This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

The life expectancy for men aged 65 years in the U.S. has gradually increased since the 1960s. Now men in the United States aged 65 can expect to live 18.2 more years on average. Women aged 65 years can expect to live around 20.7 more years on average. Life expectancy in the U.S. As of 2023, the average life expectancy at birth in the United States was 78.39 years. Life expectancy in the U.S. had steadily increased for many years but has recently dropped slightly. Women consistently have a higher life expectancy than men but have also seen a slight decrease. As of 2023, a woman in the U.S. could be expected to live up to 81.1 years. Leading causes of death The leading causes of death in the United States include heart disease, cancer, unintentional injuries, and cerebrovascular diseases. However, heart disease and cancer account for around 42 percent of all deaths. Although heart disease and cancer are the leading causes of death for both men and women, there are slight variations in the leading causes of death. For example, unintentional injury and suicide account for a larger portion of deaths among men than they do among women.

This statistic depicts the average life expectancy at the age of 60 worldwide in 1990 and 2013, by income group. In 2013, a person aged 60 from a high income household had a life expectancy of 23 more years, while a person of the same age from a low income household was expected to live 17 more years.

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

Healthy life expectancy (HALE) at age 60 (years)

This dataset contains the state-wise and gender-wise life expectancy at birth as well as at 60 years. Only major states have been considered.

Life expectancy at age 60, female or male is the average number of years that a female or male at age 60 would live if prevailing patterns of mortality at the time of age 60 were to stay the same throughout her or his life.

Taiwan Life Expectancy: Female: Age 60 data was reported at 26.114 Year Old in 2017. This records an increase from the previous number of 25.880 Year Old for 2016. Taiwan Life Expectancy: Female: Age 60 data is updated yearly, averaging 23.837 Year Old from Dec 1993 (Median) to 2017, with 25 observations. The data reached an all-time high of 26.114 Year Old in 2017 and a record low of 21.130 Year Old in 1993. Taiwan Life Expectancy: Female: Age 60 data remains active status in CEIC and is reported by Ministry of the Interior. The data is categorized under Global Database’s Taiwan – Table TW.G006: Vital Statistics.

Data Series: Life expectancy at age 60, by sex Indicator: III.10 - Life expectancy at age 60, by sex Source year: 2024 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Health and related services

Context

I am developing my data science skills in areas outside of my previous work. An interesting problem for me was to identify which factors influence life expectancy on a national level. There is an existing Kaggle data set that explored this, but that information was corrupted. Part of the problem solving process is to step back periodically and ask "does this make sense?" Without reasonable data, it is harder to notice mistakes in my analysis code (as opposed to unusual behavior due to the data itself). I wanted to make a similar data set, but with reliable information.

This is my first time exploring life expectancy, so I had to guess which features might be of interest when making the data set. Some were included for comparison with the other Kaggle data set. A number of potentially interesting features (like air pollution) were left off due to limited year or country coverage. Since the data was collected from more than one server, some features are present more than once, to explore the differences.

Content

A goal of the World Health Organization (WHO) is to ensure that a billion more people are protected from health emergencies, and provided better health and well-being. They provide public data collected from many sources to identify and monitor factors that are important to reach this goal. This set was primarily made using GHO (Global Health Observatory) and UNESCO (United Nations Educational Scientific and Culture Organization) information. The set covers the years 2000-2016 for 183 countries, in a single CSV file. Missing data is left in place, for the user to decide how to deal with it.

Three notebooks are provided for my cursory analysis, a comparison with the other Kaggle set, and a template for creating this data set.

Inspiration

There is a lot to explore, if the user is interested. The GHO server alone has over 2000 "indicators". - How are the GHO and UNESCO life expectancies calculated, and what is causing the difference? That could also be asked for Gross National Income (GNI) and mortality features. - How does the life expectancy after age 60 compare to the life expectancy at birth? Is the relationship with the features in this data set different for those two targets? - What other indicators on the servers might be interesting to use? Some of the GHO indicators are different studies with different coverage. Can they be combined to make a more useful and robust data feature? - Unraveling the correlations between the features would take significant work.

The average number of years that a group of individuals could expect to live at a given age if they are at risk of dying observed at each age during the reference year(s). The calculation is done over several years in order to have a more stable estimate. Note: The entity's life expectancy may be influenced by the presence or absence of a nursing home in the entity's territory. Although the calculation includes all the deaths observed over the selected period, the impact of some deaths on life expectancy remains greater in a sparsely populated entity. The classification of entities according to their life expectancy should therefore be interpreted with caution.

