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. Author manuscript; available in PMC: 2022 Mar 1.
Published in final edited form as: Body Image. 2020 Dec 23;36:214–217. doi: 10.1016/j.bodyim.2020.12.001

Body Surveillance as a Prospective Risk Factor for Depressive Symptoms in Low-Income Adolescent Girls from the United States

Stephanie Milan 1, Sophia Dominguez Perez 1
PMCID: PMC7987769  NIHMSID: NIHMS1657582  PMID: 33360478

Abstract

Adolescent girls who engage in frequent self-objectification often report a greater number of depressive symptoms. Although concurrent associations between self-objectification and depression are well-documented, it is less clear if objectification contributes to the course of symptoms. The current study examined: (a) whether body surveillance is prospectively related to depressive symptoms over a 1-month period in a sample of 150 low-income adolescent girls in the United States, and; (b) whether receiving certain types of weight-relevant information (i.e., learning one’s weight is much higher than estimated) moderates this association. Heightened body surveillance at baseline predicted greater symptom severity one month later, but the strength of this relationship depended on what type of weight information girls received. Among girls high in body surveillance, those who found out their actual weight was much higher than they estimated subsequently reported more severe depressive symptoms; those who learned their actual weight was consistent or lower than they estimated reported fewer depressive symptoms. For girls low in body surveillance, weight-relevant information was not significantly related to the subsequent severity of depressive symptoms. Findings highlight the potential utility of assessing and addressing heightened body surveillance in depression interventions for adolescent girls.

Keywords: self-objectification, body surveillance, depression, adolescent, weight

1. Introduction

According to objectification theory (Fredrickson & Roberts, 1997), girls and women are often viewed and treated by others as objects or collections of body parts. These pervasive experiences lead girls and women to adopt an outsider’s perspective on their body, in which they focus on physical appearance more than physical functioning. Women who engage in frequent self-objectification, as indicated by more habitual body surveillance, are at increased risk for mental health problems (e.g., Jones & Griffiths, 2015; Tiggemann & Williams, 2012). The negative impact of self-objectification on mental health may start early. In Hyde and colleagues’ (2008) biopsychosocial model of adolescent depression, body surveillance is posited as a key causal factor for the increased prevalence of depression in girls and women that emerges during the teenage years and remains evident throughout adulthood.

Consistent with this conceptualization of self-objectification, numerous studies have reported significant correlations between body surveillance and depressive symptoms, with concurrent associations potentially larger for adolescents than adults (for review, see Jones & Griffiths, 2015). However, only a handful of these studies were longitudinal (for review of child and adolescent self-objectification studies, see Daniels et al., 2020). Consequently, the role of body surveillance in the course of depressive symptoms during this developmental period is unclear. Understanding the extent to which body surveillance influences the course of symptoms, rather than simply being a correlate of symptoms at one time-point, can inform the utility of targeting self-objectification processes in interventions with adolescent girls.

Although causality can only be established in experimental studies, evidence of certain conditions would support the potential role of body surveillance as a mechanism contributing to adolescent depression. These conditions include: demonstrating temporality through longitudinal designs, establishing dose-response effects, and elaborating plausibility through hypotheses about how an assumed mechanism actually works (Kendler, 2014). With this in mind, the first objective of this study was to test whether body surveillance is prospectively related to increases in depressive symptom severity over a 1-month period. Significant results would provide support for temporality and gradient associations between body surveillance and depressive symptoms in adolescence. Consistent with objectification theory, we hypothesized that higher body surveillance at baseline would predict greater depression symptom severity one month later, after controlling for baseline depression. We focused on body surveillance rather than other aspects of self-objectification (e.g., body shame) given evidence that body surveillance is more amenable to change through interventions (e.g., Kilpela et al., 2017).

The second objective of this study was to explore how heightened body surveillance might contribute to depressive symptoms among adolescent girls. Rosser et al. (2010) found that young adults with heightened appearance concerns showed attentional and interpretational biases towards appearance-related stimuli compared to peers. Relatedly, Moya-Garofano and Moya (2019) found that young women experimentally manipulated to focus on their body showed a subsequent increase in contingent self-worth and body shame; the same change was not evident in women who focused on their personalities. These findings suggest that individuals higher in body surveillance may have cognitive biases leading them to process appearance-related information in more negative ways, and that exposure to appearance-related information may have greater impact on their subsequent self-regard and emotional well-being. Similar biases in processing weight-related information may occur for adolescent girls, contributing to their risk for depression.

