The Validation of a Digital Diet Method project is very innovative because it links three methods to address the gap in measuring food intake of HS preschool children. Data collection is based on EMA theory; participant burden is low, and the Food Image App decreases participant and staff burden even further. Data management and analysis are semi-automated and relies on advanced computer algorithms. A strength of this approach is its semi-automation, which allows us to leverage the strengths of human operators and computer automation.

The goal of the proposed research is to modify the Remote Food Photography Method (RFPM) for use with preschoolers. Primary caregivers (the majority will be mothers) and HS assistants will use a Smartphone to capture 24-hour images of HS children's food selection and plate waste. The RFPM, Ecological Momentary Assessment (EMA). and the Food Photography Application© will be used to estimate the energy and nutrient intake of preschoolers. The accuracy of the RFPM will be examined by determining the energy and nutrient intake (collectively referred to as food intake [FI]) to established methods: 1) actual gram (g) weights of laboratory-based test meals and 2) doubly labeled water (DLW) in a natural environment.

Inclusion Criteria:

• 3-5 years old
• Attends Head Start
• African-American
• Hispanic American
• Can physically complete the tasks required in the proposed research

Exclusion Criteria:

• Younger than 3 years old
• Older than 5 years old
• Does not attend Head Start
• Race/Ethnicity other than African-American or Hispanic-American
• Cannot physically complete the tasks required in the proposed research

With an anticipated attrition rate of 15%, 62 children will be recruited, resulting in a sample size of 54 after attrition (14 HA boys; 14 HA girls; 13 AA boys; 13 AA girls).