In the United States, the leading causes of death among women are heart disease and cancer. Heart disease and cancer are similarly the leading causes of death among U.S. men. In 2023, heart disease accounted for **** percent of all deaths among women in the United States, while cancer accounted for **** percent of deaths. COVID-19 was the third leading cause of death among women in 2020 and 2021, and the fourth leading cause in 2022, however, by 2023 it had dropped to ninth place. Cancer among women in the U.S. The most common types of cancer among U.S. women are breast, lung and bronchus, and colon and rectum. In 2025, there were around ******* new breast cancer cases among women, compared to ******* new cases of lung and bronchus cancer. Although breast cancer is the most common form of cancer among women in the United States, lung and bronchus cancer causes the highest number of cancer deaths. In 2025, around ****** women were expected to die from lung and bronchus cancer, compared to ****** from breast cancer. Breast cancer Although breast cancer is the second most deadly form of cancer among women, rates of death have decreased over the past few decades. This decrease is possibly due to early detection, progress in therapy, and increasing awareness of risk factors. In 2023, the death rate due to breast cancer was **** per 100,000 population, compared to a rate of **** per 100,000 in the year 1990. The state with the highest rate of deaths due to breast cancer is Oklahoma, while South Dakota had the lowest rates.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.

Heart disease is currently the leading cause of death in the United States. In 2022, COVID-19 was the fourth leading cause of death in the United States, accounting for almost six percent of all deaths that year. The leading causes of death worldwide are similar to those in the United States. However, diarrheal diseases and neonatal conditions are major causes of death worldwide, but are not among the leading causes in the United States. Instead, accidents and chronic liver disease have a larger impact in the United States.

Racial differences

In the United States, there exist slight differences in leading causes of death depending on race and ethnicity. For example, assault, or homicide, accounts for around three percent of all deaths among the Black population but is not even among the leading causes of death for other races and ethnicities. However, heart disease and cancer are still the leading causes of death for all races and ethnicities.

Leading causes of death among men vs women

Similarly, there are also differences in the leading causes of death in the U.S. between men and women. For example, among men, intentional self-harm accounts for around two percent of all deaths but is not among the leading causes of death among women. On the other hand, influenza and pneumonia account for more deaths among women than men.

Leading Causes of Death US

1980–2009 by Sex, Race, and Hispanic Origin

By Health [source]

About this dataset

This fascinating dataset takes a look at the leading causes of death in the United States from 1980-2009, broken down by sex, race, and Hispanic origin. This data sheds light on how mortality in the US has changed over time among these categories. Accounting for everything from heart disease to cancer to suicide, this insight can be used by health researchers and policy makers to gain a better understanding of disparities in healthcare and deaths across different groups. Whether studying questions related to public health or more targeted population issues such as gender biases in death rates, this dataset provides an important resource for anyone interested in examining mortality across demographic lines

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How to use the dataset

This dataset can be used to explore some of the leading causes of death in the United States from 1980 to 2009, broken down by sex, race, and Hispanic origin. This data can be used to better understand mortality trends and risk factors associated with different populations in America.

By using this dataset you can compare and contrast mortality rates across different gender, racial, and ethnic groups during this time period. You can also compare different causes of death within these demographic categories to see if there are any patterns over time or notable differences between groups.

You could even use this data to track changes across population groups as a whole or look at details for specific years or types of causes of death in particular groups. With this information one may gain insight into health disparities across population segments in America— aiding advocates for social change & public policy shifts toward improved health outcomes for all Americans!

Research Ideas

• Analyzing regional or state-level differences in mortality rates over time.
• Examining the beahvioral factors or risk factors associated with each cause of death for different genders and populations.
• Examining the prevalence of each cause of death as a proportion to an overall population trend in different socio-economic categories such as race or income level

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Selected_Trend_Table_from_Health_United_States_2011._Leading_causes_of_death_and_numbers_of_deaths_by_sex_race_and_Hispanic_origin_United_States_1980_and_2009.csv | Column name | Description | |:-------------------|:---------------------------------------------------------------------------------------------------------| | Group | The group of people the cause of death applies to (e.g. men, women, whites, blacks, hispanics). (String) | | Year | The year the cause of death was recorded. (Integer) | | Cause of death | The cause of death. (String) | | Flag | A flag indicating whether the cause of death is considered a leading cause. (Boolean) | | Deaths | The number of deaths attributed to the cause of death. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Health.

