Working Memory and Inhibition as Mediators in the Relationship Between Adverse Childhood Experiences and Emotional Eating

Abstract

Objective: Previous studies have focused on the dual relationship among adverse childhood experiences (ACEs), cognitive abilities, and emotional eating. The current study aims to test the mediating role of executive functioning (working memory and inhibition) between ACEs and emotional eating. Methods: A total of 1105 community-based participants, aged 18–45 (Mean = 26.28, SD = 7.09), were included in the study. Among the participants, 698 (63.16%) were female, and 407 (36.84%) were male. Participants completed the Childhood Trauma Questionnaire; the Adult Executive Functioning Inventory; the Dutch Eating Behaviour Scale; the Life Events Checklist; and the Depression, Anxiety, Stress Scale Short Form. Multiple mediation analyses were employed using MPlus 8.3. Results: Multiple mediation analysis results showed that working memory and inhibition mediate the relationship between ACEs and emotional eating. Furthermore, working memory and inhibition were positively correlated with emotional eating. Discussion: Our findings indicate that difficulties in working memory and inhibition may increase the risk of emotional eating. Early intervention targeting executive functions may prevent emotional eating. Public Significance: Our findings highlight the relationship among ACEs, executive functioning, and emotional eating. Intervening in executive function may have clinical benefits for individuals with ACEs.

Keywords

adverse childhood experiences emotional eating inhibition working memory

Adverse childhood experiences (ACEs), such as neglect, abuse, absence of parents, and household challenges, are frequently used to describe adverse experiences that occur before age 18 (Felitti et al., 1998; Taylor-Robinson et al., 2018; Wickrama & Noh, 2010). Epidemiological studies have consistently demonstrated the widespread prevalence of exposure to ACEs in societies. Over two-thirds of individuals in the United States (Giano et al., 2020; Merrick et al., 2018) and China (Lin et al., 2021) have at least one ACE before the age of 18. Moreover, the consequences of ACEs have burdened countries’ health systems (e.g., Hughes et al., 2020; Miller et al., 2020). For instance, Peterson et al. (2023) reported that the annual burden of health problems associated with ACEs on the U.S. health system is approximately $14.1 trillion.

Consequences of ACEs for Mental and Cognitive Health

Previous studies have indicated the adverse effects of growing up under stressful conditions (Dube et al., 2002; Kalmakis & Chandler, 2015). ACEs may lead to various mental health problems that include mood disorders (Elmore & Crouch, 2023), anxiety disorders (Li et al., 2016), and post-traumatic stress disorders (Rameckers et al., 2021). In addition, previous studies have indicated that ACEs lead to cognitive impairment (e.g., Goodman et al., 2019). In particular, studies often focus on ACE-based impairments in executive function (EF; Letkiewicz et al., 2021; Lund et al., 2020; Lund et al., 2022), a high-level cognitive function that regulates our goal-directed behavior (Miyake et al., 2000). ACEs impair many aspects of cognitive functioning in adulthood; therefore, individuals who are exposed to ACEs commonly exhibit poor performance in dimensions of EFs such as inhibition, working memory, and cognitive flexibility (Letkiewicz et al., 2021; Lund et al., 2022; Lynch & Widom, 2022). In addition, findings from neurodevelopmental research support the relationship between ACEs and EFs (Letkiewicz et al., 2021; Nikulina & Widom, 2013).

Neurodevelopmental Mechanisms Linking ACEs and Executive Functions

The prefrontal-limbic system, which includes the hippocampus, amygdala, and prefrontal cortex (PFC), plays a central role in stress regulation (Godsil et al., 2013). Mental health issues are likely to develop in the event of dysregulation within the prefrontal-limbic system, which research has suggested may have roots in ACEs (Teicher et al., 2016). Studies have shown a decline in hippocampal volume associated with ACEs (Chaney et al., 2014; Opel et al., 2014). ACEs have also been linked to amygdala abnormalities, affecting functions like memory and decision-making (Janak & Tye, 2015). However, some research has indicated these results remain unclear (Hoy et al., 2012; Kuhn et al., 2016). Moreover, ACEs broadly correlate with a reduction in gray matter volume within the PFC (Chaney et al., 2014), a central region for EFs (Funahashi & Andreau, 2013). Therefore, the PFC and EFs may be susceptible to ACEs due to their connections with the hypothalamic-pituitary-adrenal (HPA) axis, hippocampus, and amygdala.

Emotional Eating and its Psychological Underpinnings

Emotional eating reflects the tendency to engage in excessive food consumption in response to negative emotional states such as anxiety or irritability (Devonport et al., 2019; van Strien et al., 2012). Research has suggested that emotional eating is prevalent among overweight and obese individuals. Over 60% of these people exhibit tendencies toward emotional eating (Ganley, 1989; Konttinen et al., 2019; van Strein, 2018). Moreover, individuals who tend toward emotional eating behavior are prone to choose foods rich in fat, sugar, and calories when confronted with negative emotional experiences (Elfhag & Rössner, 2005; Frayn & Knäuper, 2018; Ling & Zahry, 2021).

EFs play a crucial role in eating behaviors (e.g., Colton et al., 2023; Dohle et al., 2018; Segura-Serralta et al., 2020) through their connection to various abilities, such as impulse control and emotion regulation. EF is necessary to regulate eating behavior, for instance, generating a meal plan and preventing goal-directed responses to food cues (Goldschmidt et al., 2018).

Theoretical Links Between ACEs, Executive Functions, and Emotional Eating

Emotion-based eating problems result from difficulties in self-regulating or behavioral inhibition, characterized by poor EF performance (Pieper & Laugero, 2013). In particular, the left inferior frontal gyrus is associated with the inhibition skill required when individuals encounter food (García-García et al., 2021; Lopez et al., 2014). In general, EFs are strongly associated with planning and decision-making, regulating complex actions sequentially, suppressing automatic responses, and navigating situations that demand resistance to appealing stimuli (Allan et al., 2011; Norman & Shallice, 1986). One possible explanation is that the maturation of forebrain regions linked to EFs may restrict emotional eating behaviors rooted in the limbic system. It has been hypothesized that improved EF skills lead to a more mindful approach to eating (Dallman, 2010; Tuulari et al., 2015). Conversely, emotional eating patients demonstrate reduced inhibition performance (Lezak, 2004; Sims et al., 2014) and working memory (Gunstad et al., 2010; Houben et al., 2016). Therefore, it is reasonable to suggest that EFs, intimately associated with behaviors such as resisting alluring yet unhealthy habits and engaging in strategic meal planning, play a role in emotional eating behavior.

In addition to the neurodevelopmental and cognitive mechanisms linking adverse childhood experiences (ACEs) to eating behaviors, other pathways, such as learning maladaptive coping strategies, poverty, and food scarcity, provide valuable insights into this relationship. ACEs often foster maladaptive coping mechanisms, where individuals turn to emotional eating as a way to self-regulate distress. This behavior, rooted in childhood, becomes a learned response to manage negative emotions, leading to overeating or consuming high-calorie, palatable foods during stressful situations (Elfhag & Rössner, 2005; Frayn & Knäuper, 2018). Furthermore, socioeconomic hardships, which frequently co-occur with ACEs, play a critical role in shaping eating patterns. Childhood poverty limits access to nutritious food, increasing dependence on inexpensive, calorie-dense options while also exacerbating stress and anxiety—factors known to drive emotional eating (Darling et al., 2020; Drewnowski & Specter, 2004). Coupled with this, food insecurity during childhood can contribute to a “scarcity mindset,” where individuals overconsume food when available, driven by fears of future deprivation. This survival-based approach to eating, formed during critical developmental periods, reinforces disordered patterns such as binge eating and heightened sensitivity to food-related cues (Schag et al., 2013). Together, these pathways highlight how ACEs, through their intersection with learned behaviors, socioeconomic instability, and environmental constraints, create a multifaceted impact on eating behaviors that extends beyond direct neurocognitive effects, emphasizing the need for trauma-informed and context-sensitive interventions (Hager et al., 2010; Seligman et al., 2010).

