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The effects of weight self-monitoring on weight change, body mass index, and waist circumference during a worksite weight loss program

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Running head: THE EFFECTS OF WEIGHT SELF-MONITORING
The Effects of Weight Self-Monitoring on Weight Change, Body Mass Index, and Waist
Circumference during a Worksite Weight Loss Program
Submitted to the Department of Physical Education of Kean University in Partial Fulfillment of
the Requirements of the Degree of Masters of Science
Michelle A. Sadlowski
Advisor: Walter Andzel, Ph.D.
Kean University, Union, NJ
Faculty Advisor________________________________ Date_______________________
UMI Number: 1479302
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a note will indicate the deletion.
UMI 1479302
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The Effects of Weight Self-Monitoring ii TABLE OF CONTENTS
List of Tables
v
Acknowledgements
vii
Abstract
viii
Chapter
1.Introduction
1
Statement of the Problem
1
Purpose of the Study
3
Hypotheses
4
Scope of the Study
4
Delimitations
5
Limitations
5
Operational Definitions
6
2.Review of Literature
7
Obesity in the United States
7
Health Promotion Programs
9
Weight Monitoring
12
Weight monitoring during weight loss
13
Weight monitoring during weight maintenance
15
3.Method
18
Participants
18
Apparatus
18
Procedure
19
The Effects of Weight Self-Monitoring iii Stimuli
4.Results
Descriptive Data of the Sample by Treatment Group
20
21
21
Initial descriptive data
21
Final descriptive data
23
Post-Intervention Results by Treatment Group
24
ANOVA Results for %Weight Change, %BMI Change, %WC Change by Treatment
Group
Descriptive Data of the Sample by Gender
26
29
Initial descriptive data
29
Final descriptive data
32
Post-Intervention Results by Gender
34
ANOVA Results for %Weight Change, %BMI Change, %WC Change by Gender
37
Survey Results
39
Pre-treatment survey
39
Post-treatment survey
40
5.Discussion
46
References
53
Appendices
59
A.Recruitment email
59
B.Consent to participate in a research study
60
C.Pre- and Post-Treatment Survey
65
D.Debriefing Form
67
E.Week 1 email
68
The Effects of Weight Self-Monitoring iv F.Week 2 email
69
G.Week 3 email
70
H.Week 4 email
71
I.Week 5 email
72
J.Week 6 email
73
K.Week 7 email
74
L.Week 8 email
75
M.Week 9 email
76
The Effects of Weight Self-Monitoring v
LIST OF TABLES
Table 1. Initial Descriptive Data of Participants: Mean and Standard Deviation
Values
22
Table 2. Initial Descriptive Data of Participants Combined: Mean and Standard
Deviation Values
22
Table 3. Final Descriptive Data of Participants: Mean and Standard Deviation
Values
23
Table 4. Final Descriptive Data of Participants: Combined Mean and Standard
Deviation Values
24
Table 5. Mean and Standard Deviation Values for %Weight Change, %BMI
Change, and % WC Change
25
Table 6. Combined Mean and Standard Deviation Values for %Weight
Change, %BMI Change, and %WC Change
25
Table 7. ANOVA Comparing %Weight Change between Treatment Groups
26
Table 8. Fisher LSD Post Hoc Test Results for %Weight Change
27
Table 9. ANOVA Comparing %WC Change between Treatment Groups
28
Table 10. Fisher LSD Post Hoc Test Results for %WC Change
28
Table 11. ANOVA Comparing Mean %BMI Change between Treatment
Groups
29
Table 12. Initial Descriptive Data of Males by Treatment Group: Mean and
Standard Deviation Values
31
Table 13. Initial Descriptive Data of Females by Treatment Group: Mean and
Standard Deviation Values
31
Table 14. Initial Descriptive Data of Males and Females: Combined Mena and
Standard Deviation Values
32
Table 15. Final Descriptive Data of Males by Treatment Group: Mean and
Standard Deviation Values
33
Table 16. Final Descriptive Data of Females by Treatment Group: Mean and
Standard Deviation Values
33
The Effects of Weight Self-Monitoring vi
Table 17. Final Descriptive Data of Males and Females: Combined Mean and
Standard Deviation Values
34
Table 18. Mean and Standard Deviation Values for %Weight Change, %BMI
Change, and %WC Change in Male Participants by Treatment Group
35
Table 19. Mean and Standard Deviation for %Weight Change, %BMI Change,
and %WC Change in Female Participants by Treatment Group
36
Table 20. Combined Mean and Standard Deviation for %Weight Change,
%BMI Change, and %WC Change in Male and Female Participants
36
Table 21. ANOVA Comparing %Weight Change between Genders
37
Table 22. Fisher LSD Post Hoc Test Results for %Weight Change between
Genders
38
Table 23. ANOVA Comparing %WC Change between Genders
38
Table 24. ANOVA Comparing Mean %BMI Change between Genders
39
Chart 1. Group A Pre- and Post-Treatment Survey Results
43
Chart 2. Group B Pre- and Post-Treatment Survey Results
44
Chart 3. Group C Pre- and Post-Treatment Survey Results
45
The Effects of Weight Self-Monitoring
vii
Acknowledgements
I am most appreciative of my thesis advisor, Dr. Walter Andzel, and Dr. Joshua Palgi, whose
knowledge, dedication to research, and mentorship made all aspects of my graduate training,
including the completion of this master’s thesis, rewarding and enjoyable. Dr. Wolde Woubneh
of the Kean University Statistics Department deserves appreciation not only for his thoughtful
assistance with the statistical analysis of my data, but also for generously offering his time and
expertise. William McLaughlin, Ph.D., and Janice McHugh, Ph.D., made important suggestions
that improved the study design and offered guidance and support throughout my research. I am
deeply indebted to my colleagues Robin Gara, Megan Waszaj, Chris Hamerschlag, Renee
Finelli, Ingrid Wollmer, Neha Reyes, Risa Levine, and Cathy Colello for their assistance with
data collection and their willingness to help this research become a reality. Many thanks to
Shean Wang, Ph.D., who shared valuable advice based on his own extensive research
experience. Finally, thank you to my friends and family, your love and encouragement have been
a special blessing.
The Effects of Weight Self-Monitoring
viii
Abstract
Obesity is a significant economic and public health concern in the United States today. Over
half of the population is overweight and over a third are considered obese. Worksite health
promotion programs with a focus on weight loss are becoming a cost-effective way to decrease
employers’ healthcare expenses. This study evaluated the effects of different frequencies of
weight self-monitoring on % weight change, % Body Mass Index (BMI) change, and % waist
circumference (WC) change among 77 pharmaceutical company employees during a nine week
worksite weight loss program. After initial measurements of age, height, weight, BMI, and WC
were taken, participants were classified into three study groups based on worksite location.
Group A (n=31) weighed weekly, Group B (n=25) weighed semi-weekly, and Group C (n=21)
weighed at week 1 and week 9 only. Upon completion of the nine weeks, final body weight,
BMI, and WC measurements were taken. Data were analyzed using an analysis of variance and
Fisher’s Least Significant Difference Post Hoc test to determine whether significant differences
in % weight change, % BMI change, and % WC change existed among the three treatment
groups. Significant differences were found in % weight change (p=.001) and % WC change
(p=.03). No significant difference was found in % BMI change. Groups A and B had the greatest
reduction in body weight and Group B had the greatest reduction in WC. No significant
differences in % weight change, % BMI change, or % WC changes between genders were
shown. Further research is warranted among different types of worksite facilities and using
larger populations.
Keywords: Body Mass Index, waist circumference, worksite health promotion
The Effects of Weight Self-Monitoring
1
Chapter 1 - Introduction
Statement of the Problem
Employers seeking proactive solutions to rising healthcare costs are using wellness
programs to improve the health of their employees. These workplace programs focus on
reducing health risks associated with poor eating habits, inactivity, overweight and obesity,
tobacco use, chronic stress, and other unhealthy behaviors. The increasing prevalence of obesity
in the United States has become a national concern for employers. Obese individuals spend
about 36% more on health services and 77% more on medications than non-obese individuals
according to studies by Strum (2002) and the USDHHS (2002). Successful health promotion
programs usually incorporate three major components of effective weight management: calorie
restriction, physical activity, and behavior modification (i.e. self-monitoring, stimulus control,
social support, and stress management) (Foreyt, 2007). The purpose of this research was to
study the effectiveness of self-monitoring, specifically regular weight self-monitoring, on
reducing body weight, body mass index (BMI) and waist circumference (WC) during a worksite
weight loss program.
Behavioral modification has been identified as a critical element of successful weight
management. Research on self-monitoring has focused primarily on recording food intake,
eating behaviors, and physical activity. Daily self-monitoring of these important behaviors has
been emphasized as a useful tool for weight control (Foster et al., 1997). Weight self-monitoring
can also be a valuable form of behavior modification. However, the most effective frequency of
monitoring during weight loss has not been established. Research that focuses specifically on
weight monitoring and its effect on the weight loss phase in worksite health promotion programs
The Effects of Weight Self-Monitoring
2
is limited. It is interesting to note though that self-assessment of body weight on a daily basis is
not widely accepted and recommended in weight control programs (Linde et al., 2005). Many
clinical programs recommend self-weighing only weekly, and public health recommendations
for weight control developed by the U.S. Department of Agriculture and the Centers for Disease
Control do not recommend self-weighing at all
(http://www.nhlbi.nih.gov/health/public/heart/obesity/lose_wt/behavior.htm). The reasoning
behind the USDA’s recommendation is that today's weight is not a true measure of how well one
has followed their program yesterday, since the body's water weight will change much more
from day to day than fat weight, and water changes are often the result of things that have
nothing to do with weight-management efforts.
In general, there is no consensus on how often one should weigh himself or herself while
actively losing weight. However, it seems to be a more commonly recommended form of
behavior modification during weight maintenance. Wing et al. (2006) found that a selfregulation program based on daily weighing improved the maintenance of weight loss as
compared to a control group. However, controversy still exists as noted by Linde et al. (2005)
who found that daily weighing is valuable to individuals trying to lose weight or prevent weight
gain. It is important to realize that daily weighing can be a time consuming and labor intensive
process during a worksite weight loss program because the employees managing the program
must track all of the daily weights of each individual. It would be more reasonable to weigh
participants less often, such as weekly or semi-weekly, if similar results could be achieved. This
study attempted to understand the most effective weight monitoring frequency by comparing
three different operating companies of an undisclosed pharmaceutical company participating in
the same worksite weight loss program.
The Effects of Weight Self-Monitoring
3
Purpose of the Study
The purpose of this research was to study the effectiveness of regular weight monitoring
on reducing body weight, BMI, and waist circumference during a nine week worksite weight loss
program. The study focused specifically on the potential differences in reduction of weight, BMI
and WC among three different groups of participants in the same weight loss program: those
required to weigh-in weekly, those required to weigh in every other week (i.e. semi-weekly), and
those required to weigh-in once at the beginning and once at the end of the nine week program.
The Effects of Weight Self-Monitoring
4
Hypotheses
Based on a review of the current literature, this study tested the following hypotheses:
1. The participants who are required to weigh themselves weekly will experience a more
significant reduction in weight (% weight loss) than those who are not required to weigh
themselves semi-weekly or once at the beginning and end of the nine week weight loss
program.
2. The participants who are required to weigh themselves weekly will experience a more
significant reduction in waist circumference (WC) than those who are not required to
weigh themselves semi-weekly or once at the beginning and end of the nine week weight
loss program.
3. The participants who are required to weigh themselves weekly will experience a more
significant reduction in body mass index (BMI) than those who are not required to weigh
themselves semi-weekly or once at the beginning and end of the nine week weight loss
program.
Scope of Study
Research is limited on workplace weight loss programs that compare the successes of
weekly weight monitoring to monitoring less often. Based on the results of this study, on-site
health promotion programs may be able to develop more successful weight loss programs using
improved weight monitoring guidelines.
