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H Community Intervention Resources Included in this appendix: •  ABLE H-1 Description of Selected Community-Level Obesity Prevention Initiatives with T Population-Level Results •  ABLE H-2 Description of Selected Community-Level Obesity Prevention Initiatives: T In Progress or No Population-Level Measurement • TABLE H-3 Selected Tools for Evaluating Community Obesity Prevention Initiatives • Evaluations Illustrating Best Practices for Measurement and Design — Cultural Competence and Photovoice — Logic Model Design Examples — Causal Modeling: The Healthy Communities Study — A Potential Regression-Discontinuity Evaluation 421

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TABLE H-1 Description of Selected Community-Level Obesity Prevention Initiatives with Population- Level Results (n=17) Initiative Target Population/ (Time period) Design Intervention Evaluation Methods Results 5-2-1-0 Let’s Go! Setting: Greater Community-level Parent surveys from Increased prevalence (AHRQ Health Portland, ME environmental and 2007-2011 reporting of targeted behaviors Care Innovations (Community, US) messaging strategies program awareness based on parent self- Exchange, 2012h) Target population: targeting physical and proxy report of reported data (2009-2011) Children/adolescents activity, fruits and children’s behavior Design: Pre/post vegetables, sugary drinks, screen time Allegiance Health— Setting: Jackson, MI Health partnership Pilot evaluation of Participants managed Health Improvement (Community, US) efforts among worksite wellness stress better, avoided Organization Target population: patients, physicians, component; tracking weight gain, controlled (AHRQ Health Adults, children/ employers, schools, of employee blood pressure and Care Innovations adolescents faith-based participation health cholesterol, avoided Exchange, 2012d) Design: Pre/post organizations, the status measures sick days, and reduced (2000-)a health system, and overall health risk the health plan Arkansas Obesity Setting: Arkansas Range of statewide School district No change in obesity Prevention Initiative (State-level, US) efforts to support surveys, stakeholder rates. Decreases in (University of Target population: local schools in interviews with student purchases from Arkansas for Children/adolescents making policy and parents and school vending machines; but Medical Sciences, Design: environmental leaders, BMIb no changes in soda 2011) Quasi-experimental change, including monitoring; sample consumption or visits (2000-2010) Coordinated School of 484 schools across to fast food restaurants Health and Safe the state Routes to School grants EPODE (Together Setting: 2 small A school-based Repeated, cross- Age-adjusted odds ratio Let’s Prevent towns in northern nutrition information sectional, school- for overweight Childhood Obesity) France (Community, program initiated in based survey for significantly lower in (Romon et al., 2009) Europe) 1992 followed by selected school years 2003 and 2004 (girls (1992-2004) Target population: several community- from 1992-2004 plus only). In 2004, the Children, 5-12 yrs based interventions BMI on all 5-12 yrs overweight prevalence old old children attending was significantly lower Design: Quasi- school; survey in than in the comparison experimental (post comparison towns in towns only comparison) 2004 only 422 Evaluating Obesity Prevention Efforts

