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. Author manuscript; available in PMC: 2022 Mar 1.
Published in final edited form as: Body Image. 2020 Dec 3;36:107–116. doi: 10.1016/j.bodyim.2020.10.010

State versus trait weight, shape, and eating concerns: Disentangling influence on eating behaviors among sexual minority women

Emily Panza a,b, KayLoni Olson a,b, Edward A Selby c, Rena R Wing a,b
PMCID: PMC7987775  NIHMSID: NIHMS1644753  PMID: 33279785

Abstract

This study examined the relative influence of trait and state weight, shape, and eating concerns on dysregulated eating in the daily lives of sexual minority women with overweight and obesity. This study is a secondary analysis of data from an Ecological Momentary Assessment (EMA) study of 55 sexual minority women with overweight/obesity. Trait shape, weight, and eating concerns were assessed at baseline. For the following five days, participants used a smartphone to report state weight/shape concerns, overeating, and binge eating five times daily. Women who endorsed higher levels of trait weight, shape, and eating concerns at baseline reported more frequent state weight/shape concerns in daily life. Trait eating concerns were associated with higher odds of binge eating during EMA, but trait weight/shape concerns were unrelated to future dysregulated eating. In daily life, state weight/shape concerns was associated with greater risk for over/binge eating at the concurrent EMA prompt, the subsequent EMA prompt, and over the course of a full day, independent of trait concerns. State weight and shape concerns may play an important role in predicting dysregulated eating in daily life among sexual minority women of higher body weight.

Keywords: obesity, body dissatisfaction, sexual minority women, Ecological Momentary Assessment

Introduction

In the U.S., sociocultural standards of attractiveness emphasize thinness (and sometimes athleticism) and reinforce weight and shape as important features of self-worth (Schaefer et al., 2015; Thompson & Stice, 2001). These standards promote concerns about weight, shape, and eating, especially among women and individuals of higher body weight who are judged to be ‘farther from the ideal’ (Groesz et al., 2002). Weight, shape, and eating concerns are a specific component of negative body image that involve preoccupation, dissatisfaction, and/or over-concern with weight, shape, and eating. Individuals who tend to report greater weight, shape, and eating concerns are more likely to develop subsequent dysregulated eating behaviors (Masheb & Grilo, 2006; Stice et al., 2002), eating disorder diagnoses (Killen et al., 1996), and obesity (Stice et al., 1999) relative to those with fewer weight, shape, and eating concerns (Stice & Shaw, 2002).

Although most body image research has investigated body image among heterosexual women, weight, shape, and eating concerns are also prevalent among sexual minority women (Mason, Lewis, et al., 2018; Morrison et al., 2004; Nagata et al., 2020). Sexual minority women include women who self-identify a sexual minority orientation (e.g., lesbian) or who report same-sex attraction or behavior (Sell, 1996). Historically, it has been theorized that sexual minority women may be protected from body image concerns because they are more likely to reject male-centered standards of female beauty (Brown, 1987). Within sexual minority subculture, body ideals emphasize athleticism (Aaron et al., 2001; Beren et al., 1996; Smith et al., 2017) and acceptance of diverse and larger bodies (Alvy, 2013; Kelly, 2007; Mason & Lewis, 2014; Swami & Tovée, 2006). Yet sexual minority women are also consistently exposed to predominant cultural ideals of thinness (Dworkin & Kerr, 1987; Smith et al., 2017), positioning women in this group to contend with unique and conflicting cultural pressures around body size (Beren et al., 1997; Huxley et al., 2014; Kelly, 2007). In fact, recent work has shown that sexual minority women report comparably high (Feldman & Meyer, 2007; Koff et al., 2010) or even higher (Hadland et al., 2014) levels of body image concerns relative to heterosexual women. Thus, it is understandable that many factors that shape heterosexual women’s body image are also influential for sexual minority women, such as body mass index (BMI), thin ideal internalization, and self-esteem (Mason, Lewis, et al., 2018). Yet there are also many unique cultural factors that shape sexual minority women’s body image, including levels of masculinity and femininity (Steele et al., 2019), romantic partner’s gender (Smith et al., 2017), internalized heterosexism and level of “outness” (Huxley et al., 2014), and involvement and support within sexual minority communities (Chmielewski & Yost, 2013).

It is critical to study body image in sexual minority women because weight, shape, and eating concerns may be important contributors to dysregulated eating and obesity risk in this population (Mason & Lewis, 2016; Mason, Lewis, et al., 2018; Strong et al., 2000). Dysregulated eating is an umbrella term that describes eating behaviors that are cued not by homeostatic hunger, but by other external (i.e., environmental) or internal (i.e., negative affect) cues (Mason, Smith, & Lavender, 2018). Sexual minority women are disproportionately affected by dysregulated eating behaviors (Austin et al., 2013; Bankoff & Pantalone, 2014) and obesity (Azagba et al., 2019; Eliason et al., 2015). Within this group, body image concerns have been consistently linked to greater pressure to diet (Beren et al., 1996), higher BMI (Mason, Lewis, et al., 2017b), and dysregulated eating (Bankoff et al., 2016; Strong et al., 2000; Watson et al., 2015). More research is needed to understand body image concerns and links to dysregulated eating among sexual minority women, and particularly those women with overweight/obesity who are at highest risk for body image concerns, dysregulated eating, and poor weight-related health outcomes (Puhl & Pearl, 2018; Weinberger et al., 2016).

The majority of research investigating sexual minority women’s body image has studied women’s trait tendencies to experience weight, shape, and eating concerns and other facets of negative body image. These one-time trait measures assess weight, shape, and eating concerns as relatively stable constructs, assessing their frequency over extended periods of time with questions such as, “Over the past 28 days, how dissatisfied have you been with your weight?” (Fairburn & Beglin, 2008; Nagata et al., 2020). Yet advancements in methodology now allow us to assess negative body image states moment-to-moment as they occur in daily life (Fuller-Tyszkiewicz, 2019). For example, individuals may experience momentary concerns about shape or weight while getting dressed in the morning, looking in the mirror, or engaging in sexual activities, even if one’s body image is generally positive (Fuller-Tyszkiewicz, 2019). These momentary states may be clinically relevant events that are not captured by existing trait measures.

Rather, they are captured by Ecological Momentary Assessment (EMA), a data collection method wherein participants use a smartphone to report their body image states multiple times daily as they go about their lives (Shiffman et al., 2008). Emerging EMA research shows that negative body image states may vary considerably within and across days (Fuller-Tyszkiewicz et al., 2018; Srivastava et al., 2020), and that body image states may have unique utility in predicting eating behaviors. For example, EMA studies have shown that trait and state body dissatisfaction independently predict eating pathology among women in the general population (Fuller-Tyszkiewicz et al., 2018), and state body dissatisfaction predicts the onset of binge eating in daily life above and beyond trait concerns (Holmes et al., 2014). Although a handful of prior studies have used EMA to study links between minority stress and dysregulated eating among sexual minority women in daily life (Mason, Lewis, et al., 2017a; Panza et al., 2020), we are not aware of any studies investigating links between negative body image states and dysregulated eating among sexual minority women. Such research is vital for identifying momentary predictors of dysregulated eating in sexual minority women’s daily lives, information that can inform treatments to reduce maladaptive eating behaviors and improve weight-related health in an at-risk group of sexual minority women.

The Current Study

To address this research gap, the current study used EMA methods to explore associations between trait and state weight, shape, and eating concerns and dysregulated eating behaviors among 55 sexual minority women with overweight and obesity. At baseline, participants completed assessments of trait weight, shape, and eating concerns and demographics. Weight and height were also measured to compute body mass index (BMI). For the five days following the baseline visit, participants completed five random EMA “prompts” (i.e., momentary assessments) per day assessing recent frequency of state weight/shape concerns and dysregulated eating behaviors. We examined two types of dysregulated eating that are linked to weight-related health: overeating (e.g., eating a larger portion than intended) and binge eating (e.g., eating an unusually large amount of food while feeling unable to stop; Goldschmidt et al., 2015; Thomas et al., 2011).

The first aim of this study was to examine whether trait weight, shape, and eating concerns predicted state weight/shape concerns and dysregulated eating in daily life in sexual minority women with overweight/obesity. To do this, we examined whether baseline levels of trait weight, shape, and eating concerns predicted more frequent state weight/shape concerns and more frequent over/binge eating episodes during the EMA period. Shape, weight, and eating concerns were modeled separately in this study to identify distinct effects of each type of concern on outcomes.

The second aim was to assess whether state weight/shape concerns influence dysregulated eating in the daily lives of sexual minority women with overweight/obesity, independent of trait weight, shape, and eating concerns. Thus, we examined whether state weight/shape concerns were associated with more frequent state over/binge eating episodes at the same EMA prompt (concurrently), at the subsequent EMA prompt (in the future), and across an entire day, controlling for trait concerns.

We expected that sexual minority women with higher levels of weight, shape, and eating concerns, both as a general trait and a momentary state, would report more frequent overeating and binge eating episodes in daily life.

Methods

This study is a secondary analysis of data from a larger trial that was designed to assess the influence of multiple minority stressors, such as stigma due to sexual orientation and body weight, on daily dysregulated eating behaviors among sexual minority women with overweight/obesity (Panza et al., 2020).

Participants

Participants were 55 women (mean age = 25±9, range: 18 – 60 years) assigned female at birth who were recruited from the local community. Participants were included in the study if they were over age 18 (years), self-identified a sexual minority sexual orientation (e.g., bisexual, lesbian), had a BMI≥25kg/m2 at baseline, owned and used a smartphone, and spoke fluent English. Participants with a history of psychotic symptomatology, a developmental disorder, weight loss surgery, or a current pregnancy or serious medical condition were not invited to participate. To ensure a representative sample of women with overweight/obesity, eating pathology was not a criterion for participation.

