In 2022, about 37.7 percent of the U.S. population who were aged 25 and above had graduated from college or another higher education institution, a slight decline from 37.9 the previous year. However, this is a significant increase from 1960, when only 7.7 percent of the U.S. population had graduated from college. Demographics Educational attainment varies by gender, location, race, and age throughout the United States. Asian-American and Pacific Islanders had the highest level of education, on average, while Massachusetts and the District of Colombia are areas home to the highest rates of residents with a bachelor’s degree or higher. However, education levels are correlated with wealth. While public education is free up until the 12th grade, the cost of university is out of reach for many Americans, making social mobility increasingly difficult. Earnings White Americans with a professional degree earned the most money on average, compared to other educational levels and races. However, regardless of educational attainment, males typically earned far more on average compared to females. Despite the decreasing wage gap over the years in the country, it remains an issue to this day. Not only is there a large wage gap between males and females, but there is also a large income gap linked to race as well.

In 2022, Canada had the highest share of adults with a university degree, at over 60 percent of those between the ages of 25 and 64. India had the smallest share of people with a university degree, at 13 percent of the adult population. University around the world Deciding which university to attend can be a difficult decision for some and in today’s world, people are not left wanting for choice. There are thousands of universities around the world, with the highest number found in India and Indonesia. When picking which school to attend, some look to university rankings, where Harvard University in the United States consistently comes in on top. Moving on up One of the major perks of attending university is that it enables people to move up in the world. Getting a good education is generally seen as a giant step along the path to success and opens up doors for future employment. Future earnings potential can be determined by which university one attends, whether by the prestige of the university or the connections that have been made there. For instance, graduates from the Stanford Graduate School of Business can expect to earn around 250,000 U.S. dollars annually.

According to the Global Gender Gap Report 2020, 88 percent of females worldwide had primary education, compared to 91 percent of males. By comparison, more females than males had attained tertiary education. The Global Gender Index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2020, the leading country was Iceland with a score of 0.87.

The average for 2022 based on 117 countries was 1.21 percent. The highest value was in Qatar: 1.79 percent and the lowest value was in Benin: 0.59 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

Among the OECD countries, Canada had the highest proportion of adults with a tertiary education in 2022. About 63 percent of Canadians had achieved a tertiary education in that year. Japan followed with about 56 percent of the population having completed a tertiary education, while in Ireland the share was roughly 54 percent. In India, on the other hand, less than 13 percent of the adult population had completed a tertiary education in 2022.

The average for 2022 based on 78 countries was 439.569 index points. The highest value was in Singapore: 574.664 index points and the lowest value was in Cambodia: 336.396 index points. The indicator is available from 2003 to 2022. Below is a chart for all countries where data are available.

This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Gymnasium Is High School Equivalent In His Country. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Gymnasium Is High School Equivalent In His Country. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

Online Music Education Market Outlook

The global market size for online music education was valued at approximately USD 1.75 billion in 2023 and is expected to reach USD 4.25 billion by 2032, growing at a compound annual growth rate (CAGR) of 10.5% during the forecast period. This robust growth is driven by several factors, including the increasing penetration of internet services, the rising popularity of online learning platforms, and a growing interest in music education among individuals of all age groups.

One of the primary growth drivers for the online music education market is the widespread availability of internet services and the growing use of digital devices. In an era where technology is deeply integrated into daily life, online platforms offer unparalleled convenience and flexibility. This is particularly appealing to working professionals and students who may not have the time or resources to attend traditional music classes. Additionally, the COVID-19 pandemic significantly accelerated the adoption of online education, including music education, as people sought productive ways to utilize their time during lockdowns and social restrictions.

Another key factor contributing to market growth is the increasing popularity of personalized learning experiences. Online music education platforms often offer tailored lessons that cater to the individual needs and skill levels of learners. This adaptability makes it easier for students to progress at their own pace, thereby enhancing their learning experience. Moreover, the use of advanced technologies such as artificial intelligence (AI) and machine learning (ML) in these platforms helps in creating more engaging and interactive educational content, further boosting the appeal of online music education.

The rise in disposable income and the growing importance of extracurricular activities in holistic education also play crucial roles in driving market growth. Parents and guardians are increasingly willing to invest in music education for their children, recognizing its benefits for cognitive development and emotional well-being. This trend is not just limited to children; adults are also showing a keen interest in learning music as a hobby or even as a second career, contributing to the market's expansion.

