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.

Over the past 160 years, life expectancy (from birth) in the United States has risen from 39.4 years in 1860, to 78.9 years in 2020. One of the major reasons for the overall increase of life expectancy in the last two centuries is the fact that the infant and child mortality rates have decreased by so much during this time. Medical advancements, fewer wars and improved living standards also mean that people are living longer than they did in previous centuries.

Despite this overall increase, the life expectancy dropped three times since 1860; from 1865 to 1870 during the American Civil War, from 1915 to 1920 during the First World War and following Spanish Flu epidemic, and it has dropped again between 2015 and now. The reason for the most recent drop in life expectancy is not a result of any specific event, but has been attributed to negative societal trends, such as unbalanced diets and sedentary lifestyles, high medical costs, and increasing rates of suicide and drug use.

Life expectancy at birth for males and females for Middle Layer Super Output Areas (MSOAs), Leicester: 2016 to 2020The average number of years a person would expect to live based on contemporary mortality rates.For a particular area and time period, it is an estimate of the average number of years a newborn baby would survive if he or she experienced the age-specific mortality rates for that area and time period throughout his or her life.Life expectancy figures have been calculated based on death registrations between 2016 to 2020, which includes the first wave and part of the second wave of the coronavirus (COVID-19) pandemic.

Half of American Millennials believed that term life insurance cost one thousand U.S. dollars or more per year in 20120, whereas only 28 percent of non-Millennials said the same. The average cost of such a policy is about 160 U.S. dollars annually, according to the source, which shows that many Americans, especially Millennials, overestimate the cost of term life insurance.

A global phenomenon, known as the demographic transition, has seen life expectancy from birth increase rapidly over the past two centuries. In pre-industrial societies, the average life expectancy was around 24 years, and it is believed that this was the case throughout most of history, and in all regions. The demographic transition then began in the industrial societies of Europe, North America, and the West Pacific around the turn of the 19th century, and life expectancy rose accordingly. Latin America was the next region to follow, before Africa and most Asian populations saw their life expectancy rise throughout the 20th century.

Callao and Lima were the departments in Peru with the highest life expectancy. Both are tied with 80.3 years of life to every person born between the years of 2020 and 2025. Other departments that come close to 80 years of life expectancy are Ica, Lambayeque and Arequipa.

Abstract

Opportunity-focused, high-growth entrepreneurship and science-led innovation are crucial for continued economic growth and productivity. Working in these fields offers the opportunity for rewarding and high-paying careers. However, the majority of youth in developing countries do not consider either as job options, affecting their choices of what to study. Youth may not select these educational and career paths due to lack of knowledge, lack of appropriate skills, and lack of role models. We provide a scalable approach to overcoming these constraints through an online education course for secondary school students that covers entrepreneurial soft skills, scientific methods, and interviews with role models.

The study comprises three experimental trials provided Before and during COVID-19 pandemic in different regions of Ecuador. This catalog entry includes data from Experiment 1: Educational Zone 2/Municipality of Quito 2019-2020. The data from the other two experiments are also available in the catalog.

Experiment 1: Educational Zone 2/Municipality of Quito 2019-2020 In course of Showing Life Opportunities project we conducted a randomized control trial in high schools in Educational Zone 2, Ecuador and Municipality of Quito, Ecuador in 2019-2020; Students finish the program in July 2020. The intervention is an online education course that covers entrepreneurial soft skills, scientific methods, and interviews with role models. This course is taken by students at school (some students finish the program at school during COVID-19 outbreak). We work with mostly 14-19 year-old students (16,570 students). The experimental program covers 126 schools in Educational Zone 2 and 11 schools in Municipality of Quito. We randomly assign schools either to treatment (and receiving the entrepreneurship courses online), or placebo-control (receiving a placebo treatment of online courses from standard curricula) groups. We also cross-randomize the role models and evaluate set of nimble interventions to increase take-up.

