In addition to depressed mood, perceived stress has been linked with weight [ 19 ]. For example, lower ratings of baseline stress were associated with greater weight loss in one study [ 20 ]. However, the literature is mixed with some studies failing to find an association between perceived stress and body weight [ 21 ]. Finally, social support is another psychosocial variable that has been shown to be associated with improvements in weight and physical activity behavior e.
Psychological factors like depression and stress may interact with other theory-based variables like self-efficacy to promote participant behavior change that is associated with weight loss. With regard to physical activity promotion and weight management, Social Cognitive Theory SCT; [ 23 ] and the Transtheoretical Model of Change TTM; [ 24 ] are discussed frequently within the literature and used to tailor interventions e.
Self-efficacy eating and exercise-related has been shown to be predictive of short-term weight change [ 27 , 28 ]. Additionally, self-efficacy has been shown to be a critical intermediate variable associated with physical activity and weight loss maintenance [ 29 ].
The TTM also highlights other constructs like decisional balance, or the pros and cons of behavior change, and the processes of change cognitive and behavioral [ 30 , 31 ]. Decisional balance and processes of change have been associated with increased physical activity and weight loss [ 27 , 29 ]. However, participation in an exercise promotion trial may not always improve all theoretical constructs e. Overall, theory-based interventions targeting physical activity and body weight have been shown to be largely effective, and these interventions have been delivered via a number of channels including face-to-face, mailings, and the Internet [ 33 — 37 ].
Despite these studies, additional work is needed to determine the ideal components of interventions designed to promote physical activity and weight loss. In particular, there is a continued need to clarify the roles of behavioral and psychosocial variables that affect physical activity and weight management.
In this project, women were randomly assigned to one of three groups: 1 Choose to Move CTM , a print-based physical activity intervention designed specifically for women, 2 JumpStart , a motivationally tailored print-based intervention, or 3 Wellness contact-control group.
The interventions see below focused on the adoption on maintenance of physical activity and did not include calorie goals or weight loss targets. Since participants completed 1-year follow-up assessments, this type of physical activity trial is useful for assessing change in weight status among participants.
A 1-year time point was selected as this is a designated time point for determining long-term maintenance of weight loss [ 12 ]. Given the importance of understanding individual variability in weight stability and response to physical activity interventions, we proposed to examine and identify evidence-based constructs associated with weight stability. Therefore, we hypothesized that psychosocial and behavioral variables, selected based on research and theory e.
Additionally, flyers were distributed in the libraries, to town employees with their paychecks, and to school department employees in their mailboxes. Mass media approaches included inserts in local, regional, and special interest newspapers and public service announcements on cable-access television and radio.
The recruitment message was targeted to women and included a brief overview of eligibility requirements and study purpose. Potential participants were prompted to call a toll free number to obtain information and determine eligibility and via a brief telephone screen prior to participation. Healthy, sedentary women between the ages of 18 to 65 years were recruited, with sedentary defined as participating in 90 minutes or less of purposeful physical activity or 61 minutes or less of vigorous physical activity [ 35 ].
Other exclusion criteria included medical problems that could potentially impede or be exacerbated by physical activity e. Physician consent was required for individuals with hypertension, murmurs, and mitral valve prolapse. In addition, individuals were excluded if there was a planned move from the area within the next year, current or planned pregnancy, hospitalization for a psychiatric disorder within the last 6 months, current suicidal or psychotic episodes, or current use of certain prescription medications e.
A total of women responded to the recruitment strategies for the study. See Figure 1 for a participant flow chart. Of the participants who met the eligibility requirements for the study, participants were randomly assigned at baseline into one of the three study arms. For these analyses, an of will be used as this is the sample size for which we have complete BMI data at baseline and Month The mean BMI was The primary assessment time points were Months 3 and 12 after baseline.
At these time points, participants attended an in-person assessment session and completed questionnaires and objective measures. For the purposes of these analyses, only the baseline and Month 12 values will be used.
Choose to Move was a print-based booklet developed by the American Heart Association to help women adopt and maintain physical activity. The booklet was a week program targeted to women, with each week covering a topic of relevance from Social Cognitive Theory and the Transtheoretical Model such as goal setting, benefits of physical activity, increasing confidence, as well as self-report logs and self-administered worksheets.
No information was included regarding calorie or fat goals. Jumpstart was a print-based intervention that was developed and validated by researchers at the Miriam Hospital and Brown University [ 38 , 39 ]. The Jumpstart intervention consisted of tailored expert system reports and a booklet matched to Stage of Motivational Readiness for Change [ 38 , 39 ].
The expert system report consisted of pre-written counseling messages on self-efficacy, barriers, benefits, social support, goal setting, and strategies for change that were provided based on information obtained from each participant [ 26 ]. Each participant in the tailored-intervention group received a mailing 4 times during the course of the 12 months baseline, Month 1, Month 3, and Month 6. Sample topics included emotional and mental well-being and stress management. Height and weight were obtained at the baseline and Month 12 clinic visits.
Height was assessed via a stadiometer; weight was measured via a calibrated scale. The interviewer administered PAR [ 40 , 41 ], was the primary outcome measure. The PAR has established validity and reliability [ 40 , 41 ], and it has been shown to be sensitive to change in studies of moderate intensity activity e.
The scale has good internal consistency 0. Each subscale has demonstrated reliability coefficient alphas of 0. This item measure assesses the Processes of Change for physical activity. There are two factors, behavioral and cognitive processes, each consisting of five subscales.
