1 / 56

Taryn Chalmers 1 Supervisors: Associate Professor Sara Lal 1 , Dr. Tim Luckett 2

DOES DEPRESSION DRIVE YOU? The prevalence of mood states within a sample of Australian professional drivers. Taryn Chalmers 1 Supervisors: Associate Professor Sara Lal 1 , Dr. Tim Luckett 2 1 Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney.

lois
Download Presentation

Taryn Chalmers 1 Supervisors: Associate Professor Sara Lal 1 , Dr. Tim Luckett 2

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. DOES DEPRESSION DRIVE YOU?The prevalence of mood states within a sample of Australian professional drivers Taryn Chalmers1 Supervisors: Associate Professor Sara Lal1, Dr. Tim Luckett2 1Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney

  2. Heavy vehicle truck driving in Australia Introduction Large distances between metropolitan hubs have facilitated reliance on road freight industry Fundamental to Australia’s affluence Contributes $AUD 43.3 billion dollars annually to Australia's economy(Bureau off Infrastructure Transport and Regional Economics) Unique workforce profile: (Australian Government, 2012)

  3. Train driving in Australia Introduction • Allows for the movement of goods, services and individuals between cities and metropolitan hubs • Approximately 17,000 drivers employed each year (Australian Government, 2015) • Unique workforce profile: • Higher percentage of males (97.4% male vs. national average of 54.9% male) (Mina and Casolin, 2007)

  4. Health concerns for professional drivers Introduction • Many workplace similarities between heavy vehicle and train drivers • Long hours spent sitting • Workplace isolation • Intermittent rest and work cycles • Monotonous driving conditions • Necessity of strict mental alertness

  5. Health concerns for professional drivers Introduction Pain Cancer Sleep apnoea Diabetes Cardiovascular disease Affective disorders

  6. Depression (affective disorder) Introduction • Leading cause of disability worldwide (World Health Organisation, 2010) • Fourth leading contributor to the global burden of disease (World Health Organisation, 2009) • Depression affects: • 121 million worldwide • 11.6% of the Australian population • Neglecting to address mental health in the workplace will cost $10.9 billion annually in Australia (Pricewaterhousecoopers, 2014)

  7. Theories of depression Introduction Monoamine theory (Schildkraut, J., 1965) • Depression is the result of underactive monoamines • Serotonin and norepinephrine Diathesis-stress theory (Abela and D'Alessandro, 2002) • Early adverse life events • Hypothalamic-pituitary-adrenal axis Stressful lifetime event

  8. Hypothalamic-pituitary-adrenal axis Introduction Stressors elicit the release of cortisol Hippocampus – detects serum cortisol Chronic hypercortisolemia leads to destruction of hippocampal cells  reduced negative feedback Hippocampus Hypothalamus CRH Pituitary gland ATCH Adrenal gland CORTISOL -

  9. Mental illness and stress in truck and train drivers Introduction 13.3% of Australian heavy vehicle drivers exhibited some form of depression (Hilton et al., 2009) 14.5% of truck drivers feel more depressed since starting work within the industry(Wong et al., 2007) Train drivers report the highest number of accepted claims for workers compensation For mental or stress related issues, almost 26 times the number of claims of the average male job in Australia(SafeWork, 2013) Males less likely to report affective disorders, therefore rates may be higher (Klint and Weikop, 2004)

  10. Depression and driver performance Introduction Increases odds ratio (5.0) of an accident or near miss whilst driving (Hilton et al., 2009)Reaction time and steering control reduced by 5.7% (Hilton et al., 2009)

  11. Aims • A sub-study within a larger global health study • Assess prevalence of • Negative mood states • Depression • Anxiety

  12. Experimental protocol • Human ethics approved • Truck drivers (>4.5 Gross vehicle mass) • Train drivers • Endorsed by Australia Post, Sydney Trains and the Australian Trucking Association

  13. Experimental protocol Introduction Lifestyle Appraisal Questionnaire(Craig et al., 1996) Professional Driver Package (Adapted from Kavanagh, 2007) Profile of Mood States (McNair et al., 1971) Beck’s Anxiety Inventory (Beck et al., 1993) Beck’s Depression Inventory (Beck et al., 1996) Likert fatigue scale (Lal and Craig, 2002)

  14. Results – Sample size Introduction Approval obtained to test on-site at Australia Post Study advertising undertaken by Sydney Trains in February of 2015

  15. Results – Demographic Introduction Train and truck driving sample groups age and weight matched Both samples in high range overweight category Key: BMI = Body mass index (weight (kgs)/height (m2)

  16. Results – Lifestyle and stress Introduction • Lifestyle appraisal questionnaire - truck drivers compared to train drivers: • Truck drivers - • Lifestyle risk factors for developing chronic diseases (p=<0.0001) • Stress (p=<0.0001)

  17. Results - Mood states Introduction * * * * * * * * = Significant (p≤0.05)

  18. Results – Stress links p=<0.05

  19. Discussion summary Introduction Both samples in high range overweight range of BMI High levels of negative mood states in truck driving population Improvements in mental health awareness and management may improve psychological health of individuals within the industry, reduce economic burden of absenteeism and workers compensation Improvements in commuter safety

  20. Acknowledgements Introduction • Supervisors: Associate Professor Sara Lal, Dr Tim Luckett • Neuroscience Research Unit • Jaymen Elliott • Ty Lees • Louisa Giblin • Leon Rothberg • Dr Budi Jap • Volunteers • Australia Post • Sydney Trains • Australian Trucking Association • Jeffrey Schaffer, Operations manager, Australia Post • Paul Doherty, Regional area manager, Sydney Trains • Anthony Chalmers

  21. Introduction Questions?

  22. References ABELA J.R., D'ALESSANDRO D.U. 2002. Beck's cognitive theory of depression: a test of the diathesis-stress and causal mediation components. Br J ClinPsychol 41: Pt 2: 111-28 ACHARYA U.R., SANKARANARAYANAN M., NAYAK J., XIANG C., TAMURA T. 2008. Automatic identification of cardiac health using modeling techniques: A comparative study. Information Sciences 178: 23: 4571-82 ARBOUR A. 2012. Male Depression. http://www.livinglifecounseling.com/male-depression.html. AUSTRALIAN BUREAU OF STATISTICS. 2008. Australian National Accounts: National Income, Expenditure and Product. Canberra ACT AUSTRALIAN BUREAU OF STATISTICS. 2011. 9309.0 - Motor Vehicle Census, Australian Government, Canberra ACT BECK A.T., STEER R.A., BROWN G.K. 1996. BDI-II, Beck Depression Inventory: Manual, 2nd ed. Boston: Harcourt, Brace, and Company. BUREAU OF INFRASTRUCTURE TRANSPORT AND REGIONAL ECONOMICS. 2008. Australian Transport Statistics Yearbook 2007,. ed. Department of Infrastructure and Transport Regional Development and Local Government. Canberra ACT: Australian Government BUREAU OF INFRASTRUCTURE TRANSPORT AND REGIONAL ECONOMICS. 2011. Fatal heavy vehicle crashes Australia quarterly bulletin. ed. Department of Infrastructure and Transport, pp. 1-8. Canberra: Australian Government COOLEY K. 2009. Chaos on Kessels Road. http://city-south-news.whereilive.com.au/news/story/chaos-on-kessels-road-macgregor/. 12/03/2012 DA SILVA-JUNIOR F.P., DE PINHO R.S., DE MELLO M.T., DE BRUIN V.M., DE BRUIN P.F. 2009. Risk factors for depression in truck drivers. Soc Psychiatry PsychiatrEpidemiol 44: 2: 125--9 DEPARTMENT OF INFRASTRCUTURE TRANSPORT REGIONAL DEVELOPMENT AND LOCAL GOVERNMENT. 2009. Road Deaths Australia 2008 Statistical Summary, Canberra ACT DRISCOLL O.P. 2009. Major Accident Investigation Report 2009. ECKBERG D.L. 1997. Sympathovagal balance: a critical appraisal. Circulation 96: 9: 3224-32 FURNESS J.B. 2009. Autonomic Nervous System. In Encyclopedia of Neuroscience, pp. 833-35: Oxford: Academic Press GANGWISCH J.E., HEYMSFIELD S.B., BODEN-ALBALA B., BUIJS R.M., KREIER F., PICKERING T.G., RUNDLE A.G., ZAMMIT G.K., MALASPINA D. 2006. Short sleep duration as a risk factor for hypertension: analyses of the first National Health and Nutrition Examination Survey. Hypertension 47: 5: 833-9 HARTVIG P.A.M., O. 1983. Coronary Heart Diease Risk Factors in Bus and Truck Drivers. International archives of occupational and environmental health 52353-60HAUKKALA A., KONTTINEN H., LAATIKAINEN T., KAWACHI I., UUTELA A. 2010. Hostility, anger control, and anger expression as predictors of cardiovascular disease. Psychosom Med 72: 6: 556-62 HE J., WHELTON P.K. 1999. Elevated systolic blood pressure as a risk factor for cardiovascular and renal disease. J HypertensSuppl 17: 2: S7-13 HILTON M.F., STADDON Z., SHERIDAN J., WHITEFORD H.A. 2009. The impact of mental health symptoms on heavy goods vehicle drivers' performance. Accident analysis and prevention 41: 3: 453-61 JAL S.P. 2012. Blood Pressure. http://www.sportstek.net/blood-pressure.htm. LICHT C.M.M., PENNINX B.W.J.H., DE GEUS E.J.C. 2011. Reply to: Effects of Serotonin Reuptake Inhibitors on Heart Rate Variability: Methodological Issues, Medical Comorbidity, and Clinical Relevance. Biol Psychiatry 69: 8: e27-e28 LINDEN W., MOSELEY J.V. 2006. The efficacy of behavioral treatments for hypertension. ApplPsychophysiol Biofeedback 31: 1: 51-63 LINGGO. E. 2012. Principles of Human Anatomy and Physiology Chapter Seven. http://hap1nuo1group3.blogspot.com.au/2012/01/chapter-7a.html. 01.08.2012 MCNAIR D., LORR M., DROPPELMAN L. 1971. Manual for the Profile of Mood States. San Diego, CA: Educational and Industrial Testing Service MEYER J.H. 2008. Applying neuroimaging ligands to study major depressive disorder. SeminNucl Med 38: 4: 287-304 TASMAN A. 2004. Trucking – Driving Australia’s Growth and Prosperity, Economics Policy Strategy WONG W.C., TAM S.M., LEUNG P.W. 2007. Cross-border truck drivers in Hong Kong: their psychological health, sexual dysfunctions and sexual risk behaviors. J Travel Med 14: 1: 20-30 WORLD HEALTH ORGANISATION. 2009. Mental Health - Depression. http://www.who.int/mental_health/management/depression/definition/en/. 20/02/2012 Introduction

  23. Results - Mood states Profile of Mood States t-tests between sample groups: • Truck drivers – • Tension-anxiety (p=<0.0001) • Anger-aggression (p=0.004) • Fatigue-Inertia (p=0.023) • Depression-dejection (p=<0.0001) • Confusion bewilderment (p=<0.0001) • Total mood disturbance (p=<0.0001) • Train drivers – • Vigor-activity (p=<0.0001)

