Analysis of current status and potential categories of nutritional literacy in elderly patients with chronic diseases: a single-center cross-sectional study - Wang, Zhitong; Jiang, Wenxiu; Wang, Jialin (Frontiers in Nutrition, 2025)
ObjectiveThis study identifies nutritional literacy subgroups and influencing factors among elderly chronic disease patients to develop targeted interventions.MethodsA total of 316 elderly chronic disease patients from a tertiary hospital in Deyang, China, were surveyed using standardized scales (General Information, Nutritional Literacy, Chronic Disease Management Self-Efficacy). Latent profile analysis identified nutritional literacy subgroups, with univariate and ordered logistic regression verifying influencing factors.ResultsA total of 316 valid samples were included, with a nutritional literacy score of 67.50 (51.00, 84.00). Nutritional literacy among elderly patients with chronic diseases was classified into three latent categories: “passive dependent type” (23.1%), “cognitive fluctuation type” (42.4%), and “autonomous management type” (34.5%). Ordered logistic regression showed that younger age groups had 25.64-fold [95% confidence interval (CI):5.07–129.66], 13.93-fold (95% CI: 3.10–62.61), and 9.66-fold (95% CI:2.42–38.54) higher odds of better nutritional literacy compared to the reference group aged ≥90 years. Compared to the highest income group (≥5,001 yuan), lower monthly income levels were associated with reduced odds of better nutritional literacy, with odds of 0.13-fold (95% CI: 0.04–0.45), 0.31-fold (95% CI: 0.11–0.91), and 0.25 -fold (95% CI: 0.09–0.64) for the ≤1,000 yuan, 1,001–3,000 yuan, and 3,001–5,000 yuan brackets, respectively. Smartphone use was associated with 1.96-fold higher odds versus non-users (95% CI: 1.03–3.74), while each unit increase in self-efficacy for chronic disease management was associated with 1.04-fold higher odds (95% CI:1.01–1.07) (all p < 0.05).ConclusionNutritional literacy among elderly patients with chronic diseases is moderately low and heterogeneous, and can be categorized into three latent profiles. Different categories of elderly patients exhibit distinct nutritional characteristics; therefore, interventions should be tailored to each nutritional literacy category to develop personalized improvement strategies. In particular, more education and support should be provided to “passive dependent type” patients to help enhance their self-management ability and improve their nutritional status, thereby better managing their chronic diseases and improving their quality of life. However, this single-center convenience sample from one Chinese city limits generalizability due to unaccounted regional/cultural diversity. Future multi-center studies across diverse settings should validate these findings.