The internal consistency of the Processes of Change scales averaged 0. This social support scale is a item measure that assesses the degree to which family or friends are sources of support specific to physical activity.
This item measure assessed the extent to which a participant evaluated different situations as stressful e. The Perceived Stress scale has been shown to have good reliability and validity [ 47 ]. The CES-D scale is a item self-report measure developed to assess depressive symptoms in the general population [ 48 ].
The CES-D scale is composed of 1 depressive affect; 2 positive affect; 3 somatic and retarded activity; 4 interpersonal problems; with.
For the purpose of this study, participants self-reported the number of hours spent watching television per week. The Fruit and Vegetable screener assesses 10 fruit and vegetable food items over the period of the last month. It includes items assessing the frequency of eating certain foods e. This measure is designed to provide an estimate of the total number of Pyramid servings of fruits and vegetables consumed daily.
Estimated correlations between this instrument and a recall were 0. The Fat Screener is a item measure designed to provide an estimate of the percent of energy from fat. This measure includes items to assess the frequency a participant consumed certain foods e. Responses were coded and weighted in order to estimate the percent of energy from fat. This screener was validated against two hour recalls collected from a nationally representative sample in the United States and a Food Frequency Questionnaire.
The Fat Screener correlations with true fat intake ranged from 0. All analyses were performed using SAS 9.
A list of theoretically and research-based constructs was selected to investigate which variables discriminated weight status change i. Change scores were calculated with change from baseline to Month 12 on the variables of interest.
First, a stepwise discriminant analysis was used to select the subset quantitative variables for the use of subsequent analysis to discriminate among the classes. Next, a discriminant function analysis using the variables identified in the stepwise discriminant analysis was conducted. At the month follow-up, participants in all treatment arms had increased their physical activity , , with no differences between the arms [ 35 ].
There were no differences on key variables i. Furthermore, there was no differential dropout between the groups. There also were no differences between the treatment arms on weight change ;.
Therefore, for the purpose of this paper, data will be collapsed across treatment arms. Based on the research literature of behavioral and psychological factors related to weight change e. The constructs were depressive symptoms, physical activity, sedentary behavior i.
See Table 1 for the change scores from baseline to Month Models were run with both stepwise and forward entries, with the same cluster of variables being produced by each model. The results of the stepwise entry will be presented here. Discriminant analyses revealed depressive symptoms F ; , physical activity behavior F ; , self-efficacy F ; , fat consumption F ; , and cognitive processes of change F ; as discriminating variables. Tests of dimensionality indentified two distinct dimensions; both of the dimensions were statistically significant.
Dimension 1 F ; had a canonical correlation of 0. Standardized canonical coefficients for both dimensions were examined with the first dimension positively weighted by changes in mood 0. The second discriminant dimension was more weighted to change in physical activity 0.
The first dimension reflects a negative affect and self-confidence dimension, while the second reflects a physical activity and dietary behavior dimension. See Table 2 for the standardized pooled, within class standardized canonical coefficients, which can be interpreted similarly to standardized regression coefficients. For example, a one standard deviation increase on the depression variable will result in a.
The results from the discriminant function analysis indicated two statistically significant dimensions. The first dimension was a psychological dimension weighted by changes in depressive symptoms and self-efficacy for physical activity.
When examining the mean changes on these variables by weight status classification, women who gained weight reported increases in depressed mood ; , compared with women who lost weight ; or remained weight stable ;. This finding is consistent with other studies in which depressive symptomatology was negatively associated with weight regain [ 12 ]. There are a few explanations for the association between mood and weight.
Successful and purposeful weight loss is associated with improved mood [ 17 , 18 ]. A child will learn to use food to numb pain and cut off from, or suppress, emotions.
In the present day, food is still used to soothe difficult emotions, brought about by dysfunctional relationships, which are an echo of the blueprint laid down by the earlier abusive relationship. Obesity and a larger physical size can become a protective physical barrier to make an individual unattractive to others, thus keeping them safe from unwanted attention. Eating remains as an unhealthy coping mechanism for dealing with overwhelming feelings. The sections above describe some of the most common psychological factors that shape weight issues for our obese clients.
It is essential to understand how and why you struggle with eating and your weight in the present day, and this comes from investigating what happened to you in the past. With this awareness and understanding, we can support you in changing and updating the old patterns that are keeping you rooted in your weight dysfunction. Every obese individual is different, and you will have your own unique story that explains your struggle with food.
For this reason the treatment and support we offer must be tailored to address your individual needs. We have developed different psychological and nutritional services to support you in healing your mind and body. By addressing your nutrition, lifestyle and mindset, we can help you reach optimal wellness and develop a healthy relationship with food, eating and body image. Please Book A Call with our experienced assessment team who will explain how our services can help you.
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Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings. If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again. Here are some psychological factors that maintain obesity: avoidance of emotions low self-worth poor body image self-criticism negative core beliefs binge eating Cognitive-behavioural strategies CBT can be very effective in helping you calm your eating, improve mood and give you a sense of feeling more in control.
We review a few of the more common reasons here. Here are several reasons why weight loss before bariatric surgery is important. When it comes to determining whether your weight is healthy or not, it often comes down to numbers, namely your body mass index calculation. Here, we outline what you can do in advance to ease the way forward to the new you.
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