The child mortality rate in the United States, for children under the age of five, was 462.9 deaths per thousand births in 1800. This means that for every thousand babies born in 1800, over 46 percent did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, and the rate has dropped to its lowest point ever in 2020 where it is just seven deaths per thousand births. Although the child mortality rate has decreased greatly over this 220 year period, there were two occasions where it increased; in the 1870s, as a result of the fourth cholera pandemic, smallpox outbreaks, and yellow fever, and in the late 1910s, due to the Spanish Flu pandemic.

This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); 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 National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

The COVID-19 pandemic increased the global death rate, reaching *** in 2021, but had little to no significant impact on birth rates, causing population growth to dip slightly. On a global level, population growth is determined by the difference between the birth and death rates, known as the rate of natural change. On a national or regional level, migration also affects population change. Ongoing trends Since the middle of the 20th century, the global birth rate has been well above the global death rate; however, the gap between these figures has grown closer in recent years. The death rate is projected to overtake the birth rate in the 2080s, which means that the world's population will then go into decline. In the future, death rates will increase due to ageing populations across the world and a plateau in life expectancy. Why does this change? There are many reasons for the decline in death and birth rates in recent decades. Falling death rates have been driven by a reduction in infant and child mortality, as well as increased life expectancy. Falling birth rates were also driven by the reduction in child mortality, whereby mothers would have fewer children as survival rates rose - other factors include the drop in child marriage, improved contraception access and efficacy, and women choosing to have children later in life.

This table presents a wide variety of historical data in the field of health, lifestyle and health care. Figures on births and mortality, causes of death and the occurrence of certain infectious diseases are available from 1900, other series from later dates. In addition to self-perceived health, the table contains figures on infectious diseases, hospitalisations per diagnosis, life expectancy, lifestyle factors such as smoking, alcohol consumption and obesity, and causes of death. The table also gives information on several aspects of health care, such as the number of practising professionals, the number of available hospital beds, nursing day averages and the expenditures on care. Many subjects are also covered in more detail by data in other tables, although sometimes with a shorter history. Data on notifiable infectious diseases and HIV/AIDS are not included in other tables.

Data available from: 1900

Status of the figures:

2025: The available figures are definite.

2024: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, hiv, aids; - causes of death.

2023: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, HIV/AIDS; - diagnoses at hospital admissions; - number of hospital discharges and length of stay; - number of hospital beds; - health professions; - perinatal and infant mortality. Figures are revised provisional for: - expenditures on health and welfare.

2022: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, HIV/AIDS; - diagnoses at hospital admissions; - number of hospital discharges and length of stay; - number of hospital beds; - health professions. Figures are revised provisional for: - expenditures on health and welfare.

2021: Most available figures are definite. Figures are provisional for: - notifiable infectious diseases, HIV/AIDS; Figures are revised provisional for: - expenditures on health and welfare.

2020 and earlier: Most available figures are definite. Due to 'dynamic' registrations, figures for notifiable infectious diseases, HIV/AIDS remain provisional.

Changes as of 4 July 2025: The most recent available figures have been added for: - population on January 1; - live born children, deaths; - persons in (very) good health; - notifiable infectious diseases, HIV/AIDS; - diagnoses at hospital admissions; - use of medication; - sickness absence; - lifestyle; - use of health care services; - number of hospital discharges and length of stay; - number of hospital beds; - health professions; - expenditures on health and welfare; - healthy life expectancy; - causes of death.

Changes as of 18 december 2024: - Due to a revision of the statistics Health and welfare expenditure 2021, figures for expenditure on health and welfare have been replaced from 2021 onwards. - Revised figures on the volume index of healthcare costs are not yet available, these figures have been deleted from 2021 onwards.

When will new figures be published? December 2025.

