Contract No.: 53-3198-3-014MPR Reference No.: 8167-060

INDICATORS OF DIETARY QUAL111ESOF USDA SCHOOL LUNCHES

February 10, 1995

Authors:

Nancy E. WemmerusMary Kay Fox

Allen L. Schirm

Submitted to:

Submitted by:

U.S. Department of Agriculture

Mathematica Policy Research, Inc.Food and Consumer Service

600 Maryland Avenue, S.W.3101 Park Center Drive

Suite 5502nd Floor

Washington, D.C. 20024Alexandria, VA 22302

Project Officer: Carla McTigue/Mattew McKearn

Project Director: Thomas Fraker

ACKNOWLEDGMENTS

We want to thank Jeff Wilde of the Food and Consumer Service for providing critical guidanceto us on a wide range of issues. We are also grateful for the important contributions of severalindividuals: Tom Fraker of Mathematica Policy Research (MPR) for reviewing the report; JohnBurghardt and Dexter Chu of MPR for sharing their extensive knowledge of the SNDA data; DexterChu, Marcia Stoddard, and Elyse Forkosh of MPR for programming support; Joy Conn of MPR forpreparing the tables in Appendix B; Nancy Cole of Abt Associates for preparing the tables inAppendix C; and Deborah Patterson of MPR for preparing the report.

iii

CONTENTS

Chapter

Page

EXECUTIVE SUMMARY xi

I

INTRODUCTION 1

II

DATA AND METHODOLOGY 3

A. THE SNDA DATA 3

B. DIETARY QUALITIES 5

C. POTENTIAL INDICATOR VARIABLES 9

D. OVERVIEW OF ANALYTIC METHODS 14

III

BIVARIATE RESULTS 17

A. ANALYTIC APPROACH 17

B. RESULTS 19

IV

MULTIVARIATE RESULTS 23

A. ANALYTIC APPROACH 23

B. RESULTS 25

V

IMPLICATIONS AND LIMITATIONS 27

REFERENCES 33

APPENDIX A: METHODOLOGY USED TO CREATE AVERAGELUNCH OFFERED 35

APPENDIX B: BIVARIATE RESULTS 47

APPENDIX C: MULTIVARIATE MODELS 67

v

TABLES

Table Page

II.1 DIETARY QUALITY VARIABLES 7

11.2 POTENTIAL INDICATORS 11

111.1 BEST INDICATORS 20

vii

FIGURES

Figure Page

V.1 MODEL MAIL SURVEY QUESTIONNAIRE FOR SCHOOLFOOD SERVICE MANAGERS 28

V.2 SURVEY RESPONSES FROM AN ILLUSTRATIVE SCHOOL 29

ix

EXECUTIVE SUMMARY

Using School Nutrition Dietary Assessment (SNDA) data collected nationwide from 515 schoolsparticipating in the National School Lunch Program (NSLP), this study identifies indicators of thedietary qualities of NSLP lunches and estimates multivariate models for predicting the qualities ofschool lunches from survey data on the indicators. The interest in indicators among policy analystsstems from the importance of nutrition monitoring in formulating and evaluating food and nutrition,policy. Indicators for predicting school meal qualities are sought because direct measurement of thequalities would be time-consuming and costly and, therefore, not suitable for ongoing nutritionmonitoring.

The dietary qualities considered in this study include the food energy, total fat, saturated fat,cholesterol, sodium, vitamin C, calcium, iron, and fiber content of lunches, as well as the food contentfrom the five USDA Food Pyramid food groups. From a broad array of potential indicators reflectingspecific foods offered, meal planning and preparation practices, and characteristics of school foodservice programs, we find that the best indicators of dietary qualities are school grade level andwhether schools participating in the NSLP offer the following food items or groups of items for lunchat least two days per week: (1) fresh fruit; (2) fresh vegetables; (3) at least four fruits and vegetables;(4) dark green or deep yellow vegetables; (5) high-fat vegetables; (6) french fries, hash browns, ortater tots; (7) cheeseburgers; (8) hamburgers; (9) pizza; (10) cheese; (11) ice cream; (12) dessert; and(13) whole wheat bread. Our findings provide insight into the associations between the dietaryqualities of lunches and specific foods offered at lunch. However, the accuracy with which dietaryqualities can be predicted in the future and, therefore, the usefulness of our findings for nutritionmonitoring cannot be assessed with available data.

xi

I. INTRODUCTION

"For the two out of three Americans who do not smoke and do not drink excessively, one

personal choice seems to influence long-term health prospects more than any other: what we eat"

(U.S. Department of Health and Human Services 1988). This choice can be especially important for

children because dietary habits developed during youth can contribute to obesity, unsafe weight loss

practices, and eating disorders and can increase the risk for major chronic disease (Trowbridge and

Collins 1993). Schools can play a vital role in the national efforts to achieve the Year 2000 health

objectives pertaining to children, including the nutrition-related objectives. Recognizing that role,

Objective 2.17 is to "increase to at least 90 percent the proportion of school lunch and breakfast

services and child care food services with menus that are consistent with nutrition principles in the

Dietary Guidelines for Americans" (U.S. Department of Health and Human Services 1991). Systems

for monitoring the nutritional status of children can provide valuable information for measuring

progress toward this and other health objectives and, more generally, for formulating and evaluating

food and nutrition policies targeting children.

Collecting detailed information from schools on planned menus, recipes, and portion sizes is

costly and imposes a significant burden on respondents. These are serious limitations for an ongoing

nutrition monitoring system. Therefore, an important question is whether there are "indicators" of

school meal qualities, that is, simple, yet accurate quality measures that could be obtained using a

brief, self-administered survey instrument to be completed by school food service personnel.

Data from the School Nutrition Dietary Assessment (SNDA) study (Burghardt, et al. 1993)

provide an excellent opportunity for conducting empirical analyses to guide the development of a

survey instrument for measuring the qualities of school meals. The SNDA data include detailed

information on the composition and nutrient content of meals offered in 515 USDA schools for up

to five school days, in addition to information on menu planning, food purchasing, and food

1

preparation practices used in those schools. The SNDA data can be used to examine relationships

between key measures of dietary quality (e.g., proportion of total food energy from fat) and selected

food service practices (e.g., use of nutrient-based menu planning standards, use of low-fat meats and

cheeses, and how frequently french fries are offered). The objective of this study is to identify a small

number of indicators that can be easily measured in a survey of school food service personnel and

used to predict dietary qualities for which direct measurement would be costly and burdensome. For

monitoring change over time in the dietary qualities of school meals, the average value for a

particular quality, as predicted from recent survey data on the indicators, could be compared to the

average values for that quality at earlier points in time.

Chapter II describes the SNDA data and our methodology, including the dietary qualities and

potential indicator variables that we considered. As we discuss in Chapter II, our analytic approach

had two stages. In the first stage, we used bivariate measures of statistical association to identify a

small set of "best" indicator variables that could be measured easily in a future survey and are

relatively closely associated with the dietary qualities considered. In the second stage, we developed

multivariate models for predicting qualities from survey data on the best indicator variables identified

in the first stage. Chapters III and IV present our bivariate and multivariate results, respectively.

In Chapter V, we discuss the implications and limitations of our findings.

2

H. DATA AND METHODOLOGY

This study used School Nutrition Dietary Assessment (SNDA) data to identify indicators of the

dietary qualities of USDA lunches. This chapter describes the SNDA data and our methodology.

After briefly describing the SNDA data in Section A, we discuss in Section B the dietary qualities that

we considered and how we measured those qualities. The dietary qualities considered have been

identified as important for maintaining good health and, thus, for nutrition monitoring. In Section

C, we list the potential indicator variables that were considered. These variables reflect whether

specific foods are offered at lunch, the frequency with which specific foods are offered over the

course of a week, characteristics of the school lunch environment, food purchasing and preparation

practices, and alternative sources of food. In Section D, we provide an overview of our analytic

approach, which has two stages. In the first stage, we sought to identify a small number of indicator

variables that are relatively highly correlated with the dietary quality variables. In the second stage,

we developed models for predicting the dietary qualities of USDA lunches from survey data on the

indicator variables identified in the first stage. More detailed descriptions of our analytic methods

are given in Chapters III and N.

A. THE SNDA DATA

The SNDA dataset contains information on meals offered by and characteristics of a nationally

representative sample of 515 schools that offer National School Lunch Program (NSLP) lunches

(hereafter referred to as USDA schools). The data were collected in the spring of 1992 by

Mathematica Policy Research and its subcontractors, the National Opinion Research Center and the

Nutrition Coordinating Center (NCC) at the University of Minnesota. Three types of information

were collected from school officials:

1. Information on Meals Offered. The SNDA meals-offered data include descriptions of allfoods served as part of NSLP lunches during a specific one-week period between

3

January and May 1992. SNDA survey materials were mailed to designated school foodservice personnel in the participating schools, requesting that they provide acomprehensive list of all food items offered at lunch on each day of the target week.Food service staff were asked to include both foods that do and do not count towardsatisfying a USDA meal-pattern requirement. l They were also requested to providemenus; the recipes for food items prepared in the school district; manufacturers' labels,nutrient analysis, or product specifications of food items purchased from vendors; anddetails on food-preparation procedures and portion sizes for all items. This detailedinformation was used to estimate the nutrient content of the foods offered. From thoseestimates, we estimated the nutrient content of an average NSLP lunch--the unit ofanalysis for this study.

2. School and Meal-Service Characteristics. Basic descriptive information on studentenrollment level; demographic composition of the school; nutrition-programparticipation rates; food planning, purchasing, and preparation practices; and other mealservice characteristics was collected from the principal, cafeteria manager, and directorof the local school food authority (SFA) for each school.

3. Information on Alternative Sources of Food in School. Information was also collected ontwo sources of food offered as alternatives to NSLP lunches: (1) foods sold a la cartein the cafeteria at lunch and (2) food in vending machines available to studentsthroughout the day. The data collection team gathered this information using checkliststo record which of several categories of food and beverage items were offered a la carteor in vending machines on the target day. Because this information was collected inperson, it is only available for the 329 participating "in-person" schools in which personalinterviews were conducted with students.

Our unit of analysis is an average lunch offered on an average day by a USDA school. For each

school, we performed the following calculations:

(1) We first created distinct meals from all of the food items offered for lunch on agiven day. A detailed description of this process can be found in Appendix A.

(2) We averaged the nutrient content of each of the distinct meals offered on a singleday, creating a daily measure of the nutrient content of an average lunch.

(3) We averaged the nutrient content of each of the average daily measures for thethree, four, or five days of data, creating an average meal offered on an averageday.

1To receive federal reimbursement, schools must offer lunches that conform to the NSLP mealpattern, which requires that daily lunches include five foods from four meal components: (1) oneserving of a meat or meat alternate; (2) one serving or more of a bread or bread alternate; (3) twoor more servings of vegetables and/or fruits; and (4) one serving of fluid milk.

4

Because not all USDA schools offer SBP breakfasts, we limited our analysis to NSLP lunches.

We elected to use the average weekly meal measure rather than to select at random a single day

of lunches at each school for two main reasons. First, accounting for an entire week of lunches

served allows us to include measures of offering frequency, such as how many times a week pizza is

served or whether fresh fruit is offered at least twice a week. Second, averaging meals offered over

three to five days yields a more accurate portrayal of the variety of foods a school offers since it is

likely that schools will try to offer a "balanced" menu over the course of a week.

The SNDA data were weighted to adjust for differences between the composition of the sample

and the composition of the population of interest. In this study, these differences arose by design

(i.e., differential sampling rates for schools of different sizes) as well as by differences in response

rates. The SNDA sample weights compensate for both types of differences between the sample and

the target population. All estimates presented in this analysis are weighted. The weighted total

number of schools equals the number of non-special education schools in the 48 contiguous states

and the District of Columbia in the spring of 1992.

B. DIETARY QUALITIES

Our first step in undertaking this study was to select the key dietary qualities to examine. We

began with a list of eight dietary components identified as high priority by previous nutrition

monitoring task forces (U.S. Department of Health and Human Services and U.S. Department of

Agriculture 1986; Life Sciences Research Office 1989):

• Total Food Energy

• Total Fat

• Saturated Fat

• Cholesterol

• Sodium

5

• Vitamin C

• Calcium

• Iron

To this list, we added dietary fiber. Then, we broadened our focus to include measures associated

with particular types of food. These measures were derived from the USDA's Food Pyramid (U.S.

Department of Agriculture 1992). The Food Pyramid defines five constituent food groups: (1)

Breads, Cereals, Rice, and Pasta; (2) Vegetables; (3) Fruits (including fruit juices); (4) Milk, Yogurt,

and Cheese; and (5) Meat, Poultry, Fish, Dry Beans, Eggs, and Nuts. 2 Our last five dietary qualities

reflected the amount of food from each of these food groups in an average school meal, and brought

to 14 the number of dietary qualities we considered.

To measure the 14 specified dietary qualities, we examined the total amount offered in an

average lunch in kilocalories, grams, or milligrams and, to the extent possible, how the nutrient

content of the meal offered compared to accepted standards. As standards, we utilized the Dietary

Guidelines for Americans (U.S. Department of Agriculture and U.S. Department of Health and

Human Services 1990) and recommendations made by the National Research Council (1989) in its

publication Diet and Health. The rationale for these reference standards is discussed below. Table

11.1 summarizes the 20 variables initially specified to measure the 14 dietary qualities.

We based quality standards for total fat content and saturated fat content on the Dietary

Guidelines for Americans. For both, a meal that is high quality meets or falls below the specified

threshold, defined on the basis of the percent contribution to total food energy (see Table 11.1). To

obtain standards for cholesterol and sodium content of school meals, we turned to the NRC

21n the remainder of this report, these groups will often be referred to as the bread, vegetable,fruit, milk, and meat groups, respectively.

6

TABLE II.1

DIETARY QUALITY VARIABLES

Dietary QualityTotal Content in

Average Lunch Variable Adequacy Variables

Total Food EnergyTotal content in

kilocalories

Total FatTotal content in

kilocaloriesTotal content as apercentage of total

food energy

Is no more than30% of total foodenergy from fat?a

Saturated FatTotal content in

kilocaloriesTotal content as apercentage of total

food energy

Is less than 10% oftotal food energy

from saturated fat?b

CholesterolTotal content in

milligramsIs content less than

or equal to 100

mg?c

SodiumTotal content in

milligramsIs content less than

or equal to 800mg?a,e

Vitamin CTotal content in

milligrams

CalciumTotal content in

milligrams

IronTotal content in

milligrams

Fiber Total content in grams

Bread, Cereal, Rice,and Pasta Group

Total content in grams

Vegetable Group Total content in grams

Fruit Group Total content in grams

7

TABLE 11.1 (continued)

Dietary QualityTotal Content in

Average Lunch Variable Adequacy Variables

Milk, Yogurt, andCheese Group

Total content in grams

Meat, Poultry, Fish,Dry Beans, Eggs,and Nuts Group

Total content in grams

NOTES:

a This variable was deleted from our final list of quality variables because only 8 of the 515 averageschool lunches satisfied the dietary standard for total fat content.

b This variable was deleted from our final list of quality variables because only 1 of the 515 averageschool lunches satisfied the dietary standard for saturated fat content.

100 milligrams represents one-third of the National Research Council's maximum recommendeddaily intake of 300 milligrams.

d 800 milligrams represents one-third of the National Research Council's maximum recommendeddaily intake of 2,400 milligrams.

e This variable was deleted from our final list of quality variables because none of the 515 averageschool lunches satisfied the dietary standard for sodium content.

8

recommendations in Diet and Health.3 We divided the NRC's maximum daily recommended intakes

of cholesterol and sodium by three to create lunch-specific quality measures.

For total fat and saturated fat, we created continuous variables reflecting the percentage

contribution to total food energy. For these two qualities, as well as for cholesterol and sodium, we

also constructed binary measures indicating whether a specific dietary standard was satisfied (see

Table 11.1). However, we dropped three of the four binary measures--the adequacy variables for fat,

saturated fat, and sodium--because less than two percent of the schools in the SNDA sample served

lunches meeting the applicable dietary standards.4

For the other 10 dietary qualities, we did not construct variables measuring total content relative

to a standard. Instead, we measured only the total amount offered (in kilocalories, milligrams, or

grams) in an average meal. For food energy, vitamin C, calcium, and iron, we elected not to use

RDA-based standards (e.g., the proportion of the RDA contributed by a school lunch) because the

RDAs vary by age and sex. For fiber, there is, at present, no widely-accepted standard. For the food

group qualities, we would have tallied, ideally, the number of servings within each food group in a

meal. However, the data files are organized in such a way that this tabulation could not be

accomplished without a lengthy and costly recoding process.

C. POTENTIAL INDICATOR VARIABLES

This section describes the potential indicator variables that we considered. They measure the

frequency with which particular food items are offered; food planning, purchasing, and preparation

practices; the school lunch environment; and school meal service characteristics.

In developing our list of potential indicator variables, we were influenced by several

considerations. First, we must be able to construct an indicator variable from the SNDA data.

