| Contributors: |
Naghavi, M.; Kyu, H. H.; Bhoomadevi, A.; Aalipour, M. A.; Aalruz, H.; Ababneh, H. S.; Abafita, B. J.; Abaraogu, U. O.; Abbafati, C.; Abbasi, M.; Abbaspour, F.; Abbastabar, H.; Abd Al Magied, A. H. A.; Elhafeez, S. A.; Abdalla, A. N.; Abdalla, M. A.; Abdallah, E. M.; Abdeeq, B. A.; Abdel Razeq, N. M. I.; Abdelgalil, A. A.; Abdel-Hameed, R.; Abdelmasseh, M.; Abdelnabi, M.; Abdel-Rahman, W. M.; Abdous, A.; Abdrabou, M. M.; Aziz, J. M. A.; Abdulah, D. M.; Abdullahi, A.; Abdul-Rahman, T.; Getahun, H. A.; Abedi, A.; Abedi, P.; Abejew, A. A.; Zuniga, R. A. A.; Abid, S. U. A.; Abidi, S. H.; Abie, A.; Abiodun, O. O.; Aboagye, R. G.; Abohashem, S.; Abolhassani, H.; Abonie, U. S.; Abourashed, N. M.; Abouzid, M.; Abramov, D.; Abreu, L. G.; Abtahi, D.; Farha, R. K. A.; Abuadas, F. H. A.; Abubakar, A. K.; Abu-Elala, N.; Abu-Gharbieh, E.; Abuhammad, S.; Abuhelwa, A. Y.; Abukhadijah, H. J.; Abu-Rmeileh, N. M. E.; Aburuz, S.; Abushanab, D.; Accrombessi, M. M. K.; Acharya, A. B.; Acharya, A.; Adal, O.; Adams, L. C.; Adamu, A. A.; Addo, I. Y.; Adeagbo, O. A.; Adebisi, T. A.; Adedeji, I. A.; Adedokun, K. A.; Adegbile, O. E.; Adegoke, N. A.; Adeleke, O. T.; Adema, B. G.; Aden, B.; Adesina, I. A.; Adesina, M. A.; Adetunji, J. B.; Adewuyi, H. O.; Adeyeoluwa, T. E.; Adhana, M. T.; Adhikary, R. K.; Adiga, U.; Parvar, T. A.; Adnan, M.; Adnani, Q. E. S.; Adoma, P. O.; Adzigbli, L. A.; Adzrago, D.; Affinito, G.; Afifi, A. M.; Afoakwah, C.; Afolabi, A. A.; Afolabi, R. F.; Afrasanie, V. -A.; Afzal, S.; Agafari, G. B.; Agampodi, S. B.; Agampodi, T. C. |
| Description: |
Background Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. Methods GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the ... |