Retirement Age Men in the United States increased to 66.83 Years in 2025 from 66.67 Years in 2024. This dataset provides - United States Retirement Age Men - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Retirement Age Women in the United States increased to 66.83 Years in 2025 from 66.67 Years in 2024. This dataset provides - United States Retirement Age Women - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Not in Labor Force - With No Disability, 65 Years and over (LNU05075379) from Jun 2008 to May 2025 about 65 years +, disability, labor force, labor, household survey, and USA.

This dataset provides values for RETIREMENT AGE MEN reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

We study how couples allocate retirement-saving contributions across each spouse's account. In a new dataset covering over a million U.S. individuals, we find retirement contributions are not allocated to the account with the highest employer match rate. This lack of coordination—which goes against the assumptions of most models of household decision-making—is common, costly, persistent over time, and cannot be explained by inertia, auto-enrollment, or simple heuristics. Complementing the administrative evidence with an online survey, we find that inefficient allocations reflect both financial mistakes as well as deliberate choices—especially when trust and commitment inside the households are weak.

SHARE (Survey on Health, Aging and Retirement in Europe www.share-project.org) is a pan-European longitudinal survey of the elderly (50+) population, which focuses on the study of the course of the individual aging process and the causal relationships that influence it, on the one hand, and is, on the other hand, an important source for both monitoring existing policy measures and the science-based initiation of new measures.

The panel waves of the SHARE survey have taken place since 2004 in 2-year increments. The SHARE methodology is designed to be comparable with the similar survey HRS (Heat and Retirement Survey, waves since 1992) in the USA, and in England in 2002. with the ongoing ELSA survey (English Longitudinal Survey on Aging).

This dataset provides values for RETIREMENT AGE WOMEN reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Note: After May 3, 2024, this dataset will no longer be updated because hospitals are no longer required to report data on COVID-19 hospital admissions, hospital capacity, or occupancy data to HHS through CDC’s National Healthcare Safety Network (NHSN). The related CDC COVID Data Tracker site was revised or retired on May 10, 2023.

This dataset represents weekly COVID-19 hospitalization data and metrics aggregated to national, state/territory, and regional levels. COVID-19 hospitalization data are reported to CDC’s National Healthcare Safety Network, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN and included in this dataset represent aggregated counts and include metrics capturing information specific to COVID-19 hospital admissions, and inpatient and ICU bed capacity occupancy.

Reporting information:

• As of December 15, 2022, COVID-19 hospital data are required to be reported to NHSN, which monitors national and local trends in healthcare system stress, capacity, and community disease levels for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN represent aggregated counts and include metrics capturing information specific to hospital capacity, occupancy, hospitalizations, and admissions. Prior to December 15, 2022, hospitals reported data directly to the U.S. Department of Health and Human Services (HHS) or via a state submission for collection in the HHS Unified Hospital Data Surveillance System (UHDSS).
• While CDC reviews these data for errors and corrects those found, some reporting errors might still exist within the data. To minimize errors and inconsistencies in data reported, CDC removes outliers before calculating the metrics. CDC and partners work with reporters to correct these errors and update the data in subsequent weeks.
• Many hospital subtypes, including acute care and critical access hospitals, as well as Veterans Administration, Defense Health Agency, and Indian Health Service hospitals, are included in the metric calculations provided in this report. Psychiatric, rehabilitation, and religious non-medical hospital types are excluded from calculations.
• Data are aggregated and displayed for hospitals with the same Centers for Medicare and Medicaid Services (CMS) Certification Number (CCN), which are assigned by CMS to counties based on the CMS Provider of Services files.
• Full details on COVID-19 hospital data reporting guidance can be found here: https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf

Metric details:

• Time Period: timeseries data will update weekly on Mondays as soon as they are reviewed and verified, usually before 8 pm ET. Updates will occur the following day when reporting coincides with a federal holiday. Note: Weekly updates might be delayed due to delays in reporting. All data are provisional. Because these provisional counts are subject to change, including updates to data reported previously, adjustments can occur. Data may be updated since original publication due to delays in reporting (to account for data received after a given Thursday publication) or data quality corrections.
• New COVID-19 Hospital Admissions (count): Number of new admissions of patients with laboratory-confirmed COVID-19 in the previous week (including both adult and pediatric admissions) in the entire jurisdiction.
• New COVID-19 Hospital Admissions (7-Day Average): 7-day average of new admissions of patients with laboratory-confirmed COVID-19 in the previous week (including both adult and pediatric admissions) in the entire jurisdiction.
• Cumulative COVID-19 Hospital Admissions: Cumulative total number of admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) in the entire jurisdiction since August 1, 2020.
• Cumulative COVID-19 Hospital Admissions Rate: Cumulative total number of admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) in the entire jurisdiction since August 1, 2020 divided by 2019 intercensal population estimate for that jurisdiction multiplied by 100,000.
• New COVID-19 Hospital Admissions Rate (7-day average) percent change from prior week: Percent change in the 7-day average new admissions of patients with laboratory-confirmed COVID-19 per 100,000 population compared with the prior week.
• New COVID-19 Hospital Admissions (7-Day Total): 7-day total number of new admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) in the entire jurisdiction.
• New COVID-19 Hospital Admissions Rate (7-Day Total): 7-day total number of new admissions of patients with laboratory-confirmed COVID-19 (including both adult and pediatric admissions) for the entire jurisdiction divided by 2019 intercensal population estimate for that jurisdiction multiplied by 100,000.
• Total Hospitalized COVID-19 Patients: 7-day total number of patients currently hospitalized with laboratory-confirmed COVID-19 (including both adult and pediatric patients) for the entire jurisdiction.
• Total Hospitalized COVID-19 Patients (7-Day Average): 7-day average of the number of patients currently hospitalized with laboratory-confirmed COVID-19 (including both adult and pediatric patients) for the entire jurisdiction.
• COVID-19 Inpatient Bed Occupancy (7-Day Average): Percentage of all staffed inpatient beds occupied by patients with laboratory-confirmed COVID-19 (including both adult and pediatric patients) within the entire jurisdiction is calculated as an average of valid daily values within the past 7 days (e.g., if only three valid values, the average of those three is taken). Averages are separately calculated for the daily numerators (patients hospitalized with confirmed COVID-19) and denominators (staffed inpatient beds). The average percentage can then be taken as the ratio of these two values for the entire jurisdiction.
• COVID-19 Inpatient Bed Occupancy absolute change from prior week: The absolute change in the percent of staffed inpatient beds occupied by patients with laboratory-confirmed COVID-19 represents the week-over-week absolute difference between the 7-day average occupancy of patients with confirmed COVID-19 in staffed inpatient beds in the past 7 days, compared with the prior week, in the entire jurisdiction.
• COVID-19 ICU Bed Occupancy (7-Day Average): Percentage of all staffed inpatient beds occupied by adult patients with confirmed COVID-19 within the entire jurisdiction is calculated as a 7-day average of valid daily values within the past 7 days (e.g., if only three valid values, the average of those three is taken). Averages are separately calculated for the daily numerators (adult patients hospitalized with confirmed COVID-19) and denominators (staffed adult ICU beds). The average percentage can then be taken as the ratio of these two values for the entire jurisdiction.
• COVID-19 ICU Bed Occupancy absolute change from prior week: The absolute change in the percent of staffed ICU beds occupied by patients with laboratory-confirmed COVID-19 represents the week-over-week absolute difference between the average occupancy of patients with confirmed COVID-19 in staffed adult ICU beds for the past 7 days, compared with the prior week, in the in the entire jurisdiction.

Note: October 27, 2023: Due to a data processing error, reported values for avg_percent_inpatient_beds_occupied_covid_confirmed will appear lower than previously reported values by an average difference of less than 1%. Therefore, previously reported values for avg_percent_inpatient_beds_occupied_covid_confirmed may have been overestimated and should be interpreted with caution.

October 27, 2023: Due to a data processing error, reported values for abs_chg_avg_percent_inpatient_beds_occupied_covid_confirmed will differ from previously reported values by an average absolute difference of less than 1%. Therefore, previously reported values for abs_chg_avg_percent_inpatient_beds_occupied_covid_confirmed should be interpreted with caution.

December 29, 2023: Hospitalization data reported to CDC’s National Healthcare Safety Network (NHSN) through December 23, 2023, should be interpreted with caution due to potential reporting delays that are impacted by Christmas and New Years holidays. As a result, metrics including new hospital admissions for COVID-19 and influenza and hospital occupancy may be underestimated for the week ending December 23, 2023.

