Transcript Slide 1

Global Burden of Diseases, Injuries
and Risk Factors: methodological
aspects and trends
1st International Conference on the Burden of Diseases
Studies in Brazil
November 18th, 2009
Rafael Lozano, MD. MSc.
UNIVERSITY OF WASHINGTON
Outline
• What is “GBD”
• GBD in the last 20 years
• GBD 2005 is not only an update of the reference year
• Where is GBD making contributions to global health
2
Burden of Disease
“…the gap between a population’s
health status and some reference
standard…”
Murray 1996
7
Outline
• What is “GBD”
• GBD in the last 20 years
• GBD 2005 is not only an update
• Where is GBD making contributions to global
health
8
Brief History
In May of 1993, a group of
Mexicans went to Boston to
learn the methods of the BOD
Dr Chris Murray was
contracted as advisor of the
study “The Health and the
Economy” conducted by Dr
Julio Frenk
• Tension into UN agencies:
lack of leadership from WHO
• WHO “Health for all” 1987
• WB “Investing in health,
1993”
• Easy Questions, hard to
answer: If HIV/AIDS is the first
cause of death, what is the
next ?
From Economist to Public Health
practitioners
• What are the leading causes of
death worldwide?
• Women, men, children, adults,
regions
• Which are the health priorities?
• Due to the magnitude of the
problem, Is it enough to use
mortality as measurement?
• How can we select the best
health interventions?
• How we can know if our
investments on health system are
producing positive effects on the
population health?
• How can we improve the
allocation of health resources
(financial)?
9
Global Context before GBD
1. Public health statistics, which were partial and
fragmented
2. Estimates for numbers of people that die or impacted by
disease, which were in some cases exaggerated
beyond plausible limits or missing estimates entirely
3. Traditional health statistics did not allow policy-makers
to compare relative cost-effectiveness of different
interventions across diseases
4. Many reports were influenced by politics which diluted
truth and prevented effective intervention
10
GBD 1990
- First GBD commissioned by World
Bank, published :
- 1993 WDR (WB) Investing in Health
- 1994 WHO, Setting Health Priorities
- 1996: GBD and GHS
- Produced estimates for 1990 and
projections to 2020
- Led by Christopher Murray and Alan
Lopez
- Disentangled epidemiology from
advocacy in order to produce
objective, plausible estimates
- Measured burden of mortality and
non-fatal conditions in a metric that
could be compared across diseases
(DALY), ages, and regions
11
Leading Causes of Death and DALYs 1990
DALYs
Deaths
%
Ischemic heart disease
%
12.4
Lower Resp infec.
Cerebrovascular disease
8.7
Diarrhoeal diseases
7.2
Lower respiratory infec
8.5
Perinatal conditions
6.7
Diarrhoeal diseases
5.8
Perinatal conditions
4.8
Ischemic Heart Dis
3.4
C.O.P.D.
4.4
Cerebrovascular Dis
2.8
Tuberculosis
3.9
Tuberculosis
2.8
Measles
2.1
Measles
2.6
Road traffic accidents
2.0
Road traffic accidents
2.5
Lung Cancer
Source: Murray and Lopez, 1996
1.9
Depression
8.2
3.7
Congenital anomalies 2.4
UPDATES of BOD 1990
• Since 1998, WHO has produced annually
up to dates of the GBD, publishing them in
the Statistical Annexes of the WHR, as well
in the web site www.who.int
• From the 8 original regions WHO increased
them to 14
• Updates of epidemiological estimates of
TB, Malaria, HIV/AIDS, Neuropsychiatric
diseases, were produced for the GBD 2000
• In order to increase the theory and
methods of summary measures, WHO
published a book in 2002
Comparative Risk Assessment
The second round of estimates of the Attributable Burden due
to some risk factors was initiated in 2001. That study expanded
the number of risk factors from 10 to 29.
