Few studies have described the range and health impacts of obesity prevention
strategies in local communities supported by the Communities Putting Prevention to Work
To address this gap, we reviewed implemented strategies in Los Angeles County (LAC) for 3 program focus areas: physical activity-promotion, health marketing, and creation of healthy food environments. Local context and results from an impact simulation are presented.
Information on population reach and program milestones was synthesized to describe historical and programmatic progress of the obesity prevention
efforts during 2010-2012. To forecast health impacts, the Prevention Impacts Simulation Model (PRISM) was used to simulate population health outcomes, including projected changes in obesity burden and health behaviors 30 years into the future.
LAC with more than 9.8 million residents.
Low-income adults and youth who were the intended audiences of the Communities Putting Prevention to Work
program in LAC.
Implemented strategies for the 3 focus areas.
Main Outcome Measures:
Documentation of program reach and PRISM forecasting of obesity rates and health impacts.
Implemented strategies in LAC ranged from best practices in healthy food procurement (estimated reach: 600 000 students, 300 000 meals per day) to completed shared-use agreements (10+ agreements across 5 school districts) to a series of strategically designed health marketing campaigns on healthy eating (>515 million impressions). On the basis of PRISM simulations, these highlighted program activities have the potential to reduce by 2040 the number of youth (−29 870) and adults (−94 136) with obesity, youth (−112 453) and adults (−855 855) below recommended levels of physical activity, and youth (−14 544) and adults (−28 835) who consumed excess junk food, as compared with baseline (2010-2011).
Program context and PRISM-simulated health impacts showed modest but promising results in LAC, which may lead to further population health improvements in the future. Downstream health and behavioral surveillance data are needed to confirm these estimates.