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. Author manuscript; available in PMC: 2022 Mar 1.
Published in final edited form as: Body Image. 2020 Oct 23;36:5–15. doi: 10.1016/j.bodyim.2020.10.004

Associations between weight talk exposure and unhealthy weight control behaviors among young adults: A person-centered approach to examining how much the source and type of weight talk matters

Melissa Simone 1, Vivienne M Hazzard 2, Jerica M Berge 3, Nicole Larson 4, Dianne Neumark-Sztainer 4
PMCID: PMC7987583  NIHMSID: NIHMS1638418  PMID: 33160257

Abstract

This study characterized common patterns of weight talk and examined associations with unhealthy weight control behaviors (UWCBs) in young adults. Participants (n=1298) were from EAT 2018 (Eating and Activity Over Time), a population-based study of emerging adults (mean age=22.2; 53.6% women). Latent class analyses (LCA) derived classes based on weight talk exposure for men and women. Generalized linear models examined the association between weight talk classes and extreme/less extreme UWCBs. LCA results revealed 4 patterns of weight talk exposure among young adult women: minimal weight talk (38.8%), peer weight talk (35.2%), multi-source weight talk (13.5%), and parental weight talk (12.6%). Three classes emerged among men: minimal weight talk (44.0%), peer weight talk (29.7%), and multi-source weight talk (26.3%). Among young adult women, the parental weight talk class reported the highest levels of extreme and less extreme UWCBs. Among young adult men, the multi-source weight talk class reported the highest levels of less extreme UWCBs. Results provide evidence regarding the importance of parental weight talk, even among young adult children, whether or not parental weight talk is accompanied by peer weight talk. Parents have the potential to improve their young adults’ weight-related behaviors through avoiding weight talk.

Keywords: weight talk, unhealthy weight control behaviors, young adults, parental influence, peer influence

Introduction

Unhealthy weight control behaviors (UWCBs), such as laxative use or skipping meals to control or reduce weight, are common among adolescents and adults (Neumark-Sztainer et al., 2002, 2006, 2011). Prevalence estimates indicate that more than 50% of young adult women and one-third of young adult men engage in UWCBs (Haynos et al., 2018). The high prevalence of UWCBs in the general population (Haynos et al., 2018) is concerning given the harmful effects of such behaviors on young adult physical (Nagata et al., 2018) and psychological health (Mitchison et al., 2012). For instance, UWCBs have been linked with the onset of clinically significant eating disorders among other health concerns (Stice et al., 2017). Thus, a reduction in UWCB prevalence is needed to prevent eating disorders and improve psychological health among young adults.

Sociocultural theories offer frameworks for the understanding development of UWCBs (Thompson et al., 1999; Schaefer et al., 2015). Environmental pressures to attain an idealized body shape (e.g., the thin ideal, the muscular ideal) are central to sociocultural theories, wherein exposure to such pressures may increase body dissatisfaction and/or the value an individual places on their weight or shape, which may inadvertantly result in the development of UWCBs (Thompson et al., 1999) in attempts to reduce or control weight. One such environmental factor includes weight talk, which is defined as conversations about dieting (e.g., encouraging someone to diet), comments about body shape or size, weight teasing, or negative comments about appearance (Berge et al., 2013). To this end, weight talk is an environmental variable that has been consistently linked with increased UWCBs (Eisenberg et al., 2011; Bauer et al., 2013; Berge et al., 2019). While much research has focused on the association between weight talk and UWCBs during adolescence (e.g., Bauer et al., 2013; Berge et al., 2019; Berge et al., 2016), less is known about the association between weight talk and UWCBs during young adulthood (e.g., Bauer et al., 2013; Berge et al., 2019). As such, the present study aims to examine patterns of weight talk exposure and their association with UWCBs during young adulthood.

Weight talk is a broad concept that covers a wide range of weight-related conversations but is notably different from general appearance-oriented talk, as weight talk is specifically oriented around weight and/or body shape. Weight talk may be framed negatively (e.g., shaming) or positively (e.g., as a compliment). Negative weight talk often occurs when social groups participate in self-disparaging conversations about their body shape as it pertains to the ideal body shape. For instance, conversations among female peer groups may more often pertain to body fat concerns as it relates to the thin ideal (Thompson & Stice, 2001), which has been labeled “fat talk” (e.g., “I’m so fat”; Nichter & Vuckovic, 1994). In contrast, male peer groups may focus conversations around muscularity concerns in conjunction with the muscular ideal (Thompson & Cafri, 2007), which has been labeled “muscle talk” (e.g., “I need to hit the gym more”; Engeln et al., 2013). To this end, fat talk and muscle talk have consistently been linked to increased eating disorder symptomology (Lin et al., 2019; Arroyo & Harwood, 2012; Ahlich et al., 2019). In contrast, positive weight talk is typically complimentary in nature and may highlight or praise an individual’s weight loss or body shape. While negative weight talk has been consistently associated with increased eating disorder risk and symptomology (e.g., Ahlich et al., 2019; Nichter & Vuckovic, 1994), the literature on positive weight talk has been mixed. Some evidence suggests that positive weight talk is associated with improved body image and self-esteem (Herbozo & Thompson, 2006). Yet, more recent research has demonstrated that positive weight talk is associated with increased eating disorder symptomology (Herbozo et al., 2017; Hart, Chow, & Tan, 2017) and harmful effects on body esteem, body surveillance, and body dissatisfaction (Calogero et al., 2009). Taken together, even positively-framed weight talk emphasizes that value should be derived from attaining or moving towards a socially sanctioned body shape, and thus inadvertently promotes and perpetuates anti-fat attitudes. As such, the present study focuses on the broad construct of weight talk, as evidence suggests that both positive and negative weight talk may increase UWCBs and eating disorder risk.

Weight talk permeates multiple social domains and may be directed at individuals from various sources such as parents, siblings, and peers (Berge et al, 2016). While weight talk is associated with increased UWCBs (Lin et al., 2019; Herbozo et al., 2017), the magnitude of influence of weight talk on UWCBs may differ both by type (e.g., self- or listener-directed) and source (e.g., mother, peer) of the exposure. For instance, findings from a recent study suggested that mothers use weight talk to address concerns about their child’s weight or weight status, whereas fathers may focus more on specific body parts to highlight the need to lose weight (Berge et al., 2016). Given that the content and purpose of weight-related conversations may differ by source, the influence of weight talk on UWCBs likely differs as well. Moreover, weight talk may be directed at the self, the listener, someone else, or no one at all (Herbozo & Thompson, 2006), each of which may influence the listener in different ways. For instance, a young adult may comment on their own body shape, weight, or the way that their clothes fit (self-directed weight talk), which may be experienced differently than would listener-directed weight talk, such as: “Your pants are looking tighter. Did you gain weight?” (Berge et al., 2016). In other examples, weight talk can be directed towards someone else, including another friend, a stranger, or passerby to name a few. Thus, the target of weight talk likely influences the way young adults respond when exposed to weight talk. However, to date little is known about the patterns of weight talk exposure by the source of weight talk and the target of the conversation (e.g., the self, someone else) among young adults. As such, person-centered approaches to modeling weight talk exposure may be particularly useful in gaining a deeper understanding the nuanced nature of the relationship between weight talk and UWCBs. Specifically, person-centered approaches (e.g., latent class analysis) can identify the extent to which patterns of weight talk that are characterized by exposure to weight talk from specific sources (e.g., father, peer) and/or specific forms (e.g., self- or other-directed) are more strongly associated with UWCBs during young adulthood relative to other patterns of weight talk exposure. To this end, the present study aims to identify common patterns of weight talk exposure and their association with UWCBs, which will provide a more detailed account of weight talk exposure relative to traditional regression frameworks.