January 5, 2024: Hospitalization data reported to CDC’s National Healthcare Safety Network (NHSN) through December 30, 2023 should be interpreted with caution due to potential reporting delays that are impacted by Christmas and New Years holidays. As a result, metrics including new hospital admissions for COVID-19 and influenza and hospital occupancy may be underestimated for the week ending December 30, 2023.

Graph and download economic data for Labor Force Participation Rate - With No Disability, 65 Years and over (LNU01375379) from Jun 2008 to May 2025 about 65 years +, disability, participation, civilian, labor force, labor, household survey, rate, and USA.

In 2021, about 5.96 million people aged 65 years or older were living in California -- the most out of any state. In that same year, Florida, Texas, New York, and Pennsylvania rounded out the top five states with the most people aged 65 and over living there.

Graph and download economic data for Income Before Taxes: Social Security, Private & Government Retirement by Number of Earners: Consumer Units of Two or More People, Two Earners (CXURETIRINCLB0706M) from 1984 to 2023 about social, retirement, social assistance, tax, government, consumer, private, income, persons, and USA.

NOTE: This dataset has been retired and marked as historical-only. The recommended dataset to use in its place is https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccination-Coverage-Citywide/6859-spec. COVID-19 vaccinations administered to Chicago residents based on the reported race-ethnicity and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). Vaccination Status Definitions: ·People with at least one vaccine dose: Number of people who have received at least one dose of any COVID-19 vaccine, including the single-dose Johnson & Johnson COVID-19 vaccine. ·People with a completed vaccine series: Number of people who have completed a primary COVID-19 vaccine series. Requirements vary depending on age and type of primary vaccine series received. ··People with an original booster dose: Number of people who have a completed vaccine series and have received at least one additional monovalent dose. This includes people who received a monovalent booster dose and immunocompromised people who received an additional primary dose of COVID-19 vaccine. Monovalent doses were created from the original strain of the virus that causes COVID-19. People with a bivalent dose: Number of people who received a bivalent (updated) dose of vaccine. Updated, bivalent doses became available in Fall 2022 and were created with the original strain of COVID-19 and newer Omicron variant strains. Weekly cumulative totals by vaccination status are shown for each combination of race-ethnicity and age group. Note that each age group has a row where race-ethnicity is "All" so care should be taken when summing rows. Vaccinations are counted based on the date on which they were administered. Weekly cumulative totals are reported from the week ending Saturday, December 19, 2020 onward (after December 15, when vaccines were first administered in Chicago) through the Saturday prior to the dataset being updated. Population counts are from the U.S. Census Bureau American Community Survey (ACS) 2019 1-year estimates. For some of the age groups by which COVID-19 vaccine has been authorized in the United States, race-ethnicity distributions were specifically reported in the ACS estimates. For others, race-ethnicity distributions were estimated by the Chicago Department of Public Health (CDPH) by weighting the available race-ethnicity distributions, using proportions of constituent age groups. Coverage percentages are calculated based on the cumulative number of people in each population subgroup (age group by race-ethnicity) who have each vaccination status as of the date, divided by the estimated number of Chicago residents in each subgroup. Actual counts may exceed population estimates and lead to >100% coverage, especially in small race-ethnicity subgroups of each age group. All coverage percentages are capped at 99%. All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined. CDPH uses the most complete data available to estimate COVID-19 vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Data reported in I-CARE only include doses administered in Illinois and some doses administered outside of Illinois reported historically by Illinois providers. Doses administered by the federal Bureau of Prisons and Department of Defense are also not currently reported in I-CARE. The Veterans Health Administration began reporting doses in I-CARE beginning September 2022. Due to people receiving vaccinations that are not recorded in I-CARE that c

Spotzi's Income dataset for the United States offers valuable insights into the intricacies of yearly income at various levels. This dataset is meticulously curated, presenting a detailed analysis of total income, types of household earnings, and the critical aspect of whether households are above the poverty level. This dataset is available at Census Block level, and allows for a holistic understanding of the economic landscape at both regional and national scales.

What is included?