Procedures

Study procedures were approved by the Institutional Review Board at Rutgers, the State University of New Jersey. Participants responded to advertisements for a research study about “stress and eating” that were targeted to sexual minority women. Advertisements were posted online (e.g., Facebook) and in the local community. Potentially eligible individuals received additional study information from a research assistant and were invited to complete a 65-minute in-person baseline visit. During this visit, participants completed informed consent, height and weight was measured using an advanced digital scale and stadiometer, and a laptop was used to complete measures of demographics and weight, shape, and eating concerns using Qualtrics Survey software (Qualtrics, 2005). Following survey completion, participants used their personal smartphone to download the LifeData smartphone application (LifeData LLC, 2016), which was used to administer EMA measures. A research assistant provided training to participants on how to use the LifeData smartphone application, on the EMA prompt schedule, and on how to report behaviors assessed via EMA, such as weight/shape concerns, overeating, and binge eating. Participants were given definitions and examples of each construct, they practiced answering questions in-session, and they were given a detailed written manual explaining each question on the smartphone application. Participants were compensated $15 for their time.

Following the baseline visit, participants used the LifeData smartphone application to complete prompted assessments of state weight/shape concerns, overeating, and binge eating five times daily for five days. Participants were prompted to complete entries via an on-screen notification from LifeData five times randomly between 9:00AM and 9:30PM, a standard time range based on prior research (Heron et al., 2014). with prompts occurring at least 120 minutes apart. Prompts not answered within 75 minutes of receipt counted as missing data, a time range that was chosen based on prior work (Sala et al., 2017) and that provides flexibility for participants who receive prompts while driving/working. After completing EMA procedures, participants completed an online de-briefing survey and were compensated $30 for their time.

Baseline (Trait) Measures

Demographics.

Participants self-reported their racial and ethnic background, age, and education level, variables that were used as covariates in all analyses. Participants also self-reported their assigned sex at birth and their gender identity (e.g., cisgender, transgender, gender-queer/gender non-conforming). These variables were used as inclusion criteria.

Sexual Orientation.

Women self-reported their sexual identity (i.e., self-identification as lesbian, bisexual, or something else; Eliason et al., 2015).

Body Mass Index (BMI).

Weight (kilograms) and height (centimeters) were measured at baseline using an advanced digital scale and stadiometer to calculate participants’ current BMI in kg/m2. Participants were measured in light clothing without shoes.

Weight, Shape, and Eating Concerns.

The 28-item Eating Disorder Examination-Questionnaire (EDE-Q; Fairburn & Beglin, 2008) was used to assess the frequency and intensity of trait weight, shape, and eating concerns over the past 28 days. Individual subscales assess weight concerns (5 items; α = 0.76), shape concerns (8 items; α = 0.89), and eating concerns (5 items, α = 0.76). Items were rated on a scale from 0 (not at all) to 6 (markedly). The restraint subscale of the EDE-Q was not included because characterizing dietary restraint as entirely maladaptive may mischaracterize the construct, particularly in the context of overweight/obesity (Schaumberg et al., 2016). These subscales show good stability over time (Pearson r = 0.87 – 0.94; Luce & Crowther, 1999). This scale has been extensively used to assess weight, shape, and eating concerns in both sexual minority women (Davids & Green, 2011; Mason, Lewis, et al., 2018) and adults with obesity (Mason, Smith, et al., 2017). Weight, shape, and eating concerns were modeled separately in data analyses to identify the distinct effects of each subscale on outcomes.

EMA (State) Measures

Compliance.

Compliance to EMA procedures was determined by calculating the average number of prompts completed out of all possible prompts (25) delivered during EMA.

Weight and Shape Concerns.

This study used a two-item composite measure to assess the frequency of recent weight and shape concerns. At every EMA prompt, participants answered the following two questions: “Since the last prompt, (1) have you had negative thoughts about your weight, body size or body appearance?”, (2) have you felt self-hatred, anger or disgust toward yourself for your weight?” Response options were 0 (no), 1 (yes, a few times), and 2 (yes, frequently). The two items were averaged to create one composite measure of state weight/shape concerns. At the time this study was conceptualized, little prior research had used EMA to assess state weight/shape concerns. Thus, these items were derived from a trait measure of state weight/shape concerns (Fairburn & Beglin, 2008). The reliability of these two items, as assessed by computing Cronbach’s co-efficient alpha, was excellent (α = 0.9; Tavakol & Dennick, 2011).

Dysregulated Eating.

Recent eating episodes were assessed at every EMA prompt. Participants could report up to three separate eating episodes at each prompt, and they were asked to answer a separate set of follow-up questions for each eating episode they reported. Follow-up questions assessed binge eating, overeating, and other details of food intake (e.g., food content, eating location). To assess binge eating, participants answered two questions: (1) “Did you eat what most people would regard as an unusually large amount of food given the circumstances?”, and (2) “While you were eating, did you feel out of control?” Response options were Yes/No. If participants endorsed both items, the episode was coded as binge eating. To assess overeating, participants rated the extent to which they had overeaten, defined as eating a larger portion than intended and/or eating beyond physical satiety, on an 11-point scale from 0 (not at all) to 10 (extremely). Overeating was defined as any episode with a rating ≥ 5 that did not meet criteria for binge eating (Coker et al., 2015; Harney & Liao, 2017). Thus, episodes that were coded as binge eating were not also coded as overeating. These items were derived from the EDE-Q (Fairburn & Beglin, 1994) and have been used in prior EMA studies assessing eating in adults with obesity (Berg et al., 2014; Mason, Smith, Crosby, et al., 2018). While overeating and binge eating behaviors differ in severity, both were assessed given their unique links to weight-related health (Goldschmidt et al., 2015).

