The leading causes of death among the white population of the United States are cardiovascular diseases and cancer. Cardiovascular diseases and cancer accounted for a combined **** percent of all deaths among this population in 2022. In 2020 and 2021, COVID-19 was the third leading cause of death among white people. Disparities in causes of death In the United States, there exist disparities in the leading causes of death based on race and ethnicity. For example, chronic liver disease and cirrhosis is the ***** leading cause of death among the white population and the ****** among the Hispanic population, but is not among the ten leading causes for Black people. On the other hand, homicide is the ******* leading cause of death among the Black population, but is not among the 10 leading causes for whites or Hispanics. However, cardiovascular diseases and cancer by far account for the highest share of deaths for every race and ethnicity. Diseases of despair The American Indian and Alaska Native population in the United States has the highest rates of death from suicide, drug overdose, and alcohol. Together, these three behavior-related conditions are often referred to as diseases of despair. Asians have by far the lowest rates of death due to drug overdose and alcohol, as well as slightly lower rates of suicide.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical

As of June 14, 2023, around 66 percent of all COVID-19 deaths in the United States have been among non-Hispanic whites, although non-Hispanic whites account for 60 percent of the total U.S. population. On the other hand, non-Hispanic Asians have accounted for just three percent of all deaths due to COVID-19 even though this group makes up almost six percent of the entire U.S. population. This statistic shows the distribution of COVID-19 (coronavirus disease) deaths in the United States, by race/ethnicity.

Note: Starting April 27, 2023 updates change from daily to weekly. Summary The cumulative number of confirmed COVID-19 deaths among Maryland residents by race and ethnicity: African American; White; Hispanic; Asian; Other; Unknown. Description The MD COVID-19 - Confirmed Deaths by Race and Ethnicity Distribution data layer is a collection of the statewide confirmed and probable COVID-19 related deaths that have been reported each day by the Vital Statistics Administration by categories of race and ethnicity. A death is classified as confirmed if the person had a laboratory-confirmed positive COVID-19 test result. Some data on deaths may be unavailable due to the time lag between the death, typically reported by a hospital or other facility, and the submission of the complete death certificate. Probable deaths are available from the MD COVID-19 - Probable Deaths by Race and Ethnicity Distribution data layer. Terms of Use The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

As of June 23, 2020, 54 percent of deaths due to COVID-19 in the state of Michigan were among White Americans, where they make up 78 percent of the total population. This statistic shows the percentage of coronavirus (COVID-19) deaths compared to population among White Americans in select U.S. states as of June 23, 2020.

Sadly, the trend of fatal police shootings in the United States seems to only be increasing, with a total 1,173 civilians having been shot, 248 of whom were Black, as of December 2024. In 2023, there were 1,164 fatal police shootings. Additionally, the rate of fatal police shootings among Black Americans was much higher than that for any other ethnicity, standing at 6.1 fatal shootings per million of the population per year between 2015 and 2024. Police brutality in the U.S. In recent years, particularly since the fatal shooting of Michael Brown in Ferguson, Missouri in 2014, police brutality has become a hot button issue in the United States. The number of homicides committed by police in the United States is often compared to those in countries such as England, where the number is significantly lower. Black Lives Matter The Black Lives Matter Movement, formed in 2013, has been a vocal part of the movement against police brutality in the U.S. by organizing “die-ins”, marches, and demonstrations in response to the killings of black men and women by police. While Black Lives Matter has become a controversial movement within the U.S., it has brought more attention to the number and frequency of police shootings of civilians.

Graph and download economic data for Premature Death Rate for White County, AR (CDC20N2U005145) from 1999 to 2020 about White County, AR; premature; death; AR; rate; and USA.

In 2021, the death rate from stroke among Black non-Hispanic men in the United States aged 35 years and older was almost *** per 100,000 population. In comparison, the stroke death rate among non-Hispanic white men was about ** per 100,000 population. This statistic shows the rate of stroke death among Black and White men in the United States aged 35 years and older from 2015 to 2021.

In 2020, the death rate for COVID-19 in the United States among Black or African American, non-Hispanics was around 155 per 100,000 population. That year there was a total of 61,401 deaths from COVID-19 among Black or African American, non-Hispanics. This statistic shows the death rate for COVID-19 in the United States in 2020, 2021, and 2022, by race/ethnicity.

Graph and download economic data for Age-Adjusted Premature Death Rate for White County, AR (CDC20N2UAA005145) from 1999 to 2020 about White County, AR; premature; death; AR; rate; and USA.

This project contains a city-level panel dataset of deaths-by-cause from the U.S. Census Bureau for the years 1915 to 1938, annually, as reported in the publication “Mortality Statistics.” For some cities, the data is available separately for white and non-white deaths. This data is based on transcripts of death certificates received by the Census Bureau from certain areas of the country called “registration areas.” In 1918, the data covers an estimated population of 82,091,523, or 77.8% total estimated population of the United States, and includes 30 states, the District of Columbia, and 27 cities in nonregistration states. States and cities are added over time, so the panel is not complete. When data is reported based on white and non-white deaths, the majority (95%+) are Blacks (1918, page 11).

Crude, age-specific, and age-standardized COVID-19 mortality rates per 100,000 person-years for non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic American Indian or Alaska Native, and non-Hispanic Asian or Pacific Islander populations, and age-specific mortality rate ratios and rate differences per 100,000 person-years.

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'.

Age-adjusted rate of death (all causes) by sex, race/ethnicity, age; trends. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau; 2010 Census, Tables PCT12, PCT12H, PCT12I, PCT12J, PCT12K, PCT12L, PCT12M; generated by Baath M.; using American FactFinder; Accessed June 20, 2017. METADATA:Notes (String): Lists table title, notes and sourcesYear (Numeric): Year of dataCategory (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); age categories as follows: child age groups: <1, 1 to 4, 5 to 11, 12 to 17; youth age groups: 10 to 19, 20 to 24; age groups 1: 0 to 17, 18 to 64, 65+; age groups 2: <1, 1 to 4, 5 to 14, 15 to 24, 25 to 34, 35 to 44, 45 to 54, 55 to 64, 65 to 74, 75 to 84, 85+; United StatesRate per 100,000 people (Numeric): Rate of deaths by all causes. Rates for age groups are reported as age-specific rates per 100,000 people. All other rates are age-adjusted rates per 100,000 people.

Premature Death Rate for White County, AR was 678.00000 Rate per 100,000 in January of 2020, according to the United States Federal Reserve. Historically, Premature Death Rate for White County, AR reached a record high of 678.00000 in January of 2020 and a record low of 439.80000 in January of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for Premature Death Rate for White County, AR - last updated from the United States Federal Reserve on September of 2025.

This data includes counts of deaths by race (total, Black, white) by age grouping and cause of death by Census Tract aggregated over a five-year period (2014-18). Data extracted from Pennsylvania's Electronic Death Registry System (EDRS) with the following disclaimer: "These data were provided by the Pennsylvania Department of Health. The Department specifically disclaims responsibility for any analyses, interpretations, or conclusions."

Census tract of residence was determined using address-level data. Records were excluded from analysis if address was missing or unmatched to a census tract (≈1% records). Census tracts starting with 980x.xx, 981x.xx, and 982x.xx were also excluded due to a geocoding error.

