Abstract
Background and aims
Compulsive Buying-Shopping Disorder (CBSD) is linked to disordered eating behaviors (DEB) and body image (BI) concerns, sharing traits like impulsivity and low self-control. Societal pressures and idealized body standards exacerbate body dissatisfaction, which may drive individuals toward buying/shopping or DEB as coping strategies. This review aims to clarify these connections, including from a gender-sensitive perspective.
Methods
This systematic review was pre-registered (PROSPERO CRD42023489555) and followed PRISMA guidelines. A search was conducted across PsycINFO, Web of Science, PubMed MEDLINE, and Scopus. Study quality was assessed using the Quality Assessment Tool for Observational Studies.
Results
CBSD is often associated with DEB regardless of gender, particularly binge-eating disorder. Women are more affected by CBSD than men, with higher rates of comorbid bulimia nervosa, and they experience greater psychological distress. Several studies found that CBSD and DEB are often linked through maladaptive coping strategies. Body dissatisfaction is consistently identified as a key predictor of CBSD, which may serve as a coping mechanism for emotional distress.
Discussion and Conclusions
Gender differences were analyzed in only 14 studies, limiting the generalizability of the findings. A significant gap in research on sexual and/or gender minorities (SGM) is highlighted. This gap is crucial to address, as SGM individuals often face unique stressors (e.g., social stigma) that may influence their mental health and coping behaviors differently than cisgender/heterosexual individuals. Future research should focus on more diverse, longitudinal studies.
Keywords: compulsive buying-shopping disorder, CBSD, pathological buying, body image, eating disorders, gender differences, behavioral addictions
Introduction
Compulsive buying-shopping disorder
Pathological buying, first mentioned in medical literature in 1892 (Magnan, 1892), has long been recognized as a mental disorder (Demling & Müller, 2023). Over time, it has been classified as an impulse control disorder due to its impulsive nature (Grant & Chamberlain, 2016) and is included as compulsive buying-shopping disorder (CBSD) under other specified impulse control disorders in the International Classification of Diseases 11th Revision (ICD-11; World Health Organization, 2024). In the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5; American Psychiatric Association, 2013), excessive buying is mentioned under hoarding disorder, but not as a distinct condition.
CBSD is increasingly viewed as a behavioral addiction due to neurobiological similarities to other addictions (Brand et al., 2020; Lawrence, Ciorciari, & Kyrios, 2014). This condition is characterized by a strong urge to buy or shop in a perceived uncontrollable manner, known as craving (Tiffany & Wray, 2012), in addition to a loss of control over the behavior, and ample preoccupation with buying-/shopping-related thoughts (Laskowski, Trotzke, De Zwaan, Brand, & Müller, 2021; Müller et al., 2021), leading to negative consequences (e.g., familial, occupational and/or social conflicts, financial burdens, and a reduced quality of life; Adamczyk, 2021; Müller et al., 2021; Zhang, Brook, Leukefeld, De La Rosa, & Brook, 2017). Over time, CBSD evolves from generating positive emotions to regulating negative ones (Brand et al., 2019, 2025), though this relief is short-lived, leading to guilt and shame (Yi & Baumgartner, 2011) and thus perpetuating a cycle of distress-induced buying/shopping.
The prevalence of CBSD is estimated at around 5% in the general population (Maraz, Griffiths, & Demetrovics, 2016) but is not exclusively a female phenomenon (Laskowski, Hildebrandt, & Muschalla, 2024). While some studies suggest that women may be more frequently affected, the reasons for potential gender differences remain unclear. The current research on gender disparities in CBSD is inconsistent, making it difficult to determine whether prevalence truly differs between men and women (Laskowski et al., 2024).
Gender differences in CBSD may arise from both biological and sociocultural factors and their interaction. Biologically, men and women differ in genetic disposition, physiological and hormonal regulation, and overall vulnerability to mental disorders (Ihle, Laucht, Schmidt, & Esser, 2007). From a social science perspective, gender differences regarding the manifestation of mental disorders are linked to variations in life circumstances, opportunities for participation, and experiences in education, employment, family, and healthcare (Merbach & Brähler, 2016). Regarding CBSD specifically, research suggests that women tend to associate shopping with positive emotions and greater enjoyment, whereas men experience more negative emotions and less satisfaction from purchases (Gallagher, Watt, Weaver, & Murphy, 2017). Such differences, possibly the result of distinct socializations of the genders, may contribute to gender-specific pathways into CBSD. Overall, gender phenotypes of CBSD are under-researched. From a public health perspective, gender-sensitive measures may help reduce gender inequalities in health, aligning with the European Union's Gender Action Plan (European Commission, 2023) and the World Health Organization's objectives (World Health Organization, 2024).
Disordered eating behavior and body image
Eating disorders (EDs) are serious mental health conditions characterized by abnormal eating behaviors that negatively affect a person's physical and emotional well-being. They are also associated with one of the highest mortality rates among psychiatric disorders (Amiri & Ab Khan, 2024). The most common types include anorexia nervosa (AN), characterized by restrictive eating, underweight, and an intense fear of weight gain; bulimia nervosa (BN), marked by cycles of binge eating followed by compensatory behaviors such as purging; and binge-eating disorder (BED), which involves recurrent episodes of binge eating without compensatory behaviors (American Psychiatric Association, 2013). Research suggests that biological predisposition plays a significant role in the development of EDs. For instance, twin studies indicate that up to 74% of phenotypic variation can be explained by additive genetic factors in AN (Yilmaz, Hardaway, & Bulik, 2015). At the same time, psychological factors, such as low self-esteem, perfectionism, and anxiety, are also strongly linked to disordered eating behaviors (DEB). A meta-analysis found that low self-esteem is significantly associated with the development of EDs (Krauss, Dapp, & Orth, 2023). Additionally, societal pressures to attain an idealized body image (BI), fueled by pervasive cultural norms, exacerbate the prevalence of these disorders (Vandenbosch, Fardouly, & Tiggemann, 2022). BI plays a crucial role in the development and maintenance of EDs, as negative body perceptions and body dissatisfaction -defined as a multifaceted concept encompassing an individual's perceptions, thoughts, and feelings about their physical appearance (Cash, 2002)- are strongly linked to DEB (Dumstorf, Halbeisen, & Paslakis, 2024). Gender differences in DEB are well-established, with women displaying higher rates of lifetime diagnosed EDs (8.4%) compared to men (2.2%; Galmiche, Déchelotte, Lambert, & Tavolacci, 2019). Women are also more likely to be dissatisfied with their weight, engage in dieting, and use purging for weight control (Fischetti, Latino, Cataldi, & Greco, 2020; MacNeill, Best, & Davis, 2017; Zayas et al., 2018). Dieting behaviors are prevalent in men as well (Gillen, Markey, & Markey, 2012), although the motivations may differ; women, generally following a thinness beauty ideal, aim to lose weight, while men, being more muscularity-oriented compared to women, seek to achieve a leaner and more muscular physique (Grabe, Ward, & Hyde, 2008; Halbeisen, Laskowski, Brandt, Waschescio, & Paslakis, 2024; McCabe & Ricciardelli, 2004).
Compulsive buying-shopping disorder, disordered eating behavior and body image: Interconnections
The interplay between CBSD, DEB, and BI involves complex psychological, behavioral, and social factors. Both CBSD and DEB are marked by maladaptive behaviors often rooted in emotional dysregulation, impulsivity, and dysfunctional self-perception (Atiye, Miettunen, & Raevuori-Helkamaa, 2015; Devoe et al., 2022; Mestre-Bach, Steward, Jiménez-Murcia, & Fernández-Aranda, 2017; Voth et al., 2014). Behaviors in both conditions may serve as coping mechanisms for stress or negative emotions (Thomas, Schmid, et al., 2024; Yau & Potenza, 2013). BI may play a pivotal role in both disorders, as body dissatisfaction can drive DEB (Eck, Quick, & Byrd-Bredbenner, 2022) and CBSD, particularly regarding the purchase of goods aimed at enhancing one's self-image (Consiglio & van Osselaer, 2022). Societal pressures and unrealistic body ideals exacerbate body dissatisfaction, fueling dysfunctional behaviors related to both DEB and/or CBSD in attempts to control or boost self-esteem (Aparicio-Martinez et al., 2019).
A deeper exploration of these relationships may uncover interconnected psychological mechanisms, while also highlighting distinct pathways that distinguish CBSD from DEB. In order to identify tailored therapeutic approaches, this differential understanding is essential. The following sections define and explore the relationships between CBSD, DEB, and BI in more depth, thus offering a foundation for understanding their interconnectedness.
Compulsive buying-shopping disorder and disordered eating behavior
CBSD has been reported to co-occur with EDs in studies with regard to AN, BN, and BED (Black, Repertinger, Gaffney, & Gabel, 1998; Fernando Fernández-Aranda et al., 2008; Laskowski, Georgiadou, Tahmassebi, de Zwaan, & Müller, 2021). CBSD has been found to be the most common comorbid impulse control disorder among individuals with current EDs, whereby prevalence rates vary by ED subtype as shown by Devoe et al. (2022): the highest prevalence (42%) was found among patients with BN, followed by 24% in those with BED and 11% in those with AN. Similarly, CBSD was the most common comorbid impulse control among women with lifetime EDs (12%; Fernando Fernández-Aranda et al., 2008).
