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. 2023 Jul 31;15(15):3408.
doi: 10.3390/nu15153408.

Association between Nonfood Pre- or Probiotic Use and Cognitive Function: Results from NHANES 2011-2014

Affiliations

Association between Nonfood Pre- or Probiotic Use and Cognitive Function: Results from NHANES 2011-2014

Jingyi Chen et al. Nutrients. .

Abstract

In this study, we collected data from the National Health and Nutrition Examination Survey (NHANES) for the years 2011-2014. Multiple linear regression and logistic regression were used to analyse the association between nonfood pro- or prebiotic use and cognitive function among elderly Americans. To estimate the potential unobserved results, propensity score matching (PSM) was used to analyse the causal effect. Nonfood pro- or prebiotic use was analysed through the Dietary Supplement Use 30-Day Study. Cognitive function was evaluated by the Digit Symbol Substitution Test (DSST), the Animal Fluency Test (AFT), the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), and a composite Z-score calculated by summing the Z-scores of three tests. Male participants who used nonfood pro- or prebiotics tended to have higher comprehensive cognitive function (sum.z) with a β-coefficient of 0.64 (95% CI: 0.08-1.19). Probiotics or prebiotics may be a protective factor against cognitive impairment in males, with an odds ratio of 0.08 (95% CI: 0.02-0.29). Furthermore, the average treatment effect for the treated (ATT) with nonfood pro- or prebiotics (0.555) on sum.z in males was statistically significant (p < 0.05). Our research revealed that nonfood pre- or probiotic use was an effective method to improve cognitive function in elderly men from the USA.

Keywords: NHANES; cognitive function; prebiotic; probiotic.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The flow diagram of the sample screening procedure.
Figure 2
Figure 2
Association between nonfood pre- or probiotic use and different cognitive function scores stratified by age, ethnicity, and BMI. Adjusted for age, gender, ethnicity, BMI, drink, smoke, education, PIR, hypertension, stroke, DM, and CVD. The strata variable was not included in the model when stratifying by itself. (A) CERAD; (B) AFT; (C) DSST; (D) Composite-z score (sum.z). * p < 0.05.

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