Abstract

BackgroundThe prevalence of depression is increasing in the elderly population, and growing evidence suggests that malnutrition impacts mental health. Despites, research on the factors that predict depression is limited.MethodsWe included 2946 elderly individuals from National Health and Nutrition Examination Survey (NHANES) spanning the years 2011 through 2014. Depressive symptoms were assessed using the PHQ-9 scale. Multinomial logistic regression was performed to evaluate the independent association between Geriatric Nutritional Risk Index (GNRI) and depression prevalence and scores. Subgroup analysis was conducted to explore potential factors influencing the negative correlation between GNRI and depression. Restricted cubic spline graph was employed to examine the presence of a non-linear relationship between GNRI and depression.ResultsThe depression group had a significantly lower GNRI than the non-depression group, and multivariate logistic regression showed that GNRI was a significant predictor of depression (P < 0.001). Subgroup analysis revealed that certain demographic characteristics were associated with a lower incidence of depression in individuals affected by GNRIs. These characteristics included being female (P < 0.0001), non-Hispanic black (P = 0.0003), having a moderate BMI (P = 0.0005), having a college or associates (AA) degree (P = 0.0003), being married (P = 0.0001), having a PIR between 1.50 and 3.49 (P = 0.0002), being a former smoker (P = 0.0002), and having no history of cardiovascular disease (P < 0.0001), hypertension (P < 0.0001), and diabetes (P = 0.0027). Additionally, a non-linear negative correlation (non-linear P < 0.01) was found between GNRI and depression prevalence, with a threshold identified at GNRI = 104.17814.ConclusionThe GNRI demonstrates efficacy as a reliable indicator for forecasting depression in the elderly population. It exhibits a negative nonlinear correlation with the prevalence of depression among geriatric individuals.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call