According to the findings of a survey by IPSOS, the majority of countries underestimate the proportion of people who die from cancer each year. Those in the Philippines were the most likely to accurately guess the percentage of deaths attributable to cancer in their country. This statistic shows the actual vs public estimates for number of deaths per 100 which occur as a result of cancer worldwide as of 2019, by country.

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The "Cancer and Deaths Dataset: 1990~2019 Globally" is a comprehensive dataset containing information on cancer incidence and mortality rates across the world from 1990 to 2019.

The dataset is an excellent resource for researchers, healthcare professionals, and policymakers who are interested in understanding the global burden of cancer and its impact on populations.

[ Total 9 file , 160 columns, All the countries, 30Years data ]

>In 2017, 9.6 million people are estimated to have died from the various forms of cancer. Every sixth death in the world is due to cancer, making it the second leading cause of death – second only to cardiovascular diseases.1

Progress against many other causes of deaths and demographic drivers of increasing population size, life expectancy and — particularly in higher-income countries — aging populations mean that the total number of cancer deaths continues to increase. This is a very personal topic to many: nearly everyone knows or has lost someone dear to them from this collection of diseases.

## Data vastness of this dataset: 01. annual-number-of-deaths-by-cause data. 02. total-cancer-deaths-by-type data. 03. cancer-death-rates-by-age data. 04. share-of-population-with-cancer-types data. 05. share-of-population-with-cancer data. 06. number-of-people-with-cancer-by-age data. 07. share-of-population-with-cancer-by-age data. 08. disease-burden-rates-by-cancer-types data. 09. cancer-deaths-rate-and-age-standardized-rate-index data.

BackgroundUnderstanding the effects of demographic drivers on lung cancer mortality trends is critical for lung cancer control. We have examined the drivers of lung cancer mortality at the global, regional, and national levels.MethodsData on lung cancer death and mortality were extracted from the Global Burden of Disease (GBD) 2019. Estimated annual percentage change (EAPC) in the age-standardized mortality rate (ASMR) for lung cancer and all-cause mortality were calculated to measure temporal trends in lung cancer from 1990 to 2019. Decomposition analysis was used to analyze the contributions of epidemiological and demographic drivers to lung cancer mortality.ResultsDespite a non-significant decrease in ASMR [EAPC = −0.31, 95% confidence interval (CI): −1.1 to 0.49], the number of deaths from lung cancer increased by 91.8% [95% uncertainty interval (UI): 74.5–109.0%] between 1990 and 2019. This increase was due to the changes in the number of deaths attributable to population aging (59.6%), population growth (56.7%), and non-GBD risks (3.49%) compared with 1990 data. Conversely, the number of lung cancer deaths due to GBD risks decreased by 19.8%, mainly due to tobacco (−12.66%), occupational risks (−3.52%), and air pollution (−3.47%). More lung cancer deaths (1.83%) were observed in most regions, which were due to high fasting plasma glucose levels. The temporal trend of lung cancer ASMR and the patterns of demographic drivers varied by region and gender. Significant associations were observed between the contributions of population growth, GBD risks and non-GBD risks (negative), population aging (positive), and ASMR in 1990, the sociodemographic index (SDI), and the human development index (HDI) in 2019.ConclusionPopulation aging and population growth increased global lung cancer deaths from 1990 to 2019, despite a decrease in age-specific lung cancer death rates due to GBD risks in most regions. A tailored strategy is needed to reduce the increasing burden of lung cancer due to outpacing demographic drivers of epidemiological change globally and in most regions, taking into account region- or gender-specific risk patterns.

In 2019, around 32.8 percent of all deaths globally were caused by cardiovascular diseases and almost 18 percent were caused by cancer. This statistic shows the distribution of causes of death worldwide in 2019.

