BackgroundChildhood obesity proves to be an important public health issue, since it serves as a potential risk factor for multiple diseases. Food addiction could also serve as an important etiological factor. As childhood obesity plays a serious issue also in Hungary, we aimed to adapt and validate the Hungarian version of the Yale Food Addiction Scale for Children (H-YFAS-C).MethodsA total of 191 children were assessed with the H-YFAS-C and the Eating Disorder Inventory (EDI). The following psychometric properties were analyzed: internal consistency, construct validity, convergent, and discriminant validity.ResultsA good construct validity was revealed by confirmatory factor analysis (RMSEA = 0.0528, CFI = 0.896, χ2 value = 279.06). Question 25 proved to have no significant effect on its group and was removed from further analyses. The Kuder–Richardson 20 coefficient indicated good internal consistency (K20 = 0.82). With the use of the eight EDI subscales, a good convergent and discriminant validity could be determined. Food addiction was diagnosed in 8.9% of children. The mean symptom count was 1.7 ± 1.2 (range: 0–7). Females were more often diagnosed with food addiction than males (p = .016; OR = 3.6, 95% CI: 1.2–10.6). BMI percentiles were significantly higher in children with diagnosed food addiction (p = .003). There proved to be no correlation between age and the occurrence of food addiction.Discussion and conclusionOur results show that H-YFAS-C is a good and reliable tool for addictive-like behavior assessment.

Functional response traits influence the ability of species to colonize and thrive in a habitat and to persist under environmental challenges. Functional traits can be used to evaluate environment-related processes and phenomena. They also help to interpret distribution patterns, especially under limiting ecological conditions. In this study, we investigate landscape-scale functional distribution responses of beech forests in a climatic transitional zone in Europe. We construct empirical density distribution responses for beech forests by applying coping-resilience-failure climatic traits based on 27 bioclimatic variables, resulting in prevalence-decay-exclusion distribution response patterns. We also perform multivariate exploratory cluster analysis to reveal significant sets of response patterns from the resilience and adaptation aspects. Temperature-related distribution responses presented a prevalence-dominated functional pattern, with Annual mean temperature indicating the most favorable adaptation function. Precipitation indices showed climate-limited response patterns with the dominance of extinction function. Considering regional site-specific climate change projections, these continental beech forests could regress moderately due to temperature increase in the near future. Our results also suggest that both summer and winter precipitation could play a pivotal role in successful resilience. Functions and variables that indicate climate sensitivity can serve as a useful starting point to develop adaptation measures for regional forest management.

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