Current Study

ACEs are consistently linked to adverse psychological outcomes, such as emotional eating behaviors (Michopoulos et al., 2015). There is a need for a better understanding of the mediating links that contribute to the occurrence of harmful outcomes such as emotional eating behaviors. For this purpose, we aimed to investigate the mediating role of the two dimensions of EFs: inhibition and working memory. To the best of our knowledge, no research has investigated the association between working memory, inhibition, ACEs, and emotional eating. Therefore, the current study’s results may provide implications for interventions targeting executive functions.

Various factors may influence ACEs, EFs, and emotional eating behaviors. First, prior studies have continually indicated that traumatic experiences, excluding those from childhood, can impact EFs. For instance, studies have shown that stressors related to traumatic events, such as the COVID-19 pandemic, may lead to deficits in working memory and inhibition (Kira et al., 2021, 2022). Another study has demonstrated that exposure to earthquake-related stress can impair EFs in adulthood (Li et al., 2015). Second, it is crucial to consider the effects of psychopathology on eating behaviors.

Emotional eating is a response to negative emotions by consuming palatable and energy-dense foods (Konttinen, 2020; Macht & Simons, 2011; İnalkaç & Arslantaş, 2018). Individuals with eating disorders often have symptoms of depression (Kaner et al., 2023; Murga et al., 2023; Speranza et al., 2003), anxiety (Bourdier et al., 2018; Kaner et al., 2023; Schulz & Laessle, 2010), and stress (Barrington et al., 2014). In summary, based on these considerations, the current study uses other traumatic experiences, depression, anxiety, and stress as covariates.

Many cognitive functions, such as EFs (Friedman et al., 2007; Salthouse, 2009), decline with age (Smith & Rush, 2006). In studies on cognitive aging, the 40s are often used as a cut-off point (Phillips & Henry, 2010). Therefore, we collected data from healthy adults aged between 18 and 45.

The study suggests several hypotheses: a positive relationship between ACEs and (a) emotional eating behavior, (b) working memory, and (c) inhibition. Moreover, it is expected that (d) working memory and (e) inhibition will mediate the relationship between ACEs and emotional eating (see Figure 1).

Method

Participants and Procedure

The participants were 1105 adults aged 18–45 (Mean = 26.28, SD = 7.09). Data were collected relying on convenience sampling in Türkiye. Among the participants, 698 (63.16%) were female, and 407 (36.84%) were male. Regarding educational status, 245 participants (22.2%) had a high school education, 682 (61.7%) had attained a college-level education, and 178 (16.1%) held a graduate-level education. In terms of marital status, 870 respondents (78.9%) were single, 195 (17.6%) were married, 27 (2.4%) were divorced, and 11 (1.0%) were widowed. As for socioeconomic status (SES), participants reported as follows: 179 (16.2%) low SES, 677 (61.3%) middle SES, 215 (19.5%) high SES, and 34 (3.1%) very high SES. SES categories were defined based on the current minimum wage in Türkiye. Table 1 presents the participants’ demographic characteristics.

Table 1.

Participants’ Demographic Characteristics.

Variable	n	%
Gender
Female	698	63.16
Male	407	36.84
Educational status
High school	245	22.2
College-level	682	61.7
Graduate-level	178	16.1
Marital status
Single	870	78.9
Married	195	17.6
Divorced	27	2.4
Widow	11	1
Socioeconomic status
Low	179	16.2
Middle	677	61.3
High	215	19.5
Very high	34	3.1

We collected data from April to May 2022 via an online self-report survey (Google Forms). In this study, 26 undergraduate students (Grade 4) from the Mersin University Psychology Department participated in the data collection process. These students shared the online forms on their social media accounts. Participants answered a set of questionnaires in the survey. All participants were informed about the purpose of the study and provided written informed consent. Participants were not given any reward for their participation.

