Co-occurrence between eating disorder symptoms and addictive behaviors among adult women: a controlled analysis

Abstract

Background

While associations between abnormal eating behaviors and attitudes (AEBs) and addictive behaviors have been explored, existing research does not adequately control for confounding variables, leaving the possibility of spurious correlations. Therefore, this study aims to provide clearer insights by examining the relationships between anorexic and bulimic symptoms (i.e., drive for thinness and binge eating) and specific addictive behaviors, while controlling for psychological distress and multiple addictive behaviors.

Methods

Using a sample of 2,000 adult women, the participants self-reported their drive for thinness, binge eating, psychological distress, alcohol misuse, problematic internet use, compulsive shopping, and problem gambling.

Results

Multiple regression analyses revealed that the drive for thinness was positively and negatively associated with alcohol misuse and compulsive shopping, and problem gambling, respectively. Binge eating was positively linked to problematic internet use and compulsive shopping. However, the effect sizes of these associations ranged from very small to small.

Conclusion

While the strength of the associations between AEBs and addictive behaviors among adult women, as reported in previous research, may reflect spurious correlations, the co-occurrence of different types of AEBs appears to be far more pronounced.

Plain english summary

This study investigated the associations between eating disorder symptoms—specifically, a heightened desire for thinness and binge eating—and addictive behaviors like excessive drinking, compulsive shopping, and problematic internet use. We analyzed data from 2,000 adult women who reported on their experiences with these behaviors, and their levels of psychological distress.

Our findings showed that women with a strong drive for thinness were more likely to report alcohol misuse and compulsive shopping, but less likely to engage in problem gambling. Women with binge eating behaviors were more likely to struggle with excessive internet use and compulsive shopping. However, these connections were generally weak.

Overall, the results suggest that some previous studies may have overestimated the links between eating disorders and addictive behaviors. At the same time, the co-occurrence of different types of eating disorders remains an important area for further study. This research highlights the complexity of these issues and the need for a more nuanced understanding to better support those affected.

Background

Abnormal eating behaviors and attitudes (AEBs), which are symptoms of eating disorders, are among the most common mental health problems among women [1]. Although AEBs often manifest during adolescence [2], these symptoms have also been reported to occur during adulthood. A Finnish cohort study reported that approximately 20% (17.7–22.4%) of adult women aged 32, 42, and 52 years experienced body dissatisfaction [3]. Similarly, a study conducted in the United States found that approximately half (44.6–65.5%) of adult women aged 27 to 33 had engaged in unhealthy weight control behaviors, and more than 10% (12.0–17.9%) had experienced binge eating in the past year [4].

Similar findings have been observed in Asia. For example, a study in Taiwan found that the incidence rate of eating disorders among women in their 30s was comparable to that of late teenage girls [5]. Additionally, 6.9% of female nurses in South Korea aged 20 to 45 (n = 7,267) exhibited excessive binge eating symptoms [6]. In Japan, 2.4% of women in their 20s and 30s (n = 4,517) scored above the cutoff on the Eating Attitude Test-26 [7]. Because AEBs lead to reduced social functioning, decreased quality of life, and increased mortality rates [1, 8, 9], they are critical factors affecting women’s well-being.

AEBs are likely to be associated with, or co-occur with, various addictive behaviors. One of these behaviors is problematic internet use, which refers to patterns of internet use that result in psychological, social, academic, or work-related impairments in daily life [10]. Although there are ongoing discussions regarding the classification of problematic internet use as a behavioral addiction [11, 12], it has been suggested that its severity should be viewed as a continuum rather than a dichotomy (i.e., present or absent) [13, 14]. Accordingly, this study conceptualizes the level of problematic internet use as a continuous variable.

A meta-analysis of studies on students reported that problematic Internet users have a higher prevalence of eating disorders compared with their counterparts, with a medium effect size [15]. Studies conducted among Chinese adolescents and young adults show that women with problematic Internet use were more likely to engage in severely restrictive dieting and binge eating behaviors compared with their counterparts [16, 17]. Another study among college students found that problematic social media use was positively associated with the severity of binge eating behaviors [18]. However, some studies do not find a significant association between AEBs and problematic internet use [19].