From a regional perspective, North America and Europe are currently the leading markets for online music education. These regions benefit from advanced technological infrastructure, high levels of digital literacy, and a strong culture of music appreciation. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by the increasing adoption of online learning platforms and the growing popularity of music education in countries like China, India, and Japan. Meanwhile, Latin America and the Middle East & Africa are also showing promising growth, although they currently hold smaller market shares compared to other regions.

Type Analysis

The online music education market can be segmented by type into instrumental, vocal, and theory. Each of these segments caters to different aspects of music education and targets varied learner demographics. Instrumental education, for instance, focuses on teaching how to play various musical instruments, such as the guitar, piano, or violin. This segment has gained substantial traction due to the availability of diverse courses that cater to both beginners and advanced learners. The ability to access high-quality instructional videos and interactive lessons from renowned musicians and educators worldwide has made instrumental education a preferred choice for many.

Vocal training is another significant segment that has seen considerable growth. This segment offers lessons on various singing techniques, voice modulation, and performance skills. The increasing popularity of virtual choirs, online singing competitions, and social media platforms where individuals showcase their singing talents has further fueled the demand for online vocal training. Moreover, vocal training platforms often incorporate features like real-time feedback and AI-powered assessments, which enhance the learning experience and make it more interactive.

The theory segment focuses on the foundational aspects of music education, such as reading music, understanding scales, chords, and rhythm, and comprehending music history and theory. This segment is crucial for those who wish to gain a deeper understanding of music and its components. Online platforms offering music theory courses often provide com

Abstract

This survey intends to: -

· Measure the labour force or economically active population size in relation to the general population in the country. · Identify and analyse the factors leading to the emergence and growth of Labour Force in the country. · Monitor the labour force participation. · Identify and measure the informal sector from within the labour force. · Monitor other Key Indicators of the Labour Market such as employment rates,unemployment rates, hours of work, average income and/or wages etc.

Furthermore, the survey seeks to examine the relationships of socio-economic factors such as education, health, social security, employment within the labour force, and more importantly to measure the causes and effects of children’s involvements in economic activities with special focus on the conditions and environment under which affected children operate.

The main objective of the 2012 LFS was to collect data on the social and economic activities of the population, including detailed information on employment, unemployment, underemployment, wages, informal sector, general characteristics of the labour force and economically inactive population. The survey was designed to specifically measure and monitor Key Indicators of the Labour Market (KILM) such as employment levels, unemployment, income and child labour in Zambia. However, indicators on child labour are not part of this 2012 LFS report. There will be a separate report on child labour later. The measurement of the KILM was with a view to informing users and policy-makers for decision-making. The methodology used in carrying out the survey and the design of questionnaire conform to internationally acceptable standards.

Geographic coverage

The 2012 Labour Force Survey (LFS) was a nation-wide survey covering household population in all the ten provinces and, in both rural and urban areas. The survey covered a representative sample of 11, 520 households, which were selected at two stages. In the first stage, 576 Standard Enumeration Areas (SEAs) were selected from a sampling frame developed from the 2010 Census of Population and Housing. In the second stage, households in each of the selected SEA were first listed/updated and then 20 households for enumeration were selected. The total sample of 11,520 households was first allocated between rural, urban and the provincial domains in proportion to the population of each domain according to the 2010 Census results.

Analysis unit

The unit of analysis was Households and Individuals ( Men and Women of 5 years and older). Additionally, the analysis focused on national level at both rural/urban and provincial level. The micro-data has provisions to generate major indicators at district and constituency levels. As much as possible the micro-data have also been analyzed by sex and age.