Statistics from the Department of Health

The study’s theme: The development of infant mortality in Germany for the 19th century is only poorly documented. Especially for the period prior to 1871 only small area statistics are available. With the preparation of the information collected by the authorities of the former German States the author tries to create a new statistical basis. The reconstructed national series of birth and infant mortality (from 1826) documents relatively high infant mortality rates with little progress (i.e. improvement of the situation) until the beginning of the 20th Century. Considering the influence of urbanization the evaluation of the different regional patterns and trends leads to a new weighting of the problem. Thus the living and working conditions in the country were of considerable importance. Overall, the prevailing habits and attitudes are considered crucial to the survival of small children (Gehrmann 2011, S. 807) Data and data preparation, source problems:The federal structure of the Empire leads to the problem that the printed statistics on infant mortality before 1901 remained incomplete. In some German states, information concerning infant mortality was not collected from the beginning of the registry offices. However, the ‘Kaiserliches Statistisches Amt’ (Imperial Statistical Office) was able to create despi9te the difficult situation a life table, which represented 97,3% of live birth for the period of 1872 to 1880. Hence, the annual infant mortality rate in 1872 is known. „Die föderale Struktur des Kaiserreichs hatte (…) zur Folge, dass die gedruckte Statistik zur Säuglingssterblichkeit vor 1901 lückenhaft blieb. Mehr noch: es wurden offensichtlich in einigen Staaten diesbezügliche Angaben gar nicht oder zumindest nicht von Anfang an bei den Standesämtern abgefragt. Als das Kaiserliche Statistische Amt in den 1880er Jahren die erste Sterbetafel für das Deutsche Reich erstellen wollte, musste es deshalb konstatieren, dass in den Einzelstaaten „fast alle in der Statistik überhaupt üblichen Arten und Grade der Spezialisierung vertreten“ (Kaiserliches Statistisches Amt 1887: 21) waren, aus manchen aber trotzdem keine geeigneten Unterlagen beschafft werden konnten. Immerhin repräsentierte die Sterbetafel am Ende doch 96,8% der Reichsbevölkerung im Jahre 1885 und 97,3% der Lebendgeborenen 1872 bis 1880. Damit ist auch die jährliche Säuglingssterblichkeitsrate ab 1872 bekannt. (…) Mit Hilfe des Sterbetafel-Materials kann die statistische Reihe aus „Bevölkerung und Wirtschaft“ also um fast 30 Jahre nach hinten verlängert werden. (…) Komplizierter stellt sich die Sachlage für weiter zurückliegende Zeitabschnitte dar. „ (S. 812-813)Although in most German states statistical collection on population movement has been carried out, the statistics vary considerably in quality. In the first step therefore, the author reject the procedure of simply extrapolating the birth rates because of the qualitative differences of the early statistics are too fundamental. Especially, in this approach of simply summing up, the values of the undocumented areas would equate with the values of the other well documented regions. Therefore, the author chose a complex way to estimate the lacking values: The missing values in small territories are estimated on the basis of the values of neighboring regions. Finally, it can be seen, that the data for the period from 1828 to 1871, calculated by the complex procedure of filling in missing data does not lead to significantly different results comparing to the data row calculated by the simple sum of the different sources. Per year, the difference between the two series (the series calculated in the complex way and the series calculated by summing up the values of the available statistics) is not more than 0,9 percent points, which can be seen as a slight difference between the two series in relation to the former level of infant mortality. The indeterminate values of those German states lacking a birth statistics may not being significantly different to those calculated on the basis of the complex procedure, because even unexpected, extreme runaway values in individual states can not realistically assumed to be so large that they could have a sufficient impact on the overall values. Thus, the presented row is a solid basis for the assessment of the overall development of the German Empire’s birth development. „Vielmehr empfiehlt es sich, zunächst in kleinen Schritten für die einzelnen Territorien fehlende Werte durch wahrscheinliche zu ersetzen. Diese ergeben sich in erster Linie aus dem Vergleich der Säuglingssterblichkeitswerte benachbarter Gebiete zu anderen Zeitpunkten. So können für Württemberg die vor 1859 zu längeren Zeiträumen zusammengefassten Informationen auf Einzeljahre herunter gerechnet werden, indem die Verteilung über die Jahre wie in Bayern angenommen wird. … Alle ermittelten Werte beziehen sich auf Lebendgeborene.“ (S. 814) „Die komplexe Prozedur der Ergänzung fehlend...

In 2021, the infant mortality rate in the United Kingdom was four deaths one year per 1,000 live births, one of the lowest infant mortality rate in this period. Infant mortality has fallen considerably since 1900, when there were 150 infant deaths per 1,000 live births.

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.

