The average for 2022 based on 196 countries was 8.24 deaths per 1000 people. The highest value was in the Central African Republic: 55.13 deaths per 1000 people and the lowest value was in Qatar: 0.93 deaths per 1000 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

In 2023, Germany had an overall crude death rate of 12 per 1,000 people. In comparison, the death rate in South Korea was six per 1,000 people. This statistic represents a ranking of select developed and developing countries based on death rates as of 2023.

As of 2023, the countries with the highest death rates worldwide were Monaco, Bulgaria, and Latvia. In these countries, there were ** to ** deaths per 1,000 people. The country with the lowest death rate is Qatar, where there is just *** death per 1,000 people. Leading causes of death The leading causes of death worldwide are, by far, cardiovascular diseases, accounting for ** percent of all deaths in 2021. That year, there were **** million deaths worldwide from ischaemic heart disease and **** million from stroke. Interestingly, a worldwide survey from that year found that people greatly underestimate the proportion of deaths caused by cardiovascular disease, but overestimate the proportion of deaths caused by suicide, interpersonal violence, and substance use disorders. Death in the United States In 2023, there were around **** million deaths in the United States. The leading causes of death in the United States are currently heart disease and cancer, accounting for a combined ** percent of all deaths in 2023. Lung and bronchus cancer is the deadliest form of cancer worldwide, as well as in the United States. In the U.S. this form of cancer is predicted to cause around ****** deaths among men alone in the year 2025. Prostate cancer is the second-deadliest cancer for men in the U.S. while breast cancer is the second deadliest for women. In 2023, the tenth leading cause of death in the United States was COVID-19. Deaths due to COVID-19 resulted in a significant rise in the total number of deaths in the U.S. in 2020 and 2021 compared to 2019, and it was the third leading cause of death in the U.S. during those years.

In 2025, Japan had the highest death rate in the Asia-Pacific region, with **** deaths per one thousand population. In comparison, the death rate for the population of the Maldives amounted to *** deaths for every one thousand inhabitants in that year.

The statistic shows the death rate in the Arab world (Arab League) countries in 2023. In 2023, there were about 9.84 deaths per 1,000 inhabitants in Somalia.

In 2023, with just *** death per one thousand people, Qatar and the United Arab Emirates were the countries with the lowest death rates worldwide. This statistic shows a ranking of the 20 countries with the lowest death rates worldwide, as of 2023. Health in high-income countries Countries with the highest life expectancies are also often high-income countries with well-developed economic, social and health care systems, providing adequate resources and access to treatment for health concerns. Health care expenditure as a share of GDP varies per country; for example, spending in the United States is higher than in other OECD countries due to higher costs and prices for care services and products. In developed countries, the main burden of disease is often due to non-communicable diseases occurring in old age, such as cardiovascular diseases and cancer. High burden in low-income countries The countries with the lowest life expectancy worldwide are all in Africa- including Nigeria, Chad, and Lesotho- with life expectancies reaching up to 20 years shorter than the average global life expectancy. Leading causes of death in low-income countries include respiratory infections and diarrheal diseases, as these countries are often hit with the double burden of infectious diseases plus non-communicable diseases, such as those related to cardiovascular pathologies. Additionally, these countries often lack the resources and infrastructure to sustain effective healthcare systems and fail to provide appropriate access and treatment for their populations.

The average for 2022 based on 47 countries was 5.85 deaths per 1000 people. The highest value was in Japan: 12.9 deaths per 1000 people and the lowest value was in Qatar: 0.93 deaths per 1000 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Graph and download economic data for Infant Mortality Rate for Low and Middle Income Countries (SPDYNIMRTINLMY) from 1990 to 2023 about mortality, infant, income, and rate.

This dataset is about countries. It has 194 rows. It features 2 columns including death rate. It is 100% filled with non-null values.