Given the known gender differences in idealized body shape (e.g., thin versus muscular; Thompson & Cafri, 2007; Thompson & Stice, 2001) and subsequent weight talk within peer groups (Engeln et al., 2013; Nichter & Vuckovic, 1994), it is possible that common patterns of weight talk exposure also differ by gender. For instance, some research suggests that adolescent girls are exposed to weight talk from mothers more frequently than adolescent boys, and that parental weight talk is more strongly associated to UWCBs among girls relative to boys (Rodgers et al., 2009). Additional evidence suggests that adolescent boys experience more sociocultural pressures to attain an idealized body shape from fathers, whereas adolescent girls experience more pressures from mothers and peers (McCabe & Riccardelli, 2005). Yet, research in this domain is relatively inconsistent, as some studies have revealed no gender differences with regard to frequency of weight talk exposure from mothers and fathers (Berge et al., 2013). As such while, the present study aimed to elucidate patterns of weight talk exposure and their associations with UWCBs separately for men and women, specific hypotheses pertaining to how weight talk exposure may differ by gender were not formed.

While weight talk has been widely studied in adolescent populations (Bauer, Bucchianeri, & Neumark-Sztainer, 2013; Berge et al., 2019, 2016; Neumark-Sztainer et al., 2010; Paxton et al., 1999), much less is known about the relative influence of multi-source weight talk exposure among young adults. For instance, a few studies have indicated that family (Eisenberg et al., 2011, 2012) and peer weight talk (Eisenberg et al., 2011, 2012; Forney, Holland, & Keel, 2012) are associated with increased eating pathology among young adults, yet the relative importance of source of weight talk during young adulthood remains relatively unknown. For instance, peer and parental weight talk are both strongly associated with weight control behaviors during adolescence (Tremblay & Lariviere, 2009; Vincent & McCabe, 2000), yet the developmental transition into young adulthood, which includes numerous changes to social roles, likely shifts the ways in which sociocultural pressures from peers and parents relate to psychological health and health behaviors (Larson et al., 1996; Gutman & Sameroff, 2004), such as UWCBs. Identifying the importance of each source of weight talk will provide valuable insight that can be considered when developing interventions targeting UWCBs. Without gaining a full picture of the role of weight talk exposure on UWCBs in young adults, it is possible that interventions may target weight talk among less influential sources.

Building off of past research (Eisenberg et al., 2011, 2012; Forney et al., 2012), the present study employs a person-centered approach to identify patterns of weight talk across sources (mother, father, peers) and types (self-, listener-, and other-directed), allowing for comprehensive understanding of patterns of weight talk exposure and their associations with eating behaviors. The present study aims to advance understanding of the patterns of weight talk exposure across source and type and their associations with UWCBs among young adults. The study aims to address the following research questions: (1) Which types and sources of weight talk do young adults most commonly experience?; (2) Which combinations or patterns of weight talk exposure are most commonly experienced among young adult women and men?; (3) Who experiences each pattern of weight talk?; and (4) What are the associations between patterns of weight talk exposure and UWCBs among young adult women and men? Study results will provide insight into the importance of various weight talk types and sources, providing empirical evidence for their associations with UWCBs both independently and in unison. Such insights will provide detailed information to help identify patterns of weight talk exposure associated with the greatest risk of UWCBs, which will be useful in the development of future intervention efforts targeting healthy eating and weight behaviors. We hypothesized that a number of distinct patterns of weight talk exposure would emerge, producing a multi-profile solution for both men and women, however due to the exploratory nature of the present study the structure of each profile was not hypothesized. Guided by the well-documented gender differences in ideal body images (Smolak & Stein, 2006; Thompson & Stice, 2001) and peer social norms pertaining to weight talk (Alich et al., 2019; Nichter & Vuckovic, 1994; Forney et al., 2012), it was predicted that analyses would yield different profile solutions for young men and women. We further hypothesized that the emergent profiles will have differential relations with UWCBs, with profiles marked by higher probability of multi-source weight talk exposure more strongly associated with UWCBs than those marked by weight talk exposure from fewer sources.

Method

Study Design and Participants

Data for this cross-sectional analysis were drawn from the second wave of the EAT 2010-2018 (Eating and Activity over Time) longitudinal study. EAT 2010-2018 is a population-based, cohort study of weight, weight-related behaviors, and factors associated with these outcomes in young people. Participants were first enrolled and completed the EAT 2010 survey during the 2009-2010 academic year at one of 20 public post-secondary schools in the urban area of Minneapolis-St. Paul, Minnesota (Larson et al., 2013; Neumark-Sztainer et al., 2012). At follow-up, study invitation letters were mailed to EAT 2010 participants with the opportunity to complete the EAT 2018 survey online or by mail. The EAT 2018 survey response rate was 65.8% of the original participants who could be contacted at follow-up. Given the aims of the present study, only participants who indicated that they had at least one close friend at EAT 2018 were included in the analytic sample. After removing the 250 young adults who reported having no close friends, the analytic sample (N=1298) included 53.6% (n=766) young adult women and 46.4% (n=532) young adult men. The analyses were stratified by gender identity, and thus participants who identified with a different gender identity (e.g., transgender n=9) were excluded from the analytic sample. Participants in the EAT 2018 survey had a mean age of 22.2 ± 2.0 years. All protocols were approved by the University of Minnesota’s Institutional Review Board Human Subjects Committee.

Attrition from EAT 2010 to EAT 2018 did not occur completely at random; nonresponders were more likely than responders to be male (53.3% versus 41.7%), non-white (87.0% versus 76.7%), report being born outside the U.S. (20.0% versus 16.3%), and have parents with low educational attainment (41.4% versus 36.0%) in 2010. To account for missing data, inverse probability weighting (IPW) was used for all analyses (Little, 1986), allowing for extrapolation back to the original EAT 2010 school-based sample. Weights for IPW were derived as the inverse of the estimated probability that an individual responded at the two time points based on several characteristics reported in 2010, including demographics, dieting, and weight status. After weighting, there were no significant differences between the analytic sample and the full EAT 2010 sample on demographic characteristics, dieting, or weight status (p > 0.9). In the present study, participants were 21.3% White, 26.7% African American or Black, 19.7% Asian American, 17.9% Latino/Hispanic, and 14.4% mixed or other. The weighted distribution across categories of parental socioeconomic status was: 37.8% low, 21.3% low-middle, 18.3% middle, 14.4% upper-middle, and 8.2% high.

The EAT 2018 survey was largely based on the EAT 2010 survey but modified to ensure the language of questions and topics addressed were age-appropriate as well as to explore issues of emerging interest. Based on our prior research addressing weight talk and stigma, the survey was expanded to assess additional forms and sources of weight talk (e.g., Eisenberg et al., 2012). The test-retest reliability of measures was examined using data from a subgroup of 112 young adult participants who completed the EAT 2018 survey twice within a period of three weeks. Survey development and test-retest reliability for baseline measures have been described elsewhere (Larson et al., 2013). All survey measures included in the EAT 2010 and 2018 surveys were found to have strong (test-retest agreement ≥ 80%) or adequate (test-retest agreement ≥ 70%) test-retest reliability.