Universe

The survey covered all de jure household members (usual residents) in non-institutionalised housing units, all women and men aged 5 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to allow separate estimates at national level for rural and urban areas. Further, it also allowed for provincial estimates. A cluster, which is equivalent to a Standard Enumeration Area (SEA), was the primary sampling unit in the ?rst stage. In the second stage, a household was a sampling unit for enumeration purposes. Zambia is administratively divided into ten provinces. Each province is in turn subdivided into districts. For statistical purposes each district is subdivided into Census Supervisory Areas (CSAs) and these are in turn demarcated into Standard Enumeration Areas (SEAs). The Census mapping exercise of 2006-2010 in preparation for the 2010 Census of Population and Housing, demarcated the CSAs within wards, wards within constituencies and constituencies within districts. As at the time of the survey, Zambia had 74 districts, 150 constituencies, 1,430 wards and about 25,000 SEAs. Information borne on the list of SEAs from the sampling frame also includes number of households and the population size as at the last update of the SEA. The number of households determined the selection of primary sampling units (PSU). The SEAs are stratifed as urban and rural. The total sample of 11,520 households was first allocated between rural, urban and the provincial domains in proportion to the population of each domain according to the 2010 Census results. The proportional allocation does not however allow for reliable estimates for lower domains like district, ward or constituency. Adjustments to the proportional allocation of the sample were made to allow for reasonable comparison to be achieved between strata or domains. Therefore, disproportionate allocation was adopted, for the purpose of maximizing the precision of survey estimates. The disproportionate allocation is based on the optimal square root allocation method designed by Leslie Kish. The sample was then selected using a stratifed two-stage cluster design.

Sampling deviation

There was no deviation from sample design.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of questionnaires (Form A and Forma B) were used to collect data from the household members. Form A was used in the first stage for listing purposes while Form B was used in the second stage for collecting detailed data from the selected households. It was a requirement for each household member to provide responses during the face-to-face interview to the questions that were asked.

The main questionnaire has ten sections namely:

a. Demographic Characteristics b. Education, Literacy and Skills Training c. Economic Activity d. Employment e. Hours of Work and Underemployment f. Income g. Unemployment/Job Search h. Previous Work Experience i. Household Chores j. Working Conditions (i.e. Forced labour)

Cleaning operations

Data editing took place at a number of stages throughout the processing. These included:

1. Field editing
2. Office editing and coding
3. During data entry
4. Structure checking and completeness
5. Secondary editing
6. Strucural checking of SAS data files

Response rate

At the end of the field work and editing in the provinces, a total of at least 11,000 of completed questionnaires, representing a 99.8 percent response rate were sent to Head Office for data processing.

Data appraisal

A series of data quality tables and graphs are available to review the quality of the data and in addition to this, external resources such as the 2012 Labour Force Survey report has been attached.

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

Appendix A: Search Strategy

This appendix details the systematic search protocol used to identify relevant literature, adhering to PRISMA 2020 guidelines. It specifies the SCOPUS database query executed on January 5, 2025, covering peer-reviewed articles from 2015–2024 in English. The Boolean search strategy is outlined, combining terms related to patient safety, nursing education, and undergraduate training to ensure comprehensive retrieval of 6,889 initial records. This rigorous methodology underpins the review’s credibility, ensuring replicability and transparency in study selection.

Appendix B: Key Characteristics of Included Studies

Appendix B provides a detailed summary of the 21 studies included in the integrative review, covering publication details, objectives, methodologies, sample characteristics, key findings, and implications for patient safety education. It serves as a foundational reference, synthesizing empirical evidence from diverse research designs (qualitative, quantitative, mixed methods) to highlight trends, gaps, and pedagogical innovations in undergraduate nursing education. This tabular compilation ensures clarity and traceability of the evidence base.

Appendix C: Bibliometric Network of Co-occurring Terms

This appendix presents a bibliometric network visualizing keyword co-occurrences in patient safety education research (2015–2024). Generated using VOSviewer’s clustering techniques, it maps thematic linkages, emphasizing terms like “patient safety,” “nursing education,” and “clinical competence.” The network underscores the centrality of simulation-based learning and competency development, revealing a shift toward evidence-based pedagogies. It provides a quantitative lens on the field’s conceptual structure, complementing the qualitative synthesis.

Appendix D: Longitudinal Trend Analysis of Research Themes

Appendix D, created using Bibliometrix on Posit Cloud, tracks the evolution of research themes in patient safety education from 2015–2024. It highlights the persistent marginalization of patient safety in curricula despite its recognized importance, with dominant terms like “nurse,” “nursing student,” and “medication errors” indicating a focus on clinical competency. The analysis exposes gaps in curricular integration and advocates for sustained pedagogical strategies like simulation and quality improvement to bridge theory-practice divides.

Appendix E: Conceptual Structure Mapping (Multiple Correspondence Analysis)

Using Multiple Correspondence Analysis (MCA), Appendix E offers a two-dimensional conceptual map of patient safety education research (2015–2024). Dense clustering around “nursing student,” “nursing education,” “clinical competence,” and “patient safety” underscores their centrality. The map highlights the field’s focus on undergraduate training and competency development, reinforcing the need for evidence-based curricular reform to prioritize safety as a core competency rather than a peripheral topic.