Alcohol misuse is also associated with AEBs. A recent meta-analysis has found a positive association between binge drinking, recognized as a risk factor for both binge eating and alcohol use disorders [20], and binge eating [21]. Moreover, a longitudinal study by Horváth and colleagues [22] with young adults revealed that anorexic and bulimic symptoms, such as drive for thinness, excessive weight loss, and binge eating, indirectly predicted increased alcohol consumption and more frequent episodes of drunkenness. However, drive for thinness among women did not predict the development of alcohol misuse. Other studies have yielded similar and conflicting findings. For instance, female adolescents with AEBs, including drive for thinness, body dissatisfaction, and binge eating, have been reported to be more likely to engage in alcohol use behaviors [23, 24]. However, Fischer and Smith [25] found no significant correlation between binge eating and alcohol misuse.

Compulsive shopping and problem gambling also co-occur with AEBs. However, compared with alcohol misuse and problematic internet use, research on the relationship between AEBs and these addictive behaviors is limited. Compulsive shopping is a preoccupation with shopping and spending that causes subjective distress and/or impairs quality of life [26]. One review found that 8–35% of adults with compulsive shopping disorder have a co-occurred eating disorder [27]. In another study, college students with more severe drive for thinness or binge eating were more likely to have higher levels of compulsive buying [28]. However, one study found no difference in the prevalence of eating disorders between adults with compulsive buying and the general population [29].

Problem gambling includes individuals who suffer clinically significant impairment because of their gambling activities [30]. A survey of Swedish individuals with a gambling disorder found that approximately 8% of female patients had been diagnosed with an eating disorder [31]. Another study with adults diagnosed with gambling disorder found that approximately 30% of women with gambling disorder exhibited binge eating symptoms [32]. However, Jiménez-Murcia et al. also reported that the prevalence of gambling disorder among adults with any eating disorder (1.49%) is comparable to the general population (1.5%) [33].

As noted above, AEBs are associated with or co-occur with various addictive behaviors. The co-occurrence of multiple psychiatric symptoms results in poor symptom improvement [34]. A review also suggested that the co-occurrence of other psychiatric symptoms with AEBs contributes to longer duration and greater severity of AEBs, poorer functional outcomes, and poorer treatment outcomes [35]. In particular, adult women are likely to have more severe AEBs than adolescent girls [36, 37]. Given these considerations, practitioners must understand the addictive behaviors that are more likely to be co-occurred with AEBs to treat women with AEBs, particularly adult women, effectively.

However, existing research has several limitations. First, previous studies often failed to account for the interrelationships between different addictive behaviors, despite evidence suggesting that these behaviors are frequently associated with one another [38,39,40,41]. Most of these studies examined the association between an individual’s AEB and a single addictive behavior in isolation, without controlling for other co-occurring addictive behaviors that might influence the results.

Second, many studies have not controlled for levels of depressive and anxiety symptoms, which are strongly associated with both AEBs and addictive behaviors [39, 42]. Consequently, the reported associations between AEBs and a particular addictive behavior in previous research may reflect spurious correlations, mediated either by other unmeasured addictive behaviors or by psychological factors such as depression and anxiety.

Third, although numerous studies have demonstrated a strong relationship between anorexic and bulimic symptoms [42, 43], most have explored only one of these symptoms when examining their associations with addictive behaviors [18, 19]. Hence, the findings might have been influenced by unmeasured confounding variables from the other types of AEBs.

Moreover, AEBs often show a high degree of crossover. For instance, individuals with anorexia nervosa may also exhibit bulimic symptoms such as binge eating and compensatory behaviors [30]. Conversely, those diagnosed with bulimia nervosa may engage in excessive dietary restriction as part of their compensatory behaviors, or demonstrate an intense fear of weight gain [30, 44]. These findings suggest that specific AEBs are not necessarily confined to a single diagnostic category.

Therefore, although some studies have reported associations between addictive behaviors and specific eating disorder diagnoses [27, 31, 33], such diagnostic labels alone may not accurately capture the nature of these associations. Examining the associations at the level of specific symptoms, rather than diagnostic categories, may provide more precise insights into how AEBs relate to addictive behaviors.

Given these limitations, this study aims to extend the existing literature by examining the associations between both types of AEBs and individual addictive behaviors, while simultaneously accounting for additional addictive behaviors and psychological distress in the analytic models. Accordingly, this study elucidates the nature and strength of the associations between AEBs and specific addictive behaviors. We hypothesized that although the associations between AEBs and addictive behaviors reported in previous research would remain significant, the strength of these associations would be reduced when controlling for multiple addictive behaviors and the two types of AEBs.

Materials and methods

Participants

The participants included Japanese women aged 20 to 59, who were registered with a research company as potential respondents. Based on the findings of a previous study [45] stating that the onset of eating disorders is rarely observed after the age of 60, this study explores adult women under 60. The inclusion criteria included: participants had to be women and between the ages of 20 and 59. Using national demographic data on the age and regional distribution of the woman population in 2022 [46], 2,000 women were randomly selected from the research company’s respondent pool using a random number table based on their registration numbers. For example, national data indicate that 9.5% of the total woman population in Japan are in their 40s, and living in the Kanto area. Using stratified random sampling, we recruited 190 women (9.5%) in their 40s from the Kanto region.

Given that this study recruited participants from the panel of Rakuten Insight, an online survey company in Japan, sampling bias may be presented. However, because the sample was drawn based on Japan’s population distribution, biases typically arising from surveys conducted in a specific region have been minimized. Participants received a financial incentive in the form of electronic money (800 Japanese yen, approximately 5 USD)—digital payment points that could be redeemed for a wide variety of goods and services both within Japan and internationally, including at affiliated retailers and online stores. Data was collected in September 2023. Table 1 presents the demographic details of the sample.

Table 1 Sample characteristics

Measures

Japanese version of the 91-item eating disorder inventory (J-EDI-91)

Drive for thinness is a core symptom of anorexia nervosa [47]. Therefore, this study measured anorexic symptoms through drive for thinness. Regarding bulimic symptoms, we explored binge eating, one of its central features [41]. Both drive for thinness and binge eating were assessed using the J-EDI-91 [48], developed from the Eating Disorder Inventory-2 [49]. The J-EDI-91 has been demonstrated to have high reliability and validity [48]. In this study, the Drive for Thinness and Bulimia subscales were used to assess participants’ levels of drive for thinness and binge eating, respectively. The Drive for Thinness subscale comprises eight items (e.g., “I think about dieting”), while the Bulimia subscale includes seven items (e.g., “I stuff myself with food”), both rated on a 6-point scale (1 = never to 6 = always). In this study, higher scores indicated more severe symptoms for both subscales, with McDonald’s omega values of 0.928 and 0.891 for the Drive for Thinness and Bulimia subscales, respectively.

Internet addiction test (IAT)

Problematic internet use was measured using the Internet Addiction Test (IAT; Young [14]). The IAT comprises 20 questions about internet use frequency, such as “How often do you find that you stay online longer than intended?” Items are rated on a 5-point scale (1 = rarely to 5 = always); the total score ranges from 20 to 100, with higher scores indicating more severe problematic internet use. The Japanese version of the IAT has demonstrated reliability and validity [50, 51]. In this study, McDonald’s omega for the IAT was 0.957.

Kurihama alcoholism screening Test– Female version (KAST-F)

Alcohol misuse was assessed using the KAST-F [46], which includes eight items, such as “I often cannot fall asleep without drinking alcohol.” Responses are binary (1 = no, 2 = yes), with higher scores indicating more severe alcohol use problems. Previous research [52] has demonstrated that the KAST-F has superior screening ability compared with standard tools such as the cut-down, annoyed, guilty, and eye-opener questionnaire [53] and Alcohol Use Disorders Identification Test [54] owing to its ability to discriminate between clinical and non-clinical groups. The Japanese Ministry of Health, Labour, and Welfare [55] recommends using the KAST-F for assessing alcohol misuse among adult women. Although the KAST-F has a clinical cutoff score (3 or more points suggest alcohol dependence), this study uses continuous scores. McDonald’s omega for the KAST-F was 0.853.

Process dependence scale (PDS)

Compulsive shopping and gambling behaviors were measured using the PDS [56], which assesses six behavioral addictions, including gambling and shopping. Each PDS subscale comprises five items, with statements such as “I have spent a lot of money gambling” and “Once I start shopping, I can’t stop.” Previous research has confirmed the reliability and validity of the PDS [56]. In this study, McDonald’s omega values for the gambling addiction and compulsive shopping subscales were 0.948 and 0.897, respectively.

Kessler 6 Japanese version (K6-J)

Psychological distress, including symptoms of depression and anxiety, was measured using the K6-J [57]. This six-item scale (e.g., “In the past 30 days, how often have you felt nervous?“) uses a 5-point response scale (1 = all the time to 5 = none of the time). Higher scores indicate greater psychological distress. The K6-J has been validated for use in Japan [57]. In this study, McDonald’s omega for the K6-J was 0.925.

Demographic variables

Demographic data collected in this study included occupation, annual household income, marital status, and the presence of children. Occupation was classified into ten categories (see Table 1). Annual household income, an indicator of socioeconomic status, was measured on a 10-point scale (1 = less than 1,000,000 yen to 10 = 20,000,000 yen or more), with an additional “don’t know/prefer not to answer” option. Marital status was assessed on a 2-point scale (1 = married, 2 = single [divorced, widowed, or never married]), and participants were asked if they had children (1 = no, 2 = yes).

Procedures

All data were collected via an online survey in December 2022. Before completing the survey, participants provided informed consent, and their identities were anonymized to ensure confidentiality. The study was approved by the ethics committee of the faculty with which the first author is affiliated (approval number: 2021-40). Some sentences in this manuscript were translated from Japanese to English using Paperpal, a generative AI-based tool.

Data analysis

Because the dataset obtained from the survey company contained no missing data, handling of the missing data was not required. Zero-order correlations were calculated between each measured variable to obtain the descriptive statistics. However, correlation analyses do not account for potential confounding effects from other variables, which could lead to spurious correlations. Consequently, the observed association between each AEB (i.e., drive for thinness or binge eating) and a specific addictive behavior might be confounded by other variables, such as the remaining AEB, other addictive behaviors, or psychological distress. Consequently, accurately determining the effect size of the relationship between each AEB and the individual addictive behaviors becomes challenging.

To address this, multiple regression analyses were conducted to examine the associations between each AEB (i.e., drive for thinness or binge eating) and specific addictive behaviors, while controlling for the effects of other relevant variables. Specifically, a separate multiple regression was performed for each addictive behavior as the dependent variable. Independent variables included both types of AEBs, other addictive behaviors, psychological distress, and demographic variables.

While definitive standards for interpreting effect sizes in regression analyses (e.g., B or β) are not universally established, we followed the approach commonly used in previous studies [58, 59]. Specifically, we employed the t-to-r transformation to evaluate the effect sizes of the associations between each AEB and each addictive behavior. The effect sizes of the correlation coefficients were interpreted according to the guidelines for psychological research proposed by Funder and Ozer [60], where the r values of 0.05, 0.10, 0.20, 0.30, and 0.40 or greater indicate very small, small, medium, large, and very large effects, respectively. All quantitative variables were standardized before analysis.

We conducted four separate analyses using the same dataset (i.e., with problematic internet use, alcohol misuse, compulsive shopping, and problem gambling as dependent variables). Existing research indicates that repeated analyses on the same data increase the risk of Type I errors [61]. To avoid such risks, we adjusted the significance level to 0.0125 using the Bonferroni correction. All analyses used Predictive Analytics SoftWare (PASW) Statistics (SPSS ver. 27.0).

Results

Descriptive statistics

Table 2 shows the means, standard deviations, and zero-ordered correlations among the variables of interest. Regarding annual house income, approximately 24% of the participants (n = 472) responded that they “don’t know/prefer not to answer.” There were no regional or age group differences in refusal rates (i.e., 20–29, 30–39, 40–49, and 50–59; χ2(21) = 17.98, n.s.). These participants were excluded from the following correlation analysis.

Table 2 Descriptive statistics and pearson’s product-moment correlations among variables

Drive for thinness was positively correlated with binge eating (r =.667, p <.001), indicating a very large effect size. It was also significantly correlated with higher levels of problematic internet use and psychological distress (r =.349 and 0.357, respectively; ps < 0.001), with large effect sizes. Additionally, drive for thinness was positively correlated with alcohol misuse (r =.145), problem gambling (r =.110), and compulsive shopping (r =.286), all ps < 0.001; however, these correlations reflected small to medium effect sizes.

Similarly, binge eating was positively correlated with both problematic internet use and psychological distress (r =.432 and 0.461, respectively; ps < 0.001), indicating very large effect sizes. Binge eating was also positively correlated with compulsive shopping (r =.341, p <.001), reflecting a large effect size, and with problem gambling (r =.200, p <.001) and alcohol misuse (r =.147, p <.001), both of with indicated small to medium effect sizes.

Multiple regression analysis

Multiple regression analyses were conducted to examine the associations between each AEB (i.e., drive for thinness or binge eating) and individual addictive behaviors, controlling for other variables. Initially, the participants who answered that they “don’t know/prefer not to answer” for socioeconomic status (SES; i.e., annual hose income) were excluded. Except for problem gambling, SES was not significantly associated with any of the addictive behaviors examined (problematic internet use: β = 0.015, p =.469.; alcohol misuse: β = 0.020, p =.463.; compulsive shopping: β = 0.023, p =.309.; problem gambling: β = -0.016, p =.010). Therefore, SES was not controlled for in the multiple regression analyses where problematic internet use, alcohol misuse, and compulsive shopping were the dependent variables, and the full sample (n = 2,000) was included in the analysis. However, SES was controlled for in the multiple regression analysis where problem gambling was the dependent variable. Participants who selected “don’t know” or “prefer not to answer” for the SES item were excluded, and only those who answered the level of their annual household income (n = 1,528) were included in the final analysis.

Table 3 presents the results of the multiple regression analysis with problematic internet use as the dependent variable. Drive for thinness showed an insignificant association (β = 0.038, p >.05; r =.035), and the effect size was very small. In contrast, binge eating showed a significant positive association (β = 0.170, p <.001; r =.149), with a small effect size. All addictive behaviors (i.e., alcohol misuse, compulsive shopping, and problem gambling) as well as psychological distress, were significantly positively associated with problematic internet use (β = 0.055, 0.202, 0.056, and 0.327, respectively; all ps < 0.01). The effect sizes for these associations ranged from small to medium. Among them, compulsive shopping showed a moderate association (r =.202), while psychological distress showed a strong association (r =.340).

Table 3 Result of the multiple regression analysis with problematic internet use as a dependent variable (n = 2,000)

Table 4 presents the results of the multiple regression analysis with alcohol misuse as the dependent variable. Although binge eating showed an insignificant association (β = -0.011, p >.05; r = -.008), drive for thinness showed a significant positive association (β = 0.123, p <.001; r =.092), indicating a very small effect size. Both problematic internet use and problem gambling were also significantly positively associated with alcohol misuse (β = 0.084 and 0.092, respectively, ps < 0.01; r =.068 and 0.080, respectively); however, the effect sizes were very small.

Table 4 Result of the multiple regression analysis with alcohol misuse as a dependent variable (n = 2,000)

Table 5 presents the results of the multiple regression analysis with compulsive shopping as the dependent variable. Both AEBs (i.e., drive for thinness and binge eating) showed significant positive associations (β = 0.090 and 0.095, respectively, ps < 0.001; r =.083 and 0.084, respectively), indicating very small effect sizes. Problem gambling also showed a significant positive association with compulsive shopping (β = 0.427, p <.001; r =.460), reflecting a very large effect size.

Table 5 Result of the multiple regression analysis with compulsive shopping as a dependent variable (n = 2,000)

Table 6 presents the results of the multiple regression analysis with problem gambling as the dependent variable. While binge eating showed an insignificant association (β = 0.046, p >.05; r =.038), drive for thinness showed a significant negative association (β = -0.109, p <.001; r = −.095), indicating a small effect size. All other addictive behaviors (i.e., problematic internet use, alcohol misuse, and compulsive shopping) were significantly positively associated with problem gambling (β = 0.077, 0.079, and 0.484, respectively, ps < 0.01; r =.072, 0.091, and 0.454, respectively). Among these, compulsive shopping demonstrated a very strong association, while the associations with problematic internet use and alcohol misuse were weak. Table 7 summarizes the correlation coefficients between both types of AEBs and each addictive behavior, based on zero-order correlations and multiple regression analyses.

Table 6 Result of the multiple regression analysis with problem gambling as a dependent variable (n = 1,528)

Table 7 Summary of correlation coefficients between AEBs and addictive behaviors

Discussion

This study surveys 2,000 adult women to examine the concurrent associations between two types of behaviors associated with eating disorder (drive for thinness and binge eating) and several addictive behaviors. Controlling for both types of AEBs, multiple addictive behaviors, and psychological distress, multiple regression analyses revealed distinct associations between drive for thinness and binge eating with different addictive behaviors, except for compulsive shopping, where both were similarly related. Drive for thinness was positively associated with alcohol misuse and compulsive shopping, but negatively associated with problem gambling. By contrast, binge eating was positively associated with problematic internet use and compulsive shopping.

Associations of AEBs with problematic internet use

In the zero-order correlation analyses, both drive for thinness and binge eating were strongly and positively correlated with problematic internet use. However, in the multiple regression analyses controlling for the other AEBs, addictive behaviors besides problematic internet use and psychological distress, binge eating maintained a weak positive association with problematic internet use. At the same time, drive for thinness lost its significance. These findings suggest that among AEBs, only binge eating is directly associated with problematic internet use. This suggests that the initial correlation between drive for thinness and problematic internet use, as observed in the zero-order correlation, was likely spurious, driven by confounding effects from other variables.

The non-significant association between drive for thinness and problematic internet use diverges from some earlier studies. For instance, Tao and Liu [16] found that women with problematic internet use engaged in more frequent dieting behaviors. Nevertheless, their study did not control for other addictive behaviors, which increases the possibility of spurious correlations. Moreover, their study found no significant differences in body dissatisfaction, a construct closely associated with drive for thinness [17, 62]. These inconsistencies underscore the complexity of the relationship between drive for thinness and problematic internet use. Considering the methodological differences, particularly the inclusion of confounding factors in this study, the absence of a significant association between drive for thinness and problematic internet use seems plausible and warrants further investigation.

The positive association between binge eating and problematic internet use found in this study aligns with previous research that did not consider other addictive behaviors [17, 18]. By controlling for both drive for thinness and psychological distress—two factors previously shown to be linked to both binge eating and problematic internet use—this study provides more robust evidence of the association between binge eating and problematic internet use among adult women.

This positive association may be partly explained by interoceptive difficulties. Patients with bulimia nervosa and binge eating disorder have been shown to exhibit significantly greater interoceptive difficulties compared with healthy controls [63]. Similarly, another study found that individuals with problematic internet use demonstrated lower levels of interoception, including reduced emotional differentiation and decreased confidence in perceiving one’s body as reliable, compared with non-clinical individuals [64]. These findings suggest that interoceptive difficulty may mediate the relationship between binge eating and problematic internet use, as observed in this study. Future research is warranted to empirically test this mediating mechanism.

Association of AEBs with alcohol misuse

Both types of AEBs showed a weak positive correlation with alcohol misuse in simple correlation analyses. In multiple regression analyses, while drive for thinness maintained a very weak positive association with alcohol misuse, the association between binge eating and alcohol misuse became insignificant. This finding is surprising in light of the results of previous research. Several studies have reported that binge eating is weakly to moderately associated with alcohol misuse [23, 65, 66]. Moreover, some researchers argued that binge eating was more strongly linked to alcohol misuse than anorexic symptoms, such as drive for thinness [23, 66]. our knowledge, this study provides the first empirical evidence that alcohol misuse among adult women is associated with drive for thinness rather than binge eating.

Several factors may explain the discrepancy between the results of this study and those of previous research. One key factor is the methodological rigor of this study, particularly the simultaneous inclusion of drive for thinness, binge eating, and multiple addictive behaviors in the analytic model. Meanwhile, previous studies, such as those conducted by Baker et al. [23, 24], have examined the associations between alcohol misuse and anorexic or bulimic symptoms (i.e., drive for thinness or binge eating) separately. This approach might have limited their ability to fully capture the complex interplay between these variables. Furthermore, meta-analyses such as those conducted by Gadalla and Piran [66] often included studies that did not control for the confounding effects of anorexic symptoms (e.g., drive for thinness or dietary restraint) and bulimic symptoms (e.g., binge eating or purging). This methodological limitation might have contributed to the previous conclusion that binge eating is strongly associated with alcohol problems, while the effect of anorexic symptoms, such as drive for thinness, might have been underestimated.

The underlying mechanism through which drive for thinness was positively associated with alcohol misuse can be understood in light of existing knowledge. First, women with a strong drive for thinness can often closely monitor their caloric intake [30], which may lead them to restrict food consumption before, during, or after alcohol consumption to compensate for the calories gained. Young adults with higher levels of drive for thinness were reported to be more likely to engage in compensate behaviors to reduce calorie intake surrounding alcohol consumption; such behaviors were positively associated with greater alcohol use [67]. Similarly, a recent study has found that approximately 10% of women in their 30s regularly restrict their food intake before and after drinking alcohol [68]. As a slim female body is widely idealized today [67], adult women may internalize a strong association between alcohol consumption and dietary restraint. Consequently, alcohol misuse and drive for thinness may be directly linked through the perceived “reward” of preventing weight gain.

Association of AEBs with compulsive shopping

Both types of AEBs were positively correlated with compulsive shopping, with effect sizes ranging from moderate to strong. In the multiple regression analyses, although the effect sizes were greatly reduced and became very weak, both AEBs maintained significant positive associations. These results suggest that while the presence of either type of AEB is directly related to the co-occurrence of compulsive shopping, the strength of this influence is quite small.

Consistent with these findings, Claes et al. [28] reported that even after controlling for depressive symptoms among female university students, the severity of compulsive shopping was moderately and positively correlated with both drive for thinness and binge eating. However, compared with the findings of Claes et al. [28], the effect sizes in this study were smaller for the associations between the AEBs (i.e., drive for thinness and binge eating) and compulsive shopping. This difference is likely attributable to this study’s control for other addictive behaviors and the inclusion of both types of AEBs in the analysis. Indeed, the correlation coefficients reported by Claes et al. [28] (drive for thinness: r =.23, binge eating: r =.37) are largely consistent with those observed in this study. Therefore, it can be inferred that the co-occurrence of behaviors associated with eating disorders and compulsive shopping is a well-established phenomenon among women.

Associations of AEBs with problem gambling

In the simple correlation analysis, both AEBs showed a weak positive correlation with problem gambling. However, in the multiple regression analysis that controlled for other variables, no significant association was identified between binge eating and problem gambling, and surprisingly, drive for thinness exhibited a very weak inverse association with problem gambling. While the effect size of this association was small, to our knowledge, this is the first study to demonstrate a negative relationship between drive for thinness and the severity of problem gambling behaviors among adult women. Given the lack of previous quantitative studies directly examining the relationship between the severity of problem gambling and AEBs, this study advances the understanding of the co-occurrence between AEBs and problem gambling.

The results of this study are partially consistent with previous research, but also offer new insights. In the zero-order correlation analysis, both types of AEBs were weakly and positively correlated with problem gambling. This aligns with the findings of Boughton and Falenchuk [69], who reported that adult women who engage in problem gambling are more likely to exhibit excessive dietary restraint or binge eating compared with the general woman population. However, in contrast to the correlation analysis, the multiple regression analysis, which controlled for the impacts of other variables, revealed that only drive for thinness had a significant inverse association with problem gambling. These results suggest that the relationship between AEBs and problem gambling among adult women is highly complex, likely influenced by various factors such as other AEBs, addictive behaviors, and psychological distress.

The positive association between problem gambling and food restriction observed in previous research [69] is theoretically plausible. For example, difficulties in interoception, as well as impulsivity, which is positively correlated with impaired interoception [70], have been linked to increased levels of problem gambling [70,71,72]. Furthermore, compared with healthy controls, individuals with anorexia nervosa or bulimia nervosa have been shown to exhibit significantly greater interoceptive dysfunction [63, 73]. Based on these empirical findings, a positive association between problem gambling and drive for thinness would seem reasonable.

However, findings in non-clinical samples have been inconsistent with this expectation. For instance, a study on university students found a weak positive correlation between dietary restraint and impulsivity (r =.16) among underweight and normal-weight individuals, but no significant correlation among those who were overweight [74]. Moreover, Borlimi et al. [73] reported a strong positive correlation between drive for thinness and interoceptive dysfunction among individuals with bulimia nervosa (r =.51), but a non-significant negative correlation (r = −.23) among healthy individuals. These findings suggest that the strength and the direction of the association between problem gambling and drive for thinness may vary depending on sample characteristics, regardless of whether the population is clinical or non-clinical.

One possible explanation for the negative association between drive for thinness and problem gambling observed in this study is that adult women in modern society place great importance on how they are perceived and valued by other people, especially regarding their appearances. In contemporary society, socio-cultural and structural pressures, such as diet culture, patriarchal systems, pervasive weight bias and weight discrimination, and healthism, reinforce associations between femininity and thinness [75, 76]. Within these systems, women may strive for thinness as an expectation of femininity and gender expression. For example, a Japanese study [64] found that many adult women with an average body mass index (BMI) perceive themselves as “overweight,” and this perception is linked to the belief that maintaining a slim figure contributes to both their sense of femininity and psychological stability [77]. Indeed, in various cultures, including Japan, being overweight can hinder women’s social and career successes [75, 76].