Measurements

The Childhood Trauma Questionnaire (CTQ)

The CTQ (Bernstein et al., 1998) is a retrospective 33-item self-report questionnaire scored on a 5-point Likert scale (1 = never, 5 = very often). The CTQ assesses five dimensions of childhood neglect and abuse (emotional neglect, emotional abuse, physical neglect, physical abuse, and sexual abuse). A higher score indicates a higher level of exposure to traumatic events under age 18. Şar et al. (2012) conducted an adaptation study of the scale into Turkish, and they reported good internal consistency for the total score (α = 0.87). In the current study, the total score’s Cronbach’s alpha was calculated as 0.85.

The Adult Executive Functioning Inventory (ADEXI)

The ADEXI (Holst & Thorell, 2018) is a 14-item self-report questionnaire scored on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). ADEXI was developed to assess two dimensions of executive functioning (inhibition and working memory). Five items of the scale focus on inhibition deficits (e.g., “I have a tendency to do things without first thinking about what could happen”) and nine working memory deficits (e.g., “When someone asks me to do several things, I sometimes remember only the first or last”). A higher score reflects higher deficits in executive functioning domains. Cronbach’s alpha scores for inhibition and working memory were reported as 0.72 and 0.88, respectively. The scores of the whole scale and the working memory dimension have been reported to correlate significantly with the Color-Word Test in both clinical and non-clinical samples. Additionally, the working memory dimension has been found to have a significant relationship with the Digit Span and Number-Letter Sequencing tests in non-clinical samples (Holst & Thorell, 2018). Alpay and Kızılöz (2023) conducted an adaptation study of the scale to Turkish; the authors reported Cronbach’s alpha scores for the whole scale and for working memory and inhibition as 0.80, 0.83, and 0.73, respectively. In the current study, Cronbach’s alpha scores were calculated for working memory and inhibition as 0.78 and 0.66, respectively.

Dutch Eating Behaviour Scale (DEBS)

The DEBS (Van Strein et al., 1986) is a 33-item self-report questionnaire scored on a 5-point Likert scale (1 = never, 5 = very often). The DEBS was developed to assess three dimensions of eating behaviors (emotional eating, restrictive eating, and external eating). Cronbach’s alpha scores were reported as 0.95, 0.81, and 0.95 for emotional eating, external eating, and restricted eating behavior dimensions, respectively. A higher score reflects higher deficits in eating behavior. Bozan (2009) conducted an adaptation study of the scale to Turkish; in this study, Cronbach’s alpha for emotional eating was reported as 0.90. In the current study, we used the emotional eating dimension of the DEBS to assess the participants’ emotional eating behaviors, and Cronbach’s alpha score for emotional eating was calculated as 0.90.

Life Events Checklist (LEC)

The LEC (Blevins et al., 2015) is a 17-item self-report questionnaire scored on a 6-point Likert scale (1 = I experienced it myself, 2 = I witnessed it, 3 = I learned it, 4 = it is necessary for my job, 5 = I am not sure, 6 = it is not suitable for me). The LEC aims to assess the way an individual experiences an adverse event. In the scale, participants can mark more than one way of experiencing the questions. Boysan et al. (2017) conducted an adaptation study of the scale to Turkish; in this study, the scale’s Kuder–Richardson (KR-20) reliability coefficient was reported as 0.66 for clinical samples and 0.61 for non-clinical samples. In the current study, the KR-20 reliability coefficient was calculated as 0.72. When scoring the LEC, it has been reported that scoring directly experienced events gives more stable results compared to witnessed ones (Pugach et al., 2021). In addition, scoring based on direct experience yields higher kappa values than the condition in which other indirect exposure responses are included (Gray et al., 2004). Therefore, we coded LEC dichotomously as experience versus no experience (e.g., Bae et al., 2008).

Depression, Anxiety, and Stress Scale Short Form (DASS-21)

The DASS-21 (Lovibond & Lovibond, 1995) is a 21-item self-report questionnaire scored on a 4-point Likert scale (0 = never, 1 = sometimes, 2 = quite often, 3 = always). DASS-21 has three dimensions: depression, anxiety, and stress. Higher scores reflect higher levels of symptoms. Sarıçam (2018) conducted an adaptation study of the scale to Turkish in which Cronbach’s alpha scores for anxiety, depression, and stress were reported as 0.84, 0.91, and 0.90, respectively. In the current study, Cronbach’s alpha scores for depression, anxiety, and stress were calculated as 0.89, 0.85, and 0.87, respectively.

Statistical Method

A total of 1223 participants were included in the study. We determined the minimum number of participants according to the recommendations of Bryman and Cramer (2004). We checked for missing data and outliers, and 30 individuals were excluded from the data due to more than 25% missing data, while 68 participants were excluded based on the Mahalanobis distance. Therefore, analyses were performed with 1105 participants. We checked the data’s normality assumptions using skewness and kurtosis scores, which were within acceptable limits for all variables (George & Mallery, 2010; maximum skewness = 0.854, maximum kurtosis = −1.273).

In the statistical analysis, we first calculated descriptive statistics and used Pearson correlation analysis to investigate the relationships between study variables. For this analysis, we used the SPSS 26.0 program. To test our model, we used multiple mediation analysis. In this analysis, we tested mediating roles, working memory, and inhibition in the relationship between ACEs and emotional eating. Moreover, we added other traumatic experiences, depression, anxiety, and stress as covariates. We tested all indirect effects with bootstrapping with 10,000 resamples and 95% bias-corrected confidence intervals (CIs). We employed Mplus 8.3 for multiple mediation analyses with self-written code (Muthén et al., 2017).

Results

Preliminary Analyses

In preliminary analyses, we first calculated the variables’ means and standard deviations, and we calculated Pearson correlation scores among the variables (Table 2). The findings showed that ACEs were positively associated with working memory (r = 0.42, p < .001), inhibition (r = 29, p < .001), and emotional eating (r = 0.33, p < .001). Moreover, emotional eating was significantly related to working memory (r = 0.55, p < .001) and inhibition (r = 0.45, p < .001).

Table 2.

Descriptive Statistics and Correlations Between Study Variables (n = 1105).

Variables	1	2	3	4	5	6	7
1. Childhood traumatic experiences	1
2. Working memory	.42^**	1
3. Inhibition	.29^**	.64^**	1
4. Emotional eating	.33^**	.55^**	.45^**	1
5. Depression	.10^**	.03	.04	.05	1
6. Anxiety	.07^**	.02	.06^*	.04	.75^**	1
7. Stress	.06^**	.05	.07^*	.07^*	.81^**	.80^**	1
M	68.57	25.13	13.91	34.57	9.12	6.95	9.75
SD	15.87	7.85	3.99	12.58	6.28	5.22	5.96

Note. ^*p < .05, ^**p < .01.

Mediation Analysis

Here, we investigated the mediating roles of working memory and inhibition in the relationship between ACEs and emotional eating (See Figure 2). In addition, we added other traumatic experiences, depression, anxiety, and stress as covariates.

The results showed a significant positive relationship between ACEs, working memory (B = 0.208, SE = 0.013, p < .001, 95% CI (0.173, 0.242)), and inhibition (B = 0.070, SE = 0.008, p < .001, 95% CI (0.050, 0.090)). In addition, both working memory (B = 0.635, SE = 0.056, p < .001, 95% CI (0.495, 0.782)) and inhibition (B = 0.512, SE = 0.056, p < .001, 95% CI (0.230, 0.792)) had a significantly positive relationship with emotional eating. Moreover, ACEs’ direct effect on emotional eating was significant and positive (B = 0.090, SE = 0.022, p < .001, 95% CI (0.034, 0.148)). Finally, ACEs’ total effect on emotional eating was also significant and positive (B = 0.258, SE = 0.023, p < .001, 95% CI (0.258, 0.413)).

