Systematic review of general burden of disease studies using disability-adjusted life years
1 Department of Public Health, Erasmus MC, Rotterdam, Netherlands
2 Division of Information, Evidence, Research and Innovation, WHO Regional Office for Europe, Copenhagen, Denmark
3 National Institute for Public Health and the Environment, Laboratory for Zoonoses and Environmental Microbiology, Bilthoven, Netherlands
4 University Utrecht, Institute for Risk Assessment Sciences, Utrecht, Netherlands
Population Health Metrics 2012, 10:21 doi:10.1186/1478-7954-10-21Published: 1 November 2012
To systematically review the methodology of general burden of disease studies. Three key questions were addressed: 1) what was the quality of the data, 2) which methodological choices were made to calculate disability adjusted life years (DALYs), and 3) were uncertainty and risk factor analyses performed? Furthermore, DALY outcomes of the included studies were compared.
Burden of disease studies (1990 to 2011) in international peer-reviewed journals and in grey literature were identified with main inclusion criteria being multiple-cause studies that quantified the burden of disease as the sum of the burden of all distinct diseases expressed in DALYs. Electronic database searches included Medline (PubMed), EMBASE, and Web of Science. Studies were collated by study population, design, methods used to measure mortality and morbidity, risk factor analyses, and evaluation of results.
Thirty-one studies met the inclusion criteria of our review. Overall, studies followed the Global Burden of Disease (GBD) approach. However, considerable variation existed in disability weights, discounting, age-weighting, and adjustments for uncertainty. Few studies reported whether mortality data were corrected for missing data or underreporting. Comparison with the GBD DALY outcomes by country revealed that for some studies DALY estimates were of similar magnitude; others reported DALY estimates that were two times higher or lower.
Overcoming “error” variation due to the use of different methodologies and low-quality data is a critical priority for advancing burden of disease studies. This can enlarge the detection of true variation in DALY outcomes between populations or over time.