Heart disease is currently the leading cause of death in the United States. In 2022, COVID-19 was the fourth leading cause of death in the United States, accounting for almost six percent of all deaths that year. The leading causes of death worldwide are similar to those in the United States. However, diarrheal diseases and neonatal conditions are major causes of death worldwide, but are not among the leading causes in the United States. Instead, accidents and chronic liver disease have a larger impact in the United States.

Racial differences

In the United States, there exist slight differences in leading causes of death depending on race and ethnicity. For example, assault, or homicide, accounts for around three percent of all deaths among the Black population but is not even among the leading causes of death for other races and ethnicities. However, heart disease and cancer are still the leading causes of death for all races and ethnicities.

Leading causes of death among men vs women

Similarly, there are also differences in the leading causes of death in the U.S. between men and women. For example, among men, intentional self-harm accounts for around two percent of all deaths but is not among the leading causes of death among women. On the other hand, influenza and pneumonia account for more deaths among women than men.

This dataset presents the age-adjusted death rates for the 10 leading causes of death in the United States beginning in 1999. Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia using demographic and medical characteristics. Age-adjusted death rates (per 100,000 population) are based on the 2000 U.S. standard population. Populations used for computing death rates after 2010 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 death classified by the International Classification of Diseases, Tenth Revision (ICD–10) are ranked according to the number of deaths assigned to rankable causes. 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. 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.

From 2018 to 2023, heart disease and cancer accounted for the highest share of deaths in the United States. In 2020 and 2021, COVID-19 became the third leading cause of death, accounting for around 12 percent of all deaths in 2021. However, by 2023, COVID-19 was responsible for only 1.6 percent of deaths, making it the tenth leading cause of death. This statistic shows the distribution of the 10 leading causes of death in the United States from 2018 to 2023.

This dataset contains information on the number of deaths and age-adjusted death rates for the five leading causes of death in 1900, 1950, and 2000. 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). 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 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. 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. 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. 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. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

The leading causes of death by sex and ethnicity in New York City in since 2007. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City. Report last ran: 09/24/2019 Rates based on small numbers (RSE > 30) as well as aggregate counts less than 5 have been suppressed in downloaded data Source: Bureau of Vital Statistics and New York City Department of Health and Mental Hygiene

Heart disease and cancer remained the leading causes of death in the United States from 2018 to 2023. However, there have been slight changes in the 10 leading causes of death in the U.S. from 2018 to 2023. Most notable is that COVID-19 became the third leading cause of death in 2020 and 2021, but by 2023 it was the tenth leading cause. This statistic shows the rates of the 10 leading causes of death in the United States from 2018 to 2023.

According to the NCHS classification, the leading causes of death are provided for the total Santa Clara County population and by race/ethnicity and sex. Data are for Santa Clara County residents.Data trends are from year 2007 to 2016. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017.METADATA:Notes (String): Lists table title, sourceYear (Numeric): Year of death Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, and race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only).Causes of death (String): Cause-of-death were coded using the Tenth Revision of the International Classification of Diseases codes (ICD-10). Causes are classified according to the Centers for Disease Control and Prevention, National Center for Health Statistics, Leading causes of death methodology.Count (Numeric): Number of deaths per cause of deathPercentage (Numeric): Percentage of deaths per cause of death out of total deaths in that year. Percentage value less than 1 is replaced by '<1'.

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.

MMWR Surveillance Summary 66 (No. SS-1):1-8 found that nonmetropolitan areas have significant numbers of potentially excess deaths from the five leading causes of death. These figures accompany this report by presenting information on potentially excess deaths in nonmetropolitan and metropolitan areas at the state level. They also add additional years of data and options for selecting different age ranges and benchmarks. Potentially excess deaths are defined in MMWR Surveillance Summary 66(No. SS-1):1-8 as deaths that exceed the numbers that would be expected if the death rates of states with the lowest rates (benchmarks) occurred across all states. They are calculated by subtracting expected deaths for specific benchmarks from observed deaths. Not all potentially excess deaths can be prevented; some areas might have characteristics that predispose them to higher rates of death. However, many potentially excess deaths might represent deaths that could be prevented through improved public health programs that support healthier behaviors and neighborhoods or better access to health care services. Mortality data for U.S. residents come from the National Vital Statistics System. Estimates based on fewer than 10 observed deaths are not shown and shaded yellow on the map. Underlying cause of death is based on the International Classification of Diseases, 10th Revision (ICD-10) Heart disease (I00-I09, I11, I13, and I20–I51) Cancer (C00–C97) Unintentional injury (V01–X59 and Y85–Y86) Chronic lower respiratory disease (J40–J47) Stroke (I60–I69) Locality (nonmetropolitan vs. metropolitan) is based on the Office of Management and Budget’s 2013 county-based classification scheme. Benchmarks are based on the three states with the lowest age and cause-specific mortality rates. Potentially excess deaths for each state are calculated by subtracting deaths at the benchmark rates (expected deaths) from observed deaths. Users can explore three benchmarks: “2010 Fixed” is a fixed benchmark based on the best performing States in 2010. “2005 Fixed” is a fixed benchmark based on the best performing States in 2005. “Floating” is based on the best performing States in each year so change from year to year. 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 Moy E, Garcia MC, Bastian B, Rossen LM, Ingram DD, Faul M, Massetti GM, Thomas CC, Hong Y, Yoon PW, Iademarco MF. Leading Causes of Death in Nonmetropolitan and Metropolitan Areas – United States, 1999-2014. MMWR Surveillance Summary 2017; 66(No. SS-1):1-8. Garcia MC, Faul M, Massetti G, Thomas CC, Hong Y, Bauer UE, Iademarco MF. Reducing Potentially Excess Deaths from the Five Leading Causes of Death in the Rural United States. MMWR Surveillance Summary 2017; 66(No. SS-2):1–7.