For cause of death by census tract, counts were assessed using census tract by age and race; records were excluded if age, race, or location data were missing. Census-tract level counts < 5 are censored and displayed as NULL. Census-tract-level counts may not equal county-level counts when summed due to censored data or missing data.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

This is a database (parquet format) containing publicly available multiple cause mortality data from the US (CDC/NCHS) for 2014-2022. Not all variables are included on this export. Please see below for restrictions on the use of these data imposed by NCHS. You can use the arrow package in R to open the file. See here for example analysis; https://github.com/DanWeinberger/pneumococcal_mortality/blob/main/analysis_nongeo.Rmd . For instance, save this file in a folder called "parquet3":

library(arrow)

library(dplyr)

pneumo.deaths.in <- open_dataset("R:/parquet3", format = "parquet") %>% #open the dataset
filter(grepl("J13|A39|J181|A403|B953|G001", all_icd)) %>% #filter to records that have the selected ICD codes
collect() #call the dataset into memory. Note you should do any operations you canbefore calling 'collect()" due to memory issues

The variables included are named: (see full dictionary:https://www.cdc.gov/nchs/nvss/mortality_public_use_data.htm)

year: Calendar year of death

month: Calendar month of death

age_detail_number: number indicating year or part of year; can't be interpreted itself here. see agey variable instead

sex: M/F

place_of_death:

Place of Death and Decedent’s Status
Place of Death and Decedent’s Status
1 ... Hospital, Clinic or Medical Center
- Inpatient
2 ... Hospital, Clinic or Medical Center
- Outpatient or admitted to Emergency Room
3 ... Hospital, Clinic or Medical Center
- Dead on Arrival
4 ... Decedent’s home
5 ... Hospice facility
6 ... Nursing home/long term care
7 ... Other
9 ... Place of death unknown

all_icd: Cause of death coded as ICD10 codes. ICD1-ICD21 pasted into a single string, with separation of codes by an underscore

hisp_recode: 0=Non-Hispanic; 1=Hispanic; 999= Not specified

race_recode: race coding prior to 2018 (reconciled in race_recode_new)

race_recode_alt: race coding after 2018 (reconciled in race_recode_new)

race_recode_new:

1='White'

2= 'Black'

3='Hispanic'

4='American Indian'

5='Asian/Pacific Islanders'

agey:

age in years (or partial years for kids <12months)

https://www.cdc.gov/nchs/data_access/restrictions.htm

Please Read Carefully Before Using NCHS Public Use Survey Data

The National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention (CDC), conducts statistical and epidemiological activities under the authority granted by the Public Health Service Act (42 U.S.C. § 242k). NCHS survey data are protected by Federal confidentiality laws including Section 308(d) Public Health Service Act [42 U.S.C. 242m(d)] and the Confidential Information Protection and Statistical Efficiency Act or CIPSEA [Pub. L. No. 115-435, 132 Stat. 5529 § 302]. These confidentiality laws state the data collected by NCHS may be used only for statistical reporting and analysis. Any effort to determine the identity of individuals and establishments violates the assurances of confidentiality provided by federal law.

Terms and Conditions

NCHS does all it can to assure that the identity of individuals and establishments cannot be disclosed. All direct identifiers, as well as any characteristics that might lead to identification, are omitted from the dataset. Any intentional identification or disclosure of an individual or establishment violates the assurances of confidentiality given to the providers of the information. Therefore, users will:

1. Use the data in this dataset for statistical reporting and analysis only.

1. Make no attempt to learn the identity of any person or establishment included in these data.

1. Not link this dataset with individually identifiable data from other NCHS or non-NCHS datasets.

1. Not engage in any efforts to assess disclosure methodologies applied to protect individuals and establishments or any research on methods of re-identification of individuals and establishments.

By using these data you signify your agreement to comply with the above-stated statutorily based requirements.

Sanctions for Violating NCHS Data Use Agreement

Willfully disclosing any information that could identify a person or establishment in any manner to a person or agency not entitled to receive it, shall be guilty of a class E felony and imprisoned for not more than 5 years, or fined not more than $250,000, or both.

Each Maryland County's number of infant deaths and infant mortality rates by race in 2012 and 2013. Includes: a) Number of Infant Deaths of All Races, 2012, b) Number of Infant Deaths of All Races, 2013, c) Infant Mortality Rate of All Races Per 1,000 Live Births, 2012, d) Infant Mortality Rate of All Races Per 1,000 Live Births, 2013, e) White Infant Deaths, 2012, f) White Infant Deaths, 2013, g) White Infant Mortality Rate Per 1,000 Live Births 2012, h) White Infant Mortality Rate Per 1,000 Live Births 2013, i) Black Infant Deaths, 2012, j) Black Infant Deaths, 2013, k) Black Infant Mortality Rate Per 1,000 Live Births 2012, l) Black Infant Mortality Rate Per 1,000 Live Births 2013, m) Number of Infant Deaths All Races from 2004-2008, n) Number of Infant Deaths All Races from 2009-2013, o) Average Infant Mortality Rate of All Races from 2004-2008, p) Average Infant Mortality Rate of All Races from 2009-2013, q) Percent Change of Infant Deaths. Values = Rates based on <5 deaths are not presented since rates based on small numbers are statistically unreliable.

This dataset is no longer being updated as of 5/11/2023. It is being retained on the Open Data Portal for its potential historical interest.

This table displays the number of COVID-19 deaths among Cambridge residents by race and ethnicity. The count reflects total deaths among Cambridge COVID-19 cases.

The rate column shows the rate of COVID-19 deaths among Cambridge residents by race and ethnicity. The rates in this chart were calculated by dividing the total number of deaths among Cambridge COVID-19 cases for each racial or ethnic category by the total number of Cambridge residents in that racial or ethnic category, and multiplying by 10,000. The rates are considered “crude rates” because they are not age-adjusted. Population data are from the U.S. Census Bureau’s 2014–2018 American Community Survey estimates and may differ from actual population counts.

Of note:

This chart reflects the time period of March 25 (first known Cambridge death) through present.

It is important to note that race and ethnicity data are collected and reported by multiple entities and may or may not reflect self-reporting by the individual case. The Cambridge Public Health Department (CPHD) is actively reaching out to cases to collect this information. Due to these efforts, race and ethnicity information have been confirmed for over 80% of Cambridge cases, as of June 2020.

Race/Ethnicity Category Definitions:

“White” indicates “White, not of Hispanic origin.”

“Black” indicates “Black, not of Hispanic origin.”

“Hispanic” refers to a person having Hispanic origin. A person having Hispanic origin may be of any race.

“Asian” indicates “Asian, not of Hispanic origin.”

To protect individual privacy, a category is suppressed when it has one to four people. Categories with zero cases are reported as zero.

"Other" indicates multiple races, another race that is not listed above, and cases who have reported nationality in lieu of a race category recognized by the US Census. Population data are from the U.S. Census Bureau’s 2014–2018 American Community Survey estimates and may differ from actual population counts. "Other" also includes a small number of people who identify as Native American or Native Hawaiian/Pacific islander. Because the count for Native Americans or Native Hawaiian/Pacific Islanders is currently < 5 people, these categories have been combined with “Other” to protect individual privacy.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Death rate has been age-adjusted by the 2000 U.S. standard populaton. All-cause mortality is an important measure of community health. All-cause mortality is heavily driven by the social determinants of health, with significant inequities observed by race and ethnicity and socioeconomic status. Black residents have consistently experienced the highest all-cause mortality rate compared to other racial and ethnic groups. During the COVID-19 pandemic, Latino residents also experienced a sharp increase in their all-cause mortality rate compared to White residents, demonstrating a reversal in the previously observed mortality advantage, in which Latino individuals historically had higher life expectancy and lower mortality than White individuals despite having lower socioeconomic status on average. The disproportionately high all-cause mortality rates observed among Black and Latino residents, especially since the onset of the COVID-19 pandemic, are due to differences in social and economic conditions and opportunities that unfairly place these groups at higher risk of developing and dying from a wide range of health conditions, including COVID-19.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.