3The Dietary Guidelines for Americans recommend "moderate" consumption of cholesterol andsodium, but do not offer specific numerical recommendations.

4The 14 qualities were thus measured by 17 variables, rather than the initially-specified 20.

9

Whether schools make a purposeful effort to serve low-fat meals, for example, may be an important

indicator of the nutritional quality of lunches offered. However, the SNDA survey obtained

information only on whether official district-level guidelines exist for such efforts, not whether they

are actually followed in practice. Second, an indicator variable must be subject to observable changes

over relatively brief periods of time, in the aggregate. Although certain school characteristic

variables, such as race and ethnic composition and public/private status, may be significant predictors

of the dietary quality of lunches served, we could observe changes in those variables in the population

of schools only over long periods of time--periods that are too long for monitoring dietary trends.

Third, we dropped from our list any variables that could not be easily constructed in the future from

simple questions, such as those that could be administered in a mail survey of school food service

workers. For example, we do not believe that it would be possible to obtain precise information on

whether a low-fat meals or a high-fat vegetable6 is offered, because this would require relatively

sophisticated nutrient analysis of foods offered.

Table 11.2 presents a complete list of all the indicators we considered and a description of how

these indicators are represented by variables constructed from the SNDA dataset. The indicator

variables are organized into groups and subgroups based on a simple conceptual framework. For

example, we have specified one group of variables to capture whether specific food items are offered

at lunch during the target week. Within that group, we have specified subgroups of variables to

capture how often the food items are offered.

A series of dummy variables indicate whether particular food items were offered to students

during the target week and whether these items were offered at least twice over the course of the

week. We also included a continuous variable for each specified food item that measures the total

number of days on which the item was offered during the target week. A complete list of the food

sDefined as a meal containing less than 32 percent of its total food energy from fat.

6Defined as a vegetable dish providing more than 20 percent of food energy from fat.

10

TABLE H.2

POTENTIAL INDICATORS

Indicator Variable Variable Categories

Specific Food Items Offered a

Item ever offered during target week yes/no

Item offered at least twice during target week yes/no

Number of times item offered during target week 0-5

Whether school reported less than five days of meals-offered data yes/no

Recommended or Required Nutritional Guidelines

Any state nutritional guidelines? yes/no

Any district nutritional guidelines? yes/no

Limit total calories from fat or saturated fat

Recommended guideline yes/no

Required guideline yes/no

Recommended or required guideline yes/no

Limit dietary cholesterolb recommended/required

Limit sodiumb recommended/required

Increase servings of fruitb recommended/required

Increase servings of vegetables b recommended/required

Increase servings of dietary fiberb recommended/required

Increase servings of whole grainb recommended/required

Limit number of dessertsb recommended/required

Limit sugarb recommended/required

Serve a variety of foodsb recommended/required

Limit competition recommended/required

Total number of recommended guidelines 0-11

Total number of required guidelines 0-11

Total number of recommended or required 0 - 11

Meal Planning/Purchasing Practices

How the nutritional content of meals is evaluated

Review ingredient lists yes/no

Advice of sales representatives or food vendors yes/no

11

TABLE 11.2 (continued)

Indicator Variable

Variable Categories

Computer analysis

yes/no

Use information provided by state Department of Education

yes/no

Use professional training material

yes/no

Review USDA literature

yes/no

Total number of nutritional evaluation procedures followed

0-6

Location where lunch is planned

At school

yes/no

At district level

yes/no

At off-site kitchen

yes/no

Location where food purchasing is coordinated

At school

yes/no

At district level

yes/no

At central kitchen

yes/no

Location where lunch is prepared

At school

yes/no

At off-site kitchen

yes/no

At central kitchen

yes/no

Food service management company used

yes/no

Food Preparation Practices

Limit service of breaded or fried meats and vegetables

yes/no

Use reduced fat cheese

yes/no

Substitute chicken and fish for red meat

yes/no

Offer lower fat hot dogs and sandwich meat

yes/no

Rinse or drain cooked ground beef

yes/no

Rinse and drain cooked ground beef

yes/no

Cook chicken without skin

yes/no

Serve skim milk

yes/no

Provide fresh fruits and vegetables daily

yes/no

Total number of healthy food preparation practices

0-9

Meal Service Characteristics/School Lunch Environment

Offer versus serve option available

yes/no

12

TABLE 11.2 (continued)

Indicator Variable Variable Categories

Open campus yes/no

Full lunch price price in cents

Alternative Sources of Food for Lunch

A la carte food available at lunch yes/no

School store available yes/no

Vending machine available yes/no

School Characteristics

Public school yes/no

School level elementary/high'

School size continuous

School offers SBP yes/no

Percent students certified proportion certified

a See accompanying list of specific food items. Each of the three item-offered indicator variables was constructedfor every food items listed.

b All three guideline dummy variables (recommended guideline; required guideline; and recommended or requiredguideline) were constructed for each nutritional guideline.

Two dummy variables were constructed.

SPECIFIC FOOD ITEMS CONSIDERED

CheeseHamburgerCheeseburgerHot dogPizzaPrebreaded chicken or turkeyAt least 3 fruits and vegetables )At least 4 fruits and vegetables )Fresh fruitFresh vegetableDark green or deep yellow vegetable

French friesFrench fries, hashbrowns, or tater totsHigh fat vegetable2Whole wheat breadPotato chipsChips and other salty snacksDessert3Ice cream/milk dessertsFresh fruit or vegetableSalad barBuffet-style food bar

tlncludes vegetables that are ingredients in entree recipes.

2lnciudes french fries, hashbrowns, tator tots, creamed potatoes, potato au gratin, potato salad, and potato chips.

3lncludes cakes, cookies, pies, cobblers, pastries, danishes, doughnuts, gelatin desserts, candies, ices or popsicles, frozenmilk and yogurt desserts, puddings, and custards.

13

items and groups of food items considered appears at the end of Table 11.2.

Although SNDA was designed to collect information on meals offered by schools for an entire

five-day school week, due to school holidays, vacations, and weather cancellations, it was not possible

to collect five days of meals-offered data for the entire sample. We have just four days of data for

63 schools (12.2 percent of the NSLP sample) and three days of information for 2 schools (0.4

percent of the NSLP sample). To account for the truncation bias that might arise from using

indicator variables measuring the frequency with which specific food items are served when some

schools have fewer than five days of data, we included in our analysis a dummy variable that indicates

whether a school provided fewer than five days of meals-offered data.

To determine whether district-mandated nutritional guidelines affect the nutritional content of

lunches offered, we specified a series of dummy variables that record whether specific nutritional

guidelines, such as limiting sugar and increasing servings of dietary fiber, have been implemented.

Other dummy variables indicate which meal planning and purchasing practices are followed, including

at what location in the district lunches are planned and purchased.

To capture the importance of food preparation practices, we considered as potential indicators

several variables measuring whether a school follows specific healthy food preparation activities, such

as rinsing and draining ground beef and removing the skin from chicken. Other variables considered

reflect characteristics of the school lunch environment, such as offer-versus-serve and a la carte

options and the full price of lunch. Alternative sources of lunch food were captured through dummy

variables that indicate whether the school has a school store or vending machines. Finally, basic

characteristics of the school, such as total enrollment, public/private status, and the percentage of

students certified to received free or reduced-price lunches were included.

D. OVERVIEW OF ANALYTIC METHODS

Stated narrowly, the objective of this study is to identify indicators of the dietary qualities of

USDA lunches as offered by USDA schools. Placed in the context of developing a system for

14

nutrition monitoring, the objective is to identify a small number of indicators that can be easily

measured in future surveys of school food service personnel and used to predict dietary qualities.

Based on predicted values for a particular quality, average quality at one point in time could be

compared with average quality at an earlier point in time to see whether that quality has improved

or deteriorated in the aggregate. The reason for predicting qualities is that their direct measurement

is burdensome and costly; hence, we seek indicators.

With the broader objective of prediction in mind, we conducted our analysis of the SNDA data

in two stages:

• Bivariate Analysis. Our purpose in the first stage was to identify using bivariatemeasures of statistical association a small set of "best" indicator variables that couldbe easily measured in a future mail survey of school food service personnel and arerelatively closely associated with the quality variables.

• Multivariate Analysis. Our purpose in the second stage was to develop multivariatemodels for predicting quality variables from survey data on the best indicatorvariables identified in the first stage.

Although we could have stopped with the first stage bivariate analysis and predicted a given quality

using only its best indicator, it is likely that more accurate predictions could be obtained if other best

indicators included in the future survey were also used. For example, even if the best indicator of

saturated fat in school lunches is whether a school offers cheese at least twice a week, we may be

able to improve our prediction of saturated fat intake by also taking into account how often ice cream

is offered. Therefore, in the second stage, we allow dietary qualities to be predicted by more than

one indicator variable.

15

III. BIVARIATE RESULTS

This chapter presents the results from our bivariate analysis of the SNDA data. The purpose

of that analysis was to identify a small set of "best" indicator variables that could be easily measured

in a future survey of school food service personnel and are relatively closely associated with the

quality variables described in Chapter II. Section A discusses our analytic approach, and Section B

describes our findings. Estimates for bivariate measures of association are presented in the tables in

Appendix B.

A. ANALYTIC APPROACH

In this first stage of our analysis, we explored the bivariate associations between the quality and

indicator variables described in Chapter II. We measured the association between each of the 14

qualities, as represented by the 17 quality variables, and each of the over 150 indicator variables. In

Appendix B, Tables B1-B17 present our results. Each table presents results for one dietary quality

variable. Table B1, for example, pertains to the total food energy content of an average lunch

measured in kilocalories. Table B3 pertains to the fat content of an average lunch measured as a

percentage of total food energy.

To measure the associations between quality and indicator variables, we performed bivariate

regressions, regressing each quality variable on each indicator variable. For each quality variable, we

display in the tables in Appendix B, the 50 indicator variables that are most highly correlated with

that quality variable, the R2 values from those 50 bivariate regressions, and the signs of the

correlations between the quality and indicator variables (1 implies a positive correlation, -1 a

negative correlation). The indicator variables are listed in rank order by R2. For each indicator

variable above the dashed line, the correlation between the quality and indicator variables equals or

exceeds 0.2 in absolute value (which is the same as a bivariate regression R2 value greater than or

17

equal to 0.04). 1 Although the 50 variable and 0.2 correlation cut-offs are arbitrary, they are useful

for narrowing the scope of our investigation to the most promising indicator variables. As discussed

in Chapter II, all estimates presented in this chapter and the remainder of this report are based on

analyses using the sample weights.

As discussed previously in this chapter and in Chapter II, the objective of our bivariate analysis

was to identify "best" indicators. We applied three criteria for selecting best indicators: (1)

correlation, (2) "askability," and (3) generality. For a given quality, the best indicator variables are

relatively highly correlated with the one, two, or three variables measuring that quality. However,

in selecting the best indicators, we also considered askability, favoring variables that can be easily

constructed in the future from responses to simple questions in a mail survey. 2 We also sought to

identify a small number of best indicators, taking into account an indicator's generality--its

performance for qualities other than the quality in question. Therefore, we sometimes favored a

slightly weaker indicator for a given quality if, for example, that indicator is a strong indicator for

other qualities.3'4

1The absolute value of a correlation coefficient equals the square root of R2. As the tables show,some correlations are positive and some are negative.

2Although an indicator variable measuring the number of times during a week that low-fat entreesare offered, for example, is relatively highly correlated with several quality variables, this indicatordoes not fare well according to the askability criterion since it would require future survey recipientsto have a detailed knowledge of the nutritional content of lunches offered.

3For instance, whether a school offered french fries alone during the target week was somewhatmore highly correlated with average fat content (as a percent of total food energy) than whether acombination of french fries, hash browns, and tater tots were offered. However, the latter scoredhigher on the generality criterion because it was more highly correlated than the former with totalfood energy and fat content measured in kilocalories.

4As we discuss in Chapter V, best is only a relative characteristic and does not imply that a bestindicator can be used to predict a quality accurately.

18

B. RESULTS

Our broad findings concerning the performance of the various classes of indicator variables are:

Variables pertaining to specific foods offered--particularly cheese, french fries, and icecream--are often good indicators of dietary qualities.

• Variables pertaining to broader categories of foods offered--particularly dessert, freshfruits and vegetables, and high-fat vegetables--are often good indicators of dietaryqualities.

• Variables pertaining to recommended or required nutrition guidelines are not goodindicators of dietary qualities.

• Variables pertaining to meal planning and purchasing procedures are not goodindicators of dietary qualities.

• Variables pertaining to food preparation practices are not good indicators of dietaryqualities.

• Variables pertaining to meal service characteristics--particularly the availability of theOVS option--are sometimes good indicators of dietary qualities.

• Variables pertaining to alternative sources of food at lunch--particularly availability ofvending machines--are sometimes good indicators of dietary qualities.

• Variables pertaining to school characteristics are generally not good indicators of dietaryqualities, although, grade category is a potentially important control for student agecomposition.

"Good," like "best," is a relative characteristic; compared with a "bad" indicator, a good indicator is

at least modestly correlated with one or more qualities.

Applying the criteria outlined in Section A, we selected the best indicators displayed in Table

111.1 for the 14 dietary qualities. As the R2 values in the appendix tables show, the best indicators

usually have relatively high correlations with the quality variables. However, the askability criterion

did influence several of our choices of best indicators. As noted before, we rejected the indicator

variables measuring how often low-fat entrees are offered, despite their high correlations with several

quality variables. Similarly, we rejected our original variables indicating whether a high-fat vegetable

was served because these variables were based on percentage of fat in vegetables rather than on a

19

TABLE 111.1

BEST INDICATORS

Quality

Total Food Energy

Total Fat

Indicator

Whether dessert s is offered at least twice a week

Whether dessert s is offered at least twice a week

Whether french fries, hash browns, or tator tots are offered at least twice a week

Whether dessert s is offered at least twice a week

Whether a high-fat vegetable2 is offered at least twice a week

Whether dessert s is offered at least twice a week

Whether french fries, hash browns, or tator tots are offered at least twice a week

Whether a high-fat vegetable2 is offered at least twice a week

Saturated Fat

Cholesterol

Sodium

Vitamin CWhether at least 4 fruits or vegetables are offered at least twice a week

Whether dark green or deep yellow vegetables are offered at least twice a week

Calcium

Whether cheese is offered at least twice a week

Whether dessert s is offered at least twice a weekIron

Whether a cheeseburger is offered at least twice a week

Whether fresh fruit is offered at least twice a week

Fiber

Whether cheese is offered at least twice a week

Whether whole wheat bread is offered at least twice a week

20

TABLE 111.1 (continued)

Quality

Indicator

Whether dessert s is offered at least twice a week

Whether fresh vegetables are offered at least twice a week

Whether a high-fat vegetable2 is offered at least twice a week

Whether fresh fruit is offered at least twice a week

Whether ice cream is offered at least twice a week

Whether french fries are offered at least twice a week

NOTES:1. Includes cakes, cookies, pies, cobblers, pastries, doughnuts, gelatin desserts, candies, ices orpopsicles, frozen milk and yogurt desserts, puddings, and custards.

2. Includes french fries, hashbrowns, tator tots, creamed potatoes, potatoes au gratin, potato salad,and potato chips.

Vegetable Group

Fruit Group

Milk Group

Meat Group

21

list of specific high-fat vegetable dishes. However, because this variable is highly correlated with

several quality variables, for the multivariate component of this analysis, we created a new "high-fat

vegetable offered" variable, defined, not by the fat content of a vegetable, but rather as a specific set

of high-fat vegetable dishes--french fries, hash browns, tater tots, potato salad, creamed potatoes,

potatoes au gratin, and potato chips. Because we retained this "askable" version of the variable in

our final analysis, whether a high-fat vegetable is offered at least twice a week is included as a best

indicator in Table 111.1. Finally, the generality criterion was less important than the correlation and

askability criteria, although it did lead us to reject some indicator variables that appeared near the

top of only one or two tables.

We did apply one other criterion not discussed in Section A that led us to reject a class of

indicator variables. Although "total number of times offered" variables are somewhat more highly

correlated with several qualities than the corresponding "offered at least twice a week" variables, we

favored the latter because simple description tabulations suggested there was truncation bias due to

having fewer than five days of meals-offered data. This issue, particularly the implications for

multivariate modeling, requires much more extensive investigation.

22

IV. MULTIVARIATE RESULTS

Once a future survey of school food service personnel has collected data on a set of best

indicators, there is no reason necessarily to use a single indicator to predict a particular quality; a

multivariate model allowing several indicators to be used would likely provide more accurate

predictions. This chapter presents the results from our multivariate analysis of the SNDA data. Our

purpose was to develop multivariate models for predicting qualities from survey data on the best

indicators. Section A describes our analytic approach, and Section B discusses our findings. The

estimated multivariate models are presented in Appendix C.