In 2024, malignant neoplasms were the leading cause of death among the male population in Japan at around ******* cases. This number accounted for approximately **** percent of the death cases of men recorded during that year. Heart diseases, excluding hypertensive heart diseases, followed with a share of around **** percent. Malignant neoplasmsIn recent years, malignant neoplasms have been the leading cause of death for both female and male populations in Japan. The most frequent cause of cancerous tumor related deaths has continued to be lung cancer for both men and women. As smoking and passive smoking are some of the main causes of lung cancer, the health ministry in Japan set the goal of reducing the smoking rate of adults. To minimize the risk of passive smoking, the government amended the Health Promotion Act and prohibited smoking in public facilities, offices, most restaurants, and public areas starting from April 2020. SuicideOne of the leading causes of death specific to men in Japan was suicide. In the last decade, the number of suicides committed by men in Japan remained roughly double the number of those committed by women. While close to half of the suicides in Japan were committed due to health reasons in previous years, the number of suicides owning to work-related problems has also become a serious social issue in the current Japanese society. One of the reasons behind it is said to be the working condition of employees in Japan with a severe workload. The government has been aiming to reduce working hours and overtime to improve the working conditions of workers in Japan.

Number of deaths and age-specific mortality rates for selected grouped causes, by age group and sex, 2000 to most recent year.

The objective of this paper is to analyze the differential mortality between sexes, in the southern Minas Gerais, Brazil, in 2002 and 2012. Mortality data and information on population were collected at the website of the Department of the Unified Health System (DATASUS). To measure the difference in mortality between the sexes were analyzed the sex ratio between specific mortality rates, the gap in life expectancy at birth and the contribution of different ages in the hiatus in life expectancy at birth. In addition, it was investigated the main causes of death by sex, which affect the general population and in each age group. The results show that while life expectancy at birth increases, the gap in life expectancy has decreased. Furthermore, despite high sex ratio between specific mortality rates of young, the elderly are the main responsible for increases in mortality differentials. Moreover, the main causes of death in the region are Cardiovascular diseases, cancer and respiratory diseases, which affects more intensely the elderly. In general, characteristics of an aging population and in advanced stages of epidemiological transition are already observed in the region.

Cause of death distribution across sample, % of all deaths for men and women separately.

BackgroundOur current understanding of Asian American mortality patterns has been distorted by the historical aggregation of diverse Asian subgroups on death certificates, masking important differences in the leading causes of death across subgroups. In this analysis, we aim to fill an important knowledge gap in Asian American health by reporting leading causes of mortality by disaggregated Asian American subgroups.Methods and FindingsWe examined national mortality records for the six largest Asian subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese) and non-Hispanic Whites (NHWs) from 2003-2011, and ranked the leading causes of death. We calculated all-cause and cause-specific age-adjusted rates, temporal trends with annual percent changes, and rate ratios by race/ethnicity and sex. Rankings revealed that as an aggregated group, cancer was the leading cause of death for Asian Americans. When disaggregated, there was notable heterogeneity. Among women, cancer was the leading cause of death for every group except Asian Indians. In men, cancer was the leading cause of death among Chinese, Korean, and Vietnamese men, while heart disease was the leading cause of death among Asian Indians, Filipino and Japanese men. The proportion of death due to heart disease for Asian Indian males was nearly double that of cancer (31% vs. 18%). Temporal trends showed increased mortality of cancer and diabetes in Asian Indians and Vietnamese; increased stroke mortality in Asian Indians; increased suicide mortality in Koreans; and increased mortality from Alzheimer’s disease for all racial/ethnic groups from 2003-2011. All-cause rate ratios revealed that overall mortality is lower in Asian Americans compared to NHWs.ConclusionsOur findings show heterogeneity in the leading causes of death among Asian American subgroups. Additional research should focus on culturally competent and cost-effective approaches to prevent and treat specific diseases among these growing diverse populations.

Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.

BackgroundPatients with atrial fibrillation are known to have a high risk of mortality. There is a paucity of population-based studies about the impact of atrial fibrillation on the mortality risk stratified by age, sex, and detailed causes of death.MethodsA total of 15,411 patients with atrial fibrillation from the Korean National Health Insurance Service-National Sample Cohort were enrolled, and causes of death were identified according to codes of the 10th revision of the International Classification of Diseases.ResultsFrom 2002 to 2013, a total of 4,479 (29%) deaths were confirmed, and the crude mortality rate for all-cause death was 63.3 per 1,000 patient-years. Patients with atrial fibrillation had a 3.7-fold increased risk of all-cause death compared with the general population. The standardized mortality ratio for all-cause death was the highest in young patients and decreased with increasing age (standardized mortality ratio 21.93, 95% confidence interval 7.60–26.26 in patients aged <20 years; standardized mortality ratio 2.77, 95% confidence interval 2.63–2.91 in patients aged ≥80 years). Women with atrial fibrillation exhibited a greater excess mortality risk than men (standardized mortality ratio 3.81, 95% confidence interval 3.65–3.98 in women; standardized mortality ratio 3.35, 95% confidence interval 3.21–3.48 in men). Cardiovascular disease was the leading cause of death (38.5%), and cerebral infarction was the most common specific disease. Patients with atrial fibrillation had an about 5 times increased risk of death due to cardiovascular disease compared with the general population.ConclusionsPatients with atrial fibrillation had a 4 times increased risk of mortality compared with the general population. However, the impact of atrial fibrillation on mortality decreased with age and in men. Cerebral infarction was the most common cause of death, and more attention should be paid to reducing the risk of stroke.

Obesity traits are causally implicated with risk of cardiometabolic diseases. It remains unclear whether there are similar causal effects of obesity traits on other non-communicable diseases. Also, it is largely unexplored whether there are any sex-specific differences in the causal effects of obesity traits on cardiometabolic diseases and other leading causes of death. We constructed sex-specific genetic risk scores (GRS) for three obesity traits; body mass index (BMI), waist-hip ratio (WHR), and WHR adjusted for BMI, including 565, 324, and 337 genetic variants, respectively. These GRSs were then used as instrumental variables to assess associations between the obesity traits and leading causes of mortality in the UK Biobank using Mendelian randomization. We also investigated associations with potential mediators, including smoking, glycemic and blood pressure traits. Sex-differences were subsequently assessed by Cochran’s Q-test (Phet). A Mendelian randomization analysis of 228,466 women and 195,041 men showed that obesity causes coronary artery disease, stroke (particularly ischemic), chronic obstructive pulmonary disease, lung cancer, type 2 and 1 diabetes mellitus, non-alcoholic fatty liver disease, chronic liver disease, and acute and chronic renal failure. Higher BMI led to higher risk of type 2 diabetes in women than in men (Phet = 1.4×10−5). Waist-hip-ratio led to a higher risk of chronic obstructive pulmonary disease (Phet = 3.7×10−6) and higher risk of chronic renal failure (Phet = 1.0×10−4) in men than women. Obesity traits have an etiological role in the majority of the leading global causes of death. Sex differences exist in the effects of obesity traits on risk of type 2 diabetes, chronic obstructive pulmonary disease, and renal failure, which may have downstream implications for public health.

Risk of death from all causes, cardiovascular disease (CVD), and cancer in men compared to women (reference group), both for the total population and stratified by hepatitis C virus (HCV) infection status.

Global Cause of the Deaths other than diseases

This data was part of the project Global Disease Burden 2017. Data contain the number of deaths within a country and each year along with cause of deaths such conflict and terrorism, famine, pandemic, natural disaster, and Other injuries. These are global causes of deaths other than diseases.

