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.

In the United States, the average person has a * in * chance of dying from heart disease and a * in * chance of dying from cancer. In comparison, the odds of dying from a dog attack are * in ******. Sadly, the odds of dying from an opioid overdose in the U.S. are * in **, making death from an opioid overdose more likely than dying from a motor vehicle accident. Opioid overdose death rates have increased insignificantly in the U.S. over the past decade. Leading causes of death in the United States Given the high lifetime odds of dying from heart disease or cancer, it is unsurprising that heart disease and cancer are the leading causes of death in the United States. Together, heart disease and cancer account for around ** percent of all deaths. Other leading causes of death include accidents, stroke, chronic lower respiratory diseases, and Alzheimer’s disease. However, in 2020 and 2021, COVID-19 was the third leading cause of death in the United States and remained the fourth leading cause of death in 2022, with around **** deaths per 100,000 population. Heart disease in the U.S. In 2023, the death rate from heart disease in the United States was around *** per 100,000 population. The states with the highest rates of death from heart disease are Oklahoma, Mississippi, and Alabama. Coronary heart disease is the most common form of heart disease in the United States. Common risk factors for heart disease include high blood pressure, high cholesterol, smoking, excessive drinking, and being overweight or obese.

United States US: Mortality Rate: Adult: Male: per 1000 Male Adults data was reported at 133.993 Ratio in 2015. This records an increase from the previous number of 131.567 Ratio for 2014. United States US: Mortality Rate: Adult: Male: per 1000 Male Adults data is updated yearly, averaging 176.083 Ratio from Dec 1960 (Median) to 2015, with 56 observations. The data reached an all-time high of 240.957 Ratio in 1968 and a record low of 131.037 Ratio in 2013. United States US: Mortality Rate: Adult: Male: per 1000 Male Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Adult mortality rate, male, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old male dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) University of California, Berkeley, and Max Planck Institute for Demographic Research. The Human Mortality Database.; Weighted average;

United States US: Probability of Dying at Age 5-9 Years: per 1000 data was reported at 0.600 Ratio in 2019. This stayed constant from the previous number of 0.600 Ratio for 2018. United States US: Probability of Dying at Age 5-9 Years: per 1000 data is updated yearly, averaging 0.700 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 1.100 Ratio in 1992 and a record low of 0.600 Ratio in 2019. United States US: Probability of Dying at Age 5-9 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Probability of dying between age 5-9 years of age expressed per 1,000 children aged 5, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

The leading causes of death in the United States have changed significantly from the year 1900 to the present. Leading causes of death in 1900, such as tuberculosis, gastrointestinal infections, and diphtheria have seen huge decreases in death rates and are no longer among the leading causes of death in the United States. However, other diseases such as heart disease and cancer have seen increased death rates. Vaccinations One major factor contributing to the decrease in death rates for many diseases since the year 1900 is the introduction of vaccinations. The decrease seen in the rates of death due to pneumonia and influenza is a prime example of this. In 1900, pneumonia and influenza were the leading causes of death, with around *** deaths per 100,000 population. However, in 2023 pneumonia and influenza were not even among the ten leading causes of death. Cancer One disease that has seen a large increase in death rates since 1900 is cancer. Cancer currently accounts for almost ** percent of all deaths in the United States, with death rates among men higher than those for women. The deadliest form of cancer for both men and women is cancer of the lung and bronchus. Some of the most common avoidable risk factors for cancer include smoking, drinking alcohol, sun exposure, and obesity.

US: Mortality Rate: Adult: Female: per 1000 Female Adults data was reported at 80.229 Ratio in 2015. This records an increase from the previous number of 79.191 Ratio for 2014. US: Mortality Rate: Adult: Female: per 1000 Female Adults data is updated yearly, averaging 94.263 Ratio from Dec 1960 (Median) to 2015, with 56 observations. The data reached an all-time high of 130.823 Ratio in 1968 and a record low of 77.137 Ratio in 2010. US: Mortality Rate: Adult: Female: per 1000 Female Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Adult mortality rate, female, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old female dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) University of California, Berkeley, and Max Planck Institute for Demographic Research. The Human Mortality Database.; Weighted average;

The leading causes of death in the United States are heart disease and cancer. However, in 2022, COVID-19 was the fourth leading cause of death in the United States, accounting for around six percent of all deaths that year. In 2022, there were around 45 deaths from COVID-19 per 100,000 population.

Cardiovascular disease

Deaths from cardiovascular disease are more common among men than women but have decreased for both sexes over the past few decades. Coronary heart disease accounts for the highest portion of cardiovascular disease deaths in the United States, followed by stroke and high blood pressure. The states with the highest death rates from cardiovascular disease include Oklahoma, Mississippi, and Alabama. Smoking tobacco, physical inactivity, poor diet, stress, and being overweight or obese are all risk factors for developing heart disease.

