Dataset

This dataset was created by valcho valev

Contents

The dataset presents life expectancy at birth estimates based on annual complete period life tables for each of the 50 states and the District of Columbia (D.C.) in 2021 for the total, male and female populations.

Abstract

The Health Inequality Project uses big data to measure differences in life expectancy by income across areas and identify strategies to improve health outcomes for low-income Americans.

Section 7

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution. Both race-adjusted and unadjusted estimates are reported.

Source

Section 13

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each percentile of the national income distribution separately by year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 6

This dataset was created on 2020-01-10 18:53:00.508 by merging multiple datasets together. The source datasets for this version were:

Commuting Zone Life Expectancy Estimates by year: CZ-level by-year life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy: Commuting zone (CZ)-level life expectancy estimates for men and women, by income quartile

Commuting Zone Life Expectancy Trends: CZ-level estimates of trends in life expectancy for men and women, by income quartile

Commuting Zone Characteristics: CZ-level characteristics

Commuting Zone Life Expectancy for larger populations: CZ-level life expectancy estimates for men and women, by income ventile

Section 15

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by state of residence and year. Both race-adjusted and unadjusted estimates are reported.

Source

Section 11

This table reports US mortality rates by gender, age, year and household income percentile. Household incomes are measured two years prior to the mortality rate for mortality rates at ages 40-63, and at age 61 for mortality rates at ages 64-76. The “lag” variable indicates the number of years between measurement of income and mortality.

Observations with 1 or 2 deaths have been masked: all mortality rates that reflect only 1 or 2 deaths have been recoded to reflect 3 deaths

Source

Section 3

This table reports coefficients and standard errors from regressions of life expectancy estimates for men and women at age 40 for each quartile of the national income distribution on calendar year by commuting zone of residence. Only the slope coefficient, representing the average increase or decrease in life expectancy per year, is reported. Trend estimates for both race-adjusted and unadjusted life expectancies are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

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Section 9

This table reports life expectancy estimates at age 40 for Males and Females for all countries. Source: World Health Organization, accessed at: http://apps.who.int/gho/athena/

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Section 10

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by county of residence. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for counties with populations larger than 25,000 only

Source

Section 2

This table reports life expectancy point estimates and standard errors for men and women at age 40 for each quartile of the national income distribution by commuting zone of residence and year. Both race-adjusted and unadjusted estimates are reported. Estimates are reported for the 100 largest CZs (populations greater than 590,000) only.

Source

Section 8

This table reports US population and death counts by age, year, and sex from various sources. Counts labelled “dm1” are derived from the Social Security Administration Data Master 1 file. Counts labelled “irs” are derived from tax data. Counts labelled “cdc” are derived from NCHS life tables.

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Section 12

This table reports numerous county characteristics, compiled from various sources. These characteristics are described in the county life expectancy table.

Two variables constructed by the Cen

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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 dataset presents life expectancy at birth estimates based on annual complete period life tables for each of the 50 states and the District of Columbia (D.C.) in 2020 for the total, male and female populations.

Namur - Population - Life expectancy - Difference between women and men Difference from the average of the municipality (4.13 years) Considering that the difference in life expectancy between the two sexes should be as small as possible, Neighborhoods with a smaller difference are in a more favourable situation (in red) than those with a larger difference (in blue)

Years of life lost (YLL) is the difference in LE between the general population and the diagnostic groups (presented with 95% confidence intervals,95% CI). N = 4,689. Modelled using flexible parametric models.

Gender differences in estimated and actual life expectancy (men’s minus women’s), 2004 and 2015.

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.

The dataset presents life expectancy at birth estimates based on annual complete period life tables for each of the 50 states and the District of Columbia (D.C.) in 2018 for the total, male and female populations.

Life expectancy at birth and at age 65 for the UK and local areas in England and Wales, 1991–93 to 2011–13

This dataset provides estimates of life expectancy at birth and at 65 years of age and 95% uncertainty interval estimates by location, male, female and both sexes combined, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2016. This age-specific mortality dataset is used to enable health systems to target interventions for the older adult populations.