A. ANALYTIC APPROACH

To develop multivariate models, we used the previously identified "best" indicator variables to

specify a set of potential predictors and, for each quality variable, selected predictors from that set

using a procedure described later in this section. We estimated two types of multivariate models: (1)

linear regression models for the continuous quality variables (all the quality variables except one are

continuous) and (2) a logistic regression model for the dichotomous quality variable (whether the

dietary standard for cholesterol content was met).' A linear regression model relates the level of a

quality variable--measured in kilocalories, grams, milligrams, or as a percentage of a dietary standard--

to one or more predictors. A logistic model relates the probability that a dietary standard is achieved

to one or more predictors. The predictor variables in our multivariate models are the best indicators

and functions of the best indicators, as discussed next.

In our bivariate analysis described in Chapter III, we identified 16 variables that are best

indicators of the dietary qualities of lunched offered:

'A logit model is an appropriate specification for handling a dichotomous dependent variable ina regression framework.

23

• Whether cheese was offered at least twice during the target week

• Whether dessert was offered at least twice during the target week 2

• Whether a cheeseburger was offered at least twice during the target week

• Whether pizza was offered at least twice during the target week

• Whether whole wheat bread was offered at least twice during the target week

• Whether ice cream was offered at least twice during the target week

• Whether fresh fruit was offered at least twice during the target week

• Whether fresh vegetables were offered at least twice during the target week

• Whether at least 4 fruits or vegetables were offered at least twice during the targetweek

• Whether dark green or deep yellow vegetables were offered at least twice duringthe target week

• Whether french fries, hash browns, or tater tots were offered at least twice duringthe target week

• Whether a high-fat vegetable was offered at least twice during the target week3

• Elementary School4

• High School4

In addition to including these variables in the set of potential predictors, we also included the product

of each pair of best indicators in the set of potential predictors to allow for "interactions" between

indicators. For example, while high cholesterol content of lunches may be associated with offering

dessert at least twice a week or with offering a high-fat vegetable at least twice a week, especially

high cholesterol content might be found in lunches served by schools offering both dessert and high-

2Dessert items are cakes, cookies, pies, cobblers, pastries, doughnuts, gelatin desserts, candies, icesor popsicles, frozen milk and yogurt desserts, puddings, and custards.

3High-fat vegetables are french fries, hash browns, tater tots, creamed potatoes, potatoes augratin, potato salad, and potato chips.

4These variables are included as controls for the age composition of students to whom the lunchesare offered.

24

fat vegetables at least twice a week. Such an effect would be captured by including in a model the

product of the dummy variables representing whether dessert was offered at least twice and whether

a high-fat vegetable was offered at least twice. 5

We used a stepwise procedure to select the predictors for our multivariate models from the set

of potential predictors. At each step (beginning with a model with an intercept but no predictors),

the predictor that most improved the fit of the model according to R2 was added to the model. Then,

if any of the predictors already in the model no longer contributed substantially to the fit of the

model, they were removed from the model. This review of variables continued until the fit of the

model could not be improved appreciably. 6

B. RESULTS

Linear and logit regression coefficients for the estimated multivariate models are displayed in the

tables in Appendix C. Each column in a table pertains to a single quality variable. For example, the

first column of estimates in Table C3 presents the model for average saturated fat content of lunches

in kilocalories. The second column of estimates presents the model for the average saturated fat

content of lunches as a percentage of total food energy. According to Table C3, saturated fat

content in kilocalories and saturated fat content as a percentage of total food energy are predicted

by a total of eight indicator variables: whether dessert was offered at least twice a week; whether

cheese was offered at least twice a week; whether fresh vegetables were offered at least twice a week;

whether at least four fruits and vegetables were offered at least twice a week; whether school level

is elementary; and interactions between offering cheese and elementary school, offering french fries

and fresh vegetables, offering four fruits and vegetables and elementary school, and offering high-fat

5That product will equal zero unless both items are offered at least twice a week.

6A predictor was added to or retained in the model if it increased R2 by approximately 0.01.

25

vegetables and elementary school. Each table lists only the indicator variables that appear in one of

the models presented in the table. ?

According to the tables in Appendix C, most quality variables are predicted by several indicators,

suggesting that there is potentially some gain to estimating multivariate, rather than bivariate, models.

This inference is supported by comparing the R2 values for the multivariate models (displayed at the

bottom of each table) with the R2 values from our bivariate analysis. The multivariate model for total

food energy in kilocalories has an R2 of 0.37 according to Table Cl, whereas the highest R2 for a

single indicator is 0.24 according to Table B1. 8 Although the estimated multivariate models typically

fit the data better than any bivariate model and account for substantially more of the variability in

any quality according to R2 values, the multivariate models still often leave much of the variability

in the dietary quality of lunches unexplained. An R2 value of 0.2, for example, implies that 20

percent of the variance in the quality variable is explained by the multivariate model, while 80 percent

is not. A further note of caution is that even a model with a high R2 may not predict accurately, as

discussed in the next chapter.

?The interpretation of the multivariate models is discussed in greater detail in Chapter V.

8That indicator is whether dessert was offered at least twice week.

26

V. IMPLICATIONS AND LIMITATIONS

In this study, we have identified a set of best indicator variables that measure school grade level

and whether USDA schools offer the following food items or groups of items for lunch at least two

days per week: (1) fresh fruit; (2) fresh vegetable; (3) at least four fruits and vegetables; (4) dark

green or deep yellow vegetable; (5) high-fat vegetable; (6) french fries, hash browns, or tater tots;

(7) cheeseburger; (8) hamburger; (9) pizza; (10) cheese; (11) ice cream; (12) dessert; and (13) whole

wheat bread. The next step in using our findings to monitor the dietary qualities of NSLP lunches

would be to collect survey data from which the best indicators can be constructed. Without having

had the opportunity to conduct any pretesting, we would recommend Figure V.1 as a model for

developing a mail survey instrument to be completed by school food service managers.

If a school food service manager completed Figure V.1, it would be possible to construct all of

the best indicator variables for that school. Consider the responses in Figure V.2 of an illustrative

school. For that school, the best indicator variables take the following values:

• Fresh fruit (02_FRFR) = 1 ("yes")

• Fresh vegetables (02_FRVEG) = 1 ("yes")

• At least four fruits and vegetables (02_4FV) = 0 ("no")

• Dark green or deep yellow vegetables (02_GYVEG) = 0 ("no")

• High-fat vegetables (02_HIVEG) = 1 ("yes")

French fries, hash browns, or tater tots (02_FRYPL) = 1 ("yes")

Cheeseburger (02_CBURG) = 1 ("yes")

Hamburger (02_BURG) = 1 ("yes")

• Pizza (02_PIZZA) = 0 ("no")

• Cheese (02_CHEES) = 1 ("yes")

• Ice cream (02_ICECR) = 1 ("yes")

27

FIGURE V.1

MODEL MAIL SURVEY QUESTIONNAIRE FOR SCHOOL FOOD SERVICE MANAGERS

1. School Name

2. School Grade Levelq Elementary q Middle q High

3. Which of the following items did you offer at lunch at least two times last week?

a. Hamburger (with or without cheese)q Yes q No

b. Cheeseburgerq Yes q No

c. Pizzaq Yes q No

d. French fries, hash browns, or tater totsq Yes q No

e. French fries, hash browns, tater tots, potato salad, creamed potatoes, potatoes augratin, or potato chipsq Yes q No

f. Fresh fruitq Yes q No

g. Fresh vegetableq Yes q No

h. Dark green or deep yellow vegetable (broccoli, spinach, collard greens, kale, carrots,pumpkin, squash, sweet potatoes)

D Yes q No

i. At least 4 fruits or vegetables in a single day (including fruits or vegetables that areingredients in an entree or side dish)

q Yes q No

Cheese (including cheese that is an ingredient in an entree or side dish)q Yes q No

k. Whole wheat breadq Yes q No

1. Ice creamq Yes q No

m. Dessertq Yes q No

J-

28

FIGURE V.2

SURVEY RESPONSES FROM AN ILLUSTRATIVE SCHOOL

1. School Name Thomas Jefferson Elementary

2. School Grade Level® Elementary q Middle q High

3. Which of the following items did you offer at lunch on at least two days last week?

a. Hamburger (with or without cheese)• Yes q No

b. CheeseburgerE Yes

q No

c. Pizzaq Yes ® No

d. French fries, hash browns, or tater tots® Yes q No

e. French fries, hash browns, tater tots, potato salad, creamed potatoes, potatoes augratin, or potato chips

® Yes q No

f. Fresh fruitE Yes q No

g. Fresh vegetableE Yes q No

h. Dark green or deep yellow vegetable (broccoli, spinach, collard greens, kale, carrots,pumpkin, squash, sweet potatoes)

q Yes No

i. At least 4 fruits or vegetables in a single day (including fruits or vegetables that areingredients in an entree or side dish)

q Yes No

Cheese (including cheese that is an ingredient in an entree or side dish)® Yes q No

k. Whole wheat breadq Yes E No

1. Ice creamE Yes q No

m. DessertE Yes q No

29

• Dessert (02_DESS) = 1 ("yes")

• Whole wheat bread (02_WWBR) = 0 ("no")

• Elementary school (ELEMENT) = 1 ("yes")

• High School (HIGH) = 0 ("no")

For each best indicator variable, we have displayed the variable name used in the tables of

multivariate models presented in Appendix C. The interaction variables appearing in the multivariate

models are also easily obtained from the school's survey responses. For example, 02_CHEESE x

02_ICECR (the interaction between cheese and ice cream) = 1 x 1 = 1.

The values for the indicator variables and the estimated multivariate models can be used to

predict values for the dietary quality variables for our illustrative school. Using the estimated

coefficients in Table Cl, we would predict the total food energy content in kilocalories of an average

lunch in this school to be:

718.3 + (95.8 x 0 2_DESS) + (70.9 x 0 2_CHEES) + (76.1 x 0 2_HFV2)— (33.6 x 0 2_FRVEG) — (49.2 x ELEMENT) — (45.0 x 0 2_GYVEG x ELEMENT)

= 718.3 + (95.8 x 1) + (70.9 x 1) + (76.1 x 1) — (33.6 x 1) — (49.2 x 1)—(45.0 x 0 x 1)

= 718.3 + 95.8 + 70.9 + 76.1 — 33.6 — 49.2

= 878.3

To predict the probability that an average lunch from this school would meet the dietary standards

for cholesterol, we use the second column of coefficients in Table C4 to calculate the "logit" for the

average lunch, which is:

2.66 — (0.30 x ELEMENT) (0.91 x 0 2_DESS) + (2.05 x PIZZA x HIGH)— (0.71 x 0 2_FRVEG x HIGH) — (0.52 x 0 2_CHEES) — (1.17 x 0 2_GYVEG)+ (1.60 x 02_GYVEG x ELEMENT)

= 2.66 — (0.30 x 1) — (0.91 x 1) + (2.05 x 0 x 0) — (0.71 x 1 x 0) — (0.52 x 1)—(1.17x0)+(1.60x0x1)

30

= 2.66 — 0.30 — 0.91 -0.52

= 0.93

Then, the predicted probability is: 1

exp(—0.93) [1 + exp(—0.93)] = 0.39 + 1.39 = 0.28

This implies that there is about a 28 percent chance that this school's average lunch will meet the

NRC cholesterol standard.

An important point is that for the purposes of nutrition monitoring, we are interested in

aggregate predictions, not predictions for individual schools. The latter are made only to obtain the

former. To predict average food energy content in kilocalories across all schools, we would predict

food energy content for each school in the survey sample and average the predicted values. To

predict the proportion of school lunches for which the cholesterol content meets recommended

guidelines, we would predict, for each school in the survey sample, the probability that cholesterol

content is less than 100 mg and, then, average the predicted probabilities across all schools. The

averages calculated in this way could be compared to averages from an earlier point in time to

determine whether particular dietary qualities have improved or deteriorated, on average.

There are several potential limitations to the usefulness of this study's findings for nutrition

monitoring. First, even for the schools in the SNDA data, the models may not predict many dietary

qualities very well. As we discussed in Chapter IV, the multivariate models often leave much of the

variation in quality across lunches unexplained. Second, because the models were selected to fit the

SNDA data as well as possible, they would almost certainly predict qualities less accurately when used

with another data source. Third, the models were selected because of their ability to explain cross-

sectional relationships, that is, the relationships between indicators and qualities at a point in time.

lexp() is the exponentiation operator, that is, e = 2.718281828... raised to the power given bythe number in parentheses.

31

For nutrition monitoring, however, we want to know how changes in indicators are related to changes

in qualities. Panel data, in which each school is observed at several points in time, are best suited

to providing that knowledge. Fourth, the relationships implied by some models are not easy to

understand. For example, it is not intuitively obvious why offering cheese at least twice a week

predicts higher vitamin C and fiber content of lunches. In such cases, the indicators are probably best

interpreted as indicators of other, unmeasured, indicators. Finally, as discussed in Chapter III, the

effects of having truncated meals-offered data have not been fully explored. 2 We have not, for

example, estimated multivariate models including the "number of times offered during target week"

indicator variables.

A validation study is required to address some of these concerns and assess how well the

multivariate models perform in terms of their predictive ability. The database required for the

validation study must contain measurements on not only the indicator variables but also the quality

variables so that predicted qualities can be compared to directly measured qualities. Ideally, the

database would be a panel.

It is important to understand that none of the concerns expressed above implies that individual

and, especially, aggregate predictions will necessarily be inaccurate. Rather, the implication is that

the expected predictive accuracy is unknown. Nevertheless, because many of the estimated models

are intuitively sensible, we believe that our findings provide insight into the associations between the

dietary qualities of lunches and specific foods offered.

2As discussed in Chapters II and III, 13 percent of the USDA schools sampled did not providefive days of meals offered information.

32

REFERENCES

Burghardt, John, et al. The School Nutrition Dietary Assessment Study: School Food Service, MealsOffered, and Dietary Intakes. Alexandria, VA: U.S. Department of Agriculture, Food andNutrition Service, Office of Analysis and Evaluation, October 1993.

Life Sciences Research Office. Nutrition Monitoring in the United States: An Update Report onNutrition Monitoring. DHHS Publication no. (PHS) 89-1255. Washington, DC: U.S.Government Printing Office, 1989.

National Research Council. Diet and Health: Implications for Reducing Chronic Disease.Washington, DC: National Academy Press, 1989.

Trowbridge, Frederick and Beth Collins. "Measuring Dietary Behaviors Among Adolescents." PublicHealth Reports, vol. 108, no. S1, 1993, pp. 37-41.

U.S. Department of Agriculture. The Food Guide Pyramid. Home and Garden Bulletin no. 252.Washington, DC: U.S. Government Printing Office, 1992.

U.S. Department of Agriculture and U.S. Department of Health and Human Services. Nutrition andYour Health: Dietary Guidelines for Americans, 3rd ed. Home and Garden Bulletin no. 232.Washington, DC: U.S. Government Printing Office, 1990.

U.S. Department of Health and Human Services, Public Health Service. Healthy People 2000:National Health Promotion and Disease Prevention Objectives. Washington, DC: U.S.Government Printing Office, 1991.

U.S. Department of Health and Human Services, Public Health Service. The Surgeon General'sReport on Nutrition and Health. Washington, DC: U.S. Government Printing Office, 1988.

U.S. Department of Health and Human Services and U.S. Department of Agriculture. NutritionMonitoring in the United States: A Progress Report from the Joint Nutrition Monitoring EvaluationCommittee. DHHS Publication no. (PHS) 86-1255. Washington, DC: U.S. Government PrintingOffice, 1986.

33

APPENDIX A

METHODOLOGY USED TO CREATE AVERAGE LUNCH OFIERED

A. OVERVIEW OF THE ANALYSIS OF MEALS OFFERED

This appendix describes the process by which the nutrient content of an average lunch offered

was calculated for each SNDA school. Cafeteria managers were asked to supply information on all

foods offered as part of NSLP lunches during a target week. l The information requested included

a list of all foods served at lunch, complete descriptions of the foods, amounts served, recipes for

foods prepared in the district, and labels (or vendors' names and addresses, so that nutrient

information could be requested) for all preprepared items purchased by the school's food service

program. Respondents were asked to complete one list of foods served every day and to complete,

for each day of the week, separate lists of foods that varied, by day. If the school offered a salad bar

or other self-serve bar, respondents were asked to furnish information about the first self-serve bar

offered during the week.2 Respondents were asked to indicate on a separate milk checklist the types

of milk served and the container sizes of each type of milk.

Staff at NCC coded the nutrients in each food item on the basis of the information provided.

In addition, study staff at NCC and MPR applied codes indicating to which USDA meal-pattern

requirement each food item contributed (USDA codes). They also applied codes linking items that

were served together (LINK codes). For example, if the school offered a cheeseburger, the cheese,

meat, and bun were linked. If it served mashed potatoes with gravy, the mashed potatoes and gravy

were linked. If it served a salad with salad dressing, the dressing was linked to the salad.

Two aspects of school food service posed analytical challenges. To compute the average

nutrients offered in a meal, the foods comprising the meal must be defined, and the nutrients in all

foods must be summed. In general, each meal offered was assumed to contain the numbers and types

'Target weeks were assigned randomly, and schools were asked to complete the data collectionduring one of three preassigned weeks, or during an agreed-on week with the school staff, if one ofthe preselected target weeks was unacceptable. In schools in which dietary intake data were collectedfrom students, the target week was always the week of the visit to the school.

2Most salad bars were offered every day. Some schools provided information on all salad barsduring the week, and the information was used, if available.

37

of food items required by the USDA meal pattern, plus any noncreditable food items linked to the

required items. 3 The first challenge was posed by the large number of choices that many school

cafeterias offer within the required meal components. Schools that offer choices posed an analytical

challenge because they made it necessary to take into account different possible combinations of

foods when calculating the average nutrient content of meals offered on each day of the target week.

The second challenge arose because, in some situations, students can choose the amount of the food

item (self-serve foods). For meals containing self-serve foods, the only way to estimate the average

nutrient content of the meal as offered is to make assumptions about the average amount of each

self-serve item offered by cafeterias.

Choice and self-service were more prevalent at the middle school and high school levels.

However, many elementary schools offered their students some choice among items and/or some self-

serve items.

B. CALCULATING THE AVERAGE NUTRIENTS IN NSLP LUNCHES AS OFFERED

To be reimbursable by the USDA, a school lunch must include at least:

• One serving of meat or meat alternate (2 ounces or equivalent)

• One or two servings of bread or bread alternate (at least eight servings per week), whereone serving is 1 slice of bread or equivalent

• Two or more distinct vegetables and fruits totalling 3/4 of a cup

One serving (8 ounces) of fluid milk

The basic approach to variable construction and analysis was to define, for each day of the target

week, the entrees offered, the breads offered that were not part of a particular entree, the fruits and

3Lunches were also assumed to include one serving of dessert (if offered), and one serving ofunlinked condiments (if offered). See Section B for more details.

38

vegetables offered, the types of milk offered, and the desserts and condiments offered. 4 The average

nutrient content of each lunch was calculated as the sum of the nutrients in one average entree, one

average bread, two average vegetable/fruit servings, one average milk, one average dessert (if

offered), and one average condiment (if offered).

The following sections describe the operational procedures and assumptions used to construct

these variables. The first section describes how lunch components were defined for non-self-serve

foods. The second section describes how salad bars (and other self-serve bars) were handled. The

third section describes how daily and weekly totals were calculated.

1. Defining Lunch Components for Non-Self-Serve Foods

The following rules were used to define the various components of lunch:

(1) Group together all foods that are served together, using the LINK codes.

(2) Define entrees:

• An entree is an item with a USDA meal-component code indicating meat, eitheralone or in combination with bread and or vegetable/fruit. 5 There may also beitems linked to an entree that do not contribute to a USDA meal component(sauces or condiments). In addition to meat, entrees included bread, but novegetable, 51 percent of the time; both bread and vegetable 29 percent of the time;and vegetable, but no bread, 7 percent of the time.

• For each entree, assign total nutrients (add up the nutrients in all linked foods), totalgram weight (add up the weight of all linked foods), and a USDA meal-componentcode (based on the USDA component codes for each of the linked foods thatcomprise the entree). For example, an entree could consist of a hamburger (USDAcode=meat) on a bun (USDA code=bread). The USDA code for the entree asa whole would be meat/bread.

(3) Define bread items to include breads and bread alternates that are not linked to any entreedefined above:

• These items include breads and bread alternates not part of entrees, and itemslinked to breads, such as butter or gravy.

4References to bread also include bread alternates, such as rice or pasta.

5"Meat" is used in the rest of this subsection to indicate meat or meat alternate.

39

• Assign total nutrients, total gram weight, and a USDA meal-component codeindicating bread to each bread item.

(4) Define vegetable/fruit items that are not linked to any of the entrees defined above:

• These items include vegetable or fruit dishes not linked to entrees, and items linkedto vegetables or fruits, such as butter, mayonnaise or salad dressing.

• Assign total nutrients, total gram weight, and a USDA meal-component codeindicating vegetable or fruit to each vegetable/fruit item.

• There are a few vegetable/bread items. Because most of these appear to besatisfying primarily the vegetable requirement, they are counted as vegetables only.

(5) Define desserts:

• Desserts are foods with Nationwide Food Consumption Survey (NFCS) codes inthese ranges: 531-536 (cakes, cookies, pies, cobblers), 915 (gelatin desserts), 916 (iceor popsicles), 917 (candies), or 131-132 (milk desserts).

• Most dessert items are coded as noncreditable foods (USDA code=none).However, some desserts are coded as vegetable/fruit items, because they containenough fruit to count toward the meal pattern. It appears that schools do notusually rely on desserts to satisfy the vegetable/fruit requirement; thus, fruit dessertsare coded as desserts, rather than as vegetable/fruit items. Each student is assumedto be offered one average dessert, if any are offered. (Thirty-eight percent ofmenus offer at least one dessert, and 8 percent offer at least two desserts.)

(6) Define condiments:

• Salad dressings (NFCS = 831 or 832) are always linked to the salads theyaccompany. Each student taking a salad is assumed to be offered one averageserving of salad dressing--i.e., when a choice of salad dressings is offered, thenutrients in each dressing are averaged.

• Other condiments (such as mayonnaise, pickles, catsup, or mustard) are not linked,except in the rare cases in which the link is unambiguous and obvious. A separatevariable was created for unlinked condiments. Such condiments can be defined asfollows: item is unlinked, and NFCS = 744 (catsup, salsa, barbecue sauce), 6 orNFCS = 755 (pickles, mustard, olives, Louisiana hot sauce), or NFCS = 831(mayonnaise)7

6744 also includes tomato sauce without meat and tomato paste, but these should always belinked.

7831 includes salad dressing, but salad dressing should always be linked to salad.

40

• Pickles may count as a vegetable, but most schools do not appear to be usingpickles as a vegetable. (At least 1/8 of a cup of pickles must be offered to countas a vegetable.) Thus, pickles are treated as a condiment. 8

(7) Define spreads:

• Spreads are defined as unlinked foods with NFCS codes 123 (sour cream), 143(cream cheese), 285 (gravy), 811 (butter or margarine), or 911-914 (sugar, syrup,jelly, jam). The nutrients in one serving of each type of spread offered areaveraged and then added to the nutrients in an average serving of bread (if anyunlinked breads). If there are no unlinked breads, the nutrients from the spreadsare added to the average entree.

2. Defining Lunch Components in Self-Serve Bars

Information on salad bars was provided by cafeteria managers on a form showing only the salad

bar items. Respondents provided complete descriptions, labels, and recipes, as with all other foods.

Sometimes amounts were indicated, but in most cases, respondents indicated only that the items were

"self-serve."

a. Nutrient Coding. When no amount was indicated, standardized amounts were assumed for

purposes of nutrient coding.

• For fruit/vegetable items that are likely to be a main ingredient in a salad (such aslettuce, tomato, carrot) 3/8-cup portions are coded (assuming at least two itemstotalling 3/4 of a cup to meet the meal-pattern requirement).

• For meat/meat alternate items, 2-ounce portions or equivalent are coded. 9

• For items that are likely to be toppings, and for condiments, spreads, and saladdressings, smaller standardized portions are coded.

8Portion sizes were assumed for self-serve condiments and spreads. See the discussion of saladbars.

9Later, these items were scaled up to 3 ounces, for middle and high school students. Seediscussion in subsection B.2.b.

41

These serving sizes were assumed for nutrient coding purposes. In some cases, amounts were

rescaled in the analysis (as discussed in the next section), and the nutrients in each item were adjusted

proportionately.

b. Overview of Analysis. The most difficult problem in the analysis of salad bars is to develop

reasonable assumptions about the quantity of each item offered and the combinations of items

offered. Several approaches to constructing a "meal" from a salad bar were considered.

One approach is to assume a student is offered the minimum amount necessary for the lunch

to be reimbursable. For example, the minimum could be defined as:

• 1 serving of bread (for example, one slice of bread or eight saltines)

• 2 ounces of meat/meat alternate

• 3/4 of a cup of fruit/vegetable, with at least two different items, plus 1 serving of saladdressing (if dressing offered)

However, this approach seems inappropriate, because schools are encouraged to offer more than the

minimum amounts, especially to older students, and salad bars enable students to take larger portions.

Another approach would be to assume students are offered one serving of everything on the salad

bar. A problem with this approach is that schools did not offer full portions of everything on the

salad bar. Furthermore, in some schools, so many items are offered that students who took a full

serving of each item would consume well over 1,000 calories (1,000 calories was judged the maximum

reasonable amount).

An intermediate approach between these extremes was chosen, which assumed that students are

offered the minimum, and that students are offered everything on the salad bar. This approach is

as follows:

• Assume students in elementary schools are offered the minimum plus up to three servingsof "topping."

Assume middle and high school students are offered:

42

3 ounces of meat or meat alternate1 serving of bread or bread alternate3/4 of a cup of vegetables (one-half of which is lettuce)

- 1 serving of fruitUp to 3 servings of "topping"1 serving of salad dressing

• When choices are offered for a given meal component on the salad bar (such as meat/meatalternate), average the nutrients in each choice, and rescale to the assumed amount, ifnecessary.

When salad bars did not offer all meal components, the meal components offered were coded using

the same rules as the rules for full salad bars.

All other food bars were coded in the same way (with the exception of potato bars). Potato bars

usually had amounts coded for each item by the schools. The serving sizes given were not rescaled.

The potato was coded as a vegetable. All nonmeat toppings were treated as condiments--one average

topping was linked to the potato. All meat toppings were averaged to equal one serving of meat.

When combining potato bar items with other items, the composite stuffed potato from the potato bar

was counted as one vegetable/fruit item if no meat toppings were served, and as one entree if any

meat was offered.

c. Details of Calculation of the Average Nutrients Offered in Salad Bars. The first step in

calculating the average nutrients offered in salad bars was to assign a portion size to each food. The

calculation was performed as follows:

• Meat/meat alternates (entrees)

Meats are foods with NFCS codes 140-147 (cheese), 210-284 (meat), or 311-350 (eggs).

If a food with one of these codes has a coded weight of less than 14 grams, the item isa "topping" (an example would be grated parmesan cheese). Bacon bits are alwayscoded as a topping.

If the coded weight is greater than or equal to 14 grams, rescale the serving size (andassociated nutrients) to 1.2 ounces (2 x 28.35 grams) for elementary schools or 2.3ounces (3 x 28.35 grams) for middle/high schools.

43

Assume students are offered one average serving of meat/meat alternate from the saladbar.

•

Breads and bread alternates

- Breads are foods with NFCS codes in the 500s.

If the coded weight is less than 2 grams, the item is a "topping" (for example, croutons).

If the coded weight is between 2 grams and 18 grams, inflate it to 20 grams (and inflatethe nutrients proportionately), and treat as one serving of bread.

If the coded weight is more than 18 grams, use the weight given and treat as oneserving of bread.

- Assume students are offered one average serving of bread.

- If the salad bar contains a meat/meat alternate, link the average nutrients in thebread/bread alternate to those in the meat/meat alternate, to form a composite entree.

• Vegetables and Fruits

- Vegetables are foods with NFCS codes 721-755.

- Fruits are foods with NFCS codes of 610-650.

- If the item is on the "topping" list, code as one topping. Otherwise, each item is codedas one serving of vegetable/fruit (3/8 of a cup).

Compute a weighted average of nutrients per serving of vegetable, in which one-halfof the amount of vegetable offered is assumed to be lettuce, with the balance equallydivided among all other vegetables on the salad bar.

For elementary schools, assume the student is offered either one average serving ofvegetable (3/8 of a cup) plus one average serving of fruit (3/8 of a cup) or two servingsof vegetable, if no fruit is offered.

For middle and high schools, assume students are offered either two average servingsof vegetable (3/4 of a cup) plus one average serving of fruit (3/8 of a cup) or threeservings of vegetable, if no fruit is offered.

"Toppings" include both salad garnishes (such as olives or grated cheese), condiments, and spreads.

The nutrients in an average topping and an average salad dressing are calculated for each salad bar.

The nutrients in up to three average toppings plus one average serving of salad dressing are then

added (linked) to the nutrients in the vegetable/fruit servings.

3. Calculation of Average Nutrients Offered per Day and per Week

To calculate the average nutrients in meals offered on each day of the week, all of the foods

offered were considered:

• Foods on the "all days" list were included with the foods served each day of the week, andcoded using the same rules.

• Items from salad (and other self-serve) bars were included along with other foods (seebelow).

• Milk items were marked on the milk checklist. In general, schools offered the same typesof milk each day, and most offered only 8-ounce servings. The nutrients in each type ofmilk offered were averaged and added to the total.

Three formulas were used to calculate the average nutrients offered for lunch each day. For "simple"

cases, in which the menu included no more than one entree, one bread (not in an entree), and three

vegetables or fruits, students were assumed to be offered all items, and the nutrients in all these

components were summed. For cases with choices among entrees or breads, or more than three

fruits and vegetables, but no salad bar, the following formula was used:

Average nutrients offered =(1 x average nutrients per entree) + (2 x average nutrients per vegetable/fruit) + (1 xaverage nutrients per bread) + (1 x average nutrients per milk) + (1 x average nutrients perdessert) + (1 x average nutrients per condiment)

For cases in which choices include a salad (or other self-service) bar:

• If salad bar includes an entree. The nutrients in the meat items on the salad bar wereaveraged into one composite meat (scaled--as described--to 2 ounces for elementary schoolsand 3 ounces for middle and high schools). The composite bread from the salad bar waslinked to the meat to make up a composite entree. Then, the nutrients across all entrees(including the one composite salad bar entree and all other entrees) were averaged.

45

• Other salad bar items. The composite bread from the salad bar was counted as one breadoffering if no entree was offered on the salad bar. The total nutrients in the compositevegetables and fruits from the salad bar were counted as two vegetable/fruit offerings incomputing the average for the day.

Then, the formula for average nutrients offered was applied.

For each school, the average nutrients offered in school lunches during the target week were

calculated by adding up the average nutrients offered each day and then dividing by the number of

days that lunch was served.

46

TABLE 81

INDICATORS OF AVERAGE FOOD ENERGY CONTENT OF LUNCHES (KILOCALORIES)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.24336 1 ON_DESS # times offered: Dessert

2 0.18326 1 02_DESS Offer 2+ times: Dessert

3 0.17639 1 ON_CHEES # times offered: Cheese

4 0.16816 1 ON_HIVEG # times offered: High Fat Vegetable

5 0.16414 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

6 0.16314 1 ON_FV4 # times offered: At least 4 fruit/veg

7 0.15235 -1 ELEMENT Elementary School

8 0.13128 1 ON_FRIES # times offered: French fries

9 0.11719 1 ON_FV3 # times offered: At least 3 fruit/veg

10 0.10400 1 ON_FRVEG # times offered: Fresh Vegetable

11 0.10317 1 HIGH High School

12 0.09049 1 ON_CBURG # times offered: Cheeseburger

13 0.08963 1 ON_FRESH # times offered: Fresh fruit or veg

14 0.08871 1 02_CHEES Offer 2+ times: Cheese

.15 0.08765 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

16 0.08502 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

17 0.08136 1 02_FRIES Offer 2+ times: French fries

18 0.07996 1 CERTPER Percent Students certified free/RP

19 0.07787 1 OL_DESS Offer for lunch: Dessert

20 0.07615 1 ON_SALTY # times offered: Chips/Salty snacks

21 0.07313 1 OL_FRIES Offer for lunch: French fries

22 0.07133 1 VENDING Vending Machine available

23 0.06955 1 ON_PIZZA # times offered: Pizza

24 0.06701 1 02_CBURG Offer 2+ times: Cheeseburger

25 0.06346 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

26 0.06261 1 02_HIVEG Offer 2+ times: High Fat Vegetable

27 0.05741 1 OL_CBURG Offer for lunch: Cheeseburger

28 0.05641 1 ON_ICECR # times offered: Ice cream

29 0.05441 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

30 0.05141 1 FPRICELN Full price for lunch (dollars)

31 0.04674 1 02_PIZZA Offer 2+ times: Pizza

32 0.04542 1 02_SALTY Offer 2+ times: Chips/Salty snacks

33 0.04344 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

34 0.04309 1 OVSLUNCH Offer verse Serve (OVS) at lunch

35 0.04143 1 ON_FRYPL Offer for lunch: Fries, hashbrowns,etc

36 0.04013 1 02_ICECR Offer 2+ times:

Ice cream

37 0.04007 1 ON_LOFAT # times offered: Low Fat Entree

---------------------- -------------------------------------------------------------38 0.03877 1 02_FRVEG Offer 2+ times: Fresh Vegetable

39 0.03747 1 OL_HIVEG Offer for lunch: High Fat Vegetable

40 0.03729 1 ON_FRFR # times offered: Fresh Fruit

41 0.03709 1 OL_ICECR Offer for lunch: Ice cream42 0.03618 1 OL_CHEES Offer for lunch: Cheese

43 0.03383 1 ON_BURG # times offered: Hamburger

44 0.03345 1 02_BURG Offer 2+ times: Hamburger

45 0.03244 1 OLFV3 Offer for lunch: At least 3 fruit/veg

46 0.03211 1 02_HOTDG Offer 2+ times: Hot Dog47 0.03142 1 ON_HOTDG # times offered: Hot Dog

48 0.03012 1 OL_FRESH Offer for lunch: Fresh fruit or veg49 0.02846 1 ON_PBCH # times offered: Prebreaded chicken/turk50 0.02748 1 ON_BUFF # times offered: Buffet style food bar

49

TABLE 82

INDICATORS OF AVERAGE FAT CONTENT OF LUNCHES (KILOCALORIES)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.15734 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

2 0.14049 1 ON_FRIES # times offered: French fries

3 0.13792 1 ON_DESS # times offered: Dessert

4 0.13675 1 ON_HIVEG # times offered: High Fat Vegetable

5 0.12533 1 02_DESS Offer 2+ times: Dessert

6 0.12130 1 ON_CHEES # times offered: Cheese

7 0.10878 -1 ELEMENT Elementary School

8 0.10603 1 OL_FRIES Offer for lunch: French fries

9 0.09907 1 ON_FV4 # times offered: At least 4 fruit/veg

10 0.09477 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

11 0.09218 1 02_FRIES Offer 2+ times: French fries

12 0.08854 1 HIGH High School

13 0.08043 1 ON_FRVEG # times offered: Fresh Vegetable

14 0.07284 1 ON_FV3 # times offered: At least 3 fruit/veg

15 0.06610 1 ON_FRESH # times offered: Fresh fruit or veg

16 0.06460 1 02_HIVEG Offer 2+ times: High Fat Vegetable

17 0.06359 1 OL_FRYPL Offer for lunch: Fries, hashbrowns,etc

18 0.05940 1 ON_CBURG # times offered: Cheeseburger

19 0.05615 1 VENDING Vending Machine available

20 0.05463 1 02_CHEES Offer 2+ times: Cheese

21 0.05442 1 CERTPER Percent Students certified free/RP

22 0.05079 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

23 0.04889 1 OL_CBURG Offer for lunch: Cheeseburger

24 0.04270 1 ON SALTY # times offered: Chips/Salty snacks

25 0.04142 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

26 0.04127 1 02_CBURG Offer 2+ times: Cheeseburger

-------------------------------------------- _____________________________________________

27 0.03905 1 OL HIVEG Offer for lunch: High Fat Vegetable

28 0.03724 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

29 0.03686 1 OL_DESS Offer for lunch: Dessert

30 0.03358 1 FPRICELN Full price for lunch (dollars)

31 0.03328 1 OL_CHEES Offer for lunch: Cheese

32 0.03212 1 ON_HOTDG # times offered: Hot Dog

33 0.03096 1 02_FRVEG Offer 2+ times: Fresh Vegetable

34 0.03068 1 02_HOTDG Offer 2+ times: Hot Dog

35 0.02938 1 ON_PIZZA # times offered: Pizza

36 0.02827 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

37 0.02794 1 OL_FV3 Offer for lunch: At least 3 fruit/veg

38 0.02564 1 ON_PBCH # times offered: Prebreaded chicken/turk

39 0.02421 1 OVSLUNCH Offer verse Serve (OVS) at lunch

40 0.02343 1 02_SALTY Offer 2+ times: Chips/Salty snacks

41 0.02314 1 OL_FRESH Offer for lunch: Fresh fruit or veg

42 0.02209 1 ON_ICECR # times offered: Ice cream

43 0.02042 -1 SCHSBP Offer SBP breakfast

44 0.01979 1 ENROLLMT Total school enrollment

45 0.01883 -1 RC_CFAT Recommended GL-Energy from fat 30-35%

46 0.01859 -1 RR_DESS Recommended/Required GL-Limit dessert

47 0.01833 1 02_BURG Offer 2+ times: Hamburger

48 0.01752 1 ON_SALBR # times offered: Salad Bar

49 0.01714 1 02_PIZZA Offer 2+ times: Pizza

50 0.01698 1 OL_ICECR Offer for lunch: Ice cream

50

TABLE B3

INDICATORS OF AVERAGE FAT CONTENT OF LUNCHES (AS PERCENTAGE OF TOTAL FOOD ENERGY)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.10335 -1 02_LOFAT Offer 2+ times: Low Fat Entree

2 0.09089 -1 ON_LOFAT # times offered: Low Fat Entree

3 0.08067 -1 OL_LOFAT Offer for Lunch: Low Fat Entree

4 0.06522 1 OL_FRIES Offer for Lunch: French fries

5 0.04588 1 ON_FRIES # times offered: French fries

6 0.04055 1 OL_FRYPL Offer for lunch: Fries, hashbrowns,etc

-----------------------------------------------------------------------------------------

7 0.03909 1 02_FRIES Offer 2+ times: French fries

8 0.03824 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

9 0.03477 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

10 0.02490 1 02_HIVEG Offer 2+ times: High Fat Vegetable

11 0.02431 1 ON_HIVEG # times offered: High Fat Vegetable

12 0.02373 -1 N_RECS Total number recommended guidelines

13 0.02301 -1 RC_VEGET Recommended GL-Increase vegetable

14 0.02187 -1 RC GRAIN Recommended GL-Increase whole grain

15 0.01998 -1 RC_FIBER Recommended GL-Increase fiber

16 0.01857 -1 RC_CHSOD Recommended GL-Cholesterol and/or sodium

17 0.01772 -1 RC_SODIU Recommended GL-Limit sodium

18 0.01742 -1 RC FRUIT Recommended GL-Increase fruit

19 0.01741 -1 RR VEGET Recommended/Required GL-Increase vegetable

20 0.01707 -1 RR_GRAIN Recommended/Required GL-Increase whole grain

21 0.01705 -1 RC_SFAT Recommended GL-Limit saturated fat

22 0.01700 -1 RC_CFAT Recommended GL-Energy from fat 30-35%

23 0.01631 -1 RC_FRVEG Recommended GL-Fruits and/or vegetables

24 0.01568 -1 RC_COMPT Recommended GL-Limit competitive food

25 0.01555 -1 N _RR Total number guidelines

26 0.01551 -1 RR_CHSOD Recommended/Required GL-Cholesterol and/or sodium

27 0.01464 1 OL_HIVEG Offer for lunch: High Fat Vegetable

28 0.01463 -1 RR_CFAT Recommended/Required GL-Energy from fat 30-35%

29 0.01411 -1 RC_SWEET Recommended GL-Dessert and/or sugar

30 0.01378 -1 ON_FRFR # times offered: Fresh Fruit

31 0.01339 1 HIGH High School

32 0.01323 -1 RC FAT Recommended GL-Total fat and/or sat fat

33 0.01300 -1 RR_SFAT Recommended/Required GL-Limit saturated fat

34 0.01286 -1 EV_COMPU Evaluation nutrition: computer analysis

35 0.01284 -1 RR_FRVEG Recommended/Required GL-Fruits and/or vegetables

36 0.01276 -1 RC_SUGAR Recommended GL-Limit sugar

37 0.01263 -1 RC_CHOL Recommended GL-Limit cholesterol

38 0.01241 -1 RC_DESS Recommended GL-Limit dessert

39 0.01232 -1 PRLFDELI Practice: Lower fat hot dog/sandwich meat

40 0.01222 -1 RR_CHOL Recommended/Required GL-Limit cholesterol

41 0.01158 -1 RR_FIBER Recommended/Required GL-Increase fiber

42 0.01148 -1 OL_WWBR Offer for lunch: Whole wheat bread

43 0.01085 -1 02_WWBR Offer 2+ times: Whole wheat bread

44 0.01084 -1 RR_FRUIT Recommended/Required GL-Increase fruit

45 0.01078 -1 RR_DESS Recommended/Required GL-Limit dessert

46 0.01073 1 ON_FRVEG # times offered: Fresh Vegetable

47 0.01066 -1 RR_SWEET Recommended/Required GL-Dessert and/or sugar

48 0.01061 -1 OL_CHIPS Offer for lunch: Potato chips

49 0.00980 -1 RR SODIU Recommended/Required GL-Limit sodium

50 0.00977 -1 RR_FAT Recommended/Required GL-Total fat and/or sat fat

51

TABLE 84

INDICATORS OF AVERAGE SATURATED FAT CONTENT OF LUNCHES (KILOCALORIES)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.14279 1 ON_DESS # times offered: Dessert

2 0.13509 1 02_DESS Offer 2+ times: Dessert

3 0.12129 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

4 0.11125 1 ON_HIVEG # times offered: High Fat Vegetable

5 0.09675 1 ON_CHEES # times offered: Cheese

6 0.07829 1 ON_FRIES # times offered: French fries

7 0.07169 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

8 0.06895 -1 ELEMENT Elementary School

9 0.06879 1 02_CHEES Offer 2+ times: Cheese

10 0.06701 1 02_HIVEG Offer 2+ times: High Fat Vegetable

11 0.06552 1 HIGH High School

12 0.06521 1 OL_FRYPL Offer for lunch: Fries, hashbrowns,etc

13 0.06348 -1 CERTPER Perc Students certified free/RP

14 0.05827 1 OL_FRIES Offer for lunch: French fries

15 0.05260 1 ON_CBURG # times offered: Cheeseburger

16 0.05222 1 OL_CBURG Offer for lunch: Cheeseburger

17 0.04890 1 VENDING Vending Machine available

18 0.04307 1 02_FRIES Offer 2+ times: French fries

19 0.04216 1 OL_DESS Offer for lunch: Dessert

20 0.04172 1 ON_SALTY # times offered: Chips/Salty snacks

21 0.04094 1 ON FV4 # times offered: At least 4 fruit/veg

22 0.03628 1 02_CBURG Offer 2+ times: Cheeseburger

23 0.03608 1 ON_FV3 # times offered: At least 3 fruit/veg

24 0.03490 1 OL_HIVEG Offer for lunch: High Fat Vegetable

25 0.03371 1 OL_CHEES Offer for lunch: Cheese

26 0.03330 1 ON_FRVEG # times offered: Fresh Vegetable

27 0.02798 -1 SCHSBP Offer SBP breakfast

28 0.02728 -1 RR_DESS Recommended/Required GL-Limit dessert

29 0.02711 -1 02_LOFAT Offer 2+ times: Low Fat Entree

30 0.02577 1 ON_HOTDG # times offered: Hot Dog

31 0.02488 1 FPRICELN Full price for lunch (dollars)

32 0.02433 -1 RC_CFAT Recommended GL-Energy from fat 30-35%

33 0.02413 1 ON_FRESH # times offered: Fresh fruit or veg

34 0.02355 1 OL_FV3 Offer for lunch: At least 3 fruit/veg

35 0.02340 -1 RC_DESS Recommended GL-Limit dessert

36 0.02325 -1 PRLFDELI Practice:

lower fat hot dog/sandwich meat

37 0.02283 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

38 0.02273 1 ON_ICECR # times offered: Ice cream

39 0.02266 -1 N_EVS Total number evaluation procedures

40 0.02242 -1 RR_CFAT Recommended/Required GL-Energy from fat 30-35%

41 0.02052 -1 RC_GRAIN Recommended GL-Increase whole grain

42 0.02045 -1 GL_DESS Guideline-Limit dessert

43 0.01983 -1 EV_COMPU Evaluation nutrition: computer analysis

44 0.01961 -1 N_RECS Total number recommended guidelines

45 0.01922 1 PRDRAIN Practice: drain cooked ground beef

46 0.01907 1 02_HOTDG Offer 2+ times: Hot Dog

47 0.01866 -1 RC_FIBER Recommended GL-Increase fiber

48 0.01830 1 ON_PIZZA # times offered: Pizza

49 0.01827 -1 RR_GRAIN Recommended/Required GL-Increase whole grain

50 0.01794 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

52

TABLE B5

INDICATORS OF AVERAGE SATURATED FAT CONTENT OF LUNCHES (AS PERCENTAGE OF TOTAL FOOD ENERGY)

RANK

R-squared

SIGN

VAR NAME

VARIABLE

DESCRIPTION

1

0.16746

-1

ON_LOFAT

# times offered: Low Fat Entree

2

0.15386

-1

02_LOFAT

Offer 2+ times: Low Fat Entree

3

0.10141

-1

OL_LOFAT

Offer for lunch: Low Fat Entree

-----------------------------------------------------------------------------------------

4 0.03830 -1 ON_WWBR # times offered: Whole wheat bread

5 0.03720 -1 ON_FRFR # times offered: Fresh Fruit

6 0.03340 -1 ON_FV4 # times offered: At least 4 fruit/veg

7 0.03300 -1 02_WWBR Offer 2+ times: Whole wheat bread

8 0.03063 -1 EV_COMPU Evaluation nutrition: computer analysis

9 0.03036 -1 N_RECS Total number recommended guidelines

10 0.02751 -1 RC SODIU Recommended GL-Limit sodium

11 0.02700 -1 RC_VEGET Recommended GL-Increase vegetable

12 0.02673 -1 PRLFDELI Practice:

lower fat hot dog/sandwich meat

13 0.02623 -1 EV_USDAL Evaluation nutrition:

Literature from USDA

14 0.02492 -1 RR_VEGET Recommended/Required GL-Increase vegetable

15 0.02490 -1 RC_SWEET Recommended GL-Dessert and/or sugar

16 0.02474 -1 RC FIBER Recommended GL-Increase fiber

17 0.02455 -1 RC GRAIN Recommended GL-Increase whole grain

18 0.02428 -1 OL_WWBR Offer for lunch: Whole wheat bread

19 0.02413 -1 RC_DESS Recommended GL-Limit dessert

20 0.02303 -1 RC_SUGAR Recommended GL-Limit sugar

21 0.02188 1 OL_FRYPL Offer for lunch: Fries, hashbrowns,etc

22 0.02075 -1 N _RR Total number guidelines

23 0.02061 -1 RR GRAIN Recommended/Required GL-Increase whole grain

24 0.02049 -1 RR_CFAT Recommended/Required GL-Energy from fat 30-35%

25 0.02039 -1 ON_FRESH # times offered: Fresh fruit or veg

26 0.02032 -1 N_PRACS Total number healthy food prep practices

27 0.02024 -1 RC_CHSOD Recommended GL-Cholesterol and/or sodium

28 0.01969 -1 DISTGL District guidelines for nutrition

29 0.01893 -1 N_EVS Total number evaluation procedures

30 0.01825 -1 RC_VARTY Recommended GL-Increase variety

31 0.01817 -1 RC_SFAT Recommended GL-Limit saturated fat

32 0.01801 -1 OL_GYVEG Offer for lunch: Dark Green/Yellow Veg

33 0.01799 -1 RC_CFAT Recommended GL-Energy from fat 30-35%

34 0.01787 -1 ON_GYVEG # times offered: Dark Green/Yellow Veg

35 0.01765 -1 RR_DESS Recommended/Required GL-Limit dessert

36 0.01713 -1 RR_CHSOD Recommended/Required GL-Cholesterol and/or sodium

37 0.01701 -1 RR_FIBER Recommended/Required GL-Increase fiber

38 0.01688 -1 GL_CFAT Guideline-Energy from fat 30-35%

39 0.01675 -1 ON_FV3 # times offered: At least 3 fruit/veg

40 0.01668 -1 02 FRFR Offer 2+ times: Fresh Fruit

41 0.01557 -1 RR_SWEET Recommended/Required GL-Dessert and/or sugar

42 0.01531 -1 GL_VEGET Guideline-Increase vegetable

43 0.01527 -1 RC_FRUIT Recommended GL-Increase fruit

44 0.01515 -1 ON_FRVEG # times offered: Fresh Vegetable

45 0.01499 -1 RR_VARTY Recommended/Required GL-Increase variety

46 0.01417 -1 02_FV4 Offer 2+ times: At least 4 fruit/veg

47 0.01400 -1 RR_SUGAR Recommended/Required GL-Limit sugar

48 0.01367 -1 RC_FRVEG Recommended GL-Fruits and/or vegetables

49 0.01349 -1 RC_CHOL Recommended GL-Limit cholesterol

50 0.01308 -1 RR_FRVEG Recommended/Required GL-Fruits and/or vegetables

53

TABLE B6

INDICATORS OF AVERAGE CHOLESTEROL CONTENT OF LUNCHES (MG)

