Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

As of July 2024, the largest age group among the United States population were adults aged 30 to 34 years old. There were 11.9 million males and some 12.1 million females in this age cohort. The total population of the country was estimated to be 340.1 million Which U.S. state has the largest population? The United States is the third most populous country in the world. It is preceded by China and India, and followed by Indonesia in terms of national population. The gender distribution in the U.S. has remained consistent for many years, with the number of females narrowly outnumbering males. In terms of where the residents are located, California was the state with the largest population. The U.S. population by race and ethnicity The United States poses an ethnically diverse population. In 2023, the number of Black or African American individuals was estimated to be 45.76 million, which represented an increase of over four million since the 2010 census. The number of Asian residents has increased at a similar rate during the same time period and the Hispanic population in the U.S. has also continued to grow.

In 2023, about 17.7 percent of the American population was 65 years old or over; an increase from the last few years and a figure which is expected to reach 22.8 percent by 2050. This is a significant increase from 1950, when only eight percent of the population was 65 or over. A rapidly aging population In recent years, the aging population of the United States has come into focus as a cause for concern, as the nature of work and retirement is expected to change to keep up. If a population is expected to live longer than the generations before, the economy will have to change as well to fulfill the needs of the citizens. In addition, the birth rate in the U.S. has been falling over the last 20 years, meaning that there are not as many young people to replace the individuals leaving the workforce. The future population It’s not only the American population that is aging -- the global population is, too. By 2025, the median age of the global workforce is expected to be 39.6 years, up from 33.8 years in 1990. Additionally, it is projected that there will be over three million people worldwide aged 100 years and over by 2050.

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

This statistic depicts the age distribution in the United States from 2014 to 2024. In 2024, about 17.32 percent of the U.S. population fell into the 0-14 year category, 64.75 percent into the 15-64 age group and 17.93 percent of the population were over 65 years of age. The increasing population of the United States The United States of America is one of the most populated countries in the world, trailing just behind China and India. A total population count of around 320 million inhabitants and a more-or-less steady population growth over the past decade indicate that the country has steadily improved its living conditions and standards for the population. Leading healthier lifestyles and improved living conditions have resulted in a steady increase of the life expectancy at birth in the United States. Life expectancies of men and women at birth in the United States were at a record high in 2012. Furthermore, a constant fertility rate in recent years and a decrease in the death rate and infant mortality, all due to the improved standard of living and health care conditions, have helped not only the American population to increase but as a result, the share of the population younger than 15 and older than 65 years has also increased in recent years, as can be seen above.

Created for the 2023-2025 State of Black Los Angeles County (SBLA) interactive report. To learn more about this effort, please visit the report home page at https://ceo.lacounty.gov/ardi/sbla/. For more information about the purpose of this data, please contact CEO-ARDI. For more information about the configuration of this data, please contact ISD-Enterprise GIS. table_name indicator_name Universe source timeframe source_url

life_expectancy_countyhealthrankings_2020 Life Expectancy Total Population County Health Rankings 2018-2020 https://www.countyhealthrankings.org/app/california/2022/measure/outcomes/147/data

obese_est_adult_lachs_2018 Obese Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

obese_perc_adult_lachs_2018 Obese Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

overweight_est_adult_lachs_2018 Overweight Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

overweight_perc_adult_lachs_2018 Overweight Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

diabetes_est_adult_lachs_2018 Ever Diagnosed with Diabetes Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

diabetes_perc_adult_lachs_2018 Ever Diagnosed with Diabetes Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

regular_source_of_care_est_adult_lachs_2018 Reported Having a Regular Source of Health Care Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

regular_source_of_care_perc_adult_lachs_2018 Reported Having a Regular Source of Health Care Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

depression_est_adult_lachs_2018 Ever Diagnosed with Depression Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

depression_perc_adult_lachs_2018 Ever Diagnosed with Depression Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

perceived_safe_est_adult_lachs_2018 Perceived Their Neighborhood to Be Safe from Crime Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

