The relative importance and stability of disease burden causes over time: summarizing regional trends on disease burden for 290 causes over 28 years

Abstract

Background Since the Global Burden of Disease study (GBD) has become more comprehensive, data for hundreds of causes of disease burden, measured using Disability Adjusted Life Years (DALYs), have become increasingly available for almost every part of the world. However, undergoing any systematic comparative analysis of the trends can be challenging given the quantity of data that must be presented. Methods We use the GBD data to describe trends in cause-specific DALY rates for eight regions. We quantify the extent to which the importance of ‘major’ DALY causes changes relative to ‘minor’ DALY causes over time by decomposing changes in the Gini coefficient into ‘proportionality’ and ‘reranking’ indices. Results The fall in regional DALY rates since 1990 has been accompanied by generally positive proportionality indices and reranking indices of negligible magnitude. However, the rate at which DALY rates have been falling has slowed and, at the same time, proportionality indices have tended towards zero. These findings are clearest where the focus is exclusively upon non-communicable diseases. Notably, large and positive proportionality indices are recorded for sub-Saharan Africa over the last decade. Conclusion The positive proportionality indices show that disease burden has become less concentrated around the leading causes over time, and this trend has become less prominent as the DALY rate decline has slowed. The recent decline in disease burden in sub-Saharan Africa is disproportionally driven by improvements in DALY rates for HIV/AIDS, as well as for malaria, diarrheal diseases, and lower respiratory infections.

Gini coefficient decomposition-based and mortality-rate-difference-based description of mortality causes in the Chinese population from 1991 to 2019: a retrospective cross-sectional surveillance study

“…In the decomposition of G changes (online supplemental file 1 part A),7 the G difference (∆normalG) in the studied periods (1991–2000, 2000–2010, 2010–2019 and 1991–2019) is decomposed into reranking ( R ) and proportionality ( P ). R represents the importance of the G changes from reranking of causes and indicates the mobility of causes; P indicates the G changes that account for the proportion when ranking is held constant at the original distribution and indicates the progressivity of causes (online supplemental table S1).…”

“… 6 Previous studies have focused on high-ranking causes that implicitly obscured the complex picture of varying mortality causes and changes in their relative importance over time. 7 Despite stable rates, certain mortality causes increased in rank due to the decline of other causes. Increasing uncertainties, including the coronavirus disease pandemic, have increased the diversity of the mortality causes, engendering concerns about the prioritisation of resource reallocation.…”

“…Thus, researchers introduced the modified Gini coefficient ( G ) 7–10 to quantitatively evaluate whether changes in overall rates including disability-adjusted life-years and obesity rates, are disproportionately centralised toward high-ranking causes. 7 9 The continuing increasing availability of data sources, whereby the changes between the crude mortality rates (CMRs) can be interpreted in terms of the components attributable to various factors, provides an epidemiological perspective. 11 12 It is important to quantify the contributions of population ageing and other risk factors to CMRs, which can be obtained by the mortality-rate-difference method, a widely used technique in demography.…”

“…The marked improvement in the registration of mortality causes and the accessibility of insight into variations in mortality causes have generated more unpredictable mortality patterns in the Chinese population 6. Previous studies have focused on high-ranking causes that implicitly obscured the complex picture of varying mortality causes and changes in their relative importance over time 7. Despite stable rates, certain mortality causes increased in rank due to the decline of other causes.…”

“…Increasing uncertainties, including the coronavirus disease pandemic, have increased the diversity of the mortality causes, engendering concerns about the prioritisation of resource reallocation. Thus, researchers introduced the modified Gini coefficient ( G )7–10 to quantitatively evaluate whether changes in overall rates including disability-adjusted life-years and obesity rates, are disproportionately centralised toward high-ranking causes 7 9. The continuing increasing availability of data sources, whereby the changes between the crude mortality rates (CMRs) can be interpreted in terms of the components attributable to various factors, provides an epidemiological perspective 11 12.…”