Creating a replicable, valid cross-platform buffering technique: The sausage network buffer for measuring food and physical activity built environments

International Journal of Health Geographics

Dianne Neumark-Sztainer¹  Melanie Wall³  Nicole Larson¹  David Van Riper²  Ann Forsyth⁴ 

[1] Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA;Minnesota Population Center, University of Minnesota, Minneapolis, MN, USA;Division of Biostatistics, Department of Psychiatry and Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA;Department of City and Regional Planning, Cornell University, Ithaca, NY, USA

关键词: Utility;    Validity;    Reliability;    GIS;    Food environments;    Physical activity environments;    Obesity;    Network;    Buffer;   

Others  :  811704
DOI  :  10.1186/1476-072X-11-14

 received in 2012-02-11, accepted in 2012-05-03,  发布年份 2012

【 摘 要 】

Background

Obesity researchers increasingly use geographic information systems to measure exposure and access in neighborhood food and physical activity environments. This paper proposes a network buffering approach, the “sausage” buffer. This method can be consistently and easily replicated across software versions and platforms, avoiding problems with proprietary systems that use different approaches in creating such buffers.

Methods

In this paper, we describe how the sausage buffering approach was developed to be repeatable across platforms and places. We also examine how the sausage buffer compares with existing alternatives in terms of buffer size and shape, measurements of the food and physical activity environments, and associations between environmental features and health-related behaviors. We test the proposed buffering approach using data from EAT 2010 (Eating and Activity in Teens), a study examining multi-level factors associated with eating, physical activity, and weight status in adolescents (n = 2,724) in the Minneapolis/St. Paul metropolitan area of Minnesota.

Results

Results show that the sausage buffer is comparable in area to the classic ArcView 3.3 network buffer particularly for larger buffer sizes. It obtains similar results to other buffering techniques when measuring variables associated with the food and physical activity environments and when measuring the correlations between such variables and outcomes such as physical activity and food purchases.

Conclusions

Findings from various tests in the current study show that researchers can obtain results using sausage buffers that are similar to results they would obtain by using other buffering techniques. However, unlike proprietary buffering techniques, the sausage buffer approach can be replicated across software programs and versions, allowing more independence of research from specific software.

【 授权许可】

   
2012 Forsyth et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Brownson R, Hoehner C, Day K, Forsyth A, Sallis J: Measuring the built environment for physical activity: state of the art. Am J Prev Med 2009, 36(4s):s99-s123.
• [2]Cromley EK, McLafferty SL: GIS and Public Health. 2nd edition. Guilford Press, New York; 2011.
• [3]Daratech, Inc: GIS/geospatial industry worldwide growth slows to 1% in 2009. Directions Magazine 2009. http://www.directionsmag.com/pressreleases/gisgeospatial-industry-worldwide-growth-slows-to-1-in-2009/119103 webcite
• [4]Lytle L: Measuring the food environment: state of the science. Am J Prev Med 2009, 36(4S):S134-S144.
• [5]Burton NW, Haynes M, Wilson LAM, Giles-Corti B, Oldenburg BF, Brown WJ, Giskes K, Turrell G: HABITAT: A longitudinal multi-level study of physical activity change in mid-aged adults. BMC Public Health 2009, 9:76-87. BioMed Central Full Text
• [6]Forsyth A, Schmitz KJ, Oakes JM, Zimmerman J, Koepp J: Standards for environmental measurement using GIS: toward a protocol for protocols. J of Phys Activity and Health 2006, 3(S1):s241-s257.
• [7]Banerjee T, Baer W: Beyond the Neighborhood Unit. Plenum, New York; 1984.
• [8]Forsyth A, Oakes JM, Schmitz KH, Hearst M: Does residential density increase walking and other physical activity? Urban Stud 2007, 44(4):679-697.
• [9]Pasch KE, Hearst MO, Nelson MC, Forsyth A, Lytle LA: Alcohol outlets and youth alcohol use: exposure in suburban areas. Health Place 2009, 15:642-646.
• [10]Oliver LN, Schurman N, Hall AW: Comparing circular and network buffers to examined the influence of land use on walking for leisure and errands. Int J of Health Geographics 2007, 6:41. BioMed Central Full Text
• [11]Forsyth A: LEAN GIS (Local Environment for Activity and Nutrition) Protocols.Version 2.1. 2012. Http:// www.designforhealth.net/techassistance/trec. webcite
• [12]Neumark-Sztainer D, Wall M, Larson N, Story M, Fulkerson JA, Eisenberg ME, Hannan PJ: Secular trends in weight status and weight-related attitudes and behaviors in adolescents from 1999–2010. Prev Med 2012, 54:77-81.
• [13]Forsyth A, Lytle L, Van Riper D: Finding food: issues and challenges in using GIS to measure food access. J of Transp Land Use 2010, 3(1):43-65.
• [14]Liese AD, Colabianchi N, Lamichhane AP, Barnes TL, Hibber JD, Porter DE, Nichols MD, Lawson AB: Validation of 3 food outlet databases: completeness and geospatial accuracy in rural and urban food environments. Am J Epidemiol 2010, 172(11):1324-1333.
• [15]Metropolitan Council: Generalized land use 2010 for the Twin Cities Metropolitan Area. Metadata. 2010. http://www.datafinder.org/metadata/GeneralizedLandUse2010.htm webcite
• [16]Rockett H, Wolf A, Colditz G: Development and reproducibility of a food frequency questionnaire to assess diets of older children and adolescents. J Am Diet Assoc 1995, 95:336-340.
• [17]Rockett H, Breitenbach M, Frazier A, Witschi J, Wolf A, Field A, Colditz G: Validation of a youth/adolescent food frequency questionnaire. Prev Med 1997, 26:808-816.
• [18]Godin G, Shepard R: A simple method to assess exercise behavior in the community. Can J of Appl Sport Sciences. 1985, 10(3):141-146.
• [19]Sallis JF, Boone MJ, Roby JJ, Mycale FG, Nelson JA: Seven-day recall and other physical activity self-report in children and adolescents. Med Sci Sports Exec 1993, 25:99-108.
• [20]Chen K, McAneney J, Blong R, Leigh R, Hunter L, Magill C: Defining area at risk and its effect on catastrophic loss estimation: a days metric mapping approach. Appl Geog 2004, 24:97-117.