CBSD shares several personality traits and clinical features with EDs, such as impulsive behaviors and low levels of effortful control (Claes, Robinson, Muehlenkamp, Vandereycken, & Bijttebier, 2010; Devoe et al., 2022; Munguía et al., 2021; Vohs & Faber, 2007). For example, attentional impulsivity has been linked to more dieting and greater preoccupation with food (Lundahl, Wahlstrom, Christ, & Stoltenberg, 2015). Impulsivity traits are also relevant in understanding the heightened cue reactivity observed in CBSD (Trotzke, Starcke, Pedersen, & Brand, 2014). Moreover, individuals with bulimic spectrum disorders and comorbid CBSD tend to display higher levels of harm avoidance and novelty seeking alongside lower levels of self-directedness and cooperativeness (Munguía et al., 2021). Both conditions, binge spectrum disorders (encompassing BN and BED) and CBSD, involve altered dopamine signaling, associated with reward hypersensitivity and impaired decision-making (Munguía et al., 2021). The decision-making impairments in CBSD are linked to reduced so-called somatic markers – emotional and cognitive correlates of decision-making – suggesting that diminished emotional feedback plays a crucial role (Trotzke, Starcke, Pedersen, Müller, & Brand, 2015).
Cue reactivity studies suggest parallels between CBSD and EDs, particularly in reward processing. Women with CBSD show heightened reactivity/increased activation in brain reward circuits in response to marketing-related cues, such as brand logos (Hubert, Hubert, & Mariani, 2024). Similarly, individuals who engage in binge eating (without compensatory behaviors) exhibit increased responsiveness to food cues (Stojek et al., 2018). Moreover, individuals with CBSD demonstrate greater reactivity to addiction-related cues compared to neutral stimuli (Starcke, Antons, Trotzke, & Brand, 2018), exhibiting stronger affective responses and heightened arousal and urge ratings, while no group differences emerged in implicit cognitive tasks or stress-related performance (Müller et al., 2025). These findings may suggest a shared etiological basis, where heightened sensitivity to reward cues may contribute to the comorbid development and maintenance of both CBSD and EDs. However, the specific role of gender in these processes remains unclear.
Compulsive buying-shopping disorder and body image
One factor in CBSD is the desire to improve perceived BI through material possessions (Consiglio & van Osselaer, 2022). BI includes one's perception and evaluation of their physical appearance, heavily influenced by societal norms and social comparisons (Gallagher, 2007). Body dissatisfaction and the desire to boost self-esteem are linked to increased buying/shopping behaviors (Consiglio & van Osselaer, 2022; de Valle, Gallego-García, Williamson, & Wade, 2021; Yurchisin & Johnson, 2004). Vosylis, Žukauskienė, and Crocetti (2020) demonstrated that CBSD is associated with BI concerns, particularly among individuals prone to rumination and identity issues. Similarly, Adebo and Hamsan (2023) found that conspicuous consumption fully mediates the relationship between BI and identity exploration, highlighting the significant role of conspicuous buying/shopping in this relationship. Previous research (e.g., D’Alessandro & Chitty, 2011; Moulding, 2007; Yu, Damhorst, & Russell, 2011) has already explored the role of body dissatisfaction in consumer research, noting that it influences the effectiveness of advertising and consumer attitudes towards brands. Social media amplify these connections, as platforms increasingly showcase idealized BIs, driving consumers towards purchasing behaviors. Finally, higher levels of social comparison are associated with greater dissatisfaction with one's body (Yang, Holden, Carter, & Webb, 2018), and research shows a link between social media consumption and negative BI (Ateq, Alhajji, & Alhusseini, 2024; Jiotsa, Naccache, Duval, Rocher, & Grall-Bronnec, 2021; Rounsefell et al., 2020). The extent to which gender influences the relationship between CBSD and BI remains an open question and requires further research.
Aim of the study
There is an increasing research interest and a growing body of evidence-based findings on CBSD, including its description and phenomenology (e.g., Black, 2022; Laskowski & Müller, 2021), neurocognitive aspects (e.g., Kyrios et al., 2018; Trotzke, Starcke, Pedersen, & Brand, 2021), and treatment (see overview by Müller et al., 2023). Additionally, several proposals for diagnostic criteria (e.g., McElroy, Keck, Pope, Smith, & Strakowski, 1994; Müller et al., 2021) and various survey instruments (e.g., Müller et al., 2022; Müller, Mitchell, Vogel, & de Zwaan, 2017) have been suggested.
However, to the best of our knowledge, the associations between CBSD and DEB, as well as between CBSD and BI, have not yet been systematically explored. Given that body dissatisfaction and DEB are linked to lower quality of life (Ágh et al., 2016) and low self-esteem (Morán et al., 2024), the comorbidity may significantly increase the psychological distress of individuals with CBSD, thereby exacerbating their symptoms. Therefore, it is crucial to further investigate the connections between the two conditions and consider them in the treatment of affected individuals.
It is also important to consider possible gender-specific differences, as it has been suggested that CBSD may be more prevalent among women (Maraz et al., 2016), although it remains unclear whether there is a significant gender difference in its overall prevalence (Laskowski et al., 2024). Gender differences in body dissatisfaction (Gualdi-Russo et al., 2022) and DEB (Elgin & Pritchard, 2006), with women being more affected, may influence the relationship between the conditions. Therefore, this systematic review also aims to provide an overview of the relationship between CBSD and DEB, as well as between CBSD and BI, by gender. By synthesizing previous findings, we seek to identify common patterns and interconnected characteristics between these disorders. Additionally, we aim to highlight gaps in the current research and suggest directions for future studies.
Methods
Search strategy and study selection
This study was pre-registered with PROSPERO (Schiavo, 2019; (CRD42023489555, registered 15th of December 2023), registered 15th of December 2023) and was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance (Moher, Liberati, Tetzlaff, Altman, & Group, 2009). An evidence-based electronic search was conducted in accordance with the Peer Review of Electronic Search Strategies (PRESS) guideline using the databases PsycINFO, Web of Science (WOS), PubMed MEDLINE, and Scopus (last search February 05, 2025). For each database, a comprehensive search strategy was developed consisting of a combination of Medical Subject Headings (MeSH) terms, keywords, and various terms connected to CBSD, DEB, and BI. To manage the studies, the software Covidence (Veritas Health Innovation, 2024) was used. The search strategy can be viewed at: https://www.crd.york.ac.uk/PROSPEROFILES/489555_STRATEGY_20231204.pdf.
Eligibility criteria
There were no limitations regarding the publication year of the included studies, given the overall expected low number of studies. We excluded studies investigating Parkinson's disease and populations with dopaminergic medication, to avoid potential confounding effects. Parkinson's disease is primarily caused by a depletion of nigrostriatal dopamine (Ramesh & Arachchige, 2023). Dopamine medications, such as dopamine agonists used in the treatment of Parkinson's disease, have been associated with the side effect of impulse control disorders, including CBSD and binge eating (Moore, Glenmullen, & Mattison, 2014; Weintraub, David, Evans, Grant, & Stacy, 2015). Instances of panic buying and stockpiling, as observed during the COVID-19 pandemic (Georgiadou et al., 2021), were also excluded. This specific form of purchasing is primarily driven by factors such as, e.g., feelings of scarcity, and fear of the unknown and is therefore not considered pathological buying in the sense of CBSD (Arafat et al., 2020; Yuen, Wang, Ma, & Li, 2020). Shoplifting, on the other hand, is driven by a variety of factors, including the attraction of novelty or risk, as well as the desire to obtain restricted or prohibited products, such as items that are not legally accessible to young people. The theft of goods for resale also contributes to this behavior. Shoplifting must therefore also be distinguished from CBSD and has been excluded (Cox, Cox, & Moschis, 1990). The domains relevant for inclusion and exclusion criteria are detailed in Table 1.
Table 1.
Inclusion and exclusion criteria
| Domain | Inclusion | Exclusion |
| Population |
|
|
| Type of study |
|
|
| Outcome |
|
|
Two authors (NML, GB, MP, PR, CBR) independently screened all articles for inclusion (Cohen's kappa: 0.55); the resulting articles were retrieved, and again each was screened and rated by two reviewers (Cohen's kappa: 0.60). Consensus discussions were used to resolve discrepancies among reviewers. Consensus for inclusion or exclusion was reached under the supervision of the first author (NML). The final selection was approved by the entire study team (i.e., all authors).
All data (e.g., study design, sample size and composition, country, and assessment of CBSD and outcomes of interest) were also evaluated and extracted by two independent reviewers. In case of discordance, the first author (NML) was consulted, and consensus was reached by discussion. Statistical values, including means (M), standard deviations (SD), odds ratios (OR), p-values and, where applicable, gender differences, are reported.
Quality assessment
We used the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies (National Heart Lung and Blood Institute, 2013). This tool includes questions regarding aspects of study design and execution (e.g., research question, population, sample size justification, outcome measurement, confounding variables). Response categories encompass “yes”, “no”, “not applicable”, “cannot determine”, and “not reported”, as well as an overall quality rating (“good”, “fair”, or “poor”).
Results
Extracted studies
The literature search resulted in 5417 hits. After a comprehensive selection process, we were able to include 44 studies, 37 regarding DEB and 12 regarding BI (16,158 participants overall). Five studies analyzed both outcomes and are therefore presented twice below (Harnish, Gump, Bridges, Slack, & Rottschaefer, 2019; Kim et al., 2018; Lochner et al., 2005; Mitchell et al., 2002; Müller et al., 2007). Figure 1 depicts the PRISMA flow chart.
Fig. 1.
PRISMA diagram
Note. Five studies consider both outcomes and are therefore assigned twice.
Terminology
In the included studies, various terms were used to describe CBSD, such as “excessive buying” (Liang & Meg Tseng, 2011), “pathological buying” (e.g., Zander, Claes, Voth, De Zwaan, & Müller, 2016), “impulsive buying” (Verplanken, Herabadi, Perry, & Silvera, 2005), “compulsive buying” (e.g., Peñas-Lledó et al., 2010), “overspending” (Schippers & Cox, 1994), “buying disorder” (Müller et al., 2018), “compulsive consumption behavior” (Trautmann-Attmann & Johnson, 2009), and “shopping addiction” (Charzyńska, Sussman, & Atroszko, 2021). In the sections of this article referring to direct results, we have used CBSD-related terms as they had been originally used in the included studies, to present findings as accurately as possible and to account for different underlying aspects of CBSD discussed in the literature. Following the ICD-11 terminology and for better readability, we use the term CBSD in all other sections of the article.
Disordered eating behavior
Clinical samples
The 37 studies on DEB included 22 studies with clinical samples (6,559 participants; range from 40 to 1,197). Of these participants, 79.2% (n = 5,195) were women and 20.8% (n = 1,364) were men. With respect to study design, 12 were cross-sectional studies, 8 case-control studies and 2 cohort studies. The following section presents results differentiated by diagnostic groups, specifically samples with a CBSD diagnosis, samples with EDs, bariatric surgery candidates, and treatment-seeking patients with alcohol use disorder (AUD). For each group, findings from cross-sectional studies are reported first, followed by results from cohort and case-control studies.
Among clinical CBSD samples, Lejoyeux, Tassain, Solomon, and Adès (1997) reported in their cross-sectional study a significant higher relative risk for BN in French patients with depression and comorbid compulsive buying, particularly women, compared to patients without comorbid compulsive buying. Schlosser, Black, Repertinger, and Freet (1994) found comorbid impulsivity, mood disorders, and other psychiatric comorbidities in patients with compulsive buying and EDs, reporting that 17% of individuals with compulsive buying exhibited lifetime BN. Kim et al. (2018) found that compared to men, women with obsessive compulsive disorder (OCD) were more likely to have comorbid compulsive buying disorder, which was associated with a higher odds ratio for further comorbid psychiatric diagnoses characterized by high impulsivity, such as BED. In a Brazilian treatment-seeking sample, de Mattos et al. (2016) reported that 5% of men and 9% of women with compulsive buying disorder had comorbid BN, while 20% of men and 13% of women had comorbid BED; however, gender differences were not significant. Men with compulsive buying disorder were significantly more likely to identify as non-heterosexual (34%) compared to women (4%) in the same study. In a later study, de Mattos et al. (2018) found that 9% of participants with compulsive buying had comorbid BN, and 14% had BED. In a case-control study, Müller et al. (2008) found higher ED rates (23% vs. 3%) and personality disorder rates (73% vs. 10%) in women with pathological buying, compared to the female control group. However, Mitchell et al. (2002) and Zander et al. (2016) reported no significant differences in DEB or binge eating episodes between individuals with compulsive shopping/pathological buying and controls, although they noted significant higher rates of dermatillomania in individuals with pathological buying compared to those without pathological buying or controls. Faber, Christenson, de Zwaan, and Mitchell (1995) found that individuals with BED, especially those with obesity, reported higher rates of compulsive buying than those without BED.
In samples with EDs, Claes et al. (2012) reported that 10% of outpatient women with BN exhibited compulsive buying. Peñas-Lledó et al. (2010) identified a cluster characterized by compulsive buying, high BED rates, social anxiety, and novelty-seeking behavior. However, Montourcy et al. (2018) found that compulsive buying was no relevant factor in the latent class analysis. In a case-control study, Jiménez-Murcia et al. (2015) found more severe ED symptoms in patients with BN and comorbid compulsive buying compared to patients with BN without comorbid compulsive buying, while Munguía et al. (2021) reported higher rates of psychological distress, ED severity, and poorer treatment outcomes for the comorbidity between ED and compulsive buying compared to women with bulimic spectrum disorders but without compulsive buying and to controls. Liang and Meg Tseng (2011) found that 35% of Taiwanese women in an outpatient ED-setting (vs. 32% in controls) engaged in excessive buying, especially those with BN. Raemen et al. (2020) found pathological buying in 10% of women with EDs compared to 2% in controls.
In bariatric surgery candidates, Schmidt, Körber, De Zwaan, and Müller (2012) found that 8% exhibited compulsive buying and 6% reported a current ED. Müller et al. (2018) found significant correlations of food addiction and severe ED symptoms with buying disorder symptoms − findings later corroborated by the cohort study by Dickhut et al. (2021), which reported decreased buying-shopping disorder symptoms post-surgery.
In a cross-sectional study of treatment-seeking patients with AUD, Cavicchioli, Vassena, Movalli, and Maffei (2018) reported that compulsive buying, BED, and starvation were significantly correlated with maladaptive coping in patients with AUD. Lochner et al. (2005) found significant correlations between compulsive shopping and EDs with OCD severity and childhood emotional abuse in a case-control setting.
In summary, clinical studies highlight a significant bi-directional association between CBSD and EDs, especially BN and BED. Patients with CBSD report elevated rates of both lifetime and current EDs, and patients with this comorbidity exhibit more severe psychopathology, including anxiety, depression, and impulsivity, as well as poorer treatment outcomes and greater psychological distress. Table 2 presents the detailed results of the included studies regarding CBSD and DEB in clinical samples including the country and used measures.
Table 2.
Compulsive buying-shopping disorder and disordered eating behavior in clinical samples
| Reference | Measurement | Sample and study description | Results | ||
| CBSD | DEB | ||||
| Cross-sectional studies | |||||
| Cavicchioli et al. (2018) | Shorter PROMIS Questionnaire (SPQ), Italian version | Cross-sectional with 1 time point, 456 treatment-seeking individuals with AUD (186, 40.8% women), Italy |
Main findings (no gender differences investigated)
|
||
| Claes et al. (2012) | Compulsive Buying Scale (CBS), Dutch version | Eating Disorder Inventory-2 (EDI-II), Dutch version | Cross-sectional with 1 time point, 60 women with ED, country not reported |
Main findings (only women investigated)
|
|
| de Mattos et al. (2016) | CBS, Portuguese version | SPQ, Portuguese version | Cross-sectional with 1 time point, 171 treatment-seeking individuals with compulsive buying disorder (151, 88.3% women), Brazil |
Main findings
|
|
| de Mattos et al. (2018) | CBS, Portuguese version | Binge Eating Scale (BES), Portuguese version; clinical interview | Cross-sectional with 1 time point, 434 treatment-seeking individuals with compulsive buying disorder (378, 87.1% women), Brazil |
Main findings (no gender differences investigated)
|
|
| Lejoyeux et al. (1997) | Diagnostic criteria by McElroy et al. (1994) | Mini-International Neuropsychiatric Interview (M.I.N.I.) | Cross-sectional with 1 time point, 119 psychiatric patients (91, 76.5% women), 38 with compulsive buying, 81 without, France |
Main findings BN was sign. more frequent among those with depression and comorbid compulsive buying (n = 8, 21%) compared to those without (n = 6, 7%; RR = 2.9, p = 0.03) Gender differences Sign. more women with depression and comorbid compulsive buying (8.6 vs. 1 man) than with depression without compulsive buying (2.5 vs. 1 man; p = 0.05) |
|
| Lochner et al. (2005) | Yale-Brown Obsessive-Compulsive Scale (YBOCS) | SCID-I/P | Cross-sectional study with 1 time point, 210 patients with OCD (108, 51.4% women), South Africa |
Main findings cluster analysis
Cluster II scores were significantly associated with being a woman (t = −2.45; p = 0.02) |
|
| Kim et al. (2018) | SCID-IV | Cross-sectional with 1 time point, 993 patients with OCD (563, 56.7% women), Brazil |
Main findings
Women were sign. more often diagnosed with compulsive buying disorder than men (77.3% vs. 22.7%, OR = 3.48, χ2 = 14.1; p < 0.001) |
||
| Müller et al. (2007) | CBS; YBOCS shopping version (Y-BOCS-SV) |
SCID, German version | Cross-sectional with 1 time point, 77 women with compulsive buying, Germany/USA |
Main findings (only women investigated)
|
|
| Müller et al. (2018) | Pathological Buying Screener (PBS) | Yale Food Addiction Scale 2.0 (YFAS 2.0), German version; Eating Disorders Examination-Questionnaire (EDE-Q), German version | Cross-sectional with 1 time point, 216 bariatric surgery candidates (173, 80.1% women), Germany |
Main findings (no gender differences investigated)
|
|
| Peñas-Lledó et al. (2010) | SCID-I | SCID-I; EDI-II; Bulimic Investigatory Test Edinburgh (BITE); diary for binge eating/purging (Fernández-Aranda & Turón, 1998) | Cross-sectional with 1 time point, 825 female patients with EDs, Spain |
Main findings cluster analysis (only women investigated)
|
|
| Schlosser et al. (1994) | CBS; MIDI | DSM-111-R (Robins, Helzer, Cottler, & Goldring, 1989) | Cross-sectional with 1 time point, 46 individuals with compulsive buying (37, 80.4% women), USA |
Main findings (no gender differences investigated)
|
|
| Schmidt et al. (2012) | SCID-I-RV | EDE-Q, German version | Cross-sectional with 1 time point, 100 bariatric surgery candidates (74, 74% women), Germany |
Main findings (no gender differences investigated)
|
|
| Cohort studies | |||||
| Dickhut et al. (2021) | PBS | YFAS 2, German version | Cohort study with 3 time points, 125 bariatric surgery candidates (104, 83.2% women), Germany |
Main findings (no gender differences investigated)
|
|
| Montourcy et al. (2018) | Diagnostic criteria by McElroy et al. (1994) | M.I.N.I. | Cohort study with 3 time points, 302 treatment-seeking individuals for behavioral addictions or EDs (151, 50% women), France |
Main findings (no gender differences investigated)
|
|
| Case-control studies | |||||
| Faber et al. (1995) | CBS | 1. Clinical interview 2. Modified SCID; Minnesota Impulse Disorder Interview (MIDI) |
Case-control and cross-sectional study with 1 time point, 1. 197 women with obesity, USA 2. 48 individuals (44, 91.7% women): 50% with compulsive buying, 50% matched controls, USA |
Main findings study 1 (no gender differences investigated)
|
Main findings study 2 (no gender differences investigated)
|
| Jiménez-Murcia et al. (2015) | Diagnostic criteria by McElroy et al. (1994) | SCID-II; BITE; EDI-II | Case-control study with 1 time point, 188 women: 50 with BN, 49 with BN and compulsive buying, 36 with compulsive buying, 53 with gambling disorder, Spain |
Main findings (only women investigated)
|
|
| Liang and Meg Tseng (2011) | Self-designed | SCID-I/P | Case-control study with 1 time point, 458 women: outpatients with EDs, psychiatric controls without, Taiwan |
Main findings (only women investigated)
|
|
| Mitchell et al. (2002) | CBS | EDE-Q; SCID-I/P | Case-control study with 1 time point, 40 women: 20 with compulsive shopping, 20 controls, USA |
Main findings (only women investigated)
|
|
| Müller et al. (2008) | SCID; diagnostic criteria by McElroy et al. (1994); SKSK |
SCID | Case-control study with 1 time point, 60 women: 30 patients with pathological buying, 30 bariatric surgery candidates and 30 female controls, Germany |
Main findings (only women investigated)
|
|
| Munguía et al. (2021) | DSM-5; Diagnostic criteria by McElroy et al. (1994) | EDI-II, Spanish version | Case-control study with 1 time point, 75 women: 25 with bulimic spectrum disorders, 25 with bulimic spectrum disorders and comorbid compulsive buying, 25 controls, Spain |
Main findings (only women investigated)
|
|
| Raemen et al. (2020) | CBS | Clinical interview; EDI-II, Dutch version | Case-control study with 1 time point, 314 individuals: 254 community adults (124, 48.8% women), 60 women with EDs, Belgium |
Main findings
|
|
| Zander et al. (2016) | CBS, German version (Müller et al., 2010); SCID-ICD | EDE-Q; 1 item (overeating) | Case-control study with 1 time point, 93 individuals: 31 treatment seeking outpatients with pathological buying, 31 treatment seeking psychiatric inpatients, 31 controls (25 women each group, matched samples), Germany |
Main findings (no gender differences investigated)
|
|
Note. CBSD = compulsive buying-shopping disorder; DEB = disordered eating behavior; OR = odds ratio; RR = relative risk; AUD = alcohol use disorder; ED = eating disorder; BN = bulimia nervosa; AN = anorexia nervosa; BED = binge-eating disorder; OCD = obsessive compulsive disorder; EDNOS = ED not otherwise specified; ADHD = attention deficit hyperactivity disorder; BPD = borderline personality disorder; DSM-5 = Diagnostic and Statistical Manual of Mental Disorders, 5th revision (American Psychiatric Association, 2013); SPQ = Shorter PROMIS Questionnaire; CBS = Compulsive Buying Scale (Faber & O'guinn, 1992), German version (Müller et al., 2010); EDI-II = Eating Disorder Inventory 2 (Garner, 1991), Dutch version (van Strien & Ouwens, 2003); BES = Binge Eating Scale (Gormally, Black, Daston, & Rardin, 1982); PBS = Pathological Buying Screener (Müller et al., 2015); YFAS 2 = Yale Food Addiction Scale 2.0 (Gearhardt, Corbin, & Brownell, 2016), German version (Meule, Müller, Gearhardt, & Blechert, 2017); MIDI = Minnesota Impulse Disorder Interview (Christenson et al., 1994); SCID = Structured Clinical Interview for DSM (American Psychiatric Association, 1994; First, Spitzer, Gibbon, & Williams, 1996); SCID-II = SCID for DSM-IV Axis II (First, Spitzer, Williams, & Benjamin, 1997); BITE = Bulimic Investigatory Test Edinburgh (Henderson & Freeman, 1987); M.I.N.I. = Mini-International Neuropsychiatric Interview (Lecrubier et al., 1997; Sheehan et al., 1998); SCID-I/P=SCID for DSM-IV-TR Axis I, patient edition (First, Spitzer, Gibbon, & Williams, 1995; First, Spitzer, & Williams, 2002); YBOCS = Yale-Brown Obsessive-Compulsive Scale (Goodman et al., 1989), shopping version (Monahan, Black, & Gabel, 1996); EDE-Q = Eating Disorder Examination Questionnaire (Fairburn & Beglin, 1994), German version (Hilbert & Tuschen-Caffier, 2006); SKSK = Screeningverfahren zur Erhebung von kompensatorischem und süchtigem Kaufverhalten (Raab, Neuner, Reisch, & Scherhorn, 2005); SCID-I=SCID for DSM-IV Axis I (First, Spitzer, Gibbon, & Williams, 1997), research version (First, Spitzer, Gibbon, & Williams, 2002).
General public samples
All 15 included studies from the general population were cross-sectional, involving 6,039 participants (sample sizes: 128–1,157). Of these, 77.2% (n = 4,663) were women, 22.5% (n = 1,360) were men, and 0.3% (n = 16) identified as “other” gender without specification. The following section presents results by different general public samples, including community cohorts, students, fitness center clients, and women who teleshop.
Grant and Chamberlain (2024) found that community members with probable compulsive buying disorder were significantly more likely to have BED compared to those without compulsive buying disorder, those with probable OCD, attention-deficit/hyperactivity disorder (ADHD) or borderline personality disorder (BPD), and those with substance use disorder (Grant & Chamberlain, 2024). Rachubińska et al. (2024) further reported that individuals at risk of compulsive buying had higher scores for cognitive restraint and uncontrolled eating on the Three-Factor Eating Questionnaire (TFEQ), while emotional eating did not significantly predict compulsive buying.
Among female student samples, regression analyses revealed connections between compulsive clothing buying/compulsive consumption behavior and the binge/control subscale of the Bulimia Test Revised (BULIT-R; Trautmann & Johnson, 2007; Trautmann-Attmann & Johnson, 2009). Claes, Bijttebier, Mitchell, De Zwaan, and Müller (2011) found a significant correlation between compulsive buying and BN. Similarly, Harnish et al. (2019) reported significant correlations between compulsive buying, dieting, and BN in US-American undergraduate students. Charzyńska et al. (2021) found a cluster with shopping and food addiction in Polish students, while Macía et al. (2023) noted that 21% of Spanish young adults were at risk for EDs and 16% for compulsive buying, with women being more affected than men. Schippers and Cox (1994) found significant differences in overspending, obesity, and EDs between Dutch and American students, again with greater impacts on women compared to men. In contrast, Davenport, Houston, and Griffiths (2012) found no significant correlations between excessive eating and compulsive buying behaviors but observed an association with impulsivity and anxiety in a regression analysis using a female British opportunity sample. Van Malderen et al. (2024) identified a group of adolescents in a school students' sample labeled as “impulsive/under-controlled”, who showed the highest levels of BED symptoms and frequently engaged in multiple dysfunctional and addictive behaviors, including pathological buying. This “impulsive/under-controlled” cluster was characterized by a lack of inhibitory control and a great tendency to impulsivity, which was strongly associated with a higher symptom burden in BED and other addictive behaviors.
Beyond student samples, Lejoyeux, Avril, Richoux, Embouazza, and Nivoli (2008) found significant group differences between BN and compulsive buying among French fitness center clients, especially those with exercise dependence compared to those without exercise dependence. Müller, Loeber, Söchtig, Te Wildt, and De Zwaan (2015) found that fitness center clients had low rates of pathological buying and also identified negative correlations between pathological buying and ED pathology.
Lee, Lennon, and Rudd (2000) reported regression results indicating a link between compulsive consumption behavior and BED in US-American women who engaged in TV shopping.
In summary, research highlights a notable connection between CBSD and DEB, particularly in student samples, with women generally reporting higher prevalence rates of both. Table 3 presents the detailed results of the included studies regarding CBSD and DEB in the general population, including the country and used measures.
Table 3.
Compulsive buying-shopping disorder and disordered eating behavior in the general population
| Reference | Measurement | Sample and study description | Result | |
| CBSD | DEB | |||
| Charzyńska et al. (2021) | Bergen Shopping Addiction Scale (BSAS), Polish version | Modified Yale Food Addiction Scale (mYFAS) | Cross-sectional with 1 time point, 1,157 students (601, 51.9% women; 10, 0.9% did not disclose gender), Poland |
Main findings
Profile I (28.6%) exhibited elevated levels of shopping and food addiction, profile II (24.6%) exhibited elevated levels of gaming addiction and pornography, profile III (23.7%) low/average scores and profile IV (23.1%) highest levels of examined behavioral addictions Gender differences
|
| Claes et al. (2011) | Compulsive Buying Scale (CBS) | Eating Disorder Inventory-II (EDI-II) | Cross-sectional with 1 time point, 211 female students, Belgium/USA |
Main findings (only women investigated)
|
| Davenport et al. (2012) | CBS | Three-Factor Eating Questionnaire (TFEQ)-revised 18-Item (TFEQ-R18) | Cross-sectional with 1 time point, 134 female students, UK |
Main findings (only women investigated)
|
| De Pasquale et al. (2022) | CBS, Italian version | EDI-II, Italian version; Binge Eating Scale (BES), Italian version | Cross-sectional with 1 time point, 352 individuals (convenience sample; 239, 67.9% women), Italy |
Main findings Sign. correlation between compulsive buying behavior and EDs (r = 0.34, p < 0.001) and BED (r = 0.20, p < 0.001) Structural equation modeling
Women exhibited higher CBS scores than men (t(350) = −2.71, p < 0.05) |
| Grant and Chamberlain (2024) | Minnesota Impulse Disorder Interview (MIDI) | Cross sectional with 1 time point, 300 adults (158, 53.7% women), USA |
Main findings (no gender differences investigated)
|
|
| Harnish et al. (2019) | Richmond Compulsive Buying Scale (RCBS) | Eating Attitudes Test (EAT-26) | Cross-sectional with 1 time point, 360 students (187, 51.9% women; 3, 0.8% self-described gender), USA |
Main findings (no gender differences investigated)
|
| Lee et al. (2000) | CBS, questionnaire for shopping channel exposure | Binge Eating Behavior Questionnaire | Cross-sectional with 1 time point, 334 female nonclinical television shopper (34 with compulsive consumption behaviors), USA |
Main findings (no gender differences investigated)
|
| Lejoyeux et al. (2008) | Questionnaire for assessment of compulsive buying (Lejoyeux et al., 1997) | DSM-IV-R criteria for bulimia (Bell, 1994); number of bulimic episodes/week during last 2 months | Cross-sectional with 1 time point, 300 fitness room clients (126, 42% women), France |
Main findings (no gender differences investigated)
|
| Macía et al. (2023) | MULTICAGE CAD 4 (Pedrero Pérez et al., 2007), items 25–28 | Cross-sectional with 1 time point, 352 individuals: 51.4% university students, 25% students/workers, 20% workers, rest missing responses (274, 77.8% women), Spain |
Main findings 20.7% were at risk for EDs, 15.9% at risk for compulsive buying, 32.2% at risk for AUD, 11.5% at risk for drug use disorder, 9.1% at risk of gambling disorder Gender differences latent class analysis
|
|
| Müller et al. (2015) | CBS, German version | EDE-Q, German version | Cross-sectional with 1 time point, 128 fitness room clients (49, 38.3% women), Germany |
Main findings EDs pathology and pathological buying were negatively correlated (rwomen = −0.20; rmen = −0.20) Gender differences
|
| Rachubińska et al. (2024) | Buying Behavior Scale (BBS) | TFEQ 13-item (TFEQ-13) | Cross-sectional with 1 time point, 556 women, Poland |
Main findings (no gender differences investigated)
|
| Schippers and Cox (1994) | Dutch Problem History Questionnaire (DPHQ), 1 item for inappropriate amount of spending money | DPHQ, items for obesity, BN, AN, inappropriate amount of exercise | Cross-sectional with 1 time point, 1,072 students: Netherlands: 468 (353, 75.4% women; 5, 0.5% did not disclose gender), USA: 604 (383, 45%, 1 missing gender identification) |
Main findings Significant more overspending (23.2% vs. 10.7%, p < 0.05), obesity (19.7% vs. 6.4%, p < 0.05), BN (19.3% vs. 7.1%, p < 0.05), and AN in Dutch students (8.5% vs. 3.1%, p < 0.01) compared to US students Gender differences
|
| Trautmann and Johnson (2007), Trautmann-Attmann and Johnson (2009) | Compulsive clothing buying scale (revised from Edwards (1993) | Bulimia Test-Revised (BULIT-R) | Cross-sectional with 1 time point, 228 female students, USA |
Main findings (only women investigated)
|
| Van Malderen et al. (2024) | Pathological Buying Screener (PBS); questionnaire on loss of control over pathological buying in last 12 months | Loss of Control over Eating Scale, brief version (LOCES-B); questionnaire on loss of control over BED in last 12 months | Cross-sectional with 1 time point, 341 community adolescents (186, 54.5% women), country not reported |
Main findings cluster analysis
Cluster III consisted of 76% girls; cluster I and II were gender-balanced (48% girls, 52% boys; 47% girls, 53% boys); these differences were sign. (χ2(2) = 23.89, p = 0.001). |
| Verplanken et al. (2005) | Impulse Buying Tendency (Verplanken & Herabadi, 2001) | Eating Disturbance Scale (EDS-5); Self-Report Habit Index (Verplanken & Orbell, 2003); self-report on snacking |
Cross-sectional with 1 time point, 214 adults travelling at a domestic airport (convenience sample, 98, 45.8% women), Norway |
Main findings (no gender differences investigated)
|
Note. CBSD = compulsive buying-shopping disorder; DEB = disordered eating behavior; ED = eating disorder; BN = bulimia nervosa; AN = anorexia nervosa; BED = binge-eating disorder; BMI = body mass index; AUD = alcohol use disorder; BSAS = Bergen Shopping Addiction Scale (Andreassen et al., 2015); mYFAS = modified Yale Food Addiction Scale (Lemeshow, Gearhardt, Genkinger, & Corbin, 2016); CBS = Compulsive Buying Scale (Faber & O'guinn, 1992), Italian version (Tommasi & Busonera, 2012), German version (Müller et al., 2010), EDI-II = Eating Disorder Inventory 2 (Garner, 1991), Italian version (Garner, 1998); TFEQ(-R 18)/(-13) = Three-Factor Eating Questionnaire (revised 18-item version; Karlsson, Persson, Sjöström, & Sullivan, 2000)/(13-item version; (Stunkard & Messick, 1985), polish version (Mazur et al., 2009); BES = Binge Eating Scale (Gormally et al., 1982), Italian version (Di Bernardo et al., 1998); BBS = Buying Behavior Scale (Oginska-Bulik, 2009); RCBS = Richmond Compulsive Buying Scale (Ridgway, Kukar-Kinney, & Monroe, 2008); EAT-26 = Eating Attitudes Test (David M. Garner, Olmsted, Bohr, & Garfinkel, 1982); EDE-Q = Eating Disorder Examination Questionnaire (Fairburn & Beglin, 1994), German version (Hilbert & Tuschen-Caffier, 2006); DPHQ = Dutch Problem History Questionnaire (Schippers, 1988); BULIT-R = Bulimia Test Revised (Thelen et al., 1991); PBS = Pathological Buying Screener (Müller et al., 2015); LOCES-B = Loss of Control over Eating Scale Brief Version (Latner, Mond, Kelly, Haynes, & Hay, 2014); EDS-5 = Eating Disturbance Scale (Rosenvinge et al., 2001).
Body image
Twelve studies, comprising a total of 3,512 participants, were included in the analysis of BI, with sample sizes ranging from 40 to 993 participants. Women represented 67.5% of the overall sample (n = 2,369), while men accounted for 32.5% (n = 1,140). Three participants (0.10%) self-described their gender without further specification. The following section presents results based on study design, distinguishing between ten cross-sectional and two case-control studies, all utilizing a single time point for data collection. The results are further categorized by sample type, including five student samples, four patient samples, and three general population samples.
In a study by Kale, Sağtaş, Bir, Koç, and Koç (2023), body appreciation positively affected impulse buying behavior. Gender differences emerged, with men demonstrating higher body appreciation scores compared to women. However, there were no significant differences in impulsive buying behavior between genders. Similarly, Cengiz and Barin (2024) demonstrated that body appreciation indirectly influences compulsive and impulse buying through fashion clothing involvement. Their findings suggest that individuals with higher body appreciation are more engaged in fashion clothing, which in turn increases the likelihood of fashion-oriented compulsive and impulse buying. Azevedo and Azevedo (2023) found that lower body appreciation led to increased social avoidance and compulsive shopping behavior. Cai et al. (2021) showed that the relationship between BI dissatisfaction and impulse buying was mediated by self-esteem. Higher BI dissatisfaction was associated with lower self-esteem, which in turn was linked to increased CBSD. Lucas and Koff (2017) revealed that negative affect mediated the link between BI and impulse buying, tied to appearance orientation and physical appearance comparisons. Yoo and Lee (2022) found that body satisfaction was negatively correlated to compulsive shopping behaviors but was positively correlated to life satisfaction. Harnish et al. (2019) identified appearance orientation and health evaluation as key predictors of compulsive buying. Kim et al. (2018) found higher body dysmorphic disorder rates in individuals with OCD and compulsive buying disorder compared to those with OCD but without comorbid compulsive buying disorder. Park and Ko (2011) linked appearance comparisons and body esteem to compensatory buying in a regression analysis. In another case-control study, Lochner et al. (2005) identified three clusters in OCD patients: reward deficiency, impulsivity (linked to compulsive shopping), and somatic cluster (linked to body dysmorphic disorder). However, Mitchell et al. (2002) found no significant differences in BI evaluations and perceptions in compulsive buyers compared to healthy controls.
