In 2023, the median age of the population of the United States was 39.2 years. While this may seem quite young, the median age in 1960 was even younger, at 29.5 years. The aging population in the United States means that society is going to have to find a way to adapt to the larger numbers of older people. Everything from Social Security to employment to the age of retirement will have to change if the population is expected to age more while having fewer children. The world is getting older It’s not only the United States that is facing this particular demographic dilemma. In 1950, the global median age was 23.6 years. This number is projected to increase to 41.9 years by the year 2100. This means that not only the U.S., but the rest of the world will also have to find ways to adapt to the aging population.

Data on age in single years including average age and median age and gender for the population of census metropolitan areas, tracted census agglomerations and census tracts.

Population by age Source: Census 2001 Publisher: Neighbourhood Statistics Geographies: Output Area (OA), Lower Layer Super Output Area (LSOA), Middle Layer Super Output Area (MSOA), Ward, Local Authority District (LAD), Government Office Region (GOR), National Geographic coverage: England and Wales Time coverage: 2001 Type of data: Survey (census) Notes: Age is derived from the date of birth question on the 2001 Census, and is the age at a person's last birthday. Dates of birth that imply an age over 110 were treated as invalid and the person's age was imputed.

Average age and median age by sex, observations and year

Data on age in single years including average age and median age and gender for the population of Canada, provinces and territories, census divisions and census subdivisions, 2021 and 2016 censuses.

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Data on age in single years including average age and median age and gender for the population of Canada and forward sortation areas.

The median age of a given population is the age separating the group into two halves of equal size. In the case of this indicator it means that half of the student population, i.e. persons enrolled in tertiary education (ISCED levels 5 and 6), is younger than the median age and the other half is older.

Mean, median and modal ages at death in the UK and its constituent countries, 2001 to 2003 and 2016 to 2018.

1- Temporal fluctuations in growth rates can arise from both variation in age-specific vital rates and temporal fluctuations in age structure (i.e., the relative abundance of individuals in each age-class). However, empirical assessments of temporal fluctuations in age structure and their effects on population growth rate are rare. Most research has focused on understanding the contribution of changing vital rates to population growth rates and these analyses routinely assume that: (i) populations have stable age distributions, (ii) environmental influences on vital rates and age structure are stationary (i.e., the mean and/or variance of these processes does not change over time), and (iii) dynamics are independent of density. 2- Here we quantified fluctuations in age structure and assessed whether they were stationary for four populations of free-ranging vertebrates: moose (observed for 48 years), elk (15 years), tawny owls (15 years) and gray wolves (17 years). We also assessed the e...

Albania Population: Average: Age 35 to 39 data was reported at 179.750 Person th in 2022. This records an increase from the previous number of 177.710 Person th for 2021. Albania Population: Average: Age 35 to 39 data is updated yearly, averaging 176.315 Person th from Dec 2001 (Median) to 2022, with 22 observations. The data reached an all-time high of 216.905 Person th in 2001 and a record low of 161.921 Person th in 2015. Albania Population: Average: Age 35 to 39 data remains active status in CEIC and is reported by Institute of Statistics. The data is categorized under Global Database’s Albania – Table AL.G001: Population: by Gender and Age Group.

Mean age and median age at divorce and at marriage, for persons who divorced in a given year, by sex or gender and place of occurrence, 1970 to most recent year.

The European Union Statistics on Income and Living Conditions (EU-SILC) collects timely and comparable multidimensional microdata on income, poverty, social exclusion and living conditions.

The EU-SILC collection is a key instrument for providing information required by the European Semester (_[1]) and the European Pillar of Social Rights, and the main source of data for microsimulation purposes and flash estimates of income distribution and poverty rates.

AROPE remains crucial to monitor European social policies, especially to monitor the EU 2030 target on poverty and social exclusion. For more information, please consult EU social indicators.

The EU-SILC instrument provides two types of data:

• Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions.
• Longitudinal data pertaining to individual-level changes over time, observed periodically over four‐or more year rotation scheme (Annex III (2) of 2019/1700).

