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Diet index-based and empirically derived dietary patterns are associated with colorectal cancer risk.

ABSTRACT: Previous studies have derived patterns by measuring compliance with preestablished dietary guidance or empirical methods, such as principal components analysis (PCA). Our objective was to examine colorectal cancer risk associated with patterns identified by both methods. The study included 431 incident colorectal cancer cases (225 men, 206 women) and 726 healthy controls (330 men, 396 women) participating in a population-based, case-control study. PCA identified sex-specific dietary patterns and the Healthy Eating Index-2005 (HEI-05) assessed adherence to the 2005 Dietary Guidelines for Americans. A fruits and vegetables pattern and a meat, potatoes, and refined grains pattern were identified among men and women; a third pattern (alcohol and sweetened beverages) was identified in men. The fruits and vegetables pattern was inversely associated with risk among men [odds ratio (OR) = 0.38, 95% CI = 0.21-0.69 for the highest compared with the lowest quartile] and women (OR = 0.35, 95% CI = 0.19-0.65). The meat, potatoes, and refined grains pattern was positively associated with risk in women (OR = 2.20, 95% CI = 1.08-4.50) and there was a suggestion of a positive association among men (OR = 1.56, 95% CI = 0.84-2.90; P-trend = 0.070). Men and women with greater HEI-05 scores had a significantly reduced risk of colorectal cancer (OR = 0.56, 95% CI = 0.31-0.99; OR = 0.44, 95% CI = 0.24-0.77, respectively). Following the Dietary Guidelines or a dietary pattern lower in meat, potatoes, high fat, and refined foods and higher in fruits and vegetables may reduce colorectal cancer risk.

SUBMITTER: Miller PE

PROVIDER: S-EPMC3499942 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLatent class models (LCMs) have been used in exploring dietary behaviors over a wide set of foods and beverages in a given population, but are prone to overgeneralize these habits in the presence of variation by subpopulations.ObjectivesThis study aimed to highlight unique dietary consumption differences by both study site and ethnic background of Hispanic/Latino populations in the United States, that otherwise might be missed in a traditional LCM of the overall population. This was achieved using a new model-based clustering method, referred to as robust profile clustering (RPC).MethodsA total of 11,320 individuals aged 18-74 y from the Hispanic Community Health Study/Study of Latinos (2008-2011) with complete diet data were classified into 9 subpopulations, defined by study site (Bronx, Chicago, Miami, San Diego) and ethnic background. At baseline, dietary intake was ascertained using a food propensity questionnaire. Dietary patterns were derived from 132 food groups using the RPC method to identify patterns of the general Hispanic/Latino population and those specific to an identified subpopulation. Dietary patterns derived from the RPC were compared to those identified from an LCM.ResultsThe LCM identified 48 shared consumption behaviors of foods and beverages across the entire cohort, whereas significant consumption differences in subpopulations were identified in the RPC model for these same foods. Several foods were common within study site (e.g., chicken, orange juice, milk), ethnic background (e.g., papayas, plantain, coffee), or both (e.g., rice, tomatoes, seafood). Post hoc testing revealed an improved model fit in the RPC model [Deviance Information Criterion DICRPC = 2.3 × 104, DICLCM = 9.5 × 106].ConclusionsDietary pattern behaviors of Hispanics/Latinos in the United States tend to align by ethnic background for some foods and by location for other foods. Consideration of both factors is imperative to better understand their contributions to population health and developing targeted nutrition intervention studies.

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Diet index-based and empirically derived dietary patterns are associated with colorectal cancer risk.

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