Historical dataset of population level and growth rate for the Florence, Italy metro area from 1950 to 2025.

About this dataset

Context

This list ranks the 9 cities in the Florence County, SC by Italian population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Italian Population: This column displays the rank of city in the Florence County, SC by their Italian population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Italian Population: The Italian population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Italian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Florence County Italian Population: This tells us how much of the entire Florence County, SC Italian population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

Osteoporosis (OP) and osteoarthritis (OA), the two most common age-related chronic disorders of articular joints and skeleton, represent a major public health problem in most developed countries. They are influenced by environmental factors and exhibit a strong genetic component. Large population studies clearly show their inverse relationship; therefore, an accurate analysis of the genetic bases of one of these two diseases may provide data of interest for the other disorder. The discovery of risk and protective genes for OP and OA promises to revolutionize strategies for diagnosing and treating these disorders. The primary goal of this symposium was to bring together scientists and clinicians working on OP and OA in order to identify the most promising and collaborative approaches for the coming decade. This meeting put into focus the importance of an adequate genetic approach to several areas of research: the search for the genetic determinants underlying new susceptibilities, the optimization of previously acquired data; the establishment of correlations between genetic polymorphism and functional variants, and gene–gene and gene–environment interactions (particularly those between genes and nutrients). An adequate genetic approach is also essential with regard to determining more selective criteria for phenotypic definition of familial OP, in order to obtain more homogeneous and statistically powerful family-based studies. The symposium concluded with an interesting overview of the future perspectives offered by DNA microarray technologies for identifying novel candidate genes, for developing proteomics and bioinformatics analyses and for designing low-cost clinical trials.