The Impact of Weight Stigma on Caloric Consumption
TL;DR: It is suggested that among overweight women, exposure to weight stigmatizing material may lead to increased caloric consumption, which directly challenges the notion that pressure to lose weight in the form of weight stigma will have a positive, motivating effect on overweight individuals.
Abstract: The present study assessed the influence of exposure to weight stigma on energy intake in both overweight and normal-weight adult women. Seventy-three women (mean age: 31.71 ± 12.72 years), both overweight (n = 34) and normal weight (n = 39), were randomly assigned to view one of two videos depicting either weight stigmatizing material or neutral material, after which they consumed snacks ad libitum. Pre- and post-video measures included blood pressure, attitudes toward overweight individuals, and positive and negative affect. Participants' body weight was measured, as was the number of kilocalories consumed following video exposure. Overweight women who watched the stigmatizing video ate more than three times as many kilocalories as overweight women who watched the neutral video (302.82 vs. 89.00 kcal), and significantly more calories than the normal-weight individuals who watched either the stigmatizing or the neutral video. A two-by-two analysis of covariance revealed that even after adjusting for relevant covariates, there was a significant interaction between video type and weight status in that when overweight, individuals consumed significantly more calories if they were in the stigmatizing condition vs. the neutral condition (F(1,65) = 4.37, P = 0.04, η(2) = 0.03). These findings suggest that among overweight women, exposure to weight stigmatizing material may lead to increased caloric consumption. This directly challenges the notion that pressure to lose weight in the form of weight stigma will have a positive, motivating effect on overweight individuals.
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TL;DR: This work provides illustrative evidence on the health consequences of stigma and presents a conceptual framework describing the psychological and structural pathways through which stigma influences health.
Abstract: Bodies of research pertaining to specific stigmatized statuses have typically developed in separate domains and have focused on single outcomes at 1 level of analysis, thereby obscuring the full significance of stigma as a fundamental driver of population health. Here we provide illustrative evidence on the health consequences of stigma and present a conceptual framework describing the psychological and structural pathways through which stigma influences health. Because of its pervasiveness, its disruption of multiple life domains (e.g., resources, social relationships, and coping behaviors), and its corrosive impact on the health of populations, stigma should be considered alongside the other major organizing concepts for research on social determinants of population health.
1,768 citations
Cites background from "The Impact of Weight Stigma on Calo..."
...participants who watched the neutral videos, further supporting the link between stigma and health-compromising behaviors.(86) Stress...
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TL;DR: The purpose of this review is to evaluate the existing literature for evidence supporting a cyclic obesity/weight-based stigma model, propose ways in which individuals enter, fight against, and exit the cycle, and conclude by outlining fruitful future directions in this nascent yet important area of research.
427 citations
Additional excerpts
...Schvey, Puhl, and Brownell (2012)Fig....
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King's College London1, University of Cambridge2, University of Connecticut3, University of Washington4, Anschutz Medical Campus5, Louisiana State University6, Icahn School of Medicine at Mount Sinai7, Mount Sinai Hospital8, Diabetes UK9, Boston University10, Boston Medical Center11, Cornell University12, University College London13, University College Hospital14, Louisiana State University System15, Adolfo Ibáñez University16, University of Padua17, Rabin Medical Center18, Indiana University19, Stanford University20, University of Leeds21, City University of New York22, Harvard University23, Pennington Biomedical Research Center24, Columbia University25, University College Dublin26, American Diabetes Association27, The Catholic University of America28, Penn State Milton S. Hershey Medical Center29, University of Michigan30, Complutense University of Madrid31, Baker IDI Heart and Diabetes Institute32
TL;DR: In this paper, a multidisciplinary group of international experts, including representatives of scientific organizations, reviewed available evidence on the causes and harms of weight stigma and, using a modified Delphi process, developed a joint consensus statement with recommendations to eliminate weight bias.
Abstract: People with obesity commonly face a pervasive, resilient form of social stigma. They are often subject to discrimination in the workplace as well as in educational and healthcare settings. Research indicates that weight stigma can cause physical and psychological harm, and that affected individuals are less likely to receive adequate care. For these reasons, weight stigma damages health, undermines human and social rights, and is unacceptable in modern societies. To inform healthcare professionals, policymakers, and the public about this issue, a multidisciplinary group of international experts, including representatives of scientific organizations, reviewed available evidence on the causes and harms of weight stigma and, using a modified Delphi process, developed a joint consensus statement with recommendations to eliminate weight bias. Academic institutions, professional organizations, media, public-health authorities, and governments should encourage education about weight stigma to facilitate a new public narrative about obesity, coherent with modern scientific knowledge.
404 citations
TL;DR: The nature and extent of weight stigmatization against overweight and obese individuals, as well as the resulting consequences that these experiences create for social, psychological, and physical health for children and adults who are targeted, are summarized.
368 citations
University of South Florida1, Cleveland Clinic Lerner College of Medicine2, University of Kent3, University of North Carolina at Chapel Hill4, Chapman University5, University of Hawaii6, State University of New York System7, University of Florence8, University of Sussex9, Michigan State University10, La Trobe University11, University of Westminster12
TL;DR: The Sociocultural Attitudes Towards Appearance Questionnaire-3 (SATAQ-3) and its earlier versions are measures designed to assess societal and interpersonal aspects of appearance ideals as discussed by the authors.
Abstract: The Sociocultural Attitudes Towards Appearance Questionnaire-3 (SATAQ-3) and its earlier versions are measures designed to assess societal and interpersonal aspects of appearance ideals. Correlational, structural equation modeling, and prospective studies of the SATAQ-3 have shown consistent and significant associations with measures of body image disturbance and eating pathology. In the current investigation, the SATAQ-3 was revised to improve upon some conceptual limitations and was evaluated in 4 U.S. and 3 international female samples, as well as a U.S. male sample. In Study 1, exploratory and confirmatory factor analyses for a sample of women from the Southeastern United States (N = 859) indicated a 22-item scale with 5 factors: Internalization: Thin/Low Body Fat, Internalization: Muscular/Athletic, Pressures: Family, Pressures: Media, Pressures: Peers. This scale structure was confirmed in 3 independent and geographically diverse samples of women from the United States (East Coast N = 440, West Coast N = 304, and North/Midwest N = 349). SATAQ-4 scale scores demonstrated excellent reliability and good convergent validity with measures of body image, eating disturbance, and self-esteem. Study 2 replicated the factorial validity, reliability, and convergent validity of the SATAQ-4 in an international sample of women drawn from Italy, England, and Australia (N = 362). Study 3 examined a sample of college males from the United States (N = 271); the 5-factor solution was largely replicated, yet there was some evidence of an underlying structure unique to men. Future research avenues include additional item testing and modification of the scale for men, as well as adaptation of the measure for children and adolescents.
363 citations
References
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Book•
01 Jan 1983
TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
Abstract: In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Book Chapter 3 Review of Univariate and Bivariate Statistics Chapter 4 Cleaning Up Your Act: Screening Data Prior to Analysis Chapter 5 Multiple Regression Chapter 6 Analysis of Covariance Chapter 7 Multivariate Analysis of Variance and Covariance Chapter 8 Profile Analysis: The Multivariate Approach to Repeated Measures Chapter 9 Discriminant Analysis Chapter 10 Logistic Regression Chapter 11 Survival/Failure Analysis Chapter 12 Canonical Correlation Chapter 13 Principal Components and Factor Analysis Chapter 14 Structural Equation Modeling Chapter 15 Multilevel Linear Modeling Chapter 16 Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS Chapter 1: Introduction Multivariate Statistics: Why? Some Useful Definitions Linear Combinations of Variables Number and Nature of Variables to Include Statistical Power Data Appropriate for Multivariate Statistics Organization of the Book Chapter 2: A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques Some Further Comparisons A Decision Tree Technique Chapters Preliminary Check of the Data Chapter 3: Review of Univariate and Bivariate Statistics Hypothesis Testing Analysis of Variance Parameter Estimation Effect Size Bivariate Statistics: Correlation and Regression. Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to Analysis Important Issues in Data Screening Complete Examples of Data Screening Chapter 5: Multiple Regression General Purpose and Description Kinds of Research Questions Limitations to Regression Analyses Fundamental Equations for Multiple Regression Major Types of Multiple Regression Some Important Issues. Complete Examples of Regression Analysis Comparison of Programs Chapter 6: Analysis of Covariance General Purpose and Description Kinds of Research Questions Limitations to Analysis of Covariance Fundamental Equations for Analysis of Covariance Some Important Issues Complete Example of Analysis of Covariance Comparison of Programs Chapter 7: Multivariate Analysis of Variance and Covariance General Purpose and Description Kinds of Research Questions Limitations to Multivariate Analysis of Variance and Covariance Fundamental Equations for Multivariate Analysis of Variance and Covariance Some Important Issues Complete Examples of Multivariate Analysis of Variance and Covariance Comparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated Measures General Purpose and Description Kinds of Research Questions Limitations to Profile Analysis Fundamental Equations for Profile Analysis Some Important Issues Complete Examples of Profile Analysis Comparison of Programs Chapter 9: Discriminant Analysis General Purpose and Description Kinds of Research Questions Limitations to Discriminant Analysis Fundamental Equations for Discriminant Analysis Types of Discriminant Analysis Some Important Issues Comparison of Programs Chapter 10: Logistic Regression General Purpose and Description Kinds of Research Questions Limitations to Logistic Regression Analysis Fundamental Equations for Logistic Regression Types of Logistic Regression Some Important Issues Complete Examples of Logistic Regression Comparison of Programs Chapter 11: Survival/Failure Analysis General Purpose and Description Kinds of Research Questions Limitations to Survival Analysis Fundamental Equations for Survival Analysis Types of Survival Analysis Some Important Issues Complete Example of Survival Analysis Comparison of Programs Chapter 12: Canonical Correlation General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Canonical Correlation Some Important Issues Complete Example of Canonical Correlation Comparison of Programs Chapter 13: Principal Components and Factor Analysis General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Factor Analysis Major Types of Factor Analysis Some Important Issues Complete Example of FA Comparison of Programs Chapter 14: Structural Equation Modeling General Purpose and Description Kinds of Research Questions Limitations to Structural Equation Modeling Fundamental Equations for Structural Equations Modeling Some Important Issues Complete Examples of Structural Equation Modeling Analysis. Comparison of Programs Chapter 15: Multilevel Linear Modeling General Purpose and Description Kinds of Research Questions Limitations to Multilevel Linear Modeling Fundamental Equations Types of MLM Some Important Issues Complete Example of MLM Comparison of Programs Chapter 16: Multiway Frequency Analysis General Purpose and Description Kinds of Research Questions Limitations to Multiway Frequency Analysis Fundamental Equations for Multiway Frequency Analysis Some Important Issues Complete Example of Multiway Frequency Analysis Comparison of Programs
53,113 citations
TL;DR: Two 10-item mood scales that comprise the Positive and Negative Affect Schedule (PANAS) are developed and are shown to be highly internally consistent, largely uncorrelated, and stable at appropriate levels over a 2-month time period.
Abstract: In recent studies of the structure of affect, positive and negative affect have consistently emerged as two dominant and relatively independent dimensions. A number of mood scales have been created to measure these factors; however, many existing measures are inadequate, showing low reliability or poor convergent or discriminant validity. To fill the need for reliable and valid Positive Affect and Negative Affect scales that are also brief and easy to administer, we developed two 10-item mood scales that comprise the Positive and Negative Affect Schedule (PANAS). The scales are shown to be highly internally consistent, largely uncorrelated, and stable at appropriate levels over a 2-month time period. Normative data and factorial and external evidence of convergent and discriminant validity for the scales are also presented.
34,482 citations
"The Impact of Weight Stigma on Calo..." refers background in this paper
...The PANAS may be used as a trait version or may be used to assess state affect (when prefaced with “right now” or “in this moment”)....
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...The PANAS is highly internally consistent and has strong convergent and discriminant validity (30)....
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...The PANAS was administered to assess affect both before, and after, the video clips, and thus, the “state” instructions were employed....
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...Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales....
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...The Positive Affect Negative Affect Schedule (PANAS) (30) is a 20-item scale that measures participants’ positive and negative affect along a number of dimensions....
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TL;DR: A meta-analysis of the BDI's internal consistency estimates yielded a mean coefficient alpha of 0.86 for psychiatric patients and 0.81 for non-psychiatric subjects as mentioned in this paper.
11,149 citations
TL;DR: The increases in the prevalence of obesity previously observed do not appear to be continuing at the same rate over the past 10 years, particularly for women and possibly for men.
Abstract: Results In 2007-2008, the age-adjusted prevalence of obesity was 33.8% (95% confidence interval [CI], 31.6%-36.0%) overall, 32.2% (95% CI, 29.5%-35.0%) among men, and 35.5% (95% CI, 33.2%-37.7%) among women. The corresponding prevalence estimates for overweight and obesity combined (BMI 25) were 68.0% (95% CI, 66.3%-69.8%), 72.3% (95% CI, 70.4%-74.1%), and 64.1% (95% CI, 61.3%66.9%). Obesity prevalence varied by age group and by racial and ethnic group for both men and women. Over the 10-year period, obesity showed no significant trend among women (adjusted odds ratio [AOR] for 2007-2008 vs 1999-2000, 1.12 [95% CI, 0.89-1.32]). For men, there was a significant linear trend (AOR for 2007-2008 vs 1999-2000, 1.32 [95% CI, 1.12-1.58]); however, the 3 most recent data points did not differ significantly from each other.
7,730 citations
"The Impact of Weight Stigma on Calo..." refers background in this paper
...The ANCOVA revealed a significant main effect of video type on caloric consumption, in that those in the stigmatizing condition, collapsed across weight status, consumed more calories than those in the neutral condition (F(1,65) = 7....
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...In accordance with our hypothesis, there was a significant weight status by video type interaction; when in the stigmatizing condition, individuals consumed significantly more calories if they were overweight (F(1,65) = 4....
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...There was no main effect of weight status on caloric consumption (F(1,65) = 0....
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...004), and age was the only significant covariate in the model (F(1,65) = 7....
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...More than two-thirds of Americans over the age of 20 are now overweight and over one-third are obese (1)....
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TL;DR: The first step was a collation of items from two existing questionnaires that measure the related concepts of 'restrained eating' and 'latent obesity', to which were added items newly written to elucidate these concepts.
4,391 citations
"The Impact of Weight Stigma on Calo..." refers background in this paper
...The TFEQ has been shown to be a valid and reliable instrument (24) with internal consistency coefficients ranging from 0.70 to 0.90 (26)....
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...Karlsson J, Persson LO, Sjöström L, Sullivan M. Psychometric properties and factor structure of the Three-Factor Eating Questionnaire (TFEQ) in obese men and women....
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...The Three-Factor Eating Questionnaire (TFEQ) (24,25) is a 51-item self-report questionnaire that assesses restraint, disinhibition, and susceptibility to hunger....
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...The TFEQ was administered before the video clip....
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