The details of intervention can be found in AEA registry: Asanov, Igor and David McKenzie. 2020. Showing Life Opportunities: Increasing opportunity-driven entrepreneurship and STEM careers through online courses in schools. AEA RCT Registry. July 19.

Geographic coverage

Experiment 1: Municipality of Quito and Educational Zone 2 Educational Zone 2 has its administrative headquarters in the city of Tena, Napo province. Its covers provinces of Napo, Orellana and Pichincha, 8 districts (15D01, 22D01, 17D10, 17D11, 15D02, 17D12, 22D02, 22D03), its 16 cantons and 68 parishes. It has an area of 39,542.58 km². The educational zone 2 spread from east to the western border of the Ecuador. We cover students of age 14-18 in schools that has sufficient access to the internet and classes of the K10, K11, or K12. We included the municipality of Quito in the study to enrich the coverage of program by having large (capital) city in the sample.

Analysis unit

Student

Kind of data

Sample survey data [ssd]

Sampling procedure

All students in selected schools who were present in classes filled out the baseline questionnaire

Mode of data collection

Internet [int]

Research instrument

Questionnaires We execute three main sets of questioners. A. Internet (Online Based survey)

The survey consists of a multi-topic questionnaire administered to the students through online learning platform in school during normal educational hours before COVID-19 pandemic or at home during the COVID-19 pandemic. We collect next information: 1. Subject specific knowledge tests. Spanish, English, Statistics, Personal Initiative (only endline), Negotiations (only endline). 2. Career intentions, preferences, beliefs, expectations, and attitudes. STEM and entrepreneurial intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics. Personal Initiative, Negotiations, General Cognitions (General Self-Efficacy, Youth Self-Efficacy, Perceived Subsidiary Self-Efficacy Scale, Self-Regulatory Focus, Short Grit Scale), Entrepreneurial Cognitions (Business Self-Efficacy, Identifying Opportunities, Business Attitudes, Social Entrepreneurship Standards). 4. Behavior in (incentivized) games: Other-regarding preferences (dictator game), tendency to cooperate (Prisoners Dilemma), Perseverance (triangle game), preference for honesty, creativity (unscramble game). 5. Other background information. Socioeconomic level, language spoken, risk and time preferences, trust level, parents background, big-five personality traits of student, cognitive abilities. Background information (5) collected only at the baseline. B. First follow-up Phone-based Survey Zone 2, Summer (Phone Based). The survey replicates by phone shorter version of the internet-based survey above. We collect next information: 1. Subject specific knowledge tests.
2. Career intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics

C. (Second) Follow-up Phone-Based Survey, Winter, Zone 2, Highlands Educational Regime.

We execute multi-topic questionnaire by phone to capture the first life-outcomes of students who finished the school. We collect next information:

1. Life Outcome 1- Education. The set of questions that aims to measure the learning success, career/study intentions, propensity to plan and approach others with studying tasks, entrepreneurial intentions.
2. Life Outcome 2- Labor. The set of questions that aims to measure employment status and income, job searching behavior, time devoted for working/business, salary expectations and knowledge about the careers, self-initiated contribution to the family.
3. Personal Initiative/Negotiations related and other measures. The set of questions that aim to measure level of personal initiative, negotiation strategies, pregnancy rate, gender stereotypes, math/STEM self-efficacy, gender attitudes, parent-student communication effects.

Cleaning operations

Data Editing A. Internet, Online-based surveys. We extracted the raw data generated on online platform from each experiment and prepared it for research purposes. We made several pre-processing steps of data: 1. We transform the raw data generated on platform in standard statistical software (R/STATA) readable format. 2. We extracted the answer for each item for each student for each survey (Baseline, Midline, Endline). 3. We cleaned duplicated students and duplicated answers for each item in each survey based on administrative data, performance and information given by students on platform. 4. In case of baseline survey, we standardized items/scales but also kept the raw items.

