Causes of death

Rafael Lozano, MD.

Director of the Center for Health System Research, NIPH, Mexico

Director of the Latin America and the Caribbean initiatives, IHME.

Global Burden of Diseases, Injuries, and Risk Factors Study 2010: workshop on methods and key findings

June 18, 2013

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Outline

• Background

• Methods: Main Issues for calculating causes of death

• Key findings

• Conclusions

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Background

• Causes of death (CoD) is one of the most fundamental metrics for population health.

• Trends in CoD provide an important summary of whether society is or is not making progress in reducing burden of premature mortality and especially avoidable mortality.

• Usually CoD assessments show success and failures of Health Information Systems and provide directions of how to improve them.

• GBD 1990 was the first comprehensive study to present the global leading causes of death.

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Global cause of death assessment: main issues

• The universe of data

• Efforts to assess and enhance quality and comparability of data

• The statistical modeling strategy

• Causes of death constrained to sum to all cause mortality

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The universe of CoD data

We have to identify all available data on causes of death for all countries for a period of time

We have to identify all different sources of CoD data

• We collected data on around 600 million deaths in the last 30 years

• Data available varies by disease:o More on maternal, cancer, injurieso Less on NTD, diarrhea and LRI

pathogens

Only VR

All Sources

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Data Sources, Countries, and Site years, 1900-2010

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Assessment and enhancement of data quality and comparability1. Assessment of

completeness

2. Causes of death mapping

3. Redistribution of misclassified causes of death

4. Age and age-sex splitting

5. Smoothing for stochastic variation due to small numbers

6. Outlier detection

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Mapping one cause in different ICD

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Mapping the cause of death lists

BTL1 2 3 4 5 Tab B 6,7 Tab A 89 tab

9 VA 10Tab

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Different type of ICD

1900 2010SPC countries map

Different type of ICD

GBD 1990 Cause List (100)

GBD 2010 Cause List (235)

24 causes

39 causes

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Group A: Communicable, maternal, perinatal and nutritional conditions

D. Intestinal infectious diseases

1. Diarrheal disease

Group B: Non communicable diseases

H. Cardiovascular and circulatory diseases

Group C: Injuries

A. Unintentional injuries

a .Cholerac. Shigellosisi. Rotaviral enteritis

4. Cerebrovascular diseaseb. Hemorrhagic stroke

1. Transport Injuriesa. Road injury

a3. injury - motorized two-wheeler rider

GBD2010 has a list of 235 CoDUsing ICD9th and ICD10th revisions

Top down hierarchical map

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Percent of Garbage Codes by type, and sex in all ICD10 ,IHME

data set (26.6%)

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Garbage Codes from ICD10 (Percent of deaths

Redistribution of Garbage Codes

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Garbage Codes

C26 ill-defined Cancers for digestive organs

Target CodesC16 Stomach cancer

C17 Cancer of the small intestine

C18 Colon cancer

C19 Malignant neoplasm of rectosigmoid junction

C23 Gallbladder cancer

C24 Malignant neoplasm of other parts of biliary tract

C25 Pancreatic cancer

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Modeling causes of death

1. Causes of death ensemble modeling, CODEm (133 causes), including all major causes except HIV. CODEm selects models and ensembles of models based on out-of-sample performance.

2. Negative binomial (12 causes).

3. Fixed proportion models (27 causes).

4. Disaggregation by pathogens or sub-causes (36 causes).

5. Natural history models (8 causes).

6. Mortality shock regressions (2 causes).

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Combining results: CoDCorrect algorithm

• Because we developed single-cause models, it was imperative as a final step to ensure that individual cause estimates summed to the all-cause mortality estimate for every age-sex-country-year group.

• This is one of the innovations of this study:o Implemented taking into account uncertainty in every cause of

death model outcome

o We proportionately rescaled every cause such that the sum of the cause-specific estimates equaled the number of deaths from all causes generated from the demographic analysis (by country, year, age, and sex).

o We applied CoDCorrect in a hierarchical way.

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Shift of causes of death in the last 20 years

Comm/Mater/

Neonat/Nutr34%

Injuries9%

Comm/Mater/

Neonat/Nutr25%

Injuries10%

1990 2010

Non CommunicableDiseases

57%

Non CommunicableDiseases

65%

46.5 million 52.7 million

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Death decomposition analysis by changes in population

% change 1990-2000 % change due to change in rates

% change due to pop ageing % change due to pop growth

-75%

-50%

-25%

0%

25%

50%

75%

All Causes Com/MatNeo/Nut

NCD Injuries

Percentage of global deaths for female and male individuals in 2010 by cause and age

Males Females

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Rapid shifts in leading causes of global death

Percentage of YLLs for all ages and both sexes combined by cause and region in 1990 and 2010

1990 2010

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Key findings

• The shifting pattern of the number of deaths by cause across time, countries, and age groups is consistent with the three key drivers of change

• Despite the important epidemiological shift in the world, the MDGs related deaths in Sub Sahara Africa represent 60% of all deaths in that region during 2010

• New set of analytical approaches and methods:o Improved diagnostic redistribution

o The modeling strategy depends of the strength of available data: CODEM and CoD Correct are both innovations in the field

• Adding time trends and quantifying the uncertainty differentiate GBD 2010 from similar studies in the past, however without correction of known bias, comparability is impossible.