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 ...).

Note: This dataset is historical only and there are not corresponding datasets for more recent time periods. For that more-recent information, please visit the Chicago Health Atlas at https://chicagohealthatlas.org. This dataset gives the average life expectancy and corresponding confidence intervals for sex and racial-ethnic groups in Chicago for the years 1990, 2000 and 2010. See the full description at: https://data.cityofchicago.org/api/views/3qdj-cqb8/files/pJ3PVVyubnsS2SpGO5P5IOPtNgCJZTE3LNOeLagC3mw?download=true&filename=P:\EPI\OEPHI\MATERIALS\REFERENCES\Life Expectancy\Dataset description_LE_ Sex_Race_Ethnicity.pdf

Note: This dataset is historical only and there are not corresponding datasets for more recent time periods. For that more-recent information, please visit the Chicago Health Atlas at https://chicagohealthatlas.org.

This dataset gives the average life expectancy and corresponding confidence intervals for each Chicago community area for the years 1990, 2000 and 2010. See the full description at: https://data.cityofchicago.org/api/views/qjr3-bm53/files/AAu4x8SCRz_bnQb8SVUyAXdd913TMObSYj6V40cR6p8?download=true&filename=P:\EPI\OEPHI\MATERIALS\REFERENCES\Life Expectancy\Dataset description - LE by community area.pdf

Effect of suicide rates on life expectancy dataset

Abstract
In 2015, approximately 55 million people died worldwide, of which 8 million committed suicide. In the USA, one of the main causes of death is the aforementioned suicide, therefore, this experiment is dealing with the question of how much suicide rates affects the statistics of average life expectancy.
The experiment takes two datasets, one with the number of suicides and life expectancy in the second one and combine data into one dataset. Subsequently, I try to find any patterns and correlations among the variables and perform statistical test using simple regression to confirm my assumptions.

Data

The experiment uses two datasets - WHO Suicide Statistics[1] and WHO Life Expectancy[2], which were firstly appropriately preprocessed. The final merged dataset to the experiment has 13 variables, where country and year are used as index: Country, Year, Suicides number, Life expectancy, Adult Mortality, which is probability of dying between 15 and 60 years per 1000 population, Infant deaths, which is number of Infant Deaths per 1000 population, Alcohol, which is alcohol, recorded per capita (15+) consumption, Under-five deaths, which is number of under-five deaths per 1000 population, HIV/AIDS, which is deaths per 1 000 live births HIV/AIDS, GDP, which is Gross Domestic Product per capita, Population, Income composition of resources, which is Human Development Index in terms of income composition of resources, and Schooling, which is number of years of schooling.

LICENSE

THE EXPERIMENT USES TWO DATASET - WHO SUICIDE STATISTICS AND WHO LIFE EXPECTANCY, WHICH WERE COLLEECTED FROM WHO AND UNITED NATIONS WEBSITE. THEREFORE, ALL DATASETS ARE UNDER THE LICENSE ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 3.0 IGO (https://creativecommons.org/licenses/by-nc-sa/3.0/igo/).

[1] https://www.kaggle.com/szamil/who-suicide-statistics

[2] https://www.kaggle.com/kumarajarshi/life-expectancy-who

This table contains the cohort survival tables (by birth cohort of 1 year) by gender and age for the population of the Netherlands. The table shows how many boys or girls from a group of 100 thousand newborns have reached the year in which they are 1, 2, 3, etc. years old. It can also be seen how old these children will be on average.

The table can be broken down by mortality, the number of people living (table population), the number of deceased (table population) and the (cohort) life expectancy per generation by gender and age.

The (cohort) life expectancy, calculated from a cohort survival table, indicates the actual lifespan (or is expected to be, when the observed mortality rates are complemented by mortality from the forecast period). See section 4 for an explanation of the difference between the period survival table and a cohort survival table.

It is possible to choose from figures in which only observed numbers are calculated or a series in which the observed numbers are supplemented by future expectations of numbers of deceased for the birth generations that are still alive.

Data available: from birth generation 1850

Status of the figures: The figures based on the number of deaths observed up to and including the year 2020 are definitive. Figures supplemented by future expectations of the number of deceased are from the CBS Core Forecast 2021-2070. This forecast shall be reviewed once a year.

Changes as of 16 December 2021: — The figures relating to mortality observations for 2020 are included in the table; — The figures relating to the projections have been replaced by those from the Core Forecast 2021-2070.

When are new figures coming? In December 2022, mortality observations for 2021 will be reflected in this table and future expectations will be replaced by those from the Core Forecast 2022-2070.

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

Subnational trends in the average number of years people will live beyond their current age measured by “period life expectancy”.

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

This table contains mortality indicators by sex for Canada and all provinces except Prince Edward Island. These indicators are derived from three-year complete life tables. Mortality indicators derived from single-year life tables are also available (table 13-10-0837). For Prince Edward Island, Yukon, the Northwest Territories and Nunavut, mortality indicators derived from three-year abridged life tables are available (table 13-10-0140).

