GROWTH AND ADIPOSITY OF CHILDREN WITH DOWN SYNDROME: EFFECT OF TOTAL ENERGY EXPENDITURE. Rosemary K. DeLuccia

GROWTH AND ADIPOSITY OF CHILDREN WITH DOWN SYNDROME: EFFECT OF TOTAL ENERGY EXPENDITURE by Rosemary K. DeLuccia A thesis submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Master of Science in Human Nutrition Spring 2017 2017 Rosemary K. DeLuccia All Rights Reserved

GROWTH AND ADIPOSITY OF CHILDREN WITH DOWN SYNDROME: EFFECT OF TOTAL ENERGY EXPENDITURE by Rosemary K. DeLuccia Approved: Jillian C. Trabulsi, Ph.D., R.D. Professor in charge of thesis on behalf of the Advisory Committee Approved: P. Michael Peterson, Ed.D. Chair of the Department of Behavioral Health and Nutrition Approved: Kathleen S. Matt, Ph.D. Dean of the College of Health Sciences Approved: Ann L. Ardis, Ph.D. Senior Vice Provost for Graduate and Professional Education

ACKNOWLEDGMENTS I would like to thank my advisor, Dr. Jillian Trabulsi, for her continuous guidance through my thesis project, as well as throughout the rest of my undergraduate and graduate studies. The knowledge that I have gained from her expertise in nutrition is unparalleled. I would also like to thank my thesis committee members, Dr. Shannon Robson and Dr. Mia Papas, for their valuable advice through the progression of my thesis writing. Finally, I would like to thank my family and friends for their nonstop encouragement and support throughout my academic endeavors. iii

TABLE OF CONTENTS LIST OF TABLES... vi ABSTRACT... vii Chapter 1 INTRODUCTION... 1 2 REVIEW OF THE LITERATURE... 3 2.1 Down Syndrome... 3 2.2 Feeding and Growth of Children with Down Syndrome... 4 2.3 Overweight and Obesity Prevalence in Children with Down Syndrome.. 5 2.4 Energy Intake in Children with Down Syndrome... 7 2.5 Resting Energy Expenditure in Children with Down Syndrome... 8 2.6 Total Energy Expenditure in Children with Down Syndrome... 10 2.7 Physical Activity in Children with Down Syndrome... 11 2.8 Summary of Literature Review... 11 3 AIMS... 13 3.1 Specific Aims... 13 4 METHODS... 15 4.1 Subjects... 15 4.2 Study Visit Procedures... 16 4.3 Anthropometric Measurements... 16 4.4 Total Energy Expenditure Measurements... 17 4.5 Energy Intake Measures... 19 4.6 Data Analysis and Statistics... 19 5 RESULTS... 23 5.1 Normality Testing and Distribution of Outcome Variables... 23 5.2 Demographic and Anthropometric Characteristics for All Enrolled Children (n=72)... 23 5.3 Demographic and Anthropometric Characteristics for Enrolled Children with Total Energy Expenditure Measure at Baseline (n=61)... 24 iv

5.4 Baseline Differences in TEE by Health Status (Down Syndrome vs. Control)... 25 5.5 Baseline TEE Contribution to Changes in Adiposity Over Three Year Period... 26 5.6 Baseline Differences in EI:TEE Ratio by Health Status (Down Syndrome vs. Control)... 27 5.7 Baseline EI:TEE Contribution to Changes in Adiposity Over Three Year Period... 28 5.8 Anthropometric Characteristics for Enrolled Children with Baseline Total Energy Expenditure Measure at Three Year Time Point... 29 6 DISCUSSION... 30 7 CONCLUSION... 33 REFERENCES... 35 Appendix A TABLES... 41 v

LIST OF TABLES Table 1a - Basic Characteristics of All Enrolled Children at Baseline: Down Syndrome (DS) versus Control siblings... 41 Table 1b - Basic Characteristics of Enrolled Children with Total Energy Expenditure Measured at Baseline: Down Syndrome (DS) versus Control siblings... 42 Table 2a Regression Models on the effect of health status on baseline TEE including potential covariates (Model 1) and final covariates (Model 2).... 43 Table 2b- Generalized Estimating Equations for the effect of baseline TEE and health status on changes in adiposity over three years.... 44 Table 3a Regression Models on the effect of health status on baseline EI:TEE = (Model 1) and on baseline log EI:TEE (Model 2).... 45 Table 3b- Generalized Estimating Equations for the effect of baseline EI:TEE and health status on changes in adiposity over three years.... 46 Table 4 - Anthropometric Characteristics of Enrolled Children with Baseline Total Energy Expenditure Measure at Three-Year Time Point: Down Syndrome (DS) versus Control siblings... 47 vi

ABSTRACT Children with Down syndrome (DS) have different growth patterns compared to their healthy counterparts and have a higher incidence of overweight (body mass index (BMI) at or above the 85 th percentile and below the 95 th percentile) and obesity (BMI at or above the 95 th percentile) by age three to four years. The factors that contribute of overweight and obesity in this population are not fully understood, although weight gain typically results from positive energy balance, where energy intake exceeds energy requirements. Limited evidence has investigated energy intake (EI), resting energy expenditure (REE), total energy expenditure (TEE), and the ratio of energy intake to total energy expenditure (EI:TEE) in prepubescent children with DS compared to healthy children of similar age. A better understanding of the components of energy balance in this population is needed to inform intervention strategies and prevent children with DS from becoming overweight/obese in childhood. The purpose of this study was to determine whether TEE or EI:TEE differs in children with DS compared to healthy sibling controls at baseline, and whether there was an association between TEE or the EI:TEE ratio and changes in adiposity in the subsequent three year period in children. This study enrolled a total of 72 children, 36 children with DS and 36 healthy sibling controls. Sixty-one children (29 DS and 32 controls) had successful TEE measures. At baseline, TEE (with adjustment for fat free mass) was significantly lower (p<0.001) in children with DS (1466.7 ± 38.4 kcal/d) compared to controls (1593.0 ± 35.2 kcal/d); however, the EI:TEE ratio (1.07 ± 0.0 and 101 ± 0.0 for DS and healthy controls, respectively) was not statistically vii