  24. Results - Mood states • Beck’s Anxiety Inventory: • Train drivers: 3.71 ± 3.63 • Truck drivers: 2.89 ± 3.29 • Normative values: 6.6 ± 8.1 (Gilis et al., 1995) • Beck’s Depression Inventory: • Train drivers: 6.4 ± 4.81 • Truck drivers: 7.9 ± 10.14 • Normative values: 9.11 ± 7.6 (Dozios et al., 1998)

  25. Control group • Biphasic assessment (active and baseline) • It is well established in psychophysiology literature that individuals should act as their own control to eliminate inter-individual variability • Once associations were established, age and weight matched control group on non-professional drivers will be included

  26. Sample size Under similar laboratory conditions conducted at the University of Technology Sydney in the Neuroscience Research Unit, for the type of data collected (analysing heart rate variability), it has already been identified that a sample of 25 yields sufficient sample power to perform the non-parametric statistical analysis used in this study. This is well established in the psychophysiology literature(Lal & Craig, 2002)

  27. Randomisation • Randomisation not part of the first phase of clinical testing • Subject assessed on availability

  28. Time of day • Volunteers are tested between the hours: • 9am – 2pm • This is in order to avoid an electrocardiogram recording during the dip in heart rate variability between 8 – 9 am and 2 – 3pm recently reported by Chen in 2011. • Post-prandial dip in blood pressure

  29. Biochemical measures of depression Well-validated psychometric questionnaires remain the most reliable measure of assessing depression May introduce a pilot study of salivary cortisol

  30. Honesty of participant responses • All psychometric tools used are clinical, validated and reliable psychometric tools • Questions are often asked repeatedly, with responses being required a number of times • Participants voluntarily included in study • Wide range of depression scores • Confidentiality assured

  31. Lifestyle appraisal tool part 1 • Assesses collective lifestyle factors. • No definitive causation point • Allows us to obtain a global lifestyle score • Correct to postulate that negative factors are linked to increases in stress, depression, etc.

  32. Abstinence Nicotine – 4 hours • Increases blood pressure • Elevates both low and high frequency heart rate variability(Erblich, 2011) Caffeine – 4 hours • Increased sympathetic nervous system activation (Corti et al., 2001) • Decreases parasympathetic nervous system activity (Corti et al., 2001) Alcohol – 12 hours • Decreases heart rate variability (Koskinen, 1994)

  33. Modes of analysis • Dependent sample t-test • to identify if the means of two samples were significantly different • Pearson's coefficient • an estimation of both the direction and strength of a linear relationship between an dependent and independent variable • -1 to +1 • Regression analysis • establishes the predictive variable with the most significance when numerous independent variables are significant predictors for a particular parameter

  34. Normal distribution • Not normally distributed: • Clean the data • This involves determining measurement errors, data-entry errors and outliers, and removing them from the data for valid reasons. • 2. Stratify two or more processes: • If two or more data sets that would be normally distributed on their own are overlapped, data may look bimodal or multimodal. • Determine which X’s cause bimodal or multimodal distribution and then stratify the data and recheck for normality, after which the stratified process can be worked with together. • 3. Use alternate tools for non-normally distributed data: • Mann-Whitney test (t-test) • Kruskall-Wallis test (ANOVA)

  35. Depression-dejection • A mood of depression accompanied by a sense of personal inadequacy • Includes scales: • Personal worthlessness • Futility regarding the struggle to adjust • Sense of emotional isolation from others • Sadness • Guilt • Internal consistency of 0.95

  36. Tension-anxiety • Heightened musculoskeletal tension • Includes scales: • Somatic tension • Observable psychomotor manifestation • Internal consistency of 0.92

  37. Anger-hostility • A mood of anger and antipathy towards others • Includes scales: • Intense, overt anger • Hostility • Sullen behaviour • Suspicious behaviour • Internal consistency of 0.92

  38. Vigor-activity • A mood of vigorous, ebullience, and high energy • Internal consistency of 0.88

  39. Fatigue-inertia • A mood of weariness, inertia, and low energy level • Internal consistency of 0.93

  40. Heart rate variability and fish oil 810 mg/day of marine n-3 PUFA (fish oil) was shown to decrease resting heart rate and increase parasympathetic modulation of the heart  favorable alterations to reduce risk of cardiovascular mortality (Australian Heart Foundation, 2008)

  41. Hypertensive medication Calcium channel blockers • Decreases heart rate Statins • Lower blood cholesterol levels Beta blockers • Decreases heart’s reactivity to sympathetic input ACE inhibitors • Increases cardiac output and blocks conversion of angiotensin I to angiotensin II

  42. Monoamine theory of depression • Serotonin • originating in the raphe nuclei of the brain and projecting through the frontal cortex, cerebellum and limbic system, has significant effects on mood behaviour and social interactions • Noradrenaline • originating in the locus coeruleus and projecting through the forebrain, prefrontal cortex, cerebellum and limbic system, noradrenaline has regulatory effects on attention, stress management and the fight or fight • deficits in the amygdala have been implicated in the development of depressive behaviour

  43. Diathesis-stress theory • The effect of early childhood stressors and/or genetic diatheses cause biological alterations in the hypothalamic-pituitary-adrenal axis (HPA axis) • Disrupted activation of the hippocampal glucocorticoid receptors leads to a decreased inhibition of cortisol release hyperactivation of the HPA axis

  44. Depicts the process of monoamine loss in a depressed patient. • Depicts monoamine release in a synapse in a healthy person. • During a major depressive episode, monoamine oxidase A (MAO-A) density is elevated resulting in greater metabolism of monoamines such as serotonin, norepinephrine, and dopamine in the brain. • Outcomes range from (C) to (D).

  45. HPA axis and depression Of direct relevance to depression, elevated cortisol has been shown to reduce the density of pyramidal neurons and cell survival in the hippocampus, reducing cognitive processing of stressors, and increase growth in the basolateral amygdala neurons, leading to anxious behaviour. Stress-related increases in cortisol contribute to induce neuropsychiatric disorders such as depression via prolonged glucocorticoid activation due to inhibited glucocorticoid receptor responses in the hippocampus leading to impaired negative feedback processes, atrophy and debranching of dendrites in the hippocampus and resultant downgrading of hippocampus functioning.

  46. Depression and an increased risk of CVD

  47. P: Atrial depolarisation Q: Depolarisation of the interventricular septum R: Ventricular depolarisation S: Ventricular depolarisation T: Ventricular repolarisation U: Atrial repolarisation PR interval: The interval of time required for the impulse to reach the atrioventricular node from the sinoatrial node PR segment: This interval represents the time between the onset of atrial depolarization and the onset of ventricular depolarization QRS interval: The duration of the ventricular depolarization

  48. Affective disorders • Dysthymia: • depressed mood most of the time for at least two years, along with at least two of the following symptoms: poor appetite or overeating; insomnia or excessive sleep; low energy or fatigue; low self-esteem; poor concentration or indecisiveness; and hopelessness • Symptoms not associated are anhedonia (inability to feel pleasure) and psychomotor symptoms (chiefly lethargy or agitation) • (The American Psychiatric Association, 2010) • Bipolar affective disorder: • extremes of mood that may include the lows of depression as well as the highs of a very elated mood (known as mania) • (Synapse, 2009)

  49. Heart rate variability and depression • The Australian Heart Foundation Meta-analysis the impact of depression and antidepressant treatment on HRV in depressed patients without CVD(Kemp et al., 2010) • 18 articles • Depression severity negatively correlated with HRV Impact of depression subtype and comorbid anxiety on heart rate variability (Kemp et al., 2011)

  50. Basis of heart rate variability • Parasympathetic • Synaptic release of acetylcholine • Short latency period • Fast metabolism • Sympathetic • Synaptic release of noradrenaline • Slow metabolism

More Related