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The cardiovascular, respiratory, systemic, and autonomic responses to exercise in diesel exhaust Giles, Luisa 2014

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THE CARDIOVASCULAR, RESPIRATORY, SYSTEMIC, AND AUTONOMIC RESPONSES TO EXERCISE IN DIESEL EXHAUST  by Luisa Giles  B.Sc., Staffordshire University, 2003 M.Sc., The University of British Columbia, 2007  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY  in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Kinesiology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   February 2014  ? Luisa Giles 2014 ii  Abstract Purpose: To determine the cardiovascular, respiratory, systemic inflammatory, and autonomic nervous system responses to varying exercise intensities during exposure to diesel exhaust (DE), and to determine how pre-exercise DE exposure affects the cardio-respiratory system and subsequent exercise performance. Methods: Eighteen males performed six 30-minute trials, which included rest, low-intensity, and high-intensity cycling. Each trial was performed twice, once breathing filtered air (FA) and once breathing DE (300ug/m3 of PM2.5), with seven days between trials. Before, and following exercise, exhaled nitric oxide, pulmonary function, heart rate variability, flow-mediated dilation (FMD), complete blood count, endothelin-1, and plasma nitrite/nitrate (NOx) were measured. During exercise, minute ventilation ( E), oxygen consumption ( O2), CO2 production (CO2), respiratory exchange ratio (RER), and rating of perceived exertion (RPE) for lungs and legs were measured. In a second experiment, eight males were exposed to DE (300ug/m3 of PM2.5) or FA for 60-minutes, followed by an indoor 20-km cycling time trial. Pulmonary function was assessed before and after exposure and after exercise. Heart rate was measured during exposure and exercise performance was measured as mean power output during exercise. Results:  In the first experiment, RER was significantly lower (0.94 vs. 0.96), and RPE significantly greater, in DE compared to FA (p<0.05). During low-intensity exercise, E (44.5 vs. 40.5 L?min-1), O2 (27.9 vs. 24.9 ml?kg?min-1) and CO2 (25.9 vs. 23.6 ml?kg?min-1) were iii  significantly greater during DE (p<0.05). Following exercise in DE, plasma NOx significantly increased (p<0.05). On low-intensity exercise days, FMD/Shear rate area under the curve (SRAUC) was significantly lower in DE compared to FA (9.7 x10-5 vs. 11.7x10-5; p<0.05). In the second experiment, we found that pre-exercise exposure to DE did not impair exercise performance but attenuated exercise-induced bronchodilation and increased exercise heart rate (163.9 vs. 157.3 bpm; p<0.05). Conclusion: Metabolic and endothelial responses to low- but not high-intensity cycling in DE differ from those in FA. Therefore, reducing exercise intensity during bouts of air pollution may have no benefit. Exposure to DE prior to exercise increased exercise heart rate and decreased exercise-induced bronchodilation. Consequently, encouraging individuals to minimize exposure to air pollution prior to exercise could be beneficial.  iv  Preface Chapter 1 A version of Chapter one has been published as: Giles, LV. Koehle, MS. ?The health effects of exercising in pollution? (Sports Medicine. 2013 Nov 1. [Epub ahead of print] PMID: 24174304). The version within this thesis has been reproduced with permission from Springer (License # 325754500939). I performed the literature review and wrote the manuscript. Dr. Koehle provided feedback on the manuscript. My overall contribution was 95%. Chapter 3 A version of Chapter 3 has been accepted for publication in Medicine Science Sports and Exercise (Manuscript# MSSE-D-13-01140R1) as Giles LV. Brandenburg, JP. Carlsten, C. and Koehle, MS. entitled ?Physiological responses to diesel exhaust exposure are modified by cycling intensity?. For this manuscript, I identified the research question, designed the study, collected and analyzed the data, and wrote the manuscript. Dr. Koehle, obtained financial support for the research, provided guidance throughout the project and feedback for the manuscript. Dr. Carlsten, provided laboratory space required to conduct the study, guidance throughout the project, and feedback for the manuscript. Dr. Brandenburg provided assistance with data collection and analysis, as well as feedback for the manuscript. My overall contribution was 95%. Chapters 4 and 5 For Chapters 4 and 5, I identified the research question, designed the study, collected and analyzed the data. Dr. Koehle, obtained financial support for the research and provided guidance throughout the project. Dr. Carlsten, provided laboratory space required to conduct the study, v  and guidance throughout the project. Normand Richard analyzed plasma NOx samples. Jian Ruan analyzed endothelin-1 samples. My overall contribution was 90%. Chapter 6 A version of Chapter 6 has been previously published: Giles LV, Carlsten C, and Koehle MS. as ?The effect of pre-exercise diesel exhaust exposure on cycling performance and cardio-respiratory variables? (Inhalation Toxicology. 2012;24(12):783-9. PMID: 23033992). The version within this thesis had been reproduced with permission from Informa Healthcare (License # 3194381376831). For this chapter, I identified the research question, designed the study, collected and analyzed the data, and wrote the manuscript. Dr. Koehle, obtained financial support for the research, provided guidance throughout the project and feedback for the manuscript. Dr. Carlsten, provided laboratory space required to conduct the study, guidance throughout the project and feedback for the manuscript. My overall contribution was 90%. Ethical approval Work presented in Chapters 3, 4, 5 and 6, was conducted with approval from the UBC Clinical Research Ethics Board (Certificate # H08-03055). vi  Table of contents Abstract.......................................................................................................................................... ii Preface........................................................................................................................................... iv Table of contents .......................................................................................................................... vi List of tables.................................................................................................................................. ix List of figures..................................................................................................................................x List of symbols and abbreviations ............................................................................................. xii Acknowledgements .................................................................................................................... xvi CHAPTER 1: LITERATURE REVIEW ....................................................................................1 1.1 Introduction........................................................................................................................ 1 1.1.1 Particulate matter ........................................................................................................ 1 1.1.2 Carbon monoxide........................................................................................................ 3 1.1.3 Ozone .......................................................................................................................... 3 1.1.4 Sulphur dioxide........................................................................................................... 4 1.1.5 Nitrogen oxides........................................................................................................... 4 1.1.6 Volatile organic compounds ....................................................................................... 5 1.2 Why diesel exhaust? .......................................................................................................... 5 1.3 Air pollutants of concern during exercise with diesel exhaust exposure........................... 6 1.4 How exercise may increase susceptibility to particulate matter air pollution ................... 7 1.5 The physiological effects of particulate matter air pollution exposure during exercise .... 9 1.5.1 Pulmonary inflammation ............................................................................................ 9 1.5.2 Pulmonary function................................................................................................... 10 1.5.3 Endothelial vascular function ................................................................................... 12 1.5.4 Systemic inflammation ............................................................................................. 13 1.6 Exercise performance in air pollution.............................................................................. 14 1.7 Balancing risk and benefit ............................................................................................... 14 1.8 Conclusions and research gaps ........................................................................................ 16 1.9 Thesis rationale ................................................................................................................ 16 1.10 Objectives ........................................................................................................................ 17 1.11 Hypotheses....................................................................................................................... 18 CHAPTER 2: RESEARCH OVERVIEW.................................................................................19 2.1 Methods overview............................................................................................................ 19 2.1.1 Project 1 .................................................................................................................... 19 2.1.1.1 Participants......................................................................................................... 19 2.1.1.2 Experimental design........................................................................................... 20 2.1.1.3 Introductory session (day 1)............................................................................... 22 2.1.1.4 Testing days (days 2-7)...................................................................................... 22 2.1.1.5 Apparatus ........................................................................................................... 23 2.1.1.6 Exposure set-up.................................................................................................. 24 CHAPTER 3: THE RESPIRATORY AND METABOLIC RESPONSES TO DIESEL EXHAUST EXPOSURE ARE MODIFIED BY CYCLING INTENSITY.............................28 3.1 Introduction...................................................................................................................... 28 3.2 Methods............................................................................................................................ 29 3.2.1 Exposure setup .......................................................................................................... 31 3.2.2 Statistical analysis..................................................................................................... 31 vii  3.3 Results.............................................................................................................................. 32 3.3.1 Exposures.................................................................................................................. 32 3.3.2 Cardio-respiratory and metabolic responses............................................................. 32 3.4 Discussion ........................................................................................................................ 38 3.5 Conclusion ....................................................................................................................... 44 CHAPTER 4: THE ENDOTHELIAL RESPONSES TO LOW- AND HIGH-INTENSITY CYCLING WITH DIESEL EXHAUST EXPOSURE .............................................................46 4.1 Introduction...................................................................................................................... 46 4.2 Methods............................................................................................................................ 47 4.2.1 Outcome measures and apparatus............................................................................. 48 4.2.1.1 Blood parameters ............................................................................................... 48 4.2.1.2 Endothelial function........................................................................................... 50 4.2.2 Exposure setup .......................................................................................................... 52 4.2.3 Statistical analysis..................................................................................................... 52 4.3 Results.............................................................................................................................. 53 4.3.1 Exposures.................................................................................................................. 53 4.3.2 Plasma NOx .............................................................................................................. 53 4.3.3 Endothelin-1.............................................................................................................. 55 4.3.4 Endothelial function.................................................................................................. 57 4.4 Discussion ........................................................................................................................ 59 4.5 Conclusion ....................................................................................................................... 65 CHAPTER 5: THE RESPIRATORY, SYSTEMIC, AND AUTONOMIC RESPONSES TO LOW- AND HIGH-INTENSITY CYCLING WITH DIESEL EXHAUST EXPOSURE ....67 5.1 Introduction...................................................................................................................... 67 5.2 Methods............................................................................................................................ 68 5.2.1 Outcome measures and apparatus............................................................................. 69 5.2.1.1 Heart rate variability .......................................................................................... 69 5.2.1.2 Blood pressure ................................................................................................... 70 5.2.1.3 Complete blood count ........................................................................................ 70 5.2.1.4 FeNO.................................................................................................................. 70 5.2.1.5 Pulmonary function............................................................................................ 71 5.2.2 Exposure setup .......................................................................................................... 71 5.2.3 Statistical analysis..................................................................................................... 71 5.3 Results.............................................................................................................................. 73 5.3.1 Heart rate variability ................................................................................................. 76 5.3.2 Blood pressure .......................................................................................................... 76 5.3.3 Complete blood count ............................................................................................... 76 5.3.4 FeNO......................................................................................................................... 79 5.3.5 Pulmonary function................................................................................................... 81 5.4 Discussion ........................................................................................................................ 83 5.5 Conclusion ....................................................................................................................... 91 CHAPTER 6: THE EFFECTS OF EXPOSURE TO DIESEL EXHAUST PRIOR TO EXERCISE ON CARDIO-RESPIRATORY VARIABLES AND EXERCISE PERFORMANCE........................................................................................................................92 6.1 Introduction...................................................................................................................... 92 viii  6.2 Methods............................................................................................................................ 93 6.2.1 Participants................................................................................................................ 93 6.2.2 Procedures................................................................................................................. 94 6.2.3 Exposure setup .......................................................................................................... 95 6.2.4 Statistical analysis..................................................................................................... 96 6.3 Results.............................................................................................................................. 96 6.4 Discussion ...................................................................................................................... 102 6.5 Conclusion ..................................................................................................................... 103 CHAPTER 7: CONCLUSION..................................................................................................108 7.1 Summary of findings...................................................................................................... 109 7.1.1 Chapter 3................................................................................................................. 109 7.1.2 Chapter 4................................................................................................................. 110 7.1.3 Chapter 5................................................................................................................. 110 7.1.4 Chapter 6................................................................................................................. 111 7.2 Limitations ..................................................................................................................... 111 7.3 Future directions ............................................................................................................ 115 7.3.1 Other populations.................................................................................................... 115 7.3.2 Non-acute effects .................................................................................................... 115 7.3.3 Environmental physiology ...................................................................................... 115 7.4 Synthesis of research and recommendations ................................................................. 116 7.4.1 Implications for individual exercisers..................................................................... 117 7.4.2 Implications for organizations advising exercisers about exercising in air pollution 117 7.4.3 Implications for sporting organizational bodies and city planners ......................... 118 7.5 Overall conclusion ......................................................................................................... 119 References...................................................................................................................................121 Appendices..................................................................................................................................138 Appendix A Detailed hypotheses............................................................................................ 138 Appendix B Experimental design ........................................................................................... 140 Appendix C Chapter 4 additional material ............................................................................. 141 C.1 Baseline endothelial function .................................................................................... 141 C.2 P-value summary for plasma NOx............................................................................ 142 C.3 Intensity-by-time interactions for endothelial function............................................. 143 C.4 Significant differences for endothelial function (intensity-by-time interaction) ...... 144 Appendix D Chapter 5 additional material ............................................................................. 146 D.1 Intensity-by-time interactions for heart rate variability ............................................ 146 D.2 Significant differences for heart rate variability (intensity-by-time interaction)...... 147 D.3 Intensity-by-time interactions for blood pressure ..................................................... 150 D.4 Hemoglobin intensity-by-time interaction ................................................................ 151 D.5 Red cell distribution width intensity-by-time interaction ......................................... 152 D.6 Platelet count intensity-by-time interaction .............................................................. 153  ix  List of tables Table 1.1 Size classifications of particulate matter ........................................................................ 2 Table 2.1 Mean air pollutant concentrations during a 30 min exposure to filtered air or diesel exhaust with rest or cycling .......................................................................................................... 27 Table 3.1 Mean cardio-respiratory variables in eighteen recreationally-active males during rest, or low-intensity, or high-intensity cycling.................................................................................... 37 Table 5.1 The mean pre-exposure heart rate variability of six experimental test days in 18 recreationally-active males. Mean (sd) ......................................................................................... 73 Table 5.2 Mean pre-exposure blood pressure of six experimental test days in 18 recreationally-active males. Mean (sd) ................................................................................................................ 74 Table 5.3 Mean pre-exposure complete blood count of six experimental test days in 18 recreationally-active males. Mean (sd) ......................................................................................... 74 Table 5.4 Mean pre-exposure pulmonary function over six experimental test days in 18 recreationally-active males. Mean (sd) ......................................................................................... 75 Table 6.1 Mean concentration of air pollutants during a 60-minute exposure to filtered air or diesel exhaust that occurred prior to a 20 km cycling time trial................................................... 97 Table 6.2 Individual FEV1 (L) values in eight endurance-trained males prior to and following a 60-minute exposure to filtered air or diesel exhaust and following a 20 km cycling time trial ... 99 Table 6.3 Mean individual heart rate in eight endurance-trained males during a 20 km cycling time trial that followed a 60-minute exposure to filtered air or diesel exhaust .......................... 101 Table C.1 Mean pre-exposure endothelial function over six experimental test days in 18 recreationally-active males. Mean (sd) ....................................................................................... 141 Table C.2 Intensity-by-time interaction summary table for endothelial function, summarizing significant differences (p<0.05) at each intensity between time points...................................... 144 Table C.3 Intensity-by-time interaction summary table for endothelial function, summarizing significant differences (p<0.05) at each time point between exercise intensities....................... 145  x  List of figures Figure 2.1 Experimental design of project 1 detailing one maximal exercise test day and six experimental test days consisting of rest, low-intensity cycling, or high-intensity cycling with exposure to filtered air or diesel exhaust ...................................................................................... 21 Figure 2.2 Overview of testing days 2-7 in project 1 detailing data collected prior to, during and following 30 min of rest, low-intensity cycling, or high-intensity cycling with exposure to filtered air or diesel exhaust.......................................................................................................... 23 Figure 2.3 Representation of the exposure and exercise set-up during test days for project 1..... 24 Figure 2.4 Production and delivery schematic of diluted and aged diesel exhaust. ..................... 26 Figure 3.1 (a) RER, (b) O2, (c) E, and (d) CO2 in 18 recreationally-active males during 30 min of rest, low-intensity cycling, or high-intensity cycling in filtered air or diesel exhaust.................. 34 Figure 3.2 (a) Rating of perceived exertion (RPE) for the lungs and (b) legs in 18 recreationally-active males in the final minute of 30 minutes of rest, low-intensity cycling, or high-intensity cycling in filtered air or diesel exhaust ......................................................................................... 35 Figure 3.3 (a) Ratio of oxygen consumption to power output (O2 cost of exercise) and gross efficiency (b) in 18 recreationally-active males during 30 min of low-intensity or high-intensity cycling in filtered air or diesel exhaust ......................................................................................... 36 Figure 4.1 Overview of test day procedures prior to and following 30 min of rest, low-intensity, and high-intensity cycling in filtered air or diesel exhaust ........................................................... 48 Figure 4.2 Plasma NOx in 18 recreationally-active males prior to and following 30-min of (a) rest, (b) low-intensity cycling, or (c) high-intensity cycling in filtered air or diesel exhaust....... 54 Figure 4.3 Plasma endothelin-1 in 18 recreationally-active males pre, post, 1 h- and 2 h- post (a) 30-min of exposure to filtered air or diesel exhaust (exposure-by-time interaction), or  (b) 30-min of rest, low-intensity cycling, or high-intensity cycling (intensity-by-time interaction).............. 56 Figure 4.4 FMD/SRAUC in 18 recreationally-active males on rest, low-intensity cycling, or high-intensity cycling days in filtered air or diesel exhaust.................................................................. 58 Figure 5.1 Overview of test day procedures prior to and following 30 min of rest, low-intensity, and high-intensity cycling in filtered air or diesel exhaust ........................................................... 69 Figure 5.2 (a) White blood cell count (WBC) or  (b) neutrophils in 18 recreationally-active males prior to and following 30-min of rest, low-intensity cycling, or high-intensity cycling .............. 78 Figure 5.3 Monocytes in 18 recreationally-active males prior to and following 30-min of rest, low-intensity cycling, or high-intensity cycling. .......................................................................... 79 Figure 5.4 FeNO in 18 recreationally-active males prior to and following 30-min of (a) rest, (b) low-intensity cycling, or (c) high-intensity cycling in filtered air or diesel exhaust .................... 80 Figure 5.5 Peak expiratory flow rate (PEFR) in 18 recreationally-active males on rest, low-intensity, or high-intensity cycling days in diesel exhaust or filtered air. (a) Exposure-by-intensity interaction, (b) intensity-by-time interaction ................................................................. 82 Figure 6.1 Overview of test days for project 2 ............................................................................. 96 Figure 6.2 Mean percent change in FEV1 in 8 endurance-trained males following exposure to filtered air or diesel exhaust and following a 20 km time trial ..................................................... 98 Figure 6.3 Mean heart rate in eight endurance-trained males during a 20 km time trial that followed a 60 min exposure to filtered air or diesel exhaust. ..................................................... 100 Figure 6.4 (a) Minute ventilation, (b) tidal volume, (c) frequency of breathing, and (d) oxyhemoglobin saturation, in eight endurance-trained men during a 20 km cycling time trial . 102 Figure B.1 Experimental design for Chapters 3, 4, and 5........................................................... 140 xi  Figure C.1 (a) Pre-occlusion artery diameter, (b) peak artery diameter, (c) time to peak dilation, (d) pre-occlusion shear rate, and (e) SRAUC, in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling.............................................................. 143 Figure D.1 HRV in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling ................................................................................................................. 146 Figure D.2 Systolic blood pressure (SBP) in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling .............................................................................. 150 Figure D.3 Hemoglobin in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling ............................................................................................. 151 Figure D.4 Red cell distribution width (RDW) in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling.............................................................. 152 Figure D.5 Platelet count in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling ............................................................................................. 153  xii  List of symbols and abbreviations ?: represents delta, which is the change in a value between two points ANOVA: Analysis of variance bpm: Beats per minute DBP: Diastolic blood pressure DE: Diesel exhaust ELISA: Enzyme-linked immunosorbent assay eNOS: Endothelial nitric oxide synthase FA: Filtered air FB: Frequency of breathing FEF25-75: Forced expiratory flow in the middle 50% of expiration FeNO: Fraction of exhaled nitric oxide FEV1: Forced expiratory volume in 1 second FMD: Flow mediated dilation FVC: Forced vital capacity H: Hour(s) Hct: Hematocrit HF (nu): High frequency power in normalized units HFP: High frequency power xiii  HRV: Heart rate variability iNOS: Inducible nitric oxide synthase LF (nu): Low frequency power in normalized units LF/HF: Low frequency/high frequency ratio LFP: Low frequency power MAP: Mean arterial pressure Min: Minutes NN: Normal-to-normal interval NO: Nitric oxide NO2: Nitrogen dioxide NOS: Nitric oxide synthase PEFR: Peak expiratory flow rate PM: Particulate matter PM10: Particulate matter with a mass median aerodynamic diameter less than 10 ?m PM2.5-10: Particulate matter with a mass median aerodynamic diameter between 2.5 ?m and 10 ?m  PM2.5: Particulate matter with a mass median aerodynamic diameter less than 2.5 ?m PM1: Particulate matter with a mass median aerodynamic diameter less than 1 ?m PM0.1: Particulate matter with a geometric median diameter of 0.1 ?m or less xiv  PNC: Particle number concentration  RER: Respiratory exchange ratio RMSSD: Root mean square of successive intervals RM O2: Respiratory muscle oxygen consumption RPE: Rating of perceived exertion RPELegs: Rating of perceived exertion for the legs RPELungs: Rating of perceived exertion for the lungs SBP: Systolic blood pressure SDNN: Standard deviation of normal-to-normal intervals SpO2: Oxyhemoglobin saturation measured by pulse oximetry SRAUC: Shear rate area under the curve TTP: Time to peak dilation UFP: Ultrafine particulate matter CO2: Carbon dioxide production E: Minute ventilation O2: Oxygen consumption O2max: Maximal oxygen consumption O2peak: Peak oxygen consumption xv  VOC: Volatile organic compounds VT: Tidal volume  xvi  Acknowledgements The University of British Columbia Graduate and Postdoctoral Studies, and Faculty of Education, and the Robert Caton Scholarship for Air Quality Research, provided financial support for my training. Financial support for my thesis work was provided by the Canadian Academy of Sport and Exercise Medicine, Health Canada, the Fraser Basin Council BC Clean Air Research Fund, the Natural Science and Engineering Research Council, and The University of British Columbia Faculty of Education. I would like to thank my supervisor and supervisory committee for their support and guidance during my PhD. Michael Koehle, you have provided unconditional support throughout the challenges of my PhD, you have provided the perfect balance of freedom and support that has allowed me to grow as a scientist and a person. You have always supported my decisions and helped me overcome the ebbs and flows of a PhD, more importantly you have always reminded me to get out and enjoy life outside of work. Chris, I will be forever grateful for the opportunities that you have provided. Your honest and critical evaluations of my work, as well as your enthusiasm and confidence in my work (often when I do not have it), have played a key role in my development throughout graduate school. Michael Brauer, I am thankful for your 20,000ft view of air pollution research, science and life, and your willingness to promptly offer help and provide guidance when it was needed. Jim, I am always thankful for your ?curve ball?, questions, they always keep me on my toes and remind me that there is so much to learn. I would like to thank past and present members of the Environmental Physiology Lab (Eric, Sarah, Normand), and the GRIP Lab (Pei, Cynthia, Martin, Kristen), the HIP Lab (Paolo, Glen, Meaghan) for their kind support and fun times along the way. I would like to thank Simon xvii  Adamson, Rei Ahn, Jason Brandenburg, Walter Cheung, Arminta Chicka, Shabnam Montazeri, Melanie Portal, and Normand Richard, who helped with data collection; as well as Walter Karlen, and Tavinder Ark, for their help with data processing and statistical analysis.  An enormous thank you to my friends for their support during my PhD. Kala, Marg, and Meg, our friendship is best summed up when you fed, watered, and paddled me around the Bowron Lakes. What more fun, dedicated and amazing friends can I ask for? SJ, I haven?t found the same kindness and sincerity in anyone else, I am so lucky that we met in the basement of Osborne in 2004. A huge thank you to my other lovely friends who distracted me during my PhD with fun skiing, mountain biking, climbing, and food obsessions (Tom, SJ, Par, Daisy, Marc, Nikki, Alex, Bethany, Dana, Brad, Ger, Suzanne, Sarah K, Andrew, Lina, Jay B, Paul, Angie).   To Mum, Dad and Dan, often unacknowledged, you have provided me with the confidence to try anything. You have supported me in everything that I have done, from lots of sports training and competitions, to a strange climbing habit that I picked up. Without question, you supported my choice to move thousands of miles away from home, despite (I?m sure) wanting me to stay. I am eternally grateful for the foundation that you gave me.  Jason, you are my pillar and my scientific mentor, and thank you in so many ways for making my PhD possible. You were the person who has kept me calm, grounded, fed, watered, rested and stress free while trying to recover from 2 head injuries during a PhD. You have unquestioningly supported and guided me with my decisions. It has been the icing on the cake to have a home office mate who is as excited to talk about science, eat amazing food, drink good coffee, ride bicycles, and play in the mountains. Thank you for your loyalty, your confidence in me, and all the fun that we have had in the last 5 years.  1 CHAPTER 1: LITERATURE REVIEW Regular physical activity decreases the likelihood of developing diseases such as heart disease, type-2 diabetes, cancer, and stroke [1, 2]. Furthermore, it is estimated that regular physical activity and exercise prevent 3.2 million premature deaths annually [3]. The most accessible forms of physical activity and exercise, such as walking, cycling, and running often occur outdoors. Globally, 52% of people live in urban centres whereas in the developed world this figure approaches 78% [4]. Therefore, for a significant proportion of the population these factors indicate that exercise participation may increase exposure to urban outdoor air pollution. 1.1 Introduction Air pollution is a complex mixture of gases and particles that are emitted directly from a source (primary), or is formed in the atmosphere (secondary) [5, 6].  In Canada, common air pollutants routinely monitored that have the potential to impact health during exercise include particulate matter (PM), carbon monoxide, ozone, sulphur dioxide (SO2), nitrogen oxides (including nitrogen oxide and nitrogen dioxide: NO2), volatile organic compounds (VOC), and ammonia. Through a series of reactions, primary gas emissions, such as SOx and nitrogen oxides, can be transformed into secondary sulphate and nitrate particles that will contribute to overall ambient PM.  In addition, in the presence of sunlight, VOC and nitrogen oxide interact to form the secondary pollutant ozone. Below is a summary of the common air pollutants monitored in Canada that are relevant to this dissertation. 1.1.1 Particulate matter Particulate matter is a mixture of solid and liquid components of varying sizes and chemical compositions. Sources of PM include wood and fossil fuel combustion, incense and candle burning, the oxidation of gases emitted from automobiles and power plants, as well as  2 natural sources such as wind blown dust and wildfires [5]. Particulate matter is typically categorized by its mass median aerodynamic diameter, which differs from geometric diameter. Aerodynamic diameter standardizes the shape and density of a particle, it considers the behavior of the particle in air, which plays a key role in deposition in the respiratory tract and associated health effects. Particulate matter is grouped into three size fractions that are summarized below in Table 1.1.  Table 1.1 Size classifications of particulate matter Name Abbreviation Description Coarse PM PM2.5-10 PM with a mass median aerodynamic diameter between 2.5 ?m and 10 ?m Fine PM PM2.5 PM with a mass median aerodynamic diameter of 2.5 ?m or less Ultrafine PM  UFP or PM0.1 PM with a geometric median diameter of 0.1 ?m or less Abbreviations: PM: particulate matter Particulate matter exposure in the fine and ultrafine range is associated with mortality and the development of cardiovascular and respiratory conditions such as myocardial infarction, stroke, atherosclerosis, chronic bronchitis, and asthma [7-11]. The cardiovascular and respiratory health outcomes due to PM exposure can initiate through pulmonary oxidative stress and inflammation [12]. Reactive oxygen species generated on the surface of PM cause oxidative stress that stimulates airway epithelial cells to express inflammatory cytokines [13-16]. The oxidative damage and chronic inflammation due to PM exposure plays a role in asthma and COPD through airway remodeling or by enhancing atopy [17-19]. Particulate matter exposure can also perturb the autonomic nervous system or translocate into the circulation.  Pulmonary inflammation, autonomic nervous system disruption, and particle translocation (independently and collectively) may result in systemic oxidative stress, systemic inflammation, platelet  3 aggregation, vasoconstriction, endothelial dysfunction, increases in blood pressure and heart rate, arrhythmias, hypercoagulability, decreases in heart rate variability (HRV), and atherosclerotic progression and plaque vulnerability [12, 20].  1.1.2 Carbon monoxide Carbon monoxide is a colorless, odorless gas that is produced from the incomplete combustion of fuels containing carbon [21]. Common outdoor sources of carbon monoxide include car exhaust fumes (gasoline and diesel), stationary combustion equipment such as heating and power generating plants, smoke from fires, and gas-powered engines [22-24]. Outdoor concentrations are highest near car exhaust, in congestion, and near traffic intersections [23]. Typical eight-hour concentrations in European cities are 17 ppm with short peaks below 53 ppm [25]. Carbon monoxide exerts a toxic health effect through hypoxic and non-hypoxic mechanisms and has a 210-240 times greater affinity for hemoglobin (Hb) compared with O2. Approximately 80?90% of absorbed carbon monoxide binds with Hb to form carboxyhemoglobin (COHb), which reduces the O2-carrying capacity of blood and leads to tissue hypoxia [22, 24, 26, 27]. Carbon monoxide exposure may result in a pro-oxidant cellular environment [28] and affect mitochondrial respiratory chain components: both of which attenuate energy production and cause cellular injury or dysfunction [29] 1.1.3 Ozone Ground level ozone is a secondary gaseous pollutant that forms by chemical reactions in the atmosphere involving nitrogen dioxide, sunlight, and hydrocarbons [5]. Mean one-hour maximum concentrations in North America and Europe can approach 100 ppb [5]. However, in cities such as S?o Paulo and Mexico City, concentrations may exceed 200 ppb for several days  4 [5]. Many monitoring locations in the US often exceed the World Health Organization eight-hour ozone guideline of 50 ppb [30]. Ozone is a respiratory irritant that impairs pulmonary function and heart rate variability, causes lung inflammation airway hyper-responsiveness, and may interact with lung defense mechanisms by impairing mucociliary clearance, decreasing macrophage activity and depleting airway antioxidant defenses [5, 31, 32]. 1.1.4 Sulphur dioxide Sulphur dioxide is a gaseous air pollutant produced from the combustion of fuels containing sulphur. In most developed countries, the sulphur content in motor fuel tends to be low; however, in developing countries the burning of coal and the combustion of fuel containing higher sulphur content are major sources of SO2 [5]. Concentrations of SO2 have been declining in Europe and North America with daily concentrations rarely exceeding 0.044 ppm [25]. Inhalation of SO2 can rapidly (within 10 minutes) reduce lung function, increase airway resistance, and cause wheezing and shortness of breath [33-35]; however, concentrations typically exceeding ambient concentrations (> 0.25 ppm) are required to elicit changes. 1.1.5 Nitrogen oxides Nitrogen oxides are a group of nitrogen containing compounds that include nitrogen oxide and nitrogen dioxide (NO2), which are produced during fuel combustion. Road traffic and electricity generation are major sources of nitrogen oxides outdoors. Nitrogen oxide contributes to 95% of the total nitrogen oxides and NO2 contributes to 5% of the total nitrogen oxides emitted from road traffic and electricity generation [5]. Of the family of nitrogen oxides, nitrogen dioxide is of concern to human health [25]. Outdoor concentrations of NO2 by busy roadsides can exceed 0.5ppm [5]; however, concentrations greater than 1 ppm are necessary to impair pulmonary function in healthy adults (although asthmatics tend to be more sensitive) [5].  5 1.1.6 Volatile organic compounds Volatile organic compounds are carbon-containing vapors that can originate from the evaporation of liquid fuel (e.g. benzene from vehicle fuel). Additionally, partially burned or unburned fuel fragments can be emitted as VOC from the combustion of fossil fuels and from the incineration process [5]. Volatile organic compounds contribute to ozone formation, the secondary formation of PM, and may impact health as carcinogens or neurotoxins. High concentrations of VOC cause pulmonary inflammation and impair pulmonary function; benzene specifically is associated with an increased risk of leukemia [36-38] 1.2 Why diesel exhaust? For this thesis, diluted and aged diesel exhaust (DE) was chosen as a model air pollution mixture as, unlike exposure to carbon monoxide or ozone (i.e. singular gaseous exposure), DE contains both gaseous and particulate elements; therefore, it is more representative of ambient conditions. Although DE alone does not perfectly mimic ambient air pollution, it is a mixture that can provide an array of different stimuli to exercising subjects. Additionally, DE was chosen to represent a mixture similar to that in an urban street canyon. For example, in a street canyon in close proximity to a major highway peak particle number concentration (PNC) was similar to experimental exposures conducted in our laboratory, where PNC exceeds 300,000 particles/cm3 [39, 40]. Furthermore, 30-min peak carbon monoxide concentrations in downtown street canyons exceed carbon monoxide concentrations within our laboratory (17.5-35 ppm vs. 11.2 ppm in the current study) [39, 41]. The combustion of diesel fuel generates a complex mixture of gases and particles. Gaseous components of DE include carbon monoxide, carbon dioxide, oxygen, water vapor, nitrogen oxides, sulphur compounds, and VOC [42]. Additionally, DE contains particulate matter (PM) in the fine (<2.5 microns: PM2.5) and ultrafine (<0.1 micron) range. The PM within  6 DE is composed of elemental carbon, adsorbed organic compounds, and small amounts of sulphate, nitrate, metals, and trace elements [42, 43]. The use of diesel fuel has increased significantly since the 1990s and freight transport has doubled since the 1970s; therefore, the contribution of DE to the fuel market is expected to increase a further 20% by 2020[44]. Diesel exhaust contributes to ambient PM; however, individual exposure varies depending on the number and types of diesel engines, how the exhaust disperses, and time-activity patterns of the individual. In urban areas in the US, the contribution of DE to the total ambient PM can be up to 36% and it can reach 53% in locations in close proximity to diesel buses [42]. In the lower Fraser Valley of British Columbia, it is estimated that DE contributes to 19% of ambient PM [45]. However, within-city spatial variation may mean that some individuals are exposed to a mixture containing PM that predominantly originates from DE. Dilute DE exposure causes lung inflammation, depletes airway antioxidant defences and impairs vascular and fibrinolytic function [46-48].  1.3 Air pollutants of concern in during exercise with diesel exhaust exposure In outdoor air, individuals are exposed to a mixture that typically contains all of the criteria (common) air contaminants, with their proportions present in varying degrees. Compared to other commonly measured pollutants, PM is the constituent that is most consistently and independently related to daily and long-term mortality [49]. Furthermore, the cardiovascular effects of VOC, NO2, O3, and SO2 are not well understood and there is limited research focusing on exposure to criteria air contaminants during exercise. Of the components contained in DE, there is a reasonable body of research focusing on carbon monoxide, sulphur dioxide, and PM exposure during exercise. In a typical laboratory exposure to DE, the fuel can be low in sulphur and the concentration of carbon monoxide in the exhaust also tends to be lower than levels that elicit health effects in healthy individuals [39]. As sulphur and carbon monoxide concentrations  7 in DE are low and there is limited research on how other criteria pollutants affect health during exercise, the next section will focus on the health effects of PM exposure during exercise.  1.4 How exercise may increase susceptibility to particulate matter air pollution Inhalation studies have assessed the effects of breathing pattern (without exercise as a stimulus) on particle deposition. For particles smaller than 0.1 ?m in geometric median diameter, total deposition fraction (the percentage of particles that remain in the respiratory tree following inhalation) increases as particle size decreases (when participants have the same breathing pattern) [50]. In contrast, for particles greater than 1 ?m in aerodynamic diameter total deposition fraction increases with particle size [51]. During exercise a number of physiological changes occur that could exacerbate the effects of PM air pollution on health. Greater deposition fraction, a greater total particle deposition over the course of an exercise bout, and oral breathing could all increase the dose (the amount deposited and retained in the body) of PM [52-55]. The role that exercise plays in total particle deposition is multifaceted as there is a complex interaction between particle size and the total deposition fraction that is then dependent on tidal volume, breathing frequency, and airflow velocity. Irrespective of particle size, breathing patterns with longer respiratory times and larger tidal volumes result in the greatest deposition [50]. However, the typical response to exercise would encompass a shorter respiratory time accompanied by a larger tidal volume as well as an increase in respiratory rate and airflow velocity. During inhalation studies that involve no exercise, the total deposition fraction of particles (3 and 5 ?m in aerodynamic diameter) increases as tidal volume, respiratory rate, and airflow velocity also increase (following a similar pattern to exercise) [50]. In contrast, in studies where exercise is a stimulus to increase E, exercise does not impact deposition fraction of PM2.5. However, as E is elevated during exercise the total deposition of PM2.5 within the lungs  8 will be greater than during rest [56-59]. During exercise, UFP deposition fraction increases from 0.6 during rest, which means that 60% of ultrafine particles inhaled are not exhaled, to 0.8 during exercise [52, 53]. Over the course of an exercise bout, the combination of a greater deposition fraction and total inhaled PM (due to higher E) results in a fourfold increase in the total number of UFPs deposited in the airways during light exercise and a further doubling during high-intensity exercise [53, 55].  In addition to alterations in deposition that could occur with exercise, as exercise intensity increases, breathing switches from predominately nasal to oronasal [54]. As the nose plays an important role in particle removal, the transition to oral breathing may consequently lead to an increase in pulmonary particle deposition and potentially greater physiological effects. Following exercise, the speed of mucociliary transport in the lungs increases. The increase in transport may be related to elevated circulating catecholamines, greater lung movement or airflow during exercise, or stimulation of airway and parenchymal receptors that increases parasympathetic activity and therefore mucus secretion [60-62]. Based on the greater mucociliary transport following exercise, it is possible that PM removal from the lungs is also elevated. To support this, other research demonstrates that 2 h  and 24 h following exercise the retention of PM2.5 within the lungs is less, and the estimated bronchial clearance is greater, than compared to rest [59].  The greater total inhalation and deposition of PM during exercise occurs in opposition to the greater clearance of particles post-exercise, which makes the relationship between particles and health during exercise challenging to predict. If one assumes that the health effects of air pollution are proportional to the inhaled dose, one would expect the health effects to be greater following exercise than following rest. However, regular exercise plays a key role in improving  9 some of the physiological mechanisms and health outcomes that air pollution exposure may exacerbate. It is not well understood if exercise in air pollution is detrimental or not harmful to health. Gaining a better understanding of the interaction between air pollution and exercise should allow us to better advise individuals about exercising during bouts of high levels of air pollution.  1.5 The physiological effects of particulate matter air pollution exposure during exercise  1.5.1 Pulmonary inflammation Particulate matter air pollution causes pulmonary inflammation, which plays a role in development and exacerbation of asthma and COPD [63]. Pulmonary inflammation due to PM represents an important part of the inflammatory cascade that may lead to cardiovascular complications and can result in systemic inflammation, endothelial dysfunction, coagulation, thrombosis, and oxidative stress [12].  The fraction of exhaled nitric oxide (FeNO) is a non-invasive measure of pulmonary inflammation; FeNO correlates with the eosinophil count in induced sputum and bronchoalveolar lavage and is higher in asthmatics compared to non-asthmatics [64-66]. As exposure to air pollution causes pulmonary inflammation, and FeNO is a surrogate measure of pulmonary inflammation, one would expect FeNO to increase with air pollution exposure. Despite this assumption, the majority of studies indicate that acute exercise in a high pollution/high traffic area that contains PM is not associated with elevated FeNO in healthy individuals [67-69], which could be attributed to stress reductions in FeNO that offset the inflammatory effects of air pollution [70]. Similarly, a study of adolescent runners who trained regularly outdoors did not demonstrate any acute changes in pulmonary inflammation (measured by breath pH) following a training session despite 40% of test days occurring during air quality advisories [71]. In contrast,  10 only one study by Weichenthal et al. showed a small but significant relationship between FeNO and PM2.5 following cycling in traffic  (1.1 ppb increase in FeNO per 8.7 ?g/m3 increase in PM2.5; 95% CI, 0.08?2.2 ppb) [72]. Despite the association, Weichenthal et al. did not find significant differences in FeNO between the low and high-traffic route [72]; therefore, the importance of this relationship is unclear. Furthermore, as the FeNO value used to indicate eosinophilic pulmonary inflammation in asthmatics is  > 50 ppb, and < 25 ppb suggest that inflammation is less likely, the clinical relevance of such a small increase in FeNO (1.1 ppb) is unclear [73].  In addition to acute exposure, the pulmonary inflammatory effects of a chronically elevated air pollution dose from regular training are important to consider. Twelve weeks of training in an urban environment with higher levels of PM significantly increased FeNO, whereas individuals undergoing the same training plan in a rural environment did not experience the same increase [74]. The research on FeNO and exercise highlights the potential pulmonary inflammatory effects of chronic exposure to PM during exercise. Despite the lack of an acute change in FeNO with PM exposure during exercise, it would still be beneficial to gain a more comprehensive understanding of how FeNO could be affected by exercise in a polluted environment, particularly in a controlled laboratory setting where confounding factors such as stress do not play a role. 1.5.2  Pulmonary function Exposure to air pollution containing PM impairs pulmonary function [75-78], which may be the result of oxidative stress, greater bronchial responsiveness, greater airway resistance, and an increase in airway inflammatory cells [79, 80]. Studies examining how acute exposure to air pollution (containing PM) during exercise affects lung function are inconsistent. Studies in  11 healthy adolescents suggest that forced expiratory volume in 1 second (FEV1) is significantly lower following moderate exercise in ambient air containing PM (compared to purified air) [81]. Similarly, in healthy adults, FEV1 (~2% decrease) and forced expiratory flow in the middle 50% of expiration (FEF25-75; ~6% decrease) significantly decrease following high-intensity exercise (30 minutes (min) at 85%-90% of maximum heart rate) in a high PM1 environment (77,529 particles/cm3) compared to a low PM1 environment (7382 particles/cm3) [68]. Asthmatics tend to be more sensitive to air pollution exposure, requiring only moderate exercise (walking) during exposure to adversely affect FEV1 and FVC [82, 83]. In contrast to research suggesting that pulmonary function is impaired by PM exposure, other studies do not find any effects [84, 85]. For example, Strak et al. [85] found that cycling 7.7-8 km on a high traffic (28,443 particles/cm3) compared to low traffic route (18,047 particles/cm3) did not impair pulmonary function. Similarly, Jarjour et al. [84] found that cycling for 8-9.5 km on a high traffic (18,545 particles/cm3) compared to low traffic route (14,311 particles/cm3) did not impair pulmonary function. It is possible that Strak et al. and Jarjour et al. did not observe pulmonary effects because the UFP concentration during the ?high? exposure condition was considerably less than during the study of Rundell et al. [68]  This contrast implies that the pulmonary effects of PM exposure during exercise could be dose-dependent. However, as the research is conflicting it is difficult to conclude how exercise with exposure to PM acutely affects pulmonary function. The effect of chronic PM exposure (weeks-years) during exercise on pulmonary function has also been examined. Female ice hockey players were followed for four years; two years were spent training regularly in ice arenas with low levels of PM1 followed by 2 years of training regularly in ice arenas with high concentrations of PM1. Compared to training in a low PM1 arena, baseline FEV1 and FEF25-75 following two years of training in a high PM1 arena were  12 significantly decreased by up to 11%, and 22%, respectively [86]. The authors attributed the decrements in baseline pulmonary function to the high concentrations of PM arising from fossil fuel ice resurfacers. It is also possible that the pulmonary effects could be attributed to NO2; however, the authors suggested that there were no unacceptable levels of NO2 (< 1ppm) in arenas throughout the study [86]. In conclusion, acute and chronic PM exposure during exercise may impair pulmonary function; however, the results are inconsistent and confounded by differing exercise protocols, air pollution mixtures, and inhaled doses of air pollution. The confounding factors make it difficult to draw conclusions on how acute air pollution exposure during exercise affects pulmonary function. Despite this, the adverse effects may be more apparent in vulnerable populations such as asthmatics and children as well as following chronic exposures during exercise. Therefore, until further research is conducted vulnerable populations may want to consider avoiding air pollution exposure during exercise. 