Florida Poverty Rate by County

Data Item State
Loading map...
Persons below poverty level, percent, 2009-2013 - (Percent)
County Value
Alachua 24.9
Baker 17.3
Bay 14.7
Bradford 18.2
Brevard 13.5
Broward 14.3
Calhoun 23.5
Charlotte 12.6
Citrus 16.8
Clay 9.8
Collier 14.1
Columbia 19.8
DeSoto 29.6
Dixie 17.4
Duval 16.9
Escambia 18.1
Flagler 16.6
Franklin 20.6
Gadsden 26.5
Gilchrist 24.1
Glades 24.5
Gulf 16.4
Hamilton 23.6
Hardee 29.6
Hendry 26.7
Hernando 15.4
Highlands 20.1
Hillsborough 16.8
Holmes 23.8
Indian River 15.1
Jackson 19.9
Jefferson 17.2
Lafayette 20.2
Lake 13.8
Lee 15.4
Leon 23.2
Levy 23.7
Liberty 24.1
Madison 22.5
Manatee 15.1
Marion 18.1
Martin 13.0
Miami-Dade 19.9
Monroe 13.5
Nassau 12.6
Okaloosa 13.4
Okeechobee 26.9
Orange 17.0
Osceola 17.9
Palm Beach 14.5
Pasco 13.9
Pinellas 14.1
Polk 18.2
Putnam 26.4
Santa Rosa 12.3
Sarasota 12.2
Seminole 11.3
St. Johns 9.6
St. Lucie 18.4
Sumter 12.0
Suwannee 23.6
Taylor 16.7
Union 19.6
Volusia 16.8
Wakulla 14.4
Walton 17.9
Washington 20.1

Value for Florida (Percent): 16.3%

Data item: Persons below poverty level, percent, 2009-2013

Source: U. S. Census Bureau, American Community Survey, 5-Year Estimates. Updated every year. http://factfinder2.census.gov


Poverty statistics in ACS products adhere to the standards specified by the Office of Management and Budget in Statistical Policy Directive 14. The Census Bureau uses a set of dollar value thresholds that vary by family size and composition to determine who is in poverty. Further, poverty thresholds for people living alone or with nonrelatives (unrelated individuals) vary by age (under 65 years or 65 years and older). The poverty thresholds for two-person families also vary by the age of the householder. If a family's total income is less than the dollar value of the appropriate threshold, then that family and every individual in it are considered to be in poverty. Similarly, if an unrelated individual's total income is less than the appropriate threshold, then that individual is considered to be in poverty.

How the Census Bureau Determines Poverty Status

Poverty status is determined by comparing annual income to a set of dollar values called poverty thresholds that vary by family size, number of children and age of householder. If a family's before tax money income is less than the dollar value of their threshold, then that family and every individual in it are considered to be in poverty. For people not living in families, poverty status is determined by comparing the individual's income to his or her poverty threshold.

The poverty thresholds are updated annually to allow for changes in the cost of living using the Consumer Price Index (CPI-U). They do not vary geographically. The ACS is a continuous survey and people respond throughout the year. Since income is reported for the previous 12 months, the appropriate poverty threshold for each family is determined by multiplying the base-year poverty threshold (1982) by the average of monthly CPI values for the 12 months preceding the survey month.

Scope and Methodology:

These data are collected in the American Community Survey (ACS). The data for each geographic area are presented together with margins of error at factfinder2.census.gov. The data are period estimates, that is, they represent the characteristics of the population over a specific 60-month data collection period.

Since answers to income questions are frequently based on memory and not on records, many people tended to forget minor or sporadic sources of income and, therefore, underreport their income. Underreporting tends to be more pronounced for income sources that are not derived from earnings, such as public assistance, interest, dividends, and net rental income.

Margins of Error (MOE). ACS estimates 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 MOE. The MOE used with ACS estimates can be interpreted as providing a 90 percent probability that the interval defined by the estimate plus the MOE and the estimate minus the MOE (the upper and lower confidence bounds) contains the full population value of the estimate.

For example, suppose the 5-year ACS reported the percentage of people 25 years and older in Birmingham, Alabama who had a bachelor's degree was 21.3 percent and that the MOE associated with this estimate is plus or minus (+/-) 0.9 percent. By adding and subtracting the MOE from the estimate, we can calculate the 90-percent confidence interval for this estimate at 21.3%, +/-0.9%:

21.3% - 0.9% = 20.4% = Lower-bound estimate
21.3% + 0.9% = 22.2% = Upper-bound estimate

Therefore, we can be 90 percent confident that the percent of the population in Birmingham, Alabama of age 25 years and older having a bachelor's degree in 2007-2011 falls somewhere between 20.4 percent and 22.2 percent.

For this Fact and other 5-year Economic Characteristic Facts (listed below), their estimates and margins of error or percents and percent margins of errors can be found on Data Profile - Economic Characteristics. This profile is displayed by geography. Click on the link for "Browse for Data sets (geography picked)" near the top of the Quick facts profile page, click on the link for People QuickLinks/American Community Survey - "Economic Characteristics" for the data profile.

Mean travel time to work (minutes), workers age 16 and over;
Per capita money income in the past 12 months,
Median household income,
Persons below poverty level, percent

More Information: