Can non-fatal burden estimates from the Global Burden of Disease study be used locally? An investigation using models of stroke and diabetes for South Africa

Dados Bibliográficos

ID19530556
AutoresVictoria Pillay‐van Wyk (0000-0001-8772-7197, South African Medical Research Council, autor correspondente), Rifqah Abeeda Roomaney (0000-0003-3267-8484, South African Medical Research Council), Mweete D Nglazi (0000-0003-0695-7316, South African Medical Research Council), Oluwatoyin Folashade Awotiwon (South African Medical Research Council), Oluwatoyin Awotiwon (0000-0003-4377-3997, South African Medical Research Council), Judy Katzenellenbogen (0000-0001-5287-5819, The University of Western Australia), Tracy R Glass (0000-0001-7075-9803, South African Medical Research Council), Tracy Glass (0000-0001-8493-3649, South African Medical Research Council), Janetta Debora Joubert (South African Medical Research Council), Debbie Bradshaw (0000-0002-3588-2184, South African Medical Research Council)
Ano2021
Volume14
Fascículo1
Páginas1856471-1856471
Data de publicação2021-01-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoGlobal Health Action (JOURNAL)
Identificadores do periódicoISSN: 1654-9716 • E-ISSN: 1654-9880
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/16549716.2020.1856471
PMID33393896
OpenAlexW3120646687
IdiomaEN
Referências citadas21

Background: The Global Burden of Disease (GBD) approach estimates disease burden by combining fatal (years of life lost) and non-fatal burden prevalence-based years of life lived with disability (PYLDs) estimates. Although South Africa has data to estimate mortality, prevalence data to estimate non-fatal burden are sparse. PYLD estimates from the GBD study for South Africa can potentially be used. However, there is a divergence in mortality estimates for South Africa between the second South African National Burden of Disease (SANBD2) and 2013 GBD studies.Objective: We investigated the feasibility of utilising GBD PYLD estimates for stroke and diabetes by exploring different disease modelling scenarios.Method: DisMod II software-generated South African stroke and diabetes PYLDs for 2010 from models using local epidemiological parameters and demographic data for people 20–79 years old. We investigated the impact on PYLD estimates of 1) differences in the cause-of-death envelope, 2) differences in the cause-specific mortality estimates (increase/decrease by 15% for stroke and 30% for diabetes), and 3) difference using local disease parameters compared to other country or region parameters. Differences were expressed as ratios, average ratios and ratio ranges.Results: Using the GBD cause-of-death envelope (16% more deaths than SANBD2) and holding other parameters constant yielded age-specific ratios of PYLDs for stroke and diabetes ranging between 0.89 and 1.07 (average 0.98) for males. Similar results were observed for females.A 15% change in age-specific stroke mortality showed little difference in the ratio comparison of PYLDs (range 0.98–1.02) while a 30% change in age-specific diabetes mortality resulted in a ratio range of 0.96–1.07 for PYLDs depending on age.Conclusion: This study showed that GBD non-fatal burden estimates (PYLDs) can be used for stroke and diabetes non-fatal burden in the SANBD2 study

Burden of disease · Cause of death · Diabetes mellitus · Disease · Disease burden · Environmental health · Epidemiological transition · Estimation · Life expectancy · Mortality rate · Population · Years of potential life lost · Demography · Global Health Care Issues · Global Public Health Policies and Epidemiology · Health disparities and outcomes · Medicine · Epidemiology · Gerontology · Internal Medicine