Data Analytic Strategy

SPSS Version 25.0 was used to conduct data analysis. Study data included Level 2 variables (person-level; e.g., BMI, demographics, trait weight, shape, and eating concerns) and Level 1 variables (moment-level; e.g., state weight/shape concerns, state dysregulated eating). Given the nested nature of study data, generalized linear mixed models (GLMMs) were used to account for non-independent data (i.e., multiple observations nested within participants). First, GLMMs were used to determine whether trait weight, shape, and eating concerns predicted levels of state weight/shape concerns and state over/binge eating (Aim 1). Each individual subscale (i.e., weight, shape, eating concerns) was examined independent of other subscales. Participants could report up to three separate episodes of over/binge eating at each prompt, so prompt-level state over/binge eating were originally conceptualized as count variables. However, participants only reported more than one over/binge eating episode at <0.01% of EMA prompts, so the prompt-level over/binge eating variables were recoded as binary (yes/no). To analyze the binary outcome variables (i.e., occurrence of over/binge eating), GLMMs used a binomial distribution and logit link function. To analyze positively skewed variables like state weight/shape concerns, GLMMs used a gamma distribution with a log link function. Gamma effect sizes were measured with relative risk ratios (RRs), which denote a relative increase in the outcome count for every one unit increase in the independent variable. Binomial effect sizes were measured with odds ratios (ORs), which denote the constant effect of the predictor on the likelihood that over/binge eating will occur.

GLMMs were also used to determine whether state weight/shape concerns were associated with concurrent, future, and daily frequency of overeating and binge eating episodes (Aim 2). To determine the extent to which effects of state weight/shape concerns (a Level 1 variable) on dysregulated eating were attributable to between-subjects differences (e.g., participants’ weight/shape concern levels relative to others) versus within-subjects differences (e.g., participants’ weight/shape concern levels relative to themselves), we used the approach outlined by Curran and Bauer (2011) to disaggregate these sources of variance.

To examine risk for future eating behaviors, we created a time-lagged variable for state weight/shape concerns by shifting participant scores at any given prompt to the next prompt time point. Reports of eating behaviors at the first prompt of each day, which had no preceding report of weight/shape concerns, were not included when creating lag variables. When predicting risk for overeating and binge eating at the concurrent and future EMA prompts, momentary over/binge eating (prompt-level) were recoded as binary variables (yes/no). The associated GLMMs used a binomial distribution and logit link function.

To examine risk for eating behaviors across a full day, we computed each participant’s mean state weight/shape concerns score across the 5 daily ratings and summed the total number of over/binge eating episodes that each participant reported over the course of a given day. As daily aggregates, these total daily over/binge eating variables had a broader range of values than prompt-level eating variables, and thus their original coding as count variables was retained in GLMMs to capture the full variance of the outcome. These GLMMs used a negative binomial distribution and log link function, and negative binomial effect sizes were measured with RRs.

All models included the following covariates: baseline BMI, demographic factors (i.e., age, racial background, education), compliance to EMA procedures, and time. Prior work has shown that levels of body image concerns and/or dysregulated eating may differ systematically based on BMI and age (Rø et al., 2012), racial background (Wildes et al., 2001), and education level (Kashubeck-West & Huang, 2013), and thus all analyses controlled for these factors. Several steps were taken to determine whether compliance to EMA procedures was systematically associated with key study variables, and whether there was evidence of reactivity to EMA procedures. First, we correlated compliance with Level 2 variables such as trait weight, shape, and eating concerns and baseline BMI. Next, GLMMs were conducted to determine whether there were systematic differences in Level 1 variables (state weight/shape concerns, overeating, and binge eating) due to time of day, whether it was a weekday versus weekend day, and EMA prompt number over the course of the study to assess reactivity effects.

Results

Descriptive Statistics

As presented in Table 1, sexual minority women in this sample were racially diverse (45% reported being multiracial or a member of a racial minority group) and highly educated (93% completed at least some college). Most participants identified as bisexual (62%), with others identifying as lesbian (33%) or queer (5%). Participants reported their gender identity as cisgender (96%) and gender-queer/gender non-conforming (4%). Mean BMI was 32 kg/m2 ± 5, with similar distribution across weight categories (36% overweight, 29% Class I obesity, 35% Class II-III obesity). Average levels of trait weight concerns (M = 3.5±1.4), shape concerns (M = 3.8±1.4), and eating concerns (M = 1.8±1.3) were also reported (see Table 1 for the percentage of participants who met clinical cut-offs). Nearly half of participants (48%) reported at least one recent binge eating episode on the EDE-Q, with 7% reporting >5 episodes in the past month.

Table 1.

Participant characteristics.

