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Food Accessibility in Wisconsin: Comparison of Self-Report, Direct Observation, and Mapping Data ResultsKey Findings Results Conclusions Background Results.

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Presentation on theme: "Food Accessibility in Wisconsin: Comparison of Self-Report, Direct Observation, and Mapping Data ResultsKey Findings Results Conclusions Background Results."— Presentation transcript:

1 Food Accessibility in Wisconsin: Comparison of Self-Report, Direct Observation, and Mapping Data ResultsKey Findings Results Conclusions Background Results Research Objectives Study Sample and Methods Alina McIntyre 1, Maggie Grabow 2, Kristen Malecki 2, Ana Martinez-Donate 2, Jonathan Patz 2 1) West High School, Madison, WI; 2) University of Wisconsin, Madison, WI West High School 1)To identify the actual distance that people travel to go to the grocery store and to better understand why SHOW participants choose to shop at that certain grocery store 2)To assess SHOW study participants’ perceptions of the distance to the grocery stores where they do most of their shopping 3)To identify potential disparities among residents living in Wisconsin relating to access to grocery stores An emerging area of public health interest is the extent to which the nutrition environment (places where people eat and/or buy food) influences eating patterns. However, there is limited information about how the accessibility of food options in stores and restaurants contributes to obesity rates and other adverse outcomes, particularly in diverse populations. The purpose of this study is to assess perceptions of food store availability and proximity, actual food store availability, and disparities within the nutrition environment in Wisconsin. Data analyzed in this study were previously collected from two studies of Wisconsin residents: 1) the Survey of the Health of Wisconsin (SHOW); and 2) the Assessment of Nutritional Environment of Wisconsin Communities (ANEWC). Gender (n= 338) Female 59% Age (n=380) Years, mean48 Education (n=379) Average highest schooling/degree Associate degree Urbanicity (n=337 ) Urban 64% Suburban 19% Rural 16% Income (n=364) Midpoint household income $26,254 Race (n=379) White88% Non-white12% Data previously collected in 2009-2011, from a random sample of households surveyed in Wisconsin (N=381) Data imported into ArcGIS; food store addresses geocoded to find latitude and longitude Network Analyst and manual mapping used to determine street network distance between participant households and grocery stores Microsoft Excel and SAS used for descriptive statistical analysis and Chi-square tests used to compare participant demographics Further research is needed to evaluate if increasing access to stores that sell fresh fruits and vegetables, or healthy foods, increases consumption of those foods and leads to better health outcomes. As food environments are controlled by a variety of public and private interests, engaging a wide range of stakeholders in local communities will be an important step in developing and implementing public health and educational interventions to reduce potential disparities. Participants with an annual income less than $25,000, who are non-white, or live in urban areas, are more likely to live in closer proximity to a grocery store compared to those with higher incomes, those who are white, or those who live in Wisconsin rural or suburban areas (Table 1). Participants with incomes greater than $25,000 traveled up to twice as far from their home to go to a store, rather than choose a grocery store within close proximity (Table 1). Freshness of fruits and vegetables was the most frequent reason all participants gave for shopping at their chosen grocery store (Table 3). Price and convenience were the second and third most frequent reasons indicated for shopping at a chosen grocery store (Table 3). White (n=294) Non- White (n=35) High School (n=47) College (n=115) Graduate School (n=35) <25,000 (n=79) 25- 44,900 (n=54) 45- 74,900 (n=77) 75- 124,900 (n=62) >125,000 (n=47) Urban (n-182) Suburban (n=58) Rural (n=50) Distance to grocery store where participants shop Average (miles) Standard deviation 7.39 7.46 2.45 1.83 7.80 9.01 7.01 6.96 5.30 6.26 3.74 4.07 7.56 8.72 5.00 4.86 6.62 7.24 6.11 6.10 3.07 3.26 9.44 6.54 10.52 8.81 P value 0.0065 0.2954 0.0001 0.0003 Distance to their closest grocery store Average (miles) Standard deviation 3.94 2.39 1.59 8.53 3.01 3.36 4.04 4.84 2.23 2.73 1.76 1.64 2.66 2.78 2.37 1.87 2.90 2.91 2.95 2.56 1.49 1.07 4.34 2.88 3.97 3.08 P value 0.00010.0023 0.0001 Table 1. Distance to grocery store where participants shop vs. distance to their closest grocery store Participant h ouseholds # SHOW food stores # ANEWC food stores Closest food store Preferred food store RACEURBANICITY HIGHEST DEGREE INCOME Figure 1. Beaver Dam, WI, example: Participant households and food store locations Wisconsin Food Stores Pick ‘N Save26% Woodman’s13.6% Walmart10.1% County Market7.3% Piggly Wiggly4.8% Festival Foods4.4% Copp’s3.8% Table 2. Top food stores where participants report doing most of their grocery shopping (n=315 ) Freshness of fruits and vegetables39.5% Price of foods26.8% Convenience19.7% Quality of meats and seafood7.4% Organic foods available1.9% Large selection1.9% Table 3. Most frequent reasons participants report for shopping at their preferred food store (n=324) Select References: Cummins et al. 2002, BMJ 325 (7631); Glanz et al. 2007, Journal of Preventive Medicine 32 (4); Nieto et al. 2010, BMC Public Health 10:785; Richardson et al. 2012, BMJ Open 2 (2). Map Legend Household 1 Closest 3.3 Preferred 5.5 Household 2 Closest5.4 Preferred5.9 Food Store Distance (miles)


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