BackgroundThe exponential growth of the cancer burden attributable to metabolic factors deserves global attention. We investigated the trends of cancer mortality attributable to metabolic factors in 204 countries and regions between 1990 and 2019.MethodsWe extracted data from the Global Burden of Disease Study (GBD) 2019 and assessed the mortality, age-standardized death rate (ASDR), and population attributable fractions (PAFs) of cancers attributable to metabolic factors. Average annual percentage changes (AAPCs) were calculated to assess the changes in the ASDR. The cancer mortality burden was evaluated according to geographic location, SDI quintiles, age, sex, and changes over time.ResultsCancer attributable to metabolic factors contributed 865,440 (95% UI, 447,970-140,590) deaths in 2019, a 167.45% increase over 1990. In the past 30 years, the increase in the number of deaths and ASDR in lower SDI regions have been significantly higher than in higher SDI regions (from high to low SDIs: the changes in death numbers were 108.72%, 135.7%, 288.26%, 375.34%, and 288.26%, and the AAPCs were 0.42%, 0.58%, 1.51%, 2.36%, and 1.96%). Equatorial Guinea (AAPC= 5.71%), Cabo Verde (AAPC=4.54%), and Lesotho (AAPC=4.42%) had the largest increase in ASDR. Large differences were observed in the ASDRs by sex across different SDIs, and the male-to-female ratios of ASDR were 1.42, 1.50, 1.32, 0.93, and 0.86 in 2019. The core population of death in higher SDI regions is the age group of 70 years and above, and the lower SDI regions are concentrated in the age group of 50-69 years. The proportion of premature deaths in lower SDI regions is significantly higher than that in higher SDI regions (from high to low SDIs: 2%, 4%, 7%, 7%, and 9%). Gastrointestinal cancers were the core burden, accounting for 50.11% of cancer deaths attributable to metabolic factors, among which the top three cancers were tracheal, bronchus, and lung cancer, followed by colon and rectum cancer and breast cancer.ConclusionsThe cancer mortality burden attributable to metabolic factors is shifting from higher SDI regions to lower SDI regions. Sex differences show regional heterogeneity, with men having a significantly higher burden than women in higher SDI regions but the opposite is observed in lower SDI regions. Lower SDI regions have a heavier premature death burden. Gastrointestinal cancers are the core of the burden of cancer attributable to metabolic factors.

In 2019, the global death rate of alcohol-associated liver cancer among the elderly was highest in Europe and the Americas, with around 10 and 8 deaths per 100,000 people, respectively. This statistic shows the age-standardized death rate (ASDR) of alcohol-related liver cancer among the elderly worldwide in 2019, by region.

BACKGROUND Comprehensive analyses of statistical data on breast cancer incidence, mortality, and associated risk factors are of great value for decision-making related to reducing the disease burden of breast cancer. METHODS: Based on data from the Annual Report of China Tumour Registry and the Global Burden of Disease (GBD), we conducted summary and trend analyses of incidence and mortality rates of breast cancer in Chinese women from 2014 to 2018 for urban and rural areas in the whole, eastern, central, and western parts of the country, and projected the incidence and mortality rates of breast cancer for 2019 in comparison with the GBD 2019 estimates. And the comparative risk assessment framework estimated risk factors contributing to breast cancer deaths and disability-adjusted life years (DALYs) from GBD. RESULTS: The Annual Report of the Chinese Tumour Registry showed that showed that the mortality rate of breast cancer declined and the incidence rate remained largely unchanged from 2014 to 2018. There was a significant increasing trend in incidence rates among urban and rural women in eastern China and rural women in central China, whereas there was a significant decreasing trend in mortality rates among rural women in China. The two data sources have some differences in their predictions of breast cancer in China in 2019. The GBD data estimated the age-standard DALYs rates of high body-mass index, high fasting plasma glucose and diet high in red meat, which are the top three risk factors attributable to breast cancer in Chinese women, to be 29.99/100,000, 13.66/100,000 and 13.44/100,000, respectively. Conclusion: The trend of breast cancer incidence and mortality rates shown in the Annual Report of China Tumour Registry indicates that China has achieved remarkable results in reducing the burden of breast cancer, but there is still a need to further improve breast cancer screening and early diagnosis and treatment, and to improve the system of primary prevention. The GBD database provides risk factors for breast cancer in the world, Asia, and China, and lays the foundation for research on effective measures to reduce the burden of breast cancer.

In 2019, the global death rate of alcohol-associated liver cancer among the elderly was over four times as high in men compared to women. Men reported over 13 deaths per 100,000 population, while women reported approximately three deaths per 100,000 population. This statistic shows the age-standardized death rate (ASDR) of alcohol-related liver cancer among the elderly worldwide in 2019, by gender.