RANK

R-squared

SIGN

1

0.10656

1

2

0.08410

1

3

0.08176

1

4

0.08086

-1

5

0.07780

1

6

0.07386

1

7

0.07382

1

8

0.06865

1

9

0.06327

1

10

0.06308

1

11

0.06271

1

12

0.05980

1

13

0.05866

1

14

0.05850

1

15

0.05684

1

16

0.05176

1

17

0.04607

1

18

0.04450

1

-----------------------------

VAR NAME

VARIABLE DESCRIPTION

ON_HIVEG

# times offered: High Fat Vegetable

ON_DESS

# times offered: Dessert

ON_CHEES

# times offered: Cheese

ELEMENT

Elementary School

ON_FV4

# times offered: At least 4 fruit/veg

ON_FRIES

# times offered: French fries

02_DESS

Offer 2+ times: Dessert

ON_GYVEG

# times offered: Dark Green/Yellow Veg

02_FRIES

Offer 2+ times: French fries

ON_FRVEG

# times offered: Fresh Vegetable

HIGH

High School

02_HIVEG

Offer 2+ times: High Fat Vegetable

ON_FV3

# times offered: At least 3 fruit/veg

ON_FRYPL

# times offered: Fries, hashbrowns,etc

OL_FRIES

Offer for lunch: French fries

OL_CBURG

Offer for Lunch: Cheeseburger

02_FV4

Offer 2+ times: At least 4 fruit/veg

ON_FRESH

# times offered: Fresh fruit or veg

-----------------------------------------------------------

19

0.03379

20

0.03363

1

21

0.03259

1

22

0.02957

1

23

0.02915

1

24

0.02893

1

25

0.02681

1

26

0.02439

1

27

0.02209

1

28

0.02178

1

29

0.01788

1

30

0.01753

1

31

0.01540

1

32

0.01524

1

33

0.01429

1

34

0.01425

-1

35

0.01422

1

36

0.01355

-1

37

0.01288

1

38

0.01232

1

39

0.01169

1

40

0.01089

1

41

0.01071

1

42

0.01063

1

43

0.00964

-1

44

0.00962

1

45

0.00954

-1

46

0.00889

1

47

0.00862

1

48

0.00830

1

49

0.00820

1

50

0.00820

-1

1

02_CHEES

Offer 2+ times: Cheese

VENDING

Vending Machine available

02_FRYPL

Offer 2+ times: Fries, hashbrowns,etc

OL_DESS

Offer for lunch: Dessert

02_GYVEG

Offer 2+ times: Dark Green/Yellow Veg

ON_CBURG

# times offered: Cheeseburger

OL_FRYPL

Offer for lunch: Fries, hashbrowns,etc

OL_FV4

Offer for lunch: At least 4 fruit/veg

FPRICELN

Full price for lunch (dollars)

ENROLLMT

Total school enrollment

02_FRVEG

Offer 2+ times: Fresh Vegetable

02_FV3

Offer 2+ times: At least 3 fruit/veg

OL_CHEES

Offer for lunch: Cheese

OVSLUNCH

Offer verse Serve (OVS) at lunch

OL_HIVEG

Offer for lunch: High Fat Vegetable

EV_USDAL

Evaluation nutrition: literature from USDA

LPR_SCHL

Food preparation(lunch): School

CERTPER

Perc Students certified free/RP

02_CBURG

Offer 2+ times: Cheeseburger

ON_BUFF

# times offered: Buffet style food bar

OL_FRESH

Offer for lunch: Fresh fruit or veg

OL_FRVEG

Offer for lunch: Fresh Vegetable

02_BUFF

Offer 2+ times: Buffet style food bar

ON_SALBR

# times offered: Salad Bar

PRLFMEAT

Practice: substitute chick/fish for meat

PRDRAIN

Practice: drain cooked ground beef

RC_DESS

Recommended GL-Limit dessert

02_SALTY

Offer 2+ times: Chips/Salty snacks

ON_SALTY

# times offered: Chips/Salty snacks

02_SALBR

Offer 2+ times: Salad Bar

OL_BUFF

Offer for lunch: Buffet style food bar

RC_VEGET

Recommended GL-Increase vegetable

54

TABLE 87

INDICATORS OF AVERAGE CHOLESTEROL CONTENT OF LUNCHES (WHETHER CHOLESTEROL <= 100 MG)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.085158 -1 ON_DESS # times offered: Dessert

2 0.062779 -1 02_DESS Offer 2+ times: Dessert

3 0.055899 -1 ON_HIVEG # times offered: High Fat Vegetable

4 0.050843 -1 ON_FV4 # times offered: At least 4 fruit/veg

5 0.050576 -1 ON_FRIES # times offered: French fries

6 0.050286 -1 ON_CHEES # times offered: Cheese

7 0.040052 1 ELEMENT Elementary School

-----------------------------------------------------------------------------------------

8 0.037995 -1 02_FRIES Offer 2+ times: French fries

9 0.037696 -1 OL_FRIES Offer for lunch: French fries

10 0.037616 -1 ON_GYVEG # times offered: Dark Green/Yellow Veg

11 0.035856 -1 02_FV4 Offer 2+ times: At least 4 fruit/veg

12 0.034568 -1 ON_FRVEG # times offered: Fresh Vegetable

13 0.034150 -1 HIGH High School

14 0.033080 -1 OL_DESS Offer for lunch: Dessert

15 0.032344 -1 OL_CBURG Offer for lunch: Cheeseburger

16 0.031508 -1 ON_FRYPL # times offered: Fries, hashbrowns,etc

17 0.030809 -1 ON_FV3 # times offered: At least 3 fruit/veg

18 0.028201 -1 02_HIVEG Offer 2+ times: High Fat Vegetable

19 0.025648 -1 02_CHEES Offer 2+ times: Cheese

20 0.023164 -1 ON_FRESH # times offered: Fresh fruit or veg

21 0.021841 -1 VENDING Vending Machine available

22 0.020875 1 CERTPER Perc Students certified free/RP

23 0.019937 -1 OL_FV4 Offer for lunch: At least 4 fruit/veg

24 0.018004 -1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

25 0.015634 1 RC_DESS Recommended GL-Limit dessert

26 0.015165 -1 FPRICELN Full price for lunch (dollars)

27 0.014807 1 RR_DESS Recommended/Required GL-Limit dessert

28 0.013567 -1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

29 0.012792 1 RR_GRAIN Recommended/Required GL-Increase whole grain

30 0.012553 -1 ON_CBURG # times offered: Cheeseburger

31 0.012469 1 RC_GRAIN Recommended GL-Increase whole grain

32 0.012446 1 GL_CFAT Guideline-Energy from fat 30-35%

33 0.012204 1 RC_SWEET Recommended GL-Dessert and/or sugar

34 0.011936 -1 ENROLLMT Total school enrollment

35 0.011231 1 RR_VEGET Recommended/Required GL-Increase vegetable

36 0.011215 -1 02_FRVEG Offer 2+ times: Fresh Vegetable

37 0.011133 1 02_LOFAT Offer 2+ times: Low Fat Entree

38 0.011049 1 PRLFDELI Practice:

lower fat hot dog/sandwich meat

39 0.011034 1 RQ_FAT Reqrd GL-Total fat and/or sat fat

40 0.011001 -1 ON_BUFF # times offered: Buffet style food bar

41 0.010917 -1 02_FV3 Offer 2+ times: At least 3 fruit/veg

42 0.010776 1 RR_SWEET Recommended/Required GL-Dessert and/or sugar

43 0.010046 -1 OL_FRESH Offer for lunch: Fresh fruit or veg

44 0.010045 -1 OL_CHEES Offer for lunch: Cheese

45 0.010033 1 GL_VEGET Guideline-Increase vegetable

46 0.009842 1 RR_CFAT Recommended/Required GL-Energy from fat 30-35%47 0.009399 1 N_EVS Total number evaluation procedures

48 0.009360 1 GL_GRAIN Guideline-Increase whole grain

49 0.009338 -1 02_SALTY Offer 2+ times: Chips/Salty snacks

50 0.009325 1 GL FRUIT Guideline-Increase fruit

55

TABLE B8

INDICATORS OF AVERAGE SODIUM CONTENT OF LUNCHES (MG)

RANK

R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1

0.20404 ON_HIVEG # times offered: High Fat Vegetable

2

0.18794 ON_CHEES # times offered: Cheese

3

0.18207 ON_FRYPL # times offered: Fries, hashbrowns,etc

4

0.18175 -1 ELEMENT Elementary School

5

0.13217 HIGH High School

6

0.13003 ON_FRIES # times offered: French fries

7

0.11329 ON_FRVEG # times offered: Fresh Vegetable

8

0.11206 ON_FV4 # times offered: At least 4 fruit/veg

9

0.11050 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

10

0.09269 02_CHEES Offer 2+ times: Cheese

11

0.09214 02_FRIES Offer 2+ times: French fries

12

0.08654 1 ON_FRESH # times offered: Fresh fruit or veg

13

0.08190 1 02_HIVEG Offer 2+ times: High Fat Vegetable

14

0.07869 1 ON_CBURG # times offered: Cheeseburger

15

0.07827 1 VENDING Vending Machine available

16

0.07406 1 ON_FV3 # times offered: At least 3 fruit/veg

17

0.06721 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

18

0.06304 ON_DESS # times offered: Dessert

19

0.06094 1 OL_FRIES Offer for lunch: French fries

20

0.05861 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

21

0.05777 1 OL_CBURG Offer for lunch: Cheeseburger

22

0.05700 1 OL_FRYPL Offer for lunch: Fries, hashbrowns,etc

23

0.05689 1 02_CBURG Offer 2+ times: Cheeseburger

24

0.05485 ON_PIZZA # times offered: Pizza

25

0.05467 ON_LOFAT # times offered: Low Fat Entree

26

0.05265 02_DESS Offer 2+ times: Dessert

27

0.04883 ENROLLMT Total school enrollment

28

0.04782 OL_CHEES Offer for Lunch: Cheese

------------------

29

0.03997 1 02_FRVEG Offer 2+ times: Fresh Vegetable

30

0.03923 1 ON BURG # times offered: Hamburger

31

0.03818 1 OVSLUNCH Offer verse Serve (OVS) at lunch

32

0.03812 1 02_PIZZA Offer 2+ times: Pizza

33

0.03637 1 ON_SALBR # times offered: Salad Bar

34

0.03631 1 ON_BUFF # times offered: Buffet style food bar

35

0.03490 1 LPR_SCHL Food preparation(lunch): School

36

0.03314 1 FPRICELN Full price for Lunch (dollars)

37

0.03277 1 02 BURG Offer 2+ times: Hamburger

38

0.03239 1 ON_PBCH # times offered: Prebreaded chicken/turk

39

0.03224 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

40

0.03172 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

41

0.03160 1 ON_SALTY # times offered: Chips/Salty snacks

42

0.03054 1 02_SALBR Offer 2+ times: Salad Bar

43

0.03026 1 ON_HOTDG # times offered: Hot Dog

44

0.02986 1 02_BUFF Offer 2+ times: Buffet style food bar

45

0.02954 1 OL_HIVEG Offer for lunch: High Fat Vegetable

46

0.02891 1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

47

0.02725 1 OL_BUFF Offer for lunch: Buffet style food bar

48

0.02637 1 02_HOTDG Offer 2+ times: Hot Dog

49

0.02481 -1 CERTPER Perc Students certified free/RP

50

0.02469 1 OL_SALBR Offer for lunch: Salad Bar

56

TABLE B9

INDICATORS OF AVERAGE VITAMIN C CONTENT OF LUNCHES (MG)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.17902 1 ON_FV4 # times offered: At least 4 fruit/veg

2 0.14842 1 ON_FRFR # times offered: Fresh Fruit

3 0.14402 1 ON_CHEES # times offered: Cheese

4 0.12610 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

5 0.11021 1 ON_FV3 # times offered: At least 3 fruit/veg

6 0.10106 1 02_FRFR Offer 2+ times: Fresh Fruit

7 0.09737 1 02_CHEES Offer 2+ times: Cheese

8 0.09656 1 ON_HIVEG # times offered: High Fat Vegetable

9 0.09428 1 ON_FRESH # times offered: Fresh fruit or veg

10 0.08566 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

11 0.08557 1 ON_FRVEG # times offered: Fresh Vegetable

12 0.07044 -1 ELEMENT Elementary School

13 0.06403 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

14 0.06400 1 ON_FRIES # times offered: French fries

15 0.06360 1 OL_FRFR Offer for lunch:

Fresh Fruit

16 0.05304 1 ON_DESS # times offered: Dessert

17 0.05103 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

18 0.04551 1 02_FRIES Offer 2+ times: French fries

19 0.04448 1 OVSLUNCH Offer verse Serve (OVS) at lunch

20 0.04209 1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

-------------------------- --------------------------------------------------------------

21 0.03713 1 02_HOTDG Offer 2+ times: Hot Dog

22 0.03672 1 O2_FV3 Offer 2+ times: At least 3 fruit/veg

23 0.03645 1 02_HIVEG Offer 2+ times: High Fat Vegetable

24 0.03639 1 ON_CBURG # times offered: Cheeseburger

25 0.03492 1 02_FRVEG Offer 2+ times: Fresh Vegetable

26 0.03178 1 ON_SALBR # times offered: Salad Bar

27 0.03110 1 ON_BUFF # times offered: Buffet style food bar

28 0.03106 1 02_SALBR Offer 2+ times: Salad Bar

29 0.03098 1 OL_SALBR Offer for lunch: Salad Bar

30 0.03065 1 02_BURG Offer 2+ times: Hamburger

31 0.03023 1 02_BUFF Offer 2+ times: Buffet style food bar

32 0.03009 1 HIGH High School

33 0.02976 1 OL_BUFF Offer for lunch: Buffet style food bar

34 0.02904 1 VENDING Vending Machine available

35 0.02880 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

36 0.02831 1 OL_CBURG Offer for lunch: Cheeseburger

37 0.02803 1 ON_PIZZA # times offered: Pizza

38 0.02764 1 OL_GYVEG Offer for lunch: Dark Green/Yellow Veg

39 0.02639 1 LPR_CKIT Food preparation(lunch): Central kitchen

40 0.02593 1 02_CBURG Offer 2+ times: Cheeseburger

41 0.02488 1 ON_HOTDG # times offered: Hot Dog

42 0.02487 1 OL_CHEES Offer for lunch: Cheese

43 0.02324 1 02_PIZZA Offer 2+ times: Pizza

44 0.02183 1 TRUNC4 School has 4 days of data

45 0.02110 1 TRUNC School has < 5 days of data

46 0.02089 1 OL_HIVEG Offer for lunch: High Fat Vegetable

47 0.01998 1 OL_FRIES Offer for lunch: French fries

48 0.01766 1 ON_LOFAT # times offered: Low Fat Entree

49 0.01741 1 02_DESS Offer 2+ times: Dessert

50 0.01712 1 OL_DESS Offer for lunch: Dessert

57

TABLE B10

INDICATORS OF AVERAGE CALCIUM CONTENT OF LUNCHES (MG)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.24364 1 ON_CHEES # times offered: Cheese

2 0.22096 1 02_CHEES Offer 2+ times: Cheese

3 0.11184 1 ON_PIZZA # times offered: Pizza

4 0.10287 1 ON_FRVEG # times offered: Fresh Vegetable

5 0.09722 1 ON_FRESH # times offered: Fresh fruit or veg

6 0.08503 1 ON_PIZZA Offer for lunch: Pizza

7 0.07582 -1 ELEMENT Elementary School

8 0.07483 1 ON_FV4 # times offered: At least 4 fruit/veg

9 0.07060 1 OL_CHEES Offer for lunch: Cheese

10 0.07019 1 02_PIZZA Offer 2+ times: Pizza

11 0.06820 1 ON_FV3 # times offered: At least 3 fruit/veg

12 0.06399 1 HIGH High School

13 0.05911 1 ON_CBURG # times offered: Cheeseburger

14 0.05826 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

15 0.05553 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

16 0.05418 1 02_FRVEG Offer 2+ times: Fresh Vegetable

17 0.05172 1 ON_ICECR # times offered: Ice cream

18 0.05026 1 02_CBURG Offer 2+ times: Cheeseburger

19 0.04695 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

20 0.04282 1 FPRICELN Full price for lunch (dollars)

21 0.04165 1 OVSLUNCH Offer verse Serve (OVS) at lunch

22 0.04135 1 ON_LOFAT # times offered: Low Fat Entree

23 0.04132 1 OL_CBURG Offer for lunch: Cheeseburger

24 0.04082 1 ON_SALBR # times offered: Salad Bar

25 0.04064 1 02 SALBR Offer 2+ times: Salad Bar

------------------------- ---------------------------------------------------------

26 0.03953 1 02_BUFF Offer 2+ times: Buffet style food bar

27 0.03907 1 ON_BUFF # times offered: Buffet style food bar

28 0.03775 1 OL_ICECR Offer for lunch: Ice cream

29 0.03555 1 ON_FRIES # times offered: French fries

30 0.03535 1 02_ICECR Offer 2+ times: Ice cream

31 0.03530 1 OL_SALBR Offer for lunch: Salad Bar

32 0.03500 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

33 0.03449 1 ENROLLMT Total school enrollment

34 0.03412 1 OL_BUFF Offer for lunch: Buffet style food bar

35 0.03267 1 ON_HIVEG # times offered: High Fat Vegetable

36 0.03256 1 ON_DESS # times offered: Dessert

37 0.02899 1 VENDING Vending Machine available

38 0.02890 1 ON_SALTY # times offered: Chips/Salty snacks

39 0.02656 1 OL_FV4 Offer for Lunch: At least 4 fruit/veg

40 0.02579 -1 CERTPER Perc Students certified free/RP

41 0.02520 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

42 0.02466 1 ON_HOTDG # times offered: Hot Dog

43 0.02318 1 02 GYVEG Offer 2+ times: Dark Green/Yellow Veg

44 0.02216 1 ON_FRFR # times offered: Fresh Fruit

45 0.02172 1 02_FRESH Offer 2+ times: Fresh fruit or veg

46 0.02084 1 02_FRIES Offer 2+ times: French fries

47 0.02081 1 02_SALTY Offer 2+ times: Chips/Salty snacks

48 0.01846 1 02_DESS Offer 2+ times: Dessert

49 0.01739 1 02_HOTDG Offer 2+ times: Hot Dog

50 0.01683 1 ON_FRVEG Offer for lunch: Fresh Vegetable

58

TABLE B11

INDICATORS OF AVERAGE IRON CONTENT OF LUNCHES (MG)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.13509 -1 ELEMENT Elementary School