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TABLE H-1 Continued Initiative Target Population/ (Time period) Design Intervention Evaluation Methods Results Five-a-Day Setting: Five Community-based 810 people in Knowledge increased Community economically interventions to pilot intervention as did access to fruits Evaluation Tool deprived communities improve fruit and communities and vegetables, but no (Ashfield-Watt et al., in England vegetable intake compared with 270 demonstrable effect on 2007) (Community, Europe) people participating total fruit and vegetable (2001-2005) Target population: in an unrelated intake Adults observational study Design: as controls Quasi-experimental Girls Health Setting: Memphis, Culturally Randomized to Memphis: no change Enrichment Multi- TN; Oakland, CA appropriate obesity prevention in BMI site Studies (GEMS) (Community, US) obesity prevention program intervention Oakland: changes in (Klesges et al., 2010; Target population: approaches or alternative self- BMI were not different Robinson et al., Preadolescent involving girls esteem building in the intervention 2010) overweight/obese and their parents, program versus the control (1999-2001) African American community centers group girls or YWCAs (Young Design: Randomized- Women’s Christian controlled trial Association), and (individual-level) schools Hartslag Limburg Setting: Maastricht Integrative Cohort study Adjusted difference (Schuit et al., 2006) region, Netherlands community-based comparing 5-year in mean change in (1998-2003) (Community, Europe) cardiovascular disease mean change in risk risk factors between Target population: prevention program factors between the intervention and Adults promoting a healthy intervention and reference group was Design: lifestyle reference area significant for BMI, Quasi-experimental waist circumference, total cholesterol, and serum glucose Healthy Eating, Setting: 14 low- Policy and Repeated cross- Findings from the Active Communities income communities environmental sectional surveys school survey combined and Central in CA (Community, interventions in of 400 randomly with environmental California Regional US) schools, worksites, selected 7th and assessments confirm Obesity Prevention Target population: health care 9th grade students that when students are Program (HEAC/ Youth and adults organizations, and from 13 HEAC exposed to healthier CCROPP) Design: the community at communities environments they are (Samuels & Quasi-experimental large and 6 out-of- more likely to make Associates, 2010) area comparison healthier choices (2007-2010) communities continued Appendix H 423

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TABLE H-1 Continued Initiative Target Population/ (Time period) Design Intervention Evaluation Methods Results Healthy Eating Setting: Rural Using elements of Pre- and post- Significantly increased Active Lifestyles Armstrong County, the national We Can! implementation levels of physical Together Helping PA program to help comparisons of activity and improved Youth (HEALTHY) (Community, US) children improve student behaviors, food choices made by Armstrong Target population: their nutritional including time students, who consume (AHRQ Health Children habits and engage in engaged in physical less “junk food” Care Innovations Design: Pre/post more physical activity activity, purchases of and more fruits and Exchange, 2012a) high-calorie foods, vegetables in school (2005-2009) and school cafeteria expenditures on fresh fruits and vegetables Healthy Hawks Setting: Communities Working with Pre/post BMI; caloric Significantly reduced program in Kansas children and their intake (self-reported caloric intake and BMI (AHRQ Health (Community, US) families to develop dietary data) among participants Care Innovations Target population: goals and strategies after 12 weeks Exchange, 2012f) Overweight children and establish a (2006-) Design: Pre/post healthier lifestyle. (individual-level) Community support built for recruitment and sustainability of changes Healthy Living Setting: Cambridge, Community-based Comparison of BMI BMI z-scoresc and Cambridge Kids MA effort to support the and fitness test results proportion obese (Chomitz et al., (Community, US) “5-2-1” guidelines: in a 1,900 students decreased, and mean 2010) Target population: 5+ servings of fruits tested at baseline and number of fitness tests (2004-2007) Students K-8 and vegetables, screen 3 years after program (0-5) passed increased. Design: Pre/post time <2 hours, 1+ implementation Obesity among all hour of exercise race/ethnicity groups declined Kaiser Permanente Setting: Three low- Policy and School-based surveys Improvements in Healthy Eating income communities environmental and Fitnessgramd physical activity Active Living in Northern CA interventions in measures of students behaviors found where Community Health (Community, US) schools, worksites, in intervention and high-dose interventions Initiative (HEAL- Target population: health care matched comparison were present in schools CHI) Youth and adults organizations, and communities; (Cheadle et al., Design: Quasi- the community at surveys of adults 2012a) experimental logic large using Interactive (2006-2010) model design Voice Response in intervention communities 424 Evaluating Obesity Prevention Efforts

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TABLE H-1 Continued Initiative Target Population/ (Time period) Design Intervention Evaluation Methods Results Nemours Delaware Setting: Delaware Statewide policy Statewide survey Leveling off of obesity Initiative (State-level, US) change; learning in 2006, 2008. rates statewide. (Chang et al., 2010) Target population: collaboratives; Fitnessgram Students in pilot PE (2006-) Children technical assistance measurement in schools were 1.5 times Design: to schools, child care, pilot school physical more likely to be in Quasi-experimental and primary care education (PE) Healthy Fitness Zone program (n=19) (indicator of physical fitness) New York City Setting: New York, Community-based Use of existing Decline in K-8 obesity (NYC) Department NY (Community, US) environment and surveys: NYC rate 5.5% between of Health obesity Target population: policy change efforts, Community Health 2006-2007 (21.9%) prevention initiative Students K-8, adults including schools, Survey, New York and 2010-2011 (NYC Obesity Task Design: Pre/post restaurants, grocery Youth Risk Behavior (20.7%). No report on Force, 2012) stores, hospitals, Survey, NYC adult progress (2002-) worksites Fitnessgram Paso del Norte Setting: El Paso, TX Community-based Population-based Children in 4th grade Foundation Obesity and surrounding area initiatives that representative survey had a 7.0% decrease Initiative (Coleman, (Community, US). included coordinated of school children in in obesity (statistically 2006; Coleman et Target population: school health Texas Health Service significant). Also al., 2005; Heath Adults, children program support Region 9/10 between related changes in and Coleman, 2003; Design: Pre/post (Coordinated 2000-2002 and behavior Hoelscher et al., (children) Approach to Child 2004-2005 (School 2010; Smith et al., Health [CATCH]), Physical Activity and 2005) plus community Nutrition [SPAN] (2002-2005) nutrition (Que survey) Sabrosa Vida) and activity (Walk El Paso) programs, and a media program for radio and TV Romp & Chomp Setting: Geelong, Community- Repeat cross- Significantly lower (de Silva-Sanigorski Australia wide, multisetting, sectional design with mean weight, BMI, et al., 2010) (Community, multistrategy a comparison sample and BMI z-scores (2004-2008) Australia) intervention focused in the intervention Target population: on community group. Significantly Young children (0-5 capacity building lower relative intake of yrs old) and environmental packaged snacks and Design: changes fruit juice Quasi-experimental continued Appendix H 425

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TABLE H-1 Continued Initiative Target Population/ (Time period) Design Intervention Evaluation Methods Results Shape Up Somerville Setting: Somerville, Comprehensive Non-randomized BMI z-scores decreased (Economos et al., MA community-level controlled trial: 3 by –0.1005 compared 2007) (Community, US) intervention involving intervention schools with children in the (2002-2005) Target population: children, parents, compared to 2 control communities Children grades 1-3 teachers, schools, city comparison schools. after controlling for Design: departments, health Pre/post BMI was covariates Quasi-experimental care providers primary outcome measure a Dates are approximate—often not explicitly included in articles or reports, and sometimes unclear if an initiative is ongoing. b Body mass index (BMI) is a number calculated from a person’s weight and height. BMI provides a reliable indicator of body fatness for most people and is used to screen for weight categories that may lead to health problems. c BMI z-scores indicates how many units (of the standard deviation) an individual’s BMI is above or below the average value for their age group and sex. d Fitnessgram is a fitness assessment and reporting program for youth developed in 1982, which measures aerobic capacity; body composition; and muscular strength, endurance, and flexibility. 426 Evaluating Obesity Prevention Efforts

