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Dalys
1. Disability Adjusted Life Years
(DALYs) and the Traffic-Related
Burden of Disease in California
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2. Quick Outline
• Background
– Summary measures of health
– Disability Adjusted Life Years (DALYs)
– DALYs & the Global Burden of Disease study
– Relevance for the Traffic Safety Center
• Methodology
• Results
• Conclusions
• Future Directions
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3. Measures of Population Health:
Mortality and Morbidity Measures
# deaths, death rate, # injured, # head injuries,
# severe injuries, rate of injuries, # hospitalizations
Summary Measures
Aggregate mortality and morbidity into a
single measure
# years healthy life lost (DALYs, QALYs)
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4. Summary Measures of Population
Health: Why use them?
• Compare the health of one population with another
• Analyze the benefits of health interventions for use
in cost-effectiveness analysis
• Identify and quantify overall health inequalities
within populations
• Informing debates on health policy
• Monitor changes in the health of a given population
• Attribute burden from risk factors
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[WHO – Summary Measures of
JAVED Population Health, 2002]
5. Disability Adjusted Life Years
(DALYs)
• Measures healthy time lost from specific
diseases and injuries in a population
• Comparable and additive across diseases
Ex: Broken scapula = .5 DALYs lost
Protein deficiency = 2 DALYs lost
• Based on relatively accessible incidence
data (ICD codes)
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6. DALY Calculation
(the easiest way)
Years lost to
Years of lost life disability
+
(YLLs) (YLDs)
Inputs
Inputs
• Duration of disease/injury
• Life expectancy at age of
death • Disability weight of
disease/injury
• Age at death
• % long-term cases
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7. DALY Calculation: an example
A Two-Car Collision
1 family dies 2 people injured
– 10 year old girl – 45 y/o woman – SCI
– 8 year old boy
– 55 y/o man – fractured rib
– 38 year old mother
– 42 year old father
YLLs from deaths YLDs from injuries
– 70 year life expectancy - Duration (36 year LE) *
– 73 year life expectancy Disability Wt (.725) = 26 YLDs
– 46 year life expectancy - Duration (.115 years) * Disability
– 33 year life expectancy Wt (.199) = 0.02 YLDs
222 YLLs +
JAVED
26.02 YLDs
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= 248.02 YLDs
8. DALY Calculations: Adjustments
• Designed to allow tailoring to local social values
and specific applications for the DALYs
• Age-weighting – weights the life of a 21 year-old
(for instance) more heavily than other ages
according to societal preferences.
• Discounting – commonly used in economic
analyses, recommended for DALYs if using the
outcome measure in such analyses
• Caused much contention
• DALYs can be calculated without such
adjustments
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9. DALYs and the Global Burden of
Disease
• WHO/World Bank Global • Quick results
Burden of Disease study – Ranked 9th in cause of
outlined methodology for total DALYs in the
DALYs world in 1990
• First attempt at a – Still ranked 9th in 2000
comprehensive picture of estimates
global health
– Predicted to be ranked
• Ranked diseases according 3rd in 2020
to the number of DALYs
• Projected rankings to 2020
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10. DALYs and the Traffic-Related
Burden of Disease in California
• DALYs as a measure of traffic-related outcomes
in California
– Different than that captured by mortality or injury
alone?
• Characterize the traffic-related burden of disease
in more detail for age, gender, and ethnicity
– By occupant, pedestrian, bicyclist, etc.
• Construct a database of traffic-related DALYs for
California for use in comparisons to global,
regional, state, and city trends.
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11. Methods: Case Definitions
• GBD case definition for injury:
“One that leads immediately to death or that is non-fatal
but severe enough to warrant hospital treatment.”
• “Road Traffic Accidents” category based on the
E-codes on hospital discharge
– CDC and the GBD recommendations do not entirely
coincide
• Each injury type has a specified disability weight,
duration, % long-term cases in the GBD
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12. Methods: DALY Calculation
Data Sources
Mortality Morbidity
CA Vital Statistics OSHPD hospital
discharge data
EPIC database
EPIC database
+ Age- and sex- specific + Age- & sex-specific
deaths listed by injuries by ethnicity and
ethnicity and county county
+ Injury by E-code and
+/- ICD-10 coding for nature of injury codes
1999 and later +/- ICD-9 coding
-- Need individual level data
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--
13. Methods: DALY calculations
YLLs and YLDs
• Ethnicity, gender, age by External injury category
(Motor vehicle Occupant, Pedestrian,
Motorcyclist, or Bicyclist)
• Using highest world life expectancy and 3%
discount rate
• YLL calculation
• YLDs – calculated for each type of injury and
body part injured by age, gender, and ethnicity
Ex: Amputation of upper limb for 50-55 y/o Asian
males = x YLDs
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14. Methods: DALY calculations
Comparison Measures
• Sum YLLs and YLDs for population = DALYs
• Calculate the # of deaths and the # of injuries for
same categories from same data
• Test rank-order for DALYs, deaths, injuries,
others?
• Compare rates to global, regional, national, city
(San Francisco, Los Angeles) DALY rates.
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15. Results?
• Not much yet.
• Gender and age DALY calculations by
injury category is complete (as of yesterday)
• YLLs by ethnicity are complete while YLDs
are still being calculated
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16. Preliminary Results: Gender
• Consistency of the distribution of total traffic-
related burden between genders ~70%
California DALYs – 71% male
Regional DALYs – 70% male
World DALYs – 70% male
California deaths – 69% male
California injuries – 62% male
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17. Preliminary Results: Ethnicity
YLLs
Death Death
GBD YLL CDC YLL Rate per GBD CDC YLL Rate per
Females rates rates 100,000 Males YLL rates rates 100,000
White 144 119 6 White 328 274 15
Native American81
2 182 6 Native American
302 201 13
Hispanic 168 146 5 Hispanic 482 392 14
Black 143 123 8 Black 387 349 8
Asian 117 95 5 Asian 231 212 9
Death
GBD CDC YLL Rate per
Totals YLL rates rates 100,000
White 472 393 10
Native American 583 383 10
Hispanic 650 537 10
Black 531 473 8
Asian 348 307 7
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18. Conclusions thus far…
• The epi data necessary for YLD calculation
is limited.
– Primary diagnosis may not be the most severe
injury underestimation
• Traffic-related DALYs are largely
composed of the YLL (deaths)
• Future analyses will be more challenging
with HIPPA system in place
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19. Future directions…
• By how much can the burden be reduced?
How low can we feasibly get it?
• How much of the burden is attributable to
lack of restraint-use? How much could we
reduce the burden if we increase seatbelt
use by 5%? Would we get more DALYs if
we decrease alcohol-related burden by 5%?
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