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. Author manuscript; available in PMC: 2021 Aug 11.
Published in final edited form as: Int J Eat Disord. 2021 May 4;54(8):1426–1437. doi: 10.1002/eat.23530

Food cravings and loss-of-control eating in youth: Associations with gonadal hormone concentrations

Megan N Parker 1,2, Marian Tanofsky-Kraff 1,2,3, Ross D Crosby 4,5, Meghan E Byrne 1,2, Sarah LeMay-Russell 1,2, Taylor N Swanson 2,6, Eliana Ramirez 2, Lisa M Shank 2,3,6, Kweku G Djan 2, Esther A Kwarteng 2, Loie M Faulkner 2, Shanna B Yang 7, Anna Zenno 2, K Karthik Chivukula 8, Scott G Engel 4,5, Sheila M Brady 2, Susan Z Yanovski 9, Jack A Yanovski 2
PMCID: PMC8355041  NIHMSID: NIHMS1695909  PMID: 33942921

Abstract

Objective:

Among youth with overweight, food cravings (FC) are associated with loss-of-control (LOC)-eating, but the impact of sex-associated biological characteristics on this relationship is unknown. We examined whether sex and gonadal hormone concentrations moderated the relationships between FC and LOC-eating severity among healthy boys and girls across the weight strata in natural and laboratory environments.

Method:

Using ecological momentary assessment (EMA), FC and LOC-eating severity were reported 3-5 times a day for 2 weeks. In the laboratory, participants reported FC, consumed lunch from a buffet test meal designed to simulate LOC-eating, and rated LOC-eating severity during the meal.

Results:

Eighty-seven youth (13.0±2.7y, 58.6% female, 32.2% with overweight/obesity) participated. EMA measured general and momentary FC were positively associated with LOC-eating severity (ps<.01), with no differences by sex (ps=.21-.93). Estradiol and progesterone significantly moderated the relationships between FC and LOC-eating such that general FC and LOC-eating severity were only positively associated among girls with greater (vs lower) estradiol (p=.01), and momentary FC and LOC-eating severity were only positively associated among girls with greater (vs lower) progesterone (p=.01). Boys’ testosterone did not significantly moderate the associations between FC and LOC-eating severity (ps=.36-.97). At the test meal, pre-meal FC were positively related to LOC-eating severity (p<.01), without sex or hormonal moderation (ps=.20-.64).

Discussion:

FC were related to LOC-eating severity in boys and girls. In the natural environment, gonadal hormones moderated this relationship in girls, but not boys. The mechanisms through which gonadal hormones might affect the relationship between FC and LOC-eating warrant investigation.

Keywords: Food cravings, loss-of-control eating, children, adolescents, sex, ecological momentary assessment, laboratory intake, gonadal hormones, testosterone, estradiol

Introduction

Food cravings (FC), intense desires to consume specific palatable foods (Weingarten & Elston, 1991), can be conceptualized as motivational states driven by a desire to obtain pleasure/reward from food (Hill, 2007). FC are experienced by youth (Silvers et al., 2014), are associated with increased food intake and body weight (Boswell & Kober, 2016), and are theorized to be factors in the etiology of obesity and loss-of-control (LOC)-eating (Kober & Boswell, 2018; Potenza & Grilo, 2014). LOC-eating, the subjective experience of feeling unable to stop eating (American Psychiatric Association, 2013), is experienced by approximately 23% of youth with overweight/obesity (Byrne, LeMay-Russell, & Tanofsky-Kraff, 2019a). Pediatric LOC-eating is prospectively associated with excess weight (Tanofsky-Kraff et al., 2009b) and adiposity gain (Tanofsky-Kraff et al., 2006), worsening of metabolic syndrome components (Tanofsky-Kraff et al., 2012), and development of sub- or full-threshold binge-eating disorder (Tanofsky-Kraff et al., 2011). Yet, only one relatively small pediatric study of youth with overweight has examined the relationship between FC and LOC-eating (Goldschmidt et al., 2018). Goldschmidt et al. (2018) found, during a study that utilized two weeks of ecological momentary assessment (EMA), youth with higher average FC reported greater LOC-eating severity in the natural environment. Research conducted within larger samples of youth of broad weight strata is needed to elucidate whether this relationship is present prior to excess weight gain.

Biological sex-associated factors are relevant for FC (Hallam, Boswell, DeVito, & Kober, 2016) and LOC-eating (Culbert, Sisk, & Klump, 2021; Hudson, Hiripi, Pope, & Kessler, 2007). Females disproportionately experience, and are more susceptible to FC than males (Hallam et al., 2016). From adolescence into adulthood, females report greater rates of LOC-eating (American Psychiatric Association, 2013; Bulik, 2002; Hudson et al., 2007). In adults, some (Hormes, Orloff, & Timko, 2014; Sobik, Hutchison, & Craighead, 2005), but not all (Chao, Grilo, & Sinha, 2016) studies have linked increased FC to increased LOC-eating among females, but not males. The extent to which these relationships differ between boys and girls is unknown.

Biological sex-based differences in LOC-eating increase during puberty (Culbert, Sisk, & Klump, 2018; Klump, 2013; Klump, Culbert, & Sisk, 2017). Endogenous concentrations of gonadal hormones (GH) such as estradiol, progesterone, and testosterone increase during pubertal development and may underlie these differences. Studies of between-person differences in GH concentrations suggest lower circulating estradiol (Klump et al., 2018) and testosterone (Culbert, Burt, Sisk, Nigg, & Klump, 2014) may increase risk for LOC-eating in girls and boys, respectively. Following pubertal onset in girls, estrogens and progesterone fluctuate on a monthly cycle, leading to menstruation (Chumlea et al., 2003). It has been suggested that the effects of GH on LOC-eating emerge during puberty (Klump, Keel, Sisk, & Burt, 2010). Following menstrual onset, within-person interactions among circulating concentrations of estradiol and progesterone promote susceptibility to FC (Dye & Blundell, 1997) and LOC-eating (Klump, Keel, Culbert, & Edler, 2008; Klump et al., 2014) such that concurrently high or concurrently low estradiol and progesterone are linked to increased LOC-eating frequency. As progesterone is known to reduce estrogen receptor availability and thus reduce at least some of estradiol effects (Kuhl, 2005), it may be that high progesterone antagonizes estradiol’s actions on LOC-eating. Relatively little is known about how testosterone, the predominant androgen in males, impacts FC intensity and LOC-eating in boys. Advanced pubertal stage is associated with greater food intake (Shomaker et al., 2010), thus testosterone may increase consummatory drive. Yet, the effects of lower concentrations of testosterone on LOC-eating persist into adulthood (Culbert, Shope, Sisk, & Klump, 2020). Importantly, GH are hypothesized to increase LOC-eating by modulating “wanting for” and neurobiological sensitivity to the rewarding and pleasurable aspects of palatable foods (Culbert et al., 2021; Ma et al., 2020), particularly among females. Empirical tests of this theory in youth are needed.

Together, examining the impact of biological sex and GH concentrations on both general and momentary levels of FC may provide insight into how FC are related to LOC-eating. Established associations among adiposity, pubertal development (Burt Solorzano & McCartney, 2010) and GH concentrations in boys (Mogri, Dhindsa, Quattrin, Ghanim, & Dandona, 2013) and girls (Hirschberg, 2012) warrant examination of these variables for LOC-eating development among youth of a broad weight spectrum. We studied boys and girls of a broad weight strata in their natural environment using EMA, and in the laboratory using a test meal designed to simulate LOC-eating (Tanofsky-Kraff et al., 2009a), to investigate the associations between FC and LOC-eating. We hypothesized that using EMA: 1) youth with higher (vs lower) general FC would report greater LOC-eating severity, and 2) greater momentary FC would be positively associated with LOC-eating severity during the next eating episode. At the laboratory meal, we expected that more intense FC immediately prior to a test meal would be associated with greater LOC-eating severity. In both settings, we expected that positive associations between FC and LOC-eating would be stronger for girls than boys and would be affected by GH concentrations.

Methods

Participants

A convenience sample of non-treatment girls and boys (8-17 years) was recruited via flyers and mailings for a study that aims to understand how eating behaviors impact weight gain (ClinicalTrials.gov ID# NCT02390765). Exclusionary criteria included 1) current/past significant physical or psychiatric disorder, brain injury, or pregnancy, 2) current use of medication known to affect body weight/food intake (including those affecting pubertal hormones), 3) weight loss (>5%) or body mass index (BMI, kg/m2) <5th percentile for age and sex in the past 3 months, 4) current regular use of tobacco products and/or alcohol, and 5) a full-scale intelligence quotient score <70.

Procedures

Study procedures were approved by the National Institutes of Health (NIH) Institutional Review Board and were conducted at the outpatient Pediatric Clinic at the NIH Hatfield Clinical Research Center (Bethesda, MD). Written consent and assent were obtained from parents/guardians and children, respectively. Participants underwent a physical examination and were given the option to complete a two-week EMA protocol. The opportunity to participate in the EMA protocol was first offered to youth in September 2016, approximately 18 months after protocol initiation. Those interested were trained on completing the EMA protocol and were provided a smartphone for EMA data collection. For ~14 days following an in person visit, participants completed multiple surveys on the smartphone in the natural environment. Approximately two weeks later, they returned to the NIH following an overnight fast and underwent body composition assessments, phlebotomy, and participated in a laboratory test meal designed to simulate LOC-eating. From this cohort, the EMA, GH data, and LOC-eating severity ratings during the test meal have not previously been published. Test meal data have been reported (Byrne et al., 2021; Byrne et al., 2020; Byrne et al., 2019b; Kelly et al., 2020; Mi et al., 2019; Shank et al., 2019).

Ecological momentary assessment protocol

Consistent with prior pediatric research (Goldschmidt et al., 2018; Hilbert, Rief, Tuschen-Caffier, de Zwaan, & Czaja, 2009; Ranzenhofer et al., 2014), the EMA protocol contained signaled surveys (i.e., notifications to complete a survey), interval surveys (i.e., to complete immediately after the end of school and before bed), and event surveys (i.e., to complete any time they ate or drank something they considered to be a meal or snack). Signaled surveys were randomly delivered around stratified daily intervals, at approximately 11:10am, 1:50pm, 3:30pm, 5:40pm, and 8:20pm. On weekends, participants were asked to complete one interval survey before bed and received five signaled surveys between 11am and 9pm. On weekdays, to minimize interference with school, participants were instructed to complete two interval surveys, one after school and one before bed, and received three signaled surveys between 3pm and 9pm. Completion of event surveys were optional but encouraged.