As covariates, other traumatic experiences did not have a significant relationship with working memory and inhibition. Similarly, depression, anxiety, and stress did not have a significant relationship with ACEs, emotional eating, working memory, and inhibition.

Bootstrap results for the indirect effects are presented in Table 3. The total indirect effect was significant and positive (B = 0.168, SE = 0.014, p < .001, 95% CI (0.132, 0.208)). Specifically, the indirect effect of ACEs on emotional eating through working memory was significant and positive (B = 0.132, SE = 0.014, p < .001, 95% CI (0.097, 0.171)). Similarly, the indirect effect through inhibition was also significant and positive (B = 0.036, SE = 0.008, p < .001, 95% CI (0.016, 0.060)).

Table 3.

Bootstrap Results of the Indirect Effects.

Variables	Standardized Estimate	Standardized Error	p	Confidence Intervals
Variables	Standardized Estimate	Standardized Error	p	LL	UL
1.CTQ → WM	0.208	0.013	0.000	0.173	0.242
2. CTQ → IHB	0.070	0.008	0.000	0.050	0.090
3.WM → EE	0.635	0.056	0.000	0.495	0.782
4.IHB → EE	0.512	0.108	0.000	0.230	0.792
5.Total effect	0.258	0.023	0.000	0.198	0.319
6.Direct effect	0.090	0.022	0.000	0.034	0.148
7.Total indirect effect	0.168	0.014	0.000	0.132	0.208
5. CTQ → WM → EE	0.132	0.014	0.000	0.128	0.220
6. CTQ → IHB → EE	0.036	0.008	0.000	0.021	0.079

Note. CTQ: Childhood Trauma Questionnaire Total score; WM: Working Memory dimension of the Inventory of Adult Executive Functioning; IHB: Inhibition dimension of the Inventory of Adult Executive Functions; EE: Dutch Eating Behaviours Scale Emotional Eating dimension; LL: Lower limit; UL: Upper limit; Bootstrap sample size = 10000.

Discussion

In the current study, we investigated the mediating role of working memory and inhibition between ACEs and emotional eating while controlling for the effects of other traumatic events and mental health problems such as depression, anxiety, and stress. The relationship between ACEs and emotional eating behavior in adulthood has frequently been documented in the literature (Deprince et al., 2009; Lund et al., 2022). However, the mechanisms underlying this association remain unclear. Therefore, we tested two variables that may potentially mediate between these two variables, consistent with the current literature (Augusti & Melinder, 2013; Mothes et al., 2015). Additionally, we controlled for other traumatic experiences and psychopathologies, given their known associations with emotional eating behavior (Bilici et al., 2020; Kuijer & Boyce, 2012; Talbot et al., 2013).

Consistent with prior research, our findings showed that ACEs are related to working memory and inhibition (e.g., Cowell et al., 2015; Gould et al., 2012; Kaczmarczyk et al., 2018). A developmental perspective might suggest that these results are related to ACEs’ effects on self-regulatory systems (Narvaez et al., 2012). These traumatic experiences modulate tolerance to distressing emotional states, increase stress, and possibly affect the sense of control (Mullen et al., 1994). Exposure to chronic stress in early life may also interfere with neurodevelopment, which could affect the brain’s structure and function in the long term. Studies have indicated that extended stress is linked to deficiencies in EFs resulting from changes in brain neural connections in the frontal areas (De Bellis et al., 1999). For example, research has suggested that people who experienced chronic stress or maltreatment in their early years exhibit changes in brain neural structure and connectivity, particularly in the dorsolateral prefrontal cortex (Philip et al., 2014), the medial prefrontal cortex (Van Harmelen et al., 2010), and the anterior cingulate cortex (Klaming et al., 2019). These alterations include reductions in gray matter volume in the prefrontal cortex and overall cortical volume (Carrion et al., 2010; Van Harmelen et al., 2010). Furthermore, these changes appear to persist independently of psychopathological factors (Philip et al., 2014). Moreover, dysregulation of the HPA axis due to ACEs also impacts forebrain areas crucial for EFs (Kalmakis et al., 2015).

