C A N A D I A N F O R C E S M O R A L E A N D W E L F A R E S E R V I C E S

D I R E C T O R O F F I T N E S S

H U M A N P E R F O R M A N C E R E S E A R C H A N D D E V E L O P M E N T

TECHNICAL REPORT

ESTABLISHING THE RELATIONSHIP BETWEEN CARDIORESPIRATORY FITNESS

AND PERFORMANCE ON THE FORCE EVALUATION, AGE, SEX AND

ANTHROPOMETRICS

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Report prepared on July 12th, 2018 by

Jacqueline Laframboise, MSc CEP Senior Officer Human Performance

Barry Stockbrugger, MSc CEP Research Assistant/ Laboratory Coordinator

Evan Walsh, MSc CPT Research Assistant Human Performance

Reviewed by

Patrick Gagnon, MSc CEP Senior Manager Human Performance

Approved by

Daryl Allard, MA CEP Director of Fitness, Sports and Health Promotion

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ACKNOWLEDGEMENTS

The Directorate of Fitness (DFIT) research team would like to acknowledge all of the CAF volunteers

who participated in this research from 2014 -2016.

Many thanks for the members of the HQ research team who contributed to data collection namely Julie

Martin, Phil Newton, Kerry-Ann Dow, Tara Reilly, the PSP staff from CFSU(O) for collaborating on their

annual FORCE testing, and the PSP fitness staff from CFLRS, Jérémie Boileau, Samuel V.Côté, Marie-

Andrée Laroche and Caroline Boucher. The final phase of the 2016 data collection was possible with the

support of the PSP leadership at CFLRS, in particular Guillaume Leclerc who coordinated and recruited

the participants, and Marc-Andre Déry, who provided logistics support on site.

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Research Team

Senior Manager: Patrick Gagnon, MSc CEP

Senior Officer Research Jacqueline Laframboise, MSc CEP

Research Assistants

Research Support

Barry Stockbrugger, MSc CEP

Evan Walsh, MSc CPT

Kerry-Ann Dow, BSc CPT

Julie Martin, PhD

Phil Newton, MSc CEP

Tara Reilly, PhD CEP

Jérémie Boileau

Samuel V. Côté

Marie-Andrée Laroche

Caroline Boucher

Suggested format for citation of this document:

Laframboise JL, Walsh ES and B Stockbrugger. (2018). Establishing the relationship between cardiorespiratory fitness, and performance on the FORCE evaluation, age, sex and anthropometrics Technical Report: Department of National Defence, Assistant Deputy Minister (Science and Technology). Ottawa.

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TABLE OF CONTENTS

Acknowledgements ................................................................................................................................... 4

Table of Contents ...................................................................................................................................... 6

List of Tables .............................................................................................................................................. 8

List of Figures ............................................................................................................................................ 9

List of Acronyms ...................................................................................................................................... 10

Executive Summary ................................................................................................................................. 13

1 Background ................................................................................................................................. 16

1.1 Hypotheses ............................................................................................................................ 19

2 Review of Literature .................................................................................................................... 20

3 Methods ...................................................................................................................................... 22

3.1 Research Design .................................................................................................................... 22

3.2 Participants ........................................................................................................................... 22

3.3 Anthropometric measurements ........................................................................................... 23

3.4 Evaluation Protocol ............................................................................................................... 24

3.4.1 Day 1: Graded Exercise test (VO2max) ............................................................................ 24

3.4.2 Day 2: FORCE Evaluation Protocol .................................................................................. 26

3.5 Analyses ................................................................................................................................ 26

4 Results ......................................................................................................................................... 28

4.1 Participants ........................................................................................................................... 28

4.1.1 Demographics Compared to the CAF population ........................................................... 28

4.1.2 Performance Results - FORCE Evaluation and VO2max, and Participant Descriptive Characteristics ................................................................................................................. 29

4.2 Predicted VO2max - regressions............................................................................................ 32

4.2.1 Phase 1 - FORCE evaluation order: SBL, ILS, 20mR, SBD ................................................. 32

4.2.2 Phase 2 - FORCE evaluation order: 20mR, SBL, ILS, SBD ................................................. 33

4.2.3 Phase 1 compared to Phase 2 ......................................................................................... 38

5 Discussion .................................................................................................................................... 40

5.1 Accuracy and Quality of Regression Models ......................................................................... 40

5.2 Compared to literature ......................................................................................................... 42

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5.3 Cross Validation - Applicability to similar Sample................................................................. 43

5.4 Bland – ALtman Plots – Potential Bias in Prediction of VO2max .......................................... 44

5.5 Models applied to caf eFit data: ........................................................................................... 46

5.6 SUmmary of Model Selection: .............................................................................................. 49

5.7 FORCE as a Predictor for CRF ................................................................................................ 50

5.8 Limitations ............................................................................................................................. 51

5.9 Recommendations and Conclusions ..................................................................................... 52

6 References................................................................................................................................... 53

6.1 APPENDIX A - Recruitment Study Poster (2014-003) ........................................................... 57

6.2 APPENDIX B - Recruitment Study Poster (2016-011) ............................................................ 60

6.3 APPENDIX C - PARTICIPANT INFORMATION SHEET (2014-003) ............................................ 62

6.4 APPENDIX D - Participant Information Sheet (2016-011) ..................................................... 64

6.5 APPENDIX E - Preliminary Instructions to Participants ......................................................... 66

6.6 APPENDIX F - Informed Consent FORM 2014-003 ................................................................ 67

6.7 APPENDIX G - Informed Consent FORM 2016-011 ............................................................... 71

6.8 APPENDIX H - Physical Activity Readiness – Questionnaire.................................................. 76

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LIST OF TABLES

Table 1-1. High and low risk cut-offs for 40-60 years based on Kodoma (2009) and extrapolated for those under 40 years (Reilly, 2014). ...................................................................................... 17

Table 4-1. Phase 1 and 2 samples, and CAF (eFit entries) populations by five-year increments, separated by males (M) and females (F). ................................................................................... 29

Table 4-2. Mean, (standard deviation), and range for the four components of the FORCE evaluation, WC, relative VO2max, and anthropometrics of Phase 1 and 2 samples compared to the 2016-2017 fiscal year CAF - eFit population (where available). ..................... 30

Table 4-3. Means and (standard deviations) of Male 2016-2017 CAF FORCE evaluation performances in seconds, and WC in centimetres by 5-year age categories............................. 31

Table 4-4. Means and (standard deviations) of Female 2016-2017 CAF FORCE evaluation performances in seconds, and WC in centimetres by 5-year age categories............................. 31

Table 4-5. Phase 1 prediction of measured relative VO2max model summary. ..................................... 32

Table 4-6. Phase 1 linear regression model constants and prediction variable coefficients. ................ 32

Table 4-7. Phase 2 prediction of measured relative VO2max model summaries. .................................. 33

Table 4-8. Phase 2 linear regression model constants and prediction variable coefficients. ................ 35

Table 5-1. Means and 95% confidence intervals (mean ± 1.96SD) of male 2016-2017 CAF FORCE evaluation performances in seconds and WC in centimetres by 5-year age categories. ........... 46

Table 5-2. Predicted relative VO2max, in mL/kg/min of female 2016-2017 CAF FORCE evaluation performance and WC means and 95% confidence intervals by 5-year categories; with the absolute difference between models 1 and 2. ........................................................................... 48

Table 5-3. Field Variable Regression Model Summary Comparison ....................................................... 50

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LIST OF FIGURES

Figure 1-1. CAF Fitness Profile; Operational fitness (vertical axis) is based on performance of the 4 FORCE tasks, health-related fitness (horizontal axis) is calculated based on estimated cardiorespiratory fitness and WC. .............................................................................................. 16

Figure 4-1. Analysis 1 Predicted VO2max compared to Measured VO2max. .......................................... 34

Figure 4-2. Analysis 2 Predicted VO2max compared to Measured VO2max. .......................................... 35

Figure 4-3. Bland-Altman plot for regression analysis 1. ........................................................................ 37

Figure 4-4. Bland-Altman plot for regression analysis 2. ........................................................................ 37

Figure 4-5. Analysis 1 compared to Phase 1. .......................................................................................... 38

Figure 4-6. Analysis 2 compared to Phase 1. .......................................................................................... 39

Figure 5-1. Male (solid) and Female (dashed) 95% confidence intervals for the 2016-2017 eFit records (red) and Phase 2 sample (blue). ................................................................................... 44

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LIST OF ACRONYMS

ACSM American College of Sports Medicine

AED Artificial External Defibrillator

ANOVA Analysis of variance

BP Blood pressure

CAF Canadian Armed Forces

CEP Certified Exercise Physiologist

CF Canadian Forces

CFLRS Canadian Forces Leadership and Recruit School

CFMWS Canadian Forces Moral and Welfare Services

cm Centimeter

CO Commanding Officer

CO2 Carbon Dioxide

CPR Cardio-pulmonary Resuscitation

CRF Cardio-Respiratory Fitness

CSEP Canadian Society for Exercise Physiology

DAOD Defence Administrative Order and Directive

DAIP Directorate of Access to Information and Privacy

DRDC Defence Research and Development Canada

ECD Electrocardiogram

EXPRES Exercise Prescription

F Female

FORCE Fitness for Operational Requirements of CF Employment

GXT Graded exercise test

Ht Height

HR Heart Rate

HRM Heart Rate Monitor

HREC Human Research Ethics Committee

HPR&D Human Performance Research and Development

IAW In Accordance With

ID identification

ILS Intermittent loaded shuttle

LBM Lean Body Mass

kg Kilogram

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M Male

m Meter

mL Milliliter

mph Miles per hour

min Minute

NCR National Capital Region

O2 Oxygen

PAR-Q+ Physical Activity Readiness Questionnaire +

PATH Physical Activity Training for Health

PRESS Predicted Residual Sum of Squares

PSP Personnel Support Programs

QHCPs Qualified health care practitioners including medical doctors, nurse practitioners and physician assistants

QR&Os Queen’s Regulations & Orders

R Regression statistics

RP PRESS Statistics

R2 Coefficient of Determination

R2P Coefficient of Determination for Predicted Residual Sum of Squares

RBP Resting Blood Pressure

RER Respiratory exchange ratio

RHR Resting Heart Rate

RPE Rate of perceived exertion

SAD Sagittal abdominal diameter

SBD Sandbag drag

SBL Sandbag lift

SN Service Number

SEE Standard Error of Estimation

SEEP Standard Error of Estimation for Predicted Residual Sum of Squares

VO2peak Peak aerobic capacity

VO2max Maximal aerobic capacity

WC Waist Circumference

WHR Waist to hip ration

Wt Weight

20mR 20 meter rush

%SEM Percent Standard Error of Mean

% Percent

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EXECUTIVE SUMMARY

This research is novel such that it uses a test battery including the Fitness for Operational Requirements

of CAF Employment (FORCE) evaluation, sex, age and anthropometrics to accurately predict cardio-

respiratory fitness (CRF) in a sample of healthy adults aged 17-59 years (all models: R2 range 0.72-0.76;

SEE range 3.82-4.12mL/kg/min). There are no other studies that use a series of military tasks as a

physical employment standard to predict aerobic fitness.

To encourage Canadian Armed Forces (CAF) members to strive to achieve higher levels than the

minimum on the annual physical fitness evaluation, an incentive program – The Fitness Profile, has been

developed (Figure 1-1). In addition to the vertical axis, which reflects operational fitness as defined by

performance times on the FORCE evaluation, the Human Performance Research and Development

(HPR&D) team proposed the inclusion of a health-related component (horizontal axis) as a component

of this incentive program (Reilly, 2014). Using the relative maximum aerobic capacity (VO2max;

mL/kg/min) range cut-offs established through meta-analysis (Kodama, 2009), sex and age related cut-

offs were created to identify those individuals with elevated health risk based on CRF (Reilly, 2014).

These VO2max values were used in the development of the scoring of the horizontal axis of the Fitness

Profile.

Using performance results from the annual FORCE evaluation, non-invasive and easily measured tests

such as waist circumference (WC), height (Ht), weight (Wt) and lean body mass (LBM), as well as sex

and age, may provide an opportunity for estimating CRF without adding any additional components to

the current FORCE evaluation. Therefore, the purpose of this research was to determine the

relationship between CRF as measured by a maximal graded exercise test (GXT) and performance on

the FORCE evaluation, sex, age and various anthropometric measurements. The equation derived from

a preliminary - Phase 1 of this research, is currently used in the Fitness Profile calculator in dfit.ca,

available for use by all CAF members; the outcome of this Phase 2 will replace this equation.

One hundred and ninety-five male and female military members, 17-59 years of age, with a wide range

of fitness and anthropometric measurements, were recruited from the National Capital Region,

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garrison Petawawa, and the Canadian Forces Leadership and Recruit School (CFLRS). On two separate

testing days all participants performed 1) a maximal graded exercise treadmill test (GXT), and 2) a

maximum effort FORCE evaluation, defined as their best effort.

Linear regressions were run predicting the criterion of measured relative VO2max, using Stepwise and

Enter methods. The predictive ability of the models improved for each of the regression metrics with

the addition of more anthropometric data as shown in Table 4-7. Because all of the coefficients of

determination (R2) are above 0.72, they are classified as a large (>0.6) approaching very large (>0.8),

thus are considered reasonable predictions for estimating CRF (Hopkins, 2000). These regressions

yielded errors (%SEM) ranging from 8.4 to 9.1%, which fall within the 10% error range accepted for

predictive tests (McCardle, 1991).

Table 0-1. Phase 2 prediction of measured relative VO2max model summaries; WC, Ht, Wt, LBM; all

models include four components of the FORCE vealuation.

Analysis/

Models

Variable

Set

Regression

Method R

Adjusted

R2 SEE %SEM

Residual

SD Power

Adjusted

R2P SEEP

1 WC

Stepwise 0.850 0.718 4.118 9.1 4.086 0.66 0.711 4.159

2 Enter 0.855 0.720 4.102 9.0 4.027 0.50 0.705 4.200

3 WC, Ht,

& Wt

Stepwise 0.863 0.738 3.980 8.8 3.928 0.61 0.728 4.030

4 Enter 0.867 0.739 3.970 8.7 3.876 0.50 0.722 4.077

5 WC, Ht,

Wt, & LBM

Stepwise 0.875 0.759 3.816 8.4 3.767 0.67 0.752 3.854

6 Enter 0.876 0.755 3.848 8.5 3.747 0.51 0.740 3.940

Adjusted R2P and the SEEP were calculated for cross validation; these analyses assess the stability of the

regression model with a leave-one-out method of determining the average individual effect of

participants on the strength of the regression. The degree of ‘shrinkage’ of the prediction under this

method indicates the robustness of the model. All six models (Table 0-1) demonstrated minimal

shrinkage when compared to the original adjusted R2 and SEE, suggesting strength and quality of the

prediction when applied to similar populations.

