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This publication reports on newly diagnosed cancers registered in England in addition to cancer deaths registered in England during 2020. It includes this summary report showing key findings, spreadsheet tables with more detailed estimates, and a methodology document.
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Cuba CU: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 17.600 % in 2021. This records an increase from the previous number of 16.900 % for 2020. Cuba CU: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 17.050 % from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 18.300 % in 2001 and a record low of 16.200 % in 2012. Cuba CU: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cuba – Table CU.World Bank.WDI: Social: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.4.1 [https://unstats.un.org/sdgs/metadata/].
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COVID-19 Cases and Deaths by Race/Ethnicity
COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.
The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.
The age-adjusted rates are directly standardized using the 2018 ASRH Connecticut population estimate denominators (available here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Annual-State--County-Population-with-Demographics).
Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age-adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.
This dataset will be updated on a daily basis. Data are subject to future revision as reporting changes.
Starting in July 2020, this dataset will be updated every weekday.
Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.
A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differs from the timestamp in DPH's daily PDF reports.
Thanks to catalog.data.gov.
Cancer was responsible for around *** deaths per 100,000 population in the United States in 2023. The death rate for cancer has steadily decreased since the 1990’s, but cancer still remains the second leading cause of death in the United States. The deadliest type of cancer for both men and women is cancer of the lung and bronchus which will account for an estimated ****** deaths among men alone in 2025. Probability of surviving Survival rates for cancer vary significantly depending on the type of cancer. The cancers with the highest rates of survival include cancers of the thyroid, prostate, and testis, with five-year survival rates as high as ** percent for thyroid cancer. The cancers with the lowest five-year survival rates include cancers of the pancreas, liver, and esophagus. Risk factors It is difficult to determine why one person develops cancer while another does not, but certain risk factors have been shown to increase a person’s chance of developing cancer. For example, cigarette smoking has been proven to increase the risk of developing various cancers. In fact, around ** percent of cancers of the lung, bronchus and trachea among adults aged 30 years and older can be attributed to cigarette smoking. Other modifiable risk factors for cancer include being obese, drinking alcohol, and sun exposure.
Number and rate of new cancer cases diagnosed annually from 1992 to the most recent diagnosis year available. Included are all invasive cancers and in situ bladder cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.
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Analysis of ‘COVID-19 Cases and Deaths by Race/Ethnicity’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3fdc6593-c708-4a6a-8073-5ca862caa279 on 27 January 2022.
--- Dataset description provided by original source is as follows ---
COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.
The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.
The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.
Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf
Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.
Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More infor
--- Original source retains full ownership of the source dataset ---
Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.
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Directly age and sex standardised mortality rate from Cancer for people aged under 75 in the respective calendar year per 100,000 registered patients March 2020: In addition to the changes in March 2019, the indicator production process has been fully automated. As a result there are two changes to this publication: 1) Data in this file are published from 2016 only; all data is based on the most recent methodology and comparable across years. For the historic time series of this indicator please refer to the zip files in the March 2019 publication: https://digital.nhs.uk/data-and-information/publications/clinical-indicators/ccg-outcomes-indicator-set/archive/ccg-outcomes-indicator-set---march-2019 2) Data are run against the CCG configuration at the time of processing; the 2016 and 2017 data points have been restated based on the new automated process. As of the March 2019 release the processing of the Primary Care Mortality Database (PCMD) and the standard population used to calculate the indicator for new data periods changed; this file now contains only those data periods processed under the new method. For the historic time series of this indicator please refer to the zip files in the March 2019 publication referenced above. Legacy unique identifier: P01808
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Austria AT: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 9.900 % in 2021. This records a decrease from the previous number of 10.100 % for 2020. Austria AT: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 12.150 % from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 15.300 % in 2000 and a record low of 9.900 % in 2021. Austria AT: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Austria – Table AT.World Bank.WDI: Social: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.4.1 [https://unstats.un.org/sdgs/metadata/].
Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical
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Germany DE: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 11.600 % in 2021. This records a decrease from the previous number of 11.700 % for 2020. Germany DE: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 12.900 % from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 16.100 % in 2000 and a record low of 11.600 % in 2021. Germany DE: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.4.1 [https://unstats.un.org/sdgs/metadata/].
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PurposeThis study aimed to describe the demographic and clinical characteristics of cancer patients with COVID-19, exploring factors associated with adverse outcomes.Patients and methodsThis retrospective cohort study methodically extracted and curated data from electronic medical records (EMRs) of numerous healthcare institutions on cancer patients diagnosed with a confirmed SARS-CoV-2 infection between May 2020 and August 2021, to identify risk factors linked to extended hospitalization and mortality. The retrieved information encompassed the patients’ demographic and clinical characteristics, including the incidence of prolonged hospitalization, acute complications, and COVID-19-related mortality.ResultsA total of 1446 cancer patients with COVID-19 were identified (mean [Standard deviation] age, 59.2 [14.3] years). Most patients were female (913 [63.1%]), non-white (646 [44.7%]), with non-metastatic (818 [56.6%]) solid tumors (1318 [91.1%]), and undergoing chemotherapy (647 [44.7%]). The rate of extended hospitalization due to COVID-19 was 46% (n = 665), which was significantly impacted by age (p = 0.012), sex (p = 0.003), race and ethnicity (p = 0.049), the presence of two or more comorbidities (p = 0.006), hematologic malignancies (p = 0.013), metastatic disease (p = 0.002), and a performance status ≥ 2 (p = 0.001). The COVID-19-related mortality rate was 18.9% (n = 273), and metastatic disease (
Abstract Background: This study analyzed the causes of death in the Korean population in 2020. Methods: Cause-of-death data for 2020 from Statistics Korea were examined based on the Korean Standard Classification of Diseases and Causes of Death, 7th revision and the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Results: In total, 304,948 deaths occurred, reflecting an increase of 9,838 (3.3%) from 2019. The crude death rate (the number of deaths per 100,000 people) was 593.9, corresponding to an increase of 19.0 (3.3%) from 2019. The 10 leading causes of death, in descending order, were malignant neoplasms, heart diseases, pneumonia, cerebrovascular diseases, intentional self-harm, diabetes mellitus, Alzheimer’s disease, liver diseases, hypertensive diseases, and sepsis. Cancer accounted for 27.0% of deaths. Within the category of malignant neoplasms, the top 5 leading organs of involvement were the lung, liver, colon, stomach, and pancreas. Sepsis was included in the 10 leading causes of death for the first time. Mortality due to pneumonia decreased to 43.3 (per 100,000 people) from 45.1 in 2019. The number of deaths due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was 950, of which 54.5% were in people aged 80 or older. Conclusion: These changes reflect the continuing increase in deaths due to diseases of old age, including sepsis. The decrease in deaths due to pneumonia may have been due to protective measures against SARS-CoV-2. With the concomitant decrease in fertility, 2020 became the first year in which Korea’s natural total population decreased.
According to the data, the number of individuals who died from a tumor in Italy decreased constantly between 2006 and 2021. Indeed, the rate of deaths due to cancer among Italians dropped from **** deaths per 10,000 inhabitants in 2006 to **** in 2021. Moreover, in Italy, the cancer mortality rates among women and men are lower than the ones observed in the European Union. Women’s cancer Breast cancer is the most common and deadliest type of cancer among women in Italy. As a matter of fact, around *** thousand women in Italy were living with a diagnosis of breast cancer in 2023, and over **** thousand died from it in 2022. Colorectal and lung cancer follow in the list of the most frequently diagnosed cancers among females in Italy. Men’s cancer The most frequently diagnosed cancer among males in Italy is prostate cancer. Lung cancer, which is also the deadliest type of cancer for men, follows. As of 2023, the number of men living with a diagnosis of prostate cancer in Italy amounted to *** thousand, while the number of new cases of prostate cancer during that year was estimated at **** thousand.
In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.
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Directly age standardised mortality rate from breast cancer for females in the respective time period per 100,000 registered female patients. March 2020: In addition to the changes in March 2019, the indicator production process has been fully automated. As a result there are two changes to this publication: 1) Data in this file are published for 2016-2018 only; all data is based on the most recent methodology. For the historic time series of this indicator please refer to the zip files in the June 2018 publication: https://digital.nhs.uk/data-and-information/publications/clinical-indicators/ccg-outcomes-indicator-set/archive/ccg-outcomes-indicator-set---june-2018 Please note, neither version of the file contains data for 2015-2017; changes in the data processing meant the 2015 data was not comparable to the 2016 and 2017 data processed under the new method. 2) Data are run against CCGs which were in existence at the time of processing. As of the March 2019 release the processing of the Primary Care Mortality Database (PCMD) and the standard population used to calculate the indicator for new data periods changed; this file now contains only those data periods processed under the new method. For the historic time series of this indicator please refer to the June 2018 publication referenced above. Legacy unique identifier: P01819
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Afghanistan Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 32.700 % in 2021. This records a decrease from the previous number of 34.800 % for 2020. Afghanistan Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 37.400 % from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 43.500 % in 2001 and a record low of 32.700 % in 2021. Afghanistan Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Social: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.4.1 [https://unstats.un.org/sdgs/metadata/].
According to the latest reports, more people died in Spain than were being born, with figures reaching over 439,000 deaths versus 322,000 newborns. The number of deaths experienced an upward trend over the 11-year period, presumably due to Spain’s aging population and in more recent years, the spread of COVID-19. Circulatory system diseases and cancer ranked as the most common causes of death in SpainThe cause of death can vary significantly across the globe and depends highly on economic development, presence of a competent healthcare system and one’s choices in lifestyle. In Spain, diseases related to the circulatory system and certain infectious and parasitic diseases ranked as the main causes of death, amounting to nearly 50,000 cases in the 2022. The annual number of deaths as a result of a disease of the circulatory system maintained steadily over the most recent years, with the illness being more common among female than male individuals. Cancer numbers in SpainThe number of deaths as a result of a cancer grew steadily in Spain for both women and men, although the disease seems to affect more male individuals than female, with about 68,000 cases occurring in men and 45,000 in women according to the most recent data. Furthermore, of the total 276,260 new cases of cancer in Spain in 2023, roughly 158,500 were diagnosed among male individuals.
This dataset presents the footprint of cancer mortality statistics in Australia for all cancers combined and the 6 top cancer groupings (colorectal, leukaemia, lung, lymphoma, melanoma of the skin …Show full descriptionThis dataset presents the footprint of cancer mortality statistics in Australia for all cancers combined and the 6 top cancer groupings (colorectal, leukaemia, lung, lymphoma, melanoma of the skin and pancreas) and their respective ICD-10 codes. The data spans the years 2006-2010 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS). Mortality data refer to the number of deaths due to cancer in a given time period. Cancer deaths data are sourced from the Australian Institute of Health and Welfare (AIHW) 2013 National Mortality Database (NMD). For further information about this dataset, please visit: Australian Institute of Health and Welfare - Cancer Incidence and Mortality Across Regions (CIMAR) books. Australian Institute of Health and Welfare - 2013 National Mortality Database. Please note: AURIN has spatially enabled the original data using the Department of Health - PHN Areas. Due to changes in geographic classifications over time, long-term trends are not available. Values assigned to "n.p." in the original data have been removed from the data. The Australian and jurisdictional totals include people who could not be assigned a PHN. The number of people who could not be assigned a PHN is less than 1% of the total. The Australian total also includes residents of Other Territories (Cocos (Keeling) Islands, Christmas Island and Jervis Bay Territory). Cause of Death Unit Record File data are provided to the AIHW by the Registries of Births, Deaths and Marriages and the National Coronial Information System (managed by the Victorian Department of Justice) and include cause of death coded by the Australian Bureau of Statistics (ABS). The data are maintained by the AIHW in the NMD. Year refers to year of occurrence of death for years up to and including 2012, and year of registration of death for 2013. Deaths registered in 2011 and earlier are based on the final version of cause of death data; deaths registered in 2012 and 2013 are based on revised and preliminary versions, respectively and are subject to further revision by the ABS. Cause of death information are based on underlying cause of death and are classified according to the International Classification of Diseases and Related Health Problems (ICD). Deaths registered in 1997 onwards are classified according to the 10th revision (ICD-10). Colorectal deaths presented are underestimates. For further information, refer to "Complexities in the measurement of bowel cancer in Australia" in Causes of Death, Australia (ABS cat. no. 3303.0). Copyright attribution: Government of the Commonwealth of Australia - Australian Institute of Health and Welfare, (2016): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 3.0 Australia (CC BY 3.0 AU)
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Slovenia SI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 11.600 % in 2021. This records an increase from the previous number of 11.000 % for 2020. Slovenia SI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 13.400 % from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 18.500 % in 2000 and a record low of 11.000 % in 2020. Slovenia SI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Slovenia – Table SI.World Bank.WDI: Social: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.4.1 [https://unstats.un.org/sdgs/metadata/].
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This publication reports on newly diagnosed cancers registered in England in addition to cancer deaths registered in England during 2020. It includes this summary report showing key findings, spreadsheet tables with more detailed estimates, and a methodology document.