Live Long: What Really Extends Lifespan?

What factors will really increase your average life expectancy and lifespan?

What will really increase your average life expectancy and lifespan?

Why do women live longer than men?

What’s the best method of life extension?

Diet and exercise?

Or polygamy and pets?

Let the latest data decide.

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

Pivot table for life expectancy by sex and area type, divided by three-year intervals starting from 2001 to 2003.

Age-Adjusted Death Rates

Death Rates and Life Expectancy in the United States, 2011-2013

By Health [source]

About this dataset

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How to use the dataset

In order to use this dataset, start by selecting a particular set of variables to investigate. You can choose from Measure Names (e.g., Death Rates or Life Expectancy), Race (e.g., All Races), Sex (Male/Female) and Year (2011-2013). Once you have selected your desired variables, you can begin analyzing the data by looking at mortality rates and life expectancy averages amongst different populations in the United States over time.

You may also wish to perform more detailed analyses such as identifying trends or examining correlations between features, regional disparities in mortality rates or changes in average life expectancies over time. If so, you can do so by creating line graphs plotted against one or more independent variables such as Race and Sex to see how demographics impact these statistics overall and on a yearly basis using the Year variable computed from July 1st 2010 estimates

Research Ideas

• Analyzing mortality and life expectancy trends among certain races and sexes over time.
• Examining the effects of different socioeconomic factors on death rates and life expectancies.
• Making predictions about future mortality rates and average life expectancies with machine learning algorithms

Acknowledgements

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

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - 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. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: rows.csv | Column name | Description | |:----------------------------|:----------------------------------------------------------------------| | Measure Names | The type of measure being reported. (String) | | Race | The race of the population being reported. (String) | | Sex | The gender of the population being reported. (String) | | Year | The year the data was collected. (Integer) | | Average Life Expectancy | The average life expectancy of the population being reported. (Float) | | Mortality | The mortality rate of the population being reported. (Float) |

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.

This table represents five variants of health expectancies: -life expectancy in perceived good health. -life expectancy without physical limitations. -life expectancy without chronic morbidity. -without psychological complaints (until 2023) -life expectancy without GALI-limitations In addition, figures of 'normal' life expectancy are included, so the figures of health expectancy can be related to them. In the table, the data on health expectancy can be split into the following characteristics: -sex (starting from the data of 2018, the category ‘total, men + women’ is added). -age.

Using this table one can see the developments over time of health expectancies. For example it can be seen that morbidity free life expectancy of women shortened during the eighties and nineties. In the same period the life expectancy free of moderate and severe limitations of men increased.

Data available from: 1981

Status of the figures: The figures in this table are definitive.

Changes as of June 19, 2025: The 2024 figures have been added.

When will new figures be published? The figures for 2025 will be published in the third quarter of 2026.

Time series data for the statistic School life expectancy, primary to tertiary, gender parity index (GPI) and country British Virgin Islands. Indicator Definition:Ratio of female school life expectancy to the male school life expectancy. It is calculated by dividing the female value for the indicator by the male value for the indicator. A GPI equal to 1 indicates parity between females and males. In general, a value less than 1 indicates disparity in favor of males and a value greater than 1 indicates disparity in favor of females.The Serie's long term average value is 1.12. It's latest available value, on 12/31/2018, is 4.58 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2018, to it's latest available value, on 12/31/2018, is +0.0%.The Serie's change in percent from it's maximum value, on 12/31/2000, to it's latest available value, on 12/31/2018, is -11.00%.

Time series data for the statistic School life expectancy, primary to tertiary, gender parity index (GPI) and country Curacao. Indicator Definition:Ratio of female school life expectancy to the male school life expectancy. It is calculated by dividing the female value for the indicator by the male value for the indicator. A GPI equal to 1 indicates parity between females and males. In general, a value less than 1 indicates disparity in favor of males and a value greater than 1 indicates disparity in favor of females.