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
1
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
Changes
what is being done differently in GBD2005
1. More disorders
2. Emphasis on empirical evidence
3. New disease modeling tool (Dismod3)
- Derive missing data, use of co-variates
4. Disability weights
5. Discounting
6. Age weighting
Mental disorders – GBD1990 and 2010
Mental disorder
Schizophrenia
1990
Yes
Current GBD
Yes
Depressive disorders
Unipolar
depression
Major depression, Dysthymia
Bipolar disorders
Bipolar disorder
Bipolar disorder
Anxiety disorders
OCD, PTSD,
panic disorder
Any anxiety disorder
Eating disorders
Autistic Spectrum
disorders
Childhood behavioural
disorders
-
Anorexia nervosa, Bulimia
-
Autism, Asperger’s disorder
-
ADHD, Conduct disorder &
ODD
Illicit drug use disorders – GBD1990 and 2010
Drug dependence
1990
Current GBD
Heroin and other opioids
combined
Yes
Cocaine
combined
Yes
Amphetamines
combined
Yes
Benzodiazepines
--
NO
Cannabis
--
Yes
Results of Systematic review
Depressive disorders
Data
sources
Data
sources
Final number of data sources
Electronic
databases
Grey lit, ref
lists, experts
Prev.
Incid.
Remiss /
duration
Mort
35,579
36
188
7
7
12
Bipolar disorder
2,442
44
32
2
0
7
Schizophrenia
3,673
14
53
34
11
30
Anxiety disorders
22,423
34
96
3
5
2
Eating disorders
12,777
4
33
7
21
11
5,532
3
41
8
5
5
13,923
129
119
1
13
0
96,349
264
562
62
62
67
Autism & Asperger’s
ADHD & Conduct
Total
Changes
what is being done differently in GBD2005
1. More disorders
2. Emphasis on empirical evidence
3. New disease modeling tool (Dismod3)
- derive missing data, use of co-variates
4. Disability weights
5. Discounting
6. Age weighting
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 postconflict countries.
Changes
what is being done differently in GBD2005
1. More disorders
2. Emphasis on empirical evidence
3. New disease modeling tool (Dismod3)
- Derive missing data, use of co-variates
4. Disability weights
5. Discounting
6. Age weighting
DALYs: Social values
1. How to compare years lost due to death with
years lived in poor health?
essential
 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
http://www.who.int/healthinfo/global_burden_disease/daly_disability_weight/en/index.html
optional
4. Disability Weights
 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
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.
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
Why discount?
1. Consistency with cost-effectiveness analyses
2. Prevent giving ‘excessive’ weight to deaths at
younger ages
0
25
40
Discounted
YLL
30.3
27
23.5
Undiscounted
YLL
80
55.5
40.6
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
Age weighting
Arguments against:
relative value
1.6
1.2

Unacceptable on
equity grounds

Does not reflect
actual social values
0.8
But: everyone
potentially lives
through every age
 not inequitable
0.4
0.0
0
20
40
60
age
80
100
Source: Murray and Lopez, 2006.
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 ?
Acknowledgements
Co-Chairs - Mental Disorders
and Illicit Drug Use Disorders
Expert Group
Prof Harvey Whiteford
Prof Louisa Degenhardt
Research Team
Alize Ferrari
Fiona Charlson
Adele Somerville
Roman Schuerer
Holly Erskine
GBD Technical Assistance
Prof Theo Vos
Rosana Norman