1.5.3 Endothelial vascular function A disturbance in endothelial function is considered a key event in the development and clinical manifestation of atherosclerosis [87].  Additionally, reduced endothelial function is associated with future cardiovascular events in those with cardiovascular disease [88]. Flow-mediated dilation (FMD) is a technique used to assess nitric oxide (NO) mediated vasodilation and endothelial function [89]. In healthy individuals and in those with cardiovascular disease, exposure to air pollution containing PM impairs endothelial function [12]. However, there are only a small number of studies assessing the vascular effect of PM exposure during exercise and these show conflicting results. In healthy individuals, some research suggests that acute exposure to high levels of PM1 (gasoline engine) during exercise impairs vascular function (measured by  13 FMD) [90-92] and increases pulmonary artery pressure [90]. In contrast, acute exposure to high levels of PM2.5 with exercise does not cause microvascular dysfunction [93, 94] despite the dysfunction being present with rest [94], implying that exercise may offset the adverse effects of PM. The affect of exposure to PM on post-exercise brachial artery diameter is also unclear [91, 92]. The differences in air pollution mixture, exercise duration and intensity, and measurements of endothelial function make it challenging to conclude how PM exposure during exercise affects endothelial function. However, given the key role that endothelial function plays in cardiovascular disease and the response to exercise training, endothelial function would be an important parameter to research further.  1.5.4 Systemic inflammation Systemic inflammation predicts future cardiovascular events [95] and may play an important role in how air pollution affects the cardiovascular system [12]. In laboratory studies, acute exposure to DE containing high levels of PM2.5 causes platelet activation with exercise, but not during rest, implying that exercise may exacerbate the effects of PM2.5 exposure on health [96]. Field studies suggest that following acute exposure with exercise, parameters such as neutrophil and white blood cell count (WBC) as well as markers of systemic oxidative stress and DNA damage increase following exposure to PM in traffic and by inhaling particle-rich air [67, 97, 98]. Chronic exposure to air pollution by training in an urban environment with high levels of UFP increases WBC and neutrophil count compared to training in a rural environment with lower levels of UFP [74]. As the above studies vary methodologically and do not always have overlapping end points/measures, it is difficult to draw conclusions; therefore, more research examining the systemic inflammatory effects of air pollution containing PM would be beneficial.  14 1.6 Exercise performance in air pollution Exercise competitions have been held in countries with poor air quality [99, 100]; therefore, understanding how air pollution affects exercise performance will provide important information for future events taking place in polluted environments. Initial studies assessing the effects of air pollution exposure on exercise performance date back to the 1960s and involved exposure to car exhaust [101]. Since then, the effects of air pollutants such as PM, ozone, and carbon monoxide have been investigated; however, as in a typical laboratory exposure to DE, the fuel can be low in sulphur and the concentration of carbon monoxide in the exhaust also tends to be lower than levels that elicit health effects in healthy individuals the next section will focus on the effects of PM exposure on exercise performance.  In children, higher levels of PM10 are negatively associated with cardio-respiratory fitness and predicted maximal oxygen consumption ( O2max) [102, 103].  In women, but not men, there is also an association between higher PM10 levels and reduced marathon performance [104]. Additionally, experimental studies imply that acute exposure to PM during exercise impairs maximal accumulated work on a six-minute exercise test [90, 105]. The small body of research indicates that exercise performance is impaired with exposure to air pollution containing PM; however, as there are only a few experimental studies in this area, further investigations are warranted.  1.7 Balancing risk and benefit Exercise plays a key role in improving some of the physiological mechanisms and health outcomes that air pollution exposure may exacerbate. Acutely, increases in arterial compliance and distencibility following exercise [106, 107], exercise-induced hypotension [108], and exercise induced bronchodilation [109] may offset any the effects of air pollution exposure.  15 Furthermore, regular exercise reduces blood pressure, systemic inflammation, and the risk of blood coagulation, and enhances autonomic tone and endothelial function. All of which may play a role in lowering the risk of heart disease and stroke [110, 111] but may be adversely affected by air pollution exposure [12].  Animal studies support the notion that exercise protects against adverse effects of PM. Specifically, studies show that aerobic exercise training protects against air pollution and environmental tobacco smoke-induced lung inflammation [112, 113], the pro-inflammatory response to inhaled aluminum refinery dust [114], and ozone-induced oxidative stress [115]. In humans, low physical fitness and obesity increase the effects of air pollution on increasing blood pressure [116]. For a 10.5 ?g/m3 increase in PM2.5, individuals with a resting heart rate greater than 70 bpm experienced a significant increase in exercise diastolic and mean arterial pressure. However, the change in blood pressure is not seen in those with a heart rate less than 70 bpm [117]. As regular exercisers have lower heart rates, this research suggests that there is a differential response to exercise in air pollution that depends on fitness level. Finally, a series of impact assessments have been conducted to estimate the population health implications of exercising in air pollution.  These studies, using hypothetical scenarios and estimates from epidemiologic research, suggest that the beneficial effects of exercise outweigh the adverse effects of air pollution [118-122] and that exercise offsets the adverse impacts of air pollution-related mortality [122, 123].  For example, a modeling study in The Netherlands estimated that 3-14 months of life could be gained by cycling regularly compared to 1-40 days lost due to additional air pollution exposure [118]. Active commuting is associated with an 11% reduction in cardiovascular risk compared with those who do not actively commute [120].  Further, exercising at least once per month may protect against air pollution-related mortality  16 [122, 123]. Finally, the estimated savings in health care costs from the health benefits and pollution reductions due to cycling could be up to $7 billion/year [119]. 1.8 Conclusions and research gaps Exposure to air pollution during exercise impairs pulmonary function, endothelial function, and exercise performance while increasing systemic inflammation and markers of thrombosis. However, the data are far from comprehensive and are confounded by exposure to pollutant mixtures containing varying concentrations of pollutants, different exercise protocols, and different measurements to assess the same health outcome.  Given the role that pulmonary function, pulmonary inflammation, and systemic inflammation may play in the cardiovascular response to air pollution, not to mention the pathophysiological basis of impaired vascular function with PM exposure, the effects of air pollution exposure during exercise on these specified health outcomes warrant further investigation.  1.9 Thesis rationale Cardio-respiratory events are strongly associated with exposure to PM2.5 from traffic where DE is a key source [12, 63, 124]. Acute and regular exercise results in physiological changes that could offset some of the pathophysiological effects of air pollution. Additionally, the beneficial effects of high-intensity exercise on longevity and risk of cardiovascular disease are greater than lower intensity exercise [125, 126]. Currently, the recommendations for exercising in air pollution are not based on a substantial body of research that addresses if exercise enhances the effect of air pollution [127]. These recommendations advise individuals to reduce vigorous activity during times of high levels of pollution, which for competing athletes and ambitious amateurs may be unrealistic. Additionally, as some individuals live in areas with  17 consistently poor air quality, the advice to reduce or reschedule exercise would result in the individuals not exercising frequently enough to gain health benefits. One might expect that as exercise intensity increases, the dose of air pollution also increases, and this could lead to greater physiological impairments; therefore, advising individuals to modify exercise intensity during bouts of high pollution makes intuitive sense. Despite this rationale, the physiological responses to air pollution and exercise in isolation are complex; therefore, predicting the resultant physiological responses when exercise and air pollution interact are particularly challenging. There are currently no studies assessing the effects of exposure to air pollution during exercise of different intensities. Furthermore, recommendations for exercising in air pollution, such as those provided by the Air Quality Health Index do not encourage individuals to take into account the exposure preceding exercise. Therefore, it is important to generate novel data with a tailored study design to better understand how the cardio-respiratory system responds to different exercise intensities during exposure to air pollution such as DE. Such research may allow us to better advise individuals about how to modify exercise routines during bouts of high pollution.  1.10 Objectives The principal objectives of this doctoral thesis are to: 1. Determine if the cardiovascular, respiratory, systemic inflammatory, and autonomic nervous system responses to exercise in DE differ from exercise in FA;   2. Determine if the cardiovascular, respiratory, systemic inflammatory, and autonomic nervous system responses to exercise in DE are potentiated by increasing exercise intensity;  3. Determine how exposure to DE prior to exercise affects the cardio-respiratory system and subsequent exercise performance.  18 1.11 Hypotheses The hypotheses in this section are based on the assumption that a proportional increase in the dose of DE would result in proportionally greater physiological or health effects.  1. Exposure to DE will impair cardio-pulmonary system function, increase systemic inflammation, and cause alterations in the autonomic nervous system. 2. The magnitude of physiological effects due to DE will be proportional to the exercise intensity.  3. Exposure to DE prior to exercise will impair the cardio-respiratory system and exercise performance. More detailed hypotheses on specific outcome measures can be found in Appendix A.  19 CHAPTER 2: RESEARCH OVERVIEW 2.1 Methods overview There are two main projects detailed in this thesis; Project 1 is summarized in Chapters 3, 4 and 5, and Project 2 is summarized in Chapter 6. To decrease redundancy within Chapters 3, 4, and 5 the commonalities are briefly described below while the methodology that is specific to only one chapter is discussed in detail in their respective chapter. The methodology for Project 2 is summarised in detail in section 6.2. 2.1.1 Project 1 2.1.1.1 Participants Eighteen recreationally active Caucasian males aged 24.5 (6.2) yr (mean (sd); height: 1.78 (0.08) m, body mass: 74.2 (10.5) kg), volunteered for the study. We chose recreationally active individuals to mitigate confounding adverse effects of sedentary behavior on our measures, and because less fit individuals might not be motivated to complete the challenging exercise protocols in the study. Participants were considered recreationally active and included in the study if they met Canada?s physical activity guidelines of 150 minutes of moderate to vigorous activity per week. Only males were studied because parameters such as endothelial function and circulating nitrate vary across the menstrual cycle [128, 129]. Participants were recruited through poster and website advertisements. Flow mediated dilation was used as the basis for a sample size calculation as it is a key marker of cardiovascular health that can be impaired by pollutant exposure, and conversely improved by exercise training.  Thus, FMD is a key outcome to assess to understand the balance between the positive effects of exercise and the negative effects of pollutant exposure.  The sample size was calculated based on a minimal  20 detectable difference in FMD of 1.59%, using an effect size of 0.32, a power of 0.8, and an alpha of 0.05 [90]. Participants had a mean O2peak of 55.0 (9.1) mL?kg-1?min-1, a mean maximum power output of 320.4 (58.9) W, and a mean maximum heart rate of 182.1 (12.7) bpm. Each participant was a non-smoker and had no history of respiratory or cardiovascular disease. The Clinical Research Ethics Board of the University of British Columbia approved this study. Participants had an orientation session and a reflection period prior to signing the informed consent. Prior to all visits, participants were asked to refrain from food high in nitrites and nitrates for 48 h, exhaustive exercise and alcohol for 24 h, caffeine for 6 h, and food or non-water beverages for 2 h. Each participant performed all trials at the same time of day. Participants were also asked to maintain the same pre-test routine including the same mode of travel to the laboratory and pre-test meal, and were asked to restrict vitamin supplementation for the duration of the study. 2.1.1.2 Experimental design Each participant attended the lab on seven occasions (Figure 2.1). The initial visit served as familiarization for all study procedures; during the initial visit a maximal exercise test was also performed. On the remaining testing days, participants performed 30 min trials of low-intensity cycling, high-intensity cycling, or rest. Each intensity (including rest) was performed once in FA and once in DE containing 300 ?g/m3 of PM2.5, for a total of six trials, each of which was separated by a 7-day period. This dose of DE is occupationally relevant and has been experienced by miners, construction workers, mechanics, and dockside workers [130-132]. The concentration of PM2.5 is approximately 1 order of magnitude greater than 24-h ambient standard in Canada. Exercise intensity (rest, low-intensity, and high-intensity) and the exposure (FA and DE) were randomized. To avoid experimental bias, both the participant and research assistant  21 collecting the data were blinded to the exposure of FA or DE. Additionally, the residual smell within the laboratory resulting from previous DE exposures added to the potential blinding to DE or FA exposure. The crossover design was chosen for its inherent power to mitigate variability caused by between-subject differences.  Figure 2.1 Experimental design of project 1 detailing one maximal exercise test day and six experimental test days consisting of rest, low-intensity cycling, or high-intensity cycling with exposure to filtered air or diesel exhaust Days 2-7 Day 1 Maximal  Exercise Test Filtered Air Diesel Exhaust Low-intensity Rest High-intensity Low-intensity Rest High-intensity Days 2-7 were performed on different days with a 7 day period in between  22 2.1.1.3 Introductory session (day 1) Day 1 consisted of familiarization with all study procedures, obtaining informed consent, and performance of a maximal exercise test on a cycle ergometer. For the maximal exercise test, the cycling work rate started at 100 W and increased by 0.5 W/s until volitional exhaustion. Peak power was taken as the power output before cycling cadence dropped below 60 revolutions per min. Heart rate (HR), oxyhemoglobin saturation (pulse oximetry: SpO2), E, tidal volume (VT), frequency of breathing (FB), oxygen consumption ( O2), carbon dioxide production ( CO2), and respiratory exchange ratio (RER) were measured throughout the maximal exercise test. Peak values were taken as the highest 10s average. These variables were also measured during subsequent trials. To exclude those subjects with possible exercised-induced bronchoconstriction, any individual with a post-exercise decrease in FEV1 by 10% or greater was excluded from the study.  2.1.1.4 Testing days (days 2-7) Testing days 2-7 consisted of 30 min trials of cycling or 30 min of rest.  Work rates on cycling days were based on the peak power achieved during the maximal exercise test.  Low-intensity cycling was set at 30% of the power at O2peak (96.1 (17.7) W) and high-intensity cycling was set at 60% of power at O2peak (192.2 (35.3) W). During testing days containing cycling exercise, individuals first performed a self-selected 10-min warm-up. Following this, individuals were attached to the breathing apparatus and the exposure chamber. Participants were told to begin cycling and 5 seconds following the initiation of cycling the full resistance was added to the cycle ergometer. Control exposures involved sitting for the same period of time (30 min), but without performing exercise.  During the 30 min exposure with cycling or rest,  23 respiratory and metabolic data were collected as detailed in Chapter 3. Prior to, immediately post, 1 h, and 2 h post-exercise cardiovascular, pulmonary, autonomic, and systemic measures were collected as detailed in Chapters 4 and 5 (Figure 2.2). For a more detailed overview of the specific measures performed in Figure 2.2 see sections 3.2, 4.2, 5.2 and Appendix B.   Figure 2.2 Overview of testing days 2-7 in project 1 detailing data collected prior to, during and following 30 min of rest, low-intensity cycling, or high-intensity cycling with exposure to filtered air or diesel exhaust  2.1.1.5 Apparatus Exercise tests were performed using a Velotron Dynafit Pro cycle ergometer (Racermate Inc, Seattle, WA, USA). During trials, participants breathed through a facemask (7450 Series, Hans Rudolph Inc, Kansas City, MO, USA) attached to a low-resistance, non-rebreathing valve (NRB 2700, Hans Rudolph Inc, Kansas City, MO, USA). Participants were outside the environmental booth with 3.2 cm diameter hoses (made from a high performance ethylene-vinyl acetate copolymer) connected from the inspired and expired sides of the non-rebreathing valve to the exposure booth (Figure 2.3).   24  Figure 2.3 Representation of the exposure and exercise set-up during test days for project 1 For all trials, end-tidal gases were analyzed breath-by-breath using O2 and CO2 analyzers (Vacumed Fast Response Edition 17625 and 17630, Ventura, CA, USA). Flow was measured using a heated athletic-range pneumotach (Vacumed R3813 to - 800 liters per minute; Ventura, CA, USA). Heart rate and SpO2 were measured using a heart rate monitor (S810, Polar Electro, Finland) and pulse oximeter at the ear or finger (Avant 9600, Nonin, Plymouth MN, USA). Data were acquired and converted to digital signals at a sampling frequency of 200Hz (PowerLab 16/30 ADInstruments, Colorado Springs, CO, USA) and viewed in real-time using commercially-available software (LabChart, ADInstruments, Colorado Springs, CO, USA).  2.1.1.6 Exposure set-up All exposures were performed using an environmental exposure booth [39]. For DE exposures, participants were exposed to calibrated, aged, and diluted DE containing 300?g/m3 of PM2.5. A schematic of the exposure system can be found in Figure 2.4. An Environmental Protection Agency Tier 3-compliant, 5.5 kW diesel generator was operated under a constant 2.5 kW load. A portion of the raw exhaust was drawn into the primary dilution system and diluted  25 9:1 with compressed air, resulting in an atmospheric-like exposure inside the 1.2?1.8?2.1 meter exposure booth. The aging of particles from source to subject was approximately five min. In-booth PM mass concentration measurements were made using a Tapered Element Oscillating Microbalance (TEOM; Model 1400a, Rupprecht & Pattashnick, Albany, NY, USA) using 10 min averages. The TEOM was set to 30 C and the data were not adjusted for documented losses due to the heating element of the TEOM. A TSI Scanning Mobility Particle Scanner (Model 3936, TSI, Shoreview, MN, USA) classified the particle size distribution between 2.5 nm and 1000 nm. Thermo Model 48C and Model 42C analyzers (Thermo Fisher Scientific, Mississauga, ON, Canada) were used to measure and record carbon monoxide and oxides of nitrogen concentration levels in the exposure booth, respectively.  A GrayWolf TG-503 probe was placed within the exposure booth and is used to measure the total volatile organic compounds (TVOC), relative humidity, and temperature in real-time. For FA exposures, participants were exposed to compressed, HEPA-filtered air. A summary of exposure data for Project 1 can be found in Table 2.1.  26   Figure 2.4 Production and delivery schematic of diluted and aged diesel exhaust. Reproduced with permission from Informa Healthcare (License# 3282710291200), original source was Birger et al. [39].  27 Table 2.1 Mean air pollutant concentrations during a 30 min exposure to filtered air or diesel exhaust with rest or cycling  Filtered Air Diesel Exhaust PM2.5 (?g/m3) 9.30 (6.20) 302.10 (6.50) PNC (#/cm3) 0.14 x 104 61.60 x 104 Median Particle Diameter (nm) 59.40 (1.80) 87.70 (0.60) NO2 (ppm) 0.04 (0.04) 0.58 (0.15) NO (ppm) 0.02 (0.02) 7.00 (0.09) Carbon Monoxide (ppm) 3.00 (0.40) 13.90 (2.10) Total VOC (ppb) 106 (62.8) 1310 (226.3)  Abbreviations: NO: Nitric oxide; NO2: Nitrogen dioxide PM2.5: Particulate matter with a mass median aerodynamic diameter less than 2.5 ?m; PNC: Particle number concentration; VOC: volatile organic compounds   28 CHAPTER 3: THE RESPIRATORY AND METABOLIC RESPONSES TO DIESEL EXHAUST EXPOSURE ARE MODIFIED BY CYCLING INTENSITY 3.1 Introduction Regular exercise reduces the risk of developing chronic diseases [1, 2], but some accessible forms of exercise (such as walking, cycling, and running) occur outdoors, which may increase exposure to urban air pollution. The combustion of diesel fuel generates PM2.5, UFP [43] and gases such as NO2 and carbon monoxide, which can adversely affect the cardiovascular and respiratory system. For example, PM2.5 and UFP may result in systemic oxidative stress and inflammation, platelet aggregation, vasoconstriction, endothelial dysfunction, increased blood pressure and heart rate, arrhythmias, hypercoagulability, decreased HRV, and atherosclerotic progression and plaque vulnerability [12, 20]. Nitrogen dioxide exposure can impair pulmonary function in healthy adults [5]. Carbon monoxide reduces the O2-carrying capacity of blood, leading to tissue hypoxia [22, 24, 26, 27], and exerts toxic effects through non-hypoxic mechanisms that result in a pro-oxidant cellular environment [28].  Oral breathing [54], greater particle intake and deposition [52, 53], and elevated E may increase air pollution dose during exercise and consequently lead to greater physiological effects. As exercise intensity increases, associated increases in E and total dose of air pollution could lead to even greater physiological responses. However, as the cardiovascular and respiratory response to exercise and air pollution in isolation is complex, we cannot assume that an increase in exercise intensity will lead to a proportionally greater physiological effect related to a greater air pollution dose.  29 How the respiratory and metabolic responses to exercise are affected by DE exposure and how these responses change with exercise intensity is unknown. If parameters such as E, O2, and HR are altered due to DE exposure, exercise efficiency and exercise performance could be impaired. In individuals with cardiovascular and respiratory conditions, DE exposure could cause additional cardiovascular and respiratory strain, resulting in adverse events or premature termination of exercise. Understanding how the cardio-respiratory system is affected by DE exposure during different exercise intensities is important, as it would allow us to advise individuals about how to modify exercise routines during bouts of high pollution. To this end, the purpose of this study was to determine the respiratory, metabolic, and perceptual responses to low- and high-intensity cycling during a DE exposure. We hypothesized that any physiological effects due to DE would be magnified as exercise intensity increases.  3.2 Methods A summary of participant data can be found in section 2.1.1.1, an overview of the general apparatus used in this chapter can be found in section 2.1.1.5, and an overview of the exposure setup can be found in section 2.1.1.6. An overview of the experimental design can be found in section 2.1.1.2. Day 1 consisted of familiarization with all study procedures and a maximal exercise test that is detailed in section 2.1.1.3. An overview of testing days 2-7 can be found in 2.1.1.4. Briefly, testing days 2-7 consisted of 30-min trials of cycling or rest. Each intensity (including rest) was performed once in FA and once in DE containing 300 ?g/m3 of PM2.5, for a total of six trials, each of which was separated by a 7-day period. Work rate for low-intensity cycling was set at 30% of power at O2peak (96.1 (17.7) W; mean (SD)), and for high-intensity cycling was set at 60% of power at O2peak (192.2 (35.3) W). Resting exposures involved  30 sitting with the same setup as during the cycling trials and for the same period of time (30 min), but without performing exercise.   For all trials, E, VT, FB, O2, CO2, RER, were measured and calculated on a breath-by-breath basis and then averaged every 10 s. Heart rate and SpO2 were measured continuously. All variables were measured using equipment described in section 2.1.1.5. All data, aside from SpO2, were averaged over the 30 min exposure period and subsequently used for analysis. Due to equipment limitations, three participants had their SpO2 measured using a finger pulse oximeter, while the remainder used an ear oximeter. To mitigate differences in SpO2 between the ear and finger oximeter, SpO2 was analyzed as the mean change from baseline over the 30 min test.  