Association of Oral Microbiome Diversity With Depression Status: NHANES 2009–2012

萧条(经济学) 全国健康与营养检查调查 置信区间 医学 逻辑回归 优势比 内科学 混淆 人口学 人口 环境卫生 宏观经济学 社会学 经济
作者
Zhang Cui-feng,Lei Qu,Yanhua Huang,Lan Tang,Jie Ma,Kaipeng Xie,Huaying Wu
出处
期刊:Journal of Public Health Dentistry [Wiley]
卷期号:85 (3): 252-260 被引量:2
标识
DOI:10.1111/jphd.12671
摘要

ABSTRACT Objectives To investigate the relationship between oral microbial diversity and depression symptoms in the U.S. population. Methods We utilized the US National Health and Nutrition Examination Survey (NHANES; 2009–2012) to assess the association between oral microbial diversity and depression symptoms. A cut‐off PHQ‐9 score of 15 was used to define severe depression symptoms. We conducted the multivariate linear regression to explore the association of the amplicon sequence variants (ASVs) with PHQ‐9 scores. A restricted cubic spline (RCS) model was introduced to curve the dose‐response relationship. A logistic regression model was used to calculate the odds ratio (OR) and 95% confidence interval (CI) of the association between ASVs and the risk of severe depression symptoms. Based on Bray‐Curtis dissimilarity of beta diversity, analysis of similarity (ANOSIM) is used to assess the dissimilarity between different depression groups. Results A total of 1497 participants were included, with 111 (7.41%) meeting the criteria for severe depression. After adjusting for confounders, we found that ASVs were negatively correlated with PHQ‐9 scores (β = −0.008, p = 0.014). The RCS plot showed a linear relationship ( p non‐linear = 0.232). Logistic regression showed that ASVs were associated with a decreased risk of severe depression symptoms (OR = 0.992, p = 0.003). Analysis of β diversity identified a statistically significant difference (R = 0.087, p = 0.003). Additionally, we developed a nomogram to estimate an individual's risk of severe depression symptoms. Conclusions Alpha diversity of the oral microbiota was associated with a reduced risk of severe depression symptoms, which could contribute to the early identification and intervention of severe depression.
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