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The focus of this research was on models 1 (Stepwise) and 2 (Enter), as currently only WC is measured

during the FORCE evaluation. The results for both the Enter and Stepwise models are essentially equal

and appropriate for adoptions. Regardless, whichever is chosen will require education to prevent

misunderstanding when used in conjunction with the online Fitness Profile calculator available on

dfit.ca. The practical difference between the two models is the inclusion of discordant coefficients

(highlighted in red in Table 4-8) for the Enter model (2) and the exclusion of three of the components

of FORCE for the Stepwise model (1) as shown in Table 4-8; both of which could affect the user

perception.

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1 BACKGROUND

On April 1, 2014 the Common Military Task Fitness Evaluation (CMTFE) was adopted as the new physical

fitness standard for the Canadian Armed Forces (CAF), predicting the ability to meet the Universality of

Service requirements for physical fitness. Due to the significant time and logistical requirements of

administration, the FORCE Evaluation was also introduced as the annual screening test that all members

perform annually to identify those potentially at risk of not being able to complete the CMTFE and meet

Universality of Service. To encourage CAF members to strive to achieve higher levels than the minimum

standard on the FORCE Evaluation, an incentive program – The Fitness Profile, has been developed

(Figure 1-1).

Figure 1-1. CAF Fitness Profile; Operational fitness (vertical axis) is based on performance of the four

FORCE tasks, health-related fitness (horizontal axis) is calculated based on estimated cardiorespiratory

fitness and WC.

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In addition to the vertical axis, which reflects FORCE performance, the Human Performance Research

and Development (HPR&D) team proposed the inclusion of a health-related component (horizontal

axis) to be included as a component of this incentive program (Reilly 2014). The strategy of developing

a health-based fitness profile grounded on health risk has already been adopted by the US Air Force,

the Royal (British) Air Force, and the US Army National Guard (Talbot 2009), who use aerobic fitness to

predict 10-year coronary heart disease risk. These standards are used as a motivational tool to reduce

coronary heart disease risk factors and to identify those with an increased risk for coronary events while

deployed. Using the VO2max (mL/kg/min) range cut-offs established through meta-analysis (Kodama,

2009), sex and age related cut-offs were created (Table 1-1) to identify those individuals with elevated

risk based on cardiorespiratory fitness (CRF) (Reilly, 2014). These values were used in the development

of the scoring on the horizontal axis of the Fitness Profile.

Table 1-1. High and low risk cut-offs for 40-60 years based on Kodoma (2009) and extrapolated for those

under 40 years (Reilly, 2014).

VO2max (mL/kg/min) Male Female

Risk Cut-off Age High Low High Low

15-20 38.1 48.6 31.5 41.7 20-25 36.4 46.9 29.4 39.9 25-30 34.6 45.1 27.6 38.1 30-35 32.9 43.4 25.9 36.4 35-40 31.1 41.6 24.1 34.6 40-45 29.4 39.9 22.4 32.9 45-50 27.6 38.1 20.6 31.1 50-55 25.9 36.4 18.9 29.4 55-60 24.1 34.6 17.1 27.6

Using performance results from the annual FORCE evaluation, when performed using maximum effort,

may provide an opportunity for estimating CRF without adding any additional components to the

current FORCE evaluation. In addition, because CAF members are familiar with the FORCE evaluation

which has been their annual evaluation since 2013, their performance should be reliable. The FORCE

evaluation has been shown to be reliable after three attempts (Stockbrugger, In Press). However, the

relationship between CRF and performance on the FORCE evaluation was not well understood as this

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evaluation requires a certain degree of CRF as well as muscular strength/endurance, mobility, speed

and agility across the four tasks, 20m rushes (20mR), sandbag lift (SBL), intermittent loaded shuttles

(ILS), sandbag drag (SBD), which may be above those required for the performance of a maximal aerobic

fitness test.

In addition to using the FORCE evaluation to estimate CRF, including non-invasive and easily measured

tests such as WC, Ht, Wt and body composition, as well as sex and age may also contribute to the

relationship. Therefore, the purpose of this research was to examine the relationship between

cardiorespiratory fitness, as measured by a maximal graded exercise test (GXT), and performance on

the FORCE evaluation, sex, age and various anthropometric measurements.

The following report presents two phases of the research that describes the ability to predict CRF using

the FORCE evaluation and anthropometrics. Based on the preliminary research approved in Phase 1:

HREC DRDC protocol 2014-003, performance results from the annual FORCE evaluation provided an

opportunity for estimating CRF without introducing any additional components to the current FORCE

evaluation; this provided the equation currently used in the Fitness Profile calculator in dfit.ca. In

addition, to limit the measurements taken during the annual fitness evaluation, it was decided that

because WC offered almost the same value to the prediction as Ht and Wt, and was already being

measured for its associate links to health risks, it could be used. However, while this research was in

process the order of the four tasks that make up the FORCE evaluation was changed. Internal research

demonstrated that the order of the four tasks that make up the FORCE evaluation has an effect on

performance for each task. Therefore, the relationship between FORCE and cardiorespiratory fitness

may be affected, thus the research was repeated as a Phase 2 HREC DRDC protocol 2016-018.

The results from this research should provide a validated prediction of CRF. This prediction can then be

used to establish an aerobic fitness score and be applied to the horizontal axis of the CAF Fitness Profile

which predicts member’s risk of all–cause mortality.

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1.1 HYPOTHESES

It was hypothesized that:

Cardiorespiratory fitness can be predicted by maximal performance on the FORCE evaluation in

combination with anthropometric measurements, age and sex.

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2 REVIEW OF LITERATURE

There is strong evidence that CRF is an important predictor of all-cause mortality (Kodama, 2009).

Similarly, ACSM recommends using CRF for stratifying cardiovascular risk (ACSM 2006). High levels of

fitness offered protection against all-cause and cardiovascular disease mortality in men in contrast to

those with low fitness, even if recommended physical activity/leisure time pursuits were followed in

the low fit individuals; differences in these two variables is likely attributable to the intensity of training

(Lee 2011, Sassen 2009). Furthermore, based on VO2peak levels, active 50-59 year old (average

VO2peak: 36.9±6.2 F, 46.7±8.4 M) had similar prevalence of cardiovascular risk clusters (based on

definition of metabolic syndrome: hypertension, WC, HDL cholesterol) as inactive 20-29 year olds

(average VO2peak: 36.7±7.7 F, 42±9.1 M) (Aspenes 2011). Peterson et al, determined that achieving 85-

100% of one’s recommended age predicted exercise capacity in terms of metabolic equivalents (METs)

was significantly associated with decreased risk of all-cause mortality (Peterson 2008).

Research over the last 20 years has established that CRF substantially attenuates or possibly eliminates

the mortality risk of obesity (Lee 2010, McAuley 2010, Lee 1999). Aspenes et al, demonstrated that the

cardiovascular risk factors of fit-fat (BMI>30) were no different than inactive-normal body weight

(BMI<25) suggesting a protective effect of CRF (Aspenes 2011). WC, used as a measure of body

composition (Wier 2006), and related to cardiovascular fitness (Ross 2003, Wong 2004), has also been

shown to be associated with the same diseases and disorders found in low fitness and obesity (Han

1996, Dobberlsteyn 2001). Furthermore, there is a protective effect of CRF on mortality, even

independent of other risk factors such as age, ethnicity, adiposity, smoking status, alcohol intake, and

health conditions (Lee 2010). A large study involving 4042 male and female participants demonstrated

that as you move from low to high levels of CRF as measured by direct graded exercise testing on a

treadmill and self-reported activity levels, the prevalence of negative levels of cardiovascular risk

factors (hypertension, high WC, BMI-obesity, hyperglycemia, total serum cholesterol, HDL-cholesterol)

decreases (Aspenes 2011). In fact, each 5 mL/kg/min lower VO2peak corresponded to a 54-58% increase

in cardiovascular risk factor clustering in men and women respectively (Aspenes 2011).

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Research, originating from the Cooper Institute, involving large longitudinal epidemiological studies,

indicates that it is as important for a clinician to assess a patients’ CRF as it is to measure other health

indicators such as fasting blood glucose, cholesterol level, blood pressure, or smoking (Wei 1999). Low

CRF is also a strong predictor of mortality with risk ratios (predicting morbidity or mortality) comparable

to, if not greater than, type II diabetes (Wei 1999). Evidence suggests that CRF is a very strong correlate

to health, even above weight, blood pressure and cholesterol (Blair 2009). In addition, the research

from the Copper Institute (Blair 1996) revealed that highly fit persons with multiple predictors of all-

cause mortality had lower death rates than low-fit persons who had no other predictors of all-cause

mortality.

It is well documented that there is a physiological decline in CRF fitness with age, although longitudinal

studies suggest that vigorous exercise can slow the rate of decline by as much as 50% (Zoeller 2008).

Cardiovascular (measured as VO2peak) fitness levels have been shown to decrease about 3.5 mL/kg/min

for each decade between the ages of 20 and 90 years of age (Loe 2013). In addition, sex differences in

cardiovascular system aging affect risk and disease progression, and may in fact be explained by

differences between the sexes in the system’s responsiveness (arterial vasculature, heart, autonomic

control of the circulation) to physical activity (Parker 2010). Therefore, the interaction between sex and

age on cardiovascular fitness affect health risk.

Cardiorespiratory fitness has been estimated in adults, using non-exercise models, including height

weight, age, waist circumference, BMI, %BF, LBM, thigh girth, and physical activity behavior yielding r

values as high as 0.93 (Wier 2006, Neto 2003, Bradshaw 2005). Anthropometric measurements have

been demonstrated as being relevant and significant for predicting CVF when used in multiple

regression analysis in these non-exercise models (Bradshaw 2005, Jackson 1990).

Aerobic capacity is commonly estimated in adults, using submaximal and maximal effort tests, such as

20m shuttle run, 1.5 mile run, 12 min run, Bruce treadmill test, with criterion-related validity of the

better predicting tests yielding values of 0.80 or greater (Mayorga-Vega 2016, Cooper 1968, Loe, 2016).

Furthermore, maximal tests tend to be more accurate than submaximal tests (ACSM, 2010, Astrand

2003).

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3 METHODS

3.1 RESEARCH DESIGN

The research protocols, 2014-003 and 2016-018, for this study were approved by the Defence Research

and Development Canada Human Ethics Committee. Recruitment was conducted in the National

Capital Region (NCR), garrison Petawawa and at Canadian Forces Leadership and Recruit School (CFLRS)

in St-Jean sur Richelieu, QC and only military participants were included in the research.

On two separate testing days all volunteers performed 1) a maximal graded exercise treadmill test

(GXT), and 2) a maximum effort FORCE Evaluation, defined as their best effort.

Day 1 included: project brief, consent form, health screening, anthropometrics and GXT. During the

2014 phase of research, on day 1, participants also performed a FORCE familiarization as FORCE was

still a relatively new test for them. For the second phase of research (2016) all participants were familiar

with the FORCE evaluation as it is now their annual physical fitness evaluation, thus did not require a

familiarization. Day 2 testing was completed within 2 weeks of day 1 and included performance of the

FORCE Evaluation. All testing sessions were completed at least with at least one day of active recovery

or rest prior to day 2 of testing (Boyd 2015).

3.2 PARTICIPANTS

With the approval of their Chain of Command, healthy male and female CAF members between the

ages of 18-59 were recruited from the CAF National capital region (NCR) population, garrison Petawawa

and from CFLRS by advertising with a recruitment ‘call for participants’ poster (Appendix A). An effort

was made to recruit 600 volunteers from all body types, ages, genders, and fitness levels based on

FORCE performance and cardiorespiratory fitness. Participants were provided with the participant

information sheet (Appendix B), preliminary instructions (Appendix C) and the consent form (Appendix

D). On day 1, after a research briefing outlining the requirements of the study, written, informed

consent was obtained from all participants prior to any additional screening.

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Participants were pre-screened using the PAR-Q+ (Appendix E) (Wartburton 2011). Based on the

information provided in the handouts and in the briefing regarding the risk to a fetus from maximal

physical exertion, pregnant females were asked to remove themselves from participation. During phase

1, protocol 2014-003, pregnant females were excluded from the study, as determined by self-

identification and/or medical screening prior to day 1. During Phase 2, females were not specifically

asked if they were pregnant, but as with all participants, they were asked through the PAR-Q+ screening

if there was any reason they should not participate; with the awareness of the risks to a fetus as per

the information provided prior to signing the consent form. Prior to testing, resting heart rate (RHR)

and resting blood pressure was conducted in accordance with CSEP-PATH (CSEP 2013) using a Multi-

Cuff Sphygmomanometer (AMG Medical Inc, Montreal, QC).

3.3 ANTHROPOMETRIC MEASUREMENTS

Once participants had been medically cleared the following anthropometric measurements were taken

on day 1.

Height was obtained using a Seca 213 Portable Stadiometer (Seca Industries, Hanover Maryland) and

weight using the InBody 520 (BioSpace Technologies, Los Angeles, California), as per protocol

http://www.statcan.gc.ca/imdb-bmdi/document/5071_D2_T1_V1-eng.pdf. The standing height was

recorded to the nearest 0.1cm while the breath is being held.

As used in the annual FORCE evaluation, waist circumference protocol was obtained as the participant

stands erect, in a relaxed manner, with feet shoulder width apart and arms crossed over chest in a

relaxed manner. The measure was taken directly on the skin. Landmarked at the top of the iliac crest,

with the tape positioned directly around the abdomen so that the inferior edge of the tape is at a level

of the landmarked point, in a horizontal plane around the abdomen. Sufficient tension to the tape was

maintained without causing indentation of the skin surface, and the participant was instructed to

breathe normally as the measure was read at the end of a normal expiration.

http://www.csep.ca/english/view.asp?x=724&id=84. The measurement was recorded to the nearest

0.5cm.

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Lean Body Mass, % body fat and mass were obtained using bioelectrical impedance - InBody 520

(BioSpace Technologies, Los Angeles, California) http://biospaceamerica.com/. As per protocol the

participant was instructed to remove his/her footwear and socks, any heavy accessories,

additional/heavy clothing and empty his/her pockets; to step on the center of the scale (on each foot

placement), with his/her hands at the side and look straight ahead. The participant was told to relax,

look straight ahead and not to speak for the duration of the test.