The Effects of Weight Self-Monitoring
5
Delimitations
This study was delimited to:
1. Current employees of an undisclosed pharmaceutical corporation who are located at one
of three different operating companies located in New Jersey.
2. Current employees of an undisclosed pharmaceutical corporation who have volunteered
for said weight loss program and consented to participating in the study.
3. Participants with body mass index >/= 18.5 kg/m2 and who are not currently pregnant.
Limitations
This study was limited by the following:
1. Participants may not adhere fully to the weight monitoring protocol of their operating site
due to traveling, holidays, sick days, forgetfulness, or other unforeseen circumstances.
2. Participants are not required to follow a specific diet or physical activity program while
involved in this study. This may account for some variability in weight loss results.
3. The entire sample of participants will be selected from an undisclosed pharmaceutical
corporation located in central New Jersey, which limits the ability to generalize the data
to other worksite populations and the general population.
The Effects of Weight Self-Monitoring
6
Operational Definitions
Behavioral modification: the use of various techniques to improve an individual’s behavior.
Behavioral modification techniques for weight management include self-monitoring, stimulus
control, stress management, and social support (Foreyt, 2007).
Body mass index (BMI): a number calculated from a person's weight and height (kg/m2). BMI
provides a reliable indicator of body fatness for most people and is used to screen for weight
categories that may lead to health problems (www.cdc.gov).
Overweight: categorized as having a BMI of 25 – 29.9 kg/m2 (www.cdc.gov).
Obesity: categorized as having a BMI of >/= 30 kg/m2 (www.cdc.gov).
Waist circumference: a high-risk waist circumference is categorized as a man with waist
measurement over 40 inches (102 cm) or a woman with waist measurement over 35 inches (88
cm) (www.cdc.gov).
The Effects of Weight Self-Monitoring
7
Chapter II – Review of Literature
Obesity is a significant public health concern in the United States today. Over half of the
population is overweight and over a third are considered obese. The economic impact of
overweight and obesity has led many employers to offer health promotion programs in an
attempt to decrease rising healthcare costs. Not all workplace health promotion programs that
focus on weight reduction are designed the same. Most however include a dietary intervention,
encourage increased physical activity, and promote behavior modifications, such as selfmonitoring, which may have a positive effect on weight control. The purpose of this research
was to study the effectiveness of self-monitoring, specifically regular weight monitoring, on
reducing body mass index (BMI) and waist circumference (WC) during a worksite weight loss
program.
Obesity in the United States
During the past twenty years there has been a dramatic increase in obesity in the United
States. Currently, 68% of the adult population is categorized as overweight and 34% of the adult
population is categorized as obese (http://www.cdc.gov/nchs/fastats/overwt.htm). Obesity is a
serious health concern because it increases the risk of many diseases and health conditions,
including coronary heart disease, Type 2 diabetes, cancers (i.e. endometrial, breast, and colon),
high blood pressure, high total cholesterol, high triglycerides, stroke, liver and gallbladder
disease, sleep apnea and other respiratory problems, osteoarthritis, and gynecological problems
(i.e. abnormal menses and infertility) (http://www.cdc.gov/nccdphp/dnpa/obesity/index.htm).
The accepted standard used to calculate obesity is the BMI, which measures weight in
relation to height. According to the National Institutes of Health (NIH) Clinical Guidelines,
The Effects of Weight Self-Monitoring
8
overweight is defined as an adult who has a BMI between 25.0 - 29.9 kg/m2 and obesity is
defined as an adult who has a BMI of greater than or equal to 30 kg/m2. There are some
limitations associated with BMI that are important to mention. This standard of measurement
can overestimate body fat in muscular individuals (Mathews et al., 2008), such as weightlifters,
and it can underestimate body fat in individuals who have lost a large amount of muscle tissue,
such as the elderly and those who are malnourished (Alley et al., 2008). Despite these
limitations, BMI is a commonly used assessment of obesity because it is simple to calculate,
does not require any specialized equipment, and is non-invasive.
Recently, there has been some positive research published by the Centers for Disease
Control (CDC) indicating no significant increase in obesity prevalence between 2003-2004 and
2005-2006 for either men or women (Ogden et al., 2007). However, the numbers are still high as
indicated in the latest National Health and Nutrition Examination Survey (NHANES), which
shows that the prevalence of obesity among adult men was 33.3% and 35.3% among adult
women in 2005-2006 (Ogden et al., 2007). There is still a significant amount of work that needs
to be done in this country to result in a downward trend. Current obesity statistics are more than
double the Healthy People 2010 goal of reducing the prevalence of overweight and obesity
among adults to less than 15% (USDHHS).
BMI is just one indicator of potential health risks associated with being overweight or
obese. For assessing someone’s likelihood of developing overweight- or obesity-related diseases,
the National Heart, Lung, and Blood Institute guidelines recommend looking at other predictors,
such as WC (http://www.cdc.gov/nccdphp/dnpa/obesity/defining.htm). There is a higher risk of
developing obesity-related conditions in a man whose WC is more than 40 inches (101.6 cm) and
The Effects of Weight Self-Monitoring
9
in a non-pregnant woman whose WC is more than 35 inches (88.9 cm). Adipose tissue,
particularly from visceral fat deposits, secretes potential mediators in the development of chronic
diseases (Haslam and James, 2005). This process may explain why Pischon et al (2008) found
that abdominal fat distribution was related to risk of death independently of BMI. They also
found that body mass is more closely related to the amount of visceral fat in men than in women,
which may be among the reasons that, among those with a high BMI, the relative risk of death
was greater for men than for women.
The National Institutes of Health (NIH) recommends weight loss for overweight people
with a high WC or with two or more risk factors for cardiovascular disease and other
comorbidities, such as high blood pressure, high cholesterol, or Type II diabetes (NIH, 1998).
The NIH suggests a reduction of 10% in total body weight as an initial goal, but even a more
modest weight loss of between 5% to 10% has been shown to significantly reduce the risk of
heart disease and stroke (Krauss et al., 2000). Furthermore, the decreased levels of glucose,
insulin, glycated hemoglobin, triglycerides, LDL cholesterol, blood pressure, and increased
levels of HDL cholesterol and quality of life associated with a modest weight loss will remain as
long as the weight loss is maintained (Foreyt, 2007).
Health Promotion Programs
Unfavorable changes in the worksite environment, such as desk jobs, unhealthy cafeteria
food, vending machines, and long sedentary commutes, may have significantly contributed to the
obesity problem. Most jobs have transitioned from heavy manual labor to sedentary desk jobs
over the past century. Furthermore, the activities of daily living performed outside of work have
been transformed from highly physical duties to predominantly technology-powered tasks
The Effects of Weight Self-Monitoring
10
involving little to no physical exertion. The transition from a physically demanding environment
to a mechanically-powered environment has been a main contributor to the significant decrease
in physical activity (Engbers et al., 2008). This new environment we currently live in can be
referred to as an “obesigenic” environment (Swinburn & Egger, 2004) where the ability to make
healthy decisions has become more and more difficult and more importantly, not obvious for the
majority of people (Engbers et al., 2008). On the other hand, the workplace can be a favorable
setting to attempt healthy lifestyle and behavior changes among employees because a large
proportion of the population can be accessed and workers spend a large portion of their waking
hours at the office (Engbers et al., 2008).
Worksite health promotion has been defined as the combined efforts of employers,
employees, and society to improve the health and well-being of people at work (http://www.enwhp.org/workplace-health-promotion.html). According to the World Health
Organization, the workplace has been established as one of the priority locations for health
promotion into the 21st century because it influences physical, mental, economic, and social
well-being and offers an ideal setting and infrastructure to support the health promotion of a
large audience (http://www.who.int/occupational_health/topics/workplace/en/index1.html).
Employers are seeking proactive solutions to rising healthcare costs, using wellness
programs that target obesity to improve the health of their employees. These programs can be as
simple as improving the vending machine selections or as complex as offering sophisticated
weight management programs through employees’ health insurance plans. Due to the increasing
prevalence of obesity in the United States it has become a national concern for employers.
According to Clark (2008), Blue Cross Blue Shield of Massachusetts found that with every 1%
increase of BMI, an employee’s yearly health care costs increase on average by $120. It has been
The Effects of Weight Self-Monitoring
11
estimated that an obese individual will pay $10,000 more than a normal weight individual for
lifetime medical costs related to diabetes, heart disease, hypertension, high cholesterol, and
stroke. A ten percent reduction in total body weight in an obese individual could reduce these
medical costs in the range of $2,200 to $5,300 (Battacharya & Sood, 2004). On average, obese
individuals spend about 36% more on health services and 77% more on medications than nonobese individuals according to studies by Strum (2002) and the USDHHS (2002). Obesity adds
to the rising cost of health insurance rendering insurance less affordable to employers and
employees (Gabel et al., 2009). A reduction in body weight, even a modest ten percent loss, can
have a significant impact on healthcare costs.
Not only is it important to consider the healthcare savings of weight loss, but
there are other significant economic consequences as well. For instance, there is a decrease of
total lifespan and total years of quality life (Lancet, 2009). So the overall amount of productive
years as a member of the workforce decreases with excessive weight. Also, obese individuals
are more likely to have chronic health problems, which correlate into increased absenteeism and
disability claims (Finkelstein et al., 2005). According to Gabel et al. (2009), employers and
employees agree that weight management programs in the workplace are appropriate and
effective. Additionally, they found that employers connected the appropriateness of these
programs with their concern about medical claims expenses, sickness and disability expenses,
and lost productivity. Even though employers believe workplace weight management programs
are appropriate, they also believe that they are not the only stakeholders that should be
addressing the obesity problem. Other responsible parties in no particular order include the
employees themselves, physicians, health insurers, the food and beverage industry, and the
government (Gabel et al.). The rising levels of obesity are a public health concern, which needs
The Effects of Weight Self-Monitoring
12
to be dealt with in the both the government and private sectors in order to provide the attention
and funds necessary to make an impact.
Weight Monitoring
Regular self-weighing has been a focus of attention recently in the obesity literature and
has been reported as a weight management strategy in population surveys (McGuire et al., 1998;
McGuire et al., 1999). It has received conflicting endorsement in that some researchers and
practitioners recommend it as a key behavioral strategy for weight management, while others
caution against its use due to its potential to cause negative psychological consequences
associated with weight management failure (VanWormer et al., 2008). The evidence on frequent
self-weighing for either weight loss or weight maintenance, however, has not yet been
synthesized in the clinical setting, where most of the research has taken place, and even less so in
the worksite setting.
The theoretical rationale for weight monitoring is that self-awareness is a necessary
precursor for self-regulation (Butryn, 2006). Most self-regulation theories consider selfmonitoring, the systemic observation of target behaviors, to be an essential element of selfregulation (Kanfer & Karoly, 1972; Kirschenbaum, 1987). Regular weight self-monitoring may
not reflect accurate measures of total body weight since today’s weight is not a true measure of
how well one has followed a weight management program yesterday. Actually the body's water
weight will change much more from day to day than fat weight, and water changes are often the
result of things that have nothing to do with weight-management efforts (USDA), such as
hormones or sodium intake. However, the act of regular weighing may be effective because it
forces one to remain aware of what he or she is doing to manage their weight. The body of
The Effects of Weight Self-Monitoring
13
evidence on weight self-monitoring is limited, but beginning to expand as more researchers focus
their attention on the importance of behavior modification during weight management. The
research is more in favor of frequent monitoring during maintenance of weight loss than during
the active weight loss phase. Additionally, much of the evidence consists of clinical weight loss
or weight maintenance trials, rather than the less controlled setting of the workplace.
