Sprawl and Health

Rajamani 2003 - "Assessing the Impact of Urban Form Measures in Nonwork Trip Mode Choice After Controlling for Demographic and Level-of Service Effects"

Jayanthi Rajamani, Chanra R.  Bhat, et al.
"Assessing the Impact of Urban Form Measures in Nonwork Trip Mode Choice After Controlling for Demographic and Level-of Service Effects"
Presented at the Transportation Research Board Annual Meeting (2003)
Session 747: Transportation and Urban Form
Wednesday, January 15, 2003, 7:30 PM - 9:30 PM, Hilton
On the Web

The abstract:
The relation between travel behavior and the local built environment has always been a contentious issue, despite several research efforts in the area. The current paper investigates the significance and explanatory power of a variety of urban form measures on nonwork activity travel mode choice. The data used for analysis is the 1995 Portland Metropolitan Activity Survey conducted by Portland Metro. The multinomial logit mode choice model results indicate that higher residential densities and mixed-uses promote walking behavior for nonwork activities.

 

Crane 1998 - "Does Neighborhood Design Influence Travel?: A Behavioral Analysis of Travel Diary and GIS Data"

Randall Crane and Richard Crepeau
"Does Neighborhood Design Influence Travel?: A Behavioral Analysis of Travel Diary and GIS Data"
Transportation Research Part D: Transport and Environment
3(4):225-238 (July 1998)
On the Web

 

From the abstract:
An analysis of household travel diary and GIS data for San Diego finds little role for land use in explaining travel behavior, and no evidence that the street network pattern affects either short or long non-work travel decisions. While results may vary in other areas, the empirical argument for using land use as an element of regional air quality or other environmental plans remains to be demonstrated.

(I didn't read the study intensively enough to comment, but see Cervero and Gorham (1995) for another study on Southern California.)

 

Cervero 2002 - "Built Environments and mode Choice: Toward a Normative Framework"

Robert Cervero
"Built Environments and mode Choice: Toward a Normative Framework"
Transportation Research Part D
7(4):265-284 (2002)
On the Web

From the abstract:
The analysis reveals intensities and mixtures of land use significantly influence decisions to drive-alone, share a ride, or patronize transit, while the influences of urban design tend to be more modest. Elasticities that summarize relationships are also presented...

Cervero 1995 - "Commuting in Transit Versus Automobile Neighborhoods"

Robert Cervero and Roger Gorham
"Commuting in Transit Versus Automobile Neighborhoods"
Journal of the American Planning Association
61(2):210-225 (Spring 1995)

From the abstract:
This article compares commuting characteristics of transit-oriented and auto-oriented suburban neighborhoods in the San Francisco Bay Area and in Southern California. Transit neighborhoods averaged higher densities and had more gridded street patterns compared to their nearby counterparts with auto-oriented physical designs. . . For both metropolitan areas, pedestrian modal shares and trip generation rates tended to be considerably higher in transit than in auto-oriented neighborhoods. Transit neighborhoods had decidedly higher rates of bus commuting only in the Bay Area. Islands of transit-oriented neighborhoods in a sea of freeway -oriented suburbs seem to have negligible effects on transit commuting.

Soot n/a - "Are Sprawl and Obesity Related? Evidence from the Chicago Area"

Siim Soot, Lise Dirks, et al
"Are Sprawl and Obesity Related? Evidence from the Chicago Area"
Unpublished: Metropolitan Transportation Support Initiative (METSI) working paper 06-01
Relevance: medium
On the Web

The authors estimate the effect of urban, socio-economic, and personal characteristics on BMI using height, weight, and ZIP code data from 7 million driver's licenses and state IDs in greater Chicago. Their regression finds that population density has a slight but significant effect, dwarfed by other variables. I have many questions about their methodology, but nonetheless don't think they overturn the bulk of sprawl and obesity research.

Dumbaugh 2005 - "Safe Streets, Livable Streets"

Dumbaugh, Eric
"Safe Streets, Livable Streets"
Journal of the American Planning Association
Summer 2001; vol.71, n.3; pp.283-300
On the Web
Relevance: low

While conventional wisdom recommends limiting roadside hazards, such as trees, and increasing lane and shoulder width will reduce the number and severity of crashes where the driver leaves the roadway, this author posits that trees and narrow lanes encourage drivers to drive more slowly and carefully, reducing the total number of crashes.

The author cites a few studies, including on in Washington on an urban/rural arterial (HWY 99?), where the presence of trees, sign supports, and other fixed objects is associated with fewer total crashes while wider lanes and shoulders are associated with more crashes. The author then conducts his own study comparing different sections of the same roadway, finding similar results.

I'd say that the numerical results in this study are a little squishy, the they and the theory are nonetheless very compelling.

Handy 2005 - "Correlation or Causality Between the Built Environment and Travel Behavior? Evidence from Northern California"

Handy, Susan; Cao, Xinyu; Mokhtarian, Patricia
"Correlation or Causality Between the Built Environment and Travel Behavior? Evidence from Northern California"
Transportation Research Part D
November 2005; v.10, n.6; pp.427-444
On the Web
Relevance: medium

Handy et al surveyed residents of traditional and suburban neighborhoods on their travel habits, travel attitudes, perceived neighborhood attributes, and socio-economic status. They found that while residents of traditional neighborhoods drove 18% fewer miles than suburban residents, the variation in this cross-section could be better explained by differences in attitudes and SES factors than in the built environment.