Life expectancy is the average number of years of life left at a particular age, based on death rates for a given period. This is a hypothetical measure useful for tracking mortality trends in the population.

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. Infant Mortality is defined as the number of deaths in infants under one year of age per 1,000 live births. Infant mortality is often used as an indicator to measure the health and well-being of a community, because factors affecting the health of entire populations can also impact the mortality rate of infants. Although California’s infant mortality rate is better than the national average, there are significant disparities, with African American babies dying at more than twice the rate of other groups. Data are from the Birth Cohort Files. The infant mortality indicator computed from the birth cohort file comprises birth certificate information on all births that occur in a calendar year (denominator) plus death certificate information linked to the birth certificate for those infants who were born in that year but subsequently died within 12 months of birth (numerator). Studies of infant mortality that are based on information from death certificates alone have been found to underestimate infant death rates for infants of all race/ethnic groups and especially for certain race/ethnic groups, due to problems such as confusion about event registration requirements, incomplete data, and transfers of newborns from one facility to another for medical care. Note there is a separate data table "Infant Mortality by Race/Ethnicity" which is based on death records only, which is more timely but less accurate than the Birth Cohort File. Single year shown to provide state-level data and county totals for the most recent year. Numerator: Infants deaths (under age 1 year). Denominator: Live births occurring to California state residents. Multiple years aggregated to allow for stratification at the county level. For this indicator, race/ethnicity is based on the birth certificate information, which records the race/ethnicity of the mother. The mother can “decline to state”; this is considered to be a valid response. These responses are not displayed on the indicator visualization.

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

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Live Oak. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Live Oak. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Live Oak, householders within the 45 to 64 years age group have the highest median household income at $91,071, followed by those in the 25 to 44 years age group with an income of $79,917. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $68,162. Notably, householders within the under 25 years age group, had the lowest median household income at $36,766.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Live Oak median household income by age. You can refer the same here

This dataset shows daily confirmed and probable cases of COVID-19 in New York City by date of specimen collection. Total cases has been calculated as the sum of daily confirmed and probable cases. Seven-day averages of confirmed, probable, and total cases are also included in the dataset. A person is classified as a confirmed COVID-19 case if they test positive with a nucleic acid amplification test (NAAT, also known as a molecular test; e.g. a PCR test). A probable case is a person who meets the following criteria with no positive molecular test on record: a) test positive with an antigen test, b) have symptoms and an exposure to a confirmed COVID-19 case, or c) died and their cause of death is listed as COVID-19 or similar. As of June 9, 2021, people who meet the definition of a confirmed or probable COVID-19 case >90 days after a previous positive test (date of first positive test) or probable COVID-19 onset date will be counted as a new case. Prior to June 9, 2021, new cases were counted ≥365 days after the first date of specimen collection or clinical diagnosis. Any person with a residence outside of NYC is not included in counts. Data is sourced from electronic laboratory reporting from the New York State Electronic Clinical Laboratory Reporting System to the NYC Health Department. All identifying health information is excluded from the dataset. These data are used to evaluate the overall number of confirmed and probable cases by day (seven day average) to track the trajectory of the pandemic. Cases are classified by the date that the case occurred. NYC COVID-19 data include people who live in NYC. Any person with a residence outside of NYC is not included.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Live Oak County. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Live Oak County, the median income for all workers aged 15 years and older, regardless of work hours, was $39,080 for males and $19,724 for females.

These income figures highlight a substantial gender-based income gap in Live Oak County. Women, regardless of work hours, earn 50 cents for each dollar earned by men. This significant gender pay gap, approximately 50%, underscores concerning gender-based income inequality in the county of Live Oak County.

- Full-time workers, aged 15 years and older: In Live Oak County, among full-time, year-round workers aged 15 years and older, males earned a median income of $65,313, while females earned $39,194, leading to a 40% gender pay gap among full-time workers. This illustrates that women earn 60 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Live Oak County, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Live Oak County median household income by race. You can refer the same here

Average (mean) rating for 'Life Satisfaction' by County and Unitary Authority in the First ONS Annual Experimental Subjective Wellbeing survey, April 2011 - March 2012.

The Office for National Statistics has included the four subjective well-being questions below on the Annual Population Survey (APS), the largest of their household surveys.

• Overall, how satisfied are you with your life nowadays?
• Overall, to what extent do you feel the things you do in your life are worthwhile?
• Overall, how happy did you feel yesterday?
• Overall, how anxious did you feel yesterday?

This dataset presents results from the first of these questions, "Overall, how satisfied are you with your life nowadays?" Respondents answer these questions on an 11 point scale from 0 to 10 where 0 is ‘not at all’ and 10 is ‘completely’. The well-being questions were asked of adults aged 16 and older.

Well-being estimates for each unitary authority or county are derived using data from those respondents who live in that place. Responses are weighted to the estimated population of adults (aged 16 and older) as at end of September 2011.