Cancer

Although cancer is the second leading cause of death in the United States, like deaths from cardiovascular disease, deaths from cancer have decreased over the last few decades. The highest death rates from cancer come from lung cancer for both men and women. Breast cancer is the second deadliest cancer for women, while prostate cancer is the second deadliest cancer for men. West Virginia, Mississippi, and Kentucky lead the nation with the highest cancer death rates.

U.S. Mortality and Health Indicators

Impact of Risk Factors on Population Health Outcomes

By Data Society [source]

About this dataset

This dataset provides county-level mortality and health indicators that are useful for measuring the impact of health policies in the United States. It includes data elements and values from over a dozen categories, including Demographics, Leading Causes of Death, Summary Measures of Health, Measures of Birth and Death, Relative Health Importance, Vulnerable Populations and Environmental Health, Preventive Services Use, Risk Factors and Access to Care. Additionally, this dataset offers Healthy People 2010 Targets and US Percentages or Rates for easy comparison across states. With comprehensive information for each county in each indicator domain available here at your fingertips could help you get insight into American population health from the local level like never before. Discover trends on disease outbreaks or immunizations that are unprecedentedly localized with insights from this dataset!

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How to use the dataset

This dataset contains various data elements related to the mortality and health of the US population at various levels such as county, state, etc. This dataset is an ideal source of information for researchers and policy makers who are interested in exploring patterns in the mortality and health of US citizens.

In order to use this dataset effectively, it is important to understand the different indicators included as well as how to interpret these indicators. In this guide we will look at each indicator domain separately so that users can easily identify which relevant data elements they need for their analysis.

Demographics: The Demographics indicator domain includes data elements related to demographic characteristics such as age composition, gender composition etc. These indicators can be used to explore trends across different parts of the country or identify disparities among populations.

Leading Causes of Death: The Leading Causes of Death indicator domain contains information on fatalities by cause over a set period of time -- either two years or five years depending on availability -- so that researchers can identify causes that pose major threats to public health overall or in more specific regions such as certain counties. It is important to note that these largely report figures based on death certificates which may not always tell an exact story due to reporting inaccuracies caused by both individual factors and registration biases across counties/states over time.

 **Summary Measures Of Health**: The Summary Measures Of Health Indicator Domain includes measures commonly used for gauging overall population health such as birth rates and death rates but also key quality-of-life considerations like prevalence rate physical activity rate . These can be used together with other data sources (such as income info) when analyzing population health outcomes from a broader perspective than individual diseases or conditions would allow for . 

 **Measures Of Birth And Death**: This category provides further insight into the important summary level figures mentioned earlier by providing observations about frequency , timing , type etc where available . Additionally , it offers valuable insights about trends related specifically (among others ) out - migration /in - migration mortality ratio changes/births outside hospitals marriage age / labor force participation trends etc – all essential ingredients when trying solve complex issues related improving public one's life expectancy positively  

 **Relative Health Importance & Vulnerable Populations And Environment Capacity :** This section covers two closely intertwined fields revealing how they interact – socioeconomic status disparities & environment quality – around boundaries & neighborhoods influencing risks factors (not only related medical matters ) aspects such disabilities insurance coverage alcohol use & smoking habits road fatalities veh

Research Ideas

• Using the Health Status Indicators as input features, machine learning models can be built to predict county-level mortality rate, which can then be used as an important indicator for health and medical resource allocation.
• The data can also be used to analyze the social determinants of health in different counties by combining with socioeconomic indicators such as poverty, population density and educational attainment levels.
• Additionally, the dataset could help assess th...

In 2023, there were approximately 750.5 deaths by all causes per 100,000 inhabitants in the United States. This statistic shows the death rate for all causes in the United States between 1950 and 2023. Causes of death in the U.S. Over the past decades, chronic conditions and non-communicable diseases have come to the forefront of health concerns and have contributed to major causes of death all over the globe. In 2022, the leading cause of death in the U.S. was heart disease, followed by cancer. However, the death rates for both heart disease and cancer have decreased in the U.S. over the past two decades. On the other hand, the number of deaths due to Alzheimer’s disease – which is strongly linked to cardiovascular disease- has increased by almost 141 percent between 2000 and 2021. Risk and lifestyle factors Lifestyle factors play a major role in cardiovascular health and the development of various diseases and conditions. Modifiable lifestyle factors that are known to reduce risk of both cancer and cardiovascular disease among people of all ages include smoking cessation, maintaining a healthy diet, and exercising regularly. An estimated two million new cases of cancer in the U.S. are expected in 2025.