The results were published in WHR 2002, and the detail
literature review and methods in 2004
Underweight
Unsafe sex
High blood pressure
Tobacco
Alcohol
Unsafe water, sanitation, and hygiene
High cholesterol
Indoor smoke from solid fuels
Iron deficiency
High BMI
High-mortality developing
Lower-mortality developing
Developed
Zinc deficiency
Low fruit and vegetable intake
Vitamin A deficiency
Physical inactivity
Occupational risk factors for injury
Lead exposure
Illicit drugs
Unsafe health care injections
Lack of contraception
Childhood sexual abuse
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
Attributable DALY (% of global DALY - Total 1.46 billion)
10.0%
Disease Control Priorities II (2006)
New estimates of GBD for
2001, based on the WHO
revisions and more deatil
sensitivity analysis
Includes more
documentation of diseases
and risk factor estimates
Chile, Costa Rica,
Peru, Ecuador
Turkey
Iran
Tanzania,
Mozambique
Morocco, Tunisia,
etc., etc.
17
Outline
• What is “GBD”
• GBD in the last 20 years
• GBD 2005 is not only an update of the year of
reference
• Where is GBD making contributions to global health
18
Why a new GBD study
Reasons for executing a new round
 Demand for burden data
from governments, funders,
policy makers
 Only piecemeal revisions of
epidemiology for conditions
since 1996
 Methods advances for
mortality measurement,
cause of death attribution,
modelling missing data,
DW estimation and data
collection techniques
 No comprehensive revision
of disability weights since 1996
(most criticized part of study)
Need for new tools,
approaches to share
results of GBD study with
diverse audiences
 No consistent time trend
available (methods for ‘00, ‘01,
‘02 not comparable to ‘90)
Involve collaboration of
many more people
19
GBD 2005
New Round
- Funded by the Bill and Melinda Gates Foundation
- Started September 2007, Ending November 2010
Objectives
- Produce specific DALY, YLL, and YLD estimates for over
220+ diseases/injuries and 40+ risk factors by age range,
sex, and for 21 regions for the years 1990 and 2005.
- Create simplified analytical tools to facilitate national
burden estimates and policy use
20
Who are the key participants
Johns Hopkins
University
44 expert
groups, with
over 800
members
worldwide
Harvard
University
World Health
Organization
University of
Queensland
University of
Washington
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Who are the key participants
Organization
Core Team
External
Advisory Board
Tools and Curricula
Development Sub-Team
Mortality Sub-Team
Alan Lopez and
Chris Murray
Cluster A
CVD, COPD, Cancer
Majid Ezzati
Harvard University
Cluster B
Child/Maternal
Bob Black
Johns Hopkins
University
DW Sub-Team
Josh Salomon and
Colin Mathers
COD Sub-Team
R Lozano, M
Naghavi
Cluster C
Injuries and Mental
Health
Theo Vos
University of Queensland
CRA Sub-Team
Majid Ezzati
Cluster D
Communicable
Diseases
Neff Walker
Johns Hopkins University
YLD Sub-Team
Rafael Lozano
and Colin Mathers
Cluster E
Noncommunicable
Diseases
Catherine Michaud
Harvard University
22
How is the work done at IHME contributing to the study
Mortality
COD
Epidemiological
Estimates
DISMOD
Disability
Weights
YLL
YLD
DALY
23
Mortality Envelopes
• Deaths by age, sex and GBD region
• Contains the number of deaths for all causes
• Death is attributed to one cause
• Estimated using all-cause mortality data
• Child mortality (0-4) estimated separately
Vital
Registers*
Assessing and
adjusting for
incompleteness
Surveys
Adjusting for biases
Synthesis
Estimation Process:
Envelopes
Models
24
Synthesis of Child Mortality: Examples
Estimation Process: Adults
Adjusting for Incompleteness in VR
• Death Distribution Methods (DDM)
• Demographers long-used tools for assessing level of completeness in death
registration
– 3 families
– Many variants
Adjusting For Biases
• Survey Data: Sibling Survival Model
Models: Predicting adult mortality
• Leverage relationship between adult and child mortality
• Build model, predict logit (45q15) for Males and Females separately (HIV
prevalence, TFR, Country or Regional FE, Adjustment for post-Soviet
collapse
26
Synthesis of Adult Mortality: Examples
Russian Federation RUS
male
0
.2
45q15
.4
.6
female
1950
1960
1970
1980
1990
2000
20101950
1960
1970
1980
1990
2000
2010
Year
Complete VR
Prediction model country FE
DDM-adjusted VR
Prediction model region FE
extrapolated completeness
outlier
sib histories
xxxx = DSS site
Graphs by sex
27
Objectives
• To produce estimates of
selected causes of death by
country, age and sex.