Description of the Data

The data contains 10 columns and 36 K rows, and the description of the data is as follow.. Country: Contains the Names of the Country ISO_CODE: Is the ISO-3 country identification code Year: Year of the number of Deaths Deaths: Total death of the individuals (including both male and female) Cause: Cause of the death such as Conflict and Terrorism Male POP: Male Population with given Country Female POP: Female Population within given country Total Pop: Total Population with each country GDP: GDP (current US$) PCAP: GDP per capita (current US$)

Inspiration

This Data would be helpful to investigate which global cause of death is impacting which country. It would also help to evaluate the rate of change in the causes of death.

Data Visualization

https://public.tableau.com/views/CausedofDeaths1980-2017-GlobalDiseaseBurden/CausesofDeaths?:language=en&:display_count=y&:origin=viz_share_link

The Rufiji Health and Demographic Surveillance System (HDSS) was established in October 1998 to evaluate the impact on burden of disease of health system reforms based on locally generated data, prioritization, resource allocation and planning for essential health interventions. The Rufiji HDSS collects detailed information on health and survival and provides a framework for population-based health research of relevance to local and national health priorities. Monitoring of households and members within households is undertaken in regular 6-month cycles known as 'rounds'. Self-reported information is collected on demographic, household, socioeconomic and geographical characteristics. Verbal autopsies were done by trained Field interviewers to collect detailed data through structured and standardized INDEPTH Network verbal autopsy forms on symptoms and signs during the terminal illness, allowing assignment of cause of death following physician's review to a list of causes of death, based on the 10th Revision of the International Classification of Diseases. From 2008 to 2015 Rufiji HDSS recorded about 5500 deaths. About 90% of them were interviewed and assigned the underlying cause of death. The Ifakara Health Institute VA data portal will be periodically updated depending on the availability of new data from the field. Face-to-face interview At the initial census (October 1998-anuary 1999), all individuals who were intending to be resident in the DSA for at least 4 months were eligible for inclusion. Verbal consent to participate in the census was sought from the head of every household. Definitions of several characteristics such as household, membership, migration and head of household are set in order to correctly assign individuals or households to events or attributes. A household in Rufiji HDSS is defined as a group of individuals sharing, or who eat from, the same cooking pot. A member of the HDSS is defined as someone who has been resident in the DSA for the preceding 4 months. New members qualify to be an in-migrant if s/he moves into the Rufiji HDSS and spends at least 4 months there. Women married to men living in the Rufiji HDSS and children born to these women qualify to be members of the Rufiji HDSS. In the case of multiple wives, the husband will be registered as a permanent resident in only one household. He will be linked to other wives by his husband identification number given to his wives. After the census, the study population is visited three times a year in cycles or updated rounds over February-May, June-September and October-January to update indicators. From July 2013 onwards, Rufiji HDSS switched to two data collection rounds per year, which happen in July-December and January-June. Mapping of households and key structures such as schools, health facilities, markets, churches and mosques was done by field interviewers using handheld global positioning systems (GPS). Updating of GPS coordinates has been an ongoing exercise especially for new structures and for demolished structures. In 2012 the population size of the DSA was about 103 503 people, residing in 19 315 households. There are several ethnic groups in the DSA. The largest is the Ndengereko; other groups include the Matumbi, Nyagatwa, Ngindo, Pogoro and Makonde. The population comprises mainly Muslims with few Christians and followers of traditional religions. The main language spoken is Kiswahili. English is not commonly used in the area. Around 75% of the population aged 7-15 years have attended primary education, 14% of those in age group 15-65 years have secondary education and only 1% of the population has tertiary education. Almost 50% of the adult population aged 15-65 are self-employed in agriculture, 28% engage in other small economic activities, 16% are selfemployed in small-scale business and 6% are unemployed. Fuel wood is the main source of energy for cooking and shallow wells are the main source of water for domestic use. The household heads in Rufiji HDSS are considered as breadwinners and most (67.3%) are male. Active community engagement programmes are in place which include key informants (KIs) days, where the HDSS team convenes meetings with KIs for presentations on recent findings to feed back to community and for distribution of newsletters to households. Community sensitization events are held at the time of introducing new studies. These initiatives have cemented good relationships with the community and eventually maintained high participation. In Health and Demographic Surveillance System (HDSS), the follow-up of individuals aged 1559years was categorized into three periods: before ART (19982003), during ART scale-up (20042007), and after widespread availability of ART (20082011). Residents were those who never migrated within and beyond HDSS, internal migrants were those who moved within the HDSS, and external migrants were those who moved into the HDSS from outside. Mortality rates were estimated from deaths and person-years of observations calculated in each time period. Hazard ratios were estimated to compare mortality between migrants and residents. AIDS deaths were identified from verbal autopsy, and the odds ratio of dying from AIDS between migrants and residents was estimated using the multivariate logistic regression model.