This dataset contains the mean responses: the average reported value for respondents resident in each area. It also contains the standard error, the sample size and lower and upper confidence limits at the 95% level.

The data cabinet also makes available the proportion of people in each county and unitary authority that answer with ‘low wellbeing’ values. For the ‘life satisfaction’ question answers in the range 0-6 are taken to be low wellbeing.

The ONS survey covers the whole of the UK, but this dataset only includes results for counties and unitary authorities in England, for consistency with other statistics available at this website.

At this stage the estimates are considered ‘experimental statistics’, published at an early stage to involve users in their development and to allow feedback. Feedback can be provided to the ONS via this email address.

The APS is a continuous household survey administered by the Office for National Statistics. It covers the UK, with the chief aim of providing between-census estimates of key social and labour market variables at a local area level. Apart from employment and unemployment, the topics covered in the survey include housing, ethnicity, religion, health and education. When a household is surveyed all adults (aged 16+) are asked the four subjective well-being questions.

The 12 month Subjective Well-being APS dataset is a sub-set of the general APS as the well-being questions are only asked of persons aged 16 and above, who gave a personal interview and proxy answers are not accepted. This reduces the size of the achieved sample to approximately 120,000 adult respondents in England.

The original data is available from the ONS website.

Detailed information on the APS and the Subjective Wellbeing dataset is available here.

As well as collecting data on well-being, the Office for National Statistics has published widely on the topic of wellbeing. Papers and further information can be found here.

This table contains 38577 series, with data for years 1997 - 2001 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (167 items: Canada; Health and Community Services Eastern Region; Newfoundland and Labrador; Newfoundland and Labrador; Health and Community Services St. John's Region; Newfoundland and Labrador ...), Age group (20 items: At birth; At age 10;At age 1;At age 5 ...), Sex (3 items: Both sexes; Males; Females ...), Characteristics (4 items: Life expectancy; Low 95% confidence interval; life expectancy; Coefficient of variation for life expectancy; High 95% confidence interval; life expectancy ...).

File List Data files are in ASCII format, tab delimited. No compression schemes are used. Data set consists of 1440 records, not including header row. Mammal_lifehistories_v2.txt Description The purpose of this data set was to compile general life history characteristics for a variety of mammalian species to perform comparative life history analyses among different taxa and different body size groups. Data were collected from the literature, and data sources are documented for each species within the data file. Since life history characteristics will show minor variation with environmental conditions (resource availability, climate, competitive environment, and predation pressure) a general life history for each species was sought to average over minor differences in local populations. To create a general life history for each species, life history values are often an average from several literature sources. Life history variables included in the data set are: Maximum Lifespan (months), Age of First Reproduction (months), Gestation time (months), Weaning age (months), Weaning Mass (grams), Litter size (months), litters per year, newborn mass (grams), and adult body mass (grams). Since these data were collected with the intent to examine general life history patterns, these data are good for examining large-scale patterns, specifically in comparing life history characteristics for different orders or families of mammals. All orders of placental mammals, except Chiroptera (bats) are represented in this data set: Artiodactyla (161 species), Carnivora (197), Cetacea (55 species), Dermoptera (2 species), Hydracoidea (4 species), Insectivora (91 species), Lagomorpha (42 species), Macroscelidea (10 species), Perissodactyla (15 species), Pholidota (7 species), Primates (156 species), Proboscidea (2 species), Rodentia (665 species), Scandentia (7 species), Sirenia (5 species), Tubulidentata (1 species), and Xenarthra (20 species). There are two caveats on this data set, however. First, these data are not appropriate for asking population-level questions where the integration of life history parameters with specific environmental conditions is important. Second, while this data set is extensive, it is not exhaustive. The creation of an exhaustive data set is the ultimate goal, but that goal is still several years from completion. In the meantime, researchers utilizing the data set are urged to conduct their own search for data not reported within the current data set. Researchers are also encouraged to contact the author of the data set and alert her to literature sources containing data for missing variables or species. The updated data set will be made available to Ecological Archives periodically. Key words: adult mass; age of first reproduction; gestation time; life history; litter size; litters per year; maximum lifespan; newborn mass; non-volant mamals; weaning age.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Live Oak. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Live Oak, the median income for all workers aged 15 years and older, regardless of work hours, was $55,656 for males and $38,659 for females.

These income figures highlight a substantial gender-based income gap in Live Oak. Women, regardless of work hours, earn 69 cents for each dollar earned by men. This significant gender pay gap, approximately 31%, underscores concerning gender-based income inequality in the city of Live Oak.

- Full-time workers, aged 15 years and older: In Live Oak, among full-time, year-round workers aged 15 years and older, males earned a median income of $59,760, while females earned $53,843, resulting in a 10% gender pay gap among full-time workers. This illustrates that women earn 90 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Live Oak.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Live Oak.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Live Oak median household income by race. You can refer the same here

The average number of years care home residents aged 65 years and over are expected to live beyond their current age in England and Wales. Classified as Experimental Statistics.