| Title |
Gaussian graphical models identified food intake networks and risk of type 2 diabetes, CVD, and cancer in the EPIC-Potsdam study
|
|---|---|
| Published in |
European Journal of Nutrition, May 2018
|
| DOI | 10.1007/s00394-018-1714-1 |
| Pubmed ID | |
| Authors |
Khalid Iqbal, Lukas Schwingshackl, Anna Floegel, Carolina Schwedhelm, Marta Stelmach-Mardas, Clemens Wittenbecher, Cecilia Galbete, Sven Knüppel, Matthias B. Schulze, Heiner Boeing |
| Abstract |
The aim of the study was to investigate the association between the previously identified Gaussian graphical models' (GGM) food intake networks and risk of major chronic diseases as well as intermediate biomarkers in the European Prospective Investigation into Cancer and nutrition (EPIC)-Potsdam cohort. In this cohort analysis of 10,880 men and 13,340 women, adherence to the previously identified sex-specific GGM networks as well as principal component analysis identified patterns was investigated in relation to risk of major chronic diseases, using Cox-proportional hazard models. Associations of the patterns with intermediate biomarkers were cross-sectionally analyzed using multiple linear regressions. Results showed that higher adherence to the GGM Western-type pattern was associated with increased risk (Hazard Ratio: 1.55; 95% CI 1.13-2.15; P trend = 0.004) of type 2 diabetes (T2D) in women, whereas adherence to a high-fat dairy (HFD) pattern was associated with lower risk of T2D both in men (0.69; 95% CI 0.54-0.89; P trend < 0.001) and women (0.71; 95% CI: 0.53, 0.96; P trend = 0.09). Among PCA patterns, HFD pattern was associated with lower risk of T2D (0.74; 95% CI 0.58-0.95; P trend < 0.001) in men and bread and sausage pattern was associated with higher risk of T2D (1.79; 95% CI 1.29-2.48; P trend < 0.001) in women. Moreover, The GGM-HFD pattern was positively associated with HDL-C in men and inversely associated with C-reactive protein in women. Overall, these results show that GGM-identified networks reflect dietary patterns, which could also be related to risk of chronic diseases. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Greece | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 10% |
| Student > Bachelor | 6 | 10% |
| Student > Doctoral Student | 5 | 8% |
| Student > Master | 4 | 7% |
| Librarian | 2 | 3% |
| Other | 9 | 15% |
| Unknown | 27 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 10 | 17% |
| Medicine and Dentistry | 9 | 15% |
| Neuroscience | 2 | 3% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 6 | 10% |
| Unknown | 30 | 51% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 May 2018.
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#20,493,046
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Outputs from European Journal of Nutrition
#2,144
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Outputs of similar age from European Journal of Nutrition
#55
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