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The impact of food insecurity on mental health has not yet been examined in graduate students, a population widely considered at elevated risk for financial strain and negative mental health outcomes. This study aimed to derive initial prevalence estimates of food insecurity in a sample of current graduate students at a large state university and to elucidate the relationship between food insecurity and depression, anxiety and stress in this sample.
Cross-sectional online survey including the US Household Food Security Survey Module: Six-Item Short Form and the Depression, Anxiety, and Stress Scales (DASS-21).
University in the northeastern region of the USA.
Two hundred sixty-three graduate students.
In the present sample, 59·7 % of participants reported high/marginal food security, 18·5 % reported low food security and 21·8 % reported very low food security. Graduate students with very low food security reported significantly greater depression (η2 = 0·09), anxiety (η2 = 0·10) and stress (η2 = 0·10), compared with those with low food security and high food security (all P’s < 0·001).
Food insecurity occurred in nearly half of the graduate students surveyed, and very low food security was associated with elevated levels of depression, anxiety and stress. Findings highlight the need to address food insecurity and associated elevated mental health problems present among graduate students.
In the past decade, network analysis (NA) has been applied to psychopathology to quantify complex symptom relationships. This statistical technique has demonstrated much promise, as it provides researchers the ability to identify relationships across many symptoms in one model and can identify central symptoms that may predict important clinical outcomes. However, network models are highly influenced by node selection, which could limit the generalizability of findings. The current study (N = 6850) tests a comprehensive, cognitive–behavioral model of eating-disorder symptoms using items from two, widely used measures (Eating Disorder Examination Questionnaire and Eating Pathology Symptoms Inventory).
We used NA to identify central symptoms and compared networks across the duration of illness (DOI), as chronicity is one of the only known predictors of poor outcome in eating disorders (EDs).
Our results suggest that eating when not hungry and feeling fat were the most central symptoms across groups. There were no significant differences in network structure across DOI, meaning the connections between symptoms remained relatively consistent. However, differences emerged in central symptoms, such that cognitive symptoms related to overvaluation of weight/shape were central in individuals with shorter DOI, and behavioral central symptoms emerged more in medium and long DOI.
Our results have important implications for the treatment of individuals with enduring EDs, as they may have a different core, maintaining symptoms. Additionally, our findings highlight the importance of using comprehensive, theoretically- or empirically-derived models for NA.
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