Appendix F: Sankey Diagram of Keyword Associations and Geographic Trends

Appendix F’s Sankey diagram maps relationships between keywords, leading authors, and countries in patient safety education research (2015–2024). It identifies patient safety education as a central node, with significant research output from the USA and Iran, and emerging contributions from India, Australia, and Ethiopia. Underrepresented themes like prevention and drug safety, linked to China and Nigeria, signal global research disparities. This appendix emphasizes the need for inclusive, context-adaptive curricula to address inequities in safety education.

Appendix G: Emerging Trends in Patient Safety Education

This appendix catalogs transformative trends in patient safety education, including interprofessional simulation, non-punitive error disclosure protocols, and competency tracking via tools like H-PEPSS. It highlights the shift from skill-based learning to cultural enculturation, emphasizing systems-aware pedagogies that integrate human factors and organizational culture. However, it notes implementation challenges, such as resource disparities and hierarchical clinical norms, which hinder scalability and impact in diverse settings.

Appendix H: Comprehensive Curriculum Strategies

Appendix H proposes a tiered curriculum framework to embed patient safety as a core competency in nursing education. It advocates vertical integration across courses, interprofessional collaboration, and accreditation-driven mandates. Micro-curricular innovations—dedicated education units, gamified drills, and low-cost tools like mobile-based error reporting—ensure adaptability for resource-constrained settings. The framework’s evidence-based strategies, including a 38% reduction in latent error rates through early safety enculturation, offer a scalable blueprint for global reform.

These appendices collectively provide a robust, multi-faceted foundation for the review’s findings, combining methodological rigor (A, B), quantitative bibliometric insights (C, D, E, F), and practical recommendations (G, H). They underscore the urgent need for systematic, equitable, and evidence-based transformation in patient safety education to prepare nursing graduates for modern healthcare’s complexities.

Abstract

The authors combine data from 84 Demographic and Health Surveys from 46 countries to analyze trends and socioeconomic differences in adult mortality, calculating mortality based on the sibling mortality reports collected from female respondents aged 15-49.

The analysis yields four main findings. First, adult mortality is different from child mortality: while under-5 mortality shows a definite improving trend over time, adult mortality does not, especially in Sub-Saharan Africa. The second main finding is the increase in adult mortality in Sub-Saharan African countries. The increase is dramatic among those most affected by the HIV/AIDS pandemic. Mortality rates in the highest HIV-prevalence countries of southern Africa exceed those in countries that experienced episodes of civil war. Third, even in Sub-Saharan countries where HIV-prevalence is not as high, mortality rates appear to be at best stagnating, and even increasing in several cases. Finally, the main socioeconomic dimension along which mortality appears to differ in the aggregate is gender. Adult mortality rates in Sub-Saharan Africa have risen substantially higher for men than for women?especially so in the high HIV-prevalence countries. On the whole, the data do not show large gaps by urban/rural residence or by school attainment.

This paper is a product of the Human Development and Public Services Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org.

Geographic coverage

We derive estimates of adult mortality from an analysis of Demographic and Health Survey (DHS) data from 46 countries, 33 of which are from Sub-Saharan Africa and 13 of which are from countries in other regions (Annex Table). Several of the countries have been surveyed more than once and we base our estimates on the total of 84 surveys that have been carried out (59 in Sub-Saharan Africa, 25 elsewhere).

The countries covered by DHS in Sub-Saharan Africa represent almost 90 percent of the region's population. Outside of Sub-Saharan Africa the DHS surveys we use cover a far smaller share of the population-even if this is restricted to countries whose GDP per capita never exceeds $10,000: overall about 14 percent of the population is covered by these countries, although this increases to 29 percent if China and India are excluded (countries for which we cannot calculate adult mortality using the DHS). It is therefore important to keep in mind that the sample of non-Sub-Saharan African countries we have cannot be thought of as "representative" of the rest of the world, or even the rest of the developing world.

Analysis unit

Country

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Cleaning operations

In the course of carrying out this study, the authors created two databases of adult mortality estimates based on the original DHS datasets, both of which are publicly available for analysts who wish to carry out their own analysis of the data.