2 0.10511 1 ON HIVEG # times offered: High Fat Vegetable

3 0.10387 1 ON_FV4 # times offered: At least 4 fruit/veg

4 0.09980 1 ON_CHEES # times offered: Cheese

5 0.09116 1 ON_DESS # times offered: Dessert

6 0.08747 1 ON LOFAT # times offered: Low Fat Entree

7 0.08628 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

8 0.08273 1 ON_CBURG # times offered: Cheeseburger

9 0.08221 1 ON_FV3 # times offered: At least 3 fruit/veg

10 0.07847 1 HIGH High School

11 0.07062 1 ON_FRVEG # times offered: Fresh Vegetable

12 0.06754 -1 CERTPER Perc Students certified free/RP

13 0.06569 1 02...MSS Offer 2+ times: Dessert

14 0.06448 1 ON_BURG # times offered: Hamburger

15 0.06390 1 VENDING Vending Machine available

16 0.06340 1 02_CBURG Offer 2+ times: Cheeseburger

17 0.05331 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

18 0.05254 1 ON_FRESH # times offered: Fresh fruit or veg

19 0.05176 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

20 0.04981 1 02_CHEES Offer 2+ times: Cheese

21 0.04978 1 ON_PIZZA # times offered: Pizza

22 0.04972 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

23 0.04823 1 02_BURG Offer 2+ times: Hamburger

24 0.04666 1 ON_FRIES # times offered: French fries

25 0.04027 1 OL_CBURG Offer for lunch: Cheeseburger

26 0.03843 1 OL_DESS Offer for lunch: Dessert

27 0.03829 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

28 0.03735 1 02_PIZZA Offer 2+ times: Pizza

29 0.03729 1 02_LOFAT Offer 2+ times: Low Fat Entree

30 0.03691 1 ON_SALTY # times offered: Chips/Salty snacks

31 0.03542 1 FPRICELN Full price for

lunch (dollars)

32 0.03482 1 OVSLUNCH Offer verse Serve (OVS) at lunch

33 0.03467 1 02_HIVEG Offer 2+ times: High Fat Vegetable

34 0.03232 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

35 0.02962 1 02_FRIES Offer 2+ times: French fries

36 0.02893 1 OL_LOFAT Offer for lunch: Low Fat Entree

37 0.02868 1 ENROLLMT Total school enrollment

38 0.02605 1 02_SALTY Offer 2+ times: Chips/Salty snacks

39 0.02501 1 OL_FV3 Offer for lunch: At least 3 fruit/veg

40 0.02368 1 02_FRVEG Offer 2+ times: Fresh Vegetable

41 0.02351 1 OL_FRESH Offer for lunch: Fresh fruit or veg

42 0.02100 1 OL_FRVEG Offer for Lunch: Fresh Vegetable

43 0.02087 1 OL_BURG Offer for lunch: Hamburger

44 0.02021 1 ON_BUFF Offer for lunch: Buffet style food bar

45 0.01993 1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

46 0.01979 1 02_BUFF Offer 2+ times: Buffet style food bar

47 0.01938 1 OL_GYVEG Offer for lunch: Dark Green/Yellow Veg

48 0.01877 1 ON_FRFR # times offered: Fresh Fruit

49 0.01863 1 ON_BUFF # times offered: Buffet style food bar

50 0.01801 1 PRDRAIN Practice: drain cooked ground beef

59

TABLE B12

INDICATORS OF AVERAGE FIBER CONTENT OF LUNCHES (GRAMS)

RANK

R-squared

SIGN

VAR NAME

VARIABLE DESCRIPTION

1

0.090878

2

0.073061

3

0.070598

4

0.060209

5

0.057626

6

0.056720

7

0.054088

8

0.052228

9

0.044626

10

0.042790

11

0.040479

12

0.040106

------------------

13

0.039552

14

0.038682

15

0.036714

16

0.034111

17

0.033753

18

0.033723

19

0.033524

20

0.033103

21

0.032976

22

0.031391

23

0.028833

24

0.028399

25

0.028014

26

0.026141

27

0.025339

28

0.024647

29

0.024055

30

0.023501

31

0.022616

32

0.021823

33

0.021797

34

0.021731

35

0.021053

36

0.021050

37

0.020950

38

0.019962

39

0.017804

40

0.017748

41

0.017256

42

0.016531

43

0.015827

44

0.015398

45

0.014744

46

0.013236

47

0.012298

48

0.012026

49

0.011113

50

0.011003

1

ONFRFR

# times offered: Fresh Fruit

-1

ELEMENT

Elementary School

1

ON_CHEES

# times offered: Cheese

1

ON_FV4

# times offered: At least 4 fruit/veg

1

02_CHEES

Offer 2+ times: Cheese

1

ON_WWBR

# times offered: Whole wheat bread

1

ON_FRESH

# times offered: Fresh fruit or veg

1

ON_FV3

# times offered: At least 3 fruit/veg

1

02 FRFR

Offer 2+ times: Fresh fruit

1

02_WWBR

Offer 2+ times: Whole wheat bread

1

ON_FRVEG

# times offered: Fresh Vegetable

1

02_FV3

Offer 2+ times: At least 3 fruit/veg-------------------------------------------------------------------

# times offered: Cheeseburger

Offer 2+ times: At least 4 fruit/veg

# times offered: Dessert

High School

# times offered: High Fat Vegetable

Offer for lunch: At least 4 fruit/veg

Perc Students certified free/RP

# times offered: Fries, hashbrowns,etc

Offer 2+ times: Dessert

Offer 2+ times: Cheeseburger

Full price for lunch (dollars)

Offer 2+ times: Fresh Vegetable

Offer for lunch: At least 3 fruit/veg

# times offered: Pizza

# times offered: Dark Green/Yellow Veg

Offer for lunch: Dessert

Vending Machine available

# times offered: Chips/Salty snacks

# times offered: French fries

Offer for lunch: Fresh fruit or veg

Offer 2+ times: Low Fat Entree

Total school enrollment

Offer for lunch: Fresh Fruit

Practice: serve skim milk

Offer 2+ times: Pizza

Offer for lunch: Low Fat Entree

Offer for lunch: Dark Green/Yellow Veg

# times offered: Hot Dog

Offer for lunch: Fresh Vegetable

Offer 2+ times: Hamburger

Offer for lunch: Cheeseburger

Offer for lunch: Cheese

Offer 2+ times: Hot Dog

Offer 2+ times: French fries

Use Food Service Management Co

Offer 2+ times: Chips/Salty snacks

ON_LOFAT

# times offered: Low Fat Entree

OL_WWBR

Offer for lunch: Whole wheat bread

ON_CBURG

02_FV4

ON DESS

HIGH

ON_HIVEG

OL_FV4

CERTPER

ON_FRYPL

02_DESS

02_CBURG

FPRICELN

02_FRVEG

OL_FV3

ON_PIZZA

ON_GYVEG

OL_DESS

VENDING

ON_SALTY

ON_FRIES

OL_FRESH

02_LOFAT

ENROLLMT

OL_FRFR

PRSKIM

02_PIZZA

OL_LOFAT

OL_GYVEG

ON_HOTDG

OL_FRVEG

02_BURG

OL_CBURG

OL_CHEES

02_HOTDG

02_FRIES

FSMC

02 SALTY

60

TABLE B13

INDICATORS OF AVERAGE BREAD GROUP CONTENT OF LUNCHES (GRAMS)

RANK

R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1

0.10345 1 ON DESS # times offered: Dessert

2

0.07860 1 02_DESS Offer 2+ times: Dessert

3

0.07058 1 ON PIZZA # times offered: Pizza

4

0.06905 1 ON_LOFAT # times offered: Low Fat Entree

5

0.05790 1 ON_FV4 # times offered: At least 4 fruit/veg

6

0.05380 1 02 PIZZA Offer 2+ times: Pizza

7

0.04973 1 ON FRVEG # times offered: Fresh Vegetable

8

0.04698 1 ELEMENT Elementary School

9

0.04541 1 ON_FRESH # times offered: Fresh fruit or veg

10

0.04464 1 ON_CHEES # times offered: Cheese

11

0.04428 1 ON_FV3 # times offered: At least 3 fruit/veg

12

0.04216 1 02_LOFAT Offer 2+ times: Low Fat Entree

13

0.04003 1 02_FRVEG Offer 2+ times: Fresh Vegetable

---------------------- --------------

14 0.03694 1 02_CHEES Offer 2+ times: Cheese

15 0.03248 1 HIGH High School

16 0.03151 1 ON_CHIPS # times offered: Potato chips

17 0.03065 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

18 0.02918 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

19 0.02863 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

20 0.02792 1 VENDING Vending Machine available

21 0.02695 -1 CERTPER Perc Students certified free/RP

22 0.02622 1 ON_HIVEG # times offered: High Fat Vegetable

23 0.02540 1 OL_DESS Offer for lunch: Dessert

24 0.02494 1 ON_SALTY # times offered: Chips/Salty snacks

25 0.02342 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

26 0.02319 1 02_CHIPS Offer 2+ times: Potato chips

27 0.02314 1 ON_WWBR # times offered: Whole wheat bread

28 0.02256 1 OL_WWBR Offer for Lunch: Whole wheat bread

29 0.02137 1 02_SALTY Offer 2+ times: Chips/Salty snacks

30 0.02130 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

31 0.02052 1 ON_CBURG # times offered: Cheeseburger

32 0.02031 1 02_BUFF Offer 2+ times: Buffet style food bar

33 0.02021 1 ON_BUFF # times offered: Buffet style food bar

34 0.01991 1 OL_FRESH Offer for Lunch: Fresh fruit or veg

35 0.01982 1 OL_BUFF Offer for lunch: Buffet style food bar

36 0.01843 1 02_SALBR Offer 2+ times: Salad Bar

37 0.01809 1 02_CBURG Offer 2+ times: Cheeseburger

38 0.01768 1 02_FRESH Offer 2+ times: Fresh fruit or veg

39 0.01753 1 ON_SALBR # times offered: Salad Bar

40 0.01714 1 OL_LOFAT Offer for lunch: Low Fat Entree

41 0.01697 1 OL_CHIPS Offer for lunch: Potato chips

42 0.01628 1 OL_SALBR Offer for lunch: Salad Bar

43 0.01620 1 OL_PIZZA Offer for lunch: Pizza

44 0.01601 1 OVSLUNCH Offer verse Serve (OVS) at lunch

45 0.01590 1 ON_FRIES # times offered: French fries

46 0.01543 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

47 0.01523 1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

48 0.01324 1 RQ_VEGET Reqrd GL-Increase vegetable

49 0.01269 1 OL_GYVEG Offer for Lunch: Dark Green/Yellow Veg

50 0.01248 -1 LPR_CKIT Food preparation(lunch): Central kitchen

61

TABLE B14

INDICATORS OF AVERAGE VEGETABLE GROUP CONTENT OF LUNCHES (GRAMS)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.16447 1 ON_HIVEG # times offered: High Fat Vegetable

2 0.13464 1 ON_FRIES # times offered: French fries

3 0.12046 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

4 0.09588 1 02 FRIES Offer 2+ times: French fries

5 0.08807 1 02_HIVEG Offer 2+ times: High Fat Vegetable

6 0.08655 -1 ELEMENT Elementary School

7 0.08623 1 ON_FRVEG # times offered: Fresh Vegetable

8 0.07266 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

9 0.07228 1 ON_CHEES # times offered: Cheese

10 0.07167 1 HIGH High School

11 0.06596 1 ON_FV3 # times offered: At least 3 fruit/veg

12 0.06521 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

13 0.05726 1 OL_FRIES Offer for lunch: French fries

14 0.05576 1 ON_FV4 # times offered: At least 4 fruit/veg

15 0.05114 1 ON_FRESH # times offered: Fresh fruit or veg

16 0.04187 1 OL_FRYPL Offer for lunch: Fries, hashbrowns,etc

17 0.03839 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

18 0.03692 1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

19 0.03542 1 OL_FV3 Offer for lunch: At least 3 fruit/veg

20 0.03473 1 OL_HIVEG Offer for lunch: High Fat Vegetable

21 0.03210 1 VENDING Vending Machine available

22 0.03008 1 02_FV3 Offer 2+ times: At least 3 fruit/veg

23 0.02995 1 LPR_SCHL Food preparation(lunch): School

24 0.02751 1 ON_BURG # times offered: Hamburger

25 0.02718 1 02_BURG Offer 2+ times: Hamburger

26 0.02558 1 02_CHEES Offer 2+ times: Cheese

27 0.02531 -1 RR DESS Recommended/Required GL-Limit dessert

28 0.02461 -1 RC_DESS Recommended GL-Limit dessert

29 0.02452 -1 LPR_CKIT Food preparation(lunch): Central kitchen

30 0.02450 1 FPRICELN Full price for lunch (dollars)

31 0.02404 -1 RC_SWEET Recommended GL-Dessert and/or sugar

32 0.02373 -1 CERTPER Perc Students certified free/RP

33 0.02358 -1 RC_SODIU Recommended GL-Limit sodium

34 0.02344 1 02_FRVEG Offer 2+ times: Fresh Vegetable

35 0.02173 -1 RC_GRAIN Recommended GL-Increase whole grain

36 0.02121 -1 N_EVS Total number evaluation procedures

37 0.02110 -1 EV_COMPU Evaluation nutrition: computer analysis

38 0.02106 1 02_DESS Offer 2+ times: Dessert

39 0.02034 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

40 0.01925 -1 RC_SUGAR Recommended GL-Limit sugar

41 0.01919 1 ENROLLMT Total school enrollment

42 0.01916 1 02_HOTDG Offer 2+ times: Hot Dog

43 0.01814 1 ON_CBURG # times offered: Cheeseburger

44 0.01772 -1 RR_GRAIN Recommended/Required GL-Increase whole grain

45 0.01739 -1 RR_CFAT Recommended/Required GL-Energy from fat 30-35%46 0.01737 1 ON_LOFAT # times offered: Low Fat Entree

47 0.01709 -1 GL_DESS Guideline-Limit dessert

48 0.01613 1 LMP_SCHL Lunch menu planning: School

49 0.01538 -1 PRLFMEAT Practice: substitute chick/fish for meat

50 0.01516 1 OL_FRESH Offer for lunch: Fresh fruit or veg

62

TABLE B15

INDICATORS OF AVERAGE FRUIT GROUP CONTENT OF LUNCHES (GRAMS)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.13845 1 ON_FRFR # times offered: Fresh Fruit

2 0.08496 1 02_FRFR Offer 2+ times: Fresh Fruit

3 0.04864 1 ON FV4 # times offered: At least 4 fruit/veg

----------------------------------------- ------------------------------------------------4 0.03387 1 ON CHEES # times offered: Cheese

5 0.02807 1 TRUNC School has < 5 days of data

6 0.02793 1 02_CHEES Offer 2+ times: Cheese

7 0.02717 1 TRUNC4 School has 4 days of data

8 0.02477 1 02_HOTDG Offer 2+ times: Hot Dog

9 0.02186 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

10 0.02160 1 OL_FRFR Offer for lunch: Fresh Fruit

11 0.02014 1 ON_FV3 # times offered: At least 3 fruit/veg

12 0.01938 1 ON_ICECR # times offered: Ice cream

13 0.01808 1 ON_HOTDG # times offered: Hot Dog

14 0.01582 -1 SCHSBP Offer SBP breakfast

15 0.01486 1 FPRICELN Full price for lunch (dollars)