We explore this possibility by testing whether the relation between body surveillance and subsequent depressive symptoms is moderated by weight-relevant information, specifically information about the discrepancy between one’s actual weight and estimated weight. We hypothesized that for girls high in body surveillance, those who learn they weigh more than they thought will report greater symptom severity one month later compared to girls high in body surveillance who learn their actual weight is consistent with or less than estimated. In contrast, for girls low on body surveillance, different weight-relevant information will not have implications for subsequent depression. This pattern of results would provide additional support of heightened body surveillance as a potential mechanism in the course of depressive symptoms by elaborating specific conditions for risk processes (i.e., heightened body surveillance is associated with more depressive symptoms only when girls receive negative weight-relevant information).

2. Method

2.1. Participants

Participants included 150 adolescent girls residing in a midsized, economically depressed city in the Northeast United States whose families were participating in an NIH-funded study on health disparities. Adolescent girls in 9th to 10th grades residing with a female caregiver were eligible for participation. The average age was 15.22 years (SD = 1.01; Range = 13–17), with 54.7% identifying as Latina, 24.3% as African American/Black, and 20.9% as non-Hispanic, White. Among mothers, 10.1% had education beyond high school and 34.5% were living with the adolescent’s biological father. Most families (89.5%) received subsidized school lunch, indicating family income below 130% of the national poverty rate.

2.2. Measures

2.2.1. Demographic.

Mothers provided information on age, marital status, family size, race/ethnicity, education, and socioeconomic factors.

2.2.2. Body mass index (BMI).

Participants were weighed without shoes to the nearest 0.1 pound using a digital scale (BT-350e; Tanita, Arlington Heights, IL). Height was measured to the nearest 0.25 inch using a height rod on a standard spring scale. Weight and height were converted to body mass index (BMI) as kg/m2. BMI was used as a covariate to control for differences in actual weight.

2.2.3. Weight-discrepant information.

At the interview start, adolescents were asked to guess their current height and weight. At interview completion, adolescents were weighed as described above. The examiner said the weight aloud to the adolescent and then recorded the weight directly from the scale. The difference between adolescents’ estimated and actual weight was used as an indicator of “weight-discrepant information,” with positive numbers indicating an actual weight higher than the estimated weight (i.e., the adolescent underestimated).

2.2.4. Body surveillance.

The Objectified Body Consciousness Scale–Youth Version (OBCS; Lindberg et al., 2006) body surveillance subscale was used to measure the tendency to habitually engage in body checking and thinking about one’s appearance (sample item: “During the day, I think about how I look many times”). Items were rated on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree), with higher scores indicating more body surveillance (ω = .83, 95% CI = .77, .87).

2.2.5. Depressive symptoms.

Adolescents completed the Adolescent Psychopathology Scale (APS; Reynolds, 1998) Major Depression subscale, which includes 13 items evaluating depressive symptoms based on the Diagnostic and Statistical Manual of the American Psychiatric Association (DSM-IV). Responses range from 0 (almost never) to 2 (nearly every day) based on symptoms over the last two weeks (ω = .90, 95% CI = .86, .92).

2.3. Procedures

Procedures were approved by the University of Connecticut Institutional Review Board. Participants were recruited from schools, community agencies, media outlets, and word-of-mouth between 2010 and 2014. Interviews were conducted in English and Spanish based on participant preference1. Mothers and daughters gave consent and then completed a semi-structured interview and computer-based survey in separate rooms. Afterwards, participants had their height and weight measured in a private hallway and were informed aloud of their weight. At completion, families were compensated $80 and provided information on community resources. A subset of families (79.9% of all families) participated in a follow-up phone interview four weeks later. The follow-up was added four months after study initiation, excluding the first 20 participants from eligibility. Of participants recruited after the follow-up began (n = 174), six families declined and 13 were unable to be reached after multiple attempts. Nonparticipants did not differ from participants on demographic characteristics or baseline symptoms.

2.4. Data Analytic Plan

Hayes (2018) PROCESS was used with SPSS 26 to test whether body surveillance and weight-discrepant information predicted depressive symptoms at 1-month follow-up, controlling for baseline depression and BMI. In Grabe and colleagues’ (2007) study of self-objectification and depressive symptoms, the longitudinal effect size was f2 = .054. Using this as a critical effect size for regression, a sample of 150 provides sufficient statistical power (1 – β = .80) at α = .05.

3. Results

At baseline, 12.7% of girls were above the cutoff for clinically elevated depressive symptoms on the APS. The average BMI was 25.23 kg/m2 (SD = 5.91), with 22.1% categorized as overweight and 21.4% as obese based on Center for Disease Control guidelines. The mean discrepancy between self-reported and actual weight was 8.20 (SD = 14.41), indicating that on average girls underestimated their weight by about eight pounds. Depressive symptoms and body surveillance were positively correlated at baseline, r = .48, p < .001. Body surveillance was not significantly correlated with BMI, r = −.01, p = .998, or weight discrepancy, r = −.03, p = .763. Similarly, depressive symptoms had nonsignificant relationships with BMI, r = −.04, p = .660, and weight discrepancy, r = −.02, p = .817. BMI and weight-discrepancy were highly correlated, r = .60, p <.001, such that adolescents with higher BMIs also gave greater underestimates of their weight.

Hierarchical regression was used to test whether body surveillance predicted depressive symptoms in Time 2, beyond symptoms at Time 1 and BMI, and whether this association was moderated by weight-discrepancy information. As shown in Table 1, the overall model was significant, with body surveillance and the body surveillance x weight-discrepant information interaction significantly predicting Time 2 depressive symptoms. Post hoc probing of the interaction (Figure 1) indicated that the extent to which body surveillance predicted depressive symptoms at Time 2 depended on the nature of weight-related information. The predictive relationship was strongest among girls who learned their actual weight was numerically much greater than they had estimated. Among girls who engaged in the most frequent body surveillance at baseline, depressive symptoms at follow-up were elevated for girls who learned their actual weight was greater than estimated, but not for girls who received weight information consistent or below their estimated weight.2

Table 1.

Hierarchical regression predicting depressive symptoms at Time 2 from body surveillance and weight-discrepant information at Time 1, controlling for body mass index (BMI) and Time 1 depressive symptoms (n = 150)

Predictors: B
(95% CI)		 β t p Model F,
Adjusted R2
Body Mass Index (BMI) −.12
(−.31, .08)		 −.10 1.19 .233
Depressive Symptoms T1 .35
(.16, .55)		 .30 3.54 .001
Body Surveillance T1 .72
(.07, 1.36)		 .19 2.20 .030
Weight Discrepancy T1 .04
(−.04, .12)		 .10 1.07 .294
Body Surveillance x Weight Discrepancy .04
(.00, .08)		 .16 2.05 .041
Overall Model F(5, 144) = 8.20,
p < .001, Adj. R2 = .20
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Figure 1.

Figure 1.

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Post hoc probing of interaction between body surveillance and weight-discrepant information on Time 2 depressive symptoms, controlling for Time 1 depressive symptoms and body mass index (N = 150)

Note. Values in the figure reflect unstandardized coefficients and standard errors from simple slopes. *** p < .001, *p < .05, ns = not significant (p = .722).

4. Discussion

In a sample of low-income, adolescent girls in the United States, we found that body surveillance was prospectively related to depressive symptoms over a 1-month period. These findings align with Hyde et al.’s (2008) model of adolescent depression, which posits body objectification as a key cognitive vulnerability factor for depression among teenage girls. Our findings are consistent with other studies showing that heightened body objectification may have negative mental health implications for adolescent girls from various racial/ethnic and economic backgrounds (Daniels et al., 2020). The current findings also suggest that body surveillance may be a mechanism contributing to the course of depressive symptoms for at least some adolescent girls, rather than simply a concurrent correlate of symptom severity.