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

A dataset to advance the study of life-cycle interactions of biomedical and socioeconomic factors in the aging process. The EI project has assembled a variety of large datasets covering the life histories of approximately 39,616 white male volunteers (drawn from a random sample of 331 companies) who served in the Union Army (UA), and of about 6,000 African-American veterans from 51 randomly selected United States Colored Troops companies (USCT). Their military records were linked to pension and medical records that detailed the soldiers������?? health status and socioeconomic and family characteristics. Each soldier was searched for in the US decennial census for the years in which they were most likely to be found alive (1850, 1860, 1880, 1900, 1910). In addition, a sample consisting of 70,000 men examined for service in the Union Army between September 1864 and April 1865 has been assembled and linked only to census records. These records will be useful for life-cycle comparisons of those accepted and rejected for service. Military Data: The military service and wartime medical histories of the UA and USCT men were collected from the Union Army and United States Colored Troops military service records, carded medical records, and other wartime documents. Pension Data: Wherever possible, the UA and USCT samples have been linked to pension records, including surgeon''''s certificates. About 70% of men in the Union Army sample have a pension. These records provide the bulk of the socioeconomic and demographic information on these men from the late 1800s through the early 1900s, including family structure and employment information. In addition, the surgeon''''s certificates provide rich medical histories, with an average of 5 examinations per linked recruit for the UA, and about 2.5 exams per USCT recruit. Census Data: Both early and late-age familial and socioeconomic information is collected from the manuscript schedules of the federal censuses of 1850, 1860, 1870 (incomplete), 1880, 1900, and 1910. Data Availability: All of the datasets (Military Union Army; linked Census; Surgeon''''s Certificates; Examination Records, and supporting ecological and environmental variables) are publicly available from ICPSR. In addition, copies on CD-ROM may be obtained from the CPE, which also maintains an interactive Internet Data Archive and Documentation Library, which can be accessed on the Project Website. * Dates of Study: 1850-1910 * Study Features: Longitudinal, Minority Oversamples * Sample Size: ** Union Army: 35,747 ** Colored Troops: 6,187 ** Examination Sample: 70,800 ICPSR Link: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06836

For most of the past two centuries, falling birth rates have been associated with societal progress. During the demographic transition, where pre-industrial societies modernize in terms of fertility and mortality, falling death rates, especially among infants and children, are the first major change. In response, as more children survive into adulthood, women have fewer children as the need to compensate for child mortality declines. This transition has happened at different times across the world and is an ongoing process, with early industrial countries being the first to transition, and Sub-Saharan African countries being the most recent to do so. Additionally, some Asian countries (particularly China through government policy) have gone through their demographic transitions at a much faster pace than those deemed more developed. Today, in countries such as Japan, Italy, and Germany, birth rates have fallen well below death rates; this is no longer considered a positive demographic trend, as it leads to natural population decline, and may create an over-aged population that could place a burden on healthcare systems.

This data collection contains detailed county and state-level ecological and descriptive data for the United States for the years 1790 to 2002. Parts 1-43 are an update to HISTORICAL, DEMOGRAPHIC, ECONOMIC, AND SOCIAL DATA: THE UNITED STATES, 1790-1970 (ICPSR 0003). Parts 1-41 contain data from the 1790-1970 censuses. They include extensive information about the social and political character of the United States, including a breakdown of population by state, race, nationality, number of families, size of the family, births, deaths, marriages, occupation, religion, and general economic condition. Parts 42 and 43 contain data from the 1840 and 1870 Censuses of Manufacturing, respectively. These files include information about the number of persons employed in various industries and the quantities of different types of manufactured products. Parts 44-50 provide county-level data from the United States Census of Agriculture for 1840 to 1900. They also include the state and national totals for the variables. The files provide data about the number, types, and prices of various agricultural products. Parts 51-57 contain data on religious bodies and church membership for 1906, 1916, 1926, 1936, and 1952, respectively. Parts 58-69 consist of data from the CITY DATA BOOKS for 1944, 1948, 1952, 1956, 1962, 1967, 1972, 1977, 1983, 1988, 1994, and 2000, respectively. These files contain information about population, climate, housing units, hotels, birth and death rates, school enrollment and education expenditures, employment in various industries, and city government finances. Parts 70-81 consist of data from the COUNTY DATA BOOKS for 1947, 1949, 1952, 1956, 1962, 1967, 1972, 1977, 1983, 1988, 1994, and 2000, respectively. These files include information about population, employment, housing, agriculture, manufacturing, retail, services, trade, banking, Social Security, local governments, school enrollment, hospitals, crime, and income. Parts 82-84 contain data from USA COUNTIES 1998. Due to the large number of variables from this source, the data were divided into into three separate data files. Data include information on population, vital statistics, school enrollment, educational attainment, Social Security, labor force, personal income, poverty, housing, trade, farms, ancestry, commercial banks, and transfer payments. Parts 85-106 provide data from the United States Census of Agriculture for 1910 to 2002. They provide data about the amount, types, and prices of various agricultural products. Also, these datasets contain extensive information on the amount, expenses, sales, values, and production of farms and machinery. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR02896.v3. We highly recommend using the ICPSR version, as they made this dataset available in multiple data formats and updated the data through 2002.

