19 datasets found
  1. Health Inequality Project

    • redivis.com
    application/jsonl +7
    Updated Jan 17, 2020
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    Stanford Center for Population Health Sciences (2020). Health Inequality Project [Dataset]. http://doi.org/10.57761/7wg0-e126
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    parquet, arrow, avro, spss, csv, stata, sas, application/jsonlAvailable download formats
    Dataset updated
    Jan 17, 2020
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 1, 2001 - Dec 31, 2014
    Description

    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.

    Source

    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/

    Source

    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.

    Source

    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

  2. r

    National Mortality

    • redivis.com
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). National Mortality [Dataset]. https://redivis.com/datasets/w5kt-6wb4cxdnz
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    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2001 - 2014
    Description

    National mortality rates by gender, age, year, and income percentile

  3. Life expectancy at birth, by race, Hispanic origin and sex U.S. 2020

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Life expectancy at birth, by race, Hispanic origin and sex U.S. 2020 [Dataset]. https://www.statista.com/statistics/260410/life-expectancy-at-birth-in-the-us-by-race-hispanic-origin-and-sex/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    United States
    Description

    In 2020, a newborn Hispanic child in the United States had a projected life expectancy of 77.9 years, the highest life expectancy among the ethnic groups studied. In comparison, the life expectancy at birth for a Black, non-Hispanic child in 2020 was 71.5 years.

  4. Life expectancy in North America 2022

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). Life expectancy in North America 2022 [Dataset]. https://www.statista.com/statistics/274513/life-expectancy-in-north-america/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    North America
    Description

    This statistic shows the average life expectancy in North America for those born in 2022, by gender and region. In Canada, the average life expectancy was 80 years for males and 84 years for females.

    Life expectancy in North America

    Of those considered in this statistic, the life expectancy of female Canadian infants born in 2021 was the longest, at 84 years. Female infants born in America that year had a similarly high life expectancy of 81 years. Male infants, meanwhile, had lower life expectancies of 80 years (Canada) and 76 years (USA).

    Compare this to the worldwide life expectancy for babies born in 2021: 75 years for women and 71 years for men. Of continents worldwide, North America ranks equal first in terms of life expectancy of (77 years for men and 81 years for women). Life expectancy is lowest in Africa at just 63 years and 66 years for males and females respectively. Japan is the country with the highest life expectancy worldwide for babies born in 2020.

    Life expectancy is calculated according to current mortality rates of the population in question. Global variations in life expectancy are caused by differences in medical care, public health and diet, and reflect global inequalities in economic circumstances. Africa’s low life expectancy, for example, can be attributed in part to the AIDS epidemic. In 2019, around 72,000 people died of AIDS in South Africa, the largest amount worldwide. Nigeria, Tanzania and India were also high on the list of countries ranked by AIDS deaths that year. Likewise, Africa has by far the highest rate of mortality by communicable disease (i.e. AIDS, neglected tropics diseases, malaria and tuberculosis).

  5. r

    National Life Expectancy by year

    • redivis.com
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). National Life Expectancy by year [Dataset]. https://redivis.com/datasets/w5kt-6wb4cxdnz
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    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2001 - 2014
    Description

    National by-year life expectancy estimates for men and women, by income percentile

  6. Death rates for suicide, by sex, race, Hispanic origin, and age: United...

    • healthdata.gov
    • data.virginia.gov
    • +2more
    application/rdfxml +5
    Updated Jun 16, 2021
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    data.cdc.gov (2021). Death rates for suicide, by sex, race, Hispanic origin, and age: United States [Dataset]. https://healthdata.gov/dataset/Death-rates-for-suicide-by-sex-race-Hispanic-origi/fivt-ftbp
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    tsv, xml, application/rdfxml, csv, json, application/rssxmlAvailable download formats
    Dataset updated
    Jun 16, 2021
    Dataset provided by
    data.cdc.gov
    Area covered
    United States
    Description

    Data on death rates for suicide, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time.

    SOURCE: NCHS, National Vital Statistics System (NVSS); Grove RD, Hetzel AM. Vital statistics rates in the United States, 1940–1960. National Center for Health Statistics. 1968; numerator data from NVSS annual public-use Mortality Files; denominator data from U.S. Census Bureau national population estimates; and Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics. 2021. Available from: https://www.cdc.gov/nchs/products/nvsr.htm. For more information on the National Vital Statistics System, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

  7. d

    Population Health Measures: Age-Adjusted Mortality Rates

    • catalog.data.gov
    • data.montgomerycountymd.gov
    • +2more
    Updated Jun 21, 2025
    + more versions
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    data.montgomerycountymd.gov (2025). Population Health Measures: Age-Adjusted Mortality Rates [Dataset]. https://catalog.data.gov/dataset/population-health-measures-age-adjusted-mortality-rates
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    Dataset updated
    Jun 21, 2025
    Dataset provided by
    data.montgomerycountymd.gov
    Description

