March 2009

Grant Results

SUMMARY

From December 2006 to January 2008, a research team at the Urban Institute in Washington analyzed the relationship between community characteristics and the prevalence of childhood obesity, and used the results to predict the risk for childhood obesity in states and communities across the country.

Among the community factors included in the analysis were racial/ethnic makeup, income and education levels, employment characteristics, family composition, housing stock and access to supermarkets.

The purpose was to increase understanding of childhood obesity at the state and local levels so that policy-makers and funders could more readily target resources to geographic areas where children are most at risk.

Key Results

  • The Urban Institute produced a report, available on its Web site, with a series of maps and tables predicting the relative risk for childhood obesity in all 50 states and within communities across each state.

Key Findings
Among the report's findings:

  • Children ages 6 to 17 are estimated to be at above-average risk for obesity in 34 percent of the nation's census tracts and are at the highest risk for obesity in 6.5 percent of the tracts.
  • Communities where childhood obesity is predicted to be highest face disadvantages across multiple dimensions. For example, 40 percent of the children living in census tracts at the highest risk for childhood obesity were living in poor households, compared to 31 percent in tracts at above-average risk and less than 10 percent in tracts at average or below-average risk.
  • The community indicators that proved most influential in determining a child's probability of being obese were demographic characteristics, household structure and the education and English language proficiency of the population in the child's community.

Conclusions
In their report, the researchers conclude:

  • Strategies to address childhood obesity in communities at greatest risk will be most effective if they recognize the context of the underlying community problems and tailor programs to local circumstances.

Funding
The Robert Wood Johnson Foundation (RWJF) funded the solicited project with a $166,916 grant from December 2006 to January 2008.

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THE PROBLEM

The prevalence of overweight among American children and adolescents almost tripled between the late 1970s and the early 2000s. By 2003–2004, one in every six children (17.1 percent), ages 2–19, was overweight, according to national survey data collected by National Center for Health Statistics of the federal Centers for Disease Control and Prevention (CDC).

While the magnitude of the problem at the national level was documented, no single data source provided measures of childhood obesity for all states and individual communities.

The Urban Institute

The Urban Institute — a nonprofit economic and social policy research organization in Washington — has 10 policy centers, including one that addresses public health issues and another that concentrates on urban housing and neighborhood policies.

In 2006, RWJF asked the Urban Institute to use its resources to predict the risk for childhood obesity in communities across the country.

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RWJF STRATEGY

Reversing the childhood obesity epidemic is a major goal of RWJF. Its strategies include investing in research that will help ensure implementation and replication of the most promising approaches to the obesity problem.

RWJF was interested in filling the gap in state and local data about childhood obesity. A better understanding would help policy-makers and funders target resources to geographic areas where children are most at risk, RWJF staff believed.

See the RWJF Web site for more information on RWJF's childhood obesity funding strategy.

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THE PROJECT

From December 2006 to January 2008, a research team at the Urban Institute analyzed the relationship between community characteristics and the prevalence of childhood obesity, and used the results of the analysis to predict the risk for childhood obesity in all 65,443 census tracts across the country.

Among the community factors included in the analysis were racial/ethnic makeup, income and education levels, employment characteristics, family composition, housing stock and access to supermarkets.

RWJF supported this work with a $166,916 grant (ID# 059831). Sharon K. Long, Ph.D., principal research associate of the Urban Institute's Health Policy Center, directed the project.

Methodology Overview

The research team based its analysis on two types of data:

  • Child height and weight data from three national health surveys sponsored by agencies of the U.S. Department of Health and Human Services. Two of the surveys reported data by census tracts and one by ZIP codes.
  • Data on community demographics, household structure, income, education, supermarkets per capita and other factors obtained from various national sources. These included the 2000 census and databases maintained by government agencies ranging from the U.S. Department of Education to the FBI.

The data focused on children ages 6 to 17.

See Appendix 1 for the definition of childhood obesity used in the study, and sources of data.

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RESULTS

  • The Urban Institute published Mapping the Childhood Obesity Epidemic: A Geographic Profile of the Predicted Risk for Childhood Obesity in Communities Across the United States. The December 2007 report submitted to RWJF — and made publicly available on the Urban Institute Web site — provided a series of maps and tables predicting the relative risk for obesity for children in all 50 states and within communities within each state.

Findings

Mapping the Childhood Obesity Epidemic included the following findings:

  • Children ages 6 to 17 are at an above-average risk for obesity in 34 percent of all census tracts and are at the highest risk for obesity in 6.5 percent of tracts.
    • The states with the highest proportions of census tracts at above-average risk are clustered in the southeast, with the highest proportion in Mississippi (77 percent). The at-risk proportions were also high in Hawaii (65 percent) and the District of Columbia (66 percent).
    • On the other end of the scale, children were predicted to be above-average risk in only 2.3 percent of Wyoming's census tracts and 3.4 percent of Vermont's. Neither state had any tracts predicted to be at highest risk.
  • Communities where childhood obesity is predicted to be highest face disadvantages across multiple dimensions. For example:
    • The child poverty rate in census tracts at highest risk was nearly 40 percent compared to 31 percent for tracts at above-average risk. The child poverty rate was less than 10 percent in tracts with average or below-average risk for childhood obesity.
    • The average median household income was more than $30,000 per year higher in census tracts at average or below-average risk, compared to census tracts at the highest risk for obesity.
  • Compared to tracts at average or below-average risk for childhood obesity, tracts predicted to be at above-average or highest risk are more likely to have:
    • Minority residents.
    • Higher unemployment rates.
    • Higher proportions of children living in households headed by a non-parent.
    • Higher poverty rates.
    • Lower female labor force participation.
    • Lower education and income levels.
    • Lower homeownership rates.
  • The community indicators that proved most influential in determining a child's probability of being obese were the demographic characteristics, household structure and the education and English language proficiency of the population in the child's community.