Life expectancy at birth and at age 65, by sex, on a three-year average basis.

In 2022, the life expectancy at birth for women born in the UK was 82.57 years, compared with 78.57 years for men. By age 65 men had a life expectancy of 18.25 years, compared with 20.76 years for women.

In 2023, a woman in the United States aged 65 years could expect to live another **** years on average. This number decreased in the years 2020 and 2021, after reaching a high of **** years in 2019. Nevertheless, the life expectancy of a woman aged 65 years in the United States is still higher than that of a man of that age. In 2023, a man aged 65 years could be expected to live another 18.2 years on average. Why has the life expectancy in the U.S. declined? Overall, life expectancy in the United States has declined in recent years. In 2019, the life expectancy for U.S. women was **** years, but by 2023 it had decreased to **** years. Likewise, the life expectancy for men decreased from **** years to **** years in the same period. The biggest contributors to this decline in life expectancy are the COVID-19 pandemic and the opioid epidemic. Although deaths from the COVID-19 pandemic have decreased significantly since 2022, deaths from opioid overdose continue to increase, reaching all-time highs in 2022. The leading causes of death among U.S. women The leading causes of death among women in the United States in 2022 were heart disease, cancer, stroke, and COVID-19. That year, heart disease and cancer accounted for a combined **** percent of all deaths among women, while around *** percent of deaths were due to COVID-19. The overall leading causes of death in the United States generally reflect the leading causes among women, with some slight variations. For example, Alzheimer’s disease is the ***** leading cause of death among women but the ******* leading cause of death overall in the United States.

Total life expectancy, healthy life expectancy and unhealthy life expectancy at age 60 in years and the percentage of healthy years by gender for Chile, Costa Rica and Spain during the mid-2000s.

Taiwan Life Expectancy: Male: Age 60 data was reported at 22.030 Year Old in 2017. This records an increase from the previous number of 21.792 Year Old for 2016. Taiwan Life Expectancy: Male: Age 60 data is updated yearly, averaging 20.516 Year Old from Dec 1993 (Median) to 2017, with 25 observations. The data reached an all-time high of 22.030 Year Old in 2017 and a record low of 18.050 Year Old in 1993. Taiwan Life Expectancy: Male: Age 60 data remains active status in CEIC and is reported by Ministry of the Interior. The data is categorized under Global Database’s Taiwan – Table TW.G006: Vital Statistics.

Life expectancy at age 60 (years)

  Dataset Description

This dataset provides information on 'Life expectancy at age 60' for countries in the WHO African Region. The data is disaggregated by the 'Sex' dimension, allowing for analysis of health inequalities across different population subgroups. Units: years

  Dimensions and Subgroups

Dimension: Sex Available Subgroups: Female, Male

  Data Structure

The dataset is in a wide format.

Index: Year (formatted… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/life-expectancy-at-age-60by-sex-for-african-countries.

Average number of years a group of individuals could expect to live at a given age if they are at risk of dying observed at each age in the reference year (or years). The calculation is done over several years in order to have a more stable estimate. Note: The life expectancy of the entity may be influenced by the presence or absence of a rest home in the entity’s territory. Although the calculation includes all the deaths observed over the period, the impact of a few deaths on life expectancy remains greater in a sparsely populated entity. The classification of entities according to their life expectancy should therefore be interpreted with caution.

France Life Expectancy: Men: 60 Years data was reported at 23.200 Year in 2017. This records an increase from the previous number of 23.100 Year for 2016. France Life Expectancy: Men: 60 Years data is updated yearly, averaging 17.450 Year from Dec 1946 (Median) to 2017, with 72 observations. The data reached an all-time high of 23.200 Year in 2017 and a record low of 14.900 Year in 1951. France Life Expectancy: Men: 60 Years data remains active status in CEIC and is reported by French National Institute for Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.G004: Vital Statistics: Life Expectancy.

