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CX 3 Tier 1/Mapping Training An investment in neighborhoods December 2011 Valerie Quinn, M.Ed, Network for a Healthy California.

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Presentation on theme: "CX 3 Tier 1/Mapping Training An investment in neighborhoods December 2011 Valerie Quinn, M.Ed, Network for a Healthy California."— Presentation transcript:

1 CX 3 Tier 1/Mapping Training An investment in neighborhoods December 2011 Valerie Quinn, M.Ed, Network for a Healthy California

2 Research: Clear connection between neighborhood factors & health outcomes

3 Neighborhoods Matter

4

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6 Store Marketing Include Walgreen’s picture?

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8 CX 3 : Project Background Objectives: 1.Collect real-world data that accurately conveys neighborhood conditions 2. Activate consumers to improve food availability in low-income neighborhoods* Focused initiative with local health depts. Began 2006 (6 pilot sites) Collect neighborhood-level data using CX 3 standardized tools & methods Over 100 neighborhoods * >50% 185% FPL

9 CX 3 Sites CX 3 LOCAL HEALTH DEPARTMENTS Alameda (2006) ▲ San Bernardino (2006) ▲ Berkeley (2006) ▲ San Diego (2007) Contra Costa (2007) San Joaquin (2009) Humboldt (2011) San Mateo (2009) Kern (2006) ▲ Santa Barbara (2008) Long Beach (2009) Santa Clara (2006) ▲ Marin (2007) Shasta (2008) Monterey (2008) Solano (2007 Orange (2008) Sonoma (2008) Pasadena (2008) Stanislaus (2008) Riverside (2006/2011) ▲ Tulare (2009) Sacramento (2007) Ventura (2007) Yolo (2011) ▲ Pilot sites

10 Data Uses Design/tailor nutrition education interventions Expose disparities Resource allocation Engage residents in advancing change Real-world data to create healthier neighborhoods –City/Co Planners, Redevelopment agencies, inform General Plan, health impact, etc. Program evaluation

11 Neighborhood Focus

12 Top Picks

13 CX 3 – How does it work? Standardized Indicators Tools & Methods Real world data 4 STEPS 1. Compile localized data 2. Set priorities based on data 3. Implement strategic, community-focused action plan 4. Evaluate progress over time

14 Neighborhood Marketplace How are the consumers influenced by neighborhood in their food choices? Collecting neighborhood nutrition data… Are healthy food choices available and accessible to residents of low-income neighborhoods? What is the density of FF outlets in neighborhood and around schools? How much and what are the types of healthy/unhealthy marketing messages on billboards around schools? Is it safe to walk to store? Is it accessible? What kinds of food are available from emergency food outlets? Nutrition education? And more!

15 Today’s Q’s Supermarket Access Supermarket Access Transit Markets Around Schools Farmers’ Markets Fast Food Outlets

16 Tier 1 Tier 2 Community Assets

17 Building a Neighborhood Profile… …to inspire community action!

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19 Key to success: Community involvement

20 CX 3 Benefits Advances local change – Proven! Puts local groups at forefront for obesity prevention Standardized indicators, measures, tools Appealing to funders

21 CX 3 Team Valerie Quinn, M.Ed. Network 916.552.9908, valerie.quinn@cdph.ca.govvalerie.quinn@cdph.ca.gov Alyssa Ghirardelli, RD, MPH, Network 916.449.5342, alyssa.ghirardelli@cdph.ca.govalyssa.ghirardelli@cdph.ca.gov Lynn Moreno - Fuhrman, - Network 916.552.9862, lynn.moreno@cdph.ca.govlynn.moreno@cdph.ca.gov Chris Bilbrey – Network 916.319.9809, chris.bilbrey@cdph.ca.govchris.bilbrey@cdph.ca.gov Network Program Managers CX 3 Local Health Departments YOU!!!

22 Real Freshness!

23 Neighborhood Selection

24 CX 3 Neighborhood Selection Don’t take it lightly! Investment in Community, Future So… ponder, connect, discuss!

25 CX 3 Neighborhood Selection – cont. 4 Requirements 1.SNAP-Ed eligible census tracts (>50% at <185% FPL; aka dark blue zones)

26 CX 3 Neighborhood Selection – cont. BUT now required to use American Community Survey data. –Race/ethnicity data layers by 185% FPL due soon (early 2012)

27 CX 3 Neighborhood Selection – Cont. 2a. Pick 3 – 7 neighborhoods: Urban, rural, suburban, remote, dense... What mix do you want?

28 CX 3 Neighborhood Selection – Cont. 2b. Reassessing- Which ones did you implement interventions in? Must do those for program evaluation purposes.

29 CX 3 Neighborhood Selection – Cont. 3. “Recognized” Neighborhood

30 CX 3 Neighborhood Selection – Cont. 4. Middle or High School (preferred)

31 CX 3 Neighborhood Selection – Cont. If not using SNAP-Ed funding, #1 and 2 don’t apply. Do a middle/upper income neighborhood?

32 CX 3 Neighborhood Selection – Cont. Population Considerations –Level of Poverty –Racial/Ethnic Makeup –Geographic Diversity –Obesity rates –Comparison neighborhoods– upper income (if other funding sources)

33 CX 3 Neighborhood Selection – Cont. Program Considerations –Research/New Focus Area –Map More, Survey Fewer –Community Activism –Additional Program Resources, Partnerships or Similar Initiatives –Political Will –Other?

34 CX 3 Neighborhood Selection – Cont. Strategic, leveraging resources Building Healthy Communities grants- TCE foundation, 10 year commitment Community Transformation Grants- Several CA counties! Strategic Growth Council’s Sustainable Communities Planning grants http://sgc.ca.gov/selected_apps_2010.html

35 CX 3 Neighborhood Selection – Cont. Tip: Set up a special CX 3 planning team or workgroup to participate in making decisions about neighborhoods.

36 This material was produced by the California Department of Public Health’s Network for a Healthy California with funding from USDA SNAP, known in California as CalFresh (formerly Food Stamps). These institutions are equal opportunity providers and employers. CalFresh provides assistance to low-income households and can help buy nutritious foods for better health. For CalFresh information, call 877-847-3663. For important nutrition information, visit www.cachampionsforchange.net. Thank you!

37 Of CX 3 neighborhoods, which ones did you implement interventions? As program evaluation: – Required to reassess any neighborhood where conducted intervention work. – Comparison CX 3 neighborhood if possible (and no intervention work) – Data complexities, expecting more precise federal data in early 2012 (Race/ethnicity data layers by 185% FPL) Reassessing


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