In 2019, the leading causes of death worldwide were ischemic heart disease, stroke, and chronic obstructive pulmonary disease (COPD). That year, ischemic heart disease and stroke accounted for a combined ** percent of all deaths worldwide. Although the leading causes of death worldwide vary by region and country, heart disease is a consistent leading cause of death regardless of income, development, size, or location. Heart disease In 2019, around **** million people worldwide died from ischemic heart disease. In comparison, around **** million people died from lung cancer that year, while *** million died from diabetes. The countries with the highest rates of death due to heart attack and other ischemic heart diseases are Lithuania, Russia, and Slovakia. Although some risk factors for heart disease, such as age and genetics, are unmodifiable, the likelihood of developing heart disease can be greatly reduced through a healthy lifestyle. The biggest modifiable risk factors for heart disease include smoking, an unhealthy diet, being overweight, and a lack of exercise. In 2019, it was estimated that around *** million deaths worldwide due to ischemic heart disease could be attributed to smoking. The leading causes of death in the United States Just as it is the leading cause of death worldwide, heart disease is also the leading cause of death in the United States. In 2023, heart disease accounted for ** percent of all deaths in the United States. Cancer was the second leading cause of death in the U.S. that year, followed by accidents. As of 2023, the odds that a person in the United States will die from heart disease is * in *. However, rates of death due to heart disease have actually declined in the U.S. over the past couple decades. From 2000 to 2022, there was a *** percent decline in heart disease deaths. On the other hand, deaths from Alzheimer’s disease saw an increase of *** percent over this period. Alzheimer’s disease is currently the sixth leading cause of death in the United States, accounting for **** deaths per 100,000 population in 2023.

Age-standardised rate of mortality from oral cancer (ICD-10 codes C00-C14) in persons of all ages and sexes per 100,000 population.RationaleOver the last decade in the UK (between 2003-2005 and 2012-2014), oral cancer mortality rates have increased by 20% for males and 19% for females1Five year survival rates are 56%. Most oral cancers are triggered by tobacco and alcohol, which together account for 75% of cases2. Cigarette smoking is associated with an increased risk of the more common forms of oral cancer. The risk among cigarette smokers is estimated to be 10 times that for non-smokers. More intense use of tobacco increases the risk, while ceasing to smoke for 10 years or more reduces it to almost the same as that of non-smokers3. Oral cancer mortality rates can be used in conjunction with registration data to inform service planning as well as comparing survival rates across areas of England to assess the impact of public health prevention policies such as smoking cessation.References:(1) Cancer Research Campaign. Cancer Statistics: Oral – UK. London: CRC, 2000.(2) Blot WJ, McLaughlin JK, Winn DM et al. Smoking and drinking in relation to oral and pharyngeal cancer. Cancer Res 1988; 48: 3282-7. (3) La Vecchia C, Tavani A, Franceschi S et al. Epidemiology and prevention of oral cancer. Oral Oncology 1997; 33: 302-12.Definition of numeratorAll cancer mortality for lip, oral cavity and pharynx (ICD-10 C00-C14) in the respective calendar years aggregated into quinary age bands (0-4, 5-9,…, 85-89, 90+). This does not include secondary cancers or recurrences. Data are reported according to the calendar year in which the cancer was diagnosed.Counts of deaths for years up to and including 2019 have been adjusted where needed to take account of the MUSE ICD-10 coding change introduced in 2020. Detailed guidance on the MUSE implementation is available at: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/articles/causeofdeathcodinginmortalitystatisticssoftwarechanges/january2020Counts of deaths for years up to and including 2013 have been double adjusted by applying comparability ratios from both the IRIS coding change and the MUSE coding change where needed to take account of both the MUSE ICD-10 coding change and the IRIS ICD-10 coding change introduced in 2014. The detailed guidance on the IRIS implementation is available at: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/impactoftheimplementationofirissoftwareforicd10causeofdeathcodingonmortalitystatisticsenglandandwales/2014-08-08Counts of deaths for years up to and including 2010 have been triple adjusted by applying comparability ratios from the 2011 coding change, the IRIS coding change and the MUSE coding change where needed to take account of the MUSE ICD-10 coding change, the IRIS ICD-10 coding change and the ICD-10 coding change introduced in 2011. The detailed guidance on the 2011 implementation is available at https://webarchive.nationalarchives.gov.uk/ukgwa/20160108084125/http://www.ons.gov.uk/ons/guide-method/classifications/international-standard-classifications/icd-10-for-mortality/comparability-ratios/index.htmlDefinition of denominatorPopulation-years (aggregated populations for the three years) for people of all ages, aggregated into quinary age bands (0-4, 5-9, …, 85-89, 90+)

In 2019, the leading causes of death globally included ischemic heart disease, stroke and chronic obstructive pulmonary disease (COPD). There were **** million deaths from ischemic heart disease at that time and about **** million deaths caused by stroke. In recent history, increases in life expectancy, increases in population and better standards of living have changed the leading causes of death over time. Non-Communicable Disease Deaths The number of deaths due to non-communicable diseases has remained relatively stable in recent years. A large majority of non-communicable or chronic disease deaths globally are caused by cardiovascular diseases, followed by cancer. Various lifestyle choices cause or exacerbate many of these chronic diseases. Drinking, smoking and lack of exercise can contribute to higher rates of non-communicable diseases and early death. It is estimated that the relative risk of death before the age of 65 was ** times greater among those that smoked and never quit. Infectious Disease Deaths Trends indicate that the number of deaths due to infectious diseases have decreased in recent years. However, infectious diseases still disproportionately impact low- and middle-income countries. In 2021, tuberculosis, malaria and HIV/AIDS were still among the leading causes of death in low-income countries. However, the leading causes of death in upper income countries are almost exclusively non-communicable, chronic conditions.

Number and rate of new cancer cases diagnosed annually from 1992 to the most recent diagnosis year available. Included are all invasive cancers and in situ bladder cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.

Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 90.598 % in 2019. This records a decrease from the previous number of 91.046 % for 2015. Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 91.273 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 91.869 % in 2000 and a record low of 90.598 % in 2019. Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.;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;

Cancer diagnoses and age-standardised incidence rates for all types of cancer by age and sex including breast, prostate, lung and colorectal cancer.

Austria AT: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 90.985 % in 2019. This records a decrease from the previous number of 91.949 % for 2015. Austria AT: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 91.726 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 91.949 % in 2015 and a record low of 90.985 % in 2019. Austria AT: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Austria – Table AT.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.;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;

ObjectivesTo quantify the burden and variation trends of cancers in children under 5 years at the global, regional, and national levels from 1990 to 2019.MethodsEpidemiological data for children under 5 years who were diagnosed with any one childhood cancer were obtained from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) from 1990 to 2019. The outcomes were the absolute numbers and rates of incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) for different types of cancer.ResultsIn 2019, 8,774,979.1 incident cases (95% uncertainty interval [UI]: 6,243,599.2 to11,737,568.5) and 8,956,583.8 (6,446,323.9 to 12,364,520.8) prevalent cases of cancer in children under 5 years were identified worldwide; these cancers resulted in 44,451.6 (36,198.7 to 53,905.9) deaths and 3,918,014.8 (3,196,454.9 to 4,751,304.2) DALYs. From 1990 to 2019, although the numbers of incident and prevalent cases only decreased by −4.6% (−7.0 to −2.2) and −8.3% (−12.6 to −3.4), respectively, the numbers of deaths and DALYs clearly declined by −47.8% (−60.7 to −26.4) and −47.7% (−60.7 to −26.2), respectively. In 2019, the middle sociodemographic index (SDI) regions had the highest incidence and prevalence, whereas the low SDI regions had the most mortality and DALYs. Although all of the SDI regions displayed a steady drop in deaths and DALYs between 1990 and 2019, the low-middle and low SDI regions showed increasing trends of incidence and prevalence. Leukemia remained the most common cancer globally in 2019. From 1990 to 2019, the burdens of leukemia, liver cancer, and Hodgkin's lymphoma declined, whereas the incidence and prevalence of other cancers grew, particularly testicular cancer.ConclusionsThe global childhood cancer burden in young children has been steadily decreasing over the past three decades. However, the burdens and other characteristics have varied across different regions and types of cancers. This highlights the need to reorient current treatment strategies and establish effective prevention methods to reduce the global burden of childhood cancer.