3.4 EVALUATION PROTOCOL

3.4.1 Day 1: Graded Exercise test (VO2max)

A Graded Exercise Test (GXT) was conducted to determine the individual’s VO2max and maximum heart

rate (HR). Expired gases were collected using the Parvo Medics True One 2400 (Parvo Medics Inc, Utah,

USA) metabolic measurement system. Oxygen (O2) and carbon dioxide (CO2) was analyzed using

paramagnetic O2 and infrared CO2 sensors (Parvo Medics Inc, Utah, USA). A Hans Rudolph two-way non-

re-breathing valve (Hans Rudolph Inc, Kansas, USA) and V2 facemask, and head support was fitted on

the participant. As well, a Polar Wear Link and coded transmitter (Polar Electro Canada Inc, Lachine,

QC) to monitor heart rate was fitted and secured around the chest beneath the participants’ nipple line,

next to the skin.

Prior to the start of the test, participants were permitted to familiarize themselves with treadmill

running by warming up for a period of five minutes. For the warm-up, participants were not hooked up

to the breathing apparatus but wore the Polar HR monitor. Participants began running on the treadmill

at a speed of 4.0 miles per hour (mph) and were gradually increased until they reached a comfortable

warm-up speed between 5.0 – 7.0 mph; warm-up speed as well as their HR response was used to

identify the starting speed for their GXT. During the five min recovery period, the participants were

hooked up to the breathing apparatus (i.e. facemask). The treadmill speeds for the tests were based on

the HR and running speed the participants attained during the warm-up period.

For participants that failed to attain 65% of their heart rate reserve, as defined as age predicted

maximum, or 208-0.7×age (Tanaka 2001), less measured resting heart rate, the test speed was

25

increased by 0.5 mph over their warm-up. Conversely, if the participants achieved over 80% of their

heart rate reserve during the warm-up, the test speed was decreased by 0.5 mph. Dependent upon the

participant’s previous running experience, the treadmill speed for the test was modified by the tester

in consultation with the participant.

For the first two minutes of the treadmill test, the initial grade was 0%. Thereafter, the treadmill incline

was increased by 2% every two minutes until a Respiratory Exchange Ratio (RER) of 1.00 is achieved.

When a RER value of 1.00 was achieved, the treadmill incline only increased by 1% every minute until

volitional fatigue, at which time the test was terminated. At the end of each two minute test increment,

up to when a RER value of 1.00 was achieved, the participants were requested to provide a rating of

their perceived exertion using a Borg Scale as Rate of Perceived Exertion (RPE). RPE has been found to

be a valuable and reliable indicator in monitoring an individual’s exercise tolerance. Perceived exertion

ratings correlate highly with measured exercise HR and were developed to allow the exerciser to

subjectively rate his/her feelings during exercise (ACSM 2010).

Every effort was made to conduct the test in a manner as to minimize discomfort and risk. Criteria for

the termination of the VO2max test was be as follows: (ACSM 2010)

onset of angina (chest pain) or angina-like symptoms;

signs of poor perfusion – light headedness, confusion, pallor (pale appearance to the skin),

cyanosis (bluish discoloration); ataxia (failure of muscular coordination), nausea, or cold and

clammy skin;

participant requests to stop;

volitional fatigue;

physical or verbal manifestations of severe fatigue;

failure of testing equipment;

shortness of breath, wheezing, leg cramps; or

failure of HR to increase with increased exercise intensity.

Various objective and subjective indicators were useful to confirm that maximal effort had been elicited

during the GXT. The following indicators were used to confirm VO2max (ACSM 2010):

failure of HR to increase with further increases in exercise intensity;

26

a plateau in oxygen uptake (or failure to increase oxygen uptake by 150 mL/min) with

increased workload;

a RER greater than 1.15; and

a RPE of more than 17 (6 to 20 scale).

3.4.2 Day 2: FORCE Evaluation Protocol

The testing sequence for the FORCE evaluation was:

Phase 1 (protocol 2014-003): SBL, ILS, 20mR, and SBD each separated by a 5 min rest period which

reflected the original research design order for the delivery of the FORCE evaluation as annual CAF

fitness evaluation. FORCE familiarization included performing the 4 FORCE tasks at no more than 50%

effort.

Phase 2 (protocol 2016-018): 20mR, SBL, ILS, and SBD each separated by a 5 min rest period which

reflects the current (post April 2016) delivery of the new FORCE evaluation as annual CAF fitness

evaluation.

Detailed methodology can be found here:

(https://www.cfmws.com/en/AboutUs/PSP/DFIT/Fitness/FORCEprogram/Documents/FORCE%20Oper

ations%20Manual%20EN_Jan%202015.pdf:

3.5 ANALYSES

The demographic, anthropometric, and performance data were characterized using descriptive

statistics. Where possible, the Phase 1 and Phase 2 samples were compared to the CAF population from

the 2015/2016 testing year.

Linear regression models predicting measured maximum aerobic capacity, as defined by VO2max

(mL/kg/min), were created with various combinations of the demographic, anthropometric, and

performance data as predictor variables using both Stepwise and Enter methods. All of the Stepwise

analyses used pin ≤ 0.05 and pout ≤ 0.10 as inclusion and exclusion criteria, respectively.

27

Bland-Altman plots were created from the criterion data and each of the predicted models. Microsoft

Excel was used to plot the mean difference between the measured and predicted VO2max against the

average of these 2 measures.

Predicted residual sum of squares (PRESS) analysis was used to estimate generalized error of our

models, and cross validate our results (Holiday 1995, Palmer 2009). PRESS is a method of leave-one-out

analysis which provides an estimate of the amount of error attributed to each individual when they are

not included in the calculation of a given model. Calculating PRESS (P) allows for the calculation of the

associated coefficient of determination (R2) PRESS (R2P) and standard error of the estimate (SEE) PRESS

(SEEP) which are used in the cross validation of models.

Data were analyzed using IBM SPSS 24 and Microsoft Excel. Graphical representations were created

with Microsoft Excel 2013.

28

4 RESULTS

4.1 PARTICIPANTS

This report includes the research from two phases of data collection, 2014 and 2016; the results will be

presented as Phase 1 (2014) and Phase 2 (2016). When possible, data from the CAF will be reported to

add perspective to the results; the intention of the research was to determine a regression model

predicting aerobic capacity that is applicable to the CAF population, thus draws from a similar subgroup.

Therefore, the goal was to recruit a diverse enough sample to obtain representation of the CAF across,

age, physical characteristics and performance.

For Phase 1, all 53 CAF members that volunteered were included in the analysis. For Phase 2, 199 CAF

members volunteered and 195 were included in the analysis. Of the 4 participants that were removed,

one was identified as an outlier as defined by a Z-score of over 5 for one of the FORCE evaluation

components. For the 3 other participants, there were issues with the VO2max data sets.

4.1.1 Demographics Compared to the CAF population

As of 13 June 2017, the overall strength of the Canadian Armed Forces was 98 710. Of that number, 64

661 were Regular Force, 54 959 males and 9701 females, and 34 049 were Reserve Force, 26 611 males

and 7437 females. One Regular Force and one Reserve Force member were of unidentified gender. For

the period of 01 April 2016 to 31 March 2017, 42 312 males and 6561 females had unique entries in the

eFit system; the electronic FORCE evaluation database. Phase 1 of this study included 37 males and 16

females, and Phase 2 included 138 males and 57 females. Table 4-1 documents the breakdown of Phase

1 and 2 samples, and CAF populations for five-year increments, separated by sex, as used in the fitness

profile. Phase 1 sample population ranged between 27 and 59, Phase 2 sample age ranged between 17

and 59. One of the participants from Phase 2 was a lower leg amputee and was therefore unable to

complete the bio-electrical impedance assessment for the body composition measures.

29

Table 4-1. Phase 1 and 2 samples, and CAF (eFit entries) populations by five-year increments,

separated by males (M) and females (F).

Age

Phase 1 2014 Phase 2 2016 CAF - eFitA

M F M F M F

≤ 20 0 0 11 0 1490 198

21-25 0 0 17 7 6494 866

26-30 6 2 24 7 8911 1293

31-35 8 6 22 9 7726 1256

36-40 3 1 12 11 6058 1139

41-45 6 1 16 6 4285 811

46-50 9 3 15 9 3637 600

51-55 4 2 13 8 2842 327

56-60 1 1 8B 0 869 71

Total 37 16 138 57 42 312 6561 A numbers are based on the age of the member on the date of their FORCE evaluation from the eFit

records for 01 April 2016 to 31 March 2017.

BN=7 for body composition measures.

4.1.2 Performance Results - FORCE Evaluation and VO2max, and Participant Descriptive Characteristics

Time in seconds for each of the four FORCE evaluation tasks (20mR, SBL, ILS, SBD) and WC in

centimeters were measured for Phases 1 and 2, and are shown in Table 4-2, separated by males and

females. These performances are compared to the eFit records for the 48 873 CAF members for the

2016-2017 fiscal year, also shown in Table 4-2.

Relative VO2max, as defined as the amount of oxygen consumed per kilogram of body mass every

minute, is reported in Table 4-2 for Phase 1 and 2, separated by males and females. No direct measures

of VO2max are available for the CAF population.

Height (cm), body mass (kg), and LBM (kg) were measured for each of the Phase 1 and Phase 2 study

participants, and are presented in Table 4-2, separated by males and females. Similar to aerobic

capacity, these anthropometric measures are not available for the CAF population.

30

Table 4-2. Mean, (standard deviation), and range for the four components of the FORCE evaluation,

WC, relative VO2max, and anthropometrics of Phase 1 and 2 samples compared to the 2016-2017 fiscal

year CAF - eFit population (where available).

Phase 1 2014 Phase 2 2016 CAF - eFit M F M F M F

20mR, s 39.6 (5.6) 46.1 (4.7) 36.5 (3.7) 42.4 (4.9) 37.7 (4.3) 42.5 (4.5)

31.8-58.0 39.0-53.1 29.7-46.7 34.9-55.2 23.0-73.9 29.0-89.7

SBL, s 62.2 (11.5) 93.1 (19.1) 61.2 (10.8) 89.2 (18.3) 69.0 (16.0) 98.1 (23.2)

42.3-87.3 64.0-143.3 43.8-98.3 56.3-145.8 36.1-197.2 48.5-213.4

ILS, s 163.4 (18.8) 209.2 (20.0) 168.7 (20.7) 195.5 (21.4) 184.7 (26.2) 208.4 (26.9)

134.6-203.0 172.2-246.6 129.8-226.8 138.9-250.5 112.9-357.7 134.3-316.9

SBD, s 16.1 (4.1) 26.7 (5.9) 14.3 (3.7) 22.7 (6.9) 16.3 (4.5) 27.2 (7.6)

10.8-29.7 18.0-38.7 8.9-28.6 14.5-48.4 6.1-98.1 10.5-70.7

WC, cm 90.7 (10.4) 88.3 (12.4) 90.5 (9.3) 86.7 (10.6) 95.0 (12.0) 85.1 (11.6)

71.0-122.5 67.0-105.5 69.0-118.0 67.0-120.0 63.5-162.0 59.0-146.0

VO2max, mL/kg/min

47.9 (7.4) 35.7 (4.7) 47.7 (7.0) 40.0 (6.6)

32.6-62.7 28.8-44.9 29.5-66.6 24.7-54.3

Height, cm 176.8 (6.3) 162.8 (5.1) 177.2 (7.8) 165.6 (6.5)

164.0-190.0 155.0-174.0 158.0-201.0 151.5-182.5 Body Mass, kg

84.1 (6.7) 73.4 (15.3) 83.1 (12.4) 68.6 (13.7) 58.2-109.8 45.7-108.5 53.5-114.0 49.0-110.2

LBM, kg 66.4 (7.4) 48.4 (5.7) 66.6 (8.0) 49.1 (6.5) 47.4-81.4 39.4-62.4 41.5-91.2 40.0-67.8

31

Table 4-3 and

Table 4-4 below, present the mean and standard deviation performance times and WC for the 2016-

2017 fiscal year CAF - eFit records separated by the 5-year age categories used in the vertical axis of the

FORCE profile. These data will be used in the discussion to compare regression model when applied to

the CAF Fitness Profile.

Table 4-3. Means and (standard deviations) of Male 2016-2017 CAF FORCE evaluation performances in

seconds, and WC in centimetres by 5-year age categories.

Age

≤ 20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55 <

20mR 35.3 (3.6)

35.6 (3.8)

36.5 (3.8)

37.4 (3.8)

38.3 (3.8)

39.5 (3.8)

40.7 (3.8)

41.9 (3.6)

43.2 (3.6)

SBL 61.9

(11.5) 62.5 (13)

65.9 (14.6)

68.5 (15.4)

70.9 (15.7)

73.1 (15.4)

77.1 (16.5)

81.2 (17)

86.4 (17.5)

ILS 170.7 (21.1)

175.6 (24.1)

180.5 (25.1)

184.6 (25.5)

187.5 (24.9)

191.4 (25)

196.6 (25.6)

201.1 (25.6)

207.7 (26.6)

SBD 15.8 (4.2)

15.1 (3.9)

15.4 (3.9)

15.9 (4)

16.5 (4.1)

17.3 (4.4)

18.2 (4.7)

19.6 (5.1)

21.3 (5.5)

WC 85.0 (9.6)

89.5 (10.6)

93.4 (11.5)

96.0 (11.5)

98.0 (11.5)

99.5 (11.2)

100.4 (10.6)

99.5 (9.9)

99.3 (9.7)

Table 4-4. Means and (standard deviations) of Female 2016-2017 CAF FORCE evaluation performances

in seconds, and WC in centimetres by 5-year age categories.

Age

≤ 20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55 <

20mR 40.0 (3.9)

40.3 (3.9)

41.2 (3.9)

42.0 (3.8)

42.9 (3.8)

44.1 (3.7)

45.2 (3.3)

45.9 (3.0)

46.9 (2.9)

SBL 88.4

(20.8) 89.8

(21.1) 94.6

(22.8) 95.8

(20.9) 100.1 (22.3)

104.5 (22)

109.7 (22.5)

114.2 (24.8)

125.5 (21.5)

ILS 194.8 (23.0)

200.3 (25.3)

203.5 (25.4)

204.9 (25.0)

210.7 (27.2)

216.8 (25.2)

222.7 (25.7)

227.5 (26.6)

233.9 (23.2)

SBD 24.8 (6.4)

24.8 (6.6)

25.6 (6.9)

26.5 (6.8)

28.0 (7.2)

28.6 (7.4)

30.6 (8.1)

32.3 (8.2)

36.6 (8.4)

WC 80.1 (9.4)

82.2 (10.7)

84 (11.4)

85.2 (11.4)

86.1 (11.9)

87.8 (11.9)

87.8 (11.3)

87.8 (11.3)

84 (10.3)

32

4.2 PREDICTED VO2MAX - REGRESSIONS

4.2.1 Phase 1 - FORCE evaluation order: SBL, ILS, 20mR, SBD

For Phase 1, a VO2max prediction formula was developed for use with the FORCE evaluation and eFit

system based on an Enter method linear regression model. Age, sex, WC, and the four timed

components of the FORCE evaluation (order: SBL, ILS, 20mR, SBD) were included as predictor variables,

as well as models of all combinations of FORCE components from single items, combinations of 2, and

3 components. The results are displayed in Table 4-5 as the regression statistic (R), the coefficient of

determination adjusted to the degrees of freedom based on the number of predictor variables included

in the regression analysis (Adjusted R2), the standard estimate of the error (SEE), the percent standard

error of the mean (%SEM), as defined by SEE divided by the mean measured VO2max, the standard

deviation of the residual error, the effect size, and the power of the analysis, calculated as 1 minus the

Type II error (β). Adjusted R2P and the SEEP are also included for comparison, and are discussed in

section 4.2.2.2 Cross Validation; where R2P = 1 – [PRESS/SStotal] and SEEP = [√𝑃𝑅𝐸𝑆𝑆 𝑛⁄ ].