During low and high-intensity cycling, the ratio of the mean O2 over the 30 min trial to power output was used as an indication of the O2 cost of exercise during trials. Additionally, gross efficiency was calculated using the ratio of power output to energy expenditure using the following accepted equations [133]:   Gross efficiency = power output ?100%/ energy expenditure Energy expenditure = [(3.89 ? O2) + (1.195 ? CO2)] ? [(4.186/60) ?1000]  For each test day, work of breathing (WoB) and respiratory muscle oxygen consumption (RM O2) were estimated using the mean E over the 30 min trial and the following equations proposed by Coast et al. [134]:  31  Work of Breathing (WoB) = -0.430 + (0.0504? E) + (0.00161? E2) kg?m?min-1 Respiratory muscle O2 consumption (RM O2) = 34.9 + (7.45?WoB) mL?min-1   During the final min of trials, rating of perceived exertion (RPE) for the lungs (RPELungs) and legs (RPELegs) were recorded on a 6-20 Borg scale. Prior to this measurement participants were familiarized with the scale, when the measurement was conducted individuals were first asked on a scale of 6-20 for RPELungs followed by RPELegs. 3.2.1 Exposure setup All exposures were performed using an environmental exposure booth described in detail elsewhere [20, 39] and in section 2.1.1.6. For FA exposures, participants were exposed to compressed, HEPA-filtered air.  For DE exposures, participants were exposed to freshly generated DE, diluted to 300 ?g/m3 of PM2.5 and containing 0.58 ppm of NO2 and 7 ppm of NO. 3.2.2 Statistical analysis Statistical analyses were completed using SPSS software (SPSS Inc, version 20, Chicago, IL). For each parameter, data were analyzed using a 2 (exposure: FA vs. DE) x 3 (intensity: rest, low-intensity, high-intensity) repeated measures analysis of variance (ANOVA). Significance was set at p<0.05. For all repeated measures ANOVA, the Huynh-Feldt adjustment was used to correct for violations of sphericity. Main or interaction effects were further analyzed using paired t-tests comparisons. All means are reported with standard deviations in parentheses. The  32 statistical analyses chosen were based on consultation with a statistician with relevant expertise in human experimental studies. 3.3 Results All participants performed all six trials, although three participants were unable to finish the high-intensity trial in DE due to discomfort/cramping. Therefore, in these individuals the second high-intensity exercise trial mimicked the first, in that the duration in the FA trial was reduced to match the DE trial. This meant that exercise was performed for the same duration and intensity for both FA and DE. In these individuals, only the first 20 min of data for both FA and DE were used. 3.3.1 Exposures A summary of exposure data can be found in Table 2.1. As expected, there were main effects of exposure for PM2.5, PNC, median particle diameter, nitrogen dioxide (NO2), and carbon monoxide, which were significantly greater during DE exposure (p<0.001 for all variables). There was a main effect of exercise intensity for NO2, which was significantly greater on rest days compared to high-intensity days (0.35 (0.02) vs. 0.28 (0.02) ppm; p=0.013). There were no other main effects of exercise intensity between rest, low-intensity, and high-intensity days for all exposure variables. There were no main or interaction effects for temperature or humidity.  3.3.2 Cardio-respiratory and metabolic responses  During low and high-intensity cycling (combined FA and DE), heart rate was 68% and 91% of maximum, respectively.  The mean O2 during low- and high-intensity cycling (combined FA and DE) was 48% and 77% of VO2peak. As expected, there were main effects of  33 intensity for all variables. There was a main effect of exposure on RER, which was lower in DE compared to FA. When pooled across exercise intensities, RER was 0.02 lower in DE vs. FA (p=0.008, Figure 3.1a). The RPELungs (p=0.001, Figure 3.2) and RPELegs (p=0.017, Figure 3.2) were significantly greater in DE exposure compared to FA. When pooled across exercise intensities RPELungs was 0.9 greater and RPELegs 0.6 greater in DE vs. FA. There was a trend towards a decrease in gross efficiency (0.7% decrease; p=0.08, Figure 3.3) in DE compared to FA. There were no main effects of exposure for HR, VT, FB, SpO2, WoB, or RM O2 (Table 3.1). There was a significant interaction effect (exposure-by-intensity) for E (p=0.021), O2 (p=0.046), CO2 (p=0.049), and the ratio of O2 consumption to power output (p=0.004). Follow-up analysis revealed that during low-intensity exercise, O2 (3 mL?kg-1?min-1 increase, p=0.001, Figure 3.1b), E (4 L?min-1 increase, p<0.001, Figure 3.1c), CO2 (2.3 mL?kg-1?min-1 increase; p=0.006, Figure 3.1d), and ratio of O2 consumption to power output (0.034 O2 ?W-1 increase; p=0.003, Figure 3.3) were significantly greater during DE exposure. There were no interaction effects for HR, VT, FB, RER, SpO2, RPELungs, RPELegs, WoB, RM O2 or gross efficiency.  34  Figure 3.1(a) RER, (b) O2, (c) E, and (d) CO2 in 18 recreationally-active males during 30 min of rest, low-intensity cycling, or high-intensity cycling in filtered air or diesel exhaust Abbreviations: RER: Respiratory exchange ratio; CO2: carbon dioxide production; E: Minute ventilation; O2; oxygen consumption.  * = a main effect of exposure for RER  35  Figure 3.2 (a) Rating of perceived exertion (RPE) for the lungs and (b) legs in 18 recreationally-active males in the final minute of 30 minutes of rest, low-intensity cycling, or high-intensity cycling in filtered air or diesel exhaust * = a main effect of exposure    36  Figure 3.3 (a) Ratio of oxygen consumption to power output (O2 cost of exercise) and gross efficiency (b) in 18 recreationally-active males during 30 min of low-intensity or high-intensity cycling in filtered air or diesel exhaust    37 Table 3.1 Mean cardio-respiratory variables in eighteen recreationally-active males during rest, or low-intensity, or high-intensity cycling   Heart Rate (bpm) SpO2 (%) VT (L) FB  (breaths?min -1) WoB  (kg?m?min-1) RM O2 (mL?min-1) Rest 67.4 (9.5) 98.7 (1.4) 0.8 (0.3) 15.8 (3.0) 0.26 (0.11) 36.8 (0.9) Low-intensity 124.1 (14.2) 98.3 (1.7) 2.0 (0.4) 25.5 (4.7) 4.7 (1.6) 70.1 (11.8) High-intensity 166 (12.2) 97.7 (2.0) 2.5 (0.5) 37.5 (5.2) 14.0 (4.3) 139.3 (32.3)  Abbreviations: FB: Frequency of breathing; RM O2: Estimated respiratory muscle oxygen consumption; SpO2: Oxyhemoglobin saturation measured by pulse oximetry; WoB: Estimated work of breathing; VT: Tidal volume. Data are represented as diesel exhaust and filtered air combined.  38 3.4 Discussion This study is the first to determine the effects of simultaneous DE exposure and exercise on cardio-respiratory and metabolic parameters. In healthy recreationally-active males, we found that RER was significantly less, while RPELungs and RPELegs were significantly greater, in DE compared to FA. During low-intensity exercise E, O2, CO2, and the O2 cost of exercise were significantly greater in DE compared to FA, and these differences were not present during high-intensity exercise or rest. The effects of DE exposure on breathing pattern during exercise have not been adequately studied, but several studies have examined the effects of ozone during exercise.  In comparison to clean air, submaximal exercise with ozone exposure increases FB and decreases VT, while E is unchanged [135-146]. In the current study, during low-intensity exercise, VT and FB tended to be higher in DE compared to FA (ns), which resulted in a significantly greater E. The greater E in the current study could be the result of an increased stimulation of lung irritant receptors causing hyperpnoea and subsequently increasing E [147-150]. There are three major types of sensory receptors that innervate the airways and the lungs: C-fibres, irritant receptors (also known as rapidly acting pulmonary receptors), and slow adapting pulmonary receptors. Of these receptors, C-fibres and irritant receptors play a role in the pulmonary response to inhaled irritants and toxins [151]. With wood smoke and cigarette smoke exposure irritant receptors and C-fibres are stimulated. Irritant receptors cause an augmentation of ventilation, whereas C-fibres cause an initial attenuation of ventilation [147, 150-154]. It has been postulated that in single-breath exposures in animals, attenuation of ventilation from of C-fibres dominates [147, 151, 152]. However, how the C-fibre and irritant receptor activity  39 dominance changes with exercise, DE exposure, and in humans is unknown. Given that there was an elevated E in DE in the current study, it is possible that lung irritant receptors were stimulated to a greater extent and this caused the greater E. Also, one cannot discount that DE may have stimulated C-fibres causing neurogenic inflammation in the airway [155, 156], or that VOC within DE could have cause nasal and airway inflammation [36, 37]. An inflammatory response in the airway could have altered breathing pattern and thus E; however, as there were no differences in FEV1 or FeNO following DE exposure (see Chapter 5) the changes in E may be more likely related to irritant receptor stimulation. One other way in which DE may affect E is through hyperthermia. Rats exposed to DE experienced a 0.9?C increase in core temperature (1 h into exposure) [157], which was related to sympathetic nervous system activation. Increases in core temperature of ?1?C increase E [158]; therefore, the elevated E seen with low-intensity exercise in DE could be related to a greater increase in core temperature than that seen during FA.  During low-intensity exercise in DE we also found a significant increase in exercise O2 and CO2. We initially hypothesized that the greater O2 could be due to increased RMO2; however, our results do not support this, as the increase in RM O2 in DE compared to FA was not significant. The higher O2 in DE could be explained by a combination of factors potentially including: greater RM O2 related to elevated E and WoB, greater peripheral O2 due to an increase in extraneous movements during cycling that occurs in response to the increase in RPE in DE, elevated catecholamines that results from sympathetic nervous system  40 stimulation by DE, or increased myocardial O2 related to PM induced vasoconstriction, and therefore a small increase in afterload. Respiratory exchange ratio, the ratio of CO2 to O2, was reduced in DE. The decrease in RER with DE exposure may also be attributable to alterations in catecholamines. A decrease in RER represents an increase in O2 for a given CO2. Particulate matter exposure stimulates the sympathetic nervous system, which could play a role in epinephrine and norepinephrine release.  However, the role of PM exposure on catecholamine release is not fully understood. In obese rats, one day of exposure to concentrated ambient particles increases norepinephrine in regions of the brain [159], and in rabbits, three weeks of exposure to passive smoke increases plasma norepinephrine [160]. Acutely, rats exposed to smoke for three min, experienced an increase in norepinephrine compared to baseline [161]. To date one experimental study in humans did not find a consistent effect of DE exposure on catecholamines; however, the concentration of PM in DE was less than in the current study [162]. The higher concentration of PM in the current study may still have stimulated to sympathetic nervous system and any increases in epinephrine or norepinephrine could have resulted in an increased O2 compared to CO2, and thus decrease RER [163, 164]. We hypothesized that any physiological difference between DE and FA would be magnified as exercise intensity increased. However, our results do not support this hypothesis despite the higher dose of DE in the high-intensity exercise bout. The higher O2 in DE during low-intensity exercise, but not during high-intensity exercise, follows a similar pattern to exercise in the cold. Specifically, O2 is higher during submaximal exercise in the cold compared to a moderate environment, but this is not seen at near maximum exercise intensities  41 [165]. In the cold, the increase in O2 during submaximal exercise has been attributed to thermogenesis for shivering, which at high exercise intensities is not required due to metabolic heat production of the exercising muscles [165]. It is unlikely that similar mechanisms are occurring within the current study, but research in the cold highlights that we cannot always assume that physiological changes in extreme environments are potentiated by exercise intensity. A potential contributor to a greater E in DE compared to FA during low- but not high-intensity cycling could be related to the location of PM deposition within the respiratory tree. For example, as exercise intensity increases the deposition of PM in the alveolar-interstitial region of the lung also increases [55]. Irritant receptors that may play a role in the hyperpnoea due to air pollution exposure are found in the airway wall from the nasopharynx to the larger bronchi [166, 167]; therefore, if a higher proportion of particles are deposited peripherally in the alveolar-interstitial region during high-intensity exercise, the irritant receptors may be relatively less stimulated by PM during high-intensity exercise than low-intensity exercise. Lower stimulation of these receptors during high-intensity exercise in DE would not potentiate E, as seen in low-intensity exercise.  As we did not see differences during high-intensity exercise, it is also possible that the physiological stimulus of exercise outweighed the noxious stimulus of DE. For example, relative to lower-intensity exercise, high-intensity exercise will increase catecholamines [168, 169], core temperature [170], and decrease pH, all of which may increase E and O2. Compared to a resting concentration of 0.4 ng/mL, following moderate exercise and at maximal aerobic power, norepinephrine concentrations increase to 1.3 ng/mL and 2 ng/mL, respectively [169]. In comparison, rats exposed to smoke increase plasma norepinephrine concentration from 0.18  42 ng/mL to 0.66 ng/mL [161]. While comparing humans and animals is challenging, the approximately five-fold increase in norepinephrine due to high-intensity exercise may washout the threefold increase due to air pollution exposure, thus any exposure effect on O2 would not be seen. Whereas during moderate exercise, the smaller three fold increase in plasma norepinephrine may mean that the effects of DE are not washed out and the effect of norepinephrine (from DE) on O2 is apparent. In addition to a direct catecholamine effect, there could also be an indirect effect from the increased catecholamines present during high-intensity exercise. Following exercise, the speed of mucociliary transport in the lungs increases, which may be related to increased circulating catecholamines, greater lung movement or airflow during exercise, or stimulation of airway and parenchymal receptors that increase parasympathetic activity and thus mucus secretion [60-62]. Research demonstrates that 2 h following exercise, retention of PM within the lung is less, and estimated bronchial clearance is greater, than compared to rest [59]. Despite the greater inhalation of PM during high-intensity exercise, it is possible that particle clearance increases with exercise intensity and this may have played a role in the lack of effect during high-intensity exercise. However, if it is assumed that as exercise intensity increases greater deposition of PM occurs in the non-ciliated airways, it is unclear if particle removal by cilia plays a role [55]. To summarize, the greater E and O2 observed during low- but not high-intensity exercise in DE may be attributable to elevated catecholamines during high-intensity exercise that wash out the effects of DE, increased particle remove during high-intensity exercise, or PM bypassing irritant receptors during high-intensity exercise.  43 Compared to FA exposures, DE exposure significantly increased RPELungs, and RPELegs. Similarly, Flouris et al. found that 1 h of passive smoke inhalation followed by 30 min of cycling at 60% of O2max or a maximal exercise test, increased perceived exertion during exercise [171, 172]. McMurray et al. also found that exposure to cigarette smoke during 20 min of running at 70% O2max significantly increases perceived exertion [173]. These finding corroborate the elevated RPE in the current study and highlight that exercise following or during exposure to air pollution containing PM increases effort perception [171-173]. It is likely that the increase in RPELungs with DE exposure in this study is related to the high E that resulted from stimulation of irritant receptors in the lung [147-150]. A greater RPE will cause individuals to perceive exercise in air pollution to be more difficult or unpleasant.  Such a perception could impair exercise performance and participation in self-paced exercise as well as increase the chance of premature exercise termination. The increased effort perception due to pollution exposure is important to consider for those beginning an exercise program. The elevated perception may reduce adherence to an exercise program, and thus reduce the health gains while increasing the likelihood of morbidity or mortality. In those with cardio-respiratory disease, the higher effort perception (as well as increase respiratory and metabolic demand) may also cause premature exercise termination. The reduction in exercise duration due to premature exercise termination could translate into less exercise health benefits and increased morbidity. It cannot be discounted that the increased effort perception in DE serves as a protective mechanism; if elevated RPE did result in premature exercise termination this may aid in preventing adverse cardio-pulmonary effects associated with DE exposure. Gross efficiency is the ratio of work completed to energy expended and is known to influence exercise performance [174]. Within the current study, the ratio of O2 consumption to  44 power output was used to determine the O2 cost of exercise and one would expect that as the O2 cost of exercise increases, gross efficiency would decrease. Changes in E and O2 due to DE exposure may reduce gross efficiency, exercise economy, and increase the O2 cost of exercise, and thus impair exercise performance. Within the current study we did not measure exercise performance, although we estimated gross efficiency and the O2 cost of exercise, both of which allow us to make inferences about how exercise performance might be affected. There was a trend towards a decrease in gross efficiency in DE and a significant increase in the O2 cost of exercise during low-intensity exercise in DE. Studies of exercise performance in PM show that high levels of PM impair exercise performance (as measured by lower work accumulation on a six min maximal exercise trial) [90, 105]. The higher RPE, O2 cost of exercise, and lower gross efficiency seen in this study, although not direct performance measures, could account for the reductions in exercise performance seen during air pollution exposure. At higher workloads, the increased respiratory muscle work, O2 cost of exercise, and the decreased exercise efficiency could divert blood away from the exercising muscle, and thus impair exercise performance [174, 175]. We did not demonstrate an increase in the O2 cost of exercise during high-intensity exercise, but cannot discount that during maximal exercise the O2 cost of exercise could be affected.  3.5 Conclusion This study assessed the respiratory and metabolic responses to low- and high-intensity cycling with DE exposure in recreationally-active individuals. We found that a 30 min exposure to DE (300 ?g/m3 of PM2.5) significantly increased RPE and decreased RER. During low-intensity exercise, E, O2, CO2, and the O2 cost of exercise were significantly greater in DE. As these effects were not seen during high-intensity exercise, it is likely that the heavy  45 exercise stimuli outweigh the stimulus of air pollution, that particle removal is enhanced, and/or that alterations in regional deposition of PM differentially stimulate airway irritant receptors. Practically, the respiratory, metabolic, and perceptual responses during low-intensity exercise in DE could have implications for individuals with cardiopulmonary disease, resulting in adverse events or premature exercise termination. Also, the elevated RPE during DE could impair performance and participation in self-paced exercise.    46 CHAPTER 4: THE ENDOTHELIAL RESPONSES TO LOW- AND HIGH-INTENSITY CYCLING WITH DIESEL EXHAUST EXPOSURE 4.1 Introduction The endothelium is a thin layer of cells located on the inner lumen of the blood vessel which sense mechanical and chemical stimuli and respond by releasing substances that regulate vascular tone, cell adhesion, thrombosis, smooth cell proliferation and inflammation [176]. Endothelial dysfunction is characterized by impaired vasodilation, a pro-inflammatory state, and pro-thrombotic tendencies [177], and is considered a key event in the development of atherosclerosis [87]. Endothelial dysfunction occurs in those with chronic heart failure [178], hyperlipidemia [179], and hypertension [180], and is also a key predictor of future cardiovascular events in those with cardiovascular disease [181]. Improvements in endothelial function occur with regular exercise [182]. Likewise, compared to active individuals, sedentary individuals have impaired endothelial function as demonstrated by attenuated vasodilation in response to mechanical stimuli [110].  Particulate matter exposure is associated with cardiovascular mortality and morbidity, such as myocardial infarction and stroke [7, 9, 183-185]. Two of the major effects of PM on the cardiovascular system are vasoconstriction and endothelial dysfunction [12, 20]. The effects of exercise on the cardiovascular system are clear; specifically, the abovementioned improvement in endothelial function with regular exercise is a key mechanism in the reduction of cardiovascular disease risk [111, 182]. However, the limited research on how PM or DE exposure during exercise acutely affects endothelial function is conflicting [90-92]. During exercise, factors such as greater E, higher particle deposition fraction, total particle deposition,  47 and oral breathing increase the dose of air pollution [52-55, 186]. Furthermore, with increasing exercise intensity, dose should theoretically be magnified in healthy populations. The higher dose of DE during exercise may then increase the magnitude of physiological and health effects of air pollution, which may further increase with exercise intensity. Currently, recommendations regarding exercising in polluted environments are not based on a substantial body of research that addresses if exercise enhances the effect of air pollution. The recommendation to reduce strenuous activity during poor air quality assumes that when exercise intensity increases there will be a greater pathophysiological response resulting from the increased dose of air pollution. Understanding how a key mechanism in cardiovascular health (such as endothelial function) is affected by DE exposure during exercise would provide greater insight into the interaction between air pollution, exercise, and health. A better understanding of the relationship between exercise intensity and DE exposure would also allow us to advise individuals about how to modify exercise routines during bouts of high PM air pollution.  To this end, the purpose of this study was to determine the acute endothelial responses to low- and high-intensity cycling with DE exposure. We hypothesized that DE exposure would impair the endothelium and any physiological effects due to DE would be magnified as exercise intensity increases.  4.2 Methods A summary of participant data can be found in section 2.1.1.1, an overview of the general apparatus used in this chapter can be found in section 2.1.1.5, and an overview of the exposure setup can be found in section 2.1.1.6. An overview of the experimental design can be found in section 2.1.1.2. Day 1 consisted of familiarization with all study procedures and a maximal exercise test that is detailed in section 2.1.1.3. An overview of testing days 2-7 can be found in  48 2.1.1.4. Briefly, testing days 2-7 consisted of 30-min trials of cycling or rest. Each intensity (including rest) was performed once in FA and once in DE containing 300 ?g/m3 of PM2.5, for a total of six trials, each of which was separated by a 7-day period. Work rates on days 2-7 were based on the peak power achieved during the maximal exercise test.  Low-intensity cycling was set at 30% of power at O2peak (96.1 (17.7) W) and high-intensity cycling was set at 60% of power at O2peak (192.2 (35.3) W). Control exposures involved sitting with the same setup as cycling and for the same period of time (30 min), but without performing exercise.  4.2.1 Outcome measures and apparatus The following measurements were made prior to, immediately following, 1 h, and 2 h post each trial: endothelial function by FMD, plasma NOx (the sum of plasma nitrite and nitrate), and plasma endothelin-1 (Figure 4.1).   Figure 4.1 Overview of test day procedures prior to and following 30 min of rest, low-intensity, and high-intensity cycling in filtered air or diesel exhaust 4.2.1.1 Blood parameters Blood samples were taken from the right antecubital fossa with a 21-gauge needle. All blood samples were immediately centrifuged at 1500 g for 20 min to separate plasma from formed elements. Plasma was extracted, frozen, and stored at -80?C until assayed. Plasma concentrations of endothelin-1 were determined using commercially-available enzyme-linked  49 immunosorbent assay (ELISA) kits (Endothelin-1 Immunoassay Quantikine ELISA, R&D Systems, MN, USA) and according to the procedures outlined by the manufacturer. Plasma levels of endothelin-1 were measured using a Versa Max microplate reader (Molecular Devices Corporation, CA, USA). The duplicate-sample coefficient of variation for endothelin-1 assays within the current study was 3.5%.  Nitric oxide has a very short half-life [187]; therefore, end products of NO such as nitrate and nitrite are used as indicators of NO production [188, 189], and the sum of plasma nitrite and nitrate is referred to as plasma NOx. Plasma nitrite and nitrate levels were determined using a commercially-available assay kit (total nitric oxide and nitrate/nitrite assay, R&D Systems MN, USA) according to the procedures of the manufacturer.  Plasma levels of nitrite and nitrate were measured using a BioTek 96-well plate reader (BioTek Instruments, Winooski, VT, US). The duplicate sample coefficient of variation for nitrite and nitrate assays within the current study was 6.2%.  Levels of endothelin-1 and plasma NOx were adjusted for changes in plasma volume from baseline. The estimated post-exercise concentration of markers due to plasma volume changes alone was estimated using the following equation [190]:  where Hct represents hematocrit. The adjusted concentration was then calculated by subtracting the estimated concentration due to plasma volume changes from the pre-concentration; this difference was the added to the measured concentration within the plasma and is detailed in the following equation: ? ConcetrationESTIMATED=HctPOST? (100 ?HctPRE)HctPRE? (100 ?HctPOST)? ConcentrationPRE 50  4.2.1.2 Endothelial function Endothelial function was measured by FMD as per the guidelines of the International Brachial Artery Reactivity Task Force [191]. This technique assesses the change in diameter of the brachial artery following occlusion of the vessel with a pneumatic cuff.  For the duration of the test, participants were resting in a supine position. Prior to each sampling test, participants were supine for 20 min.  During the test, the participants left arm was extended and supported at an abduction angle of ?80? from the torso. For assessment of the FMD response, a blood pressure cuff was positioned on the imaged arm distal to the olecranon process to provide a stimulus of forearm ischemia. The brachial artery was imaged in the distal third of the upper arm; the site of measurement as well as transducer angle was the same for each person between trials. Following the 20 min resting period, the brachial artery diameter and blood flow velocity were measured at baseline for one min. Subsequently, the occlusion cuff was inflated to >200 mmHg for five min. Brachial artery diameter and velocity recordings were made at least 30 s before cuff deflation and continued for at least three min after deflation.  