CHANGE IN MILK AND OTHER BEVERAGE INTAKE AMONG

PRETEENS IN AN INTERVENTION AIMED AT INCREASING

CALCIUM

_______________

A Thesis

Presented to the

Faculty of

San Diego State University

_______________

In Partial Fulfillment

of the Requirements for the Degree

Master

in

Public Health

_______________

by

Disly Mariela Juarez Munoz

Spring 2011

iii

Copyright © 2011

by

Disly Mariela Juarez Munoz

All Rights Reserved

iv

DEDICATION

I want to thank God who gives me the strength, endurance, knowledge and guidance

every day to go on. I want to thank my beloved family who supported me through every step

of this process. No matter how far I was from them, no matter in what continent, they always

remain so close to me. I will always and forever appreciate your patience, advice, guidance,

prayers and love. This is for you, I love you.

v

ABSTRACT OF THE THESIS

Milk and Beverage Consumption Patterns Among Preteens in an Intervention Aimed at Increasing Calcium Intake

by Disly Mariela Juarez Munoz

Masters in Public Health San Diego State University, 2011

Children’s replacement of milk with sugar-sweetened beverages (SSB) is associated with lower intake of calcium, vitamin D, vitamin A, folate, vitamin B-12, and magnesium. Research indicates a relationship between this consumption pattern and obesity, osteoporosis, nutrient deficiency and dental caries. This study is a secondary analysis of the cross-sectional dietary data from the Healthy Youth and Parent Program (HYPP). HYPP, a family behavioral intervention produced significant increases in calcium intake among the experimental group as compared to controls (N = 124). This secondary analysis analyzed beverage consumption, calcium-rich beverages and sugar sweet beverages, to test if the experimental intervention resulted in differential change from baseline to 3-months. Beverages included milk (whole, reduced and fat free), 100% juices, SSB (juice and soda) and calcium-fortified juices (calcium-100% juices and calcium-not 100% juices). This study evaluated if the increase in calcium intake in HYPP participants was due to an increase intake of milk and explored the type of milk that caused significant differences. Results indicate that total milk consumption increased in the experimental group relative to controls (p = .004). Consumption of whole milk decreased (p = .019) with a corresponding increase in reduced (p = .002) and fat-free milk (p = .036). No effect was observed for juices or SSB. This analysis supports parent-child interventions as a means of increasing the consumption of calcium rich beverages including reduced and fat-free milk in children. Dietary modification through such interventions should be considered as a means to successfully decrease the childhood obesity epidemic and potential osteoporosis rise among children in the United States.

vi

TABLE OF CONTENTS

PAGE

ABSTRACT ...............................................................................................................................v

LIST OF TABLES ................................................................................................................. viii

ACKNOWLEDGEMENTS ..................................................................................................... ix

CHAPTER

1 INTRODUCTION .........................................................................................................1 

Theoretical Background ...........................................................................................4 

Purpose of the Study ................................................................................................4 

Research Questions ..................................................................................................5 

2 METHODS ....................................................................................................................6 

HYPP Participants and Recruitment ........................................................................6 

HYPP Parent Training .......................................................................................6 

HYPP Child Training .........................................................................................7 

HYPP Control Group .........................................................................................7 

HYPP IRB and Incentives .......................................................................................7 

HYPP Data Analyses/ Results .................................................................................7 

Present Data: Variables ............................................................................................8 

Present Study: Analyses ...........................................................................................9 

3 RESULTS ....................................................................................................................10 

Baseline Beverage Consumption by Gender, Ethnicity and Group .......................10 

Baseline and 3-Months Consumption of at Least One Beverage on an Average Day ..........................................................................................................11 

Group Differences at 3-Months .............................................................................13 

Change in Beverage Gram Consumption from Baseline to 3-Months in Control and Experimental Groups .........................................................................13 

Change in Beverage Gram Consumption Regressed on Age, Group, Ethnicity and Gender .............................................................................................13 

4 DISCUSSION ..............................................................................................................16 

Milk ........................................................................................................................16 

vii

SSB & Sodas ..........................................................................................................17 

Juices ......................................................................................................................17 

Ethnicity and Beverage Consumption ...................................................................18 

Family-Based Interventions ...................................................................................19 

Limitations .............................................................................................................20 

Implications............................................................................................................20 

REFERENCES ........................................................................................................................23 

viii

LIST OF TABLES

PAGE

Table 1. Participant Demographics (N = 124) .........................................................................10 

Table 2. Baseline Beverage Grams Consumption by Gender and Ethnicity (Geometric Mean and 25th and 75th quartiles) .................................................................................11 

Table 3. Percentages of Participants in Control and Experimental Groups at Baseline and 3-Months that Consumed at Least One Beverage on an Average Daya ................11 

Table 4. Grams of Beverage Consumed per Group at Baseline, 3-Month Measures and Change Scores (Baseline& 3- Month Geometric Means/Change Score Raw Value a) (25th& 75th Interquartiles) ......................................................................14 

Table 5. Multiple Linear Regression of the Raw Change of Beverage Grams Consumed and Regressed on Group Assignment a ......................................................15 

ix

ACKNOWLEDGEMENTS

I would like to thank my advisor and my mentors, Dr. Hovell and Veronica Irvin for

their support, patience and guidance through the completion of this process. I would like to

thank my committee members, Dr. Madanat and Dr. Nichols for their advice and

contribution. I would also like to thank the staff at the Center for Behavioral Epidemiological

and Community Health (CBEACH) for allowing my endless visits to the center. Finally, I

would like to thank my friends and family who where the foundation of my endurance.

