Fatty acid intake and its dietary sources in relation with markers of type 2 diabetes risk: The NEO study.
The aim of this study was to examine the relations between intakes of total, saturated, mono-unsaturated, poly-unsaturated and trans fatty acids (SFA, MUFA, PUFA and TFA), and their dietary sources (dairy, meat and plant) with markers of type 2 diabetes risk.



This was a cross-sectional analysis of baseline data of 5675 non-diabetic, middle-aged participants of the Netherlands Epidemiology of Obesity (NEO) study. Associations between habitual dietary intake and fasting and postprandial blood glucose and insulin, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), HOMA of β-cell function (HOMA-B) and Disposition Index were assessed through multivariable linear regression models with adjustments for demographic, lifestyle and dietary factors.



Mean (s.d.) intakes in percent of energy (En%) were 34.4 (5.8) for total fatty acids, 12.4 (2.9) for SFA, 12.2 (2.4) for MUFA, 6.9 (1.9) for PUFA and 0.6 (0.2) for TFA. As compared with carbohydrates, only SFA was weakly inversely associated with fasting insulin, HOMA-IR and HOMA-B. When stratified by dietary source, all fatty acids from meat were positively associated with fasting insulin - total fatty acidsmeat(per 5 En%: 10.0%; 95% confidence interval: 4.0, 16.3), SFAmeat(per 1 En%: 3.7%; 0.4, 7.2), MUFAmeat(per 1 En%: 5.0%; 2.0, 8.1), PUFAmeat(per 1 En%: 17.3%; 6.0, 29.7) and TFAmeat(per 0.1 En%: 10.5%; 3.2, 18.3). Similarly, all fatty acids from meat were positively associated with HOMA-IR and HOMA-B and inversely with Disposition Index.



Our study suggests that the relations between fatty acid intakes and markers of type 2 diabetes risk may depend on the dietary sources of the fatty acids. More epidemiological studies on diet and cardiometabolic disease are needed, addressing possible interactions between nutrients and their dietary sources.
Unilever R&D, Vlaardingen, The Netherlands.
A J
AJ
Wanders
Unilever R&D, Vlaardingen, The Netherlands.|Department of Epidemiology and Biostatistics and The EMGO Institute for Health and Care Research, VU Medical Center, Amsterdam, The Netherlands.
M
M
Alssema
Department of Nephrology, LUMC, Leiden, The Netherlands.|Department of Endocrinology, LUMC, Leiden, The Netherlands.
E J P
EJ
de Koning
Department of Medical Statistics and Bioinformatics, LUMC, Leiden, The Netherlands.|Department of Clinical Epidemiology, LUMC, Leiden, The Netherlands.
S
S
le Cessie
Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands.
J H
JH
de Vries
Unilever R&D, Vlaardingen, The Netherlands.
P L
PL
Zock
Department of Medical Statistics and Bioinformatics, LUMC, Leiden, The Netherlands.|Department of Thrombosis and Hemostasis, LUMC, Leiden, The Netherlands.
F R
FR
Rosendaal
Department of Clinical Epidemiology, LUMC, Leiden, The Netherlands.|Department of Internal Medicine, VU Medical Center, Amsterdam, The Netherlands.
M den
MD
Heijer
Department of Clinical Epidemiology, LUMC, Leiden, The Netherlands.
R
R
de Mutsert
D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D003430:Cross-Sectional Studies; D003611:Dairy Products / Q000032:analysis; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000209:etiology; D004032:Diet / Q000379:methods*; D004041:Dietary Fats / Q000008:administration & dosage / Q000032:analysis / Q000097:blood*; D002149:Energy Intake / Q000502:physiology; D005215:Fasting / Q000097:blood; D005227:Fatty Acids / Q000008:administration & dosage / Q000032:analysis / Q000097:blood*; D005260:Female; D006801:Humans; D007328:Insulin / Q000097:blood; D016014:Linear Models; D008297:Male; D008460:Meat / Q000032:analysis; D008875:Middle Aged; D009426:Netherlands; D010945:Plants, Edible / Q000737:chemistry; D019518:Postprandial Period / Q000502:physiology*; D012307:Risk Factors
D015415:Biomarkers; D001786:Blood Glucose; D004041:Dietary Fats; D005227:Fatty Acids; D007328:Insulin