This poverty rate data shows what percentage of the measured population* falls below the poverty line. Poverty is closely related to income: different “poverty thresholds” are in place for different sizes and types of household. A family or individual is considered to be below the poverty line if that family or individual’s income falls below their relevant poverty threshold. For more information on how poverty is measured by the U.S. Census Bureau (the source for this indicator’s data), visit the U.S. Census Bureau’s poverty webpage.

The poverty rate is an important piece of information when evaluating an area’s economic health and well-being. The poverty rate can also be illustrative when considered in the contexts of other indicators and categories. As a piece of data, it is too important and too useful to omit from any indicator set.

The poverty rate for all individuals in the measured population in Champaign County has hovered around roughly 20% since 2005. However, it reached its lowest rate in 2021 at 14.9%, and its second lowest rate in 2023 at 16.3%. Although the American Community Survey (ACS) data shows fluctuations between years, given their margins of error, none of the differences between consecutive years’ estimates are statistically significant, making it impossible to identify a trend.

Poverty rate data was sourced from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Poverty Status in the Past 12 Months by Age.

*According to the U.S. Census Bureau document “How Poverty is Calculated in the ACS," poverty status is calculated for everyone but those in the following groups: “people living in institutional group quarters (such as prisons or nursing homes), people in military barracks, people in college dormitories, living situations without conventional housing, and unrelated individuals under 15 years old."

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (25 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (16 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).

Note: These layers were compiled by Esri's Demographics Team using data from the Census Bureau's American Community Survey. These data sets are not owned by the City of Rochester.Overview of the map/data: This map shows the percentage of the population living below the federal poverty level over the previous 12 months, shown by tract, county, and state boundaries. Estimates are from the 2018 ACS 5-year samples. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Current Vintage: 2019-2023ACS Table(s): B17020, C17002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer will be updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico.Census tracts with no population are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Cook County, IL (S1701ACS017031) from 2012 to 2023 about Cook County, IL; Chicago; IL; poverty; percent; 5-year; population; and USA.

Socioeconomic indicators like the poverty rate, population change, unemployment rate, and education levels vary across the nation. ERS has compiled the latest data on these measures into a mapping and data display/download application that allows users to identify and compare States and counties on these indicators.

Count and rate of population with income in the last 12 months below poverty level in an area. ( B17001). County and State values are from ACS 1-year survey.

This table contains data on the percentage of the total population living below 200% of the Federal Poverty Level (FPL), and the percentage of children living below 200% FPL for California, its regions, counties, cities, towns, public use microdata areas, and census tracts. Data for time periods 2011-2015 (overall poverty) and 2012-2016 (child poverty) and with race/ethnicity stratification is included in the table. The poverty rate table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Poverty is an important social determinant of health (see http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicid=39) that can impact people’s access to basic necessities (housing, food, education, jobs, and transportation), and is associated with higher incidence and prevalence of illness, and with reduced access to quality health care. More information on the data table and a data dictionary can be found in the About/Attachments section.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Middlesex County, MA (S1701ACS025017) from 2012 to 2023 about Middlesex County, MA; Boston; MA; poverty; percent; 5-year; population; and USA.

Goal and Objective : Primary objective is to study variability in the poverty rate in the US counties by means of one or more of independent or control variable and provide best suitable model to quantify relationships in determining target value Our goal is to design various models to take into consideration the effect of various factors like employment, population and education to predict the poverty rate in all US Counties We further wish to analyze the status of a county based on whether it is metropolitan or not

List of datasets:

Socioeconomic indicators like poverty rates, population change, unemployment rates, and education levels vary geographically across U.S. States and counties 1. Unemployment 2. PovertyEstimates 3.Population Estimates 4. Education

All the four individual datasets have common unique id FIPS Code defined as State-County FIPS Code. It is unique for each county falling under the states. In our dataset, we are covering all 52 USA states including federal district DC and Puerto Rico.

Data Modelling :

Target Variable: Metro_2015 – This binary variable shows status of County as Metro or Non-Metro A decision tree model designed using Metro_2015 as target variable will efficiently determine the classification of the population into Metro and Non-metro counties. Dataset will be partitioned into training and validation datasets before implementing decision tree rules. The attributes that will be considered in selecting best model will be fit statistics, misclassification rate, and average square error.

