Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Characteristics of counties in the sample compared to all counties in the USa.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
All-cause, COVID-19, and non-COVID-19 ASDR for ages 25+ by state and time period.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Mean estimated losses from the economic crisis generated by COVID-19 by 2030: Country income groups.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Preston median household income by race. The dataset can be utilized to understand the racial distribution of Preston income.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Preston median household income by race. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the median household income in Preston. It can be utilized to understand the trend in median household income and to analyze the income distribution in Preston by household type, size, and across various income brackets.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Preston median household income. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This study delves into the global evolution of 43 Sustainable Development Goals (SDG) indicators, spanning 7 major health themes across 185 countries to evaluate the potential progress loss due to the COVID-19 pandemic. Both the cross-country and temporal variability of the dataset are employed to estimate an empirical model based on an extended version of the Preston curve, which links well-being to income levels and other key socioeconomic health determinants. The approach reveals significant global evolution trends operating in each SDG indicator assessed. We extrapolate the model yearly between 2020 and 2030 using the IMF’s pre-COVID-19 economic growth projections to show how each country in the dataset are expected to evolve in these health topics throughout the decade, assuming no other external shocks. The results of this baseline scenario are contrasted with a post-COVID-19 scenario, where most of the pandemic costs were already known. The study reveals that economic growth losses are, on average, estimated as 42% and 28% for low- and lower middle-income countries, and of 15% and 7% in high- and upper middle-income countries, respectively, according to the IMF’s projections. These disproportional figures are shown to exacerbate global health inequalities revealed by the curves. The expected progress loss in infectious diseases in low-income countries, for instance, is an average of 34%, against a mean of 6% in high-income countries. The theme of Infectious diseases is followed by injuries and violence; maternal and reproductive health; health systems coverage; and neonatal and infant health as those with worse performance. Low-income countries can expect an average progress loss of 16% across all health indicators assessed, whereas in high-income countries the estimated loss is as low as 3%. The disparity across countries is even more pronounced, with cases where the estimated progress loss is as high as nine times worse than the average loss of 8%. Conversely, countries with greater fiscal capacity are likely to fare much better under the circumstances, despite their worse death count, in many cases. Overall, these findings support the critical importance of integrating the fight against inequalities into the global development agendas.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Qualitative data themes.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Preston household income by gender. The dataset can be utilized to understand the gender-based income distribution of Preston income.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Preston income distribution by gender. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Community-based social models of care for seniors promote better outcomes in terms of quality of life, managing chronic illness and life expectancy than institutional care. However, small rural areas in high income countries face an ongoing crisis in coordinating care related to service mix, workforce and access. A scoping review was conducted to examine initiatives that promoted integrated models of multisectoral, collaborative aged care in rural settings which could help respond to this ongoing crisis and improve responses to emergencies such as the COVID-19 pandemic. A systematic database search, screening and a two-stage full text review was followed by a case study critical appraisal. A content analysis of extracted data from included papers was undertaken. Integrated care services, activities and facilities were identified that helped guide the review process and data synthesis. The three included case studies all emphasized key principles that crucially underpinned the models related to collaboration, cooperation and innovation. Challenges to effective care included fiscal and structural constraints, with underlying social determinant impacts. Based on these findings, we describe the genesis of a “toolkit” with components of integrated models of care. Effective care requires aging to be addressed as a complex, interconnected social issue rather than solely a health problem. It demands a series of coordinated system-based responses that consider the complex and heterogeneous contexts (and needs) of communities. Such models are underpinned by leadership and political will, working with a wide breadth of stakeholders across family, community and clinical domains in private and public sectors.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the median household income in Lake Preston. It can be utilized to understand the trend in median household income and to analyze the income distribution in Lake Preston by household type, size, and across various income brackets.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Lake Preston median household income. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Preston household income by age. The dataset can be utilized to understand the age-based income distribution of Preston income.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Preston income distribution by age. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Preston township household income by gender. The dataset can be utilized to understand the gender-based income distribution of Preston township income.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Preston township income distribution by gender. You can refer the same here
Not seeing a result you expected?
Learn how you can add new datasets to our index.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Characteristics of counties in the sample compared to all counties in the USa.