Table_1_Longitudinal analysis of ovarian cancer death patterns during a rapid transition period (2005-2020) in Shanghai, China: A population-based study.xlsx

ObjectivesIt is important to assess the burden of ovarian cancer related premature death so as to develop appropriate evidence-based care and improve women’s health. This study aimed to characterize the long-term trends in mortality, survival and disease burden of ovarian cancer in Shanghai, China.Materials and MethodsCo-morbidities, crude mortality rate (CMR), age-standardised mortality rate by Segi’s world standard population (ASMRW), years of life lost (YLL), and survival rates were analysed. Temporal trends for the mortality rates and disease burden were analyzed using the Joinpoint Regression Program. Mortality rate increases by demographic and non-demographic factors were estimated by the decomposition method.ResultsA total of 1088 ovarian cancer as underlying cause of deaths were recorded. CMR and ASMRW were 4.82/105 and 2.32/105 person-years, respectively. The YLL was 16372.96 years, and the YLL rate was 72.46/105 person-years. The YLL rate increased only in the age group of 70-79 years (P = 0.017). The survival rates of ovarian cancer patients did not improve during the ten year period (2005-2015). The top co-morbidities were diseases of the respiratory system, digestive system, and circulatory system. The rates of ovarian cancer deaths caused by non-demographic and demographic factors increased by 21.29% (95%CI: 4.01% to 41.44%, P = 0.018) and 25.23% (95%CI: 14.64% to 36.81%, P ConclusionsPopulation ageing and all cause of death may affect ovarian cancer related deaths in Pudong, Shanghai. The high mortality and the stagnant survival rates suggest the need for more efforts in targeted prevention and treatment of this disease.</p

Table_6_Longitudinal analysis of ovarian cancer death patterns during a rapid transition period (2005-2020) in Shanghai, China: A population-based study.xlsx

ObjectivesIt is important to assess the burden of ovarian cancer related premature death so as to develop appropriate evidence-based care and improve women’s health. This study aimed to characterize the long-term trends in mortality, survival and disease burden of ovarian cancer in Shanghai, China.Materials and MethodsCo-morbidities, crude mortality rate (CMR), age-standardised mortality rate by Segi’s world standard population (ASMRW), years of life lost (YLL), and survival rates were analysed. Temporal trends for the mortality rates and disease burden were analyzed using the Joinpoint Regression Program. Mortality rate increases by demographic and non-demographic factors were estimated by the decomposition method.ResultsA total of 1088 ovarian cancer as underlying cause of deaths were recorded. CMR and ASMRW were 4.82/105 and 2.32/105 person-years, respectively. The YLL was 16372.96 years, and the YLL rate was 72.46/105 person-years. The YLL rate increased only in the age group of 70-79 years (P = 0.017). The survival rates of ovarian cancer patients did not improve during the ten year period (2005-2015). The top co-morbidities were diseases of the respiratory system, digestive system, and circulatory system. The rates of ovarian cancer deaths caused by non-demographic and demographic factors increased by 21.29% (95%CI: 4.01% to 41.44%, P = 0.018) and 25.23% (95%CI: 14.64% to 36.81%, P ConclusionsPopulation ageing and all cause of death may affect ovarian cancer related deaths in Pudong, Shanghai. The high mortality and the stagnant survival rates suggest the need for more efforts in targeted prevention and treatment of this disease.</p

Table_2_Longitudinal analysis of ovarian cancer death patterns during a rapid transition period (2005-2020) in Shanghai, China: A population-based study.xlsx

ObjectivesIt is important to assess the burden of ovarian cancer related premature death so as to develop appropriate evidence-based care and improve women’s health. This study aimed to characterize the long-term trends in mortality, survival and disease burden of ovarian cancer in Shanghai, China.Materials and MethodsCo-morbidities, crude mortality rate (CMR), age-standardised mortality rate by Segi’s world standard population (ASMRW), years of life lost (YLL), and survival rates were analysed. Temporal trends for the mortality rates and disease burden were analyzed using the Joinpoint Regression Program. Mortality rate increases by demographic and non-demographic factors were estimated by the decomposition method.ResultsA total of 1088 ovarian cancer as underlying cause of deaths were recorded. CMR and ASMRW were 4.82/105 and 2.32/105 person-years, respectively. The YLL was 16372.96 years, and the YLL rate was 72.46/105 person-years. The YLL rate increased only in the age group of 70-79 years (P = 0.017). The survival rates of ovarian cancer patients did not improve during the ten year period (2005-2015). The top co-morbidities were diseases of the respiratory system, digestive system, and circulatory system. The rates of ovarian cancer deaths caused by non-demographic and demographic factors increased by 21.29% (95%CI: 4.01% to 41.44%, P = 0.018) and 25.23% (95%CI: 14.64% to 36.81%, P ConclusionsPopulation ageing and all cause of death may affect ovarian cancer related deaths in Pudong, Shanghai. The high mortality and the stagnant survival rates suggest the need for more efforts in targeted prevention and treatment of this disease.</p

