OSU Plate Waste Study
Condition: Plate Waste
Study type: Interventional

Summary: 
      Globally, about one-third of edible food is lost or wasted 1. Wasted food depletes resources
      used to produce the food (as a matter of definition, "produce" includes all activities to
      distribute, package and prepare food for human consumption at any venue, but does not include
      growing, transporting and processing), deprives hungry people from needed nutrition and
      represents the most common (>20%) and most environmentally deleterious component (in terms of
      greenhouse gas) of US landfills3-6. The Organization for Economic Co-operation and
      Development (OECD) identified reducing FW as a key to increasing global food security (OECD
      2011) 7. The Obama Administration recently announced a first ever FW reduction goal for the
      United States of 50% by 2030. USDA and EPA will pursue this goal via partnerships with the
      private sector, charitable and faith-based organizations, as well as state, local and tribal
      governments.

      In developed economies, consumers are the largest source of FW via home preparation and
      dining out2, 8. In order to achieve FW goals, we must anticipate how consumer FW generation
      and handling decisions will respond to proposed policies and interventions. However, there
      exist substantial barriers to measuring consumer FW: existing methods have high respondent
      burden and yield biased measurements of FW generation9-11. In this project we will test a
      smartphone application (app) for measuring household FW.
    

Detailed description: 
      The objective of this project is to pilot test the Remote Food Photography Method (RFPM) and
      SmartIntake smartphone app as an approach for measuring food waste in controlled and
      free-living environments. The RFPM and SmartIntakeTM app constitutes a distinct improvement
      over self-report FI methods, such as pen-and-paper surveys and dietary recall methods that
      rely on subjects' ability to accurately recall the types and portion sizes of foods consumed.
      After training, people use the SmartIntakeTM app to capture images of their foods both before
      and after each eating occasion. Photos are automatically uploaded from the user's smartphone
      to a secure server at Pennington Biomedical. The images are analyzed to quantify food
      selection, food waste, and food intake using validated methods and a computer program (the
      Food Photography Application©) built by Pennington Biomedical. The method has been found to
      accurately quantify food selection, food waste, and food intake.

      Importantly, the RFPM and SmartIntakeTM app eliminate one of the largest sources of error
      associated with self-report methods - subjects' inability to accurately estimate portion
      size, which accounts for ~50% of the error in self-report methods11, 13-15. FI estimation
      studies have observed that overweight subjects react to monitoring by underestimating the
      self-reported amounts of FI or eat less when monitored16, 17. Similarly, FW behavioral
      studies have observed that subjects start self-reporting smaller amounts of FW, however it is
      not clear if this is the result of increased awareness and less generation, or if it due to
      not appearing as wasteful individuals18. However, people respond less to the RFPM/SmartIntake
      app and experiment results show that the underestimation from RFPM does not vary with energy
      intake level12.

      Many shortcomings that plague FI measurement likely hamper FW measurement. Biases in the
      opposite direction (e.g., cleaning your plate to show less FW) likely emerge when measuring
      FW and may be similarly mitigated with the proposed app. We believe using RFPM and
      SmartIntakeTM app as the base for a FW estimation app holds great promise to transform FW
      measurement. First, we note that FW associated with dining situations (i.e., plate waste) is
      directly estimated by the RFPM, hence only a simple transform of current outputs is required.
      To fully adapt RFPM for FW measurement, the procedures will be modified to estimate FW
      created during food preparation and during stored food purges (e.g., cleaning the fridge).
      The RFPM method already works in dine-out settings, which are currently omitted by some
      existing FW measurement methods. Additional functionality, such as estimating edible vs
      inedible FW (and hence calories wasted), estimating waste rate among food categories, and
      estimating rates of diversion from landfills, will also be explored so that multiple policy
      relevant metrics can be instantly calculated and stored.
    

Intervention name(s): Food Photography Application©
Intervention type(s): Device
Intervention description(s): Group testing RFPM as method of recording plate waste
Intervention model: Single Group Assignment
Masking: None (Open Label)
Primary purpose: Other