perceived_safe_perc_adult_lachs_2018 Perceived Their Neighborhood to Be Safe from Crime Estimate (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

dental_care_est_child_lachs_2018 Had Dental Care within the past Year Estimate (#) Children (Ages 17 Years and Younger) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

dental_care_perc_child_lachs_2018 Had Dental Care within the past Year Percent (%) Children (Ages 17 Years and Younger) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

no_usual_source_est_chis_2020 No usual source of care Estimate (#) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

no_usual_source_perc_chis_2020 No usual source of care Percent (%) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

delayed_care_est_chis_2020 Delayed or didn't get medical care last year Estimate (#) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

delayed_care_est_chis_2020 Delayed or didn't get medical care last year Percent (%) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

covid_vax_one_or_more_est_2022 COVID-19 Vaccination 1+ Dose Estimate (#) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_perc_2022 COVID-19 Vaccination 1+ Dose Percent (%) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_full_est_2022 COVID-19 Fully Vaccinated Estimate (#) Population 6 months and older LAC DPH Sep-22publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_full_perc_2022 COVID-19 Fully Vaccinated Percent (%) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_children_est_2022 COVID-19 Vaccination 1+ Dose - Children under 5 Estimate (#) Population older than 6 months and under 5 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_children_perc_2022 COVID-19 Vaccination 1+ Dose Children under 5 Percent (%) Population older than 6 months and under 5 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_youth_est_2022 COVID-19 Vaccination 1+ Dose - Youth 5-17 Estimate (#) Population 5-17 years LAC DPH Sep-22publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_youth_perc_2022 COVID-19 Vaccination 1+ Dose Youth 5-17 Percent (%) Population 5-17 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_adults_est_2022 COVID-19 Vaccination 1+ Dose - Adults Estimate (#) Population 18 and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_adults_perc_2022 COVID-19 Vaccination 1+ Dose Adults Percent (%) Population 18 and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

insured_pop_est_acs_2020 Insured population # Civilian noninstitutionalized population 2016-2020 ACS - S2701 https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S2701

insured_pop_perc_acs_2020 Insured population % Civilian noninstitutionalized population 2016-2020 ACS - S2701 https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S2701

mch_indicators_2019 Babies Born with Positive MCH Indicators Babies born in time frame Strong Start Index 2016-2019 https://infogram.com/1pj576jwy166z1s6ywvk32l5lkammrym3wy?live

current_asthma Percent of Adults (Ages 18 Years and Older) with Current Asthma Adults Los Angeles County Health Survey 2018 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

no_med_insurance Percent of Insured Adults (Ages 18 Years and Older) Who Reported a Time Without Medical Insurance in the past 12 Months. Adults Los Angeles County Health Survey 2011 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

transportation_problems Percent of Adults (Ages 18 Years and Older) Who Reported That Transportation Problems Kept Them from Obtaining Needed Medical Care in the past Year. Adults Los Angeles County Health Survey 2007 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Marquette Heights, the median income for all workers aged 15 years and older, regardless of work hours, was $52,316 for males and $40,734 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Marquette Heights. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Marquette Heights.

- Full-time workers, aged 15 years and older: In Marquette Heights, among full-time, year-round workers aged 15 years and older, males earned a median income of $65,909, while females earned $51,375, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Oxford, the median income for all workers aged 15 years and older, regardless of work hours, was $32,242 for males and $25,302 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Oxford. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Oxford.

