Next Article in Journal
Metacognitive Dysfunction in Women with Eating Disorders: A Narrative Review
Previous Article in Journal
Feminine Gender Norms Among Women with Eating Disorders: Findings from an Exploratory Pilot Study
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Women
Volume 6
Issue 1
10.3390/women6010016
women-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Body Dissatisfaction and Eating Disorder Risk Indicators in Older Women: Associations with Medically Supervised Dietary Treatment

by
Patrizia Carmen Marruffi-Bonfante
1,
Manuel Rosety-Rodríguez
1,2,
Alberto Bable-Marruffi
3,
Javier Choquet de Isla
4 and
Javier Riscart-López
1,2,*
1
Department of Medicine, Faculty of Medicine, University of Cádiz, 11003 Cadiz, Spain
2
Salud, Deporte e Inflamación Research Group, Biomedical Research and Innovation Institute of Cádiz (INiBICA), Puerta del Mar University Hospital, University of Cádiz, Plaza Fragela, s/n, 11003 Cadiz, Spain
3
Faculty of Psychology, University of Cádiz, 11510 Cadiz, Spain
4
Department of Human Anatomy and Embryology, Faculty of Medicine, University of Cadiz, 11003 Cadiz, Spain
*
Author to whom correspondence should be addressed.
Women 2026, 6(1), 16; https://doi.org/10.3390/women6010016
Submission received: 5 January 2026 / Revised: 19 February 2026 / Accepted: 24 February 2026 / Published: 26 February 2026
Browse Figure
Versions Notes

Abstract

Body dissatisfaction and eating disorder (ED) risk indicators can persist into later life but are less frequently assessed in routine care for older women. Among women aged 50 years and older, attendance on dietary care pathways in clinical settings may offer a pragmatic opportunity for early identification (screening) of ED risk indicators and related psychological distress, particularly during the menopausal transition. Thus, the aim of this study was to compare body dissatisfaction and ED risk indicators in older women attending dietary treatment versus those not following a dietary regimen. This cross-sectional study compared women aged ≥50 years without a prior ED diagnosis who were receiving medically supervised dietary treatment (DTG; n = 42) with peers not following any dietary regimen (NDG; n = 40) in Cádiz (Spain). Participants completed the Eating Disorder Inventory-3 Referral Form (EDI-3RF), AF-5 Self-Concept Questionnaire, List of Brief Symptoms (LBS-50), and the International Physical Activity Questionnaire (IPAQ) and underwent anthropometric assessment. Compared with those women in the NDG, those in the DTG had a higher body mass index (p = 0.002), higher drive for thinness (p < 0.001) and body dissatisfaction (p < 0.001), lower physical self-concept (p = 0.001), and higher total EDI-3RF scores (p < 0.001). Based on the EDI-3RF, 11.9% of the DTG met clinical referral criteria versus none in the NDG (p = 0.031). These findings indicate that, in this sample of women aged ≥ 50 years, women attending dietary care pathways exhibited a higher ED risk profile, higher psychopathological symptom levels, and lower physical self-concept than women not following a dietary regimen. Given the cross-sectional design, results should be interpreted as associations and may reflect pre-existing differences among women who enter dietary care; nonetheless, dietary care pathways may represent a practical opportunity to incorporate brief screening for body image concerns and ED risk indicators in older women.

1. Introduction

Human development spans distinct life stages, and psychological vulnerability can vary across these periods, including later life. In women, risk for psychological distress and related disorders may vary across hormonally and psychosocially salient periods, including puberty, the premenstrual phase, pregnancy/postpartum, and the menopausal transition [1]. Aging has evolved in the last decades, and now is characterized by a set of attitudes, behaviors, and strategies associated with a permanent concern about weight and body image [2]. Feeling dissatisfied with these changes can also affect the mood and self-esteem of older people, causing body dissatisfaction.
Women aged 50 years and older commonly receive dietary counseling in routine healthcare to address weight management and cardio-metabolic risk. Although these interventions are delivered within the healthcare system and aim to improve physical health, they may also coincide with heightened attention to weight and shape. Therefore, dietary care settings may constitute a pragmatic point for screening of body image concerns and eating disorder (ED) risk indicators in older women, yet this topic remains insufficiently examined. Accordingly, understanding ED risk indicators and their psychological correlates in older women receiving dietary treatment can inform women’s health practice by supporting early detection and prevention within routine dietary care. Women aged 50 years and older may experience heightened body dissatisfaction due to menopausal symptoms, lifestyle factors (e.g., physical inactivity), and age-related changes. Relevant correlates in this life stage include psychological and somatic symptoms (e.g., hot flashes, sleep disturbances), lifestyle factors, and physical inactivity, alongside broader aging-related changes [3,4].
EDs are serious psychiatric conditions characterized by persistent disturbances in eating behaviors, weight-control strategies, and body image, typically driven by an enduring preoccupation with shape and weight [2,5]. Although EDs have long been conceptualized as disorders of adolescence and early adulthood, accumulating evidence indicates that they also affect adults and older women, where they often remain underrecognized and undertreated [6,7,8]. In Spain, the overall prevalence of EDs in the general population has been estimated to be between 4.1% and 6.41% [9], yet epidemiological data specifically focused on women over 50 years remain scarce [8]. In a large web-based survey in the United States, 13% of women over 50 reported current ED symptoms, 60% expressed significant concerns about weight and shape, and 70% were dieting at the time of assessment [10]. Community-based and clinical research in Europe also indicates that older women may present full-syndrome EDs as well as disordered eating and body dissatisfaction, with binge eating and related symptoms being particularly common in this age group [11,12,13,14,15]. However, many affected individuals never enter specialist care, underestimating the real cases [8,14].
From a psychological perspective, body dissatisfaction and drive for thinness are core ED-related risk indicators for EDs that may persist or even arise in midlife and older women [7,16,17]. Previous studies reported that between 60% and 89% of women in midlife experience significant body dissatisfaction, which constitutes an important vulnerability for ED risk in this population [18,19,20]. At the same time, some studies suggest that a subset of older women may display greater resilience to thin-ideal pressures, underscoring heterogeneity in body image experiences in later life [21,22]. Later life is heterogeneous; patterns may differ across the wide age range typically encompassed by the term ‘older women’, making it important to examine women aged ≥50 across a broad span.
Several life course and sociocultural factors may increase ED vulnerability in older women. The menopausal transition has been conceptualized as a critical window, comparable in some respects to adolescence, during which hormonal changes, weight gain, and body shape changes can exacerbate body dissatisfaction and emotional dysregulation [15,23,24]. In addition, midlife and older women are increasingly exposed to sociocultural pressures and appearance-focused content through traditional and social media, with social comparison processes on social networking platforms being associated with bulimic symptoms and restrictive eating in this age group [25,26,27]. Beyond cognitive and sociocultural variables, recent work has emphasized the role of self-conscious emotions, particularly guilt, in the maintenance of maladaptive eating behaviors in adults with EDs [28], suggesting that emotional processes remain clinically relevant in later life. Dieting and behavioral weight management interventions represent another key context for understanding ED risk in adults. A recent systematic review of adults who are overweight or obese indicates that engagement in weight management may be accompanied by increases in ED symptoms in a subset of patients, especially when restrictive dieting, weight-focused goals, and weight stigma are prominent [29]. Among older women, community surveys report high rates of current dieting and weight-control behaviors, often intertwined with long-standing dissatisfaction with weight and shape [10,13,30]. However, most epidemiological studies have not specifically examined women over 50 who are currently receiving medically supervised dietary treatment, nor have they systematically explored how core psychological variables—such as drive for thinness, body dissatisfaction, physical self-concept, and general psychopathological symptoms—relate to ED risk in this context [15,31]. In Spain, this gap is particularly relevant. Existing national data describe overall ED prevalence but provide limited information on older women and virtually none on those engaged in dietary treatment plans in routine medical care [9]. Given population aging and the high prevalence of being overweight, obesity, and metabolic comorbidities in older women, dietary treatment based on structured, Mediterranean-style hypocaloric plans prescribed by physicians is increasingly common in primary care and specialist settings. Yet the potential psychological correlates observed in dietary care contexts—particularly in terms of ED risk and body image disturbance—remain insufficiently documented from a clinical–epidemiological perspective [15,29]. Because referral to dietary care is not random and may reflect pre-existing differences (e.g., higher BMI and weight/shape concerns), dietary treatment is conceptualized here as a clinical context and potential marker for screening rather than a causal risk factor. Accordingly, the present cross-sectional study compared women aged ≥50 years receiving medically supervised dietary treatment with peers not following a dietary regimen, focusing on ED risk indicators and body image-related variables. Specifically, we examined group differences in EDI-3RF risk indicators, drive for thinness, body dissatisfaction, physical self-concept, and general psychopathological symptoms. Based on the previous literature, it was hypothesized that women receiving medically supervised dietary treatment would report higher ED risk indicator values and greater body dissatisfaction than peers not following a dietary regimen within this cross-sectional sample.

