIL) and non-HDL cholesterol levels (¸ = j0.29 T 0.54 mmolIL). They also lowered their resting systolic (¸ = j5 T 10 mm Hg) and diastolic (¸ = j4 T 6 mm Hg) BP, their Framingham risk score (¸ = j0.9 T 2.9), and their vascular age (¸ = j2.1 T 5.4) (P G 0.0001 for all variables). In the third subgroup, workers reduced their submaximal HR (¸ = j11 T 6 bpm) and increased their estimated METs (¸ = 1.28 T 2.62 METs) (P G 0.01 for all variables), whereas no change was observed in their WC (¸ = 0.6 T 1.5 cm, NS). An increase in NQI was also observed (¸ = 5.2 T 9.3) but to a lesser extent than in the two first subgroups. This subgroup also significantly reduced their resting systolic (¸ = j7 T 10 mm Hg) and diastolic (¸ = j3 T 5 mm Hg) BP, their systolic (¸ = j8 T 15 mm Hg) and diastolic (¸ = j6 T 12 mm Hg) BP
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measured at a standardized submaximal treadmill workload (data not shown) as well as their vascular age (¸ = j2.3 T 4.2), whereas no change was noted regarding the BMI nor for the lipid profile. Finally, workers who did not reduce neither their WC (¸ = 0.9 T 1.8 cm) nor their submaximal HR (¸ = 4 T 7 bpm) nevertheless improved their NQI (¸ = 5.6 T 9.1) and reduced their resting systolic (¸ = j5 T 10 mm Hg) and diastolic (¸ = j3 T 7 mm Hg) BP. This subgroup showed no significant change in the BMI, lipid profile, estimated METs, Framingham risk score, or in vascular age. However, workers in this subgroup were less abdominally obese (lower WC) and were more fit (higher CRF) at baseline than the other subgroups (see Table, Supplemental Digital Content 3, Participants’ characteristics at baseline according to the four subgroups of subjects classified on the basis of WC and CRF, http://links.lww.com/MSS/A458).
DISCUSSION In a cohort of 787 workers involved in a 3-month lifestyle modification program focusing on increased PA level, healthy eating, and smoking cessation, a high prevalence of physical inactivity as well as a low NQI was observed at baseline. Moreover, 13% of the population were active smokers. After the 3-month lifestyle modification, PA level and NQI increased and 60% of smokers ceased smoking. Our results showed significant improvements in adiposity variables as reflected by reductions in BMI, WC, and fat mass. The intervention also resulted in significant improvements in the plasma lipid profile and CRF. As revealed by our subgroup analysis, the magnitude of the response to the program varied depending on whether or not participants reduced their waistline or improved their CRF. Results showed that the subgroup of workers who reduced their WC and while also improving their CRF were those who improved the most their CMR profile. Furthermore, the subgroup who had the most deteriorated CMR profile at baseline was the one who benefited the most from this worksite intervention (see Table, Supplemental Digital Content 3, Participants’ characteristics at baseline according to the four subgroups of subjects classified on the basis of waist circumference and CRF, http://links.lww.com/MSS/A458), a finding which is fully consistent with our previous lifestyle interventions (14). In the current health care system, legitimate attention is given to the management of traditional CVD risk factors, such as dyslipidemia and hypertension. However, it is now recognized that there are risk factors that tend to cluster in patients, making them more susceptible to develop CVD. Therefore, it is essential to consider a comprehensive approach in the evaluation and management of CMR. Several imaging studies using measurements of abdominal adiposity have shown that excess visceral adipose tissue (VAT) is a driving factor behind the metabolic abnormalities observed in sedentary overweight/ obese patients, independent of total body fat (16,19). Lifestyle intervention studies have documented their beneficial effects on VAT mobilization and on improving the CMR profile,
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CLINICAL SCIENCES FIGURE 4—Adiposity and lipid profile changes according to the four subgroups of subjects classified on the basis of waist circumference and cardiorespiratory fitness changes. Subgroup 1, reduction in WC and reduction in submaximal HR; subgroup 2, reduction in WC and increase in submaximal HR; subgroup 3, increase in WC and reduction in submaximal HR; and subgroup 4, increase in WC and increase in submaximal HR. ‡Significantly different from baseline, P G 0.0001. 1, 2, and 3, Significantly different from the corresponding subgroups.