BackgroundInequalities between men and women in morbidity and mortality show a contrast, which has been called gender paradox. Most studies evaluating this paradox were conducted in high-income countries and, until now, few investigations have been performed in Brazil. This study aims to estimate the magnitude of inequalities between adult men and women in several dimensions: demographic and socioeconomic, health behaviors, morbidity, use of health services and mortality.MethodsThe data were obtained from population-based household survey carried out in Campinas (Campinas Health Survey 2008/09) corresponding to 957 people, and data from the Mortality Information System (MIS) between 2009 and 2011. Prevalences and prevalence ratios were analyzed in order to verify the differences between men and women regarding socioeconomic and demographic variables, health behaviors, morbidities and consultations in the last two weeks. Mortality rates and the ratio between coefficients considering the underlying causes of death were calculated.ResultsWomen had a greater disadvantage in socioeconomic indicators, chronic diseases diagnosed by a health professional and referred health problems as well as make more use of health services, while men presented higher frequency of most unhealthy behaviors and excessive mortality for all causes investigated.ConclusionsThe findings contribute to the discussion of gender paradox and demonstrate the need to employ health actions that consider the differences between men and women in the various health dimensions analyzed. The premature male mortality from preventable causes was outstanding, making clear the need for more effective prevention and health promotion directed to this segment of the population.

Abstract Mortality indicators for Brazilians aged between 10 and 24 years old were analyzed. Data were obtained from the Global Burden of Disease (GBD) 2019 Study, and absolute numbers, proportion of deaths and specific mortality rates from 1990 to 2019 were analyzed, according to age group (10 to 14, 15 to 19 and 20 to 24 years), sex and causes of death for Brazil, regions and Brazilian states. There was a reduction of 11.8% in the mortality rates of individuals aged between 10 and 24 years in the investigated period. In 2019, there were 13,459 deaths among women, corresponding to a reduction of 30.8% in the period. Among men there were 39,362 deaths, a reduction of only 6.2%. There was an increase in mortality rates in the North and Northeast and a reduction in the Southeast and South states. In 2019, the leading cause of death among women was traffic injuries, followed by interpersonal violence, maternal deaths and suicide. For men, interpersonal violence was the leading cause of death, especially in the Northeast, followed by traffic injuries, suicide and drowning. Police executions moved from 77th to 6th place. This study revealed inequalities in the mortality of adolescents and young adults according to sex, causes of death, regions and Brazilian states.

ICD10h2024.2 (this version, published June 2025) incorporates the following changes: - Manual: new preface to list changes to files; changes relating to code changes; a small number of other corrections and improvements. - Masterlist (see 2025MasterlistChanges): 9 new codes added, 5 codes deleted, and 17 changes made to ICD10 or ICD10h descriptions. - Transferfile (see 2025TransferfileChanges): 47 errors were fixed. - InfantCat (see 2025InfantCatChanges): 17 ICD10h codes were updated. - Historic Strings English (see 2025HistoricStringsEnglishChanges): 14 changes were made to ICD10h or ICD10hInjury codes were made. ICD10hDescription and ICD10hInjuryDescription columns were deleted.