significantly different (p=0.4229) between groups. Consequently, children with DS had a stronger positive association between baseline TEE and change in adiposity over three years compared to their healthy control siblings (p=0.032), but there was no difference in the relationship between EI:TEE ratio and changes in adiposity over time by health status (DS versus healthy controls) (p=0.568). Post-hoc power calculations found that this study was underpowered to detect differences in EI:TEE outcomes between groups, and as such these results should be interpreted with caution. Further analysis with a larger sample size is needed to confirm TEE and EI:TEE associations with changes in adiposity in children with DS. viii

Chapter 1 INTRODUCTION Down syndrome (DS) is a medical condition caused by the abnormality of chromosome 21. 1,2 This chromosomal variation results in multiple physical and mental attributes and defects, and ultimately is associated with abnormal growth in children with DS compared to healthy counterparts. 2-8 Growth retardation in children with DS starts in utero, 9,10 and continues to be reduced during infancy and young childhood. 11-14 Delayed motor skill development due to cognitive impairments results in suboptimal feeding and overall poor energy balance at this time. 4,7,11,15-21 Despite poor feeding and delayed growth during infancy, by three to four years, children with DS are more likely to be overweight or obese as compared to healthy age-matched controls. 6,22 Population specific studies suggest that up to 50% of children with DS between ages one month and 18 years are considered overweight (body mass index (BMI) at or above the 85 th percentile and below the 95 th percentile), 23 and of this approximately 30% of children with DS to be considered obese (BMI at or above the 95 th percentile). 13 Excess weight can result in a variety of negative outcomes later in life in all individuals, 24-26 and the effect of overweight and obesity on the health of individuals with DS, who already have a reduced lifespan, 3,4,19 requires further study. 27 For these reasons, overweight prevention and treatment is considerably important for children with DS. 1

The exact causes of overweight and obesity in children with DS are unknown, but are hypothesized to result from positive energy balance, where energy intake (EI) exceeds energy requirements. Studies examining EI suggest that prepubescent children with DS have a significant lower EI compared to healthy controls of similar age. 28-29 Studies examining energy expenditure also suggest significantly lower resting energy expenditure (REE) in prepubescent children with DS compared to healthy controls. 30,31 A small study of energy balance in prepubescent children with DS (n=10) and healthy controls (n=10), found that EI, total energy expenditure (TEE) and the ratio of energy intake to energy expenditure (EI:TEE) appeared lower in children with DS compared to healthy controls, however the difference between groups was not statistically significant. 23 A better understanding of energy balance, and more specifically the EI:TEE ratio, in this population is needed to inform intervention strategies and prevent children with DS from becoming overweight/obese in childhood. 2

Chapter 2 REVIEW OF THE LITERATURE 2.1 Down Syndrome Down syndrome (DS), also known as Trisomy 21 or Trisomy G, occurs due to an abnormality of chromosome 21. 1,2 There are three types of DS, which vary chromosomally, but are outwardly in differentiable. Trisomy 21, the most common variation of DS, occurs in about 95% of all individuals with DS, and is caused by a third copy of chromosome 21, instead of the typical two copies. Translocation DS, occurs when an extra chromosome 21 is present, but is attached to a different chromosome rather than being completely distinct. Mosaic DS occurs when an individual has some cells with three copies of chromosome 21, and other cells with the typical two copies. 1,2 The typical count of chromosomes in human beings is 46. The extra chromosome in Trisomy 21 and in some cells of individuals with Mosaic DS results in a total of 47 chromosomes. Translocation DS individuals have 46 chromosomes, because the translocated chromosome is not counted independently. 1.3 Although the chromosomal variations involved in the different forms of DS are small, they result in multiple physical and mental attributes and defects. Physical attributes of DS include: a flat face especially around the bridge of the nose, almondshaped eyes with an upward slant, a short neck, small ears, a tongue that sticks out of the mouth, white spots on the iris of the eye, small hands and feet, small pinkies that 3

curve inward, a single palmar crease on the hand, poor muscle tone, loose joints, and short stature. 2-5 Systematically, about 40-50%, of DS individuals have congenital heart disease. 2,3,6 Gastrointestinal complications, most commonly celiac disease and Hirschsprung disease, and endocrine diseases, including hypothyroidism and diabetes, may also be present. 2-4,7 Cognitively, individuals with DS typically have learning and memory impairments that begin in late infancy and become more noticeable in childhood through adulthood. 8 Individuals with DS have an intelligence quotient (IQ) in the ranges of 20-35 (indicating severe cognitive impairment) or slightly higher around 50-75 (indicating mild cognitive impairment), compared to a normal IQ range of 90-110. In early life, slower language and gross motor skill development is common. 3,5,8 2.2 Feeding and Growth of Children with Down Syndrome The growth of children with Down syndrome is abnormal compared to their healthy counterparts. Growth retardation in children with DS starts in utero, 9 and infants with DS are more likely to be born preterm, 32 have lower birth weights (<2500g), 14,32 and have significantly decreased muscle tone compared to healthy infants. 14,17,33 Short stature is common in children with DS. 11-13,34 Growth velocity is reduced between six months and three years and by the age of three years old, 90% of children with DS are shorter than healthy children of the same age. 11 Two studies reported that the mean height for children with DS between one month and 18 years was anywhere between one and a half to four standard deviations below the mean 4

height of healthy controls, depending on the age of comparison. 12,13 Adult heights for individuals with DS are reached at a relatively young age, 15 to 16 years old. 34 By adulthood, height remains shorter than that of adults without DS. 12,14 In a recent study of 637 U.S. children with DS from 25 states, z-scores calculated from standard World Health Organization (WHO) and Centers for Disease Control (CDC) growth charts found a mean length for age z-score (children birth to two years) and mean height for age z-score (children two to 20 years) of -1.7 and -2.1, respectively; the negative z- scores indicate that average lengths and heights in individuals with DS ages birth to 20 years are shorter compared to healthy children of similar age. 14 For this reason, growth charts specifically for individuals with DS have been developed, reflecting DS specific growth patterns. 14 Due to cognitive impairments, delayed motor skill development is typical for infants with DS, and may result in suboptimal feeding related to oral reflex dysfunction such as poor suckling, poor lip closure, swallowing difficulties, choking, aspiration, and emesis. 15-17 As infants with DS age and transition from breastfeeding or bottle feeding to solid foods, they show increased food refusal, reluctance to chew, sucking on food, and refusal of foods not pureed or softened. 18 Other conditions that are attributed to poor energy balance in infants with DS include: prematurity, gastroesophageal reflux, gastrointestinal anomalies, congenital heart disease, food refusal, surgeries, and other chronic diseases or infections. 4,7,11,19-21 2.3 Overweight and Obesity Prevalence in Children with Down Syndrome Despite poor feeding and delayed growth during infancy, as children with DS 5

age, overweight and obesity becomes more prevalent. Children with DS typically begin life underweight and progress to age appropriate weight and height, but overweight and obese become prevalent by age three to four years. 6 One recent metaanalysis found the prevalence of overweight and obesity in children and adolescents with intellectual disabilities, including DS, to be 15% and 13% respectively for children, and 18% and 15% respectively for adolescents. 35 Another recent study of 303 children with DS ages two to 18 (mean age 10.6 years) found the prevalence of overweight and obesity in children with DS was 22.4% and 47.8%, respectively, compared to 15.1% and 12.1% for age-matched healthy controls. 22 Despite clear difference in overweight and obesity rates, one study measuring parent perceptions of their children s weight status indicated that parents do not consider the weight status of their children with DS to be different than the weight status of their healthy children. 36 Use of BMI to classify overweight and obesity is not a direct measure of fat mass (FM) and fat free mass (FFM); however, results from a recent study that used both bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) to assess body composition found high amounts of body fat in children with DS, 30.5% and 22.5% body fat in girls and boys, respectively. Based on these fat mass percentages rather than on BMI classifications, 38% of girls and 23% of boys with DS in the sample population were classified as obese. 37 In a study of adults with DS ages 18-86 (mean age 37.1 years), 30.9% of the individuals with DS in the study were overweight, 53.4% were obese, and 10.4% were morbidly obese. Individuals with DS had the highest rates of overweight, obesity, and 6

morbid obesity compared to other intellectual disorder classifications in this study such as autism, cerebral palsy, and unknown etiology intellectual disorders. 38 While some body fat is necessary for various body functions, excess weight can result in a variety of negative outcomes later in life in both healthy children and children with DS, including: type 2 diabetes mellitus; cardiovascular, cerebrovascular, and renal diseases; musculoskeletal issues; and negative psychological effects. 24-26 Historically, the lifespan of individuals with DS was documented to be shorter that of a healthy individual; however, more recently, individuals with DS have lived into their 70s due to the advances in health care. 3,4,19 While cardiac diseases are identified as the biggest influence on early death, 3,32 weight-related co-morbidities can also shorten life expectancy. 26 For these reasons, overweight prevention and treatment is considerably important for children with DS, as they have higher rates of overweight and obesity during childhood and are more likely be overweight and obese in adulthood. 2.4 Energy Intake in Children with Down Syndrome The exact factors that lead children with DS to transition from low birth weight and poor growth during infancy, to an overweight or obese status in child- and adulthood are unknown. Weight gain typically results from positive energy balance, where EI exceeds energy requirements. With respect to EI, the age at which EI is measured is an important consideration as energy needs are based on age, in addition to sex and body weight. In a study comparing 44 toddlers with DS to 37 healthy control children aged one to four years, EI for toddlers with DS was significantly lower, 27% below the Recommended Daily Allowance (RDA) as compared to 9% 7

below for healthy controls. 28 Similarly, in a study comparing intake between children with DS and sibling controls aged two to 14 (mean age of male children with DS 4.1 ± 2.5 years compared to male controls 5.9 ±2.9 years, and mean age of female children with DS 5.1 ± 2.8 years compared to female controls 6.9 ± 3.5 years), EI, calculated as a percentage of the estimated needs, was 88.7% in children with DS and 95% in healthy controls, meaning control children came closer to meeting their estimated energy requirements (EER). Though EI was lower for children with DS, the difference was not significant. 29 Another study in similarly aged children, aged five to 11, found children with DS (mean age 8.8 ± 2.5 years), compared to controls (mean age 9.1 ± 2.9 years), appeared to consumed less energy, 1861 ± 488 kcal/d compared to 2393 ± 781 kcal/d respectively, however this difference was not significant. When EI was compared to EER estimated by the age appropriate RDA, children with DS consumed 86.5 ± 28.6% of their RDA and controls consumed 111.3 ± 21.6% of their RDA, meaning that controls seemed to over-consume EI according to their EER, while children with DS did not achieve an EI equal to their EER. 23 Taken together, the findings related to EI are conflicting, with some studies finding children with DS have lower EI than healthy controls and other studies finding no differences. 2.5 Resting Energy Expenditure in Children with Down Syndrome Another proposed mechanism for weight gain and development of overweight/obesity in individuals with Down syndrome (DS) is lower energy expenditure. Resting energy expenditure (REE) is the amount of energy expended by an individual in a resting state and is predominately influenced by age, body size, and fat free mass. REE accounts for approximately 65-70% of total energy expenditure 8