Measures

Parental weight talk

Participants were asked to indicate the extent to which their mother and separately the extent to which their father engage in specific types of weight talk. The prompts read: “My mother…” and “My father…” followed by several items, including: (1) talks about her/his weight; (2) encourages me to diet to control my weight; (3) talks to me about my weight; and (4) makes comments about other people’s weight (Neumark-Sztainer et al., 2010). Response options included: not at all, a little bit, somewhat, and very much. Consistent with past applications of LCA analysis with categorical indicators with multiple response options, responses were recoded to represent a dichotomous (any/none) response for each item to ease the interpretation of the LCA results (Maas et al., 2019; Thullen et al., 2016; Nylund et al., 2007).

Peer weight talk

Participants were asked to report on the demographics, engagement with, and health behaviors of up to their three closest friends. Specific to the peer weight talk construct, for each close friend that a participant reported, they were asked the question “How often does this friend…” followed by several items, including: (1) talk about concerns regarding their own weight or body shape; (2) comment on other people’s weight; and (3) encourage you to diet? Response options included: never, rarely, sometimes, often, and I don’t know. For each friend, responses were dichotomized (any/never) for each weight talk domain. Dichotomous scores for all close friends of a participant were combined and recoded to reflect exposure (yes/no) to a domain of weight talk engaged in by any close friend.

Unhealthy weight control behaviors (UWCBs)

UWCBs were assessed with a modified version of the Pound of Prevention Survey (Jeffrey & French, 1999). Past year UWCBs were assessed with the question: “Have you done any of the following things to lose weight or keep from gaining weight during the past year?” (Neumark-Sztainer et al., 2002). Consistent with prior research, (Neumark-Sztainer et al., 2011; Haynos et al., 2018), the UWCBs considered most problematic were categorized as extreme UWCBs. Extreme UWCBs scores (range: 0-4) reflect a count of behaviors (yes/no) used to control weight during the past year, including: diet pills, self-induced vomiting, laxative use, and diuretics (test-retest = 93%). As with prior analyses (Neumark-Sztainer et al., 2011; Haynos et al., 2018), UWCBs considered to be less problematic were categorized as less extreme UWCBs scores (range: 0-5) reflect a count of behaviors used to control weight during the past year including: fasting, eating very little, used food substitute, skipped meals, or smoked more cigarettes (test-retest = 76%).

Sample Characteristics

Several sample characteristics were included in the study analyses. Specifically, analyses were stratified by gender (male, female). Additionally, study covariates included: age in years, race/ethnicity, body mass index (BMI), and socioeconomic status (SES), as these covariates have previously demonstrated associations with UWCBs (Mayer-Brown et al., 2016; Story et al., 1994). Household SES was coded in 5 groupings: low, low-middle, middle, upper-middle, and high. SES was derived from parental education level and employment status, family eligibility for public assistance, family eligibility for free or reduced school meals during EAT 2010 (Neumark-Sztainer et al., 2003).

Statistical Analysis

Prevalence of weight talk exposure across types (self-, listener-, or other-directed) and source (mother, father, peer) and gender differences were tested with chi-square tests (Research Question 1). To identify common combinations of sources of weight talk (e.g., mother, friend) experienced among young adults, latent class analyses (LCAs) were conducted separately for men and women (Research Question 2). LCAs were conducted using the 11 items representing experiences of weight talk among men and women, wherein mothers, fathers, and peers serve as the sources from whom young adults may experience weight talk using Mplus statistical software (Muthén & Muthén, 2011). Individuals were assigned to the weight talk exposure group that they had the highest probability of membership in based on their responses to each of the weight talk items across sources.

LCAs used 500 sets of random start values along with 250 initial stage iterations to ensure that model estimates were not based on local maxima of the likelihood function. Each model was run a second time with two times the iterations and random start values to ensure that the best log likelihood values were still obtained. Latent class solutions were selected based on model fit guidelines for LCA. Specifically, model fit was assessed using Bayesian Information Criterion (BIC), sample-size adjusted Bayesian Information Criterion, Log Likelihood, entropy, and the Lo-Mendell-Rubin likelihood ratio test (LMR; Lo, Mendell, & Rubin, 2001; Nylund, Asparouhov, & Muthén, 2007). When comparing models, lower AIC, BIC and aBIC are preferred and as well as higher log likelihood and entropy values. LMR estimates an empirical p value for testing a model with k classes against the k – 1 class model. A significant p-value indicates that a model with k classes significantly improves model fit relative to a model with k-1 classes. When indices of model fit endorse different solutions, entropy was given most weight in deciding the number of classes. To compare weight talk exposure classes, ANOVA analyses examined differences between the derived latent classes on outcome variables (extreme and less extreme UWCB) and characteristics including BMI, SES, and age (Research Question 3).

Generalized linear models (GLM) analyses examined the relationship between weight talk exposure and UWCBs (Research Question 4). Poisson GLM (appropriate for count data when the mean and the variance are approximately equal) was used to examine the influence of weight talk patterns on less extreme UWCBs (e.g., skipping meals). Negative binomial GLM models can be used for overdispersed count data. To this end, negative binomial GLM models are similar to Poisson models, however they include an additional parameter in the model to account for overdispersion. As such, negative binomial GLM was applied to test the association between weight talk patterns across sources and extreme UWCBs (e.g., laxative use). All GLM models were first tested with age, ethnic/racial identity, and SES included as covariates. Because exposure to weight talk likely differs by body size, a second set of analyses were conducted wherein self-reported BMI was included as an additional covariate (Eisenberg et al., 2012).

Results

Frequency of weight talk exposure among young adult women and men

Exposure to weight talk was pervasive among young adult women and men. Specifically, 94.1% of women and 90.6% of men reported experiencing at least one form of weight talk. Prevalence of weight talk exposure from mothers was most common among women (85.3%) and men (80.2%), followed by peers (72.6% and 66.8%) and fathers (54.1% and 57.5%). Prevalence of exposure differed by the type (e.g., self- or listener-directed) of weight talk. For instance, young adults endorsed self-directed weight talk exposure most frequently from their peers. Prevalence of weight talk exposure by young adults across potential sources are presented in Table 1. Young adult women were exposed to higher prevalence of most forms of weight talk from their mothers (directed at the self, young adult, and others, ps < .05) relative to young adult men. In contrast, men reported a higher prevalence of diet-specific weight talk from their mothers relative to women (p < .05). While women generally reported higher rates of weight talk exposure from their mothers than did men, no significant gender differences were observed with regard to prevalence of weight talk from fathers, suggesting that men and women experienced weight talk from their fathers at a similar rate. Finally, young women reported a higher prevalence of peer self-directed weight talk (p = .01) than did young men.

Table 1:

Frequency of weight talk across sources among young adult women and men

Weight Talk Source
n (%)
Mother Father Friends
Women
Talks about their own weight 513 (67.1)a 233 (30.5) 536 (70.1)a
Encourages me to diet 337 (50.7)a 222 (29.0) NA
Talks to me about my weight 413 (54.0)a 179 (23.4) 327 (42.7)
Makes comments about other people’s weight 339 (44.3)a 191 (25.0) 376 (49.2)
Any weight talk 638 (85.3) 454 (54.1) 555 (72.6)
Men
Talks about their own weight 305 (59.8)b 178 (33.5) 336 (63.3)b
Encourages me to diet 262 (51.2)b 165 (31.1) NA
Talks to me about my weight 253 (49.8)b 147 (27.7) 204 (38.4)
Makes comments about other people’s weight 197 (38.7)b 148 (27.9) 257 (48.4)
Any weight talk 410 (80.2) 267 (57.5) 355 (66.8)
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Note. Superscripts indicate differences between by gender. For example, women report higher rates of their mother’s talking about their own weight (67.1%) relative to men (59.8%).

