Modeling and prediction of age-specific mortality rates using the Lee–Carter model
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Modeling and prediction of age-specific mortality rates using the Lee–Carter model |
| 2. | Creator | Author's name, affiliation, country | Evgenii L. Borschuk; Orenburg State Medical University; Russian Federation |
| 2. | Creator | Author's name, affiliation, country |
Dmitrii N. Begun; Orenburg State Medical University ; Russian Federation |
| 2. | Creator | Author's name, affiliation, country | Irina P. Bolodurina; Orenburg State Medical University; Orenburg State University; Russian Federation |
| 2. | Creator | Author's name, affiliation, country | Larisa I. Menshikova; Northern State Medical University; Russian Federation |
| 2. | Creator | Author's name, affiliation, country | Svetlana V. Kolesnik; Orenburg State University; Russian Federation |
| 2. | Creator | Author's name, affiliation, country | Aislu N. Duisembaeva; Orenburg State University; Russian Federation |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | mortality; population; age and sex mortality rates; modeling; forecasting |
| 4. | Description | Abstract | BACKGROUND: High mortality remains one of the most significant health concerns in Russia. One of the priorities of the state policy is to reduce mortality rates among the working-age population and increase life expectancy. Predicting population mortality rates serves as a valuable tool for effectively allocating the available resources. AIM: To perform mathematical modeling and prediction of mortality rates of the population of the Orenburg region using the Lee–Carter model. MATERIAL AND METHODS: The age- and sex-specific mortality rates and the population size of the Orenburg region for the period 1991–2020 was used as a study base. The Lee–Carter method was applied to model and predict population mortality. By deriving key parameters, a random walk model with drift was developed, and an accuracy assessment was performed. RESULTS: The Lee-Carter model has been utilized to analyze the mortality rates of the male population in the Orenburg region. Through this modeling process, an accuracy rate of 87% was achieved, providing a reliable basis for long-term prediction. Mortality forecasts have been generated up to the year 2035, allowing for a comprehensive evaluation of future trends in the region. CONCLUSION: The analysis of the results indicates that the pandemic's impact on population mortality is expected to be short-term. In the upcoming years, the mortality rate of the male population in the Orenburg region is projected to continue decreasing. |
| 5. | Publisher | Organizing agency, location | Eco-Vector |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (DD-MM-YYYY) | 13.09.2024 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | Research Article |
| 9. | Format | File format | PDF (Rus), PDF (Rus) |
| 10. | Identifier | Uniform Resource Identifier | https://hum-ecol.ru/1728-0869/article/view/611099 |
| 10. | Identifier | Digital Object Identifier (DOI) | 10.17816/humeco611099 |
| 10. | Identifier | Digital Object Identifier (DOI) (PDF (Rus)) | 10.17816/humeco611099-151213 |
| 11. | Source | Title; vol., no. (year) | Ekologiya cheloveka (Human Ecology); Vol 31, No 1 (2024) |
| 12. | Language | English=en | ru |
| 13. | Relation | Supp. Files |
Fig. 1. Mortality rates of the male and female population of the Orenburg region per 1000 population. (138KB) doi: 10.17816/humeco611099-4215380 Fig. 2. Age-specific mortality rates among males in the Orenburg region per 1000 population. (99KB) doi: 10.17816/humeco611099-4215385 Fig. 3. Age-specific mortality rates among females in the Orenburg region per 1000 population. (98KB) doi: 10.17816/humeco611099-4215386 Fig. 4. Values of the aₓ parameter for the baseline period 1991–2020. (92KB) doi: 10.17816/humeco611099-4215387 Fig. 5. Values of the bₓ parameter for the baseline period 1991–2020. (99KB) doi: 10.17816/humeco611099-4215388 Fig. 6. Values of the kt parameter for the base period 1991–2020. (109KB) doi: 10.17816/humeco611099-4215389 Fig. 7. Forecast of the mortality index until 2035. (166KB) doi: 10.17816/humeco611099-4215390 |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2024 Eco-Vector This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |