MEAL PATTERNS AND PRACTICAL APPLICATIONS FOR

MANAGEMENT

A Thesis

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Matthew F. Good

May, 2008 MEAL PATTERNS AND PRACTICAL APPLICATIONS FOR OBESITY

MANAGEMENT

Matthew F. Good

Thesis

Approved: Accepted:

Advisor School Director Dr. Deborah Marino Dr. Richard Glotzer

Faculty Reader Dean of the College Mrs. Evelyn Taylor Dr. James Lynn

Faculty Reader Dean of the Graduate School Dr. David Witt Dr. George Newkome

Date

ii ACKNOWLEDGEMENTS

I would like to extend my appreciation to the Summa System of Akron,

Ohio, for the gracious permission of use of the data collected through the REACH Trial.

I would also like to extend a special thanks to the faculty of The University of Akron, namely Dr. Deborah Marino, Dr. Isabelle Stombaugh (Retired), Mrs. Evelyn, Taylor, and

Dr. David Witt. Your dedication to student education and mentoring is surpassed by none.

iii TABLE OF CONTENTS

Page

LIST OF TABLES ...…………………………………………………………………….vii

CHAPTER

I. INTRODUCTION ...…………………………………………………………………...1

Background ...……………………………………………………………………..1

Purpose and Objectives ...…………………………………………………………4

Research Problem ...………………………………………………………………5

Significance of Study ...…………………………………………………………...5

Assumptions of the Study ...……………………………………………………....6

Limitations of the Study ...………………………………………………………...6

Definitions ...………………………………………………………………………7

II. REVIEW OF THE LITERATURE ...………………………………………………..10

Introduction ...……………………………………………………………………10

Obesity and Fat Cells ...………………………………………………………….10

Obesity and Genetics ...………………………………………………………….11

Obesity and Environment ...……………………………………………………..14

Previous Research ...……………………………………………………………..15

Past Research Discoveries and the Need for Continual Investigation ...………...19

Research Hypotheses ...………………………………………………………….21

iv III. METHODOLOGY ...……………………………………………………………….22

Methodology of the Original Study ...…………………………………………...22

Subjects ...………………………………………………………………..22

Available Data ...………………………………………………………...23

Anthropometric Measurements ...………………………………………..24

Dietary Patterns and Nutrient Intake …………………………………….24

Physical Activity ...………………………………………………………25

Medical History and Psychosocial Questionnaires ...……………………25

Data Collection Procedures ...……………………………………………25

Dietary Recall Database …...…………………………………………….26

Data Processing ...………………………………………………………..26

Methodology of the Current Study ...……………………………………………27

IV. RESULTS/FINDINGS ……………………………………………………………..29

Primary Variables and Subscore Calculations ...………………………………...29

Regression Analysis ……………………………………………………………..33

V. DISCUSSION OF FINDINGS ……………………………………………………...38

Meal Frequency and Energy Intake ……………………………………………..39

Meal Frequency and BMI Change ………………………………………………41

Time of Consumption …………………………………………………………...43

Extenuating Influential Factors ………………………………………………….44

Summary of Findings ……………………………………………………………45

VI. SUMMARY AND IMPLICATIONS ………………………………………………46

Future Research …………………………………………………………………47

v Practical Implications …………………………………………………………....47

REFERENCES ………………………………………………………………………….49

APPENDICES …………………………………………………………………………..55

APPENDIX A. SUBJECTS APPROVAL …………………………..56

APPENDIX B. PRIMARY DATA ……………………………………………..57

vi LIST OF TABLES

Table Page

1. Variable Legend ……………………………………………………………………..32

2. Summary of Pertinent Variables ………………………………………………….....33

3. Regression Analysis – Association of Meal Frequency and Kcal Consumed per Meal …………………………………………………………………………………34

4. Regression Analysis – Association of Meal Frequency and Weight Change and Change ...…………………………………………………………34

5. Regression Analysis – Association of Percentage of Kcal Eaten at Night with Total Kcal Consumed per Day …...……………………………………………….....36

6. Regression Analysis – Association of Percentage of Kcal Eaten at Night with Weight Change and Body Mass Change …...…………………………………….....36

vii CHAPTER I

INTRODUCTION

Background

The prevalence of obesity in the has increased dramatically over the past decade, and while reducing obesity to less than 15% of the population is a national health objective for 2010, research indicates the opposite is occurring. According to the

Center for Disease Control (CDC) Behavior Risk Factor Surveillance System (BRFSS), in 1991, an estimated 12% of the United States population was obese. By the year 2000, the prevalence of obesity had risen to 19.8% of the population, a 61% increase in nine years. By 2000, an estimated 38.8 million people were obese, and increases in the prevalence of obesity were occurring in almost every subgroup of the United States population. According to NHANES 2003-2004, currently 66.2% of U.S. adults, age 20 to 74 years are categorized as (BMI >25). Of the same age group, 32.9% are categorized as obese (BMI >30). With the prevalence of obesity rising to epidemic proportions, the causes of this problem, its health costs, and ways to prevent or treat it need to be addressed (1).

Obese individuals have an elevated risk for physical ailments, as reported by

Stunkard et al. and the National Institute of Health (2). These risks include , dyslipidemia, Type II mellitus, glucose intolerance or insulin resistance, and

1 hyperinsulinemia. Other health risks include coronary heart disease, angina pectoris, congestive and stroke. , cholescystitis and cholelithiasis, and gout are potential health risks. Other possible ailments accompanying obesity are obstructive and respiratory problems, some types of cancers (endometrial, , prostate, and colon), poor female reproductive health (menstrual irregularities, infertility, irregular ovulation), bladder control problems (stress incontinence), , gastroesophageal reflux disease (GERD), and uric acid nephrolithiasis. In addition to these physical hazards, obesity can also be accompanied by psychological disorders such as depression, eating disorders, distorted body image, and low self esteem (2).

In addition to the physical ailments associated with obesity, this health problem is a great cause for financial concern in this country. According to Yee et al. (3), the related medical expenses accounted for 9.1% of the total U.S. medical expenditures in 2004, as well as total state expenditures on obesity-related medical expenditures were approximately $75 billion, excluding costs related to absenteeim and loss of productivity.

Obesity is a chronic condition that seems to have multiple etiologies. Researchers have found that obesity is a condition caused by a combination of behavioral, environmental, and genetic factors (4).

Behavior affects the prevalence of obesity in the most obvious of ways. Energy imbalance occurs when more energy is consumed than is being used. This imbalance can be the result of eating too much, not exercising enough, or a combination of both. Over time, this excess energy can result in and, eventually, obesity.

A more covert, yet equally important obesogenic factor is one’s environment.

While the human gene pool has been and is geared towards a hunter-gatherer lifestyle,

2 technologically advanced societies are experiencing increases of obesity in their populations. Historically speaking, an active lifestyle was required for the acquisition of a person’s food source, whether it be hunting livestock or harvesting crops, which made for an equal balance of energy consumption and expenditure. In today’s , readily available elevators, escalators, transportation, garage door openers, television remote controls, automobiles, passive entertainment, and uncountable other devices geared towards a decrease in physical activity, have contributed to societies with populations that are in positive energy balance. Other factors such as workplaces with on-site cafeterias and/or vending machines may make for a convenient, yet unhealthy, environment for food choices (5). Socioeconomic factors, such as one’s ethnicity, occupational prestige, education level attained, and income, can also contribute to obesity.

Researchers have shown that genetics can play a role in obesity. Heredity affects a person’s susceptibility to obesity. Genes can influence the body’s efficiency to burn and store energy. Conditions such as Bardet-Biedl syndrome and Prader-Willi syndrome can directly cause obesity.

With the prevalence of obesity rising in the United States, and numerous factors causing this increase, it is imperative that the scientific research community find practical methods of obesity treatment and prevention. Unfortunately, there are numerous advocates of “fad diets” that are disseminated via the media that prey on uneducated consumers. The vast majority of these weight reduction schemes has proven to have little or no effectiveness and can actually cause more harm than good.

3 Lifestyle habits, including those that contribute to obesity, are among the most difficult to change. Since technologically advanced societies will not return to a hunter- gatherer lifestyle, societal behavior change related to obesity must be addressed promptly, delicately, and above all, practically (4).

Purpose and Objectives

While much attention has been given to media-driven and ill-advised severe decreases in food consumption to help reverse obesity, significantly less attention has been paid to less drastic changes in eating patterns that might lead to . Such changes would include the timing of an eating episode and number of eating episodes per day. Wahlqvist et al. (6) examined the number of meals and the times meals were eaten, among other variables. Consumption of the majority of a day’s nutrient intake early in the day was correlated with a lower body mass index and body fat in this study, as were more frequent eating episodes throughout the day. The results of their study suggest that simple lifestyle changes may give positive weight loss results to obese individuals.

The purpose of this study was to investigate the effect of the frequency and timing of eating episodes on body weight. This study involved the secondary analysis of data that were originally collected through the Reasonable Eating and Activity to Change

Health (REACH) trial sponsored by Summa Health System of Akron, Ohio, the Agency for Health Care Research and Quality (AHRQ), and the National Institute of Diabetes and

Digestive and Kidney Disorders (NIDDK). The primary intention of the REACH trial was to analyze the longitudinal nutritional, physical activity, and weight data from obese primary care patients to see what factors were associated with weight loss. The REACH study was done in an attempt to increase the scientific understanding of effective obesity

4 management and prevention. This researcher took one aspect of the REACH trial’s data, meal patterns, and completed detailed analysis of the relationship between meal timing and frequency and obesity management.

Research Problem

Based on limited past investigation, this researcher hypothesized that meal patterns and timing of dietary intakes might be significant factors in managing obesity.

More specifically, it was hypothesized that an increase in the number of eating episodes per day might be positively associated with a reduction in overall Kcal intake, lowered body mass index, and lowered body weight. Also, that a shift of eating pattern from consumption of more Kcal later in the day to earlier in the day might lead to a reduction in overall Kcal intake, lowered body mass index, and lowered body weight.

Significance of Study

Scientific investigation in the area of obesity management and prevention is sorely needed to help reverse the near epidemic growth of obesity in the United States. A thorough review of the literature related to obesity reveals a lack of long-term longitudinal studies that investigate effective obesity management techniques. Moreover, there are very few studies on the effect of meal patterns on obesity. Therefore, the current analysis of meal patterns and obesity, with an incorporated statistical adjustment for changes in physical activity, may suggest a simple intervention in the treatment of obesity that could be adopted easily in weight reduction programs (7).

Primary care physicians and registered dietitians see an increasing number of patients with unhealthy eating habits who have little hope of reducing their weight if drastic lifestyle changes are required. This research will help to determine if a strategy as

5 simple as altering the time and frequency of eating episodes can positively impact weight loss.

Assumptions of the Study

The assumptions made in this study are as follows:

1. All height measurements in the REACH trial were performed using standard

procedures and calibrated tools.

2. All weight measurements in the REACH trial were performed using standard

procedures and calibrated tools.

3. All body mass index values for subjects in the REACH trial were calculated using

the standard formula.

4. The subjects in the REACH trial answered all 24-hour dietary recalls accurately

and truthfully.

5. The subjects in the REACH trial answered all 7-day Stanford Physical Activity

Recalls accurately and truthfully.

6. All coding and data entry from the REACH trial were performed accurately.

7. A decrease in body mass index value is positively associated with a reduction in

body fat.

Limitations of the Study

The limitations of this researcher’s study are as follows:

1. All data collection for the REACH trial was done prior to the involvement of this

researcher; therefore, this researcher does not have first hand knowledge about the

decisions made by REACH personnel related to the coding of dietary recalls.

6 2. Any coding errors made in the original REACH study cannot be detected by this

researcher and have become part of the current study.

Definitions

Angina Pectoris - severe paroxysmal pain in the chest associated with an insufficient supply of blood to the heart.

Bardet-Biedl Syndrome - an autosomal recessive disorder characterized by retinitis pigmentosa, polydactyly, obesity, mental retardation, hypogenitalism, renal dysplasia, and short stature.

Body Mass Index (BMI) - a measurement of the relative percentages of fat and muscle mass in the human body. BMI is calculated by taking weight in pounds and dividing it by height in inches squared. The product is then multiplied by 705 to determine BMI.

CDC Behavioral Risk Factor Surveillance System - the world’s largest telephone survey that tracks health risks in the United States. Information from the survey is used to improve the health of the American people.

Cholelithiasis - the presence or formation of gallstones in the gallbladder or bile ducts.

Cholecystitis - an inflammation of the gallbladder, caused by gallstones that are formed by cholesterol and bilirubin in bile.

Dyslipidemia - a disorder of lipoprotein metabolism, including lipoprotein overproduction or deficiency.

Eating episode - any conscious ad libitum ingestion of food.

Gastroesophageal reflux disease (GERD) - a chronic condition in which the lower esophageal sphincter allows gastric acids to reflux into the esophagus causing heartburn, acid indigestion, and possible injury to the esophageal lining.

7 Gout - a disturbance of uric-acid metabolism occurring chiefly in males, characterized by painful inflammation of the joints, especially of the feet and hands, and arthritic attacks resulting from elevated levels of uric acid in the blood and the deposition of urate crystals around the joints.

Hyperphagia - abnormally increased appetite for and consumption of food, thought to be associated with a lesion or injury in the hypothalamus.

Nephrolithiasis - a condition in which one or more stones are present in the pelvis or calyces of the kidney or in the ureter.

Obesogenic - a trait of being obesity causing.

Obstructive Sleep Apnea - a temporary suspension of breathing occurring repeatedly during sleep that often affects overweight people or those having an obstruction in the breathing tract, an abnormally small throat opening, or a neurological disorder.

Osteoarthritis - a form of arthritis, occurring mainly in older persons, that is characterized by chronic degeneration of the cartilage of the joints.

Prader-Willi Syndrome - a genetic disorder characterized by short stature, mental retardation, abnormally small hands and feet, hypogonadism, and uncontrolled appetite leading to obesity.

Prochaska’s Transtheoretical Model - the six stages of change individuals progress and regress through while attempting behavioral change; precontemplation, contemplation, preparation, action, maintenance, and termination.

Reasonable Eating and Activity to Change Health (REACH) Trial - a two-year study sponsored by Summa Health System and the U.S. Public Health Service with the purpose

8 of finding practical ways for physicians and dietitians to improve the health of obese individuals via changes in eating and habits.

9 CHAPTER II

REVIEW OF THE LITERATURE

Introduction

While attaining and maintaining a slim body has been, and remains, a preoccupation in the United States, obesity rates continue to climb (8). As stated previously, in 1991, an estimated 12% of the United States population was obese. By the year 2000, the prevalence of obesity had risen to 19.8% of the population, a 61% increase in nine years. By 2000, an estimated 38.8 million people were obese, and increases in the prevalence of obesity were occurring in almost every subgroup of the United States population. According to NHANES 2003-2004, currently 66.2% of U.S. adults, age 20 to 74 years are categorized as overweight (BMI >25 and <30). Of the same age group,

32.9% are categorized as obese (BMI >30) (1,3). Obesity is so widespread and has such an alarming increase in prevalence that it is now being considered an epidemic.

Obesity and Fat Cells

Obesity occurs when there is a shift in energy balance with more energy being consumed than is being spent. This excess energy is stored in as fat. As fat is added to fat cells, they increase in size. Eventually, when existing fat cells have reached maximum capacity, more fat cells are produced to hold more fat. Thus, the total number of fat cells in the body increases. With weight loss, the existing fat cells can

10 shrink; however, once a fat cell is created, it is not destroyed. This means that obese individuals, even those who lose all excess weight, will have more fat cells than individuals who have never been overweight or obese. Researchers have shown that with an increased number of fat cells, the regaining of fat is easier (9).

Lipoprotein lipase (LPL) is the enzyme that promotes fat storage in adipose and muscle tissue. LPL is attached to fat cell membranes; therefore, the more fat cells an individual has, the higher their LPL activity is overall. This greater amount of LPL activity makes for easier fat deposition within obese people, even with a minimal intake of excess calories (10). Researchers have shown that LPL activity is highest among those individuals who have or had the most fat at one point in their lives. The loss of this fat, caused by factors such as changes and/or exercise, triggers a signal to the genes that produce LPL to produce more as an internal defense mechanism. The resulting increases in LPL make it much harder for current or former obese individuals to lose fat as opposed to individuals who have less LPL (9).

Obesity and Genetics

Genetics seems to play an important role in obesity. Studies indicate that adopted children have body types more similar to their biological parents than their adoptive parents (11).

Although genes may not be the sole cause of obesity, genetic factors may predispose an individual to obesogenic tendencies. Researchers have identified the ob gene, an obesity gene which codes the protein leptin. Leptin acts in the hypothalamus as a hormone to suppress energy consumption and to increase energy expenditure, promoting negative energy balance. Leptin’s suppression of energy consumption is a

11 result of its effect on appetite control in the hypothalamus. Leptin’s ability to increase energy expenditure is the result of its ability to increase the basal metabolic rate. In rare situations, have been found to have a genetic deficiency of leptin (12). This deficiency would cause uncontrollable eating and a lowered basal metabolic rate, and would result in obesity.

There are numerous other genes that code for proteins that may cause obesity.

These proteins might affect the efficiency of the expenditure or storage of energy in the body or the production of different types of fat. Human beings have two types of fat, white and brown adipose tissue. White adipose tissue stores fat for energy use by other cells. Brown adipose tissue releases energy stores as heat via pigmented mitochondria.

These mitochondria produce heat instead of adenosine triphosphate (ATP). This process is called uncoupling. During the oxidation of fat, some of the resultant energy is released as heat and some is captured in ATP. The heat produced in brown fat enables the body to spend versus save energy, and is an important mechanism in newborns, adults living in extremely cold climates, and animals that hibernate. This reaction and the role of brown adipose tissue is just beginning to be understood.

While investigating the protein that codes for the uncoupling reaction in brown adipose tissue, researchers found a protein that codes for an uncoupling reaction in brown adipose tissue as well as in white adipose tissue and many other tissues. This second protein exerts its effect by increasing basal metabolic rate, which helps to prevent weight gain (13). Children with a genetic deficiency of this uncoupling protein seem to be more obese than those without a deficiency. Whether excess calories are dissipated as heat or is stored as body fat is a major factor in the etiology of obesity.

12 While not completely synonymous with genetics, a relationship between obesity and age does exist. The population of people in the United States living past the age of

65 is growing, as is the percentage of this population who is considered overweight.

Well over half of all adult Americans are overweight, and one in every three is obese

(14). Leading a is thought to be the primary factor contributing to obesity across age groups. Many older individuals view a more sedentary lifestyle and the consequent weight gain as an inevitable part of the aging process. Other factors that contribute even more to overweight with aging are an alteration in metabolic rate and an increase in the efficiency of fat storage (15). The increase in body mass and associated with middle-age occurs in men after 40 and in women after menopause. Since the aging process is associated with a decline in food intake, age related changes in activity levels, BMR and fat storage play a significant role in weight gain in older individuals.

Even a modest weight gain of 10 pounds in middle-age is associated with health problems such as hypertension, diabetes mellitus, , and osteoarthritis (16). Thus the growing number of older Americans is a major contributor to the rapidly increasing cost of health care resources. It is projected that the cost of health care for treating middle-aged, overweight American women over the next 25 years is $16 billion (17). The cost of directly treating , coronary heart disease, hypertension, and gallstones in the general population of obese people was estimated at

$22.62 billion, compared to $5.89 billion for those not classified as obese (18). Not withstanding the reduction of health costs, an increase in understanding of aging and

13 weight loss needs to be achieved to promote improved health, function and quality of life for the growing number of elderly adults in the United States.

Obesity and Environment

Genetics cannot be considered the sole cause of obesity. The environment also plays a role in this epidemic. The United States has been labeled as a toxic food environment. This environment is characterized by high-energy, high-fat, readily available foods, compounded by an “everything made easy society” (19). At the time that caloric intakes have increased, individuals in the U.S. need to expend significantly fewer calories in physical activity than our ancestors. Scientific and technological advances have decreased energy expenditures but Americans are not reducing their dietary intakes to match their reduced caloric needs.

Another factor involved in the association of obesity and the environment is socioeconomic status (SES). The idea of SES can be defined as a complex, multidimensional paradigm, based on one’s ethnicity, occupational prestige, education level attained, and income. While SES has previously been considered one variable with numerous factors, it is now being recognized as a paradigm with separate and numerous components to be researched as such. Few researchers have investigated the relationship between obesity and these components (20). The empirical studies that have been done in this area have found one commonality. Socioeconomic status is inversely associated with BMI and obesity in females. The relationship between SES and obesity for male subjects is less conclusive (20-25).

14 Previous Research

There is limited previous research that has investigated eating patterns and their effects on obesity. Researchers have noted that daily energy consumption is more easily regulated in habitual eaters than in those individuals who consume less frequent, larger meals (26). Clifton (27) has also documented that decreases in energy intake depend on reductions in meal size and feeding rate while keeping meal frequency constant. This may represent an enhancement of endogenous satiety mechanisms, or those “feeling of fullness” mechanisms originating within an individual. While limited, and regardless of cause, data from past research suggests that improvements in appetite control appear when energy consumption is spread evenly throughout the day.

Fabry and associates (28) discovered that lessened meal frequency resulted in weight gain in Prague schoolchildren. Over a one-year period, 226 children from different Prague schools were assigned a different number of eating episode frequencies.

They were instructed to eat three, five, or seven times per day and total caloric intake was not controlled. Those students who ate three meals per day had the greatest increase in body weight and skinfold thickness.

Another study, using 440 male subjects, ages 60 to 64, from urban Prague, had similar findings to the study involving the children. After the males’ eating patterns were determined via an interview, the researchers found that the proportion of overweight individuals in this population tended to decrease as meal frequency increased from three to five or more meals per day. Consequently, the proportion of normal weight in this group also increased with increased meal frequency (29).

15 Further research, conducted by Metzner et al. (30), investigated whether or not increasing eating episodes per day would affect adiposity index (AI) if total energy consumption remained the same. The researchers found that in both male and female subjects, AI decreased as the number of meals per day increased from two to six.

In addition to number of eating episodes per day, some attention has been paid to the time of day that the energy was consumed. Societal trends in Western cultures reveal a shift from consumption of three meals per day to continuous and nocturnal eating.

Factors that may be promoting this behavior are multiple careers in single households; the emergence of convenience and fast-foods; prepared foods available in grocery stores nearly all of which are 24 hour/7 day per week establishments; television and other media entertainment that encourage sedentary behavior; home food delivery; and the availability of microwavable convenience foods (31-35). Wahlqvist et al. (6) tested the research hypothesis that meal frequency, time, size, and composition are associated with weight control. Meal frequency, consumption of the main meal at midday, and earlier breakfast times were all negatively associated with body fatness. Later dinner times were positively associated with higher fasting blood sugar and obesity.

Research by Birketvedt et al. (36) has investigated neuroendocrine and behavioral patterns of night eating syndrome (NES). NES was first described in 1955 as a complex of symptoms such as morning anorexia, evening hyperphagia, and insomnia. Those suffering from NES have more awakenings per night with more than half of these awakenings being accompanied with food consumption. People with NES consume more than 50% of their caloric intake at night while those without the syndrome consume about

15%.

16 While the studies previously discussed suggest a positive correlation between increased meal frequency, earlier hour energy consumption and lowered risk of obesity, several studies show little or no such correlation. A study performed by Roos et al. (37) showed that energy consumption from less than five eating times per day versus more than five eating times per day had only a small effect on dietary intake and, therefore, weight gain. Basdevant and associates (38) have shown that increased snacking throughout the day is cause for a positive energy balance leading to further obesity.

Another study of college-aged obese men found that those eating one meal per day consisting of 1800 kcal had the same weight loss as those eating 1800 kcal per day separated as three or six meals per day (39-40). In a study by Edelstein et al. (41), when groups of similar demographics were separated into groups characterized by number of meals eaten per day (1-2, 3, and >4), there was no significant difference in body mass index.

Therefore, while the results of several studies indicate that meal frequency and hour at which the main meal is consumed are noteworthy factors in daily energy consumption, weight gain, and maintenance, other studies show little correlation between these factors. A clearer understanding of any relationship between these factors requires further research.

Researchers have found higher rates of obesity among individuals of lower SES

(42,43). A study by Ball et al. (20) investigated the association among body fat and distribution, and four empirically derived domains of SES. These were employment, housing, migration status, and family unit. Four thousand one hundred and sixty-seven men and 4500 women who were participants in the 1995 Australian National Health and

17 Nutrition Surveys were assessed on numerous health factors including height, weight, and body fat distribution, as well as a number of sociodemographic factors. Researchers found that women of low status employment were 1.4 times as likely to be overweight as women of high status employment. Less consistent relationships were observed among the male population. Little consistency was found when comparing family unit, migration, and housing to body weight and body fat.

Another study by Wardle et al. (21) had similar results. Data from the 1996

Health Survey for England were analyzed to compare the ways in which education, occupational status, and economic status were associated with obesity. Both males and females with lower attained educational levels were more likely to be obese than those with higher levels with a graded effect across years of education. A negative association between occupational status and obesity was found in female participants; however, no such linear relationship was found in the male participants. There were no direct measures of income, so it was difficult to precisely assume its effect on obesity. While ethnic differences were not a primary focus of this research, a sample of Black women proportionate to their presence in the British population did show high obesity rates. This risk was independent of other SES factors but was not significant for Black men.

One commonality of research in the area of SES and obesity is the negative relationship between facets of SES and obesity. A study by Wamala et al. (22) attempted to distinguish the factors accounting for this association. Overweight and obesity were examined in relation to socioeconomic status among 300 healthy women who previously comprised the control group of the Stockholm Female Coronary Risk Study in .

Education and occupation were utilized as measures of SES. Low SES seemed to be a

18 strong predictor of overweight and obesity among middle-aged healthy Swedish women.

The odds of being overweight or obese increased with lowered social status 2.2 and 2.7 times respectively. Both low social position and obesity were related to reproductive history (higher parity and earlier age at menarche), unhealthy dietary habits, and unfavorable psychosocial factors, such as low self-esteem and job strain.

Past research regarding the association of aging with obesity is limited. A study was conducted by Rothaker et al. (44), who attempted to estimate the prevalence of overweight and obesity and weight changes over a five-year period in a rural adult population categorized by age group. Age, body weight, and height were collected from a convenience sample of Caucasian men and women, ages 20-74. Age groups were defined in 10-year increments by the subjects’ ages in 1992. In 1992, men and women had average body weights of 88.4 and 72.4 kg, respectively. Five years later, average body weights were 96.4 for men and 79.3 kg for women. The greatest increase in body weight (11.0-12.1 kg) over the five-year period occurred in the 20-30 year age group.

The second largest increase in body weight occurred in the 30-40 year old age group.

Over the five-year study period, 229 of the 393 normal-weight subjects moved into the overweight or obese categories. The already overweight and obese majority continued to gain weight. Only 20 of the 572 overweight or obese moved from an unhealthy to a healthy body weight during the five-year trial.

Past Research Discoveries and the Need for Continual Investigation

While past research has contributed to the knowledge base regarding possible causes of obesity, such as excess caloric intake and physical inactivity, less attention has been paid to meal timing and, especially, time of day of consumption. It is unclear why

19 certain dietary patterns appear to associate positively with excess caloric intake and others negatively (45-47). The further use of longitudinal studies could help uncover new insights in this understudied area of dietary patterns, energy intake, and weight change.

These longitudinal studies may be able to establish strong associations between changes in the frequency and/or time of eating and subsequent weight loss.

Investigating whether the frequency and timing of eating episodes is associated with consuming excess calories, and therefore leads to obesity, would give insight into lifestyle changes that might help the obese to lose weight (48). Some researchers have suggested that infrequent meals and late night eating may contribute to increased energy intake or weight gain (49). Although several studies have investigated the effects of both meal time and frequency together, it may be possible to isolate these factors in a study of sufficient sample size that includes detailed dietary and activity records.

The effects of dietary patterns on body weight are mediated by altering energy consumption both consciously and subconsciously (50). Consciously, these dietary patterns are mediated in such ways as deliberately increasing the number of eating episodes or altering the time of day that most eating occurs. It is also possible to alter energy consumption by subconsciously increasing the number of meals per day, which could affect feelings of satiety and ultimately could affect overall caloric consumption.

Conscious and subconscious changes made in dietary patterns could also be affected by environmental, socioeconomic, and psychological factors. Additional research may help to identify specific eating patterns that are both culturally acceptable and desirable from a health perspective. Such changes could be incorporated into clinical interventions to prevent or reverse obesity.

20 While age and SES and their relationships with obesity are not the primary intent of the current research, since information is available on these variables in the current study, they can be controlled for when the effects of meal timing and frequency on obesity are tested.

In the past, obesity research has had limited applicability due to small sample sizes and short study durations. The current study had a large sample size and included baseline data as well as follow-up data every six months for two years. With a larger sample size and longer timeframe for the current study, the associations between eating frequency and/or timing and possible weight loss could become apparent if such associations did exist.

Research Hypotheses

Using data acquired through the two-year REACH trial, this researcher investigated whether meal patterns might be significant factors in managing obesity. The hypotheses that were tested in the current study were as follows:

Hypothesis 1. The number of eating episodes per day is negatively associated

with overall Kcal intake per meal, and positively associated with body mass index

(BMI) change and body weight change. A series of regression analyses were

conducted, after controlling for average activity per day in the REACH

population.

Hypothesis 2. A greater percentage of total Kcal eaten earlier in the day is

positively associated with a lower total daily Kcal intake, greater body mass index

loss, and greater body weight loss, after adjustment for differences in physical

activity in the REACH population.

21 CHAPTER III

METHODOLOGY

Methodology of the Original Study

The purpose of this study was to complete a secondary analysis of data that were originally collected through the Reasonable Eating and Activity to Change Health

(REACH) trial sponsored by Summa Health System of Akron, Ohio, NHRQ, and

NIDDK. The primary intention of the REACH trial was to analyze the longitudinal nutritional, physical activity, and weight data from obese primary care patients to see which were associated with weight loss. The premise of the experimental intentions was that individuals will change their behaviors by moving, progressing, and regressing through distinct stages that require different cognitive-behavioral changes. Also that most obesity cannot be cured, only managed over a lifetime, in an obesogenic environment. This study was done in an attempt to increase the scientific understanding of effective obesity management and prevention.

Subjects

Six hundred and sixty-five overweight or obese patients were recruited from 15 primary care practices in the Akron, Ohio area. The subjects were recruited via letters of invitation from the practice, recruited via waiting room brochures and posters, or personally referred by their physicians. Following acquisition of informed consent,

22 baseline data were collected and patients were randomized into either usual care or to an experimental intervention derived from Prochaska’s Transtheoretical Model and a chronic disease paradigm (51).

Subjects were required to be 40 to 69 years of age at the time of the study’s onset.

Subjects were also required to have an elevated body mass index (> 27 kg/m 2) or have an elevated waist to hip ratio (> 0.80 for women and > 0.95 for men). Other criteria for selection included the subjects’ ability to engage in light or moderate physical activity and willingness to be randomized into treatment groups. Individuals with higher risk of heart or lung disease were excluded from the study. African-American patients were over-sampled compared to that of the general population of Summit County, Ohio (29% of the REACH trial population compared to 12% of Summit County), because of the increased prevalence of obesity among this group. In accordance with approval by the

Summa IRB and in compliance with all federal regulations, informed consent for participation was obtained. Training on ethical conduct of research and the protection of human research subjects was received by all personnel. All data were handled in a confidential manner. Confidentiality was obtained via password protected computer workstations, a password protected database, absence of participant identifiers, locked offices and file cabinets, and internal institutional security arrangements, such as identification badges worn on premises, daily anti-virus protection on workstations, and armed uniformed, security personnel.

Available Data

Baseline measurements were taken and were followed by measurements in six- month intervals for 24 months. These assessments included standardized anthropometric

23 measurements, as well as medical, psychosocial and physical activity questionnaires.

Blood pressure measurements, three 24-hour dietary recalls, and fasting venous blood samples for lipid profiles were also obtained for each subject. Primary care physicians provided medical records which were reviewed for obesity related diagnoses, treatments, or referrals, and also for missing lipid or weight values. Measured heights and weights in the medical records at follow-up assessments had a Pearson correlation of 0.95 or larger.

Anthropometric Measurements

Anthropometric measurements included height, weight, and waist and hip girth.

Height was measured after removal of shoes via portable stadiometer and rounded up to the nearest inch. Weight was measured after shoes and heavy clothing were removed via calibrated electronic scale and rounded to the nearest 0.10 kg. Waist and hip girths were measured to the nearest cm with the umbilicus as the landmark for waist measurements.

Dietary Patterns and Nutrient Intake

Three 24-hour dietary recalls were obtained at each six-month follow-up assessment. Following the baseline face-to-face interview, a second and third telephone- administered 24-hour dietary recall was conducted and then coded with Nutrition Data

System for Research (NDS-R) software. These recalls were designed to include a weekday and a weekend day since most people tend to alter their eating patterns on the weekends. For the dietary recall purposes of the REACH trial, the interview process was standardized by utilizing NDS-R certified interviewers, and training patients to use a

Food Portion Visual Poster to estimate food portions and to code them.

24 Physical Activity

The Stanford 7-Day Physical Activity Recall was employed to approximate total energy spent (kcal/kg/day) in occupational, recreational, and metabolic activities via metabolic equivalent (MET) coding. At each six-month follow-up assessment, the

REACH trial participants were questioned about how many hours each weekday and weekend day that they spent sleeping (1.0 MET) or participating in moderate (4.0 METs), hard (6.0 METs), or very hard (10.0 METs) activities. Participants assessed the degree of activity via comparison to examples of occupational and recreational activities in each of the three non-sleep MET categories in an attempt to standardize the reporting. Research assistants then checked for accuracy of activity to MET coding.

Medical History and Psychosocial Questionnaires

The medical history questionnaire included information regarding the participants’ socio-demographic characteristics, medical history, smoking, use, and weight-loss related history. The SF-12 questionnaire was used to assess general health status. A separate questionnaire was used to attain psychosocial information which included questions concerning self-efficacy and social support for healthy eating and exercise; decisional balance for exercise and healthy eating; and Stage of Change for smaller portions, less dietary fat, more fruits and vegetables, increased usual physical activity, and increased planned exercise.

Data Collection Procedures

Approval for the original REACH trial was obtained from the Institutional

Review Board (IRB) of the sponsoring institution, Summa Health System of Akron,

Ohio. Originally, baseline measurements were taken to determine the patient’s eligibility

25 for participation in the study. If said patient met criteria for BMI and/or waist to hip ratio and gave willing informed consent, the participant was asked to complete questionnaires, complete a face-to-face interview with the dietitian, and an appointment was scheduled for a fasting lipid profile. Two telephone dietary recalls were scheduled during the following two weeks. At each of the four, six-month follow-up assessments, measurements were obtained at primary care sites and via telephone interviews.

Dietary Recall Database

The NDS-R software, developed by the University of Minnesota, creates a database of information separating it into food files, meal files, and daily intake files which can then be imported into SAS statistical software for further analysis. Meal files can also be used to label the time of the meal and composition of the meal within each recall day. Daily intake files can also be used to determine an estimated daily intake of macro- and micronutrients.

Data Processing

Most data acquired via questionnaire were scanned, verified, and edited using

Teleform software. Data were then exported to Microsoft Access and then exported to

SAS software for an initial analysis of data. Some of this data were directly incorporated into Microsoft Access and consistency checks were performed on all data obtained through the REACH trial before releasing it for initial analysis. Data were then checked again during the descriptive analysis stage where any remaining problematic data were checked against original documents.

26 Methodology of the Current Study

Data used in this study were limited to only the data collected in the original

REACH trial. Since the current study did not allow for additional data collection, the data set and hypothesis testing on that set could have possibly been affected by missing information and/or inaccurate data from the initial REACH trial.

Upon receiving approval for using the existing REACH trial data set from Summa

Health System of Akron, Ohio, this researcher obtained said data set. This data set was coded so that this researcher did not have access to information that could be used to identify the participants. The data set from the original REACH trial was examined and shortened so that only those participants who completed the entire 24-month trial are incorporated. It was also manipulated so to contain only the primary variables analyzed in the current study. These variables are as follows:

• Weight Change; Baseline to Month 24

• BMI Change; Baseline to Month 24

• Average Meals per Day; total number of meals (eating episodes) a specific

participant logged divided by the total number of dates that participant logged

• Average Kcal per Day; total Kcal consumed throughout trial for a specific

participant divided by the total number of dates that participant logged

• Average Kcal per Meal; total Kcal consumed throughout trial for a specific

participant divided by the total number of meals (eating episodes) that

participant logged

• Percentage of Night Kcal; percentage of total Kcal consumed after seven

o’clock pm 27 • Average Activity per Day (min); total minutes a specific participant logged,

engaged in physical activity

This data was input into a Microsoft Excel spreadsheet. From spreadsheet form, the data was transferred to Statistical Package for the Sciences (SPSS) software. Descriptive statistics were then used on the population variables. Following this, a regression analysis was used to test the current study’s hypotheses.

28 CHAPTER IV

RESULTS/FINDINGS

The purpose of this current study was to investigate the effect of the frequency and timing of eating episodes on body weight. This study involved the secondary analysis of data that were originally collected through the Reasonable Eating and Activity to Change Health (REACH) trial sponsored by Summa Health System of Akron, Ohio, the Agency for Health Care Research and Quality (AHRQ), and the National Institute of

Diabetes and Digestive and Kidney Disorders (NIDDK). The primary intention of the

REACH trial was to analyze the longitudinal nutritional, physical activity, and weight data from obese primary care patients to see what factors were associated with weight loss. The REACH study was done in an attempt to increase the scientific understanding of effective obesity management and prevention. This researcher took one aspect of the

REACH trial’s data, meal patterns, and completed detailed analysis of the relationship between meal timing and frequency and obesity management. The results of this study are presented numerically and descriptively according to the type of data collected.

Primary Variables and Subscore Calculations

Survey data were collected between July 22, 1998, and November 7, 2002. Six hundred and sixty-five participants originally enrolled in the program. This researcher worked with data of participants who completed the baseline evaluation and continued to

29 participate through all four follow-up evaluations at six, 12, 18, and 24 months from baseline. A total of 303 participants, 99 males and 204 females, met these criteria.

The primary variables utilized in analyzing these data were as follows:

• Weight Change; Baseline to Month 24

• BMI Change; Baseline to Month 24

• Average Meals per Day; total number of meals (eating episodes) a specific

participant logged divided by the total number of dates that participant logged

• Average Kcal per Day; total Kcal consumed throughout trial for a specific

participant divided by the total number of dates that participant logged

• Average Kcal per Meal; total Kcal consumed throughout trial for a specific

participant divided by the total number of meals (eating episodes) that

participant logged

• Percentage of Night Kcal; percentage of total Kcal consumed after seven

o’clock pm

• Average Activity per Day (min); total minutes a specific participant logged,

engaged in physical activity

Subscore calculations were completed from existing variables for purposes of necessity and ease of analysis. This has been addressed in Chapter III. It is important for the reader to truly understand the actual meaning of each variable. Misinterpretation runs the risk of inaccurate conclusions from results. A variable that may run such a risk might be

Total Meals, and subsequently, all other variables derived from subscore calculation including this variable. The label “Meal” must be understood to represent any episode of caloric consumption by a participant. This was explained in detail to the participants at 30 enrollment for purposes of logging said intake. This label is not meant to describe only so called full meals, such as breakfast, lunch, and dinner, or that a minimum number of

Kcal had to be consumed. Another variable that may run a risk of reader misinterpretation is Total Activity, and all other variables derived from subscore calculation including this variable. Activity is not to be confused with exercise. Activity is a variable label that represents, in terms of minutes, how long a said participant was active during the day. This was at the discretion of the participant to log times said participant was active, derived from a list of activities that were to be considered to fall under this variable. Each participant was instructed on this matter at enrollment in the trial. Yet another variable which stands to be misinterpreted is Percentage of Night Kcal.

This variable was held consistent with the parameters determined in the REACH Trial.

This parameter states night eating is determined by any caloric consumption after seven o’clock pm. It is important to hold consistent to this parameter, as a vague term such as

“night eating” could be confusing to the reader. Participants were not susceptible to misinterpretation of this variable as it was derived from subscore calculation after the fact, using participant food logs which listed the time of day the eating episode occurred.

For reference purposes, this information, for all variables, has been summarized and included in the following table.

31 Table 1: Variable Legend

Variable Label Variable Definition participants’ height in inches at baseline measurement Height (in)

participants’ weight in pounds at baseline measurement Baseline Weight (lbs)

participants’ weight in pounds at month 24 follow-up measurement Month 24 Weight (lbs)

difference in participants’ body mass index defined by calculation Weight Change (lbs) (Month 24 Weight) - (Baseline Weight) = x participants’ body mass index at baseline measurement defined by calculation Baseline BMI 2 (Baseline Weight) / (Height) * 705 = x participants’ body mass index at month 24 follow-up measurement defined by Month 24 BMI 2 calculation (Month 24 Weight) / (Height) * 705 = x difference in participants’ body mass index defined by calculation BMI Change (Month 24 BMI) – (Baseline BMI) = x total number of days when food consumption recall and physical activity recall were Total Dates recorded by participants sum of all eating episodes recorded by participants Total Meals

average number of eating episodes participants engaged in per day defined by Average Meals per Day calculation (Total Meals) / (Total Dates) = x sum of Kcal consumed for every food consumption recall recorded per participant Total Kcal

average Kcal consumed each day defined by calculation Average Kcal per Day (Total Kcal) / (Total Dates) = x average Kcal consumed each eating episode defined by calculation ( Total Kcal) / Average Kcal per Meal (Total Meals) = x time of day recorded by participant for each eating episode Time

average percentage of total Kcal consumed after 7 pm defined by calculation Percentage of Night Kcal (Total Night Kcal) / (Total Kcal) = x sum of minutes of physical activity as recorded by participants for physical activity Total Activity (min) recall

average minutes spent engaging in physical activity per day defined by calculation Average Activity per Day (min) (Total Activity) / (Total Dates) = x

Descriptive statistics were run on the pertinent variables for the purposes of providing a quick glimpse of the results of the current study. These descriptive statistics are summarized in the following table, Table 2.

32 Table 2: Summary of Pertinent Variables

Variable Min Max Mean Height (in) 58.50 79.00 66.34 + 3.86 Baseline Weight (lbs) 136.20 412.50 216.67 + 48.71 Month 24 Weight (lbs) 124.50 430.00 214.80 + 51.12 Weight Change (lbs)* -43.20 37.25 -1.87 + 13.12 Baseline BMI 24.93 55.33 34.60 + 6.65 Month 24 BMI 22.47 57.67 34.31 + 7.13 BMI Change* -7.10 5.32 -0.29 + 2.15 Average Eating Episodes per Day 2.67 9.83 5.06 + 1.26 Average Kcal per Day 1363.43 8896.64 3802.34 + 1366.52 Average Kcal per Meal 122.00 1096.65 363.49 + 122.07 Percentage of Night Kcal 2.71% 64.28% 27.76% + 11.80% Average Activity per Day (min) 0.00 699.00 249.89 + 173.43 *A negative number indicates Weight/BMI loss *A positive number indicates Weight/BMI gain n=303; n males=99, n females=204

It may be of interest to note the minimum BMI value at baseline in the previous table. Participants were required at enrollment to have an elevated BMI of greater than

27. However, it is noticed that the BMI minimum at baseline was 24.93. However, when reviewing the criteria for REACH Trial enrollment in Chapter III, it is clearly stated that a secondary criterion for enrollment is elevated waist to hip ratio, which is the case with any of the participants having a BMI of less than 27.

Regression Analysis

Hypothesis 1. The number of eating episodes per day is negatively associated with overall Kcal intake per meal, and positively associated with body mass index (BMI) change and body weight change. A series of regression analyses were conducted, after controlling for average activity per day in the REACH population.

Regression analyses were completed utilizing Average Kcal per Meal as the dependent variable, Average Meals per Day as the independent variable, while controlling for activity. The following table, Table 3, is a summary of these analyses. 33 Table 3: Regression Analysis – Association of Meal Frequency and Kcal Consumed per

Meal

Variable Beta Score Significance Average Kcal per Meal (Dependent) Average Meals per Day (Independent) -0.538* 0.00* *Controlled for Average Activity per Day n=303; n males=99, n females=204

Analysis reveals a strong negative association (p = 0.00) between Meal Frequency and Kcal Consumed per Meal. To summarize, there is statistical evidence that as the frequency of eating episodes per day increases, the Kcal content of those meals will decrease, and conversely as the frequency of eating episodes decreases, the Kcal content of each meal increases. In simpler terms, as one might suspect, as an individual increases the number of eating episodes in a day, the amount of Kcal contained in each meal would decrease, and vice versa.

Regression analyses were also completed for the purposes of looking at the association between meal frequency and changes in weight and BMI (Table 4).

Table 4: Regression Analysis – Association of Meal Frequency and Weight Change and

Body Mass Index Change

Variable Beta Score Significance Weight Change (Dependent) Average Meals per Day (Independent) -0.115* 0.047* BMI Change (Dependent) Average Meals per Day (Independent) -0.116* 0.045* *Controlled for Average Activity per Day n=303; n males=99, n females=204

It is noticeable that the variables Weight Change and BMI Change Baseline to Month 24 mirror each other. This can be easily determined when comparing the beta scores and significance of the two variables in Table 4 above.

34 Analysis reveals a negative association between Meal Frequency and weight change and meal frequency and body mass index change (p = 0.047 and p = 0.045 respectively). Participants with a greater number of eating episodes per day had less weight change over the 24-month trial. Those participants having fewer eating episodes per day had the greatest weight change. In summary, Hypothesis 1 is partially supported.

There appears to be a significant negative association between meal frequency and the energy content of meals. This is supportive of this researcher’s hypothesis. There also appears to be a negative association between meal frequency and weight change and body mass index change. This is unsupportive of this researcher’s hypothesis.

Hypothesis 2. A greater percentage of total Kcal eaten earlier in the day is positively associated with a lower total daily Kcal intake, greater body mass index loss, and greater body weight loss, after adjustment for differences in physical activity in the

REACH population.

Regression analysis was completed utilizing Weight Change as the dependent variable, Percentage of Night Kcal as the independent variable, while controlling for

Average Activity per Day. The following table, Table 5, is a summary of this analysis.

Table 5: Regression Analysis – Association of Percentage of Kcal Eaten at Night with

Total Kcal Consumed per Day

Variable Beta Score Significance Average Kcal per Day (Dependent) Percentage of Night Kcal (Independent) 0.101* 0.081* *Controlled for Average Activity per Day n=303; n males=99, n females=204

Analysis reveals no statistically significant association (p = 0.081) between

Average Kcal per Day and Percentage of Night Kcal. To summarize, there is no

35 statistical evidence that an increased percentage of Kcal consumed after 7 pm is associated with a total increased Kcal intake. There is no evidence that consuming more of one’s Kcal intake later in the day is related to a greater total Kcal intake.

Regression analyses were completed for the purposes of testing whether weight change or BMI change is associated with time of Kcal consumption. As stated earlier,

BMI is a value calculated using weight and height ratios, and these regression analyses should again mirror each other. Table 6 summarizes the results of the associations between weight change and time of Kcal consumption.

Table 6: Regression Analysis – Association of Percentage of Kcal Eaten at Night with

Weight Change and Body Mass Change

Variable Beta Score Significance Weight Change (Dependent) Percentage of Night Kcal (Independent) 0.067* 0.247* BMI Change (Dependent) Percentage of Night Kcal (Independent) 0.058* 0.313* *Controlled for Average Activity per Day n=303; n males=99, n females=204

It is noticeable that the variables Weight Change and BMI Change mirror each other, as expected.

Analysis reveals no statistically significant association between percentage of

Kcal eaten at night and weight change, and percentage of Kcal eaten at night and body mass index change (p = 0.247 and p = 0.313 respectively).

In summary, Hypotheses 2 is unsupported by the current study. When analyzing the data, there appears to be no significant association between meal frequency and total daily Kcal consumption. There also appears to be no significant association between

36 percentage of Kcal consumed at night with weight change or body mass index change.

Hypothesis 2 is unsupported.

37 CHAPTER V

DISCUSSION OF FINDINGS

As stated with each hypothesis, the current study sought to discover correlation between frequency of eating episodes, timing of those eating episodes, and changes in weight and BMI. Again, the hypotheses were:

Hypothesis 1. The number of eating episodes per day is negatively associated

with overall Kcal intake per meal, and positively associated with body mass index

(BMI) change and body weight change. A series of regression analyses were

conducted, after controlling for average activity per day in the REACH

population.

Hypothesis 2. A greater percentage of total Kcal eaten earlier in the day is

positively associated with a lower total daily Kcal intake, greater body mass index

loss, and greater body weight loss, after adjustment for differences in physical

activity in the REACH population.

Taken together, had these hypotheses been supported, then it would be expected that the most advantageous scenario for all individuals would be that they consume the greatest proportion of daily Kcal before seven o’clock in the evening in the form of small, frequent meals. This researcher’s hypotheses were based on conventional wisdom of

38 clinical practice and validated from past research (6,7,26-30,36-41,46,47). That being said, most of these finding were not supported by the current research.

Meal Frequency and Energy Intake

Analysis revealed statistical evidence that as an individual increases the number of eating episodes per day, the relative Kcal content of these meals would decrease. This is supportive of Hypothesis 1, as well as supportive of conventional wisdom and past research which may lead the pubic to believe a diet consisting of small meals throughout the day may be beneficial in Kcal control and .

Speechly et al. (52) found that with greater meal frequency, obese men reduced the energy content per meal. Speechly looked at the effect of meal frequency in obese men by providing isocaloric diets over five hours consisting of either one large or five smaller meals. As compared to those consuming only one meal, the men consuming five meals ate 27% fewer Kcal at a follow-up ad-libitum meal.

There are conflicting findings in the literature about the effect of meal frequency on energy distribution in meals. For obese individuals, especially, more research needs to be done on the impact of environmental and psychological factors affecting food intake in an uncontrolled setting.

Although results of the current study, as well as conventional wisdom and similar research, reveal that meal frequency is inversely related to Kcal content of meals, it is not clear if the participants would be in a positive, static, or negative energy balance, which ultimately determines a person’s weight. Recently, much attention has been given to the pattern of serving large meal portions, greater than that necessary for sustenance.

Consequently, perception of appropriate portion size may be distorted. While energy

39 balance is understood to be the ultimate determinant of a person’s weight status, there is a constant pursuit of knowledge regarding what behavioral patterns may affect energy intake. Yet, some of these mechanisms, namely meal frequency, meal timing, and appetite control remain to be fully understood.

It has been hypothesized that the cultural acceptability of snacking in the United

States has contributed to increased energy intake and higher prevalence of obesity (5).

Yet, there is little evidence to support this (53). It would be important to distinguish between the impact of increased meal frequency of moderate energy composition snacks versus high energy, high fat snacks. Johnstone et al. (53) found that in a group of eight normal weight men, randomized into “snack” or “no snack” groups with free access to food, that addition of mandatory snacks decreased the total amount of food eaten at meals and did not significantly alter their total daily energy intake or their weight.

However, it has been suggested that overweight individuals may not compensate for an increased meal frequency by reducing the energy content per meal (53). This finding would suggest that an increase in meal frequency in overweight individuals may result in a higher total daily energy intake and risk for weight gain. More research in overweight individuals is needed.

It is common knowledge that energy consumption in humans is not solely used for sustenance, but rather can be a coping mechanism for stress and boredom, or an act of socialization. There is research that has related specific macronutrient consumption, i.e. carbohydrates versus fats, and volume of consumption to subsequent consumption choices (46,54). Louis-Sylvestre et al. and Campfield et al. (55-57) have determined that low blood glucose concentration may trigger a subsequent eating episode. This is also

40 supported by Rolls et al. (58) whose research found that premeal snacks higher in carbohydrates had a more satiating effect when compared to snacks higher in fat, as determined by energy consumption at the following meal. Another interesting result of this study was that participants who consumed a higher fat premeal snack did not compensate at subsequent meals by consuming less fat. Since fat has more than double the Kcal density of protein or carbohydrates, it might be assumed that low-fat premeal snacks might assist in Kcal intake regulation.

In another study by Rolls et al. (59), 20 healthy males with normal BMIs, and in their late twenties, were studied to investigate the effect of snack volume on satiety. The participants were given isoenergetic, milk-based preloads, but varied in volumes of 300-,

450-, and 600 ml per drink. Results showed that the volume of the snack was inversely related to the energy content of the subsequent meal. It should be noted that in the current study, participants were free to choose the meal timing, amount, and composition of their diet. The variability of these factors among participants makes it difficult to make a comparison with more controlled studies. However, the findings from the current study may be more applicable to consumption patterns in free-living populations.

Meal Frequency and BMI Change

Analyses in the current study did reveal a negative correlation between meal frequency and weight change or BMI change. For example, increased meal frequency was significantly correlated to a smaller weight change. However, in this study, weight and BMI change is not defined as a gain or loss, rather a measure of weight difference from baseline to study conclusion. Since this was a weight loss program, we could assume that the change is a loss, however that cannot be confirmed. Not being able to

41 determine the direction of the change is a serious limitation of this study. What the current research results insinuate is that as meal frequency increases, less weight change

(loss) is seen. Conversely, results suggest that as meal frequency decreases, a greater weight change (loss) is seen. While these findings do not support the hypothesis or the findings in the literature about the effect of meal frequency on body weight in normal weight individuals, little is known about the impact of meal frequency on weight change in overweight individuals. It is possible that in the overweight population participating in the current study that increased meal frequency could result in a more continuous eating pattern resulting in a larger number of total daily Kcal eaten per day and a smaller amount of weight lost. Further research on the effect of eating frequency on weight and weight change in overweight individuals is needed.

Although inconclusive, this study’s results are not without significance. While keeping in mind the population of the study, 303 obese individuals, knowledge regarding how to maintain weight is equally important as how to create a weight change. It is unknown to this researcher as to where the participants’ current weight status was at the time of the original REACH Trial inception. If it can be assumed that a majority of these participants, given that they were already obese, and targeted by there primary care physicians for weight loss necessary to improve health, were continuing to gain weight at the time of REACH trial enrollment, then the current study results are very beneficial.

If these participants were able to increase the number of meals per day, therefore decreasing the number of Kcal per meal, which ultimately lead to the participants being able to keep their body weight static, instead of increasing, then this is a strategic weight management intervention that should be introduced as a way to prevent further weight

42 gain. This is consistent with the research of Westerterp-Plantenga and associates (26).

Their study concluded that energy consumption is more easily regulated in frequent eaters as opposed to individuals who consume larger, infrequent meals.

Time of Consumption

This researcher hypothesized that eating earlier in the day would be beneficial to an individual’s weight status. Research conducted by Keim et al. (60) revealed greater weight loss in women if two large meals were consumed during the day as opposed to two meals in the late afternoon and evening. Another study by Wahlqvist et al. (6) also found that in Greek older adults, consumption of the majority of a day’s nutrient intake earlier in the day was correlated to lower BMI and body fat. However, analysis in the current study revealed no statistically significant correlation between time of Kcal consumption and total daily Kcal consumption.

The inability to support this hypothesis in the current study may be due to factors out of the control of this researcher. For example, as discussed earlier in this thesis, there are physical comorbidities associated with overweight and obesity. One of the most frequent comorbidities is Type II diabetes mellitus (DM). Often, when one is diagnosed with Type II DM, the primary care physician will develop a treatment plan which will include medication therapy that also requires diet alteration. For example, if an individual is taking a long-acting insulin, meal frequency must be regulated to prevent severe highs and lows in blood glucose level. Also, many times people with diabetes are instructed to consume a snack before bedtime to ensure that their blood glucose level does not drop critically low during the night which could result in a diabetic coma. At times, this advised “bedtime snack” is taken to extremes, leading to excessive Kcal intake

43 late at night. It is not known by this researcher how many of the participants may have had diabetes. However, given the populations criteria for enrollment in the REACH trial, it is fair to assume that many had , diabetes, or .

Extenuating Influential Factors

As previously discussed, overweight and obesity are often accompanied with numerous comorbidities, i.e. Type II diabetes mellitus, cardiovascular disease and depression. Often times, these comorbidities are treated with medications. Kushner and

Blatner (61) reported that there are many medications that can affect body weight. Some drugs can induce weight gain; others can inhibit weight loss. Still others promote peripheral edema to result in weight gain though there has been no increase in body fat.

Among the classes of medications known to have weight-associated side effects are:

…anti-diabetes agents (insulin, sulfonylureas, thiazolidinediones), steroid hormones, psychotropic agents, mood stabilizers (lithium), antidepressants (tricyclics, monoamine oxidase inhibitors, paraxetine, mirtazapine), and antiepileptic drugs (valproate, gabapentin, carbamazepine) (61).

While it is unknown to this researcher the percentage of participants in this study that may have been affected by side effects of these medications, it is justifiable to assume that many had an existing comorbidity that required at least one of these medications.

Another factor that may be considered a limitation in this study, possibly affecting the results, is the age of the participants. Participants were required to be between ages

40 to 69 years. It is well documented that during the aging process, muscle-wasting occurs, leading to a less metabolically active body. A sedentary lifestyle is thought to be the primary factor contributing to obesity across age groups. Many older individuals view a more sedentary lifestyle and the consequent weight gain as an inevitable part of

44 the aging process (16). Other factors that contribute to weight gain with aging are an alteration in metabolic rate and an increase in the efficiency of fat storage (9,10). The increase in body mass and body fat percentage associated with middle-age occurs in men after 40 and in women after menopause. Since the aging process is associated with a decline in food intake, age related changes in activity levels, BMR and fat storage play a significant role in weight gain in older individuals. A study was conducted by Rothaker et al. (44), who attempted to estimate the prevalence of overweight and obesity and weight changes over a five-year period in a rural adult population categorized by age group. While the greatest increase in body weight over the five-year period occurred in the 20-30 year age group and 30-40 year age group, there was evidence still that metabolism slows and weight gain progresses well into the later decades.

Summary of Findings

This researcher hypothesized that those individuals who eat more frequent meals earlier in the day will consume fewer Kcal during meals and throughout the day, thus leading to weight reduction. Analyses found differing, yet interesting results. The current research implies eating more frequent meals does, indeed lead to fewer Kcal per meal, but does not necessarily lead to weight loss. Results also imply that the time that

Kcal intake occurs during the day does not affect total daily Kcal intake or weight or BMI change.

45 CHAPTER VI

SUMMARY AND IMPLICATIONS

As stated with each hypothesis, the current study sought to discover correlations between frequency of eating episodes, timing of those eating episodes, and weight and

BMI change. The original study used data gained from a large study of 665 participants screened for BMI >27 or an elevated predetermined waist-to-hip ratio, absence of heart or lung disease, and age between 40 and 69 years. This researcher worked with data of participants who completed the baseline evaluation and continued to participate through all four follow-up evaluations at six, 12, 18, and 24 months from baseline. A total of 303 participants, 99 males and 204 females, met these criteria.

Had the hypotheses been supported, it would be expected that the most advantageous scenario for individuals would be that they consume the greatest proportion of daily Kcal intake earlier in the day, in the form of small frequent meals, and consume few if any of their daily calories past the early evening hours. Although this idea is consistent with conventional wisdom, it was not supported with the current research.

Instead, this researcher found there to be no correlation between number of eating episodes during the day and weight loss, and no correlation between the timing of eating episodes and weight loss. Only one portion of this researcher’s hypothesis was found to be significant; that as meal frequency per day increased, the Kcal content of each meal

46 decreased. It might be assumed that although the participants in this study decreased the

Kcal content of their meals while increasing meal frequency, a negative daily Kcal balance was not achieved. It might then be assumed that while some research supports weight loss interventions, such as increased meal frequency, and reduced late night eating, that the core science behind weight management is Kcal balance.

Available evidence from previous literature suggests that most people consume an average of five to six meals per day, typically ranging from two to nine meals per day.

This researcher’s findings were consistent with those of the Food and Agriculture

Organization and the World Health Organization suggesting that the variation of periodicity of meals does not influence the balance of Kcal intake throughout the day

(67). Upon review of previous literature, many sources have documented a significant correlation between periodicity and timing of meals with obesity (6,26-36), while others have documented no such correlation (37-41). Conflicting data from this previous research relating periodicity of meals and timing of meals to obesity can be viewed as unconvincing at best.

Future Research

Although this researcher’s hypotheses were not fully supported by the current study, future research could further investigate the relationship between meal timing strategies and weight loss. Researchers may want to concentrate on interventions which could aid in creating an overall negative Kcal balance.

Practical Implications

Weight management professionals should be aware of the limitations of the current study and not be too quick to reject conventional wisdom because it was not 47 supported in the current study. As the preceding sections discuss, there are many factors affecting energy balance in individuals that were not accounted for or controlled for in the REACH approach. Because the current researcher had limited access to additional client data, it was not possible to explore these potentially confounding factors further.

Only gender, age range, and general health status were known to the researcher.

It is neither appropriate nor possible for the author of the current study to make conclusions for practice based on the outcome of the current study. Any conclusion reached from the current study would discount the conventional wisdom that individuals should consume most of their calories during the day when they are busiest and most likely to use the calories consumed rather than store them as fat. It also would need to reject the traditional advice to not eat too close to bedtime. Recommendations based on findings from the current study would not be in the best interests of practitioners' clients, since they are contradictory to lessons of clinical practice and volumes of previous research (66).

48 REFERENCES

1. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. Journal of the American Medical Association. 2006; 295: 1549-1555.

2. Overweight and Obesity. Health consequences. . Accessed October 24, 2002.

3. Yee SL, Williams-Piehota P, Sorensen A, Roussel A, Hersey J, Hamre R. The nutrition and physical activity program to prevent obesity and other chronic diseases: monitoring progress in funded states. Preventing Chronic Disease. 2006 Jan (February 19, 2008). Available from: http://www.cdc.gov/pcd/issues/2006/ jan/05_0077.htm.

4. Overweight and Obesity. Factors contributing to obesity. . Accessed October 24, 2002.

5. Poston II WSC, Foreyt JP. Obesity is an environmental issue. . 1999; 146: 201-209.

6. Wahlqvist ML, Kouris-Blazos A, Wattanapenpaiboon N. The significance of eating patterns: an elderly Greek case study. Appetite . 1999; 32: 23-32.

7. Drummond SE, Crombie NE, Cursiter MC, Kirk TR. Evidence that eating frequency is inversely related to body weight status in male, but not female, non-obese adults reporting valid dietary intakes. International Journal of Obesity . 1998; 22: 105-112.

8. Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP. The spread of the obesity epidemic in the United States, 1991-1998. Journal of the American Medical Association . 1999; 282: 1519-1522.

9. Whitney EN, Rolfes SR (2001). Understanding Nutrition , Ninth Edition.

10. Kern PA. Potential role of TNFa and lipoprotein lipase as candidate genes for obesity. Journal of Nutrition . 1997; 127: 1917s-1922s.

49

11. Farooqi IS, Jebb SA, Langmack G, Lawrence E, Cheetham CH, Prentice AM, Hughes IA, McCamish MA, O'Rahilly S. Effects of recombinant leptin therapy in a child with congenital leptin deficiency. New England Journal of Medicine . 1999; 341: 879-884.

12. Fors H, Matsuoka H, Bosaeus I, Rosberg S, Wikland KA, Bjarnson R. Serum leptin levels correlate with growth hormone secretion and body fat in children. Journal of Clinical Endocrinology & Metabolism . 1999; 84: 3586-3590.

13. Wolf G. A new uncoupling protein: a potential component of the human body weight regulation system. Nutrition Reviews . 1997; 55: 178-179.

14. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults . Bethesda, MD: National Institutes of Health, National Heart, Lung, and Blood Institute; Preprint June 1998.

15. Pi-Sunyer F. Weight and non-insulin dependent diabetes mellitus. American Journal of Clinical Nutrition . 1996; 63 s: 42s-49s.

16. Stevens J, Cai J, Pamuk ER, Williamson DF, Thun MJ, Wood JL. The effect of age on the association between body mass index and mortality. New England Journal of Medicine . 1998; 338: 1-7.

17. Gorsky RD, Pamuk E, Williamson DF, Shaffer PA, Kaplan JP. The 25-year health costs of women who remain overweight after 40 years of age. American Journal of Preventative Medicine . 1996; 12: 338-394.

18. Wolf A, Colditz G. Social and economic effects of body weigh tin the United States. American Journal of Clinical Nutrition . 1996; 63s: 466s-469s.

19. Brownell K. The pressure to eat – why we’re getting fatter. Nutrition Action Healthletter . 1998; July/August: 3-6.

20. Ball K, Mishra G, Crawford D. Which aspects of socioeconomic status are related to obesity among men and women? International Journal of Obesity . 2002; 26: 559- 565.

21. Wardle J, Walter J, Jarvis MJ. Sex differences in the association of socioeconomic status with obesity. American Journal of Public Health . 2002; 92: 1299-1304.

22. Wamala SP, Wolk A, Orth-Gomer K. Determinants of obesity in relation to socioeconomic status among middle-aged Swedish women. Preventative Medicine . 1997; 26: 734-744.

50 23. Monteiro CA, Code WL, Popkin BM. Independent effects of income and education on the risk of obesity in the Brazilian adult population. Journal of Nutrition . 2001; 131: 881s-886s.

24. Blazer DG, Moody-Ayers S, Craft-Morgan J, Burchett B. Depression in diabetes and obesity: racial/ethnic/gender issues in older adults. Journal of Psychosomatic Research . 2002; 53: 913-916.

25. Haukkala A, Uutela A. Cynical hostility, depression, and obesity: the moderating role of education and gender. International Journal of Eating Disorders . 2000; 27: 106-109.

26. Westerterp-Plantenga MS, Wijckmans-Duysens NEG, ten Hoor F. Food intake in the daily environment after energy-reduced lunch related to habitual meal frequency. Appetite . 1994; 22: 173-182.

27. Clifton PG. Meal patterning in rodents: psychopharmacological and neuroanatomical studies. Neuroscience and Biobehavioral Reviews . 2000; 24: 213-222.

28. Fabry P, Hejda S, Cerny K, Osancova K, Pechar J. Effect of meal frequency in school children, changes in weight-height proportion and skinfold thickness. American Journal of Clinical Nutrition . 1966; 18: 358-361.

29. Fabry P, Hejl Z, Fodor J, Braun T, Zvolankova K. The frequency of meals, its relation to overweight, hypercholesterolemia and decreased glucose tolerance. Lancet 2 . 1964; 614.

30. Metzner HL, Lamphiear DE, Wheeler NC, Larkin FA. The relationship between frequency of eating and adiposity in adult men and women in the Tecumseh Community Health Study. American Journal of Clinical Nutrition . 1977; 30: 712- 715.

31. McCrory MA, Fuss PJ, Hays NP, Vinken AG, Greensburg AS, Roberts SB. Overeating in American: association between restaurant food consumption and body fatness in healthy adult men and women ages 19 to 80. Obesity Research . 199; 7: 564-571.

32. McCrory MA, Fuss PJ, McCallum JE, Yao M, Vinken AG, Hays NP, et al. Dietary variety within food groups: association with energy intake and body fatness in men and women. American Journal of Clinical Nutrition . 1999; 69: 440-447.

33. McCrory MA, Fuss PJ, Saltzman E, Roberts SB. Dietary determinants of energy intake and weight regulation in healthy adults. Journal of Nutrition . 2000; 130: 276s-279s.

51 34. Edmonds J, Baranowski T, Baranowski J, Cullen KW, Myres D. Ecological and socioeconomic correlates of fruit, juice and vegetable consumption among African- American boys. Preventative Medicine . 2001; 32: 476-481.

35. Egger G, Swinburn B. An “ecological” approach to the obesity pandemic. BMJ . 1997; 315:477-480.

36. Birketvedt GS, Florhomen J, Sundsfjord J, Osterud B, Dinges D, Bilker W, et al. Behavioral and neuroendocrine characteristics of the night-eating syndrome. Journal of the American Medical Association . 1999; 282: 657-663.

37. Roos E, Prattala R. Meal Pattern and nutrient intake among adult Finns. Appetite . 1997; 29: 11-24.

38. Basdevant A, Carplet C, Guy-Grand B. Snacking patterns in obese French women. Appetite . 1993; 21: 17-23.

39. Young CM, Scanlan Ss, Topping CM, Simko V, Lutwak L. Frequency of feeding, weight reduction, and . Journal of the American Dietetic Association . 1971; 59: 466-472.

40. Young CM, Frankel DL, Scanlan SS, Simko V, Lutwak L. Frequency of feeding, weight reduction, and nutrient utilization. Journal of the American Dietetic Association . 1971; 59: 473-480.

41. Edelstein SL, Barrett-Connor EL, Wingard DL, Cohn BA. Increased meal frequency associated with deceased cholesterol concentrations; Rancho Bernardo, CA, 1984- 1987. American Journal of Clinical Nutrition . 1992; 55: 664-669.

42. Lynch JW, Kaplan GA, Salomen JT. Why do poor people behave poorly? Variations in adult health behaviour and psychosocial characteristics, by stage of the socioeconomic lifecourse. Social Science of Medicine . 1997; 44: 809-820.

43. Berkman LF, Breslow L (1983). Health and Ways of Living: the Alameda County Study . New York: Oxford University Press.

44. Rothaker DQ, Blackburn GL. Obesity prevalence by age group and 5-year changes in adults in rural Wisconsin. Journal of the American Dietetic Association . 2000; 100: 784-790.

45. Woods SC, Schwartz MW, Baskin DG, Seeley RJ. Food intake and the regulation of body weight. Annual Psychology Review . 2000; 51: 255-277.

52 46. Rolls BJ, Kim-Harris S, Fischman MW, Foltin RW, Moran TH, Stoner SA. Satiety after preloads with different amounts of fat and carbohydrate; implications for obesity. American Journal of Clinical Nutrition . 1994; 60: 476-487.

47. Kumanyika SK, Van Horn L, Bowen D, Perri MG, Rolls BJ, Czajkowski SM, et al. Maintenance of dietary behavior change. Health Psychology . 2000; 19: 42s-56s.

48. Hu FB, Rimm E, Smith-Warner SA, Feskanich D, Stampfer MJ, Ascherio A, et al. Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire. American Journal of Clinical Nutrition . 1999; 69: 243-249.

49. Rand, CA, Macgregor AM, Stunkard AJ. The night eating syndrome in the general population and among postoperative obesity surgery patients. International Journal of Eating Disorders . 1997; 22: 65-69.

50. Freedman MR, King J, Kennedy E. Popular diets: a scientific review. Obesity Research . 2001; 9: 1s-40s.

51. Prochaska JO, Redding CA, Evers KE. The Transtheoretical Model and Stage of Change. Health Behavior and Health Education: Theory, Research, and Practice . Second Edition. San Francsico: Jossey-Bass, 1997: 60-84.

52. Speechly DP, Rogers GG, Buffenstein R. Acute appetite reduction associated with an increased frequency of eating in obese males. International Journal of Obesity Related Metabolic Disorders. 1999; 23: 1151-1159.

53. Johnstone AM, Shannon E, Whybrow S, et al. Altering the temporal distribution of energy intake with isoenergetically dense foods given as snacks does not affect total daily energy intake in normal-weight men. British Journal of Nutrition. 2000; 83 (1): 7-14.

54. Rolls BJ, Roe LS, Meenga JS. Salad and satiety: energy density and portion size of a first-course salad affect energy intake at lunch. Journal of the American Dietetic Association. 2004; 104: 1570-1576.

55. Louis-Sylvestre J, Le Magnen J. Fall in blood glucose level preceded meal onset in free-feeding rats. Neuroscience and Biobehavioral Reviews. 1980; 4 (supplement 1): 13-15.

56. Campfield LA, Smith FJ. Transient declines in blood glucose signal meal initiation. International Journal of Obesity. 1990; 14 (supplement 3): 15-31; discussion 31-14.

57. Campfield LA, Smith FJ. Functional coupling between transient declines in blood glucose and feeding behavior: temporal relationships. Brain Research Bulletin. 1986; 17: 427-433.

53 58. Rolls BJ, Kim-Harris S, Fischman MW, et al. Satiety after preloads with different amounts of fat and carbohydrate: implications for obesity. American Journal of Clinical Nutrition. 1991; 53: 908-915.

59. Rolls BJ, Castellanos VH, Halford JC, et al. Volume of food consumed affects satiety in men. American Journal of Clinical Nutrition. 1998; 67: 1170-1177.

60. Keim NL, Van Loan MD, Horn WF, Barbieri TF, Mayclin PL. Weight loss is greater with consumption of large morning meals and fat-free mass is preserved with large evening meals in women on a controlled weight reduction regimen. Journal of Nutrition . 1997; 127: 75-82.

61. Kushner R, Blatner D. Risk Assessment of the Overweight and Obese Patient. Journal of the American Dietetic Association. 2005; 105: 53-62.

62. Creswell JW. Qualitative Inquiry and Research Design: Choosing among Five Traditions. Thousand Oaks, CA: Sage, 1997: 26.

63. Nutrition for diabetics. University of Iowa Hospitals and Clinics. . Accessed August 1, 2006.

64. Treatment of Diabetes. Endocrine Web. . Accessed August 1, 2006.

65. MyPyramid Tracker. Center for Nutrition Policy and Promotion. . Accessed August 1, 2006.

66. Jonker JT, De Laet C, Franco OH, Peeters A, Mackenbach J, Nusselder WJ. Physical activity and life expectancy with and without diabetes: life table analysis of the Framingham Heart Study. Diabetes Care. 2006; 29: 38-43.

67. Gibney, MJ, Wolever TMS. Periodicity of eating and human health: present perspective and future directions. British Journal of Nutrition. 1997; 77 (supplement 1): S3-S5

54

APPENDICES

55 APPENDIX A

HUMAN SUBJECTS APPROVAL

56 APPENDIX B

PRIMARY DATA

BMI BMI BMI BMI Kcal Kcal Total Total Total Total Total Total Total Dates Meals Weight Gender Change Average Average Average Average Baseline Baseline Kcal/Day Month 24 Month 24 Kcal/Meal Night Kcal Height (in) Meals/Day Weight (lbs) Weight (lbs) Change (lbs) Activity (min) Participant ID Percentage of Activity/Day(min)

1003 F 64.50 226.00 231.00 5.00 38.30 39.15 0.85 6 51 5.83 11014 57.38% 1835.69 215.96 1280.00 256.00

1012 F 68.50 250.20 245.00 -5.20 37.59 36.81 -0.78 7 58 4.43 19040 37.00% 2720.02 328.28 975.00 195.00

1013 F 65.00 213.20 230.50 17.30 35.58 38.46 2.89 6 57 4.83 17103 25.54% 2850.46 300.05 310.00 62.00

1015 F 60.50 244.80 238.00 -6.80 47.15 45.84 -1.31 5 38 4.80 11455 29.80% 2291.08 301.46 320.00 64.00

1021 F 68.75 249.80 242.00 -7.80 37.26 36.10 -1.16 6 63 6.33 15472 20.94% 2578.66 245.59 2145.00 429.00

1022 M 72.00 322.20 325.75 3.55 43.82 44.30 0.48 7 54 5.14 34320 42.02% 4902.90 635.56 1470.00 294.00

1024 M 69.25 320.80 330.00 9.20 47.16 48.51 1.35 6 62 5.67 21417 25.54% 3569.47 345.43 3350.00 670.00

1026 F 63.50 243.20 253.00 9.80 42.52 44.23 1.71 3 58 5.17 21461 13.57% 7153.61 370.01 800.00 160.00

1027 F 66.00 200.40 231.00 30.60 32.43 37.39 4.95 6 73 5.62 29551 12.81% 4925.15 404.81 0.00 0.00

1029 F 64.00 217.40 214.50 -2.90 37.42 36.92 -0.50 6 40 4.00 19196 42.42% 3199.26 479.89 2055.00 411.00

1031 F 61.00 176.80 164.50 -12.30 33.50 31.17 -2.33 6 57 4.67 14549 19.82% 2424.75 255.24 1245.00 249.00

1034 F 65.00 201.80 192.00 -9.80 33.67 32.04 -1.64 3 48 4.80 20502 31.17% 6834.05 427.13 480.00 96.00

1038 F 63.00 178.40 186.00 7.60 31.69 33.04 1.35 6 54 4.17 15933 12.83% 2655.43 295.05 625.00 125.00

1039 M 71.00 293.00 296.00 3.00 40.98 41.40 0.42 6 53 4.50 27647 8.11% 4607.84 521.64 465.00 93.00

1041 F 64.00 196.80 193.00 -3.80 33.87 33.22 -0.65 6 66 6.67 15979 26.49% 2663.14 242.10 1505.00 301.00

1046 M 70.50 293.60 304.50 10.90 41.65 43.19 1.55 7 102 7.71 24506 22.79% 3500.89 240.26 1070.00 214.00

1048 F 60.25 149.20 153.50 4.30 28.98 29.81 0.84 6 40 4.17 19257 24.00% 3209.50 481.43 990.00 198.00

1056 F 67.50 189.00 161.75 -27.25 29.24 25.03 -4.22 7 44 4.29 15506 12.03% 2215.12 352.41 1800.00 360.00

1058 M 74.00 379.50 380.20 0.70 48.86 48.95 0.09 8 52 3.63 28982 19.07% 3622.78 557.35 960.00 192.00

1059 F 61.00 163.75 165.80 2.05 31.02 31.41 0.39 9 74 4.78 28797 39.33% 3199.69 389.15 360.00 72.00

2002 F 62.00 175.80 193.80 18.00 32.24 35.54 3.30 9 91 6.33 29334 33.29% 3259.28 322.35 323.00 64.60

2006 F 61.50 192.00 193.10 1.10 35.79 35.99 0.21 9 88 6.11 26666 17.45% 2962.87 303.02 2315.00 463.00

2008 F 61.75 153.80 143.40 -10.40 28.44 26.51 -1.92 7 68 6.43 20637 25.25% 2948.19 303.49 813.00 162.60

2009 M 67.25 197.40 191.50 -5.90 30.77 29.85 -0.92 9 52 4.56 24482 14.97% 2720.26 470.81 1540.00 308.00

2011 F 65.75 183.00 159.00 -24.00 29.84 25.93 -3.91 9 73 4.33 32880 39.22% 3653.35 450.41 855.00 171.00

2013 F 66.25 281.40 257.00 -24.40 45.20 41.28 -3.92 9 129 7.89 28081 23.32% 3120.11 217.68 1035.00 207.00

2014 F 66.25 221.20 252.00 30.80 35.53 40.48 4.95 9 82 5.33 27101 31.92% 3011.17 330.49 420.00 84.00

2015 M 68.00 218.40 221.00 2.60 33.30 33.69 0.40 9 52 4.44 21793 27.28% 2421.43 419.09 1100.00 220.00

2016 M 71.50 270.60 245.00 -25.60 37.32 33.79 -3.53 9 71 4.78 27387 14.85% 3043.05 385.74 1843.00 368.60

2019 F 61.00 260.00 246.00 -14.00 49.26 46.61 -2.65 9 58 4.44 15317 34.48% 1701.85 264.08 1640.00 328.00

2022 F 63.75 172.40 181.90 9.50 29.91 31.55 1.65 9 113 7.56 18547 17.49% 2060.82 164.14 655.00 131.00

2027 M 69.75 381.40 391.20 9.80 55.27 56.69 1.42 7 48 5.00 37441 44.25% 5348.71 780.02 860.00 172.00

3003 M 72.25 255.80 250.25 -5.55 34.55 33.80 -0.75 9 53 4.56 27525 15.01% 3058.38 519.35 1440.00 288.00

3004 F 67.25 175.40 189.20 13.80 27.34 29.49 2.15 7 64 5.82 16727 36.89% 2389.60 261.36 0.00 0.00

3006 F 65.25 206.80 207.40 0.60 34.24 34.34 0.10 7 72 5.43 19887 30.73% 2840.99 276.21 520.00 104.00

3007 F 59.25 150.40 149.50 -0.90 30.20 30.02 -0.18 7 45 3.46 18861 23.94% 2694.49 419.14 75.00 18.75 57 3008 M 70.00 230.80 237.40 6.60 33.21 34.16 0.95 9 90 6.33 37234 52.45% 4137.11 413.71 147.00 29.40

3009 F 65.25 178.00 154.60 -23.40 29.47 25.60 -3.87 7 96 7.38 20509 39.44% 2929.89 213.64 120.00 24.00

3011 F 62.25 206.40 192.00 -14.40 37.55 34.93 -2.62 9 67 6.00 19221 23.82% 2135.67 286.88 1200.00 240.00

3013 F 66.50 203.00 170.40 -32.60 32.36 27.17 -5.20 9 55 5.78 12271 17.27% 1363.43 223.11 960.00 192.00

3014 F 62.00 148.40 129.60 -18.80 27.22 23.77 -3.45 9 84 6.00 22278 22.71% 2475.31 265.21 1425.00 285.00

3015 F 61.00 162.20 163.75 1.55 30.73 31.02 0.29 9 65 5.22 17015 36.62% 1890.53 261.77 2290.00 572.50

3017 F 61.50 160.40 151.80 -8.60 29.90 28.30 -1.60 9 68 5.67 17541 17.88% 1949.04 257.96 1290.00 258.00

3018 F 65.50 269.00 270.50 1.50 44.20 44.45 0.25 9 61 5.22 21475 16.52% 2386.13 352.05 1170.00 234.00

3019 F 64.50 196.00 191.60 -4.40 33.21 32.47 -0.75 8 97 7.13 20382 37.82% 2547.72 210.12 1805.00 361.00

3020 F 64.50 214.40 225.00 10.60 36.33 38.13 1.80 5 38 5.20 17333 14.97% 3466.57 456.13 585.00 117.00

3022 F 61.75 188.40 178.25 -10.15 34.83 32.96 -1.88 8 100 7.50 12977 32.15% 1622.07 129.77 780.00 156.00

3023 M 79.00 260.80 265.50 4.70 29.46 29.99 0.53 9 70 4.78 32521 22.20% 3613.48 464.59 1245.00 249.00

3026 M 76.00 359.80 366.75 6.95 43.92 44.76 0.85 10 84 5.40 45361 24.87% 4536.06 540.01 620.00 124.00

3027 F 64.00 204.20 203.20 -1.00 35.15 34.97 -0.17 8 66 6.38 16035 17.01% 2004.32 242.95 315.00 63.00

3029 F 64.00 146.60 156.60 10.00 25.23 26.95 1.72 9 67 5.44 25163 33.20% 2795.90 375.57 1605.00 321.00

3030 F 62.75 167.60 157.80 -9.80 30.01 28.25 -1.75 9 81 5.67 20072 10.63% 2230.25 247.81 1700.00 340.00

3031 F 62.00 174.20 179.25 5.05 31.95 32.87 0.93 7 48 4.00 21131 21.53% 3018.71 440.23 240.00 48.00

3032 F 67.50 172.20 154.00 -18.20 26.64 23.83 -2.82 9 101 7.22 21838 34.20% 2426.41 216.21 3010.00 602.00

3034 F 65.00 187.00 158.80 -28.20 31.20 26.50 -4.71 9 77 5.44 25610 38.14% 2845.59 332.60 570.00 114.00

3035 F 63.75 154.40 145.20 -9.20 26.78 25.19 -1.60 9 78 5.00 18615 16.65% 2068.38 238.66 1175.00 235.00

3038 F 67.25 231.20 208.60 -22.60 36.04 32.52 -3.52 9 62 4.22 17911 12.10% 1990.13 288.89 1970.00 394.00

3039 F 62.50 223.80 224.00 0.20 40.39 40.43 0.04 9 99 5.78 21123 24.39% 2347.01 213.36 335.00 67.00

3040 F 65.50 192.00 179.50 -12.50 31.55 29.50 -2.05 7 73 5.29 14269 24.27% 2038.38 195.46 1075.00 215.00

3041 F 66.50 213.20 204.40 -8.80 33.99 32.59 -1.40 9 74 5.33 23992 21.78% 2665.72 324.21 1110.00 222.00

3042 M 72.00 242.60 233.00 -9.60 32.99 31.69 -1.31 7 40 4.71 23085 14.18% 3297.80 577.12 1585.00 396.25

3044 F 63.50 186.00 177.50 -8.50 32.52 31.03 -1.49 9 72 6.33 23271 28.11% 2585.72 323.22 630.00 126.00

3045 F 68.00 202.80 201.20 -1.60 30.92 30.68 -0.24 10 71 5.50 26473 43.44% 2647.34 372.86 985.00 197.00

3046 F 67.50 162.80 170.00 7.20 25.19 26.30 1.11 11 109 6.91 22373 24.06% 2033.92 205.26 960.00 192.00

3048 F 62.75 216.25 216.20 -0.05 38.72 38.71 -0.01 9 65 5.33 18504 23.47% 2056.03 284.68 1665.00 416.25

3049 F 63.50 174.25 158.00 -16.25 30.47 27.62 -2.84 6 69 5.00 21312 28.76% 3551.93 308.86 795.00 159.00

3050 M 72.50 247.20 261.40 14.20 33.16 35.06 1.90 7 42 3.73 26431 22.56% 3775.79 629.30 2790.00 558.00

3051 F 64.50 223.50 228.00 4.50 37.87 38.64 0.76 4 45 5.50 16951 32.05% 4237.80 376.69 1050.00 262.50

3052 F 64.00 182.40 174.80 -7.60 31.39 30.09 -1.31 5 52 5.00 18017 6.41% 3603.31 346.47 590.00 118.00

3055 F 64.25 183.20 183.20 0.00 31.29 31.29 0.00 6 70 5.17 25858 13.38% 4309.61 369.40 480.00 96.00

3057 F 65.00 205.80 195.00 -10.80 34.34 32.54 -1.80 6 60 5.83 19241 17.89% 3206.78 320.68 930.00 186.00

3061 F 72.50 193.00 190.50 -2.50 25.89 25.55 -0.34 6 81 6.00 20943 14.76% 3490.45 258.55 750.00 150.00

3063 F 64.50 173.20 146.80 -26.40 29.35 24.88 -4.47 6 56 5.83 13749 40.42% 2291.44 245.51 240.00 48.00

3064 M 77.25 252.25 242.80 -9.45 29.80 28.68 -1.12 6 54 3.83 31215 25.08% 5202.44 578.05 2745.00 549.00

3066 F 64.50 170.20 165.00 -5.20 28.84 27.96 -0.88 6 73 6.33 19837 20.14% 3306.08 271.73 1420.00 284.00

3067 F 59.25 214.60 214.50 -0.10 43.10 43.08 -0.02 6 67 5.33 17116 10.20% 2852.59 255.46 720.00 144.00

3068 F 62.50 160.60 166.50 5.90 28.99 30.05 1.06 6 89 6.33 24954 30.62% 4158.99 280.38 780.00 195.00

3069 M 71.00 271.00 270.80 -0.20 37.90 37.87 -0.03 7 66 5.08 32458 37.59% 4636.87 491.79 960.00 192.00

3070 M 63.00 182.20 155.75 -26.45 32.36 27.67 -4.70 6 79 5.67 28828 19.14% 4804.71 364.91 1440.00 288.00

3074 M 68.00 223.20 225.00 1.80 34.03 34.30 0.27 3 75 6.33 25288 33.15% 8429.28 337.17 880.00 293.33

3075 M 72.00 230.60 235.60 5.00 31.36 32.04 0.68 6 84 6.00 34810 42.93% 5801.70 414.41 1035.00 207.00

3077 F 62.25 157.80 162.00 4.20 28.71 29.47 0.76 6 70 6.00 18043 13.10% 3007.11 257.75 1665.00 333.00

3084 F 69.25 322.60 343.00 20.40 47.43 50.42 3.00 4 50 4.75 19716 40.67% 4929.03 394.32 900.00 180.00

3090 F 64.50 156.20 155.20 -1.00 26.47 26.30 -0.17 6 76 6.17 17814 31.64% 2969.01 234.40 395.00 79.00

3094 F 65.25 260.25 235.00 -25.25 43.09 38.91 -4.18 6 77 5.83 17954 19.84% 2992.26 233.16 1470.00 294.00

3096 F 66.25 222.25 231.60 9.35 35.70 37.20 1.50 5 74 7.20 19565 42.36% 3913.10 264.40 2970.00 594.00

3097 F 60.75 196.60 206.60 10.00 37.56 39.47 1.91 6 49 4.67 17907 24.83% 2984.53 365.45 1260.00 252.00

3098 F 62.50 156.20 144.00 -12.20 28.19 25.99 -2.20 6 96 6.17 18234 6.01% 3039.00 189.94 900.00 180.00

58 3100 M 75.25 258.00 258.00 0.00 32.12 32.12 0.00 6 71 5.50 34512 28.24% 5751.93 486.08 910.00 182.00

3101 F 62.00 163.20 177.75 14.55 29.93 32.60 2.67 6 71 4.67 19955 23.38% 3325.90 281.06 1320.00 264.00

3106 F 62.00 207.20 178.70 -28.50 38.00 32.77 -5.23 6 45 5.00 11784 27.55% 1963.92 261.86 970.00 194.00

3108 F 66.00 156.20 161.20 5.00 25.28 26.09 0.81 6 69 4.17 25513 31.09% 4252.18 369.76 255.00 51.00

3109 F 64.50 305.20 311.80 6.60 51.72 52.84 1.12 5 46 3.60 23575 27.01% 4715.07 512.51 1180.00 236.00

3110 F 60.75 184.80 167.50 -17.30 35.30 32.00 -3.30 6 74 5.67 15223 16.56% 2537.15 205.71 805.00 161.00

3111 F 62.50 199.00 210.60 11.60 35.92 38.01 2.09 7 52 3.29 28528 24.44% 4075.45 548.62 1245.00 249.00

4002 F 67.75 295.00 287.00 -8.00 45.31 44.08 -1.23 6 83 6.17 32248 15.75% 5374.74 388.54 330.00 66.00

4003 M 76.00 278.20 261.00 -17.20 33.96 31.86 -2.10 6 64 4.83 31984 41.70% 5330.67 499.75 2120.00 424.00

4004 M 70.25 246.20 220.00 -26.20 35.17 31.43 -3.74 6 78 6.17 21496 27.78% 3582.67 275.59 1445.00 289.00

4006 F 63.50 185.60 188.00 2.40 32.45 32.87 0.42 4 119 7.50 23587 17.45% 5896.83 198.21 1310.00 262.00

4009 F 67.75 187.80 186.50 -1.30 28.84 28.65 -0.20 5 58 4.60 28923 34.02% 5784.67 498.68 3420.00 684.00

4010 M 70.50 344.50 357.00 12.50 48.87 50.64 1.77 5 85 7.00 21124 26.58% 4224.78 248.52 1090.00 218.00

4012 M 71.00 248.20 250.40 2.20 34.71 35.02 0.31 3 32 5.67 11746 56.39% 3915.18 367.05 1005.00 201.00

4015 M 73.00 332.40 333.00 0.60 43.97 44.05 0.08 6 71 5.33 45617 31.37% 7602.78 642.49 150.00 37.50

4017 M 71.00 208.40 202.00 -6.40 29.15 28.25 -0.90 5 130 8.00 32792 21.94% 6558.46 252.25 3090.00 618.00

4018 M 70.50 225.60 228.00 2.40 32.00 32.34 0.34 5 64 4.80 24906 21.37% 4981.18 389.15 2190.00 438.00

4020 F 62.00 165.20 172.00 6.80 30.30 31.55 1.25 6 58 5.50 18945 33.12% 3157.55 326.64 750.00 150.00

4021 M 69.50 221.40 215.00 -6.40 32.31 31.38 -0.93 6 123 7.67 30923 35.84% 5153.80 251.40 1222.00 244.40

4022 M 73.75 205.80 204.00 -1.80 26.68 26.44 -0.23 6 73 5.33 23992 33.86% 3998.68 328.66 925.00 185.00

4023 F 63.75 206.80 194.00 -12.80 35.87 33.65 -2.22 3 34 4.00 12622 17.59% 4207.27 371.23 1185.00 237.00

4024 F 65.50 238.80 247.00 8.20 39.24 40.59 1.35 3 80 5.71 26690 34.27% 8896.64 333.62 210.00 42.00

4026 F 62.25 179.60 187.30 7.70 32.68 34.08 1.40 6 52 4.67 15183 5.53% 2530.52 291.98 1150.00 230.00

4031 M 69.00 222.30 221.00 -1.30 32.92 32.73 -0.19 6 76 6.33 21040 50.38% 3506.63 276.84 1495.00 299.00

4036 M 70.25 239.25 235.40 -3.85 34.18 33.63 -0.55 3 57 5.33 15951 34.77% 5317.06 279.85 1170.00 234.00

4037 F 62.50 231.60 249.00 17.40 41.80 44.94 3.14 5 76 6.80 14311 24.01% 2862.22 188.30 360.00 72.00

4038 F 67.00 260.40 253.80 -6.60 40.90 39.86 -1.04 4 41 7.00 12109 19.46% 3027.33 295.35 75.00 15.00

4040 F 63.00 284.00 255.60 -28.40 50.45 45.40 -5.04 4 42 5.00 11563 27.33% 2890.65 275.30 682.00 136.40

4042 M 70.25 326.25 323.80 -2.45 46.61 46.26 -0.35 6 132 9.83 42133 3.93% 7022.15 319.19 1080.00 270.00

4043 M 71.25 247.25 244.12 -3.13 34.34 33.90 -0.43 6 63 7.88 17654 45.97% 2942.37 280.23 90.00 18.00

4044 M 68.25 231.25 229.04 -2.21 35.00 34.67 -0.33 6 126 6.17 44097 29.44% 7349.43 349.97 2070.00 414.00

4046 F 64.00 164.20 174.70 10.50 28.26 30.07 1.81 4 50 5.75 12347 47.88% 3086.80 246.94 1520.00 380.00

4050 F 63.50 163.30 200.70 37.40 28.55 35.09 6.54 6 74 5.83 17924 41.34% 2987.37 242.22 3120.00 624.00

4051 M 70.00 234.80 233.50 -1.30 33.78 33.60 -0.19 6 75 6.00 20299 36.83% 3383.15 270.65 2722.00 544.40

4052 M 71.00 295.40 298.00 2.60 41.31 41.68 0.36 6 72 6.67 16145 49.86% 2690.82 224.24 1080.00 270.00

4053 M 66.25 221.25 220.08 -1.17 35.54 35.35 -0.19 6 61 6.17 25086 29.02% 4180.97 411.24 900.00 180.00

4057 F 69.50 183.40 180.60 -2.80 26.77 26.36 -0.41 6 46 5.17 13314 18.31% 2218.95 289.43 1590.00 318.00

4058 M 68.75 272.40 248.20 -24.20 40.63 37.02 -3.61 6 98 7.67 42818 19.47% 7136.27 436.91 1630.00 326.00

4061 M 75.25 322.25 335.80 13.55 40.12 41.81 1.69 6 81 4.67 27470 30.66% 4578.40 339.14 1830.00 366.00

4063 F 61.25 161.00 164.40 3.40 30.26 30.89 0.64 6 57 5.17 13652 12.30% 2275.29 239.50 1515.00 303.00

4064 F 60.00 163.60 166.10 2.50 32.04 32.53 0.49 6 52 4.67 13947 13.57% 2324.48 268.21 625.00 125.00

4065 M 74.00 262.00 264.00 2.00 33.73 33.99 0.26 6 37 4.17 16203 30.52% 2700.51 437.92 1035.00 207.00

4072 F 63.50 199.60 199.50 -0.10 34.90 34.88 -0.02 6 96 8.67 15395 33.54% 2565.84 160.37 2704.00 676.00

4076 F 61.00 149.20 153.20 4.00 28.27 29.03 0.76 6 73 5.62 19919 13.99% 3319.91 272.87 170.00 34.00

4077 M 67.00 199.00 197.50 -1.50 31.25 31.02 -0.24 6 58 5.17 25241 35.42% 4206.75 435.18 2035.00 407.00

4079 F 65.50 188.20 145.00 -43.20 30.93 23.83 -7.10 6 96 6.50 18388 58.19% 3064.70 191.54 360.00 72.00

4080 F 66.50 156.40 157.40 1.00 24.93 25.09 0.16 6 77 5.83 18639 14.78% 3106.44 242.06 1530.00 306.00

4081 M 67.50 211.40 205.70 -5.70 32.71 31.83 -0.88 6 73 6.00 23566 43.66% 3927.68 322.82 1620.00 324.00

4083 F 65.00 191.00 195.50 4.50 31.87 32.62 0.75 6 56 5.50 25341 29.38% 4223.45 452.51 1253.00 250.60

4084 F 63.75 158.00 145.40 -12.60 27.41 25.22 -2.19 5 40 5.40 11505 48.62% 2301.00 287.62 765.00 191.25

4086 F 63.00 200.60 204.30 3.70 35.63 36.29 0.66 6 81 5.00 21065 27.96% 3510.83 260.06 275.00 55.00

4087 F 64.00 149.60 154.10 4.50 25.75 26.52 0.77 6 90 6.17 22385 30.44% 3730.88 248.73 380.00 76.00

59 4090 F 66.25 196.25 197.70 1.45 31.52 31.76 0.23 6 64 5.00 20486 26.40% 3414.38 320.10 600.00 120.00

4096 M 69.25 216.60 218.20 1.60 31.84 32.08 0.24 6 97 6.83 28438 34.49% 4739.69 293.18 1410.00 282.00

4097 M 73.25 237.40 242.30 4.90 31.19 31.84 0.64 6 72 6.17 25120 48.56% 4186.64 348.89 2195.00 439.00

4098 F 63.25 160.80 160.20 -0.60 28.34 28.23 -0.11 6 61 4.33 22157 17.46% 3692.77 363.22 525.00 105.00

4099 M 69.25 214.00 207.10 -6.90 31.46 30.45 -1.01 6 56 5.17 23867 42.64% 3977.79 426.19 880.00 176.00

4105 F 67.00 165.60 155.25 -10.35 26.01 24.38 -1.63 5 63 6.40 12561 51.48% 2512.18 199.38 1135.00 227.00

4108 M 75.50 222.40 199.00 -23.40 27.51 24.61 -2.89 5 79 6.60 21069 27.32% 4213.89 266.70 1680.00 336.00

4110 F 64.25 178.50 174.12 -4.38 30.48 29.74 -0.75 4 70 6.25 19737 21.32% 4934.37 281.96 1680.00 336.00

4114 M 70.00 228.60 226.90 -1.70 32.89 32.65 -0.24 5 50 5.40 33671 25.39% 6734.14 673.41 3010.00 602.00

4115 F 65.50 234.60 248.00 13.40 38.55 40.75 2.20 6 123 8.17 25021 34.28% 4170.17 203.42 1530.00 306.00

4120 M 67.25 238.60 226.20 -12.40 37.19 35.26 -1.93 6 78 6.50 25688 38.04% 4281.41 329.34 570.00 114.00

4123 F 65.00 159.10 160.08 0.98 26.55 26.71 0.16 5 78 6.20 20300 16.69% 4060.07 260.26 1285.00 257.00

5003 M 68.25 196.80 178.50 -18.30 29.79 27.02 -2.77 6 79 4.17 29402 34.07% 4900.25 372.17 3225.00 645.00

5006 M 70.25 237.25 238.50 1.25 33.89 34.07 0.18 6 48 4.00 52639 37.66% 8773.20 1096.65 1020.00 255.00

5009 M 71.25 229.40 239.50 10.10 31.86 33.26 1.40 6 79 5.33 28001 22.06% 4666.85 354.44 2690.00 538.00

5010 M 67.25 217.60 204.00 -13.60 33.92 31.80 -2.12 6 62 5.17 23800 16.08% 3966.70 383.87 2460.00 492.00

5011 F 63.25 166.25 144.00 -22.25 29.30 25.38 -3.92 6 79 5.33 21669 37.21% 3611.47 274.29 855.00 171.00

5012 F 62.50 182.60 182.00 -0.60 32.96 32.85 -0.11 7 40 3.14 16663 50.37% 2380.46 416.58 1440.00 288.00

5013 F 61.40 183.40 181.50 -1.90 34.30 33.94 -0.36 6 56 4.00 22380 17.19% 3730.05 399.65 765.00 153.00

5015 M 69.25 228.60 216.00 -12.60 33.61 31.75 -1.85 6 78 4.50 18969 15.51% 3161.45 243.19 2145.00 429.00

5017 F 63.25 145.80 145.00 -0.80 25.69 25.55 -0.14 6 60 4.83 19953 19.96% 3325.48 332.55 1845.00 369.00

5018 F 69.25 266.40 275.00 8.60 39.16 40.43 1.26 6 31 3.50 16842 50.90% 2806.95 543.28 1545.00 309.00

5019 F 63.25 155.40 156.20 0.80 27.39 27.53 0.14 6 39 3.50 17562 28.42% 2926.94 450.30 1705.00 341.00

5022 M 68.50 231.80 226.75 -5.05 34.83 34.07 -0.76 6 54 4.33 19570 36.72% 3261.66 362.41 2070.00 414.00

5027 F 65.00 204.40 203.25 -1.15 34.11 33.92 -0.19 6 46 3.67 20324 32.11% 3387.29 441.82 80.00 16.00

5031 F 61.50 160.80 155.80 -5.00 29.97 29.04 -0.93 4 34 4.75 12535 29.84% 3133.65 368.66 647.00 129.40

5032 F 65.00 195.00 192.75 -2.25 32.54 32.16 -0.38 6 58 5.17 15767 28.37% 2627.85 271.85 275.00 55.00

5033 F 67.00 183.40 197.00 13.60 28.80 30.94 2.14 5 83 5.60 18875 34.40% 3775.04 227.41 285.00 57.00

5040 F 61.25 198.00 180.50 -17.50 37.21 33.92 -3.29 6 87 7.17 25344 30.19% 4223.95 291.31 1325.00 265.00

5042 M 71.25 217.60 237.00 19.40 30.22 32.91 2.69 6 51 4.83 35107 46.86% 5851.14 688.37 1110.00 222.00

5044 F 66.25 166.80 172.25 5.45 26.79 27.67 0.88 6 67 4.50 24453 22.46% 4075.47 364.97 2565.00 513.00

5045 M 72.00 231.60 226.00 -5.60 31.50 30.73 -0.76 6 79 4.83 33790 20.90% 5631.60 427.72 1530.00 306.00

5046 F 69.00 175.00 152.00 -23.00 25.91 22.51 -3.41 5 101 7.20 12322 23.05% 2464.37 122.00 3305.00 661.00

5047 M 66.00 196.20 193.75 -2.45 31.75 31.36 -0.40 6 75 5.67 23234 49.19% 3872.34 309.79 2145.00 429.00

5048 M 69.00 208.60 210.50 1.90 30.89 31.17 0.28 6 85 6.50 27520 36.79% 4586.70 323.77 545.00 109.00

5050 F 60.00 170.40 171.00 0.60 33.37 33.49 0.12 6 33 3.67 14858 29.68% 2476.35 450.24 1335.00 267.00

5051 F 62.75 169.00 195.00 26.00 30.26 34.91 4.66 6 55 4.00 26239 21.96% 4373.16 477.07 1390.00 278.00

5052 F 66.00 154.80 171.00 16.20 25.05 27.68 2.62 5 43 3.80 24065 24.12% 4813.03 559.66 780.00 156.00

5053 F 65.00 158.60 144.50 -14.10 26.46 24.11 -2.35 6 64 6.67 16810 32.18% 2801.72 262.66 1605.00 321.00

5054 M 71.00 195.40 182.00 -13.40 27.33 25.45 -1.87 6 46 3.17 21856 8.46% 3642.64 475.13 3240.00 648.00

5056 F 65.00 177.60 159.00 -18.60 29.64 26.53 -3.10 5 83 7.40 26777 27.66% 5355.34 322.61 635.00 127.00

5058 F 65.00 167.20 162.00 -5.20 27.90 27.03 -0.87 6 86 4.83 22295 27.36% 3715.78 259.24 3495.00 699.00

5060 M 72.00 246.20 255.75 9.55 33.48 34.78 1.30 6 30 3.00 18413 39.83% 3068.76 613.75 480.00 120.00

5061 M 75.00 229.20 228.00 -1.20 28.73 28.58 -0.15 6 94 6.67 33161 9.82% 5526.86 352.78 2175.00 435.00

5062 F 66.00 190.00 169.25 -20.75 30.75 27.39 -3.36 5 71 5.40 24719 29.94% 4943.85 348.16 835.00 167.00

5064 F 64.00 203.00 207.25 4.25 34.94 35.67 0.73 6 41 4.50 11225 44.42% 1870.89 273.79 1228.00 245.60

5066 F 65.25 231.60 238.50 6.90 38.35 39.49 1.14 6 35 3.17 11221 12.66% 1870.12 320.59 45.00 9.00

5067 F 64.25 166.20 147.25 -18.95 28.38 25.15 -3.24 6 33 2.67 12138 2.71% 2022.95 367.81 2880.00 576.00

5069 F 62.00 229.00 244.75 15.75 42.00 44.89 2.89 3 53 6.00 18746 33.84% 6248.63 353.70 905.00 181.00

5070 F 66.00 169.20 151.00 -18.20 27.38 24.44 -2.95 6 86 8.50 22043 37.59% 3673.82 256.31 1600.00 320.00

5073 F 67.50 178.00 179.00 1.00 27.54 27.70 0.15 6 54 4.00 20674 31.56% 3445.72 382.86 1065.00 213.00

5074 F 61.00 136.20 141.00 4.80 25.81 26.71 0.91 6 49 4.00 20356 20.73% 3392.73 415.44 540.00 108.00

60 5075 F 61.50 172.60 163.00 -9.60 32.17 30.38 -1.79 6 58 4.50 14580 26.19% 2429.95 251.37 780.00 156.00

5077 F 63.00 182.00 178.75 -3.25 32.33 31.75 -0.58 6 77 5.33 26207 21.78% 4367.82 340.35 1350.00 270.00

5078 F 66.25 203.00 194.00 -9.00 32.61 31.16 -1.45 5 56 3.40 12751 18.08% 2550.14 227.69 900.00 180.00

5081 F 65.00 224.40 211.00 -13.40 37.44 35.21 -2.24 6 41 3.83 25259 64.28% 4209.76 616.06 420.00 84.00

5082 F 63.25 211.80 197.50 -14.30 37.32 34.80 -2.52 5 56 5.40 28045 43.48% 5609.06 500.81 1090.00 218.00

5083 F 69.00 186.60 185.50 -1.10 27.63 27.47 -0.16 6 118 6.00 29040 20.43% 4840.08 246.11 2295.00 459.00

5086 F 62.30 233.20 238.10 4.90 42.36 43.25 0.89 6 47 3.92 20151 27.71% 3358.49 428.74 3060.00 612.00

5088 F 68.50 168.00 156.50 -11.50 25.24 23.51 -1.73 6 45 4.83 12585 9.76% 2097.58 279.68 430.00 107.50

5097 F 70.25 303.20 312.00 8.80 43.31 44.57 1.26 5 42 3.20 30772 41.86% 6154.49 732.68 120.00 24.00

5099 F 64.50 237.50 238.10 0.60 40.25 40.35 0.10 6 56 4.17 21660 41.19% 3610.04 386.79 665.00 133.00

5105 F 67.25 243.00 251.90 8.90 37.88 39.27 1.39 4 75 6.00 24446 48.22% 6111.49 325.95 540.00 108.00

5106 F 62.50 218.75 231.80 13.05 39.48 41.84 2.36 5 36 3.40 13445 39.53% 2689.02 373.47 546.00 136.50

6002 F 69.25 191.00 202.00 11.00 28.08 29.70 1.62 5 54 4.40 19287 21.21% 3857.49 357.18 2725.00 545.00

6004 F 66.25 272.60 294.30 21.70 43.79 47.27 3.49 4 50 3.50 20787 29.46% 5196.71 415.74 1410.00 282.00

6005 F 63.25 225.60 241.00 15.40 39.76 42.47 2.71 6 48 3.00 24710 10.55% 4118.32 514.79 810.00 162.00

6009 M 67.75 197.40 182.50 -14.90 30.32 28.03 -2.29 5 29 3.60 12630 18.55% 2526.06 435.53 510.00 102.00

6010 M 73.00 274.00 256.50 -17.50 36.25 33.93 -2.32 6 73 4.17 24627 7.66% 4104.58 337.36 1455.00 291.00

6015 F 62.50 220.00 197.30 -22.70 39.71 35.61 -4.10 3 32 4.00 12284 10.01% 4094.69 383.88 1110.00 277.50

6016 M 67.25 231.40 227.00 -4.40 36.07 35.39 -0.69 6 34 3.17 20489 20.80% 3414.88 602.63 470.00 94.00

6017 M 68.25 183.80 185.00 1.20 27.82 28.00 0.18 6 50 5.50 12410 28.96% 2068.36 248.20 3220.00 644.00

6019 M 69.00 204.20 204.00 -0.20 30.24 30.21 -0.03 6 54 3.67 29955 8.59% 4992.50 554.72 2250.00 450.00

6020 M 67.50 204.60 189.00 -15.60 31.66 29.24 -2.41 7 61 5.00 24177 23.32% 3453.85 396.34 3440.00 688.00

6022 F 66.75 218.40 229.40 11.00 34.56 36.30 1.74 5 35 3.60 20781 47.40% 4156.17 593.74 270.00 67.50

6023 M 69.50 246.80 239.75 -7.05 36.02 34.99 -1.03 6 54 4.17 28801 11.86% 4800.14 533.35 30.00 6.00

6024 F 66.75 240.60 242.00 1.40 38.07 38.29 0.22 6 73 5.00 28129 31.05% 4688.11 385.32 800.00 160.00

6028 M 67.25 231.80 226.00 -5.80 36.13 35.23 -0.90 6 63 4.00 25290 9.44% 4215.02 401.43 950.00 190.00

6029 F 62.50 207.20 204.25 -2.95 37.40 36.86 -0.53 7 47 3.57 17018 43.46% 2431.15 362.09 1545.00 309.00

6031 M 72.50 412.50 430.00 17.50 55.33 57.67 2.35 6 60 4.67 29757 44.25% 4959.53 495.95 3045.00 609.00

6032 M 69.50 228.20 219.00 -9.20 33.31 31.96 -1.34 4 50 3.75 26227 36.37% 6556.84 524.55 3193.00 638.60

6034 F 66.00 201.40 206.00 4.60 32.60 33.34 0.74 5 85 5.00 27220 32.36% 5444.09 320.24 975.00 195.00

6036 M 68.50 176.40 168.08 -8.32 26.50 25.25 -1.25 6 65 5.17 18833 17.87% 3138.80 289.74 3345.00 669.00

6037 M 73.00 319.40 292.00 -27.40 42.26 38.63 -3.62 6 47 3.67 18480 33.86% 3080.08 393.20 1345.00 269.00

6040 F 68.50 183.80 181.50 -2.30 27.62 27.27 -0.35 6 64 3.50 20825 26.73% 3470.89 325.40 195.00 39.00

6041 M 68.25 214.50 203.75 -10.75 32.46 30.84 -1.63 6 72 5.83 24634 33.73% 4105.59 342.13 1480.00 370.00

6042 M 64.00 174.20 172.50 -1.70 29.98 29.69 -0.29 4 55 5.00 21051 18.47% 5262.64 382.74 1575.00 393.75

6044 F 62.50 156.00 124.50 -31.50 28.15 22.47 -5.69 6 67 5.50 14881 12.95% 2480.12 222.10 1080.00 216.00

7003 F 66.25 165.60 172.75 7.15 26.60 27.75 1.15 6 36 3.17 15208 48.03% 2534.63 422.44 2770.00 692.50

7006 F 69.25 229.25 230.20 0.95 33.70 33.84 0.14 6 44 3.45 17284 34.15% 2880.60 392.81 0.00 0.00

7008 F 64.50 248.00 254.50 6.50 42.03 43.13 1.10 7 52 3.14 23531 22.59% 3361.51 452.51 350.00 70.00

7009 F 63.00 375.50 336.00 -39.50 66.70 59.68 -7.02 6 37 3.36 27783 28.03% 4630.46 750.89 0.00 0.00

7010 F 62.75 158.00 166.50 8.50 28.29 29.81 1.52 6 72 5.17 23160 35.07% 3859.93 321.66 685.00 171.25

7011 F 66.50 248.00 236.30 -11.70 39.54 37.67 -1.87 4 39 4.00 16560 21.01% 4139.99 424.61 975.00 195.00

7012 M 69.25 224.00 231.10 7.10 32.93 33.97 1.04 2 33 4.00 16438 45.64% 8219.12 498.13 3370.00 674.00

7013 F 66.50 194.50 186.70 -7.80 31.01 29.76 -1.24 6 38 3.83 15747 44.51% 2624.44 414.39 125.00 31.25

8002 F 67.25 346.20 360.00 13.80 53.97 56.12 2.15 5 30 3.80 18976 39.30% 3795.24 632.54 1373.00 274.60

8003 F 61.00 249.80 235.00 -14.80 47.33 44.52 -2.80 4 55 4.00 19070 14.11% 4767.62 346.74 158.00 31.60

8004 M 68.50 199.40 203.25 3.85 29.96 30.54 0.58 7 60 4.86 22353 38.22% 3193.23 372.54 3030.00 606.00

8005 M 72.00 292.40 288.00 -4.40 39.77 39.17 -0.60 6 58 4.50 31767 24.07% 5294.48 547.71 1135.00 227.00

8011 F 65.00 194.20 190.25 -3.95 32.40 31.75 -0.66 4 68 6.25 17477 28.11% 4369.14 257.01 1110.00 222.00

8012 M 74.00 223.20 226.75 3.55 28.74 29.19 0.46 4 47 3.75 23848 17.82% 5962.12 507.41 540.00 108.00

8013 M 69.00 217.00 225.00 8.00 32.13 33.32 1.18 10 56 3.40 29270 55.21% 2926.96 522.67 785.00 157.00

8015 M 69.25 186.50 172.90 -13.60 27.42 25.42 -2.00 6 61 5.67 28765 22.02% 4794.10 471.55 2760.00 552.00

61 8016 M 74.50 328.50 316.00 -12.50 41.73 40.14 -1.59 6 93 6.33 37127 45.68% 6187.87 399.22 90.00 18.00

8019 M 71.25 196.80 200.25 3.45 27.33 27.81 0.48 6 54 5.17 26586 23.60% 4430.92 492.32 990.00 198.00

8021 M 68.50 276.90 258.40 -18.50 41.60 38.82 -2.78 6 83 5.50 32999 33.10% 5499.90 397.58 670.00 346.80

8022 M 69.00 185.60 183.75 -1.85 27.48 27.21 -0.27 6 42 5.00 16600 45.75% 2766.66 395.24 2470.00 617.50

8024 M 65.00 222.00 231.00 9.00 37.04 38.55 1.50 6 65 4.67 24518 22.66% 4086.36 377.20 1490.00 298.00

8028 M 73.00 252.00 236.90 -15.10 33.34 31.34 -2.00 6 67 4.83 21867 30.04% 3644.46 326.37 1275.00 255.00

8032 M 74.00 376.25 341.00 -35.25 48.44 43.90 -4.54 5 36 4.40 14084 29.48% 2816.78 391.22 2505.00 626.25

8033 M 69.50 214.20 216.90 2.70 31.26 31.66 0.39 4 73 5.25 27968 39.23% 6992.12 383.13 1045.00 209.00

8034 M 70.75 235.00 244.60 9.60 33.10 34.45 1.35 4 43 4.25 19636 63.88% 4908.89 456.64 1637.00 327.40

8037 M 67.50 182.00 181.60 -0.40 28.16 28.10 -0.06 6 98 8.50 22413 13.75% 3735.56 228.71 3015.00 603.00

8038 M 72.00 247.30 245.75 -1.55 33.63 33.42 -0.21 6 107 6.50 29563 20.12% 4927.10 276.29 1610.00 264.40

8042 M 70.50 198.60 188.00 -10.60 28.17 26.67 -1.50 5 45 3.80 24170 35.37% 4834.07 537.12 1072.00 214.40

8043 M 74.00 255.00 258.75 3.75 32.83 33.31 0.48 6 66 4.50 30354 15.56% 5058.95 459.90 2020.00 505.00

11003 F 64.25 172.60 158.60 -14.00 29.48 27.09 -2.39 5 57 4.20 18636 25.32% 3727.26 326.95 1205.00 241.00

12001 F 65.25 239.80 230.90 -8.90 39.71 38.23 -1.47 6 58 4.00 33939 31.92% 5656.54 585.16 1215.00 243.00

12005 F 66.25 272.20 291.50 19.30 43.72 46.82 3.10 2 13 3.00 5183 21.95% 2591.35 398.67 555.00 111.00

12006 F 66.25 320.60 328.20 7.60 51.50 52.72 1.22 5 46 4.80 8816 20.27% 1763.26 191.66 150.00 30.00

12009 F 64.25 223.60 229.00 5.40 38.19 39.11 0.92 6 38 2.67 20409 13.61% 3401.45 537.07 150.00 30.00

12011 F 62.25 232.60 204.50 -28.10 42.32 37.21 -5.11 6 35 2.92 15873 25.27% 2645.44 453.50 385.00 77.00

12013 F 65.25 189.60 174.30 -15.30 31.40 28.86 -2.53 2 52 3.50 13629 23.58% 6814.40 262.09 390.00 78.00

12020 F 65.25 258.30 250.10 -8.20 42.77 41.41 -1.36 6 52 3.67 25299 47.22% 4216.42 486.51 120.00 40.00

12021 F 65.50 218.50 203.00 -15.50 35.91 33.36 -2.55 5 40 3.40 15094 26.39% 3018.87 377.36 360.00 90.00

12023 F 67.25 205.50 194.50 -11.00 32.03 30.32 -1.71 6 50 4.75 19301 36.21% 3216.90 386.03 1740.00 348.00

13001 F 66.25 223.25 246.25 23.00 35.86 39.55 3.69 4 50 4.50 19974 15.23% 4993.61 399.49 860.00 172.00

13003 F 60.00 230.00 235.40 5.40 45.04 46.10 1.06 5 35 3.40 10526 31.16% 2105.13 300.73 335.00 67.00

13006 F 66.25 202.25 201.20 -1.05 32.49 32.32 -0.17 6 63 4.67 21777 29.76% 3629.50 345.67 405.00 81.00

13007 F 65.25 286.25 285.00 -1.25 47.40 47.19 -0.21 4 38 3.00 15803 22.09% 3950.84 415.88 225.00 45.00

13008 F 67.25 195.00 196.60 1.60 30.40 30.65 0.25 2 22 3.00 8089 51.74% 4044.30 367.66 2355.00 471.00

13009 F 65.25 241.25 257.60 16.35 39.95 42.66 2.71 4 49 3.75 16372 16.14% 4092.89 334.11 1150.00 230.00

13012 F 64.25 176.80 166.80 -10.00 30.19 28.49 -1.71 6 67 5.50 18023 31.26% 3003.76 268.99 2095.00 419.00

13013 F 61.25 322.80 329.80 7.00 60.66 61.98 1.32 6 75 5.17 32993 43.34% 5498.87 439.91 255.00 51.00

13014 F 58.50 159.50 147.50 -12.00 32.86 30.39 -2.47 4 50 4.25 13170 30.38% 3292.47 263.40 775.00 155.00

13015 F 64.25 209.00 225.00 16.00 35.69 38.43 2.73 5 29 3.22 12312 11.81% 2462.50 424.57 600.00 120.00

13020 F 63.25 192.40 201.10 8.70 33.91 35.44 1.53 4 60 4.75 15976 16.58% 3993.95 266.26 590.00 118.00

13023 F 64.25 187.40 204.75 17.35 32.00 34.97 2.96 5 70 5.40 19962 24.11% 3992.48 285.18 195.00 39.00

13024 F 62.50 232.00 227.75 -4.25 41.87 41.10 -0.77 3 46 4.33 15816 36.64% 5272.11 343.83 910.00 182.00

13025 M 70.25 231.00 268.25 37.25 33.00 38.32 5.32 8 72 4.38 26403 37.98% 3300.38 366.71 2190.00 438.00

13027 F 67.25 281.30 277.50 -3.80 43.85 43.26 -0.59 7 45 3.00 20738 28.31% 2962.57 460.84 750.00 150.00

13029 F 62.50 292.50 340.00 47.50 52.79 61.36 8.57 7 52 3.57 22580 31.26% 3225.65 434.22 380.00 76.00

13031 F 64.50 183.75 195.00 11.25 31.14 33.04 1.91 6 41 3.50 13750 4.70% 2291.61 335.36 660.00 132.00

13034 F 65.00 214.25 214.80 0.55 35.75 35.84 0.09 6 61 3.50 16559 12.60% 2759.75 271.45 2270.00 454.00

13038 F 60.50 146.00 151.00 5.00 28.12 29.08 0.96 7 54 4.50 24567 20.23% 3509.52 454.94 120.00 30.00

13040 F 59.00 259.75 276.70 16.95 52.61 56.04 3.43 4 42 3.25 10736 20.24% 2684.00 255.62 1545.00 309.00

13042 F 63.00 221.00 211.00 -10.00 39.26 37.48 -1.78 6 99 6.60 26039 11.79% 4339.79 263.02 620.00 124.00

13044 M 71.25 260.00 253.80 -6.20 36.11 35.25 -0.86 4 48 4.25 22421 46.51% 5605.22 467.10 1890.00 378.00

13045 M 70.25 207.25 187.10 -20.15 29.61 26.73 -2.88 4 38 4.00 21262 38.12% 5315.43 559.52 1095.00 273.75

13047 F 60.50 167.25 171.20 3.95 32.21 32.97 0.76 4 41 3.50 18295 38.92% 4573.64 446.21 2650.00 530.00

13053 F 64.25 202.00 240.00 38.00 34.50 40.99 6.49 3 41 5.00 18442 27.94% 6147.38 449.81 391.00 78.20

13054 F 62.50 173.00 186.20 13.20 31.22 33.61 2.38 5 74 6.60 18103 12.31% 3620.55 244.63 2285.00 457.00

13055 F 62.50 234.00 235.70 1.70 42.23 42.54 0.31 4 43 3.25 14813 13.44% 3703.17 344.48 555.00 111.00

13056 F 64.50 196.25 197.00 0.75 33.26 33.38 0.13 2 53 7.00 16034 10.59% 8017.07 302.53 200.00 40.00

13059 F 64.25 193.25 186.20 -7.05 33.00 31.80 -1.20 5 53 4.20 20101 41.99% 4020.25 379.27 980.00 196.00

62 13061 F 60.25 164.25 165.40 1.15 31.90 32.12 0.22 5 44 3.60 18067 31.52% 3613.47 410.62 400.00 100.00

13066 M 68.50 262.00 267.20 5.20 39.36 40.15 0.78 6 43 3.33 18682 16.64% 3113.65 434.46 560.00 112.00

13068 F 65.50 197.00 190.70 -6.30 32.37 31.34 -1.04 4 54 5.50 14587 14.23% 3646.74 270.13 1545.00 309.00

13071 F 65.00 182.25 195.00 12.75 30.41 32.54 2.13 6 68 4.67 17379 24.94% 2896.47 255.57 1210.00 242.00

13072 F 63.25 217.00 197.70 -19.30 38.24 34.84 -3.40 4 49 3.50 13345 27.47% 3336.27 272.35 790.00 158.00

13073 F 64.25 215.00 214.60 -0.40 36.72 36.65 -0.07 6 61 5.17 18143 16.05% 3023.88 297.43 540.00 135.00

13076 F 67.25 284.00 291.00 7.00 44.27 45.36 1.09 6 76 5.07 22689 25.75% 3781.57 298.54 1695.00 339.00

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