Dataset Information

Diet-quality scores and the risk of type 2 diabetes in men.

ABSTRACT:

Objective

To 1) compare associations of diet-quality scores, which were inversely associated with cardiovascular disease, with incident type 2 diabetes and 2) test for differences in absolute-risk reduction across various strata.

Research design and methods

Men from the Health Professionals Follow-Up Study, who were initially free of type 2 diabetes, cardiovascular disease, or cancer (n = 41,615), were followed for ? 20 years. The Healthy Eating Index (HEI) 2005, the alternative HEI (aHEI) the Recommended Food Score, the alternative Mediterranean Diet (aMED) Score, and the Dietary Approaches to Stop Hypertension (DASH) Score were calculated from food-frequency questionnaires. Cox proportional hazard models with time-varying covariates were used to assess risk by quintiles and continuous intervals.

Results

There were 2,795 incident cases of type 2 diabetes. After multivariate adjustment, the aHEI, aMED, and DASH scores were significantly associated with reduced risk. A 1-SD increase was associated with 9-13% reduced risk (P < 0.01), and the DASH score was associated with lower risk independent of other scores. These scores were associated with lower absolute risk among those who were overweight or obese compared with normal weight (P for interaction < 0.01).

Conclusions

Several diet-quality scores were associated with a lower risk of type 2 diabetes and reflect a common dietary pattern characterized by high intakes of plant-based foods such as whole grains; moderate alcohol; and low intakes of red and processed meat, sodium, sugar-sweetened beverages, and trans fat. High-quality diets may yield the greatest reduction in diabetes cases when followed by those with a high BMI.

SUBMITTER: de Koning L

PROVIDER: S-EPMC3114491 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Publications

Diet-quality scores and the risk of type 2 diabetes in men.

de Koning Lawrence L Chiuve Stephanie E SE Fung Teresa T TT Willett Walter C WC Rimm Eric B EB Hu Frank B FB

Diabetes care 20110404 5

<h4>Objective</h4>To 1) compare associations of diet-quality scores, which were inversely associated with cardiovascular disease, with incident type 2 diabetes and 2) test for differences in absolute-risk reduction across various strata.<h4>Research design and methods</h4>Men from the Health Professionals Follow-Up Study, who were initially free of type 2 diabetes, cardiovascular disease, or cancer (n = 41,615), were followed for ≤ 20 years. The Healthy Eating Index (HEI) 2005, the alternative H ...[more]

PMID: 21464460

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Project description:BackgroundBoth genetic and lifestyle factors contribute to the risk of type 2 diabetes, but the extent to which there is a synergistic effect of the 2 factors is unclear. The aim of this study was to examine the joint associations of genetic risk and diet quality with incident type 2 diabetes.Methods and findingsWe analyzed data from 35,759 men and women in the United States participating in the Nurses' Health Study (NHS) I (1986 to 2016) and II (1991 to 2017) and the Health Professionals Follow-up Study (HPFS; 1986 to 2016) with available genetic data and who did not have diabetes, cardiovascular disease, or cancer at baseline. Genetic risk was characterized using both a global polygenic score capturing overall genetic risk and pathway-specific polygenic scores denoting distinct pathophysiological mechanisms. Diet quality was assessed using the Alternate Healthy Eating Index (AHEI). Cox models were used to calculate hazard ratios (HRs) for type 2 diabetes after adjusting for potential confounders. With over 902,386 person-years of follow-up, 4,433 participants were diagnosed with type 2 diabetes. The relative risk of type 2 diabetes was 1.29 (95% confidence interval [CI] 1.25, 1.32; P < 0.001) per standard deviation (SD) increase in global polygenic score and 1.13 (1.09, 1.17; P < 0.001) per 10-unit decrease in AHEI. Irrespective of genetic risk, low diet quality, as compared to high diet quality, was associated with approximately 30% increased risk of type 2 diabetes (Pinteraction = 0.69). The joint association of low diet quality and increased genetic risk was similar to the sum of the risk associated with each factor alone (Pinteraction = 0.30). Limitations of this study include the self-report of diet information and possible bias resulting from inclusion of highly educated participants with available genetic data.ConclusionsThese data provide evidence for the independent associations of genetic risk and diet quality with incident type 2 diabetes and suggest that a healthy diet is associated with lower diabetes risk across all levels of genetic risk.

Project description:ObjectiveTo evaluate current risk models and scores for type 2 diabetes and inform selection and implementation of these in practice.DesignSystematic review using standard (quantitative) and realist (mainly qualitative) methodology. Inclusion criteria Papers in any language describing the development or external validation, or both, of models and scores to predict the risk of an adult developing type 2 diabetes.Data sourcesMedline, PreMedline, Embase, and Cochrane databases were searched. Included studies were citation tracked in Google Scholar to identify follow-on studies of usability or impact.Data extractionData were extracted on statistical properties of models, details of internal or external validation, and use of risk scores beyond the studies that developed them. Quantitative data were tabulated to compare model components and statistical properties. Qualitative data were analysed thematically to identify mechanisms by which use of the risk model or score might improve patient outcomes.Results8864 titles were scanned, 115 full text papers considered, and 43 papers included in the final sample. These described the prospective development or validation, or both, of 145 risk prediction models and scores, 94 of which were studied in detail here. They had been tested on 6.88 million participants followed for up to 28 years. Heterogeneity of primary studies precluded meta-analysis. Some but not all risk models or scores had robust statistical properties (for example, good discrimination and calibration) and had been externally validated on a different population. Genetic markers added nothing to models over clinical and sociodemographic factors. Most authors described their score as "simple" or "easily implemented," although few were specific about the intended users and under what circumstances. Ten mechanisms were identified by which measuring diabetes risk might improve outcomes. Follow-on studies that applied a risk score as part of an intervention aimed at reducing actual risk in people were sparse.ConclusionMuch work has been done to develop diabetes risk models and scores, but most are rarely used because they require tests not routinely available or they were developed without a specific user or clear use in mind. Encouragingly, recent research has begun to tackle usability and the impact of diabetes risk scores. Two promising areas for further research are interventions that prompt lay people to check their own diabetes risk and use of risk scores on population datasets to identify high risk "hotspots" for targeted public health interventions.

Dataset Information

Diet-quality scores and the risk of type 2 diabetes in men.

Objective

Research design and methods

Results

Conclusions

Publications

Diet-quality scores and the risk of type 2 diabetes in men.

Similar Datasets

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