B. Phone-based surveys. The phone-based surveys are collected with help of advanced CATI kit. It contains all cases (attempts to call) and indication if the survey was effective. The data is cleaned to be ready for analysis. The data is anonymized but contains unique anonymous student id for merging across datasets.

Period life expectancy by age and sex. Each life table is based on population estimates, births and deaths for a single year.

Attendance records for the "Swim for Life" program, which provides swimming instruction to second grade public school students. Explore the Data Dictionary View Open Data for Swim for Life (2022 onwards): here Learn more about this program on the NYC Parks website: here Note: Swim for Life program was on pause due to COVID-19 pandemic. The program resumed Spring 2022.

According to the data, 19 percent of U.S. adults had trouble sleeping because they were anxious about COVID-19 in 2021, which is only a slight decrease from 22 percent in 2020. This statistic displays the percentage of U.S. adults who said the COVID-19 pandemic currently affected their day-to-day life in select ways in 2020 and 2021.

Life expectancy (LE), healthy life expectancy (HLE), disability-free life expectancy (DFLE), Slope Index of Inequality (SII) and range by national deprivation deciles using the Index of Multiple Deprivation 2015 for data periods from 2011 to 2013 to 2015 to 2017, and the Index of Multiple Deprivation 2019 for data periods from 2016 to 2018 to 2018 to 2020: England, 2011 to 2013 to 2018 to 2020.

Abstract

This dataset is from the Gauteng City-Region Observatory which is a partnership between the University of Johannesburg, the University of the Witwatersrand, the Gauteng Provincial Government and several Gauteng municipalities. The GCRO has conducted previous Quality of Life Surveys in 2009 (Round 1), 2011 (Round 2), 2013-2014 (Round 3) and 2015-2016 (Round 4), and 2017-2018 (Round 5). Round 6 was conducted in 2020-2021 and is the latest round of the survey.

Geographic coverage

The survey covers the Gauteng province in South Africa.

Analysis unit

Households and individuals

Universe

The survey covers all adult residence in Gauteng province, South Africa.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Abstract

The COVID-19 pandemic closed schools around the world, forcing school systems and students to quickly attempt remote learning. We conducted a rapid response phone survey of over 1,500 high school students aged 14 to 18 in Ecuador to learn how students spend their time during the period of quarantine, examine their access to remote learning, and measure their mental health status.

Geographic coverage

Region 2 of Ecuador covers three provinces: Pichincha, a relatively urban province that includes the capital city of Quito, and two provinces Orellana and Napo that cover the jungle region.

Analysis unit

Student

Universe

Our sampling frame for the phone survey consisted of 4,163 students in 177 classes in 88 schools in Zone 2 of Ecuador.

Kind of data

Sample survey data [ssd]

Sampling procedure

In partnership with the Ministry of Education of Ecuador, Zone 2 (MINEDUC, Zona 2), we have an ongoing project that aims to teach high school students, in grades 10, 11 and 12, skills relevant for careers in entrepreneurship and science, using an online course called Showing Life Opportunities (DOV for the Spanish acronym) that was taught during class time using computers in schools. To be eligible for our project, schools had to have a reliable internet connection and a computer center with enough computers for one class to study. We cover 126 high schools in Zona 2, and more than 80% of students in the targeted grades. Our sampling frame for the phone survey consisted of 4,163 students in 177 classes in 88 schools. We stratified sampling by treatment status and class, to sample an equal number of students from both treatment arms and include students from all classes.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

An English version of the questionnaire is provided under the Documentation tab.

Response rate

We successfully interviewed 1,552 students for an overall survey response rate of 64.3%. Only 10 students (0.4%) refused the survey, while the rest had phone numbers that were not answered (11.0%), were non-existent (5.4%), or went straight to voicemail (16.8%).

