May 2009

Grant Results


Researchers at Lawrence Frank and Company analyzed data collected from the greater Atlanta area to see if the distance people travel for food varies by gender, race/ethnicity, neighborhood characteristics and type of food outlet. They also examined the relative contributions of diet and physical activity in explaining Body Mass Index (BMI) in men, women, Whites and Blacks.

Key Findings

  • People traveled farthest to go to sit-down restaurants and superstores. They traveled the least far for grocery stores and coffee shops.
  • There were not large differences in distances traveled to food outlets by Whites and Blacks or by high- and low-income households.
  • While physical activity, neighborhood walkability and where people went for food all contributed modestly to explaining differences in BMI, the relative contribution of these factors differed significantly between men and women and between Whites and Blacks.

The Robert Wood Johnson Foundation (RWJF) supported this unsolicited project with a grant of $87,963 from May 2006 to June 2007.

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According to a 2006 article in the Journal of the American Medical Association, obesity increased in the past several decades to the point that about a third of the U.S. population is obese. Using 2003-2004 data, researchers found that 45 percent of Blacks are obese, compared to 30 percent of Whites. Though weight is influenced by diet and physical activity, few studies have examined:

  • The relationship of weight to where people buy food and their physical activity.
  • Whether these relationships differ by gender or race/ethnicity.

Increases in obesity could be associated with people eating more meals away from home, according to Lawrence D. Frank, Ph.D., whose Washington-state consulting firm focuses on the health, environmental and economic impacts of community design. It is possible that people's patterns of physical activity or sedentary behaviors interact with where they go for food, and that these interactions differ across genders or racial/ethnic groups. Eating more fast food meals has been linked to poorer diets, weight gain and higher BMI.

In 1998, Frank founded the SMARTRAQ (Strategies for Metropolitan Atlanta's Regional Transportation and Air Quality) research program to assess land use and transportation policies that might reduce vehicle emissions in 13 counties around Atlanta. SMARTRAQ includes telephone interviews on demographic characteristics, and a travel diary in which respondents record their mode of travel, origin, destination, purpose and time of trip over two days. For this project, researchers used 2001–2002 data from those sources to assess the impact of food and activity environments on BMI.

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RWJF has developed three integrated strategies to reverse the childhood obesity epidemic: evidence, action and advocacy.


Investments in building the evidence base will help ensure that the most promising efforts are replicated throughout the nation.

The Foundation's major research efforts in this area—Active Living Research (also see Grant Results), Healthy Eating Research and Bridging the Gap—are contributing to the nation's collective knowledge about the changes to policies and to community and school environments that are most effective in increasing physical activity and improving the nutrition of children.

RWJF also seeks to evaluate innovative approaches under way in states, schools and communities across the country. Examples include:


RWJF's action strategy for communities and schools focuses on engaging partners at the local level, building coalitions and promoting the most promising approaches.

  • RWJF is working with the Food Trust, a Philadelphia-based advocacy organization whose mission is to ensure that everyone has access to affordable, nutritious food. The Food Trust has been bringing supermarkets back to underserved communities in Pennsylvania and is working with RWJF to replicate those results nationwide.
  • RWJF also is working closely with the Alliance for a Healthier Generation (a partnership of the American Heart Association and the William J. Clinton Foundation) to support its efforts to improve nutrition, physical activity and staff wellness in schools nationwide.


As staff learns from the evidence and action strategies, RWJF shares results by educating leaders and investing in advocacy, building a broad national constituency for childhood obesity prevention.

  • RWJF supported the National Governors Association when Arkansas Governor Mike Huckabee designated wellness in schools, homes and workplaces as his Chairman's Initiative for 2005–06.
  • Through Leadership for Healthy Communities: Advancing Policies to Support Healthy Eating and Active Living, RWJF works closely with national organizations that represent elected and appointed officials—such as the National Conference of State Legislatures and the U.S. Conference of Mayors—to educate their members about successful approaches to increasing physical activity and healthy eating among children. The goal is to support leaders and decision-makers in their efforts to create healthier states, counties and cities.

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Under this grant, researchers from Lawrence Frank and Company analyzed household travel data collected by the SMARTRAQ program in 2001–2002 to:

  • Document how distance of travel for food varies by gender, race/ethnicity, neighborhood characteristics and type of food outlet.
  • Examine how diet-related and physical activity-related behaviors are associated with BMI among men and women and among Whites and Blacks.
  • Create a model to predict the availability of healthy food choices and affordable prices in four types of food outlets in four Atlanta neighborhoods.