Weight Monitoring During Weight Loss
Regular weighing as a self-monitoring technique has received very little additional attention
from weight control researchers. The available body of evidence appears to be conflicted on the
benefit of regular weight self-monitoring during active weight loss. Some studies strongly
support weight monitoring (Linde, Jeffery, French, Pronk, & Boyle, 2005) whereas others note
the possible detrimental effects (Ogden & Whyman, 1996). Weight control literature indicates
that self-monitoring, in general, is central to the behavioral modifications necessary for weight
loss (Wing, 2004) and that participants who monitor eating and exercise behaviors typically
achieve better weight losses than those who do not monitor (Wadden & Letizia, 1992). As
nutrition and physical activity recommendations form the core of most behavioral weight control
programs (Wing, 2004), individuals who are willing to engage in and monitor these behaviors to
control their weight may be more likely to accept additional messages about regular weighing for
the purpose of regular weight monitoring as well (Linde et al, 2005). Although most studies
focus primarily on daily or weekly weights, the most effective frequency of weighing has not
been established.
For obese participants enrolled in a weight loss study more frequent weight selfmonitoring at baseline was associated with lower dietary fat intake (Linde et al., 2005). At 12
The Effects of Weight Self-Monitoring
14
and 24 months of the study, regular weight self-monitoring was associated with greater weight
loss. Self-weighing was associated with other healthy behaviors such as improved eating habits,
getting more exercise, and not smoking. However, self-weighing did have an independent effect
on weight change, as evidenced by results that did not change when behavioral covariates (i.e.
walking and fat intake) were added to the statistical models (Linde et al., 2005). Another study
by Qi & Dennis (2000) supports the effectiveness of self-weighing compared with other
behavioral modifications used in weight loss regimens. The results indicated that careful selfmonitoring of food intake was the best predictor of the amount of weight loss, but daily weighing
and keeping a record of these results were the next most important factors (Qi & Dennis).
Despite the positive effect of regular weighing on the amount of weight lost, there is
some concern that it may have a negative psychological and behavioral impact. Attention
focused on one's current, and presumably undesirable, body size can be motivating for those who
want to modify a pattern of unhealthful behaviors. For others, this feedback may result in
psychological distress and could lead to outcomes that are, in fact, counter to a weight loss
strategy, such as attrition from programs, misreporting of dietary intake, and emotional states
associated with binge eating (Dionne & Yeudall, 2005).
To better understand the potential negative effects of frequent weighing, Ogden &
Whyman (1996) conducted a longitudinal study aimed at examining the effects of daily weighing
on mood, self-esteem, body image, and eating behavior. The participants in the daily weighing
group showed decreased mood in terms of increased levels of anxiety and depression and
lowered self-esteem compared to subjects in the non-weighing group. The effects of repeated
weighing were not related to the subjects' dieting status, but were related to their actual weight
change. The results from this study suggest that weighing may not be as benign a practice as
The Effects of Weight Self-Monitoring
15
often assumed and may result in psychological deterioration (Ogden & Whyman). It is
important to note that these participants were all of normal weight. Consequently, daily
weighing may not have had the same psychological effect in overweight or obese participants.
Overall, current evidence supports the use of regular weight self-monitoring during
weight loss. Evidence from clinical weight control trials suggests that more frequent weighing is
associated with greater weight loss. Daily and weekly weights were the most common
interventions applied. Weekly weighing and daily weighing were both successful for weight loss
in clinical trials. It should be noted that these studies used BMI as an indicator of weight loss and
did not assess WC. There is limited research available focusing specifically on the impact of
semi-weekly weights, or less frequent weighing, on weight loss in the clinical or workplace
setting.
Weight Monitoring During Weight Maintenance
The available body of research appears to be more supportive of regular weight selfmonitoring during the weight maintenance phase. A major challenge in the treatment of obesity
is maintenance of weight loss. Weight-loss programs involving diet, exercise, and behavior
modification produce initial weight losses of approximately 10%, resulting in clinically
important health benefits (Wing, 2004; Knowler et al., 2002). However, most dieters regain
about one third of the weight lost during the next year and are typically back to baseline in 3 to 5
years (Wadden & Phelan, 2002).
Although that is not always the case according to the data compiled over the past 15 years
by the National Weight Control Registry (NWCR). The NWCR is the largest prospective
investigation of successful long-term weight loss maintenance. Their data indicate that more than
The Effects of Weight Self-Monitoring
16
75% of their participants weigh themselves regularly. Specifically, 44% weigh themselves at
least once a day and an additional 33% weigh themselves at least once a week (Phelan et al.,
2003). Since this data was not experimentally derived, it is possible that weight self-monitoring
is related to weight maintenance because it correlates individual differences in motivation with
improved weight control.
Evidence from weight control trials suggests that higher weighing frequency is associated
with less weight regain. According to Wing et al. (2006), daily weighing improved maintenance
of weight loss, particularly when delivered face to face. Weighing in person may have increased
participant accountability. Their study found that a self-regulation program based on daily
weighing improved maintenance of weight loss compared to a control group. Daily selfweighing increased in both intervention groups and was associated with a decreased risk of
regaining 2.3 kg or more. Another study by Linde, Jeffery, French, Pronk, & Boyle (2005)
found that for overweight individuals participating in a weight gain prevention study, more
frequent weight self-monitoring at baseline was associated with lower dietary fat intake. At 12
and 24 months of the study, regular weight self-monitoring was associated with less weight gain
and greater weight loss.
There has been some concern that regular self-weighing, especially daily weighing, may
have a detrimental psychological effect on participants during the weight loss phase (Ogden &
Whyman). This does not appear to be the case with weight loss maintenance. The research on
the effects of self-weighing on BMI among overweight adults with or without depression
indicated that higher self-weighing frequency and negative depression status were independently
associated with lower BMI, with no interaction observed between depression and self-weighing.
The Effects of Weight Self-Monitoring
17
Frequent self-weighing appears to be associated with lower BMI in both depressed and nondepressed overweight women (Linde et al., 2007).
Regular weight self-monitoring may have a less detrimental effect on psychological
status during the maintenance phase than during active weight loss. When someone is new to
weight loss, they have to start making significant lifestyle changes and the expected weight loss
is high. These lifestyle changes and high expectations can be very stressful at first. However,
someone who has lost weight and is now is looking to maintain that weight loss has probably
already instituted important lifestyle changes, such as healthier food choices, portion control,
physical activity, and behavior modification, so the initial stress associated with a lifestyle
change is behind them. This different level in perceived stress may explain why frequent weight
self-monitoring (i.e. daily weighing) appears to have a more detrimental effect on the
psychological status of individuals actively trying to lose weight.
Overall, current evidence supports the use of regular weight self-monitoring during
weight maintenance. Individuals who do weigh themselves more often are more successful at
maintaining a previous weight loss. Daily and weekly weights were the most common
interventions applied. Weekly weighing and daily weighing were both successful for weight
maintenance in clinical trials. Also, it should be noted that these studies used BMI as an
indicator of weight loss and did not assess WC. Finally, there is limited research available
focusing specifically on the impact of semi-weekly weights, or less frequent weighing, on weight
loss maintenance in the clinical or workplace setting.
The Effects of Weight Self-Monitoring
18
Chapter III – Method
Participants
Participants were recruited by voluntarily registering in a nine week worksite weight-loss
program. All participants were recruited via interoffice email (Appendix A), posters, and desk
drops advertising the program. They were all employees of an undisclosed pharmaceutical
company located at three separate locations in central New Jersey. All participants signed an
informed consent form (Appendix B) and completed a pre-treatment survey (Appendix C) upon
initial weigh-in. The participants ranged in age from 20 – 68 years (R = 48). No monetary
incentive was offered to join the study. Participants voluntarily participated in the weight loss
program because of the inducement of a potential weight reduction.
Apparatus
All participants were weighed on digital scales without wearing their shoes. They were
instructed to consistently not wear their shoes while weighing themselves throughout the
program. The following scales were used at each location: Tanita Body Composition Analyzer,
Model # TBF-410 (Group A); Healthometer Weight Tracking Scale, Model # HDM839-53
(Group B); and Weight Watchers digital scale, Model # V17083 (Group C). All participants’
waist circumference (WC) was measured using a retractable tape measure. The participants’ WC
was measured as per NHANES III protocol
(http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=obesity.box.236), which instructs that the
measuring tape be placed in a horizontal plane around the abdomen at the level just above the
uppermost lateral border of the right iliac crest.
The Effects of Weight Self-Monitoring
19
Procedure
All participants who voluntarily registered for the weight loss program received and
signed an informed consent form (Appendix B) and completed a pre-treatment survey (Appendix
C).
All formal communications with participants from this point on were conducted via email
on a company network. All participants were required to have their WC measured during week
one and week nine. WC was measured according to NHANES III protocol by a Wellness
Professional (WP) at each location using a retractable tape measure. All participants stated their
age and height at the initial weigh-in during week one. All participants were weighed on digital
scales and the initial weights were observed and recorded by a WP. All ages, weights, heights,
and WC were kept on an MS Excel spreadsheet, which was stored on a file in a computer at each
location that could only be accessed by a WP using a private login and password. Group A was
required to weigh themselves weekly, Group B was required to weigh themselves every other
week (semi-weekly), and Group C was required to weigh themselves on week one and week nine
only. Participants reported all of their weights to the WP at their work location. At the final
weigh-in during week 9, weights were observed by and WC was measured by a WP at each
location. All participants were required to complete a post-treatment survey (Appendix C) and
were given a debriefing form (Appendix D). Weight self-monitoring may have presented a
potential psychological risk to participants related to not achieving their goal weight and/or not
losing the expected amount of weight.
Upon completion of the nine week program, all MS Excel spreadsheets were collected
from the three locations. The following dependent variables were calculated: % weight change,
The Effects of Weight Self-Monitoring
20
% BMI change, and % WC change. The independent variable was the frequency of weight selfmonitoring. These results were compared among the three groups using the Analysis of Variance
(ANOVA) statistical method. The level of significance was set at p < .05.
Stimuli
Each week an informational email was sent out to all participants providing them with
nutrition, physical activity, and behavioral modification tips to assist them with weight loss
(Appendices E-M). A nutrition lecture was offered to participants at each location. The one hour
lecture covered the following topics: portion control, protein intake during weight loss, fluid
intake, increasing nutritionally dense whole foods (i.e. fruits, vegetables, lean proteins, low fat or
non fat dairy, and whole grains), and eating smaller, more frequent meals. Participants
voluntarily attended this lecture. Group exercise classes were offered to participants in the onsite fitness centers. All participants who attended these exercise classes had been previously
cleared to use the fitness center per protocol of the undisclosed pharmaceutical corporation. The
group classes offered were low-impact aerobic classes geared towards beginners. Dumbbells
between 1 to 5 pounds were provided and used during class. A possible risk to participants was
acute minor muscle soreness. Participants were encouraged to improve their eating habits and
increase their physical activity in order to aid their weight loss efforts, but they were not told to
follow a specific meal plan or exercise program.
The Effects of Weight Self-Monitoring
21
Chapter IV - Results
The purpose of this research was to evaluate the effectiveness of regular weight selfmonitoring on reducing body weight, BMI, and waist circumference (WC) during a nine week
worksite weight loss program. The study focused specifically on the potential differences in
reduction of body weight, BMI, and WC among three different groups of participants in the same
weight loss program. Group A was required to weigh weekly, Group B was required to weigh in
every other week (i.e. semi-weekly), and Group C was required to weigh once at the beginning
and once at the end of the nine week program. The physical characteristics of the population
sample as well as the analysis of % weight change, % BMI change, and % WC change among all
three treatment groups through ANOVA and Post Hoc evaluation were discussed.
Descriptive Data of the Sample by Treatment Group
A total of 77 participants satisfied all the research protocols and completed the nine week
study. Group A contained 25 participants, Group B contained 31 participants, and Group C
contained 21 participants.
Initial Descriptive Data
The average age of all participants in this study was 42.5 years (± 10.5), with Group A
averaging 46.3 years (± 10.2), Group B averaging 38.3 years (± 8.5), and Group C averaging
42.9 years (± 12.0). Mean height was greatest in Group C (169.8 cm ± 7.4) and lowest in Group
A (165.3 cm ± 7.3). Mean initial weight was greatest in Group A (79.1 kg ± 15.4) and lowest in
Group B (77.1 kg ± 15.8). Since height was lowest and initial weight was highest in Group A,
the overall initial mean BMI (29.0 kg/m2 ± 5.2) in this treatment group was greater than in
Groups B (28.8 kg/m2 ± 5.2) or C (27.1 kg/m2 ± 3.5). The initial mean WC was greatest in
The Effects of Weight Self-Monitoring
22
Group C (88.9 cm ± 12.2) and lowest in Group B (87.7 cm ± 13.8). Data in Table 1 provides
mean and standard deviation values for age, height, initial weight, initial BMI, and initial WC for
all treatment groups.
Table 1
Initial Descriptive Data of Participants: Mean and Standard Deviation Values
Group
Age (y) ± SD
Height (cm) ±
Initial Weight
Initial BMI
Initial WC
SD
(kg) ± SD
(kg/m2) ± SD
(cm) ± SD
A
46.3 ± 10.2
165.3 ± 7.3
79.1 ± 15.4
29.0 ± 5.2
88.3 ± 13.1
B
38.3 ± 8.5
165.4 ± 7.0
77.1 ± 15.8
28.8 ± 5.2
87.7 ± 13.8
C
42.9 ± 12.0
169.8 ± 7.4
78.1 ± 13.0
27.1 ± 3.5
88.9 ± 12.2
Combined mean and standard deviation values for age, height, initial weight, initial BMI,
and initial WC are provided in Table 2.
Table 2
Initial Descriptive Data of Participants: Combined Mean and Standard Deviation Values
Group
All
Age (y) ± SD
42.5 ± 10.5
Height (cm) ±
Initial Weight
Initial BMI
Initial WC
SD
(kg) ± SD
(kg/m2) ± SD
(cm) ± SD
166.6 ± 7.4
78.1 ± 14.8
28.2 ± 4.8
88.3 ± 13.0
The Effects of Weight Self-Monitoring
23
Final Descriptive Data
Mean final weight was lowest in Group B (75.3 kg ± 15.6) and greatest in Group C (77.9
kg ± 13.0). However, mean final BMI was lowest in Group C (27.0 kg/m2 ± 3.5) than in both
Groups A (28.2 kg/m2 ± 5.0) or B (27.5 kg/m2 ± 5.1). The final mean WC was lowest in Group
B (85.2 cm ± 13.9) and greatest in Group A (87.6 cm ± 12.4). Data in Table 3 provides mean and
standard deviation values for final weight, final BMI, and final WC for all treatment groups. The
combined mean and standard deviation values for final weight (76.5 kg ± 14.4), final BMI (27.6
kg/m2 ± 4.7), and final WC (86.5 cm ± 12.7) had all decreased from their initial values of 78.1 kg
± 14.8, 28.2 kg/m2 ± 4.8, and 88.3 cm ± 13.0, respectively.
Table 3
Final Descriptive Data of Participants: Mean and Standard Deviation Values
Group
Final Weight
Final BMI
Final WC
(kg) ± SD
(kg/m2) ± SD (cm) ± SD
A
76.7 ± 14.5
28.2 ± 5.0
87.6 ± 12.4
B
75.3 ± 15.6
27.5 ± 5.1
85.2 ± 13.9
C
77.9 ± 13.0
27.0 ± 3.5
86.9 ± 11.3
The Effects of Weight Self-Monitoring
24
Combined mean and standard deviation values for final weight, final BMI, and final WC
are provided in Table 4.
Table 4
Final Descriptive Data of Participants: Combined Mean and Standard Deviation Values
Group
All
Final Weight
Final BMI
Final WC (cm)
(kg) ± SD
(kg/m2) ± SD
± SD
76.5 ± 14.4
27.6 ± 4.7
86.5 ± 12.7
Post-Intervention Results by Treatment Group
After the 9 week weight loss intervention program, mean % weight change was lowest in
Group C (-0.24% ± 1.96) and greatest in Group A (-2.78% ± 3.13). However, mean % BMI
change was lowest in Group A (-1.52% ± 4.01) than in both Groups B (-2.92% ± 3.75) or C (2.14% ± 3.43). The mean % WC was greatest in Group B (-2.46% ± 2.00) as compared to
Groups A (-0.34% ± 5.31) and C (-0.31% ± 1.96). Data in Table 5 provides mean and standard
deviation values for % weight change, % BMI change, and % WC change for all treatment
groups.
The Effects of Weight Self-Monitoring
25
Table 5
Mean and Standard Deviation Values for % Weight Change, % BMI Change, and % WC Change
Group
% Weight Change ±
% BMI Change ± SD
% WC Change ± SD
SD
A
-2.78 ± 3.13
-1.52 ± 4.01
-0.34 ± 5.31
B
-2.32 ± 2.01
-2.92 ± 3.75
-2.46 ± 2.00
C
-0.24 ± 1.96
-2.14 ± 3.43
-0.31 ± 1.96
Combined mean and standard deviation values for % weight change, % BMI change, and
% WC change are provided in Table 6.
Table 6
Combined Mean and Standard Deviation Values for % Weight Change, % BMI Change, and %
WC Change
Group
% Weight Change ±
% BMI Change ± SD
% WC Change ± SD
-2.2 ± 3.7
-1.2 ± 3.5
SD
All
-1.9 ± 2.6
The Effects of Weight Self-Monitoring
26
ANOVA Results for % Weight Change, % BMI Change, and % WC Change
An analysis of variance was performed to evaluate changes in % body weight, % BMI,
and % WC to determine whether significant differences existed between the three treatment
groups. Significant differences in means were determined by establishing an F ratio of 1.0 or (F
> 1.0) and alpha at (p = .05).
The data provided in Table 7 showed significant differences in mean % weight change (F
= 7.07, p = .0015). The Fisher LSD Post Hoc analysis revealed Group C to have a significantly
lower % weight change (-0.24% ± 1.96) than either Groups A (-2.78% ± 3.13) or B (-2.32% ±
2.01). Data from the Fisher LSD Post Hoc test can be found in Table 8.
Table 7
ANOVA Comparing % Weight Change between Treatment Groups
df
Mean Square
F
p1
82.95
2
41.47
7.07
0.0015
Error
434.02
74
5.86
Corrected
516.97
76
Source of
Sum of
Variance
Squares
Model
Total
1
p < .05
The Effects of Weight Self-Monitoring
27
Table 8
Fisher LSD Post Hoc Test Results for % Weight Change
t Grouping1
Mean
N
Group
A
-0.24
21
C
B
-2.32
31
B
B
-2.78
25
A
1
Means with the same letter are not significantly different.
The data provided in Table 9 showed significant differences in mean % WC change (F =
3.57, p = .0331). The Fisher LSD Post Hoc analysis revealed Group B to have a significantly
greater % WC change (-2.46% ± 2.00) than either Groups A (-0.34% ± 5.31) or C (-0.31% ±
1.96). Data from the Fisher LSD Post Hoc test can be found in Table 10.
The Effects of Weight Self-Monitoring
Table 9
ANOVA Comparing % WC Change between Treatment Groups
df
Mean Square
F
p1
84.41
2
42.20
3.57
0.0331
Error
874.44
74
11.81
Corrected
958.85
76
Source of
Sum of
Variance
Squares
Model
Total
1
p < .05
Table 10
Fisher LSD Test Results for % WC Change
t Grouping1
Mean
N
Group
A
-0.31
21
C
A
-0.34
25
A
B
-2.46
31
B
1
Means with the same letter are not significantly different.
The data provided in Table 11 did not show significant differences in mean % BMI
change (F = 0.97, p = .3845) between treatment groups.
28
The Effects of Weight Self-Monitoring
29
Table 11
ANOVA Comparing Mean % BMI Change between Treatment Groups
df
Mean Square
F
p1
27.39
2
13.69
0.97
0.3845
Error
1046.64
74
14.14
Corrected
1074.03
76
Source of
Sum of
Variance
Squares
Model
Total
1
p < .05
Descriptive Data of the Sample by Gender
Of the 77 participants that satisfied all the research protocols and completed the nine
week study, 80% were females (n=62) and 20% were males (n=15). Group A contained 25
participants, 80% females (n=20) and 20% males (n=5). Group B contained 31 participants,
81% females (n=25) and 19% males (n=6). Group C contained 21 participants, 76% females
(n=16) and 24% males (n=5).
Initial Descriptive Data
Mean age for males was greatest in Group A averaging 42.6 years (± 13.4) and lowest in
Group C averaging 32.8 years (± 7.9). Mean height for males was greatest in Group C (177.8 cm
± 6.5) and lowest in Group A (172.4 cm ± 5.8). Mean initial weight for males was greatest in
Group B (92.2 kg ± 9.9) and lowest in Group C (89.4 kg ± 9.6). The initial mean BMI (30.9
The Effects of Weight Self-Monitoring
30
kg/m2 ± 4.5) for males in Group B was greater than in Groups A (30.5 kg/m2 ± 4.9) or C (28.4
kg/m2 ± 2.0). The initial mean WC for males was greatest in Group B (100.3 cm ± 6.2) and
lowest in Group A (97.0 cm ± 14.9).
Mean age for females was greatest in Group A averaging 47.3 years (± 9.5) and lowest in
Group B averaging 38.5 years (± 8.7). Mean height for females was greatest in Group C (167.4
cm ± 5.9) and similar in Groups A (163.5 cm ± 6.6) and B (163.5 cm ± 6.0). Mean initial weight
for females was greatest in Group A (76.3 kg ± 13.8) and lowest in Group B (73.6 kg ± 14.8).
Since height was one of the lowest and initial weight was highest in Group A, the overall initial
mean BMI (28.7 kg/m2 ± 5.3) for females in this treatment group was greater than in Groups B
(27.6 kg/m2 ± 5.2) or C (26.7 kg/m2 ± 3.8). The initial mean WC for females was similar in
Groups A (86.1 cm ± 12.0) and C (86.1 cm ± 11.6) and lowest in Group B (84.7 cm ± 13.5).
Data in Tables 12 and 13 provide mean and standard deviation values for age, height, initial
weight, initial BMI, and initial WC for males and females, respectively, by treatment group.
The Effects of Weight Self-Monitoring
31
Table 12
Initial Descriptive Data of Males by Treatment Group: Mean and Standard Deviation Values
Group
Age (y) ± SD
Height (cm) ±
Initial Weight
Initial BMI
Initial WC
SD
(kg) ± SD
(kg/m2) ± SD
(cm) ± SD
A
42.6 ± 13.4
172.4 ± 5.8
90.5 ± 17.7
30.5 ± 4.9
97.0 ± 14.9
B
37.6 ± 8.5
173.5 ± 5.5
92.2 ± 9.9
30.9 ± 4.5
100.3 ± 6.2
C
32.8 ± 7.9
177.8 ± 6.5
89.4 ± 9.6
28.4 ± 2.0
98.0 ± 10.4
Table 13
Initial Descriptive Data of Females by Treatment Group: Mean and Standard Deviation Values
Group
Age (y) ± SD
Height (cm) ±
Initial Weight
Initial BMI
Initial WC
SD
(kg) ± SD
(kg/m2) ± SD
(cm) ± SD
A
47.3 ± 9.5
163.5 ± 6.6
76.3 ± 13.8
28.7 ± 5.3
86.1 ± 12.0
B
38.5 ± 8.7
163.5 ± 6.0
73.6 ± 14.8
27.6 ± 5.2
84.7 ± 13.5
C
46.1 ± 11.4
167.4 ± 5.9
74.6 ± 12.1
26.7 ± 3.8
86.1 ± 11.6
Combined mean and standard deviation values for age, height, initial weight, initial BMI,
and initial WC for males and females are provided in Table 14.