From the mid-19th century until today, life expectancy at birth in the United States has roughly doubled, from 39.4 years in 1850 to 79.6 years in 2025. It is estimated that life expectancy in the U.S. began its upward trajectory in the 1880s, largely driven by the decline in infant and child mortality through factors such as vaccination programs, antibiotics, and other healthcare advancements. Improved food security and access to clean water, as well as general increases in living standards (such as better housing, education, and increased safety) also contributed to a rise in life expectancy across all age brackets. There were notable dips in life expectancy; with an eight year drop during the American Civil War in the 1860s, a seven year drop during the Spanish Flu empidemic in 1918, and a 2.5 year drop during the Covid-19 pandemic. There were also notable plateaus (and minor decreases) not due to major historical events, such as that of the 2010s, which has been attributed to a combination of factors such as unhealthy lifestyles, poor access to healthcare, poverty, and increased suicide rates, among others. However, despite the rate of progress slowing since the 1950s, most decades do see a general increase in the long term, and current UN projections predict that life expectancy at birth in the U.S. will increase by another nine years before the end of the century.

The study’s theme: The development of infant mortality in Germany for the 19th century is only poorly documented. Especially for the period prior to 1871 only small area statistics are available. With the preparation of the information collected by the authorities of the former German States the author tries to create a new statistical basis. The reconstructed national series of birth and infant mortality (from 1826) documents relatively high infant mortality rates with little progress (i.e. improvement of the situation) until the beginning of the 20th Century. Considering the influence of urbanization the evaluation of the different regional patterns and trends leads to a new weighting of the problem. Thus the living and working conditions in the country were of considerable importance. Overall, the prevailing habits and attitudes are considered crucial to the survival of small children (Gehrmann 2011, S. 807)

Data and data preparation, source problems: The federal structure of the Empire leads to the problem that the printed statistics on infant mortality before 1901 remained incomplete. In some German states, information concerning infant mortality was not collected from the beginning of the registry offices. However, the ‘Kaiserliches Statistisches Amt’ (Imperial Statistical Office) was able to create despi9te the difficult situation a life table, which represented 97,3% of live birth for the period of 1872 to 1880. Hence, the annual infant mortality rate in 1872 is known. „Die föderale Struktur des Kaiserreichs hatte (…) zur Folge, dass die gedruckte Statistik zur Säuglingssterblichkeit vor 1901 lückenhaft blieb. Mehr noch: es wurden offensichtlich in einigen Staaten diesbezügliche Angaben gar nicht oder zumindest nicht von Anfang an bei den Standesämtern abgefragt. Als das Kaiserliche Statistische Amt in den 1880er Jahren die erste Sterbetafel für das Deutsche Reich erstellen wollte, musste es deshalb konstatieren, dass in den Einzelstaaten „fast alle in der Statistik überhaupt üblichen Arten und Grade der Spezialisierung vertreten“ (Kaiserliches Statistisches Amt 1887: 21) waren, aus manchen aber trotzdem keine geeigneten Unterlagen beschafft werden konnten. Immerhin repräsentierte die Sterbetafel am Ende doch 96,8% der Reichsbevölkerung im Jahre 1885 und 97,3% der Lebendgeborenen 1872 bis 1880. Damit ist auch die jährliche Säuglingssterblichkeitsrate ab 1872 bekannt. (…) Mit Hilfe des Sterbetafel-Materials kann die statistische Reihe aus „Bevölkerung und Wirtschaft“ also um fast 30 Jahre nach hinten verlängert werden. (…) Komplizierter stellt sich die Sachlage für weiter zurückliegende Zeitabschnitte dar. „ (S. 812-813) Although in most German states statistical collection on population movement has been carried out, the statistics vary considerably in quality. In the first step therefore, the author reject the procedure of simply extrapolating the birth rates because of the qualitative differences of the early statistics are too fundamental. Especially, in this approach of simply summing up, the values of the undocumented areas would equate with the values of the other well documented regions. Therefore, the author chose a complex way to estimate the lacking values: The missing values in small territories are estimated on the basis of the values of neighboring regions. Finally, it can be seen, that the data for the period from 1828 to 1871, calculated by the complex procedure of filling in missing data does not lead to significantly different results comparing to the data row calculated by the simple sum of the different sources. Per year, the difference between the two series (the series calculated in the complex way and the series calculated by summing up the values of the available statistics) is not more than 0,9 percent points, which can be seen as a slight difference between the two series in relation to the former level of infant mortality. The indeterminate values of those German states lacking a birth statistics may not being significantly different to those calculated on the basis of the complex procedure, because even unexpected, extreme runaway values in individual states can not realistically assumed to be so large that they could have a sufficient impact on the overall values. Thus, the presented row is a solid basis for the assessment of the overall development of the German Empire’s birth development. „Vielmehr empfiehlt es sich, zunächst in kleinen Schritten für die einzelnen Territor...