When the authors separated out those who had moved in the past year for a quasi-longitudinal study, differences in the built environment (mainly in accessibility) appeared significant. The built environment seemed to affect increased walking more than decreased driving.

I'm a bit wary of the quasi-longitudinal part of this study. Why would the built environment be significant there but not in the cross-sectional analysis?

Riediker 2004 - "Particulate Matter Exposure in Cars is Associated with Cardiovascular Effects in Healthy Young Men"

Riediker, Michael; Cascio, Wayne; et al.
"Particulate Matter Exposure in Cars is Associated with Cardiovascular Effects in Healthy Young Men"
American Journal of Respiratory and Critical Care Medicine
April 15, 2004; v.168, n.8; pp.934-940
On the Web
Relevance: medium-low

Part of a larger research project measuring air quality in cars, the authors measured the effects of exposure to PM2.5 on the cardiovascular functions of nine young, healthy patrol officers in North Carolina. They concluded that in-vehicle PM2.5 negatively affected inflammation, coagulation, and cardiac rhythm in slight but significant amounts. However, they also measured PM2.5 concentrations to be lower in the vehicles than on the side of the road or at the ambient location.

This study suggests to me that even a small amount of PM2.5 from vehicles is bad.

Chang 2000 - "Hourly Personal Exposures to Fine Particles and Gaseous Pollutants--Results from Baltimore, Maryland"

Chang, Li-Te; Koutrakis, Petros; et al
"Hourly Personal Exposures to Fine Particles and Gaseous Pollutants--Results from Baltimore, Maryland"
Journal of the Air and Waste Management Association
July 2000; v.50, n.7; pp.1223-1235
On the Web
Relevance: medium

The authors measured personal VOC exposure in a variety of microenvironments that older adults generally encounter. PM 2.5 concentrations were highest in the food court, while walking and driving, and in a kitchen and TV room at home. Ozone levels were elevated while walking at noon and while driving. Carbon monoxide levels were elevated i the middle of the day and while driving.

Ambient concentrations of PM 2.5 seem to be fairly well with personal exposure (r>.6 for all but one case). Ambient concentrations of ozone were also highly correlated with personal exposure for outdoor and in-vehicle microenvironments, less so for indoor environments, and barely at all for homes. There seems to be little correlation between ambient BTEX levels and personal exposures in homes and cars (except for benzene in homes), which suggests to me that personal exposure in those places comes mostly from personal activities (cooking, cleaning, and driving).

Chan 1991 - "Commuter Exposure to VOCs in Boston, Massachusetts"

Chan, Chang-Chuan; Spengler, John D; et al.
"Commuter Exposure to VOCs in Boston, Massachusetts"
Journal of the Air and Waste Management Association
December 1991; v.41, n.12; pp.1594-1600
On the Web
Relevance: high

The authors measured VOC exposure for four commuting methods (car, subway, walking, biking) plus concentrations in homes, offices, and on the sidewalk in Boston. They found that concentrations were generally highest in cars and lowest in homes/offices. "For most VOCs, the concentrations in homes and offices were about three to five times lower than the VOC concentrations during commuting." Around 10-20% of daily VOC exposure for car and subway commuters occurred during the commute.

Driving on urban roads was correlated with higher VOC concentrations (1.5 times higher) than driving on interstates.  Using the heater also increased VOC levels. On the other hand, the age of the car or country of origin (US vs. imported) did not seem to make a difference.

Riediker 2003 - "Exposure to Particulate Matter, Volatile Organic Compounds, and Other Air Pollutants Inside Patrol Cars"

Riediker, Michael; Williams, Ronald; et al.
"Exposure to Particulate Matter, Volatile Organic Compounds, and Other Air Pollutants Inside Patrol Cars"
Environmental Science and Technology
2003; v.37 n.10; pp.2084-2093
On the Web
Relevance: high

The authors measured PM and VOCs in patrol cars, roadsides, and a remote (ambient) site in North Carolina. They found that BTEX levels were significantly higher in the cars; elemental carbon levels were higher in the cars; but NO2 and PM2.5 levels were a little higher in at the ambient site; and ozone levels were nearly twice as high at the ambient site.

Larson 2004 - "Source Apportionment of Indoor, Outdoor, and Personal PM2.5 in Seattle, Washington, Using Positive Matrix Factorization"

Larson, Timothy Gould, Timothy; et al.
"Source Apportionment of Indoor, Outdoor, and Personal PM2.5 in Seattle, Washington, Using Positive Matrix Factorization"
Journal of the Air and Waste Management Association
September 2004, v.54, n.9; pp.1175-1187
On the Web
Relevance: medium

The authors measured indoor, outdoor, and personal concentrations of fine particulate matter (PM2.5) in the city of Seattle and estimated the sources of this PM. They concluded that vegetative burning (wood, incense, candles) contributed the most PM mass to outdoor (35%), indoor (49%), and personal (62%) exposure. In general, it seems that PM concentrations are higher outdoors than indoors.

