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      Global, regional, and national burden of kidney, bladder, and prostate cancers and their attributable risk factors, 1990–2019

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          Abstract

          Background

          The burden of kidney, bladder, and prostate cancers has changed in recent decades. This study aims to investigate the global and regional burden of, and attributable risk factors for genitourinary cancers during the past 30 years.

          Methods

          We extracted data of kidney, bladder, and prostate cancers from the Global Burden of Disease 2019 database, including incidence, mortality, disability-adjusted life-years (DALYs), and attributable risk factors from 1990 to 2019. Estimated annual percentage changes (EAPC) were calculated to assess the changes in age-standardized incidence rate, age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR). The associations between cancers burden and socio-demographic index (SDI) were also analyzed.

          Results

          Compared with 1990, the global incident cases in 2019 were higher by 154.78%, 123.34%, and 169.11% for kidney, bladder, and prostate cancers, respectively. During the 30-year study period, there was a downward trend in ASMR and ASDR for bladder cancer (EAPC = − 0.68 and − 0.83, respectively) and prostate cancer (EAPC = − 0.75 and − 0.71, respectively), but an upward trend for kidney cancer (EAPC = 0.35 and 0.12, respectively). Regions and countries with higher SDI had higher incidence, mortality, and DALYs for all three types of cancers. The burden of bladder and prostate cancers was mainly distributed among older men, whereas the burden of kidney cancer increased among middle-aged men. Smoking related mortality and DALYs decreased, but high body mass index (BMI) and high fasting plasma glucose (FPG) related mortality and DALYs increased among kidney, bladder, and prostate cancers during the study period.

          Conclusions

          Kidney, bladder, and prostate cancers remain major global public health challenges, but with distinct trend for different disease entity across different regions and socioeconomic status. More proactive intervention strategies, at both the administrative and academic levels, based on the dynamic changes, are needed.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40779-021-00354-z.

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          Cancer statistics, 2019

          Rebecca Siegel, Kimberly D Miller, Ahmedin Jemal (2019)
          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data, available through 2015, were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data, available through 2016, were collected by the National Center for Health Statistics. In 2019, 1,762,450 new cancer cases and 606,880 cancer deaths are projected to occur in the United States. Over the past decade of data, the cancer incidence rate (2006-2015) was stable in women and declined by approximately 2% per year in men, whereas the cancer death rate (2007-2016) declined annually by 1.4% and 1.8%, respectively. The overall cancer death rate dropped continuously from 1991 to 2016 by a total of 27%, translating into approximately 2,629,200 fewer cancer deaths than would have been expected if death rates had remained at their peak. Although the racial gap in cancer mortality is slowly narrowing, socioeconomic inequalities are widening, with the most notable gaps for the most preventable cancers. For example, compared with the most affluent counties, mortality rates in the poorest counties were 2-fold higher for cervical cancer and 40% higher for male lung and liver cancers during 2012-2016. Some states are home to both the wealthiest and the poorest counties, suggesting the opportunity for more equitable dissemination of effective cancer prevention, early detection, and treatment strategies. A broader application of existing cancer control knowledge with an emphasis on disadvantaged groups would undoubtedly accelerate progress against cancer.
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            Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

            Theo Vos, Stephen S Lim, Cristiana Abbafati … (2023)
            Summary Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding Bill & Melinda Gates Foundation.
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              Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

              Christopher J L Murray, Aleksandr Y Aravkin, Peng Zheng … (2021)
              Summary Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding Bill & Melinda Gates Foundation.
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                Author and article information

                Contributors
                Hao Zi: zihao0828@126.com
                Shao-Hua He: heshaohua915@126.com
                Xie-Yuan Leng: 1986879503@qq.com
                Xiao-Feng Xu: 1061314087@qq.com
                Qiao Huang: stat_bigdata@163.com
                Hong Weng: wengh92@163.com
                Cong Zhu: zhucong268@163.com
                Lu-Yao Li: 1529343494@qq.com
                Jia-Min Gu: g378527624@163.com
                Xu-Hui Li: Xuhuili2011@hotmail.com
                Dao-Jing Ming: mingdaojing@qq.com
                Xiao-Dong Li: hndxhhyylxd@126.com
                Shuai Yuan: yuanshuai021@whu.edu.cn
                Xing-Huan Wang: wangxinghuan1965@163.com
                Da-Lin He: hedl@xjtu.edu.cn
                Xian-Tao Zeng:
                ORCID: http://orcid.org/0000-0003-1262-725X
                zengxiantao1128@whu.edu.cn , zengxiantao1128@163.com
                Journal
                Journal ID (nlm-ta): Mil Med Res
                Journal ID (iso-abbrev): Mil Med Res
                Title: Military Medical Research
                Publisher: BioMed Central (London )
                ISSN (Print): 2095-7467
                ISSN (Electronic): 2054-9369
                Publication date (Electronic): 24 November 2021
                Publication date PMC-release: 24 November 2021
                Publication date Collection: 2021
                Volume: 8
                Electronic Location Identifier: 60
                Affiliations
                [1 ]GRID grid.413247.7, ISNI 0000 0004 1808 0969, Department of Urology, , Zhongnan Hospital of Wuhan University, ; Wuhan, 430071 China
                [2 ]GRID grid.413247.7, ISNI 0000 0004 1808 0969, Center for Evidence-Based and Translational Medicine, , Zhongnan Hospital of Wuhan University, ; Wuhan, 430071 China
                [3 ]Precision Medicine Centre, The Second People’s Hospital of Huaihua, Huaihua, 418000 China
                [4 ]GRID grid.186775.a, ISNI 0000 0000 9490 772X, The First School of Clinical Medicine, , Anhui Medical University, ; Hefei, 230000 China
                [5 ]GRID grid.440299.2, Department of Urology, , Xianyang Central Hospital, ; Xianyang, 712000 China
                [6 ]GRID grid.452438.c, ISNI 0000 0004 1760 8119, Department of Urology, , The First Affiliated Hospital of Xi’an Jiaotong University, ; Xi’an, 710061 China
                [7 ]GRID grid.256922.8, ISNI 0000 0000 9139 560X, Institutes of Evidence-Based Medicine and Knowledge Translation, , Henan University, ; Kaifeng, 475000 China
                [8 ]GRID grid.256922.8, ISNI 0000 0000 9139 560X, Department of Urology, , Huaihe Hospital of Henan University, ; Kaifeng, 475000 China
                [9 ]GRID grid.49470.3e, ISNI 0000 0001 2331 6153, Institute of Urology, , Wuhan University, ; Wuhan, 430071 China
                Author information
                http://orcid.org/0000-0003-1262-725X
                Article
                Publisher ID: 354
                DOI: 10.1186/s40779-021-00354-z
                PMC ID: 8611255
                PubMed ID: 34819142
                SO-VID: c40eb802-2b5e-48c0-9271-00f99ecb33fd
                Copyright © © The Author(s) 2021
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 22 April 2021
                Date accepted : 1 November 2021
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2021

                Keywords: genitourinary cancer,kidney cancer,bladder cancer,prostate cancer,incidence,mortality,disability-adjusted life-years,global burden of disease
                Data availability:
                Keywords: genitourinary cancer, kidney cancer, bladder cancer, prostate cancer, incidence, mortality, disability-adjusted life-years, global burden of disease

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