• To produce estimates of
causes of death, based in GBD
cause list for 21 GBD regions
by age and sex, 1990 and
2005.
24 to 36 causes for
200 countries and
territories (IHME)
268 causes for 21
GBD new regions
• To produce friendly tools to aid
cause of death estimates:
CODMOD
• Mapping ICD across time and
populations
• Redistribution of garbage
codes
• Modeling causes of death for
countries without VR
28
Mapping GBD Cause List with ICD Revisions and Other Tabulated List
GBD 2005 Cause List (268 )
GBD 1990 Cause List (100)
CODMOD level B (36)
1
2
3
CODMOD level 2 (24)
4
5
Tab B
6,7
Tab A
8
BTL
9 tab
9
VA
10
Tab
10
ICD and other formats
29
Availability of COD data
More than 4550
country-years
ICD 07A
815
-
100%
ICD 07B
110
-
100%
ICD 08 detail/ICD 08A
70
-
100%
ICD 08A
776
-
100%
ICD 08B
35
-
100%
ICD 09 detail/BTL
664
-
100%
ICD 09 detail (9M)
13
-
100%
ICD 09 BTL
ICD 10
ICD 10 Tabulated
1082
702
70
09A
47%
09B
28%
09N
23%
09C (China tabulation)
1%
09I (India tabulation)
1%
103 (3-digit)
14%
104 (4-digit)
80%
10M (mixed)
6%
101 (WHO tabulation)
73%
10I (India tabulation)
4%
10Ir (Iran tabulation)
10%
10S (Syria tabulation)
4%
10C (China tabulation)
9%
ICD 10
%
R00-R99
26.0
Heart Failure
I50
18.0
Renal Failure
N18
6.4
Atherosclerosis
Malignant neoplasm without
specification of site
I70
6.0
C80
4.8
Septicaemia
A41
4.2
Essential (primary) hypertension
I10
3.0
Exposure to Unspecified factor
X59
2.7
Pulmonary embolism
I26
2.2
Respiratory Failure
J96
2.0
Ill-defined
Distribution of Garbage Codes
by Type and Region
• ~20% total deaths from VR are
GCs
•10 causes accumulate 75%
• Intermediate causes
are the most important Garbage
Codes
35.0
30.0
Specials
Immediate
Sequelae
Intermediate
I&D UNS
Cancer
Ill Def
25.0
% of GC
Causes
20.0
15.0
10.0
5.0
0.0
SSA
Asia
LA
Europe C&E
ALL
Europe W
Caribbean
N.America
Australasia
Percent of deaths with garbage codes
Select Countries of the Americas, circa 2005
Mortalidad por códigos basura en países
de la región, 1979-2007
Guatemala
Grenada
El Salvador Barbados
Argentina
Surinam
T&T
Belice
The Problem is how to predict CoD for 100 countries
without VR data
• Data quality
• Sparseness : Approximately 75% of total country-years missing
• Compositional bias
• Both sampling and non-sampling error
• Sometimes multiple (discrepant) observations per country-year
• Poor covariates
• No global time-series available for many important covariates
• The covariates we do have fail to explain much of the variation in the data
• Need predictions
• Not only do we need to fit the data we have, but we need to forecast
forward (and backwards in many cases)
How to maximize our use of all the data available?
11
Estimating Cause of Death Strategy
METHOD APPLIED
TYPE OF
COUNTRY’S DATA
A. Complete VR
VR
CODMOD
CODMOD
DATABASE
Country Fixed Effect
Region Fixed Effect
When we have
countries with
data in 2005
When we have countries with data
before 2005, we project for 2005
For adults use VR
for 2005
Estimates for 0-4 assuming
Completeness=1.0, GC = 0.0
B. Adults Complete
Children
Incomplete (43)
C. Adults/Children
Estimates for all ages, assuming
Incomplete
C=1.0, GC = 0.0
D. VA
Estimates assuming
Estimates assuming
C=1.0, GC = 0.0
C=1.0, GC = 0.0
Estimates assuming
E. No Data Available
C=1.0, GC = 0.0
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Some results
1000
500
Death Rate (per 100,000)
Mexico
Communicable Diseases, Males 45-49
0
0
50
100
150
200
United States of America
Communicable Diseases, Males 45-49
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Year
Simple Mixed Effects Model
Observed Data
Weighted Regression Model
Russian Federation
Communicable Diseases, Males 45-49
Simple Mixed Effects Model
200
300
400
Paraguay
Communicable Diseases, Males 45-49
0
100
Death Rate (per 100,000)
50
100
150
200
250
Observed Data
Weighted Regression Model
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Year
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Year
Observed Data
Weighted Regression Model
Simple Mixed Effects Model
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Year
Observed Data
Weighted Regression Model
Simple Mixed Effects Model
26
How is the work done at IHME contributing to the study
Mortality
Epidemiological
Estimates
COD
DisMod
YLL
YLD
Disability
Weights
DALY
37
Expert Groups and Epidemiological Estimates
Fitting in to GBD
• Estimates are critical for determining YLD of disease
• Estimates get fed in to DisMod for internal consistency
checking
Who is involved
• 44 disease expert groups from all around the world; over
800 researchers
• Very well established and published experts
Deliverables
• Systematic review of journal articles for data
• Produce estimates, using review data, methods
38
GBD schematic for neonatal infections
2
1
Prenatal risk
factors
Intrapartum risk
factors
Dead
Neonatal
infections
2
2
Pneumonia Sepsis
2
4
Meningitis
Postnatal risk
factors
3
Exclude?
Sequalae*
Mild, moderate, severe
Single or multi-domain
Full recovery
Parameters for disease model
1 Incidence of the condition
2 Case-fatality rate
3 Case-complication rate (risk of sequelae) & distribution of severity of sequelae
4 Complication-fatality rate
Neonatal infections incidence – Searches and data selection
DATABASES
SEARCH TERMS
PubMed, Embase, Web of Science, Popline,
WHO regional databases + Reference lists and
Key Review articles
Infection OR Sepsis OR Pneumonia OR Meningitis +
Variables of Interest (eg. Incidence etc.)