Baseline Measures M (SD)
Age 25.0 years (9.3)
Body mass index (BMI) 32.5 kg/m2 (± 4.9)
EDE-Q eating concerns (0–6, 6 = greater concerns) 1.8 (1.3)
% of participants scoring ≥4 7%
EDE-Q shape concerns (0–6, 6 = greater concerns) 3.8 (1.4)
% of participants scoring ≥4 53%
EDE-Q weight concerns (0–6, 6 = greater concerns) 3.5 (1.4)
% of participants scoring ≥4 40%
% Participants
Race/ethnicity
White, non-Hispanic 55%
Asian 13%
Black/African American/Caribbean 7%
Hispanic/Latino 7%
More than one race 18%
Sexual orientation
Gay/lesbian 33%
Bisexual or pansexual 62%
Queer 5%
Gender Identity
Cisgender 96%
Gender-queer/gender non-conforming 4%
Education
High school graduate or equivalent 7%
Bachelor’s degree/some college/Associate’s degree 74%
Graduate degree/some gra duate school 18%
Relationship status
Single 40%
Dating/In com mitted relationship 51%
Married 7%
Divorced 2%
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Notes: Scores of ≥4 on the EDE-Q are considered clinically significant. M, mean; SD, standard deviation; EDE-Q, Eating Disorder Examination – Questionnaire

All participants (n = 55) completed both baseline and EMA procedures. There was no attrition. Compliance with EMA procedures was excellent; 76% of prompts were completed and 73% of participants completed ≥70% of EMA prompts. On average, participants completed EMA prompts within 13±18 minutes of receipt (range: 0–74 minutes), and 84% of prompts were completed with 30 minutes. The spread of EMA assessments was fairly even across the day, with 27% of prompts occurring in the morning (9AM-Noon), 39% in the afternoon (Noon-5PM), and 34% in the evening (5PM-end of EMA window). EMA compliance was positively correlated with baseline BMI (r = 0.5, p < .001), but not with trait weight (r = −0.53, p = .699), shape (r = −0.11, p = .432), or eating concerns (r = 0.06, p = .681). GLMMs revealed a main effect of time of day on state weight/shape concerns and state overeating, with sexual minority women reporting more state weight/shape concerns (b = 0.03, SE = 0.01, p =.035, RR = 1.03) and more overeating (b = 0.27, SE = 0.08, p = .001, OR = 1.30) later (versus earlier) in the day. There was also a main effect of weekend day on state binge eating (b = −0.64, SE = 0.30, p = .032, OR = 0.53), with binge eating episodes being less likely to occur on weekdays versus weekends. Thus, BMI and time of day were included as covariates in all study models, and weekend was included as a covariate in models with binge eating as an outcome. There were no significant effects of time of day on state binge eating levels, and state weight/shape concerns and overeating did not differ based on weekday (vs. weekend) or EMA prompt number over the course of the study, minimizing concerns about the influence of time and reactivity on study findings.

During the five-day EMA period, participants reported 659 total eating events (M = 12 ± 5 per participant). Of these, 150 were overeating episodes (M = 3 ± 3 per participant) and 54 were binge-eating episodes (M = 1 ± 2 per participant). Most participants (74%) reported at least one overeating episode during the study (range: 0–13), 44% reported at least one binge episode (range: 0–6), and 26% reported no episodes of overeating or binge eating. Most participants (84%) endorsed noticing state weight/shape concerns “a few times” or “frequently” at least once during the five-day EMA period (M = 0.4 ± 0.5; 0 – 2 scale). We also implemented a multi-level variance decomposition approach described in prior research (Fuller-Tyszkiewicz et al., 2015; Shiyko & Ram, 2011) to examine whether there was sufficient variance in weight/shape concerns at each proposed level of analysis to warrant investigation at each level (i.e., within individual participants, within days, and within individual EMA prompts). Results showed that 50% of variance in state weight/shape concerns occurred between participants, 8% across days, and 43% within days, justifying the approach used in this study.

Baseline Predictors of State Weight/Shape Concerns and Eating Behaviors during EMA

As outlined in Table 2, women with greater trait shape, weight, and eating concerns at baseline reported higher levels of state weight/shape concerns in daily life (RR = 1.14–1.21). Specifically, based on the RR statistic, each unit increase in trait concerns at baseline conferred 14–21% more risk for experiencing state weight/shape concerns during EMA. Results also showed that women with higher (vs. lower) trait eating concerns had 1.65 times greater odds of reporting binge eating at any given EMA prompt (b = 0.50, SE = 0.25, p =.047, OR = 1.65). Yet contrary to hypotheses, trait shape and weight concerns did not predict binge eating frequency during the EMA period, and trait weight, shape, and eating concerns did not predict overeating in daily life (p > 0.05).

Table 2.

Baseline weight, shape, and eating concerns predicting state weight/shape concerns (Aim 1).

State weight/shape concerns State binge eating (yes/no) State overeating (yes/no)
Trait body image concerns b SE Wald p RR b SE t p OR b SE t p OR
EDE-Q shape concerns (7 point scale) 0.19 0.05 4.29 <.001 1.21 0.07 0.23 0.31 .760 1.07 0.11 0.19 0.55 .580 1.11
EDE-Q weight concerns (7 point scale) 0.16 0.05 3.43 .001 1.18 0.15 0.23 0.67 .505 1.16 0.20 0.19 1.08 .280 1.23
EDE-Q eating concerns (7 point scale) 0.13 0.05 2.63 .009 1.14 0.50 0.25 1.99 .047 1.65 0.21 0.19 1.09 .277 1.23
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Notes: Covariates in all models include age, education, race, body mass index, time of day, and EMA compliance rate; models predicting state binge eating additionally controlled for week vs. weekend day. Statistically significant effects are denoted in bold-faced text. SE, Standard error; RR, Relative risk ratio; OR, Odds ratio; EDE-Q, Eating Disorder Examination – Questionnaire; EMA, Ecological Momentary Assessment.

