Food Systems and Policy Analysis

The Children’s Food and Beverage Advertising Initiative (CFBAI) is a voluntary industry initiative in which companies commit to feature only foods meeting specific nutrition criteria in advertising directed primarily to children under age 12. RTI linked household-based scanner data with nutrition label data to determine the extent to which U.S. households with children from 0 to 8 years purchase CFBAI-listed foods and to simulate the potential effects of reformulation because of changes to the nutrition criteria. The results of this study indicate the need to ensure that the design of voluntary industry initiatives will result in a positive public health impact.  

FAS actively develops U.S. agricultural trade initiatives to respond to foreign trade barriers thereby advancing a transparent, predictable, and stable global trading environment for U.S. farmers and ranchers. RTI developed an Excel-based model of over 700 products to allow USDA to quickly estimate the economic impacts of new trade policies and regulatory measures. The model allows users to analyze the effects of tariff and nontariff trade barriers on trade flows, prices, and consumer and producer surplus based on a partial-equilibrium modeling approach.

The USDA, Food Safety and Inspection Service (FSIS) has received requests and petitions to update the Safe Handling Instructions (SHI) label that is required on all raw and partially cooked meat and poultry products. To provide FSIS with information to inform decisions about potentially modernizing the SHI, we conducted a multi-phase study. First, we conducted a web-based experiment with a sample of U.S. consumers to select three variants of a revised SHI label (among 27 variants) that best attract participants’ attention. We then conducted a study in test kitchens using a randomized experimental design in which participants prepared a meal while wearing an eye-tracking device to evaluate the visual salience and effectiveness of the three revised SHI labels versus the current SHI label on adherence to recommended safe handling instructions. Information on consumer handling practices from the test kitchen study were used in a predictive model to estimate reductions in foodborne illness as a result of a revised SHI label. We then conducted a cost-benefit analysis of revising the SHI label using results from the predictive modeling, foodborne illness cost-of-illness estimates, and estimates of industry compliance costs. 

USDA’s Food Safety and Inspection Service required data on the costs for meat and poultry plants to implement food safety measures to help inform analyses of its policies. Using an expert panel process, RTI developed estimates of costs of capital equipment, labor, materials, and other costs associated with food safety investments made by meat and poultry slaughter and processing establishments under FSIS’s jurisdiction. Estimates were developed by establishment size and type for developing food safety plans, conducting food safety training, operating antimicrobial equipment, conducting third-party audits, and conducting pathogen testing.

Governments, civil society, farmers, and other stakeholders need to make data-driven, evidence-based decisions regarding agricultural production, development priorities, and policies to enhance food security, resilience, and sustainability of the agricultural sector. However, in many regions, existing data are incomplete, inconsistent, located within disparate sources, may not be spatially disaggregated, and cannot readily be used to inform integrated decision-making. RTI conducted a study utilizing geospatial data, including remote sensing imagery collected using unmanned aerial vehicles and satellites, combined with statistical and machine learning models to conduct multiple analyses of the agricultural system. These included assessment of the timing of planting, identification of major crops and estimation of area planted by crop, monitoring of crop conduction during the growing season, effects of management practices on farmer revenue, and estimation of climate change impacts on future crop productivity.