The Effects of Weight Self-Monitoring
32
Table 14
Initial Descriptive Data of Males and Females: Combined Mean and Standard Deviation Values
Height (cm) ±
Initial Weight
Initial BMI
Initial WC
SD
(kg) ± SD
(kg/m2) ± SD
(cm) ± SD
37.7 ± 10.2
174.5 ± 5.9
90.8 ± 11.9
30.0 ± 3.9
98.5 ± 10.2
Females 42.9 ± 11.5
164.5 ± 6.3
74.7 ± 13.7
27.7 ± 4.9
85.5 ± 12.4
Gender
Males
Age (y) ± SD
Final Descriptive Data
Mean final weight for males was lowest in Group A (86.8 kg ± 18.1) and greatest in
Group B (90.6 kg ± 11.0). However, mean final BMI for males was lowest in Group C (28.1
kg/m2 ± 1.8) than in both Groups A (29.2 kg/m2 ± 5.1) or B (30.3 kg/m2 ± 4.8). The final mean
WC for males was lowest in Group A (95.1 cm ± 15.0) and greatest in Group B (96.9 cm ± 6.6).
Mean final weight for females was lowest in Group B (71.7 kg ± 14.3) and greatest in
Group C (74.6 kg ± 12.3). However, mean final BMI for females was lowest in Group C (26.7
kg/m2 ± 3.9) than in both Groups A (27.9 kg/m2 ± 5.1) or B (26.9 kg/m2 ± 5.1), which may be
related to the fact that Group C had the highest average height. The final mean WC for females
was lowest in Group B (82.4 cm ± 13.9) and greatest in Group A (85.8 cm ± 11.4). Data in
Tables 15 and 16 provides mean and standard deviation values for final weight, final BMI, and
final WC for males and females by treatment group, respectively.
The Effects of Weight Self-Monitoring
Table 15
Final Descriptive Data of Males by Treatment Group: Mean and Standard Deviation Values
Group
Final Weight
Final BMI
Final WC
(kg) ± SD
(kg/m2) ± SD (cm) ± SD
A
86.8 ± 18.1
29.5 ± 5.1
95.1 ± 15.0
B
90.6 ± 11.0
30.3 ± 4.8
96.9 ± 6.6
C
88.5 ± 9.8
28.1 ± 1.8
95.7 ± 9.3
Table 16
Final Descriptive Data of Females by Treatment Group: Mean and Standard Deviation Values
Group
Final WC
Final Weight
Final BMI
(kg) ± SD
(kg/m2) ± SD (cm) ± SD
A
74.2 ± 12.8
27.9 ± 5.1
85.8 ± 11.4
B
71.7 ± 14.3
26.9 ± 5.1
82.4 ± 13.9
C
74.6 ± 12.3
26.7 ± 3.9
84.1 ± 10.6
The combined mean and standard deviation values for male participants’ final weight
(88.8 kg ± 12.5), final BMI (29.3 kg/m2 ± 4.0), and final WC (96.0 cm ± 9.9) had all decreased
from their initial values of 90.8 kg ± 11.9, 30.0 kg/m2 ± 3.9, and 98.5 cm ± 10.2, respectively.
33
The Effects of Weight Self-Monitoring
34
The combined mean and standard deviation values for female participants’ final weight (73.3 kg
± 13.2), final BMI (27.2 kg/m2 ± 4.7), and final WC (83.9 cm ± 12.7) had all decreased from
their initial values of 74.7 kg ± 13.7, 27.7 kg/m2 ± 4.9, and 85.5 cm ± 12.4, respectively.
Combined mean and standard deviation values for final weight, final BMI, and final WC for
males and females are provided in Table 17.
Table 17
Final Descriptive Data of Males and Females: Combined Mean and Standard Deviation Values
Final Weight
Final BMI
Final WC (cm)
(kg) ± SD
(kg/m2) ± SD
± SD
88.8 ± 12.5
29.3 ± 4.0
96.0 ± 9.9
Females 73.3 ± 13.2
27.2 ± 4.7
83.9 ± 12.2
Gender
Males
Post-Intervention Results by Gender
After the 9 week weight loss intervention program, mean % weight change for males was
lowest in Group C (-0.9% ± 1.9) and greatest in Group A (-4.2% ± 2.9). However, mean % BMI
change was lowest in Group C (-1.0% ± 1.9) than in both Groups A (-4.3% ± 3.2) or B (-2.1% ±
1.9). The mean % WC was greatest in Group B (-3.3% ± 3.9) as compared to Groups A (-1.9%
± 4.4) and C (-2.2% ± 1.5). Data in Table 18 provides mean and standard deviation values for %
weight change, % BMI change, and % WC change for males by treatment group.
The Effects of Weight Self-Monitoring
35
Table 18
Mean and Standard Deviation Values for % Weight Change, % BMI Change, and % WC Change
in Male Participants by Treatment Group
Group
% Weight Change ±
% BMI Change ± SD
% WC Change ± SD
SD
A
-4.2 ± 2.9
-4.3 ± 3.2
-1.9 ± 4.4
B
-1.9 ± 1.8
-2.1 ± 1.9
-3.3 ± 3.9
C
-0.9 ± 1.9
-1.0 ± 1.9
-2.2 ± 1.5
After the 9 week weight loss intervention program, mean % weight change for females
was lowest in Group C (-0.03% ± 1.9) and similar in Groups A (-2.4% ± 3.1) and C (-2.4% ±
2.1). Mean % BMI change for females was lowest in Group C (-0.1% ± 2.0) and greatest in
Group B(-2.5% ± 2.0). The mean % WC was also greatest in Group B (-2.8% ± 3.8) as
compared to Groups A (0.05% ± 5.5) and C (-2.1% ± 3.9). Data in Table 19 provides mean and
standard deviation values for % weight change, % BMI change, and % WC change for females
by treatment group.
The Effects of Weight Self-Monitoring
36
Table 19
Mean and Standard Deviation Values for % Weight Change, % BMI Change, and % WC Change
in Female Participants by Treatment Group
Group
% Weight Change ±
% BMI Change ± SD
% WC Change ± SD
SD
A
-2.4 ± 3.1
-0.8 ± 3.9
0.05 ± 5.5
B
-2.4 ± 2.1
-2.5 ± 2.0
-2.8 ± 3.8
C
-0.03 ± 1.9
-0.1 ± 2.0
-2.1 ± 3.9
Combined mean and standard deviation values for male and female participant’s %
weight change, % BMI change, and % WC change are provided in Table 20.
Table 20
Combined Mean and Standard Deviation Values for % Weight Change, % BMI Change, and %
WC Change in Male and Female Participants
Gender
% Weight Change ±
% BMI Change ± SD
% WC Change ± SD
SD
Male
-2.3 ± 2.5
-2.4 ± 2.6
-2.5 ± 3.3
Female
-1.8 ± 2.6
-1.3 ± 2.9
-1.7 ± 4.5
The Effects of Weight Self-Monitoring
37
ANOVA Results for % Weight Change, % BMI Change, and % WC Change by Gender
An analysis of variance was performed to evaluate changes in % body weight, % BMI,
and % WC to determine whether significant differences existed between genders. Significant
differences in means were determined by establishing an F ratio of 1.0 or (F > 1.0) and alpha at
(p = .05). The data provided in Table 21 showed a significant difference in mean % weight
change (F = 5.33, p = .0022). However, the Fisher LSD Post Hoc analysis revealed no
significant difference existed between genders. Data from the Fisher LSD Post Hoc test can be
found in Table 22.
Table 21
ANOVA Comparing % Weight Change between Genders
df
Mean Square
F
p1
92.88
3
30.96
5.33
0.0022
Error
424.09
73
5.80
Corrected
516.97
76
Source of
Sum of
Variance
Squares
Model
Total
1
p < .05
The Effects of Weight Self-Monitoring
Table 22
Fisher LSD Post Hoc Test Results for % Weight Change between Genders
t Grouping1
Mean
N
Gender
A
-2.63
15
Male
A
-1.73
62
Female
1
Means with the same letter are not significantly different.
The data provided in Table 23 showed no significant difference by gender in mean %
WC change (F = 2.70, p = .0517).
Table 23
ANOVA Comparing % WC Change between Genders
df
Mean Square
F
p1
95.84
3
31.94
2.70
0.0517
Error
863.01
73
11.82
Corrected
958.85
76
Source of
Sum of
Variance
Squares
Model
Total
1
p < .05
The data provided in Table 24 did not show significant differences in mean % BMI
change (F = 01.32, p = .2732) between genders.
38
The Effects of Weight Self-Monitoring
39
Table 24
ANOVA Comparing Mean % BMI Change between Genders
df
Mean Square
F
p1
55.41
3
18.47
1.32
0.2732
Error
1018.61
73
13.95
Corrected
1074.03
76
Source of
Sum of
Variance
Squares
Model
Total
1
p < .05
Survey Results
All participants (n=77) completed the pre-treatment and post-treatment surveys
(Appendix B). The same survey was given to all participants to fill out the day they weighed-in
for the study and on the day of their final weighing at the end of the nine weeks. Both surveys
consisted of the same 7 multiple choice questions and were created by the primary researcher
specifically for this study.
Pre-treatment Survey
An equal percentage of Group A participants (36%) exercised 1-2 times weekly and 3-4
times weekly prior to the study. The majority of Group B participants (45%) exercised 1-2 times
weekly, whereas the majority of Group C participants (38%) exercised more often at 3-4 times
weekly. The majority of participants from Group A (80%), Group B (87%), and Group C (86%)
The Effects of Weight Self-Monitoring
40
intentionally built activity into their day, for example, by using the stairs instead of the elevator,
parking further from the entrance to a building, and by conducting nearby errands on foot or on a
bicycle, prior to their involvement in the study.
Over the month prior to their involvement in the study, the majority of participants from
Group A (76%), Group B (58%), and Group C (63%) consumed 1-3 servings of fruits and
vegetables a day. Only a small amount of participants (4%) from Groups A and C consumed the
USDA recommended amount of 7 or more servings of fruits and vegetables a day. Additionally,
prior to this study, the majority of Group B (45%) consumed high fat foods (i.e. full fat dairy
products, fried foods, or fatty cuts of meat) 1-2 times a week, whereas an equal amount of Group
A (28%) and Group C (33%) consume these foods 1-2 times and 3-4 times weekly. The majority
of Group A (68%), Group B (78%), and Group C (76%) were consuming breakfast daily.
However, the majority of participants from Group A (84%), Group B (87%), and Group C
(80%), were not keeping a food journal to record what they were eating on a regular basis.
Prior to their involvement in this study, most Group A participants (36%) were weighing
themselves on a daily basis. However, most of Groups B and C were weighing on a once a week
(41%) and every other week (29%) basis, respectively. See Charts 1, 2, and 3.
Post-treatment Survey
Group A (68%), Group B (41%), and Group C (47%) participants increased the amount
of times per week they exercise from 1-2 times to 3-4 times during the treatment intervention.
The majority of participants from Group A (80%), Group B (87%), and Group C (90%) were still
intentionally building activity into their day during the program.
The Effects of Weight Self-Monitoring
41
During the study, the majority of participants from Group A (60%), Group B (65%), and
Group C (66%) still consumed 1-3 servings of fruits and vegetables a day. These percentages
did increase from their pre-treatment levels for all groups except Group A, which decreased by
16%, but also increased their intake of 4-6 daily servings from 16% pre-treatment to 36% posttreatment. Only Group C increased their intake of 7+ servings of fruits and vegetables from 4%
to 10% during the intervention. Overall, all groups appeared to decrease the amount of high fat
foods they consume per week. Group A increased the amount of participants that were
consuming them 1-2 times a week from 28% pre-study to 52% post-study. This coincided with a
subsequent decrease in the frequency they were eaten 3-4 and 5-6 times a week by 8% each.
However, there was also a 50% reduction in the amount of participants that eat high fat foods
less than once a week from 16% to 8% during the study. A similar occurrence was observed in
Group C, whose intake of 1-2 times a week increased from 33% to 53% during the study, but
coincided with a 6% decrease in the amount of those eating these foods less than once a week.
Group B increased the amount of participants eating fatty foods less than once a week and 1-2
times a week by 10% and 7%, respectively. Groups A and C saw an increase in the majority of
participants consuming breakfast daily to 84% and 95%, respectively. However, the percentage
eating this meal daily in Group B decreased by 3% with an equivalent increase in those eating it
only 3-4 times a week. Groups A and C saw a decrease in the amount of participants keeping a
regular food journal by 8% and 6%, respectively. However, Group B had a 6% increase in those
keeping record.