Our findings also showed that deficits in working memory and inhibition are potentially influential factors in the development of emotional eating behaviors (for a review, see Alexis et al., 2023), with inhibition and working memory being positively related to such behavior. For instance, individuals may struggle to regulate their food intake effectively if they have working memory deficits, which increase their vulnerability to emotional eating (Dohle et al., 2018). Similarly, deficits in inhibitory control have been linked to difficulties in resisting cravings and emotional triggers, thereby predisposing individuals to engage in maladaptive eating behaviors (Nederkoorn et al., 2006). Moreover, emerging research indicates that working memory and inhibition contribute to the reduction of high-calorie and unhealthy eating behaviors commonly linked with emotional eating while promoting healthier dietary choices (Allom & Mullan, 2014). For instance, according to Whitelock et al. (2018), higher working memory capacity leads to increased fruit/vegetable consumption.

This study’s final finding is that inhibition and working memory have mediating roles in the relationship between ACEs and emotional eating. This study extends previous research by describing the key cognitive mechanisms (specifically inhibition and working memory) underlying this association. Previous research has shown that ACEs are associated with heightened impulsivity and reduced inhibitory control, likely due to structural and functional changes in the prefrontal cortex (Pechtel & Pizzagalli, 2011). Impaired inhibition may predispose individuals to emotional eating by diminishing their ability to resist urges triggered by emotional distress, especially in environments where high-calorie foods are readily available (Allom & Mullan, 2014). Moreover, poor inhibitory control may impair an individual’s ability to resist emotionally driven eating urges, as evidenced in studies linking deficits in inhibition to impulsive eating behaviors (Lavagnino et al., 2016). Working memory, which facilitates goal-directed behavior and the regulation of emotions, is often compromised in individuals exposed to chronic stress or trauma (Shields et al., 2016). Similarly, deficits in working memory may exacerbate emotional eating behaviors by limiting an individual’s ability to maintain and process goal-relevant information while under stress. Chronic stress, often experienced by individuals with ACEs, has been shown to impair working memory by altering HPA axis functioning and reducing neural efficiency in the prefrontal cortex (Shields et al., 2016). This diminished capacity to regulate cognitive and emotional responses can lead to a reliance on immediate, maladaptive coping strategies, such as overeating, to manage distress.

Limitations and Future Directions

Although this study contributes to the existing literature and clinical interventions, it is essential to consider several limitations when interpreting the results. Although prior research (e.g., Johnco et al., 2014; Kamradt et al., 2014; Mitchell & Miller, 2008) supports the effectiveness of self-report measures in capturing aspects of EFs, we should acknowledge the potential for response bias or social desirability to influence our findings’ interpretation. In addition, studies showing that performance and self-report methods measure different concepts should be addressed (e.g., Toplak et al., 2013). The two main approaches to assessing EFs—self-report questionnaires and performance-based tasks—show weak correlations, suggesting they assess different EF constructs (Nordvall et al., 2017; Ten Eycke & Dewey, 2016; Toplak et al., 2013). Self-report questionnaires may better capture the practical application of EF in real-life contexts, while performance-based tasks focus on technical effectiveness (Barkley & Murphy, 2010; Gerst et al., 2017). Research highlights significant differences between the two methods, with self-reports better predicting functional outcomes and performance-based tasks more reliably predicting academic achievements like math skills (Dekker et al., 2017; Gerst et al., 2017). However, both approaches have limitations: self-reports may reflect biases and general behavioral traits, while performance-based tasks lack ecological validity, as they are conducted in controlled lab settings (McAuley et al., 2010). Overall, the evidence suggests these methods measure distinct aspects of EFs, emphasizing the need for further investigation and caution in treating them as assessments of the same construct (Barkley & Fischer, 2011; Haugen et al., 2021; Meltzer et al., 2017; van Aken et al., 2023).

