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Increasing Our Understanding of the Association Between Extreme Heat And Increasing our Understanding of the Association between Extreme Heat and Hospital Admissions in Greater Sydney, Australia Marissa Parry A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy School of Biological, Earth and Environmental Sciences Faculty of Science September 2018 1 2 3 4 5 Table of Contents Acknowledgements 10 List of Tables 11 List of Figures 15 List of Abbreviations 16 Relevant Publications and Conference Presentations 17 Thesis Abstract 19 Chapter One: Introduction 21 1.1 Background 21 1.2 Objective and Aims 30 1.3 Thesis Structure 31 1.4 Thesis Scope 31 Chapter Two: Literature Review 33 2.1 Observed and Projected Changes in Ambient Temperature 33 2.1.1 Observed Changes in Average Temperature 33 2.1.2 Projected Changes in Average Temperature 34 2.1.3 Observed Changes in Temperature Extremes 35 2.1.4 Projected Changes in Temperature Extremes 37 2.1.5 Temperature Extremes and the Paris Agreement 39 2.2 Linking Extreme Heat and Human Health Outcomes 40 2.2.1 The Association between Temperature and Health Outcomes 40 2.2.2 The Association between Extreme Heat and Health Outcomes 40 2.2.3 Climate Change and Temperature-Related Health Outcomes 47 2.3 Linking Climate Change, Ambient Air Pollution and Health Outcomes 49 2.3.1 Ambient Air Pollutants: Ozone and Particulate Matter 49 6 2.3.2 Linking Meteorology and Ambient Air Pollution 50 2.3.3 The Impact of Climate Change on Ambient Air Pollution 52 2.3.4 Linking Ambient Air Pollution and Health Outcomes 54 2.3.5 Ambient Air Pollution and Health Outcomes under Climate Change 56 2.4 Ambient Air Pollution as a Confounder 58 2.5 Ambient Air Pollution as an Effect Modifier 59 2.5.1 Temperature, Ozone and Particulate Matter 60 2.5.2 Heat Waves, Ozone and Particulate Matter 63 5.2.3 Heat Waves, Ozone, Particulate Matter and Morbidity 64 Chapter Three: Methods 65 3.1 Study Setting 65 3.1.1 Greater Sydney, Australia 65 3.2 Data 66 3.2.1 Meteorological Data 67 3.2.2 Ambient Air Pollution Data 72 3.2.4 Health Data 74 3.3 Methods 76 3.3.1 Study Design 76 3.3.2 Statistical Analysis 77 3.4 Ethics 77 Chapter Four: Aim 1 78 4.1 Introduction 78 4.2 Data and Methods 82 4.2.1 Meteorological Data 82 4.2.2 Health Data 84 4.2.3 Study Design and Statistical Analysis 84 4.3 Results 87 7 4.4 Discussion 99 4.5 Chapter Conclusion 104 Chapter Five: Aim 2 105 5.1 Introduction 105 5.2 Data and Methods 108 5.2.1 Meteorological Data 108 5.2.2 Ambient Air Pollution Data 109 5.2.3 Health Data 110 5.2.4 Study Design and Statistical Analysis 111 5.3 Results 113 5.4 Discussion 123 5.5 Chapter Conclusion 129 Chapter Six: Aim 3 130 6.1 Introduction 130 6.2 Data and Methods 133 6.2.1 Meteorological Data 133 6.2.2 Ambient Air Pollution Data 134 6.2.3 Health Data 135 6.2.4 Study Design and Statistical Analysis 136 6.3 Results 138 6.4 Discussion 147 6.5 Chapter Conclusion 152 Chapter Seven: Conclusion 154 7.1 Summary of the Key Findings 154 7.2 Potential Strengths and Limitations 157 7.3 Potential Implications 161 7.4 Directions for Future Research 164 8 7.5 Conclusion 166 References 167 Appendix 210 9 Acknowledgements I would like to express my sincere thanks and appreciation to my supervisors, Associate Professor Donna Green, Professor Andrew Hayen and Dr Ying Zhang, for their support, advice and guidance throughout my PhD studies. I would also like to thank the Climate Change Research Centre and the ARC Centre of Excellence for Climate System Science. I would like to thank and acknowledge Associate Professor Lisa Alexander for her advice and insights regarding weather station data and temperature extremes; Professor Adrian Barnett for this assistance with the application of the ‘season’ package in the R Statistical Computing Environment; James Goldie for his assistance and insights regarding public holiday data; Nicole Mealing for her advice and assistance regarding the structure of this thesis; and Jane Goodwin for her helpful comments and suggestions on an earlier version of this thesis. I would like to thank and acknowledge several government agencies for providing the data used in this thesis. These include the Bureau of Meteorology for providing the meteorological data; the NSW Office of Environment and Heritage for providing the air pollution data; the Centre for Epidemiology and Evidence, NSW Ministry of Health, for providing the hospital admissions data from the Admitted Patient Data Collection (SAPHaRI); and the NSW Department of Education for providing the school holiday data. Finally, I would like to express my deepest thanks and appreciation to my dear family and friends. I am ever so grateful for your continued support, encouragement and generosity over the past four years. 