Table_3_Longitudinal analysis of ovarian cancer death patterns during a rapid transition period (2005-2020) in Shanghai, China: A population-based study.xlsx

ObjectivesIt is important to assess the burden of ovarian cancer related premature death so as to develop appropriate evidence-based care and improve women’s health. This study aimed to characterize the long-term trends in mortality, survival and disease burden of ovarian cancer in Shanghai, China.Materials and MethodsCo-morbidities, crude mortality rate (CMR), age-standardised mortality rate by Segi’s world standard population (ASMRW), years of life lost (YLL), and survival rates were analysed. Temporal trends for the mortality rates and disease burden were analyzed using the Joinpoint Regression Program. Mortality rate increases by demographic and non-demographic factors were estimated by the decomposition method.ResultsA total of 1088 ovarian cancer as underlying cause of deaths were recorded. CMR and ASMRW were 4.82/105 and 2.32/105 person-years, respectively. The YLL was 16372.96 years, and the YLL rate was 72.46/105 person-years. The YLL rate increased only in the age group of 70-79 years (P = 0.017). The survival rates of ovarian cancer patients did not improve during the ten year period (2005-2015). The top co-morbidities were diseases of the respiratory system, digestive system, and circulatory system. The rates of ovarian cancer deaths caused by non-demographic and demographic factors increased by 21.29% (95%CI: 4.01% to 41.44%, P = 0.018) and 25.23% (95%CI: 14.64% to 36.81%, P ConclusionsPopulation ageing and all cause of death may affect ovarian cancer related deaths in Pudong, Shanghai. The high mortality and the stagnant survival rates suggest the need for more efforts in targeted prevention and treatment of this disease.</p

Table_4_Longitudinal analysis of ovarian cancer death patterns during a rapid transition period (2005-2020) in Shanghai, China: A population-based study.xlsx

ObjectivesIt is important to assess the burden of ovarian cancer related premature death so as to develop appropriate evidence-based care and improve women’s health. This study aimed to characterize the long-term trends in mortality, survival and disease burden of ovarian cancer in Shanghai, China.Materials and MethodsCo-morbidities, crude mortality rate (CMR), age-standardised mortality rate by Segi’s world standard population (ASMRW), years of life lost (YLL), and survival rates were analysed. Temporal trends for the mortality rates and disease burden were analyzed using the Joinpoint Regression Program. Mortality rate increases by demographic and non-demographic factors were estimated by the decomposition method.ResultsA total of 1088 ovarian cancer as underlying cause of deaths were recorded. CMR and ASMRW were 4.82/105 and 2.32/105 person-years, respectively. The YLL was 16372.96 years, and the YLL rate was 72.46/105 person-years. The YLL rate increased only in the age group of 70-79 years (P = 0.017). The survival rates of ovarian cancer patients did not improve during the ten year period (2005-2015). The top co-morbidities were diseases of the respiratory system, digestive system, and circulatory system. The rates of ovarian cancer deaths caused by non-demographic and demographic factors increased by 21.29% (95%CI: 4.01% to 41.44%, P = 0.018) and 25.23% (95%CI: 14.64% to 36.81%, P ConclusionsPopulation ageing and all cause of death may affect ovarian cancer related deaths in Pudong, Shanghai. The high mortality and the stagnant survival rates suggest the need for more efforts in targeted prevention and treatment of this disease.</p

Table_7_Longitudinal analysis of ovarian cancer death patterns during a rapid transition period (2005-2020) in Shanghai, China: A population-based study.xlsx

ObjectivesIt is important to assess the burden of ovarian cancer related premature death so as to develop appropriate evidence-based care and improve women’s health. This study aimed to characterize the long-term trends in mortality, survival and disease burden of ovarian cancer in Shanghai, China.Materials and MethodsCo-morbidities, crude mortality rate (CMR), age-standardised mortality rate by Segi’s world standard population (ASMRW), years of life lost (YLL), and survival rates were analysed. Temporal trends for the mortality rates and disease burden were analyzed using the Joinpoint Regression Program. Mortality rate increases by demographic and non-demographic factors were estimated by the decomposition method.ResultsA total of 1088 ovarian cancer as underlying cause of deaths were recorded. CMR and ASMRW were 4.82/105 and 2.32/105 person-years, respectively. The YLL was 16372.96 years, and the YLL rate was 72.46/105 person-years. The YLL rate increased only in the age group of 70-79 years (P = 0.017). The survival rates of ovarian cancer patients did not improve during the ten year period (2005-2015). The top co-morbidities were diseases of the respiratory system, digestive system, and circulatory system. The rates of ovarian cancer deaths caused by non-demographic and demographic factors increased by 21.29% (95%CI: 4.01% to 41.44%, P = 0.018) and 25.23% (95%CI: 14.64% to 36.81%, P ConclusionsPopulation ageing and all cause of death may affect ovarian cancer related deaths in Pudong, Shanghai. The high mortality and the stagnant survival rates suggest the need for more efforts in targeted prevention and treatment of this disease.</p

