Dataset Information

Association of a Dietary Score with Incident Type 2 Diabetes: The Dietary-Based Diabetes-Risk Score (DDS).

ABSTRACT:

Background

Strong evidence supports that dietary modifications may decrease incident type 2 diabetes mellitus (T2DM). Numerous diabetes risk models/scores have been developed, but most do not rely specifically on dietary variables or do not fully capture the overall dietary pattern. We prospectively assessed the association of a dietary-based diabetes-risk score (DDS), which integrates optimal food patterns, with the risk of developing T2DM in the SUN ("Seguimiento Universidad de Navarra") longitudinal study.

Methods

We assessed 17,292 participants initially free of diabetes, followed-up for a mean of 9.2 years. A validated 136-item FFQ was administered at baseline. Taking into account previous literature, the DDS positively weighted vegetables, fruit, whole cereals, nuts, coffee, low-fat dairy, fiber, PUFA, and alcohol in moderate amounts; while it negatively weighted red meat, processed meats and sugar-sweetened beverages. Energy-adjusted quintiles of each item (with exception of moderate alcohol consumption that received either 0 or 5 points) were used to build the DDS (maximum: 60 points). Incident T2DM was confirmed through additional detailed questionnaires and review of medical records of participants. We used Cox proportional hazards models adjusted for socio-demographic and anthropometric parameters, health-related habits, and clinical variables to estimate hazard ratios (HR) of T2DM.

Results

We observed 143 T2DM confirmed cases during follow-up. Better baseline conformity with the DDS was associated with lower incidence of T2DM (multivariable-adjusted HR for intermediate (25-39 points) vs. low (11-24) category 0.43 [95% confidence interval (CI) 0.21, 0.89]; and for high (40-60) vs. low category 0.32 [95% CI: 0.14, 0.69]; p for linear trend: 0.019).

Conclusions

The DDS, a simple score exclusively based on dietary components, showed a strong inverse association with incident T2DM. This score may be applicable in clinical practice to improve dietary habits of subjects at high risk of T2DM and also as an educational tool for laypeople to help them in self-assessing their future risk for developing diabetes.

SUBMITTER: Dominguez LJ

PROVIDER: S-EPMC4636153 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association of a Dietary Score with Incident Type 2 Diabetes: The Dietary-Based Diabetes-Risk Score (DDS).

Dominguez Ligia J LJ Bes-Rastrollo Maira M Basterra-Gortari Francisco Javier FJ Gea Alfredo A Barbagallo Mario M Martínez-González Miguel A MA

PloS one 20151106 11

<h4>Background</h4>Strong evidence supports that dietary modifications may decrease incident type 2 diabetes mellitus (T2DM). Numerous diabetes risk models/scores have been developed, but most do not rely specifically on dietary variables or do not fully capture the overall dietary pattern. We prospectively assessed the association of a dietary-based diabetes-risk score (DDS), which integrates optimal food patterns, with the risk of developing T2DM in the SUN ("Seguimiento Universidad de Navarra ...[more]

PMID: 26544985

Similar Datasets

Project description:The aim of this study was to develop and externally validate a score for use in dental settings to identify those at risk of undiagnosed nondiabetic hyperglycemia (NDH) or type 2 diabetes (T2D). The Studies of Health in Pomerania (SHIP) project comprises 2 representative population-based cohort studies conducted in northeast Germany. SHIP-TREND-0, 2008 to 2012 (the development data set) had 3,339 eligible participants, with 329 having undiagnosed NDH or T2D. Missing data were replaced using multiple imputation. Potential covariates were selected for inclusion in the model using backward elimination. Heuristic shrinkage was used to reduce overfitting, and the final model was adjusted for optimism. We report the full model and a simplified paper-based point-score system. External validation of the model and score employed an independent data set comprising 2,359 participants with 357 events. Predictive performance, discrimination, calibration, and clinical utility were assessed. The final model included age, sex, body mass index, smoking status, first-degree relative with diabetes, presence of a dental prosthesis, presence of mobile teeth, history of periodontal treatment, and probing pocket depths ≥5 mm as well as prespecified interaction terms. In SHIP-TREND-0, the model area under the curve (AUC) was 0.72 (95% confidence interval [CI] 0.69, 0.75), calibration in the large was -0.025. The point score AUC was 0.69 (95% CI 0.65, 0.72), with sensitivity of 77.0 (95% CI 76.8, 77.2), specificity of 51.5 (95% CI 51.4, 51.7), negative predictive value of 94.5 (95% CI 94.5, 94.6), and positive predictive value of 17.0 (95% CI 17.0, 17.1). External validation of the point score gave an AUC of 0.69 (95% CI 0.66, 0.71), sensitivity of 79.2 (95% CI 79.0, 79.4), specificity of 49.9 (95% CI 49.8, 50.00), negative predictive value 91.5 (95% CI 91.5, 91.6), and positive predictive value of 25.9 (95% CI 25.8, 26.0). A validated prediction model involving dental variables can identify NDH or undiagnosed T2DM. Further studies are required to validate the model for different European populations.

Project description:Aims/hypothesisThe T allele of transcription factor 7-like 2 gene variant, TCF7L2 rs7903146, increases the risk of type 2 diabetes by 40-50%. As TCF7L2 rs7903146 has been associated with diminished incretin effect we investigated whether interaction between dietary intake of carbohydrate, fat, protein or fibre and this variant affects the risk of type 2 diabetes.MethodsA cohort of 24,799 non-diabetic individuals from the Malmö Diet and Cancer Study (MDCS), with dietary data obtained by a modified diet history method, were followed up for 12 years, with 1,649 recordings of incident type 2 diabetes made. Risk of type 2 diabetes in strata of diet quintiles was analysed prospectively adjusting for potential confounders. Cross-sectional analyses were performed on baseline fasting glucose and HbA(1c) levels in a subset of 5,216 randomly selected individuals from the MDCS.ResultsThe elevated risk of type 2 diabetes with rs7903146 (OR 1.44, 95% CI 1.33, 1.56, p = 4.6 × 10(-19)) increased with higher intake of dietary fibre (OR 1.24, 95% CI 1.04, 1.47 to OR 1.56, 95% CI 1.31, 1.86 from the lowest to highest quintile; p (interaction) = 0.049). High intake of dietary fibre was inversely associated with diabetes incidence only among CC genotype carriers (OR 0.74, 95% CI 0.58, 0.94 per quintile, p = 0.025). The T allele was associated with 0.027% elevated HbA(1c) (p = 0.02) and this effect increased with higher intake of fibre (from -0.021% to 0.079% for the lowest to the highest quintile, p (interaction) = 0.02). Each quintile of higher fibre intake was associated with lower HbA(1c) levels among CC and CT but not among TT genotype carriers (-0.036%, p = 6.5 × 10(-7); -0.023%, p = 0.009; and 0.012%, p = 0.52, respectively).Conclusions/interpretationOur study suggests that dietary fibre intake may modify the association between TCF7L2 rs7903146 and incidence of type 2 diabetes, and that higher fibre intake may associate with protection from type 2 diabetes only among non-risk allele carriers.

