Dietary Flavonoid Intake and Smoking-Related Cancer Risk: A Meta-Analysis

<div><p>Purpose</p><p>To systematically investigate the effects of dietary flavonoids and flavonoid subclasses on the risk of smoking-related cancer in observational studies.</p> <p>Methods</p><p>Summary estimates and corresponding standard errors were calculated using the multivariate-adjusted odds ratio (OR) or relative risk (RR) and 95% CI of selected studies and weighted by the inverse variance.</p> <p>Results</p><p>A total of 35 studies, including 19 case-controls (9,525 cases and 15,835 controls) and 15 cohort studies (988,082 subjects and 8,161 cases), were retrieved for the meta-analysis. Total dietary flavonoids and most of the flavonoid subclasses were inversely associated with smoking-related cancer risk (OR: 0.82, 95% CI: 0.72-0.93). In subgroup analyses by cancer site, significant associations were observed in aerodigestive tract and lung cancers. Total dietary flavonoid intake was significantly associated with aerodigestive tract cancer risk (OR: 0.67, 95% CI: 0.54-0.83) marginally associated with lung cancer risk (OR: 0.84, 95% CI: 0.71-1.00). Subgroup analyses by smoking status showed significantly different results. The intake of total flavonoids, flavonols, flavones, and flavanones, as well as the flavonols quercetin and kaempferol was significantly associated with decreased risk of smoking-related cancer in smokers, whereas no association was observed in non-smokers, except for flavanones. In meta-analysis for the effect of subclasses of dietary flavonoids by cancer type, aerodigestive tract cancer was inversely associated with most flavonoid subclasses.</p> <p>Conclusion</p><p>The protective effects of flavonoids on smoking-related cancer risk varied across studies, but the overall results indicated that intake of dietary flavonoids, especially flavonols, was inversely associated with smoking-related cancer risk. The protective effects of flavonoids on smoking-related cancer risk were more prominent in smokers.</p> </div

Subgroup analysis of the association between cancer risks and global DNA hypomethylation in peripheral blood leukocytes.

<p>(A) %5-mC, (B) LINE-1, and (C) LINE-1 used same target sequence. The association between bladder cancer risk and global DNA hypomethylation (D). R: random effects model. Summary estimates were calculated based on a fixed effects model, unless otherwise stated.</p

Studies on global DNA hypomethylation in peripheral blood leukocytes and cancer risk included in the meta-analysis.

†<p>OR (95% CI) was recalculated because the reference was the lowest tertile of genomic methylation in the original result.</p><p>T: tertile, Q: quartile, %5-mC: percentage of 5-methyl cytosine, LINE-1: long interspersed nucleotide element 1, LRE1: LINE retrotransposable element 1.</p

Flow diagram of study selection.

<p>Flow diagram of study selection.</p

Flow diagram of study selection.

<p>Flow diagram of study selection.</p

Forest plot of the association between cancer risks and global DNA hypomethylation in peripheral blood leukocytes.

<p>Colorectal A: Colorectal Adenoma, Methyl: Methyl acceptance assay, LINE-1: Long interspersed nuclear elements, and %5-mC: Percentages of 5-methylcytosine. F: Fixed effects model, R: random effects model. The horizontal lines through the boxes represent 95% confidence intervals (CI). The centers of the boxes are situated in the point estimate (OR/RR), and the bigger boxes mean studies have relatively greater influence in the summary estimates.</p

Factor loadings of the dietary patterns derived from principal components analysis with orthogonal rotation.

<p>Factor loadings with absolute values <0.2 are not presented.</p><p>Factor loadings of the dietary patterns derived from principal components analysis with orthogonal rotation.</p

PRs and 95% CIs of metabolic syndrome by quartiles of dietary patterns.

<p>PR: prevalence ratio, CI: confidence interval.</p><p>*Trend test were performed by Wald test using continuous variables of each pattern score (log-transformed).</p>†<p>Adjusted for age, sex (for total) and total energy intake.</p>‡<p>Adjusted for age, sex (for total), total energy intake, smoking status, alcohol consumption, and physical activity (log-transformed).</p>§<p>PR (95% CI), compared with quartile 1 as a reference.</p><p>PRs and 95% CIs of metabolic syndrome by quartiles of dietary patterns.</p

The association between dietary patterns and the components of metabolic syndrome and BMI^*.

<p>*Participants who were taking medication for hypertension and elevated glucose were excluded for the analysis of the components of metabolic syndrome and BMI.</p>†<p>General linear model with adjustments for age, sex, smoking status, alcohol consumption, total energy intake, and physical activity (log-transformed) for the analysis of the components of metabolic syndrome and BMI, and adjustments for total energy intake for the analysis of nutrients.</p>‡<p>Regression analysis in log-log scale with adjustments for age, sex, smoking status, alcohol consumption, total energy intake, and physical activity (log-transformed) for the analysis of the components of metabolic syndrome and BMI, and adjustments for total energy intake for the analysis of nutrients.</p>§<p>Least squares means (SE) adjusted for total energy intake.</p><p>Numbers are Mean (SD), unless otherwise stated.</p><p>The association between dietary patterns and the components of metabolic syndrome and BMI^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111593#nt105" target="_blank">*</a>}.</p

Dietary Patterns of Korean Adults and the Prevalence of Metabolic Syndrome: A Cross-Sectional Study

<div><p>The prevalence of metabolic syndrome has been increasing in Korea and has been associated with dietary habits. The aim of our study was to identify the relationship between dietary patterns and the prevalence of metabolic syndrome. Using a validated food frequency questionnaire, we employed a cross-sectional design to assess the dietary intake of 1257 Korean adults aged 31 to 70 years. To determine the participants’ dietary patterns, we considered 37 predefined food groups in principal components analysis. Metabolic syndrome was defined according to the National Cholesterol Education Program Adult Treatment Panel III. The abdominal obesity criterion was modified using Asian guidelines. Prevalence ratios and 95% confidence intervals for the metabolic syndrome were calculated across the quartiles of dietary pattern scores using log binomial regression models. The covariates used in the model were age, sex, total energy intake, tobacco intake, alcohol consumption, and physical activity. The prevalence of metabolic syndrome was 19.8% in men and 14.1% in women. The PCA identified three distinct dietary patterns: the ‘traditional’ pattern, the ‘meat’ pattern, and the ‘snack’ pattern. There was an association of increasing waist circumference and body mass index with increasing score in the meat dietary pattern. The multivariate-adjusted prevalence ratio of metabolic syndrome for the highest quartile of the meat pattern in comparison with the lowest quartile was 1.47 (95% CI: 1.00–2.15, p for trend = 0.016). A positive association between the prevalence of metabolic syndrome and the dietary pattern score was found only for men with the meat dietary pattern (2.15, 95% CI: 1.10–4.21, p for trend = 0.005). The traditional pattern and the snack pattern were not associated with an increased prevalence of metabolic syndrome. The meat dietary pattern was associated with a higher prevalence of metabolic syndrome in Korean male adults.</p></div