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TABLE H-2 Description of Selected Community-Level Obesity Prevention Initiatives: In Progress or No Population-Level Measurement (n=20) Initiative Description Children and Neighbors Defeat Coalition around obesity led by a workplace-oriented wellness organization. Two Obesity (CAN DO) Houston pilot neighborhoods selected. Children aged 6-12 years targeted. Focus group (Correa et al., 2010) approach identified physical activity in one neighborhood (safety) and nutrition education in another. Collaborate for Healthy Weight National project of the National Initiative for Children’s Healthcare Quality and (NICHQ, 2012) the Health Resources and Services Administration bringing together primary care providers, public health professionals, and leaders of community organizations to work across traditional professional borders to address obesity at the community level. Communities Putting Prevention Fifty communities funded (39 obesity prevention) through a 2-year cooperative to Work (CPPW) agreement to reduce chronic disease related to obesity and tobacco using (CDC, 2013) the evidence and practice-based MAPPS.a This effort is expected to produce broad, high-impact, sustainable, health outcomes through policy, systems, and environmental change. Consortium to Lower Obesity in Obesity prevention coalition in Chicago promoting healthy and active lifestyles Chicago Children (CLOCC) for children through environmental changes, public education, advocacy, research, (Becker et al., 2008) outcome measurement, and program evaluation. Eat Smart, Move More North A statewide movement that promotes increased opportunities for healthy eating and Carolina physical activity wherever people live, learn, earn, play, and pray. Emphasizes policy (Eat Smart, Move More North and organizational change and evidence-based practices (e.g., media campaigns, Carolina, 2013) worksite interventions, body mass index [BMI] monitoring). Get a Life! Supports schools, churches, local governments, and employers in eight rural (Mississippi) Mississippi counties in addressing the area’s obesity epidemic. Key program (AHRQ, 2012c) elements include supporting local health councils, providing technical support, and regional planning. Go for Your Life Community-based interventions in six communities in regions of low socioeconomic (Victoria, Australia) (Haby et al., status. Planned and managed by primary care physicians/lead agencies, support 2009) from Department of Health Services and a state-wide evaluator. Healthy Alberta Communities Partnership between the Health Ministry and University of Alberta to promote Project (Alberta Provence, environmental approaches to obesity prevention. Canada) (Raine et al., 2010) Healthy and Active Communities Approaches include grantmaking, evaluation support, technical assistance for (Missouri) dissemination, policy assessment, and development of local, regional, and statewide (Hessel et al., 2010) collaborations to increase access to physical activity and nutrition through environmental, policy, and behavior change. continued Appendix H 427

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TABLE H-2 Continued Initiative Description Healthy Communities Study Five-year observational study of communities that aims to (1) determine the (NHLBI, 2013a) associations between community programs/policies and BMI, diet, and physical activity in children; (2) identify the community, family, and child factors that modify or mediate the associations between community programs/policies and BMI, diet, and physical activity in children; and (3) assess the associations between program/policies and BMI, diet, and physical activity in children in communities that have a high proportion of African American, Latino, and/or low-income residents. Healthy Eating Active Living Builds awareness among California city officials about the role of the physical Cities Campaign environment in promoting healthy habits and provides them with an array of (California) practical support for passing policies and resolutions to make it easier for residents (AHRQ, 2012g) to engage in healthy behaviors. Healthy Kids, Healthy Nationwide initiative in 50 communities pursuing policy and environmental change Communities strategies. (RWJF, 2013) IDEFICS Developed and implemented innovative community-oriented intervention programs (Identification and prevention for obesity prevention and healthy lifestyle primarily in children aged 2-10 years of dietary- and lifestyle-induced in eight European countries: Belgium, Cyprus, Estonia, Germany, Hungary, Italy, health effects in children and Spain, and Sweden. Eight matched pair communities per country. infants) (De Heneauw et al., 2011) Nutrition and Physical Activity Creating a cadre of early childhood health and wellness champions among state Self-Assessment for Child Care and local leaders and the professionals working with young children and families, (NAP SACC) and ensuring that children attending child care programs are served nutritious (Smart Start & The North foods, engage in physical activity, and have teachers modeling healthy behaviors.  Carolina Partnership for Children) (Iruka et al., 2009) Project FIT Collaboration between the public school system, local health systems, physicians, (Grand Rapids, MI) neighborhood associations, businesses, faith-based leaders, community agencies, (Eisenmann et al., 2011) and university researchers to develop a multi-faceted approach to promote physical activity and healthy eating. Recreation Rx Facilitates partnerships between physicians and recreation providers in underserved (San Diego, CA) communities to increase access to safe and structured activities. (AHRQ et al., 2012e) San Diego County Childhood Public/private partnership to reduce and prevent childhood obesity in San Diego Obesity Initiative County by creating healthy environments for all children and families through (San Diego County Childhood advocacy, education, policy development, and environmental change. Obesity Initiative, 2013) 428 Evaluating Obesity Prevention Efforts