Episodic Predictors of State Overeating and Binge Eating during EMA

Results showed significant within-subjects effects of state weight/shape concerns on risk for concurrent dysregulated eating at the same EMA prompt among sexual minority women with overweight/obesity. Participants who reported more frequent state weight/shape concerns at a given EMA prompt, compared to their typical levels, had 4.13 times greater odds of reporting state overeating (b = 1.42, SE = 0.31, p < .001, OR = 4.13) and 2.40 times greater odds of reporting state binge eating (b = 0.88, SE = 0.38, p = .022, OR = 2.40) at the same EMA prompt. There was also a significant between-subjects effect, such that sexual minority women who reported higher levels of state weight/shape concerns at any given prompt, relative to others, had 3.00 times greater odds of reporting overeating at the same prompt (b = 1.10, SE = 0.45, p = .016, OR = 3.00), but were only marginally more likely to report binge eating at the same prompt (b = 1.00, SE = 0.56, p = .073, OR = 2.73).

Results also showed significant effects of state weight/shape concerns on risk for future dysregulated eating at the subsequent prompt, with these effects being primarily between-subjects. Sexual minority women who reported higher levels of state weight/shape concerns at any given prompt, relative to others, had 3.41 times greater odds of reporting state overeating (b = 1.23, SE = 0.53, p = .020, OR = 3.41) and 7.53 times greater odds of reporting state binge eating at the subsequent prompt (b = 2.02, SE = 0.79, p = .011, OR = 7.53). Within-subjects elevations in state weight/shape concerns did not confer risk for overeating (p = .483) or binge eating (p = .369) at the subsequent EMA prompt.

To discern the unique predictive value of state over trait concerns, we also ran these models controlling for trait weight, shape, and eating concerns using a composite score to preserve statistical power. When accounting for trait concerns, the effects outlined above remained statistically significant.

Predictors of State Overeating and Binge Eating Over the Course of a Day

As outlined in Table 3, results showed significant between-subjects effects of mean daily levels of state weight/shape concerns on overeating and binge eating frequency over the course of a given day. Sexual minority women with higher average daily levels of state weight/shape concerns, relative to other participants, also reported more frequent overeating episodes (b = 1.00, SE = 0.47, p = .031, RR = 2.74) and binge eating episodes (b = 1.64, SE = 0.74, p = .026, RR = 5.14) on that day. Each unit increase in state concerns conferred 174% more risk for overeating and 414% more risk for binge eating. There was also a within-subjects effect of state weight/shape concerns on binge eating frequency over the course of a given day, such that when women experienced higher mean levels of weight/shape concerns throughout the day than was typical for them, it was associated with more frequent binge eating on that day (b = 0.61, SE = 0.27, p = .021, RR = 1.84).

Table 3.

Associations between state weight/shape concerns and state overeating and binge eating at the prompt-level and day-level (Aim 2).

State binge eating (yes/no) State overeating (yes/no)
b SE t p OR b SE t p OR
Concurrent Associations between State Weight/Shape Concerns and Dysregulated Eating at the Same EMA Prompt
State weight/shape concerns Between-subjects effect 1.00 0.56 1.80 .073 2.73 1.10 0.45 2.43 .016 3.00
State weight/shape concerns Within-subjects effect 0.88 0.38 2.30 .022 2.40 1.42 0.31 4.61 <.001 4.13
Time-lagged Associations between State Weight/Shape Concerns and Dysregulated Eating at the Subsequent EMA Prompt
State weight/shape concerns Between-subjects effect 2.02 0.79 2.56 .011 7.53 1.23 0.53 2.33 .020 3.41
State weight/shape concerns Within-subjects effect 0.30 0.43 0.70 .483 1.3 0.31 0.34 0.90 .369 1.36
State binge eating
(# of daily episodes)		 State overeating
(# of daily episodes)
b SE t p RR b SE t p RR
Day-Level Associations between Mean State Weight/Shape Concerns and Total Dysregulated Eating Over the Course of an Entire Day
State weight/shape concerns Between-subjects effect 1.64 0.74 2.22 .026 5.14 1.00 0.47 2.16 .031 2.74
State weight/shape concerns Within-subjects effect 0.61 0.27 2.31 .021 1.84 0.23 0.17 1.37 .172 1.26
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Notes: The state weight/shape concerns variable was disaggregated to compute between- and within-person effects. Covariates in all models include age, education, race, body mass index, time of day, and EMA compliance rate; models predicting state binge eating additionally controlled for week vs. weekend day. Statistically significant effects are denoted in bold-faced text. SE, Standard error; OR, Odds ratio; RR, Relative risk ratio; EMA, Ecological Momentary Assessment.

When accounting for trait weight, shape, and eating concerns, all effects held aside from the between-subjects association between mean daily state weight/shape concerns and daily binge eating frequency, which was only marginally significant (b = 1.51, SE = 0.85, p = .078, RR = 4.53).