Thank you.

1

CHAPTER 1

INTRODUCTION

Change in nutrient intake and increase in consumption of foods high in fat and sugars

have become a familiar pattern in schools and homes for children nation-wide (French, Lin,

& Guthrie, 2003; Marshall, Eichenberger Gilmore, Broffitt, Stumbo, & Levy, 2005; Nielsen

& Popkin, 2004; Rampersaud, Bailey, & Kauwell, 2003). Due to the increased availability

and options of sugar-sweetened beverages (SSB), including sodas, juices, energy drinks and

coffee, an over consumption of these unhealthy beverages is feasible (Bray, Nielsen, &

Popkin, 2004; James & Kerr, 2005; Swinburn, Caterson, Seidell, & James, 2004). With so

many unhealthy options, consumption of traditionally healthy beverages like milk has

decreased over the last 20 years (Nielsen & Popkin, 2004; Troiano, Breifel, Carroll, &

Bailostosky, 2000). This is not surprising considering that 34% of high school students drink

at least one soda every day (Centers for Disease Control and Prevention [CDC], 2007). In

fact, access to soda is so high that soda contributes 55% of all calories from SSB among

children 2-19 years old (Wang, Bleich, & Gortmaker, 2008). Those who consume one or

more sodas or other SSB every day have a higher prevalence of obesity than those who do

not (Babey, Jones, Yu, & Goldstein, 2009).

While juice may seem to be a healthy alternative to soda, juice drinks contribute to

energy imbalance, diarrhea, overnutrition or undernutrition, and development of dental caries

in children (American Academy of Pediatrics [AAP], 2004; French et al., 2003; Harnack,

Stang, & Story, 1999; Harrington, 2008; James & Kerr, 2005; Marshall et al., 2005; Saelens,

Couch, Wosje, Stark, & Daniels, 2006). Analyses of the National Health and Nutrition

Examination Survey III (1988-1994 and 1999-2004) showed that fruit drinks were 37% of

total SSB calories for children 2-19 years old (Wang et al., 2008). On average, children aged

2-5 years consume 148 kcal/day, 6-11 years old consume 136 kcal/day and 12-19 years old

consume 184 kcal/day of juices that are not 100% juice (Wang et al., 2008).

Studies suggest that the reduction of SSB consumption, including sodas and juice

drinks, could decrease and even prevent childhood obesity (Harrington, 2008; James,

2

Thomas, Cavan, & Kerr, 2004). Sugar-Sweetened beverages constitute the highest source of

sugar intake in adolescents (Harrington, 2008). The odds-ratio for becoming obese among

children is 1.6 times higher, per additional beverage, for those who consume more than one

SSB than those who do not (Harrington, 2008). Milk, recognized as the main source of

calcium, has been found to be potentially associated with better weight control (Saelens, et

al., 2006). Thus, methods to reduce SSB through diet modification are considered important

to combat obesity and reduce calcium insufficiency and other diet-related problems in

children (French & Story, 2004; Heaney, Davies, & Barger-Lux, 2002; Teegarden, 2003).

With the popularity of SSB and juice drinks, milk displacement is prevalent and the

diet quality of children is poorer (Marshall et al., 2005). Children are not able to consume the

recommended amount of calcium or other nutrients from sodas and juices, as they would be

if they drank more milk. Replacement of milk with SSB is associated with lower intake of

calcium, vitamin D, vitamin A, folate, vitamin B-12, and magnesium (Marshall et al., 2005).

Calcium fortified juices have attempted to fill that gap, however they do not compensate for

other nutrients found in milk.

One of the major effects of insufficient consumption of nutrients is an increase in the

risk of bone problems, such as osteoporosis and osteoarthritis in children (National Institute

of Health: Osteoporosis and Related Bone Diseases National Resource Center [NIH], 2009;

Marshall et al., 2005). Over 45% of bone mass is developed during childhood and adolescent

years (NIH, 2009). Bone accretion is crucial during these years, yet most children do not

meet the recommended dietary calcium intake of 1,300 mg/day (recommended for 9-13 years

old). According to the National Institutes of Health Osteoporosis and Related Bone Disease,

only one in ten girls and one in four boys (aged 9-13 years) meet the recommended intake of

calcium (NIH, 2009). The positive correlation between calcium, dairy, energy balance and

healthy body weight has been strongly suggested by a number of studies (Heaney et al.,

2002; Teegarden, 2003; Zemel et al., 2008).

Dietary modification interventions can impact children’s diet quality by either

decreasing the consumption of a harmful food or increasing the consumption of a nutrient.

French & Story (2004) pioneered the promotion of bone health through food intake in

children. Before 2004, the primary method of exploring the relationship among calcium and

bone health was by increasing calcium through supplements and or fortified foods (Bonjour

3

et al., 1997; Johnston et al., 1992; Lloyd et al., 1993). The intervention conducted by French

& Story (2004) focused on increasing bone health through both physical activity and diet

behavioral modification. Bone health was measured by bone mineral content, density/area,

dietary calcium intake and weight bearing physical activity (WBPA). The intervention

consisted of eight 90- minute activity courses to increase WBPA (120 minutes/week).

Calcium intake was measured by a 24-hour dietary recall provided by each participant and

measurements were taken at baseline, one year and two years follow up. In order to increase

the intake of calcium (1300 mg/day), Girl Scout troop leaders in the intervention group

advised troops to eat calcium rich foods outside of the classes. Parents were also targeted

through a web-based program as a means of support. The intake of calcium through dietary

foods was significantly greater among the intervention group (baseline mean = 1199 mg,

two-year mean = 1394 mg) than the control group (baseline mean = 1274 mg, two-year mean

= 1310 mg). This intervention proved effective in raising calcium intake in pre-adolescent

girls though calcium- rich foods.