The naming conventions for the adult mortality-related are as follows. Variables are named:

GGG_MC_AAAA

GGG refers to the population subgroup. The values it can take, and the corresponding definitions are in the following table:

All - All Fem - Female Mal - Male Rur - Rural Urb - Urban Rurm - Rural/Male Urbm - Urban/Male Rurf - Rural/Female Urbf - Urban/Female Noed - No education Pri - Some or completed primary only Sec - At least some secondary education Noedm - No education/Male Prim - Some or completed primary only/Male Secm - At least some secondary education/Male Noedf - No education/Female Prif - Some or completed primary only/Female Secf - At least some secondary education/Female Rch - Rural as child Uch - Urban as child Rchm - Rural as child/Male Uchm - Urban as child/Male Rchf - Rural as child/Female Uchf - Urban as child/Female Edltp - Less than primary schooling Edpom - Primary or more schooling Edltpm - Less than primary schooling/Male Edpomm - Primary or more schooling/Male Edltpf - Less than primary schooling/Female Edpomf - Primary or more schooling/Female Edltpu - Less than primary schooling/Urban Edpomu - Primary or more schooling/Urban Edltpr - Less than primary schooling/Rural Edpomr - Primary or more schooling/Rural Edltpmu - Less than primary schooling/Male/Urban Edpommu - Primary or more schooling/Male/Urban Edltpmr - Less than primary schooling/Male/Rural Edpommr - Primary or more schooling/Male/Rural Edltpfu - Less than primary schooling/Female/Urban Edpomfu - Primary or more schooling/Female/Urban Edltpfr - Less than primary schooling/Female/Rural Edpomfr - Primary or more schooling/Female/Rural

M refers to whether the variable is the number of observations used to calculate the estimate (in which case M takes on the value "n") or whether it is a mortality estimate (in which case M takes on the value "m").

C refers to whether the variable is for the unadjusted mortality rate calculation (in which case C takes on the value "u") or whether it adjusts for the number of surviving female siblings (in which case C takes on the value "a").

AAAA refers to the age group that the mortality estimate is calculated for. It takes on the values: 1554 - Ages 15-54 1524 - Ages 15-24 2534 - Ages 25-34 3544 - Ages 35-44 4554 - Ages 45-54

Other variables that are in the databases are:

period - Period for which mortality rate is calculated (takes on the values 1975-79, 1980-84 … 2000-04) svycountry - Name of country for DHS countries ccode3 - Country code u5mr - Under-5 mortality (from World Development Indicators) cname - Country name gdppc - GDP per capita (constant 2000 US$) (from World Development Indicators) gdppcppp - GDP per capita PPP (constant 2005 intl $) (from World Development Indicators) pop - Population (from World Development Indicators) hivprev2001 - HIV prevalence in 2001 (from UNAIDS 2010) region - Region

UNICEF's country profile for India, including under-five mortality rates, child health, education and sanitation data.

In 2023, more women than men had a post-secondary education of three years or more in Sweden. In detail, 29 percent of the Swedish women and 19 percent of the Swedish men had attained that education level. On the other hand, a higher share of men than women had a form of upper secondary education. More than one fourth of men and one fifth of women had an upper secondary education of three years. Women’s access to education More women than men completing post-secondary education programs is not a trend limited to Sweden. Across all OECD countries in 2021, more women were first-time higher education students than men. A large portion of these women are entering into healthcare and education programs, while less than a quarter are entering into science, technology, engineering, and mathematics (STEM) programs. Issues facing Swedish women today While more Swedish women are accessing education and leading autonomous lives, they still face many gender-based issues. In 2022, domestic abuse, equal pay, and sexual violence were all cited as top gender issues for Swedish women. More Swedish women than men report feeling unsafe at night, and for both genders, concerns about crime are increasing.

The average for 2022 based on 36 countries was 462.873 index points. The highest value was in Estonia: 509.947 index points and the lowest value was in Albania: 368.222 index points. The indicator is available from 2003 to 2022. Below is a chart for all countries where data are available.

Out of the OECD countries, Luxembourg was the country that spent the most on educational institutions per full-time student in 2020. On average, 23,000 U.S dollars were spent on primary education, nearly 27,000 U.S dollars on secondary education, and around 53,000 U.S dollars on tertiary education. The United States followed behind, with Norway in third. Meanwhile, the lowest spending was in Mexico.