Discussion

Sexual minority women are disproportionately impacted by dysregulated eating behaviors (Bankoff & Pantalone, 2014) and obesity (Eliason et al., 2015), and this study identified trait and state weight, shape, and eating concerns as correlates of dysregulated eating in the daily lives of sexual minority women with overweight/obesity. Reporting higher levels of negative body image states in daily life was particularly linked to dysregulated eating in this group, highlighting the need for research investigating how weight, shape, and eating concerns manifest and impact eating behaviors in the daily lives of sexual minority women of higher body weight.

As expected, sexual minority women’s trait tendencies to experience weight, shape, and eating concerns were meaningful indicators of weight/shape concerns and overeating reported in daily life. Prior research has shown that trait body image concerns predict negative body image states and dysregulated eating in daily life among adults with overweight/obesity (Fuller-Tyszkiewicz et al., 2018; Mason, Smith, et al., 2017; Melnyk et al., 2004; Rudiger et al., 2007) and sexual minority women from the general population (Mason & Lewis, 2016; Mason, Lewis, et al., 2018; Strong et al., 2000). Results from this study show similar relations among sexual minority women with overweight/obesity.

Yet study findings also revealed that state weight/shape concerns were strongly linked to dysregulated eating among sexual minority women with overweight/obesity in daily life. Unlike trait weight/shape concerns, state weight/shape concerns were associated with overeating and binge eating frequency in daily life, with these effects persisting even after accounting for trait concern levels. Within-subjects effects were particularly notable, suggesting that momentary elevations in weight/shape concerns, regardless of one’s general tendency to experience these states, predict and may even promote dysregulated eating among sexual minority women with overweight/obesity. Between-subjects effects were also robust, suggesting that sexual minority women who reported higher levels of state weight/shape concerns than others during the EMA period engaged in more frequent overeating and binge eating in daily life. Together, these findings suggest that momentary experiences of weight/shape concerns are closely linked in time to dysregulated eating among sexual minority women with overweight/obesity. Indeed, prior work has shown that trait and state body dissatisfaction contribute uniquely to predicting eating pathology in women from the general population (Fuller-Tyszkiewicz et al., 2018). Study findings are also consistent with recent work linking momentary within-subject elevations in body image concerns to binge eating risk in a clinical sample of women (Srivastava et al., 2020). These data point to the potential utility of using in-the-moment body image interventions to help sexual minority women with overweight/obesity cope with negative body image states in daily life, with the goal of reducing dysregulated eating and improving weight management.

EMA data also revealed temporal relations between state body image and dysregulated eating in daily life. Results showed that state weight/shape concerns preceded overeating and binge eating episodes among sexual minority women with overweight/obesity during the course of the day, with risk conferred by participants’ overall state weight/shape concern levels relative to others. Prior EMA studies have shown that negative body image states precede future binge eating in women with normal weight (Holmes et al., 2014) and eating disorder diagnoses (Mason, Lavender, et al., 2018; Srivastava et al., 2020). These data suggest that state weight/shape concerns may heighten risk for daily overeating and binge eating, a key area for future research given the clinical significance and substantial prevalence of dysregulated eating among sexual minority women, particularly those with overweight/obesity (Bankoff & Pantalone, 2014; Mason, 2016). Weight/shape concerns are modifiable and may be useful to target in interventions to reduce dysregulated eating in this at-risk group (Olson et al., 2018).

State weight/shape concerns were also positively associated with daily overeating behaviors among sexual minority women with overweight/obesity. Most research on negative body image states examines effects on binge eating behaviors, with less work examining overeating as an outcome (Fuller-Tyszkiewicz, 2019). Although overeating is less clinically severe than binge eating, it impairs weight-related health and thus is critical to investigate among adults with overweight/obesity (Goldschmidt et al., 2015). Indeed, 74% of women in this study reported overeating during the five-day EMA period, and 31% reported only overeating and not binge eating, suggesting that overeating is a prevalent and clinically distinct behavior that merits assessment in this population. Further, state body dissatisfaction has been shown to predict more frequent overeating in daily life among women (Holmes et al., 2014), consistent with results from this study. This mounting evidence suggests that negative body image states are linked to risk for a variety of dysregulated eating behaviors, such as overeating and binge eating, which may interfere with sexual minority women’s weight management efforts.

The need for more research investigating negative body image states in sexual minority women of higher body weight is further justified by study data showing that weight/shape concerns varied within and across days for most participants. Most participants (82%) reported changing levels of weight/shape concerns (e.g., reporting no concerns at one EMA prompt yet reporting some or frequent concerns at a different prompt) within an individual day during the EMA period, and 62% reported within-day variability on three or more days. Body image varies within and across days in the general population of women with obesity (Fuller-Tyszkiewicz, 2019; Fuller-Tyszkiewicz et al., 2018; Melnyk et al., 2004). In addition to facing many cues for negative body image that heterosexual women face (e.g., negative affect, mainstream media; Mason, Lewis, et al., 2018), sexual minority women are likely to face unique, additional cues such as sexual minority stress (Huxley et al., 2014), pressure to adhere to body ideals held within sexual minority communities (Aaron et al., 2001; Alvy, 2013; Swami & Tovée, 2006), and comparing one’s own body to a same-gender partner’s (Smith et al., 2017). Thus, future work using state-based measures is needed to identify these fluctuations and to understand their contextual contributors in this population.