    The most significant variables were the percentage of:
    • Children who lived in households headed by someone other than a parent.
    • Adults (age 25 and over) without a high school degree in the community.
  • Among the variables that demonstrated an influence on child obesity, neighborhood characteristics — whether based on census tracts or ZIP codes — had more influence than county-level characteristics.

Limitations

In its report, the study noted the following:

  • Because the team's risk estimates for childhood obesity were based on national data and modeling, the predictions do not "capture unique aspects of states and local communities that may exacerbate or mitigate the risk," according to the project director.

    For example, the analysis did not reflect any impact of Arkansas's program to combat childhood obesity on the likelihood of obesity in that state. Similarly, the team's predictions did not register the impact of Philadelphia's Food Trust program, which seeks to increase access to nutritious food. See Web site to access the report.
  • The study team was unable to identify any data sources that could be used to test the accuracy of the predicted risk. The team looked for actual body mass index (BMI) data against which it could test its predictions, but the few potential sources proved to be unusable. Body mass index is a measure of how much a person weighs related to their height.

    For example, Arkansas collects student BMI data as part of a statewide initiative, but the study team could not adequately compare these to the data it collected by geographic region.

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CONCLUSIONS

The report said:

  • Strategies to address childhood obesity in communities at highest risk "will be most effective if they recognize the context of these underlying (community) problems and tailor programs to the local circumstances of the children at risk."

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AFTER THE GRANT

The report has helped to inform RWJF's strategy for addressing childhood obesity.

The study team explored the possibility of replicating the study using additional community measures and more recent child health survey data. As of December 2008, however, the team lacked funding to support continuation of the work, Long said.

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GRANT DETAILS & CONTACT INFORMATION

Project

Analysis of Geographic Patterns of Childhood Obesity

Grantee

Urban Institute (Washington,  DC)

  • Amount: $ 166,916
    Dates: December 2006 to January 2008
    ID#:  059831

Contact

Sharon K. Long, Ph.D.
(202) 261-5656
slong@ui.urban.org

Web Site

http://www.urban.org/UploadedPDF/411773_childhood_obesity.pdf

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APPENDICES


Appendix 1

(Current as of the time of the grant; provided by the grantee organization; not verified by RWJF.)

Definition of Obesity and Data Sources

In its December 2007 report (Mapping the Childhood Obesity Epidemic: A Geographic Profile of the Predicted Risk for Childhood Obesity in Communities Across the United States), the Urban Institute team described the study's methodology, including the following aspects:

Obesity Definition
While the definitions for overweight and obesity are well established for adults, there is less consistency in the use of the terms for children. The team used the definition of childhood obesity applied by the Institute of Medicine: A body mass index (BMI) at or above the 95th percentile of a fixed reference group of U.S. children of the same age and sex.

The Institute of Medicine defines overweight children as those with a BMI between the 85th and 95th percentile. The CDC uses a similar definition.

Data Sources
Child Height and Weight:
The team obtained child height and weight data from three national surveys sponsored by agencies of the U.S. Department of Health and Human Services:

  • 1988–1994 National Health and Nutrition Examination Survey, conducted by the CDC's National Center for Health Statistics.
  • 2000–2004 Medical Expenditures Panel Survey, cosponsored by the Agency for Healthcare Research and Quality and the National Center for Health Statistics.
  • 2003–2004 National Survey of Children's Health (NSCH), sponsored by the Maternal and Child Health Bureau of the Health Resources and Services Administration.

Community Characteristics: Using census data and various other sources, the team obtained nearly 500 community variables, which it grouped in nine general categories:

  • Demographic variables — e.g., the age, race and citizenship status of the population in the community.
  • Measures of household structure — e.g., share of children living in two-parent, single-parent and non-parent households.
  • Education and language variables — e.g., percent of the adult population with a high school degree and percent of the population with poor English skills.
  • Employment status — e.g., the unemployment rate and the labor force participation rate for women.
  • Income and poverty — e.g., the poverty rate, median family income and percent of households on public assistance.
  • Housing — e.g., homeownership rate, vacancy rates and measures of overcrowding.
  • Health environment — e.g., infant mortality rate and the percentage of the population that is uninsured.
  • Food environment — e.g., number of grocery stores and restaurants per capita.
  • Physical environment — e.g., pedestrian fatalities in auto accidents, weather patterns, number of bowling alleys per capita and crime rates.

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BIBLIOGRAPHY

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

Reports

Long SK, Hendey L and Pettit K. Mapping the Childhood Obesity Epidemic: A Geographic Profile of the Predicted Risk for Childhood Obesity in Communities Across the United States. Washington: Urban Institute, December 20, 2007. Available online.

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Report prepared by: Michael H. Brown
Reviewed by: Karyn Feiden
Reviewed by: Molly McKaughan
Program Officer: Laura C. Leviton
Program Officer: Celeste Torio