This dataset contains statistics on deaths in South Africa in 2007. The registration of deaths in South Africa is regulated by the Births and Deaths Registration Act, 51 of 1992. The South African Department of Home Affairs (DHA) is responsible for the registration of deaths in South Africa. The data is collected with two instruments: The death register and the medical certificate in respect of death. The staff of the DHA Registrar of Deaths section fills in the former while the medical practitioner attending to the death completes the latter. Causes of death are coded by the Department of Home Affairs according to the tenth revision of the International Classification of Diseases (ICD-10) ICD-10, as required by the World Health Organization for their member countries. The data is used by the Department of Home Affairs to update the Population Register. The forms are sent to Statistics South Africa (Stats SA) for their use for statistical purposes. From the two forms sent to Stats SA, the following data items of the deceased are extracted: place of residence, place of death, date of death, month and year of registration, sex, marital status, occupation, underlying cause of death, whether or not the death was certified by a medical practitioner, and whether or not the deceased died in a health institution or nursing home. From 1991 death notifications do not require data on population group, and therefore this dataset includes death data for all population groups. This dataset excludes 2010 deaths that were not registered, and late registrations which would not have been available to Stats SA in time for the production of the dataset.
National coverage
Individuals
The data covers all deaths that occurred in 2006 and registered at the Department of Home Affairs.
Administrative records data [adm]
Other [oth]
The data is collected with notification / death register / still birth instrument.
The Mortality - Multiple Cause of Death data on CDC WONDER are county-level national mortality and population data spanning the yehttps://healthdata.gov/d/2sz9-6c59ars 1999-2006. These data are available in two separate data sets: one data set for years 1999-2004 with 3 race groups, and another data set for years 2005-2006 with 4 race groups and 3 Hispanic origin categories. Data are based on death certificates for U.S. residents. Each death certificate contains a single underlying cause of death, up to twenty additional multiple causes, and demographic data. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., state, and county), age group (including infants), race, Hispanic ethnicity (years 2005-2006 only), sex, year of death, and cause-of-death (4-digit ICD-10 code or group of codes). The data are produced by the National Center for Health Statistics.
Note: This dataset is historical only and there are not corresponding datasets for more recent time periods. For that more-recent information, please visit the Chicago Health Atlas at https://chicagohealthatlas.org. This dataset contains the cumulative number of deaths, average number of deaths annually, average annual crude and adjusted death rates with corresponding 95% confidence intervals, and average annual years of potential life lost per 100,000 residents aged 75 and younger due to selected causes of death, by Chicago community area, for the years 2006 – 2010. A ranking for each measure is also provided, with the highest value indicated with a ranking of 1. See the full description at: https://data.cityofchicago.org/api/views/6vw3-8p6f/files/CqPqfHSv8UUAoXCBjn4_tLqcQHhb36Ih4-meM-4zNzs?download=true&filename=P:\EPI\OEPHI\MATERIALS\REFERENCES\MORTALITY\Dataset_Description_06_10_PORTAL_ONLY.pdf
This statistic shows the number of deaths in Belgium from 2006 to 2020, by cause of death. In 2020, roughly 112,000 people died of natural causes, while in that same year approximately seven thousand people died from unnatural causes.
This dataset tracks the updates made on the dataset "Public Health Statistics- Selected underlying causes of death in Chicago, 2006 – 2010" as a repository for previous versions of the data and metadata.
https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/10210https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/10210
The North Carolina State Center for Health Services (SCHS) collects yearly vital statistics. The Odum Institute holds vital statistics beginning in 1968 for births, fetal deaths, deaths, birth/infant deaths, marriages and divorce. Public marriage and divorce data are available through 1999 only.This study focuses on deaths in North Carolina in 2006. Death is defined as the permanent disappearance of any evidence of life at any time after live birth. This definition excludes fetal death s. The data kept for deaths includes the age, race, marital status, and sex of the individual; date, time, cause and location of death; and mode of burial. The data is strictly numerical, there is no identifying information given about the individuals.
Age-adjustment mortality rates are rates of deaths that are computed using a statistical method to create a metric based on the true death rate so that it can be compared over time for a single population (i.e. comparing 2006-2008 to 2010-2012), as well as enable comparisons across different populations with possibly different age distributions in their populations (i.e. comparing Hispanic residents to Asian residents).
Age adjustment methods applied to Montgomery County rates are consistent with US Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS) as well as Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA).
PHS Planning and Epidemiology receives an annual data file of Montgomery County resident deaths registered with Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA).
Using SAS analytic software, MCDHHS standardizes, aggregates, and calculates age-adjusted rates for each of the leading causes of death category consistent with state and national methods and by subgroups based on age, gender, race, and ethnicity combinations. Data are released in compliance with Data Use Agreements between DHMH VSA and MCDHHS. This dataset will be updated Annually.
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.
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Abstract The aim of this study is to analyze the trend of the main causes of death of women of reproductive age (WRA) in Brazil by age group from 2006 to 2019. Data used are from the Mortality Information System (SIM) and the Brazilian Institute of Geography and Statistics (IBGE) of Brazil. The main causes of death of WRA (10 to 49 years) were divided by chapters as per the International Statistical Classification of Diseases and Related Health Problems (ICD-10). Subsequently, a temporal trend analysis was performed using polynomial regression models for the main causes of death in WRA. In Brazil, the highest mortality rates by cause by 100,000 WRA occurred due to: neoplasms (25.34), diseases of the circulatory system (20.15), external causes (18.69), infectious and parasitic diseases (8.79) and respiratory system diseases (6.37). For the analyzed period, after standardization, the mortality rate due to diseases of the circulatory and respiratory systems, and infectious and parasitic conditions showed a decreasing trend, with a significant drop of 26.6% for diseases of the circulatory system; while external causes and neoplasms showed an increasing trend from 2006 to 2012 and decreasing from 2013 onwards. Identifying the main causes of death of WRA in each age group is required to guide the planning of actions to optimize resources and obtain better results in women’s health.
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Published as part of Health in Ireland: Key Trends 2016 (Department of Health)
Age-adjustment mortality rates are rates of deaths that are computed using a statistical method to create a metric based on the true death rate so that it can be compared over time for a single population (i.e. comparing 2006-2008 to 2010-2012), as well as enable comparisons across different populations with possibly different age distributions in their populations (i.e. comparing Hispanic residents to Asian residents).
Age adjustment methods applied to Montgomery County rates are consistent with US Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS) as well as Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA).
PHS Planning and Epidemiology receives an annual data file of Montgomery County resident deaths registered with Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA).
Using SAS analytic software, MCDHHS standardizes, aggregates, and calculates age-adjusted rates for each of the leading causes of death category consistent with state and national methods and by subgroups based on age, gender, race, and ethnicity combinations. Data are released in compliance with Data Use Agreements between DHMH VSA and MCDHHS. This dataset will be updated Annually.
The CDC WONDER Mortality - Underlying Cause of Death online database is a county-level national mortality and population database spanning the years since 1979 -2008. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., Census region, Census division, state, and county), age group (including infant age groups), race (years 1979-1998: White, Black, and Other; years 1999-2008: American Indian or Alaska Native, Asian or Pacific Islander, Black or African American, and White), Hispanic origin (years 1979-1998: not available; years 1999-present: Hispanic or Latino, not Hispanic or Latino, Not Stated), gender, year of death, and underlying cause of death (years 1979-1998: 4-digit ICD-9 code and 72 cause-of-death recode; years 1999-present: 4-digit ICD-10 codes and 113 cause-of-death recode, as well as the Injury Mortality matrix classification for Intent and Mechanism), and urbanization level of residence (2006 NCHS urban-rural classification scheme for counties). The Compressed Mortality data are produced by the National Center for Health Statistics.
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*Deaths obtained from the multiple cause-of-death data for 1979–1998 are based on ICD-9 codes, and deaths beginning in 1999 are based on ICD-10 codes with available computerized literal death certificate data. Death information was also obtained from other surveillance mechanisms. Death rates expressed per 1,000,000. One death missing is both race and region; and one death is missing region.†Death rates are age-adjusted.
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
The CDC WONDER Mortality - Underlying Cause of Death online database is a county-level national mortality and population database spanning the years since 1979 -2008. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., Census region, Census division, state, and county), age group (including infant age groups), race (years 1979-1998: White, Black, and Other; years 1999-2008: American Indian or Alaska Native, Asian or Pacific Islander, Black or African American, and White), Hispanic origin (years 1979-1998: not available; years 1999-present: Hispanic or Latino, not Hispanic or Latino, Not Stated), gender, year of death, and underlying cause of death (years 1979-1998: 4-digit ICD-9 code and 72 cause-of-death recode; years 1999-present: 4-digit ICD-10 codes and 113 cause-of-death recode, as well as the Injury Mortality matrix classification for Intent and Mechanism), and urbanization level of residence (2006 NCHS urban-rural classification scheme for counties). The Compressed Mortality data are produced by the National Center for Health Statistics.
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France Deaths: Women: Respiratory Disease data was reported at 21,146.000 Person in 2015. This records an increase from the previous number of 16,793.000 Person for 2014. France Deaths: Women: Respiratory Disease data is updated yearly, averaging 16,890.000 Person from Dec 1996 (Median) to 2015, with 20 observations. The data reached an all-time high of 21,416.000 Person in 1999 and a record low of 14,307.000 Person in 2006. France Deaths: Women: Respiratory Disease data remains active status in CEIC and is reported by French National Institute for Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.G060: Health Statistics: Causes of Death.
The number of deaths in Spain experienced an upward trend over the 12-year period, presumably due to the aging population. Owing to this setup, the Spanish mortality rate went up from 8.33 in 2006 to 9.67 in 2022. However, in 2023 it registered a decline reaching a rate of 8.33. In Spain, diseases related to the circulatory system, infectious and parasitic diseases, and neoplasms (cancer) ranked as the main causes of death, each with over 46,000 cases in 2021. Circulatory system diseases 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. 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 in Spain The most common type of cancer among men is prostate cancer whereas among women the most common type is breast cancer. The most frequent new cases of cancer diagnosed among the general population was, however, lung cancer, which recorded 31,282 new cases in Spain in 2023.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Provides the age-standardized mortality rates per 100,000 population, for the three selected causes of death and all causes combined. The three selected causes of death are Circulatory System, Neoplasms and External Causes (Injury). Age standardization is a technique applied to make rates comparable across groups with different age distributions. A simple rate is defined as the number of people with a particular condition divided by the whole population. An age-standardized rate is defined as the number of people with a condition divided by the population within each age group. Standardizing (adjusting) the rate across age groups allows a more accurate comparison between populations that have different age structures. Age standardization is typically done when comparing rates across time periods, different geographic areas, and or population sub-groups (e.g. ethnic group). This indicator dataset contains information at both Local Geographic Area (for example, Lacombe, Red Deer - North, Calgary - West Bow, etc.) and Alberta levels. Local geographic area refers to 132 geographic areas created by Alberta Health (AH) and Alberta Health Services (AHS) based on census boundaries. This table is the part of "Alberta Health Primary Health Care - Community Profiles" report published March 2015
The Deaths in Custody Reporting Program (DCRP) is an annual data collection conducted by the Bureau of Justice Statistics (BJS). The DCRP began in 2000 under the Death in Custody Reporting Act of 2000 (P.L. 106-297). It is the only national statistical collection that obtains detailed information about deaths in adult correctional facilities. The DCRP collects data on persons dying in state prisons, local jails and in the process of arrest. Each collection is a separate subcollection, but each is under the umbrella of the DCRP collection. The DCRP collects inmate death records from each of the nation's 50 state prison systems and approximately 2,800 local jail jurisdictions. In addition, this program collects records of all deaths occurring during the process of arrest. Data are collected directly from state and local law enforcement agencies. Death records include information on decedent personal characteristics (age, race or Hispanic origin, and sex), decedent criminal background (legal status, offense type, and time served), and the death itself (date, time, location, and cause of death, as well as information on the autopsy and medical treatment provided for any illness or disease). This data collection represents a single year of DCRP Jails data. The variable names and coding, while similar to other years, have not been standardized across years. The concatenated multi-year versions of the DCRP Jails population data have been edited to correct outliers and other data anomalies. Researchers are encouraged to use the concatenated multi-year data for final jail population data.