In 1875, the average person born in Chile could expect to live to the age of 32 years, a figure that would remain largely stagnante throughout the late 19th and early 20th century, as the country’s Parliamentary era would see relatively little change in the day to day lives of the country’s citizens. Outside of two dips in 1910 and 1920, the latter primarily driven by the 1918 Spanish Flu epidemic. Life expectancy would see two sharp increases following the end of the First World War; the first in the 1920s, and the most dramatic in the early 1950s.

The first of these spikes, under President Ibáñez del Campo, can be attributed primarily to large increases in spending on public healthcare and improvements in public sanitation by the Campo administration. The second and larger spike, under President González Videla, can be attributed to a combination of mass immunization and vaccination, and the implementation of a national health care system, drastically cutting child mortality in the country. As a result of these reforms, life expectancy in Chile would more than double in just thirty years, rising from just over 33 years in 1925 to 69 years by 1955. Following the end of the Videla administration in 1952, life expectancy would continue to rise in Chile, as increasing urbanization, and the successful eradication of many childhood diseases would see both child and overall mortality decline. This rise has continued even into the 21st century, and as a result, life expectancy in Chile rose to over 78 years by the end of the century, and in 2020, it is estimated that the average person born in Chile will live to over 82 years old, the highest in South America.

Data for Figures and Tables in "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of data in the figures and tables published in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

50-e0diffT.csv

• Figure 1: Life expectancy changes 2019/20 and 2020/21 across countries. The countries areordered by increasing cumulative life expectancy losses since 2019. Grey dots indicate theaverage annual LE changes over the years 2015 through 2019.

51-arriagaT.csv

• Figure 2: Age contributions to life expectancy changes since 2019 separated for 2020 and 2021.

52-sexdiff.csv

• Figure 3: Change in the female life expectancy advantage from 2019 through 2021. Muted colorsindicate non-significant changes.

53-e0diffcodT.csv

• Figure 4:Life expectancy deficit in 2021 decomposed into contributions by age and cause of death. LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.

54-tab_arriaga.csv

• Table 1: Months of life expectancy (LE) changes and deficits (labelled ES) since the start of thepandemic attributed to age-specific mortality changes (labelled AT). LE deficit is defined as observed minus expected life expectancy had pre-pandemic mortality trends continued.

Abstract copyright UK Data Service and data collection copyright owner.

The Community Life Survey (CLS) is a household survey conducted in England, tracking the latest trends and developments across areas key to encouraging social action and empowering communities, including: volunteering and charitable giving; views about the local area; community cohesion and belonging; community empowerment and participation; influencing local decisions and affairs; and subjective well-being and loneliness.

The CLS was first commissioned by the Cabinet Office in 2012. From 2016-17, the Department for Digital, Culture, Media and Sport (DCMS) took over responsibility for publishing results. During 2020, the DCMS also commissioned the Community Life COVID-19 Re-contact Survey (CLRS) (SN 8781) to provide data on how the COVID-19 pandemic has affected volunteering, charitable giving, social cohesion, wellbeing and loneliness in England.

Background
Up to 2015-16, the survey used a face-to-face methodology. Following thorough testing (experimental online versions of the survey were released for 2013-14, 2014-15 and 2015-16), the CLS moved online from 2016-17 onwards, with an end to the previous face-to-face method. The survey uses a push-to-web methodology (with paper mode for those who are not digitally engaged). The survey informs and directs policy and action in these areas;

• to provide data of value to all users, including public bodies, external stakeholders and the public; and
• underpin further research and debate on building stronger communities.

The Community Life Survey incorporates a small number of priority measures from the Citizenship Survey, which ran from 2001-2011, conducted by the then Department for Communities and Local Government. These measures were incorporated in the Community Life Survey so that trends in these issues could continue to be tracked over time. (The full Citizenship Survey series is held at the UK Data Archive under GNs 33347 and 33474.)

Further information may be found on the GOV.UK Community Life Survey webpage.

The Community Life Survey, 2020 -2021 covers April 2020 - March 2021 and forms 'Official Statistics', meaning that it meets the high standards of quality set out by the Code of Practice for Official Statistics.