All groups showed a decrease in the frequency of the amount of times they weigh
themselves during the study. During the study, the majority of Group A participants (72%)
reported weighing themselves on a weekly basis. Group B reported weighing themselves on a
The Effects of Weight Self-Monitoring
42
weekly (46%) and every other week (35%) basis. The majority of Group C could not remember
the last time they weighed themselves (57%) during the study. See Charts 1, 2, and 3.
In summary, significant differences were observed between treatment groups in regards
to % weight change and % WC change during the nine week work site weight loss program.
Group C showed significantly less reduction in weight than either Group A or B. Group B
showed a significantly greater reduction in WC than Group A or C. There were no significant
differences between treatment groups regarding percent BMI change. Moreover, there were no
significant differences observed between genders regarding % weight change, % BMI change, or
% WC change. However, all groups reported improvement in their eating and exercise habits
during the study.
Chart 1
Group A Pre- and Post-Treatment Survey Results
The Effects of Weight Self-Monitoring
43
Chart 2
Group B Pre- and Post-Treatment Survey Results
The Effects of Weight Self-Monitoring
44
Chart 3
Group C Pre- and Post-Treatment Survey Results
The Effects of Weight Self-Monitoring
45
The Effects of Weight Self-Monitoring
46
Chapter V - Discussion
The purpose of this research was to evaluate the effectiveness of weight self-monitoring
on reducing body weight, BMI, and WC during a nine week worksite weight loss program. The
study focused specifically on the potential differences in reduction of body weight, BMI, and
WC among three treatment groups required to weigh themselves at different frequencies: Group
A was required to weigh weekly, Group B was required to weigh in every other week (i.e. semiweekly), and Group C was required to weigh once at the beginning and once at the end of the
nine week program. This chapter compared the compiled results of the study to the original
hypotheses and previously reviewed research. Based on the results, conclusions were drawn and
the need for future research considered.
Regular self-weighing has received conflicting endorsement in that some researchers and
practitioners recommend it as a key behavioral strategy for weight management, while others
caution against its use due to its potential to cause negative psychological consequences
associated with weight management failure (VanWormer et al., 2008). The evidence on frequent
self-weighing for weight loss, however, has not yet been synthesized in the clinical setting,
where most of the research has taken place, and even less so in the worksite setting where this
study took place. Furthermore, most studies (Linde et al., 2005; Qi & Dennis, 2000) focused
primarily on daily or weekly weights, but the most effective frequency of weighing has not yet
been established.
The first consideration of this study was to evaluate the effectiveness of each frequency
of weight self-monitoring on % weight change. This study hypothesized that Group A would
have the greatest reduction of body weight during the nine week program. Upon completion of
the study an ANOVA showed significant differences among treatment groups (F = 7.07, p =
The Effects of Weight Self-Monitoring
47
.0015). Fisher’s LSD Post Hoc analysis revealed Groups A and B to have significantly greater
reduction in % body weight than Group C. Although no significant difference in weight loss was
found between Groups A (weekly weights) and B (semi-weekly weights) mean test scores
revealed more favorable results for weekly (-2.78% ± 3.13) than for semi-weekly weights (2.32% ± 2.01). The results of the post hoc analysis support weekly weights and semi-weekly
weights as equally effective methods of reduction in % body weight.
These findings are supported by prior research, which shows weekly and more frequent
weight self-monitoring to be more effective for weight loss than less frequent weighing. Linde et
al (2005) found that among more than 3,000 adults trying to lose weight those who weighed
themselves more frequently lost more weight over two years. Linde et al suggested that people
who weigh themselves more often weigh less and are more successful at losing the weight.
Further support comes from VanWormer et al (2008) who found self-weighing to be a significant
predictor of body weight over time. Participants in their study lost one extra pound for every
eleven days they self-weighed during treatment. In addition, participants who self-weighed at
least weekly were eleven times more likely to lose at least 5% of their pretreatment weight after
six months. Although the VanWormer study took place over a longer period of time and
therefore had a greater average weight loss, the current study demonstrated similar results in
Group A, which lost an average of 2.78% of original body weight.
The second consideration of this study was to evaluate the effectiveness of each
frequency of weight self-monitoring on % BMI change. This study hypothesized that Group A
would have the greatest reduction of BMI during the nine week program. Upon completion of
the study an ANOVA showed no significant difference among treatment groups (F = .97, p =
The Effects of Weight Self-Monitoring
48
.3845). Although no significant difference in % BMI change was found between Groups A and
B, mean test scores revealed more favorable results for semi-weekly weights (-2.92% ± 3.75)
than for either weekly weights (-1.52% ± 4.01) or weights taken only at the beginning and end of
the nine week intervention (-2.14% ± 3.43). Therefore, this hypothesis was rejected.
This finding was not supported in the literature however, as most studies that had
demonstrated a weight loss also demonstrated a reduction in BMI with increased frequency of
self-weighing (Linde et al, 2007; Ogden & Whyman; Qi & Dennis). Since the current study took
place over nine weeks this may not have been sufficient time to significantly alter BMI since
each categorical unit of BMI is comprised of five pounds (2.3 kg). For example, if a 62 inch
(157.5 cm) woman were to reduce her BMI from 30 kg/m2 to 29 kg/m2 her weight must change
from 165 pounds (75.0 kg) to 160 pounds (72.7 kg). In order to have altered BMI significantly, a
greater amount of weight than was observed in this study would need to have been lost during
the nine week program.
The third consideration of this study was to evaluate the effectiveness of each frequency
of weight self-monitoring on % WC change. This study hypothesized that Group A would have
the greatest reduction of WC during the nine week program. Upon completion of the study an
ANOVA did show a significant difference among treatment groups (F = 3.57, p = .0331).
However, Fisher’s LSD Post Hoc analysis revealed Group B to have a significantly greater
reduction of WC (-2.46% ± 2.00) than either Groups A (-0.34% ± 5.31) or C (-0.31% ± 1.96).
Therefore, although this hypothesis was rejected, it is important to note that a significant
reduction did occur. The reason why Group B, who weighed semi-weekly, as opposed to Group
A, who weighed weekly, experienced a greater reduction in WC is not entirely understood.
Perhaps it is because Group B was the treatment group with the lowest mean age, mean initial
The Effects of Weight Self-Monitoring
49
weight, and mean initial WC. This group may have been the leanest to begin with and perhaps
benefited from that advantage. Another possibility is observer variation between the initial and
final waist measurements. WC measurements were taken following the NHANES II protocol,
however, the measuring tape may have been pulled more taut than recommended or the location
of the tape may have been slightly different each time it was measured. As per Ulijaszek & Kerr
(1999), WC shows strong between-observer variations, and should, where possible, be done by
one observer.
For assessing someone’s likelihood of developing overweight- or obesity-related
diseases, the National Heart, Lung, and Blood Institute guidelines recommend looking at the
individual’s WC (http://www.cdc.gov/nccdphp/dnpa/obesity/defining.htm). Pischon et al (2008)
found that abdominal fat distribution was related to the risk of death independently of BMI since
this tissue secretes potential mediators in the development of chronic diseases (Haslam and
James, 2005). There is a higher risk of developing obesity-related conditions in a man whose
waist circumference is more than 101.6 cm (40 inches) and in a non-pregnant woman whose
waist circumference is more than 88.9 cm (35 inches). In this study, the initial mean WC was
98.5 cm (SD ± 10.2) for males and 85.5 cm (SD ± 12.4) for females. Despite the importance of
WC, there was not much literature supporting the reduction of this parameter during weight loss
programs. Most studies used body weight and BMI as an indicator of weight loss and did not
assess WC (Ogden & Whyman; Dionne & Yeudall).
The differences in % weight change, % BMI change, and % WC change were also
analyzed to evaluate any differences among genders. Based on Fisher’s LSD Post Hoc test, there
were no significant differences between males and females for any of the above parameters.
However, mean test scores revealed a greater weight reduction for males (-2.3% ± 2.5) than for
The Effects of Weight Self-Monitoring
50
females (-1.8% ± 2.6). The results of the statistical analysis support males and females being
equally successful at weight loss in this particular study. However, more women (n = 62) than
men (n = 15) participated and the results may have shown otherwise if the gender ratio were
equivalent.
Each participant was required to complete a pre-treatment and a post-treatment survey
(Appendix A) compiled of the same seven questions. The intention of this survey was to assess
if participants made any lifestyle changes conducive to weight reduction as a result of the
intervention. In fact, all groups made positive changes. On average they increased the amount
of times participants exercise weekly. However, Group A had the greatest increase in those who
exercised 1-2 times weekly (36%) to those who exercised 3-4 (68%) times weekly. The
treatment groups did not seem to alter their eating habits as greatly. The most dramatic change
in eating habits came from the reduction of high fat food consumption. Overall, all groups
appeared to decrease the amount of high fat foods they consume per week. Group A had the
greatest improvement in their reduced intake of fatty foods: 24% of participants reduced their
intake of fatty foods to 1-2 times a week. Also, Groups A and C increased the number of
participants consuming breakfast daily to 84% and 95%, respectively, during the study. The
average daily intake of fruits and vegetables remained about 1-3 servings prior to and after
intervention. As for behavioral changes, Groups A and C actually decreased the amount of
subjects keeping a food journal by 8% and 6%, respectively, whereas Group B increased this
amount by 6%. These lifestyle changes are worth noting. However, they do not entirely explain
the changes in body weight, BMI, and WC observed among the treatment groups. For instance,
Group A appeared to make the most lifestyle changes by increasing exercise frequency and
decreasing high fat food intake more so than the other groups. However, Group A did not have
The Effects of Weight Self-Monitoring
51
the most significant % body weight change or % WC change, whereas in fact, Group B did. This
observance is important because it points out that the frequency of weight self-monitoring may
have indeed affected weight loss results independent of lifestyle changes.
In support of the above finding, Linde et al (2005) found that for obese participants
enrolled in a weight loss study, more frequent weight self-monitoring at baseline was associated
with lower dietary fat intake. At 12 and 24 months of the study, regular weight self-monitoring
was associated with greater weight loss. Self-weighing was associated with other healthy
behaviors such as exercising more. However, they also observed that self-weighing had an
independent effect on weight change, as evidenced by results that did not change when
behavioral covariates (i.e. walking and fat intake) were added to the statistical models. Another
study by Qi & Dennis (2000) supports the effectiveness of self-weighing compared with other
behavior modifications used in weight loss regimens. The results indicated that careful selfmonitoring of food intake was the best predictor of the amount of weight loss, but daily weighing
and keeping a record of these results were the next most important factors.
Overall, this research supports the use of regular weight self-monitoring during weight
loss, specifically weekly and semi-weekly weighing. The statistical analysis of this research
indicated that weekly and semi-weekly self-weighing were equally effective at promoting weight
loss as evidenced by kilograms lost. Semi-weekly weighing was the most effective frequency
for reducing waist circumference. There was no significant difference between weekly, semiweekly, or less frequent weighing in the reduction of BMI. The evidence from clinical weight
control trials also supports higher weighing frequency for greater weight loss. It should be noted
however that these studies used BMI as an indicator of weight loss and did not assess WC.
There is limited research available focusing specifically on the impact of semi-weekly weights
The Effects of Weight Self-Monitoring
52
(or less frequent self-weighing) on weight loss in the clinical or workplace setting, which is why
this study adds to the body of knowledge on weight management and worksite wellness
programs.
The statistical significance reported in the effectiveness of weekly and semi-weekly selfweighing regarding % weight change and % WC change does provide some interesting data to
be considered in future research studies as well as evaluated by health and wellness programs
operating in a workplace setting. It is important for researchers and those in the wellness
profession to regularly check-in with their participants in order to create an effective support
system and to make them feel more accountable for their own health. With regular opportunities
of contact and support, weight loss participants are more inclined to lose weight than those who
receive less support. These contacts can be created by setting up regular consultations or, as in
this study, regular weigh-ins. Limitations of this study include a small population size, which if
increased statistical significance in % BMI change or between genders may have been indicated.