In summary, CBSD appears to be strongly tied to negative BI. Body dissatisfaction and appearance concerns are found to be key predictors for CBSD, particularly among women, with social comparisons and body dysmorphic tendencies contributing to this connection. However, findings suggest that body appreciation may play a protective role. Table 4 outlines key findings on CBSD and BI, including countries and measures used.
Table 4.
Compulsive buying-shopping disorder and body image
| Reference | Measurement | Sample and study description | Result | |
| CBSD | BI | |||
| Cross-sectional studies | ||||
| Azevedo and Azevedo (2023) | Compulsive Buying Follow-Up Scale (CBFS) | Body Appreciation Scale (BAS-2), Portuguese version; Socio-cultural Attitudes Towards Appearance Scale (SATAQ-4): 2 items, Portuguese version | Cross-sectional with 1 time point, 134 adults (convenience/snowball sample; 105, 78.4% women), Portugal |
Main findings
|
| Cai et al. (2021) | Chinese Consumers' Impulse Buying Tendency Scale (Jing & Yue, 2005) | Simplified Negative BI Scale (Chen, Feng, & Huang, 2006; Liu, 2009) | Cross-sectional with 1 time point, 374 students (249, 66.6% women), China |
Main findings (no gender differences investigated)
|
| Cengiz and Barin (2024) | Fashion oriented impulse buying (Joo Park, Young Kim, & Cardona Forney, 2006); fashion clothing involvement (O’Cass, 2004); fashion-oriented compulsive buying (Ridgway et al., 2008) |
BAS-2 | Cross-sectional with 1 time point, 255 adults (141, 55.3% women), USA |
Main findings structural model evaluation
|
| Harnish et al. (2019) | Richmond Compulsive Buying Scale (RCBS) | Multidimensional Body-Self Relations Questionnaire (MBSRQ); Appearance Schemas Inventory-Revised (ASI-R) | Cross-sectional with 1 time point, 300 students (187, 62.3% women; 3, 1% self-described gender), USA |
Main findings (no gender differences investigated)
|
| Kale et al. (2023) | Impulsive Buying Scale (IBB) | BAS | Cross-sectional with 1 time point, 341 university students (217, 63.6% women), Turkey |
Main findings structural equation model
|
| Kim et al. (2018) | SCID-IV | Cross-sectional with 1 time point, 993 patients with OCD (563, 56.7% women), Brazil |
Main findings
Higher probability of women to be diagnosed with OCD and compulsive buying disorder (χ2 = 11.33, OR = 3.48, p = 0.001) |
|
| Lucas and Koff (2017) | Impulse Buying Tendency Scale (IBT) | MBSRQ subscale appearance (MBSRQ-AS); Body-Image Ideals Questionnaire (BIQ); Upward Physical Appearance Comparison Scale (UPACS) | Cross-sectional with 1 time point, 224 female students, USA |
Main findings (only women investigated)
|
| Müller et al. (2007) | Compulsive Buying Scale (CBS); Yale-Brown Obsessive-Compulsive Scale (YBOCS), shopping version (YBOCS-SV) | Germany: SCID for DSM-IV axis I/II, German version; USA: SCID for DSM-IV axis I | Cross-sectional with 1 time point, 77 women with compulsive-buying: 38 from Germany, 39 from the USA |
Main findings (only women investigated) 1 person (2.6%) in each of the samples with body dysmorphic disorder |
| Park and Ko (2011) | Compensatory buying (Valence, D'astous, & Fortier, 1988); Symbolic consumption (Piacentini & Mailer, 2004; Richins, 2004) |
SATAQ; Body esteem item scale by Heatherton and Polivy (1991) | Cross-sectional with 1 time point, 334 individuals: 47.6% students, 48.2% office workers, 4.2% other adults (228, 68.3% women), South Korea |
Main findings (no gender differences investigated)
|
| Yoo and Lee (2022) | Impulse buying scale by Rook and Fisher (1995); CBS 6 items |
Body satisfaction (Cash, 2002) | Cross-sectional with 1 time point, 230 female students, USA |
Main findings (only women investigated)
|
| Case-control studies | ||||
| Lochner et al. (2005) | SCID-II/P; YBOCS |
SCID-II/P | Case-control study with 1 time point, 210 patients with OCD (108, 51.4% women), South Africa |
Main findings cluster analysis
Cluster II was significantly associated with female gender (t = −2.45, p = 0.02), and increased severity of OCD on the YBOCS (r = 0.18, p = 0.01); cluster III did not show significant associations with gender |
| Mitchell et al. (2002) | CBS | MBSRQ | Case-control study with 1 time point, 40 women: 20 with compulsive buying, 20 controls, USA |
Main findings (only women investigated) No sign. differences in MBSRQ score between women with compulsive buying and controls |
Note. OR = odds ratio; CBSD = compulsive buying-shopping disorder; BI = body image; OCD = obsessive compulsive disorder; SCID DSM-IV axis I/II = Structured Clinical Interview for DSM IV axis I and II (American Psychiatric Association, 1994), German version (Wittchen, Zaudig, & Fydrich, 1997), patients version (First et al., 1995); CBFS = Compulsive Buying Follow-Up Scale (de Mattos, S. Kim, Zambrano Filomensky, & Tavares, 2019); BAS(-2) = Body Appreciation Scale (Avalos, Tylka, & Wood-Barcalow, 2005) (-2 Tylka & Wood-Barcalow, 2015), Portuguese version (Lemoine et al., 2018); SATAQ(-4) = Socio-cultural Attitudes Towards Appearance Scale (Heinberg, Thompson, & Stormer, 1995; Schaefer, Harriger, Heinberg, Soderberg, & Kevin Thompson, 2017), Portuguese version (Barra, da Silva, Marôco, & Campos, 2019); MBSRQ(-AS) = Multidimensional Body-Self Relations Questionnaire (Appearance Scales; Cash, 2002); IBB = impulsive buying scale (Kaytaz Yiğit, 2020; Rook & Fisher, 1995); RCBS = Richmond Compulsive Buying Scale (Ridgway et al., 2008); ASI-R = Appearance Schemas Inventory-Revised (Cash, 2002); YBOCS (SV) = Yale-Brown Obsessive-Compulsive Scale (Goodman et al., 1989), shopping version (Monahan et al., 1996); IBT = Impulse Buying Tendency Scale (Verplanken & Herabadi, 2001); BIQ = Body-Image Ideals Questionnaire (Cash & Szymanski, 1995); UPACS = Upward Physical Appearance Comparison Scale (O’Brien et al., 2009); CBS = Compulsive Buying Scale (Faber & O'guinn, 1992).
Confounding factors
In the following section, the main confounders from the included studies have been extracted to systematically identify and analyze key influencing factors (confounding variables) on CBSD and ED. A key focus was to determine factors that are either specific to CBSD or ED, or shared psychological, social, or biological influences.
Psychological health and co-occurring mental disorders
This synthesis identified several factors related to psychological health and co-occurring mental disorders that exacerbate ED and CBSD, including depression, impulsivity-related disorders such as ADHD and BPD, as well as addictive behaviors.
For instance, Rachubińska et al. (2024) demonstrated a significant correlation between depression and compulsive buying disorder. Specifically, individuals exhibiting higher levels of compulsive buying also reported more depressive symptoms, and depression was thought to influence the propensity for compulsive buying, as it remained significant in the multivariate analysis. Lucas and Koff (2017) highlighted negative affect as a key mediator between BI variables (excluding appearance evaluation) and impulse buying. Additionally, individuals at higher risk for compulsive buying behaviors were found to also display elevated levels of workaholism. Importantly, this association remained significant in the multivariate analysis, reinforcing the idea that workaholism could further exacerbate tendencies toward compulsive buying behaviors (Rachubińska et al., 2024).
Montourcy et al. (2018) found that childhood ADHD and negative life events led to more impulsive personalities and more severe compulsive shopping and ED symptoms. Similarly, Grant and Chamberlain (2024) noted that individuals with compulsive buying disorder were significantly more likely to screen positive for ADHD and BPD, suggesting that these psychiatric diagnoses may confound the relationship between buying-shopping and eating behavior. Moreover, participants with probable compulsive buying disorder showed significantly higher impulsivity scores, indicating that impulsivity may be a confounding factor in the relationship between buying behavior and eating behaviors, influencing both compulsive buying and EDs.
Regarding addictive behavior, Mestre-Bach et al. (2017) identified alcohol consumption and drug use as significant confounders for EDs. Müller et al. (2018) associated buying disorder symptoms with internet use disorder, while Lejoyeux et al. (2008) highlighted exercise addiction as a shared factor between compulsive buying and BN.
Sociodemographic influences
Several studies in this synthesis identified sociodemographic variables as key influencing factors for EDs and CBSD, including gender, age, cross-cultural differences, and socioeconomic status. One of the most prominent influencing sociodemographic factors is gender. For instance, Müller et al. (2015) found that women exhibited higher levels of ED pathology. Additionally, women had a lower BMI as well as lower levels of exercise dependence and AUD compared to men. In the same study, men reported higher rates of hypersexuality and problematic gaming compared to women. Furthermore, Kale et al. (2023) found higher body satisfaction in men compared to women. De Mattos et al. (2016) noted higher rates of compulsive buying disorder in men with non-heterosexual orientations compared to women. De Pasquale et al. (2022) found that women had higher compulsive buying behavior and body dissatisfaction scores, while men had higher perfectionism scores. Kim et al. (2018) also observed that women were three times more likely to have a comorbid diagnosis of OCD and compulsive buying disorder compared to men.
