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.
In 2016, there were around ***** million people aged 65 and older in the United States. With an increasingly aging population in the United States, this number is expected to increase to about ***** million by 2060.
In 2020, about 17.9 percent of the population in China had been 60 years and older. This share is growing rapidly and was estimated to reach 40 percent by 2050. China's aging population With China’s boomer generation growing old and life expectancy increasing at the same time, the number of people at an age of 60 or above nearly doubled between 2000 and 2020 and reached around 255 million. This development is even more pronounced for the age group of 80 and above, which nearly tripled and is expected to reach a size of roughly 132 million in 2050, up from only 32 million in 2020. At the same time, the share of the working-age population is forecasted to decrease gradually from 64 percent of the total population in 2020 to around 50 percent in 2050, which could pose a heavy economic strain on the social security system. The old-age dependency ratio, which denotes the relation of the old-age to the working-age population, is estimated to grow from 18.2 percent in 2020 to more than 50 percent in 2050, implying that by then, statistically, two working-age adults would have to support one elderly. Strain on the social security net During the last 15 years, China's government has successfully increased the coverage of the pension insurance and health insurance. Today, most of the people are covered by some kind of social insurance. Conditions in the pension system are generous, with a regular retirement age for males at 60 years and women at 50 or 55. With the number of retirees increasing quickly, the social insurance system is now under pressure. From an economic point of view, improving the productivity of China's economy would be the primary choice for mitigating alleged inconsistencies of the system. However, without increasing the burden on the working people while tightening payment conditions, balancing the social security net could prove to be challenging.
This graph shows a projection of the American population by age group from 2016 through 2060. According to this forecast, there will be 73.9 million Americans aged 18 years or younger living in the country in 2020.
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TB incidence rates, overall trend (2007-2017), by sex (2017), age (2017), race/ethnicity (2017), and nativity (2017), Santa Clara County. Source: Tuberculosis Information Management System, 2007-2009, California Reportable Disease Information Exchange, 2010-2017, data are provisional as of February 12, 2018; State of California, Department of Finance, E-2. California County Population Estimates and Components of Change by Year — July 1, 2010–2017. Sacramento, California, December 2017; State of California, Department of Finance, State and County Population Projections by Race/Ethnicity and Age, 2010-2060, Sacramento, California, January 2018; U.S. Census, American Community Survey 1-Year Estimate, 2016METADATA:Notes (String): Lists table title, notes and sourcesYear (Numeric): Year of TB diagnosisCategory (String): Lists of categories: Santa Clara County total for each year (2007-2017), sex (2017): male, female; race/ethnicity: African American, API, Latino, White (non-Hispanic); age group (2017): <15, 15-24, 25-44, 45-64, and 65 and older; foreign-born (2017), U.S.-born (2017)Rate per 100,000 people (Numeric): Number of TB diagnoses per 100,000 people in each cateogry
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Wayne County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Wayne County. The dataset can be utilized to understand the population distribution of Wayne County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Wayne County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Wayne County.
Key observations
Largest age group (population): Male # 60-64 years (2,292) | Female # 65-69 years (2,060). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Wayne County Population by Gender. You can refer the same here
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Lawrence Park township population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Lawrence Park township. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 2,060 (53.74% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age cohorts:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Lawrence Park township Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Sleepy Hollow population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Sleepy Hollow. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 2,060 (63.70% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age cohorts:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Sleepy Hollow Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Platteville by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Platteville. The dataset can be utilized to understand the population distribution of Platteville by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Platteville. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Platteville.
Key observations
Largest age group (population): Male # 20-24 years (2,060) | Female # 20-24 years (1,192). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Platteville Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Malden population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Malden. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 2,060 (53.95% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Malden Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Osage population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Osage. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 - 64 years with a poulation of 2,060 (57.53% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age cohorts:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Osage Population by Age. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Bloomfield charter township by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Bloomfield charter township. The dataset can be utilized to understand the population distribution of Bloomfield charter township by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Bloomfield charter township. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Bloomfield charter township.
Key observations
Largest age group (population): Male # 50-54 years (2,060) | Female # 55-59 years (1,759). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Bloomfield charter township Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of East Brunswick township by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for East Brunswick township. The dataset can be utilized to understand the population distribution of East Brunswick township by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in East Brunswick township. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for East Brunswick township.
Key observations
Largest age group (population): Male # 55-59 years (2,060) | Female # 45-49 years (2,170). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for East Brunswick township Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Ellensburg by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Ellensburg. The dataset can be utilized to understand the population distribution of Ellensburg by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Ellensburg. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Ellensburg.
Key observations
Largest age group (population): Male # 20-24 years (2,005) | Female # 20-24 years (2,060). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Ellensburg Population by Gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Dearborn County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Dearborn County. The dataset can be utilized to understand the population distribution of Dearborn County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Dearborn County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Dearborn County.
Key observations
Largest age group (population): Male # 55-59 years (2,060) | Female # 60-64 years (1,921). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Dearborn County Population by Gender. You can refer the same here
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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.