Each data variable is presented as a percentage of the total population within each selected area. Please see below for a complete list of available data variables:

Income

• Individual Yearly Income: Under 10K, 10K-20K, 20K-35K, 35K-50K, 50K-100K, 100K+
• Individual Yearly Income - Female: Under 10K, 10K-20K, 20K-35K, 35K-50K, 50K-100K, 100K+
• Individual Yearly Income - Male: Under 10K, 10K-20K, 20K-35K, 35K-50K, 50K-100K, 100K+
• Household Income Earning Status: Earns Income, Does Not Earn Income
• Households Below Poverty Level

Household Earnings By Type

• Salary
• Interest Dividends
• Retirement Income
• Self-Employment

• • Individual Yearly Income: Marketers can leverage individual income data to tailor their strategies based on the financial capacities of their target audience. For example, luxury brands may target individuals with higher income brackets, while budget-conscious brands may focus on those with lower income levels.
  • Household Earning by Type: Marketers can use this data to understand the sources of household income, allowing for targeted campaigns. For example, financial services may tailor promotions based on the types of income earned, offering retirement planning services to those with significant retirement income.

• This demographic data is typically available at the census block level. These blocks are smaller, more detailed units designed for statistical purposes, enabling a more precise analysis of population, housing, and demographic data. Census blocks may vary in size and shape but are generally more localized compared to ZIP codes.

  Still looking for demographic data at the postal code level? Contact sales.

• There are numerous other census data datasets available for the United States, covering a wide range of demographics. These include information on:

  • Commuting
  • Educational Attainment
  • Employment
  • Families
  • Finance
  • Housing

After October 13, 2022, this dataset will no longer be updated as the related CDC COVID Data Tracker site was retired on October 13, 2022.

This dataset contains historical trends in vaccinations and cases by age group, at the US national level. Data is stratified by at least one dose and fully vaccinated. Data also represents all vaccine partners including jurisdictional partner clinics, retail pharmacies, long-term care facilities, dialysis centers, Federal Emergency Management Agency and Health Resources and Services Administration partner sites, and federal entity facilities.

NOTE: This dataset has been retired and marked as historical-only. The recommended dataset to use in its place is https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccination-Coverage-ZIP-Code/2ani-ic5x. NOTE, 3/30/2023: We have added columns for bivalent (updated) doses to this dataset. We have also added age group columns for 0-17 and 18-64 and stopped updating the 5+ and 12+ columns, although previously published values remain for those columns. COVID-19 vaccinations administered to Chicago residents based on the home ZIP Code of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). The ZIP Code where a person lives is not necessarily the same ZIP Code where the vaccine was administered. Definitions: ·People with at least one vaccine dose: Number of people who have received at least one dose of any COVID-19 vaccine, including the single-dose Johnson & Johnson COVID-19 vaccine. ·People with a completed vaccine series: Number of people who have completed a primary COVID-19 vaccine series. Requirements vary depending on age and type of primary vaccine series received. ·People with a bivalent dose: Number of people who received a bivalent (updated) dose of vaccine. Updated, bivalent doses became available in Fall 2022 and were created with the original strain of COVID-19 and newer Omicron variant strains. ·Total doses administered: Number of all COVID-19 vaccine doses administered. Data Notes: Daily counts are shown for the total number of doses administered, number of people with at least one vaccine dose, number of people who have a completed vaccine series, and number of people who have received a bivalent dose. Cumulative totals for each measure as of that date are also provided. Vaccinations are counted based on the day the vaccine was administered. Coverage percentages are calculated based on cumulative number of people who have received at least one vaccine dose, cumulative number of people who have a completed vaccine series, and cumulative number of people who have received a bivalent dose in each ZIP Code. Population counts are from the U.S. Census Bureau American Community Survey 2015-2019 5-year estimates and can be seen in the ZIP Code, 2019 rows of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa). Actual counts may exceed population estimates and lead to >100% coverage, especially in areas with small population sizes. Additionally, the medical provider may report a work address or incorrect home address for the person receiving the vaccination which may lead to over or under estimates of vaccination coverage by geography.  All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined. For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19. Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau American Community Survey

Health Center Service Delivery and Look Alike SitesImportant Note: This item is in mature support as of March, 2025 and will be retired in July, 2025. This feature layer, utilizing data from the Health Resources and Services Administration (HRSA), displays all health center program sites in the United States and it's U.S. Territories. Per HRSA, "Health centers combine medical, dental, mental health, substance use, and other services. They focus on the needs of each patient, and they make sure their providers work together to provide the best care."Henry J. Austin Health Center-ChambersData currency: August 1, 2024Data source: Health Center Service Delivery and Look–Alike SitesData modification: NoneFor more information: About the Health Center Program; Health Center Program Look-AlikesSupport documentation: MetadataFor feedback, please contact: ArcGIScomNationalMaps@esri.comHealth Resources and Services AdministrationPer HRSA, "HRSA programs provide equitable health care to people who are geographically isolated and economically or medically vulnerable. This includes programs that deliver health services to people with HIV, pregnant people, mothers and their families, those with low incomes, residents of rural areas, American Indians and Alaska Natives, and those otherwise unable to access high-quality health care."