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TABLE H-2 Continued Initiative Description Wayne County Health Partnership working with nonprofit groups to promote better nutrition and Department/Partnership for increased physical activity among preschoolers who attend 8 local child care the Children of Wayne County centers. (NC)/Goldsborough Parks and Recreation Department (AHRQ et al., 2012b) WE CAN! National movement that offers organizations, community groups, and health (NHLBI, 2013b) professionals a centralized resource to promote a healthy weight in youth through community outreach, partnership development, and media activities. W.K. Kellogg Foundation Food Creating communities that support access to locally grown, healthy, affordable and Fitness Initiative food, and safe and convenient places for physical activity and play, for families and (USDA, 2010) children. Nine communities nationwide funded for implementation. aMAPPS = Five evidence-based strategies, when combined, expected to improve health behaviors by changing community environments: Media, Access, Point of decision information, Price, and Social support/services. Appendix H 429

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TABLE H-3 Selected Tools for Evaluating Community Obesity Prevention Initiatives Source Description Website COLLECTIONS Active Living Research Tools to collect data on streets, schools, http://www.activelivingresearch.org/ parks, or other community settings toolsandresources/toolsandmeasures to see how well they support physical activity National Collaborative on Childhood Searchable database of diet and physical http://tools.nccor.org/measures Obesity Research (NCCOR) activity measures relevant to childhood Measures Registry obesity research Measures included to describe, monitor, and evaluate interventions— particularly policy and environmental interventions—and factors and outcomes at all levels of the socio- ecological model National Cancer Institute Risk Factor Tools for researchers, including dietary http://riskfactor.cancer.gov Monitoring & Methods surveys and environmental assessments SELECTED ENVIRONMENT MEASUREMENT TOOLS Environmental Assessment of Public Comprehensive direct observation http://www.seattlechildrens.org/ Recreation Spaces (EAPRS) assessment of the physical environments research/child-health-behavior- of parks and playgrounds, with an and-development/saelens-lab/ emphasis on evaluating physical measures-and-protocols elements and qualities with respect to their functionality or potential functionality (e.g., how a park or playground element is used or could be used by adults and children) Irvine Minnesota Inventory Measures a wide range of built https://webfiles.uci.edu/kday/public/ environment features that may affect index.html physical activity, especially walking Includes 160 items covering 4 domains: accessibility, pleasurability, perceived safety from traffic, and perceived safety from crime Nutrition Environment Measures Measures focus on surveying community http://www.med.upenn.edu/nems Survey (NEMS) and consumer nutrition environments; which include the type and location of food outlets (stores and restaurants); availability of healthful choices; and information, pricing, promotion, and placement of healthier food products 430 Evaluating Obesity Prevention Efforts

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TABLE H-3 Continued Source Description Website Communities of Excellence in Field surveys of neighborhood food http://www.cdph.ca.gov/programs/ Nutrition, Physical Activity & access cpns/Pages/CX3_T2_FieldSurveys.aspx Obesity Prevention (CX3) SELECTED POLICY MEASUREMENT TOOLS Bridging the Gap Research Informing Includes surveys of school district http://www.bridgingthegapresearch. Policy and Practices for Healthy policies and practices related to org/research/district_wellness_policies Youth childhood obesity and tools for coding school district wellness policies University of California, Berkeley Surveys include Nutrition Learning http://cwh.berkeley.edu/center/ Center for Weight and Health Environments, Actions, & Policies evaluation_tools Evaluation/Tools (Nutrition LEAP); Nutrition Services Questionnaire; and Survey of Child Care Providers WellSAT: Wellness School Assessment Online tool for quantitative assessment http://www.wellsat.org Tool of school wellness policies from the Yale Rudd Center for Food Policy & Obesity School Health Index Centers for Disease Control and http://www.cdc.gov/healthyyouth/shi/ Prevention’s online self-assessment index.htm and planning tool schools can use to improve their health and safety policies and programs CoalitionsWork Tools & Resources Resources include assessments of http://coalitionswork.com/resources/ community and state plans for obesity tools prevention TRAINING Built Environment Assessment Free courses on assessing the built http://www.med.upenn.edu/beat/ Training (BEAT) Institute online environment for physical activity, onlinetraining.shtml training including an in-depth look at specific tools, and assessing the nutrition environment with the NEMS Community Tool Box sections on Free, open-source lessons and tools for http://ctb.ku.edu/en/dothework/tools_ community evaluation designing and implementing community tk_content_page_254.aspx evaluations Appendix H 431

