Indicator TR.1.a Motor vehicle access
Why Is This An Indicator Of Health and Sustainability?
Car ownership is often indicative of the degree of transportation mode choice, shaped by factors including land use, the transportation system, and individual characteristics. Transportation mode choice can have effects community health through pathways including air quality, noise, physical activity, and traffic injuries.a Air pollutants, including ozone and particulate matter, are causal factors for cardiovascular mortality and respiratory disease and illness. Traffic-related noise triggers community annoyance and sleep disturbanceb and is associated with hypertension and heart disease.c Driving time has been found to independently predict obesity risk. A study on the driving habits of over 10,000 Atlanta residents found that each additional hour spent in the car was associated with a 6% increase in the likelihood of being obese.d Additionally, areas with high levels of motor vehicle driving tend to have higher motor vehicle collisions and injury rates.e
Car ownership is dependent upon many factors including individual and household income, cost of car, insurance and maintenance, distance regularly traveled, accessibility of public transportation, presence of bike routes and walking paths, perceived and actual safety from crime and traffic hazards, weather conditions, traffic patterns, availability of parking, availability of public transit travel stipends/incentives. Neighborhoods with higher densities of development and a mix of different land uses reduce trip length, increase mode choice (i.e., opportunities to walk, bike or take public transit), and decrease the need for vehicle ownership and travel by private vehicle. Projects in these types of communities with designed with restricted residential parking, parking pricing strategies and a variety of transportation demand management programs can reduce negative health impacts associated with dependence on motor vehicles.f,g
A household can be any individual or group of individuals sharing a housing unit, including families related by blood or marriage. (A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied as a separate living quarters from other individuals in the building.)
The total number of households without a car (see data sources) was divided by the total number of occupied households (see data sources) and the margins of error were recalculated using the ACS users handbook. For more information on the margin of error or ACS guidance, please visit: http://www.census.gov/acs/www/guidance_for_data_users/handbooks/
The ACS is a sample survey, and thus, data are estimates rather than counts. Estimates have accompanying margins of error that indicate the span of values that the true value could fall within. Margins of error should be subtracted from and added to the estimate to determine the range of possible values. If the margin of error is too big relative to the value, data are not shown because they are statistically unstable. A coefficient of variation of 30% was used to determine statistical instability.
Golden Gate Park, Presidio, Seacliff and Treasure Island have been excluded from the analysis due to small population. Additionally, many of the census tracts have data that is statistically unstable.
Although there are many public health risks associated with dependence on motor vehicles and their associated hazards, people are also at a disadvantage if they lack accessibility to transport to connect with goods and services, social, education and work-related activities. In some cases, public transportation does not adequately connect households to destinations at the hours needed, or at all. While some households choose not to have a car because they are able to access basic needs with other transportation modes, others are reliant on motor vehicles in the absence of public transit that meets their transportation needs - or in the absence of a motor vehicle are unable to or severely limited in their ability to access fundamental goods and services due to factors including lower income, age (e.g., seniors) or disability.
PolicyLink, Prevention Institute, the Convergence Partnership. Healthy, Equitable Transportation Policy. 2009. Ed. Shireen Malekafzali. Available at: http://www.convergencepartnership.org/atf/cf/%7B245a9b44-6ded-4abd-a392-ae583809e350%7D/HEALTHTRANS_FULLBOOK_FINAL.PDF.
Seto EYW, Holt A, Rivard T, Bhatia R. 2007. Spatial distribution of Traffic Induced Noise Exposures in a US city: an Analytic Tool for Assessing the Health Impacts of Urban Planning Decisions. International Journal of Health Geography. 6(24). Available at: http://www.ij-healthgeographics.com/content/6/1/24. Accessed November 17, 2008.
Miedema HME, Vos H. 1998. Exposure Response for Transportation. J Acoust Soc Am. 1998;104:3432–3445.
Ewing R, Frank L, Kreutzer R. 2006. Understanding the Relationship between Public Health and the Built Environment: A Report to the LEED-ND Core Committee.
Ewing R, Frank L, Kreutzer R. 2006. Understanding the Relationship between Public Health and the Built Environment: A Report to the LEED-ND Core Committee
Litman T, Steele R. 2012. Land Use Impacts on Transport. Victoria Transport Policy Institute. Available at: http://www.vtpi.org/landtravel.pdf.