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Abstract

The prevalence of weightism and weight self-stigma are gaining more prominence globally; however, the awareness of its impact is yet to be established. This review aimed to fill the literature gaps and provide a robust and up-to-date account of the biological, psychological, social, and behavioral impact of weightism and weight self-stigma on the obese population. By using a systematic approach, this review utilized five academic databases (PubMed, Scopus, PsycInfo, Medline, Web of Science) to systematically search for studies. Thirty eligible studies met the inclusion criteria with a total of 31,221 participants and these studies either measured the impact of weightism, weight self-stigma or both on the obese population. All the studies were found to have consistent evidence on the impact of weight stigma and weight self-stigma on the obese population such as psychological distress, high body mass index (BMI), body dissatisfaction, disordered eating and more. Researchers are recommended to explore the impact of weight stigma and weight self-stigma in the Asian population as well due to the lack of evidence. The findings of this review provided significant implications and future directions for developing interventions that address weight self-stigma to improve physical and psychological well-being.

Plain language summary

Weight stigma and weight self stigma has been gaining more awareness globally; however, the awareness of its impact is yet to be established. Therefore, a systematic review was conducted by following the reporting checklist of the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA), to provide details on the biological, psychological, social, and behavioral impact of weight stigma and weight self-stigma on the obese population. Thirty eligible studies met the inclusion criteria from various countries and all the studies were found to have consistent evidence on the impact of weight stigma and weight self-stigma on the obese population such as psychological distress, high body mass index (BMI), body dissatisfaction, disordered eating, lack in motivation and more. Future research should consider exploring the impact of weight stigma and weight self-stigma in the Asian and Middle Eastern population due to the lack of evidence. The findings of this review provided significant implications and future directions for developing interventions that address weight self-stigma to improve physical and psychological well-being.

Keywords

weight stigma weight self-stigma obese population psychological impact systematic review

Introduction

The World Health Organization (WHO, 2021) defines obesity as an “abnormal or excessive fat accumulation that may impair health”. Since 1970, the prevalence rate of obesity has been drastically increasing all over the world and this globally proportioned epidemic results in far-reaching consequences among the obese population (Haththotuwa et al., 2020). Obesity is recognized as a crucial public health concern not just because of its growing recognition of the prevalence rate and its detrimental consequences on one’s physical and psychological well-being, but also because of its rank as the fifth foremost reason for mortality globally (Safaei et al., 2021). While the prevalence rate of obesity rises every year, the rate of weightism and weight self-stigma simultaneously increases too. According to the World Federation Obesity, weightism, also known as weight stigma, is defined as “the discriminatory acts and ideologies targeted towards individuals because of their weight and size,” such as believing obese people as lazy, weak-willed, lack in motivation or discipline and more (Pont et al., 2017). These ideologies and attitudes that promote stigma could result in stigmatizing acts. Previous studies have demonstrated that stigmatizing acts come about in the form of mockery (e.g., “You will break the chair if you sit on it”), humiliation (e.g., “You’re so fat, you’ll never find a romantic partner”), or biased action (e.g., social rejection, inequality, fewer opportunities in career) in academia, wage disparity, and healthcare services (Alimoradi et al., 2020; Pont et al., 2017). As a result of the constant exposure to these stigmatizing acts, individuals with overweight and obesity tend to passively internalize these weight stigmas, and this is termed weight self-stigma. Weight self-stigma is defined as the “personal experiences of shame, negative self-evaluations as well as perceived discrimination” (Lillis et al., 2019, p. 55). For instance, individuals who are continuously exposed to weight stigma are likely to internalize and believe the stereotypical statements they hear, and this gradually leads to psychological distress such as a sense of shame, self-blame, and poor self-worth (Alimoradi et al., 2020).

Since 1990, a growing body of literature has emerged around weight stigma and even though the direction of its impact seems unclear, high weight stigma is significantly associated with a decrease in the physical and psychological well-being of the obese population (Puhl, Lesard et al., 2020; Remmert et al., 2019). Papadopoulos and Brennan (2015) stated that the obese population is stigmatized more than any other social group, regardless of gender or ethnicity. Surprisingly, Jenull et al. (2021) discovered that weightism towards obese people starts as young as 3 years old, where they display strong negative emotions such as hatred, disgust, and hostility towards people with larger bodies. Furthermore, weightism is ubiquitous and prevalent across settings such as the workplace, home, healthcare settings, and even in the gym (Sikorski et al., 2016). Recent research shows that the prevalence of weight self-stigma seems higher among obese individuals, regardless of gender, age, and ethnicity (Daly et al., 2017; Jackson et al., 2015), therefore this demonstrates that weight self-stigma is equally linked to poor physical and psychological well-being.

Additionally, previous evidence has shown that weight stigma and weight self-stigma act as contributing factors to the prevalence rate of obesity and hence why obesity rates have risen dramatically over the last 50 years, despite the extreme and widespread social pressure to be skinny (Hayward et al., 2020; Suelter et al., 2018). The focus of standard weight loss treatments is primarily on calorie restrictions and physical activities (Jensen et al., 2014), and this is one of the reasons contributing to the ignorance of weightism and weight stigma, as regardless of being the contributing factors to obesity, these two factors are not widely recognized or acknowledged in the weight-loss interventions. On the other hand, even though weight stigma is widely acknowledged in research, there is still a gap in our knowledge of the impacts and complexities of weight stigma and weight self-stigma on physical and psychological well-being. Additionally, although a growing body of evidence has emphasized weight stigma and weight self-stigma, some studies focused more on the causes and types of weight-related discrimination in the overweight and obese population and provided little to no exposure to the concept of weight self-stigma (Daly et al., 2019; Hunger et al., 2020). Furthermore, most studies have also excluded the younger obese population and emphasized more on the adult population, even though the prevalence rate of obesity is high among children. The majority of the research also focused on the prevalence of weight stigma among women and less attention was given to the male population (Hunger et al., 2015; Salvia et al., 2023).

Additionally, most of the research on weightism or weight self-stigma is western-based, hence the awareness of these two factors is lesser in the Asia-Pacific region (Cheng et al., 2018; Kamolthip et al., 2022; Lin et al., 2020). Since these key contextual aspects are not taken into account, the severity of weight stigma is likely to be underestimated thus, currently little is known about the overall impact of weightism and weight self-stigma on the obese population. This is surprising given the widespread commonness of weight stigma and weight self-stigma globally, across various cultures and yet the public awareness of these social risk factors is greatly lacking. Hence, this would seem timely to revisit the literature.

This proposed systematic review aims to identify and investigate the biological, psychological, social, and behavioral impact of weightism and weight self-stigma on the obese population. Consequently, this review also aims to explore the differences in the impact of weightism and weight self-stigma between males and females.

Methods

Protocol and Registration

Based on the review aims, this systematic review was conducted by following the reporting checklist of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Page et al., 2021). Furthermore, a protocol was developed and pre-registered in PROSPERO (ID: CRD42021290304) (Mathialagan et al., 2021) to document the analysis method and inclusion criteria. For the purpose of this study, a comprehensive and transparent literature search was undertaken to identify relevant research papers.

Search Strategy

The literature search was conducted in December 2021 (and updated in February 2022) via five electronic databases: Scopus, PubMed, PsycINFO, Web of Science and MEDLINE. Furthermore, grey literature was included in the searches conducted in the first four electronic databases listed above. The authors’ profiles were thoroughly scanned to ensure all the relevant studies were included. Moreover, all papers included in the review had their references checked to see if there is any additional research that is relevant to the proposed review. The search terms were based on two concepts. The first concept included terms that are relevant to weightism and weight self-stigma, and the second concept included terms related to the interconnections such as impact, consequences, and effect (see Table 1).

Table 1.

Keywords and Search Terms Used in the Systematic Review.

Weightism	Weight self-stigma		Impact
Weight stigma	Internalized weight stigma	AND	Biological impacts OR Biological consequences OR Biological effects OR Physiological impacts OR Physiological consequences OR Physiological effects
OR	OR		OR
Weight stigma experiences	Internalized weight bias		Psychological impacts OR Psychological consequences OR Psychological effects
OR	OR		OR
Obesity stigma	Perceived weight stigma		Social impacts OR Social consequences OR Social effects
OR	OR		OR
Weight discrimination	Perceived weight discrimination		Behavioral impacts OR Behavioral consequences OR Behavioral effects
OR	OR
Weight bias	Perceived weight bias
OR
Weight stereotypes

An example of search terms was (“biological impact” OR “biological consequences” OR “biological effect”) AND (“weightism” OR “weight-stigma” OR “weight-discrimination” OR “weight-bias” OR “weight-self-stigma” OR “perceived-weight-stigma” OR “internalized-weight-stigma”). These terms were searched for in the research papers’ titles, abstracts and/or keywords. The electronic database searches were undertaken independently by two reviewers. Additionally, the reviewers checked the search terms with two experts in the field of obesity and social psychology research to ensure accuracy and comprehensiveness.

Eligibility Criteria

Studies were eligible if they recruited a sample of individuals (regardless of age, gender, and ethnicity) whose Body Mass Index (BMI) fall within the obesity range based on the World Health Organisation (WHO, 2021) and the Asia Pacific BMI guideline. For instance, studies were included in the review if they recruited participants whose BMI is higher than 30.0 for the western population and BMI higher than 25.0 for the Asian and Middle Eastern populations. Studies were eligible if they were full-length and published in English only. Hence, all other publications, including research notes, book reviews, editors’ and readers’ comments were excluded. There were no specific restrictions on the types of study design eligible for inclusion or exclusion. In general, both quantitative and qualitative studies with any study designs (e.g., cross-sectional, longitudinal, case-control) were included. Furthermore, studies were incorporated in the review if they included at least one measure of any form of weight stigma or any form of weight self-stigma as a predictor and any biological, psychological, and social outcome measure. Dissertations, theses, and as well as published studies were included in the review, provided they supplied sufficient data for the inclusion. Studies were excluded if they merely used a sample of individuals whose BMI fall within the range of underweight, healthy weight or overweight based on both WHO and Asia Pacific BMI guidelines. Moreover, systematic literature reviews and meta-analyses were excluded from the results. Additionally, a thorough cross-check of these papers was done to ensure that no relevant papers were missed out for the current review. The studies’ publication years ranged from 2014 to 2023.

Study Selection

The identified study records’ title, abstract, author’s name, keywords, journal name and year of publication were exported to a Microsoft Excel spreadsheet to be individually screened. Two independent reviewers conducted the article screening by applying eligibility criteria and selecting studies for inclusion in this systematic review. This was done in two phases. In phase one, reviewers screened both title and abstract(s) of potential articles to exclude irrelevant articles. Next, a summary table was created to organize all potentially eligible articles based on the title, year of publication, participants, abstract and study design. In phase two, the eligible articles’ full text was carefully screened to determine the eligibility based on the specified inclusion and exclusion criteria. Furthermore, the reason for exclusion was recorded as well. Any disagreements or conflicts arising at any stage of the review were resolved through discussion. A third reviewer’s views were taken into consideration when no agreement was reached. If there were any studies with uncertainty or missing data that may fit the inclusion requirements, the investigator was contacted and more information about the study was gathered to determine the study’s eligibility.

Data Extraction

After the systematic search and screening were complete, the reviewers independently extracted the data from each eligible study that meets the inclusion criteria and recorded it in a Microsoft Excel Spreadsheet. Collected data included demographic characteristics (gender, race, body mass index, age, nationality), study design (sample size, recruitment methods, study year, country where the data was collected, measures used to assess weight stigma and weight self-stigma), and outcome data (descriptive statistics for these variables, correlations, regression where applicable, possible bias, strengths, and limitations. Any disagreements arising at any stage of the review were resolved through discussion between the two reviewers. A third reviewer’s views were taken into consideration when no agreement was reached.

Assessment of Risk of Bias

The methodological quality of each study was assessed by the two reviewers based on the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a variety of fields (Kmet et al., 2004). This tool assesses 14 methodological criteria for quantitative studies, where it evaluates whether the researchers’ question was sufficiently described, whether the outcomes measure(s) are well interpreted, and whether any extraneous/confounding variables were controlled for. The total quality score was calculated for each paper by summing up the total score of all the criteria and dividing it by the total possible score. The acquired score was then multiplied by 100 to get a percentage summary quality score (SQS). Each paper’s quality was then rated from a range of “limited” (less than 50%), “adequate” (50%–70%), “good” (70%–80%) to “strong” (greater than 80%). The second reviewer independently assessed the quality of each study based on the criteria. The scores obtained from both reviewers were compared and analyzed and disagreements were resolved by discussion between the reviewers or by consulting a third reviewer. Studies deemed of low quality were excluded without consulting the third reviewer. Figure 2 shows the summary of the quality assessment for the extracted studies and the detailed scoring matrix is attached in Appendix.

Results

Identification of Studies

Entering the search terms displayed in Table 1 as the search criterion led to the retrieval of 1,403 potentially relevant articles from five search engines and citation search: PubMed, Scopus, PsycInfo, Web of Science, and Medline. After eliminating duplicates (275 articles) and reviewing articles based on the title (531 articles), a total of 572 articles were selected for further processing. Two independent reviewers carefully screened the titles and abstracts of the remaining 572 articles and 476 articles were excluded. After applying the eligibility criteria to the remaining 121 articles, 91 articles were excluded as they did not meet the eligibility criteria. Among the 91 excluded articles, 16 had a study sample that was not relevant to the current review, 28 were non-impact related studies, 40 had no data of interest, and seven were review articles. Ultimately, when the data was extracted and these studies were further scrutinized, a total of 30 articles were selected and included in this review as shown in Figure 1.

Figure 1.

PRISMA flowchart of the selected studies.

Study Characteristics

The total number of participants in these 30 included studies was (N = 31,221). These articles were published between 2014 and 2021. These studies collected data from nine different countries: United States (N = 13), United Kingdom (N = 3), Australia (N = 3), Germany (N = 4), Poland (N = 1), Saudi Arabia (N = 2), South Africa (N = 1), Portugal (N = 1), and China (N = 2). Three studies sampled females only, whereas 22 studies had a higher ratio of women to men with an average of 87% women. All 30 articles were published quantitative studies and of all the studies, 73.3% (N = 22) were cross-sectional studies, 20% (N = 6) were longitudinal studies and 6.7% (N = 2) was randomized control trial. Participants in these studies were sampled from the clinical population (N = 6), community (N = 16), university students (N = 2), elementary school students (N = 2), and primary school students (N = 1), and three studies lacked information regarding their sample and the recruitment methods.

Since this review focuses on two different constructs; weight stigma and weight self-stigma, the findings of the included studies are grouped and presented separately based on the distinct ideas of weight stigma and weight self-stigma. Out of the 30 articles, 14 were found to have focused on only weight stigma and 12 emphasized only weight self-stigma. However, four articles included data on both weight stigma and weight self-stigma. Table 2 shows a summary of the study characteristics and findings for each of the included articles.

Table 2.

Summary of the Study Characteristics for Each of the Included Articles.

Authors	Country	Study design	Study population	Sample size	Average age (years)	Average BMI (kg/m²)	Measures of stigma	Findings
Weight stigma
Jach and Krystoń (2021)	Poland	Cross-sectional	Female (100%)	374	22.0	24.24	Self-developed weight stigma experiences assessment	Weight misperception, lower levels of self-esteem, body dissatisfaction
Wang et al. (2020)	China	Cross-sectional	Female (46%); male (54%)	1,818	16.5	26.6	POTS	Uncontrolled eating, emotional eating, and stress
Gerend et al. (2020)	USA	Cross-sectional	Female (81%); male (19%)	109	32.87	38.4	William and colleagues – Perceived weight discrimination	Appearance attribution (negative feedback on their appearance)
Puhl, Lesard et al. (2020)	USA	Longitudinal study	Female (64.2%); male (35.8%)	584	24.6 (at follow up)	28.2	Pre-pandemic weight stigma (C-EAT Survey)	Higher levels of depressive symptoms
Remmert et al. (2019)	USA	Cross-sectional	Female (82.4%); male (17.6%)	85	50.3	34.9	WBIS	Higher body mass index, greater levels of uncontrolled, and emotional eating
Govender et al. (2018)	South Africa	Cross-sectional	Female (83%); male (17%)	100	Not reported	40.8	Not reported	Abnormal eating behaviors such as compulsive eating, obsession with eating and psychological problems.
Wu et al. (2019)	USA	Cross-sectional	Female (44.6%); male (55.4%)	166	45.7	26.6	SSI	Lower hair cortisol, higher level of perceived racism, and perceived stress.
Griffiths et al. (2018)	Australia	Cross-sectional	Male (99.1%); transgender (0.9%)	2,733	33.93	Not reported	Self-developed experiences of weight-related treatment assessment	Poorer treatment in healthcare leads to higher body dissatisfaction and lower psychological QoL.
Jerdrzyan et al. (2016)	Germany	Cross-sectional	Female (52%); male (48%)	1,486	9.1	Not reported	POTS	Body dissatisfaction only among girls.
Jackson and Steptoe (2017)	UK	Cross-sectional	Female (61.2%); male (38.8%)	268	62.54	36.49	William and colleagues – Perceived weight discrimination	Reduced motivation to engage in exercise for weight control purposes.
Lee et al. (2021)	USA	Cross-sectional	Female (50.4%); male (49.4%)	1,327	47.7	28.0	Self-developed weight stigma assessment	Greater disordered eating, comfort eating, alcohol use, and sleep disturbance
Sutin et al. (2019)	USA	Longitudinal study	Female (69%); male (31%)	12,053	62.89 (at follow up)	Not reported	Self-developed weight stigma assessment	40% increased risk of developing dementia over the 8–10 years follow-up.
Gudzune et al. (2014)	USA	Cross-sectional	Female (41%); male (59%)	600	40.0	33.0	Not reported	Low levels of trust in primary care providers
Panza et al. (2023)	USA	Randomized controlled trial	Female (100%)	49	35.8%	35.7	A weight stigma depicting video	Increased levels of Systolic Blood pressure and Diastolic Blood Pressure, High levels of Airway Hyperresponsiveness over the sleep hours.
Weight self-stigma
Meadows and Higgs (2019)	UK	Cross-sectional	Female (78.5%); Male (21.5%)	158	26.0	29.6	SSI	Dietary restraint, and weight/shape concerns
Puhl et al. (2018)	USA	Cross-sectional	Female (50%); male (50%)	148	15.87	34.5	WBIS-M	Severe levels of binge eating and eating to cope with distress
Jung and Luck-Sikorski (2019)	Germany	Cross-sectional	Female (44.8%); male (55.2%)	1,000	56.4	50.1	WBIS	Higher levels of loneliness, sleep disturbances, night-eating symptoms
Chan et al. (2019)	China	Cross-sectional	Female (51.8%); male (48.2%)	114	9.95	23.2	WSSQ; WBIS	Poorer mental health well-being
Puhl, Himmelstein et al. (2020)	USA	Cross-sectional	Female (51.4%); male (48.4%)	1,227	52.04	31.6	WBIS	Higher levels of diabetes-specific distress.
Jung et al. (2020)	Germany	Cross-sectional	Female (68.4%); male (31.6%)	79	32.4	35.5	WBIS-M	Chronic stress, smaller cortisol secretion and less endocrinological responses to psychosocial stress.
Jackson and Steptoe (2018)	UK	Longitudinal study	Female (60.4%); male (39.6%)	577	68.4	Not reported	William and colleagues—Perceived weight discrimination	Higher mean of hair cortisol concentration.
Pearl et al. (2017)	USA	Cross-sectional	Female (88.1%); male (11.9%)	159	43.8	41.1	WBIS	Greater odds of having high triglycerides and of meeting criteria for metabolic syndrome, binge eating, reduced physical activity motivation and poorer self-reported physical health.
Palmeira et al. (2016)	Portugal	Cross-sectional	Female (100%)	282	44.24	31.40	WSSQ	Weight-related experiential avoidance, binge-eating symptomatology, and poorer obesity-related quality-of-life.
Khodari et al. (2021)	Saudi Arabia	Cross-sectional	Female (66.2%); male (33.8%)	399	21.12	28.5	WSSQ	Deterioration in physical health, psychological health, social relationships, and environmental health.
Almutairi et al. (2021)	Saudi Arabia	Cross-sectional	Female (61.5%); male (38.5%)	886	30.87	Not reported	WSSQ	Depression and anxiety
Walsh et al. (2018)	USA	Randomized controlled trial	Female (87.6%); male (12.4%)	178	44.2	40.9	WBIS	Lower levels of weight-related quality of life.
Weight stigma and weight self-stigma
Bevan et al. (2021)	Australia	Cross-sectional	Female (73.8%); male (26.2%)	579	19.8	Not reported	POTS; WBIS	Lower enjoyment of physical activity and sport.
Himmelstein et al. (2019)	USA	Cross-sectional	Male (100%)	1,753	39.2	26.8	WBIS-M; Self-developed Experience Weight Stigma assessment	Higher levels of depressive symptoms, severe levels of binge-eating, and high dieting habits
O’Brien et al. (2016)	Australia	Cross-sectional	Female (73.4%); male (26.6%)	117	20.43	29.0	WBIS-M; POTS	Greater emotional eating, uncontrolled eating, and loss-of-control eating.
Zuba and Warschburger (2017)	Germany	Cross-sectional	Female (52%); male (48%)	546	9.0	Not reported	WBIS-C; POTS	Greater emotional problem (depression, anxiety), body image dissatisfaction, conduct problems, restrained eating habits

Note. SSI = stigmatizing situations inventory; POTS = Perception of Teasing Scale; WBIS = Weight Bias Internalization Scale; WBIS-M = Modified Weight Bias Internalization Scale; WBIS-C = Weight Bias Internalization Scale Children; WSSQ = Weight self-stigma Questionnaire.

Weight Stigma

Synthesis of Results

A total of 18 studies examined the impact of weight stigma on the obese population. It should be noted that nine out of the 18 studies reported more than one aspect of the outcome. For instance, Remmert et al. (2019) reported the biological and behavioral impacts of weight stigma on the obese population.

Biological Outcomes

Panza et al. (2023) reported that obese women who have a history of experiencing weight stigma displayed higher levels of systolic and diastolic blood pressure after watching a weight-stigmatizing video compared to the group of obese women who watched a non-stigmatizing neutral video clip. Furthermore, the levels of airway hyperresponsiveness were also reported to be high among participants who watched the weight-stigmatizing video. Wu et al. (2019) reported that a higher level of weight stigma experiences was associated with a lower log of hair cortisol level. Remmert et al. (2019) reported that weight stigma was positively correlated to body mass index, where participants who reported experiencing weight stigma were more likely to gain weight. Another study demonstrated that weight stigma was associated with a 40% increased risk of developing dementia over the follow-up period of 8–10 years, due to depressive symptoms and difficulty managing blood sugar levels (Sutin et al., 2019).