Mortality experience data from 2007-2016 of retired individuals in the United States who are covered under group pension contracts

The study curates demographic information of a short-lived native iterocarpic herb, Cirsium undulatum. This data was collected from 1990 to 2009 at two study sites, Arapaho Prairie Preserves (APP) and Niobrara Valley Preserve (NVP), in the Nebraska Sandhills, USA. At APP, four 12m by 12m plots were established. At NVP, three 12m by 12m plots were established. The data associated with each plot are as described below:1. "UAASOverview19902009RAMET 20230630.xlsx" = Original Transition data for Plot A in APP2. "UABSOverview19902009RAMET 20230630.xlsx" = Original Transition data for Plot B in APP3. "UACSOverview19902009RAMET 20230630.xlsx" = Original Transition data for Plot C in APP4. "UADSOverview19902009RAMET 20230630.xlsx" = Original Transition data for Plot D in APP5. "UNMSOverview19902009RAMET 20230630.xlsx" = Original Transition data for Plot M in NVP6. "UNKSOverview19902009RAMET 20230630.xlsx" = Original Transition data for Plot K in NVP7. "UNLSOverview19902009RAMET 20230630.xlsx" = Original Transition data for Plot L in NVPIn 1990 – 1999, ramets in the plots were monitored twice a year: in early season (May) and in late season (late June - mid July); plots at both sites were examined within one week each year. In 4 years (2000 - 2004), all ramets were measured in late May, but in general, only flowering ramets were remeasured in July; however, some late-season observations were recorded on non-flowering ramets. In 5 years late in the study (2005 – 2009), the ramets were measured only once, in mid- to late-season: in mid-July for 3 years (2005 - 2007) and in late June for two years (2008 - 2009). New ramets observed in 2008 – 2009 at the end of the study were no longer given numerical tags; so, those did not contribute to the estimation of specific stage transition rates.This data is associated with a current ongoing project which examines the time-lag effect of weather variables on the vital rates of Cirsium undulatum. The data was collected by Dr. Svata Louda (a retired Professor from the School of Biological Sciences, University of Nebraska, Lincoln) with the help of her collaborators: A. Arnett, T. A. Rand, F. L. Russell, R. W. Otley, 18 graduate students, and 21 undergraduate students over the 20 years. The data provided here was extracted by Dr. Kathleen Keeler (also a retired Professor from the School of Biological Sciences, University of Nebraska, Lincoln) from the field data records.We want to acknowledge that this study was done on the homelands of the Lakota People (Arapaho Prairie Preserve) and of the Ponca People (Niobrara Valley Preserve); we honor this legacy. We are also indebted to The Nature Conservancy, Nebraska Chapter, for permission to work in these reserves and to their incredible staff for all of the support and encouragement provided for the study, especially A. A. Steuter at the beginning of the study.

Graph and download economic data for Income Before Taxes: Social Security, Private & Government Retirement by Size of Consumer Unit: Three People in Consumer Unit (CXURETIRINCLB0505M) from 1984 to 2023 about social, retirement, consumer unit, social assistance, tax, government, private, income, persons, and USA.

Canon 401 §1 of the Code of Canon Law states that archdiocesan/diocesan bishops (including cardinals) “are requested to” submit their resignation to the pope on reaching the age of 75 years. Some do so earlier with a view to having the resignation take effect immediately on reaching 75. All Bishops on this map on September 19, 2019 with within 5 years (age 69 - 74) of submitting retirement.The Catholic Leadership global maps information is derived from the Annuario Pontificio, which is curated and published by the Vatican Statistics Office annually, diocesan and news announcements, and GoodLands global ecclesiastical boundaries. To learn more or contact us please visit: https://good-lands.org/Catholic Leadership of Admin 3 Ecclesiastical Territories near Retirement:Burhans, Molly A., Cheney, David M., Gerlt, R.. . “Catholic Leadership of Admin 3 Ecclesiastical Territories near Retirement For Web”. Scale not given. Version 1.2. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.Derived from:Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.