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. 2026 May 8;59(9):2097–2110. doi: 10.1002/eat.70123

Daily Ovarian Hormone Exposure and Loss of Control Eating in Adolescent Girls: A Stage 2 Registered Report

Tyler B Mason 1,2,✉, Jeremy C Morales 1, Kathryn E Smith 1,3, Genevieve F Dunton 1,4, Raina D Pang 1,4
PMCID: PMC13536244  PMID: 42101262

ABSTRACT

Objective

This Stage 2 Registered Report examined (1) the main effects and interaction of within‐person daily associations between ovarian hormones (i.e., estrogen, progesterone) and loss of control eating (LOCE), and (2) the within‐person mediating roles of food‐related reward anticipation and response inhibition.

Methods

Adolescent girls (n = 43) with regular menstrual cycles completed a baseline session followed by 35 days of ecological momentary assessment (multiple times per day), go/no‐go tasks measuring response inhibition (daily), and saliva samples for hormone analyses (daily).

Results

There was a significant interaction between within‐subjects estrogen and progesterone in relation to daily LOCE. Days when estrogen and progesterone were opposing (i.e., high estrogen, low progesterone and low estrogen, high progesterone) were associated with greater LOCE compared to days when both estrogen and progesterone were either high or low. Within‐subjects, day‐level progesterone level was negatively associated with higher reward anticipation, and greater prompt‐level reward anticipation predicted higher subsequent LOCE at the following prompt; the indirect effect was non‐significant, however. There were no associations of response inhibition with hormones or LOCE.

Discussion

Our findings highlight daily associations between ovarian hormones and LOCE among adolescent girls. Opposing levels of estrogen and progesterone heightened risk for LOCE. In addition, lower progesterone may increase food‐related reward anticipation and in turn LOCE. Overall, this study advances momentary models of LOCE in adolescent girls by highlighting hormones and reward anticipation as maintenance processes for real‐world LOCE.

Keywords: adolescents, binge eating, ecological momentary assessment, loss of control, ovarian hormones

Summary

  • Daily estrogen and progesterone exposure interact to predict loss of control eating in adolescent girls.

  • Reward anticipation is a possible momentary mechanism linking daily progesterone exposure and loss of control eating.

1. Introduction

Binge‐spectrum eating disorders (BSEDs) are eating disorders characterized by recurrent binge‐eating episodes (e.g., binge‐eating disorder, bulimia nervosa) and are significant public health problems associated with increased mortality and psychiatric morbidity (Mason and Smith 2022; Smink et al. 2012). As BSEDs typically have poor treatment outcomes (Linardon 2018; Linardon and Wade 2018), prevention is a key priority for BSEDs research, especially girls (Culbert et al. 2021). Disordered‐eating symptoms may help identify early indicators of BSEDs. Loss of control eating (LOCE) is a disordered‐eating symptom that involves a subjective sense of feeling like one cannot stop eating and predicts risk for full threshold BSEDs (Tanofsky‐Kraff et al. 2008, 2020). LOCE typically emerges during adolescence (Stice et al. 1998) and is considered an early manifestation of BSEDs. Thus, LOCE should be studied in the context of the unique brain and hormonal changes characteristic of the period when these behaviors often onset.

Adolescence is a developmental period in which there is new and increasing autonomy for eating behaviors (Mason et al. 2020; Ziegler et al. 2026); dramatic changes in brain and hormone functioning that exclusively occur during this timeframe (Blakemore and Choudhury 2006; Sisk and Zehr 2005); and increased sensitivity to rewards (Galván 2013). Ovarian hormones (e.g., progesterone, estrogen) are putative risk factors for BSEDs and disordered eating (Klump et al. 2017; Lester et al. 2003). Daily saliva sampling studies demonstrated that binge and emotional eating increased when both estrogen and progesterone were higher‐than‐usual (Klump, Keel, Burt, et al. 2013; Klump, Keel, Racine, et al. 2013; Klump et al. 2014; Racine et al. 2013). These findings align with cycle‐based research showing postovulatory (i.e., high estrogoen and high progesterone) increases in eating behaviors. Thus, estrogen and progesterone may act in concert to influence dysregulated eating (Culbert et al. 2016). Additionally, it is important to investigate mechanisms connecting daily estrogen and progesterone exposure and LOCE in adolescent girls.

Estrogen and progesterone are thought to influence response inhibition (i.e., the ability to suppress or interrupt automatic responses) through interactions with dopaminergic modulation of prefrontal regions, which are important for self‐control (Amin et al. 2006). Many of the studies focused on the influence of estrogen and progesterone on response inhibition have utilized a phase‐based approach (i.e., the comparison of different menstrual cycle phases/subphases as a proxy for ovarian hormone levels) and have produced mixed findings (see Le et al. 2020). Given that estrogen and progesterone vary between phases, it is possible that phase‐based research may not adequately capture potential estrogen by progesterone interactions. Additionally, research has typically studied associations of ovarian hormones and general response inhibition as opposed to food‐specific response inhibition, which is particularly salient to LOCE (Smith et al. 2018).

Estrogen and progesterone may also influence reward processes through the interaction with the dopaminergic system (Ma et al. 2020). One study found lower capacity to wait for reward during the early follicular phase (low estrogen, low progesterone) compared to late follicular phase (high estrogen, low progesterone; Diekhof 2015). This prior work is limited by a focus on the follicular phase of the menstrual cycle, which is characterized by low progesterone and is not suited for studying estrogen and progesterone interactions. This is an important gap as it is theorized that progesterone may exert an inhibitory effect on estrogen and on eating behavior (Ma et al. 2020). Given positive associations between food‐related reward anticipation (i.e., a person's “wanting” [or craving] for food) with greater LOCE (Davis et al. 2009; Finlayson and Dalton 2012; Seymour et al. 2015), daily estrogen and progesterone levels may lead to higher food‐related reward anticipation, which in turn increases the likelihood of LOCE.

Research on estrogen and progesterone, food‐related response inhibition, and reward anticipation, particularly in adolescent girls, has historically relied on laboratory‐based assessments, which precludes understanding of relationships with LOCE in a free‐living environment. There are compelling data indicating that estrogen and progesterone, response inhibition, and reward are not static and vary considerably from day to day (Fehring et al. 2006; Powell et al. 2017; Smith et al. 2020). Problems of lab‐based measures of hormones are amplified in adolescent girls as cycle variability is often greater during the first years following menarche (Shirtcliff et al. 2009). Altogether, these issues necessitate examination of relationships between these variables at the within‐person level.

This study reports the results of our Stage 1 registered report (Pang et al. 2023). The first aim of this study was to characterize the within‐person day‐level associations of hormones with LOCE severity. We hypothesized an estrogen × progesterone interaction on LOCE severity. Based on prior research demonstrating post‐ovulatory phase and higher than usual estrogen and higher than usual progesterone associate with increased binge eating (Klump, Keel, Burt, et al. 2013; Klump, Keel, Racine, et al. 2013; Klump et al. 2014; Klump and Di Dio 2022; Racine et al. 2013), we hypothesized that LOCE would be greater on days when estrogen and progesterone are both higher than usual. The second aim was to examine food‐related response inhibition and reward anticipation as mediators of ovarian hormone associations with LOCE severity (see Figure S1). We hypothesized that girls would have lower food‐related response inhibition and higher reward anticipation on days when estrogen and progesterone are both higher than usual, which in turn would be associated with LOCE severity.

2. Method

2.1. Participants

Adolescent girls were recruited through the University of Southern California patient data warehouses and social media advertising in Los Angeles County (see Pang et al. 2023 for power analyses). For the patient data warehouse, flyers were sent to emails of patients aged 18 and parents of 14–17‐year‐old patients. For social media advertising, flyers were directed toward female individuals aged 18 or adults aged 35–54. Flyers included several different messages, including “do(es) you/your child struggle with eating?” and “Is it hard for you/them to stop eating?” The inclusion criteria were: (1) 14–18 years old; (2) at least 1‐year post menarche; (3) current regular menstrual cycle lasting 24–35 days; (4) ≥ 2 LOCE episodes in the past month at baseline; (5) read and speak English; and (6) have a smart device compatible with the study apps and willing to download and use the study apps on their smart device. The exclusion criteria were: (1) diagnosis of anorexia nervosa or atypical anorexia nervosa; (2) recent changes in eating disorder treatment or psychiatric medications in the past 4 weeks; (3) enrolled in special education programs; (4) pregnancy or breastfeeding in the past 6 months (including currently); (5) past three‐month use of birth control except for barrier and fertility awareness methods; and (6) having a condition that impacts menstrual cycle function (e.g., polycystic ovary syndrome). Exclusions were chosen to reduce factors that have strong impacts on hormones as well as recent changes in eating.