Psychological and Social Outcomes

Of the included studies, only two (Gudzune et al., 2014; Wang et al., 2020) did not report full datasets of values at each time point and significant results as well. Six studies (Griffiths et al., 2018; Jach & Krystoń, 2021; O’Brien et al., 2016; Puhl, Lesard et al., 2020; Wang et al., 2020; Zuba & Warschburger, 2017) reported a significant increase in the levels of stress and psychological distress among obese participants who experienced high levels of weight stigma. Wang et al. (2020) reported a significant increase in the levels of stress that had an indirect effect on emotional eating among adolescents in China, whereas Puhl, Lesard et al. (2020) reported that obese adults who experienced weight teasing 2 years before the COVID-19 outbreak experienced higher levels of stress and were more likely to binge-eat during the pandemic.

Furthermore, Griffiths et al. (2018) and O’Brien et al. (2016) reported that weight stigma had an indirect impact on psychological distress, where weight stigma was associated with weight self-stigma and this association was mediated by greater psychological distress that led to unhealthy eating patterns. Zuba and Warschburger (2017) discovered that weight teasing and discrimination by peers led to greater emotional problems such as anxiety and psychological distress regardless of gender. However, a closer look at this study revealed a shortcoming, as since the sample population was children, their ability to self-report their symptoms appears to be questionable. For instance, children may have the tendency to over-report, which could be influenced by parents, peers, or social media (Pinheiro et al., 2018). Furthermore, two studies (Himmelstein et al., 2019; Puhl, Lesard et al., 2020) measured depression as an outcome and reported a significant increase in depressive symptoms based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) among obese participants who experienced weight stigma.

Gudzune et al. (2014) reported that overweight and obese participants who perceived judgement from their primary care providers were more likely to report low levels of trust in their patient-provider relationships. Three studies (Gerend et al., 2020; Jach & Krystoń, 2021; Jerdrzyan et al., 2016) reported that weight stigma was significantly associated with higher levels of body dissatisfaction, which then had an indirect effect on emotional eating. This may be for several reasons, such as the compulsion of having a thin body because it is the perceived societal standard of beauty, peer pressure, and transitional age as the participants in Jerdrzyan et al. (2016)‘s study were adolescents. Jach and Krystoń (2021) discovered that an increase in weight stigma experiences resulted in higher weight misperceptions where obese participants believed they were a couple of pounds bigger than their actual weight. Additionally, in terms of social outcomes, Wu et al. (2019) reported a positive correlation between weight stigma and the level of perceived racism, where higher levels of weight stigma resulted in higher levels of perceived racial discrimination.

Behavioral Outcomes

Eleven studies reported on the behavioral impact of weight stigma among the obese population, in which two of them (Bevan et al., 2021; Jackson & Steptoe, 2017) found that weight stigma had an indirect effect on physical activity. Participants with the experience of weight stigma were more likely to have reduced motivation to live a healthy lifestyle. Hence, this results in a greater tendency to avoid engaging in physical activity and sports. As an explanation, individuals who were more frequently subjected to weight stigma reported feeling ashamed or uncomfortable going to gyms, a location where they may be scrutinized by others. Nine studies (Govender et al., 2018; Himmelstein et al., 2019; Jerdrzyan et al., 2016; Lee et al., 2021; O’Brien et al., 2016; Puhl, Lesard et al., 2020; Remmert et al., 2019; Wang et al., 2020; Zuba & Warschburger, 2017) measured disordered eating outcomes and regardless of age or ethnicity, the results were consistent across the studies where weight stigma showed a positive correlation to disordered eating outcomes. Higher levels of experienced weight stigma resulted in uncontrolled and emotional eating (O’Brien et al., 2016; Remmert et al., 2019; Wang et al., 2020), binge eating (Himmelstein et al., 2019; Puhl, Lesard et al., 2020), abnormal eating patterns, such as compulsive eating and obsession with eating (Govender et al., 2018), loss of control over eating (O’Brien et al., 2016), restrained eating (in children and early adolescents) (Jerdrzyan et al., 2016; Zuba & Warschburger, 2017), and comfort eating and alcohol abuse (Lee et al., 2021).

Additionally, Zuba and Warschburger (2017) reported unhealthy weight control behavior such as purging, specifically among young girls. Moreover, weight stigma was also found to have resulted in conduct problems among girls as well (Zuba & Warschburger, 2017). This could be because females are naturally more sensitive to weight-related discrimination compared to males, therefore getting teased and mocked due to their body size could easily trigger their anger and resentment.

Weight Self-Stigma

Synthesis of Result

A total of 16 studies examined the impact of weight self-stigma on the obese population. It should be noted that eight out of the 16 studies reported more than one aspect of the outcome. For instance, Jung et al. (2020) reported the biological and psychological impacts of weight self-stigma on the obese population.

Biological Outcomes

Jung et al. (2020) and Jackson and Steptoe (2018) found a significant association between weight self-stigma and cortisol levels, however, Jung et al. (2020) measured saliva cortisol whereas Jackson and Steptoe (2018) measured hair cortisol. Higher levels of weight self-stigma resulted in either lower levels of saliva cortisol or higher levels of hair cortisol. Puhl, Himmelstein et al. (2020) reported that weight self-stigma was associated with high levels of diabetes-specific distress among participants who are obese and diabetic. Pearl et al. (2017) discovered that obese participants who scored high in weight self-stigma were three times more likely to develop metabolic syndrome, and six times more likely of having high triglycerides. However, the possibility of developing metabolic syndrome was higher among obese women compared to men. Jung and Luck-Sikorski (2019) reported that weight self-stigma was positively correlated with sleep deprivation and night-eating symptoms for obese participants. The reason is that weight self-stigma and sleep share a complex and cyclical relationship where, internalizing weight stigma could lead to sleep disturbances due to the increase in psychological distress. Consequently, sleep deprivation leads to a hormonal imbalance in the body, which promotes overeating and weight gain (Cooper et al., 2018). Thus, this contributes to a higher BMI and increased weight self-stigma.