This study aimed to analyze changing trends in child injury deaths from 2006 to 2016 and to provide basic data for initiatives to help prevent child injury deaths through improvements in social systems and education. Specific causes of death were analyzed using micro-data of the death statistics of Korea from 2006 to 2016, which were made available by Statistics Korea. Types and place of death were classified according to the KCD-7 (Korean Standard Classification of Diseases and Causes of Death). The data were compared to those of other Organization for Economic Co-operation and Development countries. Changing trends were presented. The number of child deaths by injury was 270 in 2016. The death rate was 8.1 per 100,000 population in 2006, while it was 3.9 in 2016. The death rate of boys was 1.7 times greater than that of girls. Unintentional injury deaths comprised 72.6% of all child injury deaths in 2016, while intentional injury deaths comprised 27.4%. The first leading cause of unintentional injury deaths in infants (less than 1-year-old) was suffocation, while that of children aged 1-14 years was transport accidents. The second leading cause of death in infants was transport accidents, that of children aged 1-4 was falling, and that of children aged 5-14 was drowning. Pedestrian accidents comprised 43.7% of the transport accidents from 2014 to 2016. To prevent child injury deaths by both unintentional and intentional causes, nation-wide policy measures and more specific interventions according to cause are required.
This dataset describes injury mortality in the United States beginning in 1999. Two concepts are included in the circumstances of an injury death: intent of injury and mechanism of injury. Intent of injury describes whether the injury was inflicted purposefully (intentional injury) and, if purposeful, whether the injury was self-inflicted (suicide or self-harm) or inflicted by another person (homicide). Injuries that were not purposefully inflicted are considered unintentional (accidental) injuries. Mechanism of injury describes the source of the energy transfer that resulted in physical or physiological harm to the body. Examples of mechanisms of injury include falls, motor vehicle traffic crashes, burns, poisonings, and drownings (1,2). Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia. Age-adjusted death rates (per 100,000 standard population) are based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2015 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for non-census years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Causes of injury death are classified by the International Classification of Diseases, Tenth Revision (ICD–10). Categories of injury intent and injury mechanism generally follow the categories in the external-cause-of-injury mortality matrix (1,2). Cause-of-death statistics are based on the underlying cause of death. SOURCES CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics. ICD–10: External cause of injury mortality matrix. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Murphy SL, Xu JQ, Kochanek KD, Curtin SC, and Arias E. Deaths: Final data for 2015. National vital statistics reports; vol 66. no. 6. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_06.pdf. Miniño AM, Anderson RN, Fingerhut LA, Boudreault MA, Warner M. Deaths: Injuries, 2002. National vital statistics reports; vol 54 no 10. Hyattsville, MD: National Center for Health Statistics. 2006.
This dataset contains statistics on deaths in South Africa in 2007. The registration of deaths in South Africa is regulated by the Births and Deaths Registration Act, 51 of 1992. The South African Department of Home Affairs (DHA) is responsible for the registration of deaths in South Africa. The data is collected with two instruments: The death register and the medical certificate in respect of death. The staff of the DHA Registrar of Deaths section fills in the former while the medical practitioner attending to the death completes the latter. Causes of death are coded by the Department of Home Affairs according to the tenth revision of the International Classification of Diseases (ICD-10) ICD-10, as required by the World Health Organization for their member countries. The data is used by the Department of Home Affairs to update the Population Register. The forms are sent to Statistics South Africa (Stats SA) for their use for statistical purposes. From the two forms sent to Stats SA, the following data items of the deceased are extracted: place of residence, place of death, date of death, month and year of registration, sex, marital status, occupation, underlying cause of death, whether or not the death was certified by a medical practitioner, and whether or not the deceased died in a health institution or nursing home. From 1991 death notifications do not require data on population group, and therefore this dataset includes death data for all population groups. This dataset excludes 2010 deaths that were not registered, and late registrations which would not have been available to Stats SA in time for the production of the dataset.
National coverage
Individuals
The data covers all deaths that occurred in 2006 and registered at the Department of Home Affairs.
Administrative records data [adm]
Other [oth]
The data is collected with notification / death register / still birth instrument.