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.

Estimate of the probability of death for a single age group of men and women in the next 50 years or so.

The following tables provide historical and projected probabilities of death by age, sex, and year for the period 2011 - 2090. Death probabilities for males.

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.

United States US: Probability of Dying at Age 20-24 Years: per 1000 data was reported at 5.100 Ratio in 2019. This records an increase from the previous number of 5.000 Ratio for 2018. United States US: Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 4.800 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 5.500 Ratio in 1991 and a record low of 4.200 Ratio in 2013. United States US: Probability of Dying at Age 20-24 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 20-24 years of age expressed per 1,000 youths age 20, 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.

Population Projections: Projected Mortality Tables 2024-2073: Risk of death by age and sex (per thousand). Annual. National.

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/

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. 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 https://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). 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. In this way, the original 305 Bay Area Zip codes were reduced to 218 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.

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

Sweden SE: Probability of Dying at Age 20-24 Years: per 1000 data was reported at 2.300 Ratio in 2019. This records an increase from the previous number of 2.200 Ratio for 2018. Sweden SE: Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 2.400 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 2.900 Ratio in 1990 and a record low of 2.100 Ratio in 2016. Sweden SE: Probability of Dying at Age 20-24 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank.WDI: Health Statistics. Probability of dying between age 20-24 years of age expressed per 1,000 youths age 20, 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.

Australia Probability of Dying at Age 20-24 Years: per 1000 data was reported at 2.000 Ratio in 2019. This stayed constant from the previous number of 2.000 Ratio for 2018. Australia Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 2.850 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 4.500 Ratio in 1990 and a record low of 2.000 Ratio in 2019. Australia Probability of Dying at Age 20-24 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Health Statistics. Probability of dying between age 20-24 years of age expressed per 1,000 youths age 20, 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.

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

This table contains 2394 series, with data for years 1991 -1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 3;Income adequacy quintile 2 ...), Age (14 items: At 25 years; At 30 years; At 35 years; At 40 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Probability of survival; Low 95% confidence interval; life expectancy; High 95% confidence interval; life expectancy ...).

In 2021, high blood pressure contributed to around 10.85 million deaths worldwide, while there were around 3.71 million deaths due to obesity.

Mortality experience data from 2009 through 2013 on public pension plans in the United States

India IN: Probability of Dying at Age 10-14 Years: per 1000 data was reported at 2.700 Ratio in 2019. This records a decrease from the previous number of 2.800 Ratio for 2018. India IN: Probability of Dying at Age 10-14 Years: per 1000 data is updated yearly, averaging 4.950 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 6.900 Ratio in 1990 and a record low of 2.700 Ratio in 2019. India IN: 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 India – Table IN.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, 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.

Raw data sets for life tables in Brazil between 1950-2020, originally from the GHDx website.

The statistic shows the adult mortality rate in Colombia from 2013 to 2023, by gender. According to the source, the adult mortality rate is the probability of dying between the ages of 15 and 60 - that is, the probability of a 15-year-old dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages. In 2023, the mortality rate for women was at 66.2 per 1,000 female adults, while the mortality rate for men was at 122.67 per 1,000 male adults in Colombia.

Age-specific probability of death by method of estimation in the ten study countries.

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.