Table 4-5. Phase 1 prediction of measured relative VO2max model summary.

R Adjusted

R2 SEE %SEM Residual

SD Effect Size Power

Adjusted R2

P SEEP

0.931 0.846 3.433 7.8 3.193 0.072 0.21 0.786 3.739

The linear regression analyses for Phase 1 created a predictive equation for maximum relative aerobic

capacity based on a constant and coefficients for each of the included predictor variables. These values

are reported in Table 4-6. The eFit system codes males as 0 and females as 1.

Table 4-6. Phase 1 linear regression model constants and prediction variable coefficients.

Constant Age WC 20mR SBL ILS SBD M=0 F=1

100.189 -0.125 -0.234 +0.018 +0.154 -0.218 -0.044 -7.305

However, as previously indicated in the rationale for a Phase 2 of this study, a change in the test

component order of the FORCE evaluation (new order: 20mR, SBL, ILS, SBD) was one of the factors that

triggered the re-evaluation of the relationship between the predictor variables and VO2max. More

33

importantly, Phase 2 provided an opportunity to increase the heterogeneity and size of the sample

fourfold resulting in an increased power of the prediction of the population to which it could be applied.

4.2.2 Phase 2 - FORCE evaluation order: 20mR, SBL, ILS, SBD

For Phase 2, a series of linear regressions were run predicting the criterion of measured relative

VO2max, using Stepwise and Enter methods. The Enter method was used to allow a direct comparison

to Phase 1, and the Stepwise was used as it will always include only the significant variables. All of the

Stepwise analyses in Phase 2 used variable inclusion criteria of pin≤0.05 and pout≤0.10 for subsequent

exclusion.

Predictor variables always included the current field measures of the four timed components of the

FORCE evaluation, as well as WC, sex and age. The combined anthropometric measures of Ht and Wt,

followed by lean body mass, were added in successive analyses in an attempt to improve the predictive

ability of the regressions; these variables are commonly collected in research and could potentially

increase the predictive capacity of the model.

Table 4-7, reports the regression statistics (R), the coefficients of determination adjusted to the degrees

of freedom based on the number of predictor variables included in the regression analysis (Adjusted

R2), the standard estimates of the errors (SEE), the percent standard errors of the mean (%SEM), as

defined by SEE divided by the mean measured VO2max [SEE VO2max̅̅ ̅̅ ̅̅ ̅̅ ̅̅ ̅⁄ ], the standard deviations of the

residual errors, the effect sizes; and the powers of the analyses, calculated as 1 minus the Type II error

[1 – β], according to the anthropometric predictor variable set and regression method. These analyses

are labelled as 1 through 6. Adjusted R2P and the SEEP are also included for comparison, and are

discussed in section 4.2.2.2 Cross Validation where R2P equals 1 minus the predicted residual sum of

squares divided by the sum of squares [1 – 𝑃𝑅𝐸𝑆𝑆 𝑆𝑆𝑡𝑜𝑡𝑎𝑙⁄ ] and SEEP is calculated as the square root

of the result of PRESS divided by the sample size [√𝑃𝑅𝐸𝑆𝑆 𝑛⁄ ].

Table 4-7. Phase 2 prediction of measured relative VO2max model summaries; all models included the

four components of FORCE as predictor variables.

Analysis Variable

Set Regression

Method R Adjusted

R2 SEE %SEM Residual

SD Effect Size Power

Adjusted R2

P SEEP

34

1 WC

Stepwise 0.850 0.718 4.118 9.1 4.086 0.042 0.66 0.711 4.159 2 Enter 0.855 0.720 4.102 9.0 4.027 0.043 0.50 0.705 4.200

3 WC, Ht, & Wt

Stepwise 0.863 0.738 3.980 8.8 3.928 0.047 0.61 0.728 4.030 4 Enter 0.867 0.739 3.970 8.7 3.876 0.047 0.50 0.722 4.077

5 WC, Ht, Wt, & LBM

Stepwise 0.875 0.759 3.816 8.4 3.767 0.052 0.67 0.752 3.854 6 Enter 0.876 0.755 3.848 8.5 3.747 0.051 0.51 0.740 3.940

The predictive ability of the models improved for each of the regression metrics with the addition of

more anthropometric data, but still accounted for approximately 72 percent of the variance in VO2max

using only the current field measures for both the Stepwise and Enter methods. Although, the Power

of the model was always higher for Stepwise as compared to Enter, as it included fewer variables. In

order to decrease the Type II error of the analyses to 5 percent and thus increase the Power to 95

percent, it was determined that the sample sizes would need to increase from the collected 195 to 410

for Analysis 1 and as many as 518 for Analysis 2.

As the purpose of the research was to validate the prediction of CRF to apply to the horizontal

component of the Fitness Profile, the focus of analysis is on models 1 and 2. The Stepwise model, or

Analysis 1, is represented in Figure 4-1 and the Enter model, or Analysis 2, in Figure 4-2. The Figures 3-

1, and 3-2 demonstrate how similar the yield of the analyses are.

Figure 4-1. Analysis 1 Predicted VO2max (from FORCE evaluation and WC) compared to Measured

VO2max, Adj R2=0.718.

0

15

30

45

60

75

0 15 30 45 60 75

Ph

ase

2 S

tep

wis

e P

red

icte

d (

FOR

CE

& W

C)

VO

2m

ax (

mL/

kg/m

in)

Measured VO2max (mL/kg/min)

35

Figure 4-2. Analysis 2 Predicted VO2max (from FORCE evaluation and WC) compared to Measured

VO2max, Adj R2=0.72.

Based on the linear regression analyses for Phase 2, Table 4-8 reports the criterion determination

equations as a constant and a set of variable coefficients for each of the predictors included in the

individual analyses. Each of the analyses using the Enter method for predictor variable selection

resulted in coefficients that are discordant. For example, a positive coefficient for SBL has the effect

that a longer time for this component of the FORCE evaluation results in a higher predicted VO2max.

These discordant coefficients are highlighted in red in Table 4-8.

Table 4-8. Phase 2 linear regression model constants and prediction variable coefficients.

Analysis Constant Age WC Height Weight LBM 20mR SBL ILS SBD M=0 F=1

1 105.238 -0.302 -0.179 -4.071 2 106.723 -0.039 -0.274 -0.126 0.049 -0.184 -0.007 -4.327

3 67.095 0.216 -0.268 -0.236 -0.158 -3.463 4 75.405 -0.044 -0.081 0.178 -0.206 -0.188 0.028 -0.164 -0.028 -3.887

5 83.708 -0.061 -0.424 0.409 -0.153 -2.469 6 81.637 -0.060 0.009 0.019 -0.430 0.397 -0.043 0.033 -0.156 -0.063 -2.576

0

15

30

45

60

75

0 15 30 45 60 75Ph

ase

2 E

nte

r P

red

icte

d (

FOR

CE

&

WC

) V

O2m

ax (

mL/

kg/m

in)

Measured VO2max (mL/kg/min)

36

4.2.2.1 Bland-Altman plots

Bland-Altman plots are used to graphically represent the point at which the greatest error occurs

between two measures, or in this case the worst predictions for a linear regression analysis. In other

words, this method helps identify if there is a bias in the model to under predict or over predict at any

range of VO2max. Bland Altman plots are shown for regression models 1 and 2 respectively in Figures

3-3 and 3-4. Because the prediction model to be applied to the Fitness Profile should be the one that

meets the greatest number of accuracy and application criterion, risk was also identified on these plots.

In Figure 4-3 and Figure 4-4, each entry that is not measured or predicted at a high cardiorespiratory

health risk (based on risk profiles Table 1-1) is shown as a blue dot ; three false negative entries that

were measured with a high risk but predicted as moderate risk are marked with yellow triangles ; one

false positive entry that measured as moderate risk but predicted as high risk is marked with a green

diamond ◊; and one that both measured and predicted as high risk is marked as a red cross X. Red

horizontal lines mark 1.96 standard deviations of the residual, creating a 95 percent confidence interval.

Both the Stepwise and Enter models resulted in the same ten individuals predicting outside the 95

percent confidence interval; half over predicted and half under predicted. In addition, both models had

a slight tendency to under predict at the high levels of VO2max.

37

Figure 4-3. Bland-Altman plot for regression analysis 1.

Figure 4-4. Bland-Altman plot for regression analysis 2.

4.2.2.2 Cross-Validation

To assess the stability of the regression models when applied to a similar but different sample, or the

degree of ‘shrinkage’ of the accuracy of the prediction, PRESS was calculated (Holiday 1995). PRESS is

recognized as an efficient method of cross validation, in particular when samples are smaller, although

-15

-10

-5

0

5

10

15

25 30 35 40 45 50 55 60 65

Mea

sure

d -

Pre

dic

ted

(V

O2m

ax)

½(Measured + Predicted VO2max)

-15

-10

-5

0

5

10

15

25 30 35 40 45 50 55 60 65

Mea

sure

d -

Pre

dic

ted

(V

O2m

ax)

½(Measured + Predicted VO2max)

Over predicted

Under predicted

Over predicted

Under predicted

38

some prefer it regardless of sample size (Holiday 1995, Palmer, 2009). As shown in Table 4-7, the cross

validation PRESS statistics (R2P and SEEP) for Phase 1 and all six Phase 2 models demonstrated minimal

shrinkage in the accuracy of the regressions models.

4.2.3 Phase 1 compared to Phase 2

To compare the predictive formulae for VO2max between the currently implemented Phase 1

regression model to the potential Stepwise and Enter method field options from Phase 2, correlations

were run between the Phase 1 and Phase 2 models. The coefficients of determination between the

Phase 1 model and the two Phase 2 models was 0.91 and 0.95, respectively. Figure 4-5 and Figure 4-6

illustrate the Phase 1-Phase 2 correlations graphically.

Figure 4-5. Analysis 1 compared to Phase 1.

R² = 0.9076

0

15

30

45

60

75

0 15 30 45 60 75Ph

ase

2 S

tep

wis

e P

red

icte

d V

O2m

ax

(mL/

kg/m

in)

Phase 1 Predicted VO2max (mL/kg/min)

39

Figure 4-6. Analysis 2 compared to Phase 1.

R² = 0.9464

0

15

30

45

60

75

0 15 30 45 60 75

Ph

ase

2 E

nte

r P

red

icte

d V

O2m

ax

(mL/

kg/m

in)

Phase 1 Predicted VO2 max(mL/kg/min)

40

5 DISCUSSION

5.1 ACCURACY AND QUALITY OF REGRESSION MODELS

This study is novel such that it uses a test battery such as the FORCE evaluation, sex, age and

anthropometrics to accurately predict CRF in a sample of healthy adults aged 17-59 years (all models;

Phase 2: R2 range 0.72-0.76; SEE range 3.82-4.12mL/kg/min). There are no other studies that we found

that use a series of movement and material handling tasks to predict aerobic fitness. Phase 2 of the

research study was undertaken to increase the sample size, and in part due to a change in the test order

of the four timed components of the FORCE evaluation as outlined by the release of the 2nd edition of

the FORCE Operations manual (CFMWS 2016). The relatively small sample of 37 males and 16 females

of Phase 1 had resulted in a strong adjusted coefficient of determination (R2) of approximately 85% and

an acceptable standard error of the estimate of 3.43 mL/kg/min (7.8%) or just below 1 MET. The sample

size in Phase 2 increased to 138 males and 57 females, or roughly four times the original study.

Interestingly, this increase in sample size resulted in a reduced predictive ability (R2) of the linear

regression models using the same predictor variables (20mR, SBL, ILS, SBD and WC) as Phase 1 to 72%

of the variance associated with VO2max and slightly increased the standard error of the estimate to just

over 4.1 for the SEE, or about 1.15 METs. However, when we look at the Power (Table 4-5) for Phase 1,

at 0.21 it is considerably lower than the 0.50 or 0.66 when using the same variables in Phase 2 (Table

4-7) indicating the models from Phase 2 may have a better ability to generalize to the CAF population.

The Phase 2 values for Power are in part due to the lower sample (195) than the required sample size

determined to be 410 and 518 based on post hoc power analyses (Table 4-7). Although, increasing the

sample size would increase the power, and likely improve the prediction slightly, decreasing the error

of the prediction, there would still be higher residuals for some of the sample; few people will be

predicted perfectly regardless of the sample size. Continued validation of this relationship could be

accomplished as a secondary purpose of future research.

Reflecting on the differences between VO2max prediction for Phase 1 and 2, the change that the

member will see when the new model is applied to their annual FORCE evaluation, should be

considered. Figures 4-5 and 4-6 showed that there is a very close relationship between the Phase 1

41

(Table 4-6) and Phase 2, models 1 and 2 (Table 4-8), as shown by the coefficient of determinations of

0.91 and 0.95 respectively, and thus there will not be much of a noticeable difference with either

regression models 1 or 2, if either of the new algorithms is implemented into the eFit system.

It is unclear as to why there is such a difference between Phase 1 and Phase 2 outcome. One possible

factor could simply be due to the change in the order of the testing sequence between Phase 1 and 2.

Reliability analysis of the FORCE evaluation demonstrated that there is an effect of order on

performance (CFMWS internal research), resulting in varying performances if one task came before

another; there is up to a 16% increase in component time (i.e. decreased performance) depending if a

task is performed first or last. In addition, as each individual has a different set of physical abilities that

make up their overall performance these strengths and weakness could affect their performances with

the order change.

Another possible reason could be due the subtle differences in the samples with regards to ranges of

performance measures (Table 4.2) for the FORCE components and VO2max. Similarly, although the 1.5

mile run and 20msr, both recognized as strong models for predicting CRF, have demonstrated high

validity coefficients (R=0.79-0.96) in numerous research papers (Mayorga-Vega, 2015, 2016) within

various populations, both of these tests demonstrated poor correlation coefficients of R=0.43 and 0.41,

respectively in a group of males as compared to the female group with correlation coefficients of R=0.86

for both tests. It was suggested that the variance of the range of VO2max could account for the

difference in R, as the male group was more homogeneous with a 15 mL/kg/min VO2max range than

the female group with a 26.3 mL/kg/min range (Grant 1999).

In contrast to Phase 2, in Phase 1 all of the testing was performed by one individual and in one location.

In Phase 2, four individuals performed the screening and anthropometrics; although they reviewed

testing protocols at the same time. The GXT were measured by three individuals all using the same

protocol and the same two metabolic measurement systems. Although standardization of drag

resistance is protocol, because the FORCE testing was performed in four different locations there is the

potential for different surfaces to offer more or less grip for turns at the 10m and 20m marks in the

20mR and ILS. In addition, in Phase 2, although the evaluator from Phase 1 was always present during

42

FORCE testing, and evaluators followed a standardized protocol, there were numerous evaluators

throughout the research as testing was performed at different locations, which introduces additional

inter-tester variability.

In Phase 2, as shown in Table 4-7: models 3 through 6, both R2 and the SEE improved with the inclusion

of height, weight and lean body mass as variables (R2 = 0.738-0.759 and SEE = 3.82-3.98), however one-

quarter of the VO2max variance is still undetermined. These three anthropometric variables (height,

weight and LBM) are not currently measured during the administration of the FORCE evaluation in the

field, although in a research setting where these simple measurements could be easily taken, they

would provide a more accurate model that just using WC.

5.2 COMPARED TO LITERATURE

There are no other studies that use a FORCE evaluation type model to predict aerobic fitness. Other

maximum indirect - field test models use cardiorespiratory exercise models (Mayaorga-Vega 2015,

Mayorga-Vega 2016, Loe 2016, George 2007, George 2017). The Cooper tests, a 1.5 mile run and the

12 min run, and the Leger 20m shuttle run are commonly used and reliable field tests that yield high

prediction accuracy in adults; 1.5 mile run: r = 0.79-0.90 (Grant 1999, George 1993, McNaughton 1998,

Zwiren 1991), 12 min run: r = 0.84-0.92 (Jorgensen 2009, Grant 1995, McNaughton 1998, Penry 2011),

and 20m shuttle run r = 0.79-0.90 (Leger 1982 1988 1989, Ramsbottom 1988, Grant 1995, Penry 2011,

McNaughton 1998). The predictive accuracy of these tests increases with the addition of other variables

such as age, and sex into the regression (Mayorga-Vega 2015, Mayorga-Vega 2016). The Bruce treadmill

Protocol is another indirect method of estimating CRF with an accuracy of r = 0.92, SEE = 3.1mL/kg/min

(Bruce 1973). In addition, equations have been developed for specific populations and sex, with more

accuracy for active individuals (r = 0.91-0.92 SEE = 2.27-3.35mL/kg/min) compared to cardiac patients

and elderly person (r = 0.82 SEE = 4.9mL/kg/min) (Heyward 2002). The Arizona State University (ASU)

maximal treadmill test, also yields strong predictive accuracy of CRF (r = 0.94, SEE = 3.18 mL/kg/min or

7.9% SEE) and uses age, sex, and BMI in the regression equation (George 2007). These tests all fall within

the 10% error range expected for predictive tests (Grant 1999, McKardle 1991). Likewise, the coefficient

of variation for the Phase 1 and 2 FORCE derived regressions yielded errors ranging from 7.8% (Table

43

4-5) and 8.4-9.1% (Table 4-7) respectively. Thus these models also fall within the 10% error range

accepted for predictive tests (McCardle 1991) with accuracy increasing with the addition of the height,

weight and LBM. In addition, in comparison to these maximal predictive models, using FORCE and other

variables is also classified as a large (>0.6) to very large (>0.8) relationship thus is considered a

reasonable prediction for estimating CRF (Hopkins, 2000). Although Astrand et al, suggest a correlation

(r) of 0.90 or greater is required for an accurate prediction of CRF (Astrand 2003).

5.3 CROSS VALIDATION - APPLICABILITY TO SIMILAR SAMPLE

It is important for this type of research to cross-validate results to evaluate how accurately the

regression equation can be applied in predicting criterion scores for a similar population. George et al,

cross validated their model of predicting VO2max (R = 0.94) using predicted residual sum of squares

(PRESS statistics), demonstrating a small decrease in predictive accuracy (RP = 0.93) (George 2007).

Holiday et al, suggest this analysis to be a preferred model over using split samples (Holiday 1995).

When applied to this research sample, the PRESS statistics used for cross validation for Phase 2 (Table

4-7) supports that all of these regressions equations should predict with reasonable accuracy when

applied to a similar population (R2 = 0.718 - 0.759 vs. R2P = 0.705-0.752). It is suggested that a difference

in the R2P statistics as compared to the R2 of less than 0.1 can be interpreted as being stable (Kleinbaum,

1988).

It is also important to use a research sample that reflects the population to which the equation will be

applied. Using the CAF eFit records as a tool for comparison, only the FORCE evaluation, age, gender,

and WC were available. In addition, because only half of the CAF members’ FORCE evaluations were

captured with the eFit system for the 2016-2017 fiscal year, a full comparison of populations to sample

is not possible. Table 4-2 shows how closely our sample and target population compare with respect to

these variables, looking at both the mean and the range for each variable. This information is used to

calculate 95% confidence intervals, defined as the mean ± 1.96 × standard deviation, for both the eFit

population and the Phase 2 sample; these intervals are displayed graphically in Figure 5-1, below, for

ease of reference. As with all research, participation is voluntary and thus it is difficult to capture an

exact match in particular when multiple variables are captured. The original target was to recruit 600

44

volunteers for Phase 2 and subsequently sample sizes needed for a Power of 0.95 were calculated to

be 410 and 518 for Analysis 1 and 2, however in the time frame allotted for data collection, only 195

were recruited. It is assumed that if the sample size was increased, that the variable distributions would

even more closely represent the known population.

Figure 5-1. Male (solid) and Female (dashed) 95% confidence intervals for the 2016-2017 eFit records

(red) and Phase 2 sample (blue).

5.4 BLAND – ALTMAN PLOTS – POTENTIAL BIAS IN PREDICTION OF VO2MAX

Bland Altman plots have been used to look at potential bias in the predicted VO2max when using the

12 min Cooper run favouring the most aerobically fit (Penry, 2011). Similarly, when plots were created

for Phase 2 regression models 1 (Enter) and 2 (Stepwise) (Figures 4-3 and 4-4), they both demonstrated

there was a slight tendency to underestimate the more aerobically fit. However, both models also

0 50 100 150

Circumference, cm

Population Sample

WC

0 50 100 150 200 250 300

Time, s

20mR

SBL

ILS

SBD

45

predicted the same 10 individuals outside of the 95% confidence interval, thus over or under-predicting

equally. Within the 195 participant sample, four measured VO2max were low enough to be considered

a high health risk according to thresholds presented in Table 1-1 (Kodoma 2009, Reilly 2014). Both the

Stepwise and Enter analyses using the Phase 2 field measures resulted in false negatives for three of

these four cases, predicting VO2max values high enough to result in moderate risk assessments. These

are marked as yellow triangles in the Bland-Altman plots in Figure 4-3 and Figure 4-4. The fourth high

risk individual was properly predicted and marked as a red cross. Additionally, one case created a false

positive result for both analyses, as shown by a green diamond in plots, where a measured moderate

risk individual predicted as high risk based on the two equations. As both models resulted in the equal

false negatives and false positives, this assessment did not distinguish between the applicability of the

two models. These similarities, suggest that neither model is better than the other with regards to this

measure of accuracy.

46

5.5 MODELS APPLIED TO CAF EFIT DATA:

The following section provides insight into the differences with how these models behave when applied

to the CAF. A 95 percent confidence interval envelope was created for each of the age categories of

male and female performances on the FORCE evaluation applied to the eFit records between 01 April

2016 and 31 March 2017 (Table 4-3 and Table 4-4); the mean and 1.96 times the standard deviations

are calculated from male and female CAF. The resulting representative performance times and WC are

presented in Table 5-1 and Table 5-2 for men and women, respectively and provide a snapshot of 95%

of the CAF.

Table 5-1. Means and 95% confidence intervals (mean ± 1.96SD) of male 2016-2017 CAF FORCE

evaluation performances in seconds and WC in centimetres by 5-year age categories.

Age

≤ 20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55 <

20mR

Fast 28.2 28.2 29.1 30.0 30.9 32.0 33.3 34.9 36.1

Mean 35.3 35.6 36.5 37.4 38.3 39.5 40.7 41.9 43.2

Slow 42.4 42.9 44.0 44.8 45.8 46.9 48.1 49.0 50.3

SBL

Fast 39.4 37.0 37.3 38.4 40.1 43.0 44.7 47.9 52.0

Mean 61.9 62.5 65.9 68.5 70.9 73.1 77.1 81.2 86.4

Slow 84.4 88.0 94.6 98.6 101.7 103.3 109.5 114.6 120.8

ILS

Fast 129.4 128.4 131.3 134.6 138.7 142.4 146.4 150.9 155.5

Mean 170.7 175.6 180.5 184.6 187.5 191.4 196.6 201.1 207.7

Slow 212.0 222.8 229.7 234.6 236.3 240.4 246.7 251.3 259.9

SBD

Fast 7.6 7.5 7.7 8.0 8.4 8.7 9.0 9.6 10.4

Mean 15.8 15.1 15.4 15.9 16.5 17.3 18.2 19.6 21.3

Slow 24.0 22.7 23.0 23.8 24.6 26.0 27.4 29.5 32.1

WC

Small 66.1 68.7 70.8 73.4 75.5 77.5 79.7 80.2 80.2

Mean 85.0 89.5 93.4 96.0 98.0 99.5 100.4 99.5 99.3

Large 103.8 110.4 116.0 118.6 120.5 121.5 121.1 118.9 118.3

47

Table 5-2. Means and 95% confidence intervals (mean ± 1.96SD) of female 2016-2017 CAF FORCE

evaluation performances in seconds and WC in centimetres by 5-year age categories.

Age

≤ 20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55 <

20mR

Fast 32.3 32.6 33.6 34.6 35.5 36.9 38.7 40.1 41.3

Mean 40.0 40.3 41.2 42.0 42.9 44.1 45.2 45.9 46.9

Slow 47.7 48.0 48.9 49.4 50.4 51.4A 51.7A 51.7A 52.5A

SBL

Fast 47.5 48.4 49.8 54.7 56.4 61.3 65.7 65.6 83.5

Mean 88.4 89.8 94.6 95.8 100.1 104.5 109.7 114.2 125.5

Slow 129.2 131.2 139.4 136.8 143.8 147.6 153.8 162.7 167.6

ILS

Fast 149.6 150.6 153.7 155.8 157.5 167.3 172.3 175.4 188.6

Mean 194.8 200.3 203.5 204.9 210.7 216.8 222.7 227.5 233.9

Slow 239.9 249.9 253.3 254.0 264.0 266.2 273.1 279.6 279.3

SBD

Fast 12.1 11.9 12.2 13.2 13.8 14.2 14.7 16.3 20.1

Mean 24.8 24.8 25.6 26.5 28.0 28.6 30.6 32.3 36.6

Slow 37.4 37.7 39.1 39.7 42.3 43.1 46.6 48.4 53.1

WC

Small 61.7 61.1 61.7 62.9 62.7 64.4 65.7 65.6 63.8

Mean 80.1 82.2 84.0 85.2 86.1 87.8 87.8 87.8 84.0

Large 98.5 103.2 106.3 107.6 109.4 111.2 110.0 110.0 104.2 A constitutes a failure according to the 51s standard for the 20mR.

These fast, mean, and slow (performances) and small, mean, and large (WC) measurements for each

age and sex category were applied to the linear regression models (1 and 2) as analyses 1 and 2 in Table

4-8. The resultant predicted VO2max are reported in Table 5-3 and 5-4.

48

Table 5-3. Predicted relative VO2max, in mL/kg/min of male 2016-2017 CAF FORCE evaluation

performance and WC means and 95% confidence intervals by 5-year categories; with the absolute

difference between models 1 and 2.

Age

Analysis ≤ 20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55 <

1

High 62.1 61.5 60.3 59.0 57.6 56.4 55.0 54.0 53.2

Mean 49.0 46.8 44.7 43.2 42.1 40.9 39.7 39.2 38.1

Low 36.0 32.0 29.1 27.4 26.6 25.5 24.5 24.3 23.0

2

High 62.4 61.5 60.1 58.5 57.0 55.6 53.9 52.8 51.7

Mean 49.8 47.4 45.3 43.6 42.3 41.0 39.6 38.9 37.6

Low 37.1 33.2 30.4 28.7 27.7 26.4 25.3 25.0 23.5

Absolute Difference

High 0.3 0.0 0.2 0.5 0.6 0.8 1.1 1.2 1.5

Mean 0.8 0.6 0.6 0.4 0.2 0.1 0.1 0.3 0.5

Low 1.1 1.2 1.3 1.3 1.1 0.9 0.8 0.7 0.5

Table 5-2. Predicted relative VO2max, in mL/kg/min of female 2016-2017 CAF FORCE evaluation

performance and WC means and 95% confidence intervals by 5-year categories; with the absolute

difference between models 1 and 2.

Age

Analysis ≤ 20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55 <

1

High 55.8 55.8 55.0 54.3 54.0 51.8 50.5 50.0 48.1

Mean 42.1 40.5 39.4 38.8 37.5 35.8 34.8 33.9 33.9

Low 28.5 25.2 23.7 23.2 20.9 19.9 19.1 17.9 19.7

2

High 55.4 55.2 54.2 53.4 52.9 50.5 49.0 48.1 46.6

Mean 43.0 41.2 40.0 39.2 37.8 36.1 34.9 33.9 34.0

Low 30.6 27.2 25.9 25.0 22.7 21.6 20.7 19.8 21.3

Absolute Difference

High 0.4 0.6 0.8 0.9 1.1 1.3 1.5 1.9 1.5

Mean 0.9 0.7 0.6 0.4 0.3 0.3 0.1 0.0 0.1

Low 2.1 2.0 2.2 1.8 1.8 1.7 1.6 1.9 1.6

In general, the VO2max predictions from equations 1 and 2 are slightly more divergent for the female

CAF population than for the male as shown by the larger absolute differences. Mean differences across

all age and performance categories between the two predictive equations are 0.7 and 1.1 mL/kg/min

of oxygen consumption for men and women. However, the largest predictive range for any one age,

gender, and performance category is still only 2.2 mL/kg/min, which occurs for the low performance

range females between 25 and 30 years of age. Although, mean performers at this age category display

49

the same variance for both men and women at 0.6 mL/kg/min. There appears to be no pattern with

respect to which prediction is higher or lower between age categories or gender, for either linear

regression model. Therefore, when applied to the CAF FORCE records and WC, the models offer very

similar results and no obvious reason for selection of one over the other. These predictive values are

for the situation where all five components (20mR, SBL, ILS SBD times and WC) are either all at the

average, all at the 2.5%ile or 97.5%ile performances. They do not account for a situation where

performances may vary across the components which would be more of the norm for real

performances.

