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Zhu J, Li S, Li X, Wang L, Du L, Qiu Y. Impact of population ageing on cancer-related disability-adjusted life years: A global decomposition analysis. J Glob Health 2024; 14:04144. [PMID: 39024622 PMCID: PMC11259023 DOI: 10.7189/jogh.14.04144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024] Open
Abstract
Background As the global population ages, the burden of cancer is increasing. We aimed to assess the impact of population ageing on cancer-related disability-adjusted life years (DALYs). Methods We used the decomposition method to estimate the impact of ageing, population growth, and epidemiological change on cancer-related DALYs from 1990 to 2019, stratified by 204 countries/territories and by their sociodemographic index (SDI). This approach separates the net effect of population ageing from population growth and change in age-specific DALY rates. Results Cancer-related DALYs among individuals aged ≥65 years increased by 95.14% between 1990 (52.25 million) and 2019 (101.96 million). Population growth was the main contributor to cancer-related DALYs (92.38 million, attributed proportion: 60.91%), followed by population ageing (41.38 million, 27.28%). Cancer-related DALYs attributed to population ageing followed a bell-shaped pattern when stratified by SDI, meaning they peaked in middle-SDI countries. Cancer-related DALYs attributed to ageing increased in 171 and decreased in 33 countries/territories. The top three cancer types with the highest increase in the absolute number of cancer-related DALYs associated with ageing were tracheal, bronchus, and lung (8.72 million); stomach (5.06 million); and colorectal (4.28 million) cancers, while the attributed proportion of DALYs was the highest in prostate (44.75%), pancreatic (40.93%), and non-melanoma skin (38.03%) cancers. Conclusions Population ageing contributed to global cancer-related DALYs, revealing a bell-shaped pattern when stratified by socioeconomic development, affecting middle-SDI countries the most. To respond to the growing ageing population and reduce cancer-related DALYs, it is necessary to allocate health care resources and prioritize interventions for older adults.
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Affiliation(s)
- Juan Zhu
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Sainan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Xue Li
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Le Wang
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Lingbin Du
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- School of Public Health and Management, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yanfei Qiu
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China
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Cheng X, Yang Y, Schwebel DC, Liu Z, Li L, Cheng P, Ning P, Hu G. Population ageing and mortality during 1990-2017: A global decomposition analysis. PLoS Med 2020; 17:e1003138. [PMID: 32511229 PMCID: PMC7279585 DOI: 10.1371/journal.pmed.1003138] [Citation(s) in RCA: 128] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 05/13/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND As the number of older people globally increases, health systems need to be reformed to meet the growing need for medical resources. A few previous studies reported varying health impacts of population ageing, but they focused only on limited countries and diseases. We comprehensively quantify the impact of population ageing on mortality for 195 countries/territories and 169 causes of death. METHODS AND FINDINGS Using data from the Global Burden of Disease Study 2017 (GBD 2017), this study derived the total number of deaths and population size for each year from 1990 to 2017. A decomposition method was used to attribute changes in total deaths to population growth, population ageing, and mortality change between 1990 and each subsequent year from 1991 through 2017, for 195 countries/territories and for countries grouped by World Bank economic development level. For countries with increases in deaths related to population ageing, we calculated the ratio of deaths attributed to mortality change to those attributed to population ageing. The proportion of people aged 65 years and older increased globally from 6.1% to 8.8%, and the number of global deaths increased by 9 million, between 1990 and 2017. Compared to 1990, 12 million additional global deaths in 2017 were associated with population ageing, corresponding to 27.9% of total global deaths. Population ageing was associated with increases in deaths in high-, upper-middle-, and lower-middle-income countries but not in low-income countries. The proportions of deaths attributed to population ageing in 195 countries/territories ranged from -43.9% to 117.4% for males and -30.1% to 153.5% for females. The 2 largest contributions of population ageing to disease-specific deaths globally between 1990 and 2017 were for ischemic heart disease (3.2 million) and stroke (2.2 million). Population ageing was related to increases in deaths in 152 countries for males and 159 countries for females, and decreases in deaths in 43 countries for males and 36 countries for females, between 1990 and 2017. The decreases in deaths attributed to mortality change from 1990 to 2017 were more than the increases in deaths related to population ageing for the whole world, as well as in 55.3% (84/152) of countries for males and 47.8% (76/159) of countries for females where population ageing was associated with increased death burden. As the GBD 2017 does not provide variances in the estimated death numbers, we were not able to quantify uncertainty in our attribution estimates. CONCLUSIONS In this study, we found that population ageing was associated with substantial changes in numbers of deaths between 1990 and 2017, but the attributed proportion of deaths varied widely across country income levels, countries, and causes of death. Specific preventive and therapeutic techniques should be implemented in different countries and territories to address the growing health needs related to population ageing, especially targeting the diseases associated with the largest increase in number of deaths in the elderly.
