This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex.

Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 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 noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below).

Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm.

SOURCES

CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); 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

1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm.

2. 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.

3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf.

4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf.

5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

In 2023, the age-specific death rate for men aged 90 or over in England and Wales was 248.1 per one thousand population, and 215.1 for women. Except for infants that were under the age of one, younger age groups had the lowest death rate, with the death rate getting progressively higher in older age groups.

Effective June 28, 2023, this dataset will no longer be updated. Similar data are accessible from CDC WONDER (https://wonder.cdc.gov/mcd-icd10-provisional.html). Cumulative deaths involving COVID-19 reported to NCHS by sex and age in years, in the United States.

The age-specific mortality rate of anaemias at all ages in Canada amounted to *** in 2023. Between 2000 and 2023, the age-specific mortality rate rose by ***, though the increase followed an uneven trajectory rather than a consistent upward trend.

The deaths across India in 2020, majority of deaths among males occurred in the age group of 85 years and older. During that time period, the death rate of over ** per thousand people was reported among less than one year old males in the country.

The spread of coronavirus (COVID-19) in Italy has hit every age group uniformly and claimed over 190 thousand lives since it entered the country. As the chart shows, however, mortality rate appeared to be much higher for the elderly patient. In fact, for people between 80 and 89 years of age, the fatality rate was 6.1 percent. For patients older than 90 years, this figure increased to 12.1 percent. On the other hand, the death rate for individuals under 60 years of age was well below 0.5 percent. Overall, the mortality rate of coronavirus in Italy was 0.7 percent.

Italy's death toll was one of the most tragic in the world. In the last months, however, the country started to see the end of this terrible situation: as of May 2023, roughly 84.7 percent of the total Italian population was fully vaccinated.

Since the first case was detected at the end of January in Italy, coronavirus has been spreading fast. As of May, 2023, the authorities reported over 25.8 million cases in the country. The area mostly hit by the virus is the North, in particular the region of Lombardy.

For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

The deaths across India in 2020, majority of deaths in urban regions occurred in the age group of 85 years and older. During that time period, the death rate of over ** was reported among less than one year old males in the urban areas of the country.

Graph and download economic data for Age-Adjusted Premature Death Rate for Manatee County, FL (CDC20N2UAA012081) from 1999 to 2020 about Manatee County, FL; North Port; premature; death; FL; rate; and USA.

Rate of deaths by age/gender (per 100,000 population) for people killed in crashes involving a driver with BAC =>0.08%, 2012, 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File. Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

There is no description available for this dataset.

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated 8/14/2024. Rate of deaths per 100,000 population by selected underlying causes of death among Maryland residents (1992-2017).

In 2023, the death rate for anemia among those aged 80 to 84 years in the United States was **** per 100,000 population. Anemia is a condition in which a person does not have enough healthy red blood cells. Red blood cells carry oxygen throughout the body, so a lack of these cells can cause symptoms such as fatigue, dizziness, headache, and shortness of breath. If left untreated, and it is severe enough, anemia can lead to death as organs do not work properly without enough oxygen. This statistic shows the death rate for anemia in the United States in 2023, by age.

This statistic displays the median age at death of indigenous and non-indigenous men in Australia in 2016, by state. That year, the median age for indigenous men in New South Wales was 58.4 years, compared to 79.3 years for non-indigenous men.

Graph and download economic data for Age-Adjusted Premature Death Rate for Hamilton County, IN (CDC20N2UAA018057) from 1999 to 2020 about Hamilton County, IN; Indianapolis; premature; death; IN; rate; and USA.

Graph and download economic data for Age-Adjusted Premature Death Rate for Bronx County, NY (CDC20N2UAA036005) from 1999 to 2020 about Bronx County, NY; premature; death; New York; NY; rate; and USA.

Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov. Deaths involving COVID-19, influenza, and pneumonia reported to NCHS by jurisdiction of occurrence, place of death, and age group.

Male newborns in Germany had an average further life expectancy of 78.2 years, while for female newborns this was 83 years. German men aged 100 were expected to live another 1.7 years.

Graph and download economic data for Age-Adjusted Premature Death Rate for Lake County, SD (CDC20N2UAA046079) from 1999 to 2020 about Lake County, SD; premature; death; SD; rate; and USA.

Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

40-lifetables.csv

Life table statistics 2015 through 2021 by sex, region and quarter with uncertainty quantiles based on Poisson replication of death counts. Actual life tables and expected life tables (under the assumption of pre-COVID mortality trend continuation) are provided.

30-lt_input.csv

Life table input data.

• `id`: unique row identifier
• `region_iso`: iso3166-2 region codes
• `sex`: Male, Female, Total
• `year`: iso year
• `age_start`: start of age group
• `age_width`: width of age group, Inf for age_start 100, otherwise 1
• `nweeks_year`: number of weeks in that year, 52 or 53
• `death_total`: number of deaths by any cause
• `population_py`: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)
• `death_total_nweeksmiss`: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)
• `death_total_minnageraw`: the minimum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_maxnageraw`: the maximum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_minopenageraw`: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_maxopenageraw`: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_source`: source of the all-cause death data

• `death_total_prop_q1`: observed proportion of deaths in first quarter of year

• `death_total_prop_q2`: observed proportion of deaths in second quarter of year

• `death_total_prop_q3`: observed proportion of deaths in third quarter of year

• `death_total_prop_q4`: observed proportion of deaths in fourth quarter of year

• `death_expected_prop_q1`: expected proportion of deaths in first quarter of year

• `death_expected_prop_q2`: expected proportion of deaths in second quarter of year

• `death_expected_prop_q3`: expected proportion of deaths in third quarter of year

• `death_expected_prop_q4`: expected proportion of deaths in fourth quarter of year

• `population_midyear`: midyear population (July 1st)
• `population_source`: source of the population count/exposure data
• `death_covid`: number of deaths due to covid
• `death_covid_date`: number of deaths due to covid as of
• `death_covid_nageraw`: the number of age groups in the covid input data
• `ex_wpp_estimate`: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year
• `ex_hmd_estimate`: life expectancy estimates from the Human Mortality Database
• `nmx_hmd_estimate`: death rate estimates from the Human Mortality Database
• `nmx_cntfc`: Lee-Carter death rate projections based on trend in the years 2015 through 2019

Deaths

• source:
  • STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)
  • ONS for GB-EAW pre 2020
  • CDC for US pre 2020
• STMF:
  • harmonized to single ages via pclm
  • pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110
  • smoothing parameters estimated via BIC grid search seperately for every pclm iteration
  • last age group set to [110,111)
  • ages 100:110+ are then summed into 100+ to be consistent with mid-year population information
  • deaths in unknown weeks are considered; deaths in unknown ages are not considered
• ONS:
  • data already in single ages
  • ages 100:105+ are summed into 100+ to be consistent with mid-year population information
  • PCLM smoothing applied to for consistency reasons
• CDC:
  • The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data

Population

• source:
  • for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019
  • for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100
• mid-year population
  • mid-year population translated into exposures:
    • if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates
    • if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364\*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.

COVID deaths

• source: COVerAGE-DB (https://osf.io/mpwjq/)
• the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total

External life expectancy estimates

• source:
  • World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019
  • Human Mortality Database (https://mortality.org/), single year and age tables