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Trinity College Courses
Caroline Barakat

HLTC07: Patterns of Health, Disease, and Injury Lecture 2: The Burden of Disease and Disability Lecture Outline  Global Burden of Disease  Introduction / History o Why do we need to find out about Global Burden of Disease? How is it usually done? How this data is aggregate and presented? o There’s an update to the 2004, that was supposed to be published end of 2011 – still in draft – info from diff unis and centres o Soon we’ll have update which looks at trends btn 2004-2010; then we can see if the projections are where they’re supposed to be o What are the main causes of death/disability? And how much do they impact diff countries?  Measures o DALYs o At the population level o At the individual level  Findings Global Burden of Disease  Individual-level data are aggregated to generate estimates of quantities o In order to quantify and describe the burden of disease generally use aggregated data  Individual level data  Aggregated data o When talking about GLOBAL burden of disease, you’re taking info at different levels based on individuals and putting it together and you’re aggregating and forming an estimate (based on a region, country etc;) o Sample of the population is selected and individuals are asked and from there inference is drawn from there to determine prevalence (for diabetes, for example) o Essentially, we’re working w/ aggregated data o Problems with working w/ aggregated data:  May fall with the notion of ecological fallacy; is it working, does it actually portray an accurate picture?  But these are the best estimates that we have – using individual data, aggregate to get estimate of general quantities  Ex) proportion of the population that suffers from particular health problem  Ex) proportion of the population that dies from specific cause  Limitations: (when we aggregate data at the certain level) o Difficulties in comparing indicators  One region may say for ex) rates of mortality by certain categories that aren’t the same for  another place  The ease in terms of comparing diff indicators may not exist  Nowadays, we do have general forms that we use  Every country looks at mortality of children under the age of 12 months, under age of 5; these are indicators that seem to be generally accepted  But before and different places even currently don’t work as such  When aggregating data, you may face certain difficulties in comparing certain indicators  These are all estimates (as close as possible to reality) --> numbers may have been hard to compare so people would’ve had to resort to estimates/projections to make it work o Statistics may be partial or fragmented  Ex) in some places, there’s no interest in recording death rates or it could be recorded in another way rather than what the real cause is etc; - common in many places  We’re talking about 200+ countries and within that, many diff levels (towns, cities); and not every region does the same thing  Some places captures data that is non-fatal  Ex) neurological or muscular conditions – how do you capture this type of info in diff countries – there’s no clear reporting of these types of conditions, even in developed places o Under- or over-estimates  In some places, analyses of incidence, prevalence, mortality of any single cause may be under/over estimated  Ties into partial fragmented data that’s available o Ex) person dies but ppl don’t do any investigation/record why that person died  These tend to be constrained within demographically plausible limits and sometimes not so internally consistent o So within a region, for instance, someone may die and it’s clear they died of respiratory infection but there’s no reason of what caused it, what kind of infection, specificity of that infection – becomes the case of over/under estimation of certain condition o Require detailed and comprehensive assessments  When governments have the role to provide better healthcare to their populations, they need to set priorities, and they do set these priorities based on detailed and comprehensive assessments  But the limitation wrt is how do they know that this is the most complete assessment so that they can set those priorities  That becomes also a limitations in terms of what the gvts can do  All the limitations are ties in, keep in back of mind  Why do we want to know about the global burden of disease? o To plan for future infrastructure at all levels o But at the global level, there are certain organizations whose mandate is to improve the health of pop’ns (WHO, diff conferences of diff countries, millennium development goal – goal foresets certain goals for children, people have to be healthy) o To meet these developmental goals we need to have good data WHO's Global Burden of Disease (GBD) Study  GBD started in 1990’s; was first commissioned by the WHO in early 1990s to take place o It took place but wasn’t very large scale o Eventually expanded – done in 2002 and published 2004 GBD  Goal: consistent set of estimates of mortality and morbidity by age, sex and region – comparative basis  First study was done based on 8 different world bank regions and was eventually expanded to diff regions and  there was that distinction made – high-income countries and low-income countries  So when reading 2004 report, it’ll say how it was revised – know the basics – how was it expanded and why did they look for better info (injuries, other diseases etc;)  New metric – disability-adjusted life year (DALY) o Simultaneously quantifies the burden of the disease from premature mortality and then looks at certain diseases and looks at how many years of lost life occurred due to this disability o So puts these 2 components together: how many years were lost due to early death + how many years lost due to premature disability  Main findings: o Neuropsychiatric disorders and injuries were major causes of lost years of healthy life o Non-communicable diseases, including neuropsychiatric disorders were estimated to have caused 41% of the global burden of disease in 1990  This category was eventually bigger and when this study was re-visited, categories for diseases and conditions changed – further refined o Communicable, maternal, perinatal, and nutritional conditions amounted to 44% of the global burden of disease  Eventually revised and refined into further categories o Injuries amounted to 15%  RMB: first study looked at 8 regions and bigger categories that were then refined to find out more about where the problem lies and what are the areas of concern  Refined study on 192 WHO member states o Based on injury & disease by age, sex but for 192 world health organization member states (regions) o Researchers were able to get the life tables developed based on death registration, sample registration and data on child/adult mortality from diff censuses and surveys that existed at the regional level (channelled in to the WHO to get good estimates) o Essentially, when looking at the report, keep in mind 2 main summary measures of pop’n health (SMPH): Summary Measures of Population Health (SMPH)  Health expectancies – e.g. disability-free life expectancy, active life expectancy, healthy life expectancy (which would all give the same picture – how long do you expect to live in a specific country healthily; having good health state) o With the definition of life-expectancy that existed in the past, it’s not just enough to live long, but ppl have to look at the HEALTH expectancy – how many years does a person in a country live HEALTHY (without disability/disease)  Health gaps – e.g. disability-adjusted life years (DALY) o Complementary cases of indicators that measure lost years of full health against some sort of normative ideal o How many years of lost health did one obtain in that country compared to healthy lifestyles? o DALYs gives just that: disability-adjusted life years for that individual o The opposite concept is QALY = measures of healthy years lived – quality adjusted life years DALY : measures the overall disease burden expressed as a cumulative # of years lost due to ill health, disability or early death  Formula = how many years of life lost o Person dies 5 yrs earlier than what the life expectancy is and you’re looking at how many of those years were lost due to early death and how many years lost due to disability o If a person lives with a certain health condition/status and they’re not living their life fully then there are years that are lost due to disability  YLL (years of life lost = when living less than life expectancy) = when a person has died completely = (for a given cause, age and sex) = N X L, where: o N = number of deaths o L = year lost based on standard life expectancy at age of death in years  YLD (for a particular cause)=I x DW x L where: o I = number of incident cases in that period o DW = weight factor that reflects the severity of the disease on a scale from 0 (perfect health) to 1 (dead). o L = average duration of the case until remission or death (years) DALY: Example DALY = Years Lived with Disability + Years of Life Lost (died early than life expectancy) LE = 86 years, survived until 75, years, died 11 years earlier Dealt with disability since age 30, this means 45 years of disability 0.4 years – severity, assuming 35 years living with this disability 17 ½ years lost Adding up the number of years person was inconvenient and the earlier age they died at 35(0.5) + 11 = lost 28.5 years DALY = YLD + YLL YLL = looking at how many individuals who died of disease L = 11 years LYD = I X DW X L Looks at how many people got the disease within that time period; closer to 0 is not that significant
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