Payne-Sturges 2004 - "Personal Exposure Meets Risk Assessment: A Comparison of Measured and Modeled Exposure and Risks in an Urban Community"

Payne-Sturges, Devon C; Burke, Thomas A.; et al.
"Personal Exposure Meets Risk Assessment: A Comparison of Measured and Modeled Exposure and Risks in an Urban Community"
Environmental Health Perspectives
April 2004; v.112, n.5; pp.589-598
On the Web
Relevance: low

The authors measured personal exposure, indoor concentrations, and outdoor concentrations of VOCs in South Baltimore, an area near chemical industries and an interstate highway. They found that personal exposure was generally higher than indoor concentrations, which were higher than outdoor concentrations. The authors report these concentrations and the associated cancer risks. Their main goal was to compare their measured estimates to estimates from the ASPEN model.

Levy 2000 - "Particle Concentrations in Urban Microenvironments"

Levy, Jonathan I; Houseman, E. Andres; et al.
"Particle Concentrations in Urban Microenvironments"
Environmental Health Perspectives
November 2000; v.108, n.11; pp.1051-1057.
On the Web
Relevance: medium

The authors measured particulate matter indoors and outdoors in seven microenvironments (subway, bus, restaurant, hospital, gymnasium, museum, store) in Boston. Particle counts for PM 0.3-0.5 were generally higher inside the subway and bus than outdoors, but lower inside the store, hospital, and museum. Particle counts overall were higher inside the subway and bus than outside.

Wong 2004 - "Assessing the Health Benefits of Air Pollution Reduction for Children"

Wong, Eva Y; Gohlke, Julia; et al.
"Assessing the Health Benefits of Air Pollution Reduction for Children"
Environmental Health Perspectives
February 2004; v.112, n.2; pp.226-232
On the Web
Relevance: low

The authors estimated the health and economic benefits to children of reductions in criteria air pollutants (except lead) due to the Clean Air Act from 1990 to 2010. They estimated a savings of $1-2 billion from fewer hospitalizations, emergency room visits, school absences, and low birth weight. The also estimated a savings of $0.6-$100 billion from decreased mortality.

Sexton 2004 - "Comparison of Personal, Indoor, and Outdoor Exposures to Hazardous Air Pollutants in Three Urban Communities"

Sexton, Ken; Adgate, John L; et al.
"Comparison of Personal, Indoor, and Outdoor Exposures to Hazardous Air Pollutants in Three Urban Communities"
Environmental Science and Technology
2004; v.38, n.2; pp.423-430
On the Web
Relevance: high

The authors measure personal, indoor, and outdoor exposures to 15 VOCs in three different neighborhoods of Minneapolis/St. Paul, MN. They found that outdoor community air monitors greatly underestimate personal exposures and that even indoor monitors underestimate personal exposure. For example, for benzene, the personal/outdoor (P/O) ratio of estimated relative concentrations is 6.8, while the personal/indoor concentration (P/I) is 1.6.

Allen 2004 - "Estimated Hourly Personal Exposures to Ambient and Nonambient Particulate Matter Among Sensitive Populations in Seattle"

Allen, Ryan; Wallace, Lance; et al.
"Estimated Hourly Personal Exposures to Ambient and Nonambient Particulate Matter Among Sensitive Populations in Seattle"
Journal of Air and Waste Management
September 2004; v.54; n.9; pp.1197-1411
On the Web
Relevance: High

The authors measured the concentration of particulate matter in various mircoenvironments (home indoors, home outdoors, work, school, in transit, other outdoors, other indoors) and the average exposure for 38 subjects in Seattle. The subjects selected were "sensetive populations" with asthma, coronary heart disease, or advanced age. The major findings were:

• The best air was indoors at home; the worst air was at work, followed by outdoors and in transit.
• Because subjects spend so much time at home, most of their exposure (79%) occured there.
• There was a low correlation between ambient and personal exposures (0.43) compared to findings from other studies. This means that localized sources highly affect personal exposure (i.e. cooking fumes vs.general air quality)

Nasar 1995 - "The Psychological Sense of Community in the Neighborhood"

Nasar, Julian
"The Psychological Sense of Community in the Neighborhood"
Journal of the American Planning Association
Spring 1995; v61, n2; pp 178-184
Relevance: high

There is more social capital--at least as conceived as neighborhood social ties--in mixed-use (and presumably higher density) communities than in single use communities. From the abstract: This paper describes the development and testing of an 11-item Likert scale of the sense of neighborhood community, using responses from 54 residents in three suburbs in Columbus, Ohio. One test of the scale with 100 residents in single-use and mixed-use areas near one another found significantly more sense of community in the mixed-use neighborhood. More sense of community emerged among married persons and couples with children as compared to singles and childless couples.

Much of this paper is devoted to justifying its research methodologies. Of particular interest is a list of 15 questions on page 181 that researchers used to ascertain neighborhood social ties. This could be of use in future primary research on social capital.

Fruin 2004 - "Black Carbon Concentrations in California Vehicles and Estimation of In-Vehicle Diesel Exhaust Particulate Matter Exposures"

Fruin, Scott A; Winer, Arthur M; Rodes, Charles E.
"Black Carbon Concentrations in California Vehicles and Estimation of In-Vehicle Diesel Exhaust Particulate Matter Exposures"
Atmospheric Environment
August 2004; v.38, n.25; pp.4123-4133
On the Web
Relevance: low

The authors measured black carbon (BC) concentrations inside vehicles driven around LA and Sacramento. BC is typically associated with diesel emissions. The authors found that the most important predictor of in-vehicles BC concentrations was the type of vehicle followed, with diesel buses and delivery trucks that had ground-level exhaust pipes being the worst. Following a gasoline powered car did not increase BC concentrations.

