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.

This statistic shows the 20 countries * with the lowest infant mortality rate in 2024. An estimated 1.5 out of 1,000 live births died in the first year of life in Slovenia and Singapore in 2024. Infant mortality Infant mortality rates are often used as an indicator of the health and well-being of a nation. Monaco, Iceland, and Japan are among the top three countries with the lowest infant mortality rates with around 2 infant deaths per 1,000 infants within their first year of life. Generally, the countries with the lowest infant mortality also have some of the highest average life expectancy figures. Additionally, the countries with the highest density of physicians and doctors also generally report low infant mortality. Yet, many different factors contribute to differing rates, including the overall income of a country, health spending per capita, a mother’s level of education, environmental conditions, and medical infrastructure, to name a few. This creates a lot of variation concerning the level of childbirth and infant care around the world. The countries with the highest rates of infant mortality include Afghanistan, Mali, and Somalia. These countries experience around 100 infant deaths per 1,000 infants in their first year of life. While the reasons for high rates of infant mortality are numerous, the leading causes of death for children under the year five around the world are Pneumonia, Diarrhea, and Prematurity.

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.

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.

The leading causes of death in Massachusetts are cancer, heart disease, unintentional injury, stroke, and chronic lower respiratory disease. These mortality rates tend to be higher for people of color; and Black residents have a higher premature mortality rate overall and Asian residents have a higher rate of mortality due to stroke.

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 publication of the SHMI relates to discharges in the reporting period February 2024 - January 2025. The SHMI is the ratio between the actual number of patients who die following hospitalisation at the trust and the number that would be expected to die on the basis of average England figures, given the characteristics of the patients treated there. The SHMI covers patients admitted to hospitals in England who died either while in hospital or within 30 days of being discharged. To help users of the data understand the SHMI, trusts have been categorised into bandings indicating whether a trust's SHMI is 'higher than expected', 'as expected' or 'lower than expected'. For any given number of expected deaths, a range of observed deaths is considered to be 'as expected'. If the observed number of deaths falls outside of this range, the trust in question is considered to have a higher or lower SHMI than expected. The expected number of deaths is a statistical construct and is not a count of patients. The difference between the number of observed deaths and the number of expected deaths cannot be interpreted as the number of avoidable deaths or excess deaths for the trust. The SHMI is not a measure of quality of care. A higher than expected number of deaths should not immediately be interpreted as indicating poor performance and instead should be viewed as a 'smoke alarm' which requires further investigation. Similarly, an 'as expected' or 'lower than expected' SHMI should not immediately be interpreted as indicating satisfactory or good performance. Trusts may be located at multiple sites and may be responsible for 1 or more hospitals. A breakdown of the data by site of treatment is also provided, as well as a breakdown of the data by diagnosis group. Further background information and supporting documents, including information on how to interpret the SHMI, are available on the SHMI homepage (see Related Links).

The leading cause of death in low-income countries worldwide in 2021 was lower respiratory infections, followed by stroke and ischemic heart disease. The death rate from lower respiratory infections that year was 59.4 deaths per 100,000 people. While the death rate from stroke was around 51.6 per 100,000 people. Many low-income countries suffer from health issues not seen in high-income countries, including infectious diseases, malnutrition and neonatal deaths, to name a few. Low-income countries worldwide Low-income countries are defined as those with per gross national incomes (GNI) per capita of 1,045 U.S. dollars or less. A majority of the world’s low-income countries are located in sub-Saharan Africa and South East Asia. Some of the lowest-income countries as of 2023 include Burundi, Sierra Leone, and South Sudan. Low-income countries have different health problems that lead to worse health outcomes. For example, Chad, Lesotho, and Nigeria have some of the lowest life expectancies on the planet. Health issues in low-income countries Low-income countries also tend to have higher rates of HIV/AIDS and other infectious diseases as a consequence of poor health infrastructure and a lack of qualified health workers. Eswatini, Lesotho, and South Africa have some of the highest rates of new HIV infections worldwide. Likewise, tuberculosis, a treatable condition that affects the respiratory system, has high incident rates in lower income countries. Other health issues can be affected by the income of a country as well, including maternal and infant mortality. In 2023, Afghanistan had one of the highest rates of infant mortality rates in the world.

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 his article with the provocative title ‘‘Are Recessions Good for Your Health?’’, Ruhm (J. Health Econ. 21(4) (2000) 659) has found robust and consistent evidence that the total mortality rate, age-specific mortality rates as well as most specific mortality causes are pro-cyclical. His finding that high unemployment rates are associated with lower mortality and vice versa stands in stark contrast to Brenner’s earlier work, who found the opposite effect, possibly after a time lag. Ruhm controls for state-specific effects in a panel of US states over the period 1972–1991, whereas Brenner’s work is based on time-series analysis. Extending and improving upon Ruhm’s original analysis, we analyse the effect of state unemployment and economic growth rates on mortality in the states of Germany over the period 1980–2000, both in a static and a dynamic econometric model. Controlling for state-specific effects, we find evidence that aggregate mortality rates for all age groups taken together as well as most specific age groups are lower in recessions. The same is true for mortality from cardiovascular diseases, pneumonia and influenza, motor vehicle accidents and suicides, but not for necessarily for other specific mortality causes. In particular, there is never a statistically significant effect on homicides, other external effects and malignant neoplasms. There are also few differences apparent between the effect on male and female mortality. If we do not control for state-specific effects, then we often arrive at the opposite result with higher unemployment being associated with higher mortality. This suggests that a failure to control for time-invariant state-specific effects leads to omitted variable bias, which would erroneously suggest that mortality rates move counter-cyclically. Overall, we can confirm Ruhm’s main finding for another country: recessions lower some, but not all, mortality rates in the case of Germany.