This dataset of U.S. mortality trends since 1900 highlights trends in age-adjusted death rates for five selected major causes of death.

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).

Revisions to the International Classification of Diseases (ICD) over time may result in discontinuities in cause-of-death trends.

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 2022, the most significant cause of death among men in the United States was heart disease, which contributed to **** percent of deaths. COVID-19 was the third leading cause of death among U.S. men in both 2020 and 2021, and the fourth leading cause in 2022. This statistic shows the distribution of the ** leading causes of death among men in the United States from 2020 to 2022.

A ranking of the 30 most common causes of death each year in Alberta, by ranking and total number of deaths.

The leading causes of death in the United States are by far cardiovascular diseases and cancer. However, the death rates from these diseases, as well as other leading causes of death, have decreased over the past few decades. The one major exception are deaths caused by Alzheimer’s disease, which have increased significantly. Cardiovascular disease deaths Although cardiovascular diseases are currently the leading cause of death in the United States, the death rate of these diseases has dropped significantly. In the year 1950, there were around *** deaths per 100,000 population due to cardiovascular diseases. In the year 2022, this number was ***** per 100,000 population. Risk factors for heart disease include smoking, poor diet, diabetes, obesity, stress, family history, and age. Alzheimer’s disease deaths While the death rates for cardiovascular disease, cancer, diabetes, and chronic lower respiratory diseases have all decreased, the death rate for Alzheimer’s disease has increased. In fact, from the year 2000 to 2021, the death rate from Alzheimer’s disease rose an astonishing *** percent. This increase is in part due to a growing aging population.

The leading causes of death among children aged 5 to 9 years in the United States in 2022 were unintentional injuries, cancer, and congenital malformations, deformations and chromosomal abnormalities. At that time, unintentional injuries accounted for around 28 percent of all deaths among this age group. Child abuse in the U.S. Sadly, assault or homicide, was the fourth leading cause of death among those aged 5 to 9 years in the United States in 2022, accounting for around 9.4 percent of all deaths. That year, there were around 113,259 cases of child abuse in the U.S. among children aged 6 to 9 years and 129,846 cases among children aged 2 to 5 years. In 2022, there were around 5.36 child deaths per day in the United States due to abuse and neglect. Suicide among children Assault or homicide was also among the top five leading causes of death among children aged 10 to 14 years, but perhaps even more troubling is that suicide is the second leading cause of death among this age group. As with younger children, unintentional injuries are the leading cause of death among those aged 10 to 14 years, however, suicide accounts for around 13 percent of all deaths among this age group. Comparatively, suicide is not among the ten-leading causes of death among children from the age 1 to 9 years.

This statistic shows the percentage changes in selected causes of death due to diseases in the United States, between 2000 and 2022. The number of deaths caused by prostate cancer increased by 7.4 percent during this period. Changes in selected causes of deathThere has been a decrease in the rate of death caused by many diseases, including stroke and heart disease. However, the mortality rate due to Alzheimer’s disease increased by 142 percent from 2000 to 2022. Alzheimer’s disease caused 27.7 deaths per 100,000 population in 2023, making it the sixth leading cause of death in the United States. Mortality rates due to different diseases vary by different factors, including race and ethnicity. For example, cancer is the leading cause of death among Asians and Pacific Islanders in the United States, accounting for 22 percent of total deaths among this population, while heart disease is the leading cause of death among the white population. Ischemic heart disease is the leading cause of death worldwide, accounting for around nine million deaths in 2021. In the early 1900's, the mortality rate was primarily concentrated among people of younger ages, but increasingly, this has shifted to older population groups. In recent years, decreased mortality rates are often linked to improved medical care, such as new developments in medical technologies. Shifts in lifestyle habits such as decreased smoking rates and healthier diets may also attribute to lower mortality rates.

This dataset contains counts of deaths for California as a whole based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

Every year the CDC releases the country’s most detailed report on death in the United States under the National Vital Statistics Systems. This mortality dataset is a record of every death in the country for 2005 through 2015, including detailed information about causes of death and the demographic background of the deceased.

It's been said that "statistics are human beings with the tears wiped off." This is especially true with this dataset. Each death record represents somebody's loved one, often connected with a lifetime of memories and sometimes tragically too short.