even in the absence of weight loss (31). Accordingly, results of the present study show that subgroups who reduced their WC (a relevant marker of abdominal adiposity) significantly improved their CMR profile, even in the absence of improved CRF. On the other hand, it is also well documented that a high CRF is associated with a lower risk of metabolic syndrome, coronary artery disease (CAD), and all-cause mortality (9). A large longitudinal study demonstrated that a low CRF in young adults was associated with the development of T2D, hypertension, metabolic syndrome, and CVD (12). While improving CRF is associated with beneficial effects on numerous cardiovascular risk factors, a high level of CRF also seems to provide additional protection from CVD mortality independent from these risk factors (8). Lifestyle modification programs, which are aimed at increasing PA, have shown to be effective to improve the CMR profile and CRF (6,9). In the present study, to classify the CRF response of our participants, we have selected to use the median of changes in HR measured at a standardized submaximal workload (3.5 mph, 2%
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slope), which corresponds to a decrease of 4 bpm. We have previously reported that such reduction in submaximal HR was quite sensitive to detect an improvement in CRF, as it was associated with significant improvements in several CMR factors in response to a 1-yr lifestyle intervention study (10,26). The present pilot project provides further evidences that a cheap, rapid, and inexpensive measurement of HR at a standardized submaximal workload is useful to assess and target CRF in clinical practice. Therefore, we believe that the results of the present pilot study support the notion that reducing WC and improving CRF through increased PA level and improved NQI are important clinical targets, in addition to the management of traditional cardiovascular risk factors. However, these important markers of behaviors are not often considered in most health evaluation and behavioral counseling is not consistently provided to patients (35). Furthermore, in the present study, 22% of the participants reported that they did not have a family physician, whereas 29% reported that they did not benefit from a regular
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CLINICAL SCIENCES FIGURE 5—Blood pressure (BP), estimated cardiovascular risk, estimated METs, and nutritional quality index changes according to the four subgroups of subjects classified on the basis of WC and CRF changes. Subgroup 1, reduction in WC and reduction in submaximal HR; subgroup 2, reduction in WC and increase in submaximal HR; subgroup 3, increase in WC and reduction in submaximal HR; and subgroup 4, increase in WC and increase in submaximal HR. †Significantly different from baseline, P G 0.01. ‡Significantly different from baseline, P G 0.0001. 1, 2, and 3, Significantly different from the corresponding subgroups.
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proof-of-concept study and was not designed to isolate the contribution of these variables. All subgroups examined seemed to benefit from the intervention. Although the magnitude of the response to the program was related to some of the baseline participants’ characteristics, all subgroups showed improvements in their CMR profile. Another and obviously important issue to address will be the long-term efficacy of such a lifestyle intervention approach. Since this pilot study was conducted over a 3-month period, long-term compliance and benefits remain unaddressed issues. As a final point, we consider that changes in outcome variables considered in the present study are clinically relevant. For instance, we report a robust reduction in resting and submaximal exercise BP, which is predictive of a decreased risk of CHD and stroke (13). The significant reduction in the proportion of subjects with hypertriglyceridemic waist from 35% to 23% suggests a reduction in the number of workers characterized by the high-risk visceral obesity phenotype (24). Finally, regarding the increase in HDL cholesterol, although Mendelian randomization studies have questioned its relevance as an isolated endpoint (21), we believe that an increased HDL-cholesterol concentration resulting from a lifestyle modification program is rather an integrated marker of improved insulin sensitivity and loss of visceral/ectopic fat resulting from regular exercise (4). In conclusion, results of the Grand De´fi Entreprise pilot study suggest that CRF and WC may represent important additional targets in the evaluation and prevention of CVD in the workplace. These two variables represent important clinical markers of behaviours, which should be further considered in health evaluation and management programs. Although each of these two factors independently contributed to the improvement in the CMR profile found in the present study, the combination of reduced WC and improved CRF generated the most substantial cardiometabolic benefits. Thus, the workplace has the potential to become an epicenter for CMR assessment and for the promotion of healthier lifestyle habits (eat better, move more, and quit smoking), through friendly in-house competition and peer support.