The day following the first visit, participants practiced completing EMA surveys at home. If compliance was poor (≤ 80% of signaled and interval surveys), study personnel contacted participants to discuss overcoming barriers to compliance and complete another practice day. If compliance on the practice day was satisfactory, participants began the 14-day protocol. EMA data were collected using the Real Time Assessment In the Natural Environment (ReTAINE) system (Neuropsychiatric Research Institute, 2019). Participants were compensated up to $100 ($25/week and $50 bonus if compliance with signaled and interval surveys ≥ 80%).

Laboratory test meal

Participants were instructed to fast overnight prior to the second visit. At ~10:00am, youth were given a breakfast shake standardized to provide 21% of estimated energy needs, based on weight, height, age and average activity level in the previous week. Between 11:00am-12:00pm, participants were presented with a standardized buffet style test meal (>10,000 kcal) including a variety of food types and macronutrients (e.g., 54% energy from carbohydrate, 12% energy from protein, 33% energy from fat) and were instructed to “let yourself go and eat as much as you want” and then were left alone to eat (Tanofsky-Kraff et al., 2009a). Before the meal, participants reported current food cravings and hunger. After eating, youth indicated the degree to which they experienced LOC-eating during the meal.

Measures

Participant race and ethnicity were reported by parents/guardians.

Body Composition and Pubertal Assessments

Standardized deviation BMI scores (BMIz) were calculated from objectively measured height and weight following Center of Disease Control and Prevention growth standards for age and sex (Kuczmarski et al., 2002). Total adiposity (kg) was measured by dual-energy x-ray absorptiometry (DXA) using an iDXA system (GE Healthcare, Madison WI). During the physical exam, a physician or nurse practitioner examined physical sexual characteristics and determined pubertal stage (Bonat, Pathomvanich, Keil, Field, & Yanovski, 2002). For females, pubertal development was determined by breast development through observation and palpitation (Marshall & Tanner, 1969). Tanner stage I indicates no pubertal development, stages II and III indicate early- to mid-pubertal development, and stages IV and V indicate late-pubertal development. For males, pubertal development was determined by palpation to measure testicular volume (pre-puberty: ≤ 3 mL, early- to mid-puberty: 4–12 mL, late-puberty: >12 mL) by orchidometer beads and standards according to Prader (Tanner, 1981). When stages were discordant between the right and left breasts (or testes), the higher stage was assigned.

GH Concentrations

During the second in-person visit, fasting blood was obtained at ~9:15am. Serum samples were analyzed at the NIH Department of Laboratory Medicine. Females had serum concentrations of estradiol and progesterone measured while males had free and total testosterone measured. Serum estradiol, the predominant estrogen among females prior to menopause, was determined using electrochemiluminescence immunoassay on a Roche Cobas analyzer (Roche, Basel, Switzerland; sensitivity 5 pg/mL, interassay CV 1.6 to 2.5%, intraassay CV 3.5 to 5.7%). Serum progesterone and total testosterone were determined by immunoassays that have shown adequate sensitivity, intra-assay CVs, and inter-assay CVs as previously described (Stolze et al., 2016). Free testosterone (testosterone unbound to proteins) was calculated from total testosterone and sex hormone binding globulin concentrations.

Menstrual cycle

Girls reported the date of their first and most recent menstrual periods. For girls who were postmenarchal, days since last menstrual bleeding onset was determined. Data indicate girls are likely to experience irregular menstrual cycles (Allen et al., 2016). However, the typical length of our participant’s menstrual cycles was not collected, therefore, 28 cycles were assumed. Thus, the possible number of days ranged from 0-28. Premenarchal girls were assumed to be in the follicular phase and coded as day 7. No participants were using oral contraceptive pills or other forms of birth control at the time of data collection.

Reported Food cravings, LOC-eating severity, and Hunger

EMA items assessing FC, LOC-eating and hunger are included in Table 1.

Table 1.

EMA Items

Measure Items
Food cravings
How strong is your desire to eat one or more specific foods?
How much do you crave one or more specific foods?
How strongly do you want to eat one or more specific foods?
How much does your desire or craving to eat have power over you?
Loc-eating
How much did you lose control during this eating episode?
Did you feel that you could not keep yourself from eating?
During the eating episode you just finished how much did you feel a sense of loss of control?
How upset or distressed are you about how much you just ate?
How much did you feel driven to eat?
Hunger
How hungry are you?
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Food Cravings were measured by items adapted from the Food Cravings Questionnaire state version (Moreno, Rodriguez, Fernandez, Tamez, & Cepeda-Benito, 2008). Four items from the Intense Desire to Eat subscale were averaged to create a composite FC score. Internal reliability for EMA and pre-meal craving were excellent (Cronbach’s alpha .95 and .92, respectively).