Further information may be found on the GOV.UK Community Life Survey, 2020/21 webpage.

The main topics include measures that are key to understanding our society and local communities such as volunteering, charitable giving, neighbourhood, civic engagement, social action and subjective well-being.

The Community Life Survey (CLS) is a household survey conducted in England, tracking the latest trends and developments across areas key to encouraging social action and empowering communities, including: volunteering and charitable giving; views about the local area; community cohesion and belonging; community empowerment and participation; influencing local decisions and affairs; and subjective well-being and loneliness.

The CLS was first commissioned by the Cabinet Office in 2012. From 2016-17, the Department for Digital, Culture, Media and Sport (DCMS) took over responsibility for publishing results. During 2020, the DCMS also commissioned the Community Life COVID-19 Re-contact Survey (CLRS) (SN 8781) to provide data on how the COVID-19 pandemic has affected volunteering, charitable giving, social cohesion, wellbeing and loneliness in England.

Background
Up to 2015-16, the survey used a face-to-face methodology. Following thorough testing (experimental online versions of the survey were released for 2013-14, 2014-15 and 2015-16), the CLS moved online from 2016-17 onwards, with an end to the previous face-to-face method. The survey uses a push-to-web methodology (with paper mode for those who are not digitally engaged). The survey informs and directs policy and action in these areas;

• to provide data of value to all users, including public bodies, external stakeholders and the public; and
• underpin further research and debate on building stronger communities.

The Community Life Survey incorporates a small number of priority measures from the Citizenship Survey, which ran from 2001-2011, conducted by the then Department for Communities and Local Government. These measures were incorporated in the Community Life Survey so that trends in these issues could continue to be tracked over time. (The full Citizenship Survey series is held at the UK Data Archive under GNs 33347 and 33474.)

Further information may be found on the GOV.UK https://www.gov.uk/government/collections/community-life-survey">Community Life Survey webpage.

Community Life COVID-19 Re-contact Survey, 2020
The re-contact survey (CLRS) is a follow-up to the Community Life Survey (CLS). The DCMS commissioned the CLRS to provide data on how the COVID-19 pandemic has affected volunteering, charitable giving, social cohesion, wellbeing and loneliness in England. The two waves of data are based on the 2,812 respondents who participated in both waves of the research:

• Wave 1 (pre-pandemic) survey respondents who participated in the CLS from July 2018 through to February 2020.
• Wave 2 (during the pandemic) survey: respondents who took part in a follow-up survey from 7-26 July 2020.

Further information may be found in the https://www.gov.uk/government/statistics/community-life-covid-19-re-contact-survey-2020-main-report/2-methodology-and-interpretation-community-life-recontact-survey-2020">Community Life COVID-19 Re-contact Survey 2020- Main Report and the https://www.gov.uk/government/statistics/community-life-covid-19-re-contact-survey-2020-main-report/2-methodology-and-interpretation-community-life-recontact-survey-2020">Methodology and Interpretation - Community Life COVID-19 Re-Contact Survey 2020 report.

Life expectancy of Ethiopia grew by 1.03% from 65.0 years in 2021 to 65.6 years in 2022. Since the 0.71% dip in 2020, life expectancy climb by 0.42% in 2022. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

The Kids' Life and Times Survey (KLT) began in 2008 and is conducted by Access Research Knowledge (ARK) which runs the Northern Ireland Life and Times Survey (NILT) and the Young Life and Times Survey (YLT). The KLT is a survey of Primary year 7 (P7) children in Northern Ireland which is carried out online and in school. (Note that NILT did not run in 2011, but resumed in 2012. The KLT and YLT both ran as normal in 2011.)

The aims of the KLT are to:

• provide broad-based monitoring systems to examine children's views on policy issues on a regular basis
• ensure that the information from the survey is fed back to policymakers and others engaged in the policy debates around children and their lives
• provide a high profile endorsement of 'participation' by Northern Ireland's children