Weight Talk and UWCBs Among Women

Patterns of weight talk exposure among women

Four unique patterns of weight talk exposure, including different combinations of weight talk types and sources were derived from LCA. Model fit information for all models are presented in Table 2. Women were likely to be placed in a class that accurately represented their exposure to different types and sources of weight talk, as average class assignment probabilities for the most likely class ranged between .88 and .94 in the 4-class solution. The entropy value of 0.82 suggests a clear delineation of latent profiles (Muthén & Muthén, 2011).

Table 2:

Model Fit Comparisons Across LCA Solutions in Young Adult Women and Men

Model Log-Likelihood aBIC BIC AIC Entropy LMR
p-value
Women
 1-class −5160.0 10358.2 10393.1 10342.1 NA NA
 2-class −4749.5 9578.7 9651.8 9545.0 .73 < .001
 3-class −4540.7 9202.7 9313.8 9151.4 .80 < .001
 4-class −4450.4 9063.6 9212.9 8994.8 .82 .02
 5-class −4366.8 8937.8 9125.2 8851.4 .80 .02
Men
 1-class −3650.8 7335.7 7370.6 7323.6 NA NA
 2-class −3207.6 6486.5 6559.5 6461.2 .82 < .001
 3-class −3053.7 6215.8 6326.9 6177.3 .84 < .001
 4-class −2990.4 6126.5 6275.7 6074.8 .83 .46
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Note. Bolded values highlight the best fitting model according to model entropy. aBIC = sample-size adjusted Bayesian Information Criteria; BIC = Bayesian Information Criteria; AIC = Akaike Information Criteria; LRT=Lo-Mendell-Rubin adjusted likelihood ratio test.

The conditional response probabilities for endorsing each of the 11 items across weight talk sources and types included in the 4-class solution are presented in Figure 1. Class 1, labeled the “parental weight talk exposures” class (8.6%) was the smallest group, characterized by a high probability of endorsing each type of weight talk from their mother and father, but a low probability of endorsing weight talk from their peers. Class 2, labeled the “peer weight talk exposures” class (41.5%) was characterized by a moderate-to-low probability of endorsing weight talk exposure from mothers and fathers and high probabilities of weight talk exposure across multiple facets (e.g., self-, listener-, and other-directed) from peers. Class 3, labeled the “multi-source weight talk exposures” class (15.6%), was characterized by a high probability of weight talk from mothers, fathers, and peers across all facets of weight talk. And finally, Class 4, labeled the “minimal weight talk exposures” class (34.3%) was characterized by a low probability of endorsing weight talk from any source across most facets, with only a moderate probability of endorsing maternal self-directed weight talk exposure.

Figure 1:

Figure 1:

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Patterns of Weight Talk Exposure Among Young Adult Women

Predictors of weight talk class membership among women

Among young women, the results from analyses comparing the frequency of extreme UWCB and less extreme UWCB, as well as mean BMI, age, and SES across weight talk patterns are presented in Table 3. Women in the parental weight talk exposures and the multi-source weight talk classes reported the highest number of extreme UWCBs, less extreme UWCBs, and higher BMI. Women in the multi-source weight talk exposures class were younger than those in the minimal weight talk exposures and peer weight talk exposures classes. There were no class differences in SES.

Table 3:

Mean comparisons of study outcomes and covariates across latent classes among men and women

Latent Class
Variables Parental weight
talk exposures		 Peer weight
talk exposures		 Multi-source
weight talk
exposures		 Minimal weight
talk exposures
Mean SD Mean SD Mean SD Mean SD
Women
 Extreme 0.43a 0.70 0.20b 0.53 0.28a 0.55 0.15b 0.47
 UWCBs
 Less extreme UWCBs 1.87a 1.46 1.26b 1.31 1.68a 1.36 0.84c 1.19
 BMI 29.0a 7.88 27.0b 7.10 29.9a 8.24 25.90c 6.91
 Age 21.9a 1.92 22.2ab 2.02 21.6ac 1.63 22.2ab 2.01
 SES 1.99 1.07 2.28 1.27 2.16 1.32 2.25 1.34
Men
 Extreme UWCBs -- -- 0.05 0.22 0.10 0.36 0.05 0.22
 Less extreme UWCBs -- -- 0.86a 1.19 1.27b 1.25 0.71a 1.03
 BMI -- -- 26.3a 5.65 28.4b 6.72 26.0c 5.51
 Age -- -- 22.1 2.16 22.5 2.08 22.2 2.11
 SES -- -- 2.72a 1.36 2.32b 1.39 2.58a 1.40
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UWCB=unhealthy weight control behaviors; SE=standard deviation. Different superscript letters indicate significant differences between classes.

Associations between weight talk patterns and UWCBs among women

Among women, there was a significant association between weight talk class membership (e.g., weight talk patterns) and extreme UWCBs (see Table 4), above and beyond the effect of race/ethnicity, age, and SES. Specifically, young women in the parental weight talk exposures group and the multi-source weight talk exposures group reported between 2.0 and 2.9 times more (ie, number of) extreme UWCBs relative to the minimal weight talk exposures group, suggesting that women who experience weight talk from more than one source or their parents engage in more weight control behaviors relative to women who are less likely to experience weight talk.

Table 4:

Adjusted results from GLM analyses revealing the associations between latent class membership and UWCBs among young adult women

variables Demographics-Adjusted Modela
 Fully Adjusted Modelb
Exp(B) CIs Pairwise
Comparisons		 Exp(B) CIs Pairwise
Comparisons
Extreme unhealthy weight control behaviors
 Latent Classes
 1. Parental weight talk exposures 2.90** 1.63-5.13 4 < 1, 3 2.51** 1.40-4.49
 2. Peer weight talk exposures 1.26 0.82-1.96 1 > 2 1.14 0.73-1.79 1 > 2,4
 3. Multi-source weight talk exposures 2.04* 1.21-3.43 2 = 3, 4 1.68 0.99-2.87 2 = 3, 4
 4. Minimal weight talk exposures -- -- -- --
Less extreme unhealthy weight control behaviors
 Latent Classes
 1. Parental weight talk exposures 2.08 ** 1.65-2.62 4 < 1, 2, 3 1.89** 1.50-2.39
 2. Peer weight talk exposures 1.52** 1.29-1.80 1 > 2 1.45** 1.23-1.72 4 < 1, 2, 3
 3. Multi-source weight talk exposures 1.94** 1.60-2.36 2 < 3 1.72** 1.41-2.10 1 > 2
 4. Minimal weight talk exposures -- -- -- --
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Exp(B)=exponentiated beta. For instance, within the demographics-adjusted model, women in Class 1 reported 2.90 times higher extreme unhealthy weight control behaviors than those in Class 4; CIs=95% confidence intervals.

a

Adjusted for race/ethnicity, age, and socioeconomic status.

b

Additionally adjusted for body mass index.

** =

p<.01

* =

p<.05

Pairwise comparisons for each of the 4 classes indicated that women in the parental weight talk exposures group reported more extreme UWCBs relative to all other groups. A second analysis tested the stability of the findings when BMI was added as a covariate (Table 4). When BMI was added as a covariate, the differences between the multi-source weight talk exposures group and the minimal weight talk exposures group were diminished, suggesting that group differences in BMI may better explain differences in extreme UWCBs.

