Gambling and heart disease

Transcription

1 Gambling and heart disease A multilevel analysis Angela Rintoul 1,2, Charles Livingstone 1, Chebiwot Kipsaina 1 NAGS, 21 November 2013, Sydney 1 School of Public Health and Preventive Medicine, Monash University 2 Australian Gambling Research Centre, Australian Institute of Family Studies

2 Disclosures Views expressed in this presentation are those of the authors and may not reflect the views of the AIFS or the Australian Government Funding to conduct this study was provided by Monash University. Authors do not work for, consult to, own shares in or receive funding from any company or organisation that would benefit from this study, and have no relevant affiliations Ethical approval: Monash University, Victorian Department of Justice

3 Overview Gambling problems and health conditions The socioeconomic gradient in heart disease gambling losses (harms) This multilevel study using existing datasets Policy implications, next steps, conclusions

4 Gambling and health Problem gamblers (PG) are more likely to experience poor health than non-pg Cardiovascular disease, high blood pressure Obesity Insomnia, sleep disorders Depression and anxiety Migraines, intestinal and respiratory ailments Suicide and suicidal ideation Alcohol, tobacco and other substance use Relationship dysfunction, neglect of children, injuries (Bergh et al 1994; Shaw et al 2007; Vic DOJ, 2009; Gerstein et al 1999; Hodgins et al 2006)

5 Health of problem gamblers Higher utilisation of health services (Morasco et al, 2006) French case-control study found PG more likely to experience coronary heart disease than non-pg (Germain et al, 2011) Excessive gambling is likely to exacerbate illness, magnifying health disparities

6 EGM vulnerability Melbourne Source: Rintoul, Livingstone, Mellor, Jolley, 2013

7 EGM losses follow a social gradient Source: adapted from Rintoul, Livingstone, Mellor, Jolley, 2013

8 Heart disease and disadvantage There is a social gradient in health for almost every health condition* (VPHS, 2008) Heart disease is the leading cause of death in Australia 50,000 deaths in 2008 Costs est. $5.9 billion (AIHW, 2011) Whitehall study of UK civil servants showed 3.6 fold difference in coronary mortality between the lowest and highest grade of workers (Rose & Marmot, 1981) *except alcohol consumption and overweight

9 Objectives To test the hypothesis that after controlling for confounding variables, there is a positive relationship between heart disease and gambling problems To inform health and PG services To inform the design of future studies

10 Method: Multilevel data Exploratory study Weighted Vic population health survey (VPHS) data Representative at all 79 LGAs across Victoria: 34,067 respondents, 3,277 (9.6%) reported heart disease Doctor-reported heart disease Anxiety and depression (Kessler 10) Marital status, age, sex EGM: loss, location, and no. of machines in LGA LGA EGM data applied to each of 34,067 respondents

11 Method: Statistical analysis Directed acyclic graphs (DAGs): new epi tool to map causal pathways DAGs reduce bias (Shrier & Platt 2008) encode assumptions to test in model Software: DAGitty Identify relevant variables for multiple logistic regression model Regression software: STATA v13

12 Causal diagram Selected model Predictor: EGM losses (proxy for gambling harm) Outcome: Heart disease Confounders (adjusted): EGM density Marital status Age Sex Depression & anxiety (Kessler 10) Developed using DAGitty.net

13 Gradient in heart disease

14 Results Adjusted and weighted data showed heart disease risk follows gradient as losses increased across quintiles, so did the risk of heart disease Heart disease more common in areas of high loss Adjusted OR 1.4 (95% CI ) in Q5 compared to Q1 Direction of gradient supports our hypothesis, however, it was not statistically significant (p=.14)

15 Limitations EGM harm is based on LGA level losses Ecological measure applied to individuals: more robust data needed (i.e. local prevalence of PG rather than proxy of losses) Victorian population health survey uses self report data CATI survey

16 Policy relevance Governments and communities need to understand the causes of illness in order to prevent disease, improve health, reduce costs If a relationship is demonstrated in more rigorous epidemiological study design, there will be more compelling reasons for action on preventing harm from gambling

17 Next steps Conduct a more robust study (i.e. cohort) to test the hypothesis of a positive relationship between PG and heart disease Collect information about the health of partners and family members of PG, evidence that partners experience illness associated with problems of PG

18 Conclusions Evidence base for impact of gambling problems on physiological health is limited Need for stronger studies of the relationship between physiological health and gambling Relationship between PG & heart disease plausible given the stress induced by PG Need to balance investments in research to focus on preventing gambling problems

19 Acknowledgements Drs Livingstone & Kipsaina Biostatistics Unit, Department of Epidemiology & Preventive Medicine, Monash University, (Catherine Smith) Population health survey, Victorian Department of Health (Alison Marwick, Loretta Vaughan) VCGLR (Syd Narsey) Australian Institute of Family Studies

20 References Bergh, C., & Kühlhorn, E. (1994). Social, psychological and physical consequences of pathological gambling in Sweden. Journal of Gambling Studies, 10(3), Black, D. W., Shaw, M. C., McCormick, B. A., & Allen, J. (2012). Marital status, childhood maltreatment, and family dysfunction: a controlled study of pathological gambling. J Clin Psychiatry, 73(10), Germain, C., Vahanian, A., Basquin, A., Richoux-Benhaim, C., Embouazza, H., & Lejoyeux, M. (2011). Brief report: coronary heart disease: an unknown association to pathological gambling. Front Psychiatry, 2, 11 Gerstein, D., Murphy, S., Toce, M., Hoffmann, J., Palmer, A., Johnson, R.,... Hill, M. A. (1999). Gambling Impact and Behavior Study: Report to the National Gambling Impact Study Commission: National Opinion Research Centre, University of Chicago. Hare S. A Study of Gambling in Victoria: Problem Gambling from a Public Health Perspective. Melbourne: Department of Justice, 2009 Morasco, B. J., Pietrzak, R. H., Blanco, C., Grant, B. F., Hasin, D., & Petry, N. M. (2006). Health problems and medical utilization associated with gambling disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Psychosom Med, 68(6), Productivity Commission. Gambling. Canberra, 2010 Rose, G., & Marmot, M. G. (1981). Social class and coronary heart disease. Br Heart J, 45, Rintoul, A., Livingstone, C., Mellor, A.P., & Jolley, D. (2013) Modelling vulnerability to gambling related harm: how disadvantage predicts gambling losses. Addiction Research & Theory. 21 (4): Shrier, I., Platt, R., (2008) Reducing bias through directed acyclic graphs, BMC Medical Research Methodology, 8:70 Shaw, M. C., Forbush, K. T., Schlinder, J., Rosenman, E., & Black, D. W. (2007). The Effect of Pathological Gambling on Families, Marriages, and Children. CNS Spectr, 12(8),