This file contains the list of codes and general categories associated with the ICD10h (Historic cause of death coding and classification scheme for individual-level causes of death). ICD10h has been designed by the authors to aid the coding and classification of causes of death recorded on historic individual death records and associated files include a manual, a list of exemplar strings in the English language, and a categorisation for infant mortality. The ICD10h system is based on the 10th revision of the International Classification of Diseases - 2016 version (ICD10 - 2016), and combines ICD10 codes (without modification) with new codes for archaic/historic terms. The data was derived from the following projects/deposited data: Determining the Demography of Victorian Scotland Through Record Linkage, ESRC RES-000-23-0128 held at the Cambridge Group for the History of Population and Social Structure, University of Cambridge; P. Gunn and R. Kippen, ‘Household and Family Formation in Nineteenth-Century Tasmania, Dataset of 195 Thousand Births, 93 Thousand Deaths and 51 Thousand Marriages Registered in Tasmania, 1838-1899’, 2008.

The resource creation was supported by the following projects: Digitising Scotland/Scottish Health Informatics Project (funded by the ESRC); Studying Health in Port Cities (funded by The Netherlands Organisation for Scientific Research); The Great Leap (funded by COST-Action CA22116).

SHARING/ACCESS INFORMATION

This resource is available under a CC BY licence.

Recommended citation for this dataset: Historic cause of death coding and classification scheme for individual-level causes of death – Codes [https://doi.org/10.17863/CAM.109961]

Please see the associated resources: Historic cause of death coding and classification scheme for individual-level causes of death – manual [https://doi.org/10.17863/CAM.109960] Historic cause of death coding and classification scheme for individual-level causes of death – English language historic strings [https://doi.org/10.17863/CAM.109962] Historic cause of death coding and classification scheme for individual-level causes of death – Infant Categorisations [https://doi.org/10.17863/CAM.109963]

ICD10h is a research tool created to facilitate the study of historical cause of death records and should not be used for any official purpose. It is based on the International Classification of Diseases, 10th Revision (ICD-10) version 2016 (Geneva: World Health Organization 2016) but is not a recognised version or extension of ICD-10 and is not authorised by WHO. However we have consulted with WHO: they recognise that ICD10h is a useful academic methodology and have not raised any objections to its creation. Data coded using ICD10h are not directly comparable with data coded in ICD-10, and the underlying or primary cause of death derived using the ICD10h methodology may be different from the underlying cause derived in ICD-10 according to the WHO rules. Please note that ICD-10 version 2016 is not the most recent version of ICD-10; and that WHO now recommend the use of ICD-11; a more advanced and detailed classification.

DATA & FILE OVERVIEW

ICD10h_Masterlist.xlsx Excel file consisting of 3 worksheets: 1) ReadMe sheet 2) Masterlist
3) 2020to2024transfer

Separate csv files for 2) and 3) containing the same information.

This file builds on a previous, unpublished version of ICD10h (dating from 2020). The 2020to2024transfer file enables data coded to the earlier version to be updated to the current version.

METHODOLOGICAL INFORMATION

The data were hand-coded and subject to stringent algorithm-assisted tests.

DATA-SPECIFIC INFORMATION FOR: Masterlist

Number of variables: 10

Number of cases/rows: 14088

Variable List: IDMasterlist (a unique ID number for Masterlist table) ICD10h (ICD10h code) ICD10 (ICD10 code) ICD10_2levelCATEGORY (ICD10 first part of 2 level categorisation) ICD10_2levelCAUSE (ICD10 second part of 2 level categorisation) ICD10h_DESCRIPTION (ICD10h description - this differs from ICD10_2levelCAUSE only where there is a specific historical code) Histcat (category of general historical categorisation) DoNotUse (1=do not use for mortality coding – ICD10 asterisk codes) NotForUnderlying (1=do not use for underlying mortality codes) GenderSpecific (0=can be used for men or women; 1=use for men only; 2=use for women only)

DATA-SPECIFIC INFORMATION FOR: 2020to2024transfer

Number of variables: 4

Number of cases/rows: 13763

Variable List: ID2024_transfer (unique ID for 2020to2024transfer table) IDoct2020Masterlist (ID variable from the 2020 Masterlist) ICD10h_oct2020 (ICD10h from the October 2020 Masterlist) ICD10h2024 (ICD10h value from the current version of the Masterlist)

The main cause of death in Russia of individuals at working age turned out to be diseases of the circulatory system in 2021 among ***** thousand men and **** thousand women. Overall, the mortality rate among men was significantly greater in every category.