Patwardhan, Gakidou and Co-authors Explore Health Differences Between Females and Males Across Major Causes of Disease Burden
Posted: 5/10/2024 (CSDE Research)
CSDE Affiliates Vedavati Patwardhan (Center on Gender Equity & Health, UC San Diego) and Emmanuela Gakidou (Health Metrics Sciences), along with Luisa Flor, Gabriela Gil and other co-authors from the Institute for Health Metrics and Evaluation (IHME) released an article in The Lancet Public Health, entitled “Differences across the lifespan between females and males in the top 20 causes of disease burden globally: a systematic analysis of the Global Burden of Disease Study 2021“. This study presents a systematic exploration of health differences between females and males across major causes of disease burden. The authors used data from the 2021 Global Burden of Disease Study to examine differences in health between females and males.
Their analysis examines 20 major causes of disease burden (health loss) globally, as well as by world regions, and covers females and males spanning age ranges from adolescence to older ages. They find that overall, males face higher health loss. In 2021, health loss measured in terms of disability-adjusted life years or DALYs was higher in males than females for 13 out of the top-20 causes of disease. These conditions included COVID-19, road injuries, and a range of cardiovascular, respiratory, and liver diseases. Importantly, their study highlights that females and males experience health and disease differently throughout the lifespan. Females bear a disproportionate toll from morbidity-driven conditions whose impact predominantly contributes to disability throughout life, as opposed to leading to death at a younger ages. These include low back pain, depressive disorders, headache disorders, anxiety, other musculoskeletal disorders, Alzheimer’s disease and other dementias and HIV/AIDS. On the other hand, males bear higher health loss owing to mortality-driven conditions – such as COVID-19, road injuries, and heart disease. Providing similar estimates over conditions, regions, and time enables researchers and policy makers to clearly identify key health differences, and inform priority areas for interventions targeting differences in female–male health outcomes.