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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
â Summary measures of health
â Disability Adjusted Life Years (DALYs)
â DALYs & the Global Burden of Disease study
â 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 â 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
â 10 year old girl â 45 y/o woman â SCI
â 8 year old boy
â 55 y/o man â fractured rib
â 38 year old mother
â 42 year old father
YLLs from deaths YLDs from injuries
â 70 year life expectancy - Duration (36 year LE) *
â 73 year life expectancy Disability Wt (.725) = 26 YLDs
â 46 year life expectancy - Duration (.115 years) * Disability
â 33 year life expectancy Wt (.199) = 0.02 YLDs
222 YLLs +
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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 â weights the life of a 21 year-old
(for instance) more heavily than other ages
according to societal preferences.
⢠Discounting â 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 â Ranked 9th in cause of
outlined methodology for total DALYs in the
DALYs world in 1990
⢠First attempt at a â Still ranked 9th in 2000
comprehensive picture of estimates
global health
â 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
â Different than that captured by mortality or injury
alone?
⢠Characterize the traffic-related burden of disease
in more detail for age, gender, and ethnicity
â 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:
âOne that leads immediately to death or that is non-fatal
but severe enough to warrant hospital treatment.â
⢠âRoad Traffic Accidentsâ category based on the
E-codes on hospital discharge
â 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 â 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 â 71% male
Regional DALYs â 70% male
World DALYs â 70% male
California deaths â 69% male
California injuries â 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 farâŚ
⢠The epi data necessary for YLD calculation
is limited.
â Primary diagnosis may not be the most severe
injury ď 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 directionsâŚ
⢠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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