    Age-adjustment mortality rates are rates of deaths that are computed using a statistical method to create a metric based on the true death rate so that it can be compared over time for a single population (i.e. comparing 2006-2008 to 2010-2012), as well as enable comparisons across different populations with possibly different age distributions in their populations (i.e. comparing Hispanic residents to Asian residents). Age adjustment methods applied to Montgomery County rates are consistent with US Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS) as well as Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA). PHS Planning and Epidemiology receives an annual data file of Montgomery County resident deaths registered with Maryland Department of Health and Mental Hygiene’s Vital Statistics Administration (DHMH VSA). Using SAS analytic software, MCDHHS standardizes, aggregates, and calculates age-adjusted rates for each of the leading causes of death category consistent with state and national methods and by subgroups based on age, gender, race, and ethnicity combinations. Data are released in compliance with Data Use Agreements between DHMH VSA and MCDHHS. This dataset will be updated Annually.

  8. Life Expectancy - Men at the age of 65 years in the U.S. 1960-2021

    • statista.com
    • ai-chatbox.pro
    Updated Dec 12, 2023
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    Statista (2023). Life Expectancy - Men at the age of 65 years in the U.S. 1960-2021 [Dataset]. https://www.statista.com/statistics/266657/us-life-expectancy-for-men-aat-the-age-of-65-years-since-1960/
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    Dataset updated
    Dec 12, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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 17 more years on average. Women aged 65 years can expect to live around 19.7 more years on average.

    Life expectancy in the U.S.

    As of 2021, the average life expectancy at birth in the United States was 76.33 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 2019, a woman in the U.S. could be expected to live up to 79.3 years.

    Leading causes of death

    The leading causes of death in the United States include heart disease, cancer, unintentional injuries, chronic lower respiratory diseases and cerebrovascular diseases. However, heart disease and cancer account for around 38 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.

  9. Mortality rates, by age group

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Dec 4, 2024
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    Government of Canada, Statistics Canada (2024). Mortality rates, by age group [Dataset]. http://doi.org/10.25318/1310071001-eng
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    Dataset updated
    Dec 4, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Government of Canadahttp://www.gg.ca/
    Area covered
    Canada
    Description

    Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

  10. r

    National Life Expectancy

    • redivis.com
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). National Life Expectancy [Dataset]. https://redivis.com/datasets/w5kt-6wb4cxdnz
    Explore at:
    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2001 - 2014
    Description

    National life expectancy estimates (pooling 2001-14) for men and women, by income percentile.

  11. Life expectancy of men in the United States 2023

    • statista.com
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    Statista, Life expectancy of men in the United States 2023 [Dataset]. https://www.statista.com/statistics/263731/life-expectancy-of-men-in-the-united-states/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The life expectancy of men at birth in the United States saw no significant changes in 2023 in comparison to the previous year 2022 and remained at around 75.8 years. However, 2023 marked the second consecutive increase of the life expectancy. Life expectancy at birth refers to the number of years the average newborn is expected to live, providing that mortality patterns at the time of birth do not change thereafter.Find more statistics on other topics about the United States with key insights such as total fertility rate, infant mortality rate, and total life expectancy at birth.

  12. Countries with the lowest life expectancy worldwide 2024, by gender

    • statista.com
    Updated Feb 13, 2025
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    Statista (2025). Countries with the lowest life expectancy worldwide 2024, by gender [Dataset]. https://www.statista.com/statistics/274521/countries-with-the-lowest-life-expectancy-worldwide/
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    Dataset updated
    Feb 13, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    World
    Description

    Men born in Chad have the lowest life expectancy in the world as of 2024, reaching only 53 years. The lowest life expectancy for women in the world in 2024 was for girls born in Nigeria, with only 55 years. Except for Afghanistan, all the countries with the lowest life expectancy in the world are in Africa.

  13. r

    National Population and Death

    • redivis.com
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). National Population and Death [Dataset]. https://redivis.com/datasets/w5kt-6wb4cxdnz
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    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2001 - 2014
    Description

    Comparison of population and death counts in tax data and NCHS data

  14. f

    Table 1_Association between phenotypic age and mortality risk in individuals...

