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Adequacy and Quality of Diets Consumed by Participants in the National School Lunch Program and School Breakfast Program: Findings from SNDA-III Melissa.

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Presentation on theme: "Adequacy and Quality of Diets Consumed by Participants in the National School Lunch Program and School Breakfast Program: Findings from SNDA-III Melissa."— Presentation transcript:

1 Adequacy and Quality of Diets Consumed by Participants in the National School Lunch Program and School Breakfast Program: Findings from SNDA-III Melissa A. Clark, Mary Kay Fox, Elizabeth Condon, and Patricia McKinney PRELIMINARY PREPUBLICATION AND NOT FOR CITATION Mary Kay discussed meals that are offered and served in schools—we examine what kids are actually eating—both from school meals and over the course of the day.

2 Key Research Questions
What is the quality of school meal program participants’ diets? How do diets of participants compare to those of nonparticipants? Main report examines many aspects of kids diets and participation in the school meal programs, but focus today on two broad questions. Focus on intakes of NSLP participants and nonparticipants, report also looks at intakes of SBP participants and nonparticipants.

3 Methods for Analyzing Diet Quality
Estimate distribution of usual daily intakes from 24-hour dietary recalls Compare usual daily intakes to standards Dietary Reference Intakes (DRIs) 2005 Dietary Guidelines for Americans (DGAs) SNDA-III collected data on students’ intakes on a given school day, from 24-hour dietary recalls. However, a key methodological challenge for this and others studies is that the current dietary standards apply to usual nutrient intakes, which are difficult or impossible to observe. In order to assess students’ diets relative to the current standards, we used a procedure recommended by the IOM to estimate the distribution of usual intakes from the 24-hour intake data, making use of a subsample of students from whom we collected a second 24-hour recall. We then compared these distributions for each subgroup of interest to the relevant dietary standards to estimate the proportion of the subgroup with inadequate or excess usual intakes on school days. Note no info on supplements, so may somewhat OVERSTATE inadequacy if kids are getting a lot of vitamins and minerals through supplements. Also, results don’t reflect intakes on non-school days.

4 Different Dietary Reference Intakes for Different Dietary Components
Macronutrients (fat, protein, carbohydrate) Acceptable Macronutrient Distrib. Range (AMDR) Most vitamins and minerals Estimated Average Requirement (EAR) Calcium, potassium, fiber Adequate Intake Level (AI) Sodium Tolerable Upper Intake Level (UL) Cholesterol and saturated fat No DRIs, so compare to Dietary Guidelines Different sets of DRIs for different nutrients. For macronutrients, such as fat, protein, and carbohydrate, compare to AMDR. For most vitamins and minerals, compare to EAR to assess prevalence of inadequate intakes For some minerals (calcium, potassium) and for fiber, no EAR is available, so compare intakes to AI. Sodium--UL No DRIs available for cholesterol and saturated fat, so instead compare to DGAs All vary according to age and gender

5 Methods for Comparing Intakes of Participants and Nonparticipants
“Participants” = students who consumed reimbursable school meal on target day Participants and nonparticipants differ in many ways (age, gender, income, etc.) Estimates adjusted for differences in key characteristics using propensity score matching Estimates still may not represent causal effects of school meal programs Define participants as students who consumed a reimbursable school meal (NSLP or SBP). Focus today on NSLP—but SBP participants generally also participated in NSLP, so a subset of NSLP participants. School meal program participants and nonparticipants differ in many ways—for instance, participants tend to younger, are more likely to be male, and tend to be from more economically disadvantaged households. Because of all these differences, we would expect their diets to be very different, whether or not they consumed a school meal. In order to adjust for at least some of these underlying differences, we use propensity score matching to adjust for several observable differences between the two groups—so we are essentially comparing the diets of participants to a similar group of nonparticipants. Adjust for age, income, race/ethnicity, physical activity level, parent reports of child’s appetite, etc. However, there still may be unobserved characteristics that we don’t adjust for but that do influence children’s diets—so differences in diets between participants and matched nonparticipants are not necessarily caused by the school meal programs.


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