2.2. Procedure

Following a brief screening, potentially eligible participants were scheduled for a baseline session. At the visit, adolescents < 18‐years‐old and their parent completed informed consent; adolescents ≥ 18‐years‐old completed informed consent only. Next, baseline measures were completed, and instructions for completing 35‐days of ecological momentary assessment (EMA) surveys and collecting saliva samples upon awakening were given.

2.2.1. Estradiol and Progesterone Testing

Saliva samples were stored in participants' freezers and returned following study completion. Upon return, samples were inspected for thawing and stored at −20°C. Samples that were determined to be unusable for quality reasons (i.e., arrived thawed, significant missing data) were not analyzed. Samples were packed using dry ice and insulation materials in a Styrofoam insulated cooler and delivered to Salimetrics. All samples were confirmed as being frozen upon receipt at Salimetrics.

At Salimetrics, samples were thawed to room temperature, vortexed, and then centrifuged for 15 min at approximately 3500 RPM (1500 × g) immediately before performing the assay. Samples were tested for salivary estradiol (Cat. No. 1‐3702) and progesterone (Cat. No. 1‐1502) using a high sensitivity enzyme immunoassay according to the manufacturers' protocol. Salivary estradiol sample test volume was 100 μL of saliva per determination. The estradiol assay has a lower limit of sensitivity of 0.1 pg/mL, a standard curve range from 1 to 32 pg/mL, an average intra‐assay coefficient of variation of 7.13%, and an average inter‐assay coefficient of variation of 7.45%. Salivary progesterone test volume was 50 μL of saliva per determination. The progesterone assay has a lower limit of sensitivity of 5 pg/mL, a standard curve range from 10 to 2430 pg/mL, an average intra‐assay coefficient of variation of 6.20%, and an average inter‐assay coefficient of variation of 7.55%. These values meet the manufacturers' criteria for accuracy and repeatability in Salivary Bioscience and exceed the applicable NIH guidelines for Enhancing Reproducibility through Rigor and Transparency.

To diminish the influence of hormone‐release pulsatility and smooth the pattern of hormone variability, we calculated 5‐day rolling averages (minimum of 3 days of data for each average) for estradiol and progesterone (Klump, Keel, Burt, et al. 2013; Klump, Keel, Racine, et al. 2013). Raw and rolling hormone levels of estradiol and progesterone were centered to within‐person and between‐person levels.

2.2.2. EMA Protocol

Pang et al. (2023) describes the full EMA protocol and measures. In brief, participants received 4 semi‐randomly prompted EMA surveys during non‐school time on weekdays (morning wake‐up time [open until 12 p.m.]; 3:30 p.m.–9:30 p.m.) and 6 surveys on weekend days (morning wake‐up time; 9 a.m.–10 p.m.). Prompts were open for 45 min and up to four reminder prompts were sent. About twice a week, study staff communicated with participants regarding their compliance and to address issues.

3. Measures

3.1. Baseline Measures

3.1.1. Anthropometric Assessments

Height and weight were measured in duplicate using an electronically calibrated digital scale and professional stadiometer. Body mass index (BMI; kg/m2) and Centers for Disease Control age and gender‐specific BMI z‐scores (BMI‐z) were determined using age‐based pediatric growth reference charts (Shypailo 2020).

3.1.2. BSEDs Symptom Interview

Several modules of the Eating Disorder Examination (EDE; Fairburn et al. 2008) assessed past‐28 day eating disorder symptoms (including LOCE) and provided diagnostic information for BSEDs. The “Bulimic Episodes or Other Episodes of Overeating” module was used to assess eligibility criteria, with individuals reporting at least two combined objective or subjective binge‐eating episodes qualifying for the study. The diagnostic EDE items were also used for DSM‐5 ED diagnoses and exclusion of AN. The EDE was administered by a licensed clinical psychologist with EDE training. During the interview, adolescents received training on the definition of LOCE.

3.1.3. Baseline Menstrual Cycle

Participants completed an author‐constructed assessment of the menstrual cycle including the date of the last menstrual onset (Pang et al. 2018), which was used in menstrual cycle calculation (described in EMA measures).

3.1.4. Baseline Covariates

Girls completed measures of demographics, menstrual history, depressive symptoms (Revised Children's Anxiety and Depression Scale; Chorpita et al. 2000), sleep quality (Pittsburgh Sleep Quality Index; Monk et al. 1994), and attention‐deficit/hyperactivity disorder (ADHD; Current Symptoms Scale; Barkley and Murphy 2006). Depression, ADHD, and sleep dysfunction can impact sex hormones (Morssinkhof et al. 2020; Osianlis et al. 2025) and so were considered as time‐invariant covariates in analyses.

3.2. EMA Measures

3.2.1. Food‐Related Response Inhibition

Daily food‐related response inhibition was assessed by a Go/No‐go task adapted for mobile devices via the Inquist 6.0 application. The task was prompted each day at 3:30 p.m., given that the risk for binge eating increases toward the evening (Smith et al. 2020). In this task, a neutral non‐food or palatable food image was presented in a randomized order on the screen for 500 ms, followed by a fixation cross. For Go trials, participants were instructed to respond as fast as possible to categorize the images that have either a red border or a blue border; participants were instructed to hold the phone horizontally with both hands and use their thumbs to respond to on‐screen stimuli. Participants responded using a colored button (red or blue) displayed on the left or right side of the screen. During No‐go trials, a green dot above the image signaled to participants to inhibit responses to stimuli. To establish prepotent responding, a 4:1 Go to No‐go trial ratio was used. Each task administration includes 100 trials. The outcome measures were the number of food‐related and neutral commission errors during the task (i.e., failure to inhibit a response in the presence of food or neutral images), with greater commission errors reflecting poorer response inhibition.

3.2.2. Food Reward Anticipation

At each prompt, girls were asked about their degree of food wanting as well as craving (Alabduljader et al. 2018; Goldschmidt et al. 2022). A mean score was taken of both items to represent food reward anticipation.

3.2.3. LOCE

At each prompt, girls indicated if they ate anything in the past 2 h. If they did eat, four items assessed the degree of LOCE: While you were eating, (1) did you feel a sense of loss of control; (2) did you feel that you could not stop eating once you had started; (3) did you feel like you could not resist eating; and (4) did you feel like a car without brakes, you just kept eating and eating. Each item was rated on a scale from 1 (no, not at all) to 5 (yes, extremely). Items were averaged to create a composite score at each eating episode, with higher scores indicating greater LOCE severity. This measure has shown adequate psychometric properties in previous adolescent research (Goldschmidt et al. 2022; Luo et al. 2025). There was good reliability at both levels, demonstrated by within‐ and between‐subject omegas of 0.92 and 0.99, respectively.

3.2.4. Menstrual Cycle

At the morning prompt, girls self‐reported on menstrual bleeding, which identified menstrual onset(s). Menstrual onsets (baseline, EMA) created “bookends” such that menstrual cycle day was a forward count from menstrual onset (menstrual onset = 1) and reverse cycle day was a backward count from menstrual onset (day before menstrual onset = −1). A combination of forward and backward count was used to calculate menstrual cycle day (Schmalenberger et al. 2021). We then assigned days to recommended menstrual cycle phase (Schmalenberger et al. 2021): periovulatory (reverse cycle days −15 to −12), midluteal (reverse cycle days −9 to −5), perimenstrual (reverse cycle day −3 to menstrual cycle day 2), mid‐follicular (menstrual cycle days 4 through 7).