2. Results

Table 1 shows the values obtained for both groups, sociodemographic and clinical data, and the difference between groups (DTG vs. NDG). As shown in Table 1, educational level (p = 0.966), social network use (p = 0.567), employment status (p = 0.428), and physical activity level assessed with the IPAQ (p = 0.856) were similarly distributed between the dietary treatment (DTG) and no-diet (NDG) groups. In contrast, the BMI category differed significantly between groups (p = 0.009), with obesity being more frequent in the DTG (54.8%) than in the NDG (22.5%) and normal weight more frequent in the NDG (37.5%) than in the DTG (14.3%). The EDI-3RF clinical referral criterion also differed between groups (p = 0.031), with 11.9% of women in the DTG meeting referral criteria compared with none in the NDG. Finally, in terms of DFT level (EDI-3RF), significant differences between groups (p < 0.001) were observed.
In the present study, BMI was analyzed as a categorical variable (underweight, normal weight, overweight, obesity) rather than being entered as a continuous measure. The main reason is that the relationship between BMI and the probability of belonging to the “No diet/Dietary treatment” group is not necessarily linear; risk does not increase uniformly with each one unit increase in BMI but tends to cluster beyond certain clinical thresholds. By using categories based on widely used cut-off points from the literature, the model better reflects the actual shape of the relationship and avoids imposing a logit-linearity assumption that may not hold.
Table 2 summarizes continuous anthropometric and psychological variables by group (NDG vs. DTG) as mean ± SD and median (IQR). No significant differences between groups were observed for age (p = 0.798) or height (p = 0.411). In contrast, women in the DTG exhibited significantly higher weight (p = 0.002) and BMI (p = 0.002) than women in the NDG.
Regarding ED-related measures (EDI-3RF), women in the DTG scored significantly higher in DFT (p < 0.001), body dissatisfaction (p < 0.001), and total EDI-3RF score (p < 0.001), whereas bulimia did not differ significantly (p = 0.065) compared to the NDG. Regarding self-concept (AF-5), physical self-concept was significantly lower in the DTG (p = 0.001) compared to the NDG, while the remaining AF-5 dimensions did not differ significantly between groups.
In terms of psychological symptoms (LBS-50), the DTG exhibited significantly higher scores in minimization (p = 0.004), psychoreactivity (p = 0.006), hypersensitivity (p = 0.007), depression (p = 0.015), strict sleep (p = 0.002), and prolonged sleep (p = 0.010), as well as higher GSI (p = 0.019) and PST (p = 0.005) compared to the NDG. Symptom intensity (INT) did not differ between groups (p = 0.835), and somatization–depression did not reach statistical significance (p = 0.051), but it was almost significant.
A multivariable analysis was performed using binary logistic regression, including variables with p < 0.20 in the univariable analyses (presented in Table 3). A backward stepwise procedure was applied to obtain a more parsimonious model.
As shown in Table 3, in the multivariable model, body dissatisfaction was the only variable that remained statistically significant (OR = 6.40, 95% CI: 1.01–40.65; p = 0.049). BMI categories (normal weight as reference) were not statistically significant (overweight: p = 0.088; obesity: p = 0.321), and DFT did not reach statistical significance (p = 0.055). The remaining variables included in the model were also not statistically significant (all p > 0.05), indicating that body dissatisfaction was the strongest independent correlate of belonging to the dietary treatment group in this analysis. BMI was considered a key potential confounder because it is closely related to dietary treatment indication and may also be associated with body image and ED risk indicators. Accordingly, BMI was entered into the multivariable model as a categorical variable. Although BMI categories did not reach statistical significance in the final model, residual confounding by adiposity-related factors cannot be fully excluded.
Table 4 shows the Hosmer–Lemeshow test, which is a statistical goodness-of-fit test used to evaluate how well binary logistic regression models are calibrated. Non-significant p-values indicating a good model fit and a model summary to evaluate model fit are shown in Table 4.

