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 2023, malignant neoplasms were the leading cause of death among the female population in Japan at around ******* deaths. This number accounted for **** percent of the death cases of women during that year. Senility followed with a share of **** percent.

This statistic presents the global death rates for the leading causes of deaths among females aged 15 to 19 years in 2015, per 100,000 population. Maternal conditions emerged as the leading cause of global deaths among adolescent females aged 15 to 19 years with a death rate of **** per 100,000 population, followed by self-harm and road injury.

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.

Abstract The aim of this study is to analyze the trend of the main causes of death of women of reproductive age (WRA) in Brazil by age group from 2006 to 2019. Data used are from the Mortality Information System (SIM) and the Brazilian Institute of Geography and Statistics (IBGE) of Brazil. The main causes of death of WRA (10 to 49 years) were divided by chapters as per the International Statistical Classification of Diseases and Related Health Problems (ICD-10). Subsequently, a temporal trend analysis was performed using polynomial regression models for the main causes of death in WRA. In Brazil, the highest mortality rates by cause by 100,000 WRA occurred due to: neoplasms (25.34), diseases of the circulatory system (20.15), external causes (18.69), infectious and parasitic diseases (8.79) and respiratory system diseases (6.37). For the analyzed period, after standardization, the mortality rate due to diseases of the circulatory and respiratory systems, and infectious and parasitic conditions showed a decreasing trend, with a significant drop of 26.6% for diseases of the circulatory system; while external causes and neoplasms showed an increasing trend from 2006 to 2012 and decreasing from 2013 onwards. Identifying the main causes of death of WRA in each age group is required to guide the planning of actions to optimize resources and obtain better results in women’s health.

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.

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.

In 2021, ischaemic heart disease caused approximately ****** deaths among females in the Philippines. The other leading causes of mortality among Filipino women were neoplasms, cerebrovascular diseases, diabetes mellitus, and pneumonia.

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

BackgroundCardiovascular disease (CVD) is the leading cause of morbidity and mortality among older postmenopausal women. The impact of postmenopausal breast cancer on CVD for older women is uncertain. We hypothesized that older postmenopausal women with breast cancer would be at a higher risk of CVD than similar aged women without breast cancer and that CVD would be a major contributor to the subsequent morbidity and mortality.MethodsIn a prospective Women’s Health Initiative study, incident CVD events and total and cause-specific death rates were compared between postmenopausal women with (n = 4,340) and without (n = 97,576) incident invasive breast cancer over 10 years post-diagnosis, stratified by 3 age groups (50–59, 60–69, and 70–79).ResultsPostmenopausal women, regardless of breast cancer diagnosis, had similar and high levels of CVD risk factors (e.g., smoking and hypertension) at baseline prior to breast cancer, which were strong predictors of CVD and total mortality over time. CVD affected mostly women age 70–79 with localized breast cancer (79% of breast cancer cases in 70–79 age group): only 17% died from breast cancer and CVD was the leading cause of death (22%) over the average 10 years follow up. Compared to age-matched women without breast cancer, women age 70–79 at diagnosis of localized breast cancer had a similar multivariate-adjusted hazard ratio (HR) of 1.01 (95% confidence interval [CI]: 0.76–1.33) for coronary heart disease, a lower risk of composite CVD (HR = 0.84, 95% CI: 0.70–1.00), and a higher risk of total mortality (HR = 1.20, 95% CI: 1.04–1.39).ConclusionCVD was a major contributor to mortality in women with localized breast cancer at age 70–79. Further studies are needed to evaluate both screening and treatment of localized breast cancer tailored to the specific health issues of older women.

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.

Australia Cause of Death: by Injury: % of Total data was reported at 5.945 % in 2019. This records an increase from the previous number of 5.857 % for 2015. Australia Cause of Death: by Injury: % of Total data is updated yearly, averaging 5.859 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 5.945 % in 2019 and a record low of 5.589 % in 2010. Australia Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Statistics for the leading causes of cancer deaths in Yunlin County in 2021 (female), including tumors and cancers, etc.

The leading causes of death by sex and ethnicity in New York City in since 2007. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City.