The results also revealed a significant relationship between weight talk and less extreme UWCBs (see Table 4), after controlling for race/ethnicity, age, and SES. Young women in the parental weight talk exposures, peer weight talk exposures, and multi-source weight talk exposures groups reported between 1.9 and 2.1 times higher less extreme UWCB scores relative to the minimal weight talk exposures group. This finding suggests that exposure to any form of weight talk was associated with higher less extreme UWCBs. However, pairwise comparisons indicated that women in the parental weight talk exposures group reported higher less extreme UWCBs relative to the peer weight talk exposures group, suggesting that exposure to weight talk from parents may have a stronger impact on less extreme UWCBs among women than does peer weight talk. Yet, when BMI was added as a covariate to the model, differences between the peer weight talk exposures group and the parental weight talk exposures group diminished, suggesting that class differences in BMI accounted for some of the variation in scores.

Weight Talk and UWCBs Among Men

Patterns of weight talk exposure among men

Three unique patterns of weight talk exposure across types and sources were revealed with LCA. Model fit information for all models are presented in Table 2. Men had a high probability of being placed in a latent class representing their actual pattern of weight talk exposure, as average class assignment probabilities for the most likely class ranged between .91 and .95 in the 3-class solution. The entropy value of 0.84 suggests a clear delineation of latent profiles (Muthén & Muthén, 2011).

The conditional response probabilities for endorsing each of the 11 items across weight talk sources and types included in the 3-class solution are presented in Figure 2. Class 1, labeled the multi-source weight talk exposures class (26.3%) was characterized by high response probabilities of endorsing weight talk from their mothers, fathers, and friends across all facets of weight talk. Class 2, labeled the minimal weight talk exposures class (44.0%) was the largest group, characterized by low response probabilities for all types of weight talk. Class 3, labeled the multifaceted peer weight talk exposures class (29.7%) was characterized by high response probabilities of endorsing weight talk from their peers, and low-to-moderate probabilities of endorsing weight talk from their mothers or fathers.

Figure 2:

Figure 2:

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Patterns of Weight Talk Exposure Among Young Adult Men

Predictors of weight talk class membership among men

Young men in the multi-source weight talk exposures class reported the highest levels of less extreme UWCBs and BMI as well as the lowest SES relative to other weight talk exposures classes (see Table 3).

Associations between weight talk patterns and UWCBs among men

Among men, results revealed no differences in extreme UWCBs across weight talk exposure groups (see Table 5) above and beyond the effect of race/ethnicity, age, and SES. A second set of analyses adjusted for BMI in addition to race/ethnicity, age, and SES, the results from which were consistent with the demographics-adjusted model.

Table 5:

Adjusted results from GLM analyses revealing the associations between latent class membership and UWCBs among young adult men

variables Demographics-Adjusted Modela
 Fully Adjusted Modelb
Exp(B) CIs Pairwise
Comparisons		 Exp(B) CIs Pairwise
Comparisons
Extreme unhealthy weight control behaviors
 Latent Classes
 1. Multi-source weight talk exposures 2.09 0.93-4.68 1.92 0.85-4.33
 2. Minimal weight talk exposures -- -- 1 = 2 = 3 -- -- 1 = 2 = 3
 3. Peer weight talk exposures 1.17 0.48-2.88 1.16 0.47-2.86
Less extreme unhealthy weight control behaviors
 Latent Classes
 1. Multi-source weight talk exposures 1.60* 1.29-1.98 2 < 1, 3 1.41** 1.14-1.76
 2. Minimal weight talk exposures -- -- 1 = 3 -- -- 1 > 2
 3. Peer weight talk exposures 1.28** 1.03-1.60 1.23 0.98-1.53
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Exp(B)=exponentiated beta values. For instance, within the demographics-adjusted model, Class 3 reported 1.28 times higher less extreme unhealthy weight control behaviors than Class 2; CIs=95% confidence intervals.

a

Adjusted for race/ethnicity, age, and socioeconomic status.

b

Additionally adjusted for body mass index.

** =

p<.01

* =

p<.05

The results revealed a significant relationship between weight talk exposure patterns and less extreme UWCBs (see Table 5), while controlling for race/ethnicity, age, and SES. Specifically, young men in the multi-source weight talk exposures group and the peer weight talk exposures group reported between 1.3 and 1.6 times higher less extreme UWCBs relative to the minimal weight talk exposures group. The results from pairwise comparisons indicated that young adult men in the multi-source weight talk exposures and the peer weight talk exposures groups did not differ in less extreme UWCBs, suggesting that men who were exposed to weight talk from their peers may be at increased risk of less extreme UWCBs, whether or not there were exposed to weight talk from their parents. A second analysis tested the stability of the results when BMI was added as an additional covariate in the model. The results from the second analysis revealed non-significant differences between the peer weight talk exposures and the minimal weight talk exposures groups, suggesting that BMI accounts for some of the variation in less extreme UWCBs.

Discussion

The present study aimed to identify common patterns of weight talk exposure among young adult men and women and examine associations between these patterns and UWCBs. Results both confirmed and extended prior research on weight talk. Specifically, consistent with past research (Berge et al., 2016; Eisenberg et al., 2011), findings from the present study indicate that exposure to weight talk is associated with a higher number of UWCBs. The current person-centered approach to describing weight talk patterns and how sources and type of weight talk independently and simultaneously influence UWCBs among young adult women and men expands upon past research and is described in detail below.

Nearly all of the young women and men in the sample reported at least one form of weight talk. Latent patterns of weight talk exposure examined in the present study were characterized by the type and source of weight talk exposure. Notably, a majority (e.g., > 50%) of young adult women and men were placed in a latent class with a high probability of weight talk exposure from at least one potential source, indicating that it was somewhat uncommon for young adults to avoid exposure to weight talk entirely. LCA results also revealed very little heterogeneity in the type of weight talk exposure within each weight talk source. Generally speaking, when young adults were exposed to one type of weight talk from a particular source, such as self-directed weight talk from their mother, they were likely to experience other types of weight talk from that source as well (e.g., listener- and other-directed weight talk).

Class membership was associated with several demographic variables, such as BMI and SES. To this end, men and women living in larger bodies had a higher probability of being placed in a class characterized by higher probabilities of weight talk exposure across multiple sources (e.g., peers, mother) and multiple forms of weight talk (e.g., self-, listener-directed). Moreover, individuals with a lower BMI had a higher probability of membership in a class characterized by low probabilities of weight talk exposure across multiple sources. Together, these findings suggest that individuals living in larger bodies experience more weight talk relative to individuals living in smaller bodies. Additionally, men in a class characterized by high probabilities of weight talk exposure across multiple sources reported lower SES related to men places in other weight talk classes. This suggests that SES may be uniquely associated with weight talk exposure patterns among men and thus more research in this area is necessary to further explore the association between SES and weight talk exposure among men.

The present study revealed several gender differences. For instance, women reported higher rates of self-directed weight talk (“My friend talks about their own weight”) from their peers relative to men, suggesting that weight talk may be more common among female friend groups. Moreover, women reported higher rates of self-, listener- and other-directed weight talk from mothers, whereas men reported higher rates of listener-directed weight talk from mothers with a specific focus on dieting. Thus, while women were exposed to various forms of weight talk from their mothers, the conversations focus more broadly on weight (“My mother talks to me about my weight”). In contrast, men more commonly reported weight-loss focused weight talk from their mother (“My mother encourages me to diet)”. It is possible that weight talk from mothers is more common among men living in larger bodies. Thus, women may be exposed to weight talk more from their mothers regardless of their body shape, whereas men may be exposed to parental weight talk under specific circumstances (e.g., contingent upon their body shape). Interestingly, there were no significant gender differences in the prevalence of weight talk exposure from fathers, suggesting that fathers may approach weight-related conversations with their children in similar ways, regardless of their child’s gender. This finding is consistent with past research that suggests the purpose of parental weight talk may differ between mothers and fathers (Berge et al., 2016) and thus future research should examine the content and impact of weight-related conversations between fathers and young adult children.