The probability of dying between birth and the exact age of 1, expressed per 1,000 live births. The data is sorted by both sex and total and includes a range of values from 1900 to 2019. The calculation for infant mortality rates is derived from a standard period abridged life table using the age-specific deaths and mid-year population counts from civil registration data. This data is sourced from the UN Inter-Agency Group for Child Mortality Estimation. The UN IGME uses the same estimation method across all countries to arrive at a smooth trend curve of age-specific mortality rates. The estimates are based on high quality nationally representative data including statistics from civil registration systems, results from household surveys, and censuses. The child mortality estimates are produced in conjunction with national level agencies such as a country’s Ministry of Health, National Statistics Office, or other relevant agencies.

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.

Liver cirrhosis is a chronic disease, which occurs when long-term damage and scarring to the liver prevents it from functioning to its full capacity. Although the human liver is the only organ with the capacity to regenerate itself; there is no cure for liver cirrhosis, however the effects of the condition can be slowed and even minimalized by removing the cause of the damage. The most common causes of liver cirrhosis are alcohol abuse and hepatitis. While hepatitis can be combatted with vaccinations and medication, alcohol abuse can be more complicated due to the psychological impact it has on the user. The prevention of alcohol abuse and its side-effects was one of the major aims of the Prohibition movement in the United States in the 1920s, and records show that the number of deaths due to liver cirrhosis decreased greatly during the Prohibition era, and rose again following Prohibition's repeal in 1933. In the early 1900s, the death rate due to cirrhosis of the liver was as high as 14.8 deaths per 100,000 people, however it gradually fell in the wartime Prohibition of the First World War, and then plateaued at half of this level, between 7.1 and 7.5 deaths per 100,000 people, during federal Prohibition in the 1920s and early 1930s. After Prohibition was repealed at the end of 1933, deaths due to liver cirrhosis increased again, and by the late 1960s, the rate was consistently double it's Prohibition era level.

In 1919, there were almost 13 deaths from measles per 100,000 population in the United States. However, this rate had dropped to zero by the year 2021. In early 2025, an outbreak of measles in Texas resulted in the death of a child. This was the first measles death in the United States since 2015. Measles is a highly contagious disease, that is especially dangerous for children. However, vaccines have significantly decreased the rate of cases and deaths in the United States.