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Affiliation(s)
- Xunjie Cheng
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Yang Yang
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - David C. Schwebel
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Zuyun Liu
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Li Li
- Division of Epidemiology, College of Public Health, Ohio State University, Columbus, Ohio, United States of America
| | - Peixia Cheng
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Peishan Ning
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Guoqing Hu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- * E-mail:
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Carioli G, Bertuccio P, Malvezzi M, Rodriguez T, Levi F, Boffetta P, La Vecchia C, Negri E. Cancer mortality predictions for 2019 in Latin America. Int J Cancer 2019; 147:619-632. [PMID: 31637709 DOI: 10.1002/ijc.32749] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Revised: 10/03/2019] [Accepted: 10/09/2019] [Indexed: 12/11/2022]
Abstract
We estimated mortality figures for 2019 in seven Latin American countries, with focus on breast cancer. We retrieved cancer death certification and population data from the WHO and PAHO databases. We obtained mortality statistics for Argentina, Brazil, Chile, Colombia, Cuba, Mexico and Venezuela for 1970-2015. We predicted current death numbers and age-standardised (world population) mortality rates using joinpoint regression models. Total cancer mortality is predicted to decline in all countries and both sexes, except Argentinian women. Cuba had the highest all cancer rates for 2019, 136.9/100,000 men and 90.4 women, while Mexico showed the lowest ones, 63.8/100,000 men and 61.9 women. Stomach cancer showed favourable trends over the whole period, while colorectal cancer only recently. Lung cancer rates declined in men, while in women they decreased slightly over the most recent years, only. In Cuban women, lung cancer rates overtook breast cancer ones. Breast cancer showed overall favourable trends, but rates are rising in young women. Prostate and uterine cancer had favourable trends. Pancreas, ovary, bladder and leukaemias showed slightly decreasing trends. Between 1990 and 2019, mortality from all neoplasms is predicted to fall by about 18% in Argentina, 26% in Chile, 14% in Colombia, 17% in Mexico and 13% in Venezuela, corresponding to almost 0.5 million avoided cancer deaths. No decline was observed in Brazil and Cuba. Of concern, the persisting high rates of (cervix) uterus cancer, the high lung cancer rates in Cuba, the possible increases in breast cancer in young women, and the lack of overall declines in Brazil, Cuba and Venezuelan men.
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Affiliation(s)
- Greta Carioli
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Paola Bertuccio
- Department of Biomedical and Clinical Sciences, L. Sacco, Università degli Studi di Milano, Milan, Italy
| | - Matteo Malvezzi
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Teresa Rodriguez
- Navarra General Hospital, Navarra Health Service, Pamplona, Navarra, Spain
| | - Fabio Levi
- Institute of Social and Preventive Medicine (IUMSP), University of Lausanne, Lausanne, Switzerland
| | - Paolo Boffetta
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY.,Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Carlo La Vecchia
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Eva Negri
- Department of Biomedical and Clinical Sciences, L. Sacco, Università degli Studi di Milano, Milan, Italy
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Li H, Wei C, Zhou R, Wang B, Zhang Y, Shao C, Luo Y. Mouse models in modeling aging and cancer. Exp Gerontol 2019; 120:88-94. [PMID: 30876950 DOI: 10.1016/j.exger.2019.03.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Revised: 01/19/2019] [Accepted: 03/05/2019] [Indexed: 02/04/2023]
Abstract
Mouse models have been widely used in the research of human diseases. Aging, just as cancer, is influenced by the interaction of various genetic and environmental factors. Currently, aging could be induced by many mechanism, including telomere dysfunction, oxidase stress, DNA damage and epigenetic changes. Many of these genetic pathways are also shared by aging and cancer. The mouse models generated to study these pathways might manifest either aging or cancer phenotypes, sometimes both, which in deed has worked as a good model system in understanding the correlation between aging and cancer. Here, we reviewed these mouse models that were generated to model aging or cancer. These mouse models might help us put those related pathways in context and discover essential interactions in cancer and aging regulation.
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Affiliation(s)
- Haili Li
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Lab of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Chuanyu Wei
- Lab of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Ruoyu Zhou
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Lab of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Boyuan Wang
- Lab of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Yongjin Zhang
- Lab of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Chihao Shao
- Lab of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Ying Luo
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Lab of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
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