In support of the study hypotheses, gender differences in weight talk patterns were also identified. Specifically, a unique class emerged among women, characterized by a high probability of exposure to weight talk from parents, whereas such a class did not emerge among young adult men. This finding suggests that women experience more heterogeneity in patterns of weight talk exposure than do men, particularly with regard to the probability of experiencing weight talk from parents. Finally, the association between weight talk class membership and UWCBs differed by gender, which provides additional support for the study hypotheses. Specifically, women who experienced weight talk from their parents reported a higher frequency of less extreme UWCBs whether or not they also experienced peer weight talk. In contrast, men who experienced weight talk from their peers reported a higher frequency of less extreme UWCBs, regardless of whether they also experienced weight talk from their parents. In both of these examples, the results were influenced by BMI. To this end, it is possible that parental weight talk is more harmful among women living in larger bodies, whereas peer weight talk may be more harmful among men living in larger bodies.

The results from the present study suggest that parental weight talk may be particularly important when considering extreme UWCBs among women. To this end, extreme UWCB scores were highest among women who had a high probability of experiencing weight talk from their parents but not their peers. Moreover, no significant differences in BMI were observed between the parental weight talk exposures class and the multi-source weight talk exposures class. Therefore, observed associations do not simply indicate that higher weight young adults are more likely to engage in UWCBs as well as experience weight talk from their parents, but rather suggest that the weight talk from parents itself may be harmful. Notably, rates of extreme UWCBs did not differ among women in the minimal weight talk exposure class and women in the peer weight talk exposures class. Similarly, women in the peer weight talk exposures class exhibited a weaker association with less extreme UWCBs relative to the other two classes characterized by high probabilities of weight talk exposure. Weaker associations observed for this class may be due in part to the pervasiveness of weight talk among female peers as a social norm, such that the present study may be tapping into “fat talk” among female social groups (Shannon & Mills, 2015). Young adult women exposed to weight talk from peers but not from parents may internalize the weight talk to a lesser extent as a result of its perceived normalization. Consistent with this idea, young adult women in the minimal weight talk exposures class and the peer weight talk exposures class did not significantly differ on BMI in the present study, suggesting that young adult women in the peer weight talk exposures class may experience weight talk from peers more as a result of social norms than as a result of more serious concerns about weight.

Among men, there were no differences in extreme UWCBs across patterns of weight talk exposure, which is likely the result of generally low endorsement of such behaviors. However, men in the multi-source weight talk exposure and the peer weight talk exposures classes reported higher rates of less extreme UWCBs relative to men in the minimal weight talk exposures class, suggesting that the influence of peer weight talk on less extreme UWCBs is similar to the influence of multi-source weight talk among men. One possible explanation of the present findings is that the gendered bias of the weight talk measures included in the present study may resulted in the assessment of a more severe form of weight talk among male social groups relative to a more of a pervasive social norm in female social groups. Specifically, “muscle talk” among male peer groups may be more comparable to weight talk among female peer groups, yet muscle talk was not measured in the present study. Moreover, in the present study, we were unable to distinguish between positively and negatively framed weight talk. Empirical research testing the influence of positively and negatively framed weight talk has found inconsistent results (Calogero et al., 2009; Eisenberg et al., 2017). Yet, to the best of our knowledge, studies have not yet examined the differential relationship between positively and negatively framed weight talk exposure across a diverse set of sources (e.g., peers, parents) among men. Another possible explanation of the present findings is that young adult men may be more likely to be exposed to positively framed weight talk from their parents, but negatively framed weight talk from their peers. Future research should identify patterns of weight talk exposure across various sources (e.g., parents, peers, work), types (e.g., self-, listener-, or other-directed), and framing (e.g., positive, negative) and their associations with UWCBs to deconstruct these relations.

Strengths and Limitations

The present study included several strengths and limitations. One strength of this study includes the comprehensive approach to measuring weight talk exposures across types and sources with the use of latent class analysis. Other strengths include the racially/ethnically diverse sample of men and women and the inclusion of both mothers and fathers as sources of weight talk. One limitation of the study was the inability to distinguish between positive and negative weight talk, as well as fat talk and muscle talk, each of which may vary by gender and differentially relate to UWCBs. As such, future research should seek to identify patterns of positive weight talk and negative weight talk by source and form and their associations with UWCBs among males and females. Additionally, while dichotomized variables are common in LCA analyses, dichotomizing the variables may result in a loss of sensitivity with regard to group differences in the frequency of weight talk exposure across groups. Moreover, the present study used cross-sectional data with retrospectively reported UWCBs and thus the temporality of the relationships cannot be established. Additionally, each of the weight talk forms were measured with single items and some measures had only adequate test-retest reliability (i.e., test-test agreement 70-79%). The study did not control for the relationships between parental figures and participants or the relationship between parental figures. Other limitations of the study include the inability to examine weight talk patterns in gender diverse populations due to the limited number of such participants in the sample (n=9), suggesting that future research should test the associations between weight talk exposures and eating pathology in gender diverse samples. Another limitation is the cross-sectional nature of the study, which prevents interpretation of the directionality of the identified relationships.

Implications

The present study applied a person-centered approach to explain the associations between weight talk and UWCBs. The results provide further evidence of the consequences of parental weight talk and suggests that health care providers should discuss the potential harms of weight talk with parents to reduce rates of exposure. Moreover, healthcare providers may consider discussing with parents the harmful effects that parental weight talk can have on children’s eating behaviors, while also discussing non-detrimental ways to approach weight-related conversations, such as focusing on healthy behaviors (e.g., physical activity) for the sake of health, rather than placing the emphasis on weight. In these conversations, providers should aim to raise parental awareness of what constitutes weight talk, its implications, and how to limit its use throughout their children’s lives, from childhood through adulthood. Healthcare providers should focus on non-detrimental ways to talk about health behaviors (e.g., engaging in physical activity) and nutritional guidelines, such as recommendations pertaining to fruit and vegetable consumption, rather than focusing explicitly on weight. Weight talk may also be an important target in preventive interventions for eating disorders, particularly as it relates to the internalization of idealized body shapes and UWCBs (Berge et al., 2013; Eisenberg et al., 2011; Bauer et al., 2013). For instance, the Healthy School-Healthy Kids school-based universal prevention program that targets sociocultural processes contributing to anti-fat attitudes, including weight talk (McVey et al., 2007), has been associated with reductions in internalization of body ideals and UWCBs among males and females. The Body Project is another example of an intervention that targets weight talk (Stice & Presnell, 2007), and evidence indicates that participation in the Body Project is associated with decreases in family weight talk (Vanderkruik et al., 2020). Because many young adult men and women experienced weight talk across multiple sources, interventions seeking to reduce prevalence of UWCBs among men and women should focus efforts on multiple close relationships. Specifically, interventions should aim to reduce parental and peer engagement in weight talk. Additional efforts may be made to reduce the negative harms of weight talk exposure among young adults to help diminish the effects of weight talk. More broadly, the results from the present study suggest that society-wide campaigns should aim to reduce the pervasiveness of weight talk. Such efforts may seek to build a more supportive culture that is less focused on weight and more focused on participating together in healthy behaviors while forging meaningful interpersonal connections.

The present study highlights the salience of weight talk patterns that include parents as a source in predicting young adult use of UWCBs. While some parental weight talk may be well intentioned, parents should know that parent-child weight-related conversations could be harmful even after their children have entered adulthood. These findings build upon previous research and indicate that parental weight talk may have long lasting effects on young adult eating behaviors. Future research would benefit from examining patterns of weight talk and their influence on UWCBs longitudinally to gain a deeper understanding of the temporality of these relationships.

Highlights.

  • Weight talk exposure is pervasive among young adults

  • Weight talk is associated with higher rates of unhealthy weight control behaviors

  • Men and women were exposed to parental and peer weight talk to varying degrees

  • The association between weight talk and unhealthy weight control differed by gender

Acknowledgments

Declaration of funding: Research is supported by grant numbers grant numbers R35HL139853(PI: D. Neumark-Sztainer) and R01HL116892 (PI: D. Neumark-Sztainer) from the National Heart, Lung, and Blood Institute, as well as T32MH082761 (PI: Scott Crow) from the National Institute of Mental Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung and Blood Institute, National Institute of Mental Health, or the National Institutes of Health.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Conflict of Interest: All authors declare that they have no conflict of interest.

References

  1. Ahlich E, Choquette EM, & Rancourt D (2019). Body talk, athletic identity, and eating disorder symptoms in men. Psychology of Men & Masculinities, 20(3), 347–355. 10.1037/men0000168 [DOI] [Google Scholar]
  2. Arroyo A, & Harwood J (2012). Exploring the causes and consequences of engaging in fat talk, Journal of Applied Communication Research, 40(2), 167–187. 10.1080/00909882.2012.654500 [DOI] [Google Scholar]
  3. Bauer KW, Bucchianeri MM, & Neumark-Sztainer D (2013). Mother-reported parental weight talk and adolescent girls ’ emotional health , weight control attempts , and disordered eating behaviors. Journal of Eating Disorders, 1, 45. http://doi.org/0.1186/2050-2974-1-45 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Berge JM, Christoph MJ, Winkler MR, Miller L, Eisenberg ME, & Neumark-Sztainer D (2019). Cumulative encouragement to diet from adolescence to adulthood : Longitudinal associations with health, psychosocial well-Being, and romantic relationships. Journal of Adolescent Health, 65(5), 690–697. 10.1016/j.jadohealth.2019.06.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Berge JM, Hanson C, Rowley S, MacLehose R, & Neumark-Sztainer D (2016). Do parents or siblings engage in more negative weight-based talk with children and what does it sound like?: A mixed-methods study. Body Image, 18, 27–33. 10.1016/j.bodyim.2016.04.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Berge JM, MacLehose R, Loth KA, Eisenberg M, Bucchianeri MM, & Neumark-Sztainer D (2013). Parent conversations about healthful eating and weight associations with adolescent disordered eating behaviors. JAMA Pediatrics, 167(8), 746–753. 10.1001/jamapediatrics.2013.78 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Berge JM, Pratt K, & Miller L (2016). Weight conversations in romantic relationships: What do they sound like and how do partners respond? Families, Systems and Health, 34(3), 213–220. 10.1037/fsh0000223 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Calogero RM, Herbozo S, & Thompson JK (2009). Complimentary wweightism: The potential costs of appearance-related commentary for women’s self-objectification. Psychology of Women Quarterly, 33(1), 120–132. [Google Scholar]
  9. Eisenberg ME, Berge J, Fulkerson JA, & Neumark-Sztainer D (2011). Weight Comments by Family and Significant Others in Young Adulthood. Body Image, 9(1), 12–19. 10.1016/j.bodyim.2010.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Eisenberg ME, Berge JM, Fulkerson JA, & Neumark-Sztainer D (2012). Associations between hurtful weight-related comments by family and significant other and the development of disordered eating behaviors in young adults. Journal of Behavioral Medicine, 35(5), 500–508. 10.1007/s10865-011-9378-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Eisenberg ME, Franz R, Berge JM, Loth KA, & Neumark-Sztainer D (2017). Significant others’ weight-related comments and their associations with weight-control behavior, muscle-enhancing behavior, and emotional well-being. Families, Systems and Health, 35(4), 474–485. 10.1037/fsh0000298 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Engeln R, Sladek MR, & Waldron H (2013). Body talk among college men: Content, correlates, and effects. Body Image, 10(3), 300–308. 10.1016/j.bodyim.2013.02.001 [DOI] [PubMed] [Google Scholar]
  13. Forney KJ, Holland LA, & Keel PK (2012). Influence of peer context on the relationship between body dissatisfaction and eating pathology in women and men. International Journal of Eating Disorders, 45, 982–989. 10.1002/eat.22039 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gutman LM, Sameroff AJ (2004). Continuities in depression from adolescence to young adulthood: Contrasting ecological influences. Development and Psychopathology, 16, 967–984. 10.1017/S095457940404009X [DOI] [PubMed] [Google Scholar]
  15. Haynos AF, Wall MM, Chen C, Wang SB, Loth K, & Neumark-Sztainer D (2018). Patterns of weight control behavior persisting beyond young adulthood: Results from a 15-year longitudinal study. International Journal of Eating Disorders, 51(9), 1090–1097. 10.1002/eat.22963 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Herbozo S, & Thompson JK (2006). Development and validation of the verbal commentary on physical appearance scale: Considering both positive and negative commentary. Body Image, 3(4), 335–344. 10.1016/j.bodyim.2006.10.001 [DOI] [PubMed] [Google Scholar]
  17. Herbozo S, Stevens SD, Moldovan CP, & Morrell HER (2017). Positive comments, negative outcomes? The potential downsides of appearance-related commentary in ethnically diverse women. Body Image, 21, 6–14. 10.1016/j.bodyim.2017.01.008 [DOI] [PubMed] [Google Scholar]
  18. Larson NI, Wall MM, Story MT, & Neumark-Sztainer D (2013). Home/family, peer, school, and neighborhood correlates of obesity in adolescents. Obesity, 21(9), 1858–1869. 10.1002/oby.20360.Home/family [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Larson RW, Richards MH, Moneta G, Holmbeck G, & Duckett R (1996). Changes in adolescents’ daily interactions with their families from ages 10 to 18: Disengagement and transformation. Developmental Psychology, 32(4), 744–754. 10.1037/0012-1649.32.4.744 [DOI] [Google Scholar]
  20. Lin L, Flynn M, & Roberge A (2019). Hearing vs. engaging in negative body talk: An examination of adult men. Eating Disorders, 27(6), 538–549. 10.1080/10640266.2018.1560851 [DOI] [PubMed] [Google Scholar]
  21. Little R (1986). Survey nonresponse adjustments for estimates of means. International Statistical Review, 54(2), 139–157. [Google Scholar]
  22. Lo BY, Mendell NR, & Rubin DB (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767–778. 10.1093/biomet/88.3.767 [DOI] [Google Scholar]
  23. Maas MK, Bray BC, & Noll JG (2019). Online sexual experiences predict subsequent sexual health and victimization outcomes among female adolescents: A latent class analysis, Journal of Youth and Adolescence, 48, 837–849. 10.1007/s10964-019-00995-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Mayer-Brown S, Lawless C, Fedele D, Dumont-Driscoll M, & Janicke DM (2016). The effects of media, self-esteem, and BMI on youth’s unhealthy weight control behaviors. Eating Behaviors, 21, 59–65. 10.1016/j.eatbeh.2015.11.010 [DOI] [PubMed] [Google Scholar]