Putting the sensitive nature of the topic aside, analyzing mortality data is essential to understanding the complex circumstances of death across the country. The US Government uses this data to determine life expectancy and understand how death in the U.S. differs from the rest of the world. Whether you’re looking for macro trends or analyzing unique circumstances, we challenge you to use this dataset to find your own answers to one of life’s great mysteries.

Overview

This dataset is a collection of CSV files each containing one year's worth of data and paired JSON files containing the code mappings, plus an ICD 10 code set. The CSVs were reformatted from their original fixed-width file formats using information extracted from the CDC's PDF manuals using this script. Please note that this process may have introduced errors as the text extracted from the pdf is not a perfect match. If you have any questions or find errors in the preparation process, please leave a note in the forums. We hope to publish additional years of data using this method soon.

A more detailed overview of the data can be found here. You'll find that the fields are consistent within this time window, but some of data codes change every few years. For example, the 113_cause_recode entry 069 only covers ICD codes (I10,I12) in 2005, but by 2015 it covers (I10,I12,I15). When I post data from years prior to 2005, expect some of the fields themselves to change as well.

All data comes from the CDC’s National Vital Statistics Systems, with the exception of the Icd10Code, which are sourced from the World Health Organization.

Project ideas

• The CDC's mortality data was the basis of a widely publicized paper, by Anne Case and Nobel prize winner Angus Deaton, arguing that middle-aged whites are dying at elevated rates. One of the criticisms against the paper is that it failed to properly account for the exact ages within the broad bins available through the CDC's WONDER tool. What do these results look like with exact/not-binned age data?
• Similarly, how sensitive are the mortality trends being discussed in the news to the choice of bin-widths?
• As noted above, the data preparation process could have introduced errors. Can you find any discrepancies compared to the aggregate metrics on WONDER? If so, please let me know in the forums!
• WONDER is cited in numerous economics, sociology, and public health research papers. Can you find any papers whose conclusions would be altered if they used the exact data available here rather than binned data from Wonder?

Differences from the first version of the dataset

• This version of the dataset was prepared in a completely different many. This has allowed us to provide a much larger volume of data and ensure that codes are available for every field.
• We've replaced the batch of sql files with a single JSON per year. Kaggle's platform currently offer's better support for JSON files, and this keeps the number of files manageable.
• A tutorial kernel providing a quick introduction to the new format is available here.
• Lastly, I apologize if the transition has interrupted anyone's work! If need be, you can still download v1.

Leading causes of death by race (% of total deaths), in ranked order.

In 2023, heart disease and cancer accounted for the highest share of deaths in the United States. In 2020 and 2021, COVID-19 became the third leading cause of death. However, by 2023, COVID-19 was responsible for only 1.6 percent of deaths, making it the tenth leading cause of death. This statistic shows the distribution of the 10 leading causes of death in the United States in 2023.

Chronic Disease Risk Factors

Modifiable Risk Factors for Chronic Diseases and Other Leading Causes of Death

By US Open Data Portal, data.gov [source]

About this dataset

This dataset contains data on behaviors that are risk factors for cardiovascular diseases (CVDs) from 2011 to present. It is one of many datasets included in the National Cardiovascular Disease Surveillance System, which offers comprehensive insights into the public health burden of CVDs in America. This dataset collects information on modifiable risk factors for chronic diseases and leading causes of death from the Behavioral Risk Factor Surveillance System (BRFSS). This includes indicators from CDC's Division for Heart Disease and Stroke Prevention, organized by location and indicator with stratifications based on age, sex and race/ethnicity. In providing a detailed picture of these conditions, the system can be effectively used to reduce preventative disease through education, policy changes and other interventions

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How to use the dataset

Research Ideas

• Identifying CVD risk factors by demographic, such as age, gender, and ethnicity
• Comparing differences in modifiable risk factors (diet, physical activity) between states or regions
• Analyzing trends in CVD deaths over time to inform preventive strategies

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: csv-1.csv | Column name | Description | |:-------------------------------|:-----------------------------------------------------| | Year | Year of the data. (Integer) | | LocationAbbr | Abbreviation of the location. (String) | | LocationDesc | Description of the location. (String) | | Datasource | Source of the data. (String) | | PriorityArea1 | Priority area 1 of the data. (String) | | PriorityArea2 | Priority area 2 of the data. (String) | | PriorityArea3 | Priority area 3 of the data. (String) | | PriorityArea4 | Priority area 4 of the data. (String) | | Category | Category of the data. (String) | | Topic | Topic of the data. (String) | | Indicator | Indicator if available. (String) | | Data_Value_Type | Type of data value. (String) | | Data_Value_Unit | Unit of each value field. (String) | | Data_Value_Alt | Alternative value for respective each field. (Float) | | Data_Value_Footnote_Symbol | Footnote symbol for the data value. (String) | | Break_Out_Category | Break out category for the data. (String) | | Break_out | Break out description for the data. (String) | | GeoLocation | Geographical location of the data. (String) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit US Open Data Portal, data.gov.