Although the Childhood Trauma Questionnaire demonstrated temporal consistency among adults (Goltermann et al., 2023), evidence suggests that individuals may underestimate their ACEs (MacDonald et al., 2016). Furthermore, research has also indicated inconsistencies in retrospective reporting of ACEs (Baldwin et al., 2019). In future investigations, face-to-face interviews may offer greater insight into childhood experiences. This study focused on a nonclinical sample. Therefore, our findings might not extend to individuals diagnosed with eating disorders. In future studies, the use of a sample diagnosed with eating disorders is recommended. Another limitation is the inadequate representation of male participants in the current study sample. Consequently, the effect of gender remains unclear due to the sample’s lack of variety. Future studies should employ more heterogeneous participant samples to investigate potential gender-related influences.

Finally, the study’s structure limits the analysis of the findings on causal links. Due to its cross-sectional design, it is impossible to determine the direction of the relationships or the causal effect. Future research may use longitudinal methodologies to detect causal relationships between variables.

Conclusion

As far as we know, this is the first study to assess the association between working memory, inhibition, ACEs, and emotional eating. The findings indicate that stress resulting from ACEs impairs EFs and thus impacts an individual’s eating tendencies, particularly emotional eating behaviors. Identifying and improving these functions at an early stage may also serve to prevent the development of mental health problems in adulthood among individuals who have undergone ACEs or exhibit emotional eating behaviors. Further research analyzing this mediating role should also prioritize the development of EF-based interventions, and clinicians should consider incorporating EF-focused assessments and interventions when addressing emotional eating problems, particularly in patients with ACEs. Existing EF-targeted strategies, such as cognitive training programs designed to enhance working memory and inhibitory control, including computerized or game-based interventions, have already shown promise in improving impulse control and emotion regulation (Diamond & Ling, 2016; Klingberg, 2010). Similarly, cognitive-behavioral therapy (CBT) can be adapted to strengthen self-regulation and gratification-delay skills (Goldschmidt et al., 2018). Mindfulness-based interventions, such as mindfulness-based stress reduction (MBSR), are also effective in improving EFs, reducing emotional reactivity, and decreasing emotional eating behaviors (Keng et al., 2011; Roberts & Danoff-Burg, 2010). Screening for EF deficits in individuals with ACE histories or emotional eating tendencies could help identify those who would benefit from early, targeted interventions, including trauma-informed care approaches that foster resilience and adaptive coping strategies. Theoretically, these findings support integrated models of stress, cognition, and behavior, emphasizing the mediating role of cognitive processes in the link between early adversity and maladaptive behaviors (Anda et al., 2006). Clinically, interventions to enhance EF, such as inhibitory control training and working memory tasks, may disrupt the pathway from ACEs to emotional eating, reduce impulsivity, and promote healthier eating behaviors (Houben et al., 2011). Future research should explore longitudinal designs to establish causality and evaluate the effectiveness of EF-based interventions in mitigating emotional eating.

Footnotes

Acknowledgements

We would like to express our sincere appreciation to all the participants who generously shared their time and provided valuable insights for this study.

Author contributions

Resul Çakır: Data curation; project administration, methodology; writing-original draft; investigation, software; visualization, Writing-review & editing Arzu Gül Topuz: Writing-review & editing; investigation. Emre Han Alpay: Writing-review & editing; conceptualization, supervision

Declaration of Conflicting Interests

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

Funding

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

Ethical Statement

ORCID iD

Resul Cakir

Data Availability Statement

The data of this study will be made publicly available in the Open Science Framework at

Author Biographies

Resul Çakır, Ph.D. Candidate., is an research assistant at the Department of Psychology at Toros University. His research focuses on executive functioning, Learning and Memory, Psychometrics, Cognitive Neuroscience, Clinical Neuropsychology.

Arzu Gül Topuz, Ph.D., is a lecturer at the Department of Psychology at Mersin University. Her research focuses interpersonal relationships, emerging adulthood, forgiveness and existential therapy.

Emre Han Alpay, Ph.D., is an associate professor at the Department of Psychology at Mersin University. His research focuses on negative childhood experiences, trauma, PTSD, and personality disorders.

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