Project description:ImportanceAccumulating epidemiologic evidence has suggested favorable associations between plant-based dietary patterns and risk of type 2 diabetes, although there is a lack of a quantitative summary of evidence substantiating this important association.ObjectiveTo quantitatively synthesize available prospective observational evidence on the association between plant-based dietary patterns and risk of type 2 diabetes.Data sourcesA systematic search of PubMed and MEDLINE, Embase, Web of Science, and reference lists through February 15, 2019, was conducted. Data analysis was conducted between December 2018 and February 2019.Study selectionAll prospective observational studies that examined the association between adherence to plant-based dietary patterns and incidence of type 2 diabetes among adults 18 years or older were identified.Data extraction and synthesisMeta-analysis of Observational Studies in Epidemiology guidelines for data abstraction and reporting were followed, and a National Heart, Lung, and Blood Institute assessment tool was used to evaluate study quality. Two authors independently conducted full-text assessments and data abstraction. Meta-analysis was conducted using the random-effects method to calculate the overall relative risk (RR) and 95% CI.Main outcomes and measuresLevel of adherence to a plant-based diet and incidence of type 2 diabetes.ResultsA total of 9 studies were identified, totaling 307 099 participants with 23 544 cases of incident type 2 diabetes. A significant inverse association was observed between higher adherence to a plant-based dietary pattern and risk of type 2 diabetes (RR, 0.77; 95% CI, 0.71-0.84) in comparison with poorer adherence, with modest heterogeneity across studies (I2 = 44.5%; P = .07 for heterogeneity). Similar findings were obtained when using the fixed-effects model (RR, 0.80; 95% CI, 0.75-0.84). Consistent associations were observed across predefined subgroups. This association was strengthened when healthy plant-based foods, such as fruits, vegetables, whole grains, legumes, and nuts, were included in the definition of plant-based patterns (RR, 0.70; 95% CI, 0.62-0.79). Most studies were deemed to have good quality in terms of dietary assessment, disease outcomes, and statistical adjustment for confounding factors. Using restricted cubic splines, a significant inverse linear dose-response association was identified between plant-based dietary indices and risk of type 2 diabetes.Conclusions and relevancePlant-based dietary patterns, especially when they are enriched with healthful plant-based foods, may be beneficial for the primary prevention of type 2 diabetes.

Project description:ContextEarly diagnosis of type 2 diabetes is crucial to reduce severe comorbidities and complications. Current screening recommendations for type 2 diabetes include traditional risk factors, primarily body mass index (BMI) and family history, however genetics also plays a key role in type 2 diabetes risk. It is important to understand whether genetic predisposition to type 2 diabetes modifies the effect of these traditional factors on type 2 diabetes risk.ObjectiveThis work aimed to investigate whether genetic risk of type 2 diabetes modifies associations between BMI and first-degree family history of diabetes with 1) prevalent prediabetes or undiagnosed diabetes; and 2) incident confirmed type 2 diabetes.MethodsWe included 431 658 individuals aged 40 to 69 years at baseline of multiethnic ancestry from the UK Biobank. We used a multiethnic polygenic risk score for type 2 diabetes (PRST2D) developed by Genomics PLC. Prediabetes or undiagnosed diabetes was defined as baseline glycated hemoglobin greater than or equal to 42 mmol/mol (6.0%), and incident type 2 diabetes was derived from medical records.ResultsAt baseline, 43 472 participants had prediabetes or undiagnosed diabetes, and 17 259 developed type 2 diabetes over 15 years follow-up. Dose-response associations were observed for PRST2D with each outcome in each category of BMI or first-degree family history of diabetes. Those in the highest quintile of PRST2D with a normal BMI were at a similar risk as those in the middle quintile who were overweight. Participants who were in the highest quintile of PRST2D and did not have a first-degree family history of diabetes were at a similar risk as those with a family history who were in the middle category of PRST2D.ConclusionGenetic risk of type 2 diabetes remains strongly associated with risk of prediabetes, undiagnosed diabetes, and future type 2 diabetes within categories of nongenetic risk factors. This could have important implications for identifying individuals at risk of type 2 diabetes for prevention and early diagnosis programs.

Dataset Information

Association of a Dietary Score with Incident Type 2 Diabetes: The Dietary-Based Diabetes-Risk Score (DDS).

Background

Methods

Results

Conclusions

Publications

Association of a Dietary Score with Incident Type 2 Diabetes: The Dietary-Based Diabetes-Risk Score (DDS).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets