Exploring the Epidemiological Transition Ryan Barber and Vinay
Exploring the Epidemiological Transition Ryan Barber and Vinay Srinivasan September 25, 2017
Learning objectives • Define the demographic and epidemiological transitions that occur in populations as countries develop, and identify examples over space and time • Understand how GBD uses the Socio-demographic Index to measure development and its relationship with the epidemiological profile of burden • Apply the notion of “expected” burden to benchmark epidemiological transitions across the world 2
Defining the epidemiological transition • The epidemiological transition is an extension of the notion of the demographic transition… o A characteristic evolution occurs in populations over time towards reduced fertility rates, reduced mortality rates, and an older age distribution of the population. • The widely used concept of the epidemiological transition adds the idea that, in addition to these changes, a characteristic change occurs in the contributing causes of death and disability. 3
Defining the epidemiological transition • Two key components… 1. As countries move up the spectrum of development, their mortality rates due to communicable, maternal, neonatal, and nutritional diseases decline. 2. As more people live into adulthood, the average of the population increases and its disease burden shifts to non-communicable diseases and disabilities. 4
Defining the epidemiological transition Total DALYs Crude DALY rate Population growth Age-standardized DALY rate Population aging 5
Three countries along the epidemiological transition in 2016 Nigeria • ~70% disease burden due to infectious, child and maternal health conditions (“Group 1”) • ~30% disease burden due to NCDs and injuries Germany India • ~30% disease burden due to infectious, child and maternal health conditions (“Group 1”) • ~70% disease burden due to NCDs and injuries 6 • ~5% disease burden due to infectious, child and maternal health conditions (“Group 1”) • ~95% disease burden due to NCDs and injuries
Charting epidemiological changes in Indonesia, 1990 -2016 1990 2000 2016 • ~55% disease burden due to infectious, child • ~40% disease burden due to infectious, child • ~25% disease burden due to infectious, child and maternal health conditions (“Group 1”) • ~45% disease burden due to NCDs and injuries and maternal health conditions (“Group 1”) • ~60% disease burden due to NCDs and injuries • ~75% disease burden due to NCDs and 7 and maternal health conditions (“Group 1”) injuries
Charting epidemiological changes in Indonesia, 1990 -2016 1990 2000 2016 • ~55% disease burden due to infectious, child • ~40% disease burden due to infectious, child • ~25% disease burden due to infectious, child and maternal health conditions (“Group 1”) • ~45% disease burden due to NCDs and injuries and maternal health conditions (“Group 1”) • ~60% disease burden due to NCDs and injuries • ~75% disease burden due to NCDs and 8 and maternal health conditions (“Group 1”) injuries
Defining the epidemiological transition • We want… o To determine the expected epidemiological profile corresponding to any given level of development o To evaluate any given country’s observed burden rates against the expectations set above based on their unique development status • In order to do this, we first need a continuous measure of development 9
Socio-demographic Index (SDI) • A single composite variable • Representative of demographic status and socioeconomic development • Composed of variables indicative of socioeconomic status and demographic change that are available for all GBD geographies from 1980 onwards o Income per capita (in constant international dollars) o Average years of schooling of the population after age 15 years o Total fertility rate 10
Socio-demographic Index (SDI) • 11
Socio-demographic Index (SDI) 12
Socio-demographic Index (SDI) 13
Socio-demographic Index (SDI) 14
Socio-demographic Index (SDI) 1990 2000 2016 15
Socio-demographic Index (SDI) 16
Using SDI to benchmark epidemiological transitions • By grouping countries based on their SDI, we can compare health trends and examine how development is related to changes in disease burden. 17
Using SDI to benchmark epidemiological transitions 18
Using SDI to benchmark epidemiological transitions • SDI can be used for benchmarking country-level changes – and how they may differ from what has been observed in the past. • Across countries, an average relationship emerges between improving development – or increases in SDI – and the profile of disease burden associated with any given level of SDI. • To estimate this, we model age-sex relationships between SDI and all GBD estimates 19
Using SDI to benchmark epidemiological transitions 20
Using SDI to benchmark epidemiological transitions • “Expected burden” reflects this average relationship between SDI and disease burden o Shows what a country could expect for disease burden on the basis of its level of development alone. • “Observed burden” reflects the disease burden of a given place – or what is actually observed or measured in GBD. • Comparing differences in observed and expected burden can help determine if gains in development are translating into improvements in health – and where health challenges have emerged despite increasing SDI. 21
Using SDI to benchmark epidemiological transitions OBSERVED EXPECTED 22
Using SDI to benchmark epidemiological transitions Cardiovascular disease deaths 1990 2016 23
Using SDI to benchmark epidemiological transitions • 24
Using SDI to benchmark epidemiological transitions OBSERVED Observed / expected > 1 Observed / expected < 1 EXPECTED 25
Using SDI to benchmark epidemiological transitions United States SDI: 0. 90 O-E ratio: 2. 0 Much higher than expected Peru SDI: 0. 68 O-E ratio: 0. 27 Much lower than expected Thailand SDI: 0. 73 O-E ratio: 0. 95 Similar to expected Namibia SDI: 0. 62 O-E ratio: 0. 80 Lower than expected 26 China SDI: 0. 73 O-E ratio: 1. 3 Higher than expected
Death and disability along the epidemiological transition • In addition to country-specific benchmarking, we are also able to identify broad attributes of the epi transition that will help policy makers anticipate new health system challenges that come with improving development status • One such example is that socio-economic evolution of countries tends to be accompanied by a progressive shift towards disability and away from premature mortality 27
Death and disability along the epidemiological transition 28
Death and disability along the epidemiological transition 29
Death and disability along the epidemiological transition 30
- Slides: 30