  25. McCabe MP, & Ricciardelli LA (2005). A prospective study of pressures from parents, peers, and the media on extreme weight change behaviors among adolescent boys and girls, Behaviour Research and Therapy, 43(5), 653–668. 10.1016/j.brat.2004.05.004 [DOI] [PubMed] [Google Scholar]
  26. McVey G, Tweed S, & Blackmore E (2007). Healthy Schools-Healthy Kids: A controlled evaluation of a comprehensive universal eating disorder program. Body Image, 4(2), 115–136. 10.1016/j.bodyim.2007.01.004 [DOI] [PubMed] [Google Scholar]
  27. Mitchison D, Hay P, Slewa-Younan S, & Mond J (2012). Time trends in population prevalence of eating disorder behaviors and their relationship to quality of life. PLoS One, 7, e48450. 10.1371/journal.pone.0048450 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Muthén LK, & Muthén BO (2011). Mplus User’s Guide. Los Angeles, CA. [Google Scholar]
  29. Nagata JM, Garber AK, Tabler J, Murray SB, Vittinghoff E, & Bibbins-Domingo K (2018). Disordered eating behaviors and cardiometabolic risk among young adults with overweight or obesity. International Journal of Eating Disorders, 51(8), 931–941. 10.1002/eat.22927 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Neumark-Sztainer D, Bauer KW, Friend S, Hannan PJ, Story M, & Berge JM (2010). Family weight talk and dieting: How much do they matter for body dissatisfaction and disordered eating behaviors in adolescent girls? Journal of Adolescent Health, 47(3), 270–276. 10.1016/j.jadohealth.2010.02.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Neumark-Sztainer D, Croll J, Story M, Hannan PJ, French SA, & Perry C (2002). Ethnic/racial differences in weight-related concerns and behaviors among adolescent girls and boys: findings from Project EAT. Journal of Psychosomatic Research, 53(5), 963–974. 10.1016/S0022-3999(02)00486-5 [DOI] [PubMed] [Google Scholar]
  32. Neumark-Sztainer D, Hannan PJ, Story M, Croll J, & Perry C (2003). Family meal patterns: associations with sociodemographic characteristics and improved dietary intake among adolescents. Journal of the American Dietetic Association, 103(3), 317–322. 10.1053/jada.2003.50048 [DOI] [PubMed] [Google Scholar]
  33. Neumark-Sztainer D, Wall M, Guo J, Story M, Haines J, & Eisenberg M (2006). Obesity, disordered eating, and eating disorders in a longitudinal study of adolescents: How do dieters fare 5 years later? Journal of the American Dietetic Association, 106(4), 559–568. 10.1016/j.jada.2006.01.003 [DOI] [PubMed] [Google Scholar]
  34. Neumark-Sztainer D, Wall MM, Larson NI, Eisenberg ME, & Loth K (2011). Dieting and disordered eating behaviors from adolescence to young adulthood: findings from a 10-year longitudinal study. Journal of the American Dietetic Association, 111(7), 1004–1011. 10.1016/j.jada.2011.04.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Neumark-Sztainer D, Wall MM, Larson N, Story M, Fulkerson JA, Eisenberg ME, & Hannan PJ (2012). Secular trends in weight status and weight-related attitudes and behaviors in adolescents from 1999 to 2010. Preventive Medicine, 54(1), 77–81. 10.1016/j.ypmed.2011.10.003.Secular [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Nylund KL, Asparouhov T, & Muthén BO (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14(4), 535–569. 10.1080/10705510701575396 [DOI] [Google Scholar]
  37. Nylund K, Bellmore A, Nichina A, & Graham S (2007). Subtypes, severity, and structural stability of peer victimization: What does latent class analysis say? Child Development, 78(6), 1706–1722. 10.1111/j.1467-8624.2007.01097.x [DOI] [PubMed] [Google Scholar]
  38. Paxton SJ, Schutz HK, Wertheim EH, & Muir SL (1999). Friendship clique and peer influences on body image concerns, dietary restraint, extreme weight-loss behaviors, and binge eating in adolescent girls. Journal of Abnormal Psychology, 108(2), 255–266. 10.1037/0021-843X.108.2.255 [DOI] [PubMed] [Google Scholar]
  39. Rodgers RF, Faure K, & Chabrol H (2009). Gender differences in parental influences on adolescent body dissatisfaction and disordered eating. Sex Roles, 61, 837–849. 10.1007/s11199-009-9690-9 [DOI] [Google Scholar]
  40. Schaefer LM, Burke NL, Thompson JK, Dedrick RF, Heinberg LJ, Calogero RM,… Paxton SJ (2015). Development and validation of the sociocultural attitudes towards appearance questionnaire-4 ( SATAQ-4 ). Psychological Assessment, 27(1), 54–67. 10.1037/a0037917 [DOI] [PubMed] [Google Scholar]
  41. Shannon A, & Mills JS (2015). Correlates, causes, and consequences of fat talk: A review. Body Image, 15, 158–172. 10.1016/j.bodyim.2015.09.003 [DOI] [PubMed] [Google Scholar]
  42. Smolak L, & Stein JA (2006). The relationship of drive for muscularity to sociocultural factors, self-esteem, physical attributes, gender roles, and social comparison in middle school boys, Body Image, 3, 121–129. 10.1016/j.bodyim.2006.03.002 [DOI] [PubMed] [Google Scholar]
  43. Stice E, & Presnell K (2007). The Body Project: Promoting Body Acceptance and Preventing Eating Disorders. New York, NY, US: Oxford University Press. [Google Scholar]
  44. Stice E, Gau JM, Rohde P, & Shaw H (2017). Risk factors that predict future onset of each DSM-5 eating disorder: predictive specificity in high-risk adolescent females, Journal of Abnormal Psychology, 126(1), 28–51. 10.1037/abn0000219 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Story MA, French SA, & Blum RW (1994). Ethnic/racial and socioeconomic differences in dieting behaviors and body image perceptions in adolescents. International Journal of Eating Disorders, 18(2), 173–179. 10.1002/1098-108X(199509)18:2<173::AID-EAT2260180210>3.0.CO;2-Q [DOI] [PubMed] [Google Scholar]
  46. Thompson JK, Heinberg LJ, Altabe M, & Tantleff-Dunn S (1999). Exacting Beauty: Theory, Assessment, and Treatment of Body Image Disturbance: American Psychological Association. [Google Scholar]
  47. Thompson JK & Stice E (2001). Thin-ideal internalization: Mounting evidence for a new risk factor for body-image disturbance and eating pathology, Current Directions in Psychological Science, 10, 181–183. 10.1111/1467-8721.00144 [DOI] [Google Scholar]
  48. Thullen MJ, Taliaferro LA, & Muehlenkamp JJ (2016). Suicide ideation and attempts among adolescents engaged in risk behaviors: a latent class analysis. Journal of Research of Adolescence, 26(3), 587–594. 10.1111/jora.12199 [DOI] [PubMed] [Google Scholar]
  49. Tremblay L, & Lariviere M (2009). The influence of puberty onset, Body Mass Index, and pressure to be thin on disordered eating behaviors in children and adolescents. Eating Behaviors, 10(2), 75–83. 10.1016/j.eatbeh.2008.12.001 [DOI] [PubMed] [Google Scholar]
  50. Vanderkruik R, Conte I, & Dimidjian S (2020). Fat talk frequency in high school women: Changes associated with participation in the Body Project. Body Image, 34, 196–200. 10.1016/j.bodyim.2020.06.002 [DOI] [PubMed] [Google Scholar]
  51. Vincent MA, & McCabe MP (2000). Gender differences among adolescents in family, and peer influences on body dissatisfaction, weight loss, and binge eating behaviors. Journal of Youth and Adolescence, 29(2), 205–221. 10.1023/A:1005156616173 [DOI] [Google Scholar]

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