3.2.5. Negative Affect

At every prompt, girls were asked about their current negative affect using 11 items (i.e., guilty, scared, bored, hostile, irritable, distressed, upset, shame, nervous, afraid, jittery). All items were averaged to create a composite score, with higher scores indicating greater negative affect. Negative affect items were previously used in EMA eating behavior research in adolescents (Goldschmidt et al. 2022). The within‐ and between‐subject omegas were 0.85 and 0.97, indicating good reliability at both levels.

3.3. Statistical Analyses

Descriptive statistics were examined for all demographics, food‐related and neutral commission errors, and EMA measures. General linear mixed models were conducted to test whether (1) estrogen and progesterone levels differed between phases, and (2) associations of within‐subject estrogen levels with within‐subject progesterone levels. In addition, correlates of EMA compliance were examined. Univariable multilevel models were run to examine associations of possible baseline covariates (i.e., age, menarche onset, race, BMI‐z, depressive symptoms, sleep, and ADHD symptoms) with LOCE; covariates were included in analyses if related to LOCE at p = 0.05. For Aim 2, momentary negative affect was included as a planned covariate.

All hypotheses were tested in multilevel or multilevel structural equation models (observations nested within days nested within girls) with SPSS and Mplus. Estrogen and progesterone values were disaggregated into within‐ and between‐subjects effects. Model fit indices (2 Log Likelihood [LL]) and intraclass correlation coefficients dictated the inclusion/exclusion of random slopes, yet random slopes were only examined for the main effect of within‐subjects progesterone and estrogen, given the modest person‐level sample size. Analyses for both aims were run using within‐person 5‐day rolling averages of estrogen and progesterone and raw values of estrogen and progesterone.

Aim 1 was tested with a two‐level multilevel model (i.e., days nested within persons). We first investigated whether phase independently was associated with outcomes using multilevel models with phase as the primary predictor and controlling for significant covariates. Then, we examined associations of today's estrogen and progesterone (within), and the interactions of estrogen and progesterone (within) predicting day‐level LOCE. Aim 2 was tested with three‐level multilevel moderated‐mediation structural equation models with Bayesian estimation, which allow for modeling both within‐ and between‐subject associations between variables across three levels (i.e., prompt, day, and person; Bauer et al. 2006). For each effect, significance was evaluated using credibility intervals, with significance defined as a credibility interval that excludes zero. Credibility intervals provide a probability statement about the parameter and are interpreted as the probability that the true estimate is within the interval given the observed data; a 95% credibility interval means there is a 95% probability that the true parameter value is within the interval range (Hespanhol et al. 2019).

Conditional indirect effects were tested if there were significant direct effects, and mediation was supported when the credibility interval does not include zero. Random effects were not examined as Mplus did not allow for three‐level models with random slopes when missing values are present; random slopes were not the primary interest for the mediation models.

4. Results

4.1. Sample Characteristics

There were 49 girls that met criteria and enrolled in the study, with 43 completing all procedures and included in analyses (see Figure 1 for participant flow diagram). The demographic and clinical characteristics of the sample are displayed in Table 1. The sample was generally older adolescents (M age = 17.44 ± 0.96 years). Girls were diverse regarding sexual and gender identity, weight status, and racial‐ethnic identity. According to the clinical interview, all girls met criteria for an eating disorder (see Table 1 for specific diagnoses). The mean number of objective binge‐eating episodes in the past month was 5.93 ± 5.94 (Range: 0–24), and the mean number of subjective binge‐eating episodes in the past month was 2.49 ± 4.68 (Range: 0–20). Demographic and clinical characteristics were unrelated to study completion (ps > 0.05).

FIGURE 1.

FIGURE 1

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Participant flow diagram.

TABLE 1.

Descriptive statistics for demographics (N = 43).

Characteristic M (SD) or n (%) Range
Age 17.44 (0.86) 15–18
Age of menarche 11.86 (1.30) 9–14
Years since menarche 5.62 (1.38) 2–8
BMI‐z 0.99 (0.95) −1.22 to 2.37
Gender identity
Female 42 (97.7)
I do not identify as either male or female 1 (2.3)
Sexual identity
Straight, not gay 27 (62.8)
Gay or lesbian 1 (2.3)
Bisexual 11 (25.6)
I am not sure yet 3 (7.0)
Something else 12 (2.3)
Hispanic, Latino/a or Spanish origin
Yes 21 (51.2)
No 22 (48.8)
Race/Ethnicity (select all that apply) a
Asian 12 (27.9)
Black or African American 5 (11.6)
White 15 (34.9)
Middle Eastern 1 (2.3)
Other 12 (27.9)
Grade
High school 17 (39.5)
College 23 (53.5)
Not in school 3 (7.0)
Free or reduced lunch program (high schoolers only)
Yes 13 (76.5)
No 4 (23.5)
DSM‐5 feeding and eating disorder diagnosis
Binge‐eating disorder (BED) 15 (34.9)
Bulima nervosa (BN) 9 (20.9)
Other specified feeding and eating disorder (OSFED)—BED 2 (4.7)
OSFED—BN 5 (11.6)
Unspecified feeding and eating disorder (UFED) 12 (27.9)
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a

Response options also included “American Indian or Alaskan Native” and “Native Hawaiian or Other Pacific Islander” but these were not selected by any participants.

4.2. Salivary Hormone Data Processing and Descriptives

On average, participants had 30.98 (SD = 5.33) estradiol and 30.74 (SD = 5.51) progesterone samples. A total of 1343 samples from 43 participants were sent to Salimetrics for estradiol and progesterone testing. Eleven (0.82%) samples were unable to calculate an estradiol mean value (e.g., not enough saliva, below assay sensitivity threshold). Twenty‐one (1.56%) samples were unable to calculate a progesterone mean value (e.g., not enough saliva, below assay sensitivity threshold). As expected, progesterone and estrogen levels significantly differed across phase (see S1 for detailed analyses).

4.3. EMA and Task Data Processing and Descriptives

The average number of EMA prompts completed per person was 127.14 (SD = 26.85; Range: 55–156) and the mean EMA compliance was 80.09% (SD = 15.81; Range: 34.38%–97.50%). There were 2154 prompts in which eating was recorded (39.7% of total prompts). EMA compliance was unrelated to age (r = −0.08, p = 0.52), BMI‐z (r = −0.02, p = 0.89), sex at birth (t = −0.21, p = 0.83), sexual identity (t = 0.62, p = 0.54), free/reduced lunch program status (t = 0.58, p = 0.57), Hispanicity (t = 1.01, p = 0.16), and race (F = 1.78, p = 0.16). Adolescents showed low‐to‐moderate levels of LOCE (M = 2.19, SD = 1.22; Range: 1–5), with 27.6% of prompts with LOCE scores ≥ 3. The intraclass correlation coefficient (ICC) for LOCE was 0.38, suggesting greater within‐subjects variance. In a univariable multilevel model, ADHD symptoms predicted LOCE ratings (Estimate = 0.37, p = 0.002). Age, ethnicity, BMI‐z, menarche, sleep quality, and depressive symptoms were not significantly related to LOCE rating in univariable multilevel models (Estimate p‐values > 0.05). There were eight instances in which participants completed the response inhibition task twice in one day, and only the first completion was retained. Out of 35 possible tasks, the mean number of tasks completed was 20.61 (SD = 7.92; Range: 8–35). The number of completed tasks was unrelated to demographic and clinical characteristics.

4.4. Aim 1 Analyses: Within‐Person Day‐Level Associations of Hormones With LOCE Severity

Compared to the mid‐follicular phase, daily LOCE was significantly higher in the periovulatory (B = 0.27, p < 0.001) and midluteal phases (B = 0.26, p < 0.001); there was no difference in the perimenstrual phase compared to the mid‐follicular phase (B = 0.07, p = 0.10). Model fit tests for rolling and raw models indicated variability in the intercept, within‐subjects estrogen slope, and within‐subjects progesterone slope (see Table 2). Therefore, the final models were the mixed effect models, which showed small overall effect sizes (see model estimates in Table 2).

TABLE 2.

Mixed models of daily estrogen and progesterone and daily loss of control eating.