Of possible interest is that the eFit system entry counts of 42 312 and 6561 reported in Table 4-1 only

account for approximately three-quarters of male and two-thirds of female Regular Force members for

that period. This indicates that a substantial portion of the CAF population did not complete the FORCE

evaluation with this system and, as it is unlikely that many Regular Force members completed the

evaluation using a paper DND 279 form during this period, there is a large group that must not have

had a valid FORCE evaluation as of 31 March 2017. These lowered eFit system counts may have altered

the means and standard deviations for this analysis compared to the true representation of the CAF

Regular Force potentially affecting any observed differences between models.

5.6 SUMMARY OF MODEL SELECTION:

At this point, both Phase 2 models 1 (Enter) and 2 (Stepwise) predictive formulae present similar

accuracy. As summarized in Table 5-5, neither of the Enter or Stepwise models is vastly superior to the

other based on the adjusted coefficient of determination (R2), standard error of the estimate (SEE), or

any other predictive metric other than Power, as reported in Table 4-7. In addition, there is no

noteworthy difference between the Bland-Altman plots for the two models presented in Figure 4-3 and

Figure 4-4. Therefore, model selection for use with the FORCE evaluation is not necessarily limited by

predictive ability and both are appropriate for implementation. Importantly, if continued validation of

the predictive model is to occur a smaller sample is required for Stepwise compared to Enter (410 vs.

518), to increase the Power to 0.95, and reduce type II error to 5%.

50

Table 5-3. Field Variable Regression Model Summary Comparison

Metric Stepwise Enter Advantage

Adjusted Coefficient of Variation (R2) 0.718 0.720 None

Standard Error of the Estimate (SEE) 4.118 4.102 None

Percent Standard Error of the Mean (%SEE) 9.1% 9.0% None

Residual Standard Deviation 4.086 4.027 None

Effect Size 0.042 0.043 None

Power 0.66 0.50 Stepwise

Required Sample Size 410 518 Stepwise

Cross-Validation (R2P) 0.711 0.705 None

Discordant Coefficients No Yes Stepwise

All FORCE Components No Yes Enter

False Positives CRF Risk 1 1 None

False Negatives CRF Risk 3 3 None

A practical difference between the two models is the inclusion of discordant coefficients (highlighted

in red in Table 4-8) for the Enter model (2) and the exclusion of three of the components of FORCE for

the Stepwise model (1) as shown in Table 4-8; both of which could affect the user perception of the

online dfit.ca Fitness Profile calculator.

5.7 FORCE AS A PREDICTOR FOR CRF

Mechanical efficiency, intensive training and motivation are important factors for accurately predicting

CRF in maximal effort field tests, and thus a high CRF does not guarantee the best performance (Astrand

2003). Similar to the influence that components of fitness (beyond CRF) such as, muscular endurance

and strength, and mobility play in the FORCE evaluation, running efficiency, pacing awareness and

agility are factors for tests such as the 20m shuttle run and the Cooper run tests. Thus, field tests should

be appropriately selected based on the demands of the job, sport or fitness level, of the population

being evaluated. It has been suggested that underestimations of VO2max may be explained in the 12min

Cooper run test due to inexperienced runners having difficulty finding optimal speeds (Jorgensen 2009,

Penry 2011). Similarly, potential sources of variance for the 20m shuttle run could be the efficiency of

turning at the end points (agility) and the ability to accelerate (anaerobic power) during the 20m shuttle

run causing underestimation of VO2max (Grant 1995, Grant 1999, Penry 2011).

51

As the FORCE evaluation is the proxy for the CMTFE, and CAF members have been tested annually on

the FORCE evaluation since 2013, with support from dfit.ca and base/wing PSP staff, the physical

demands of the tests beyond CRF should be considered familiar and appropriate for this group. It is

recognized that if an individual does not train appropriately or does not have a balance of fitness, the

other fitness variables will likely affect their performance and consequently, the prediction of VO2max.

Although, the results were not analysed in this report for the following purpose, it would be worthwhile

to evaluate if individuals that perform more consistently across the four FORCE tasks have a better

VO2max prediction, suggesting a more balanced fitness. In addition, further research into the changes

in the accuracy of the VO2max prediction while monitoring the changes in performance across the 4

FORCE tasks, while following fitness training reflecting best practices, might offer validation of some of

the variance in the prediction; which could be used in the communication with the CAF members. In

addition, with the implementation of the Incentive program/Fitness Profile anticipated for September

2018, it is expected that CAF members will be motivated to score as high as possible on the vertical

scale of the Fitness Profile (Figure 1-2), which is reflective of only their FORCE performance.

5.8 LIMITATIONS

It is important to recognize the limitations of this research when interpreting the results.

Unlike a simple indirect maximal test such as the 1.5 mile run, different strategies may be used to

complete each of the four components of the FORCE test. The assumption is that participants will exert

a maximal effort across each test in the same way, therefore if different strategies are used to complete

the four tasks of the FORCE evaluation the relationship may not be as accurate.

As indicated in the comparison of the CAF population and our sample, it is recognized that the full range

of performances and physical characteristics was not captured. This increases the risks of error in the

prediction of VO2max as the groups are not the same.

52

5.9 RECOMMENDATIONS AND CONCLUSIONS

The purpose of this research was to identify a regression equation for the prediction of VO2max to be

used for the calculation of the horizontal axis of the Fitness Profile (Figure 1-1). As both Enter and

Stepwise models are essentially equal and appropriate for implementation, it seems that whichever is

chosen will require education for the user when used in conjunction with the online calculator to

prevent misunderstanding. It is also necessary to determine if the level of uncertainty identified with

this research is acceptable and how to minimize the risk of incorrect Fitness Profile placement with

respect to the high health risk amber zone. Also important to consider, if an individual scores vertically

into the incentive program on the Fitness Profile (bronze, silver, gold, or platinum) inaccurate horizontal

scoring could remove them from an the incentive program and any associated career benefits. Once

the vertical scoring is re-calculated to reflect the up to date FORCE performance of the CAF, then the

effect of horizontal scoring on the Fitness Profile can be assessed. It will be important to determine how

the revised scoring accurately predicts those identified as “at risk” (in the amber) or very close to the

amber, to ensure they are appropriately supported.

A supplement will follow this report, reporting on a gender-based analysis to determine the feasibility

of removing sex as a variable.

53

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21. Holiday, DB, Ballard, JE, McKeown, BC. (1995). PRESS-related statistics: regression tools for cross-validation and case diagnostics. Med Sci Sports Exerc, 27(4): 612-20.

22. Hopkins, W. G. (2000). A new view of statistics. Internet Society for Sport Science: http://www.sportsci.org/resource/stats/.

23. Jackson, A.S., Blair, S.N., Mahar, M.T., Weir, L.T., Rossand, R.M. and J.E. Stuteville. (1990). Prediction of functional aerobic capacity without exercise testing. Medicine Science Sports Exercise, 22(6): 863-870.

24. Jorgensen T, Andersen LB, Froberg K, Maeder U , von Huth Smith L and M Aadahl. (2009) Position statement: Testing physical condition in a population – how good are the methods? Eur J Sp Sc, 9(5): 257-267.

25. Kleinbaum, D.G., Kupper, L.L. and Muller, K.E. (1988) Variable Reduction and Factor Analysis. Applied Regression Analysis and Other Multivariable Methods. PWS Kent Publishing Co., Boston, 595-640

26. Kodama, S., Saito, K., Tanaka, S., Maki, M., Yachi, Y., Asumi, M., Sugawara, A., Totsucka, K., Shimano, H., Ohashi, Y., Yamanda, N., Sone, H.(2009) Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA. May 20;301(19):2024-35.

27. Lee, C. D., Artero, E. G., Sui, X., & Blair, S. N. (2010). Mortality trends in the general population: The importance of cardiorespiratory fitness. Journal of Psychopharmacology (Oxford, England), 24(4 Suppl), 27-35.

28. Lee, C. D., Blair, S. N., & Jackson, A. S. (1999). Cardiorespiratory fitness, body composition, and all-cause and cardiovascular disease mortality in men. The American Journal of Clinical Nutrition, 69(3), 373-380.

29. Lee, C. D., Xuemei, S., Enrique G. A., Lee, I., Church, T., McAuley, P.A., Stanford, F.C., Kohl, H.W., and Blair, S.N. (2011). Long-Term Effects of Changes in Cardiorespiratory Fitness and Body Mass Index on All-Cause and Cardiovascular Disease Mortality in Men: The Aerobics Center Longitudinal Study. Circulation, 124(23): 2483–2490.

30. Leger, LA., and J Lambert (1982). A maximal multistage 20m shuttle run test to predict VO2max. Eur J Appl Physiol. 49(1):1-12.

31. Leger, L., Mercier, D., Gadoury, C., and J Lambert (1988). The multistage 20 metre shuttle run test for aerobic fitness. Journal of Sports Sciences. 6: 93-101.

32. Leger, L., and Gadoury, C. (1989) Validity of the 20 meter shuttle run test for aerobic fitness. Canadian Journal of Sports Sciences, 14:21-26.

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33. Loe, H., Rognmo, O., Saltin, B. and U. Wisloff. (2013). Aerobic Capacity Reference Data in 3816 Healthy Men and Women 20-90 years. PLoS ONE 8(5): e64319. doi:10.1371/journal.pone.0064319

34. Loe H, Nes BM, and Wisløff U (2016) Predicting VO2peak from Submaximal- and Peak Exercise Models: The HUNT 3 Fitness Study, Norway. PLoS ONE 11(1): e0144873. doi:10.1371/journal.pone.0144873

35. McArdle, W.D., Katch, F.I. and V.I. Katch (1991). Exercise Physiology: Energy, Nutrition and Human Performance (3rd ed.) Philidelphia: Lea & Febiger.

36. McAuley, P.A., Kokkinos, P.F., Oliveira, R.B., Emerson, B.T., & Myers, J.N. (2010). Obesity paradox and cardiorespiratory fitness in 12,417 male veterans aged 40 to 70 years. Mayo Clin Proc. 85(2), 115-121.

37. McNaughton L1, Hall P, Cooley D. (1998). Validation of several methods of estimating maximal oxygen uptake in young men. Percept Mot Skills. 1998 Oct;87(2):575- Percept Mot Skills. 87(2):575-84.

38. Mayorga-Vega, D. Aguilar-Soto, P. and J. Viciana. (2015). Criterion-Related Validity of the 20-M Shuttle Run Tests for Estimating Cardiorespiratory Fitness: A Systematic Review and Meta-Analysis. J Sports Sci Med, 14: 536-547.

39. Mayorga-Vega, D. Bocanegra-Parilla, R., Omelas, M. and J. Viciana. (2016). Criterion-Related Validity of the Distance and Time Based Walk-/Run Field Tests for Estimating Cardiorespiratory Fitness: A Systematic Review and Meta-Analysis. PloS ONE, 11(3):e0151671. Doi:10.137/journal.pone.0151671.

40. Neto, G. M., and P. V. Farinatti. (2003). Non-Exercise models for prediction of aerobic fitness and applicability on epidemiological studies: descriptive review and analysis of the studies. Rev Bras Med Esported, 9(5): 2003.

41. Palmer, P.B., and D.G O’Connell. (2009).Research Corner Regression Analysis for Prediction: Understanding the Process. Cardiopulmonary Physical Therapy Journal, 20(3): 23-26.

42. Parker BA, Kalasky MJ, and Proctor DN. (2010) Evidence for sex differences in cardiovascular aging and adaptive responses to physical activity. Eur J Appl Physiol., 110(2):235-46.

43. Peterson, P. N., Magid, D. J., Ross, C., Ho, P. M., Rumsfeld, J. S., Lauer, M. S., Masoudi, F. A. (2008). Association of exercise capacity on treadmill with future cardiac events in patients referred for exercise testing. Archives of Internal Medicine, 168(2), 174-179.

44. Penry JT, Wilcox AR, and J Yun. (2011) Validity and Reliability Analysis of Cooper’s 12-minute Run and the Multistage Shuttle Run in Healthy Adults. J Strength Cond Res. 25(3):597-605.

45. Ramsbottom R, Brewer J, and C Williams (1988). A progressive shuttle run test to estimate maximal

oxygen uptake. Br J Sports Med. 22(4): 141-4.

46. Reilly T, Spivock M, Prayal-Brown AL. (2014). The Fitness Profile: A case for assessing aerobic fitness and

body composition within the FORCE Evaluation. Technical Report: Department of National Defence,

Assistant Deputy Minister (Science and Technology). Ottawa.

47. Ross,R., and P.T. Katzmarzyk. (2003). Cardiorespiratory fitness is associated with diminished total and

abdominal obesity independent of body mass index. Int. J. Obes. Relat. Metab. Disord., 27:204-210.

48. Sassen, B., Cornelissen, A., Kiers, H., Wittlink, H. Kok, G.and L.Vanhees. (2009). Physical fitness matters

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49. Stockbrugger, B, Reilly, T., Blacklock, R. and Gagnon, P., Reliability of the Individual Components of the

Canadian Armed Forces Physical Employment Standard. Appl. Physiol. Nutr. Metab. (In Press)

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50. Tanaka, H., Monahan, K.D., & Seals, D.R. (2001). Age-Predicted Maximal Heart Rate Revisited. Journal of the American College of Cardiology, 37(1), 153-156.

51. Talbot, L; Weinstein, A.; Fleg, J. (2009). Army physical fitness scores predict coronary heart disease in army national guard soldiers. Military Medicine, 174; 3-245.

52. Wartburton, D., Gledhill, N., Jamnik, R., Bredin, S., McKenzie, D., Stone, J., Charlesworth, S., Shephard, R. (2011). INTERNATIONAL LAUNCH OF THE PAR-­Q+ AND ePARmed-­X+ The Physical Activity Readiness Questionnaire (PAR-­Q+) and Electronic Physical Activity Readiness Medical Examination (ePARmed-­X+): Summary of Consensus Panel Recommendations Health and Fitness Journal of Canada, 4(2) 26-37.