While body surveillance emerged as a significant predictor of subsequent depressive symptoms, the strength of the predictive relationship depended on the type of weight-related information participants received. Adolescents who were high in body surveillance and heard their actual weight was higher than they initially estimated reported the greatest depressive symptom severity at Time 2. This finding is also consistent with Hyde et al.’s (2008) biopsychosocial model, in which heightened body surveillance is a cognitive mechanism that interacts with environmental factors to increase depression risk in adolescent girls. From this perspective, cognitive vulnerabilities like habitual body surveillance lead to depression only in certain circumstances, such as when girls are exposed to negative appearance-related information about themselves. Because most adolescent girls in the United States are exposed to constant appearance-related information via social media (Rodgers, 2016), the mental health impact of habitual body surveillance may be heightened for today’s youth. This may be one factor in the rising prevalence of mood disorders among adolescents (Twenge et al., 2019).

Our findings highlight the potential utility of targeting heightened body surveillance in interventions with adolescent girls, although treatment outcome trials are needed to establish any causal role. Currently, there are surprisingly few evidence-based treatments for depression that explicitly focus on body objectification, despite longstanding theoretical speculation on its importance to women’s mental health. Body objectification has been targeted in eating disorder interventions (e.g., Kilpela et al., 2017) and standalone body image programs (Jarry & Berardi, 2004), but has generally not been included in manuals or modules for adolescent depression. Given relations to eating disorders, depression, and self-harm (Erchull et al., 2013), body surveillance may be an important transdiagnostic factor that should be assessed and addressed more systematically in mental health treatment. For example, intervention strategies that include mindfulness or self-compassion may be beneficial in reducing the negative impact of body surveillance in adolescents given success with adult women (Wollast et al., 2019).

Several study limitations should be noted. First, there is some evidence that the relation between body surveillance and body image differs by race/ethnicity (e.g., Schaefer et al., 2018). The current sample does not provide sufficient power to examine research questions within the different racial/ethnic groups. Second, several mechanisms of influence are possible. For example, higher body surveillance may have led to differential attending, interpreting, or recollecting of weight-relevant information. Because understanding body surveillance was not a primary purpose of the original study, we do not have data to help discern the actual ways weight-relevant information may have influenced girls who engaged in high body surveillance. Relatedly, it is possible that body surveillance is a proxy for other risk factors, and may no longer predict the course of depressive symptoms once these factors are considered (Jones & Griffith, 2015). Future research is needed in which self-objectification is examined in relation to other known risk factors for adolescent depression (e.g., rumination).

Finally, because aspects of the study (e.g., girls hearing their weight from the research assistant) may have contributed to increased depressed mood in a subset of girls, it is important to address ethical issues. As part of the study, all families were provided with information about community mental health resources, and all girls were provided with a free 3-month health club membership. In addition, other precautionary steps were taken when girls reported clinically concerning symptoms as indicated in informed consent procedures, including discussion with a parent, assistance with community referrals if requested, and a family follow-up. At both time points, the few girls whose symptom levels warranted these procedures were involved with services or helped to find services.

In sum, these findings provide further support that objectification, and particularly heightened body surveillance, may be a prospective risk factor for depressive symptoms among low-income adolescent girls. The relationship between body objectification and depression in women has been recognized in theoretical models and widely documented in empirical studies. The current findings highlight the potential utility of incorporating body objectification into evidence-based prevention and intervention efforts addressing depression in adolescent girls.

Highlights.

  • We examined if body surveillance (BS) predicts the course of depression symptoms.

  • Girls high in BS reported a greater number of symptoms one month later.

  • The BS-depression relation was moderated by weight-related information.

  • Girls high in BS and told their weight was high reported the most symptoms.

Acknowledgements

This study was funded with support from the National Institutes of Health (NICHD R21HDO65185) to Stephanie Milan. Several research assistants and community collaborators gave invaluable assistance, particularly Kate Zona, Viana Turcios-Cotto, and Jenna Ramirez.

Footnotes

1

Five adolescents completed measures in Spanish. By editorial request, those girls were excluded from analysis because the OBCS has not been validated for Spanish-speaking adolescents.

2

Because girls’ interpretation of weight-discrepant information may depend on whether they receive height-discrepant information, we re-ran analyses using misestimation of height as a covariate and with discrepancy based on BMI rather than pounds. Results were consistent, suggesting that knowing one had “grown taller” did not alter the potential impact of weight information on girls with high body surveillance.

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