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TwitterEmployment data in the United States for the millennial and baby boomer generations, broken up by the state, MSA, and industry for 2009-2013.
Source: Economic Modeling Specialists Inc (EMSI)
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For more than three decades UCSUR has documented the status of older adults in the County along multiple life domains. Every decade we issue a comprehensive report on aging in Allegheny County and this report represents our most recent effort. It documents important shifts in the demographic profile of the population in the last three decades, characterizes the current status of the elderly in multiple life domains, and looks ahead to the future of aging in the County. This report is unique in that we examine not only those aged 65 and older, but also the next generation old persons, the Baby Boomers. Collaborators on this project include the Allegheny County Area Agency on Aging, the United Way of Allegheny County, and the Aging Institute of UPMC Senior Services and the University of Pittsburgh.
The purpose of this report is to provide a comprehensive analysis of aging in Allegheny County. To this end, we integrate survey data collected from a representative sample of older county residents with secondary data available from Federal, State, and County agencies to characterize older individuals on multiple dimensions, including demographic change and population projections, income, work and retirement, neighborhoods and housing, health, senior service use, transportation, volunteering, happiness and life satisfaction, among others. Since baby boomers represent the future of aging in the County we include data for those aged 55-64 as well as those aged 65 and older.
Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.
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This dataset tracks annual total students amount from 2008 to 2016 for Baby Boomers
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This dataset is the most comprehensive look at volunteering and civic life in the 50 states and 51 cities across the country. Data include volunteer rates and rankings, civic engagement trends, and analysis.
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TwitterThe working-age population can be divided into two broad categories: the early-working age group (15-34) and the later working age group (35-64). The effect of fertility on the composition of these groups is obvious. The later working age group is largely composed of the baby-boomers (those born between 1946 and 1965), while the early working age group is composed of those born during the baby-bust period (1966-1974) and the children of baby-boomers. Thus, despite the fact that baby-boomers are now older, they still remain the largest group in the population. This is evident in the relatively large proportion (42.6%) of the population that belonged to the late working age group in 2006. The corresponding proportion was much smaller (31.3%) just 25 years ago in 1981. As a result of the entry into the working age group of the people born during the baby-bust period and the children of baby-boomers in 2006, only 26.0% of the population belonged to the 15 to 34 age group in 2006, compared with 36.5% in 1981.
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This dataset tracks annual diversity score from 2009 to 2016 for Baby Boomers vs. Florida and Broward School District
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This dataset tracks annual white student percentage from 2010 to 2016 for Baby Boomers vs. Florida and Broward School District
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This dataset reconstructs U.S. fertility trends with state-level Total Fertility Rates (TFR) from 1931 to the present, calculated annually. Birth data by maternal age and race (white and non-white) were digitized from the “Vital Statistics of the United States.” TFR calculations use interpolated census data on women aged 14–49. The dataset highlights regional shifts in fertility during the Baby Boom, later declines, and recent fluctuations, influenced by socio-economic and cultural factors. It provides a valuable tool for researchers and policymakers analyzing fertility determinants and their broader implications.
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Moldova's first Demographic and Health Survey (2005 MDHS) is a nationally representative sample survey of 7,440 women age 15-49 and 2,508 men age 15-59 selected from 400 sample points (clusters) throughout Moldova (excluding the Transnistria region). It is designed to provide data to monitor the population and health situation in Moldova; it includes several indicators which follow up on those from the 1997 Moldova Reproductive Health Survey (1997 MRHS) and the 2000 Multiple Indicator Cluster Survey (2000 MICS). The 2005 MDHS used a two-stage sample based on the 2004 Population and Housing Census and was designed to produce separate estimates for key indicators for each of the major regions in Moldova, including the North, Center, and South regions and Chisinau Municipality. Unlike the 1997 MRHS and the 2000 MICS surveys, the 2005 MDHS did not cover the region of Transnistria. Data collection took place over a two-month period, from June 13 to August 18, 2005. The survey obtained detailed information