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.

Background: Our previous study analyzed the age trajectory of mortality (ATM) in 14 European countries, while this study aimed at investigating ATM in other continents and in countries with a higher level of mortality. Data from 11 Non-European countries were used.Methods: The number of deaths was extracted from the WHO mortality database. The Halley method was used to calculate the mortality rates in all possible calendar years and all countries combined. This method enables us to combine more countries and more calendar years in one hypothetical population.Results: The age trajectory of total mortality (ATTM) and also ATM due to specific groups of diseases were very similar in the 11 non-European countries and in the 14 European countries. The level of mortality did not affect the main results found in European countries. The inverse proportion was valid for ATTM in non-European countries with two exceptions.Slower or no mortality decrease with age was detected in the first year of life, while the inverse proportion model was valid for the age range (1, 10) years in most of the main chapters of ICD10.Conclusions: The decrease in child mortality with age may be explained as the result of the depletion of individuals with congenital impairment. The majority of deaths up to the age of 10 years were related to congenital impairments, and the decrease in child mortality rate with age was a demonstration of population heterogeneity. The congenital impairments were latent and may cause death even if no congenital impairment was detected.

Series Name: Under-five mortality rate by sex (deaths per 1 000 live births)Series Code: SH_DYN_MORTRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.2.1: Under-5 mortality rateTarget 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live birthsGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

The average for 2021 based on 187 countries was 20 deaths per 1000 live births. The highest value was in Sierra Leone: 78 deaths per 1000 live births and the lowest value was in San Marino: 1 deaths per 1000 live births. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

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.

Series Name: Infant mortality rate (deaths per 1 000 live births)Series Code: SH_DYN_IMRTRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.2.1: Under-5 mortality rateTarget 3.2: By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live birthsGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

United States - Infant Mortality Rate for Lower Middle Income Countries was 32.60000 Number per 1,000 Live Births in January of 2023, according to the United States Federal Reserve. Historically, United States - Infant Mortality Rate for Lower Middle Income Countries reached a record high of 161.30000 in January of 1960 and a record low of 32.60000 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Infant Mortality Rate for Lower Middle Income Countries - last updated from the United States Federal Reserve on September of 2025.

In 2022, the infant mortality rate in the United States was 5.4 out of every 1,000 live births. This is a significant decrease from 1960, when infant mortality was at around 26 deaths out of every 1,000 live births. What is infant mortality? The infant mortality rate is the number of deaths of babies under the age of one per 1,000 live births. There are many causes for infant mortality, which include birth defects, low birth weight, pregnancy complications, and sudden infant death syndrome. In order to decrease the high rates of infant mortality, there needs to be an increase in education and medicine so babies and mothers can receive the proper treatment needed. Maternal mortality is also related to infant mortality. If mothers can attend more prenatal visits and have more access to healthcare facilities, maternal mortality can decrease, and babies have a better chance of surviving in their first year. Worldwide infant mortality rates Infant mortality rates vary worldwide; however, some areas are more affected than others. Afghanistan suffered from the highest infant mortality rate in 2024, and the following 19 countries all came from Africa, with the exception of Pakistan. On the other hand, Slovenia had the lowest infant mortality rate that year. High infant mortality rates can be attributed to lack of sanitation, technological advancements, and proper natal care. In the United States, Massachusetts had the lowest infant mortality rate, while Mississippi had the highest in 2022. Overall, the number of neonatal and post neonatal deaths in the United States has been steadily decreasing since 1995.

Mali ML: Mortality Rate: Infant: per 1000 Live Births data was reported at 68.000 Ratio in 2016. This records a decrease from the previous number of 69.600 Ratio for 2015. Mali ML: Mortality Rate: Infant: per 1000 Live Births data is updated yearly, averaging 131.200 Ratio from Dec 1963 (Median) to 2016, with 54 observations. The data reached an all-time high of 213.400 Ratio in 1963 and a record low of 68.000 Ratio in 2016. Mali ML: Mortality Rate: Infant: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given 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.

Israel IL: Mortality Rate: Infant: Female: per 1000 Live Births data was reported at 2.600 Ratio in 2016. This records a decrease from the previous number of 2.800 Ratio for 2015. Israel IL: Mortality Rate: Infant: Female: per 1000 Live Births data is updated yearly, averaging 3.400 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 9.000 Ratio in 1990 and a record low of 2.600 Ratio in 2016. Israel IL: Mortality Rate: Infant: Female: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Israel – Table IL.World Bank: Health Statistics. Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female live births in a given 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.