O objetivo é analisar o efeito da idade, período e coorte (APC) na mortalidade por câncer de ovário nas regiões Sul e Nordeste do Brasil. Os modelos APC foram estimados por regressão de Poisson por meio de funções estimáveis em mulheres com 30 anos ou mais residentes nos estados das regiões Sul e Nordeste. Estimados os modelos APC, verificou-se aumento nas taxas de mortalidade com o avançar da idade em todas as localidades. A região Sul apresentou redução do risco de morte nos dois últimos períodos (RR2010-2014 0,94; RR2015-2019 0,90, p<0,001) e redução do risco nas coortes de 1900 a 1929 (RR1900-04 0,55, RR1925-1929 0,89, p<0,001); perfil semelhante foi observado em todos os estados. No Nordeste, houve aumento progressivo do risco de morte nos últimos períodos, variando de 1,02 a 1,11 (2010-2014 vs. 2015-2019, p<0,001). E aumento do risco de morte nas coortes mais jovens, variando de 0,31 a 1,54 (1900-1904 vs. 1985-1989). Resultados semelhantes foram observados na maioria de seus estados isso pode estar correlacionado com os diferentes ritmos do processo de envelhecimento populacional e com as mudanças no comportamento reprodutivo das mulheres dessas duas regiões, realidade intrinsecamente ligada ao desenvolvimento socioeconômico e ao acesso aos serviços de saúde. The scope of this study was to conduct an analysis on the effect of the Age-Period-Cohort (APC) on ovarian cancer mortality in the South and Northeast regions of Brazil. The APC models were estimated by Poisson regression through estimable functions in women aged 30 and over residing in the states of the South and Northeast regions. Upon estimating the APC models, a positive gradient was found in mortality rates with advancing age in all locations The South region showed a reduction in the risk of death in the last two periods (RR2010-2014 0.94; RR2015-2019 0.90, p<0.001) and a reduction in risk in the cohorts from 1900 to 1929 (RR1900-04 0.55, RR1925-1929 0.89, p<0.001); a similar profile was observed in all states. In the Northeast, there was a progressive increase in the risk of death in the last periods, ranging from 1.02 to 1.11 (2010-2014 vs. 2015-2019, p<0.001). An increased risk of death was observed in younger cohorts, varying from 0.31 to 1.54 (cohort 1900-1904 vs. 1985-1989). Similar results were observed in most of the states.: The conclusion drawn is that heterogeneity in the APC effect on ovarian cancer mortality, which may be correlated with the different rates of the population aging process, changes in the reproductive behavior of women, and inequalities in access to health services. El objetivo es analizar el efecto de la edad, período y cohorte (EPC) sobre la mortalidad por cáncer de ovario en las regiones Sur y Nordeste de Brasil. Se estimaron modelos EPC mediante regresión de Poisson utilizando funciones estimables en mujeres de 30 años o más residentes en los estados de las regiones Sur y Nordeste. Luego de estimar los modelos EPC, se observó un aumento en las tasas de mortalidad con el avance de la edad en todas las localidades. La región Sur mostró una reducción del riesgo de muerte en los dos últimos periodos (RR2010-2014 0,94; RR2015-2019 0,90, p<0,001) y una reducción del riesgo en las cohortes de 1900 a 1929 (RR1900-04 0,55; RR1925-1929 0,89, p<0,001); Se observó un perfil similar en todos los estados. En el Nordeste, se observó un aumento progresivo del riesgo de muerte en los últimos períodos, variando de 1,02 a 1,11 (2010-2014 vs. 2015-2019, p<0,001). Y un mayor riesgo de muerte en cohortes más jóvenes, que oscila entre 0,31 y 1,54 (1900-1904 frente a 1985-1989). Resultados similares se observaron en la mayoría de sus estados, lo que puede estar correlacionado con las diferentes tasas del proceso de envejecimiento poblacional y con los cambios en el comportamiento reproductivo de las mujeres en estas dos regiones, realidad intrínsecamente ligada al desarrollo socioeconómico y al acceso a los servicios de salud. Supplementary Material Table 1. Characterization of states in the South and Northeast regions according to sociodemographic variables, health indicators and access to health services, Brazil. Supplementary Material Table S2. Analysis of the Akaike Information Criterion (AIC) in the sequential construction of age, period and cohort models for ovarian cancer fitting by estimable functions, Northeast and South, Brazil, 1980-2019. Supplementary Material Table 1. Characterization of states in the South and Northeast regions according to sociodemographic variables, health indicators and access to health services, Brazil. Supplementary Material Table S2. Analysis of the Akaike Information Criterion (AIC) in the sequential construction of age, period and cohort models for ovarian cancer fitting by estimable functions, Northeast and South, Brazil, 1980-2019. Supplementary Material Table 1. Characterization of states in the South and Northeast regions according to sociodemographic variables, health indicators and...

This statistic shows the number of famine deaths per100,000 people worldwide from 1900 to 2010. In the 1920s, about 814 people per 100,000 of the global population died as a result of famine.