Amanda Baxter Global Burden of Disease 2010 : Estimating burden of disease attributable to mental disorders Amanda Baxter Queensland Centre for Mental Health Research The University of Queensland Brisbane, AUSTRALIA Australian Society for Psychiatric Research Dunedin, 2011 Good morning, I’d like to thank everyone for coming today. My topic is probably going to differ a little from the others in that it is around epidemiology at a very broad global level. SO I hope you find it of interest. I’m currently working on the new Global Burden of Disease Study which is being led by a core team headed by Chris Murray out of Seattle. Unlike the first GBD which was funded by the World Bank, this project was funded by the Bill and Melinda Gates Foundation and aims to provide objective measures of health loss for over 200 disease and injuries for the years 1990, 2005 and 2010. 1

The Global Burden of Disease Study, 1990 A major finding of the study was the magnitude of burden associated with chronic disease, particularly mental disorders. 15-44 yr age group: 5 of 10 leading causes of burden in the world were mental disorders Depression was the leading cause of disease burden Ref: Murray & Lopez, 1996 The Global Burden of Disease Study quantifies loss of health using the Disability Adjusted Life Year (or DALY) which is a composite measure of Years of health lost due to Disability plus years of Life Lost to premature mortality. The first GBD released in 1996 resulted in a big change in the way psychiatric disorders are perceived within the context of public health. The study estimated that 5 of the top 10 causes of disease burden in 15 to 44 yr olds were mental disorders, with depression the leading cause of burden at a global level. These findings demonstrated for the first time the magnitude of health loss that is associated with chronic disorders, particularly the mental disorders. As some of you are no doubt aware, there is a new Global Burden of Disease Study underway. So why is the study being re-done. First of all, there is now a lot more data available to use as input into the burden estimates. Secondly, more work has been done around the methodology, in particular the disease modelling and the social values choices that are inherent in any summary health measure.

what is being done differently in GBD2005 Changes what is being done differently in GBD2005 More disorders Emphasis on empirical evidence New disease modeling tool (Dismod3) - Derive missing data, use of co-variates Disability weights Discounting Age weighting More of the mental disorders and illicit drug use disorders are included in the new GBD estimates, which we will take a closer look at next. There is also a greater emphasis on empirical evidence, that is, the epidemiological data. Disability weights A new project is currently underway to derive a new set of disability weights. Age weighting – used in original but not in current GBD Discounting – used in original but not in current GBD consequence=greater prominence given to childhood disorders and for adults, greater mortality relative to non-fatal disorders

Mental disorders – GBD1990 and 2010 Current GBD Schizophrenia Yes Depressive disorders Unipolar depression Major depression, Dysthymia Bipolar disorders Bipolar disorder Anxiety disorders OCD, PTSD, panic disorder Any anxiety disorder Eating disorders - Anorexia nervosa, Bulimia Autistic Spectrum disorders Autism, Asperger’s disorder Childhood behavioural disorders ADHD, Conduct disorder & ODD So the main differences are: broader coverage of specific disorders within mood and anxiety disorders; Addition of childhood-onset disorders and the eating disorders. We also did do a review of data available for personality disorders, but found there was insufficient data available to derive global estimates.

Illicit drug use disorders – GBD1990 and 2010 Drug dependence 1990 Current GBD Heroin and other opioids combined Yes Cocaine Amphetamines Benzodiazepines -- NO Cannabis

Final number of data sources Results of Systematic review   Data sources Electronic databases Grey lit, ref lists, experts Final number of data sources Prev. Incid. Remiss / duration Mort Depressive disorders 35,579 36 188 7 12 Bipolar disorder 2,442 44 32 2 Schizophrenia 3,673 14 53 34 11 30 Anxiety disorders 22,423 96 3 5 Eating disorders 12,777 4 33 21 Autism & Asperger’s 5,532 41 8 ADHD & Conduct 13,923 129 119 1 13 Total 96,349 264 562 62 67 Our team has conducted a series of systematic reviews where we searched for data through electronic databases, grey literature, reference lists from articles and texts, and through canvassing experts. We were very fortunate in that some good quality reviews had recently been published for schizophrenia (by Sukanta Saha and John McGrath) and for ADHD (by Guilherme Polanski) so data for these just required updating. Our searches focussed on studies reporting community-representative estimates. As you can see a huge number of data sources did not meet our criteria as the sample was not community-representative or the case finding instrument did not map to DSM or ICD diagnostic criteria .There were a lot of gaps in the data particularly for developing income countries. We were fortunate to obtain data from the WMHS which helped fill in some of those gaps.