The authors also estimate daily exposure to diesel particulate matter (DPM), concluding that compared to earlier models, "in-vehicle DPM exposures appear to make very significant contributions to overall DPM exposures, randing from approximately 30-55% of total DPM exposure on a statewide, population basis.  Thus the in-vehicle microenvironment may be the most important route of overall DPM exposure, though only 1.5h day-1 is spend there, on average."

Friedman 2001 - "Impact of Changes in Transportation and Commuting Behaviors During the 1996 Summer Olympic Games in Atlanta on Air Quality and Childhood Asthma"

Friedman, Michael S; Powell, Kenneth E; et al.
"Impact of Changes in Transportation and Commuting Behaviors During the 1996 Summer Olympic Games in Atlanta on Air Quality and Childhood Asthma"
Journal of the American Medical Association
February 21, 2001; vol.285, n.7; pp.897-905.
On the Web
Relevance: low

The authors compared the level of air pollution and asthma events during the Atlanta Olympics to levels just before and after. They found that ozone levels and asthma events were lower during the Oympics, likely due to changes in traffic patterns. The number of asthma acute care events decreased 41.6% in the Georgia Medicaid claims file.  Organizers increased public transportation, closed the downtown to cars, encouraged workers to change work hours, and made other adjustments. There are several caveats to this study, so we may not want to quote it alone, but it could be one building block of the case.

CARB 1998 - "Measuring Concentrations of Selected Air Pollutants Inside California Vehicles"

California Air Resources Board (CARB)
"Measuring Concentrations of Selected Air Pollutants Inside California Vehicles"
December 1998, Contract No. 95-339, Final Report
On the Web
Relevance: medium-low

CARB measured concentrations of various air pollutants inside vehicles as a range-finding experiment. They studied the effect of freeway conditions (rush vs. non-rush), roadway types, vehicle types, air vent settings, time of day, and roadside/ambient air quality.

CARB found that pollutant concentrations were higher:

• in the regular vs. carpool lane
• during rush hour
• when following diesel or other high-emitting vehicles

Other findings include:

• Vent settings and vehicle type did not seem to make a big difference
• "Most pollutants levels, especially the VOC's, were elevated inside and outside the vehicles relative to either the roadside or ambient station concentrations"
• "Particle concentrations were typically significantly higher outside the vehicles than inside, presumably due to losses in the vehicle ventilation systems (and other factors) - while significant differences were not observed between inside and outside levels of gas phase pollutants for the same vehicle."

CAVEAT: this was a preliminary, range-finding study, so we should look at other studies for confirmation and hard numbers.

Lopez n/a - "Urban Sprawl and the Risk of Physical Inactivity"

Lopez, Russ
"Urban Sprawl and the Risk of Physical Inactivity"
Unpublished
Not on the web (received from author)
Relevance: high

The author combines his sprawl index with 2001 BRFSS data on physical inactivity to estimate the sprawl connection. From the abstract

"For each one point increase in sprawl, the risk of being physically inactive [defined as no physical activity] increased by .04% ... Physical inactivity is associated with urban sprawl and other factors of the metropolitan social/physical environment, but the effect is small and minor changes in the overall metropolitan environment may not result in large changes in levels of physical activity."

Also see his published article on obesity.

Lopez 200? - "Thirty Years of Urban Sprawl in Metropolitan America: 1970-2000"

Lopez, Russ
"Thirty Years of Urban Sprawl in Metropolitan America: 1970-2000"
A report to the Fannie Mae Foundation
publication date unknown
Not on the web (received from author)
Relevance: high

The author constructed a sprawl index primarily measuring density for 330 metropolitan areas. The index ranged from 0-100 with the score roughly correlating to the percentage of residents who live in low-density census tracts, so a higher score means more sprawl. In this report the author lists his sprawl scores, compares his index to Ewing's index, and discusses changes in sprawl from 1970 to 2000. Lopez's index correlates roughly 50% to Ewing's index, and 92% to Ewing's density factor. Also see Lopez's sprawl-obesity article using this index.

Ewing 2002 - "Measuring Sprawl and Its Impact"

Ewing, Reid; Pendall, Rolf; Chen, Don
"Measuring Sprawl and Its Impact"
Smart Growth America
2002
On the Web
Relevance: high

Ewing et al. created a sprawl index for ~83 metropolitan areas, incorporating density, land use mix, centeredness, and street accessibility. The authors also estimated the impact of sprawl on various transportation-related outcomes. They found that a higher degree of sprawl is associated with higher average vehicle ownership, daily VMT per capita, annual traffic fatality rate, and maximum ozone level; more sprawl was associated with a lower share of work trips by transit and walking. Note that, as with most sprawl studies, we can't assume a causal relationship.

Guest 1999 - "Social ties at the neighborhood level: Two decades of GSS evidence"

Guest, Wierzbicki
"Social ties at the neighborhood level: Two decades of GSS evidence"
Urban Affairs Review   
September 1, 1999; v35, n1, pp 92-111
On the Web
Relevance: Medium-low

This article is mostly a by-the-book summary of the General Social Survey's findings on social capital from 1972 to the 1990s. It appears to question many of Putnam's findings about the seriousness and quality of the decline of US social capital. It also examines many of the theories about why social capital is eroding--urban form/highways, women in the workforce, structural social changes, etc. There's not much that's terribly relevant to our work, but two things bear mentioning.

The headline: "The data show a relatively continuous, albeit slow, decline in the importance of social ties on the basis of neighborhood and, in turn, an even smaller upward growth in the importance of nonneighborhood social ties."

There was no difference between central cities and suburbs (or other areas for that matter). The authors divided the GSS samples into four urban-form categories: central city of large metro area, suburbs of large metro area, other urban areas, and rural areas. "We examined the effect of locale over the three decades but found no significant interaction."

Kawachi 1997 - "Social capital, income inequality, and mortality"

Kawachi, Kennedy, Lochner, Prothrow-Stith
"Social capital, income inequality, and mortality"
American Journal of Public Health
September 1997; v87, n9, pp 1491
On the Web
Relevance: High

This is perhaps the single most compelling study that social capital--in the broad sense of civic engagement--affects health. The authors use the General Social Survey's result to perform "ecologic" analyses of 39 states' levels of social capital and income inequality compared to mortality. Still, there are some important short-comings.

The authors claim that "income inequality leads to increased mortality via disinvestment in social capital" though it is not clear to me that they actually demonstrate this. Instead, they demonstrate that income inequality is correlated to social capital and also show a correlation between social capital and mortality. (It's relatively well-documented that income inequality is associated with higher mortality).

House 1998 - "Social Relationships and Health"

House, Landis, Umberson
"Social Relationships and Health"
Science
July 29, 1988; v241 n4865, pp 540-545
Relevance: Medium

This is essentially a review of the primary studies relating social connections to health. Because the article is now 7 years old it fails to mention any of Kawachi's studies, which are arguably some of the most compelling pieces of evidence for believing that there is a link. Still, while the article is largely confined to summarizing the findings of studies that we are familiar with (Alameda County, CA; Evans County, GA; Tecumseh, MI; Gothenberg, Sweden; eastern Finland, etc), it does make at least two  interesting points that are worth attending to.

"Social relationships, or the relative lack thereof, constitute a major risk factor for health--rivaling the effects of well-established health risk factors such as cigarette smoking, blood pressure, blood lipids, obesity, and physical activity."

"In Tecumseh, Evans County, and eastern Finland, mortality is clearly elevated among the most socially isolated, but declines only modestly, if at all, between moderate and high levels of social integration."

Kawachi 1999 - "Social capital and community effects on population and individual health"

Kawachi
"Social capital and community effects on population and individual health"
Annals of New York Academy of Sciences
1999; v896; pp 120-130
On the Web
Relevance: High

This paper references what is probably the single most convincing piece of evidence we have for believing that social capital affects health--Kawachi et al's 1997 analysis of the GSS survey for 39 states, conducted between 1986 and 1990. In two reported analyses, he finds a close state-by-state correlation between social capital and health. In particular, trust was important: "the level of trust explained 58% of the variance in total mortality across states, including statistically significant associations with most major causes of death including heart disease, malignant neoplasms, stroke, homicide, and infant mortality."

Kawachi 1996 - "A prospective study of social networks in relation to total mortality and cardiovascular disease in men in the USA"

Kawachi, Colditz, Ascherio, Rimm, Giovannucci, Stampfer, Willet
"A prospective study of social networks in relation to total mortality and cardiovascular disease in men in the USA"
Journal of Epidemiology and Community Health
June 1996; v50, n3; pp 245-251
On the Web
Relevance: High

A longitudinal study of roughly 32,000 male health professionals in the US. According to the authors, "socially isolated men... were at increased risk for cardiovascular disease mortality... and deaths from accidents and suicides... [and] risk of stroke incidence." These results were most strongly seen comparing the 50% of most socially-connected men to the 6% of least socially-connected. The study defined social networks as marrital status, number of friends and relatives, and membership in church or community groups--some of these features are conceivably affected by sprawl.

McCann 2003 - "Measuring the Health Effects of Sprawl"

McCann, Barbara; Ewing, Reid
"Measuring the Health Effects of Sprawl: A National Analysis of Physical Activity, Obesity, and Chronic Disease."
Smart Growth America and Surface Transportation Policy Project
September 2003
On the Web
Relevance: high

This report is based on Ewing et al's earlier article (2003) and is longer with more details and sidebars. The conclusions, of course, are the same, but the report includes sprawl scores for all 448 counties and the web page has fact sheets for counties in most states.

Kelly-Schwartz 2004 - "Is Sprawl Unhealthy?"

Kelly-Schwartz, Alexia; Stockard, Jean, et al
"Is Sprawl Unhealthy? A Multilevel Analysis of the Relationship of Metropolitan Sprawl to the Health of Individuals"
Journal of Planning Education and Research
December 2004; v.24, n2; pp.184-196
On the Web
Relevance: high

The authors replicated and extended Ewing et al's work on the effect of sprawl on health. They compared self- and physican-rated health as well as a variety of chronic conditions across metropolitan areas while controlling for income, education, sex, etc. They found that sprawl does affect health somewhat, but in a complex way that is difficult to track.  It appears that a highly gridded street network is associated with better health while more density is associated with poorer health.  While sprawl was not significantly associated with a higher prevalence of chronic conditions, among those with those conditions, the gridded street network was associated with better health.