Documenting Distance of Travel for Food

Frank and colleagues analyzed data from the travel diaries of those 2001–2002 SMARTRAQ participants whose diaries indicated they traveled for food. They categorized participants into three groups:

  • Youth ages 5 to 18, probably not working and living at home
  • Adults of working ages 25 to 55
  • Adults age 65 or older, likely entering retirement.

Using the travel diary data and telephone survey results, the researchers documented the following:

  • Characteristics of individuals and households: income, household size, number of vehicles owned, gender, race, education, obesity status and work status.
  • Walkability of the neighborhood: the array of services that residents could feasibly walk to within one kilometer of their homes.
  • Characteristics of trips: day of the week, point of origin, point of destination, type of food source and distance. Food sources included regular and super grocery stores, fast food and sit-down restaurants and coffee shops/bakeries.

Examining the Relative Contributions of Diet and Activity in Explaining BMI

Frank analyzed data from about 10,000 SMARTRAQ male and female participants who:

  • Also completed the International Physical Activity Questionnaire (IPAQ), a telephone or written questionnaire that gathers information about physical activity within the previous seven days.
  • Were 20-65 years of age.
  • Were White or Black.

Drawing from SMARTRAQ data and IPAQ responses, Frank analyzed:

  • Neighborhood characteristics using the walkability index.
  • Distances traveled to fast food outlets or grocery stores using travel diary records.
  • Physical activity using the IPAQ responses.
  • Demographic and food outlet descriptions using SMARTRAQ survey responses.

Creating a Model to Predict the Presence of Healthy Food Choices in Various Outlets

Researchers had planned to analyze data from the RWJF-funded Nutrition Environment Measures Survey (NEMS) to predict the availability of healthy and affordable food choices in sit-down and fast food restaurants, grocery and convenience stores in four Atlanta neighborhoods covered by SMARTRAQ (ID#s 050312, 053852 and 059992).

Frank wanted to create a model that would allow measures from a sample of food outlets—featuring on-site staff observations—to be generalized to unobserved outlets of the same type. (See Grant Results on the first grant for details.)

However, this analysis proved infeasible to complete during the project, partly because creating a model would have required observing many more food outlets or developing alternative strategies to obtain accurate estimates within each neighborhood.

See After the Grant for details of ongoing work to develop this model.

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Distance of Travel to Food by Gender, Race/Ethnicity, Neighborhood and Food Source Characteristics

Frank and colleagues reported the following findings in an unpublished article entitled "Investigating Neighborhood Food Environments: How Far Do People Travel for Food?":

  • People in all three age groups traveled farthest to go to sit-down restaurants and superstores. They traveled the least far for grocery stores and coffee shops.
  • People who walked for food regardless of type, walked less than one mile. More than 93 percent of trips were by car. This suggests that high levels of density and land use mix may be required to substantially boost walking trips for food.
  • Median distances to most stores ranged from three to five miles, distances considered feasible for bicycling.
  • Visits to fast food restaurants often do not start from home, highlighting the importance of studying the proximity of fast food outlets to schools and work places. Only 18.6 percent of trips taken by people over age 18 started from home, compared to 35.1 percent of those taken by people age 18 and below.
  • Travel patterns differed across age groups:
    • When 5- to 18-year-olds started their trip from a walkable neighborhood, they appeared to go to fast food outlets more often.
    • There was no distinct pattern of travel among people ages 25–55.
    • People age 65 or older living in a walkable neighborhood appeared more likely to visit a grocery store and less likely to visit a fast food outlet.
  • There were not large differences in the distances traveled to food outlets by Whites and non-Whites or by high- and low-income households.

The Relative Contributions of Diet-Related and Physical Activity-Related Behaviors in Explaining BMI among Men and Women and Whites and Blacks

Frank and colleagues reported the following findings in an article entitled "Food Outlet Visits, Physical Activity, and Body Weight: Variations by Gender and Race-Ethnicity" published in the British Journal of Sports Medicine. The abstract is available online.