3. Discussion

The purpose of this study was to compare eating disorder (ED) risk indicators and related psychological variables in women aged ≥50 years who were receiving medically supervised dietary treatment versus peers not following any dietary regimen. An important aspect of this research was that the sample, women over 50 years old, has been far less examined in ED research than younger groups, despite evidence that body image concerns and disordered eating can persist into later life. By focusing on women in routine dietary care pathways, our study aims to inform clinical practice by highlighting a pragmatic context in which ED risk indicators and body dissatisfaction may be identified and addressed. The present cross-sectional study compared women aged ≥50 years receiving medically supervised dietary treatment (DTG) with peers not following any dietary regimen (NDG). Women in the DTG showed (i) higher BMI and a markedly higher ED risk profile, particularly a higher drive for thinness (DFT) and body dissatisfaction, (ii) lower physical self-concept, and (iii) higher levels of general psychological distress, especially sleep-related symptoms and selected LBS-50 domains. Notably, only women in the DTG met EDI-3RF clinical referral criteria. In the multivariable model, body dissatisfaction emerged as the strongest independent correlate of DTG status.
Prior studies of older women suggest that dieting and weight-management contexts are often accompanied by higher levels of body image concern and ED risk indicators, although directionality cannot be inferred [2,10,11]. These findings are in agreement with the findings of the present study, as women in the DTG had higher scores for drive for thinness and body dissatisfaction than women in the NDG (Table 2). Importantly, however, group differences should be interpreted in light of the markedly higher BMI in the DTG (Table 1), given that higher adiposity is closely linked to referral/uptake of dietary treatment and may also be associated with weight/shape concerns and ED risk indicators [2,11]. In this context, the proportion of participants exceeding the EDI-3RF threshold for drive for thinness in the DTG may reflect a higher-risk profile among women attending dietary care pathways rather than an effect of dietary treatment per se [2,10,11]. Overall, these results support the view that body dissatisfaction and drive for thinness remain key clinical signals in later life, consistent with previous work identifying these constructs as important correlates and predictors of ED risk in older women [18,32]. Although eating disorders have traditionally been associated with adolescence and early adulthood, evidence indicates that clinically relevant disordered eating and body image concerns persist into midlife and older age [7,13,19,20]. A large web-based sample of women aged 50 years and older reported substantial ED symptoms and high rates of current dieting, suggesting that dieting contexts may be settings in which ED risk indicators and body image concerns become more visible [10]. Consistent with this, women engaged in dietary treatment in our study had higher ED risk scores than those not on a diet, and a non-trivial proportion met clinical referral criteria.
From an epidemiological perspective, these findings also align with the observation that adult EDs are frequently underdetected outside specialist services [8,12]. In routine medical care, dietary treatment is often initiated for weight- and health-related reasons, which may lead clinicians to prioritize anthropometric and metabolic goals while overlooking body image disturbance and maladaptive weight-control cognitions and behaviors. Taken together, our results support the view that dietary care pathways may represent a pragmatic opportunity to enhance early identification of ED risk indicators in women aged ≥50 years, without implying a causal effect of dietary treatment itself.
To assess self-concept across different domains (social, academic/professional, emotional, family, and physical), we used the AF-5 questionnaire. In our sample, physical self-concept differed significantly between groups, with lower scores in women receiving dietary treatment (DTG) compared with peers not following any dietary regimen (NDG) (p < 0.01; Table 2). This finding is clinically relevant because, in older women, eating disorder symptoms have been linked to poorer quality of life and lower physical self-esteem, which may be reflected in more negative perceptions of physical condition and appearance [17,19]. The current study found significant differences between groups for physical self-concept (p < 0.01) (Table 3), which is in accordance with the previous studies [22,23]. Although the cross-sectional design does not allow conclusions about directionality, the observed group difference in physical self-concept supports considering a multidimensional clinical perspective in dietary care pathways for women aged ≥50 years, rather than focusing exclusively on nutritional targets [15,16]. This dimension has been less examined in relation to ED risk indicators among women aged ≥50 years, supporting the need for further research.
Clinically, the association between body dissatisfaction and DT status reinforces the relevance of assessing body dissatisfaction when women aged ≥50 years seek dietary care. At the same time, given the cross-sectional design and the likelihood of selection effects, these findings should be interpreted as reflecting a higher-risk profile among women attending dietary care pathways rather than a directional effect of dietary treatment. Larger studies are needed to obtain more stable estimates and to clarify how adiposity, body image concerns, and psychological distress co-occur in this clinical context.
It is noteworthy that our questionnaire assessment was not limited to the evaluation of at-risk symptoms for developing ED; the assessment extended beyond ED risk indicators to include broader psychopathological symptoms using the LBS-50. Compared with the NDG, the DTG showed significantly higher scores in several domains, including psychoreactivity, hypersensitivity, depression, and sleep-related symptoms (strict sleep and prolonged sleep) (p < 0.01 to p < 0.05). These results support the view that ED-related risk indicators in later life may present alongside a wider pattern of psychological distress rather than in isolation [16,29]. Sleep complaints are particularly relevant in older age and may interact with emotional regulation and body image concerns, suggesting that dietary care pathways for women aged ≥50 years may benefit from a multidimensional approach that includes brief screening and, when appropriate, support for body acceptance, emotional regulation, and sleep hygiene alongside nutritional care.
Body dissatisfaction and DFT were the most discriminative ED-related variables between groups, and body dissatisfaction remained statistically significant in multivariable analysis. This pattern is consistent with the literature identifying body dissatisfaction as a core transdiagnostic risk and maintenance factor for ED across the lifespan, including midlife [17,19,20]. It also complements work suggesting that body image concerns remain salient in middle-aged women and may interact with weight-control efforts and sociocultural pressures [22,26]. At the same time, the wide confidence interval observed in the multivariable estimate and the close interrelationships among adiposity, body dissatisfaction, and weight-control cognitions warrant cautious interpretation. Clinically, however, the convergence of higher body dissatisfaction with elevated ED risk indicators in women receiving dietary care supports prioritizing body dissatisfaction as a key screening signal in this setting. As shown in Table 4, in the multivariable model, body dissatisfaction was the only variable that remained statistically significant (OR = 6.40); however, the estimate was imprecise (wide 95% CI), likely reflecting the modest sample size and correlated predictors. Therefore, the magnitude of this association should be interpreted cautiously and confirmed in larger, preferably longitudinal, studies.
Regarding potential limitations: First, the cross-sectional design precludes causal inference; women with greater pre-existing body dissatisfaction and ED risk may be more likely to seek dietary treatment. Second, group allocation was non-random and BMI differed significantly between groups; although multivariable analyses were conducted, residual confounding related to adiposity and correlated psychosocial factors cannot be excluded. Third, the modest sample size and recruitment from a single Spanish city limit generalizability and may reduce the stability of multivariable estimates, particularly given the broad age range encompassed within older women. Importantly, the study was intentionally focused on women aged ≥50 years; therefore, findings should not be extrapolated to men or to other clinical populations without further research [33,34]. Finally, all psychological measures were self-reported and may be influenced by response biases.
Future studies should use longitudinal designs to clarify temporal relationships between dietary care uptake, trajectories of body dissatisfaction and ED risk indicators, and potential moderators relevant to midlife (e.g., menopausal status and sociocultural pressures) [20,23,26]. Multicenter Spanish studies would be particularly valuable to strengthen epidemiological inferences in this population [8].
Overall, this study adds clinically relevant evidence that women aged ≥50 years attending medically supervised dietary care pathways may present a higher ED risk profile—most notably, elevated body dissatisfaction and drive for thinness—together with lower physical self-concept and more emotional and sleep-related symptoms. Although these findings should be interpreted as associations, they support integrating brief, systematic screening for body image concerns and ED risk indicators into routine dietary consultations, with appropriate guidance and referral when needed. Future longitudinal research should examine symptom trajectories and the moderating role of midlife sociocultural factors, including ageism and appearance-related pressures. Taken together, dietary care pathways may offer a timely opportunity to identify ED risk indicators in women aged ≥50 years who might otherwise remain unrecognized.