A Logiq I portable ultrasound scanner in 2D (General Electric Inc., Fairfield CT, USA), with a vascular transducer, was used to obtain images. These images were then captured as a video using a commercially-available frame grabber (VGA2USB LR frame grabber, Epiphan Systems, Ottawa, Ontario). Brachial artery diameters were analyzed using a previously validated edge detection and wall-tracking software (Medical Image Applications, Vascular Research Tolls 5, Coralville, IA) [192]. ? ConcentrationADJUSTED= (ConcentrationPRE?ConcentrationESTIMATED) +ConcentrationMEASURED 51 Brachial artery diameter and blood flow velocity were measured in 17 and 16 participants respectively, due to an inability to acquire adequate images in one participant and flow recordings in two participants. Diameter data included mean pre-occlusion brachial artery diameter, peak post-occlusion brachial artery diameter, FMD, and time to peak dilation (TTP). Pre-occlusion shear rate was calculated, and following cuff deflation, shear rate area under the curve (SRAUC) and FMD/SRAUC were calculated. Baseline diameter and shear rate were determined as the mean of one min prior to cuff inflation. Peak diameter following cuff deflation was automatically detected according to an algorithm that identified the maximum median within a 30-frame bracket of data (3 seconds). Each bracket of data had a 20% overlap with the previous bracket. The maximum value of all the calculated median values was automatically detected and chosen to represent the peak of the diameter curve. Flow-mediated dilation was calculated as the percentage rise of this peak diameter from the preceding baseline diameter. From synchronized measurements of diameter and velocity data at 10 Hz, shear rate was calculated as 8?(average flow velocity /diameter) [193]. The post-deflation SRAUC was calculated using a trapezoid function that sums the area under the curve to the point of peak dilation. The ratio of FMD to SRAUC was calculated to normalize FMD to the shear rate stimulus [194]. Despite the strong relationship between FMD and SRAUC in within-subject studies, it is still important to determine the correlation between the two variables. Given the potential role that exercise plays in the relationship between FMD and SRAUC relationship [195], the relationship between the 2 variables was explored pre- and post-exercise. Of the 408 measures of brachial artery diameter one was not used due to a technical error during the measurement. Similarly, of the 394 measures of flow velocity 30 were excluded due to a poor signal. To prevent complete exclusion of those subjects with missing measurements and based on the recommendations of a statistician, the missing values were replaced using regression imputation [196].  52 4.2.2 Exposure setup All exposures to DE or FA were performed using an environmental exposure booth that is described in detail elsewhere [20, 39] and in Section 2.1.1.6. For FA exposures, participants were exposed to compressed, HEPA-filtered air. For DE exposures, participants were exposed to freshly-generated DE, diluted to 300 ?g/m3 of PM2.5 and containing 0.58 ppm of NO2 and 7 ppm of NO. 4.2.3 Statistical analysis Statistical analyses were completed using SPSS software (SPSS Inc, version 20, Chicago, IL). For each parameter, data were analyzed using a 2 (exposure: FA vs. DE) x 3 (intensity: rest, low-intensity, high-intensity) x 4 (time: pre, post, 1 h, 2 h) repeated measures ANOVA. Significance was set at p<0.05. For all repeated measures ANOVA the Huynh-Feldt adjustment was used to correct for violations of sphericity. Main or interaction effects were further analyzed using pair-wise comparisons and significance was adjusted to account for multiple comparisons using the Sidak adjustment. The p-values represented within this thesis have been inflated to incorporate the Sidak adjustment, meaning that ? remains at 0.05. Specifically, the Sidak adjustment uses the following equation to adjust for multiple comparisons: 1- (1-unadjusted p-value)1/k, where k is the number of comparisons in the family. For the post-hoc analysis comparing exercise intensity, p-values were adjusted for 3 groups (rest, low-intensity and high-intensity) and when time was compared, p-values were adjusted for 4 groups (pre, post, 1h, 2h). All means are reported with standard deviations in parentheses. The statistical analyses chosen were based on consultation with a statistician.  53 4.3 Results Baseline outcome variables were not significantly different across the six test days (Appendix C.1). All participants performed all six trials, although three participants were unable to finish the high-intensity trial in DE due to discomfort/cramping. In individuals who were unable to finish the first high-intensity trial, the second high-intensity exercise trial was designed to mimic the first; therefore, the duration in trial two was reduced to match the first trial.  4.3.1 Exposures A summary of exposure data can be found in Table 2.1 and is summarized in detail in Section 3.3.1.  4.3.2 Plasma NOx There was a significant three-way interaction (exposure-by-intensity-by-time) for plasma NOx (Figure 4.2, p=0.006). Post-hoc analysis showed that following low- and high-intensity exercise in DE, plasma NOx levels were significantly higher than pre-exercise values, however this did not occur in FA. Therefore, following low- and high-intensity exercise, plasma NOx values were significantly higher in DE compared to FA (at immediately post and 1 h post only). The increases in plasma NOx that occurred following exercise in DE did not occur following rest. However, 2 h post-rest in DE, NOx levels were significantly less than immediately post and 1 h post-exposure. Plasma NOx levels were significantly higher following low- and high-intensity exercise in DE compared to rest and this difference did not occur following FA. Immediately post rest in FA, plasma NOx levels significantly lower than pre exposure. However no other differences were observed in FA. A detailed summary of p-values comparisons can be found in Appendix C.2.   54  Figure 4.2 Plasma NOx in 18 recreationally-active males prior to and following 30-min of (a) rest, (b) low-intensity cycling, or (c) high-intensity cycling in filtered air or diesel exhaust ? = significantly different from pre-exercise in the corresponding exposure, in (a) FA is only significant, in (b) and (c) DE is only significant; ? = significantly different from 2h (DE only); * = significantly greater than FA at the corresponding time point; ** = significantly greater than rest at the corresponding time point (comparing DE only); ? = significantly different from 1 h (DE only)  55 4.3.3 Endothelin-1 There was a significant exposure-by-time interaction for plasma endothelin-1 concentration (p=0.003l; Figure 4.3a). In both FA and DE, endothelin-1 levels increased over time. In FA, endothelin-1 levels became significantly elevated 2 h post-exposure compared to all other time points (2 h compared to: pre p<0.001, post p=0.003, 1 h p=0.005), whereas in DE, endothelin-1 levels were significantly greater at 1 h post compared to pre-exposure (p=0.023). Two hours following exposure to DE, endothelin-1 levels were significantly less than following FA (p=0.037 Figure 4.3a). There was a significant intensity-by-time interaction (p=0.001) for endothelin-1. Plasma endothelin-1 levels were significantly greater at 2 h following high-intensity exercise than all other time points during high-intensity exercise (2 h compared to: pre p=0.001, post p=0.005, 1 h p=0.024). Plasma endothelin-1 levels were also significantly greater at 2 h post high-intensity exercise compared to 2 h following low-intensity exercise (p=0.003) and rest (p=0.035, Figure 4.3b).  56  Figure 4.3 Plasma endothelin-1 in 18 recreationally-active males pre, post, 1 h- and 2 h- post (a) 30-min of exposure to filtered air or diesel exhaust (exposure-by-time interaction), or  (b) 30-min of rest, low-intensity cycling, or high-intensity cycling (intensity-by-time interaction) ? = significantly greater than pre-exercise (DE only); * = (a) significantly less than FA or (b) high-intensity at the corresponding time point; ? = significantly less than 2 h post (a) in FA only or (b) in high-intensity only   57 4.3.4 Endothelial function Prior to exercise there was a moderate but significant correlation between FMD and SRAUC (r=0.324, p<0.001); following exercise, this relationship weakened (r=0.221, p<0.001). There was a significant exposure-by-intensity interaction for FMD/SRAUC (p=0.014, Figure 4.4). In rest with DE, FMD/SRAUC was significantly greater than during low-intensity (p=0.029, Figure 4.4) and high-intensity exercise (p=0.000, Figure 4.4). Whereas in FA, FMD/SRAUC was only significantly lower in high-intensity compared to low-intensity exercise (p=0.039, Figure 4.4). On low-intensity exercise days FMD/SRAUC was significantly greater in FA compared to DE (p=0.032), and this did not occur on rest or high-intensity exercise days. There was no exposure-by-intensity interaction for FMD, pre-occlusion shear rate SRAUC, pre-occlusion artery diameter, peak artery diameter, and TTP.  There was a significant intensity-by-time interaction for pre-occlusion shear rate (p<0.001), SRAUC (p<0.001), pre-occlusion artery diameter (p=0.003), peak artery diameter (p=0.005), and TTP (p<0.001), which all increased following high-intensity exercise. For low-intensity exercise and rest, TTP, pre-occlusion shear rate, and SRAUC decreased over time, whereas baseline artery diameter and peak artery diameter did not change. Immediately post, and 1 h post, all variables were highest during high-intensity exercise and lowest during rest (see Appendix C.3 and C.4 for detailed post-hoc comparisons). There was no intensity-by-time interaction for FMD, or FMD/SRAUC.   58   Figure 4.4 FMD/SRAUC in 18 recreationally-active males on rest, low-intensity cycling, or high-intensity cycling days in filtered air or diesel exhaust Solid lines represent FA, dotted lines represent DE. ? significantly different from rest in the corresponding exposure (DE only); * significantly greater than DE at the corresponding intensity; ** significantly less than low-intensity (comparing FA only)  59 4.4 Discussion This is the first study to examine the endothelial response to exercise of varying intensities in DE. We found that 2 h following 30 min of exposure to DE, endothelin-1 was significantly lower compared to FA. Following exercise in DE, plasma NOx was significantly increased, and immediately post and 1 h post-exercise, plasma NOx levels were significantly higher in DE compared to FA. Additionally, we found that on low-intensity exercise days FMD/SRAUC was significantly lower in DE compared to FA and this did not occur in high-intensity exercise. Nitric oxide plays an important role in the maintenance of vascular tone and endothelial function [197]. In the present study, following low- and high-intensity exercise in DE, plasma NOx (the sum of plasma nitrite and nitrate) levels increased by 20% and 46% respectively compared to pre-exercise. These plasma NOx levels following low- and high-intensity exercise in DE were 40% and 70% higher than following rest and significantly greater than in the FA condition. With the exception of a decrease immediately following rest in FA, we found that FA exposure with or without exercise did not change plasma NOx. Thirty min of rest in DE decreased plasma NOx over time; however, with the performance of low- and high-intensity exercise in DE, plasma NOx significantly increased. Immediately post and 1 h post-exercise, plasma NOx was significantly greater in DE compared to FA. The increase in plasma NOx with DE exposure in accordance with other studies [198-200]. Some authors have suggested that the elevated levels of these NO end products following DE exposure may represent an up-regulation of vascular NO generation [199]. The up-regulation may have occurred to compensate for the NO that is consumed during a state of increased oxidative stress that results from exposure to air pollution as well as in the maintenance of vascular tone and blood pressure [199]. In contrast,  60 others suggested that the higher NO end-products are simply related to higher absorption of oxides of nitrogen present in the DE [198], which is supported by studies showing that inhalation of 80 ppm of NO increased blood nitrate levels fourfold [201]. In the present study, DE used in the exposure contained 7 ppm of NO, which is more than a magnitude lower than NO exposure studies (80 ppm) [201] and may explain why plasma NOx levels did not increase during rest. The higher ventilation along with the resulting four- and sevenfold increase in the inhaled dose of NO during low- and high-intensity exercise may account for the increase in plasma NOx seen with exercise in DE. The higher circulating plasma NOx following exercise in DE may not necessarily be beneficial. For example, in the presence of exogenous NO or DE, de novo synthesis of NO is lowered through a down-regulation of endothelial nitric oxide synthase (eNOS) [202, 203] or uncoupling of eNOS [204, 205]. The term eNOS uncoupling is used to describe when eNOS is altered and produces reactive oxygen species such as superoxide instead of NO [206]. Therefore, with DE exposure, the uncoupling of eNOS could result in the production of reactive oxygen or reactive nitrogen species, rather than the production of NO [197, 207]. The higher levels of circulating NOx in the current study may then combine with reactive oxygen species via redox reactions to form peroxynitrite [208, 209]. The interaction of NO with reactive oxygen species could therefore result in oxidative stress. In a study by Nurkiewicz et al., exposing rats to inhaled titanium dioxide nanoparticles (used as a surrogate for environmental PM) confirmed this, which led to oxidative stress in the microvasculature [197]. Despite the study being conducted in rats it is possible that the same events occur in humans; therefore, in the current study, the elevated circulating NOx due to exogenous NO exposure could combine with reactive oxygen species that are produced due to PM and this may result in a cascade of oxidative stress.   61 As mentioned, endothelial function plays a role in the development of atherosclerosis [87] and predicts future cardiovascular events in those with cardiovascular disease [181]. The endothelium typically responds to short-term increases in shear stress by increasing synthesis of NO and other vasodilators that dilate the artery wall [210]. Flow-mediated dilation is a technique used to assess NO-mediated dilation and endothelial function [211].  An FMD test causes reactive hyperemia with the reactive hyperemia stimulus modified by artery size [212] and cardiovascular disease risk factors such as pulse pressure and BMI [213]; therefore, if different FMD responses are observed it is unclear if it is attributable to a difference in reactive hyperemia or endothelial function. To account for the change in reactive hyperemia affecting FMD, FMD is often normalized to shear rate from immediately post-deflation to the time of peak diameter (FMD/SRAUC) [214, 215]. In the present study, we found that with DE exposure FMD/SRAUC was significantly decreased with exercise intensity.  Additionally, on low-intensity exercise days, FMD/SRAUC was significantly less in DE compared to FA. The lower FMD/SRAUC in DE was due to a lower FMD despite a higher SRAUC, which suggests that for a given shear rate stimulus the endothelium is not dilating as effectively and could represent endothelial dysfunction. However, there is still no consensus on the use of FMD normalization; therefore, caution should be used when interpreting normalized FMD values [194].  The differential effects of exercise intensity on FMD and oxidative stress may explain why DE reduced FMD/SRAUC on low- but not high-intensity exercise days. During high-intensity exercise oxidative stress occurs and reactive oxygen species associated with oxidative stress partially modulate endothelial function [216]; therefore, during high-intensity exercise, the effect of DE on oxidative stress and endothelial function may be washed out by exercise. For example, Johnson et al. found that 30 min of exercise at 80% VO2peak increased markers of oxidative stress  62 and decreased FMD compared to 30 min of exercise at 50% VO2peak [217]. As the duration and exercise intensity in the current study is similar to Johnson et al. [217], it is possible the higher oxidative stress response to high-intensity exercise could negate the effects of DE, and thus abolish any differences in endothelial function and FMD/SRAUC. However, as low-intensity exercise does not cause oxidative stress, this would allow for PM induced oxidative stress to impair endothelial dysfunction that is manifested as a lower FMD/SRAUC in DE compared to FA. It is also possible that plasma norepinephrine may have played a role in the lower FMD/SRAUC in DE during low- but not high-intensity exercise. Plasma norepinephrine is a vasoconstrictor that is inversely related to FMD [218]; the greater norepinephrine release during high-intensity exercise may have washed out the effects of DE on FMD/SRAUC. However, as the results did not demonstrate a reduction in FMD without normalization or a reduction in baseline brachial artery diameter during low-intensity exercise in DE, it is unclear if plasma norepinephrine mediated this response. Literature on how acute exposure to PM during exercise affects vascular function is conflicting. Based on the results in the current study, one could suggest that low-intensity but not high-intensity exercise in DE impairs endothelial function. In contrast to our finding that high-intensity exercise does not affect endothelial function, Rundell et al. found that 30 min of exercise in a high PM1 environment at a similar high-intensity reduced FMD [91, 92]. Similarly, Cutrufello et al. found that exposure to PM during 26 min of exercise that included a six-minute maximal bout also decreased FMD. Based on the reduction in FMD/SRAUC on low-intensity exercise days in DE, one could suggest that low-intensity exercise impairs endothelial function. In contrast, the only study assessing the effects of moderate exercise in DE observed that 1 h post exercise microvascular dysfunction was not affected [94]. Based on the above results it is  63 challenging to determine how exercise in air pollution containing PM affects vascular endothelial function. One of the major confounders to consider when comparing these studies is heterogeneity in the methods of assessing vascular function.  For example, Wauters et al. [94] measured microvascular function by assessing the vascular response to sodium nitroprusside and acetylcholine following skin heating, while other studies use FMD, measure forearm blood flow in response to bradykinin, sodium nitroprusside, and acetylcholine, or measure microvascular function at the fingertip. Another possible reason for the different findings between our research and that by Cutrefello et al. and Rundell et al. is that the methodology for quantifying FMD differed significantly.  In the current study, automated analysis of continuous video recording was performed of video images, as opposed to manual analysis of still images in the prior two studies [90-92]. The differing techniques used to assess vascular function as well as different exercise protocols make it challenging to draw conclusions about how exercise in DE affects vascular function. Therefore, further research into how exercising in air pollution containing PM affects vascular function is warranted. Compared to pre-exercise levels, endothelin-1 significantly increased following high-intensity exercise and the increase in endothelin-1 2 h post exercise was significantly greater than 2 h following rest or low-intensity exercise. Shear stress is known to stimulate the production of endothelin-1 [219, 220], and as exercise intensity increases, post-exercise endothelin-1 levels also increase [221]. In the current study, baseline shear rate was higher following high-intensity exercise compared to rest and low-intensity exercise. Therefore, a higher post-exercise shear rate may have increased endothelin-1 following high-intensity exercise.  An exposure-by-time interaction showed that at 2 h post-exposure endothelin-1 was significantly greater in FA compared to DE. The lower endothelin-1 in DE 2 h post-exposure is  64 contrary to our initial hypothesis that endothelin-l levels would increase in response to DE. As plasma endothelin-1 may represent the balance of spillover from local release and elimination/use, the lower concentration of endothelin-1 in DE may represent a greater elimination/use of endothelin-1. Furthermore, while circulating concentrations are important they may not represent what is happening at the tissue level. For example, in hypertensive and hypertrophic rats, tissue endothelin-1 concentrations were higher than controls, despite similar plasma endothelin-1 concentrations [222, 223]. Therefore, the lower concentration of endothelin-1 in DE may represent an alteration in the level to which endothelin-1 is secreted towards the vascular lumen. In the cerebral microvasculature, most of the endothelin-1 produced is released towards the basement membrane of the vessel and not the vascular lumen [224]. The basement membrane of the vessel is in closer proximity to the vascular smooth muscle than the lumen of the vessel and when the endothelial cell releases endothelin-1 it binds to receptors on the vascular smooth muscle to cause vasoconstriction [225]; therefore, the lower circulating endothelin-1 2 h post DE exposure could represent a higher amount of endothelin-1 being secreted to the basement membrane rather than to the lumen of the vessel. If greater endothelin-1 is secreted towards the vascular smooth muscle, this may result in greater smooth muscle contraction following DE.  The increase in endothelin-1 following exercise could be perceived as detrimental; however, it may represent the normal physiological response to exercise. Endothelin-1 plays a role in the regulation of vascular tone and redistribution of blood flow to the working muscles during exercise [226]; therefore, could be considered a normal physiological response to exercise and not a pathological response that could be initiated by DE. The increase in circulating endothlelin-1 with exercise may not translate into the same expression in tissues throughout the  65 body. For example, following exercise, rats exhibited increased endothelin-1 mRNA in the plantar muscle compared to a decrease in the aorta [227]. Furthermore, acute increases in ET-1 with exercise do not translate to an increase with repetitive exercise, as demonstrated by a reduction in circulating endothelin-1 with exercise training [228]. The acute increase and chronic reduction in endothelin-1 is similar to the oxidative stress response to exercise, whereby the production of reactive oxygen or nitrogen species during or following acute exercise results in a positive chronic adaptation. The acute increase in oxidative stress is required as a signal to up-regulate antioxidant defenses following chronic training and is associated with a shift in redox balance that ultimately reduces oxidative stress [229-231]. Although at face value the increase in oxidative stress and endothelin-1 following exercise could be considered detrimental, it is possible that the acute responses with exercise play a role in the chronic and positive adaptation to exercise. The exercise-induced increases in oxidative stress and endothelin-1 discussed above may represent the key principal of overload in exercise physiology. For adaptations to occur, the physiological perturbation needs to provide an overloading stress or stimulus and the adaptations to a regular stimulus result in improvements in health and performance. 4.5 Conclusion In healthy recreationally-active males we assessed the endothelial responses to 30 min of rest, low-, and high-intensity cycling with DE exposure. Following 30 min of exposure to DE, endothelin-1 was lower compared to FA (2 h post); and following exercise in DE, plasma NOx increased compared to pre-exercise. Additionally, we found that on low-intensity exercise days, FMD/SRAUC was significantly lower in DE compared to FA, which implies that endothelial function is impaired. The significantly lower FMD/SRAUC in DE on low-intensity days was not seen on high-intensity exercise days.  66 The higher plasma NOx during both exercise intensities in DE could increase the oxidative stress potential through the combination of NO with reactive oxygen species. This greater oxidative stress potential corresponds to impairments in endothelial function during low-intensity but not high-intensity exercise. The differential effects of exercise intensity on endothelial function could be related to how high-intensity exercise causes oxidative stress and decreases vascular function, both of which could obscure any effects mediated by DE.  Practically speaking, as the effects of DE exposure were not magnified with exercise intensity, then advising individuals to reduce vigorous activity during bouts of high pollution has no additional benefit and may be detrimental to vascular health. Since the observed changes were small, and the exposure concentrations of PM were high, the clinical significance of these findings remains unknown. Despite this relationship, such research may be important to consider in clinical populations where the physiological changes observed in this study might be magnified.  67 CHAPTER 5: THE RESPIRATORY, SYSTEMIC, AND AUTONOMIC RESPONSES TO LOW- AND HIGH-INTENSITY CYCLING WITH DIESEL EXHAUST EXPOSURE  5.1 Introduction Air pollution exposures that deposit PM in the respiratory tree cause pulmonary oxidative stress and an increase in bronchial responsiveness, airway resistance, and airway inflammatory cells [79, 80]. In susceptible populations, such physiological changes can result in impaired lung function [75-78]. Lung inflammation that occurs as a result of PM exposure may represent an important step in the inflammatory cascade leading to cardiovascular complications. Additionally, perturbation of the autonomic nervous system by PM can lead to an increase in sympathetic and a decrease in parasympathetic nervous system activity, both of which are important in the cardiovascular effects of PM [12]. Heart rate variability, which assesses the variation of the time interval between heartbeats, is modulated by the sympathetic and parasympathetic nervous systems and can assess alterations in autonomic nervous system activity. In at-risk individuals, a reduction in HRV is associated with increased risk of mortality and cardiac events [232, 233].  Exposure to PM causes lung inflammation or alterations in the autonomic nervous system that result in systemic inflammation and affect the cardiovascular system through endothelial dysfunction, coagulation, thrombosis, and oxidative stress [12]. Currently, there are no studies examining the effects of exercise in DE on the autonomic nervous system. There are only a small number of studies directly examining the effects of continous exercise in PM on pulmonary inflammation [67-69] and pulmonary function [68, 81-85, 234-238], and the results of these  68 studies are inconsistent. As exercise protocol, duration, and air pollution exposure characteristics vary, drawing any robust conclusions on how exposure to air pollution containing PM during exercise affects pulmonary function or causes pulmonary (or systemic) inflammation is difficult.  When exercise intensity increases, the proportion of UFP that deposits in the respiratory tree increases [52, 53]; therefore, one might expect that pulmonary function and inflammation would be more impacted by exercise than rest and thus result in more systemic inflammation. However, as acute exercise causes bronchodilation [20] and increases airway inflammatory mediators and markers of inflammation [239, 240], it is unclear if the effects of pollution will either be offset or magnified by exercise. Therefore, the purpose of this study was to determine the pulmonary, systemic inflammatory, and autonomic nervous system responses to exercise of varying intensities in DE containing high levels of PM. We hypothesized that exposure to DE would impair pulmonary function, increase systemic inflammation, and alter autonomic nervous system function, and any physiological effects of DE would be magnified as exercise intensity increases.  