Analyses of national dietary surveys support the need of intervention programs to

improve diet quality in children. The National Health and Nutrition Examination Surveys

(1999-2004) found that the largest increase of consumption of SSB and 100% juices occurred

among children aged 6-11 years with an increase of approximately 20% (Wang et al., 2008).

In this sample population (children ages 2-19), sodas contributed 55% of all beverages

(calories) consumed. Teenagers 12-19 years old consumed the most soda (50% of all calories

consumed). Juice drinks contributed 37% of SSB calories for children 2-19 years old (Wang

et al., 2008). Due to these harmful dietary patterns in children and adolescents nationwide,

there is a need to look at effective interventions.

Healthy People 2010 aims to reduce the prevalence of children and adolescents who

are obese by five percent (objectives 19-3) (United States Department of Health and Human

Services [USDHHS], 2000). Obesity, a growing pediatric epidemic, is a concern in the U.S.

(CDC, 2010). Literature supports the relationship between the beverage patterns in children

and health status. Furthermore, health effects of SSB include, teeth decay, osteoporosis,

increase in weight, and nutrient deficiency such as calcium and vitamin D (AAP, 2004). Milk

consumption is inversely associated with the consumption of SSB. As SSB increases, milk

consumption is decreasing, resulting in calcium deficiency in children (AAP, 2004; Marshall

4

et al., 2005; Wang et al., 2008). Results of food diaries and dietary survey analyses show that

the consumption of milk and other dairy foods are the main sources of adequate intake of

multiple nutrients, including calcium and vitamin D (Marshall et al., 2005; Wang et al.,

2008). Calcium plays an important role in adolescents’ development. However, pre-teens do

not consume the daily-recommended calcium (NIH, 2009). Data demonstrate higher

consumption of sodas and juices than in calcium-fortified beverages, in children, specifically

in teenagers (Ballew, Kuester, & Gillespie, 2000; James et al., 2004; Marshall et al., 2005;

CDC, 2007). The intakes of 100% juices and sugar-added beverages have been found to be

negatively associated with adequate intakes of calcium and other nutrients (Marshall et al.,

2005; Wang et al., 2008). Thus, it is crucial to understand how the patterns displayed in

beverage consumption affect diet quality.

THEORETICAL BACKGROUND

Multiple factors play a role in a child’s choice of food and beverage such as social

relationships and cultural factors. Interventions to treat obesity and modify diet are complex

and have usually taken a comprehensive approach to be successful (Harrington, 2008;

Stokols, 1996). The Behavioral Ecological Model (BEM) is used in public health to target the

myriad of levels influencing behavior. The BEM suggests that health is affected by behavior

that is determined by environmental subsystems such as, individual, interpersonal,

organizational, community and public policy. Thus, comprehensive interventions are more

efficacious in modifying diet than interventions focused only in one behavior or

environmental factor.

PURPOSE OF THE STUDY

The purpose of this study is to analyze calcium rich beverage consumption and SSB

consumption in the experimental condition versus the control condition in the HYPP study.

The HYPP study aimed to increase bone health (density) in 10-13 year old pre-teens through

physical activity and dietary increase of calcium intake. The HYPP study resulted in the

increase in calcium consumption from baseline to post measurements among participants in

the experimental group as compared to the control group. The present study analyzed

5

changes in beverage consumption at baseline and 3-months among participants.

Experimental effects will be controlled for demographic characteristics.

RESEARCH QUESTIONS

The following questions are explored:

1. Did the experimental group increase consumption of milk and calcium-fortified juices related to the control group?

2. Is the increase in milk consumption related to a reciprocal decrease in the consumption of Sugar Sweetened Beverages (sodas and non-100% juices)?

6

CHAPTER 2

METHODS

The HYPP intervention used a randomized clinical trial study design. Groups

consisted of a control group assigned to an injury prevention program and an experimental

group assigned to a nutrition and physical activity program.

HYPP PARTICIPANTS AND RECRUITMENT

Families from San Diego, California were recruited for the 8-week intervention.

Participants consisted of 10-13 year old children with at least one English or Spanish-

speaking parent. Nine total cohorts were recruited over a period of three years. New sessions

began every three to five months from the initial date, April 2000 to February 2003. The first

cohort (April 2000) consisted of nine families. Cohorts’ size varied (9-21 families).

Recruitment took place in community settings such as, community fairs, advertisement in

local newspaper, participating pediatric clinics, and flyers placed throughout the community

(Hovell et al., 2008). A total of 124 participants completed the baseline and follow up

measurements and will be used in the present analysis.

HYPP Parent Training

Parent and child had separate 90-minute trainings once a week for 8-weeks. Each

session consisted of a 30-minute discussion, interactive activities and questions and answer

portion that focused on osteoporosis, physical activity and diet and bone health. The goals set

forth in the parent group were to help their child perform 30 minutes of moderate to vigorous

physical activity 5 or more days a week and to help their child achieve 1,300 mg of dietary

calcium intake a day. The remaining 60 minutes of each session consisted of behavior

management techniques. Parents were taught skills on how to increase their child’s physical

activity and increase dietary calcium intake. The skills taught included reinforcement

(praising), shaping, modeling, monitoring, goal setting, and behavior contracts. Coaching

calls administered by trained research assistants were given as additional parental support.

All sessions were provided in English or Spanish.

7

HYPP Child Training

Children in the intervention group received 60 minutes of supervised physical activity

and 30 minutes of discussion. Each session began with a brief discussion on bone health,

physical activity and exercise safety. This was followed by a warm-up physical activity that

incorporated “bone-loading” exercises. Fitness games were created so that participants can

perform them in their homes, community or school settings. Each session concluded with

education on calcium-rich foods, calcium-rich sources, and importance of calcium on bone

health. Participants were provided with calcium rich meals at every session. The intervention

took place at a research center.

HYPP Control Group

Parent session included behavior management skills on injury prevention in lieu of

diet and physical activity. Bone health was not discussed during the sessions. Similarly, child

session focused on injury prevention and incorporated activities related to injury prevention

rather than bone health, diet and physical activity. Coaching phone calls, and incentives

procedures were similar to the intervention group.

HYPP IRB AND INCENTIVES

Approval for a secondary analysis was obtained from San Diego State University

Institutional Review Board. Approval for HYPP was approved by San Diego State

University and the University of California, San Diego Institutional Review Boards. All

participants reviewed and consented procedures as mandated by the Institutional Review

Boards.

HYPP DATA ANALYSES/ RESULTS

Data for Calcium intake were collected through phone. Participants reported 24-hour

diet recalls for three days. The participants (child and parent) were asked to recall and report

two meals during the weekday and one during the weekend. Parents assisted and confirmed

the child’s recall. Participants were given measuring tools such as cups and spoons to

measure their intake of foods. All recall data were collected using the Nutrition Data System

(NDS) software version 4.03, developed by the Nutrition Coordination Center, University of

Minnesota, Minneapolis, MN, Food and Nutrient Database 31, released in November 2000.

8

Cross sectional analyses, log transformation, geometric means, and interquartiles for

calcium intakes were computed. Separate analysis for males and females were computed due

to gender differences in baseline levels of calcium. Both males and females in the

experimental group increased their calcium consumption, approximately 25%, from baseline

to posttest. For boys, cross-sectional differences between experimental and control groups

were achieved for 3- and 9-month calcium intake (1352 vs. 1052 mg/day, 1298 vs. 970

mg/day, p < .05). A significant group by time interaction was observed from pretest to

posttest for the full sample (p = .008) and for girls (p = .006) but not for boys (Hovell et al.,

2008).

PRESENT DATA: VARIABLES

Data for the secondary analyses were available from the HYPP’s NDS database.

SPSS version 16.0, and later the upgraded version 18.0 were used. Inclusion criteria for data

in this analysis included only beverage entries for all types of milk, juices, sodas and SSB

(non-diet sodas and non-100% juices) consumed by participants in both experimental and

control group. Other beverages were excluded for analyses due to low reporting of

consumption (less than 50 entries). Beverages excluded were cocoa, frozen treats, coffee, tea,

supplemental beverages, soy and water.

A database was constructed to include beverages to be considered in analyses.

Beverages were categorized and subcategorized. For example, a total milk variable was

created along with variables for the subcategories of total milk including whole milk,

reduced-fat milk and fat-free milk. A variable for SSB was created by adding juice drinks

and non-diet sodas. Calcium-fortified juices variable was created by identifying juice

beverages that contained added calcium. Food identifications were changed from string to

numerical variables in the SPSS data set. A total of eight beverages were used for final

analyses: total milk, whole milk, fat-free milk, reduced- fat milk, sodas, 100% juices,

calcium-fortified juices (all juices with added calcium) and SSB (non-diet & non-100%

juices).

Variables were created for frequencies and grams consumed on an average of 3 days.

Analyzing consumption of beverages in grams is commonly used in research (Watt, Dykes,

& Sheiham, 2000; Dubois, Farmer, Girard, & Peterson, 2007; Keller, Kirzner, Pietrobelli, St-

9

Onge, & Faith, 2009). The 3-day average variables for baseline and 3-month data underwent

logarithm transformation to normalize all skewed data. Log transformed variables were used

in bivariate analyses for all baseline and 3-month data. Geometric means and the 25th and

75th quartile range were reported. Three-month data were categorized using the same

procedures used in the baseline data set. The raw values (total grams consumed on an

average day) were used for change scores (3-months minus baseline) because the data were

normally distributed.

PRESENT STUDY: ANALYSES

Descriptive statistics were used to report demographics and percentages of the sample

that consumed at least one beverage on an average day. Percentage of the sample that

consumed at least one beverage on an average day is defined as reporting to have drunk at

least one beverage on an average of 3 days (frequency), regardless of quantity. Pearson’s chi

square analyses were used to look at significant differences between control and

experimental groups at baseline and three-months, and significant differences between

baseline and 3-months in each respective group, experimental and control. Fischer’s exact

test was reported for cells with expected count less than five. Geometric means and the 25th

and 75th interquartiles are reported for all measurements.

Independent sample t-tests were conducted to obtain significant differences in

consumption by ethnicity and gender at baseline measurements. Independent sample t-tests

were conducted to obtain differences of beverage consumption by group at baseline, 3-

months and change score (3-months minus baseline). Multiple linear regressions were

computed to predict change in the raw amount of beverage consumed regressed on age,

group, ethnicity, and gender for each beverage.

10

CHAPTER 3

RESULTS

A total of 124 participants completed baseline and 3-month measures used in the

present study. Of the 124 participants, 58% were female, 42% males, 38 % White, and 62%

were of other ethnicities (Table 1). Of the 124 participants at baseline, 54 were in the control

group and 70 in the experimental group. The mean age of participants was 11 years old.

Table 1. Participant Demographics (N = 124)

Gender

Male 52 42%

Female 72 58%

Ethnicity

White 47 38 %

Other 77 62 %

Group

Experimental 70 56%

Control 54 44%

BASELINE BEVERAGE CONSUMPTION BY GENDER, ETHNICITY AND GROUP

Frequencies were calculated to look at the geometric means, 25th and 75th percent

interquartiles (Table 2). Independent sample t-tests showed no significant difference in

beverage consumption between males and females at baseline. There were no significant

differences between control and experimental groups.

11

Table 2. Baseline Beverage Grams Consumption by Gender and Ethnicity (Geometric Mean and 25th and 75th quartiles)

Beverages Gender Ethnicity

Male Female White Other

Total Milk 169.5 (122, 437)

171.3 (122, 407)

164.5 (124, 488)

174 (122, 407)

Whole Milk 4.5 (0, 81)

8.1 (0, 122)

2.3* (0, 41)

11.9 (0, 163)

Reduced-Fat Milk 24.2 (0, 269)

35.7 (0, 264)

27.9 (0, 274)

32.0 (0, 253)

Fat- Free Milk 1.5 (0, 0)

0.82 (0, 0)

3.1* (0, 20)

0.36 (0, 0)

Soda 40.0 (0, 247)

37.2 (0, 201)

65.2* (61, 237)

27.7 (0, 215)

100% Juices 2.3 (0, 14)

3.4 (0, 74)

2.6 (0, 44)

3.2 (0, 60)

Calcium Fortified Juices

1.0 (0, 0)

1.5 (0, 0)

1.1 (0, 0)

1.5 (0, 0)

Sugar-Sweetened Beverages

41.8 (1, 248)

41.1 (1, 201)

68.0 (62, 237)

30.6 (0.39, 215)

* p < 0.05

Participants were categorized into White or Other. A significant difference was

observed in soda, whole milk and fat-free milk consumption between White and Other at

baseline (Table 2). White participants consumed more soda (M = 65.2 gm) than Other

participants (M = 27.7 gm), p = .048. Others (M = 11.9 gm) consumed more whole milk than

Whites (M = 2.3 gm), p = .005. Whites consumed more fat-free milk (M = 3.1 gm) than

others (M = .36 gm), p = .001.

BASELINE AND 3-MONTHS CONSUMPTION OF AT LEAST

ONE BEVERAGE ON AN AVERAGE DAY

Table 3 shows the percentage of participants in the control and experimental groups

at baseline and 3-months who consumed at least one beverage on an average day. Crosstab

12

and chi-square analysis do not show significant differences between baseline values in the

control and experimental groups. At 3-months, the chi-square analysis showed a significant

difference between control group and experimental group for the consumption of whole milk

(df = 1, p = .025). The experimental group drank significantly less whole milk than the

control group at 3-months. Inversely, the consumption of total reduced-fat milk was

significantly higher in the experimental group than in the control group (df = 1, p = .008).

Table 3. Percentages of Participants in Control and Experimental Groups at Baseline and 3-Months that Consumed at Least One Beverage on an Average Daya

Beverages Control Group Experimental Group

Baseline 3-Months Baseline 3-Months

Total Milk 70% 59% 60% 71%

Whole Milk 11% 19% + 16% 6% * +

Reduced-Fat Milk 39% 33% + 36% 57% * +

Fat-Free Milk 13% 6% + 6% 7% +

Soda 24% 24% 24% 16%

100% Juices 2% 9% 6% 14%

Calcium Fortified Juices 4% 26% 7% 33%

Sugar-Sweetened Beverages 39% 46% 42% 40% a Percentage of the sample that consumed at least one beverage on an average day is defined as reporting consumption of at least one beverage on an average of three days.

* Significant difference between control and experimental in 3- months (p < .05).

+ Significant difference between baseline and 3- months in respective control and experimental group. Fischer’s exact tests were reported for cells that had expected counts less than five (p < .05).

There was a significant difference within groups in the consumption of whole milk.

The control group (p = .008) increased its consumption of whole milk over time, as the

experimental group (p = .001) decreased its consumption. There was a significant difference

over time in the consumption of reduced-fat milk in the control (p = .003) and experimental

groups (p < .000). The control group decreased its consumption of reduced-fat milk and the

experimental group increased its consumption of reduced-fat milk over time. There was a

significant difference over time in the consumption of fat-free-milk in the control group (p =

.041) and in the experimental group (p = .001). The control group reduced its fat-free milk

13

consumption over time and the experimental group increased its fat-free milk consumption

over time.

GROUP DIFFERENCES AT 3-MONTHS

Table 4 shows a significant difference in the consumption of whole milk between the

control group (M = 0.13 gm) and the experimental group (M = 1.0 gm) at 3-months. The

experimental group consuming more whole milk than the control group, p = .049. A marginal

difference was observed in 100% juice consumption between the control group (M = 3.0 gm)

and the experimental group (M = 8.5 gm), the experimental group consuming more 100%

juices than the control group, p = .055 (Table 4).