Future research should also consider testing at other types of workplace settings, such as
manufacturing or retail companies, instead of only pharmaceutical corporations. Moreover,
these participants voluntarily joined this study, which also may have influenced outcomes. As a
result of this study, research has been added to the limited body of knowledge concerning the
effectiveness of weight self-monitoring during work site weight loss programs. Also, this study
has provided a better understanding of the importance of regular contact with weight loss
program participants in order to foster a sense of support and accountability.
The Effects of Weight Self-Monitoring
53
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59
APPENDIX A
Recruitment Email
Do you want to lose weight in a safe and healthy way during a worksite weight loss
program?
You have the opportunity to take part in a Kean University research study to learn more about
the effect of weight self-monitoring on weight change, body mass index, and waist
circumference during a 9 week worksite weight loss program. This study may provide important
information about the role weight self-monitoring may play during weight loss and will attempt
to find out the most effective weight monitoring frequency for promotion of weight loss. Weight
loss support materials include: weekly informational emails, a 60 minute nutrition lecture, twice
weekly group exercise classes, and weekly campus walks. This study is being conducted by
Wellness Professional and Kean University Exercise Science graduate student, Michelle
Sadlowski, as partial fulfillment of her Master’s degree.
Please Note:
You do not need to participate in this study in order to join the worksite weight loss program.
More information about the study will be provided in the consent forms that will be available to
you at the initial weigh-in. Your participation is completely voluntary and, if at any time, you
decide to withdraw your participation, you may do so without consequence.
Please contact Michelle Sadlowski, sadlowsm@kean.edu, with questions or to participate.
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60
APPENDIX B
Consent to Participate in a Research Study
Title of Project: The Effects of Weight Self-Monitoring on Weight Change, Body Mass Index,
and Waist Circumference during a Worksite Weight Loss Program
Researcher: Michelle Sadlowski
Department: Physical Education, Recreation and Health
Contact Information: Telephone (908) 737-0662, Email sadlowsm@kean.edu
Faculty Advisor: Dr. Walter Andzel
Department: Physical Education, Recreation and Health
Contact Information: Telephone (908) 737-0662, Email wandzel@kean.edu
Invitation to Participate:
You have been invited to take part in a research study to learn more about the effect of
weight self-monitoring on percent weight change, body mass index, and waist circumference
during a worksite weight loss program. This study may provide important information about the
role weight self-monitoring may play in weight loss. This study will attempt to find out the most
effective weight monitoring frequency for promotion of weight loss during a worksite weight
loss program. This study is being conducted by an Exercise Science graduate student from Kean
University as partial fulfillment of her Master’s degree.
Subject Selection:
You have been invited to participate in this study because you are an employee of a
pharmaceutical corporation that is offering a worksite weight loss program to its employees and
you have voluntarily chosen to register as a participant in this worksite weight loss program. By
signing this form you are agreeing to participate in this study.
Purpose of the Study:
The purpose of this research is to study the effectiveness of different frequencies of
weight self-monitoring on reducing body weight (% weight loss), body mass index (BMI), and
waist circumference (WC) during a nine week worksite weight loss program. Participants will
be divided into one of three groups: Group A will weigh themselves weekly, Group B will weigh
The Effects of Weight Self-Monitoring
61
themselves every other week, and Group C will weigh themselves once on week 1 and once on
week 9.
Procedures:
The duration of the study is 9 weeks with week 1 and week 9 being devoted to obtaining
all participants mandatory weigh-ins. Weigh-ins and waist circumference measurements will be
conducted in a private setting so that only a Wellness Professional (WP) and the participant will
be present. All participants are required to have their waist circumference measured during week
1 and week 9. Waist circumference will be measured by a WP according to NHANES III
protocol using a paper tape measure. All participants that voluntarily register for the weight loss
program will receive a Welcome email with the program guidelines. Prior to the start of the
program, all interested participants will sign an informed consent form and complete a pretreatment survey. At the week 1 initial weigh-in, all participants will state their age and height,
and will be weighed on digital scales. The initial weights will be observed and recorded by a
WP in a private setting. All evaluators will be required to complete the National Cancer
Institute’s Human Subjects Certification program prior to their involvement with the study.
Group A are required to weigh themselves weekly, Group B are required to weigh themselves
every other week, and Group C are required to weigh themselves on week 1 and week 9. All
weights will be taken privately and only a WP and the participant will be present. Upon
completion of the program all participants will be required to answer a post-treatment survey.
Note: In order to obtain valid results, it is important that participants refrain from
weighing themselves more often than instructed during the course of the study.
Stimuli. Participants will be encouraged to improve their eating habits and increase their
physical activity in order to aid their weight loss efforts, but they will not be told to follow a
specific meal plan or exercise program. The following voluntary support activities will be
offered during the program:
Email communications: Each week an informational email will be sent out to all
participants providing them with nutrition, physical activity, and behavioral modification tips to
assist them with weight loss. All formal email communications with participants will be
conducted on a company network.
Nutrition lecture: A 60 minute nutrition lecture will be offered to participants at each
location about 3 weeks into the program, for which the company has allowed release time. The
one hour lecture will cover the following topics: portion control, protein intake during weight
loss, fluid intake, increasing nutritionally dense whole foods (i.e. fruits, vegetables, lean proteins,
low fat or non fat dairy, and whole grains), and eating smaller, more frequent meals.
Participants will attend voluntarily.
The Effects of Weight Self-Monitoring
62
Group exercise classes: All participants taking attending these exercise classes have been
previously screened to become members of the fitness center as per company protocol. Classes
will be offered to participants who are fitness center members in the on-site fitness centers and
will be 30 minutes duration. The group classes offered will be low-impact aerobic classes geared
towards beginners. Dumbbells between 1 to 5 pounds will be used during class. If a participant
does sustain an injury from class, the onsite Occupational Health Services will be available to
care for the injured participant and an accident report will be completed as per company
protocol.
Campus walks: Informal walks will be offered once a week during weeks 2 through 9.
All walks will be 30 minutes in duration.
Participation:
Your participation in this research study is completely voluntary and has no bearing on
your standing as an employee of an undisclosed pharmaceutical corporation. If, at any time, you
decide that you do not wish to participate in the study, you may withdraw your participation
without any penalty or loss of benefits.
Discomforts and Potential Risks:
You will be required to weigh yourself during the study. To minimize potential
physiological risk of regular weight self-monitoring, during the program all reported weights will
be kept confidential on an MS Excel document on a company computer that can only be
accessed by authorized WP’s involved with this study. Also, the weight loss program will
advocate a gradual weight loss of 1 to 2 pounds per week since losing weight more quickly may
not be healthy. You will be encouraged to make small significant lifestyle changes in order to
promote a healthy weight loss.
You will have an opportunity to participate in low-impact group exercise classes during
the study. All participants taking attending these exercise classes must have been previously
screened to become members of the fitness center as per company protocol. The potential risk
involved with participating in these classes is acute minor muscle soreness. To minimize this,
you will perform a brief warm up, a cool down, and stretching exercises as part of each class.
You will be given modifications during class to minimize the intensity of the exercise if you so
choose. All group exercise classes will be taught by certified group exercise instructors with
current First Aid and Cardiopulmonary Resuscitation (CPR) certifications. If you do sustain an
injury from class, your onsite Occupational Health Services will be available to care for your
injury and an accident report will be completed as per company protocol.
The Effects of Weight Self-Monitoring
63
Potential Benefits:
There is the potential benefit of weight reduction, and the associated health benefits, as a
participant in this study. Additionally, by voluntarily attending or using the support programs
(i.e. nutrition lecture, group exercise classes, campus walks, and weekly emails) you may learn
to make positive lifestyle changes. However, no benefit from participation in this study is
guaranteed. It is hoped that the information gained from this study will increase understanding
of the effects of weight self-monitoring on weight loss, body mass index, and waist
circumference during a worksite weight loss program.
Financial Obligation:
There is no financial obligation to you associated with participation in this study.
Compensation/Treatment:
There is no monetary or other compensation associated with participation in this study. If
an injury should occur as a result of participation in an exercise class, medical care is available
through your onsite Occupational Health Services. In the event of psychological distress
resulting from the research, counseling is available through your onsite Employee Assistance
Program.
Confidentiality:
Your Participation in this research is confidential. All of your records will be coded with
a unique ID number, and your name will not be used. Records containing your name or other
identifying information will be kept under lock in the Kean University Exercise Physiology
Laboratory. Only the study investigators will have access to your identity and to information
that can be associated with your identity. If this research is published, no personally identifying
information will be used. After 5 years, all data, questionnaires, and participant information
forms will be destroyed.
Questions/Comments:
If you have further questions or concerns about the study, you can contact the principle
investigator, Michelle Sadlowski, or her faculty advisor, Walter Andzel:
Primary Investigator: Michelle Sadlowski, (908) 737-0662 or sadlowsm@kean.edu
Faculty advisor: Walter Andzel, (908) 737-0662 or wandzel@kean.edu
If you have questions about your rights as research participants, you can contact the Kean
University Institutional Review Board (IRB):
IRB: (908) 737-5943 or IRB@kean.edu
The Effects of Weight Self-Monitoring
64
Agreement to Participate:
Please sign and print your name where designated below if you agree to take part in the
study, “The Effects of Weight Self-Monitoring on Weight Change, Body Mass Index, and Waist
Circumference during a Worksite Weight Loss Program”. By signing this form, you are
indicating that you have read and understood the information in this document and agree to
participate in this study. If, at any time, you have questions or concerns regarding this study,
please feel free to contact the faculty advisor or primary investigator at the telephone numbers or
email addresses provided in this document.
______________________________
___________
Signature of Participant
Date
______________________________
___________
Printed Name of Participant
Date
______________________________
___________
Signature of Primary Investigator
Date
______________________________
___________
Signature of Faculty Advisor
Date
The Effects of Weight Self-Monitoring
65
APPENDIX C
Pre- and Post-Treatment Survey
Instructions: Please circle your response and return to your onsite Wellness Professional.
1. Within the past month how many days per week did you exercise for at least 30 minutes?
a. 0
b. 1-2
c. 3-4
d. 5+
2. Over the past month have you intentionally decided to do one of the following: taken the
stairs instead of the elevator, parked farther away from an entrance, conducted nearby
errands on foot or by bike, or walked to deliver a message to a co-worker’s desk instead
of call or email?
a. Yes
b. No
3. Over the past month how many fruits and vegetables did you eat on a daily basis?
a. Less than 1 serving a day
b. 1-3 servings a day
c. 4-6 servings a day
d. 7+ servings a day
4. Over the past month how many times a week did you eat high fat foods such as full fat
cheese, fried foods, steak, or full fat ice cream?
a. Less than 1 time
b. 1-2 times
c. 3-4 times
d. 5-6 times
e. Every day
5. Over the past month how many times per week have you eaten breakfast?
a. Less than 1 time
b. 1-2 times
c. 3-4 times
d. 5-6 times
e. Every day
The Effects of Weight Self-Monitoring
6. Over the past month have you recorded what you eat on a regular basis?
a. Yes
b. No
7. How often do you currently weigh yourself?
a. Daily
b. Once a week
c. Every other week
d. Once a month
e. Every other month
f. I cannot remember the last time I weighed myself
_________________________________
Name
________________
Date
66
The Effects of Weight Self-Monitoring
67
APPENDIX D
Debriefing Form
On behalf of the Department of Physical Education, Recreation and Health at Kean
University, thank you for participating in our research study, “The Effects of Weight SelfMonitoring on Weight Change, Body Mass Index, and Waist Circumference during a Worksite
Weight Loss Program”. This study examined the effects of weight self-monitoring on weight
loss, body mass index, and waist circumference during a 9 week worksite weight loss program.
This research will help the general public attempting to manage their weight, health promotion
program coordinators, and employers better understand the role weight self-monitoring plays in
weight loss and possibly be used to design more effective worksite weight loss programs.
