Nutrients, Vol. 17, Pages 2767: A Network Analysis of Food Intake and Cognitive Function in Older Adults with Multimorbidity: A National Cross-Sectional Study
Nutrients doi: 10.3390/nu17172767
Authors:
Xiyan Li
Chengyu Chen
Xinru Li
Xinyi Xu
Ting Zheng
Yuyang Li
Qinglei Cai
Huang Lin
Chichen Zhang
Background: Implementing effective interventions for specific cognitive symptoms is critical to reducing the disease burden of dementia. Previous studies have identified associations between overall cognitive function and dietary patterns in older adults with multimorbidity. However, the relationship between specific cognitive symptoms and different foods remains largely unknown. Methods: We included 3443 older adults with multimorbidity, aged 65 years or older, from the Chinese Longitudinal Health Longevity Survey (CLHLS, 2017–2018). We used the Chinese version of the Mini-Mental State Examination (MMSE) to assess cognitive function and selected 13 common foods to evaluate food consumption. Network analysis was used to identify central symptoms and bridge symptoms between the food consumption and cognitive symptom networks. Finally, the stability of the networks was examined using the case-dropping bootstrap procedure. Results: Network analysis revealed that B6 (mushrooms or algae), B4 (dairy products), and B5 (nut products) were the most influential in the food–cognition network model, and A5 (language ability), A1 (orientation ability), and B5 (nut products) were considered bridging symptoms in the food–cognition network. Bootstrap analysis showed that the 95% confidence interval of the edge weights in the network is narrow, indicating that this study accurately assesses the edge weights. The correlation stability coefficient of the centrality of the expected influence and bridge strength is 0.75, indicating that the network has good stability. Conclusions: Central symptoms as well as bridge symptoms play a key role in food and cognitive networks. Timely systematic and multilevel interventions targeting central symptoms and bridge symptoms may help to delay the risk of dementia in older adults with multimorbidity.
Background: Implementing effective interventions for specific cognitive symptoms is critical to reducing the disease burden of dementia. Previous studies have identified associations between overall cognitive function and dietary patterns in older adults with multimorbidity. However, the relationship between specific cognitive symptoms and different foods remains largely unknown. Methods: We included 3443 older adults with multimorbidity, aged 65 years or older, from the Chinese Longitudinal Health Longevity Survey (CLHLS, 2017–2018). We used the Chinese version of the Mini-Mental State Examination (MMSE) to assess cognitive function and selected 13 common foods to evaluate food consumption. Network analysis was used to identify central symptoms and bridge symptoms between the food consumption and cognitive symptom networks. Finally, the stability of the networks was examined using the case-dropping bootstrap procedure. Results: Network analysis revealed that B6 (mushrooms or algae), B4 (dairy products), and B5 (nut products) were the most influential in the food–cognition network model, and A5 (language ability), A1 (orientation ability), and B5 (nut products) were considered bridging symptoms in the food–cognition network. Bootstrap analysis showed that the 95% confidence interval of the edge weights in the network is narrow, indicating that this study accurately assesses the edge weights. The correlation stability coefficient of the centrality of the expected influence and bridge strength is 0.75, indicating that the network has good stability. Conclusions: Central symptoms as well as bridge symptoms play a key role in food and cognitive networks. Timely systematic and multilevel interventions targeting central symptoms and bridge symptoms may help to delay the risk of dementia in older adults with multimorbidity. Read More