(TEE). TEE represents the total amount of energy expended in a day and includes REE, the thermic effect of feeding (TEF), and energy expended for physical activity (PA). The EER represents the amount of energy children need for both TEE and tissue accretion/growth. 39,40 REE has been studied in various populations of children and adults with DS. A study involving 16 full-term neonates, (one week of age), eight with DS and eight controls, measured REEs once per day over a three-day period. EI was held similar between the groups through oral feedings every four hours of the same infant formula, with comparable calorie and fluid intake. The study found REE was significantly decreased in those with DS compared to the controls, by an average of 14%, with little variability in measured REE from day to day. 33 In prepubescent children, lower REE was found in children with DS, as compared to control groups. 30,31 One study of children aged four to 11 years (mean age 8 ± 2 years) found measured REE, expressed as the percentage of the basal metabolic rate (BMR) predicted by the World Health Organization (WHO) equations, was 79.5% ± 10.4% in children with DS and 96.8% ± 7.8% in the control children. 30 Another study included 28 children with DS (mean age 6.1 years) and 35 control children (mean age 6.9 years), who were siblings of the children with DS. 31 This study found median REE for the children with DS to be 1012 kcal/day and for the control group to be 1167 kcal/day. REE was significantly lower in the children with DS when adjusted for FFM, FM, sex, age, African ancestry, and thyroid function. Additionally, lower REE was not predictive of fat gain over the three-year follow-up. 31 Taken together, these studies suggest REE is lower in 9

infants/children with DS compared to healthy controls. In contrast to the results found in both neonate and prepubescent children populations, REE has not been found to be reduced in adults with DS as compared to healthy controls. In a study comparing 22 adults with DS and 20 nondisabled controls, ranging in age from 17 to 29 years (mean age 25.7 versus 27.4 years respectively), unadjusted REE was not significantly different between groups, and adjusting for body weight, body surface area, gender, or aerobic capacity did not change the significance. Adjusting for BMI resulted in higher REE for the controls, yet adjusting for FFM resulted in higher REE in those with DS. 41 The overall conclusion suggested that REE was similar between adults with DS and healthy controls. 2.6 Total Energy Expenditure in Children with Down Syndrome Studies of TEE in individuals with DS are almost nonexistent in the literature. Only one cohort study to our knowledge has addressed TEE in children with DS compared to controls. 23,30 This cohort included 10 children with DS and 10 control subjects aged four to 11 years and found that TEE in not differ significantly between children with DS and healthy controls. 23 When EI was compared to TEE, children with DS consumed 114.0±24.8% of their TEE, compared to 122.1±14.6% consumed by the controls, though the difference in EI:TEE ratios was not significant. 23 Non-REE expenditure, including PA and TEF, was also similar between the groups. 30 Given that only one study has measured TEE in children with DS, further studies are needed to fully understand TEE in this population. 10

2.7 Physical Activity in Children with Down Syndrome With respect to PA, children with DS have been shown to spend less time engaging in vigorous PA, and spend more time engaging in moderate and low intensity PA compared to their healthy sibling controls. 42 Additionally, children with DS have been reported to spend less time playing outdoors, prefer to play inside, and were seen by their parents as less active, despite being enrolled in various organized physical activities such as swimming or aerobics. 29 2.8 Summary of Literature Review Children with DS grow abnormally compared to their healthy counterparts. A shorter stature compared to healthy subjects of a similar age becomes evident as early as six months and remains through adulthood. 11,12,14 Children with DS typically begin life underweight, progress to an age-appropriate weight, and become overweight and obese by age three to four years. 6 The exact causes of overweight and obesity are unknown. Studies examining EI suggest that prepubescent children with DS have a lower EI compared to healthy controls of similar age. 23,28,29 Similarly, studies have also suggested lower REE in prepubescent children with DS compared to healthy controls. 30,31 Only one study has evaluated TEE and the EI:TEE ratio in children with DS, and found no significant difference between prepubescent children with DS and healthy controls in TEE and EI:TEE ratios. 23 Overall, there is a paucity of literature, especially current literature, on the components of energy balance (EI and TEE) in prepubescent children with DS. A better understanding of energy balance in this population is needed to inform 11

intervention strategies and prevent children with DS from becoming overweight/obese in childhood. 12

Chapter 3 AIMS The overall aim of this proposal is to determine associations among energy intake (EI), total energy expenditure (TEE), and adiposity in a cohort of prepubescent children with Down syndrome (DS) and their healthy sibling controls. 3.1 Specific Aims Primary Aim: Specific Aim 1a: Determine whether TEE differs in children with DS compared to healthy sibling controls at baseline. Specific Aim 1b: Determine the association between TEE and changes in adiposity in the subsequent three-year period in children and examine whether this association differs for children with DS versus their healthy sibling controls. Because children with DS have been shown to spend less time engaging in vigorous physical activity (PA), more time engaging in moderate and low intensity PA, 42 and were seen by their parents as less active despite being enrolled in various organized physical activities such as swimming or aerobics, 29 we hypothesize that TEE will be lower in children with DS as compared to healthy sibling controls. We also hypothesize that TEE will be predictive of changes in adiposity (% body fat) over a three-year period. Finally, we believe that there will be no difference in the 13

association between TEE and changes in adiposity in children with DS and their healthy sibling controls. Secondary Aim: Specific Aim 2a: Determine if the total EI to TEE ratio (EI:TEE) differs in children with DS compared to healthy sibling controls. Specific Aim 2b: Determine if the EI:TEE ratio is associated with changes in adiposity over a three-year period in children and whether this association differs for children with DS versus their healthy sibling controls. The EI of children with DS has been reported to be lower than the EI of healthy control subjects in two studies, 28,29 but not another. 23 Since resting energy expenditure (REE) has been consistently shown to be lower in children with DS, 30,31 we hypothesize that TEE will also be lower in children with DS, and the ratio of EI:TEE will be higher in children with DS compared to controls. We hypothesize that the EI:TEE ratio will be positively associated with changes in adiposity (% body fat) over a three-year period. We also hypothesize that there will be no difference in the relationship between EI:TEE ratio and changes in adiposity in children with DS and their healthy sibling controls. 14

Chapter 4 METHODS 4.1 Subjects This study was conducted at the Children s Hospital of Philadelphia. Thirty-six families in the Philadelphia metropolitan area were recruited through physicians, support groups, or word of mouth to participate in this study. To be eligible to participate, each family needed to have at least two prepubertal children between four and 10 years of age: one child with Down syndrome (DS) and one child without DS, equaling a total of 72 child participants in the study. The children without DS were included in this study as controls in order to minimize variability of environment on resting energy expenditure (REE) and obesity, as well as to avoid bias in recruitment of a healthy control group. If families had more than one sibling eligible as the control, the decision of who participated was determined by the caregiver. Further eligibility requirements included both children having a body mass index (BMI) below the 95 th percentile for age and sex, which was calculated based on self-reported weight and height during telephone interview screening. Exclusion criteria included: significant medical co-morbidities such as cancer, congenital heart disease requiring open heart surgery, intestinal anomalies requiring resection, 15

hypothyroidism requiring thyroid hormone medication, or other chronic conditions that could significantly affect growth or energy balance. 31 The study in its entirety was approved by the Children s Hospital of Philadelphia Institutional Review Board. Before study procedures began, written consent and assent were obtained from all parents and study subjects. 4.2 Study Visit Procedures This study was a three-year prospective cohort of 72 pre-pubertal males and females, 36 with DS and 36 sibling controls, aged four to 10 years at baseline. This study included a baseline inpatient visit and three brief annual outpatient follow-up visits which occurred at 12, 24, and 36 months. The baseline inpatient visit was an overnight stay in the General Clinical Research Center (GCRC) at The Children s Hospital of Philadelphia. Prepubertal status was confirmed at baseline using a validated self-assessment questionnaire that was completed by subjects with the help of parents if necessary. Demographic and anthropometric information were collected at this time. Demographic information included participants dates of birth, and selfreported race and ethnicity. 43 Thyroid function was assessed with a blood sample for serum T4 (thyroxine, reference range 5.53-11.0 mcg/dl). 31 Annual follow-up visits included anthropometric measurements only to assess growth and patterns of change in body composition in both groups of children, during outpatient visits to the GCRC. 4.3 Anthropometric Measurements Anthropometric measurements were collected by trained research anthropometrists at the baseline visit as well as at all follow-up visits. Anthropometric measurements were taken with the subject wearing a light gown and no shoes. Weight 16

was assessed to the nearest 0.1kg using a digital scale (Scaletronix, White Plains, NY, USA). Height was assessed to the nearest 0.1cm using a wall-mounted stadiometer (Holtain LTd., Crymych, UK). BMI (kg/m 2 ) was calculated using these measurements and was converted to Centers for Disease Control and Prevention BMI z-scores using sex and age-specific reference data. 44 Skinfold measurements (Holtain skinfold calipers) were taken at four points: triceps, biceps, subscapular, and suprailiac using standard techniques. All anthropometric measures were taken in triplicates and average measurements were used in analyses. Fat mass (FM) and fat free mass (FFM) were then determined using sex and age specific equations and the anthropometric measurements. Dual energy x-ray absorptiometry (DXA) was used to confirm body composition (FM, FFM) and determine bone mineral density (BMD) in a sub-sample of cooperative subjects. DXA scans were taken following standard positioning techniques (Hologic Delphi densitometer, Bedford, MA, USA). The in vitro coefficient of variation for bone mineral density was 0.6%, the in vivo coefficient of variation was <1%, and the coefficient of variation for FFM, FM, and percentage body fat were 0.4%, 1.27%, and 1.26% respectively. 31 4.4 Total Energy Expenditure Measurements Total energy expenditure (TEE) was measured using the Doubly Labeled Water (DLW) technique. DLW requires subjects to ingest water enriched with two stable isotopes: deuterium and oxygen-18. After equilibrating with total body water (TBW), these isotopes are eliminated from the body over time through normal metabolic processes. Deuterium is eliminated through water (urine), and oxygen-18 is eliminated through water and gas (carbon dioxide in expelled air). The differential rate 17

of elimination of these isotopes is used as a measure of carbon dioxide production, which is then converted to TEE using the Weir equation. 45 For this study s DLW protocol, a urine sample was collected at baseline to determine each subject s natural enrichment of O-18 and deuterium. Subjects then received an oral DLW dose two hours after their last evening meal on day one of their baseline visit at the GCRC. The DLW dose contained 0.14g 2 H 2 O (99.8 atom% excess, Sigma Aldrich, Milwaukee, WI), and 0.3g H 18 2 O (10 atom% excess, ICON Services, Summit NJ) per kg estimated TBW. A pre-weighed absorbent cloth was used to collect any spilling of the isotope dose water that occurred; this cloth was reweighed after DLW procedures to quantify any dose loss. Next, the first and second urine voids were collected on post DLW dose days one, two, 13, and 14. All urine samples were frozen until a mass spectrometry analysis was completed. The amount of isotope ( 2 H and 18 O) present in each urine specimens was determined using an isotope ratio mass spectrometer (ThermoQuest Finnigan Delta Plus, San Jose, CA). Urine sample were treated with 20 mg activated charcoal, mixed using a vortex mixer for 10 seconds, and filtered through a 0.45-micron filter (Millipore Corporation, Billerica, MA) before they were analyzed by mass spectrometry. Deuterium analysis was completed by reducing water to hydrogen gas followed by an automated injection of 1.0 ml sample in a quartz tube packed with chromium metal (100-200 mesh) and maintained at 850 degrees Celsius. Five measurements of isotope enrichment and five measures of standard reference hydrogen were obtained for each specimen, and the mean ± standard deviation for 18

each isotope was determined. After correction for the triprotium ion, data was expressed in parts per million (%) relative to standard mean oceanic water (SMOW). Oxygen-18 analysis was completed by placing the specimens into a gas bench analyzer, and injecting a defined volume of gas (0.3% CO 2 /99.7% He) into the vials. An 18-hour period was allowed for equilibration of water and carbon dioxide at room temperature, and then samples were injected into the isotope ratio mass spectrometer. Thirteen measurements were collected from each sample: nine for the unknown urine sample and four for the reference gas, and the mean of the nine samples was used in analyses expressed as parts per million (%) relative to SMOW. 46 4.5 Energy Intake Measures EI was determined via a three-day diet record (two weekdays, one weekend day). For each day, parents recorded the amount and type of all foods and beverages consumed. Dietary intake data were converted into nutrient intake using Nutrient Data System for Research (NDS-R) software. Nutrient intakes across the three days were averaged and the average intake of each nutrient was used in the analysis. 4.6 Data Analysis and Statistics Variables of interest in this analysis include health status (prepubescent children with DS vs. healthy sibling controls), demographic characteristics (sex, race, and age), baseline energy balance measures (EI, REE, TEE, EI:TEE ratio), baseline anthropometrics (weight, height, BMI), baseline adiposity measures (FM, FM), thyroid function (thyroxine), and changes in FFM and FM over three years. 19

Descriptive statistics were used to examine child characteristics (sex, age, health status, anthropometric measurements, etc.) for the total cohort of children and also separately by health status (DS versus control). Data are reported as means, standard error of the means (SEM), frequencies, and percentages. Specific Aim 1a: Determine whether TEE differs in children with DS compared to healthy sibling controls at baseline. To assess specific aim 1a, a multiple linear regression model was fit to examine the association between health status (prepubescent children with DS versus healthy sibling controls) and TEE (kcal/day) where health status was the independent variable and TEE measured by DLW was the dependent variable. Known confounders such as FFM, and potential confounders such as FM, % body fat, height, age, sex, race, and thyroid function were tested for inclusion in the model. All covariates had to satisfy three general criteria to be included in the model as a confounder: 1) significantly associated with health status; 2) significantly associated with TEE (kcal/day); and 2) not in the casual pathway between health status and TEE (kcal/day). 47 Specific Aim 1b: Determine the association between TEE and changes in adiposity in the subsequent three-year period in children and examine whether this association differs for children with DS versus their healthy sibling controls. To assess specific aim 1b: A generalized estimating equation (GEE) was fit to determine the association between TEE (the independent variable) and adiposity, (measured as % body fat) over time (the dependent variable). Adiposity was measured at four time points (baseline and 12, 24, and 36 months post-baseline) for each child 20

necessitating the use of a longitudinal data analytic strategy such as GEE that takes into consideration repeated measures over time. Baseline TEE was included as the independent variable and adiposity (% body fat) measured over four time points was the dependent variable within the GEE model. Known confounders such as FFM, and potential confounders such as FM, % body fat, height, age, sex, race, and thyroid function were tested for inclusion in the model. Next, we examined whether the TEE adiposity association was moderated by child health status (DS vs. healthy control). We developed a GEE model that included baseline TEE, health status (DS or healthy control), and the interaction between TEE and health status as independent variables with adiposity (% body fat) measured over four time points as the dependent variable. Specific Aim 2a: Determine if the total EI to TEE ratio (EI:TEE) differs in children with DS compared to healthy sibling controls. To assess specific aim 2a, a multiple linear regression model was fit to examine the association between health status (prepubescent children with DS versus healthy sibling controls) and EI:TEE ratios, where health status was the independent variable and EI:TEE was the dependent variable. Known confounders such as FFM, and potential confounders such as FM, % body fat, height, age, sex, race, and thyroid function were tested for inclusion in the model. All covariates had to satisfy three general criteria in order to be included in the model as a confounder: 1) significantly associated with health status; 2) significantly associated with EI:TEE; and 3) not in in the casual pathway between health status and EI:TEE. 47 21

Specific Aim 2b: Determine if the EI:TEE ratio is associated with changes in adiposity over a three-year period in children and whether this association differs for children with DS versus their healthy sibling controls. To assess specific aim 2b: A GEE was fit to determine the association between EI:TEE (the independent variable) and adiposity, (measured as % body fat) over time (the dependent variable). Adiposity was measured at four time points (baseline, 12, 24, and 36 months post-baseline) for each child, necessitating the use of a longitudinal data analytic strategy such as GEE that takes into consideration repeated measures over time. Baseline EI:TEE was included as the independent variable and adiposity (% body fat) measured over four time points was the dependent variable within the GEE model. Known covariates such as FFM, and potential covariates such as FM, height, age, sex, race, and thyroid function were tested for inclusion within this model. Next, we examined whether the EI:TEE and adiposity association was moderated by child health status (DS vs. healthy control) by developing a GEE model with baseline EI:TEE, health status (DS or healthy control), and the interaction between EI:TEE and health status as independent variables with adiposity (% body fat) measured over four time points as the dependent variable. 22

Chapter 5 RESULTS 5.1 Normality Testing and Distribution of Outcome Variables The outcome variables for these analyses including total energy expenditure (TEE), energy intake (EI), and the EI:TEE ratio were tested for normality using the Shapiro-Wilk test. TEE was normally distributed (p>0.05) and EI and EI:TEE ratio were not normally distributed (p<0.05); as such, nonparametric tests were employed for univariate analyses. 5.2 Demographic and Anthropometric Characteristics for All Enrolled Children (n=72) Subject demographic and anthropometric characteristics for all enrolled children at baseline are summarized in Table 1a. Seventy-two prepubescent children (n=36 Down syndrome (DS) and n=36 controls) participated in the study. Thirty-six children were males (n=18 DS and n=18 controls). Sixty-four children (88.9%) identified as Caucasian, (n=32 DS and n=32 controls), six children (8.3%) were African American/Black (n=3 DS and n=3 controls), and two children (2.8%) were Asian (n=1 DS and n=1 controls). Eight children (11.1%) identified as Hispanic (n=4 DS and n=4 controls). Mean age (years) for all children was 6.9 ± 0.2 standard error of the mean (SEM). Between groups, there were significant differences (p<0.005) in height (109.2 ± 1.7 cm DS and 123.1 ± 2.5 cm controls), height z-scores (-1.71 ± 0.1 DS and 0.15 ± 23

0.1 controls), body mass index (BMI) (18.4 ± 0.5 kg/m 2 DS and 16.5 ± 0.4 kg/m 2 controls), BMI z-scores (1.12 ± 0.1 DS and 0.08 ± 0.1 controls), fat free mass (FFM) (17.1 ± 0.7 kg DS and 20.5 ± 0.9 kg controls), resting energy expenditure (REE) (1067.8 ± 18.7 kcal DS and 1146.1 ± 16.9 kcal controls), and TEE (1466.7 ± 64.9 kcal DS and 1593.0 ± 35.2 kcal controls). 5.3 Demographic and Anthropometric Characteristics for Enrolled Children with Total Energy Expenditure Measure at Baseline (n=61) Subject demographic and anthropometric characteristics for enrolled children with TEE measured at baseline are summarized in Table 1b. Sixty-one prepubescent children (n=29 DS and n=32 controls) had a TEE measure at baseline. Thirty-one children (50.8%) were males (n=15 DS and n=16 controls). Fifty-four children (88.5%) identified as Caucasian, (n=25 DS and n=29 controls), five children (8.2%) were African American/Black (n=3 DS and n=2 controls), and two children (3.3%) were Asian (n=1 DS and n=1 controls). Four children (6.6%) identified as Hispanic (n=2 DS and n=2 controls). Mean age (years) for all children was 6.9 ± 0.2. Between groups, there were significant differences (p<0.005) in height (110.3 ± 1.7 cm DS and 121.3 ± 2.6 cm controls), height z-scores (-1.68 ± 0.1 DS and 0.08 ± 0.13 controls), BMI (18.8 ± 0.6 kg/m 2 DS and 16.5 ± 0.4 kg/m 2 controls), BMI z- scores (1.20 ± 0.1 DS and 0.06 ± 0.1 controls), REE (1066.6 ± 21.2 kcal DS and 1141.8 ± 18.6 kcal controls), and TEE (1466.7 ± 64.9 kcal DS and 1593.0 ± 35.2 kcal controls). There were no significant differences between all enrolled children at baseline (n=72) and enrolled children with a TEE measure at baseline (n=61) for sex (p=0.9439), age (p=0.9562), race (% Caucasian) (p=0.9288), race (% African 24

American/Black) (p=0.9795), ethnicity (% Non-Hispanic) (p=0.2602), height z-score (p=0.9438), weight z-score (p=0.8324), BMI z-score (p=0.9512), fat mass (FM) (p=0.8884), FFM (p=0.9126), thyroxine (p=0.6302), REE (p=0.9586), and EI (p=0.9608). 5.4 Baseline Differences in TEE by Health Status (Down Syndrome vs. Control) We next examined baseline differences in TEE by health status, adjusting for potential covariates. To determine covariates to include in this model, Spearman correlation coefficients were computed to identify variables significantly (p<0.05) associated with TEE. The following variables were significantly (p<0.05) associated with TEE: age, height, fat mass (FM), FFM, % body fat, and thyroxine. The association between these variables and health status was then computed using Spearman correlation coefficients. Age, FM, % body fat, and thyroxine were not statistically significantly (p>0.05) associated with health status. Therefore, those variables that met the definition of a confounder (height and FFM) were included in subsequent regression analyses. Next, a regression model was fit with TEE as the dependent variable that included the potential confounders height and FFM, as well as race, ethnicity, and sex (Table 2a, Model 1). This model yielded an adjusted R 2 =0.63 with p<0.0001. Health status (p=0.0372) and FFM (p=0.0081) were the only statistically significant factors in the model; sex, race, ethnicity, and height were not significant factors (p>0.05) in predicting TEE. Therefore, a second regression model that was more parsimonious was fit with TEE as the dependent variable that included health status and FFM as the two confounders. Health status (p=0.0206) and FFM (p<0.0001) remained significant in this model (Adjusted R 2 =0.63, p<0.0001). This model found that healthy children, 25

