CORONAVIRUS (COVID-19) RESOURCE CENTER Read More

Mean Travel Time to Work

Shows the average travel time to work (in minutes) for workers 16 years and over not working at home. Travel time to work refers to the total number of minutes that it usually took the person to get from home to work each day during the reference week. The elapsed time includes time spent waiting for public transportation, picking up passengers in carpools, and time spent in other activities related to getting to work. Data were tabulated for workers 16 years old and over--that is, members of the Armed Forces and civilians who were at work during the reference week--who reported that they worked outside their home. Mean travel time to work is obtained by dividing the total number of minutes by the number of workers 16 years old and over who did not work at home. Mean travel time to work is rounded to the nearest tenth of a minute.

  • Measurement Period: 2005-2009
Mean Travel Time to Work
30.9
GA VALUE
(27)
US VALUE
(25.2)
TREND
RANGE: 16<38.9

Understanding the color Range

Each Health Indicator includes five-color range indexes. The color range index compares all counties in the state that have the same indicator in the same timeframe. It then calculates where the selected county falls in that range and displays the color that best reflects how the county is doing in comparison to the other counties in the filtered group. The range displays the highest and lowest county values within the state that have the same indicator for the same measurement period.

Current county values will be compared to State and National values if they are available.

Green and red arrows indicate that the county value is better or worse than the state or national value. The arrows will change directions and colors based on which end of the range is positive.
This icon simply means that the county value is equal to the state or national value.
Some indicators display blue, which means the data is not meant for health-status comparison, but is intended simply to provide information.
If history data is available the trend icon will point up or down based on its relationship to the last county value.
History
Dimensions 2005-2009
Dimension Low Value High Number of Counties Compared
CDC Treatment Guidelines
Source
American Community Survey
http://www.census.gov/acs/www and related web pages. Accessed August 24, 2010.

https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml

Methodology

The American Community Survey (ACS) is an annual nationwide survey designed to supplement the decennial census. The survey, based on the decennial census long form, produces population and housing information every year instead of every 10 years. Annual estimates of demographic, social, economic, and housing characteristics are available for geographic areas with a population of 65,000 or more. This includes the nation, all states, the District of Columbia, all congressional districts, approximately 800 counties, and 500 metropolitan and micropolitan statistical areas. Multi-year estimates are available for smaller geographic areas. During the demonstration stage (2000 to 2004), the U.S. Census Bureau carried out large-scale, nationwide surveys and produced reports for the nation, the states, and large geographic areas. The full implementation stage began in January 2005, with an annual housing unit (HU) sample of approximately 3 million addresses throughout the United States and 36,000 addresses in Puerto Rico. In 2006 approximately 20,000 group quarters were added to the ACS so that the datafully describe the characteristics of the population residing in geographic areas.Each year from 2005–2010, we selected approximately 2.9 million HU addresses in the U.S. and 36,000 HU addresses in Puerto Rico. Beginning in 2011, the following changes to the ACS sample designs were implemented:1)increased the housing unit sample in June 2011, bringing the size of the sample selected to 3.54 million addresses per year; 2)added several new housing unit sampling rates that better control the allocation of the sample and improve estimate reliability for small areas; 3)increased the follow-up sample to 100 percent in select geographic areas.