53. Wei, M., Kampert, J. B., Barlow, C. E., Nichaman, M. Z., Gibbons, L. W., Paffenbarger, R. S., & S. N. Blair. (1999). Relationship between low cardiorespiratory fitness and mortality in normal-weight, overweight, and obese men. JAMA : The Journal of the American Medical Association, 282(16), 1547-1553.

54. Weir, L., Jackson, A.S., Ayers, G.W., and B. Arenare.(2006). Nonexercise Models for Estimating VO2max with Waist Girth, Percent Fat or BMI. Med Sci Sports Exerc, 38(3):555-561.

55. Wong S.L., Katzmarzyk, P.T, Nichaman, M. Z., Church, T., Blair, S.N., and R. Ross. (2004) Cardiorespiratory Fitness is Associated with Lower Abdominal Fat independent of Body Mass Index. Med. Sci. Sports. Exerc., 36(2) : 286-291.

56. Zoeller, R. F. (2008) Gender Differences in Cardiorespiratory Fitness With Advancing Age: Is the Age-Associated Decline in VO2max More Rapid in Men and Do Older Men and Women Respond Differently to Exercise? American Journal of Lifestyle Medicine. 2(6): 492-499.

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58. http://www.statcan.gc.ca/imdb-bmdi/document/5071_D2_T1_V1-eng.pdf

59. http://www.csep.ca/english/view.asp?x=724&id=84

60. http://www.csep.ca/cmfiles/certifications/cpaflainsert/06_BIA_Information_Sheet.pdf

61. http://biospaceamerica.com/

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6.1 APPENDIX A - RECRUITMENT STUDY POSTER (2014-003)

The Directorate of Fitness within the Director General Personnel Support Services is recruiting

volunteers to participate in a study to determine the relationship between maximal performance on

the FORCE evaluation, cardiovascular fitness and body composition (anthropometrics). This research

will begin February 2014. Participation in this study will also fulfill the annual Fitness evaluation

requirement for the F/Y for which it takes place.

Research Project

Establishing the relationship between performance on the FORCE evaluation, cardiovascular fitness and

anthropometrics

Participants

We are looking for male and female participants of ALL FITNESS LEVELS, all ages, and free of any

limitations to maximal exercise. This study will require participation in 2 testing sessions within a 2 week

period.

Purpose

The purpose of this research study is to determine if there is a relationship between best performance

on the FORCE evaluation, cardiovascular fitness and body composition (anthropometrics). If

cardiovascular performance can be predicted using best FORCE evaluation performance and body

composition, this information could be used to predict cardiovascular risk.

Procedure

Involvement in this project requires 2 separate days of participation, with the main objectives of: 1)

completing a maximum graded treadmill test (VO2max), and 2) performing a maximum effort FORCE

evaluation. Day one will also involve a FORCE evaluation familiarization/practice as previous research

has shown that there is an effect of learning for this test.

Prior to attending the first session, volunteers will be asked to complete an online PAR-Q+ to determine

suitability for maximal exercise. During the first day of participation volunteers will receive a research

brief to explain in more detail the study. If they agree to participate they will be required to read and

sign a consent form and discuss their Physical Activity Readiness Questionnaire + (PAR-Q+). All females

will be required to screen for pregnancy prior to participation, and pregnant females will be excluded

from participation. On both days of testing, resting blood pressure and heart rate will be measured and

58

volunteers will be asked to adhere to pretesting instructions similar to what is expected prior to the

EXPRES Test.

On day one the following body measurements will be taken: height, waist circumference, hip

circumference, abdominal depth, % lean body mass and fat mass. These circumference and diameter

measurements are obtained by a simple tape measure or calliper device and will not cause physical

discomfort. The percentages of body fat and lean body mass are obtained by standing on a scale type

device, also non-invasive and will not cause discomfort.

It is important that volunteers understand that the reliability and quality of these measured are

dependent on the participants adherence to the pre-test instructions.

Equipment

Participants may be asked to wear a heart rate monitor for both tests, and a face mask during the

graded exercise test on the treadmill (day 1).

Dress

Testing will be conducted in normal fitness dress of choice (shorts, t-shirt and running shoes).

Location

Testing will be conducted in the research and training facility at 4210 Labelle Bldg, Ottawa, ON.

Risks

The primary risk of participation is muscle strain as a result of voluntary maximal exertion. In addition,

maximal aerobic activity can be associated with feeling of nausea and dizziness. Pre-screening is

performed to alleviate as much risk as possible and participants are permitted to withdraw their

participation from the study at any time. First aid/ Cardio-pulmonary Resuscitation qualified personnel

will be available at the testing site.

Remuneration

Participants will be remunerated as per CF QR & O guidelines.

Registration for testing and training

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If interested, please send an email to Barry.Stockbrugger@forces.gc.ca or call 613-992-3994 providing

your name, age and contact information.

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6.2 APPENDIX B - RECRUITMENT STUDY POSTER (2016-011)

The Directorate of Fitness within the Canadian Forces Morale and Welfare Services is recruiting volunteers to participate in a study to validate the relationship between maximal performance on the FORCE evaluation, cardiovascular fitness and waist circumference. This research will begin May 2016.

Research Project

Validation of the relationship between performance on the FORCE evaluation, cardiovascular fitness and waist circumference

Participants

We are looking for male and female participants of ALL FITNESS LEVELS, all ages, and free of any limitations to maximal exercise. Pregnant females will be excluded from participation. This study will require participation in 2 testing sessions within a 2 week period.

Purpose

The purpose of this research study is to validate the relationship between best performance on the FORCE evaluation, cardiovascular fitness and waist circumference which will be used to predict cardiovascular risk.

Procedure

Involvement in this project requires 2(3) separate days of participation, with the main objectives of 1) information briefing, consent and screening, 2) completing a maximum graded treadmill test (VO2max), and 3) performing a maximum effort FORCE evaluation.

Prior to attending the first session, volunteers will be asked to complete a PAR-Q+ to determine suitability for maximal exercise. Pregnant females will be excluded. During the first day of participation volunteers will receive a research brief to explain in more detail the study. If they agree to participate they will be invited to read and sign a consent form and discuss their Physical Activity Readiness Questionnaire + (PAR-Q+).

Following the consent to participate, the following body measurements will be taken: height, waist circumference, % lean body mass and fat mass. Waist circumference is obtained by a simple tape measure and will not cause physical discomfort. The percentages of body fat and lean body mass are obtained by standing on a scale type device, also non-invasive and will not cause discomfort.

On both days of fitness testing, resting blood pressure will be measured and volunteers will be asked to adhere to pretesting instructions similar to what is expected prior to the FORCE evaluation. It is important that volunteers understand that the reliability and quality of these measured are dependent on the participants adherence to the pre-test instructions.

Equipment

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Participants will be asked to wear a heart rate monitor for both fitness tests, and a face mask during the graded exercise test on the treadmill.

Dress

Testing will be conducted in normal fitness dress of choice (shorts, t-shirt and running shoes).

Location

Testing will be conducted in the research and training facility at 4210 Labelle Bldg, Ottawa, ON, or in a CAF base/wing fitness facility.

Risks

The primary risk of participation is muscle strain as a result of voluntary maximal exertion. In addition, maximal aerobic activity can be associated with feeling of nausea and dizziness. Pre-screening is performed to alleviate as

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6.3 APPENDIX C - PARTICIPANT INFORMATION SHEET (2014-003)

Establishing the relationship between performance on the FORCE evaluation, cardiovascular fitness and anthropometrics

Purpose The purpose of this research study is to establish the relationship between performance on the FORCE evaluation, cardiovascular fitness and anthropometrics.

The Present Study

Data collection will begin in Jan 2014 and continue for up to 6 months or until 150 volunteers have been assessed. Cardiovascular fitness testing and the FORCE evaluation will take place on 2 separate days, separated by no more than 2 weeks in the Research and Training facility, located at 4201 Labelle street, Ottawa, ON. During the graded exercise test and the FORCE evaluation you will be asked to wear a heart rate monitor, and a face mask for the cardiovascular fitness evaluation. Anthropometrics (waist, hip circumference and % lean body mass and % body fat) will also be measured on the first day.

Voluntary Participation

Your participation is completely voluntary. You may end your participation at any time, and you may refuse to participate in any part of the study, without repercussion or penalty.

Guarantee of Anonymity and Confidentiality

Your name, age, rank Service Number and other information will be recorded in an electronic database in the field. Data will be accessible only to the Principal/Co-Investigators. Any indentifying data will be destroyed once receipt of the stress remuneration has been confirmed. Performance measures will be coded with your participant number only. Any medical information will be stored as Protected B and will be stored separately from other data, such as performance measures. Your information will be combined with that from other participants for the purpose of analyzing trends. Only group data will be reported. If information from the study is to be used in reports or publications, no identifying information will be included. If there is an Access to Information Request made for these data, the Directorate of Access to Information and Privacy (DAIP) screens the data in accordance with the Privacy Act in order to ensure that individual identities (including indirect identification due to the collection of unique identifiers such as rank, occupation, and deployment information of military personnel) are not disclosed.

Benefits The results of this study will serve to help understand if there is a relationship between cardiovascular fitness and the FORCE evaluation. If present, this information will help create an understanding of the relationship between the FORCE evaluation and health/mortality. You will receive a stress remuneration of $12.72 for participation in the cardiovascular fitness assessment, to be added to your CAF paycheque. CAF members that successfully meet the minimum standard for the FORCE evaluation will be able to use these results for their annual fitness requirement.

Risks The principal risks of the research protocol are those associated with any maximal physical activity. These include and include muscle soreness, strains and sprains as well as dizziness and nausea which may occur as a result of maximal aerobic effort. Maximal exercise stress testing is associated with a very low risk of non-fatal and fatal cardiac events in either healthy asymptomatic or clinical populations (0.2-0.8/10000) . In addition, maximal physical exertion can present a risk to a fetus - pregnancy is therefore an exclusion criterion from this study.

All on-site research team members are qualified CPR and First Aid responders.

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Contact Information

Please feel free to contact Patrick Gagnon, the Principal Investigator of this study, if you have any questions with respect to the project: by e-mail at: Patrick. Gagnon@forces.gc.ca or by telephone at: 613.996-4161 Please feel free to contact the Chair of the DRDC Human Research Ethics Committee if you have any questions with respect to ethics approval procedures: by e-mail at: hrec-ceesh-toronto@drdc-rddc.gc.ca or by telephone at: 416-635-2098.

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6.4 APPENDIX D - PARTICIPANT INFORMATION SHEET (2016-011)

Validation of the relationship between performance on the FORCE evaluation, cardiovascular fitness and waist circumference

Purpose The purpose of this research study is to validate the relationship between performance on the FORCE evaluation, cardiovascular fitness and waist circumference which will be used to predict cardiovascular risk.

The Present Study

Data collection will begin in May 2016 and continue for up to 12 months or until at least 600 volunteers (300 males and 300 females) have been assessed. Cardiovascular fitness testing and the FORCE evaluation will take place on 2 separate days, separated by no more than 2 weeks in the CAF Fitness facility on your base/wing. During the graded exercise test and the FORCE evaluation you will be asked to wear a heart rate monitor, and a face mask for the cardiovascular fitness evaluation. Anthropometrics (waist circumference and % lean body mass and % body fat) will be measured on the first day.

Voluntary Participation

Your participation is completely voluntary. You may end your participation at any time, and you may refuse to participate in any part of the study, without repercussion or penalty.

Anonymity and Confidentiality

Your name, age, rank and other information will be recorded in an electronic database in the field. Data will be accessible only to the Principal/Co-Investigators. Any identifying data will be destroyed once data collection is complete. Performance measures will be coded with your participant number only. Any medical information will be stored as Protected B and will be stored separately from other data, such as performance measures. Your information will be combined with that from other participants for the purpose of analyzing trends. Only group data will be reported. If information from the study is to be used in reports or publications, no identifying information will be included. If there is an Access to Information Request made for these data, the Directorate of Access to Information and Privacy (DAIP) screens the data in accordance with the Privacy Act in order to ensure that individual identities (including indirect identification due to the collection of unique identifiers such as rank, occupation, and deployment information of military personnel) are not disclosed.

Benefits The personal benefits of this study include obtaining an accurate assessment of cardiovascular fitness, and body composition including % body fat and lean body mass. In addition, you will obtain valuable information regarding your cardiovascular health based on results from the CAF Fitness Profile applied to your FORCE evaluation results.

The results of this study will serve to help understand the relationship between cardiovascular fitness and the FORCE evaluation. This information will help establish the relationship between the FORCE evaluation and health/morbidity/mortality.

Risks The principal risks of the research protocol are those associated with any maximal physical activity. These include and include muscle soreness, strains and sprains as well as dizziness and nausea that may occur as a result of maximal aerobic effort. Maximal exercise stress testing is associated with a very low risk of non-fatal and fatal cardiac events in either healthy asymptomatic or clinical populations (1/10,000). In addition, maximal physical exertion can present a risk to a fetus - pregnancy is therefore an exclusion criterion from this study.

All on-site research team members are qualified CPR and First Aid responders.

65

Contact Information

Please feel free to contact Jacqueline Laframboise, if you have any questions with respect to the project: by e-mail at: Jacqueline.Laframboise@forces.gc.ca or by telephone at: 613.943-4794 Please feel free to contact the Chair of the DRDC Human Research Ethics Committee if you have any questions with respect to ethics approval procedures: by e-mail at: hrec-ceesh-toronto@drdc-rddc.gc.ca or by telephone at: 416-635-2098.

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6.5 APPENDIX E - PRELIMINARY INSTRUCTIONS TO PARTICIPANTS

Validation of the relationship between performance on the FORCE evaluation, cardiovascular fitness and waist circumference

The following details are provided for your information. Should you have any questions, please do not hesitate to

ask any of the researchers.

To improve the accuracy of the body composition InBody520 Bioelectrical impedance instrument and to achieve

standardization and ease of measurements please:

Dress

requirements The graded exercise test and the FORCE evaluation will be conducted in normal fitness dress of choice (shorts, t-shirt and running shoes).

Beverage Do not drink any caffeine beverages for 2 hours prior to testing, or alcoholic beverages for 6

hours prior to testing. Ensure you are moderately hydrated. Consume approximately 2 cups

of water over the 2-3 hours prior to testing.

Food Do not eat a meal for at least 2 hours prior to testing; a small snack is acceptable. Please

bring a snack which you can consume after the body composition (bioelectrical impedance)

measurements on Day 1.

Smoking Refrain from smoking or chewing tobacco for 2 hours prior to testing.

Exercise Refrain from exercising for 6 hours prior to fitness testing.

Other: Day 1

intake screening

Avoid consuming diuretics

Use the bathroom

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6.6 APPENDIX F - INFORMED CONSENT FORM 2014-003

VOLUNTEER CONSENT FORM

Protocol #: 2014-003

Title: Establishing the relationship between performance on the FORCE

evaluation, cardiovascular fitness and anthropometrics.

Principal Investigator: Patrick Gagnon, MSc CEP

Co-investigators: Jacqueline Laframboise MSc. CEP Barry Stockbrugger MSc CEP, Tara

Reilly PhD CEP

Research Assistant: Phil Newton M.Sc CEP, Sylvie Fortier M.Sc. CEP, Audrey Prayal-Brown

BSc

Run Director: Barry Stockbrugger, Jacqueline Laframboise

Affiliations: Canadian Forces Moral and Welfare Services; Directorate of Fitness;

Human Performance Research and Development Cell.

I, of _________________________________________

NAME LOCATION and TEL NUMBER

hereby volunteer to be a participant in the study, establishing the relationship between performance on the

FORCE evaluation, cardiovascular fitness and body composition, protocol number 2014-003. I have received the

information briefing and have had the opportunity to ask questions of the Investigators. All of my questions

concerning this study have been fully answered to my satisfaction. However, I may obtain additional information

about the research project and have any questions about this study answered by contacting Barry Stockbrugger

at 613-992-3994.

I understand that I am free to refuse to participate and may withdraw my consent without prejudice or hard

feelings at any time. Should I withdraw my consent, my participation in this research project will cease

immediately. I also understand that the Investigator(s), their designate, or the physician(s) responsible for the

research project may terminate my participation at any time, regardless of my wishes.

I understand that my participation in this study will involve being outfitted with a heart rate monitor while

performing two tests to my maximal effort, and wearing a mask during the cardiovascular fitness test.

I have been told that I will be asked to participate in 2 days of maximum effort testing including; 1) body size

measurements and body composition 2) a graded exercise test on a treadmill and a FORCE evaluation

68

familiarization, and 3) the FORCE evaluation. In addition, I must not perform physical activity or drink alcoholic

beverages for 6 hours prior to testing nor eat, smoke or drink caffeinated beverages for 2 hours prior to testing.

Total time involvement (with preparation) will be as follows:

Day 1: 2 hours including information briefing, health screening and testing.

Day 2: 1 hour for testing.

I have been told that the principal risks of the research protocol are those associated with any maximal physical

activity. These include and include muscle soreness, strains and sprains as well as dizziness and nausea which

may occur as a result of maximal aerobic effort. Maximal exercise stress testing is associated with a very low risk

of non-fatal and fatal cardiac events in either healthy asymptomatic or clinical populations (0.2-0.8/10000). In

the case of pregnancy, heat production associated with maximal physical activity can present a risk to a fetus.

For Female Participants: I have been informed that this study could be potentially harmful to a fetus and, as such,

pregnancy would disqualify me from further participation in this experiment. Therefore, I consent to pregnancy

screening and counselling by a qualified health care practitioner. The health care practitioner might conclude

that further tests are needed so I may be asked to undergo additional testing to determine my pregnancy status.

I understand that all discussion pertaining to this matter will be treated as confidential between the health care

practitioner and myself. Also, I have been advised that if I have any concerns regarding a possible pregnancy, I

should consult a qualified health care practitioner before undertaking or resuming any phase of this study.

Also, I acknowledge that my participation in this study, or indeed any research, may involve risks that are

currently unforeseen by the Canadian Forces Moral and Welfare Services (CFMWS). I understand that no

additional medical support is provided, beyond what is in place for normal operations.

In the highly unlikely event that I become incapacitated during my participation, I understand that emergency

medical treatment will be instituted even though I am unable to give my consent at that time. I will go with the

Investigator(s) to seek immediate medical attention if either the Investigator(s) or I consider that it is required.

Every effort will be made to contact a family member or the designated person indicated below should that be

necessary.

I understand that my experimental data will be protected under the Government Security Policy (GSP) at the

appropriate designation and not revealed to anyone other than the CFMWS-affiliated Investigator(s) or external

investigators from the sponsoring agency without my consent except as data unidentified as to source. I consent

to the use of my data in further analysis by CFMWS without reference to my personal identification.

I understand that my name will not be identified or attached in any manner to any publication arising from this

study. Moreover, I understand that the experimental data may be reviewed by an internal or external audit

committee with the understanding that any summary information resulting from such a review will not identify

69

me personally. Any results of medical screening will be classified as protected B and maintained separately from

any other data which can identify me as an individual.

I understand that, as a Government Institutions, CFMWS and DRDC are committed to protecting my personal

information. However, under the Access to Information Act, copies of research reports and research data

(including the database pertaining to this project) held in Federal government files, may be disclosed. I

understand that prior to releasing the requested information, the Directorate of Access to Information and

Privacy (DAIP) screens the data in accordance with the Privacy Act in order to ensure that individual identities

(including indirect identification due to the collection of unique identifiers such as rank, occupation, and

deployment information of military personnel) are not disclosed.

I understand that I will be remunerated $12.72 (Stress level 1) for the cardiovascular fitness testing. I will not be

remunerated for the FORCE evaluation as this is a requirement for all CAF members. I acknowledge that Stress

Allowance is income and is subject to income tax. As a CAF member, my Service Number (SN) is required for

remuneration. The database linking my name and service number to my participant number will be kept in a

secured and encrypted format in order to prevent any of my results from identifying me as an individual. This

database will be destroyed once remuneration has been confirmed.

I understand that I am considered to be on duty for disciplinary, administrative and Pension Act purposes during

my participation in this study and I understand that in the unlikely event that my participation in this study results

in a medical condition rendering me unfit for service, I may be released from the CAF and my military benefits

apply. This duty status has no effect on my right to withdraw from the study at any time I wish and I understand

that no action will be taken against me for exercising this right.

I understand that by signing this consent form I have not waived any legal rights I may have as a result of any

harm to me occasioned by my participation in this research project beyond the risks I have assumed. Also, I

understand that I will be given a copy of this consent form so that I may contact any of the individuals mentioned

below at some time in the future should that be required.

1. To be completed by volunteer/witness

Volunteer’s Name

Volunteer’s Signature Date

Witness Name Witness Signature

Family member or other contact person: (name, address, tel number and relationship)

2. To be completed by chain of command

70

Commanding Officer’s or Designee’s signature

CO’s Unit

3. To be completed by research team

I have verbally briefed the

participant about the

requirements for this research

experiment

Principal Investigator

Signature Date

FOR PARTICIPANT ENQUIRY IF REQUIRED:

Should I have any questions or concerns regarding this project before, during, or after participation, I understand

that I am encouraged to contact the following people by surface mail at these addresses or in person, by phone

or e-mail, at any of the numbers and addresses listed below:

Principal Investigator:

Patrick Gagnon, Patrick.Gagnon@forces.gc.ca at 613-996-4161

Director General Personnel and Family Support Services

4210 Labelle St, Ottawa, Ontario, Canada, K1A 0K2

Chair DRDC Human Research Ethics Committee (HREC):

telephone: 416-635-2098, e-mail: hrec-ceesh-toronto@drdc-rddc.gc.ca

Defense R&D Canada – Toronto (DRDC Toronto), P.O. Box 2000,

1133 Sheppard Avenue West, Toronto, Ontario M3M 3B9

I understand that I will be given a copy of the participant information sheet so that I may contact any of the

above-mentioned individuals at some time in the future should that be required

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6.7 APPENDIX G - INFORMED CONSENT FORM 2016-011

VOLUNTEER CONSENT FORM

Protocol #: 2016-018

Title: Validation of the relationship between performance on the FORCE evaluation,

cardiovascular fitness and waist circumference.

Principal Investigator: Jacqueline Laframboise, MSc., CEP

Co-investigators: Barry Stockbrugger, MSc, CEP, Tara Reilly, PhD, CEP, Evan Walsh M.Sc CEP, Julie

Martin PhD, Phil Newton MSc CEP, Kevin Semeniuk MA

Run Director: Barry Stockbrugger, Evan Walsh, Jacqueline Laframboise

Affiliations: Canadian Forces Moral and Welfare Services; Directorate of Fitness; Human

Performance Research and Development Cell.

I, of _________________________________________

NAME LOCATION and TEL NUMBER

hereby volunteer to be a participant in the study, Validation of the relationship between performance on the

FORCE evaluation, cardiovascular fitness and waist circumference, protocol number 2016-018. I have received

the information briefing and have had the opportunity to ask questions of the Investigators. All of my questions

concerning this study have been fully answered to my satisfaction. However, I may obtain additional information

about the research project and have any questions about this study answered by contacting Jacqueline

Laframboise at 613-943-4794.

I understand that I am free to refuse to participate and may withdraw my consent without prejudice or hard

feelings at any time. Should I withdraw my consent, my participation in this research project will cease

immediately. I also understand that the Investigator(s), their designate, or the physician(s) responsible for the

research project may terminate my participation at any time, regardless of my wishes.

I understand that my participation in this study will involve being outfitted with a heart rate monitor while

performing two tests to my maximal effort, and wearing a mask during the cardiovascular fitness test.

I have been told that I will be asked to participate in a project briefing and screening session and 2 days of

maximum effort testing including;

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1) Body size measurements, 2) a graded exercise test on a treadmill and a FORCE evaluation familiarization, and

3) the FORCE evaluation. In addition, I must not perform physical activity or drink alcoholic beverages for 6 hours

prior to testing nor eat, smoke or drink caffeinated beverages for 2 hours prior to testing. I will refrain from taking

diuretics the first day of testing.

Total time involvement (with preparation) will be as follows:

Day 1 (or prior to day 1): 1 hour including information briefing, health screening

Day 1 testing: 1 hour for maximal graded exercise test and FORCE Evaluation familiarization

Day 2 testing: 1 hour for FORCE evaluation

I have been informed of the personal benefits of this study which include obtaining an accurate assessment of

cardiovascular fitness, and body composition, including % body fat and lean body mass which is valued at over

$200. In addition, I will obtain valuable information regarding my cardiovascular health based on results from

the CAF Fitness Profile applied to my FORCE evaluation results.

I have been told that the principal risks of the research protocol are those associated with any maximal physical

activity. These include muscle soreness, strains and sprains as well as dizziness and nausea which may occur as

a result of maximal aerobic effort. Maximal exercise stress testing is associated with a very low risk of non-fatal

and fatal cardiac events in either healthy asymptomatic or clinical populations (1/10000). In the case of

pregnancy, heat production associated with maximal physical activity can present a risk to a fetus.

For Female Participants: I have been informed that this study could be potentially harmful to a fetus and, as such,

pregnancy would disqualify me from further participation in this experiment. If I think that there is a chance that

I might be pregnant, I understand that I should withdraw from participating in this study. I understand that I will

be given a personal pregnancy test stick (to dip into urine or to place under urine stream) to take if I so desire. I

do not have to share the results of the test, but I can use this information to help me to decide whether or not

to participate in the study. If I have further questions or concerns about how this study may affect a fetus, I can

speak to the principal investigator to get more information.

Also, I acknowledge that my participation in this study, or indeed any research, may involve risks that are

currently unforeseen by the Canadian Forces Morale and Welfare Services (CFMWS). I understand that no

additional medical support is provided, beyond what is in place for normal operations.

In the highly unlikely event that I become incapacitated during my participation, I understand that emergency

medical treatment will be instituted even though I am unable to give my consent at that time. I will go with the

Investigator(s) to seek immediate medical attention if either the Investigator(s) or I consider that it is required.

Every effort will be made to contact a family member or the designated person indicated below should that be

necessary.

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I understand that my experimental data will be protected under the Government Security Policy at the

appropriate designation and not revealed to anyone other than the CFMWS-affiliated Investigator(s) or external

investigators from the sponsoring agency without my consent except as data unidentified as to source. I consent

to the use of my data in further analysis by CFMWS without reference to my personal identification.

I understand that my name will not be identified or attached in any manner to any publication arising from this

study. Moreover, I understand that the experimental data may be reviewed by an internal or external audit

committee with the understanding that any summary information resulting from such a review will not identify

me personally. Any results of medical screening will be classified as protected B and maintained separately from

any other data which can identify me as an individual.

I understand that, as Government Institutions, CFMWS and DRDC are committed to protecting my personal

information. However, under the Access to Information Act, copies of research reports and research data

(including the database pertaining to this project) held in Federal government files, may be disclosed. I

understand that prior to releasing the requested information, the Directorate of Access to Information and

Privacy (DAIP) screens the data in accordance with the Privacy Act in order to ensure that individual identities

(including indirect identification due to the collection of unique identifiers such as rank, occupation, and

deployment information of military personnel) are not disclosed.

I understand that I will not be financially remunerated.

I understand that I am considered to be on duty for disciplinary, administrative and Pension Act purposes during

my participation in this study and I understand that in the unlikely event that my participation in this study results

in a medical condition rendering me unfit for service, I may be released from the CAF and my military benefits

apply. This duty status has no effect on my right to withdraw from the study at any time I wish and I understand

that no action will be taken against me for exercising this right.

I understand that by signing this consent form I have not waived any legal rights I may have as a result of any

harm to me occasioned by my participation in this research project beyond the risks I have assumed. Also, I

understand that I will be given a copy of this consent form so that I may contact any of the individuals mentioned

below at some time in the future should that be required.

1. To be completed by volunteer/witness

Volunteer’s Name

Volunteer’s Signature Date

Witness Name Witness Signature

Family member or other contact person: (name, address, tel number and relationship)

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2. To be completed by chain of command

Commanding Officer’s or Designee’s signature

CO’s Unit

3. To be completed by research team

I have verbally briefed the

participant about the

requirements for this research

experiment

Research team member

Signature Date

FOR PARTICIPANT ENQUIRY IF REQUIRED:

Should I have any questions or concerns regarding this project before, during, or after participation, I understand

that I am encouraged to contact the following people by surface mail at these addresses or in person, by phone

or e-mail, at any of the numbers and addresses listed below:

Principal Investigator:

Jacqueline Laframboise, jacqueline.laframboise@forces.gc.ca

at 613-996-4161

Canadian Forces Morale and Welfare Services

4210 Labelle St, Ottawa, Ontario, Canada, K1A 0K2

Chair DRDC Human Research Ethics Committee (HREC):

Telephone: 416-635-2098, e-mail: hrec-ceesh-toronto@drdc-rddc.ca

Defense R&D Canada – Toronto (DRDC Toronto)

1133 Sheppard Avenue West, Toronto, Ontario M3K 2C9

I understand that I will be given a copy of the participant information sheet so that I may contact any of the

above-mentioned individuals at some time in the future should that be required

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6.8 APPENDIX H - PHYSICAL ACTIVITY READINESS – QUESTIONNAIRE

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