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evaluations illustrating best practices for measurement and design Cultural Competence and PhotoVoice PhotoVoice1 and other qualitative evaluation strategies offer one method for assessing and com- paring environmental and policy changes. PhotoVoice is particularly helpful for evaluating efforts on behalf of ethnic groups most affected by the obesity epidemic that may not have found a collective voice. PhotoVoice enables community members to document community strengths and concerns. Through discussion, photos taken by community volunteers stimulate dialogue about community issues related to obesity and other health issues and provide a basis to critically assess changes (Wang et al., 2004). PhotoVoice can greatly assist evaluation through community sense-making of the results—a critically important issue because the range of environmental changes is so large and complex and their impor- tance locally is still not well understood. Furthermore, if PhotoVoice reveals that a policy is not being enforced, or promised environmental changes have not occurred, then this is a basis for further action. Quantification is helpful to assess the extent of promised changes, but is not needed to demonstrate the lack of progress in achieving those changes. Healthy Tomorrows for New Britain Teens in Connecticut is an afterschool obesity prevention program serving predominantly low-income Latina girls of Puerto Rican descent (Hannay et al., 2013). It offers a variety of activities including nutritional counseling, physical activity, and leadership develop- ment for change in the community. A qualitative mid-course evaluation employed focus groups of teens and parents, as well as an eight-session PhotoVoice curriculum. To guide taking photos, the participants co-developed framing questions about community barriers and facilitators for physical activity and about what made for stress and happiness in their community. PhotoVoice and focus group sessions with teens were in English, and for parents they were in both English and Spanish. Themes emerged that represented a collective narrative and a basis for youth advocacy, which has led to improvements in school physical education policy and the reopening of neighborhood pools (Hannay et al., 2013). Logic Model Design Examples Examples of two approaches that systematically apply logic model designs to data from c ­ ommunity-level initiatives are the “community measurement” approach developed by the University of Kansas (Fawcett and Schultz, 2008; Francisco et al., 1993) and the “population dose” concept developed as part of the evaluation of the Kaiser Permanente Community Health Initiative (KP-CHI) (Cheadle et al., 2012b). Media research has employed principles similar to the population dose idea dating from the 1950s, a feature that is potentially important to evaluation of the Home Box Office/Institute of Medicine campaign The Weight of the Nation (Farrelly et al., 2005; Lazarsfeld and Merton, 1971; Schramm and Roberts, 1971). In the community measurement approach developed by the University of Kansas (Fawcett and Schultz, 2008), community and evaluation partners use key informant interviews and report reviews to document and score instances of community/system changes (i.e., programs, policies, practices, built envi- ronment), and to characterize aspects related to their intensity (e.g., strength of change strategy, duration, and reach; sectors and levels in which implemented). A plot of the cumulative community changes is over- 1  PhotoVoice funds photography-based projects to support social change. 432

