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Evidence-Based Guideline of the German Nutrition Society: Fat Intake and Prevention of Selected Nutrition-Related Diseases
Abstract
As nutrition-related chronic diseases have become more and more frequent, the importance of dietary prevention has also increased. Dietary fat plays a major role in human nutrition, and modification of fat and/or fatty acid intake could have a preventive potential. The aim of the guideline of the German Nutrition Society (DGE) was to systematically evaluate the evidence for the prevention of the widespread diseases obesity, type 2 diabetes mellitus, dyslipoproteinaemia, hypertension, metabolic syndrome, coronary heart disease (CHD), stroke, and cancer through the intake of fat or fatty acids. The main results can be summarized as follows: it was concluded with convincing evidence that a reduced intake of total and saturated fat as well as a larger intake of polyunsaturated fatty acids (PUFA) at the expense of saturated fatty acids (SFA) reduces the concentration of total and low-density lipoprotein cholesterol in plasma. Furthermore, there is convincing evidence that a high intake of trans fatty acids increases risk of dyslipoproteinaemia and that a high intake of long-chain polyunsaturated n-3 fatty acids reduces the triglyceride concentration in plasma. A high fat intake increases the risk of obesity with probable evidence when total energy intake is not controlled for (ad libitum diet). When energy intake is controlled for, there is probable evidence for no association between fat intake and risk of obesity. A larger intake of PUFA at the expense of SFA reduces risk of CHD with probable evidence. Furthermore, there is probable evidence that a high intake of long-chain polyunsaturated n-3 fatty acids reduces risk of hypertension and CHD. With probable evidence, a high trans fatty acid intake increases risk of CHD. The practical consequences for current dietary recommendations are described at the end of this article.
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“Most CPGs included in this meta-epidemiologic study (96%) focused on populations with conditions related to a single major health outcome of interest (general health promotion, autoimmune diseases, cancers, CVD, digestive conditions, T2D, and weight-related conditions), but 3 CPGs focused on 2 or more chronic diseases (Supplemental Table 1) [[30], [31], [32]].”
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Dawczynski, C., Kleber, M. E., März, W., Jahreis, G., & Stefan Lorkowski, A. (2014) · Annals of Internal Medicine · doi:10.7326/l14-5018-2 · Cited by 7
Plasma Phospholipid Long-Chain n-3 Polyunsaturated Fatty Acids and Body Weight Change
Jakobsen, M. U., Dethlefsen, C., Due, K. M., Slimani, N., Chajès, V., May, A. M., Sørensen, T. I. A., Halkjær, J., Tjønneland, A. M., Clavel‐Chapelon, F., et al. (2011) · Obesity Facts · doi:10.1159/000330710 · Cited by 6
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2 of the 299 references couldn’t be matched to a known paper.
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Nordic Nutrition Recommendations 2023
Blomhoff, R., Andersen, R., Arnesen, E., Christensen, J. J., Eneroth, H., Erkkola, M., Gudanaviciene, I., Halldorsson, T. I., Høyer-Lund, A., Lemming, E. W., et al. (2023) · Nordic Council of Ministers eBooks · doi:10.6027/nord2023-003 · Cited by 455
Grebenteuch, S., Kroh, L. W., Drusch, S., & Rohn, S. (2021) · Foods · doi:10.3390/foods10102417 · Cited by 197
Bechthold, A., Boeing, H., Tetens, I., Schwingshackl, L., & Nöthlings, U. (2018) · Advances in Nutrition · doi:10.1093/advances/nmy033 · Cited by 160
Sioen, I., van Lieshout, L., Eilander, A., Fleith, M., Lohner, S., Szommer, A., Petisca, C., Eussen, S. R. B. M., Forsyth, S. J., Calder, P. C., et al. (2017) · Annals of Nutrition and Metabolism · doi:10.1159/000456723 · Cited by 150
Relative validation of a food frequency questionnaire to estimate food intake in an adult population
Steinemann, N., Grize, L., Ziesemer, K., Kauf, P., Probst-Hensch, N. M., & Brombach, C. (2017) · Food & Nutrition Research · doi:10.1080/16546628.2017.1305193 · Cited by 141
Metadata
- Authors
- Wolfram, G., Bechthold, A., Boeing, H., Ellinger, S., Hauner, H., Kroke, A., Leschik-Bonnet, E., Linseisen, J., Lorkowski, S., Schulze, M., Stehle, P., & Dinter, J.
- Affiliations
- Technical University of Munich (DE)
- Fulda University of Applied Sciences (DE)
- Friedrich Schiller University Jena (DE)
- Helmholtz Munich (DE)
- German Institute of Human Nutrition (DE)
- Corresponding author
- Dinter, Jessica
- ORCID
- Venue
- Annals of Nutrition and Metabolism
- Publisher
- S. Karger AG
- Published
- 2015
- Volume
- 67
- Issue
- 3
- Pages
- 141-204
- ISSN
- 0250-6807 (ISSN-L)
- 1421-9697
- OpenAlex
- W1894359789
- Cited by
- 94
- References
- 299
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 9 · 2023: 11 · 2022: 12 · 2021: 11 · 2020: 6 · 2019: 6 · 2018: 15 · 2017: 10 · 2016: 4 · 2015: 1
- FWCI
- 9.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annals of Nutrition and Metabolism (publishedVersion)
- PubMed (publishedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion)
- Site cant be reached (submittedVersion)
- OPUS (Augsburg University) (submittedVersion)
- Topics
- Health Sciences › Nursing › Nutrition and Dietetics › Fatty Acid Research and Health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Life Sciences › Agricultural and Biological Sciences › Food Science › Nutrition, Health, and Society Studies
- Keywords
- dietary fat, fatty acids, nutrition-related chronic diseases, disease prevention, saturated fat, polyunsaturated fatty acids, trans fatty acids, omega-3 fatty acids, LDL cholesterol, dyslipoproteinemia, obesity, type 2 diabetes, hypertension, metabolic syndrome, coronary artery disease, stroke, cancer, dietary recommendations
- MeSH terms
- Energy Intake, Coronary Disease, Diabetes Mellitus, Type 2, Dietary Fats, Humans, Hypertension, Neoplasms, Diet, Fat-Restricted, Stroke, Metabolic Syndrome, Dyslipidemias, Evidence-Based Practice, Recommended Dietary Allowances
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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