EU-SILC collects:

• annual variables,
• three-yearly modules,
• six-yearly modules,
• ad-hoc new policy needs modules,
• optional variables.

The variables collected are grouped by topic and detailed topic and transmitted to Eurostat in four main files (D-File, H-File, R-File and P-file).

The domain ‘Income and Living Conditions’ covers the following topics: persons at risk of poverty or social exclusion, income inequality, income distribution and monetary poverty, living conditions, material deprivation, and EU-SILC ad-hoc modules, which are structured into collections of indicators on specific topics.

In 2023, in addition to annual data, in EU-SILC were collected: the three yearly module on labour market and housing, the six yearly module on intergenerational transmission of advantages and disadvantages, housing difficulties, and the ad hoc subject on households energy efficiency.

Starting from 2021 onwards, the EU quality reports use the structure of the Single Integrated Metadata Structure (SIMS).

_{([1]) The European Semester is the European Union’s framework for the coordination and surveillance of economic and social policies.}

Mean age and median age at marriage, for persons who married in a given year, by legal marital status, gender (when available), the couple's gender composition (when available) and place of occurrence, 1991 to most recent year.

This dataset displays data from the 2005 Census of Japan. It displays male population by age, selected age ranges, percentages of age ranges, average average, and median age in the selected prefectures in Japan for the year 2005. Only 30 of the 47 prectures were displayed in the data source. There are also 2 other datasets that break this data up by total and female figures. This data comes from Japan's Ministry of Internal Affairs and Communication's Statistics Bureau.

Provisional deaths registration data for single year of age and average age of death (median and mean) of persons whose death involved coronavirus (COVID-19), England and Wales. Includes deaths due to COVID-19 and breakdowns by sex.

Data on age in single years including average age and median age and gender for the population of Canada, provinces and territories and federal electoral districts.

National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

Although South Africa is the global epicenter of the HIV epidemic, the uptake of HIV testing and treatment among young people remains low. Concerns about confidentiality impede the utilization of HIV prevention services, which signals the need for discrete HIV prevention measures that leverage youth-friendly platforms. This paper describes the process of developing a youth-friendly internet-enabled HIV risk calculator in collaboration with young people, including young key populations aged between 18 and 24 years old. Using qualitative research, we conducted an exploratory study with 40 young people including young key population (lesbian, gay, bisexual, transgender (LGBT) individuals, men who have sex with men (MSM), and female sex workers). Eligible participants were young people aged between 18–24 years old and living in Soweto. Data was collected through two peer group discussions with young people aged 18–24 years, a once-off group discussion with the [Name of clinic removed for confidentiality] adolescent community advisory board members and once off face-to-face in-depth interviews with young key population groups: LGBT individuals, MSM, and female sex workers. LGBT individuals are identified as key populations because they face increased vulnerability to HIV/AIDS and other health risks due to societal stigma, discrimination, and obstacles in accessing healthcare and support services. The measures used to collect data included a socio-demographic questionnaire, a questionnaire on mobile phone usage, an HIV and STI risk assessment questionnaire, and a semi-structured interview guide. Framework analysis was used to analyse qualitative data through a qualitative data analysis software called NVivo. Descriptive statistics were summarized using SPSS for participant socio-demographics and mobile phone usage. Of the 40 enrolled participants, 58% were male, the median age was 20 (interquartile range 19–22.75), and 86% had access to the internet. Participants’ recommendations were considered in developing the HIV risk calculator. They indicated a preference for an easy-to-use, interactive, real-time assessment offering discrete and private means to self-assess HIV risk. In addition to providing feedback on the language and wording of the risk assessment tool, participants recommended creating a colorful, interactive and informational app. A collaborative and user-driven process is crucial for designing and developing HIV prevention tools for targeted groups. Participants emphasized that privacy, confidentiality, and ease of use contribute to the acceptability and willingness to use internet-enabled HIV prevention methods.