Bolivia BO: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 72.676 % in 2019. This records an increase from the previous number of 70.254 % for 2015. Bolivia BO: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 67.435 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 72.676 % in 2019 and a record low of 53.198 % in 2000. Bolivia BO: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.;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;

Introduction. The analysis looks at mental and physical health data from 2000-2019 from various sources the main one being the World Health Organization (WHO).

Task: Analyze health data to gain insights into current consumers health patterns globally and in Kenya to be utilized to make data driven decisions.

Stakeholders: -Company founders and C-suite teams. -Human Resource and Mental Health Professionals. -Government policy makers.

Analysis Objectives: -What is the trend in global and local consumer mental and physical health? -How can these trends influence public and corporate strategies?

ROCCC of Data: A good data source is ROCCC which stands for Reliable, Original, Comprehensive, Current, and Cited.

-Reliablity — High — The data comes from global population sample data sources.

-Originality — LOW — Third party provider (WHO).

-Comprehensive — HIGH — There are several variables summarized into between 1,700-10,980 observations for a period of over 15 years which was fairly comprehensive.

-Current — MID — Data is 3 years old and may not be as relevant as there is no covid data updated to it.

-Cited — HIGH — Data collected from a reliable third party that comprehensively reports its data collection process publicly.

Overall, the dataset is good quality data however its recommended that an updated analysis be done on the health trends during and post-covid.

Key Insights

-There is a higher average suicide rate in men than women both globally and also in Kenya.

-Kenya has a higher average suicide rate for both genders compared to the global average as at 2019.

-The average probability of death between the age of 30 to 70 from from any of cardiovascular disease, cancer, diabetes or chronic respiratory disease in Kenya has been decreasing since 2008 however an increase has been observed since 2016.

-There has been a significant increase in the prevalence of alcohol and substance use disorder in Kenya, moreover, the prevalence in the country increases as the prevalence of anxiety disorders, eating disorders and schizophrenia increases according to the Kenyan correlation heat map.

-As evident on the correlation heat map the prevalence various mental health issues have an impact on each other.

-The global probability of dying between age 30 and 70 from any of cardiovascular disease, cancer, diabetes or chronic respiratory disease has been falling significantly since the 2000s, however, its only been steadily decreasing in Kenya. Men are also at a higher risk of death from these diseases compared to women both globally and locally in Kenya.

-The probability of dying between age 30 and 70 from any of cardiovascular disease, cancer, diabetes or chronic respiratory disease in Kenya has been observed to be significantly inversely proportional to the prevalence of alcohol, substance use anxiety and eating disorders.

-Suicide rates have been observed to not have a significant direct relationship with any mental health disorders both globally and locally however the most significant correlation is the probability of dying between age 30 and 70 from any of cardiovascular disease, cancer, diabetes or chronic respiratory disease in the global analysis.

-Globally a significant inverse relationship between road traffic death rate and eating disorders has been observed however there is a slightly significant relationship between depressive disorders and road traffic death which should be an indicator for further research.

-In Kenya, its been observed that road traffic deaths are inversely proportional to the probability of dying between age 30 and 70 from any of cardiovascular disease, cancer, diabetes or chronic respiratory disease but directly proportional to eating, anxiety, alcohol and substance use disorders.

-Depressive disorders is the most significant variable that has an impact on suicide rates in Kenya therefore further study can look into the impact of depression on attempted and reported suicide cases and other factors that may influence suicide as it has been on the rise in Kenya.

-Road traffic accidents have a significant impact of the mental health of several Kenyans.

Recommendations.

-There should be more education regarding suicide prevention for NGOs.

-Corporate firms should look into providing observed health insurance and mental health days off in addition to more sick days for the affected.

-The government can implement policies and programs that provide more efficient facilities for the handling of observed health issues.

-Insurance companies can restructure their products around the knowledge that mental health issues in Kenya have a significant direct relationship to each other and also that the prevalence of alcohol and substance use critically impacts the road traffic death rate in Kenya.

-The government should critically look at the increase in the prevalence of alcohol...

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.

According to the findings of a survey by IPSOS, worldwide people generally underestimate the proportion of deaths from cardiovascular diseases and cancer, two of the leading causes of death worldwide. It was found that on average respondents thought cardiovascular diseases accounted for just 11 percent of deaths worldwide, when in reality cardiovascular diseases account for 32 percent of deaths. This statistic shows the actual vs public estimates for causes of death worldwide as of 2019.