Rolling average Pseudo R 2 Raw Values Pseudo R 2
Estimate SE p Estimate SE p
Effect estimates
Intercept 1.58 0.29 < 0.001 0.14 1.59 0.29 < 0.001 0.13
ADHD symptoms 0.69 0.25 0.01 0.66 0.25 0.01
BS estrogen 0.54 0.32 0.10 0.52 0.32 0.11
BS progesterone < 0.001 0.001 0.91 < 0.001 0.001 0.96
WS estrogen 0.01 0.03 0.71 0.03 0.03 0.25
WS progesterone −0.02 0.03 0.65 −0.07 0.03 0.04
BS estrogen × BS progesterone −0.002 0.002 0.32 −0.002 0.002 0.28
WS estrogen × WS progesterone −0.06 0.02 < 0.001 0.02 0.01 0.08
Variance components
Intercept 0.44 0.10 0.43 0.10
WS estrogen 0.04 0.01 0.04 0.01
WS progesterone 0.04 0.01 0.02 0.01
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Note: WE compared a model with all fixed effects to a model with within‐subjects progesterone and estrogen as random effects. Comparing models with rolling average estrogen and progesterone, the mixed effects model had a better model fit (2 LL = 10038.48) compared to the fully fixed effect model (2 LL = 10038.48 vs. 10307.21). Similarly, comparing models with raw value estrogen and progesterone, the mixed effects model had a better model fit (2 LL = 10038.48) compared to the fully fixed effect model (2 LL = 10268.64 vs. 10403.99). Covariates included in models were associated with outcomes at p < 0.05 in univariable models.

Abbreviations: ADHD, attention deficit/hyperactivity disorder; BS, between‐subjects; WS, within‐subjects.

Higher ADHD symptoms remained a significant predictor of greater daily LOCE in the multivariable models. In the model using rolling averages, there was a significant interaction between within‐subjects estrogen and within‐subjects progesterone in relation to daily LOCE. Days when estrogen and progesterone were opposing (i.e., high estrogen, low progesterone compared to one's average and low estrogen, high progesterone compared to one's average) were associated with greater LOCE compared to days when both estrogen and progesterone were either higher or lower than one's average (see Figure 2 for interaction plot). In the model using raw values, there was only a significant association between within‐subjects progesterone in relation to daily LOCE. On days when raw progesterone was higher than one's own average, they reported less LOCE.

FIGURE 2.

FIGURE 2

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Interaction of within‐subjects rolling estrogen and progesterone in relation to daily loss of control eating. Low = 1 SD below the mean and High = 1 SD above the mean.

4.5. Aim 2 Analyses: Mediators of Ovarian Hormone Associations With LOCE Severity

4.5.1. Aim 2a: Food‐Related Response Inhibition

Food‐related response inhibition was unrelated to LOCE as well as hormones (see Table 3 for rolling hormone model and Table 4 for raw hormone model). There were also no effects for general response inhibition (see Tables S1 and S2).

TABLE 3.

Three‐level multilevel structural equation model of rolling averaged daily progesterone and estrogen exposure, food‐related response inhibition, and loss of control eating severity.

β Posterior SD 95% C.I. Sig
Level 1—Within (momentary)
Negative affect → Loss of control eating −0.13 0.05 (−0.23, −0.02) *
Level 2—Between (day)
Negative affect → Loss of control eating 0.60 0.09 (0.46, 0.80) *
Response Inhibition → Loss of control eating −0.001 0.21 (−0.39, 0.39)
Progesterone → Response inhibition −0.01 0.01 (−0.02, −0.01)
Estrogen → Response inhibition 0.01 0.01 (−0.002, 0.03)
Progesterone × Estrogen → Response inhibition 0.01 0.01 (−0.004, 0.02)
Level 3—Between (person)
Response inhibition → Loss of control eating −0.29 0.63 (−1.47, 0.79)
Negative affect → Loss of control eating 0.43 0.20 (0.01, 0.85) *
ADHD symptoms → Loss of control eating 0.73 0.29 (0.13, 1.26) *
Progesterone → Response inhibition < 0.001 < 0.001 (−0.001, < 0.001)
Estrogen → Response inhibition −0.05 0.09 (−0.20, 0.12)
Progesterone × Estrogen → Response inhibition < 0.001 0.001 (−0.001, 0.001)
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Note: Progesterone and Estrogen represent rolling averages, and the interaction (i.e., Progesterone × Estrogen) reflects the combined effect of these two variables.

Abbreviation: Sig, Significant.

*

Credibility interval is significant.

TABLE 4.

Three‐level multilevel structural equation model of raw daily progesterone and estrogen exposure, food‐related response inhibition, and loss of control eating severity.

β Posterior SD 95% C.I. Sig
Level 1—Within (momentary)
Negative affect → Loss of control eating −0.10 0.09 (−0.25, −0.07)
Level 2—Between (day)
Negative affect → Loss of control eating 0.57 0.11 (0.34, 0.78) *
Response inhibition → Loss of control eating −0.05 0.16 (−0.34, 0.28)
Progesterone → Response inhibition −0.01 0.01 (−0.02, −0.01)
Estrogen → Response inhibition 0.003 0.01 (−0.01, 0.02)
Progesterone × Estrogen → Response inhibition −0.002 0.01 (−0.01, 0.01]
Level 3—Between (person)
Response inhibition → Loss of control eating −0.26 0.61 (−1.57, 0.83)
Negative affect → Loss of control eating 0.43 0.17 (0.11, 0.73) *
ADHD symptoms → Loss of control eating 0.68 0.29 (0.13, 1.26) *
Progesterone → Response inhibition < 0.001 < 0.001 (−0.001, < 0.001)
Estrogen → Response inhibition −0.01 0.10 (−0.19, 0.18)
Progesterone × Estrogen → Response inhibition < 0.001 < 0.001 (−0.001, 0.001)
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Note: Progesterone and Estrogen represent raw estimates, and the interaction (i.e., Progesterone × Estrogen) reflects the combined effect of these two variables.

Abbreviation: Sig, Significant.

*

Credibility interval is significant.

4.5.2. Aim 2b: Reward Anticipation

Day‐level rolling progesterone level was negatively associated with higher reward anticipation. However, day‐level rolling estrogen as well as the day‐level rolling progesterone × estrogen interaction were unrelated to reward anticipation. No participant‐level rolling hormone levels were related to reward anticipation. At the prompt‐level, greater reward anticipation than one's average predicted higher subsequent LOCE at the following prompt. Day‐level reward anticipation was unrelated to LOCE. Participant‐level reward anticipation was positively associated with greater LOCE. See Table 5 for model estimates. The results using raw hormone values did not significantly differ from the rolling hormone analyses (results reported in Table 6). The indirect effect of daily progesterone on LOCE through reward anticipation was not significant (Rolling: Estimate = −0.01, Posterior SD = 0.01, p = 0.10; Raw: Estimate = −0.01, Posterior SD = 0.01, p = 0.09).

TABLE 5.

Three‐level multilevel structural equation model of rolling averaged daily progesterone and estrogen exposure, reward anticipation, and loss of control eating severity.

β Posterior SD 95% C.I. Sig
Level 1—Within (momentary)
Reward anticipation → Loss of control eating 0.05 0.01 (0.03, 0.08) *
Negative affect → Loss of control eating −0.11 0.08 (−0.27, 0.04)
Level 2—Between (day)
Reward anticipation → Loss of control eating 0.03 0.09 (−0.10, 0.25)
Negative affect → Loss of control eating 0.61 0.11 (0.38, 0.84) *
Progesterone → Reward anticipation −0.16 0.06 (−0.26, −0.05) *
Estrogen → Reward anticipation −0.01 0.05 (−0.12, 0.10)
Progesterone × Estrogen → Reward anticipation −0.05 0.07 (−0.18, 0.08)
Level 3—Between (person)
Reward anticipation → Loss of control eating 0.32 0.08 (0.15, 0.48) *
Negative affect → Loss of control eating 0.15 0.16 (−0.16, 0.46)
ADHD symptoms → Loss of control eating 0.40 0.21 (−0.01, 0.87)
Progesterone → Reward anticipation −0.003 0.003 (−0.01, 0.003)
Estrogen → Reward anticipation 0.90 0.68 (−0.42, 2.19)
Progesterone × Estrogen → Reward anticipation −0.001 0.01 (−0.01, 0.01)
Open in a new tab

Note: Progesterone and Estrogen represent rolling averages, and the interaction (i.e., Progesterone × Estrogen) reflects the combined effect of these two variables.

Abbreviation: Sig, Significant.

*

Credibility interval is significant.

TABLE 6.

Three‐level multilevel structural equation model of raw daily progesterone and estrogen exposure, reward anticipation, and loss of control eating severity.

β Posterior SD 95% C.I. Sig
Level 1—Within (momentary)
Reward anticipation → Loss of control eating 0.06 0.01 (0.03, 0.08) *
Negative affect → Loss of control eating −0.06 0.08 (−0.19, 0.12)
Level 2—Between (day)
Reward anticipation → Loss of control eating 0.01 0.05 (−0.10, 0.11)
Negative affect → Loss of control eating 0.57 0.12 (0.36, 0.82) *
Progesterone → Reward anticipation −0.17 0.06 (−0.28, −0.06) *
Estrogen → Reward anticipation 0.01 0.06 (−0.10, 0.11)
Progesterone × Estrogen → Reward anticipation 0.04 0.05 (−0.05, 0.13)
Level 3—Between (person)
Reward anticipation → Loss of control eating 0.30 0.08 (0.14, 0.44) *
Negative affect → Loss of control eating 0.19 0.16 (−0.13, 0.50)
ADHD symptoms → Loss of control eating 0.41 0.22 (−0.03, 0.84)
Progesterone → Reward anticipation −0.002 0.003 (−0.01, 0.003)
Estrogen → Reward anticipation 0.87 0.74 (−0.65, 2.40)
Progesterone × Estrogen → Reward anticipation 0.001 0.005 (−0.01, 0.01)
Open in a new tab

Note: Progesterone and Estrogen represent raw estimates.

Abbreviation: Sig, Significant.

*

Credibility interval is significant.

5. Discussion

This study examined daily hormones and LOCE in adolescent girls as well as potential mechanisms (i.e., food‐related response inhibition and reward). We found that LOCE was higher in the periovulatory and midluteal phase compared to the mid‐follicular phase. This finding is consistent with several other studies demonstrating that emotional eating and binge eating are highest during the midluteal phase (Edler et al. 2007; Handy et al. 2022; Klump, Keel, Racine, et al. 2013; Klump et al. 2014). We found an interaction of within‐person estrogen and progesterone in relation to LOCE with low progesterone and high estrogen associated with the highest LOCE. This is consistent with our menstrual cycle findings showing increased LOCE during the periovulatory phase (i.e., high estrogen, low progesterone). Prior studies with constructs like LOCE have found interactive effects of estrogen and progesterone, with greatest maladaptive eating patterns when both estrogen and progesterone are high (Klump, Keel, Burt, et al. 2013; Klump, Keel, Racine, et al. 2013; Klump et al. 2014). Our differential findings may relate to all participants meeting current criteria for an eating disorder as ovarian hormone and dysregulated eating associations may differ depending on eating disorder status (Edler et al. 2007; Klump et al. 2014). Future studies should continue to investigate ovarian hormone associations with maladaptive eating by eating disorder status. Furthermore, our effect size was small, and the interaction was only found in the rolling average hormone models. Rolling average models reduce the day‐to‐day pulsatility of hormone levels and may reflect overall physiological shifts in ovarian hormone patterns across the menstrual cycle (e.g., luteal phase high progesterone levels). Thus, it is possible that the effects of ovarian hormones on LOCE may be more related to cumulative multi‐day shifts in ovarian hormone patterns across the cycle.

The second aim of this study was to investigate food‐related response inhibition and reward anticipation as mediators of hormone associations with LOCE. In contrast to our hypotheses, we did not find any associations of ovarian hormones, response inhibition, and LOCE. Theories have been developed proposing a role of estrogen (Eng et al. 2024) and progesterone (Barros et al. 2015) in cognitive function. Prior studies have demonstrated that exogenous progesterone administration and use of hormonal contraceptives improve cognitive function (Nobile et al. 2021; Sofuoglu et al. 2011). However, these prior studies did not examine endogenous hormone levels and were not specific to adolescents. It is likely that endogenous and exogenous hormones exert different effects and studies also suggest that effects of hormones on cognitive function changes across the lifespan (Eng et al. 2024; Henderson 2018). In addition, several theoretical and methodological factors may explain the lack of association between response inhibition and LOCE. As found in prior research (Smith et al. 2020), the relationship between response inhibition and LOCE is influenced by contextual moderators (e.g., affect). Further, a separate study assessing response inhibition and snacking multiple times over the day reported a positive association between momentary response inhibition and snacking in adolescents (Powell et al. 2017), suggesting that a once‐a‐day assessment may not be adequate. Furthermore, the timing of the daily response inhibition assessment may be important. Since adolescents varied in completion of the assessment across the afternoon and evening, several factors may have confounded our assessment of response inhibition (e.g., appetite, recent eating behavior).

We found some support that progesterone (rolling and raw hormone analyses) may influence reward anticipation and subsequently LOCE but did not find an effect of estrogen with reward anticipation. Theories tend to posit that estrogen increases reward reactions and progesterone dampens (as a main effect or through modulating estrogen) the reward response (Sakaki and Mather 2012). Our findings in progesterone are consistent with these theoretical models demonstrating progesterone showing an association with reduced reward anticipation. Studies have demonstrated that increasing estrogen in the context of low progesterone heightens reward response (Justice and De Wit 2000a, 2000b; Lile et al. 2007). It is important to note that these studies did not directly test progesterone and focused on phases where progesterone is naturally low, which makes it difficult to directly compare with findings from the current study. A prior EMA study of adults with binge‐eating disorder also found that reward anticipation was a prospective predictor of momentary binge‐eating episodes and symptoms (Schaefer et al. 2023). However, mixed findings have been observed in youth, with one study of community youth with overweight/obesity finding no association of craving with subsequent LOCE ratings (Goldschmidt et al. 2018) and a separate study of community youth varying in weight status finding that craving predicted subsequent LOCE ratings (Parker et al. 2021). Therefore, it appears that reward anticipation may be a maintenance factor for LOCE symptoms among individuals with existing binge‐eating pathology but may not reliably predict LOCE symptoms in at‐risk or community samples.

6. Clinical Implications and Future Directions

LOCE typically emerges during adolescence and is considered an early indicator of risk for future BSEDs (Stice et al. 1998; Tanofsky‐Kraff et al. 2008, 2020). This research is the first known study of mechanisms of daily ovarian hormone exposure and LOCE in adolescent girls. Specifically, we found some evidence for interactive effects of estrogen and progesterone on LOCE, with small effect sizes. There is some evidence that samples with BSEDs may have differential associations between ovarian hormones and maladaptive eating (Edler et al. 2007; Klump et al. 2014), and our study importantly contributes to the growing body of literature investigating these associations in samples of individuals with BSEDs. Emerging theories on endogenous and exogenous (e.g., combined oral contraceptives) ovarian hormones and maladaptive eating suggest a potential role of individual differences to ovarian hormones impact on maladaptive eating (Klump and Di Dio 2022; Klump et al. 2023). While our sample was too small to investigate individual differences, it will be important for future larger studies to investigate how individual differences interact with ovarian hormones in relation to LOCE. This could inform prevention efforts and interventions that target reward, such as regulation of cue training (Boutelle et al. 2022), could be utilized at various phases of the menstrual cycle to enhance efficacy.

6.1. Strengths and Limitations

A primary strength of this study is using EMA combined with daily hormone sampling for 35 days to test a biobehavioral model of LOCE in adolescent girls with clinician‐assessed BSEDs symptoms. Despite this strength, some limitations should be noted. The sample skewed older (i.e., 18‐years‐old). Debate remains in relation to the exact timeframe of maturation of ovarian hormones and cycle variability following menarche (Zhang et al. 2008), but studies indicate cycle regularity and progesterone rise continue to develop for several years post menarche (Legro et al. 2000; Zhang et al. 2008). As our sample was on average over 5 years post menarche, it is likely these findings are reflective of the impact of ovarian hormones in the context of established menstrual cycles and may not generalize to samples in adolescent girls in/close to perimenarche. In addition, autonomy for eating changes over the course of adolescence (Ziegler et al. 2026), which could affect LOCE. Causal inferences are limited, and further experimental work is needed to test causal mechanistic pathways. Eating behavior was assessed only at random prompts, and there is no way to verify if all eating episodes were reported. As such, daily LOCE symptoms could be underestimated. Further, the response inhibition task was only given once a day and not always completed at the same time, which may have confounded effects. Studies have shown that response inhibition fluctuates within a day and that inhibitory control may differ by time of day (Kalanthroff et al. 2025; Li et al. 2020), suggesting the need for more rigorous assessment of real‐world inhibitory control in future studies. Finally, we examined baseline depression, ADHD, and sleep as covariates; however, these variables may differ within‐ and between‐subjects and may function as covariates, moderators, and/or mediators. Future research should clarify the role of depression, ADHD, and sleep in models of hormones and LOCE.

7. Conclusion

These findings highlight daily associations between ovarian hormones and fluctuations in LOCE among adolescent girls. Opposing levels of estrogen and progesterone appear to heighten risk for LOCE, potentially through increased food‐related reward anticipation. Given the small effect size, moderators may be important to understanding contexts and individuals in which hormones may have a stronger effect on LOCE. Overall, this study advances momentary maintenance models of LOCE in adolescent girls by highlighting hormones and reward anticipation as processes that amplify vulnerability to LOCE within a day.

Author Contributions

Jeremy C. Morales: investigation, writing – original draft, writing – review and editing. Tyler B. Mason: conceptualization, investigation, funding acquisition, writing – original draft, methodology, formal analysis, data curation. Genevieve F. Dunton: writing – review and editing. Raina D. Pang: conceptualization, investigation, funding acquisition, writing – original draft, methodology, data curation. Kathryn E. Smith: methodology, writing – review and editing.

Lived Experience Involvement Statement

Outside lived experience that authors may contribute, no specific efforts were undertaken to involve persons with lived experience in the study design or execution, or in the preparation of this manuscript.

Funding

This work was funded by the National Institute of Mental Health (R21MH126334, mPI Mason and Pang).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Three‐level multilevel structural equation model of rolling averaged daily progesterone and estrogen exposure, general response inhibition, and loss of control eating severity.

Table S2: Three‐level multilevel structural equation model of raw daily progesterone and estrogen exposure, general response inhibition, and loss of control eating severity.

Figure S1:. Model of daily estrogen and progesterone exposure and loss of control eating.

EAT-59-2097-s001.docx (66.3KB, docx)

Acknowledgments

No AI tools were used.

Mason, T. B. , Morales J. C., Smith K. E., Dunton G. F., and Pang R. D.. 2026. “Daily Ovarian Hormone Exposure and Loss of Control Eating in Adolescent Girls: A Stage 2 Registered Report.” International Journal of Eating Disorders 59, no. 9: 2097–2110. 10.1002/eat.70123.

Action Editor: Ruth Striegel Weissman

Data Availability Statement

Data is available from the authors by request.

References

  1. Alabduljader, K. , Cliffe M., Sartor F., Papini G., Cox W. M., and Kubis H. P.. 2018. “Ecological Momentary Assessment of Food Perceptions and Eating Behavior Using a Novel Phone Application in Adults With or Without Obesity.” Eating Behaviors 30: 35–41. 10.1016/j.eatbeh.2018.05.007. [DOI] [PubMed] [Google Scholar]
  2. Amin, Z. , Epperson C. N., Constable R. T., and Canli T.. 2006. “Effects of Estrogen Variation on Neural Correlates of Emotional Response Inhibition.” NeuroImage 32, no. 1: 457–464. 10.1016/j.neuroimage.2006.03.013. [DOI] [PubMed] [Google Scholar]
  3. Barkley, R. A. , and Murphy K. R.. 2006. Attention‐Deficit Hyperactivity Disorder: A Clinical Workbook. Guilford Press. [Google Scholar]
  4. Barros, L. A. , Tufik S., and Andersen M. L.. 2015. “The Role of Progesterone in Memory: An Overview of Three Decades.” Neuroscience & Biobehavioral Reviews 49: 193–204. 10.1016/j.neubiorev.2014.11.015. [DOI] [PubMed] [Google Scholar]
  5. Bauer, D. J. , Preacher K. J., and Gil K. M.. 2006. “Conceptualizing and Testing Random Indirect Effects and Moderated Mediation in Multilevel Models: New Procedures and Recommendations.” Psychological Methods 11, no. 2: 142–163. 10.1037/1082-989X.11.2.142. [DOI] [PubMed] [Google Scholar]
  6. Blakemore, S. J. , and Choudhury S.. 2006. “Development of the Adolescent Brain: Implications for Executive Function and Social Cognition.” Journal of Child Psychology and Psychiatry 47: 296–312. 10.1111/j.1469-7610.2006.01611.x. [DOI] [PubMed] [Google Scholar]
  7. Boutelle, K. N. , Eichen D. M., Peterson C. B., et al. 2022. “Effect of a Novel Intervention Targeting Appetitive Traits on Body Mass Index Among Adults With Overweight or Obesity: A Randomized Clinical Trial.” JAMA Network Open 5, no. 5: e2212354. 10.1001/jamanetworkopen.2022.12354. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chorpita, B. F. , Yim L., Moffitt C., Umemoto L. A., and Francis S. E.. 2000. “Assessment of Symptoms of DSM‐IV Anxiety and Depression in Children: A Revised Child Anxiety and Depression Scale.” Behaviour Research and Therapy 38, no. 8: 835–855. 10.1016/S0005-7967(99)00130-8. [DOI] [PubMed] [Google Scholar]
  9. Culbert, K. M. , Racine S. E., and Klump K. L.. 2016. “Hormonal Factors and Disturbances in Eating Disorders.” Current Psychiatry Reports 18, no. 7: 65. 10.1007/s11920-016-0701-6. [DOI] [PubMed] [Google Scholar]
  10. Culbert, K. M. , Sisk C. L., and Klump K. L.. 2021. “A Narrative Review of Sex Differences in Eating Disorders: Is There a Biological Basis?” Clinical Therapeutics 43, no. 1: 95–111. 10.1016/j.clinthera.2020.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Davis, C. A. , Levitan R. D., Reid C., et al. 2009. “Dopamine for ‘Wanting’ and Opioids for ‘Liking’: A Comparison of Obese Adults With and With‐ Out Binge Eating.” Obesity 17, no. 6: 1220–1225. 10.1038/oby.2009.52. [DOI] [PubMed] [Google Scholar]
  12. Diekhof, E. K. 2015. “Be Quick About It. Endogenous Estradiol Level, Menstrual Cycle Phase and Trait Impulsiveness Predict Impulsive Choice in the Context of Reward Acquisition.” Hormones and Behavior 74: 186–193. 10.1016/j.yhbeh.2015.06.001. [DOI] [PubMed] [Google Scholar]
  13. Edler, C. , Lipson S. F., and Keel P. K.. 2007. “Ovarian Hormones and Binge Eating in Bulimia Nervosa.” Psychological Medicine 37, no. 1: 131–141. 10.1017/S0033291706008956. [DOI] [PubMed] [Google Scholar]
  14. Eng, A. G. , Nirjar U., Elkins A. R., et al. 2024. “Attention‐Deficit/Hyperactivity Disorder and the Menstrual Cycle: Theory and Evidence.” Hormones and Behavior 158: 105466. 10.1016/j.yhbeh.2023.105466. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Fairburn, C. G. , Cooper Z., and O'Connor M.. 2008. “Eating Disorder Examination (16.0D).” In Cognitive Behavior Therapy and Eating Disorders. Guilford Press. [Google Scholar]
  16. Fehring, R. J. , Schneider M., and Raviele K.. 2006. “Variability in the Phases of the Menstrual Cycle.” Journal of Obstetric, Gynecologic, and Neonatal Nursing 35, no. 3: 376–384. 10.1111/j.1552-6909.2006.00051.x. [DOI] [PubMed] [Google Scholar]
  17. Finlayson, G. , and Dalton M.. 2012. “Hedonics of Food Consumption: Are Food ‘Liking’ and ‘Wanting’ Viable Targets for Appetite Control in the Obese?” Current Obesity Reports 1, no. 1: 42–49. 10.1007/s13679-011-0007-2. [DOI] [Google Scholar]
  18. Galván, A. 2013. “The Teenage Brain: Sensitivity to Rewards.” Current Directions in Psychological Science 22: 88–93. 10.1177/0963721413480859. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Goldschmidt, A. B ., K. E. Smith , R. D. Crosby , et al. 2018. “Ecological Momentary Assessment of Maladaptive Eating in Children and Adolescents With Overweight or Obesity.” International Journal of Eating Disorders 51, no. 6: 549–557. 10.1002/eat.22864. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Goldschmidt, A. B. , Mason T. B., Smith K. E., Egbert A. H., Engel S. G., and Haedt‐Matt A.. 2022. “Typology of Eating Episodes in Children and Adolescents With Overweight/Obesity.” Eating Behaviors 44: 101596. 10.1016/j.eatbeh.2022.101596. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Handy, A. B. , Greenfield S. F., Yonkers K. A., and Payne L. A.. 2022. “Psychiatric Symptoms Across the Menstrual Cycle in Adult Women: A Comprehensive Review.” Harvard Review of Psychiatry 30, no. 2: 100–117. 10.1097/HRP.0000000000000329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Henderson, V. W. 2018. “Progesterone and Human Cognition.” Climacteric 21, no. 4: 333–340. 10.1080/13697137.2018.1476484. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hespanhol, L. , Vallio C. S., Costa L. M., and Saragiotto B. T.. 2019. “Understanding and Interpreting Confidence and Credible Intervals Around Effect Estimates.” Brazilian Journal of Physical Therapy 23, no. 4: 290–301. 10.1016/j.bjpt.2018.12.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Justice, A. J. , and De Wit H.. 2000a. “Acute Effects of d‐Amphetamine During the Early and Late Follicular Phases of the Menstrual Cycle in Women.” Pharmacology Biochemistry and Behavior 66, no. 3: 509–515. 10.1016/S0091-3057(00)00218-5. [DOI] [PubMed] [Google Scholar]
  25. Justice, A. J. , and De Wit H.. 2000b. “Acute Effects of Estradiol Pretreatment on the Response to d‐Amphetamine in Women.” Neuroendocrinology 71, no. 1: 51–59. 10.1159/000054520. [DOI] [PubMed] [Google Scholar]
  26. Kalanthroff, E. , Seror Y., Sagi N., et al. 2025. “The Rollercoaster of Obsessive‐Compulsive Disorder: How Chronotype and Time of Day Affect Behavioral Inhibition in Adults With OCD.” Journal of Mood & Anxiety Disorders 10: 100113. 10.1016/j.xjmad.2025.100113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Klump, K. L. , Culbert K. M., Johnson A. W., and Sisk C. L.. 2023. “Ovarian Hormones and Binge Eating in Adulthood: Summary of Findings and Implications for Individual Differences in Risk in Women.” Current Directions in Psychological Science 32, no. 6: 471–478. 10.1177/09637214231192835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Klump, K. L. , Culbert K. M., and Sisk C. L.. 2017. “Sex Differences in Binge Eating: Gonadal Hormone Effects Across Development.” Annual Review of Clinical Psychology 13: 183–207. 10.1146/annurevclinpsy-032816-045309. [DOI] [PubMed] [Google Scholar]
  29. Klump, K. L. , and Di Dio A. M.. 2022. “Combined Oral Contraceptive Use and Risk for Binge Eating in Women: Potential Gene × Hormone Interactions.” Frontiers in Neuroendocrinology 67: 101039. 10.1016/j.yfrne.2022.101039. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Klump, K. L. , Keel P. K., Burt S. A., et al. 2013. “Ovarian Hormones and Emotional Eating Associations Across the Menstrual Cycle: An Examination of the Potential Moderating Effects of Body Mass Index and Dietary Restraint.” International Journal of Eating Disorders 46, no. 3: 256–263. 10.1002/eat.22084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Klump, K. L. , Keel P. K., Racine S. E., et al. 2013. “The Interactive Effects of Estrogen and Progesterone on Changes in Emotional Eating Across the Menstrual Cycle.” Journal of Abnormal Psychology 122, no. 1: 131–137. 10.1037/a0029524. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Klump, K. L. , Racine S. E., Hildebrandt B., et al. 2014. “Influences of Ovarian Hormones on Dysregulated Eating: A Comparison of Associations in Women With Versus Women Without Binge Episodes.” Clinical Psychological Science 2, no. 5: 545–559. 10.1177/2167702614521794. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Le, J. , Thomas N., and Gurvich C.. 2020. “Cognition, the Menstrual Cycle, and Premenstrual Disorders: A Review.” Brain Sciences 10, no. 4: 198. 10.3390/brainsci10040198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Legro, R. S. , Lin H. M., Demers L. M., and Lloyd T.. 2000. “Rapid Maturation of the Reproductive Axis During Perimenarche Independent of Body Composition.” Journal of Clinical Endocrinology & Metabolism 85, no. 3: 1021–1025. 10.1210/jcem.85.3.6423. [DOI] [PubMed] [Google Scholar]
  35. Lester, N. A. , Keel P. K., and Lipson S. F.. 2003. “Symptom Fluctuation in Bulimia Nervosa: Relation to Menstrual‐Cycle Phase and Cortisol Levels.” Psychological Medicine 33, no. 1: 51–60. 10.1017/s0033291702006815. [DOI] [PubMed] [Google Scholar]
  36. Li, M. , Mai Z., Yang J., Zhang B., and Ma N.. 2020. “Ideal Time of Day for Risky Decision Making: Evidence From the Balloon Analogue Risk Task.” Nature and Science of Sleep 12: 477–486. 10.2147/NSS.S260321. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Lile, J. A. , Kendall S. L., Babalonis S., Martin C. A., and Kelly T. H.. 2007. “Evaluation of Estradiol Administration on the Discriminative‐Stimulus and Subject‐Rated Effects of d‐Amphetamine in Healthy Pre‐Menopausal Women.” Pharmacology Biochemistry and Behavior 87, no. 2: 258–266. 10.1016/j.pbb.2007.04.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Linardon, J. 2018. “Rates of Abstinence Following Psychological or Behavioral Treatments for Binge‐Eating Disorder: Meta‐Analysis.” International Journal of Eating Disorders 51, no. 8: 785–797. 10.1002/eat.22897. [DOI] [PubMed] [Google Scholar]
  39. Linardon, J. , and Wade T. D.. 2018. “How Many Individuals Achieve Symptom Abstinence Following Psychological Treatments for Bulimia Nervosa? A Meta‐Analytic Review.” International Journal of Eating Disorders 51, no. 4: 287–294. 10.1002/eat.22838. [DOI] [PubMed] [Google Scholar]
  40. Luo, Y. , Morales J. C., Dunton G. F., and Mason T. B.. 2025. “Assessment of EMA Binge‐Eating Symptoms in Adolescents: Factor Analysis and Associations With Social Context and Food Types.” Appetite 214: 108212. 10.1016/j.appet.2025.108212. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Ma, R. , Mikhail M. E., Culbert K. M., Johnson A. W., Sisk C. L., and Klump K. L.. 2020. “Ovarian Hormones and Reward Processes in Palatable Food Intake and Binge Eating.” Physiology 35, no. 1: 69–78. 10.1152/physiol.00013.2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Mason, T. B. , Do B., Wang S., and Dunton G. F.. 2020. “Ecological Momentary Assessment of Eating and Dietary Intake Behaviors in Children and Adolescents: A Systematic Review of the Literature.” Appetite 144: 104465. 10.1016/j.appet.2019.104465. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Mason, T. B. , and Smith K. E.. 2022. “Psychiatric Comorbidity Associated With Eating Disorders in 9‐ to 10‐Year‐Old Children.” Canadian Journal of Psychiatry 67, no. 4: 315–318. 10.1177/07067437211026485. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Monk, T. H. , Reynolds C. F. III, Kupfer D. J., et al. 1994. “The Pittsburgh Sleep Diary.” Journal of Sleep Research 3, no. 2: 111–120. 10.1111/j.1365-2869.1994.tb00114.x. [DOI] [PubMed] [Google Scholar]
  45. Morssinkhof, M. W. L. , Van Wylick D. W., Priester‐Vink S., et al. 2020. “Associations Between Sex Hormones, Sleep Problems and Depression: A Systematic Review.” Neuroscience & Biobehavioral Reviews 118: 669–680. 10.1016/j.neubiorev.2020.08.006. [DOI] [PubMed] [Google Scholar]
  46. Nobile, B. , Maimoun L., Jaussent I. D., et al. 2021. “Effects of Hormonal Contraception Use on Cognitive Functions in Patients With Bulimia Nervosa.” Frontiers in Psychiatry 12: 658182. 10.3389/fpsyt.2021.658182. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Osianlis, E. , Thomas E. H., Jenkins L. M., and Gurvich C.. 2025. “ADHD and Sex Hormones in Females: A Systematic Review.” Journal of Attention Disorders 29, no. 9: 706–723. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Pang, R. D. , Liautaud M. M., Kirkpatrick M. G., Huh J., Monterosso J., and Leventhal A. M.. 2018. “Ovarian Hormones and Transdermal Nicotine Administration Independently and Synergistically Suppress Tobacco Withdrawal Symptoms and Smoking Reinstatement in the Human Laboratory.” Neuropsychopharmacology 43, no. 4: 828–837. 10.1038/npp.2017.216. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Pang, R. D. , Morales J. C., Smith K. E., Murray S. B., Dunton G. F., and Mason T. B.. 2023. “Daily Ovarian Hormone Exposure and Loss of Control Eating in Adolescent Girls: A Registered Report.” International Journal of Eating Disorders 56, no. 6: 1246–1253. 10.1002/eat.23962. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Parker, M. N. , Tanofsky‐Kraff M., Crosby R. D., et al. 2021. “Food Cravings and Loss‐of‐Control Eating in Youth: Associations With Gonadal Hormone Concentrations.” International Journal of Eating Disorders 54, no. 8: 1426–1437. 10.1002/eat.23530. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Powell, D. , McMinn D., and Allan J. L.. 2017. “Does Real Time Variability in Inhibitory Control Drive Snacking Behavior? An Intensive Longitudinal Study.” Health Psychology 36, no. 4: 356–364. 10.1037/hea0000471. [DOI] [PubMed] [Google Scholar]
  52. Racine, S. E. , Keel P. K., Burt S. A., et al. 2013. “Individual Differences in the Relationship Between Ovarian Hormones and Emotional Eating Across the Menstrual Cycle: A Role for Personality?” Eating Behaviors 14, no. 2: 161–166. 10.1016/j.eatbeh.2013.02.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Sakaki, M. , and Mather M.. 2012. “How Reward and Emotional Stimuli Induce Different Reactions Across the Menstrual Cycle.” Social and Personality Psychology Compass 6, no. 1: 1–17. 10.1111/j.1751-9004.2011.00415.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Schaefer, L. M. , Forester G., Burr E. K., et al. 2023. “Examining the Role of Craving in Affect Regulation Models of Binge Eating: Evidence From an Ecological Momentary Assessment Study.” Journal of Psychopathology and Clinical Science 132, no. 6: 725–732. 10.1037/abn0000839. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Schmalenberger, K. M. , Tauseef H. A., Barone J. C., et al. 2021. “How to Study the Menstrual Cycle: Practical Tools and Recommendations.” Psychoneuroendocrinology 123: 104895. 10.1016/j.psyneuen.2020.104895. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Seymour, K. E. , Reinblatt S. P., Benson L., and Carnell S.. 2015. “Overlap‐ Ping Neurobehavioral Circuits in ADHD, Obesity, and Binge Eating: Evidence From Neuroimaging Research.” CNS Spectrums 20, no. 4: 401–411. 10.1017/S1092852915000383. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Shirtcliff, E. A. , Dahl R. E., and Pollak S. D.. 2009. “Pubertal Development: Correspondence Between Hormonal and Physical Development.” Child Development 80, no. 2: 327–337. 10.1111/j.1467-8624.2009.01263.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Shypailo, R. J. 2020. Age‐Based Pediatric Growth Reference Charts. Baylor College of Medicine, Children's Nutrition Research Center; Body Composition Laboratory Web Site. http://www.bcm.edu/bodycomplab/BMIapp/BMI‐calculator‐kids.html. [Google Scholar]
  59. Sisk, C. L. , and Zehr J. L.. 2005. “Pubertal Hormones Organize the Adolescent Brain and Behavior.” Frontiers in Neuroendocrinology 26, no. 3–4: 163–174. 10.1016/j.yfrne.2005.10.003. [DOI] [PubMed] [Google Scholar]
  60. Smink, F. R. , van Hoeken D., and Hoek H. W.. 2012. “Epidemiology of Eat‐ Ing Disorders: Incidence, Prevalence and Mortality Rates.” Current Psychiatry Reports 14, no. 4: 406–414. 10.1007/s11920-012-0282-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Smith, K. E. , Mason T. B., Johnson J. S., Lavender J. M., and Wonderlich S. A.. 2018. “A Systematic Review of Reviews of Neurocognitive Functioning in Eating Disorders: The State‐of‐the‐Literature and Future Directions.” International Journal of Eating Disorders 51, no. 8: 798–821. 10.1002/eat.22929. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Smith, K. E. , Mason T. B., Schaefer L. M., et al. 2020. “Examining Intra‐Individual Variability in Food‐Related Inhibitory Control and Negative Affect as Predictors of Binge Eating Using Ecological Momentary Assessment.” Journal of Psychiatric Research 120: 137–143. 10.1016/j.jpsychires.2019.10.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Sofuoglu, M. , Mouratidis M., and Mooney M.. 2011. “Progesterone Improves Cognitive Performance and Attenuates Smoking Urges in Abstinent Smokers.” Psychoneuroendocrinology 36, no. 1: 123–132. 10.1016/j.psyneuen.2010.07.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Stice, E. , Killen J. D., Hayward C., and Taylor C. B.. 1998. “Age of Onset for Binge Eating and Purging During Late Adolescence: A 4‐Year Survival Analysis.” Journal of Abnormal Psychology 107, no. 4: 671–675. [DOI] [PubMed] [Google Scholar]
  65. Tanofsky‐Kraff, M. , Marcus M. D., Yanovski S. Z., and Yanovski J. A.. 2008. “Loss of Control Eating Disorder in Children Age 12 Years and Younger: Proposed Research Criteria.” Eating Behaviors 9, no. 3: 360–365. 10.1016/j.eatbeh.2008.03.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Tanofsky‐Kraff, M. , Schvey N. A., and Grilo C. M.. 2020. “A Developmental Framework of Binge‐Eating Disorder Based on Pediatric Loss of Control Eating.” American Psychologist 75, no. 2: 189–203. 10.1037/amp0000592. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Zhang, K. , Pollack S., Ghods A., et al. 2008. “Onset of Ovulation After Menarche in Girls: A Longitudinal Study.” Journal of Clinical Endocrinology & Metabolism 93, no. 4: 1186–1194. 10.1210/jc.2007-1846. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Ziegler, A. M. , Hatzinger L. A., and Temple J. L.. 2026. “Adolescent Eating Autonomy Survey Development and Exploratory Factor Analysis.” Appetite 218: 108371. 10.1016/j.appet.2025.108371. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1: Three‐level multilevel structural equation model of rolling averaged daily progesterone and estrogen exposure, general response inhibition, and loss of control eating severity.

Table S2: Three‐level multilevel structural equation model of raw daily progesterone and estrogen exposure, general response inhibition, and loss of control eating severity.

Figure S1:. Model of daily estrogen and progesterone exposure and loss of control eating.

EAT-59-2097-s001.docx (66.3KB, docx)

Data Availability Statement

Data is available from the authors by request.

Articles from The International Journal of Eating Disorders are provided here courtesy of Wiley

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