LOC-eating severity was assessed based on items adapted from the Eating Disorder Examination (EDE; Cooper & Fairburn, 1987). The approach has been successfully used in prior EMA studies including youth (Goldschmidt et al., 2018; Ranzenhofer et al., 2014). Items were averaged to create a composite LOC-eating severity score. Internal reliability for EMA and post-meal LOC-eating were good (Cronbach’s alpha .89 and .85, respectively).

Hunger during EMA surveys and before the test meal was measured by a single item.

Measurement scales:

FC, LOC-eating, and Hunger were assessed using the same items during the EMA protocol and test meal, with slight modifications. For the EMA protocol, severity of LOC-eating, current FC and hunger were reported on a 1: ‘not at all’ to 5: ‘extremely’ Likert-type scale. For the test meal, participants rated FC immediately prior to the meal, LOC-eating severity immediately following the meal, and Hunger immediately prior to the meal, using visual analogue scales. A ruler was used to measure the distance between the left-most end of the scale and where participants drew a line bisecting the scale. The distance was then divided by the total length of the scale and multiplied by 100. Therefore, possible ratings ranged from 0 to100.

Data Analytic Plan

Analyses were conducted in SPSS version 25 (IBM Corp., 2017) and RStudio version 1.3.959 (RStudio Team, 2020). Age, race/ethnicity, sex, height, fat mass (kg), pubertal status, and hunger were considered as covariates in all analyses. Only hunger significantly contributed to models and was included in the final presented analyses. Fully adjusted models are in the Supplement. Analyses testing the effects of estradiol and progesterone were adjusted for day since last menstrual cycle.

Hormone concentrations, test meal FC, and LOC-eating severity were checked for normality. Estradiol, progesterone, and total testosterone required log-transformation. Hormone concentrations were included in analyses as continuous variables, but to facilitate visualization and interpretation of moderation analyses, levels of hormones were dichotomized as one standard deviation above and below the mean. Analytic methods used to examine descriptive statistics can be found in the Supplement.

EMA Analyses

To examine if FC were associated with LOC-eating in the natural environment, generalized linear mixed models (GLMMs) were conducted. Ratings of FC and hunger were lagged within persons and within days. Food cravings were detrended due to a linear decrease across the two-week period (see Supplement for details). General (between-subject) and momentary (within-subject) effects were disaggregated. Both general (i.e., an individual’s expected average level of FC compared to the full sample’s average level of FC) and momentary FC (i.e., the difference between a person’s momentary reported level of FC and the person’s average level of FC) were mean centered and included as independent variables in the same model. LOC-eating severity, the dependent variable in all models, was positively skewed (i.e., 65.5% of reports indicated no LOC-eating was experienced), therefore, GLMMs assumed a gamma distribution and a logit function. Surveys were nested within persons and models assumed a standard variance components covariance structure. First, potential moderators (e.g., sex and GH) were added as main effects, but not interactive effects, to the models. Then, to test whether biological sex moderated the relationships between FC and LOC-eating severity, biological sex was added into separate GLMMs as main and interactive (with general and momentary FC) independent variables. Females were set as the reference sex. To examine the moderation effect of GH, separate analyses were conducted within girls (estradiol and progesterone) and boys (testosterone). Hormones were continuous and thus mean centered and included in GLMMs as main and interactive (with general and momentary FC) independent variables. To examine effect sizes, R-square approximations for each GLMM were obtained in R-Studio using the lme4 (Bates, Mächler, Bolker, & Walker, 2015) and sjstats (Lüdecke, 2020) packages.

Test Meal Analyses

To test whether pre-meal FC predicted LOC-eating severity during the test meal, a linear regression was conducted. Next, multiple linear regressions were run including biological sex and GH as main, but not interactive effects. Finally, to test moderation effects of biological sex and GH, multiple linear regressions were run including biological sex and GH as main and interactive effects. All continuous independent variables (FC and GH) were mean centered prior to analysis. Separate sex moderation analyses were subsequently run using the PROCESS macro (Hayes, 2017) for SPSS. Separate analyses were conducted within girls (estradiol and progesterone) and boys (testosterone) to test hormonal effects. Hormones were mean centered and included as main and interactive continuous independent variables. Changes in R-square were obtained from the PROCESS macro (Hayes, 2017) and interpreted as a measure of effect size for moderation analyses.

Follow up Analyses

First, estradiol and progesterone analyses were run including the entire sample of girls. However, concentrations of GH do not fluctuate on a monthly cycle in premenarchal girls, therefore, follow-up analyses were subsequently conducted to ensure that results indicating GH moderated the relationship among food cravings and LOC-eating severity were not the result of including premenarchal girls. To confirm that pre-pubertal girls were not impacting hormonal moderation findings, we conducted analyses without pre-pubertal participants. Post-pubertal analyses are in the Supplement.

Results

Missing Data

Of the 242 participants enrolled in the parent protocol, 120 completed the EMA protocol. There were no significant differences in age, sex, race/ethnicity, or BMIz (ps=.14-.97) between participants in the parent study and those in analyses. Of the 120 who completed EMA, 6 individuals were excluded due to compliance below 30% and another 27 were excluded because they reported ≥1 eating episodes. Participants who completed EMA but were not included in analyses did not differ from participants included in analyses on age, sex, race/ethnicity or BMIz (ps= 05-.57). Of the 87 participants who completed EMA, 13 did not participate in the test meal or blood draw. All youths who completed the test meal also underwent a blood draw.

Sample Characteristics

Sample demographics and characteristics are in Table 2. Additional details, including EMA and test meal sample characteristics are included in the Supplement. Estradiol and progesterone concentrations by day since last reported menstruation are depicted in Figures 1A and 1B, respectively.

Table 2.

Sample Characteristics

Total Sample
N = 87		 Boys
n = 36		 Girls
n = 51		 Comparison
Participant Characteristics n, % n, % n, % Effect size
Non-Hispanic White (n, %) 42, 48.28 23, 63.89 19, 37.25 0.08
Pubertal Development (n, %) .27*
Pre-pubertal (n, %) 12, 13.8 8, 22.2 4, 7.8
Mid-pubertal (n, %) 19, 21.8 10, 27.8 9 , 17.6
Late-pubertal (n, %) 56, 64.4 18, 50.0 38, 74.5
Girls who reported Menstrual Onset† (n, %) 27, 62.8
M ± SD M ± SD Range M ± SD Range Effect size
Age (years) 12.98 ± 2.68 12.53 ± 2.84 8.00 - 18.00 13.29 ± 2.54 8.00 - 18.00 0.28
BMIz 0.57 ± 1.11 0.45 ± 1.19 −1.64 – 2.74 0.66 ± 1.06 −1.38 - 3.34 0.19
Gonadal Hormone Concentrations n = 33 n = 41
Boys’ Total Testosterone (ng/dL) -- 183.26 ± 147.48 20.00 - 413.00 -- -- --
Boys’ Free Testosterone (ng/dL) -- 3.44 ± 3.25 0.01 – 10.30 -- -- --
Girls’ Estradiol (pg/mL) -- -- -- 70.80 ± 60.33 13.00 - 316.00 --
Girls’ Progesterone (ng/mL) -- -- -- 1.54 ± 3.67 17.60 - 1.54 --
Days since last menstrual bleeding -- -- -- 9.35 ± 6.26 0.00 - 24.92 --
EMA N = 87 n = 36 n = 51
Hunger‡ 1.51 ± 0.56 1.54 ± 0.67 1.00 - 4.57 1.48 ± 0.46 1.00 - 3.09 0.11
Cravings‡ 1.30 ± 0.50 1.32 ± 0.66 1.00 - 4.82 1.29 ± 0.36 1.00 - 2.14 0.06
LOC severity‡ 1.23 ± 0.41 1.25 ± 0.51 1.00 - 3.62 1.21 ± 0.33 1.00 - 2.72 0.09
Test Meal n = 74 n = 33 n = 41
Pre-meal hunger 64.36 ± 21.05 64.09 ± 24.26 16.00 - 100.00 64.58 ±18.37 16.00 - 98.00 0.02
Pre-meal craving 33.36 ± 25.72 33.89 ± 28.92 0.00 - 100.00 32.94 ± 23.18 0.00 - 79.95 0.04
Post-meal LOC 18.00 ± 15.40 18.72 ± 17.01 0.00 - 60.80 17.42 ± 14.16 0.00 - 55.50 0.08
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Note:

*

p<.05; BMIz, standardized body mass index; LOC, loss of control eating; EMA, ecological momentary assessment. Unless otherwise specified data are presented as mean ± standard deviation. Group differences were tested using chi-square and independent samples t-tests, as appropriate. T-test effect sizes determined by Cohen’s d. Chi-square effect sizes determine by Cramer’s V.

†

Percentages reflect percentage of individuals within that specific group, not percentages of the total sample.

‡

Unweighted averages, aggregated within-persons, are presented.

Figure 1. Estradiol and Progesterone Concentrations by Day Since Last Menstruation.

Figure 1.

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A. Estradiol Concentrations by Day Since Last Menstruation. B: Progesterone Concentrations by Day Since Last Menstruation. In all graphs, 28-day menstrual cycles were assumed.

Food Cravings and LOC-eating in the Natural Environment

Compliance with EMA surveys among the 87 participants (M=75.52%, SD=17.81) was adequate (Liao, Skelton, Dunton, & Bruening, 2016). There were no significant associations among sex and LOC-eating or GH and LOC-eating when covarying for cravings and hunger (ßs=−0.03-0.03, ps=.48-.87; Supplemental Table 2). Full GLMM statistics are in Table 3. Higher general FC were related to higher average LOC-eating severity (Figure 2A) and increases in momentary FC were associated with higher LOC-eating severity at the next eating episode (Figure 2B). Sex did not significantly moderate either the relationship between general FC and average LOC-eating severity, or momentary FC and LOC-eating severity. Estradiol concentrations moderated the relationship with general FC, such that girls with greater concentrations of estradiol experienced positive associations among LOC-eating severity and FC, but girls with lower concentrations appeared to have a negative association among general food cravings and LOC-eating severity (Figure 3A). By contrast, estradiol did not moderate the relationship between momentary FC and LOC-eating severity. For progesterone, there was no significant moderation effect for the relationship between general FC and LOC-eating. Yet, progesterone significantly moderated the relationship between momentary FC and LOC-eating severity (Figure 3B). Only among girls with higher concentrations of progesterone were momentary increases in FC associated with increases in LOC-eating severity. Sensitivity analyses conducted exclusively for postmenarchal girls revealed that the moderating effects of estradiol on general food cravings and LOC-eating persisted (ß=0.19, p=.02), but the moderation effects of progesterone were attenuated (ß=−0.001, p=.98). Boys’ total testosterone and free testosterone did not significantly moderate the relationship between either general or momentary FC and LOC-eating severity.

Table 3.

Ecological Momentary Assessment Generalized Linear Mixed Models for LOC-Eating Severity

Model Variable ß SE t 95% CI p Conditional
R2-change
Craving † Intercept 0.14 0.03 5.24 0.09, 0.19 <.01 .10
Hunger 0.02 0.01 2.63 0.004, 0.03 .01
General Cravings 0.17 0.03 5.83 0.011, 0.23 <.01
Momentary Cravings 0.07 0.01 6.05 0.05, 0.09 <.01
Sex † Intercept 0.15 0.04 4.01 0.07, 0.23 <.01 .10
Hunger 0.02 0.01 2.56 0.004, 0.03 .01
General Cravings 0.22 0.05 4.55 0.13, 0.31 .01
Momentary Cravings 0.07 0.02 3.28 0.03, 0.11 .01
Sex −0.03 0.05 −0.53 −0.12, 0.07 .60
Sex x General Cravings −0.08 0.06 −1.26 −0.19, 0.04 .21
Sex x Momentary Cravings −0.002 0.02 −0.09 −0.05, 0.04 .93
Estradiol ‡ Intercept 0.15 0.06 2.75 0.04, 0.26 .01 .05
Hunger 0.02 0.01 1.83 −0.001, 0.03 .07
Menstrual Phase −0.001 0.01 −0.29 −0.01, 0.01 .77
General Cravings 0.17 0.04 4.43 0.09, 0.24 <.01
Momentary Cravings 0.07 0.01 5.14 0.04, 0.09 <.01
Estradiol 0.02 0.05 0.46 −0.07, 0.11 .65
Estradiol x General Cravings 0.17 0.07 2.48 0.04, 0.31 .01
Estradiol x Momentary Cravings 0.02 0.02 0.69 −0.03, 0.06 .49
Progesterone ‡ Intercept 0.17 0.07 2.43 0.03, 0.30 .02 .001
Hunger 0.01 0.01 1.46 −0.004, 0.029 .15
Menstrual Phase −0.002 0.01 −0.36 −0.02, 0.01 .72
General Cravings 0.14 0.05 2.77 0.04, 0.23 .01
Momentary Cravings 0.08 0.01 5.60 0.05, 0.10 <.01
Progesterone −0.01 0.03 −0.23 −0.06, 0.05 .82
Progesterone x General Cravings −0.01 0.06 −0.22 −0.12, 0.10 .83
Progesterone x Momentary Cravings 0.03 0.01 2.60 0.01, 0.053 .01
Total Testosterone § Intercept 0.11 0.06 1.93 −0.002, 0.22 .005 .01
Hunger 0.04 0.02 2.24 0.004, 0.07 .03
General Cravings 0.17 0.09 1.90 −0.006, 0.34 .06
Momentary Cravings 0.05 0.03 1.76 −0.006, 0.10 .08
Total T 0.02 0.04 0.54 < −0.05, 0.09 .59
Total T x General Cravings −0.04 0.05 −0.77 −0.15, 0.07 .44
Total T x Momentary Cravings −0.006 0.02 −0.32 −0.04, 0.03 .75
Free Testosterone § Intercept 0.10 0.06 1.78 −0.01, 0.21 .08 .01
Hunger 0.04 0.02 2.24 0.004, 0.07 .03
General Cravings 0.17 0.02 0.29 0.002, 0.33 .05
Momentary Cravings 0.05 0.08 2.00 −0.01, 0.10 .08
Free T 0.004 0.03 1.77 −0.03, 0.03 .78
Free T x General Cravings −0.02 0.03 −0.92 −0.07, 0.03 .36
Free T x Momentary Cravings <0.001 0.01 0.04 −0.01, 0.02 .97
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Note: ß, coefficient; SE, standard error; CI, confidence interval; Total T; total testosterone; Free T; free testosterone.

†

The conditional R2 =.31 when only hunger was included in the full sample models. Conditional R2-change was calculated by subtracting R2 of each model from .31.

‡

The conditional R2 =.36 when hunger and cravings were included in girl only models. Conditional R2-change was calculated by subtracting R2 of each model from .36.

§

The conditional R2 =.47 when hunger and cravings were included in boy only models. Conditional R2-change was calculated by subtracting R2 of each model from .35.

Figure 2. Associations Between Food Cravings and LOC-eating Severity.

Figure 2.

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A. General Food Cravings and LOC-eating Severity in the Natural Environment. Low and high general cravings represent food craving ratings one standard deviation below and above the sample’s general level of craving. B: Momentary Food Cravings and LOC-eating Severity in the Natural Environment. Low and high momentary cravings represent food cravings ratings one standard deviation below and above an individual’s afference level of craving. Beta coefficients from the GLMM were used to approximate LOC-eating severity at low and high levels of craving, these are graphed on the Y-axis. C: Food Cravings and LOC-eating Severity in the Laboratory. Test meal data were standardized for pre-meal hunger prior to graphing and beta coefficients from regressions were used to approximate LOC-eating severity.

In all graphs, High indicates higher reported food cravings; Low, lower food cravings; LOC-eating, loss-of-control eating. To facilitate visualization of EMA data, level of cravings was dichotomized as one standard deviation below and above the mean.

Figure 3. Moderation by Gonadal Hormones of Associations Between Food Cravings and LOC-eating Severity in the Natural Environment.

Figure 3.

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A: Moderation effects of estradiol for the association of general food cravings and LOC-eating severity. Estradiol was mean centered then dichotomized into low and high which were defined as one standard deviation below and above the mean. Beta coefficients from the GLMM were used to approximate LOC-eating severity at low and high levels of craving and at low and high levels of estradiol were graphed on the Y-axis. B: Moderation effects of progesterone for the association of Momentary Food Cravings and LOC-eating Severity. Progesterone was mean centered then dichotomized into low and high which were defined as one standard deviation below and above the mean. Beta coefficients from the GLMM were used to approximate LOC-eating severity at low and high levels of craving and at low and high levels of progesterone were graphed on the Y-axis.

In all graphs, High indicates higher food cravings; Low, lower food cravings; LOC-eating, loss-of-control eating. To facilitate visualization, level of cravings was dichotomized into low and high which were defined as one standard deviation below and above the mean.

Food Cravings and LOC-eating in the Laboratory

Table 2 includes ratings of pre-meal FC, LOC-eating severity, and pre-meal hunger. There were no significant main effects of sex on LOC-eating, or GH on LOC-eating, when covarying for cravings and hunger (ßs=−1.26-0.002, ps=.26-.94; see Supplemental Table 2). Pre-meal FC was a significant predictor of LOC-eating severity at the test meal (ß=0.31, p<.01; Figure 2C). Sex did not significantly moderate this relationship (sex: ß=−0.17, p=.21, R2-change=.02). Neither estradiol or progesterone moderated the relationship between girl’s pre-test meal FC and LOC-eating severity (estradiol: ß=0.14, p=.14, R2-change=.05; progesterone: ß=−0.06, p=.49, R2-change=.01). Among postmenarchal females, the moderating effects of estradiol and progesterone on general food cravings and LOC-eating remained non-significant (ß=−0.14, p=.53; ß=0.22, p=.17, respectively). Boys’ testosterone did not significantly moderate the relationship between pre-test meal FC and LOC-eating severity (total testosterone: ß=.0004, p=.52, R2-change=.01; free testosterone: ß=.02, p=.46, R2-change=.01).

Discussion

In this study of healthy children and adolescents, general and momentary levels of FC were positively associated with LOC-eating in the natural environment and pre-meal FC were positively linked to LOC-eating during a test meal in the laboratory. Findings may support the notion that FC play a role in the development of binge eating. Contrary to hypotheses, these relationships did not differ by sex in either setting; however, in the natural environment, a positive relationship between general FC and LOC-eating was observed among girls with higher (vs. lower) concentrations of estradiol. A positive association between momentary FC and LOC-eating was observed among girls with higher (vs. lower) concentrations of progesterone, although this result was nonsignificant in analyses restricted to postmenarchal girls. No GH played a significant role in the FC/LOC-eating relationship in the laboratory test meal.

Both momentary and general levels of FC were linked to LOC-eating, a finding in contrast with a previous study testing this relationship in 40 youth with overweight/obesity. Goldschmidt et al. (2018) observed a relationship between general, but not momentary, FC and LOC-eating. Study size, sample, and methodology may account for differences in findings. Our sample was larger, included a broad weight range, and greater racial and ethnic diversity. We also used a validated self-report measure to assess FC instead of a non-validated single item. However, some (Cepeda-Benito, Fernandez, & Moreno, 2003; Innamorati et al., 2014), but not all (Sobik et al., 2005; Wonderlich et al., 2017) adult research suggests that higher trait (general), but not state (momentary) FC are associated with binge eating. It is possible that over time, if momentary increases in FC promote more frequent and/or severe LOC-eating, and/or excess weight gain, state FC may become more stable. Thus, elevated levels of general FC may potentially reduce the degree to which one experiences large momentary increases in FC, thereby attenuating the link between momentary FC and LOC-eating. Considering the age range of our sample, changes in state and trait FC may not manifest until early adulthood or after onset of disordered-eating or overweight/obesity. Prospective studies should test these possibilities in adolescents and young adults.

Girls and boys reported similar levels of FC which is inconsistent with some (Hormes et al., 2014; Sobik et al., 2005), but not all (Chao et al., 2016) studies in adults. It is possible that sampling youth across pubertal stages diminished the impact of biological sex on the relationships between FC and LOC-eating. Alternatively, FC may interact with other sex-differentiated risk factors for binge eating. For example, Chao et al. (2016) found a stronger relationship among FC and eating-disordered attitudes in adult females compared to males, suggesting that learned attitudes related to gender role rather than biological sex might be important. Indeed, girls tend to report greater body dissatisfaction compared to boys (Griffiths et al., 2017). FC may contribute to this by exacerbating girls’ already heightened concerns about shape and weight following LOC-eating episodes, despite being equally impactful on girls’ and boys’ LOC-eating. To elucidate alternative sex-differentiated pathways through which FC may increase risk for binge eating, longitudinal studies should directly test sex differences in the relationships between FC and other indices of eating-disordered pathology in youth (e.g., shape/weight concerns, guilt about eating).

Results regarding the impact of GH on the FC/LOC-eating relationship are more complex. Nevertheless, our data support previous speculation (Ma et al., 2020) that increased desire for obtaining reward or pleasure from food is one psychobiological mechanism through which GH may increase risk for LOC-eating among girls. When examining all girls, greater progesterone moderated the relationship between FC and LOC-eating, however, the effects diminished when examining only postmenarchal girls. Moderation effects of estradiol were observed in both groups. This may be due to overall low levels of progesterone among all girls, which might suggest few participants had recently ovulated. Alternatively, this pattern might reflect the fact that estradiol exerts direct effects on LOC-eating, whereas progesterone acts indirectly by antagonizing estradiol (Kuhl, 2005), particularly after pubertal onset. Additionally, estradiol appears to amplify neurobiological response to palatable food in females (Culbert et al., 2018, 2021; Yoest, Quigley, & Becker, 2018), which might provide a link for the more robust and sustained impact of estradiol on the link between FC and LOC-eating. Given the study sample size, examination of interactional effects on the FC/LOC-eating relationship were not possible and require future elucidation.

Inconsistency among the moderation effects of estradiol and progesterone among EMA and test meal settings suggests that GH may interact with psychosocial stressors that are salient in one’s natural environment, but that may not be present in the laboratory (Fowler, Vo, Sisk, & Klump, 2019; Mikhail, Culbert, Sisk, & Klump, 2019). Small sample size, single assessment of GH, and between-subject differences in menstrual cycle phase during the test meal day may contribute to nonsignificant effects of hormones. Findings also suggest that increased FC is one pathway through which boys may experience increased risk for binge-eating disorders or obesity; however, testosterone does not appear to explain this pathway among healthy youth. Data suggest the effects of GH on LOC-eating varies across pubertal development in girls and boys (Culbert, Burt, & Klump, 2017; Culbert et al., 2018). Therefore, the wide age and pubertal development range of the sample may have limited our ability to detect the precise role of GH in the FC/LOC-eating relationship. Studies examining more frequent determinations of estradiol and progesterone in girls, and alternative psychobiological mechanisms in boys, are needed to better understand how FC promote LOC-eating in youth.

Strengths include the use of EMA to capture numerous data points in the natural environment in concert with a controlled laboratory test meal. Analyses adjusted for levels of hunger at the same time ratings of FC were provided. Thus, study results may be more likely to reflect the effects of maladaptive drives to eat, rather than normative physiological desires for food. Limitations include the single measurement of GH, which precluded examination of how daily changes in hormone concentrations may impact daily changes in the relationships between FC and LOC-eating. Menstrual cycle phase during participation in the EMA protocol and test meal was not standardized across postmenarchal girls. Additionally, the calculation of day since last menstrual bleeding was determined from self-reports and assumed girls experienced 28 days cycles, despite data showing irregularity and variability of cycles (Allen et al., 2016). Daily assessment of GH or more detailed report of girls’ menstrual cycles may have improved the accuracy of menstrual cycle phase assessment. Small sample size also prohibited our ability to test interactive effects of estradiol and progesterone. Studies of greater numbers of girls who are pre- and post-menarchal would also allow a better understanding of the complex role steroid sex hormones may play in FC and LOC-eating. Lastly, our data are hypothesis generating, therefore, analyses were not corrected for multiple comparisons.

These data support the relationship between increased FC and LOC-eating. Among girls, higher GH concentrations appeared to increase the salience of appetitive drivers of LOC-eating; potentially laying the foundations for the link between GH fluctuations and binge eating observed in adulthood (Klump et al., 2008). Therefore, clinicians should consider assessing for FC, and especially among girls, pubertal and menstrual cycle status in treatment planning. Among boys, more data are needed to identify the mechanisms underlying this risk pathway for developing eating-disordered behaviors. Such data would potentially serve to refine targeted interventional approaches for eating disorders and obesity in youth.

Supplementary Material

1

Acknowledgments

DISCLAIMER: The opinions and assertions expressed herein are those of the authors and are not to be construed as reflecting the views of the National Institutes of Health, USU, or the United States Department of Defense. This work was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant number ZIA-HD00641; J. Yanovski).

The data that support the findings of this study are available from the corresponding author upon request.

Footnotes

CONFLICT OF INTEREST: The authors have no conflict of interest to disclose.

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