after adjustment for FFM, expend significantly more energy (p<0.001), approximately 125 kcal/d more than their siblings with DS (1466.7 ± 38.4 kcal/d DS and 1593.0 ± 35.2 kcal/d controls) (Table 2a, Model 2). 5.5 Baseline TEE Contribution to Changes in Adiposity Over Three Year Period To determine the contribution of baseline TEE to changes in adiposity over a three-year period, a generalized estimating equation (GEE) was fit to determine if baseline TEE predicts change in adiposity in all subjects (Table 2b, Model 1a). This model resulted in a Wald chi square value of χ 2 =7.93 with p=0.0049. The coefficient for TEE was 0.0080244 (p= 0.005), indicating a significant positive association between baseline TEE and change in adiposity over the three-year period in all subjects. We examined the impact of TEE on adiposity after adjustment for FFM. This yielded an adjusted coefficient of TEE that was no longer statistically significant (Table 2b, Model 1b; TEE coefficient = -0.00449, p=0.266). Next, a second GEE model was run to determine if there was an effect of health status on change in adiposity over a three-year period after adjusting for baseline TEE (Table 2b, Model 2a). This model resulted in a Wald chi square value of χ 2 =24.40 with p<0.001. The coefficient for TEE was 0.01187 (p<0.001), and the coefficient for health status was 6.73625 (p<0.001) indicating that both health status and baseline TEE were significantly associated with positive changes in adiposity. With adjustment for FFM (Table 2b, Model 2b), only health status remained significant and having DS resulted in a 6.2% higher adiposity at the three-year time point compared to healthy control siblings. Finally, a third GEE model was run to determine if there was an interaction effect of health status and TEE on changes in 26

adiposity over time; this model included FFM (Table 2b, Model 3). The model resulted in a Wald chi square value of χ 2 =28.13 with p<0.001. The health status and TEE interaction was significant (coefficient = 0.01131, p=0.032) indicating a stronger positive association between baseline TEE and changes in adiposity over time for children with DS. 5.6 Baseline Differences in EI:TEE Ratio by Health Status (Down Syndrome vs. Control) We next examined baseline differences in EI:TEE ratio by health status adjusting for potential covariates. To determine covariates to include in this model, Spearman correlation coefficients were computed to identify variables significantly (p<0.05) associated with the EI:TEE ratio. The following variables were tested: age, height, weight, BMI, FM, FFM, % body fat, and thyroxine. The p-values for all variables were >0.05, indicating none of these variables were significantly associated with EI:TEE ratio. As such, they were not included as covariates (Table 3a, Model 1) Next, a regression model was fit with the log EI:TEE ratio as the dependent variable and health status as the independent variable. Log EI:TEE was used in this model due to the fact that EI:TEE was not normally distributed. Log EI:TEE was normal with a Shapiro-Wilk estimate of 0.97911 (p=0.4511). Potential covariates were evaluated for inclusion in the model including race, ethnicity, and sex. None of these variables were statistically significantly associated with log EI:TEE or health status (Table 3a, Model 2). Therefore a two-sample Wilcoxon rank-sum (Mann-Whitney) test was conducted to determine if EI:TEE ratio differed by health status; this yielded 27

a p-value of p=0.167 and a median EI:TEE ratio of 1.085 and 0.958 for children with DS and healthy control siblings, respectively. This suggests no significant difference in the EI:TEE ratio by health status group. 5.7 Baseline EI:TEE Contribution to Changes in Adiposity Over Three Year Period To determine the contribution of baseline EI:TEE to changes in adiposity over a three-year period, a GEE model was fit to determine if baseline EI:TEE predicts change in adiposity in all subjects (Table 3b, Model 1a). This model resulted in a Wald chi square value of. χ 2 =1.03 with p=0.3106, and an EI:TEE p-value = 0.311, indicating no statistically significant association between baseline EI:TEE and change in adiposity over the three year period in all subjects. With adjustment for FFM (Table 3b, Model 1b), there was still no statistically significant association between EI:TEE ratio change in adiposity. Next, a second GEE model was run to determine if baseline EI:TEE was associated with change in adiposity after adjusting for health status (Table 3b, Model 2a). This model resulted in a Wald chi square value of. χ 2 =4.55 with p=0.1026. The coefficient for EI:TEE was 3.21693 (p=0.398), and the coefficient for health status was 3.83747 (p=0.063), meaning no significant association. With adjustment for FFM (Table 3b, Model 2b) however, health status was significantly associated with changes in adiposity (coefficient = 5.69056, p<0.001). Finally, a third GEE model (Table 3b, Model 3) was run to determine if the relationship between baseline EI:TEE and health status on changes in adiposity over time differed by health status. This model resulted in a Wald chi square value of. χ 2 =50.38 with p<0.001. The coefficient for the health status and EI:TEE interaction term was -3.38740 (p=0.568) 28