IntroductionThe increasing survival of patients with breast cancer has prompted the assessment of mortality due to all causes of death in these patients. We estimated the absolute risks of death from different causes, useful for health-care planning and clinical prediction, as well as cause-specific hazards, useful for hypothesis generation on etiology and risk factors.Materials and methodsUsing data from population-based cancer registries we performed a retrospective study on a cohort of women diagnosed with primary breast cancer. We carried out a competing-cause analysis computing cumulative incidence functions (CIFs) and cause-specific hazards (CSHs) in the whole cohort, separately by age, stage and registry area.ResultsThe study cohort comprised 12,742 women followed up for six years. Breast cancer showed the highest CIF, 13.71%, and cardiovascular disease was the second leading cause of death with a CIF of 3.60%. The contribution of breast cancer deaths to the CIF for all causes varied widely by age class: 89.25% in women diagnosed at age

In 2021, stroke was the leading cause of death among women in Mauritania, with **** deaths per 100,000 people. It was followed by ischaemic heart disease, which caused **** deaths, and lower respiratory infections, with **** deaths per 100,000 people.

Demographic Trends and Health Outcomes in the U.S

Inequalities,Risk Factors and Access to Care

By Data Society [source]

About this dataset

This dataset contains key demographic, health status indicators and leading cause of death data to help us understand the current trends and health outcomes in communities across the United States. By looking at this data, it can be seen how different states, counties and populations have changed over time. With this data we can analyze levels of national health services use such as vaccination rates or mammography rates; review leading causes of death to create public policy initiatives; as well as identify risk factors for specific conditions that may be associated with certain populations or regions. The information from these files includes State FIPS Code, County FIPS Code, CHSI County Name, CHSI State Name, CHSI State Abbreviation, Influenza B (FluB) report count & expected cases rate per 100K population , Hepatitis A (HepA) Report Count & expected cases rate per 100K population , Hepatitis B (HepB) Report Count & expected cases rate per 100K population , Measles (Meas) Report Count & expected cases rate per 100K population , Pertussis(Pert) Report Count & expected case rate per 100K population , CRS report count & expected case rate per 100K population , Syphilis report count and expected case rate per 100k popuation. We also look at measures related to preventive care services such as Pap smear screen among women aged 18-64 years old check lower/upper confidence intervals seperately ; Mammogram checks among women aged 40-64 years old specified lower/upper conifence intervals separetly ; Colonosopy/ Proctoscpushy among men aged 50+ measured in lower/upper limits ; Pneumonia Vaccination amongst 65+ with loewr/upper confidence level detail Additionally we have some interesting trend indicating variables like measures of birth adn death which includes general fertility ratye ; Teen Birth Rate by Mother's age group etc Summary Measures covers mortality trend following life expectancy by sex&age categories Vressionable populations access info gives us insight into disablilty ratio + access to envtiromental issues due to poor quality housing facilities Finally Risk Factors cover speicfic hoslitic condtiions suchs asthma diagnosis prevelance cancer diabetes alcholic abuse smoking trends All these information give a good understanding on Healthy People 2020 target setings demograpihcally speaking hence will aid is generating more evience backed policies

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How to use the dataset

What the Dataset Contains

This dataset contains valuable information about public health relevant to each county in the United States, broken down into 9 indicator domains: Demographics, Leading Causes of Death, Summary Measures of Health, Measures of Birth and Death Rates, Relative Health Importance, Vulnerable Populations and Environmental Health Conditions, Preventive Services Use Data from BRFSS Survey System Data , Risk Factors and Access to Care/Health Insurance Coverage & State Developed Types of Measurements such as CRS with Multiple Categories Identified for Each Type . The data includes indicators such as percentages or rates for influenza (FLU), hepatitis (HepA/B), measles(MEAS) pertussis(PERT), syphilis(Syphilis) , cervical cancer (CI_Min_Pap_Smear - CI_Max\Pap \Smear), breast cancer (CI\Min Mammogram - CI \Max \Mammogram ) proctoscopy (CI Min Proctoscopy - CI Max Proctoscopy ), pneumococcal vaccinations (Ci min Pneumo Vax - Ci max Pneumo Vax )and flu vaccinations (Ci min Flu Vac - Ci Max Flu Vac). Additionally , it provides information on leading causes of death at both county levels & national level including age-adjusted mortality rates due to suicide among teens aged between 15-19 yrs per 100000 population etc.. Furthermore , summary measures such as age adjusted percentage who consider their physical health fair or poor are provided; vulnerable populations related indicators like relative importance score for disabled adults ; preventive service use related ones ranging from self reported vaccination coverage among men40-64 yrs old against hepatitis B virus etc...

Getting Started With The Dataset

To get started with exploring this dataset first your need to understand what each column in the table represents: State FIPS Code identifies a unique identifier used by various US government agencies which denote states . County FIPS code denotes counties wi...

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.