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. 2023 Sep 25;15(19):4126.
doi: 10.3390/nu15194126.

Association of Dietary Flavonoid Intake with Serum Cotinine Levels in the General Adult Population

Affiliations

Association of Dietary Flavonoid Intake with Serum Cotinine Levels in the General Adult Population

Ning Zhu et al. Nutrients. .

Abstract

Cotinine, the primary metabolite of nicotine, can be utilized as a marker for active smoking and as an indicator of exposure to secondhand smoke. However, the direct relationship between dietary flavonoid intake and serum cotinine levels remains a subject of ongoing investigation. In this study, we utilized data from the National Health and Nutrition Examination Survey (NHANES) 2007-2010 and 2017-2018 to assess the association between dietary flavonoid intake and serum cotinine levels in adults through multiple linear regression analysis. A weighted quantile sum (WQS) regression model was used to assess the association of the mixture of six dietary flavonoids with serum cotinine levels in adults, which could represent the overall effect of the mixture of six dietary flavonoids. We also conducted stratified analyses by smoke status to explore multiple linear regression associations between different flavonoid intake and serum cotinine levels. A total of 14,962 adults were included in the study. Compared to the group with the lowest dietary flavonoid intake, total flavonoid intake in the second (β = -0.29 [-0.44, -0.14]), third (β = -0.41 [-0.58, -0.24]), and highest groups (β = -0.32 [-0.49, -0.16]) was inversely related to the levels of serum cotinine after adjusting the full model. An RCS model showed that when the total dietary flavonoid intake was less than 99.61 mg/day, there was a negative linear association between dietary flavonoid intake and the serum cotinine. The WQS regression model also showed that the intake of a mixture of six dietary flavonoids was significantly negatively correlated with serum cotinine levels (β = -0.54 [-0.61, -0.46], p <0.01), with anthocyanins having the greatest effect (weights = 32.30%). Our findings imply a significant correlation between dietary flavonoid intake and serum cotinine levels among adults. The consumption of a combination of six dietary flavonoids was consistently linked to lower serum cotinine levels, with anthocyanins displaying the most pronounced impact.

Keywords: National Health and Nutrition Examination Survey; dietary flavonoids; serum cotinine; smoking status; weighted quantile sum.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Restricted cubic spline (RCS) analysis with multivariate-adjusted associations between dietary flavonoids ((A) Isoflavones; (B) Anthocyanidins; (C) Flavan-3-ols; (D) Flavanones; (E) Flavones; (F) Flavonols; (G) Total flavonoids) and serum cotinine levels in adults. Models are adjusted for age (20–39, 40–59, or ≥60), sex (male or female), and race/ethnicity (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, or Other), education level (below high school, high school, or above high school), family PIR (≤1.0, 1.1–3.0, or >3.0), drinking status (nondrinker, low-to-moderate drinker, or heavy drinker), energy intake levels (in quartiles), BMI (<25.0, 25.0–29.9, or >29.9), supplement use (yes or no), and smoking status (never smoker, former smoker, or current smoker).
Figure 2
Figure 2
Weights from weighted quantile sum regression (WQS) for mixture of six dietary flavonoids in relation to serum cotinine levels in adults. Models are adjusted for age (20–39, 40–59, or ≥60), sex (male or female), and race/ethnicity (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, or Other), education level (below high school, high school, or above high school), family PIR (≤1.0, 1.1–3.0, or >3.0), drinking status (nondrinker, low-to-moderate drinker, or heavy drinker), energy intake levels (in quartiles), BMI (<25.0, 25.0–29.9, or >29.9), supplement use (yes or no), and smoking status (never smoker, former smoker, or current smoker).

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Grants and funding

This study was supported by the Science and Technology Innovation 2025 Major Project of Ningbo (2019B10037).

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