Limits: Publication Date from 1990 to 2008
Total search results (6518)
Studies remaining after
screening title or
abstract (n=833)
Pending Translation (n= 23)
Did not meet criteria
(n= 532)
Unavailable {now coming from
Boston] (n= 64)
Studies with live
births (n=99)
Clinical sepsis
incidence
reported
(n=24)
Excluded studies
Culture proven
sepsis incidence
Reported (n=48)
Sepsis Case fatality
Rate Reported (n=23)
214
papers
entered
Studies without live
births (n=115)
Clinical sepsis
incidence
Reported
(n=1)
Culture proven
sepsis
incidence
Reported (n=8)
Sepsis Case fatality
Rate Reported (n=19)
40
Data availability for neonatal infections according to countries
grouped by level of NMR
Countries according to level of NMR
No of countries
Neonatal
sepsis data
Neonatal
sepsis
incidence (per
1000 births)
and outcomes
NMR<5
Level 1
NMR 5 - 14.99
Level 2
NMR > 15
Levels 3 (15-29), 4
(30- 45) and 5>45)
49
50
93
68 studies with live
births
N = 9,726,840
5 studies with live
births
N = 310,082
24 studies with live births
N = 240,004
Clinical:
3.4 - 136/1000 live births
Clinical
8.4 – 24.4/1000 live births
Clinical:
21-170/1000 live births
Culture proven
0.6 - 18/1000
Culture proven
2.3 - 10/1000
Culture proven
5.5 - 24.8/1000
CFR (7.1 – 30.3%)
CFR (6.7 - 26.5%)
CFR (9.6 - 67%)
Higher NMR settings have higher incidence of sepsis and higher case fatality
Expert Groups and Epidemiological Estimates
Lots of work for these groups (systematic review example)
Citations identified
(Titles and/or abstracts)
64 586
Excluded
59 960
Maternal Conditions
Expert Group
Full-text evaluation
(Articles and reports)
Reasons for
exclusion
57% – no
relevant data
15% –
sample
size<200
11% – no
dates reported
17% – other
reasons
4626
Excluded
2046
Included
2580
Reasons for
exclusion
 92% – no
relevant data
 6% – sample
size<200
 2% – other
reasons
Morbidity
outcomes
3215 data sets
Mortality
outcome
1143 data sets
42
Alcohol-attributable disease and injury 2002 (green mainly
protective)
Chronic disease:
Cancer: Mouth & oropharyngeal cancer, esophageal cancer, liver
cancer, female breast cancer
Neuropsychiatric diseases: Alcohol use disorders, unipolar major
depression, primary epilepsy
Diabetes
Cardiovascular diseases: Hypertensive diseases, ischemic heart
disease, ischemic stroke, hemorrhagic stroke
Gastrointestinal diseases: Liver cirrhosis
Conditions arising during perinatal period: Low birth weight, FAS
Injury:
Unintentional injury: Motor vehicle accidents, drownings, falls,
poisonings, other unintentional injuries
Intentional injury: Self-inflicted injuries, homicide, other intentional
injuries
New developments with respect to causality:
inclusion of alcohol-attributable disease categories
• Colorectal cancer included (IARC monograph meeting; Baan et al.,
2007)
• Tuberculosis/pneumonia incidence and worsening the disease
course included (see next slides)
• HIV discussed but not included (not enough evidence for causality
for incidence); enough evidence for alcohol worsening the disease
cause, but not enough data to quantify
• Pancreatitis included (new disease category in GBD)
• Diverse new GBD injury categories (most injury categories have
been causally linked to alcohol consumption)
• Revision of determination of risk relationship between alcohol
consumption and primary epilepsy (excluding “alcoholic seizures” –
in collaboration with epilepsy experts in GBD)
How is the work done at IHME contributing to the study
Mortality
Epidemiological
Estimates
COD
DISMOD
YLL
YLD
Disability
Weights
DALY
45
Generic Model of Disease
States
S: healthy (susceptible)
C: diseased (condition of interest)
D: dead from the disease
M: dead from all other causes
Transition rates
i: incidence
r: remission
ƒ: case fatality
m: all other mortality.
Limitations of DisMod I and II
Laborious Preprocessing
No Confidence Intervals
Ad-hoc approach to
incorporating prior
beliefs
How is the work done at IHME contributing to the study
DisMod III
Fitting in to GBD
• Critical tool to perform consistency checking on epidemiological
data from expert groups
Who is involved
• Development: Abraham Flaxman and Steve Lim
• Will be running over expert group results at IHME
• Eventually will collect volunteers from expert groups to assist in
providing further feedback on the tool
Deliverables
• New version addresses criticisms of the past
• Will be web-based, with eventual training materials
47
DisMod III: A Bayesian Approach
• Easier Preprocessing
• Model-based confidence intervals
• Systematic incorporation of prior beliefs
48
Deliverables and connections between the pieces
Mortality
Epidemiological
Estimates
COD
DisMod
YLL
YLD
Disability
Weights
DALY
49
Disability weights
• Disability weights provide the bridge between mortality and
non-fatal outcomes
• Disability weights quantify overall health levels associated with
different states, on a continuum between perfect health (d.w.=0)
and death (d.w.=1)
• GBD 1990: Six disability classes defined in reference to:
• Four domains of disability (recreation, education, procreation,
occupation)
• Activities of daily living (e.g. eating, personal hygiene)
• Instrumental activities of daily living (e.g. meal preparation,
housework)
Criticisms of GBD 1990 approach
• Dimensions of
disability not
appropriate for
characterizing child
outcomes
• No formal protocol to
guide replication of
disability weights
measurement, e.g. for
national burden
studies
• Mildest disability class
valued at 0.096 which
results in insensitivity
to very mild
decrements
Some Changes…
• Ad hoc additions and modifications
and additions to 1996 disability
weights based on, e.g.
• Dutch disability weights exercise
• Australian National Burden of
Disease disability weights
• Further conceptual, methodological
and empirical work on health state
valuations
• Marrakech conference and volume
on summary measures of population
health
• Large-scale empirical measurement
at WHO including health state
valuations in community samples
Approach to revising disability weights
• Step 1: Finalize list of sequelae
• Step 2: Develop lay descriptions of health states with
reference to standardized set of domains and key
symptoms
• Step 3: New data collection
• Community surveys in five or six field sites (to be chosen from
provisional list including sites in India, Indonesia, Vietnam,
Tanzania, Mexico, Rwanda)
• Supplemental Internet survey
Who is involved ?
Mohsen Naghavi, R Lozano C. Mathers, T Vos, M Ezzati
Ali Mokdad, Kana Fuse, IHME; Joshua Salomon, Harvard
Collaborators internationally implementing survey
Outline
• What is “GBD”
• GBD in the last 20 years
• GBD 2005 is not only an update
• Where is GBD making contributions to global health
53
Where is GBD making contributions to global health
Foster Dialogue and Transparency with Experts
Example:
• Host four rounds of Expert Groups meetings: disease
representatives present data collected in systematic
reviews in Jan/Feb 09
• Opportunity for Expert Groups to present their status,
solicit feedback, and express cross-cutting issues
• IHME previews our work on methods development to
produce mortality envelopes, cause of death estimates,
and the new DISMOD III tool
54
Where is GBD making contributions to global health
─
Potential for significant influence on health policy debates. Much
already achieved (eg. tobacco control focus at WHO).
─
Potential to greatly increase reliability/scientific basis for estimates
through more and better linkages with scientific community.
─
Data/knowledge base needs to grow at same or faster pace than
methodological advances.
─
Four key specific scientific challenges:
i.
resolving legitimate VR/EE differences in causes of death;
ii. broaden the data/knowledge base about disease/injury
epidemiology;
iii. more rigorous, acceptable and transparent procedures for
ensuring epidemiological consistency; and
iv. better methods to quantify disability and population health.
55
When - Overall Timing
Aug 2009
- DISMOD III run
Jan/Feb 2009 Meetings
- Expert Group
presentations
- Mortality data
- COD data
Iterations…
- Track down additional data
- Run DISMOD III
- Produce updated COD and
Mortality Numbers
Nov 2009
- Peer review completed
- DW data collection completed
Nov 2010
- Estimates
Completed
56
Questions
Resources
• GBD Operations Manual
(http://www.globalburden.org/gbdops.html)
• GBD External Website (http://www.globalburden.org/)
• GBD Internal Website (http://globalburden.healthmetrics.org/)
58