CHANGE IN BEVERAGE GRAM CONSUMPTION FROM

BASELINE TO 3-MONTHS IN CONTROL AND

EXPERIMENTAL GROUPS

Changes in beverage consumption were considered both in the control group and the

experimental group. It was hypothesized that participants in the experimental group will

increase their milk consumption significantly. Independent sample t-test showed a significant

increase, from baseline to 3-months, in the experimental group’s consumption in total milk

(M = 77.1 gm), p = .004, reduced-fat milk (M = 119 gm), p = .002, and fat-free milk

(M = 10.6 gm), p =. 036 while showing a reciprocal decrease in whole milk (M = -58 gm),

p = .019. A non-significant increase in 100% juice and calcium-fortified juice and a

reciprocal decrease in soda and SSB were observed.

No significant differences were observed in the change scores of the control group,

even though there was an increase in soda, 100% juices, calcium fortified juices and SSB

(Table 4).

CHANGE IN BEVERAGE GRAM CONSUMPTION

REGRESSED ON AGE, GROUP, ETHNICITY AND GENDER

Table 5 shows multiple linear regressions controlling for age, ethnicity and gender.

Each row in Table 5 represents a separate multiple linear regression. All beverages were

regressed for age, sex, ethnicity and group assignment. However, linear regressions in this

table report the betas and standard error for group assignment only. Group assignment was

14

Table 4. Grams of Beverage Consumed per Group at Baseline, 3-Month Measures and Change Scores (Baseline& 3- Month Geometric Means/Change Score Raw Value a) (25th& 75th Interquartiles)

Beverages

Control Group Experimental Group

Baseline 3 Month Change (Raw Value)

Baseline 3 Month Change (Raw Value)

Total Milk 175.9 (127, 487)

144.3 (122, 343)

-43.8 (188, 90)

166.5 (122, 407)

152.2 (143, 529)

77.1* (-61,222)

Whole Milk 5.6 (0, 81)

0.13 (0,0)

-8.30 (-28, 0))

7.0 (0, 122)

1.0 + (0,0)

-58* (-181,0)

Reduced-Fat Milk

37.3 (0, 282)

27.5 (0,244)

-12.7 (-81, 41)

25.9 (0, 258)

61.3 (0, 483)

119* (-3, 251)

Fat- Free Milk

1.7 (0, 0)

1.5 (0,0)

-9.4 (0,0)

0.69 (0,0)

1.6 (0,0)

10.6* (0,0)

Soda 39.0 (39, 238)

32.5 (0, 247)

14.4 (-121, 158)

37.8 (0, 218)

20.1 (0, 186)

-28.3 (-149, 103)

100% Juices 3.5 (0, 51)

3.0 (0, 44)

14.4 (-36, 44)

2.5 (0, 39)

8.5 (0, 165)

66.1 (0, 132)

Calcium Fortified Juices

1.1 (0,0)

26.3 (0, 237)

147 (0, 186)

1.5 (0,0)

47.2 (0, 337)

182.5 (0, 313)

Sugar-Sweetened Beverages

42.3 (2, 239)

35.6 (1, 247)

15 (-121,157)

40.8 (0.53, 218)

32.8 (1, 186)

-28.3 (-149, 103)

a This table reports baseline, 3-months and change scores beverage consumption by group assignment. The geometric means and 25th, 75th interquartiles are reported for baseline and 3-month data due to skewness. Change scores were calculated by using the raw numbers (total grams consumed on an average day at 3 months minus total grams consumed on an average day at baseline). The geometric means of the change scores resulted in skewed data. The raw numbers for the change scores were normally distributed and are reported here.

* Change Score significance: p < 0.05

+ 3-Months Control and Experimental group significance: p < 0.05

15

Table 5. Multiple Linear Regressions of the Raw Change of Beverage Grams Consumed and Regressed on Group Assignment a

Beverages GroupUnstandardized

Coefficients B SE

GroupStandardized Coefficient

Beta

GroupCoefficient

p-value

Model R2 ANOVAp-value

Total Milk 132.6 41.8 .278 .002* .107 .009* Whole Milk -47.9 21.2 -.204 .026* .058 .125 Reduced-Fat Milk 143.4 41.7 .300 .001* .116 .005* Fat-Free Milk 18.4 9.60 .173 .058* .052 .173 Soda .017 .254 .006 .948 .031 .445 100% Juices .525 .267 .178 .052 .016 .211 Calcium Fortified Juices

.121 .250 .045 .628 .023 .599

Sugar-Sweetened Beverages

.020 .241 .008 .933 .032 .417

a Numbers in cells represent the Unstandardized Coefficient B , Unstandardized Standard Error, Standardized Coefficient Beta, P-value, Model R^2 and Model ANOVA P-value of the raw change score. Each row represents a separate linear regression. All beverages were regressed for Age, Sex, Ethnicity and Group assignment. However, linear regressions in this table report the betas and standard error for group assignment only. Group assignment was the only variable that showed significance. Groups were coded Control = 0 and Experimental = 1. Significance: p < 0.05

the only variable that showed significance. Participants assigned to the experimental group

significantly increased their consumption of total milk (p = .002) and significantly increased

their consumption of reduced-fat milk (p = .001) as compared to participants in the control

group. Model variables for both total milk (F = 3.56, p = .009) and reduced-fat milk

(F = 3.90, p = .005) also increased significantly. A similar significant increase was found for

fat-free milk (p = .058) however; the overall model did not reach significance. Participants in

the experimental group significantly decreased their consumption of whole milk (p = .026)

but the overall model did not reach significance.

16

CHAPTER 4

DISCUSSION

The HYPP study aimed to increase bone density through physical activity and

calcium-rich diet in pre-teens. The HYPP study found a significant increase in calcium

among participant in the experimental group from baseline, 3-month and 9-month measures.

In this secondary analysis, we hypothesized that the experimental group in the HYPP

increased their milk consumption from baseline to 3 months relative to controls. We explored

what type of beverages resulted in the increase of calcium consumption among participants

of the HYPP study.

MILK

Milk is the main source of calcium, vitamin D, magnesium, vitamin A, phosphorus,

zinc and many others for children and adolescents in the US (Johnson, Frary, & Wang,

2002). Studies suggest that 100% fruit juice and milk consumption decreases from early

childhood into adolescence, as SSB consumption increases. In the HYPP study, calcium

increased and a change of milk consumption was observed among participants in the

experimental group. We explored the type of milk that was mainly responsible for this

calcium increase. The HYPP study encouraged the consumption of reduced-fat or fat-free

milk. Bivariate and multilinear regressions showed that there was a significant increase of

77.1 grams, more than 1/4 of a cup of total milk, in the experimental group compared to the

control group from baseline to 3-months. Furthermore, the experimental group significantly

decreased their consumption of whole milk by 58 grams, approximately less than 1/4 of a

cup. The experimental group also increased their consumption of reduced-fat milk by 119

grams, more than 1/2 a cup, and fat-free milk increased by 10.6 grams, less than 1/5 of a cup.

These changes in milk consumption concur with HYPP’s goal of encouraging the

consumption of less fattening milk types.

17

Even after controlling for age, gender and ethnicity, group significance was observed

for all categories of milk, suggesting that the target diet change was achieved by the HYPP

intervention compared to controls.

SSB & SODAS

Research indicates that 32% of adolescents who consume at least one soda per day

are overweight or obese and 27% who do not consume any soda per day are overweight or

obese (Babey et al., 2009). The national trend shows the consumption of SSB has increased

in adolescents. Participants in the control group followed this trend. The control group

increases their consumption of SSB, sodas, 100% juices, and calcium-fortified juices as

consumption of milk beverages decreased. We observed, however, that the participants in the

experimental group consumed less sodas and SSB. Even though there were no significant

group differences at 3-months in these beverage categories, the control group followed the

national trend in consuming more SSB over time.

Many factors can contribute to the increase of SSB over time, regardless of

interventions. The availability of SSB, product innovation, promotion of unhealthy

beverages, overall marketing of these beverages and the food industry’s influence has

impacted the availability and the attractiveness of SSB in the US. This results in an increase

of childhood obesity and lack of nutrient intake in children. Interventions like HYPP may be

promising in reversing beverage consumption patterns that exist today.

JUICES

Juices are a good source of vitamin C and other nutrients. Approximately, 6 ounces of

100% juice is considered one serving of fruit for children (USDHHS, 2000). Studies have

showed that the consumption of 100% juices decrease as the consumption of juice drinks and

SSB increase in children over time (Rampersaud et al., 2003). Due to the growing popularity

of all juices, 100% juices and calcium-fortified juices are recommended. We analyzed these

healthier juice choices, 100% juices and calcium fortified juice consumption. In participants

we did not see a significant change in children’s consumption of any type of juices over time;

however, both the control and experimental group increased their consumption of both 100%

and calcium- fortified juices (Table 3). When looking at consumption of at least one

18

beverage on an average day, calcium-fortified juices had an increase from baseline to 3-

months, regardless of group placement. That is, participants increased their consumption of

calcium-fortified juice from baseline to 3-months in both control and experimental group

(Table 3). This may have been due to participants knowing that dietary recalls were going to

be collected. Furthermore, participants were told that bone density was going to be measured.

Participants could have been more conscious about their food and beverage consumption in

relation to calcium and bone health. Participants could have made an effort to consume more

calcium through juices rather than milk due to it’s rewarding sugar flavors. Even though the

consumption of juices was not proven to be significant, the increasing consumption patterns

shown here hopes to reveal significance in future studies.

Juices, regardless of the nutrient content, contain more sugars than milk. The flavors

of sugars in juices may contribute to the increase of juice consumption. In addition, flavored

milk has been explored as a healthier-sweetened beverage alternative. More children

consumed flavored milk at schools when available. Even though flavored milk has sugars, it

has been found to be significantly associated with higher consumption of calcium and

phosphorus (Johnson et al., 2002). It is significantly associated with nutrient intake and not

weight gain in children (Murphy, Douglass, Johnson, & Spence, 2008). More studies should

look at the patterns of juice consumption over time, sugar content of different types of juices

and milk and how these factors contribute to nutrient intake in children and its effect on the

consumption of other beverages.

ETHNICITY AND BEVERAGE CONSUMPTION

Cultural influence might be a factor in what beverages children consume. A

significant difference was observed in soda, whole milk and fat-free milk consumption in

ethnicity at baseline. White children consumed more soda than other ethnicities. Others

(majority Latinos) consumed more whole milk than White children, while White children

consumed more fat-free milk than Others. This trend aligns with a study by Reedy & Krebs-

Smith (2010), exploring dietary sources of energy among children and adolescents in the US.

In Reedy and Krebs-Smith’s study, White children, aged 2-19, consumed more energy from

sodas and fruit drink than any other ethnicity. They also found that Mexican Americans

consumed more whole milk than Whites. Other studies have shown that minority young

19

adults significantly consume sugared beverages more than white participants (Huffman &

West, 2007). The relationship between ethnicity and beverage consumption is not clear.

Looking at the context for potential moderator is recommended. Research can include

mother, father and siblings, in a diet modification program to look at how family contributes

to a child’s consumption of beverage. For example, a mother’s choice of beverage for her

children is different than the child’s actual preference of beverage. A diet modification

program can target different ethnicities and compare the effect across ethnic groups.