  • Though physical activity, walkability and type of food outlet all contributed modestly to explaining differences in BMI, the relative contribution of these factors differed significantly across gender and race/ethnicity.
  • Among women:
    • Higher BMI was associated with visits to fast food restaurants.
    • Lower BMI was associated with grocery store visits and physical activity.
    • BMI did not decrease with walkability of the neighborhood.
    • Demographic factors—race, income, age, education, number of children, number of household members, number of vehicles owned—accounted for 12.7 percent of variance in BMI.
  • Among men:
    • BMI was not associated with where men went for food.
    • Lower BMI was associated with walkability of the neighborhood and overall physical activity.
    • Demographic factors accounted for only 5.5 percent of variance in BMI.
  • Factors associated with BMI among Whites and Blacks overall:
  • Among Blacks:
    • Lower BMI was associated with visits to grocery stores.
    • Demographic factors accounted for 5.6 percent of variance in BMI. Education, employment, size of household and number of children played the largest role in predicting BMI—people with [an undergraduate college] "degree, fewer in the household, but with two or more children and employed were less likely to be obese."
  • Among Whites:
    • Higher BMI was associated with visits to fast food restaurants.
    • Demographic factors accounted for 10.7 percent of variance in BMI. Every demographic factor except employment status was a highly significant predictor of BMI.
  • Among both:
    • Meeting moderate physical activity guidelines (30 minutes a day of activities such as brisk walking, raking leaves or gardening) was associated with lower BMI in both Whites and Blacks, but walking was associated with a lower BMI only among Whites.


Researchers reported the following limitations to the study:

    • Relies upon self-reports of trips and activities.
    • Does not capture individual dietary information.
    • Includes only two days of travel diary.
    • Does not examine the range or quality of stores within feasible travel distance.
  • Some types of food sources might have been mistakenly misclassified, such as a sit-down restaurant for a fast food restaurant.
  • The study did not capture some kinds of food intake patterns. For example, another household member may have bought food at a grocery store or fast food outlet.

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Frank reported the following in the British Journal of Sports Medicine article and in an interview:

  • "We cannot construe lower levels of walking among women or Blacks to mean that walking does not matter to them. Other factors may influence whether people walk in otherwise walkable neighborhoods. For example, we believe that in Atlanta, the more walkable neighborhoods are located in higher crime areas and for women in particular, the neighborhood has to be safe. In addition, it is possible that women and Blacks have more demands on their time, making it harder for them to walk to purchase food." (Interview)
  • "Although demographic factors explain a lot of the variance in BMI levels, it is difficult or impossible to change these factors with interventions." (Article)
  • Considerable differences appear to exist between how physical activity and types of food outlets visited contribute to body weight across genders and between Whites and Blacks. "On the surface, it would appear that reductions in BMI may be most achievable through interventions that increase access to sit-down restaurants and grocery stores for women and blacks, and through increased levels of walkability and physical activity in men." (Article)

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Researchers are continuing to work on a model capable of predicting food choices and prices for different types of food outlets. They developed several options to arrive at the model:

  • Increasing the number of observed food outlets to a size that would assure validity. This would require observations of about 300 outlets per category.
  • Combining types of outlets, such as grocery and convenience stores, in order to increase the sample size for each group.
  • Using selected nutrition environment measures, such as availability of any healthy entrees, rather than overall scores as the outcome variable.

They expect to complete this analysis in spring 2009.

Lawrence Frank and Company received another grant from RWJF (ID# 066050) for $348,288 that will allow for the duplication of the tool used to assess food outlet environments to assess the routine health impacts of land development, transportation investment decisions and the selection of infrastructure projects.

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Integrated assessment of how food and activity environments are related to body mass index in adolescents and adults


Lawrence Frank and Company (Seattle,  WA)

  • Amount: $ 87,963
    Dates: May 2006 to June 2007
    ID#:  053915


Lawrence D. Frank, Ph.D.
(604) 738-1588

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(Current as of date of this report; as provided by grantee organization; not verified by RWJF; items not available from RWJF.)


Frank L, Kerr J, Saelens B, Sallis J, Glanz K and Chapman J. "Food Outlet Visits, Physical Activity, and Body Weight: Variations By Gender and Race-Ethnicity." British Journal of Sports Medicine, published online in November 2008. Abstract available online.

Kerr J, Frank L, Saelens B, Glanz K, Sallis J and Chapman J. "Investigating Neighborhood Food Environments: How Far Do People Travel for Food?" Unpublished.

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Report prepared by: Mary Nakashian
Reviewed by: Pamela Lister
Reviewed by: Molly McKaughan
Program Officer: C. Tracy Orleans