Data issues Lack of data Non-representative samples Inconsistencies in the data Different diagnostic criteria, definitions for remission Variability in reported estimates Real differences vs issues with case identification/ study quality The major issues we came across were of course lack of data Another big issue was lack of community-representativeness of samples eg incidence based on treatment seeking samples, excess mortality derived from inpatient samples. Inconsistencies in the data, including Definition of remission : reduced impairment Vs no longer meeting diagnostic criteria Different diagnostic criteria : not only are there differences between DSM/ICD diagnostic systems but also changes to those systems over time We found enormous variability in reported estimates: Estimates were found to range widely between populations, particularly for anxiety and depression. The issue this raises is are : to what degree are these Real differences in disease occurrence Vs issues with case identification. There is some evidence that sensitivity of diagnostic instruments varies particularly between western and non-western cultures. The goal of the new modeling software IHME is developing is to derive a consistent model that is able to control for these issues.

what is being done differently in GBD2005 Changes what is being done differently in GBD2005 More disorders Emphasis on empirical evidence New disease modeling tool (Dismod3) - derive missing data, use of co-variates 4. Disability weights 5. Discounting 6. Age weighting SO this brings us to the next major change in the GBD which is the use of new disease modelling software (Dismod3) is being developed at the IHME in parallel to our own efforts in collating the epidemiological parameters.

3. Disease modeling Disease models derived using a new software application Dismod3 developed at the IHME, University of Washington. Will derive estimates for countries where no/little data available Can apply an adjustment factor to estimates based study characteristics eg. Autism - Adjust estimates from studies where case finding is passive (Case Registries) to approximate estimates from studies where case finding is active (Birth cohorts) Derive missing data taking into account country/population characteristics eg. Anxiety disorders and major depression in conflict and post- conflict countries.

what is being done differently in GBD2005 Changes what is being done differently in GBD2005 More disorders Emphasis on empirical evidence New disease modeling tool (Dismod3) - Derive missing data, use of co-variates Disability weights Discounting Age weighting Changes to the social values used in the original GBD project will potentially have the greatest effect on new burden estimates for the mental disorders.

DALYs: Social values essential optional 1. How to compare years lost due to death with years lived in poor health?  DW values between 0 and 1 2. Value of health year of life equal at all ages?  age weights 3. Value of future years of life?  discounting optional essential Summary measures of health do reflect some degree of social value. The measure used in the GBD study is the DALY, which includes a disabilty weight, or utility weight, for each disease and injury, that aims to reflect the loss of health for an individual. In the original GBD there are two other optional weightings based on social values that were applied to the DALYs : age weighting and discounting. These invited quite a lot of debate. http://www.who.int/healthinfo/global_burden_disease/daly_disability_weight/en/index.html

4. Disability Weights GBD1990 : In GBD, non-fatal consequences of diseases and injuries understood as transitions through different ‘health states’ YLD calculation requires aggregate assessments of the overall decrements in health associated with particular health states  disability weights DWs are measures of overall levels of health rather than contribution of health to overall welfare GBD1990 : DW elicited from panel of health professionals following explicit protocol evaluating 22 indicator conditions in an intensive group exercise with ‘deliberative phase’ using person trade-off (PTO) method. Responses averaged across participants In GBD, non-fatal consequences of diseases and injuries understood as transitions through different ‘health states’ Years of life lost (YLDs) are based on relative decrements in health which are quantified using disability weights. So the important point here is that ‘disability’ in the GBD is defined as ‘within the skin’ or purely in terms of health of the individual.

New Disability Weight Project The new DW will have a greater emphasis on paired comparisons, anchored by time trade-off methods. It also aims to engage members of the general community (including those in developing countries) to a greater degree. The DW project is being carried out in two stages: a community household survey in selected regions, and an online open-access survey. Summary The new DW will have a greater emphasis on paired comparisons, anchored by time trade-off methods. It also aims to engage members of the general community (including those in developing countries) to a greater degree compared to the 1996 iteration. The DW project is being carried out in two stages: a community household survey carried out in a limited number of sites, and an online open-access survey.  

New Disability Weight Project Community surveys (Pemba, Banglasdesh, Indonesia, Peru, USA) Cultural/SES diversity >> representativeness Paired comparisons Internet survey the primary source of data for the final DW will include random(?) selections from all ~230 sequelae open to all interested in participating (open-access includes a variety of measurements paired comparisons, ranking, visual analogue scale, time trade-off, population equivalence) to anchor the scale (paired comparisons, ranking, visual analogue scale, time trade-off, population equivalence) Stage 1. Household Surveys Household surveys have already been carried out in Pemba, Banglasdesh, Indonesia and Peru. They are also currently being carried out in the USA via telephone. These populations were chosen for cultural diversity (also we suspect for convenience). Approx 2,500 people were interviewed at each site with 108 of the ~230 sequelae covered. The group report that preliminary data at individual level is very noisy, however they feel it is relatively consistent at population level. A good degree of consistency was found across the first four sites. Preliminary data from the US (~700 completed so far) is also quite consistent with other sites. A few implausible results were identified (for example paraplegia was given a higher ranking than quadriplegia). Preliminary findings from the pilot household survey suggest that participants had difficulty with long lay descriptions. Josh suggests that too much info in the lay description distract from the most salient points. Also salutary qualifications (for example quadriplegia described ‘… but has no difficulty thinking or learning’) distracts from severity. Another issue identified was that disorders with a high level of stigma or cultural disapproval attached (for example substance-use disorders gained a higher rating. The example given was illicit drug use disorders and alcohol use disorders – no word on how other mental disorders rated. The DW group intend to use these findings to inform the development of internet surveys. Hence descriptions for the internet survey will be restricted to <35 words. They aim to use vocabulary that is simple and non-clinical. Also a range of descriptions will be included for substance-use disorders so a sensitivity analysis can be carried out to determine what difference certain words make to the ranking (for example substance / cannabis / medication). Stage 2. Online surveys The next stage of surveys will be online and this will be considered the primary source of data for the final DW. The Internet survey will include all ~230 sequelae, will be open to all interested in participating (open-access), and will include a variety of methods of measurement. Three versions will be available, with three different goals: The first will replicate the household survey with the goal of validating findings across diverse cultures, levels of education and language - the internet survey is expected to capture samples with higher education and a greater proportion of English-speaking people. Version 2 will fill out responses for the remaining sequelae not covered in the household survey. Version 3 will include all ~230 sequelae and multiple methods of comparison (including paired comparisons, ranking, visual analogue scale, time trade-off, population equivalence) to anchor the scale. http://gbdsurvey.org/

5. Discounting Discounting common practice in economic analyses. Assumes that individuals value their health more now than at some point in the future. So the further in the future health loss occurs the more they are discounted. GBD1990 used 3% discounting

Consistency with cost-effectiveness analyses Why discount? Consistency with cost-effectiveness analyses Prevent giving ‘excessive’ weight to deaths at younger ages   Discounted YLL Undiscounted YLL 30.3 80 25 27 55.5 40 23.5 40.6 Changes in the discount rate do have an effect on the proportion of burden due to disability, on the age distribution of burden and on the distribution of burden by broad disorder group. Basically the higher the discounting rate, the less contribution disability makes to the overall burden, and the greater contribution of mortality. EG When discounting is set to 10%, YLDs account for more than 40% of burden. When zero discounting is used, YLDs account for less than 25% of burden. A low discount rate enhances the importance of burden from disease in children 0-4 years. (All from Murray and Lopez, 2006 p279) The consequence of not including discounting in new estimates will be to give greater prominence given to childhood disorders and for adults, greater emphasis on mortality relative to disability

6. Age weighting Used to reflect a social preference that values a year lived by young adult more highly than that of young children or the elderly. Eg. An Australian survey found that respondents considered saving four 20-year olds as important as saving ten 60-year olds (Nord et al, 1996 and 1998) Not related to productivity but ‘social’ role in caring for the young and old Used in GBD to reflect social preference to value year lived by young adult more highly than that of young children or the elderly Not related to productivity but ‘social’ role in caring for the young and old The effects of using age weighting are SMALLER in magnitude than the effects of using a discount rate (Murray and Lopez, 2006 p279), but still have a not insignificant effect on burden of Mental disorders and illicit drug use disorders.

