Risk Profile for Eating Behaviours and Body Perception in a Convenience Sample of Adults: Implications for Health Policy and Person-Centred Care in Primary Healthcare

Abstract

Background/Objectives: Person-centred care necessitates addressing the growing biopsychosocial vulnerability within public health. This study analysed eating behaviours and sociocultural pressures regarding physical appearance in a convenience sample of adults to help inform potential evidence-based policies and programmes in primary care tailored to these exploratory symptom correlates. Methods: A quantitative, observational, cross-sectional study was conducted with 1287 participants. Data were collected via an online platform using the Eating Attitudes Test (EAT-26) and the Sociocultural Attitudes Towards Appearance Questionnaire (SATAQ-4). Descriptive statistics, bivariate tests, multiple linear regression models, and complementary binary logistic regression models were utilised to identify variables independently associated with scores and clinical risk thresholds (EAT-26 ≥ 20). Results: Multiple linear regression analysis determined that the scores indicating potential risk of altered eating behaviours (EAT-26) was primarily associated with female sex (β = 0.134, p < 0.001), followed by never eating in company (β = 0.149, p < 0.001), an active lifestyle (β = 0.094, p = 0.001), excessive social media usage (β = 0.088, p = 0.002), and smoking (β = 0.091, p = 0.001). Likewise, susceptibility to sociocultural pressures (SATAQ-4) showed a major association with excessive digital connectivity (β = 0.159, p < 0.001), female sex (β = 0.094, p = 0.001), smoking (β = 0.078, p = 0.004), both sometimes and never eating in company (β = 0.078, p = 0.008 and β = 0.082, p = 0.005 respectively), and younger age (β = −0.202, p < 0.001). Furthermore, the binary logistic sensitivity analysis confirmed that a high clinical risk score (≥20) was independently associated with female sex (Exp(B) = 2.660), smoking (Exp(B) = 2.381), never eating alone (Exp(B) = 2.253), excessive social media use (Exp(B) = 1.665), being active (Exp(B) = 1.500), a greater number of children (Exp(B) = 1.402), and younger age (Exp(B) = 0.969). Conclusions: Due to the non-probabilistic convenience nature of the sample, these findings cannot be directly generalized to the general population; however, they delineate the vulnerable demographic profile—young, active, female smokers who are frequent social media users and habitually eat alone—which may help generate hypotheses for future primary care prevention strategies. Furthermore, these results underscore the potential value of integrating specific screening considerations and digital literacy into person-centred healthcare, pending longitudinal validation.