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International Mortality Patterns Dataset
Data Science and Analytics
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About
This dataset provides insights into global mortality trends and the specific causes of death across various countries and world regions. With approximately 56 million people dying annually, this data helps in understanding how mortality patterns have evolved over time. It serves as a vital resource for analysing epidemiological shifts and the burden of different health conditions worldwide.
Columns
- country: Specifies the country where the deaths were recorded. This column has 261 unique values and is fully valid.
- code: Represents the country's three-letter code. There are 217 unique codes, with approximately 85% of entries being valid and 15% noted as missing.
- year: Indicates the year of data collection, ranging from 1990 to 2019. All entries in this column are valid.
- meningitis: Records the number of deaths attributed to meningitis.
- alzheimer's_diesease: Shows the number of deaths caused by Alzheimer's disease.
- parkinson's_disease: Denotes the number of deaths due to Parkinson's disease.
- nutritional_deficiency: Details the number of deaths resulting from nutritional deficiency.
- malaria: Indicates the number of deaths caused by malaria.
- drowning: Represents the number of deaths due to drowning.
- interpersonal_violence: Records the number of deaths resulting from interpersonal violence.
- maternal_disorders: Details the number of deaths related to maternal disorders.
- hiv/aids: Shows the number of deaths attributed to HIV/AIDS.
- drug_use_disorders: Indicates the number of deaths caused by drug use disorders.
- tuberculosis: Records the number of deaths due to tuberculosis.
- cardiovascular_diseases: Details the number of deaths from cardiovascular diseases.
- lower_respiratory_infections: Shows the number of deaths caused by lower respiratory infections.
- neonatal_disorders: Represents the number of deaths from neonatal disorders.
- alcohol_use_disorders: Indicates the number of deaths attributed to alcohol use disorders.
- self_harm: Records the number of deaths due to self-harm.
- exposure_to_forces_of_nature: Details the number of deaths caused by exposure to natural forces.
- diarrheal_diseases: Shows the number of deaths from diarrheal diseases.
- environmental_heat_and_cold_exposure: Indicates the number of deaths due to environmental heat and cold exposure.
- neoplasms: Records the number of deaths attributed to neoplasms.
- conflict_and_terrorism: Details the number of deaths resulting from conflict and terrorism.
- diabetes_mellitus: Shows the number of deaths caused by diabetes mellitus.
- chronic_kidney_disease: Represents the number of deaths from chronic kidney disease.
- poisonings: Indicates the number of deaths due to poisonings.
- protein_energy_malnutrition: Records the number of deaths caused by protein-energy malnutrition.
- terrorism: Details the number of deaths attributed to terrorism, noting a higher percentage (60%) of missing values for this specific column.
- road_injuries: Shows the number of deaths resulting from road injuries.
- chronic_respiratory_diseases: Indicates the number of deaths due to chronic respiratory diseases.
- chronic_liver_diseases: Records the number of deaths from chronic liver diseases.
- digestive_diseases: Details the number of deaths caused by digestive diseases.
- fire_heat_hot_substance: Shows the number of deaths due to fire, heat, and hot substance exposure.
- acute_hepatitis: Indicates the number of deaths attributed to acute hepatitis.
Note on Cause of Death Columns: For most of the specific cause of death columns, approximately 6% of the data values are missing.
Distribution
The dataset is typically provided in a CSV file format, with a sample file size of 1.45 MB. It comprises approximately 7,273 records or rows. The data is structured in a tabular format, featuring distinct columns for country, year, and a wide array of specific causes of death, enabling easy analysis.
Usage
This dataset is ideal for time series analysis to track how mortality rates and the prevalence of specific causes of death have changed over decades. It is invaluable for global health research, assisting in the identification of significant trends in health conditions across the world. Researchers, public health organisations, and policy makers can utilise this data to formulate informed health strategies, evaluate disease burdens, and compare mortality patterns across different nations and world regions. It also serves as a beneficial resource for academic studies focusing on demographics and global epidemiology.
Coverage
The dataset offers a global scope, encompassing 261 unique countries and various world regions. The data spans a significant time range from 1990 to 2019, providing a historical perspective on mortality. While specific demographic breakdowns are not detailed, the data broadly represents global populations, allowing for macro-level analysis of death causes.
License
CC0: Public Domain
Who Can Use It
- Public health researchers for detailed analysis of disease burdens and mortality trends.
- Government agencies to inform public health policy development and resource allocation.
- Data scientists and analysts for epidemiological modelling, statistical analysis, and forecasting.
- Academic institutions and students for dissertations, research papers, and educational purposes in public health, statistics, and social sciences.
- International organisations involved in tracking global health indicators and monitoring progress on health-related development goals.
Dataset Name Suggestions
- Global Mortality Causes and Trends (1990-2019)
- World Annual Death Statistics by Cause
- Historical Global Mortality Data
- Causes of Death Worldwide (1990-2019)
- International Mortality Patterns Dataset
Attributes
Original Data Source:International Mortality Patterns Dataset
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