5.2 Methods A summary of participant data can be found in section 2.1.1.1, an overview of the general apparatus used in this chapter can be found in section 2.1.1.5, and an overview of the exposure setup can be found in section 2.1.1.6. An overview of the experimental design can be found in section 2.1.1.2. Day 1 consisted of familiarization with all study procedures and a maximal exercise test that is detailed in section 2.1.1.3. An overview of testing days 2-7 can be found in 2.1.1.4. Testing days 2-7 consisted of 30 min trials of cycling or rest. Each intensity (including rest) was performed once in FA and once in DE containing 300 ?g/m3 of PM2.5, for a total of six trials, each of which was separated by a 7-day period. Work rates on these days were based on  69 the peak power achieved during the maximal exercise test.  Low-intensity cycling was set at 30% of power at O2peak (96.1 (17.7) W) and high-intensity cycling was set at 60% of power at O2peak (192.2 (35.3) W). Control exposures involved sitting with the same setup as cycling and for the same period of time (30 min), but without performing exercise.  5.2.1 Outcome measures and apparatus Prior to, immediately following, 1 h, and 2 h post each trial, HRV, blood pressure, complete blood count, FeNO, and pulmonary function were measured (Figure 5.1).    Figure 5.1 Overview of test day procedures prior to and following 30 min of rest, low-intensity, and high-intensity cycling in filtered air or diesel exhaust 5.2.1.1 Heart rate variability Heart rate variability was measured in 15 participants in a quiet, dark room. Following 20 min of supine rest, heart rate was recorded for five min while participants remained supine (Polar S810, Polar Electro, Finland). Heart rate variability was analyzed offline using custom software (Kubios HRV, Kuopio, Finland). Artifacts were removed using an automatic correction factor provided by the software. Time domain measures were evaluated.  Specifically, these included the standard deviation of normal-to-normal (NN) intervals (SDNN), the root mean square of the  70 mean differences in successive N-N intervals (RMSSD), and the HRV triangular index. Frequency domain analysis was performed using autoregressive modeling to determine the spectral powers at low frequency (LF: 0.04?0.15 Hz) and high frequency (HF: 0.15?0.40 Hz) as well as total power. Additionally, LF normalized units (LFnu), HF normalized units (HFnu), and LF/HF ratios were determined. Of the 360 measures of HRV taken, seven were excluded due to a poor signal. To prevent complete exclusion of those subjects with missing measurements and based on the recommendations of a statistician, the missing values were replaced using regression imputation [196]. 5.2.1.2 Blood pressure Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured before and following exercise. Each pressure was measured in triplicate using an automated device (BPA-060-0CA, HoMedics, Commerce Township, MI, USA) with at least one min between measures. Mean arterial pressure (MAP) was estimated as ((2?DBP)+SBP)/3.  5.2.1.3 Complete blood count Blood samples were taken from the right antecubital fossa with a 21-gauge needle. Complete blood count was analyzed in a commercial laboratory to measure the following: WBC (with differential to include neutrophils and monocytes), platelet count, red blood cell count (RBC), hemoglobin concentration, Hct, and red cell distribution width (RDW). 5.2.1.4 FeNO The FeNO was measured with a NIOX MINO? Airway Inflammation Monitor (Aerocrine, Solna, Sweden), which detects exhaled NO as an indicator of inflammation.  Measurements were performed as per the American Thoracic Society guidelines [73]. Briefly,  71 subjects inhaled to close to total lung capacity and then exhaled at a flow rate of 50 ml/s and a pressure of 10 cm H2O into the device for 6s. The device collected the expired gas from the last 3 s of the exhalation to determine the concentration of exhaled NO.  5.2.1.5 Pulmonary function Pulmonary function was measured in 17 participants using a portable spirometer (Spirobank G, Medical International Research, Rome, Italy), as per the guidelines of the American Thoracic Society [241].  In each case, spirometry was performed following the sampling of the blood and FeNO to avoid hyperventilation effects on any values.  Standard indices of pulmonary function such as FVC, FEV1, ratio of FVC to FEV1 (FEV1/FVC), and FEF25-75 were measured. Participants performed 3 maneuvers (and up to a maximum of 6, if necessary) per testing time point. For repeatability to be achieved, the difference between the highest and second highest trial for FEV1 and FVC had to fall with 0.15L. The peak value for each variable was used for analysis.  5.2.2 Exposure setup All exposures were performed using an environmental exposure booth that is described in detail elsewhere [20, 39] and in section 2.1.1.6. For FA exposures, participants were exposed to compressed, HEPA-filtered air. For DE exposures, participants were exposed to freshly-generated DE, diluted to 300 ?g/m3 of PM2.5, and containing 0.58 ppm of NO2 and 7 ppm of NO. 5.2.3 Statistical analysis Statistical analyses were completed using SPSS software (SPSS Inc, version 20, Chicago, IL). For each parameter, data were analyzed using a 2 (exposure: FA vs. DE) x 3 (intensity: rest, low-intensity, high-intensity) x 4 (time: pre, post, 1 h, 2 h) repeated measures ANOVA.  72 Significance was set at p<0.05. For all repeated measures ANOVA the Huynh-Feldt adjustment was used to correct for violations of sphericity. Main or interaction effects were further analyzed using pair-wise comparisons and significance was adjusted to account for multiple comparisons using the Sidak adjustment. The p-values represented within this thesis have been inflated to incorporate the Sidak adjustment, meaning that ? remains at 0.05. Specifically, the Sidak adjustment uses the following equation to adjust for multiple comparisons: 1- (1-unadjusted p-value)1/k, where k is the number of comparisons in the family. For the post-hoc analysis comparing exercise intensity, p-values were adjusted for 3 groups (rest, low-intensity and high-intensity) and when time was compared, p-values were adjusted for 4 groups (pre, post, 1h, 2h).  All means are reported with standard deviations in parentheses. The statistical analyses chosen were based on consultation with a statistician.  73 5.3 Results A summary of exposure data can be found in Table 2.1 and is summarized in detail in section 3.3.1. Mean baseline values for all parameters for the participants across the six testing days were not significantly different. Mean baseline FeNO values on all test days was 20.26 (8.7) ppb. All other baseline values can be found in Table 5.1 -5.4.  Table 5.1 The mean pre-exposure heart rate variability of six experimental test days in 18 recreationally-active males. Mean (sd)  HRV time domain SDNN  (ms) RMSSD (ms) HRV triangular index 66.0 (23.9) 55.4 (24.3) 14.0 (4.8) HRV frequency domain LF power (ms2) HF power (ms2) Total power (ms2) LF/HF LF power (nu) HF power (nu) 1440.5 (853.0) 1244.2 (733.1) 4565.2 (2258.4) 1.56 (1.0) 54.8 (18.1) 45.1 (16.3)  Abbreviations: HF: High frequency; HRV: Heart rate variability; LF: Low frequency; RMSSD: root mean square of successive intervals; SDNN: Standard deviation of normal-to-normal intervals   74   Table 5.2 Mean pre-exposure blood pressure of six experimental test days in 18 recreationally-active males. Mean (sd)  SBP (mmHg) DBP (mmHg) MAP (mmHg) 117.6 (5.9) 70.2 (4.4) 86.0 (4.4)  Abbreviations: DBP: Diastolic blood pressure; MAP: Mean arterial blood pressure; SBP: Systolic blood pressure.  Table 5.3 Mean pre-exposure complete blood count of six experimental test days in 18 recreationally-active males. Mean (sd)  WBC (giga?L-1) RBC (giga?L-1) Hemaglobin (g?L-1) Hct RDW (%) Platelet count (giga?L-1) Neutrophils (giga?L-1) Monocytes (giga?L-1) 5.16 (1.24) 4.88 (0.28) 145 (7.72) 0.43 (0.02) 12.57 (0.49) 208.19 (44.97) 2.95 (0.93) 2.95 (0.93)  Abbreviations: Hct: Hematocrit; RBC: Red blood cell count; RDW: Red cell distribution width; WBC: White blood cell count. 75 Table 5.4 Mean pre-exposure pulmonary function over six experimental test days in 18 recreationally-active males. Mean (sd)  FEV1 (L) FVC (L) FEV1/FVC FEF25-75 (L/s) PEFR (L/s) 4.31 (0.76) 5.48 (1.13) 0.79 (0.07) 4.00 (0.91) 9.79 (1.31) Percent Predicted FEV1 (%) FVC (%) FEV1/FVC (%) 96.6 (11.0) 103.2 (14.8) 94.0 (8.4)  Abbreviations: FEV1: Forced expiratory volume in 1 second; FVC: Forced vital capacity; FEF25-75: Forced expiratory flow in the middle 50% of expiration; PEFR: Peak expiratory flow rate.   76 5.3.1 Heart rate variability There was a significant intensity-by-time interaction for all time and frequency domain indices of HRV, which all significantly decreased following high-intensity exercise. The exception to this pattern was LF (nu) and LF/HF ratio, which significantly increased following high-intensity exercise. Immediately post and 1 h post-exposure, variables of HRV were significantly decreased following high-intensity exercise compared to following rest. The opposite was true for LF (nu) and LF/HF (see Appendix D.1 and D.2 for detailed post-hoc comparisons). There were no effects of exposure on any indices of HRV. 5.3.2 Blood pressure There was a significant intensity-by-time interaction for SBP (p=0.014). Systolic blood pressure was significantly greater 1 h post rest compared to 1 h post low-intensity (p=0.005) and high-intensity exercise (p=0.036) (Appendix D.3). Systolic blood pressure was also significantly lower 2 h post-exposure during high-intensity exercise compared to rest (p<0.001) or low-intensity exercise (p=0.001). Immediately following rest, SBP was significantly less than 2 h post-exposure (p=0.04). Systolic blood pressure was significantly lower 1 h post low-intensity exercise compared to pre (p=0.003), post (p=0.019) and 2 h post exercise (p=0.004). There were no interactions for DBP and MAP, and there were no effects of exposure on all blood pressure measurements. 5.3.3 Complete blood count There were no main effects for exposure on complete blood count; however, there was a trend towards an increase in platelets in DE compared to FA (210 (44.1) vs. 206 (44.4) giga?L-1, p=0.086). There was a significant intensity-by-time interaction for WBC (p<0.001, Figure 5.2a), neutrophils (p<0.001, Figure 5.2b), monocytes (p<0.001, Figure 5.3), hemoglobin (p=0.039,  77 Appendix D.4), red cell distribution width (p=0.003, Appendix D.5) and platelets (p=0.016, Appendix D.6). Following exercise, WBC, neutrophils, and monocytes increased over time and the increase was intensity-dependent with greater increases over time seen with high-intensity exercise. More detailed comparisons for hemoglobin, platelet count, and red cell distribution width can be found in Appendix D.4-D.6. There were no other main or interaction effects for complete blood count.   78  Figure 5.2 (a) White blood cell count (WBC) or  (b) neutrophils in 18 recreationally-active males prior to and following 30-min of rest, low-intensity cycling, or high-intensity cycling ? = Significantly greater than pre- and post-exercise (all intensities aside from neutrophil rest post vs. 1 h); ? = significantly difference between rest and low-intensity exercise; * = significantly less than high-intensity at the corresponding time point; ** = significantly less than 2 h (low- and high-intensity only)  79  Figure 5.3 Monocytes in 18 recreationally-active males prior to and following 30-min of rest, low-intensity cycling, or high-intensity cycling. ? = significantly greater than post-exercise for all intensities (rest is only significant at 2 h); ? = significantly difference between rest and low-intensity exercise; * = significantly less than high-intensity at the corresponding time point; ** = significantly less than 2 h (high-intensity only); ? significantly different from than pre-exercise (rest and high-intensity only)  5.3.4 FeNO There was a significant three-way interaction (exposure-by-intensity-by-time; p=0.045, Figure 5.4) for FeNO. Immediately following high-intensity exercise in FA, FeNO was significantly increased when compared to pre-exercise (19.9 vs. 22.7 ppb; p=0.048).  In DE, FeNO was significantly increased at 1 h post high-intensity exercise when compared to pre-exercise (19.3 vs. 21.9 ppb; p=0.024). In FA, FeNO was significantly lower 1 h post-exposure in the resting condition when compared to immediately post (19.6 vs. 21.3 ppb; p=0.025); however, there were no differences between FA and DE for any comparisons.   80  Figure 5.4 FeNO in 18 recreationally-active males prior to and following 30-min of (a) rest, (b) low-intensity cycling, or (c) high-intensity cycling in filtered air or diesel exhaust ? = significantly different from pre-exercise in the corresponding exposure (DE only); ? = significantly different from post (FA only)  81 5.3.5 Pulmonary function There was a main effect of time for % predicted FEV1/FVC, which compared to pre-exercise increased immediately post-exposure (p=0.038; 94.4% vs. 95.1%). There were significant interaction effects for PEFR  (exposure-by-intensity: p=0.036; intensity-by-time: p=0.04, Figure 5.5). An exposure-by-intensity interaction suggests that during high-intensity exercise in FA, PEFR was significantly greater than low-intensity exercise (p=0.010) and rest (p=0.017, Figure 5.5a).  However, this relationship did not occur with DE. An intensity-by-time interaction showed that immediately following high-intensity exercise PEFR was significantly greater than following low-intensity exercise (p=0.011) and rest (p=0.017, Figure 5.5b). There were no other main or interaction effects for measures of pulmonary function.  82  Figure 5.5 Peak expiratory flow rate (PEFR) in 18 recreationally-active males on rest, low-intensity, or high-intensity cycling days in diesel exhaust or filtered air. (a) Exposure-by-intensity interaction, (b) intensity-by-time interaction  * significantly different from high-intensity exercise at the post-exercise time point   83 5.4 Discussion This is the first study to determine the pulmonary, systemic inflammatory, and autonomic nervous system responses to exercise of varying intensities in DE. We found that 30 min of low- or high-intensity exercise in DE did not cause pulmonary, autonomic nervous system, or systemic inflammatory effects; however, there was a trend towards an increase in platelets in DE compared to FA.  Particulate matter exposure causes oxidative stress, increased bronchial responsiveness, increased airway resistance, and increased airway inflammatory cells [79, 80]. Pulmonary inflammation that occurs as a result of PM exposure is important in the inflammatory process that may lead to cardiovascular complications and systemic inflammation [12]. Therefore, we anticipated that any pulmonary inflammation with DE exposure would lead to subsequent impairments in pulmonary function and systemic inflammation. Compared to pre-exposure in FA, FeNO immediately post high-intensity exercise was significantly increased (2.7 ppb increase in FeNO relative to baseline). Similarly, compared to pre-exposure in DE, FeNO 1 h post high-intensity exercise was significantly elevated (2.4 ppb increase in FeNO relative to baseline). Despite the significant increase in FeNO following high-intensity exercise, DE did not magnify the response, suggesting that in healthy individuals exercise in DE does not potentiate the FeNO marker pulmonary inflammation; however, we cannot discount that other markers of pulmonary inflammation have been affected. The lack of a DE effect contradicts our initial hypothesis that DE exposure would increase the amount of pulmonary inflammation post-exercise. However, findings of the current study are similar to others showing that in healthy individuals, acute exercise in a high pollution/high traffic environment is not associated with elevated FeNO [67-69]. Rundell et al. assessed the FeNO response to 30 min of cycling at 85-95% of maximum  84 heart rate while Jacobs et al. assessed the FeNO response to 20 min of cycling at 74% of maximum heart rate [67, 68]. The intensities used by Rundell et al. and Jacobs et al. are not dissimilar to the high- and low-intensity trials in the current study [67, 68] and further corroborate our findings that exercise of varying intensities with exposure to air pollution does not affect FeNO.  One potential reason for the lack of effect of DE on FeNO in the current study is that the post-exercise measurements occurred over too short of a time frame. Barath et al. found that 6 h following a 1 h exposure to DE with intermittent exercise, FeNO was significantly elevated by 2 ppb [242]. In the current study, and the studies of Rundell et al. and Jacobs et al., FeNO was measured immediately, and up to 2 h, post-exposure [67, 68]; therefore, it is possible that FeNO levels increased after all testing was completed. As Barath et al. did not measure FeNO prior to 6 h post exposure, it is difficult to conclude the time course of the FeNO response to DE [242]. Alternatively, as high-intensity exercise in the current study caused an increase in FeNO greater than the increase due to DE in Barath et al. [242] (2.7 ppb and 2.4 ppb vs. 2ppb in Barath et al. [242]), the exercise effect may have obscured any effects of DE. It is also possible that the lack of an effect of DE could be due to the fact that FeNO may not be a stable or sensitive enough indicator of pulmonary inflammation in healthy individuals. Our finding showing that high-intensity exercise increases FeNO, contrasts with work done by Verges et al. who examined FeNO following 25 min of incremental exercise (two 10 min bouts at 46% and 60% of peak power, followed by five min at 90% of peak power) [243]. Immediately following exercise, Verges et al. found that FeNO significantly decreased [243]. Similarly, Evjenth et al. tested FeNO following an 8 min incremental test that reached 95% maximum heart rate [244] and found that immediately following and 30 min following exercise,  85 FeNO levels were significantly reduced [244]. Our results may be in opposition to others [243, 244] due to the timeframe of sampling. In the study by Verges et al., FeNO levels were returning towards baseline 15 min following exercise [243]. The measurement of post-exercise FeNO in the current study occurred following a number of other physiological measures (detailed in section 5.3), which meant that the post-exercise FeNO measurement could have been measured up to 40 min post-exercise. Therefore, an immediate post-exercise reduction in FeNO could have been missed in the current study. As exercise duration was different between the current study and others [243, 244], it is also possible that a different FeNO response was elicited.  Inflammatory cytokines such as tumor necrosis factor-alpha stimulate the production of NO [245], and act as is an initial inflammatory cytokine that regulates eosinophil recruitment into the lung [246]. Therefore, the increase in FeNO following high-intensity exercise in the current study could have occurred due to an increased activation of iNOS by inflammatory cytokines, which has not been observed in studies such as that by Verges et al [243]. In healthy and sedentary overweight males as well as coronary artery disease and COPD patients, acute exercise increases sputum eosinophils, and circulating C-reactive protein and interleukin-6 with the increase being proportional to exercise intensity [247-251]. Therefore, it is possible that the higher FeNO observed following high-intensity exercise in the current study is related to exercise-induced changes in inflammatory cytokines. In the current study, circulating or airway cytokines were not measured, but the increase in WBCs and neutrophils following high-intensity exercise further supports the inflammatory response to exercise that could increase FeNO. In susceptible populations, PM-induced physiological changes such as oxidative stress, bronchial hyperresponsiveness, and inflammation [79, 80] can result in impaired lung function [75-78, 83]. In healthy individuals, the effects of PM on pulmonary function during rest are  86 conflicting [252-254]. Similarly, studies examining the effects of exposure to PM during exercise also show conflicting results [68, 84, 85]. Within the current study, we found that in FA, PEFR was significantly greater on high-intensity exercise days compared to rest. In DE, these differences did not occur, leading to a trend towards a decrease in PEFR in DE compared to FA. As the FA vs. DE differences were not significant, and there were no effects of exposure on other parameters of pulmonary function, one could conclude that DE exposure during exercise does not affect pulmonary function. Our finding is similar to Strak et al. and Jarjour et al. who found no associations between exposure to PM and pulmonary function following ?8 km cycling in traffic [84, 85].  In contrast, Rundell et al. found small but significant decreases in FEV1 and FEF25-75 following 30 min of exercise at 85-95% of maximum heart rate close to a high traffic road [68]. These studies do not use comparable exposures, exercise durations or intensities, or time frames for post-exposure measures, which makes it challenging to form conclusions on the relationship between PM exposure during exercise and pulmonary function. Therefore, to effectively understand the interaction between PM and exercise, future research should consider using similar exposure models and exercise interventions.  There was a trend towards an increase in platelets in DE compared to FA, but exercise did not modify the response to DE. White blood cells, neutrophils, and monocytes increased following exercise; the magnitude of the increase was exercise intensity dependent, but there were no effects of DE on the response. Increased parameters of systemic inflammation and blood coagulation related to thrombogenesis are associated with an increased risk of adverse cardiovascular events [255]. These cardiovascular effects of PM may be the indirect result of an increase in blood coagulability or systemic inflammation [256-258]. Platelets are involved in thrombus formation [259] and the risk of thrombosis related to PM/DE exposure could occur  87 through an increase in platelet count, a decrease in fibrinolytic activity, or by increasing fibrinogen. We found a trend towards an increase in platelet count in DE compared to FA, which is not dissimilar to other studies in healthy humans [260] and mice [261]. Particulate matter may stimulate the bone marrow to produce platelets [262, 263]. An increase in platelet count could represent the first step in thrombogenesis, implying that the coagulation cascade may be initiated or the risk of coagulation may be higher with DE exposure. While there are no other studies examining the effects of PM or DE exposure during exercise on platelet count, acute exposure to DE during 1 h of moderate exercise causes platelet activation [96]. The platelet activation following exercise in DE did not occur following rest, which implies that the higher dose of PM during exercise may exacerbate the effects of DE exposure [96]. We did not find that exercise modified the platelet (count) response to DE. Based on the current study and the study by Wauters et al. [96], it is possible to conclude that with exposure to DE platelet count increases, and while exercise does not modify this effect on platelet count, it may affect activation. The finding that WBC and neutrophil counts increased with exercise intensity, without a further increase with DE exposure, suggests that acutely, DE may not initiate a systemic inflammatory response through WBCs. The increase in WBCs and neutrophils with exercise intensity is not surprising as acute exercise results in a biphasic response of blood neutrophils. Initially there is a rapid blood neutrophilia, followed by a second delayed increase a few hours later, and the response increases as exercise duration and intensity increase [264, 265]. The initial increase in neutrophils may be related to the release of neutrophils from the vascular wall caused by shear stress and catecholamines [266]. The secondary increase in neutrophils, which would occur at a similar time to 1 h and 2 h post-exposure in the current study, is due to a release of more WBCs from the bone marrow in response to increased cortisol levels [266].    88 The inflammatory response to exercise represented by an increase in WBCs, neutrophils, and monocytes could be perceived as detrimental; however, it may represent the normal physiological, and not pathological, response. As stated in Chapter 4, it is possible that the acute response with exercise plays an important role in the chronic and positive adaptation to exercise training. The exercise-induced increases in inflammation may represent the key principal of overload in exercise physiology. For adaptations to occur, the physiological perturbation needs to provide an overloading stimulus or stress.  If applied regularly, the overload leads to adaptation, resulting in improvements in health and performance. In patients with cardiopulmonary disease, an acute bout of exercise results in an inflammatory response; however, following chronic endurance training systemic inflammation is attenuated [267], which supports the hypothesis that an acute stimulus provokes long-term gains. Elucidating the exact differences between exercise and air pollution induced inflammation is challenging. Regular exercise attenuates systemic inflammation and risk of cardiovascular disease, where as air pollution exposure does the opposite [12, 267].  Thus, despite the same acute response it is possible that the chronic effects are manifested differently. The current study did not find that exposure to DE modified the exercise response of WBCs or neutrophils. The lack of effect of DE on the WBC response to exercise contrasts with the study of Jacobs et al. who found that cycling in traffic for 20 min significantly increased neutrophil count more than cycling in a laboratory without exposure to air pollution [67]. Our research was conducted in a tightly-controlled environment where one would expect to more easily detect any physiological changes; despite this, we did not detect an effect of DE. Furthermore, there would have been a series of extra stimuli in the Jacobs study, in addition to the air pollution, that could have confounded their result.  Specifically, acute psychological stress  89 increases inflammatory cytokines [268, 269]; therefore, the difference in findings between the current study and Jacobs et al. [67] could be related to the stress response to noise or cycling in traffic. It is also possible that in the study by Jacobs et al., PM exposure from (automotive) tire and brake wear, which has a high oxidative potential, could have played a role in the observed effects [270]. Furthermore, one cannot rule out the role of other pollutants such as ozone or re-entrained dust that are not otherwise present in a laboratory setting.  Heart rate variability is the variation in time intervals between heartbeats; it is modulated by the sympathetic and parasympathetic nervous systems and can be an indicator of cardiac autonomic function. During exercise, and as exercise intensity increases, aspects of HRV such as absolute HF power decrease [271-277]. The HF component of HRV reflects parasympathetic activity [260] and a decrease in HF power during exercise likely represents vagal withdrawal that occurs at the onset of exercise.  