4. Materials and Methods

4.1. Participants

This cross-sectional study was conducted in Cádiz (Spain) and focused on women aged ≥50 years. Between June 2022 and July 2023, 120 women initially volunteered to participate. After data collection, 38 participants were excluded due to incomplete questionnaires or invalid questionnaire completion. The final sample included 82 women aged 51–88 years. All analyses were performed on complete cases (i.e., no missing data in the analyzed dataset).
Inclusion criteria included women aged ≥50 years who provided written informed consent. Exclusion criteria excluded those with a previous diagnosis of an ED confirmed by a specialist, those in current treatment for an ED, those with severe reading comprehension difficulties, or those who refused to participate.
Participants were classified into two groups based on their current clinical status at the time of assessment. The dietary treatment group (DTG; n = 42) included women attending medical consultations for dietetic counseling in Cádiz and currently receiving a physician-prescribed, individualized, hypocaloric, balanced dietary treatment based on the Mediterranean diet. The no-diet group (NDG; n = 40) included women aged ≥50 years not following any dietary treatment, recruited in Cádiz from companions of patients attending the same consultation (n = 14) and from the local community (n = 26), who were included after eligibility screening. Group allocation reflected routine clinical practice and was not randomized (Figure 1).

4.2. Dietary Treatment Protocol

The dietary treatment was prescribed for weight control and/or obesity-related health concerns (e.g., being overweight, obesity, or metabolic risk). All dietary interventions were supervised by a physician specialized in clinical nutrition. At the time of assessment, participants had been following the dietary treatment for 2 to 10 months (mean duration, 4 months). Follow-up visits were typically scheduled every two weeks and included a review of anthropometric measures and adjustments to an individualized diet plan based on the patient’s progress.

4.3. Testing Procedures

After providing oral and written information about the study, all eligible participants who agreed to take part signed an informed consent form. Data collection was conducted in a single assessment session. Anthropometric measures were obtained first, and participants were then given the questionnaire pack to complete in a private room within the clinic, allowing them to respond calmly and without any interference. The questionnaires were self-administered and completed without the presence of the interviewer/researcher. Participants were explicitly informed that responses were anonymous; the sociodemographic questionnaire was kept separate from the psychometric measures, and no identifying information was required. Only participants who wished to receive feedback on their results could voluntarily write their name to enable score reporting. All questionnaires were administered in the same fixed order for all participants. Completion time ranged from 20 to 40 min (mean, ~30 min).
All our procedures complied with the Helsinki Declaration, which outlines ethical principles for research involving humans. The study was approved by the CEIm Hospital Clínico San Carlos (identification code: 22/576-E) Ethics Committee in Madrid (Spain).

4.3.1. Sociodemographic and Clinical Data

A study-specific sociodemographic inventory was used to collect information on age, and anthropometric measurements included height (cm) and body weight (kg), which were used to calculate body mass index (BMI; kg/m2). Height and weight were measured by medical staff using a Tanita bioelectrical impedance scale and a SECA stadiometer. In addition, marital status, educational level, employment status, and information on use of social networks were collected. These variables were used to describe the sample and explore group differences.

4.3.2. Eating Disorder Inventory-3 Referral Form (EDI-3RF)

Eating Disorder Inventory-3 Referral Form (EDI-3RF) is a self-report questionnaire used to assess the presence of at-risk symptoms for developing an ED. It is a 25-item abbreviated form of the EDI-3 [35,36] and includes three scales: (1) drive for thinness; (2) bulimia; and (3) body dissatisfaction. Participants are asked to rate their agreement with each statement on a six-point Likert scale (always, usually, often, sometimes, rarely, and never). Higher scores are associated with a greater degree of ED. The EDI-3RF has shown validity and reliability for all three subscales. Recommended cut-off scores are DFT ≥ 7, B ≥ 5, and BD ≥ 8. The EDI-3RF has shown good psychometric properties, with Cronbach’s alpha values above 0.80 for DFT and BD and around 0.70 for B, and significant concurrent validity with other measures of ED psychopathology and BMI. The estimated time to complete the questionnaire is approximately 10–15 min, which allows it to be used as a screening tool in research [36].

4.3.3. AF-5 Self-Concept Questionnaire

The AF-5 Self-Concept Questionnaire assesses five dimensions of self-concept: social, academic/professional, emotional, family, and physical. It can be administered to adolescents and adults with different educational levels and provides normative data for several age groups. The AF-5 has shown satisfactory internal consistency, with Cronbach’s alpha coefficients ranging from 0.74 to 0.88 across dimensions, and test–retest correlations between 0.52 and 0.70. In the present study, the physical self-concept dimension was used as a key variable and recorded scores in the remaining dimensions [37].

4.3.4. List of Brief Symptoms (LBS-50)

List of Brief Symptoms (LBS-50) is a self-report questionnaire used to assess psychopathological risk which measures nine clinical scales: (1) psychoreactivity; (2) hypersensitivity; (3) obesity compulsion; (4) anxiety; (5) hostility; (6) somatization; (7) depression; and two sleep-related factors, (8) strict sleep and (9) prolonged sleep. It is a 50-item questionnaire where the participant must indicate their degree of agreement on a scale of 0 to 3. The results are interpreted using percentile bands and specific scales. LBS-50 has shown validity and reliability for all nine clinical scales [32]. This scale is useful for clinical settings to screen for mental health issues and track progress during treatment. The estimated time to complete the questionnaire is approximately 10–15 min, which allows it to be used as a screening tool in research.

4.3.5. Physical Activity: International Physical Activity Questionnaire (IPAQ)

Physical activity was assessed using the short form of the International Physical Activity Questionnaire (IPAQ). This 7-item self-report tool asks about the frequency, duration, and intensity (moderate and vigorous) of physical activity performed during the last seven days, as well as walking and time spent sitting on a typical working day [35].
Physical activity was expressed in MET-minutes/week and classified into three categories (high, moderate, low) according to standard scoring criteria: (1) high: ≥7 days/week of walking and/or moderate or vigorous activities achieving ≥3000 MET-min/week, or ≥3 days/week of vigorous activity accumulating ≥1500 MET-min/week; (2) moderate: ≥3 days/week of vigorous activity for ≥20 min/day; or ≥5 days/week of moderate activity and/or walking for ≥30 min/day; or ≥5 days/week of any combination of walking, moderate, or vigorous activities achieving ≥600 MET-min/week; (3) low: not meeting the criteria for moderate or high physical activity.

4.4. Statistical Analyses

Data are presented as the mean (M) ± standard deviation (SD). The normal distribution of data was confirmed using the Shapiro–Wilk test, and Leven’s test revealed the homogeneity of variance. To compare the two groups (DTG vs. NDG), continuous dependent variable data were analyzed using an independent-samples t-test (data are normally distributed) and the Mann–Whitney U test for independent samples (data are not normally distributed). For categorical variables, data were analyzed using a chi-square test. Variables with p < 0.20 in bivariate analyses were considered for inclusion in a multivariable binary logistic regression model with dietary treatment status (DTG vs. NDG) as the dependent variable. A backward stepwise procedure was applied to derive a more parsimonious model, with final inclusion also guided by a priori clinical relevance. Results are reported as odds ratios (ORs) with 95% confidence intervals (CIs). Statistical significance was established at the p ≤ 0.05 level. The remaining analyses were performed using the SPSS 27.0 statistical software package (SPSS Inc., Chicago, IL, USA) (version 27.0; SPSS, Chicago, IL, USA).

5. Conclusions

In this sample, women aged ≥50 years attending medically supervised dietary care exhibited higher ED risk indicator values and broader psychological distress than peers not following a dietary regimen. In multivariable analysis, body dissatisfaction was the strongest independent correlation of belonging to the dietary treatment group. Routine screening for body image concerns and ED risk indicators within dietary care pathways may improve early identification in older women, and longitudinal studies are needed to clarify temporal dynamics and relevant moderators in midlife and later life.

Author Contributions

Conceptualization, P.C.M.-B. and M.R.-R.; methodology, P.C.M.-B. and M.R.-R.; software, P.C.M.-B. and J.R.-L.; validation, P.C.M.-B. and J.R.-L.; formal analysis, J.R.-L. and J.C.d.I.; investigation, P.C.M.-B.; resources, J.C.d.I., M.R.-R., J.R.-L. and P.C.M.-B.; data curation, J.R.-L., A.B.-M. and J.C.d.I.; original draft preparation, P.C.M.-B., J.R.-L. and M.R.-R.; writing—review and editing, P.C.M.-B., A.B.-M., J.R.-L. and M.R.-R.; visualization, P.C.M.-B., J.R.-L. and M.R.-R.; supervision, M.R.-R.; project administration, M.R.-R.; funding acquisition, P.C.M.-B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the CEIm Hospital Clínico San Carlos (identification code: 22/576-E, 18 October 2022) Ethics Committee in Madrid (Spain).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data shown in this study are available on request from the corresponding author. The data are not publicly available due to containing information that could compromise the privacy of research participants.

Acknowledgments

The authors thank the women who took part in the data collection for this project and the participants for their time and effort.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hantsoo, L.; Epperson, C.N. Anxiety Disorders Among Women: A Female Lifespan Approach. Focus 2017, 15, 162–172. [Google Scholar] [CrossRef] [Scilit]
  2. Castro-Fornieles, J.; Gual, P.; Lahortiga, F.; Gila, A.; Casulà, V.; Fuhrmann, C.; Imirizaldu, M.; Saura, B.; Martínez, E.; Toro, J. Self-oriented perfectionism in eating disorders. Int. J. Eat. Disord. 2007, 40, 562–568. [Google Scholar] [CrossRef] [Scilit]
  3. Grajek, M.; Krupa-Kotara, K.; Białek-Dratwa, A.; Sobczyk, K.; Grot, M.; Kowalski, O.; Staśkiewicz, W. Nutrition and mental health: A review of current knowledge about the impact of diet on mental health. Front. Nutr. 2022, 9, 943998. [Google Scholar] [CrossRef] [Scilit]
  4. White, R.; Vella, S.; Biddle, S.; Sutcliffe, J.; Guagliano, J.M.; Uddin, R.; Burgin, A.; Apostolopoulos, M.; Nguyen, T.; Young, C.; et al. Physical activity and mental health: A systematic review and best-evidence synthesis of mediation and moderation studies. Int. J. Behav. Nutr. Phys. Act. 2024, 21, 134. [Google Scholar] [CrossRef] [Scilit]
  5. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5), 5th ed.; American Psychiatric Association: Arlington, VA, USA, 2013. [Google Scholar]
  6. Lapid, M.I.; Prom, M.C.; Burton, M.C.; McAlpine, D.E.; Sutor, B.; Rummans, T.A. Eating disorders in the elderly. Int. Psychogeriatr. 2010, 22, 523–536. [Google Scholar] [CrossRef] [Scilit]
  7. Mangweth-Matzek, B.; Hoek, H.W.; Rupp, C.I.; Lackner-Seifert, K.; Frey, N.; Whitworth, A.B.; Pope, H.G.; Kinzl, J. Prevalence of eating disorders in middle-aged women. Int. J. Eat. Disord. 2014, 47, 320–324. [Google Scholar] [CrossRef] [Scilit]
  8. Ruiz Prieto, I. La presencia de los trastornos de la conducta alimentaria en adultos: Epidemiología y características clínicas. Rev. Psiquiatr. Salud Ment. 2011, 35, 389–397. [Google Scholar]
  9. Grupo de trabajo de la Guía de Práctica Clínica sobre Trastornos de la Conducta Alimentaria. Guía de Práctica Clínica Sobre Trastornos de la Conducta Alimentaria; Plan de Calidad para el SNS: Barcelona, Spain, 2009. [Google Scholar]
  10. Gagne, D.A.; Von Holle, A.; Brownley, K.A.; Runfola, C.D.; Hofmeier, S.; Branch, K.E.; Bulik, C.M. Eating disorder symptoms and weight and shape concerns in a large web-based convenience sample of women ages 50 and above: Results of the Gender and Body Image (GABI) study. Int. J. Eat. Disord. 2012, 45, 832–844. [Google Scholar] [CrossRef] [Scilit]
  11. Conceição, E.M.; Gomes, F.V.S.; Vaz, A.R.; Pinto-Bastos, A.; Machado, P.P.P. Prevalence of eating disorders and picking/nibbling in elderly women. Int. J. Eat. Disord. 2017, 50, 793–800. [Google Scholar] [CrossRef] [Scilit]
  12. Keski-Rahkonen, A.; Mustelin, L. Epidemiology of eating disorders in Europe: Prevalence, incidence, comorbidity, course, consequences, and risk factors. Curr. Opin. Psychiatry 2016, 29, 340–345. [Google Scholar] [CrossRef] [Scilit]
  13. Mangweth-Matzek, B.; Rupp, C.I.; Hausmann, A.; Assmayr, K.; Mariacher, E.; Kemmler, G.; Whitworth, A.B.; Biebl, W. Never too old for eating disorders or body dissatisfaction: A community study of elderly women. Int. J. Eat. Disord. 2006, 39, 583–586. [Google Scholar] [CrossRef] [Scilit]
  14. Podfigurna-Stopa, A.; Luisi, S.; Regini, C.; Katulski, K.; Centini, G.; Meczekalski, B.; Petraglia, F. Mood disorders and quality of life in polycystic ovary syndrome. Gynecol. Endocrinol. 2015, 31, 431–434. [Google Scholar] [CrossRef] [Scilit]
  15. Mangweth-Matzek, B.; Kummer, K.K.; Hoek, H.W. Update on the epidemiology and treatment of eating disorders among older people. Curr. Opin. Psychiatry 2023, 36, 405–411. [Google Scholar] [CrossRef] [Scilit]
  16. Bulut, E.A.; Khoury, R.; Lee, H.; Grossberg, G.T. Eating disturbances in the elderly: A geriatric-psychiatric perspective. J. Nutr. Health Aging 2019, 5, 185–198. [Google Scholar] [CrossRef] [Scilit]
  17. Kilpela, L.S.; Becker, C.B.; Wesley, N.; Stewart, T. Body image in adult women: Moving beyond the younger years. Adv. Eat. Disord Theory Res. Pract. 2015, 3, 144–164. [Google Scholar] [CrossRef] [Scilit]
  18. Panea-Pizarro, I.; Moran, J.M.; Lavado-García, J.; Beato-Fernández, L.; Domínguez-Martin, A.T.; Huerta-González, S.; Novo, A.; Pedrera-Zamorano, J.D.; López-Espuela, F. Health-related quality of life in Spanish women with eating disorders. Nutrients 2021, 13, 403. [Google Scholar] [CrossRef] [Scilit]
  19. Samuels, K.L.; Maine, M.M.; Tantillo, M. Disordered eating, eating disorders, and body image in midlife and older women. Curr. Psychiatry Rep. 2019, 21, 70. [Google Scholar] [CrossRef] [Scilit]
  20. Williams, L.; Gurung, J.; Persons, P.; Kilpela, L. Body image and eating issues in midlife: A narrative review with clinical question recommendations. Maturitas 2024, 188, 108068. [Google Scholar] [CrossRef] [Scilit]
  21. Lewis, D.M.; Cachelin, F.M. Body image, body dissatisfaction, and eating attitudes in midlife and elderly women. Eat. Disord. 2001, 9, 29–39. [Google Scholar] [CrossRef] [Scilit]