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Cumulative Number of Community Changes 100 100 90 Physical Activity 90 80 Community Changes 80 Percent Children Obese 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 1 2 3 4 5 6 7 8 FIGURE H-1  Hypothetical association of community and system changes with population-health improvement. Example of University of Kansas Work Group attribution approach. SOURCE: Collie-Akers and Fawcett, 2008. laid with a plot of the trend in a population-level outcome (such as behavior change). See Figure H-1 for an illustrative figure (drawn from Collie-Akers and Fawcett, 2008, p. 362). If shifts in the population-level outcome trend line coincide temporally with shifts in the trend of community changes, then it is plausible to attribute the population-level changes to the community-level initiative. The University of Kansas team has used this method successfully in several initiatives (e.g., Collie-Akers et al., 2007). Although it is still possible that secular trends could be responsible for this pat- tern, it is increasingly implausible with every passing year. The “population dose” approach uses elements of the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) method of combining reach and effectiveness to estimate the likely impact of a community change strategy on population-level behavior (Glasgow et al., 2006). Population dose is defined operationally as the product of penetration (reach divided by the size of the target popu- lation) and effect size (relative change in behavior for each person exposed). For example, if 20 percent of the community target population lives near a new walking trail and the average effect size is a 10 percent increase in minutes walked per day among residents living near a newly installed walking trail, the population dose is 20 percent ÷ 10 percent = 2 percent. Essentially, population dose is the effect size of the intervention, if the effect was spread across all of the residents of the target community. Because quantitative effect sizes for policy and environmental change interventions are generally unavailable in the literature, this method uses a three-level rating system (high/medium/low) to assess the strength of most intervention strategies; methods are described elsewhere (Cheadle et al., 2012b). The dose ratings are then combined with population-level outcome data to examine whether higher- dose community change strategies or clusters of strategies are associated with measured population-level Appendix H 433

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changes in the relevant outcomes. For example, if a number of built environment changes are rated as high dose for promoting walking, then a survey of community residents should show measurable increases in minutes walked (Cheadle et al., 2012a). Causal Modeling: The Healthy Communities Study Funded by the National Heart, Lung, and Blood Institute, the Healthy Communities Study will run from 2010 to 2015 and is designed to be a multi-site national study of community-level programs and policies and their relationship with childhood obesity (NHLBI, 2012). Although not designed as an evaluation, the study includes many features that strengthen the interpretation of evaluations, many of which are within reach of local evaluations. The study is not about assessing causal relationships, but it illustrates some ways in which causal inferences can be strengthened in evaluation. And the role of local implementation is critically important to its success. The observational study is both retrospective and cross-sectional, covering a 10-year period. It uses the University of Kansas community measurement approach described in Chapter 8 (e.g., Collie-Akers et al., 2007) to (a) identify discrete instances of community programs/policies, (b) characterize them along specific dimensions (e.g., by duration, reach, strength of intervention), and (c) develop an intensity score for the intervention that unfolds over time (reflecting the amount and kind of community programs/­ policies in place). The study will examine associations between intensity scores for community programs/ policies and children’s body mass index (BMI) trajectories and current behavior. The study is not designed to evaluate any specific program, policy, or community, but will instead systematically assess whether components or characteristics of representative programs/policies in communities across the country are related to BMI, diet, and physical activity in children. The study uses both qualitative and quantitative data and takes advantage of the natural variation in local programs and policies to (a) “determine the associations between community programs/policies and BMI, diet, and physical activity for children; (b) identify the community, family, and child factors that modify or mediate the associations between community programs/policies and BMI, diet, and physical activity in children; (c) assess the associations among community programs/policies and BMI, diet, and physical activity ­ in children in communities that have a high proportion of African American, Latino, and/or low-income residents” at higher risk for health disparities (NHLBI, 2013a). Children’s height and weight, diet, and physical activity will be assessed in-person for the cross- sectional component, and BMI trajectories over a 10-year period will be calculated, using baseline height and weight abstracted from participant medical records. Thus, the Healthy Communities Study includes multiple observations of intermediate outcomes (community programs/policies) and long-term outcomes. Investigators will be able to examine when various interventions started and whether there were any asso- ciated changes in behavior and BMI after that time. Community programs/policies will be identified and described through interviews with key infor- mants (e.g., school principals, parks and recreation staff, directors of community coalitions) and docu- 434 Evaluating Obesity Prevention Efforts