This study was partly supported by an unrestricted grant from Pfizer as well as by the Foundation of the Institut universitaire de cardiologie et de pneumologie de Que´bec. The project is the result of a consortium between the Grand De´fi Entreprise Inc. and the Institut universitaire de cardiologie et de pneumologie de Que´bec. Dr. Paul Poirier is a senior clinical scientist from the Fonds de recherche du Que´bec – Sante´ (FRQ-S). Vale´rie Le´vesque is supported by the training program in obesity, Canadian Institutes of Health Research (CIHR), Universite´ Laval. Dr. Jean-Pierre Despre´s is the Scientific Director of the International Chair on Cardiometabolic Risk, which is based at Universite´ Laval. Results of the present study do not constitute endorsement by the American College of Sports Medicine (ACSM). Conflicts of Interest and Source of Funding: This study was partly supported by an unrestricted grant from Pfizer as well as by the Foundation of the Institut universitaire de cardiologie et de pneumologie de Que´bec. The project is the result of a consortium between the Grand De´fi Entreprise Inc. and the Institut universitaire de cardiologie et de pneumologie de Que´bec. All authors declare that there are no conflicts of interest.
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yearly health examination. Although our pilot project only included a 3-month intervention, we hope that our results provide encouraging evidence that it is indeed possible to assess nutritional quality and PA in clinical practice. Furthermore, targeting abdominal obesity and CRF can be achieved at low cost and little time by measuring WC and using a submaximal exercise test. Previous studies have shown that the 5 A’s, the key elements of a health behavior change counseling, produce significant changes in health behavior such as smoking cessation, improvement in nutritional quality and PA habits, as well as successful weight management (23,29,38). Indeed, subjects who received 5 A’s counselling techniques were found to have higher level of motivation and intentions to change their behaviors. Considering that the workplace has a large influence on workers’ health, growing evidence supports that it could become a privileged environment to promote healthy lifestyle habits (1,3). For this purpose, a recent position paper from the American Heart Association has stated that conducting health screenings in the workplace is a promising strategy for the early detection of established CVD risk factors as putting in place health programs seems to positively influence workers’ health (2). Several workplace lifestyle intervention programs have shown that nutritional and PA programs are effective to improve nutritional quality, fitness, and weight management (32) as well as to improve quality of life and reduce behavioral symptoms (such depression, anxiety, etc.) (25). We have also recently shown that an increase in both nutritional quality and PA levels optimally reduced VAT in initially sedentary viscerally obese men (26). Results of the present study showed that workers who both reduced their WC and their submaximal HR through increased PA level and improved nutritional habits were those who showed the most substantial improvements in their CMR profile. These results highlight the importance of targeting both CRF and WC through regular PA/exercise and improving nutritional quality to improve the CMR profile. To facilitate the adoption of these healthy behaviors, companies should also provide permissive physical and social environments. Furthermore, we believe that support tools (website, diary recording, physical activities, and nutritional targets) and peer support within the company are also important factors to promote PA, healthy eating, and smoking cessation as well as to maintain a high level of motivation among employees. Our pilot study documented the feasibility and efficacy of improving CMR profile through a simple 3-month lifestyle modification intervention performed at the workplace. However, the present study was not randomized, and patients who agreed to participate in the study were motivated to change their lifestyle. Nevertheless, a fairly high percentage of workers who were approached (63.5%) volunteered to participate in this lifestyle modification program. Obviously, several confounding factors (sex, age, socioeconomic status, employee status, smoking or not, initial health, and risk factor status) could have possibly modulated participant’s response to the intervention. The present pilot project was a
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