on fertility levels, abortion levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood mortality, maternal and child health, adult health, and awareness and behavior regarding HIV infection and other sexually transmitted diseases. Hemoglobin testing was conducted on women and children to detect the presence of anemia. Additional features of the 2005 MDHS include the collection of information on international emigration, language preference for reading printed media, and domestic violence. The 2005 MDHS was carried out by the National Scientific and Applied Center for Preventive Medicine, hereafter called the National Center for Preventive Medicine (NCPM), of the Ministry of Health and Social Protection. ORC Macro provided technical assistance for the MDHS through the USAID-funded MEASURE DHS project. Local costs of the survey were also supported by USAID, with additional funds from the United Nations Children's Fund (UNICEF), the United Nations Population Fund (UNFPA), and in-kind contributions from the NCPM. MAIN RESULTS CHARACTERISTICS OF RESPONDENTS Ethnicity and Religion. Most women and men in Moldova are of Moldovan ethnicity (77 percent and 76 percent, respectively), followed by Ukrainian (8-9 percent of women and men), Russian (6 percent of women and men), and Gagauzan (4-5 percent of women and men). Romanian and Bulgarian ethnicities account for 2 to 3 percent of women and men. The overwhelming majority of Moldovans, about 95 percent, report Orthodox Christianity as their religion. Residence and Age. The majority of respondents, about 58 percent, live in rural areas. For both sexes, there are proportionally more respondents in age groups 15-19 and 45-49 (and also 45-54 for men), whereas the proportion of respondents in age groups 25-44 is relatively lower. This U-shaped age distribution reflects the aging baby boom cohort following World War II (the youngest of the baby boomers are now in their mid-40s), and their children who are now mostly in their teens and 20s. The smaller proportion of men and women in the middle age groups reflects the smaller cohorts following the baby boom generation and those preceding the generation of baby boomers' children. To some degree, it also reflects the disproportionately higher emigration of the working-age population. Education. Women and men in Moldova are universally well educated, with virtually 100 percent having at least some secondary or higher education; 79 percent of women and 83 percent of men have only a secondary or secondary special education, and the remainder pursues a higher education. More women (21 percent) than men (16 percent) pursue higher education. Language Preference. Among women, preferences for language of reading material are about equal for Moldovan (37 percent) and Russian (35 percent) languages. Among men, preference for Russian (39 percent) is higher than for Moldovan (25 percent). A substantial percentage of women and men prefer Moldovan and Russian equally (27 percent of women and 32 percent of men). Living Conditions. Access to electricity is almost universal for households in Moldova. Ninety percent of the population has access to safe drinking water, with 86 percent in rural areas and 96 percent in urban areas. Seventy-seven percent of households in Moldova have adequate means of sanitary disposal, with 91 percent of households in urban areas and only 67 percent in rural areas. Children's Living Arrangements. Compared with other countries in the region, Moldova has the highest proportion of children who do not live with their mother and/or father. Only about two-thirds (69 percent) of children under age 15 live with both parents. Fifteen percent live with just their mother although their father is alive, 5 percent live with just their father although their mother is alive, and 7 percent live with neither parent although they are both alive. Compared with living arrangements of children in 2000, the situation appears to have worsened. FERTILITY Fertility Levels and Trends. The total fertility rate (TFR) in Moldova is 1.7 births. This means that, on average, a woman in Moldova will give birth to 1.7 children by the end of her reproductive period. Overall, fertility rates have declined since independence in 1991. However, data indicate that fertility rates may have increased in recent years. For example, women of childbearing age have given birth to, on average, 1.4 children at the end of their childbearing years. This is slightly less than the total fertility rate (1.7), with the difference indicating that fertility in the past three years is slightly higher than the accumulation of births over the past 30 years. Fertility Differentials. The TFR for rural areas (1.8 births) is higher than that for urban areas (1.5 births). Results show that this urban-rural difference in childbearing rates can be attributed almost exclusively to younger age groups. CONTRACEPTION Knowledge of Contraception. Knowledge of family planning is nearly universal, with 99 percent of all women age 15-49 knowing at least one modern method of family planning. Among all women, the male condom, IUD, pills, and withdrawal are the most widely known methods of family planning, with over 80 percent of all women saying they have heard of these methods. Female sterilization is known by two-thirds of women, while periodic abstinence (rhythm method) is recognized by almost six in ten women. Just over half of women have heard of the lactational amenorrhea method (LAM), while 40-50 percent of all women have heard of injectables, male sterilization, and foam/jelly. The least widely known methods are emergency contraception, diaphragm, and implants. Use of Contraception. Sixty-eight percent of currently married women are using a family planning method to delay or stop childbearing. Most are using a modern method (44 percent of married women), while 24 percent use a traditional method of contraception. The IUD is the most widely used of the modern methods, being used by 25 percent of married women. The next most widely used method is withdrawal, used by 20 percent of married women. Male condoms are used by about 7 percent of women, especially younger women. Five percent of married women have been sterilized and 4 percent each are using the pill and periodic abstinence (rhythm method). The results show that Moldovan women are adopting family planning at lower parities (i.e., when they have fewer children) than in the past. Among younger women (age 20-24), almost half (49 percent) used contraception before having any children, compared with only 12 percent of women age 45-49. MATERNAL HEALTH Antenatal Care and Delivery Care. Among women with a birth in the five years preceding the survey, almost all reported seeing a health professional at least once for antenatal care during their last pregnancy; nine in ten reported 4 or more antenatal care visits. Seven in ten women had their first antenatal care visit in the first trimester. In addition, virtually all births were delivered by a health professional, in a health facility. Results also show that the vast majority of women have timely checkups after delivering; 89 percent of all women received a medical checkup within two days of the birth, and another 6 percent within six weeks. CHILD HEALTH Childhood Mortality. The infant mortality rate for the 5-year period preceding the survey is 13 deaths per 1,000 live births, meaning that about 1 in 76 infants dies before the first birthday. The under-five mortality rate is almost the same with 14 deaths per 1,000 births. The near parity of these rates indicates that most all early childhood deaths take place during the first year of life. Comparison with official estimates of IMRs suggests that this rate has been improving over the past decade. NUTRITION Breastfeeding Practices. Breastfeeding is nearly universal in Moldova: 97 percent of children are breastfed. However the duration of breast-feeding is not long, exclusive breastfeeding is not widely practiced, and bottle-feeding is not uncommon. In terms of the duration of breastfeeding, data show that by age 12-15 months, well over half of children (59 percent) are no longer being breastfed. By age 20-23 months, almost all children have been weaned. Exclusive breastfeeding is not widely practiced and supplementary feeding begins early: 57 percent of breastfed children less than 4 months are exclusively breastfed, and 46 percent under six months are exclusively breastfeed. The remaining breastfed children also consume plain water, water-based liquids or juice, other milk in addition to breast milk, and complimentary foods. Bottle-feeding is fairly widespread in Moldova; almost one-third (29 percent) of infants under 4 months old are fed with a bottle with
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This dataset tracks annual black student percentage from 2008 to 2016 for Baby Boomers vs. Florida and Broward School District
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TwitterIn the past, a generation covered a larger span of time, having more members. However, today, thanks to the developments in technology and many other factors generations change frequently having less members and covering a few years. What matters now is the workforce itself and how these different generations work together. The current workforce has 3 generations working together while waiting for the fourth one. Soon, it is inevitable that 5 or 6 generations will be working at the same workplace. As a result, it is crucial to understand the type of leadership a generation prefers in business and academic life. The aim of this study was to find out how leadership style choice differs among four generations (Baby Boomers, Generations X, Generation Y, and Generation Z) of academics and prospective academics in Turkey. In the study, 265 participants from different generation rated the leadership attributes that contribute or impede effective leadership. The Global Leadership and Organizational Behavior Effectiveness (GLOBE) Project research survey by House et al. (2004) was used to find out the leadership style choice of different generations. The statistical relationships were determined between the generation variable and the 16 primary leadership subscales through MANOVAs and ANOVAs. The results of the tests showed that significant differences exist among the four different generations in 3 of the 16 leadership subscales. These subscales are Charismatic 3: Self-sacrifice, Conflict-inducer, and Face saver.
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This directory contains data behind the story How Baby Boomers Get High. It covers 13 drugs across 17 age groups.
Source: National Survey on Drug Use and Health from the Substance Abuse and Mental Health Data Archive.