  22. Rodgers, R.F.; Berry, R.A.; Laveway, K. Body image concerns and disordered eating among older women: Identifying variables of interest for integrated models. Int. J. Eat. Disord. 2022, 55, 886–891. [Google Scholar] [CrossRef] [Scilit]
  23. Frazier, L.D.; Bazo Pérez, M. Unpacking eating disorder risk and resilience during menopause: A biopsychosocial perspective. Menopause 2025, 32, 443–452. [Google Scholar] [CrossRef] [Scilit]
  24. Kilpela, L.S.; Marshall, V.B.; Hooper, S.C.; Becker, C.B.; Keel, P.K.; LaCroix, A.Z.; Musi, N.; Espinoza, S.E. Binge eating age of onset, frequency, and associated emotional distress among women aged 60 years and over. Eat. Disord. 2023, 31, 479–486. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  25. Carrard, I.; Rothen, S.; Rodgers, R.F. Body image and disordered eating in older women: A Tripartite Sociocultural Model. Eat. Beha 2020, 38, 101412. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  26. Thompson, K.A.; Bardone-Cone, A.M. Disordered eating behaviors and attitudes and their correlates among a community sample of older women. Eat. Behav. 2019, 34, 101301. [Google Scholar] [CrossRef] [Scilit]
  27. Thompson, K.A.; Miller, A.J.; Walsh, E.C.; Bardone-Cone, A.M. Social media and disordered eating among middle-aged women: Not just an adolescent concern. Eat. Beha. 2023, 50, 101748. [Google Scholar] [CrossRef] [Scilit]
  28. Raffone, F.; Atripaldi, D.; Barone, E.; Marone, L.; Carfagno, M.; Mancini, F.; Saliani, A.M.; Martiadis, V. Exploring the Role of Guilt in Eating Disorders: A Pilot Study. Clin. Pract. 2025, 15, 56. [Google Scholar] [CrossRef] [Scilit]
  29. Jebeile, H.; Libesman, S.; Melville, H.; Low-Wah, T.; Dammery, G.; Seidler, A.L.; Jones, R.A.; McMaster, C.M.; Paxton, S.J.; Hill, A.J.; et al. Eating disorder risk during behavioral weight management in adults with overweight or obesity: A systematic review with meta-analysis. Obes. Rev. 2023, 24, e13561. [Google Scholar] [CrossRef] [Scilit]
  30. Midlarsky, E.; Nitzburg, G. Eating disorders in middle-aged women. J. Gen. Psychol. 2008, 135, 393–408. [Google Scholar] [CrossRef] [Scilit]
  31. Mulchandani, M.; Shetty, N.; Conrad, A.; Muir, P.; Mah, B. Treatment of eating disorders in older people: A systematic review. Syst. Rev. 2021, 10, 275. [Google Scholar] [CrossRef] [Scilit]
  32. Abuín, M.R.; de Rivera, L. La medición de síntomas psicológicos y psicosomáticos: El Listado de Síntomas Breve (LSB-50). Clínica Salud 2014, 25, 131–141. [Google Scholar]
  33. Kafyra, M.; Kalafati, I.P.; Stefanou, G.; Kourlaba, G.; Moulos, P.; Varlamis, I.; Kaliora, A.C.; Dedoussis, G.V. A Dietary Intervention in Adults with Overweight or Obesity Leads to Weight Loss Irrespective of Macronutrient Composition. Nutrients 2024, 16, 2842. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  34. Levak, N.; Lehtisalo, J.; Thunborg, C.; Westman, E.; Andersen, P.; Andrieu, S.; Broersen, L.M.; Coley, N.; Hartmann, T.; Irving, G.F.; et al. Nutrition guidance within a multimodal intervention improves diet quality in prodromal Alzheimer’s disease: Multimodal Preventive Trial for Alzheimer’s Disease (MIND-ADmini). Alzheimer’s Res. Ther. 2024, 16, 147. [Google Scholar] [CrossRef] [Scilit]
  35. Craig, C.L.; Marshall, A.L.; Sjöström, M.; Bauman, A.E.; Booth, M.L.; Ainsworth, B.E.; Pratt, M.; Ekelund, U.; Yngve, A.; Sallis, J.F.; et al. International physical activity questionnaire: 12-country reliability and validity. Med. Sci. Sports Exerc. 2003, 35, 1381–1395. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  36. Garner, D.M. Eating Disorder Inventory-3 (EDI-3) Professional Manual; Psychological Assessment Resources: Odessa, FL, USA, 2004. [Google Scholar]
  37. García, F.; Musitu, G. Autoconcepto Forma 5 (AF-5): Manual; TEA Ediciones: Madrid, Spain, 1999. [Google Scholar]
Women 06 00016 g001
Figure 1. Flow diagram describing recruitment of participants to the study.
Figure 1. Flow diagram describing recruitment of participants to the study.
Women 06 00016 g001
Table 1. Sociodemographic and clinical characteristics of the study groups.
Table 1. Sociodemographic and clinical characteristics of the study groups.
No Diet (NDG)
n = 40 		Dietary Treatment (DTG)
n = 42 		p-ValueEffect Size
n%n%
Educational level 0.966
Primary education410.037.1
Compulsory secondary education1127.51126.2
Upper secondary/vocational training1845.02047.6
University degree717.5819.0
EDI-3RF clinical referral criterion 0.0310.249 1
0 → Does not meet referral criterion401003788.1
1 → Meets referral criteria00511.9
Physical activity (IPAQ) 0.856
Low2562.52457.1
Moderate922.51023.8
High615.0819.0
BMI category 0.0090.375 2
Underweight0012.4
Normal weight1537.5614.3
Overweight1640.01228.6
Obesity922.52354.8
Drive for Thinness level (DFT; EDI-3RF) <0.0010.681 1
Low3895.01228.6
Medium25.03271.4
n = 82; NDR: no-diet group (n = 40); DTG: dietary treatment group (n = 42); BMI: body mass index (divide weight by the square of height); IPAQ: International Physical Activity Questionnaire; EDI-3RF: Eating Disorder Inventory-3 Referral Form. Categorical variables are reported as n (%) and were compared using the chi-square test (or Fisher’s exact test when appropriate). Effect size for categorical comparisons is reported as 1 Phi for 2 × 2 tables and 2 Cramer’s V for larger contingency tables. p-values correspond to the association tests.