- Full-time workers, aged 15 years and older: In Oxford, among full-time, year-round workers aged 15 years and older, males earned a median income of $56,379, while females earned $43,986, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

There were almost 4.8 million people aged between 30 and 34 in the United Kingdom in 2024, making it the most populous age group in that year. Those aged between 35 and 39 years comprised the next most numerous age group in this year, at over 4.78 million people. Millennials overtake Boomers as biggest generation Post-war demographic trends, particularly the 'baby boom' phenomenon, have significantly influenced the current age distribution in the UK. The postwar peak of live births in 1947 resulted in the dominance of the Baby Boomer generation for several decades, until 2020 when Millennials became the largest generational cohort, surpassing the Boomers for the first time. The following year, the UK Boomer population was then overtaken by Generation X, the generation born between Boomers and Millennials. Generation Z, remained smaller than the three generations that preceded it until 2024 when there were more Gen Zers than Boomers. Aging UK population poses challenges The median age of the UK population is projected to reach 44.5 years by 2050, compared to 34.9 years in 1950. This aging trend is indicative of broader global demographic shifts, with the median age of people worldwide forecasted to increase from 23.6 years in 1950 to 41.9 years by 2100. How countries like the UK manage their aging populations will be one of the key challenges of the next few decades. It is likely the UK's struggling National Health Service (NHS) will come under even more pressure in the coming years. There are also tough economic questions, in particular as more people enter retirement age and the UK's working population gets smaller in relation to it.

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Good Hope, the median income for all workers aged 15 years and older, regardless of work hours, was $58,125 for males and $45,227 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Good Hope. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Good Hope.

- Full-time workers, aged 15 years and older: In Good Hope, among full-time, year-round workers aged 15 years and older, males earned a median income of $68,750, while females earned $53,661, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Amber township, the median income for all workers aged 15 years and older, regardless of work hours, was $39,041 for males and $30,570 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Amber township. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetownship of Amber township.

- Full-time workers, aged 15 years and older: In Amber township, among full-time, year-round workers aged 15 years and older, males earned a median income of $58,906, while females earned $46,053, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

The number of Americans aged 65 and over with Alzheimer's disease is projected to more than double by 2060, reaching **** million. This significant increase highlights the growing challenge of caring for an aging population, particularly those affected by dementia. As the prevalence of Alzheimer's rises, it will have far-reaching impacts on healthcare, families, and society as a whole. Aging population trends The surge in Alzheimer's cases is closely tied to broader demographic shifts in the United States. By 2050, it's estimated that 22 percent of the American population will be 65 years or older, up from 17.3 percent in 2022. This rapid aging of the population is expected to strain healthcare systems and change the nature of work and retirement. Challenges of aging in place As the number of older adults with Alzheimer's increases, there is a growing desire among seniors to age in their own homes. A 2024 survey found that ************** of adults aged 50 and older strongly or somewhat agreed they would like to remain in their current residence for as long as possible. This preference is even stronger among those 65 and older, with ** percent expressing this desire. However, the ability to age in place may be compromised by declining physical capabilities, as only about *** in **** adults aged 72 and older reported being fully able to perform self-care and mobility activities in 2021.

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Shoreham town, the median income for all workers aged 15 years and older, regardless of work hours, was $48,750 for males and $38,188 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Shoreham town. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Shoreham town.

- Full-time workers, aged 15 years and older: In Shoreham town, among full-time, year-round workers aged 15 years and older, males earned a median income of $62,250, while females earned $48,778, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

In 2022, approximately ***** million young people between the ages of 15 to 19 years old lived in the United States. This was a slight increase from the previous year, when ***** million young people aged 15 to 19 lived in the U.S.

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Ann Arbor, the median income for all workers aged 15 years and older, regardless of work hours, was $47,054 for males and $36,492 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Ann Arbor. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Ann Arbor.