Table_5_Longitudinal analysis of ovarian cancer death patterns during a rapid transition period (2005-2020) in Shanghai, China: A population-based study.xlsx

ObjectivesIt is important to assess the burden of ovarian cancer related premature death so as to develop appropriate evidence-based care and improve women’s health. This study aimed to characterize the long-term trends in mortality, survival and disease burden of ovarian cancer in Shanghai, China.Materials and MethodsCo-morbidities, crude mortality rate (CMR), age-standardised mortality rate by Segi’s world standard population (ASMRW), years of life lost (YLL), and survival rates were analysed. Temporal trends for the mortality rates and disease burden were analyzed using the Joinpoint Regression Program. Mortality rate increases by demographic and non-demographic factors were estimated by the decomposition method.ResultsA total of 1088 ovarian cancer as underlying cause of deaths were recorded. CMR and ASMRW were 4.82/105 and 2.32/105 person-years, respectively. The YLL was 16372.96 years, and the YLL rate was 72.46/105 person-years. The YLL rate increased only in the age group of 70-79 years (P = 0.017). The survival rates of ovarian cancer patients did not improve during the ten year period (2005-2015). The top co-morbidities were diseases of the respiratory system, digestive system, and circulatory system. The rates of ovarian cancer deaths caused by non-demographic and demographic factors increased by 21.29% (95%CI: 4.01% to 41.44%, P = 0.018) and 25.23% (95%CI: 14.64% to 36.81%, P ConclusionsPopulation ageing and all cause of death may affect ovarian cancer related deaths in Pudong, Shanghai. The high mortality and the stagnant survival rates suggest the need for more efforts in targeted prevention and treatment of this disease.</p

Data_Sheet_1_Changes of the acute myocardial infarction-related resident deaths in a transitioning region: a real-world study involving 3.17 million people.zip

BackgroundThe impact of acute myocardial infarction (AMI) on the life span of residents in a transitioning region has not been studied in depth. Therefore, we aimed to evaluate the changes in AMI-related resident deaths in a transitioning region in China.MethodsA longitudinal, population-based study was performed to analyze the deaths with/of AMI in Pudong New Area (PNA), Shanghai from 2005 to 2021. The average annual percentage change (AAPC) of AMI in crude mortality rates (CMR), age-standardized mortality rates worldwide (ASMRW), and rates of years of life lost (YLLr) were calculated by the joinpoint regression. The impact of demographic and non-demographic factors on the mortality of residents who died with/of AMI was quantitatively analyzed by the decomposition method.ResultsIn 7,353 residents who died with AMI, 91.74% (6,746) of them were died of AMI from 2005 to 2021. In this period, the CMR and ASMRW of residents died with/of AMI were 15.23/105 and 5.17/105 person-years, the AAPC of CMR was 0.01% (95% CI: −0.71,0.72, p = 0.989) and 0.06% (95% CI: −0.71,0.84, p = 0.868), and the ASMRW decreased by 2.83% (95% CI: −3.66,−2.00, p ConclusionPreventative strategies for AMI should be applied to enhance the health management of residents aged 45–59 years or with comorbidities in the transitioning region.</p

Table_1_Influence of Demographic Factors on Long-Term Trends of Premature Mortality and Burden Due to Liver Cancer: Findings From a Population-Based Study in Shanghai, China, 1973–2019.DOCX

ObjectiveLiver cancer is one of the most common causes of cancer-related death. Understanding how demographic factors influence mortality due to liver cancer is crucial for optimizing disease-control strategies. We aimed to characterize the long-term trends in the mortality and years of life lost (YLL) of liver cancer in Shanghai, China, 1973–2019, and quantitatively analyze the contributions of demographic and non-demographic factors on the mortality of liver cancer.MethodsUsing mortality data from the Mortality Registration System of Pudong New Area, the largest district of Shanghai with a population of permanent resident of 5.68 million, during 1973–2019, we analyzed the temporal trends for the mortality rates and YLL by Joinpoint Regression Program. The difference decomposition method was employed to estimate the increasing mortality rates related to demographic and non-demographic factors.ResultsA total of 21,530 deaths from liver cancer occurred from 1973 to 2019. The crude mortality rates (CMR) and age-standardized mortality rate by Segi's world standard population (ASMRW) of liver cancer were 26.73/105 person-years and 15.72/105 person-years, respectively. The CMR, ASMRW, and YLL rates of liver cancer showed significantly decreasing trends in males, females and the total population from 1973 to 2019, whereas the upward trends in the YLL were seen in males, females and the total population (all P ConclusionsThe CMR and ASMRW of liver cancer continually decreased although YLL increased during 1973–2019 in Pudong New Area, Shanghai. The demographic factors, especially aging, might be responsible for the increase in the mortality of liver cancer. More effective prevention strategies tailored to liver cancer are needed to further reduce its disease burden in the elderly population.</p

Additional file 1 of Epidemiological variations and trends in glaucoma burden in the Belt and Road countries

Supplementary Material 1