This horizontal bar chart displays death rate (per 1,000 people) by country using the aggregation average, weighted by population in Mexico. The data is filtered where the date is 2021. The data is about countries per year.

This dataset is about countries per year in Europe. It has 2,816 rows. It features 3 columns: country, and death rate.

This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

All-cause mortality rates of selected European countries and regions. Breakdowns include sex and broad age group for selected countries and cities.

Global Maternal Death Rate (Lifetime Risk) by Country, 2023 Discover more data with ReportLinker!

Historical dataset showing U.S. death rate by year from 1950 to 2025.

COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

The dataset contains information on various demographic and health indicators for different countries. It is organized into several columns, each providing essential information about these countries. Here's a description of each column:

1. Country: This column represents the names of different countries or regions included in the dataset. Each row corresponds to a specific country or region, and this column serves as the identifier for each entry.

2. Life Expectancy Males: This column contains data on the average life expectancy of males in each of the listed countries. Life expectancy is a crucial health indicator and provides an estimate of the average number of years a male can expect to live, given current mortality rates and health conditions.

3. Life Expectancy Females: Similar to the "Life Expectancy Males" column, this column provides data on the average life expectancy of females in the same countries. It reflects the average number of years a female can expect to live, considering the prevailing health and mortality conditions.

4. Birth Rate: The "Birth Rate" column contains information about the birth rate in each country. Birth rate is a demographic indicator that represents the number of live births per 1,000 people in a given population over a specific period, usually a year. It can provide insights into a country's population growth or decline.

5. Death Rate: This column presents data on the death rate in each of the listed countries. The death rate is another crucial demographic indicator and represents the number of deaths per 1,000 people in a population over a specific period, often a year. It helps gauge the overall health and mortality conditions within a country.

Dear Kaggler! This dataset consists of a main CSV file: Adult mortality rate (2019-2021).csv. This file has been processed, cleaned and prepared for your use. The dataset contains information on mortality rates in different countries of the world and some factors that may affect this rate for 2019-2023.

The data contains the following columns:

Countries: Country of study.

Continent: Continent location of the country.

Average_Pop(thousands people): Average population of the country under study for 2019-2021 in thousands.

Average_GDP(M$): Average GDP of the country under study for 2019-2021 in millions of dollars.

Average_GDP_per_capita: Average GDP per capita of the country under study for 2019-2021 in dollars.

Average_HEXP($): Health Expenditure Per Capita in the country under study in dollars.

Development_level: Level of development of the state under study (calculated by GDP per capita of the country). Please note that in this dataset we calculate this indicator only by calculating GDP per capita! Despite the fact that the United Nations (UN) does not have an unambiguous classification of countries into developed, developing and backward based on only one indicator, such as the amount of GDP per capita. It uses a wider range of economic, social and quality indicators to determine the level of development of countries.

AMR_female(per_1000_female_adults): Average mortality of adult women in the country under study (per 1000 adult women per year) for 2019-2023.

AMR_male(per_1000_male_adults): Average mortality of adult men in the country under study (per 1000 adult men per year) for 2019-2023.

Average_CDR: Average crude mortality rate for 2019–2021 in the country under study.

The dataset also contains additional files: Draft_AMR.csv, Draft_CDR.csv, Draft_Expenses.csv, Draft_GDP.csv, Draft_Population.csv. In fact, the main dataset consists of parts of these files. If you are interested in working more deeply on data cleaning and preparation, you can of course use these files. You can also use these files to create your own dataset. And be careful! Additional files may contain a different number of rows and columns with different names and data types. And of course these files are not cleaned. You will see not only the NaN values, but also other symbols in their place.

Enjoy your training, my dear Kaggler!

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This horizontal bar chart displays death rate (per 1,000 people) by region using the aggregation average, weighted by population in South America. The data is about countries.

This horizontal bar chart displays death rate (per 1,000 people) by ISO 3 country code using the aggregation average, weighted by population in Middle Africa. The data is about countries.