King 2003 - "The Relationship Between Convenience of Destinations and Walking Levels in Older Women"

King, Wendy C.; Brach, Jennifer S.; et al.
"The Relationship Between Convenience of Destinations and Walking Levels in Older Women"
American Journal of Health Promotion
Sept-Oct 2003; vol.18, n.1; pp.74-82
On the Web
Relevance: medium-high

Using a small sample (149) of older women, the authors found that living within a 20 minute walk of a park; biking or walking trail; or a department, discount, or hardware store was significantly related to walking more, as objectively measured by pedometer readings.  Walking was also associated with living near more destinations and with a better neighborhood rating for walking.

Ewing 2003 - "Relationship Between Urban Sprawl and Physical Activity, Obesity, and Mortality"

Ewing, Reid; Schmid, Tom, et al
"Relationship Between Urban Sprawl and Physical Activity, Obesity, and Mortality"
American Journal of Health Promotion
September/October 2003; vol.18, n.1; pp.47-57
On the Web
Relevance: high

The authors estimated the impact of a county and metropolitan area sprawl index on obesity, physical activity, and related diseases. They found that the county  index significantly influenced the number of minutes spent in leisure-time walking, average BMI, obesity status, and prevalence of hypertension.

Thorpe 2004 - "The Impact of Obesity on Rising Medical Spending"

Thorpe, Kenneth E; Florence, Curtis S; et al
"The Impact of Obesity on Rising Medical Spending"
Health Affairs
October 2004, Web Exclusive W4-480
On the Web
Relevance: high

Comparing data from the 1987 National Medical Expenditure Survey and the 2001 Medical Expenditure Panel Survey, the authors estimate the impact of obesity on inflation-adjusted medical spending. They estimate that 27% of the increase was due to obesity, and that 12% was due to the increased obesity rate alone, exclusive of medical advances. In 2001, medical costs for an obese person were 37% higher than for a comparable normal weight person. The authors also calculate the effect of obesity on the increase in spending on diabetes (38%), hyperlipidemia (22%), and heart disease (41%).

Berrigan 1998 - "The Association Between Urban Form and Physical Activity in US Adults"

Berrigan, David; Troiano, Richard
"The Association Between Urban Form and Physical Activity in US Adults"
American Journal of Preventive Medicine
2002; v.23, n.2S; pp.74-79
On the Web
Relevance: medium

Using data from NHANES III, the authors found that people who lived in houses built before 1946 or between 1946 and 1973 were more likely to walk regularly than were people who lived in houses built after 1973. Those living in homes built before 1946 were 1.43 times more likely and those in homes built 1946-1973 were 1.36 times more likely to walk at least a mile at least 20 times a month than were those living in homes built after 1973.

Berkman 1995 - The Role of Social Relations in Health Promotion

Berkman, Lisa F.
"The Role of Social Relations in Health Promotion"
Psychosomatic Medicine - Special Issue: Superhighways for Disease
May/June 1995; v.57, n.3; pp.245-254
On the Web
Relevance: low/medium

Here's the nut of the article, from the abstract: "There is now a substantial body of evidence that indicates that the extent to which social relationships are strong and supportive is related to the health of individuals who live within such social contexts. A review of population-based research on mortality risk over the last 20 years indicates that people who are isolated are at increased mortality risk from a number of causes." According to Berkman, social isolation, "seemed to make people more vulnerable to a broad range of diseases and disabilities..." (This is in marked contrast to the standard medical etiological approach that specific causes for specific diseases.)

Must 1999 - "The Disease Burden Associated with Overweight and Obesity"

Must, Aviva; Spadano, Jennifer; et al
"The Disease Burden Associated with Overweight and Obesity"
Journal of the American Medical Association
October 27, 1999; v.282, n.16; pp.1523-1529
On the Web
Relevance: low/medium

Using NHANES III (1988-1994) the authors estimate the risk of having type 2 diabetes, gallbladder disease, coronary heart disease, high cholesterol, high blood pressure, or osteoarthritis for normal weight, overweight, obese groups.  Risk increased with BMI for all diseases except coronary hearth disease in men and cholesterol in both sexes.

Kannel 1996 - "Effect of Weight on Cardiovascular Disease"

Kannel, Wiliam B; Agostino, D; et al
"Effect of Weight on Cardiovascular Disease"
American Journal of Clinical Nutrition
March 1996; v.63, n.3; p.419S-422S
On the Web
Relevance: low

Using the Framingham Heart Study, the authors find that the optimal BMI to avoid cardiovascular disease is 22.6 for men and 21.1 for women.  Each SD (???) increment in relative weight increased risk of cardiovascular events by 15% for men and 22% for women.  The authors estimate that if everyone was their optimal BMI, there would be 1) 25% less coronary heart disease and 2) 35% fewer strokes or episodes of cardiac failure.

Xiang 2005 - "Obesity and Risk of Nonfatal Unintentional Injuries"

Xiang, Huiyun; Smith, Gary A; et al
"Obesity and Risk of Nonfatal Unintentional Injuries"
American Journal of Preventive Medicine
July 2005; v.29, n.1; pp.41-45
On the Web
Relevance: low

The authors used a survey of adults in 1999-2000 to estimate the likelihood of injuries for persons in different weight categories.  The found that injuries increase linearly with BMI category among women and that both men and women with BMI>35 had the highest likelihood of injury.

Pratt 2000 - "Higher Direct Medical Costs Associated with Physical Inactivity"

Pratt, Michael; Macera, Caroline A; Wang, Guijing
"Higher Direct Medical Costs Associated with Physical Inactivity"
The Physician and Sportsmedicine
October 2000; v.28, n.10; pp.63-70
On the Web
Relevance: medium

Using the 1987 National Medical Expenditures Survey, the authors estimate the costs of physical activity in the US. They conclude:

"The mean net annual benefit of physical activity [among people with no physical limitations] was $330 per person in 1987 dollars.  Our results suggest that increasing participation in regular moderate physical activity among the more than 88 million inactive Americans over the age of 15 might reduce annual national medical costs by as much as $29.2 billion in 1987 dollars--$76.6 billion in 2000 dollars."

Finkelstein 2004 - "State-Level Estimates of Annual Medical Expenditures Attributable to Obesity"

Finkelstein, Eric A; Fiebelkorn, Ian C; Wang, Guijing
"State-Level Estimates of Annual Medical Expenditures Attributable to Obesity"
Obesity Research
January 2004; v.12, n.1; pp.18-24
On the Web
Relevance: high

Beginning with their earlier estimates of the national medical expenditures on obesity, the authors use BRFSS data from 1998-2000 to estimate the state-level expenditures.  Idaho spent $227 million; Oregon, $781 million; and Washington, $1330 million.  In the first study, they found: "Annual U.S. obesity-attributable medical expenditures are estimated at $75 billion in 2003 dollars, and approximately one-half of these expenditures are financed by Medicare and Medicaid.

Finkelstein 2003 - "National Medical Spending Attributable to Overweight and Obesity: How Much, and Who's Paying?"

Finkelstein, Eric A; Fiebelkorn, Ian C; Wang, Guijing
"National Medical Spending Attributable to Overweight and Obesity: How Much, and Who's Paying?"
Health Affairs - web exclusive
May 2003; web published
On the Web
Relevance: high

Using the 1998 Medical Expenditure Panel Survey (MEPS) and the 1996 and 1997 National Health Interview Survey, the authors estimate that aggregate medical expenditures for obesity and overweight in 1998 were 9.1% of total US medical expenditures: $78.5 billion ($92.6 billion in 2002 dollars).  The also found that Medicare and Medicaid paid for about half of these costs.

Fontaine 2003 - "Years of Life Lost Due to Obesity"

Fontaine, Kevin R; Redden, David T; et al
"Years of Life Lost Due to Obesity"
Journal of the American Medical Association
January 8, 2003; v.289, n.2; pp.187-193
On the Web
Relevance: medium

Using data from NHANES I, II, and III, the authors calculated that a BMI of 23-25 for whites and 23-30 for black was associated with the longest life.  The estimated that years of life lost (YLL) increases with BMI in a J or U shaped curved among whites. Overweight and obesity cut more years off life for younger adults than for older adults.   Overweight had less effect on blacks, especially black women and elderly blacks.

Hu 2004 - "Adiposity as Compared with Physical Activity in Predicting Mortality among Women"

Hu, Frank B; Willet, Walter C; et al
"Adiposity as Compared with Physical Activity in Predictiong Mortality among Women"
New England Journal of Medicine
December 23, 2004; v.351, n.26' pp.2694-2703
On the Web
Relevance: high

Using the Nurse's Health Study (1976-1998?), the authors studied how both adiposity (obesity) and physical activity affect mortality risk. They found that obesity predicted a higher risk of death regardless of physical activity level, and physical inactivity predicted a higher risk of death regardless of BMI.

Gregg 2005 - "Secular Trends in Cardiovascular Disease Risk Factors According to Body Mass Index in US Adults"

Gregg, Edward W.; Cheng, Yiling J; et al
"Secular Trends in Cardiovascular Disease Risk Factors According to Body Mass Index in US Adults"
Journal of the American Medical Association
April 20, 2005; v.293, n.15; pp.1868-1875
On the Web
Relevance: high

Using data from NHES (1960-1962), NHANES I (1971-1975), II (1976-1980), and II (1988-1994) and NHANES 1999-2000, the authors looked at trends in high cholesterol, high blood pressure, and diabetes. They found that the prevalence of high cholesterol and high blood pressure have declined, and that they declined most in overweight and obese groups; however, the decline was smaller when the authors looked at the prevalence of both the conditions and treatments for the conditions. The prevalence of diabetes increased in all groups, most dramatically among the overweight and obese.

• "The net result of these phenomena may be a population that is, paradoxically, more obese, diabetic, arthritic, disabled, and medicated, but with lower overall CVD risk."

Manson 1995 - "Body Weight and Mortality Among Women"

Manson, Joann E; Willett, Walter C; Stampfer, Meir J; et al
"Body Weight and Mortality Among Women"
New England Journal of Medicine
September 14, 1995; v.333, n.11; pp.677-685
On the Web
Relevance: medium

Using data from the Nurses Health Study (1976-1992), the authors calculated the risk of mortality at various BMI levels for women of smoking and non-smoking status.  They found that among non-smoking women, mortality increases with BMI at all levels of BMI.  Smoking affects the association by raising the mortality risk for the leanest group (lowest BMI).

