4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Trends in breast cancer mortality attributable to metabolic risks in Chinese women from 1990 to 2019: an age-period-cohort analysis

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          Metabolic risks (MRs) are the primary determinants of breast cancer (BC) mortality among women. This study aimed to examine the changing trends in BC mortality associated with MRs and explore how they related to age, time period, and birth cohorts in Chinese women aged 25 and above.

          Methods

          Data were sourced from the Global Burden of Disease Study 2019 (GBD2019). The BC mortality trajectories and patterns attributable to MRs were assessed using Joinpoint regression. The age-period-cohort (APC) model was employed to evaluate cohort and time period effects.

          Results

          The age-standardized mortality rate (ASMR) of BC mortality linked to MRs displayed an escalating trend from 1990 to 2019, demonstrating an average annual percentage change (AAPC) of 1.79% (95% CI: 1.69~1.87). AAPCs attributable to high fasting plasma glucose (HFPG) and high body mass index (HBMI) were 0.41% (95% CI: 0.32~0.53) and 2.75% (95% CI: 2.68~2.82), respectively. APC analysis revealed that BC mortality due to HBMI in women aged 50 and above showed a rise with age and mortality associated with HFPG consistently demonstrated a positive correlation with age. The impact of HBMI on BC mortality significantly outweighed that of HFPG. The risk of BC mortality linked to HBMI has steadily increased since 2005, while HFPG demonstrated a trend of initial increase followed by a decrease in the period effect. Regarding the cohort effect, the relative risk of mortality was greater in the birth cohort of women after the 1960s of MRs on BC mortality, whereas those born after 1980 displayed a slight decline in the relative risk (RR) associated with BC mortality due to HBMI.

          Conclusion

          This study suggests that middle-aged and elderly women should be considered as a priority population, and control of HBMI and HFPG should be used as a primary tool to control metabolic risk factors and effectively reduce BC mortality.

          Related collections

          Most cited references67

          • Record: found
          • Abstract: found
          • Article: not found

          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            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

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

              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.
                Bookmark

                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2627868Role: Role: Role: Role:
                Role: Role:
                Role: Role: Role:
                Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2276222Role: Role: Role:
                Role: Role: Role:
                Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/1904508Role: Role: Role: Role:
                Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2632809Role: Role: Role:
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                16 April 2024
                2024
                : 14
                : 1369027
                Affiliations
                [1] 1 Department of Science and Education, Nanjing Municipal Center for Disease Control and Prevention , Nanjing, Jiangsu, China
                [2] 2 Monash Addiction Research Centre, Monash University , Frankston, VC, Australia
                [3] 3 Department of Epidemiological Research, Jiangsu Health Development Research Center , Nanjing, Jiangsu, China
                [4] 4 Department of Noncommunicable Chronic Disease Control and Prevention, Nanjing Municipal Center for Disease Control and Prevention , Nanjing, Jiangsu, China
                [5] 5 Division of Medical Affairs, Nanjing Municipal Health Commission , Nanjing, Jiangsu, China
                [6] 6 Department of Noncommunicable Chronic Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention , Nanjing, Jiangsu, China
                Author notes

                Edited by: Nadia Judith Jacobo-Herrera, National Institute of Medical Sciences and Nutrition Salvador Zubirán, Mexico

                Reviewed by: Richard J. Q. McNally, Newcastle University, United Kingdom

                Vahur Valvere, North Estonia Medical Centre, Estonia

                Emilia Nunzi, University of Perugia, Italy

                †These authors share first authorship

                Article
                10.3389/fonc.2024.1369027
                11058724
                38690163
                424adbcf-45ef-484f-a24e-cb60b05d7137
                Copyright © 2024 Zhang, Sun, Xia, Huang, Fu, Wang, Yang, Hong, Zhou and Yu

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 January 2024
                : 25 March 2024
                Page count
                Figures: 3, Tables: 1, Equations: 3, References: 68, Pages: 9, Words: 4287
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was funded by grants from the Nanjing Municipal Medical Science and Technique Development Foundation (ZKX18049) and the Nanjing Key Medical Department (of Chronic Non-Communicable Disease Prevention and Control).
                Categories
                Oncology
                Original Research
                Custom metadata
                Breast Cancer

                Oncology & Radiotherapy
                metabolic risks,high fasting plasma glucose,high body-mass index,breast cancer,age-period-cohort analysis

                Comments

                Comment on this article