United States US: Lifetime Risk Of Maternal Death data was reported at 0.026 % in 2015. This records a decrease from the previous number of 0.026 % for 2014. United States US: Lifetime Risk Of Maternal Death data is updated yearly, averaging 0.025 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 0.028 % in 2009 and a record low of 0.021 % in 1998. United States US: Lifetime Risk Of Maternal Death data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Life time risk of maternal death is the probability that a 15-year-old female will die eventually from a maternal cause assuming that current levels of fertility and mortality (including maternal mortality) do not change in the future, taking into account competing causes of death.; ; WHO, UNICEF, UNFPA, World Bank Group, and the United Nations Population Division. Trends in Maternal Mortality: 1990 to 2015. Geneva, World Health Organization, 2015; Weighted average;

United States US: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data was reported at 1.300 Ratio in 2016. This stayed constant from the previous number of 1.300 Ratio for 2015. United States US: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data is updated yearly, averaging 1.300 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 2.400 Ratio in 1990 and a record low of 1.300 Ratio in 2016. United States US: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Probability of dying between age 5-14 years of age expressed per 1,000 children aged 5, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted Average;

US Death Rates by Age and Cause

Study why are people dying

About this dataset

Data on death rates in the United States in by age and cause of death. At the bottom of the table, some of the columns are a little out of whack but if you download the file, you should be able to make out all the numbers and information

How to use the dataset

Looking at death rates in the United States can be a sobering experience, but it can also be a helpful way to see where our country needs to focus its efforts in terms of public health. This dataset contains information on death rates in the United States in 2014, by age and cause of death. This can be used to help identify which age groups are most at risk for certain causes of death, and what factors may contribute to those risks

Research Ideas

• Find out what age group is dying the most and why.
• Compare death rates from different causes of death.
• Find out which states have the highest death rates

Acknowledgements

License

Unknown License - Please check the dataset description for more information.

Columns

File: 2014 Death Rates by Age & Cause.csv | Column name | Description | |:-------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------| | Cause of death (based on ICD–10) | The cause of death that the row represents. This is given as a code based on the International Classification of Diseases (ICD). (String) | | All ages1 | The number of deaths due to the given cause in the given age group.(Integer) | | Under 1 year2 | The number of deaths due to the given cause in the given age group.(Integer) | | 1–4 | The number of deaths due to the given cause in the given age group.(Integer) | | 5–14 | The number of deaths due to the given cause in the given age group.(Integer) | | 15–24 | The number of deaths due to the given cause in the given age group.(Integer) | | 25–34 | The number of deaths due to the given cause in the given age group.(Integer) | | 35–44 | The number of deaths due to the given cause in the given age group.(Integer) | | 45–54 | The number of deaths due to the given cause in the given age group.(Integer) | | 55–64 | The number of deaths due to the given cause in the given age group.(Integer) | | 65–74 | The number of deaths due to the given cause in the given age group.(Integer) | | 75–84 | The number of deaths due to the given cause in the given age group.(Integer) | | 85 and over | The number of deaths due to the given cause in the given age group.(Integer) |

This dataset provides estimates for mortality risk at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014, as well as the changes in life expectancy and mortality risk for each location during this period.

United States US: Mortality Rate: Under-5: Male: per 1000 Live Births data was reported at 7.200 Ratio in 2017. This records a decrease from the previous number of 7.400 Ratio for 2015. United States US: Mortality Rate: Under-5: Male: per 1000 Live Births data is updated yearly, averaging 8.000 Ratio from Dec 1990 (Median) to 2017, with 5 observations. The data reached an all-time high of 12.500 Ratio in 1990 and a record low of 7.200 Ratio in 2017. United States US: Mortality Rate: Under-5: Male: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

Male child mortality rate of United States of America remained stable at 7.0 deaths per thousand live births over the last 3 years. Child mortality rate is the probability of dying between the exact ages of one and five, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000.

VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.

For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.

ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

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.

United States US: Probability of Dying at Age 10-14 Years: per 1000 data was reported at 0.800 Ratio in 2019. This stayed constant from the previous number of 0.800 Ratio for 2018. United States US: Probability of Dying at Age 10-14 Years: per 1000 data is updated yearly, averaging 0.900 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 1.300 Ratio in 1993 and a record low of 0.700 Ratio in 2017. United States US: Probability of Dying at Age 10-14 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

In 2023, the leading causes of death for children aged one to four years in the United States were unintentional injuries and congenital malformations, deformations, and chromosomal abnormalities. At that time, around 31 percent of all deaths among these children were caused by unintentional injuries. Differences in causes of death among children by age Just as unintentional injuries are the leading cause of death among children aged one to four, it is also the leading cause of death for the age groups five to nine and 10 to 14. However, congenital malformations, deformations, and chromosomal abnormalities account for fewer deaths as children become older, while the share of deaths caused by cancer is higher among those aged five to nine and 10 to 14. In fact, cancer is the second leading cause of death among five to nine-year-olds, accounting for around 16 percent of all deaths. Sadly, the second leading cause of death among children aged 10 to 14 is intentional self-harm, with 14 percent of all deaths among those in this age group caused by suicide. Leading causes of death in the United States The leading causes of death in the United States are heart disease and malignant neoplasms. Together, these two diseases accounted for around 42 percent of all deaths in the United States in 2023. In 2023, the lifetime odds that the average person in the United States would die from heart disease was one in six, while the odds for cancer were one in seven.

Historical and emerging trends in U.S. population mortality by cause of death