| Header | Definition |
|---|---|
alcohol-use | Percentage of those in an age group who used alcohol in the past 12 months |
alcohol-frequency | Median number of times a user in an age group used alcohol in the past 12 months |
marijuana-use | Percentage of those in an age group who used marijuana in the past 12 months |
marijuana-frequency | Median number of times a user in an age group used marijuana in the past 12 months |
cocaine-use | Percentage of those in an age group who used cocaine in the past 12 months |
cocaine-frequency | Median number of times a user in an age group used cocaine in the past 12 months |
crack-use | Percentage of those in an age group who used crack in the past 12 months |
crack-frequency | Median number of times a user in an age group used crack in the past 12 months |
heroin-use | Percentage of those in an age group who used heroin in the past 12 months |
heroin-frequency | Median number of times a user in an age group used heroin in the past 12 months |
hallucinogen-use | Percentage of those in an age group who used hallucinogens in the past 12 months |
hallucinogen-frequency | Median number of times a user in an age group used hallucinogens in the past 12 months |
inhalant-use | Percentage of those in an age group who used inhalants in the past 12 months |
inhalant-frequency | Median number of times a user in an age group used inhalants in the past 12 months |
pain-releiver-use | Percentage of those in an age group who used pain relievers in the past 12 months |
pain-releiver-frequency | Median number of times a user in an age group used pain relievers in the past 12 months |
oxycontin-use | Percentage of those in an age group who used oxycontin in the past 12 months |
oxycontin-frequency | Median number of times a user in an age group used oxycontin in the past 12 months |
tranquilizer-use | Percentage of those in an age group who used tranquilizer in the past 12 months |
tranquilizer-frequency | Median number of times a user in an age group used tranquilizer in the past 12 months |
stimulant-use | Percentage of those in an age group who used stimulants in the past 12 months |
stimulant-frequency | Median number of times a user in an age group used stimulants in the past 12 months |
meth-use | Percentage of those in an age group who used meth in the past 12 months |
meth-frequency | Median number of times a user in an age group used meth in the past 12 months |
sedative-use | Percentage of those in an age group who used sedatives in the past 12 months |
sedative-frequency | Median number of times a user in an age group used sedatives in the past 12 months |
This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!
This dataset is maintained using GitHub's API and Kaggle's API.
This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.
Cover photo by Eric Muhr on Unsplash
Unsplash Images are distributed under a unique Unsplash License.
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This dataset tracks annual free lunch eligibility from 2009 to 2013 for Baby Boomers vs. Florida and Broward School District
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This dataset tracks annual hispanic student percentage from 2009 to 2015 for Baby Boomers vs. Florida and Broward School District
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This dataset tracks annual reduced-price lunch eligibility from 2010 to 2013 for Baby Boomers vs. Florida and Broward School District
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Comprehensive dataset containing 12 verified Baby Boom locations in Italy with complete contact information, ratings, reviews, and location data.
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The BBBS is a longitudinal study designed to comprehensively characterise chronic disease in a community sample of ‘baby boomers’ (adults born 1946 to 1964) living in the Busselton Shire, Western Australia. A total of 5,107 baby boomers participated in the first phase (baseline) study in 2010-2015, known as the Busselton Healthy Ageing Study (BHAS). These 5,107 participants represent a 76% participation rate in the City of Busselton. The cohort are followed-up every 3-5 years.
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TwitterComprehensive YouTube channel statistics for Baby Boom-Boom, featuring 931,000 subscribers and 312,260,147 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in IN. Track 126 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.
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Beauty and wellness are terms used often in common parlance, however their meaning and relation to each other is unclear. To probe their meaning, we applied network science methods to estimate and compare the semantic networks associated with beauty and wellness in different age generation cohorts (Generation Z, Millennials, Generation X, and Baby Boomers) and in women and men. These mappings were achieved by estimating group-based semantic networks from free association responses to a list of 47 words, either related to Beauty, Wellness, or Beauty + Wellness. Beauty was consistently related to Elegance, Feminine, Gorgeous, Lovely, Sexy, and Stylish. Wellness was consistently related Aerobics, Fitness, Health, Holistic, Lifestyle, Medical, Nutrition, and Thrive. In addition, older cohorts had semantic networks that were less connected and more segregated from each other. Finally, we found that women compared to men had more segregated and organized concepts of Beauty and Wellness. In contemporary societies that are pre-occupied by the pursuit of beauty and a healthy lifestyle, our findings shed novel light on how people think about beauty and wellness and how they are related across different age generations and by sex.
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KLoSA was designed to provide basic data on population ageing in Korea. At baseline, the KLoSA cohort comprised middle- to old individuals aged 45 years or older (born in 1961 or earlier) across South Korea (not including Jeju Island). Participants were selected randomly using a multistage, stratified probability sampling design to create a nationally representative sample of community-dwelling Koreans 45 years of age and older. The exact sample size at baseline was 6,171 households and 10,254 individuals. In 2014, KLoSA recruited a new cohort of 1,000 Korean Baby Boomers (born between 1962 and 1963) in the fifth baseline survey and has continued to keep track of this new cohort since its addition.
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TwitterEmployment data in the United States for the millennial and baby boomer generations, broken up by the state, MSA, and industry for 2009-2013.
Source: Economic Modeling Specialists Inc (EMSI)