The following datasets are based on the adult (age 21 and over) beneficiary population and consist of aggregate MHS data derived from Medi-Cal claims, encounter, and eligibility systems. These datasets were developed in accordance with California Welfare and Institutions Code (WIC) § 14707.5 (added as part of Assembly Bill 470 on 10/7/17). Please contact BHData@dhcs.ca.gov for any questions or to request previous years’ versions of these datasets. Note: The Performance Dashboard AB 470 Report Application Excel tool development has been discontinued. Please see the Behavioral Health reporting data hub at https://behavioralhealth-data.dhcs.ca.gov/ for access to dashboards utilizing these datasets and other behavioral health data.

About this dataset

Context

The dataset tabulates the Boston 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 Boston. 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 487,505 (72.46% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Boston population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Boston is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Boston is shown in the following column.

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 Boston Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the North Carolina 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 North Carolina. 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 6.44 million (61.49% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the North Carolina population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in North Carolina is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the North Carolina is shown in the following column.

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 North Carolina Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Egypt 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 Egypt. 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 29 (60.42% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Egypt population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Egypt is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Egypt is shown in the following column.

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 Egypt Population by Age. You can refer the same here

Virtual Patient Model Assessment

Tracking Physical, Psychological and Cognitive Performance in Older Adults

By [source]

About this dataset

This dataset provides a comprehensive overview of the physical, psychological and cognitive health of a cohort of older adults. It contains data collected from medical experts during clinical assessments such as physical activity, nutrition, activity limitations, balance, depression and cognition. Additionally it includes parameters extracted from used devices such as average heart rate per day and average gait speed. Carefully coupled with this is detailed information relating to falls, fractures and loss of orientation within the group studied which can add even further insight into the overall trends in health for those aged 55 and above.

The dataset includes various scores capturing different aspects alongside statistics to better represent participants' lifestyles; not only does it feature basic metrics like gender or age but also complex measures like exhaustion or grip strength for each individual in the cohort. Furthermore an analytical exploration into nutrition measures (e.g., Body Mass Index), social interaction (e.g., phone calls) or leisure activities (clubs) could help uncover powerful correlations among them resulting in innovative strategies for improving well-being amongst elderly population groups

More Datasets

For more datasets, click here.

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How to use the dataset

This dataset provides a comprehensive overview of physical, psychological and cognitive health of a cohort of older adults. It includes parameters related to physical activity, nutrition, activity limitations, balance, depression, cognition and more. Through this dataset you can gain insights into the various factors affecting the health of elderlies in your population which could be helpful for researchers or practitioners in developing interventions to promote elderly health.

Before using this dataset it is advised to get familiar with the variables and fields provided. There are two sections within each variable: descriptive information such as gender and age group; and scores related to various aspects such as heart rate per day or average gait speed per month. You may also find additional coupled events like falls or fractures that can impact the assessment scores over time.

Once you have gone through all variables available in the dataset you may use simple statistical methods like measuring mean values of several key indicators (such as balance score or bmi score) across different characteristics (such as age group). Comparing these values allows researchers to identify trends amongst different groups within a population that would show differences on an individual level.

Other techniques that could be used include clustering techniques to observe patterns in data relating different indicators at once on comparative models; logistic regression which would help identify which predictors explain certain outcomes among elderly people well; or propensity matching-based approaches which suggest what kind of intervention should be given depending on each person’s characteristics based on an accumulated data source from elderly population research using this dataset . The usefulness of this dataset is not limited by stats only but it might also benefit from theoretical forms such as narrative geometry used for subjective analysis by placing story-telling elements along with formative assessments onto conceptual frameworks between inside natural ecosystems already running smoothly(between concepts) before disruption/disequilibrium happens due external stressors ecomorphonologically speaking . This will eventually help clinicians addressing psychological conditions verifying objective status via outcomes from metrics established earlier preferably prior experiments where involuntary independent behavior was detected influencing vital organ systems at homeostasis levels either causing positive adaptations / fitness ,or increasing vulnerability that when added up together shift towards severe distress turn proximally considering also other segments elsewhere varying across multiple networks simultaneous injections cumulated/integrated effects starting sometimes after take off periods way before ill health seems obviously concrete therefore important details concerning risk factors sometimes overlooked got noticed while capturing evidence based prospective by cross validated means completed longitudinal surveys taking advantage into being able understanding potentially confounding conditions sparedly manifested either forgotten beca...

Total number of young adults aged 15 to 34 years and total number of young adults aged 20 to 34 years in the UK living with their parents.

Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012 & 2014.

Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012, 2014.

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. This table displays the percentage of adults meeting Aerobic Physical Activity guidelines in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by the Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. The column percentages are weighted to the 2010 California Department of Finance (DOF) population statistics. Population estimates were obtained from the CA DOF for age, race/ethnicity, and sex. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

About this dataset

Context

The dataset tabulates the London 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 London. 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 6,108 (58.95% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the London population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in London is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the London is shown in the following column.

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 London Population by Age. You can refer the same here

2012-2020 (even years). Data from BRFSS for indicators of adult oral health for even years from 2012 through 2020. National estimates are represented by the median prevalence among 50 states and the District of Columbia data. Estimates are prepared from the BRFSS public use data sets. Estimates in this file are not age adjusted, and may differ slightly from estimates available from the BRFSS web site or Chronic Disease Indicators due to small differences in definition, age adjustment or rounding. For more information, see: https://www.cdc.gov/oralhealthdata/overview/Adult-Indicators.html.

Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012, 2014.

Child and Adult Care Food Participation plays a vital role in improving the quality of day care for children and elderly adults by making care more affordable for many low-income families. Through CACFP, nearly 3 million children and 90,000 adults receive nutritious meals and snacks each day as part of the day care they receive. The data set contains participation; meals served, and cash payments to states.

Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012, 2014.

Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012, 2014.

About this dataset

Context

The dataset tabulates the Many 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 Many. 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 1,228 (55.77% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

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

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Many population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Many is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Many is shown in the following column.

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 Many Population by Age. You can refer the same here

As part of an ongoing partnership with the Census Bureau, the National Center for Health Statistics (NCHS) recently added questions to assess the prevalence of post-COVID-19 conditions (long COVID), on the experimental Household Pulse Survey. This 20-minute online survey was designed to complement the ability of the federal statistical system to rapidly respond and provide relevant information about the impact of the coronavirus pandemic in the U.S. Data collection began on April 23, 2020. Beginning in Phase 3.5 (on June 1, 2022), NCHS included questions about the presence of symptoms of COVID that lasted three months or longer. Phase 3.5 will continue with a two-weeks on, two-weeks off collection and dissemination approach. Estimates on this page are derived from the Household Pulse Survey and show the percentage of adults aged 18 and over who a) as a proportion of the U.S. population, the percentage of adults who EVER experienced post-COVID conditions (long COVID). These adults had COVID and had some symptoms that lasted three months or longer; b) as a proportion of adults who said they ever had COVID, the percentage who EVER experienced post-COVID conditions; c) as a proportion of the U.S. population, the percentage of adults who are CURRENTLY experiencing post-COVID conditions. These adults had COVID, had long-term symptoms, and are still experiencing symptoms; d) as a proportion of adults who said they ever had COVID, the percentage who are CURRENTLY experiencing post-COVID conditions; and e) as a proportion of the U.S. population, the percentage of adults who said they ever had COVID.

Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012, 2014.

This spotlight uses 2014 National Survey on Drug Use and Health (NSDUH) to examine mental health service use among young adults aged 18 to 25 with any mental illness.

Source: Behavioral Risk Factor Surveillance System (BRFSS), 2012, 2014.