File Description: "Life Expectancy Data.csv" This dataset contains 2,938 entries and 22 columns, covering life expectancy and related health indicators for multiple nations from 2000 to 2015. It includes country-wise data and other economic, social, and health metrics. Column Description: 1. Country – Name of the country. 2. Year – Data year (ranging from 2000 to 2015). 3. Status – Economic classification (Developing/Developed). 4. Life expectancy – Average lifespan in years. 5. Adult Mortality – Probability of death between ages 15-60 per 1,000 individuals. 6. Infant Deaths – Number of infant deaths per 1,000 live births. 7. Alcohol – Per capita alcohol consumption. 8. Percentage Expenditure – Government health expenditure as a percentage of GDP. 9. Hepatitis B – Immunization coverage percentage. 10. Measles – Number of reported measles cases. 11. BMI – Average Body Mass Index. 12. Under-Five Deaths – Mortality rate for children under five. 13. Polio & Diphtheria – Immunization rates. 14. HIV/AIDS – Deaths due to HIV/AIDS per 1,000 individuals. 15. GDP – Gross Domestic Product per capita. 16. Population – Total population of the country. 17. Thinness (1-19 years, 5-9 years) – Percentage of underweight children. 18. Income Composition of Resources– Human development index proxy. 19. Schooling– Average number of years of schooling. Missing Data: Some columns (like Hepatitis B, GDP, Population, Total Expenditure) contain missing values. Further File Information: Total Countries: 193 Years Covered: 2000–2015 Total Entries: 2,938 Missing Data Overview: Some columns have missing values, notably: Hepatitis B (553 missing) GDP (448 missing) Population (652 missing) Total expenditure (226 missing) Income Composition of Resources (167 missing) Schooling (163 missing) Summary Statistics: Life Expectancy:

Range: 36.3 to 89 years Mean: 69.2 years Adult Mortality:

Mean: 165 per 1,000 Max: 723 per 1,000 GDP per Capita:

Mean: $7,483 Max: $119,172 Population:

Mean: ~12.75 million Max: 1.29 billion Education:

Schooling Average: 12 years Max: 20.7 years

Futuristic Scope of this data: For comparative analysis of the 2000–2015 life expectancy dataset with new datasets on the same parametres , you can perform several statistical tests and analytical methods based on different research questions. Below are some key tests and approaches:

1. Trend Analysis (Time-Series) Objective: Identify trends in life expectancy and related indicators over time. Methods: Moving Averages: Smooth fluctuations to detect trends. Linear/Polynomial Regression: Check whether life expectancy follows an increasing or decreasing trend. Time-Series Decomposition: Separate data into trend, seasonality, and residuals.
2. Descriptive Statistics & Comparative Summary Objective: Compare summary statistics between years or groups. Tests/Methods: Mean, Median, Standard Deviation: Compare distributions of life expectancy, GDP, or schooling. Boxplots & Histograms: Show variations over different years or between developing vs. developed countries. Coefficient of Variation (CV): Compare variability in life expectancy across regions.
3. Correlation & Regression Analysis Objective: Examine relationships between variables. Methods: Pearson/Spearman Correlation: Check relationships between life expectancy and GDP, health expenditure, etc. Multiple Linear Regression: Predict life expectancy based on GDP, immunization, and schooling. Multicollinearity (VIF Test): Ensure independent variables are not highly correlated.
4. Hypothesis Testing (Comparative Analysis) Test Objective When to Use? t-Test (Independent Samples) Compare life expectancy between developed & developing nations Two groups (e.g., 2000 vs. 2015, or developed vs. developing) Paired t-Test Compare life expectancy in the same country over two time periods Before/after comparison (e.g., 2000 vs. 2015 for the same country) ANOVA (One-Way) Compare life expectancy across multiple groups More than two groups (e.g., continents or income groups) Chi-Square Test Test if categorical distributions (e.g., immunization coverage) differ over time Categorical variables (e.g., immunization rates vs. year)
5. Clustering & Classification (Machine Learning) Objective: Group countries based on life expectancy patterns. Methods: K-Means Clustering: Identify groups with similar life expectancy trends. Hierarchical Clustering: Create a country similarity tree. Decision Trees/Random Forest: Classify countries based on development status using life expectancy factors.
6. Forecasting Future Trends Objective: Predict life expectancy in future years using historical data. Methods: ARIMA (AutoRegressive Integrated Moving Average): Time-series forecasting. Exponential Smoothing: Forecast gradual trends. Machine Learning (LSTM, XGBoost): Predict based on multiple indicators.
7. Comparative Regional Analysis O...