- Full-time workers, aged 15 years and older: In Ann Arbor, among full-time, year-round workers aged 15 years and older, males earned a median income of $92,116, while females earned $71,567, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

In 2024, there were estimated to be 976,481 people who were aged 33 in the United Kingdom, the most of any age in this year. The two largest age groups during this year were 30-34, and 35-39, at 4.8 million and 4.78 million people respectively. There is also a noticeable spike of 673,831 people who were aged 77, which is due to the high number of births that followed the end of the Second World War. Over one million born in 1964 In post-war Britain, there have only been two years when the number of live births was over one million, in 1947 and in 1964. The number of births recorded in the years between these two years was consistently high as well, with 1955 having the fewest births in this period at 789,000. This meant that until relatively recently, Baby Boomers were the largest generational cohort in the UK. As of 2024, there were approximately 13.4 million Baby Boomers, compared with 14 million in Generation X, 15 million Millennials, and 13.6 million members of Gen Z. The youngest generation in the UK, Generation Alpha, numbered approximately 9.2 million in the same year. Median age to hit 44.5 years by 2050 The population of the United Kingdom is aging at a substantial rate, with the median age of the population expected to reach 44.5 years by 2050. By comparison, in 1950 the average age in the United Kingdom stood at 34.9 years. This phenomenon is not unique to the United Kingdom, with median age of people worldwide increasing from 23.6 years in 1950 to a forecasted 41.9 years by 2100. As of 2024, the region with the oldest median age in the UK was South West England, at 43.7 years, compared with 35.7 in London, the region with the youngest median age.

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Pryor Creek, the median income for all workers aged 15 years and older, regardless of work hours, was $31,660 for males and $24,802 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 22% between the median incomes of males and females in Pryor Creek. With women, regardless of work hours, earning 78 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Pryor Creek.

- Full-time workers, aged 15 years and older: In Pryor Creek, among full-time, year-round workers aged 15 years and older, males earned a median income of $48,668, while females earned $37,956, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

As of 2023, the bulk of the Chinese population was aged between 25 and 59 years, amounting to around half of the population. A breakdown of the population by broad age groups reveals that around 61.3 percent of the total population was in working age between 16 and 59 years in 2023. Age cohorts below 25 years were considerably smaller, although there was a slight growth trend in recent years. Population development in China Population development in China over the past decades has been strongly influenced by political and economic factors. After a time of high fertility rates during the Maoist regime, China introduced birth-control measures in the 1970s, including the so-called one-child policy. The fertility rate dropped accordingly from around six children per woman in the 1960s to below two at the end of the 20th century. At the same time, life expectancy increased consistently. In the face of a rapidly aging society, the government gradually lifted the one-child policy after 2012, finally arriving at a three-child policy in 2021. However, like in most other developed countries nowadays, people in China are reluctant to have more than one or two children due to high costs of living and education, as well as changed social norms and private values. China’s top-heavy age pyramid The above-mentioned developments are clearly reflected in the Chinese age pyramid. The age cohorts between 30 and 39 years are the last two larger age cohorts. The cohorts between 15 and 24, which now enter childbearing age, are decisively smaller, which will have a negative effect on the number of births in the coming decade. When looking at a gender distribution of the population pyramid, a considerable gender gap among the younger age cohorts becomes visible, leaving even less room for growth in birth figures.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Woodlawn Heights. The dataset can be utilized to gain insights into gender-based income distribution within the Woodlawn Heights population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Woodlawn Heights, among individuals aged 15 years and older with income, there were 22 men and 38 women in the workforce. Among them, 10 men were engaged in full-time, year-round employment, while 22 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, none fell within the income range of under $24,999, while none of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 70% of men in full-time roles earned incomes exceeding $100,000, while 27.27% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

About this dataset

Context

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

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Salem, the median income for all workers aged 15 years and older, regardless of work hours, was $36,250 for males and $9,861 for females.

These income figures highlight a substantial gender-based income gap in Salem. Women, regardless of work hours, earn 27 cents for each dollar earned by men. This significant gender pay gap, approximately 73%, underscores concerning gender-based income inequality in the village of Salem.

- Full-time workers, aged 15 years and older: In Salem, among full-time, year-round workers aged 15 years and older, males earned a median income of $203,333, while females earned $44,375, leading to a 78% gender pay gap among full-time workers. This illustrates that women earn 22 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

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

Content

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

Gender classifications include:

• Male
• Female

Employment type classifications include:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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