Non-Fatal Health Outcomes: years lived with disability
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Findings and implications of the Global Burden of Disease Study 2010

Findings and implications of the Global Burden of Disease Study 2010

Royal Society, London, 14 December 2012

Professor Theo Vos
School of Population Health

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Non-Fatal Health Outcomes: years lived with disability Non-Fatal Health Outcomes: years lived with disability Presentation Transcript

  • Non-Fatal Health Outcomes:Years Lived with DisabilityFindings and implications of the Global Burden of Disease Study 2010Royal Society, London, 14 December 2012Professor Theo VosSchool of Population Health
  • Outline Summary of methods Results Reflections 2
  • New approach GBD 2010 PreviousmethodPrevalence * DW Incidence * duration * DW“True” systematic reviews and Choice of single data set for asynthesis of all available data given population/timeConsistency check between Consistency check betweendisease parameters disease parametersAdjustments for comorbidity Comorbidity ignoredUncertainty quantified No uncertaintyDWs: paired comparisons; DWs: panel of health experts;population surveys person trade off 3 3
  • Analytical steps Systematic Dismod-MR Prevalence reviewCovariates: ‒ Adjustment data‒ Study characteristics points • Definition ‒ Pooling info • Study type ‒ Predicting “gaps” • Representative? ‒ Consistency between‒ Country characteristics parameters • GDP • Access to health services • Conflict
  • DisMod-MRBayesian meta-regression5 5
  • DisMod-MRBayesian meta-regression Example of inconsistent data: osteoarthritis knee 6
  • Analytical steps Severity distribution Systematic DisMod-MR Prevalence YLDs reviewCovariates: ‒ Adjustment data‒ Study characteristics points DWs • Definition ‒ Pooling info • Study type ‒ Predicting “gaps” • Representative? ‒ Consistency between parameters‒ Country characteristics. Disability weight • GDP surveys • Access to health services • Conflict 7
  • GBD 2010 disability weights Large empirical effort – In-person surveys in Indonesia, Bangladesh, Tanzania, and Peru – Telephone survey in US – Internet survey Parsimonious set of 220 health states presented as short lay descriptions prepared with expert groups Pair-wise comparisons: “Who is the healthier?” Random set of 15 pairs for each respondent Some of the web survey respondents answered population health equivalence questions to help anchor on scale 0-1 8
  • Heat maps paired comparisons High agreement in choices between very healthy vs. unhealthy outcomes (>90%) Worst Second sequela in pairSplit responses for similaroutcomes (~50%) … or vice versa Best (<10%) Best Worst First sequela in pair 9 9
  • Comparisons between surveys 10
  • Survey and pooled results 6 6 6 r = 0.90 r = 0.94 r = 0.97 4 4 4 United States Indonesia Peru 2 2 2 0 0 0 -2 -2 -2 -2 0 2 4 6 -2 0 2 4 6 -2 0 2 4 6 Pooled Pooled Pooled 6 6 6 r = 0.75 r = 0.94 r = 0.98 4 4 4 Bangladesh Tanzania Web 2 2 2 0 0 0 -2 -2 -2 -2 0 2 4 6 -2 0 2 4 6 -2 0 2 4 6 Pooled Pooled Pooled High degree of consistency across diverse cultural settings and respondent characteristics 11
  • Special analytical cases Impairments such as vision loss and intellectual disability ‒ Outcome from many diseases and injuries ‒ Measure total  distribution by underlying cause  constrain to total Injuries ‒ Cause of injury (road traffic accident or fall) ‒ Nature of injury that causes disability (head injury or fracture) ‒ Short-term and long-term disabling consequences 12
  • Outline Summary of methods Results Reflections 13
  • Global YLDs per person by ageand sex, 1990 and 2010 14
  • Drivers of change in YLDs1990–2010 50% 40% 33% 38% 25% 5% 0% -25% -50% all causes Group 1 NCD Injuries % change 1990-2000 % change due to change in rates % change due to ageing % change due to population growth 15
  • Percentage of YLDs in 2010by cause and age Males Females 16
  • Percentage of YLDs in 2010by cause and region 17
  • Global YLDs ranks, 1990 and 2010 18
  • Prevalence and DW for top 5conditions Prevalence Average DW Back pain 9% 0.14 Depression 4% 0.23 Anaemia 14% 0.04 Neck pain 5% 0.11 COPD 5% 0.10 19
  • Outline Summary of methods Results Reflections 20
  • Advances Much more data-driven process Less researcher „choices‟ Uncertainty Greater involvement by disease/injury experts and understanding of methods – …. old adagio of GBD “decoupling epidemiology from advocacy” more acute than ever …. 21
  • Challenges Large heterogeneity – True variation in disease experience – Methodological differences  Plea for greater standardisation in data collections Data gaps – “Underserved” world regions – “Underserved” diseases – Surprising lack of data on severity and often not comparable Plea for representative large data collections with diagnostic and severity information to allow co-morbidity adjusted severity measures Mapping from patient derived severity measures to our “DW space” 22