Age weighting relative value age Arguments against: Unacceptable on equity grounds Does not reflect actual social values But: everyone potentially lives through every age  not inequitable 1.6 1.2 relative value 0.8 0.4 Use of age weighting enhances the importance of disability , because much of the disability occurs in adulthood, for which age-weights are greatest (Murray and Lopez, GBD1990 report). The use of age weights raises the proportion of burden due to YLDs. Therefore the effect of NOT including age-weighting will have important implications for mental disorders and illicit drug use disorders. 0.0 20 40 60 80 100 age

Source: Murray and Lopez, 2006. Chapter 5 This graph shows results of a sensitivity analyses around the impact of NOT using age-weighting and discounting GBD1990 DALY calculations. Sensitivity analysis found that the most important effect of using zero discount rate and uniform age-weights is the substantial reduction in the proportion of burden attributable to neuro-psychiatric disorders (Murray and Lopez, 2006 Chapter 5 p280). The RANK ORDER for mental disorders and substance use DROP with the exclusion of both adjustments. Source: Murray and Lopez, 2006. Chapter 5

what is being done differently in GBD2005 Changes what is being done differently in GBD2005 More disorders Emphasis on empirical evidence New disease modeling tool (Dismod3) - Derive missing data, use of co-variates Disability weights Discounting Age weighting Mental disorders and illicit drug use disorders as risk factors And finally, the new burden od disease estimates will include not only the morbidity and mortlaity associated directly with mental disorders, but also the attributable burden due to subsequent health outcomes where mental disorders are recognised as contributing factors.

7. Comparative Risk Assessment Mental disorders as risk factors 1. Mental and substance use disorders  suicide 2. Other health outcomes The strongest evidence available is for major depression  ischaemic heart disease Other Health Outcomes The starting point for considering other health outcomes was the 2007 Lancet paper by Prince et al. A review of the data showed that : The strongest evidence available was for major depression as a risk factor for incident cases of ischaemic heart disease. References: Charlson F, Stapelberg N, Baxter A, Whiteford H. Should global burden of disease estimates include depression as a risk factor for coronary heart disease? BMC Medicine. 2011;9(1):47. Baxter A, Charlson F, Somerville A, Whiteford H. Mental disorders as risk factors: assessing the evidence for the Global Burden of Disease Study. BMC Medicine – in press.

Drug use disorders Cannabis – schizophrenia Opioids/cocaine/amphetamines Suicide Trauma Overdose Injecting drug use HIV HCV HBV

Conclusions and consequences Ranking of mental disorders and illicit drug use disorders? More disorders MD considered risk for other health outcomes ...but if no discounting & no age weighting .... Vastly expanded evidence base Disability weights ? So, what do we know of the final estimates at this stage? We know that the ranking of mental disorders will have changed. While the range of disorders included is much more comprehensive, and we are capturing attributable risk for somatic health outcomes, the effect of not including discounting and age weighting might have a substantial impact on where mental disorders fall in relation to other disease and injury. We know the estimates are based on a vastly expanded evidence base, therefore the epi underpinning these estimates are hopefully more robust. However we have not yet seen what the new disability weights are, and this may have quite an impact on final DALYs. So

GBD Technical Assistance Acknowledgements Co-Chairs - Mental Disorders and Illicit Drug Use Disorders Expert Group Prof Harvey Whiteford Prof Louisa Degenhardt GBD Technical Assistance Prof Theo Vos Rosana Norman Research Team Alize Ferrari Fiona Charlson Adele Somerville Roman Schuerer Holly Erskine