Meanwhile, gambling, particularly in Japan, is socially stigmatized [78]. Pachinko, one of the most common forms of gambling among individuals with gambling disorder [79], is predominantly played by men and has a very low participation rate among adult women [80]. Therefore, women who engage in pachinko gambling may perceive it as damaging to their perceived femininity.

In addition, traditional cultural values in Japan may help explain the negative association between drive for thinness and problem gambling. Japanese cultural norms have historically emphasized virtues such as diligence and modesty as socially valued traits [81]. Furthermore, within traditional discourse, the concept of naijo no kō—which refers to the idea that an adult woman or wife supports her partner or family members through behind-the-scenes efforts—has been presented as one desirable way of contributing to household wellbeing [82].

Moreover, in Japanese cultural narratives, even earning money is often associated with values such as contributing to society and finding purpose in work, rather than solely pursuing personal gain [83]. In contrast, gambling is frequently portrayed as involving risk, impulsiveness, and reliance on chance [81], which may be considered misaligned with these broader Japanese societal norms. Collectively, these cultural factors may help explain why drive for thinness is inversely associated with problem gambling among adult women.

Associations between the addictive behaviors

This study reveals that all addictive behaviors showed moderate to strong positive correlations with each other. Nonetheless, in the multiple regression analyses, which controlled for the influence of other variables, most of these relationships remained significant, except for the link between alcohol misuse and compulsive shopping. One possible explanation for these positive associations among addictive behaviors is the role of heightened impulsivity and its link to interoception [70]. Several previous studies demonstrate that higher levels of impulsivity are associated with a range of addictive behaviors [71, 84]. Regarding interoception, interoceptive dysfunction has been linked to problem gambling [71] and alcohol misuse [85]. Collectively, these findings help explain the positive associations observed among the addictive behaviors in this study.

Among these relationships, two were particularly strong: the link between problematic internet use and compulsive shopping, and the association between compulsive shopping and problem gambling. Specifically, the effect size for the relationship between problematic internet use and compulsive shopping was moderate, while the association between compulsive shopping and problem gambling demonstrated a very strong effect size. The former may be understood in the context of the rapid growth of e-commerce, which has contributed to the emergence of online compulsive buying–shopping disorder [86, 87]. Similarly, the latter finding aligns with previous research indicating that women with problem gambling exhibit significantly higher rates of compulsive shopping compared with the general population [69]. Based on the results of this study and previous research, adult women who exhibit compulsive shopping behaviors may be at elevated risk for both excessive internet use and problem gambling, highlighting a notable co-occurrence of these addictive behaviors.

Limitations and future research directions

This study has several limitations. First, as the study was cross-sectional, it does not provide evidence of causality. Therefore, longitudinal studies are needed to determine the directionality of the relationships between AEBs and addictive behaviors. Second, this study exclusively explores adult women. However, it has been reported that the relationship between AEBs and addictive behaviors differs between men and women [88]. Therefore, the results of this study should not be generalized to adult men without caution.

Similarly, the extent to which these findings apply to clinical populations with eating disorders remains uncertain. Future research should aim to replicate and extend these findings in both man populations and clinical settings to confirm their generalizability. Lastly, drive for thinness and binge eating were assessed using self-report questionnaires in this study. Therefore, our data based on self-reporting measures may be susceptible to inaccurate reporting. Further, previous research shows that the severity of AEBs reported in self-reported assessments may differ from those assessed in clinical interviews conducted by professionals [89]. Therefore, the results of this study might have been influenced by the method of symptom assessment. Future studies should aim to validate this study’s findings using various assessment methods.

Conclusion

This study provides a nuanced understanding of the relationship between AEBs and addictive behaviors by accounting for confounding variables. While simple correlation analyses suggested broad positive associations, regression analyses revealed more specific patterns: drive for thinness was positively associated with alcohol misuse and compulsive shopping but negatively associated with problem gambling. Binge eating was positively linked to problematic internet use and compulsive shopping. However, the effect sizes of these significant associations ranged from very small to small. In contrast, the associations between problematic internet use and psychological distress, as well as between compulsive shopping and problem gambling, showed large effect sizes. These findings suggest that certain addictive behaviors may be more strongly related to psychological distress or to other addictive behaviors than to AEBs. These findings highlight the importance of examining the interplay between AEBs and addictive behaviors within a broader psychological framework, while acknowledging the limitations of cross-sectional data in establishing directionality.