If you have any questions about this research study, or if you would like a copy of the
results, please contact the principle investigator, Michelle Sadlowski at (908) 737-0662 or at
sadlowsm@kean.edu or her faculty advisor, Walter Andzel at (908) 737-0662 or at
wandzel@kean.edu. You can also contact the Kean University Institutional Review Board (IRB)
at (908) 737-5943 or IRB@kean.edu if you have questions about your rights as a research
participant. If an injury should occur as a result of participation in an exercise class, medical
care is available through your onsite Occupational Health Services. In the event of psychological
distress resulting from the research, counseling is available through your onsite Employee
Assistance Program.
Once again, thank you for your participation.
Signature of researcher__________________________________________________
The Effects of Weight Self-Monitoring
68
APPENDIX E
Week 1 Email
One Day at a Time
You’ve probably heard the phrase “One Day at a Time.” If you have, you may know that “One
Day at a Time” is an approach used by people who have alcohol or drug addictions. The idea is
that the person will decide not to drink, or not to take drugs, just for today. Any problems that
might come up today will be handled in some other manner, rather than using alcohol or drugs.
Read on to find out how the “One Day at a Time” approach can be applied to weight
management.
What Does “One Day at a Time” Mean?
Taking things “One Day at a Time” means focusing only on today’s challenges, and getting as
much satisfaction and pleasure out of today as you can. It means letting go of the past and the
future, just for today. It means living today in the best way you can. It means deciding not to
think about how hard it might be to live the rest of your life. You don’t have to live the rest of
your life today. You only have to get through today.
Are You Taking It “One Day at a Time”?
How do you approach weight loss? Do you take it “One Day at a Time” or do you make it a
“race to the end?” Some examples of the “One Day at a Time” approach include:
•
•
Having smaller portions of your favorite high - calorie foods
Eating out a little less frequently
“Race to the end” activities are more extreme. Some good examples of these “do it all right now”
strategies include:
•
•
Totally eliminating all high-calorie foods from your diet
Refusing all dinner invitations
For more information please contact your onsite Wellness Professional.
The Effects of Weight Self-Monitoring
69
APPENDIX F
Week 2 Email
Healthy Eating
Whether you're just starting or have been following a healthy eating plan for years, sticking to it
can be challenging. Healthy eating doesn't need to be difficult. You can learn how to eat better
and lose weight. Here are some key ideas to help jumpstart your way to a healthy plate:
Eat “real food”
Nutritionally dense whole foods are foods that are minimally processed and chock full of
essential nutrients. These foods include fruits & vegetables, whole grains, poultry, fish, low-fat
dairy, nuts, seeds, and legumes. Eating more of these foods supports weight loss because you get
more nutrients for fewer calories plus you feel fuller for longer.
Don’t skip breakfast
You probably know that this is the most important meal of the day. So why aren’t you eating it?
If you don’t have the appetite or the time in the morning try making a quick low-fat yogurt and
fruit smoothie or a hard-boiled egg with a piece of whole-wheat toast.
Eat the colors of the rainbow
Because they are low in calories and high in fiber, fruits and vegetables can help you control
your weight. Strive to eat 7 to 9 servings a day. Meet your goal by eating a fruit and/or vegetable
with all meals and snacks.
Design your plate
About 2/3 of your plate should contain fruits, vegetables, and/or whole grains and the remaining
1/3 should contain lean proteins such as skinless poultry, eggs, low-fat dairy, or legumes. Think
of plant foods as the base of your meal and the protein as a condiment.
Snack happy
Plan a mid-morning and afternoon snack rich in fiber and protein to stave off hunger and provide
essential nutrients. Good examples include: low-fat cheese and apple slices, small handful of
nuts and dried fruit, crudités and hummus.
Healthy eating doesn't have to be complicated. For more information please contact your onsite
Wellness Professional.
The Effects of Weight Self-Monitoring
70
APPENDIX G
Week 3 Email
Looking for ways to become more active? Think about your barriers to being active. Then try to
come up with creative ways to solve them. The following examples may help you overcome
barriers:
Barriers
•
•
•
•
•
I don’t have enough time.
I can’t stay motivated.
I feel self-conscious when I’m active.
I’m worried about my health or injury.
I just don’t like exercise.
Solutions
•
•
•
•
•
Be active for a few minutes at a time throughout the day. Sit less. Try to walk more while
doing your errands, or schedule some lunchtime workouts to boost your overall activity.
Plan ahead and be creative!
Try to add variety to your activities and rely on friends to stay focused on being active.
Try activity videos for extra encouragement. Set realistic goals, track your progress, and
be sure to celebrate your achievements.
Be active at home while doing household chores and find ways to move more during
your day-to-day activities. Try walking with a group of friends with whom you feel
comfortable.
You might feel better if you talk to a health care professional first. Find a fitness provider
to guide you, or sign up for a class so you feel safe. Remember that activity does not have
to be difficult. Gentle activity is good too.
Good news – you do not have to run or do push-ups to get the benefits of physical
activity. Try dancing to the radio, walking outdoors, or being active with friends to spice
things up.
For more information please contact your onsite Wellness Professional.
The Effects of Weight Self-Monitoring
71
APPENDIX H
Week 4 Email
Goal Setting Tips
Are you having trouble sticking to your program? If so, maybe it’s time to reevaluate your
objectives. The first place to start is to make a real commitment to this change and do it for you.
Once you’ve recognized your commitment, you can create a resolution that will help you avoid
the pitfalls you may face on the journey to better health. Consider the following goal setting
information to help you maintain your focus.
Goals should be S.M.A.R.T.
Specific: The goals must specifically state what you want to accomplish.
Measureable: Measurable goals allow you to evaluate your progress, and are either objective or
subjective (i.e., how you feel and look), or both.
Attainable: The goals cannot be too difficult or too easy. Easy goals do not motivate, and overly
difficult ones may frustrate you and lead to a perception of failure.
Relevant: The goals must be pertinent to your particular interests, needs and abilities.
Time-bound: The goals must have specific deadlines for completion. Timelines can be both
short-term and long-term, and should help you stay focused and on track.
Tips for Success
•
Pick one goal each week that you feel confident you can modify in your lifestyle for
years to come.
o Every week, record the date of commitment
o Modify your goals if necessary
o Lower goals that are found to be unrealistic
• Post a note of your goal on your refrigerator or other visible areas so you are more likely
to succeed.
• Identify the behaviors that are necessary to reach your goal(s).
o Planning activities & meals is essential to long-term weight loss success: "People
don't plan to fail, they fail to plan."
• Commit and implement a plan.
• Share your goal with those close to you, and ask them for their support.
• Regularly assess your progress
o Use fitness tests, training journal, food diary, etc. to gauge where you stand, and
see how far you’ve come!
o Recommit to goals if necessary
For more information please contact your onsite Wellness Professional.
The Effects of Weight Self-Monitoring
72
APPENDIX I
Week 5 Email
Healthy Living and Weight Control
The trick to healthy living and weight control is making small changes:
•
•
•
•
taking more steps,
adding fruit to your cereal,
having an extra glass of water
getting an extra hour of sleep...these are just a few ways you can start living healthy
without drastic changes.
For example, becoming more active doesn’t necessarily mean starting a formal exercise regimen.
The truth is, movement is movement, and the more you do, the healthier you’ll be. Even
moderate exercise, like gardening and walking, can make a difference. The same with dietary
changes – eating fewer calories and less fat doesn’t usually require major changes. Simply
making one or two healthy changes to your eating habits can pay off in big rewards, and small
changes are easier to maintain. Creating a healthy lifestyle doesn’t have to mean drastic changes.
In fact, drastic changes often lead to failure. Small changes can lead to big rewards, so figure out
what you can do to be healthier today!
For more information please contact your onsite Wellness Professional.
The Effects of Weight Self-Monitoring
73
APPENDIX J
Week 6 Email
Motivation Strategies
You have declared that you want to lose weight. You have begun watching what you eat and
increasing your activity, but now you must stay motivated. It is common to face mental
roadblocks and resistance when you begin a lifestyle change. Here are some strategies to bolster
and sustain the motivation you will need to be successful:
Emphasize the positives
Focus on the good things about losing weight — such as more energy and improved health —
and not what you consider the negatives. If you have a setback, don't dwell on it. Put it behind
you and move forward toward your goal.
Prioritize
Don't set yourself up for failure by trying to lose weight while distracted by other concerns.
Steer clear of dietary gimmicks
Over-the-counter pills and special food combinations aren't the answer to long-term weight
control. You want to incorporate healthy behaviors into your lifestyle, not rely on gimmicks.
Seek out support
Don't feel you have to go it alone. Exercising with a friend or family member, for example, can
help keep you motivated.
Remind yourself you're not looking for a quick fix
Healthy weight loss is slow and steady weight loss that occurs over time. Remind yourself that
quick weight loss is usually followed by weight regain a short time later.
For more information please contact your onsite Wellness Professional.
The Effects of Weight Self-Monitoring
APPENDIX K
Week 7 Email
Learn What Cross Training Can Do For You!
Cross training is a program in which several different forms of exercise are used to develop
the various components of fitness.
Benefits
•
•
•
•
Reduced risk of injury: When using the same mode of exercise, stress on particular
muscles and joints can cause injuries. Cross training allows you to spread the stress
over additional muscles and joints, thereby allowing you to exercise more frequently
and for longer durations without an elevated risk of injury.
Enhanced weight loss: Research has shown that in order to burn a significant number
of calories and decrease body fat, it is best to exercise for relatively long durations (i.e.,
more than 30 minutes) at a moderate level of intensity (i.e., 60% to 85% of maximal
heart rate). An example of this would be to exercise on an elliptical trainer for 20 to 30
minutes, and then cycle for an additional 20 to 30 minutes.
Improved total fitness: Cross training can be used with strength training as well as
aerobic conditioning programs. Research has shown that resistance training can help
individuals prevent injury, control body weight and improve functional capacity.
Enhanced exercise adherence: Cross training is a safe and relatively easy way to add
variety to an exercise program. It can play a positive role in promoting long-term
exercise adherence by reducing the incidence of injury and eliminating or diminishing
the potential for boredom.
Ways to incorporate cross training into your program
•
•
•
•
Try varying your exercise program from workout to work out by trying different types
of activities.
Simply add a new form of exercise to your existing workout routine. Examples include
resistance training, Pilates, or a boot-camp class.
Alternate between activities. For example, run one day, stair climb the next, cycle the
day after.
Alternate activities within a single workout. For instance, walk on a treadmill for 10
minutes, use an elliptical trainer for 10 minutes and cycle for 10 minutes.
Visit www.acefitness.org for more information or contact your onsite Wellness Professional.
74
The Effects of Weight Self-Monitoring
75
APPENDIX L
Week 8 Email
Can you go through ONE day without eating processed foods?
Take one day this week to see if you can go a whole day without processed or fast food. That
means no packaged breakfast cereals, processed lunch meats, breakfast muffins, frozen dinners,
candy bars or anything that has a list of ingredients that you can't pronounce. Do you think you
can do it? One day?
Just keep it fresh and simple. Focus on:
Lots of fruit, vegetables, nuts, seeds, organic grass fed meat or poultry, and whole grains.
Drink plenty of water. Try it for just one day and see how well you can do. Take the time to
notice what you are eating. Eat more whole foods and you will feel a whole lot better!
For more information please contact your onsite Wellness Professional.
The Effects of Weight Self-Monitoring
76
APPENDIX M
Week 9 Email
Stress can affect your weight loss efforts!
Some people tend to gain weight when under stress. When you're stressed out, you may find it
more difficult to maintain healthy-eating habits. Also, many people may eat in an attempt to
fulfill emotional needs during a particularly stressful time. These and other factors can contribute
to stress-related weight gain.
There are numerous ways to reduce stress. Choose a method that works for you! Not sure what to
do? Physical activity is one way to lowering stress. Try doing anything active and begin to feel
better!
For more information please contact your onsite Wellness Professional.
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