Table 2. Anthropometric and psychological variables.
Table 2. Anthropometric and psychological variables.
No Diet (NDG)
n = 40 		Dietary Treatment (DTG)
n = 42 		p-ValueEffect SizeIC 95%
MeanSDMedianIQRMeanSDMedianIQR
Weight (kg)70.513.268.460.0–77.882.217.681.669.1–94.10.002 0.345 30.129–0.562
BMI (kg/m2)27.14.226.323.8–29.930.86.431.425.9–34.90.002 −0.695 4−1.139; −0.247
Physical Self-Concept (AF-5)5.41.95.53.8–7.24.11.93.72.8–5.60.001 0.729 30.279–1.174
Drive for Thinness (EDI-3RF) 2.92.031.3–4.09.64.48.56–14<0.001 0.742 40.526–0.959
Body Dissatisfaction (EDI-3RF) 5.84.153–812.16.1117–16<0.001 0.522 40.305–0.738
Total EDI-3RF Score9.87.295.0–12.823.910.722.515–29<0.001 0.684 40.467–0.900
Minimization (LBS-50)10.36.686–1413.65.21410.8–16.30.004 0.321 40.105–0.538
Psychoreactivity (LBS-50)11.08.78.56.3–14.014.56.2159.8–19.00.006 0.304 40.088–0.521
Hypersensitivity (LBS-50)3.83.831–55.83.852.8–8.30.007 0.297 40.081–0.514
Depression (LBS-50)9.67.774–1410.64.499.0–11.50.015 0.269 40.052–0.487
Strict Sleep (LBS-50)3.43.021–65.33.243–90.002 0.336 40.119–0.552
Prolonged Sleep (LBS-50)7.26.652.3–11.59.54.895.8–13.00.010 0.283 40.067–0.500
Global Severity Index (GSI)0.860.560.640.41–1.171.050.411.100.75–1.370.019 20.258 40.042–0.475
Number of Positive Symptoms (PST)23.511.72312.0–31.830.08.330.524.8–37.00.005 1−0.640 3−1.082; −0.194
n = 82; NDG: no-diet group (n = 40); DTG: dietary treatment group (n = 42); BMI: body mass index (divide weight by the square of height); EDI-3RF: Eating Disorder Inventory-3 Referral Form; AF-5: AF-5 Self-Concept Questionnaire; LBS-50: List of Brief Symptoms. Effect size: 1 Phi for 2 × 2 tables and 2 Cramer’s V for larger contingency tables; 3 Rosenthal’s r; 4 Cohen’s d. 95% CI refers to the effect size reported in each row.
Table 3. Multivariable logistic regression.
Table 3. Multivariable logistic regression.
No Diet (NDG) n = 40Dietary Treatment (DTG) n = 42 Multivariable Logistic Regression
OR (95% CI)p-Value
n%n%
BMI category
Underweight
Normal weight
Overweight
Obesity
0
15
16
9
0
37.5
40.0
22.5
1
6
12
23
2.4
14.3
28.6
54.8		0.01
(0–82.24)		-
Ref.
0.088
0.321
MeanSDMedianIQRMeanSDMedianIQR
Weight (kg)70.513.268.460.0–77.882.217.681.669.1–94.11.11
(0.76–1.63)		0.592
Emotional Self-Concept (AF-5)5.82.05.84.0–7.45.01.74.63.8–5.814.98
(0.60–374.11)		0.099
Physical Self-Concept (AF-5)5.41.95.53.8–7.24.11.93.72.8–5.60.07
(0.003–1.75)		0.105
Drive for Thinness (EDI-3RF)2.92.031.3–4.09.64.48.56–14111.56
(0.90–13,794.72)		0.055
Body Dissatisfaction (EDI-3RF)5.84.153–812.16.1117–166.40
(1.01–40.65)		0.049
Total EDI-3RF Score9.87.295.0–12.823.910.722.515–290.20
(0.03–1.13)		0.069
Minimization (LBS-50)10.36.686–1413.65.21410.8–16.30.60
(0.29–1.24)		0.168
Magnification (LBS-50)4.03.731–65.13.453–70.19
(0.03–1.26)		0.086
Psychoreactivity (LBS-50)11.08.78.56.3–14.014.56.2159.8–19.00.80
(0.44–1.46)		0.465
Hypersensitivity (LBS-50)3.83.831–55.83.852.8–8.32.93
(0.96–8.96)		0.060
Somatization–Depression (LBS-50)7.24.764–109.24.3106–120.87
(0.48–1.60)		0.658
Strict Sleep (LBS-50)3.43.021–65.33.243–94.99
(0.68–36.72)		0.114
Prolonged Sleep (LBS-50)7.26.652.3–11.59.54.895.8–13.00.03
(0–1.62)		0.084
Number of Positive Symptoms (PST)23.511.72312.0–31.830.08.330.524.8–37.06.41
(0.75–55.07)		0.090
n = 82; NDG: no-diet group (n = 40); DTG: dietary treatment group (n = 42); BMI: body mass index (divide weight by the square of height); EDI-3RF: Eating Disorder Inventory-3 Referral Form; AF-5: AF-5 Self-Concept Questionnaire; LBS-50: List of Brief Symptoms.
Table 4. Statistical goodness-of-fit test.
Table 4. Statistical goodness-of-fit test.
Model SummaryHosmer–Lemeshow Test
Step−2 Log LikelihoodCox and Snell R2Nagelkerke R2Chi-SquaredfSig.
120.2550.6800.9070.96570.995
220.9830.6770.9031.43380.994
321.3270.6760.9011.08780.998
421.5130.6750.9001.09380.998
522.1430.6720.8971.25780.996
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Marruffi-Bonfante, P.C.; Rosety-Rodríguez, M.; Bable-Marruffi, A.; Choquet de Isla, J.; Riscart-López, J. Body Dissatisfaction and Eating Disorder Risk Indicators in Older Women: Associations with Medically Supervised Dietary Treatment. Women 2026, 6, 16. https://doi.org/10.3390/women6010016

AMA Style

Marruffi-Bonfante PC, Rosety-Rodríguez M, Bable-Marruffi A, Choquet de Isla J, Riscart-López J. Body Dissatisfaction and Eating Disorder Risk Indicators in Older Women: Associations with Medically Supervised Dietary Treatment. Women. 2026; 6(1):16. https://doi.org/10.3390/women6010016

Chicago/Turabian Style

Marruffi-Bonfante, Patrizia Carmen, Manuel Rosety-Rodríguez, Alberto Bable-Marruffi, Javier Choquet de Isla, and Javier Riscart-López. 2026. "Body Dissatisfaction and Eating Disorder Risk Indicators in Older Women: Associations with Medically Supervised Dietary Treatment" Women 6, no. 1: 16. https://doi.org/10.3390/women6010016

APA Style

Marruffi-Bonfante, P. C., Rosety-Rodríguez, M., Bable-Marruffi, A., Choquet de Isla, J., & Riscart-López, J. (2026). Body Dissatisfaction and Eating Disorder Risk Indicators in Older Women: Associations with Medically Supervised Dietary Treatment. Women, 6(1), 16. https://doi.org/10.3390/women6010016

Article Metrics

Back to TopTop