Clustering can be performed to create the collection of objects similar to each other which will give insight into data distribution. Variables will be standardized before performing clustering to avoid noisy data and outliers. Euclidean distance will be the measure to determine stability and separation.

Recommendation :

The regression equation determines % Poverty rate in a particular county based on significant factors. This model can be This model can be used by education boards to increase or decrease the funds spent on the education system in different counties in order to lower the poverty rate. Census board can use this model in identifying poverty line index based on a population estimate an average household income. By estimating the poverty rate and considering factors like unemployment and education, an analysis can be done to set up employment opportunities in targeted counties.

This data product provides poverty area measures for counties and census tracts across the 50 States and Washington DC. The measures include indicators of high poverty areas, extreme poverty areas, persistent poverty areas, and enduring poverty areas for Decennial Census years 1960–2000 and for American Community Survey (ACS) 5-year periods spanning 2007–11, 2015–19, and 2017–21. This product uses county-level data from the U.S. Department of Commerce, Bureau of the Census, 1960, 1970, 1980, 1990, and 2000 Decennial Censuses and American Community Survey (ACS) 5-year period estimates for 2007–11, 2015–19, and 2017–21. Data for census tracts include the same data sources and years except for 1960 (because of the limited number of defined census tracts in that year of data collection) and 2017–21. Poverty rates for census tracts in the years before 2007–11 are calculated using data from Geolytics’ Neighborhood Change Database. The Neighborhood Change Database normalizes Decennial Census data to 2010 census-tract geographies allowing for better comparisons of census tract poverty rates over time. USDA, Economic Research Service (ERS) relies on poverty/population counts from these sources to derive poverty rates that are used to create the poverty area measures in this data product.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Los Angeles County, CA (S1701ACS006037) from 2012 to 2023 about Los Angeles County, CA; Los Angeles; poverty; percent; CA; 5-year; population; and USA.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Coos County, OR (S1701ACS041011) from 2012 to 2023 about Coos County, OR; OR; poverty; percent; 5-year; population; and USA.

This dataset contains details about income below 200 percent of the Federal Poverty Level (FPL) in King County by Health Reporting Area (HRA) for 2021. It has been developed for the Determinant of Equity - Jobs and Jobs Training presentation. It includes information about Poverty Rate equity indicator. Fields describe the total population for whom poverty status is determined (Denominator), population below 200% of FPL (Numerator), the type of equity indicator being measured (Indicator), and the value that describes this measurement (Indicator Value).

For more information about King County's equity efforts, please see:

Equity, Racial & Social Justice Vision Ordinance 16948 describing the determinates of equity Determinants of Equity and Data Tool

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Multnomah County, OR (S1701ACS041051) from 2012 to 2023 about Multnomah County, OR; Portland; OR; poverty; percent; 5-year; population; and USA.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Routt County, CO (S1701ACS008107) from 2012 to 2023 about Routt County, CO; CO; poverty; percent; 5-year; population; and USA.

Percent of Population Below the Poverty Level (5-year estimate) in Middlesex County, MA was 7.50% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Middlesex County, MA reached a record high of 8.40 in January of 2014 and a record low of 7.20 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Middlesex County, MA - last updated from the United States Federal Reserve on December of 2025.

Percent of Population Below the Poverty Level (5-year estimate) in Alamosa County, CO was 18.20% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Alamosa County, CO reached a record high of 31.40 in January of 2016 and a record low of 15.50 in January of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Alamosa County, CO - last updated from the United States Federal Reserve on November of 2025.

Represent's the outer land boundary of Los Angeles County. Land boundaries are derived from the Los Angeles County Cadastral landbase. Ocean boundaries are drived from NOAA coastline data, modified to conform with LAR-IAC aerial imagery where needed. The most current copy of this data is available at the Los Angeles County GIS Data Portal.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Orange County, FL (S1701ACS012095) from 2012 to 2023 about Orange County, FL; Orlando; poverty; FL; percent; 5-year; population; and USA.

Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Miami-Dade County, FL (S1701ACS012086) from 2012 to 2023 about Miami-Dade County, FL; Miami; poverty; FL; percent; 5-year; population; and USA.

Percent of Population Below the Poverty Level (5-year estimate) in Pike County, MS was 27.50% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Pike County, MS reached a record high of 33.80 in January of 2018 and a record low of 26.20 in January of 2012. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Pike County, MS - last updated from the United States Federal Reserve on November of 2025.