    • figshare.com
    • frontiersin.figshare.com
    docx
    Updated Dec 9, 2024
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    Yingxuan Huang; Apei Zhou; Yisen Huang; Yubin Wang; Xiaobo Liu; Xiaoqiang Liu (2024). Table 1_Association between phenotypic age and mortality risk in individuals with obesity: a retrospective cohort study.docx [Dataset]. http://doi.org/10.3389/fpubh.2024.1505066.s001
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    docxAvailable download formats
    Dataset updated
    Dec 9, 2024
    Dataset provided by
    Frontiers
    Authors
    Yingxuan Huang; Apei Zhou; Yisen Huang; Yubin Wang; Xiaobo Liu; Xiaoqiang Liu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ObjectiveThis study investigates the association between phenotypic age acceleration (PAA) and all-cause and cause-specific mortality in obese individuals.MethodsData were drawn from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018, including 9,925 obese adults (BMI ≥ 30 kg/m2). PAA, defined as phenotypic age exceeding chronological age, was assessed using clinical biomarkers. Kaplan-Meier survival analysis and Cox proportional hazards models were used to assess the relationship between PAA and all-cause, cardiovascular, and cancer mortality, adjusting for covariates such as age, gender, race, lifestyle, and health status. Subgroup and sensitivity analyses were performed to ensure the robustness of the findings.ResultsDuring a median follow-up of 10.6 years, 1,537 deaths were recorded, including 419 from cardiovascular disease and 357 from cancer. PAA was significantly associated with all-cause mortality (HR = 1.84, 95% CI: 1.64–2.06), cardiovascular mortality (HR = 1.86, 95% CI: 1.50–2.31), and cancer mortality (HR = 1.47, 95% CI: 1.17–1.85). These associations remained significant after adjusting for multiple variables, and sensitivity analyses confirmed the robustness of the results.ConclusionPAA is an independent predictor of all-cause, cardiovascular, and cancer mortality in obese individuals. This study highlights the importance of PAA in mortality risk assessment and health management in the obese population.

  15. r

    International Mean Life Expectancy

    • redivis.com
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). International Mean Life Expectancy [Dataset]. https://redivis.com/datasets/w5kt-6wb4cxdnz
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    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Description

    International estimates of mean life expectancy at age 40, by country for men and women

  16. C

    Death Profiles by County

    • data.chhs.ca.gov
    • data.ca.gov
    • +3more
    csv, zip
    Updated May 28, 2025
    + more versions
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    California Department of Public Health (2025). Death Profiles by County [Dataset]. https://data.chhs.ca.gov/dataset/death-profiles-by-county
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    csv(28125832), csv(60517511), csv(75015194), csv(60201673), csv(60676655), csv(74351424), csv(52019564), csv(60023260), csv(74689382), csv(51592721), csv(73906266), csv(15127221), csv(1128641), csv(5095), csv(11738570), zip, csv(74043128), csv(24235858), csv(74497014), csv(21575405)Available download formats
    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    California Department of Public Health
    Description

    This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

    The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

    The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

  17. Life expectancy in African countries 2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 30, 2024
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    Statista (2024). Life expectancy in African countries 2023 [Dataset]. https://www.statista.com/statistics/1218173/life-expectancy-in-african-countries/
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    Dataset updated
    Jun 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Africa
    Description

    Algeria had the highest life expectancy at birth in Africa as of 2023. A newborn infant was expected to live over 77 years in the country. Cabo Verde, Tunisia, and Mauritius followed, with a life expectancy between 77 and 75 years. On the other hand, Chad registered the lowest average, at nearly 54 years. Overall, the life expectancy in Africa was almost 63 years in the same year.

  18. r

    Characteristics

    • redivis.com
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). Characteristics [Dataset]. https://redivis.com/datasets/w5kt-6wb4cxdnz
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    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2001 - 2014
    Description

    CZ-level characteristics

    The table Characteristics is part of the dataset Health Inequality Project, available at https://stanford.redivis.com/datasets/w5kt-6wb4cxdnz. It contains 741 rows across 68 variables.

  19. r

    County Characteristics

    • redivis.com
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). County Characteristics [Dataset]. https://redivis.com/datasets/w5kt-6wb4cxdnz
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    Dataset updated
    Jan 10, 2020
    Dataset authored and provided by
    Stanford Center for Population Health Sciences
    Time period covered
    2001 - 2014
    Description

    County-level characteristics

    The table County Characteristics is part of the dataset Health Inequality Project, available at https://stanford.redivis.com/datasets/w5kt-6wb4cxdnz. It contains 3138 rows across 76 variables.

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    Learn how you can add new datasets to our index.

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Stanford Center for Population Health Sciences (2020). Health Inequality Project [Dataset]. http://doi.org/10.57761/7wg0-e126
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Health Inequality Project

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46 scholarly articles cite this dataset (View in Google Scholar)
parquet, arrow, avro, spss, csv, stata, sas, application/jsonlAvailable download formats
Dataset updated
Jan 17, 2020
Dataset provided by
Redivis Inc.
Authors
Stanford Center for Population Health Sciences
Time period covered
Jan 1, 2001 - Dec 31, 2014
Description

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.

Source

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/

Source

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.

Source

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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