Abstract copyright UK Data Service and data collection copyright owner.Background:The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will requireto provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)to collect information on previously neglected topics, such as fathers' involvement in children's care and developmentto focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may beto emphasise intergenerational links including those back to the parents' own childhoodto investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when availableAdditional objectives subsequently included for MCS were:to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of EnglandFurther information about the MCS can be found on the Centre for Longitudinal Studies web pages.The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website. The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.End User Licence versions of MCS studies:The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.Sub-sample studies:Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).Release of Sweeps 1 to 4 to Long Format (Summer 2020)To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation. How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.Secure Access datasets:Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).Secure Access versions of the MCS include:detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)linked education administrative datasets for Key Stages 1, 2 and 4 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;Banded Distances to English Grammar Schools for MCS5 held under SN 8394linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030linked Hospital of Birth data held under SN 5724.The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application. Users are also only allowed access to either 2001 or 2011 of Geographical Identifiers Census Boundaries studies. So for MCS5 either SN 7762 (2001 Census Boundaries) or SN 7763 (2011 Census Boundaries), for the MCS6 users are only allowed either SN 8231 (2001 Census Boundaries) or SN 8232 (2011 Census Boundaries); and the same applies for MCS7 so either SN 8758 (2001 Census Boundaries) or SN 8759 (2011 Census Boundaries).Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page). MCS5: The fifth sweep took place when the children were aged around 11 and in their last year of primary school. Fieldwork started in January 2012 and finished in February 2013. Interviews were conducted with the main carer (typically the child’s parent) and their co-resident partner (typically the child’s other parent). The cohort children had measurements taken of their height, weight and body fat; participated in three cognitive assessments and completed a self-completion questionnaire. A survey of class teachers was also conducted but only in England and Wales, and consent was collected from the parent and children to contact the teacher.Latest edition informationFor the 6th edition (October 2022), a new date file mcs5_family_interview, has been added due to the family level data being split out from the parent-level data to make future merging with MCS8 onwards easier. Two data files (mcs5_parent_interview and mcs5_parent_cm_interview) have been updated to include variables that were missed from the previous edition due to a technical error (mainly from the income and employment module). There has been some further restructuring of datasets (parent responses moved out of mcs5_cm_interview and placed into mcs5_parent_cm_interview). Derived SDQ scores have been added to mcs5_cm_derived and a derived Kessler score has been added to mcs5_parent_derived. In addition, the number of cases in the mcs5_hhgrid data file have changed due to updates. Users are advised to check the Longitudinal Family File held under SN 8172 for the sample size. Main Topics: The files currently included in the MCS5 study comprise data from the main Parent Interview, the Household Grid, Child Measurement and Assessment and the Cohort Member self-completion questionnaire. The Parent Interview file comprises data from the Main Respondent, Partner Respondent and Proxy Respondent questionnaires, which covered household information; family context; education, schooling and childcare; child and family activities; parenting activities; child’s health; parent’s health; employment, income and education; housing and local area; and other matters. The Household Grid file comprises demographic data on households and additional derived variables. The Child Assessments and Measurement files include cognitive and physical measurements, including verbal similarities; a memory task (officially named the Spatial Working Memory task); a decision-making task (officially named the Cambridge Gambling task); height; weight; and waist circumference and body fat measurement. The Cohort Member paper self-completion was given to all participant children. The Teacher Survey data