16 0.01431 1 PRFRESH Practice: fresh fruits and veggies daily

17 0.01426 1 FSMC Use Food Service Management Co

18 0.01391 -1 CERTPER Perc Students certified free/RP

19 0.01389 1 N_EVS Total number evaluation procedures

20 0.01268 1 ON_PIZZA # times offered: Pizza

21 0.01235 1 02_ICECR Offer 2+ times: Ice cream

22 0.01134 1 PRFRIED Practice:

limit breaded and fried foods

23 0.01041 1 ON_CBURG # times offered: Cheeseburger

24 0.01017 1 EV_COMPU Evaluation nutrition: computer analysis

25 0.01016 1 CANLEAVE Students permitted to leave for lunch

26 0.01004 1 02_CHIPS Offer 2+ times: Potato chips

27 0.00964 1 ON_FRESH # times offered: Fresh fruit or veg

28 0.00963 1 ON_CHIPS # times offered: Potato chips

29 0.00896 1 OL_HOTDG Offer for lunch: Hot Dog

30 0.00889 -1 OL_BURG Offer for lunch: Hamburger

31 0.00871 1 N_PRACS Total number healthy food prep practices

32 0.00837 1 OL_CBURG Offer for lunch: Cheeseburger

33 0.00836 -1 02_HIVEG Offer 2+ times: High Fat Vegetable

34 0.00742 1 LPR_OFF Food preparation(lunch): Off-site kitchen

35 0.00736 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

36 0.00728 1 EV_STDED Evaluation nutrition:

info from state

37 0.00686 1 OL_ICECR Offer for lunch:

Ice cream

38 0.00658 1 EV_PROFT Evaluation nutrition:

literature,

training

39 0.00622 1 ON_SALTY # times offered: Chips/Salty snacks

40 0.00617 1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

41 0.00595 1 02_CBURG Offer 2+ times: Cheeseburger

42 0.00573 1 RQ_CHOL Reqrd GL-Limit cholesterol

43 0.00539 1 ELEMENT Elementary School

44 0.00532 1 GL_CHOL Guideline-Limit cholesterol

45 0.00512 1 02_PBCH Offer 2+ times: Prebreaded chicken/turk

46 0.00509 1 LPR_SCHL Food preparation(lunch): School

47 0.00498 1 OL_FRVEG Offer for lunch: Fresh Vegetable

48 0.00498 1 ON_PBCH # times offered: Prebreaded chicken/turk

49 0.00480 1 02_SALTY Offer 2+ times: Chips/Salty snacks

50 0.00478 1 02 PIZZA Offer 2+ times: Pizza

63

TABLE B16

INDICATORS OF AVERAGE MILK GROUP CONTENT OF LUNCHES (GRAMS)

RANK R-squared SIGN VAR NAME VARIABLE DESCRIPTION

1 0.29890 1 ON_ICECR # times offered: Ice cream

2 0.23476 1 02_ICECR Offer 2+ times: Ice cream

3 0.21011 1 OL_ICECR Offer for lunch: Ice cream

4 0.06335 1 ON_DESS # times offered: Dessert

5 0.05256 1 ON_CHEES # times offered: Cheese

6 0.05015 1 02_DESS Offer 2+ times: Dessert

7 0.04711 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

8 0.03762 1 ON_SALBR # times offered: Salad Bar

9 0.03721 1 02_CHEES Offer 2+ times: Cheese

10 0.03641 1 OL_SALBR Offer for lunch: Salad Bar

11 0.03633 1 02_SALBR Offer 2+ times: Salad Bar

12 0.03546 1 ON_FRVEG # times offered: Fresh Vegetable

13 0.03493 1 PRLFCHEE Practice: use reduced fat cheese

14 0.02821 1 02 BUFF Offer 2+ times: Buffet style food bar

15 0.02695 1 ON_BUFF # times offered: Buffet style food bar

16 0.02678 1 HIGH High School

17 0.02596 1 OL_GYVEG Offer for lunch: Dark Green/Yellow Veg

18 0.02470 1 02_FRVEG Offer 2+ times: Fresh Vegetable

19 0.02378 1 ON_FRESH # times offered: Fresh fruit or veg

20 0.02227 1 OL_BUFF Offer for lunch: Buffet style food bar

21 0.01945 1 02_GYVEG Offer 2+ times: Dark Green/Yellow Veg

22 0.01928 1 N_PRACS Total number healthy food prep practices

23 0.01812 1 PR_USELF Consciously use lofat foods/substitutes

24 0.01794 1 ON_HIVEG # times offered: High Fat Vegetable

25 0.01701 -1 LPR_CKIT Food preparation(lunch): Central kitchen

26 0.01519 1 ON_FV3 # times offered: At least 3 fruit/veg

27 0.01493 1 PRRINSDR Practice: rinse & drain cooked ground beef

28 0.01455 -1 RQ_FRUIT Reqrd GL-Increase fruit

29 0.01374 -1 RQ_FRVEG Reqrd GL-Fruits and/or vegetables

30 0.01363 -1 DISTGL District guidelines for nutrition

31 0.01361 1 LPR_SCHL Food preparation(lunch): School

32 0.01346 1 02_FV4 Offer 2+ times: At least 4 fruit/veg

33 0.01236 1 ON_SALTY # times offered: Chips/Salty snacks

34 0.01225 1 02_HOTDG Offer 2+ times: Hot Dog

35 0.01192 1 ON_FV4 # times offered: At least 4 fruit/veg

36 0.01159 1 OL_CHEES Offer for lunch: Cheese

37 0.01100 -1 ELEMENT Elementary School

38 0.01090 1 OL_FV4 Offer for lunch: At least 4 fruit/veg

39 0.01008 1 ON_PIZZA # times offered: Pizza

40 0.01003 -1 STATEGL State guidelines for nutrition

41 0.00945 1 OL_SALTY Offer for lunch: Chips/Salty snacks

42 0.00937 1 PRLFDELI Practice:

lower fat hot dog/sandwich meat

43 0.00926 1 02_HIVEG Offer 2+ times: High Fat Vegetable

44 0.00858 -1 LMP_DIST Lunch menu planning: District

45 0.00814 1 OL_PIZZA Offer for lunch: Pizza

46 0.00804 1 02_CBURG Offer 2+ times: Cheeseburger

47 0.00794 -1 02_CHIPS Offer 2+ times: Potato chips

48 0.00671 -1 OL_CHIPS Offer for lunch: Potato chips

49 0.00649 1 ON_LOFAT # times offered: Low Fat Entree

50 0.00643 1 RC FRUIT Recommended GL-Increase fruit

64

TABLE B17

INDICATORS OF AVERAGE MEAT GROUP CONTENT OF LUNCHES (GRAMS)

RANK

R-squared

SIGN

VAR NAME

VARIABLE DESCRIPTION

------------------------------------------------------------------------------------

1 0.033714 1 OL_FRIES Offer for Lunch: French fries

2 0.030127 1 02_FRIES Offer 2+ times: French fries

3 0.029780 -1 ELEMENT Elementary School

4 0.026469 1 ON_HIVEG # times offered: High Fat Vegetable

5 0.025011 1 ON_FRIES # times offered: French fries

6 0.022838 1 02_FRYPL Offer 2+ times: Fries, hashbrowns,etc

7 0.020895 1 02_HIVEG Offer 2+ times: High Fat Vegetable

8 0.017671 1 LPR_SCHL Food preparation(lunch): School

9 0.016062 1 ON_FRYPL # times offered: Fries, hashbrowns,etc

10 0.011742 1 OL_FRYPL Offer for lunch: Fries, hashbrowns,etc

11 0.011468 1 HIGH High School

12 0.011338 1 OL_LOFAT Offer for lunch: Low Fat Entree

13 0.011268 -1 FSMC Use Food Service Management Co

14 0.009582 -1 OL_PIZZA Offer for lunch: Pizza

15 0.009023 -1 EV_PROFT Evaluation nutrition:

literature,

training

16 0.008198 -1 LPR_OFF Food preparation(lunch): Off-site kitchen

17 0.008055 -1 EV_USDAL Evaluation nutrition:

Literature from USDA

18 0.007973 -1 ON_PIZZA # times offered: Pizza

19 0.007847 -1 OL_WWBR Offer for lunch: Whole wheat bread

20 0.005860 1 CERTPER Perc Students certified free/RP

21 0.005616 1 OL_DESS Offer for lunch: Dessert

22 0.005332 1 ON_HOTDG # times offered: Hot Dog

23 0.004976 1 OL_CBURG Offer for lunch: Cheeseburger

24 0.004929 1 RC_SFAT Reqrd GL-Limit saturated fat

25 0.004843 -1 PRRINSDR Practice: rinse & drain cooked ground beef

26 0.004840 -1 PR_USELF Consciously use lofat foods/substitutes

27 0.004658 1 ON_GYVEG # times offered: Dark Green/Yellow Veg

28 0.004558 -1 RC_SFAT Recommended GL-Limit saturated fat

29 0.004455 -1 PRLFMEAT Practice: substitute chick/fish for meat

30 0.004133 -1 N_PRACS Total number healthy food prep practices

31 0.004079 1 02_HOTDG Offer 2+ times: Hot Dog

32 0.003708 1 ON_CBURG # times offered: Cheeseburger

33 0.003627 -1 ON WWBR # times offered: Whole wheat bread

34 0.003520 -1 PRLFDELI Practice:

lower fat hot dog/sandwich meat

35 0.003471 -1 RC FAT Recommended GL-Total fat and/or sat fat

36 0.003454 -1 RC_CFAT Recommended GL-Energy from fat 30-35%

37 0.003386 1 RR_FAT Recommended/Required GL-Total fat and/or sat fat

38 0.003332 -1 LPR_CKIT Food preparation(lunch): Central kitchen

39 0.003216 1 DISTGL District guidelines for nutrition

40 0.003054 1 RC_FRVEG Recommended GL-Fruits and/or vegetables

41 0.002931 -1 RR_CFAT Recommended/Required GL-Energy from fat 30-35%

42 0.002776 -1 02_PIZZA Offer 2+ times: Pizza

43 0.002709 -1 02_FRVEG Offer 2+ times: Fresh Vegetable

44 0.002610 -1 OL_SALTY Offer for lunch: Chips/Salty snacks

45 0.002472 -1 N_EVS Total number evaluation procedures

46 0.002436 -1 OL_FRFR Offer for lunch: Fresh Fruit

47 0.002403 1 OL_FRVEG Offer for lunch: Fresh Vegetable

48 0.002385 -1 TRUNC3 School has 3 days of data

49 0.002340 -1 02_WWBR Offer 2+ times: Whole wheat bread

50 0.002136 1 ON_DESS # times offered: Dessert

65

APPENDIX C

MULTIVARIATE MODELS

TABLE Cl

MULTIVARIATE MODEL OF

FOOD ENERGY CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Indicator Variable Kilocalories

Intercept 718.305

Offer 2+ times: Dessert 95.790

Offer 2+ times: Cheese 70.881

Offer 2+ times: High Fat Vegetable 76.084

Offer 2+ times: Fresh Vegetable -33.627

Elementary School -49.190

Offer 2+ times: Dark Green/Yellow Veg

x Elementary School -45.045

R-squared 0.37

69

TABLE C2

MULTIVARIATE MODELS OF

FAT CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Percent of Total

Indicator Variable Kilocalories Food Energy

Intercept

Offer 2+ times: Dessert

Offer 2+ times: Cheese

Offer 2+ times: Fries, hashbrowns,etc

Offer 2 + times: At least 4 fruit/veg

x Elementary School

Offer 2+ times: Dessert

x Offer 2+ times: Cheese

Offer 2+ times: Fries, hashbrowns,etc

x < 5 days of data

Offer 2 + times: Fresh Fruit

x Offer 2+ times: At least 4 fruit/veg

R-squared

235.821 0.357

37.311 0.016

41.378 0.020

18.652 0.011

-27.004

-0.015

0.046

-0.011

0.28 0.10

70

TABLE C3

MULTIVARIATE MODELS OF

SATURATED FAT CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Percent of TotalIndicator Variable Kilocalories Food Energy

Intercept

98.631

0.152

Offer 2+ times: Dessert

17.583

0.005

Offer 2+ times: Cheese

15.617

Offer 2+ times: Fresh Vegetable

-7.670

Offer 2+ times: Cheese

x Elementary School

7.026

0.016

Offer 2+ times: Fries, hashbrowns,etc

x Offer 2+ times: Fresh Vegetable

7.267

Offer 2+ times: At least 4 fruit/veg

x Elementary School

-14.782

Offer 2+ times: At least 4 fruit/veg

-0.010

Elementary School

-0.006

Offer 2+ times: High Fat Vegetable

x Elementary School

-0.032

R-squared

0.35

0.19

71

TABLE C4

MULTIVARIATE MODELS OF

CHOLESTEROL CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Whether

Indicator Variable Milligrams < =100 mg *

Intercept 81.983 2.660

Offer 2+ times: Dessert 8.800 -0.915

Offer 2+ times: Cheese 8.930 -0.519

Offer 2+ times: Pizza -8.431

Offer 2+ times: Ice cream -10.134

Offer 2+ times: Dark Green/Yellow Veg -1.167

Elementary School -7.272 -0.298

Offer 2+ times: Dessert

x High School 6.816

Offer 2+ times: Pizza

x High School 2.052

Offer 2+ times: Fresh Vegetable

x High School -0.706

Offer 2+ times: Dark Green/Yellow Veg

x Elementary School 1.599

R-squared 0.18 0.13

* Logistic regression. The R-squared displayed pertains to thecorresponding linear probability model (estimated by ordinary least squares).

72

TABLE C5

MULTIVARIATE MODEL OF

SODIUM CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Indicator Variable Milligrams

Intercept 1324.164

Offer 2+ times: Dessert 114.034

Offer 2+ times: Cheese 155.836

High School 106.244

Offer 2+ times: At least 4 fruit/veg

x Elementary School -160.364

Offer 2+ times: Fries, hashbrowns,etc

x Offer 2+ times: At least 4 fruit/veg 172.399

Offer 2+ times: Fresh Fruit

x Offer 2+ times: Fries, hashbrowns,etc -154.154

Offer 2+ times: High Fat Vegetable

x Offer 2+ times: Fries, hashbrowns,etc 140.737

R-squared 0.31

73

TABLE C6

MULTIVARIATE MODEL OF

VITAMIN C CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Indicator Variable Milligrams

Intercept 21.485

Offer 2+ times: Fresh Fruit 1.793

Offer 2 + times: At least 4 fruit/veg 2.409

Offer 2+ times: Cheese 5.732

Offer 2+ times: Fresh Fruit

x Offer 2 + times: At least 4 fruit/veg 5.270

Offer 2 + times: At least 4 fruit/veg

x < 5 days of data 11.302

R-squared 0.24

74

TABLE C7

MULTIVARIATE MODEL OF

CALCIUM CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Indicator Variable Milligrams

Intercept 432.985

Offer 2+ times: Cheese 93.776

Offer 2+ times: Ice cream 31.195

Elementary School 21.791

Offer 2+ times: Cheese

x Elementary School -41.129

R-squared 0.29

75

TABLE C8

MULTIVARIATE MODEL OFIRON CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Indicator Variable Milligrams

Intercept 4.357

Offer 2+ times: Dessert 0.440

Offer 2+ times: Cheese 0.501

Offer 2+ times: Cheeseburger 0.294

Elementary School -0.419

Offer 2+ times: Cheesex Offer 2+ times: Fresh Vegetable -0.436

Offer 2+ times: Dark Green/Yellow Vegx Elementary School -0.222

R-squared 0.23

76

TABLE C9

MULTIVARIATE MODEL OF

FIBER CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

Indicator Variable Grains

Intercept 6.154

Offer 2+ times: Dessert 0.551

Offer 2+ times: Cheese 1.416

Elementary School -0.372

Offer 2+ times: Cheese

x Offer 2+ times: At least 4 fruit/veg -1.343

Offer 2+ times: Dark Green/Yellow Veg

x Elementary School -0.430

Offer 2+ times: Fresh Fruit

x Offer 2+ times: At least 4 fruit/veg 0.501

Offer 2+ times: Whole wheat bread 0.818

R-squared 0.24

77

TABLE C10

MULTIVARIATE MODELS OFFOOD GROUP CONTENT OF AVERAGE NSLP LUNCH

(Regression Coefficients)

FOOD GROUP CONTENT (grams)

Indicator Variable

Bread Vegetable Fruit Dairy Meat

Intercept

77.430 93.334 76.748 250.690 73.939

Offer 2+ times: Dessert

14.892 7.866

Offer 2+ times: Pizza

14.117 -16.693

Offer 2+ times: Fresh Fruit -19.248 27.790

Offer 2 + times: Cheese 9.329

Offer 2+ times: Ice cream 25.763

Offer 2+ times: Hamburger 6.343

Offer 2+ times: Fresh Vegetable -5.719

Offer 2+ times: At least 4 fruit/veg -5.298Elementary School -13.536

Offer 2+ times: Dessertx Offer 2+ times: Cheese

18.494Offer 2+ times: Dessertx Elementary School

-15.300

Offer 2+ times: At least 4 fruit/vegx Elementary School -14.803

Offer 2+ times: Fries, hashbrowns,etcx Offer 2+ times: At least 4 fruit/veg 20.099

Offer 2+ times: Dark Green/Yellow Vegx Elementary School -16.582

Offer 2+ times: Fresh Fruitx < 5 days of data -38.453

Offer 2 + times: At least 4 fruit/vegx < 5 days of data 63.041

Offer 2+ times: Cheesex Offer 2 + times: Ice cream 23.802

R-squared

0.19 0.12 0.17 0.28 0.09

.78