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Tooth loss-related dietary patterns and cognitive impairment in an elderly Japanese population: The Nakajima study.

Mai IshimiyaHiroyuki NakamuraYutaka KobayashiMoeko Noguchi-ShinoharaChiemi AbeChiaki DohmotoYoshihisa IkedaKahori TokunoKazuhiro OoiMasami YokokawaKazuo IwasaKiyonobu KomaiShuichi KawashiriMasahito Yamada
Published in: PloS one (2018)
Although several studies have demonstrated a potential correlation of dietary patterns with cognitive function, the relationship between tooth loss and dietary patterns and cognitive function have not been identified. In this cross-sectional study, we used a reduced rank regression (RRR) analysis, a technique used previously to observe dietary patterns based on the intakes of nutrients or levels of biomarkers associated with the condition of interest, to identify tooth loss-related dietary patterns and investigate the associations of such patterns with cognitive impairment in 334 community-dwelling Japanese subjects aged ≥ 60 years. According to Pearson correlation coefficients, the intakes of six nutrients (ash content, sodium, zinc, vitamin B1, α- and β-carotene) correlated significantly with the number of remaining teeth. Using RRR analysis, we extracted four dietary patterns in our subject population that explained 86.67% of the total variation in the intakes of these six nutrients. Particularly, dietary pattern 1 (DP1) accounted for 52.2% of the total variation. Food groups with factor loadings of ≥ 0.2 included pickled green leafy vegetables, lettuce/cabbage, green leaves vegetables, cabbage, carrots/squash; by contrast, rice had a factor loading of <-0.2. In a multivariate regression analysis, the adjusted odds ratios regarding the prevalence of cognitive impairment for the lowest, middle and highest tertiles of the DP1 score were 1.00 (reference), 1.224 (95% confidence interval [CI]: 0.611-2.453) and 0.427 (95% CI: 0.191-0.954), respectively. To our knowledge, this is the first report to show that tooth loss-related dietary patterns are associated with a high prevalence of cognitive impairment. These results may motivate changes in dental treatment and the dietary behaviours and thereby lower the risk of cognitive impairment.
Keyphrases
  • cognitive impairment
  • community dwelling
  • heavy metals
  • healthcare
  • magnetic resonance
  • risk factors
  • human health
  • magnetic resonance imaging
  • health risk assessment
  • data analysis
  • drinking water
  • case control