In addition to gender, Kim et al. (2018) also emphasized the influence of age and ethnicity on compulsive buying disorder and ED. Younger individuals and students appeared to be less likely to have compulsive buying disorder compared to older participants. Cai et al. (2021) demonstrated that after controlling for age, the predictive effect of body dissatisfaction on impulsive buying remained significant. Schippers and Cox (1994) provided evidence of cross-cultural differences. Their study found that Dutch students perceived EDs as more problematic, whereas American students were more concerned with psychoactive substance use and violent behavior. Kale et al. (2023) investigated the influence of monthly budget and found that impulse buying behavior scores showed significant differences based on monthly budget. Participants with a budget of 1000–2000 Turkish Lira had lower scores compared to those with a higher monthly budget (above 5100 Lira).
Personality traits
Personality traits, such as neuroticism and novelty-seeking, were additional key predictors. Trautmann and Johnson (2007) and Trautmann-Attmann and Johnson (2009) linked neuroticism to compulsive clothing buying/compulsive consumption behavior and binge eating, mediated by fashion interest. Additionally, Rachubińska et al. (2024) showed that individuals with compulsive buying disorder also had higher levels of neuroticism. Montourcy et al. (2018) added that lower self-directedness and poorer cognitive flexibility contributed to these behaviors, particularly in individuals with BN and compulsive buying. Lochner et al. (2005) linked emotional abuse to novelty-seeking traits, which are associated with both compulsive shopping and EDs.
Self-esteem
De Pasquale et al. (2022) and Davenport et al. (2012) associated low self-esteem with increased compulsive buying behavior and binge eating, while Claes et al. (2011, 2012) emphasized the role of temperament, linking high reward sensitivity and low effortful control to impulsive behaviors in both compulsive buying and EDs.
Physical activity and body-related factors
Yoo and Lee (2022) found that physical fitness improved body satisfaction, reducing psychological distress. However, compulsive shopping behavior mediated the relationship between body satisfaction and distress. Verplanken et al. (2005) showed that affective impulse buying tendency can be influenced by snacking and emotional factors such as self-liking and negative affect. Additionally, snacking habits moderated the relationship between impulsive buying tendency and ED (“eating disturbance propensity”). Furthermore, Azevedo and Azevedo (2023) identified BMI as a significant confounding variable, showing a positive correlation with family and peer pressure in the context of societal influences on BI concerns.
In conclusion, psychological health and co-occurring mental disorders, sociodemographic influences, personality traits, self-esteem, and physical activity along with body-related factors may significantly impact the development and progression of CBSD and EDs.
Quality assessment
Overview
In the DEB studies, research questions and exposure/outcome measures were generally well-defined, but gaps in reporting participation rates and sample size justifications were noted. Only a few studies examined varying exposure levels or conducted multiple exposure assessments, and the majority of studies had cross-sectional designs. Notably, several studies controlled for confounding variables and applied statistical adjustments, thus contributing to higher quality ratings. Regarding the BI research, most studies presented clear research questions and objectives. However, key methodological aspects such as participation rates, sample size justification, and the applied inclusion/exclusion criteria were often not reported. The overall quality of studies varied, with ratings ranging from fair to good. A few studies were rated as poor (n = 4). Appendix Table A1 presents the results of the quality assessment of all included studies, including their overall ratings.
Discussion and conclusions
Main findings
This systematic review synthesizes research on the associations between CBSD, DEB, and BI, based on 44 studies. Evidence shows a significant correlation between CBSD and DEB, especially binge eating (Cavicchioli et al., 2018), food addiction (Charzyńska et al., 2021; Dickhut et al., 2021; Schmidt et al., 2012), and BN (Claes et al., 2011, 2012). Personality traits such as impulsivity (Schlosser et al., 1994), mood disorders (Schlosser et al., 1994), depression (Rachubińska et al., 2024), and social anxiety are key factors of the association. Body dissatisfaction is also linked to CBSD; lower self-esteem and negative BI correlate with compulsive buying (Cai et al., 2021; Harnish et al., 2019). Negative affect plays a crucial role, as impulsive buying has been described as a way to cope with negative emotions (Lucas & Koff, 2017). Similarly, low body esteem is connected to compensatory buying, thus enhancing mood (Park & Ko, 2011).
Overall, gender differences were analyzed in only 14 studies (see Tables 2–4), limiting the generalizability of findings. Cultural and demographic factors, such as gender, impact CBSD prevalence. Women are generally more affected by CBSD, as shown in studies by Cavicchioli et al. (2018) and Kim et al. (2018), although the gender distribution in many studies has been uneven (see Tables 2–4). A review by Laskowski et al. (2024) highlighted that CBSD affects both genders, with symptoms in men potentially underrepresented in diagnostic criteria. Future research should further explore this gap. Future research should also explore emotional coping mechanisms across diverse groups, considering cultural and gender differences. As most studies are from Western countries, the applicability of findings to non-Western populations is limited. Cultural differences in consumer behavior, BI ideals, and eating behaviors may influence CBSD and DEB, further suggesting the need for culturally tailored interventions. Confounding factors like BMI, age, gender, and neuroticism complicate the relationship between CBSD and DEB/BI (Lochner et al., 2005).
Another significant gap in the current literature is the lack of studies that account for gender identities beyond the traditional man/woman binary. None of the studies in this review specifically examined sexual and/or gender minorities (SGM), highlighting a critical oversight in understanding CBSD in more diverse populations. This gap is essential to address, because SGM individuals often experience unique stressors, such as discrimination (Seiler-Ramadas et al., 2022), social stigma (Hatzenbuehler & Pachankis, 2016), and identity-related pressures (Goldbach & Gibbs, 2017), which can influence their mental health and coping behaviors differently than for cisgender and heterosexual individuals (Hughes et al., 2023; Slemon et al., 2022). As described above, de Mattos et al. (2016) indicates that men with CBSD reported more often to be non-heterosexual than women with CBSD. Not addressing these populations limits the generalizability of findings and overlooks potentially unique risk factors, making it crucial for future research to consider more inclusive samples and examine the specific experiences of SGM individuals in relation to CBSD.
In light of these findings, future research should aim to address the significant gaps identified, particularly in relation to SGM populations, the recruitment of larger and more representative samples, and a deeper exploration of the underlying psychological mechanisms linking body dissatisfaction, DEB, and CBSD.
Clinical and preventive approaches
The findings of this review may have important implications for addressing the comorbidity of CBSD and EDs. To begin with, it raises awareness for a comorbidity that may be overlooked in clinical practice, thus motivating clinicians to assess symptoms of both EDs and CBSD in the presence of either one. This may prove of relevance, as individuals with CBSD and comorbid EDs experience more severe symptoms and worse treatment outcomes (Charzyńska et al., 2021; Davenport et al., 2012; Rachubińska et al., 2024), making it imperative to address both conditions. Besides, the identification of shared underlying pathomechanisms, e.g., impulsivity, may aid in developing interventions tackling aspects driving both disorders, a transdiagnostic approach that appears promising for mental health disorders in general (Dalgleish, Black, Johnston, & Bevan, 2020). Finally, this review may initiate further research aiming to deeper understand the comorbidity of CBSD and EDs, ultimately promoting better mental health outcomes for affected individuals.
Increasing awareness, as done by the present review, is crucial for early identification and referral to treatment for CBSD and/or EDs. To mitigate the risk of developing CBSD and/or EDs, preventive strategies should be prioritized. Possible contents of prevention programs for CBSD could include the provision of information (psychoeducation) for youths, low-threshold interventions aimed at reshaping attitudes and behaviors related to CBSD, and even indicated prevention including support in managing finances or emotion regulation (Thomas, Laskowski, et al., 2024). In addition, public health campaigns that promote body positivity and healthy consumer behaviors may help to address societal pressures contributing to body dissatisfaction and compulsive buying. Educational programs in schools and communities should focus on building resilience against negative peer influences and the impact of social media on BI. Fostering environments that encourage open discussions about mental health can significantly aid in supporting at-risk individuals and promoting overall mental well-being.
Limitations
In addition to the already discussed gender distribution in study cohorts, another limitation concerns the sample size of some of the included studies. For example, the study by Müller et al. (2007) could hardly be included in the results, as it only involved a very small sample size of individuals with body dysmorphic disorder, which significantly limits the robustness of the conclusions. Moreover, we found a significant methodological heterogeneity across all included studies. Variations in study design, sample characteristics, and the measurement tools used to assess CBSD, BI, and DEB hinder direct comparisons. This heterogeneity may introduce bias and limit the generalizability of the findings. Additionally, a lack of standardization in the diagnosis and operationalization of CBSD across studies poses an additional limitation. The criteria used to identify CBSD vary, leading to potential inconsistencies in the classification of participants and limiting the comparability of findings. Also, the reliance on self-report measures in most of the studies may be influenced by social desirability bias and/or the participants' ability to accurately recall or self-assess their behaviors and mental health symptoms. Finally, the predominance of cross-sectional designs restricts the ability to draw causal inferences between CBSD, body dissatisfaction, and DEB; longitudinal research is needed to better understand the temporal dynamics of these relationships.