Following short-duration low-intensity exercise, HRV returns to resting levels within a few min; however, the return to baseline takes longer with longer-duration higher-intensity exercise [278-280]. In the current study, following high-intensity exercise, there was a reduction in most time and frequency domain parameters. When normalized, LF (nu) and HF (nu) represent the relative values of each power component in proportion to the total power. Therefore, normalization emphasizes the balance between the two branches of the autonomic nervous system [233]. When the LF and HF power were normalized following high-intensity exercise, LF (nu) and LF/HF were increased while HF (nu) was decreased. The LF/HF ratio represents sympathovagal balance and the increase in LF/HF following high-intensity exercise could be the result of increased sympathetic and/or decreased parasympathetic tone that occurs with exercise [280, 281]. Additionally, persistent sympathetic activation following exercise [282], hormones influenced by the sympathetic nervous system that affect vagal modulation  90 [283], products of exercise that may stimulate metaboreceptors with sympathetic afferents [284], or a response to the drop in blood pressure seen following exercise [280] may all influence HRV following exercise. In pathology, the assessment of HRV is a prognostic tool used to assess cardiac autonomic function and can be used to predict risk of mortality and cardiac events in at risk individuals [232, 233]. One of the potential pathways in which PM exposure causes cardiovascular effects is through a disruption in cardiac autonomic control leading to an increase in sympathetic nervous system activity and a decrease in parasympathetic nervous system activity [285]. The effects of PM on autonomic control may be independent of respiratory inflammation; therefore, despite the lack of effect of DE on FeNO, we hypothesized that it was possible to see an effect on HRV. Contrary to our hypothesis, and in accordance with other controlled experimental studies [286, 287], our research demonstrated that HRV is not impacted by exposure to DE. In contrast, some epidemiological research suggests that as PM2.5 concentrations increase, HRV decreases (as demonstrated by reductions in SDNN and RMSSD) [288, 289]. A similar effect is also seen as PM10 concentrations increase (HRV also decreases) [290]. In epidemiological and experimental research there is a lack of consensus on the magnitude, direction, and existence of an effect; as is demonstrated by some studies finding a significant but positive association between PM and as SDNN [291] and others finding no association between PM and indices of HRV [292]. Diesel exhaust exposure did not affect HRV in the current study, which could be due to the time course of the exposure response association between HRV and PM [293]. A study by Cavallari et al., assessing the time course response of HRV (as measured by SDNN) in an occupational setting, demonstrated that 3 h, 13 h, and 14 h post-exposure, a reduction in SDNN was significantly associated with PM2.5 exposure during  91 work [293]. In the current study, we only measured HRV 2 h following exposure; therefore, it is possible that effects of DE on HRV occurred once testing had terminated. As the exposure duration was different between the current study and Cavallari et al. [293] (5.5 h vs. 30 min), it is difficult to determine if the timing of post-exposure measurements would have played a role within this dissertation. Another possibility for the lack of effect within this study compared to epidemiological studies could be related to the composition of DE compared to ambient air pollution. Diesel exhaust does not contain the high levels of metals found in atmospheric air pollution such as nickel, lead, arsenic and cadmium. These metals may play a role in the autonomic nervous system response to air pollution [294, 295] and may account for the conflicting findings between the present study and epidemiological studies.  5.5 Conclusion The current study assessed the pulmonary, systemic inflammatory, and autonomic nervous system responses to 30 min of rest, low-, and high-intensity cycling with DE exposure in healthy recreationally-active males. We initially hypothesized that DE would cause pulmonary, systemic inflammatory, and autonomic responses that would be magnified by exercise intensity; however, our results do not support these hypotheses. Based on the results of this study, healthy individuals do not experience pulmonary, systemic inflammatory, and autonomic effects from exercising in DE; therefore, individuals may not gain any additional benefit from reducing vigorous activity on days with air quality advisories. However, to substantiate this claim more research is needed to determine the physiological effects of different air pollutants over different time frames during exercise and in different populations.   92 CHAPTER 6: THE EFFECTS OF EXPOSURE TO DIESEL EXHAUST PRIOR TO EXERCISE ON CARDIO-RESPIRATORY VARIABLES AND EXERCISE PERFORMANCE 6.1 Introduction Major sporting events have taken place in cities with poor air quality, which could affect exercise performance [99, 100]. Research into the effects of air pollution exposure on exercise performance have found that ozone and carbon monoxide exposure significantly reduce total exercise work [296] and exercise time [296-298], suggesting that high levels of air pollution can impair exercise performance. There are a small number of observational studies suggesting that PM10 is negatively associated with cardio-respiratory fitness and predicted O2max in children as well as reduced marathon performance in women [102-104]. Two experimental studies corroborate these findings and suggest that in healthy adults exposure to high levels of PM1 caused a decrease in exercise performance during a six-min cycling trial [90, 105]. Exposure to PM causes adverse cardiovascular outcomes such vascular constriction, impaired vascular function, and decreased reperfusion following cuff ischemia, some of which persist beyond the cessation of exposure [47, 90, 91, 162, 299]. Therefore, if the above physiological effects occur and persist following exposure, it is possible that exposure prior to exercise will impair exercise performance.  In healthy individuals and asthmatics, exposure to urban levels of PM during walking   and running can impair pulmonary function [68, 83] and in some instances these effects also persist for several hours beyond exposure cessation [83]. In healthy individuals, exercise causes  93 bronchodilation, thus it is unclear if exercise following exposure to DE containing PM will exacerbate or attenuate the effects of air pollution on pulmonary function.  There is currently no evidence regarding the effects of exposure to DE containing high levels of PM2.5 prior to exercise on subsequent exercise performance or pulmonary function. Method of travel (e.g. walking, cycling, driving), distance from the source, and fuel type all play a role in individual PM exposure [300-303]. Therefore, any PM exposure prior to exercise may affect the cardio-respiratory system and impair performance, even when exercise is performed in a climate-controlled environment. As athletes and exercisers may be exposed to air pollution during the journey to their exercise location, it is important to understand both the physiological and performance implications of exposure to air pollution prior to exercise. Therefore, the purpose of this study was to determine the effect of pre-exercise exposure to DE containing 300 ?g/m3 of PM2.5 on a 20 km cycling time trial performance. A secondary objective of this study was to determine the effect of pre-exercise exposure to DE on pulmonary function and cardio-respiratory responses during exercise. We hypothesized that pre-exercise exposure to DE would significantly impair performance of a 20 km cycling time trial, reduce pulmonary function, and alter cardio-respiratory responses during exercise.  6.2 Methods 6.2.1 Participants Eight endurance-trained males aged 29 (6) yrs, (height: 1.79 (0.10) m; body mass: 72.6 (5.4) kg), with a mean O2peak of 68 (8) mL?kg-1?min-1, volunteered for the study. The sample size was established based on an expected difference in exercise duration of 1.7 min and standard deviation of 0.5 min [297].  Each participant was a non-smoker and had no history of respiratory  94 or cardiovascular disease. This study that was approved by the Clinical Research Ethics Board at the University of British Columbia and participants had an orientation session and a 24-h reflection period prior to signing informed consent. Prior to data collection, each participant refrained from caffeine and alcohol ingestion as well as intense exercise for 12 h. Participants were also asked to maintain the same pre-test routine, including the same mode of travel to the laboratory and pre-test meal. 6.2.2 Procedures Participants attended on 3 occasions. Day 1 consisted of a maximum exercise test, a practice 20 km time trial, and familiarization with the other study procedures. For the maximal exercise test, the work rate started at 100 W and increased by 0.5 W/s until volitional exhaustion. During all trials, HR, SpO2, E, VT, and FB were measured. Peak values were taken as the highest 10s average. To exclude those subjects with possible exercised-induced bronchoconstriction, any individual with a post-exercise decrease in FEV1 by 10% or greater was excluded from the study.  For each participant, days 2 and 3 began at the same time each day and were separated by a minimum 7-day period. Testing days 2 and 3 consisted of a 60 min resting exposure to FA or DE at a concentration of 300 ?g/m3 of PM2.5, followed by a 20 km cycling time trial (Figure 6.1). Exposure order was randomized and participants and the research assistant were blinded to the exposure. Previous DE exposure left a residual smell within the laboratory and this added to the effectiveness of blinding to DE or FA exposure. This dose of DE is occupationally relevant [130, 131] and is approximately 1 order of magnitude greater than the 24-h ambient PM2.5 standard in Canada. The crossover design was chosen for its inherent power by eliminating typical concerns of between-subject variability.  95 For the 20 km cycling time trial, subjects were asked to cover the distance as fast as possible (this was an exhaustive task that lasted approximately 30 min).  Performance was measured as mean power output over the trial, which is highly repeatable in trained cyclists [304]. During the 20 km cycling time trials, participants were only provided with information on distance covered and gearing. All exercise tests were performed on a cycle ergometer (Velotron Pro, Racermate Inc, Seattle, WA, USA) in a climate-controlled room. During exercise tests, participants breathed through a mouthpiece attached to a low-resistance, non-rebreathing valve (NRB 2700, Hans Rudolph Inc, Kansas City, MO, USA).   Mixed expired gases were drawn to a computerized metabolic cart  (TrueOne? 2400, ParvoMedics, Sandy, UT, USA) and averaged every 15s. Heart rate and SpO2 were measured using a heart rate monitor (S810, Polar Electro, Finland) and pulse oximeter at the finger (Avant 9600, Nonin, Plymouth MN, USA).  Pulmonary function was assessed before and after exposure (KoKo PFT Spirometer, nSpire Health Inc, Longmont Co, USA) as well as after exercise (Figure 6.1). Standard measures of pulmonary function were measured as per the American Thoracic Society guidelines [241], including FVC, and FEV1. On tests days, participants performed the procedure 3 times and the peak values were used in the analysis. If FEV1 and FVC did not fall within 0.15 L for largest and the next largest values, the procedure was repeated until acceptable repeatability was achieved. The highest value for each FEV1 and FVC was used for analysis. 6.2.3 Exposure setup All exposures were performed using an environmental exposure booth that is described in detail elsewhere [20, 39] and in section 2.1.1.6. For FA exposures, participants were exposed to compressed, HEPA-filtered air. For DE exposures, participants were exposed to calibrated, aged, DE containing 300 ?g/m3 PM2.5, 0.58 ppm of NO2, and 11.4 ppm of NO.  96 6.2.4 Statistical analysis Statistical analyses were completed using SPSS software (SPSS Inc, version 11, Chicago, IL). Mean power output (which indicated exercise performance), mean exercise E, VT, FB, SpO2, and heart rate during time trials were analyzed using paired t-tests. Pulmonary function (FEV1 and FVC) was analyzed using a 2 (exposure: FA vs. DE) x 2 (% change in pulmonary function from baseline: ? exposure, ? exercise) repeated-measures ANOVA, where delta (?) exposure represents the change in FEV1 or FVC from baseline to post-exposure, and ? exercise represents the change in FEV1 or FVC from baseline to post-exercise (Figure 6.1). Pairwise comparisons were used for subsequent post-hoc analysis. Significance was set at p<0.05. All means are reported with standard deviations in parenthesis.  Figure 6.1 Overview of test days for project 2  6.3 Results Mean exposure data are presented in Table 6.1. Temperature (p=0.115) and humidity (p=0.296) were not significantly different between test days.    97 Table 6.1 Mean concentration of air pollutants during a 60-minute exposure to filtered air or diesel exhaust that occurred prior to a 20 km cycling time trial   Filtered Air Diesel Exhaust PM2.5 (?g/m3) 13.31 (5.96) 302.02 (11.85) Carbon monoxide (ppm) 1.85 (0.18) 16.61 (3.60) NO (ppm) 0.04 (0.03) 11.4 (2.20) NO2 (ppm) 0.04 (0.04) 0.58 (0.15) Total VOC (ppb) 181.8 (75.0) 2224.5 (749.7)   Abbreviations: NO: Nitric oxide; NO2: Nitrogen dioxide PM2.5: Particulate matter with a mass median aerodynamic diameter less than 2.5 ?m; VOC: Volatile organic compounds  Mean baseline FEV1 and FVC values from both test days were 4.68 (0.66) L and 6.03 (0.89) L. Mean baseline percent predicted FEV1 and FVC values from both test days were 107.7 (8.9) % and 115.5 (10.5) %. Absolute FEV1 values which were used to calculate FEV1 ? can be found in Table 6.2. There was a significant interaction for ? FEV1 (p=0.002). In FA, FEV1 ? exercise was significantly greater than FEV1 ? exposure (p=0.004, Figure 6.2), suggesting that exercise-induced bronchodilation occurred. However, the increase in FEV1 did not occur following exercise after the DE exposure, which meant that FEV1 ? exercise was significantly greater in FA compared to DE (mean change = 3.5% vs. -0.2% for FA and DE respectively, p=0.013, Figure 6.2).  98    Figure 6.2 Mean percent change in FEV1 in 8 endurance-trained males following exposure to filtered air or diesel exhaust and following a 20 km time trial  Percent changes were based on absolute FEV1 values in liters. Values above 0 indicate an improvement in FEV1; values below 0 indicate a reduction in FEV1. ? exposure represents the percent change in FEV1 from baseline to post-exposure. ? exercise represents the percent change in FEV1 from baseline to post-exercise. Values are depicted as mean (SD).             99 Table 6.2 Individual FEV1 (L) values in eight endurance-trained males prior to and following a 60-minute exposure to filtered air or diesel exhaust and following a 20 km cycling time trial  Filtered air Diesel Exhaust Pre-exposure  Post exposure Post-exercise Pre-exposure Post exposure Post-exercise 4.18 4.22 4.29 4.1 4.16 4.16 5.68 5.62 5.64 5.75 5.29 5.28 4.08 4.25 4.44 4.21 4.36 4.44 5.33 5.4 5.43 5.34 5.15 5.16 4.3 4.29 4.39 4.31 4.34 4.4 3.82 3.95 4.08 4.08 4.05 4.13 5.25 5.21 5.26 5.46 5.18 5.16 4.52 4.62 4.79 4.5 4.7 4.74  As shown in Figure 6.3, there was a main effect of exposure on heart rate (p=0.023). When participants performed a 20 km time trial that followed exposure to DE heart rate was 6.5 bpm greater than exercise that followed FA. There were no effects of exposure on E, VT, FB, and SpO2, during a 20 km time trial (Figure 6.4) or on mean power output (265 W vs. 255 W for DE and FA respectively, p=0.12). There were also no main or interaction effects for FVC.   100    Figure 6.3 Mean heart rate in eight endurance-trained males during a 20 km time trial that followed a 60 min exposure to filtered air or diesel exhaust.         101  Table 6.3 Mean individual heart rate (bpm) in eight endurance-trained males during a 20 km cycling time trial that followed a 60-minute exposure to filtered air or diesel exhaust    Filtered Air Diesel Exhaust 160.42 166.51 153.05 156.28 166.53 162.16 146.51 157.20 176.27 184.12 167.53 176.94 141.04 158.15 147.22 149.50  102                Figure 6.4 (a) Minute ventilation, (b) tidal volume, (c) frequency of breathing, and (d) oxyhemoglobin saturation, in eight endurance-trained men during a 20 km cycling time trialb) Filtered Air             Diesel Exhaust a) Filtered Air             Diesel Exhaust c) Filtered Air             Diesel Exhaust d) Filtered Air             Diesel Exhaust  103  6.4 Discussion This is the first study to determine the effect of pre-exercise exposure to DE on 20 km cycling time-trial performance, pulmonary function, and cardio-respiratory parameters during exercise. In healthy endurance-trained males, we found that pre-exercise exposure to DE did not impair exercise performance, but attenuated exercise-induced bronchodilation and increased exercise heart rate during exercise.  Similar to other studies demonstrating that exposure to air pollution containing PM affects pulmonary function [68, 83, 305], we found that DE exposure prior to exercise significantly attenuated exercise-induced bronchodilation. While our results do not suggest that exposure to DE negatively affects pulmonary function, they do suggest that DE exposure modifies the typical bronchodilation that occurs in response to exercise in healthy endurance-trained individuals. The clinical importance of this finding is unclear, but competing athletes should consider that when travelling to an exercise/competition location, pre-exercise exposure to PM or DE could affect their pulmonary function. While we did not perform research in asthmatics, given their inherent sensitivity to air pollution, as well as the likelihood of exercise-induced bronchoconstriction instead of bronchodilation, it is possible that exercise following DE in asthmatics could result in more of an adverse effect than healthy individuals.  Compared to FA, we found that pre-exercise exposure to DE significantly increased heart rate during exercise. Irritants in DE (e.g. PM) stimulate the sympathetic nervous system and inhibit the parasympathetic nervous system, which increases heart rate [12, 306-308]. Therefore, in the current study, the increase in exercise heart rate following DE exposure could be due to an up-regulation of sympathetic activity and thus a perturbation of the autonomic nervous system.  104 Alternatively, the elevated circulating NO that occurs following DE exposure could increase heart rate through a direct chronotropic effect of NO on the sino-atrial node [309]. It is also important to recognize that the increase in exercise heart rate in DE could be related to the non-significantly higher power output in DE compared to FA. However, based on an equation by McCarthy et al.  that predicts power output from heart rate, the 10 W difference in power output between FA and DE would equate to a 2-2.5 bpm increase in HR [310, 311]. Therefore, one can infer that pre-exercise exposure to DE would still cause a 4-4.5 bpm increase in exercise HR. Exercise practitioners should be aware that if clients are exposed to DE prior to exercise and then exercise at a constant workload, heart rate would be higher than normal. The higher exercise heart rate following DE exposure may not be problematic for healthy individuals; however, it may be of concern to those with pre-existing cardiovascular disease who cannot accommodate the additional cardiovascular strain. If exercise intensity is guided by heart rate, using the same heart rate prediction equation, the increase in heart rate due to DE could result in a 20 W reduction in power output during a workout [311]; therefore, individuals will be exercising at a lower workload and may not receive the necessary training stimulus.  Exposure to traffic-related air pollutants, such as PM2.5 during commuting, can reach 120 ?g/m3, which exceeds ambient levels [300-303]. To mimic travel to an exercise location we chose to expose individuals to DE prior to exercise. Any exposure experienced en route to an exercise location might cause physiological changes such as vascular constriction as well as impaired endothelial function and reperfusion [47, 90, 91, 162, 299]. If vascular constriction, endothelial function, and attenuated reperfusion occur, these may reduce blood supply to the exercising muscle and affect exercise performance. However, we found that 20 km time trial performance was not significantly impaired following exposure to DE. This contrasts with  105 Rundell et al.[105], and Cutrufello et al.[90], who found that exercise performance was significantly impaired with high PM1 exposure (320,000-366,000 pm/cm3).  During the experiment by Rundell et al.[105], participants were exposed to 2 low PM1 days (separated by 3 days), then a 7-day washout period, followed by 2 high PM1 days (separated by 3 days).  It is important to note that this study only found a significant impairment in exercise performance on the second day of high PM exposure, but not on the first day of high PM exposure. Despite reasonable washout periods it is possible that the decrement in performance could be because of the cumulative effect of exposure, which may explain why we did not find an effect on exercise performance. The differences between the current study and Rundell et al.[105] and Cutrufello et al.[90] could be related to timing of exposure as well as exercise duration and intensity. In the current study we chose a 20 km time trial, whereas Rundell et al.[105] and Cutrufello et al.[90] used a shorter duration and higher intensity exercise bout of six min to determine exercise performance.  It is therefore possible that the effects of exposure on exercise performance are more likely to occur in shorter duration higher-intensity exercise. During higher-intensity exercise the higher oxygen demands may not be adequately met due to impaired vascular function and reperfusion, whereas during low-intensity exercise, the body is able to compensate for this. It is also possible that for exercise performance to be implicated, exposure must occur during exercise. In Chapter 3 we demonstrated that the O2 cost of exercise is higher with DE exposure and this may have implications for exercise performance. While we only saw the higher O2 cost of exercise in low- and not high-intensity exercise, we cannot discount the possibility that the O2 cost of exercise could be higher during maximal exercise and thus affect exercise performance.   106 The effects of DE exposure prior to exercise on breathing pattern have not been adequately studied. Studies of exposure to PM show that it stimulated lung irritant receptors causing hyperpnoea, subsequently increasing E [147-150]. Additionally, several studies have examined the effects of ozone exposure during exercise.  In comparison to clean air, these studies have shown that during submaximal exercise with ozone exposure FB increases and VT decreases, while E is unchanged [135-146]. Based on this finding, we reasoned that DE exposure would irritate the airways and during exercise this would alter breathing pattern. However, we found that pre-exercise exposure to DE did not significantly alter respiratory parameters during exercise.  It is therefore possible that for respiratory irritation to manifest as alterations in breathing pattern, the exposure has to occur during exercise.  6.5 Conclusion Much of the research investigating exercise and air pollution focuses on exposure to air pollution during exercise; however, we are aware that physiological health effects occur beyond cessation of exposure. With a significant proportion of the population exercising in climate-controlled environments following a period of DE or PM exposure, this study attempted to understand the physiological and exercise performance implications of exposure to DE prior to exercise. This study addressed how the respiratory system and heart rate are affected by air pollution exposure prior to exercise. This study suggested that a 60 min exposure to DE (300 ug/m3 of PM2.5) prior to exercise significantly attenuated exercise-induced bronchodilation and increased heart rate during exercise. Pre-exercise exposure to DE did not significantly alter breathing pattern during exercise or impair 20 km cycling time trial performance in endurance-trained males. For athletes and exercising individuals it is important to understand the exercise and health implications of their environment during as well as prior to exercise. Additionally,  107 those individuals using heart rate in exercise testing and prescription should be aware that target and observed heart rates might be altered during exercise.  108 CHAPTER 7: CONCLUSION This thesis set out to identify the physiological effects of exercising at different intensities with DE exposure prior to or during exercise. With urban densification, urban exercisers may be at an increased risk of exposure to air pollution while exercising outdoors or en route to an exercise location. Current recommendations from Environment Canada and the US Environmental Protection Agency advise individuals to reduce vigorous activity during times of high pollution [127, 312], which for competing athletes and ambitious amateurs may be unrealistic or inconvenient. Additionally, as some individuals live in areas with consistently poor air quality, the advice to reduce or reschedule exercise would result in the individuals not exercising frequently enough to gain health benefits. Such recommendations are derived from a weak evidence base that focuses on research related to ozone exposure during exercise and also do not highlight the importance of exposure to air pollution prior to exercise. Understanding how the cardio-respiratory system responds to different exercise intensities in air pollution, or with exposure prior to exercise, would allow us to advise individuals about how to modify exercise routines during bouts of high pollution. Thus, the objectives of this dissertation were to:  1. Determine if the cardiovascular, respiratory, systemic inflammatory, and autonomic nervous system responses to exercise in DE differ from exercise in FA;   2. Determine if the cardiovascular, respiratory, systemic inflammatory, and autonomic nervous system responses to exercise in DE are potentiated by increasing exercise intensity;  3. Determine how exposure to DE prior to exercise affects the cardio-respiratory system and subsequent exercise performance.  109 We hypothesized that exposure to DE would impair cardio-pulmonary system function, increase systemic inflammation, and cause alterations in the autonomic nervous system; and that the magnitude of effects due to DE would be proportional to the exercise intensity. These hypotheses were based on the assumption that a proportional increase in the dose of DE would result in proportionally greater physiological and health effects. 7.1 Summary of findings 7.1.1 Chapter 3 The results described in Chapter 3 demonstrated that exposure to DE increased RPE. The higher RPE in DE supports Hypothesis 1 in section 1.11 and Objective 1, and suggests that during exercise in DE, individuals may perceive the task to be more difficult. A higher RPE will increase the likelihood of terminating exercise prematurely as well as reduce the intensity of self-paced exercise. We also found that during low-intensity exercise, respiratory and metabolic demands significantly increased in DE; however, this phenomenon did not occur during high-intensity exercise. Contrary to Hypothesis 2 in section 1.11 and as part of the Objective 2, the respiratory and metabolic responses to exercise in DE are not potentiated by exercise intensity. Data from Chapter 3 challenge the assumption that there is a proportional increase in the physiological effects related to the higher dose of DE during exercise and suggest that the assumption does not hold true for the respiratory and metabolic responses to exercise. Based on the Chapter 3 findings, it is possible that the physiological stimuli associated with higher intensity exercise outweighed the effects of air pollution. It is also possible that the clearance of particles within the lung or the location of particle deposition in the lungs changes with exercise intensity, resulting in a different physiological response that is not magnified with exercise intensity. The practical significance of the higher perceptual, respiratory, and metabolic demand  110 in healthy populations (as mentioned above) will affect pacing, intensity, and participation rates for exercise. In clinical populations, the greater respiratory and metabolic demands during low-intensity exercise may lead to increased symptoms and possibly adverse events.  