10 List of Tables Table 2.1 Main population groups identified as being susceptible or vulnerable to the effects of extreme heat in Australia. Table 3.1 Search criteria used to identify weather stations located within the SSD. Table 3.2 Description of quality control flags provided by the Bureau of Meteorology. Table 3.3 NEPM standards and goals for pollutants used in this thesis. Table 4.1 Descriptive statistics for selected heat-related EHAs during the warm season in the SSD, 2001 to 2013. Table 4.2 Effect of heat waves first in season compared to heat waves not first in season on EHAs for acute renal failure in the SSD during the warm season, 2001 to 2013. Table 4.3 Effect of heat waves first in season compared to heat waves not first in season on EHAs for dehydration in the SSD during the warm season, 2001 to 2013. Table 4.4 Effect of heat waves first in season compared to heat waves not first in season on EHAs for fluid imbalance disorders in the SSD during the warm season, 2001 to 2013. Table 5.1 Descriptive statistics for environmental variables in the SSD during the warm season, 2001 to 2013. Table 5.2 Descriptive statistics for EHAs for three respiratory diseases in the SSD during the warm season, 2001 to 2013. Table 5.3 Summary of heat wave characteristics for each heat wave definition used. 11 Table 5.4 The effect of heat wave days on EHAs for three respiratory diseases on days with high levels of ozone compared to days with low levels of ozone in the SSD during the warm season, 2001 to 2013, for all ages. Effects are presented as odds ratios with their corresponding 95% confidence intervals. Table 5.5 The effect of heat wave days on EHAs for three respiratory diseases on days with high levels of ozone compared to days with low levels of ozone in the SSD during the warm season, 2001 to 2013, for specific age groups. Effects are presented as odds ratios with their corresponding 95% confidence intervals. Table 6.1 Descriptive statistics for environmental variables in the SSD during the warm season, 2001 to 2013. Table 6.2 Descriptive statistics for EHAs for six cardiovascular diseases in the SSD during the warm season, 2001 to 2013. Table 6.3 Summary of heat wave characteristics for each heat wave definition used. Table 6.4 The effect of heat wave days on EHAs for six cardiovascular diseases on days with high levels of PM10 compared to days with low levels of PM10 in the SSD during the warm season, 2001 to 2013, for all ages. Effects are presented as odds ratios with their corresponding 95% confidence intervals. Table 6.5 The effect of heat wave days on EHAs for six cardiovascular diseases on days with high levels of PM10 compared to days with low levels of PM10 in the SSD during the warm season, 2001 to 2013, for those aged 0-64 years and 65 years and over. Effects are presented as odds ratios with their corresponding 95% confidence intervals. Table A1 Temperature thresholds calculated for the warm season in the SSD, 2001 to 2013. 12 Table A2 Fifteen definitions used to define single days of extreme heat. Table A3 Definitions used for heat waves with maximum temperature as the metric. Table A4 Definitions used for heat waves with mean temperature as the metric. Table A5 Definitions used for heat waves with minimum temperature as the metric. Table A6 Effect of heat waves first in season compared to heat waves not first in season on EHAs for direct heat-related conditions in the SSD during the warm season, 2001 to 2013. Table A7 The average and peak intensity of heat wave days comprising of the first heat wave of the season and those heat wave days that do not during the warm season in the SSD, 2001 to 2013. Table A8 The average duration of heat waves first in the warm season and those heat waves not first in the SSD during the warm season, 2001 to 2013. Table A9 Characterisation of heat wave days as high and low level ozone days. Table A10 The effect of heat wave days on EHAs for three respiratory diseases on days with high levels of ozone compared to days with low levels of ozone in the SSD during the warm season, 2001 to 2013 for all ages and specific age groups at lag2. Table A11 Characterisation of heat wave days as high and low level PM10 days.
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