Despite these limitations, this systematic review provides valuable insights into the complex relationships between CBSD, DEB, and BI. Recognizing CBSD as a distinct mental disorder is highly relevant. By synthesizing findings from diverse studies, this work lays the groundwork for future research and clinical interventions aimed at addressing these intertwined aspects, particularly in underrepresented populations. This review emphasizes the importance of understanding psychological, cultural, and demographic factors in shaping CBSD, offering a solid foundation for further exploration in this field.
Appendix
Appendix Table A1.
Quality Assessment of Included Studies
| Clear research question/objective | Well-defined study population | Participation rate ≥50% | Subjects selected/recruited from similar populations | Uniformly applied inclusion/exclusion criteria | Sample size justification/power description | Exposure measured before outcome | Sufficient timeframe for exposure-outcome association | Examined varying exposure levels | Clearly defined, valid, reliable exposure measures | Multiple exposure assessments over time | Clearly defined, valid, reliable outcome measures | Blinded outcome assessors | ≤20% loss to follow-up | Confounding variables measured/adjusted statistically | Overall rating | |
| Disordered Eating Behavior | ||||||||||||||||
| Müller et al. (2008) | Yes | Yes | NR | Yes | Yes | No | No | No | No | Yes | No | Yes | NR | NR | No | Fair |
| Müller et al. (2018) | Yes | Yes | CND | Yes | CND | No | No | No | No | Yes | No | Yes | NA | NA | Yes | Good |
| Müller et al. (2015) | Yes | No | CND | Yes | Yes | No | No | No | No | Yes | No | Yes | NA | NA | Yes | Fair |
| Cavicchioli et al. (2018) | Yes | Yes | NR | Yes | Yes | No | NA | NA | NA | No | No | Yes | NA | NA | No | Fair |
| Charzyńska et al. (2021) | Yes | Yes | Yes | Yes | Yes | No | No | No | NA | Yes | No | Yes | NA | NA | Yes | Good |
| Claes et al. (2011) | Yes | No | NR | CND | CND | No | No | No | NA | Yes | No | Yes | NA | CND | Yes | Good |
| Claes et al. (2012) | Yes | Yes | CND | CND | CND | No | No | No | No | Yes | No | Yes | NR | NA | Yes | Fair |
| Davenport et al. (2012) | Yes | No | NR | NR | NR | No | No | No | No | Yes | No | Yes | NA | NR | Yes | Fair |
| de Mattos et al. (2016) | Yes | Yes | NR | Yes | CND | No | No | No | Yes | Yes | No | Yes | NA | NR | Yes | Good |
| de Mattos et al. (2018) | Yes | No | CND | No | Yes | No | No | No | No | Yes | No | Yes | NR | NA | No | Fair |
| De Pasquale et al. (2022) | Yes | No | CND | CND | Yes | No | No | No | No | Yes | No | Yes | No | NA | Yes | Good |
| Dickhut et al. (2021) | Yes | CND | CND | CND | Yes | No | No | Yes | No | Yes | Yes | Yes | NA | Yes | No | Good |
| Faber et al. (1995) | Yes | No | CND | CND | Yes | No | Yes | No | No | Yes | No | Yes | NA | NA | Yes | Fair |
| Gerard M. Schippers and Cox (1994) | Yes | No | NR | No | NR | No | No | No | No | Yes | No | Yes | Yes | NA | Yes | Poor |
| Grant and Chamberlain (2024) | Yes | Yes | NR | Yes | Yes | No | No | CND | No | Yes | No | Yes | NR | NR | Yes | Good |
| Jiménez-Murcia et al. (2015) | Yes | Yes | NR | Yes | Yes | No | No | No | No | Yes | No | Yes | CND | NA | Yes | Fair |
| Lee et al. (2000) | Yes | No | No | NR | Yes | No | No | No | No | Yes | No | Yes | Yes | NA | Yes | Fair |
| Lejoyeux et al. (1997) | Yes | Yes | CND | Yes | Yes | No | No | No | No | Yes | No | Yes | NA | NA | No | Fair |
| Lejoyeux et al. (2008) | Yes | Yes | NR | Yes | Yes | No | No | No | No | No | No | No | NA | NA | Yes | Fair |
| Liang and Meg Tseng (2011) | Yes | Yes | NR | No | Yes | No | No | No | No | No | No | Yes | NA | NA | No | Fair |
| Macía et al. (2023) | Yes | Yes | CND | Yes | Yes | No | No | No | No | Yes | No | Yes | NA | NA | No | Good |
| Montourcy et al. (2018) | Yes | Yes | CND | Yes | Yes | No | No | Yes | No | Yes | Yes | Yes | No | CND | Yes | Good |
| Munguía et al. (2021) | Yes | Yes | CND | Yes | Yes | No | No | No | No | Yes | Yes | Yes | No | Yes | Yes | Fair |
| Peñas-Lledó et al. (2010) | Yes | Yes | NR | Yes | Yes | No | No | No | No | Yes | No | Yes | NA | NA | Yes | Fair |
| Rachubińska et al. (2024) | Yes | Yes | Yes | Yes | Yes | Yes | NA | No | No | Yes | No | Yes | No | NA | Yes | Good |
| Raemen et al. (2020) | Yes | Yes | CND | CND | NR | No | No | No | Yes | Yes | No | Yes | Yes | NA | Yes | Fair |
| Schlosser et al. (1994) | Yes | Yes | CND | Yes | Yes | No | No | No | Yes | Yes | No | Yes | NA | NA | No | Fair |
| Schmidt et al. (2012) | Yes | Yes | Yes | Yes | Yes | No | No | No | No | Yes | No | Yes | NR | NA | Yes | Good |
| Trautmann and Johnson (2007) | Yes | No | CND | CND | Yes | No | No | No | NA | Yes | No | Yes | NA | NA | Yes | Poor |
| Trautmann-Attmann and Johnson (2009) | Yes | No | CND | CND | Yes | No | No | No | No | Yes | No | Yes | NA | NA | Yes | Poor |
| Van Malderen et al. (2024) | Yes | Yes | CND | Yes | CND | No | No | No | No | Yes | NA | Yes | NA | NA | Yes | Fair |
| Verplanken et al. (2005) | Yes | No | CND | CND | CND | No | No | No | No | CND | NA | CND | NA | NA | Yes | Poor |
| Zander et al. (2016) | Yes | No | CND | CND | Yes | No | No | No | No | Yes | NA | No | No | NA | No | Fair |
| Body Image | ||||||||||||||||
| Müller et al. (2007) a | Yes | No | CND | Yes | Yes | No | No | No | No | Yes | No | Yes | No | NA | No | Fair |
| Azevedo and Azevedo (2023) | Yes | Yes | NR | NR | NR | No | No | No | Yes | Yes | No | Yes | CND | NA | Yes | Fair |
| Cai et al. (2021) | Yes | No | NR | Yes | No | No | No | No | Yes | Yes | NA | Yes | CND | NA | Yes | Good |
| Cengiz and Barin (2024) | Yes | Yes | Yes | Yes | Yes | No | No | Yes | Yes | Yes | No | Yes | Yes | NA | Yes | Good |
| Harnish et al. (2019) a | Yes | Yes | NR | Yes | CND | No | No | No | Yes | Yes | No | Yes | Yes | NA | Yes | Good |
| Kale et al. (2023) | Yes | Yes | Yes | Yes | Yes | Yes | No | No | Yes | Yes | No | Yes | CND | NA | Yes | Good |
| Kim et al. (2018) a | Yes | Yes | CND | Yes | Yes | NR | No | No | No | Yes | No | Yes | CND | NA | Yes | Good |
| Lochner et al. (2005) a | Yes | No | CND | NR | Yes | No | No | No | NA | Yes | No | Yes | CND | NA | Yes | Fair |
| Lucas and Koff (2017) | Yes | No | CND | CND | NR | No | No | No | Yes | Yes | No | Yes | NA | NA | Yes | Fair |
| Mitchell et al. (2002) a | Yes | CND | NR | CND | Yes | No | No | No | No | Yes | No | Yes | No | NA | No | Poor |
| Park and Ko (2011) | Yes | No | Yes | Yes | NR | No | Yes | No | No | Yes | No | Yes | NA | NA | No | Fair |
| Yoo and Lee (2022) | Yes | Yes | No | Yes | Yes | No | No | No | Yes | Yes | NA | Yes | NA | NA | Yes | Fair |
Note. NR = not reported; CND = cannot determine; NA = not applicable; a The study also assessed the outcome disordered eating behavior; b These studies were combined in the results section due to the same sample.
Footnotes
Funding sources: No financial support was received for this study.
Authors' contribution: Study concept and design: NML, GB; analysis and interpretation of data: NML, CBR, PR, GB; writing: NML, CBR, PR, MP, GB, GP; study supervision: GP; funding: GP; all authors had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Conflicts of interest: The authors declare no conflict of interest.
Contributor Information
Nora M. Laskowski, Email: nora.laskowski@rub.de.
Cristina Ballero Reque, Email: Cristina.BalleroReque@rub.de.
Pauline Reiß, Email: Pauline.Reiss@ruhr-uni-bochum.de.
Marie Pahlenkemper, Email: M-Pahlenkemper@t-online.de.
Gerrit Brandt, Email: Gerrit.Brandt@rub.de.
Georgios Paslakis, Email: Georgios.Paslakis@rub.de.
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