Abstract copyright UK Data Service and data collection copyright owner.Background:The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will requireto provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)to collect information on previously neglected topics, such as fathers' involvement in children's care and developmentto focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may beto emphasise intergenerational links including those back to the parents' own childhoodto investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when availableAdditional objectives subsequently included for MCS were:to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of EnglandFurther information about the MCS can be found on the Centre for Longitudinal Studies web pages.The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website. The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.End User Licence versions of MCS studies:The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.Sub-sample studies:Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).Release of Sweeps 1 to 4 to Long Format (Summer 2020)To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation. How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.Secure Access datasets:Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).Secure Access versions of the MCS include:detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)linked education administrative datasets for Key Stages 1, 2 and 4 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;Banded Distances to English Grammar Schools for MCS5 held under SN 8394linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030linked Hospital of Birth data held under SN 5724.The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application. Users are also only allowed access to either 2001 or 2011 of Geographical Identifiers Census Boundaries studies. So for MCS5 either SN 7762 (2001 Census Boundaries) or SN 7763 (2011 Census Boundaries), for the MCS6 users are only allowed either SN 8231 (2001 Census Boundaries) or SN 8232 (2011 Census Boundaries); and the same applies for MCS7 so either SN 8758 (2001 Census Boundaries) or SN 8759 (2011 Census Boundaries).Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page). While many of the areas covered in MCS3 built on the information already collected in MCS1 (age 9 months) and MCS2 (age 3 years), a number of new items were also included, such as the measurement of waist circumference. Information was gathered from the cohort members' parents or guardians for the main Parent Interview. In addition there were four cognitive assessments and three physical measurements of the cohort child, and a paper self-completion questionnaire for up to two older siblings aged 10-15 years. The Teacher Survey and Foundation Stage Profile data and documentation are available in a separate study: SN 6847 - Millennium Cohort Study: Third Survey Teacher Survey and Foundation Stage Profile, 2006. May 2017: The longitudinal family file is now available separately under SN 8172.Update 20 March 2020: The datasets became available in a long format (one row per respondent) compared to the wide old format (one row per family). Information on the restructure of the variables from long to wide is provided in Part 9 of the MCS 1-5 User Guide. Help with the distribution of the variables in datasets is provided in the MCS1-4_Wide_Long_Correspondence_v* and in the MCS_Longitudinal_Data_Dictionary.November 2023: We are aware that some errors exist in the derived variable datasets. Please do not use until next updated.This study now includes the data and documentation from the Teacher Survey completed at Sweep 3 which were previously available under SN 6847.For the ninth edition (January 2022), a new data file mcs3_family_interview has been added due to the family level data being split out from the parent-level data to make future merging with MCS8 onwards easier. Two data files (mcs3_parent_interview and mcs3_parent_cm_interview) have been updated to include variables that were missed from the previous edition due to a technical error. In addition, mcs3_hhgrid has had some data edits applied.Also the following data file specific changes have been made:mcs3_hhgridTotal number of cases has changed due to data updates. For sample size please check the longitudinal family file. Main Topics: The files currently included in the MCS3 study comprise data from the main Parent Interview, the Household Grid, Child Measurement and Assessment and the Older Siblings questionnaire. The Parent Interview file comprises data from the Main Respondent, Partner Respondent and Proxy Respondent questionnaires, which covered household information; family context; early education, schooling and childcare; child and family activities and child's behaviour; parenting activities; child's health; parent's health; employment, income and education; housing and local

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

Additional objectives subsequently included for MCS were:

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old. End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).


How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS include:

• detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
  
• detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
• linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
  
• linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
• linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
  
• linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
• linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
• Banded Distances to English Grammar Schools for MCS5 held under SN 8394
• linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
• linked Health Administrative Datasets (SAIL) for Wales held under SN 9310
  
• linked Hospital of Birth data held under SN 5724.

The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application.

Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

The MCS Linked Education Administrative Dataset (KS1), Scotland: Secure Access (SN 7414) includes a data file containing selected information from the Pupil Census, 2008, the School Meals Survey and attendance and absence records for the year 2008-2009, for those cohort members attending a school in Scotland at the time of MCS4 interview. Also included are anonymised Local Education Authorities (LEA) and anonymised School Numbers, to allow comparison of results across LEA and school. The data were obtained only for children whose parents/carers gave consent to data linkage, and who were successfully matched.

This study only includes data for MCS cohort members attending schools in Scotland. Data for England and Wales are available under SNs 8481 and 7415 respectively.

In the academic year 2023/24, there were 331,602 international students from India studying in the United States. International students The majority of international students studying in the United States are originally from India and China, totaling 331,602 students and 277,398 students respectively in the 2023/24 school year. In 2022/23, there were 467,027 international graduate students , which accounted for over one third of the international students in the country. Typically, engineering and math & computer science programs were among the most common fields of study for these students. The United States is home to many world-renowned schools, most notably, the Ivy League Colleges which provide education that is sought after by both foreign and local students. International students and college Foreign students in the United States pay some of the highest fees in the United States, with an average of 24,914 U.S. dollars. American students attending a college in New England paid an average of 14,900 U.S. dollars for tuition alone and there were about 79,751 international students in Massachusetts . Among high-income families, U.S. students paid an average of 34,700 U.S. dollars for college, whereas the average for all U.S. families reached only 28,026 U.S. dollars. Typically, 40 percent of families paid for college tuition through parent income and savings, while 29 percent relied on grants and scholarships.