Stevens 1998 - "The Effect of Age on the Association Between Body-Mass Index and Mortality"

Stevens, June; Cai, Jianwen; et al
"The Effect of Age on the Association Between Body-Mass Index and Mortality"
New England Journal of Medicine
January 1, 1998; v.338, n.1; pp.1-7
On the Web
Relevance: medium

Using data from the American Cancer Society's Cancer Prevention Study I (1960-1972), the authors found that: "Excess body weight increases the risk of death from any cause and from cardiovascular disease in adults between 30 and 74 years of age.  The relative risk associated with greater body weight is higher among younger subjects."  In short, the older you are, the less detrimental obesity and overweight are for mortality.

Calle 1999 - "Body-Mass Index and Mortality in a Prospective Cohort of U.S. Adults"

Calle, Eugenia E; Thun, Michael J; Petrelli, Jennifer M; et al
"Body-Mass Index and Mortality in a Prospective Cohort of U.S. Adults"
New England Journal of Medicine
October 7, 1999; v.341, n.15; pp.1097-1105
On the Web
Relevance: medium

Using data from the Cancer Prevention Study (1982-1996), the authors calculated the relative risks of mortality for different categories of BMI at baseline, adjusting for sex, age and other risk factors. They found the usual J-shaped BMI-mortality curve with the lowest risk at a normal BMI. Smoking and disease change the curve by making leanness more risky.

Mokdad 2004 - "Actual Causes of Death in the United States, 2000"

Mokdad, Ali H; Marks, James S; Stroup, Donna F; Gerberding, Julie L
"Actual Causes of Death in the United States, 2000"
Journal of the American Medical Association
March 10, 2004; v.291, n.10
On the Web
Relevance: medium

Mokdad et al reviewed the literature for best estimates of the numbers of deaths attributable to various causes.  "The leading causes of death in 2000 were tobacco (435 000 deaths; 18.1% of total US deaths), poor diet and physical inactivity ([365 000 deaths; 15.2%]), and alcohol consumption (85 000 deaths; 3.5%).  Other actual causes of deaht were microbial agents (75 000), toxic agents (55 000), motor vehicle crashes (43 000), incidents involving firearms (29 000), sexual behaviors ( 20 000), and illicit use of drugs (17 000)."

Colditz 1999 - "Economic Costs of Obesity and Inactivity"

Colditz, Graham A
"Economic Costs of Obesity and Inactivity"
Medicine and Science in Sport and Exercise
November 1999; v.31, n.11 (supplement); pp.S663-S667
On the Web
Relevance: medium

Using similar methods to a previous study, Colditz estimates the direct costs of lack of physical exercise to be $24 billion per year (2.4% of national health care expenditures) and the direct costs for obesity, independent of lack of exercise, to be $70 billion (9.4%) for the year 1995.

Allison 1999 - "Annual Deaths Attributable to Obesity in the United States"

Allison, David B.; Fontaine, Kevin R.; Manson, JoAnne E.; Stevens, June; VanItallie, Theodore B.
"Annual Deaths Attributable to Obesity in the United States"
Journal of the American Medical Association
October 27, 1999; v.282, n.16; pp.1530-1538.
On the Web
Relevance: High

The authors used data from 5 cohort studies and 1991 national statistics to estimate that approximately 280,000 deaths annually are attributable to obesity, using all subjects.  When restricted to non-smokers the estimate rises to 325,000 deaths annually.

Wolf 1996 - "Social and Economic Effects of Body Weight in the United States"

Wolf, Anne M.; Colditz, Graham A.
"Social and Economic Effects of Body Weight in the United States"
The American Journal of Clinical Nutrition
March 1996; v.63, n.3 (supplement); pp.466S-469S
On the Web
Relevance: medium

Wolf and Colditz estimated the direct and indirect costs of obesity using risk estimates for various diseases from the Nurses' Health Study and estimates of lost productivity from the1988 National Health Interview Study.  The authors estimate that "if obesity were prevented, the United States could have saved $45.8 billion in 1990 (in 1993 dollars) or (6.8%) of health care expenditures for that year."

ICTA 2000 - “In-Car Air Pollution: The Hidden Threat to Automobile Drivers"

International Center for Technology Assessment,
“In-Car Air Pollution: The Hidden Threat to Automobile Drivers"
Report No. 4, An Assessment of the Air Quality Inside Automobile Passenger Compartments
Washington, DC: July 2000
On the Web
Relevance: high

This report reviews 23 studies from between 1982 and 1998 covering the main pollutants inside cars: particulate matter, volatile organic compounds, carbon monoxide, nitrogen oxides, and ozone.  For all exhaust pollutants except CO and the largest PM, concentrations are typically higher inside cars in heavy traffic than elsewhere.

Batterman 2002 - “Levels and Composition of Volatile Organic Compounds on Commuting Routes in Detroit, Michigan”

Batterman, Stuart A; Peng, Chung-Yu; and Braun, James.
“Levels and Composition of Volatile Organic Compounds on Commuting Routes in Detroit, Michigan”
Atmospheric Environment
December 2002; v.36,n.39-40; pp.6015-6030
On the Web
Relevance: high

Batterman et al measured VOCs in cars and buses during rush hour on commercial, industrial, and residential routes in Detroit, Michigan.  They found that:

• VOC concentrations along roadways and in buses were similar;
• route did not much affect differences in air quality; however, the buses all traveled on congested 4 lane roads during rush hour; and
• VOC concentration varied significantly over time, which the authors attribute to changes in weather, mainly inversions and wind speed and direction;
• vehicle sourc