This need for future work was underscored by several unexpected findings. Contrary to hypotheses, trait shape and weight concerns did not predict binge eating frequency during the EMA period, and trait weight, shape, and eating concerns did not predict overeating in daily life. These findings are inconsistent with research in adults with obesity showing that weight, shape, and eating concerns predict greater EMA-measured loss-of-control eating (Mason, Smith, et al., 2017) and extensive cross-sectional work linking trait weight, shape, and eating concerns to dysregulated eating (Masheb & Grilo, 2006; Stice et al., 2002). One possibility is that the five-day EMA period was too short to capture women’s true levels of overeating and binge eating, thus underestimating effects of trait body image concerns on dysregulated eating. Alternatively, it is possible that the effects of trait body image concerns on dysregulated eating are different for lesbian versus bisexual women, and aggregating their experiences may dilute our ability to detect effects that exist. These discrepant findings highlight the need for future trials examining links between weight, shape, and eating concerns and dysregulated eating among sexual minority women with overweight/obesity.

Limitations and Future Directions

Study results must be interpreted in light of several limitations. This project was a pilot study with a small sample and a short EMA monitoring period. Thus, future research is needed using larger samples and longer monitoring periods to detect links between weight, shape, and eating concerns and dysregulated eating, to determine the causality of these links, and to empirically examine the underlying mechanisms that drive these relations among sexual minority women in daily life.

This study examined weight, shape, and eating concerns in a combined sample of lesbian and bisexual women. While this was advantageous for capturing a broad array of sexual minority women’s experiences, it also precludes our ability to understand whether lesbian and bisexual women may have differential patterns of weight, shape, and eating concerns (Puckett et al., 2016). Future studies should be designed to explore these experiences separately, or to recruit larger samples of each group to enable comparison. The external validity of study findings may also be influenced by the relatively young average age of the sample (mean = 25 years old). While all analyses controlled for the effects of age, future research should examine sexual minority women’s experiences of body image across a broader age range.

Given the early phase of EMA research, other limitations of this study relate to construct measurement. At the time this project was designed, few studies had used EMA to assess state weight/shape concerns, leading us to develop our own such items. The measures we used rely on participant self-report, which is particularly sub-optimal for the valid assessment of momentary overeating and binge eating. Thus, future studies are needed to refine and further validate these state measurements, and to examine the utility of combining EMA measures with adjunctive dietary assessment tools (e.g., 24-hour dietary recalls, food photography) to validate self-report assessments.

Further, the temporal dynamics of body image states remain unclear. Although this study showed that 8% of the variance in state weight/shape concerns occurred across days, other studies have shown minimal between-day variance (Fuller-Tyszkiewicz et al., 2015), necessitating future work using larger samples to examine this empirically. Further, a recent study showed that the potency of state body image as a predictor of a state-based dependent variable diminished with the length of the EMA time interval (Fuller-Tyszkiewicz et al., 2015), and there has recently been an emphasis on increasing sampling frequency (Fuller-Tyszkiewicz et al., 2020) when assessing body image states to capture faster momentary fluctuations. The sampling frequency of this study was designed to capture the outcomes of the parent study, so it is possible that two+ hour intervals between EMA prompts may underestimate associations between state weight/shape concerns and dysregulated eating, effects that may be amplified when exploring lagged associations in particular.

Finally, although using separate models allowed us to test the unique effects of trait weight, shape, and eating concerns on outcomes, conducting multiple comparisons increases risk for Type 1 error (Bender & Lange, 2001). While the preliminary nature of this study precludes an overly-controlled correction that might risk Type 2 error, future work is needed to replicate study findings.

Conclusions

Trait and state weight, shape, and eating concerns are related but distinct constructs with differential value in predicting dysregulated eating among sexual minority women of higher body weight. State weight/shape concerns were robustly related to daily eating behaviors above and beyond trait concerns, underscoring the unique utility of state weight/shape concerns in predicting eating behaviors. Importantly, this work emphasizes the need for future research focused on weight, shape, and eating concerns among sexual minority women with overweight/obesity, who are underrepresented in body image research.

Highlights.

  • Assessing trait and state body image concerns in sexual minority women is novel

  • Trait and state body image concerns are strongly linked among sexual minority women

  • Daily body image concerns are robustly linked to dysregulated eating in daily life

Acknowledgements

We wish to thank our research assistants for their contributions to data collection, including Maria Alba, Joshua Antunes, Gianna Distasio, Nicholas Diaz, Laura D’Adamo, Danielle Llaneza, Shadia Ahmed, Gali Zaborowski, Devin Sosa, Abeerah Wasti, Dana Manson, Jacqueline Roiter, Linda Hong, Megan Prince, Stephanie Garino, and Kaylee Little. We would also like to thank the participants who made this research possible.

Funding: This work was supported by the Rutgers University Teaching Assistant and Graduate Assistant Professional Development Fund, the Philanthropic Education Organization (PEO) International Scholar Award, the National Heart, Lung, and Blood Institute [T32 HL076134], and the National Institute of Minority Health and Health Disparities [K23 MD015092].

Footnotes

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Declaration of Interest: The authors declare that they have no conflict of interest.

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