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ment review (reports of related activities). Instances will then be scored using an observational code and protocol. An overall intensity score will be calculated: the number of community programs and policies implemented, weighted by their intensity (i.e., strength of behavior change strategy used, reach, and duration in place). This composite intensity score—calculated for each community for each year of this study—will serve as a measure of the unfolding of the comprehensive intervention being implemented in the community related to obesity prevention. Thus, the Healthy Communities Study employs the recom- mended measurement of implementation “dose.” Also, note that this retrospective review depends greatly on the extent to which local evaluation has documented implementation (or key informants are available to be interviewed). A potential weakness is that the documentation may not be as thorough as necessary to examine more fine-grained relationships between particular interventions and outcomes. However, at a community level this documentation should be sufficient to examine intermediate outcomes (com- munity programs/policies) as a particular “dose” of environmental change related to childhood obesity prevention. More than 200 communities (defined as high school catchment areas) and approximately 20,000 children and their parents/caregivers will be included. In each community, data will be collected on approximately 80 children in kindergarten through 8th grade. Communities were selected using a hybrid approach: a national probability-based sample of communities, and a purposive sample of communities that are known to be active in child obesity prevention work. The probability sample of communities can be generalized to the rest of the United States, while the purposive sample allows a better understanding of the variety of policies and programs being implemented. By including the probability sample of communities, the Healthy Communities Study greatly improves on the non-equivalent comparison group design. In one sense, the probability sample stands in for a “control” group for the purposive sample of communities that are known to be implementing pre- vention. In another sense, however, most of the communities are likely to have implemented something— what community programs/policies they have implemented varies in amount, type, time, and place. The study will characterize the temporal patterns of implementation of various interventions, as well as the dose of interventions given. This permits much more powerful causal modeling than is feasible for most local evaluations. The sheer number of communities and children involved makes causal modeling a very powerful explanatory tool. The study will have enough power to control statistically for factors known to affect childhood obesity, such as income, ethnicity, and region of the United States. In addition, it can analyze the temporal relationship between interventions and change. Finally, because communities vary in the types of intervention and the times at which those interventions were introduced, the study can disen- tangle the relative contributions of these interventions by examining the strength of association between outcomes and particular kinds of intervention (such as introduction of a school policy, strength of the policy, when the policy was implemented). A Potential Regression-Discontinuity Evaluation The regression-discontinuity design requires a strict criterion (such as need) to determine who receives intervention and who does not. It then measures the association between pre- and post-values and examines whether there is a discontinuity in this association based on receipt of intervention. It requires many units (e.g., children, schools), as in any regression analysis. This design can be applied in some areas Appendix H 435

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Effect size Effect size Post-test school Actual average regression BMI line Pre-test school average BMI FIGURE H-2  Regression discontinuity design applied to school-based obesity prevention. NOTE: BMI = body mass index. of obesity prevention based on a population’s pre-intervention weight status. For example, some states, such as California and Arkansas, measure children’s weight and height in all public schools; schools might be selected for intervention based on school-level prevalence of obesity. In that case, change would be seen in any school-level discontinuity in the regression line between pre- and post-intervention prevalence. The effect size is a change in either the intercept or slope of the regression line (see Figure H-2). References AHRQ (Agency for Healthcare Research and Quality) Health Care Innovations Exchange. 2012a. Community coali- tion supports schools in helping students increase physical activity and make better food choices. http://www. innovations.ahrq.gov/content.aspx?id=3232 (accessed April 14, 2013). AHRQ Health Care Innovations Exchange. 2012b. County, city, and community agencies support childcare centers and parents in improving nutrition and physical activity habits of preschoolers. http://www.innovations.ahrq. gov/content.aspx?id=3283 (accessed June 7, 2013). AHRQ Health Care Innovations Exchange. 2012c. Foundation supports rural stakeholders in promoting better eat- ing and physical activity, leading to anecdotal reports of improved behaviors and outcomes. http://www. innovations.ahrq.gov/content.aspx?id=3267 (accessed June 7, 2013). AHRQ Health Care Innovations Exchange. 2012d. Multistakeholder, community-wide collaborative prevents disease and promotes health. http://www.innovations.ahrq.gov/content.aspx?id=1755 (accessed April 15, 2013). AHRQ Health Care Innovations Exchange. 2012e. Recreation “prescriptions” increase use of free community exer- cise programs by low-income patients who are overweight or obese. http://www.innovations.ahrq.gov/content. aspx?id=2934 (accessed June 7, 2013). 436 Evaluating Obesity Prevention Efforts

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