University of Minnesota School of Public Health PI: Melissa Laska, PhD, RD Co-I’s: Caitlin Caspi, ScD; Lisa Harnack, DrPH, RD; Darin Erickson,

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Presentation transcript:

University of Minnesota School of Public Health PI: Melissa Laska, PhD, RD Co-I’s: Caitlin Caspi, ScD; Lisa Harnack, DrPH, RD; Darin Erickson, PhD Project Coordinator: Stacey Moe, MPH Impact of a Local Staple Food Ordinance on Healthy Food Access 1

2008: Also includes meat, fish or vegetable proteins. 2015: Also includes meats, fish or vegetable proteins (expanded); eggs; canned beans; dried peas, beans, lentils; 100% juice. Minneapolis Staple Food Ordinance Bread, cereal & grains ≥3 varieties of bread or cereal, ≥2 fresh. 4 containers of WG cereal in ≥3 varieties AND 5# of WGs in ≥3 varieties (including bread, tortillas, rice). Dairy & substitutes ≥3 varieties, ≥2 fresh. 5 gallons of unsweetened cow’s milk in ≥2 varieties: skim, 1%, 2%, plain soy or other plain milk alternative. Fruits & vegetables ≥5 varieties of fresh. 30# in ≥7 varieties, with ≥5 varieties fresh. Examples of ordinance requirements 2

STORE Study: Evaluation timeline Spring ‘14 Fall/Winter ‘14 Fall ‘15 Spring ‘16 Spring ‘17 Pre-baseline assessment: store audits, operator interviews, customer intercept surveys. Baseline: audits, interviews, intercepts, home assessments Revised policy effective; no enforcement. 12 month post-policy evaluation. 24 month post-policy evaluation. 4-6 month post-policy evaluation. April ‘15 Policy enforcement begins. April ‘16 3

Project Goals In evaluating the ordinance, our aims here are to assess: Aim 1: Disparities in changes to healthy food availability in in small- to mid-sized stores located in low versus high SES neighborhoods. Aim 2: Disparities in changes in perceptions of healthy food demand in low versus high SES neighborhoods of the city. Aim 3: Disparities in pricing of healthy items in small food stores, compared with pricing in local supermarkets. 4

Strategies Baseline sample: – 140 non-supermarket, non-WIC participating food stores. Represents a random sample of stores drawn from administrative lists of licensed grocery stores in Minneapolis and St. Paul (control community). – Nearest supermarket. Data collection: – In-store audits using a NEMS-adapted tool. – Abbreviated audit of pricing data administered in nearest supermarkets. – Structured interviews with store owners/managers. 5

Progress To Date Baseline data collection completed. Short-term goals: – Data entry and processing – Preliminary analyses examining cross-sectional, pre- policy disparities – On-going feedback from from our Community Advisory Committee 6

Ideas for Collaboration Healthy Retail Working Group Can draw from our experiences in the RWJF/HER Corner Store Working Group. Sharing lessons learned and best practices. Opportunities for multi-site data collection. – Example: assessments of outdoor advertising. 7