Additional research is also recommended, not only to explore how ethnicity affects beverage

consumption, but focus on the relationship between milk types and ethnicity.

FAMILY-BASED INTERVENTIONS

Health education given to both parents and children is fundamental to decrease SSB

consumption in children and increase calcium rich beverages. We suggest that research look

at social and physical environmental factors when considering changing a dietary behavior of

a child. The HYPP study targeted both parent and child acknowledging that parents are a big

influence to the child’s environment. In a study by (Harel, Riggs, Vaz, White, & Menzies,

1998) adolescents reported receiving information regarding calcium sources from health

classes (55%) and parents (46%). The strong relationship between parent and child, including

monitoring and communication, reinforces a child’s health behavior (Crouter & Head, 2002).

Evidence-supported, family- based interventions are popularly used in literature due

to its effectiveness in improving dietary behaviors. In a study by Kalarchian et al. (2009) a

randomized control trial was implemented to manage weight in 192, 8-12 year old severely

obese children. A family based intervention was conducted for the experimental group. The

6-month intervention consisted of 20 sessions were child and adult met separately for 60

minutes. Sessions consisted of dietary and physical activity behavioral modification

techniques. Self-monitoring, attainable goal setting, skills training, positive reinforcement

and role modeling were all incorporated into the intervention. Three follow-up supportive

phone calls and three sessions were conducted after the 6-month and 18-month period. The

primary outcome measure was child percent weight (BMI). Results indicated significant

decrease of BMI at 6-month period for the intervention.

20

Family-based interventions like HYPP have been proven to be effective in modifying

diet in children. In the HYPP study, parent and children were given independent training in a

classroom setting as well as telephone coaching. In both, HYPP and Kalarchian’s study,

parent and child were given separate, intensive educational training.

LIMITATIONS

These analyses demonstrated a significant relationship in calcium increase from a

parent-child training and its effects on beverage choice among participants. However,

limitations need to be noted. Limitations include reporting baseline and 3-month data in

geometric means and reported change scores in raw variables. This inconsistent reporting

was due to some participants consuming very little of overall beverages and few participants

consuming a lot of one beverage. This made it difficult to obtain data with a normalized

distribution. The log was taken to normalize the data. The antilog was taken to convert data

to their natural value. However, the change score were normally distributed and did not need

to be log transformed. Values were skewed in baseline and 3-month data but were normally

distributed in the change score. In order to avoiding confusion, we decided to report data that

are normally distributed at baseline, 3 months, and change scores.

Other limitations include reporting bias. Participants may have been too young to

accurately complete self-reported questionnaires or phone questionnaires. Even though

parents helped children with recall and were provided measuring tools (cups, spoons and

food pictures), they might not have been with the child at all times to know what they

consumed, resulting in under-reporting or over- reporting. Further, the validity of the self-

reported data of only three days is a limitation. Three days is a short period to truly capture

the normal consumption pattern of a child, however all recalls were averaged. The exclusion

of other beverages such as diet sodas, water, tea and multivitamin supplemental beverages is

a limitation. Due to a low number of participants consuming these beverages, analyses of

these beverages were not feasible.

IMPLICATIONS

Even though beverage trends among U.S. children are of great concern, literature

supports the relationship between food consumption, behavior modification and

21

improvement of health. This secondary analysis aimed to support interventions targeting

children’s health through the modification of diet, in particularly beverage consumption.

Interventions such as the HYPP study prove, to not only increase calcium through milk, but

also improve the choice of milk a child consumes. A shift from whole milk to less fat milk

can be promoted in more diet modification programs. There is a need for more focus on

shifting beverage trends from high-calorie beverages (SSB) to healthier beverages (reduced-

fat milk, fat-free milk and 100% juices). Furthermore, if certain beverages, such as milk,

show to be affected by the increase or decrease of another, such as SSB, researchers can

focus on these patterns and plan interventions accordingly.

Policy and environment may also play a role in the effectiveness of beverage

modification programs. In 2005, the New York City Department of Education implemented

the reduction of whole milk in schools and switched to reduced and fat free milk in order to

decrease the prevalence of childhood obesity. Children consumed 25% less calories and 81%

less fat from milk due to this change (CDC, 2010). The substitution of nutrient-dense

beverages over high calorie- sugar beverages needs to be supported through policy change.

There are various factors contributing to lack of calcium intake and over-consumption

of SSB in children. Research and interventions need to consider the child’s environment,

ethnicity and beverage content, like sugars. A comprehensive approach intervening with

various determinants are popularly used and are conceptually recommendable (Harrington,

2008). Family based interventions and cross- sectional measurements are a recommended

approach proven to be effective in various behavior modification interventions such as, diet

(Kalarchian et al., 2009; Wilfley et al., 2007). Researchers need to consider high fidelity of

interventions, that is, the extent to which the intervention was consistent with behavioral

theory. Health behaviors with high fidelity have been proven to be effective (Keller et al.,

2009). High fidelity is recommended to obtain the best replicable interventions that will have

an effect on healthier beverage consumption in children. The HYPP, based on learning

theory, proved to have high fidelity, thus obtained significant results that matched the

intervention’s purpose.

These analyses reinforce national trends of beverage consumption in children proven

by various studies. The study increased reduced and fat-free milk while decreasing whole

22

milk. This pioneers research in randomized control family-based intervention to increase

calcium through healthier choices of beverages, in particularly reduced and fat-free milk.

23

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