7.1.2 Chapter 4 The experiment described in Chapter 4 demonstrated that following exercise in DE, plasma NOx significantly increased, but this did not occur following exercise in FA. The higher plasma NOx in DE following exercise may increase the potential for oxidative stress. These findings support Hypothesis 1 in Section 1.11 suggesting that DE exposure during exercise can  affect health. As there were no differences between low-intensity and high-intensity exercise, these findings do not support Hypothesis 2 in Section 1.11, stating that the physiological and health effects of DE will be potentiated by exercise intensity. Therefore, reducing exercise intensity during bouts of high pollution may not provide additional benefits related to plasma NOx. Furthermore, the lower FMD/SRAUC in DE that was seen during low- but not high-intensity exercise also supports the notion that reducing exercise intensity during bouts of high pollution would have no additional benefit, and in fact, might be more detrimental to health.  7.1.3 Chapter 5 The results from Chapter 5 do not support Hypothesis 1 or 2 in Section 1.11. The results suggest that the acute pulmonary function, systemic, and autonomic responses to exercise in DE do not differ from exercise in FA. The results show that that responses are not potentiated by exercise intensity and question the importance of recommendations to reduce vigorous exercise during bouts of high pollution. It is important to note that these data are not exhaustive and cannot address how other physiological outcomes or populations would be affected by exercise in DE.  111 7.1.4 Chapter 6 Chapter 6 addressed Hypothesis 3 in Section 1.11 and Objective 3. Results presented in Chapter 6 suggested that exposure to DE prior to exercise significantly attenuated exercise-induced bronchodilation and increased heart rate during exercise, but did not alter breathing pattern during exercise or impair 20 km cycling time trial performance in endurance-trained males. Collectively, the work in Chapter 6 demonstrates that exposure to DE prior to exercise affected the cardio-respiratory and autonomic nervous system but did not impair exercise performance. The higher exercise heart rate may not be of concern for healthy individuals, but if a similar response occurs in those with cardiovascular disease such as coronary heart disease, it may result in additional cardiovascular strain that they are unable to accommodate. Based on these data, it is important to encourage individuals to take into account their exposure prior to exercise.  7.2 Limitations The studies in the current dissertation employed a double blind, cross-over, and counter balanced design for the inherent power to mitigate variability caused by between-subject differences. Despite the strength of study design, there were several limitations associated with the research. One potential concern is that exercisers do not typically face the concentrations of PM used in this experiment. However, the mean PNC in the current study were not dissimilar to peak values measured during commuting in Los Angeles (800,000 particles/cm3) [313]. Mean hourly PM2.5 concentrations within the US can approach 150 ?g/m3 [314]. In 2010, wildfires in British Columbia led to record-levels of PM2.5 in the communities of Prince George, Quesnel, and Williams Lake, with an hourly maximum of 421 ?g/m3 in Williams Lake [315]. Additionally, concentrations of PM2.5 in the current studies were comparable to other  112 experimental studies [47, 96] and were below concentrations that can occur during air quality advisories [100]; therefore, the concentrations in the current studies could be experienced by urban exercisers. Despite being comparable to experimental studies, and some ambient conditions, concentrations of PM2.5 are higher than typical concentrations in some cities including Vancouver, BC, where PM2.5 concentrations reach 34 ?g/m3 [316]. A concentration of 300 ?g/m3 was chosen to reduce the likelihood of not detecting an effect due to PM concentrations being too low to elicit an effect. For example, if the study did not find significant effects at 300 ?g/m3, then we anticipated that the likelihood of experiencing acute effects at lower doses would be reduced; therefore, using 300 ?g/m3 of PM2.5 means that the negative findings in this dissertation are unlikely to occur at ambient concentrations such as those seen in Vancouver and most other cities in Canada (and the US) [316]. It is also possible that the physiological effects observed with exposure to DE were related to participants perceiving that they were exposed to DE and not FA. However, data from our laboratory suggests that individuals cannot determine whether they are exposed to DE or FA [317]. As participants and the research assistant were blinded to the exposure condition, the likelihood of the effects seen in the current study being attributable to a perception of DE exposure is small. Additionally, previous DE exposures leave a residual smell within the laboratory, which adds to the effectiveness of blinding to DE or FA exposure. The goal of this study was to assess the effects of DE exposure. Diesel exhaust is a complex mixture containing both gaseous and particulate pollutants and identifying the specific components that are responsible for each of the observed health effects is not possible. The composition of gases and PM in DE may more accurately represent ambient exposure than if the health effects of pollutants were studied in isolation. Gases such as NO2, NO, and carbon  113 monoxide have pulmonary and cardiovascular consequences such as impaired lung function, increased heart rate, exercise-induced angina, and bronchodilation. For NO2, concentrations greater than 1 ppm are necessary to induce adverse changes in pulmonary function in healthy adults [5]. Within the current study, levels of NO2 were only 0.59 ppm and are therefore unlikely to have elicited significant effects on pulmonary function. Inhalation of high concentration of NO can cause bronchodilation in animals [318]; however, in humans, exposure to NO at 80 ppm does not affect airway tone [319, 320]. Within the current study, levels of NO were only 7 ppm and are therefore unlikely to have elicited any effects on airway tone. Based on modeling studies, we would expect that concentrations of carbon monoxide in the current study (13.9 ppm during DE) would not result in carboxyhaemoglobin levels that would elicit cardiovascular changes in healthy adults [321-323]. Additionally, research investigating the effects of carbon monoxide exposure on heart rate suggests that carboxyhaemoglobin levels need to be approximately 5% in order to increase heart rate during exercise [324], a level that would far exceed carboxyhaemoglobin levels in the current studies. As gas concentrations present in our DE exposure were below those which typically elicit physiological perturbations, it is most likely that the effects seen here were attributable to the PM component of the DE; however, determining which pollutant within DE contributed to observed changes is not possible with the current study design.  Diesel exhaust chemical composition and particle size vary significantly with engine type, operating conditions, and fuel formations [42]; therefore, the mixture within the current study differs from ambient conditions and other laboratories using DE [39]. Despite this consideration, DE was chosen as a model air pollution mixture as it contains both gaseous and  114 particulate pollution and represents a mixture similar to that in an urban street canyon with significant heavy goods truck traffic. Studies in Chapters 3, 4, and 5, were powered based on a difference in FMD of 1.59%, an effect size of 0.32, and a power of 0.8 [90]. It is possible that not all outcome variables were sufficiently powered and may have increased the likelihood of incorrectly in accepting the null hypothesis. However, aside from the platelet counts, all other non-significant findings displayed no obvious trends in DE and the high p-values suggest that this was not the case.  The applicability of our research is limited to acute exposures in healthy men performing 30 min of exercise. The research focused on men because parameters such as endothelial function, E, and circulating nitrate vary across the menstrual cycle [128, 129]. To address the effects of exercise intensity and DE exposure required participants to attend on seven occasions, which in females would have necessitated spanning at least seven months. During a seven-month period, marked changes in physiology and fitness may occur, which may have confounded the results and made a study in females with this design problematic.   We cannot discount that physiological responses will differ with differences in exercise duration, fitness level and/or health status. We chose a 30 min exercise bout to represent a cycle commute [325]; however, we cannot predict how our results would have been different following longer duration exercise. We assessed outcome variables following a 20 min resting period after the cessation of exercise and for up to 2 h post exercise. Therefore, it also cannot be discounted that exposure to DE could have resulted in physiological changes that occurred prior to or after the time that they were assessed.   115 Despite research from this thesis putting into question the recommendations to reduce vigorous exercise during bouts of high pollution, this research cannot address how other populations (e.g. women, elderly, children, diseased) or health outcomes (cancer, altered birth outcomes) are affected by exercise of varying intensities in DE. 7.3 Future directions  7.3.1 Other populations A large number of questions related to the field of exercise and air pollution remain unanswered. For example, what are the consequences of exercise in air pollution for vulnerable groups such as those with cardiovascular or respiratory disease? People with cardiovascular or respiratory disease are at a higher risk of adverse health effects from exposure to air pollution. Therefore, gaining a better understanding of how these groups respond to exercise in air pollution in important. Additionally, expanding the exercise and air pollution research to women is important. When matched for lung size, women have smaller airway diameters than men [326]; therefore, how smaller airway diameter influences pulmonary particle deposition and subsequent health effects is unclear. 7.3.2 Non-acute effects The time frame for post-exposure data collection employed in this series of studies may have been too short; therefore, investigating the effects of exercising in air pollution over a greater timeframe would provide a more comprehensive understanding of the interaction between air pollution, exercise and health. 7.3.3 Environmental physiology Extreme physiological environments such as high altitude, hot and cold environments, and high levels of air pollution stress the physiological systems of the body. Exercise  116 competitions can be held in locations that encompass more than one of the above environments. Understanding how multiple environmental stressors affect exercise physiology and exercise performance would allow us to better mitigate any adverse effects on health and performance. 7.4 Synthesis of research and recommendations Based on the findings of the current dissertation, it is apparent that the physiological effects of DE depend on the bodily system studied. For example, this research demonstrated that the perceptual, respiratory, metabolic, and endothelial responses to exercise in DE differed from FA. However, pulmonary function, or systemic inflammatory responses to exercise in DE did not differ from FA.  Furthermore, the differing effects of pre-exercise exposure and exposure during exercise on heart rate and thus the autonomic nervous system, make it challenging to elucidate the exact role of DE on the autonomic nervous system. This work also indicates that as exercise intensity increases, physiological effects related to DE exposure were not magnified. This relationship is clearly represented by the lower FMD/SRAUC and higher E, O2, CO2, and the ratio of O2 consumption to power output during low-intensity exercise in DE compared to FA that was not found during high-intensity exercise. It is also represented by the absence of an effect of high-intensity exercise in DE on the pulmonary, or systemic responses to exercise. Finally, this thesis also demonstrates the importance of considering exposure prior to, as well as during, exercise. In both instances, exposure to DE elicits excess metabolic, respiratory and cardiac demands.  Before recommendations can be made to those exercising during bouts of high air pollution, the results from the current study need to be corroborated. However, based on the results of the current thesis the following implications have been highlighted:   117 7.4.1 Implications for individual exercisers ? High-intensity exercise does not acutely exacerbate the physiological effects of air pollution; therefore, to maximize the beneficial effects of exercise, individuals could consider high-intensity exercise during air pollution exposure.  Endothelial function is a reversible marker of cardiovascular disease, therefore, any impairments in endothelial function should be considered important. Currently, the Air Quality Health Index suggests that individuals reduce or reschedule activity outdoors during times of poor air quality [127]. The acute findings of the current dissertation showing impaired endothelial function on low-intensity exercise days in DE, suggest that exercise in DE can impair endothelial function. However, as endothelial function was not affected during high-intensity exercise, the findings contradict the advice to reduce vigorous activity during bouts of high pollution. Before recommendations to healthy individuals exercising in air pollution can be changed; the findings in the current dissertation first need to be corroborated. The current findings emphasize the that more research is needed to provide suitable recommendations for those exercising in air pollution and raise the question of whether reducing intensity during bouts of high air pollution is beneficial or detrimental to health. The results from this dissertation also suggest that there are no additional effects of high-intensity exercise in DE compared to FA; therefore, to maximize health gains healthy individuals could consider exercising at a high-intensity. 7.4.2 Implications for organizations advising exercisers about exercising in air pollution ? Recommendations advising individuals about exercising in air pollution should encourage individuals to minimize exposure to air pollution prior to and during exercise.  118 Currently recommendations advising exercisers how to alter exercise during bouts of high pollution do not include reference to exposure to air pollution prior to exercise. The timing of exposure in relation to exercise can influence cardio-respiratory and metabolic responses to DE. For example, exposure to DE during, but not prior to exercise increased respiratory and metabolic demands during exercise. In contrast, exposure to DE prior to, but not during exercise increased exercise heart rate and affect pulmonary function. Therefore, exposure to air pollution both prior to or during exercise stressed the cardio-respiratory system. In healthy individuals, whether such changes are problematic is questionable; however, if similar effects occur in those with compromised cardio-respiratory systems, they may not be accommodated. Based on these data, recommendations advising individuals about exercising in air pollution would benefit from increasing awareness about the importance of exposure prior to exercise. 7.4.3 Implications for sporting organizational bodies and city planners ? Sporting organizational bodies could modify the location outdoor of exercise facilities and competitions to minimize exposure to air pollution and the potential for health effects and performance impairments. Despite prior exposure to DE not impairing exercise performance, it is still possible that exposure during exercise could impair exercise performance. While this thesis did not assess the effects of exposure to DE during exercise, data from Chapter 3 demonstrating a higher RPE and O2 cost of exercise with DE exposure may, during maximal exercise, result in performance impairments. Based on the potential impacts on exercise performance, organizational bodies should consider modifying the location of exercise competitions to minimize exposure to air pollution and performance impairments. There are also endothelial impairments and a higher respiratory and metabolic demand during low-intensity exercise; therefore, it is also important  119 that recreational exercisers or those who are not exercising at a high-intensity minimize exposure to air pollution during exercise. To mitigate the impact of air pollution on recreational exercisers, city planners could appropriately select outdoor exercise venues that minimize exposure to air pollution; however, the selection of an appropriate exercise venue should not decrease overall accessibility to exercise facilities. 7.5 Overall conclusion The purpose of this thesis was to provide a strategic assessment of the physiological effects of exercising in DE. We found that the perceptual, metabolic, and endothelial responses to low-intensity exercise in DE differ from FA. With the exception of similarly elevated plasma NOx during low- and high-intensity exercise in DE, the perceptual, metabolic, and endothelial responses to high-intensity exercise in DE do not differ from FA. Finally, we demonstrated that exposure to DE prior to exercise increased exercise heart rate and decreased exercise-induced bronchodilation.  Recommendations for exercising in air pollution are not based on a substantial body of evidence that addresses if exercise enhances the effect of air pollution. The findings of this thesis do not support the advice to reduce exercise intensity on high pollution days; however, these data are limited to healthy males and do not address all potential health effects of air pollution exposure.  We suggest that recommendations for exercising in air pollution should also include a statement addressing exposure prior to exercise. Based on the health, physiological, and exercise performance implications of exercising in air pollution, city planners and event organizers should choose appropriate outdoor exercise facility locations that minimize exposure to air pollution. 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Br J Sports Med. 2007;41(1):8-12. 326. Sheel AW, Guenette JA, Yuan R et al. Evidence for dysanapsis using computed tomographic imaging of the airways in older ex-smokers. J Appl Physiol. 2009;107(5):1622-8.    138 Appendices  Appendix A  Detailed hypotheses  The hypotheses in this section are based on the assumption that a proportional increase in the dose of DE would result in proportionally greater physiological or health effects. The term adverse is taken to assume physiological/health effects greater than, or in opposition to the normal physiological response to either exercise or a filtered air environment. 4. Exposure to DE will impair cardio-pulmonary system function, increase systemic inflammation, and cause alterations in the autonomic nervous system. a. Exposure to DE will reduce: i. Endothelial function as measured by FMD and FMD/SRAUC ii. Heart rate variability iii. Pulmonary function b. Exposure to DE will increase: i. Blood pressure ii. Pulmonary inflammation iii. Plasma endothelin-1, WBC, neutrophils, monocytes, and platelets  5. The magnitude of physiological effects due to DE will be proportional to the exercise intensity.   139 a. Compared to rest and low-intensity exercise in DE, high-intensity exercise in DE will further reduce: i. Endothelial function as measured by FMD and FMD/SRAUC ii. Heart rate variability iii. Pulmonary function b. Compared to rest and low-intensity exercise in DE, high-intensity exercise in DE will further increase: i. Blood pressure ii. Pulmonary inflammation iii. Plasma endothelin-1, WBC, neutrophils, monocytes, and platelets 6. Exposure to DE prior to exercise will impair the cardio-respiratory system and exercise performance. a. Exposure to DE prior to exercise will i. Impair pulmonary function ii. Impair mean power output on a 20km cycling time trial        140 Appendix B  Experimental design   Figure B.7.1 Experimental design for Chapters 3, 4, and 5 Abbreviations: HRV: Heart rate variability; FeNo: Fraction of exhaled nitric oxide, RER: Respiratory exchange ratio; VCO2: volume of carbon dioxide produced; VO2: Volume of oxygen consumed.  Pre Post 1 h  2 h 30-min exposure with exercise or rest 20 minutes of supine rest Blood pressure Supine HRV Flow mediated dilation Complete blood count FeNO Pulmonary function 20 minutes of supine rest Blood pressure Supine HRV Flow mediated dilation Complete blood count FeNO Pulmonary function Minute Ventilation Tidal Volume  Breathing Frequency VO2, VCO2, RER Heart Rate Oxygen Saturation Ratings of perceived exertion (RPE)  141  Appendix C  Chapter 4 additional material C.1 Baseline endothelial function Table C.1 Mean pre-exposure endothelial function over six experimental test days in 18 recreationally-active males. Mean (sd)   Endothelial function Pre-occlusion diameter (mm) Peak diameter (mm) FMD (%) TTP (s) 4.26 (0.35) 4.53 (0.59) 6.5 (1.6) 52.2 (9.3) Endothelial function SRAUC FMD/SRAUC 6.6x104 (1.7x104) 1.07x10-4 (0.3 x10-4)   142 C.2 P-value summary for plasma NOx Comparing changes over time within the same intensity and same exposure FA rest pre vs. post: p=0.005,  DE rest post vs. 2 h: p = 0.02, DE rest 1 h vs. 2 h: p=0.030 DE low-intensity pre vs. post: p=0.013; DE low-intensity pre vs. 1 h: p<0.001, DE-low-intensity 1 h vs. 2 h: p=0.008  DE high-intensity pre vs. post: p=0.00, DE high-intensity pre vs. 1 h: p<0.001; DE high-intensity pre vs. 2 h: p=0.001  Comparing exposures within the same intensity and at the same time Low-intensity post-DE vs. FA: p=0.02; Low-intensity 1 h DE vs. FA: p=0.007;  High-intensity post-DE vs. FA: p=0.021; Low-intensity 1 h DE vs. FA: p=0.04  Comparing intensities within the same exposure at the same time DE Post-rest vs. low-intensity: p=0.024, rest vs. high-intensity: p<0.001;  DE 1 h rest vs. low-intensity: p=0.002, rest vs. high-intensity: p<0.001,  DE 2 h: rest vs. low-intensity: p=0.012, rest vs. high-intensity: p<0.001    143 C.3 Intensity-by-time interactions for endothelial function  Figure C.1 (a) Pre-occlusion artery diameter, (b) peak artery diameter, (c) time to peak dilation, (d) pre-occlusion shear rate, and (e) SRAUC, in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling.  A summary of significant differences can be found in C.4 144 C.4 Significant differences for endothelial function (intensity-by-time interaction) Table C.2 Intensity-by-time interaction summary table for endothelial function, summarizing significant differences (p<0.05) at each intensity between time points  Intensity Time Comparison Endothelial function Rest Pre vs. Post Pre-occlusion shear rate  Pre vs. 1 h TTP Pre-occlusion shear rate SRAUC Low-Intensity Pre vs. 1 h Pre-occlusion shear rate  Pre vs. 2 h Pre-occlusion shear rate SRAUC  Post vs. 1 h Pre-occlusion shear rate SRAUC  Post vs. 2 h Pre-occlusion shear rate SRAUC High-Intensity Pre vs. Post Baseline artery diameter TTP Pre-occlusion shear rate SRAUC  Pre vs. 2 h Pre-occlusion shear rate  Post vs. 1 h TTP Pre-occlusion shear rate SRAUC  Post vs. 2 h TTP Pre-occlusion shear rate SRAUC  1 h vs. 2 h Pre-occlusion shear rate  145 Intensity Time Comparison Endothelial function SRAUC  All parameters shown have a p<0.05 after adjustment for multiple comparisons using Sidak  Table C.3 Intensity-by-time interaction summary table for endothelial function, summarizing significant differences (p<0.05) at each time point between exercise intensities  Time Intensity comparison Endothelial function Post Rest vs. Low-Intensity Pre-occlusion shear rate  Rest vs. High-Intensity Baseline diameter TTP Pre-occlusion shear rate SRAUC   Low vs. High-Intensity TTP Pre-occlusion shear rate SRAUC 1 h Rest vs. High-Intensity TTP Pre-occlusion shear rate SRAUC  Low vs. High-Intensity TTP Pre-occlusion shear rate SRAUC  Pre values were not compared between exercise intensities as a 1-way repeated measures ANOVA was performed to ensure that all pre test values were not significantly different. All parameters shown have a p<0.05 after adjustment for multiple comparisons using Sidak.     146 Appendix D  Chapter 5 additional material D.1 Intensity-by-time interactions for heart rate variability  Figure D.1 HRV in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling Abbreviations: RMSSD: root mean square of successive intervals; SDNN: Standard deviation of NN intervals  A summary of significant differences can be found in D.2. 147 D.2 Significant differences for heart rate variability (intensity-by-time interaction)  Table D.1 Intensity-by-time interaction summary table for heart rate variability, summarizing significant differences (p<0.05) at each intensity between time points  Intensity Time comparison HRV time domain HRV frequency domain Rest Pre vs. Post SDNN    1 h vs. 2 h TRI  Low-Intensity Pre vs. 2 h RMSSD  High-Intensity Pre vs. Post SDNN RMSSD TRI LFP HFP Total Power LF/HF LF (nu) HF (nu)  Pre vs. 1 h SDNN RMSSD TRI HFP Total Power LF (nu) HF (nu)  Post vs. 1 h SDNN RMSSD TRI LFP HFP Total Power LF/HF LF (nu) HF (nu)  Post vs. 2 h SDNN RMSSD TRI LFP HFP Total Power LF/HF  148 Intensity Time comparison HRV time domain HRV frequency domain LF (nu) HF (nu)  1 h vs. 2 h SDNN RMSSD TRI LFP HFP Total Power LF/HF LF (nu) HF (nu)  All parameters shown have a p<0.05 after adjustment for multiple comparisons using Sidak  Table D.2 Intensity-by-time interaction summary table for heart rate variability, summarizing significant differences (p<0.05) at each time point between exercise intensities  Time Intensity comparison HRV time domain HRV frequency domain Post Rest vs. Low-Intensity Mean RR PNN50    Rest vs. High-Intensity SDNN RMSSD TRI LFP HFP Total Power LF/HF LF (nu) HF (nu)  149 Time Intensity comparison HRV time domain HRV frequency domain  Low- vs. High-Intensity SDNN RMSSD TRI LFP HFP Total Power LF/HF LF (nu) HF (nu) 1 h Rest vs. High-Intensity SDNN RMSSD TRI LFP HFP Total Power LF/HF LF (nu) HF (nu)  Low- vs. High-Intensity SDNN RMSSD TRI LFP HFP Total Power LF/HF LF (nu) HF (nu) 2 h Rest vs. High-Intensity RMSSD  LF/HF LF (nu) HF (nu)  Pre values were not compared between exercise intensities as a 1-way repeated measures ANOVA was performed to ensure that all pre test values were not significantly different. All parameters shown have a p<0.05 after adjustment for multiple comparisons using Sidak.    150 D.3 Intensity-by-time interactions for blood pressure   Figure D.2 Systolic blood pressure (SBP) in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling  *= significantly less than rest at the corresponding time point; ?= significantly greater than high-intensity at the corresponding time point; ? significantly greater than 1 h ( Low-Intensity only); ** significantly less than 2 h (rest only)    151 D.4 Hemoglobin intensity-by-time interaction  Figure D.3 Hemoglobin in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling ? = significantly greater than pre-exercise (rest and low-intensity only); * = significantly greater than low-intensity at the corresponding time point; ** = significantly less than 2 h (low-intensity only); ? significantly greater than post (low-intensity only)   152 D.5 Red cell distribution width intensity-by-time interaction    Figure D.4 Red cell distribution width (RDW) in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling ** = significantly less than 2 h (high-intensity only)   153 D.6 Platelet count intensity-by-time interaction  Figure D.5 Platelet count in 18 recreationally-active males prior to and following rest, low-intensity, or high-intensity cycling ** = significantly less than 2 h (low-intensity only)       

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