Psychological and Social Outcomes

Of the included studies, three of them (Jung et al., 2020; Khodari et al., 2021; Walsh et al., 2018) found that higher weight self-stigma scores were strongly associated with higher levels of chronic stress based on the Patient Health Questionnaire (PHQ-9) (Löwe et al., 2004), and lower levels of self-esteem. Chan et al. (2019) reported that weight self-stigma was associated with higher levels of depressive symptoms based on the Brief Symptom Rating Scale (Lung & Lee, 2008) among children. Palmeira et al. (2016) reported a positive correlation between weight self-stigma and experiential avoidance among obese women who were seeking nutritional treatment. As an explanation, higher weight self-stigma resulted in a higher tendency to avoid unwanted internal experiences, such as emotions, thoughts, memories, or bodily sensations. Almutairi et al. (2021) discovered that participants who reported higher scores in weight self-stigma were more likely to develop mental health disorders like depression and anxiety and this result is consistent with prior studies demonstrating that overweight and obese people who internalize weight stigma have greater rates of distress and anxiety. Jung and Luck-Sikorski (2019) discovered that weight self-stigma was associated with higher levels of loneliness among older adults in Germany. Khodari et al. (2021) reported the social impact of weight self-stigma on the obese population and found that weight self-stigma was negatively correlated with social relationships. Participants with higher levels of weight self-stigma were found to have poorer social skills and socialization.

Behavioral Outcomes

Six studies reported on the behavioral impacts of weight self-stigma on the obese population, in which six of them (Meadows & Higgs, 2019; Palmeira et al., 2016; Puhl et al., 2018) measured disordered eating as outcomes and discovered that weight self-stigma was significantly associated to disordered eating. Higher levels of weight self-stigma among obese participants resulted in higher levels of dietary restraints (Meadows & Higgs, 2019), binge eating (in adolescents) (Palmeira et al., 2016; Puhl et al., 2018), and emotional eating (O’Brien et al., 2016). However, Puhl et al. (2018) found that the scores of binge-eating habits were higher among adolescents compared to adults. Bevan et al. (2021) found a positive correlation between weight self-stigma and physical activity avoidance, as higher levels of weight self-stigma resulted in a greater tendency to avoid physical activity. Surprisingly, in contrast to previous studies, weight self-stigma was associated with high dieting habits among obese males (Himmelstein et al., 2019).

Studies Quality Assessment

Most of the included studies had high-quality scores as assessed based on the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a variety of fields (Kmet et al., 2004) independently by two reviewers. The three intervention based items; random allocation, blinding of investigators, and blinding of subjects were only reviewed in two studies, as the rest of the studies were non-interventional studies. Figure 2 shows the summary of the quality assessments of the 30 quantitative studies. The detailed scoring table is attached in Appendix. The average summary score of all the included studies was 84%, which fell under the strong quality rank (range = 64%–75%).

Figure 2.

Summarized quality assessment of the included studies (N = 30).

Discussion

Weight stigma generally refers to the social discrimination that individuals experience because of their body size, whereas weight self-stigma refers to the self-devaluation that individuals employ due to their body size. The current systematic review demonstrates a growing interest in understanding the biological, psychological, social, and behavioral impact of weight stigma and weight self-stigma on the obese population. Overall, the findings suggest that there is a lack of research investigating the impact of weight stigma and weight self-stigma on the obese population, especially in the Asian and Middle Eastern regions as there were only four studies found from the non-western region. Even though a small number of studies are included, this review indicates consistent findings across studies that specified the impact of weight-related discrimination on people with high body mass index. The majority of the studies that included participants who were undergoing weight loss treatment found lower scores of unhealthy eating patterns, and psychological distress compared to participants who were not undergoing any form of treatment at that time. Moreover, scores varied among males and females as well where females scored lower in physical and psychological well-being compared to males. However, non-binary and transgender obese individuals on the other hand scored lower compared to females and this could be due to the fact that they have to deal with weightism and heterosexism (Mereish, 2014). No studies reported having moderate or even high levels of physical or psychological quality of life, regardless of age or ethnicity.

The findings in the present review provided a piece of additional evidence that weight self-stigma mediates the relationship between weight stigma and biological, psychosocial, and behavioral outcomes, which is consistent with previous studies that suggest perceived weight stigma leads to heightened weight self-stigma, which consecutively leads to decreased physical and psychological well-being. However, it should be noted that weight stigma is not the only risk factor for weight self-stigma. Both weight stigma and weight self-stigma reported similar outcomes, such as psychological impacts: psychological distress, depression and anxiety, experiential avoidance, body shame and body dissatisfaction, biological impacts: high/low cortisol levels, high BMI, low quality of life, and metabolic syndrome, social impacts: less socialization, avoidance of crowded place, and other behavioral impacts: disordered eating, and avoidance of physical exercise. Interestingly, weight self-stigma resulted in poorer physical and psychological well-being compared to weight stigma. This suggests that weight-related internal experiences, such as thoughts, emotions, memories, or mental imagery have more impact on obese individuals compared to external experiences. For this reason, it is imperative that future research incorporates this element in developing a weight loss intervention for better awareness and results.

Furthermore, the reviewed studies also presented some methodological issues, such as small sample sizes, lack of long-term follow-up, and inaccurate assessment to measure variables that affected the validity of the findings. Jung et al. (2020) and Remmert et al. (2019) presented a small sample size in their study that could potentially increase the margin of error, which could imply that the findings of the study are less likely to represent the entire population (Deziel, 2018). Most of the studies included in the review were of good quality. However, some studies provided inadequate statistical information regarding the indirect effect(s) and measures of error/dispersion and instead simply reported the significance value only. Next, Walsh et al. (2018) did not have a long term follow up in their RCT study, and since it was an interventional study, the lack of long term follow-up failed to provide the long term effects of the weight loss intervention on weight self-stigma. Furthermore, most of the studies used the Weight Bias Internalization Scale to measure weight self-stigma. However, according to previous research, there is insufficient data on content validity for this measure (Pearl & Puhl, 2014). Hence, significant caution should be applied when evaluating these findings. In addition, some studies used Weight Bias Internalization Scale to measure weight stigma. However, since WBIS is designed to measure the internalized weight bias and there are only two items that measure perceived weight stigma, it should be noted that using WBIS to measure weight stigma could affect the validity of the findings.

Limitations of the Reviewed Studies

There are some limitations of the reviewed studies. First, the homogeneity of the participants in the included studies, who were predominantly white women. This prevents generalizations to a larger population; thus, future research should aim to include diverse ethnicities, sexual minority groups, men, children, teenagers, and older adults as well. Second, the generalizability of the findings was highly restricted when it comes to Asian and Middle Eastern countries, as most of the studies included in the review were conducted in the USA or UK and only two studies in Saudi Arabia and two studies in China. Thus, future research should consider assessing the Asian and Middle Eastern populations more to examine if there are any cultural differences in the impact of weight stigma and weight self-stigma on the obese population. Third, the instruments that assessed weight stigma and weight self-stigma were mostly different in the reviewed studies, hence the scores accumulated in those instruments are difficult to be compared due to the difference in scoring. For instance, the scores of WBIS may indicate a more severe level of weight self-stigma, compared to the scores of WSSQ, therefore future research is recommended to evaluate the impact of weight stigma or weight self-stigma based on one instrument to get more accurate findings.

Strengths and Limitations of the Current Review

The present review provides the synthesis of results for studies that examined the biological, psychosocial, and behavioral impacts of weight stigma and weight self-stigma on the obese population. This review is both relevant and essential because obesity is one of the epidemics that is expanding every year all over the world (Mitchell et al., 2011). Despite various weight loss treatments and new approaches, the prevalence of obesity is still high across the countries. Thus, this review of the current evidence would shed some light to establish recommendations for future directions and in the development of weight-related interventions. Moreover, two independent reviewers completed every step of this investigation, which minimizes errors and boosts the study’s power. There are notable limitations to this current review where the reviewers conducted a literature search on the five major electronic databases only: Scopus, PubMed, PsycINFO, Web of Science and MEDLINE. However, additional potentially relevant studies may have been missed as no other databases were searched.

Next, some of the participants were found to have a comorbid of depression or anxiety which could have or not have been present due to their weight-related struggles. Thus, if participants have developed mental health disorders for other reasons such as job stress, financial issues, marital issues, and not weight-related issues, then this would affect the accuracy of the findings in this review. Therefore, the presence of mental health disorders should have been added as one of the exclusion criteria in the current review. Finally, only fully open access papers were included in this review. However, this could have deterred the quality of the review.

Implications of the Review

It is important to highlight the implications of this study’s findings for both the research community and real-world applications. This study contributes to the existing knowledge by emphasizing the significant impact of weightism and weight self-stigma on individuals’ well-being. The findings align with previous research and underscore the need to prioritize the development of new weight loss approaches to enhance individuals’ physical and mental well-being. Additionally, the practical implications of this study’s findings are relevant for practitioners and health professionals addressing weight stigma. It is crucial to develop evidence-based interventions that challenge weight bias, promote body acceptance, and create an inclusive environment for individuals of all body sizes. Healthcare professionals, educators, and employers should receive training to identify and address weight stigma, ensuring fairness and equal opportunities for individuals with larger bodies. Furthermore, education and media play a vital role in raising awareness and knowledge about the negative impacts of weight stigma and weight self-stigma. These avenues can foster a compassionate and supportive society. For instance, education can enhance understanding and empathy among students, teachers, and the wider community by providing information about the experiences and challenges faced by those affected. Media, including advertisements, films, and news outlets, can humanize and challenge weight stigma through narrative portrayals, promoting compassion and support for individuals of all body sizes. Moreover, education and media can empower individuals affected by weight stigma and weight self-stigma to seek help. By providing information about available resources, support networks, and professional assistance, education and media can promote help-seeking behaviors in individuals who face weight-based discrimination or experience negative psychological effects.

Conclusion

In conclusion, weight stigma and weight self-stigma are crucial aspects that need to be tackled and taken into consideration by healthcare providers when supporting overweight and obese individuals. Overall, the current review demonstrated preliminary evidence that regardless of gender, age or geographical region, weight stigma and weight self-stigma are positively associated with medical issues, psychological distress, and unhealthy lifestyle. As mentioned above, developing a weight loss intervention that addresses weight stigma would bring more awareness to its impacts and reduce weight stigma for obese individuals. However, this would eventually reduce the prevalence rates of obesity. Given the abovementioned restrictions on generalizing the findings due to the homogeneity of the participants, there is scope for future researchers to further explore these issues in the Asian and Middle Eastern regions and future studies could also consider investigating the severity of weightism and weight self-stigma during the COVID-19 pandemic. Future research is also required on the risk factors of weight stigma and weight self-stigma among adolescents and young adults who fall under the non-obese category, as it would assist in developing an appropriate intervention for them. In conclusion, the implications of this study suggest the importance of addressing weight stigma and weight self-stigma for both research and practice. Through evidence-based interventions, education, and responsible media practices, we can create a society that is more understanding, inclusive, and supportive of individuals of all body sizes.

Footnotes

Appendix

Studies	Standard quality assessment criteria for evaluating primary research papers from a variety of fields items
	1	2	3	4	5	6	7	8	9	10	11	12	13	14	Total score
Meadows and Higgs (2019)	Yes	Yes	Yes	Yes	NA	NA	NA	Partial	Yes	Yes	Yes	Yes	Yes	Partial	91
Jach and Krystoń (2021)	Yes	Yes	Partial	Yes	NA	NA	NA	Yes	Partial	Yes	Partial	Yes	Yes	Partial	82
Puhl et al. (2018)	Yes	Yes	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Partial	Yes	No	86
Jung and Luck-Sikorski (2019)	Partial	Yes	Yes	Partial	NA	NA	NA	No	Yes	No	Yes	Yes	No	Yes	64
Bevan et al. (2021)	Partial	Yes	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Yes	Yes	Yes	95
Wang et al. (2020)	Yes	Yes	No	No	NA	NA	NA	Yes	Yes	Yes	Yes	No	Yes	Yes	73
Puhl, Himmelstein et al. (2020)	Yes	Yes	Yes	Yes	NA	NA	NA	Yes	Partial	Yes	Yes	Partial	Yes	Yes	91
Gerend et al. (2020)	Yes	Yes	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Yes	Yes	Partial	95
Jung et al. (2020)	Yes	Partial	Yes	No	NA	NA	NA	Yes	Yes	Yes	Yes	No	Yes	Yes	77
Puhl, Lesard et al. (2020)	Partial	Yes	Yes	Yes	NA	NA	NA	Yes	Partial	Yes	Yes	Yes	Yes	Partial	86
Remmert et al. (2019)	Yes	No	Yes	Yes	NA	NA	NA	Yes	Partial	Partial	Partial	Yes	Yes	Partial	73
Panza et al. (2023)	No	Partial	Yes	Yes	yes	partial	yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	90
Govender et al. (2018)	Partial	Yes	Partial	Yes	NA	NA	NA	Yes	Partial	No	Yes	Yes	Yes	Yes	77
Wu et al. (2019)	Yes	Yes	Yes	Yes	NA	NA	NA	Partial	Yes	Yes	Yes	Yes	Yes	Yes	95
Jackson and Steptoe (2018)	Partial	No	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Yes	Yes	Partial	82
Griffiths et al. (2018)	Yes	No	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Yes	Yes	Yes	91
Pearl et al. (2017)	Yes	No	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Partial	Partial	Yes	Yes	82
Palmeira et al. (2016)	Yes	No	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Partial	Yes	Partial	82
O’Brien et al. (2016)	Yes	Partial	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Partial	Yes	Partial	86
Jerdrzyan et al. (2016)	No	Partial	Yes	Yes	NA	NA	NA	Yes	Partial	Yes	Yes	Yes	Yes	Yes	91
Khodari et al. (2021)	Partial	Yes	No	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Partial	Yes	Yes	82
Jackson and Steptoe (2017)	Yes	Yes	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Partial	Yes	Yes	95
Chan et al. (2019)	Partial	Partial	Yes	Yes	NA	NA	NA	Yes	Yes	Partial	Yes	Yes	Yes	Yes	86
Almutairi et al. (2021)	Partial	Yes	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Partial	Yes	Yes	91
Lee et al. (2021)	Yes	No	Yes	Yes	NA	NA	NA	Partial	Yes	Yes	Partial	Yes	Yes	Partial	77
Sutin et al. (2019)	No	No	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Partial	Partial	Yes	Partial	68
Gudzune et al. (2014)	Yes	Yes	Yes	Partial	NA	NA	NA	Yes	Yes	Yes	Yes	Yes	Yes	Yes	95
Himmelstein et al. (2019)	Partial	No	Yes	Yes	NA	NA	NA	Yes	Yes	Yes	Yes	Partial	Yes	Partial	77
Walsh et al (2018)	Yes	Yes	Yes	Yes	yes	partial	no	Yes	Yes	Yes	Yes	Yes	Yes	Partial	86
Zuba and Warschburger (2017)	Yes	Yes	Yes	Partial	NA	NA	NA	Yes	Yes	Yes	Yes	Yes	Yes	Yes	95

Note. Item 1: objective sufficiently described; Item 2: study design evident and appropriate; Item 3: source of information appropriate; Item 4: baseline characteristics described; Item 5: random allocation; Item 6: blinding of investigators; Item 7: blinding of subjects; Item 8: outcome well defined; Item 9: sample size appropriate; Item 10: analytic methods appropriate; Item 11: variance is reported; Item 12: controlled for confounding; Item 13: results reported appropriate; Item 14: conclusions appropriate.

Scoring: yes (2), partial (1), no (0); A summary score was calculated for each paper by summing the total score obtained across relevant items and dividing by the total possible score. That is, [(20/22) × 100]

Acknowledgements

We wish to thank Mr Amos Lian for his invaluable contribution and support as a second reviewer during the study selection and data extraction stages. We would also like to extend our sincerest gratitude to Dr Harris Shah for assisting us in this journey and guiding us on writing this systematic review paper.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Shubashini Mathialagan

Poh Li Lau

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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The Impact of Weightism and Weight Self-Stigma on Obese Population: A Systematic Review

Abstract

Plain language summary

Keywords

Introduction

Methods

Protocol and Registration

Search Strategy

Eligibility Criteria

Study Selection

Data Extraction

Assessment of Risk of Bias

Results

Identification of Studies

Study Characteristics

Weight Stigma

Synthesis of Results

Biological Outcomes

Psychological and Social Outcomes

Behavioral Outcomes

Weight Self-Stigma

Synthesis of Result

Biological Outcomes

Psychological and Social Outcomes

Behavioral Outcomes

Studies Quality Assessment

Discussion

Limitations of the Reviewed Studies

Strengths and Limitations of the Current Review

Implications of the Review

Conclusion

Footnotes

Appendix

Acknowledgements

Declaration of Conflicting Interests

Funding

ORCID iDs

Data Availability Statement

References