Objectives To investigate the association between long term intake of individual saturated fatty acids (SFAs) and the risk of coronary heart disease, in two large cohort studies. Design Prospective, longitudinal cohort study.Setting Health professionals in the United States.Participants 73 147 women in the Nurses’ Health Study (1984-2012) and 42 635 men in the Health Professionals Follow-up Study (1986-2010), who were free of major chronic diseases at baseline.Main outcome measure Incidence of coronary heart disease (n=7035) was self-reported, and related deaths were identified by searching National Death Index or through report of next of kin or postal authority. Cases were confirmed by medical records review.Results Mean intake of SFAs accounted for 9.0-11.3% energy intake over time, and was mainly composed of lauric acid (12:0), myristic acid (14:0), palmitic acid (16:0), and stearic acid (18:0; 8.8-10.7% energy). Intake of 12:0, 14:0, 16:0 and 18:0 were highly correlated, with Spearman correlation coefficients between 0.38 and 0.93 (all P<0.001). Comparing the highest to the lowest groups of individual SFA intakes, hazard ratios of coronary heart disease were 1.07 (95% confidence interval 0.99 to 1.15; Ptrend=0.05) for 12:0, 1.13 (1.05 to 1.22; Ptrend<0.001) for 14:0, 1.18 (1.09 to 1.27; Ptrend<0.001) for 16:0, 1.18 (1.09 to 1.28; Ptrend<0.001) for 18:0, and 1.18 (1.09 to 1.28; Ptrend<0.001) for all four SFAs combined (12:0-18:0), after multivariate adjustment of lifestyle factors and total energy intake. Hazard ratios of coronary heart disease for isocaloric replacement of 1% energy from 12:0-18:0 were 0.92 (95% confidence interval 0.89 to 0.96; P<0.001) for polyunsaturated fat, 0.95 (0.90 to 1.01; P=0.08) for monounsaturated fat, 0.94 (0.91 to 0.97; P<0.001) for whole grain carbohydrates, and 0.93 (0.89 to 0.97; P=0.001) for plant proteins. For individual SFAs, the lowest risk of coronary heart disease was observed when the most abundant SFA, 16:0, was replaced. Hazard ratios of coronary heart disease for replacing 1% energy from 16:0 were 0.88 (95% confidence interval 0.81 to 0.96; P=0.002) for polyunsaturated fat, 0.92 (0.83 to 1.02; P=0.10) for monounsaturated fat, 0.90 (0.83 to 0.97; P=0.01) for whole grain carbohydrates, and 0.89 (0.82 to 0.97; P=0.01) for plant proteins.Conclusions Higher dietary intakes of major SFAs are associated with an increased risk of coronary heart disease. Owing to similar associations and high correlations among individual SFAs, dietary recommendations for the prevention of coronary heart disease should continue to focus on replacing total saturated fat with more healthy sources of energy.

Background: The association between saturated fatty acid (SFA) intake and ischemic heart disease (IHD) risk is debated. Objective: We sought to investigate whether dietary SFAs were associated with IHD risk and whether associations depended on 1) the substituting macronutrient, 2) the carbon chain length of SFAs, and 3) the SFA food source. Design: Baseline (1993-1997) SFA intake was measured with a foodfrequency questionnaire among 35,597 participants from the European Prospective Investigation into Cancer and Nutrition-Netherlands cohort. IHD risks were estimated with multivariable Cox regression for the substitution of SFAs with other macronutrients and for higher intakes of total SFAs, individual SFAs, and SFAs from different food sources. Results: During 12 y of follow-up, 1807 IHD events occurred. Total SFA intake was associated with a lower IHD risk (HR per 5% of energy: 0.83; 95% CI: 0.74, 0.93). Substituting SFAs with animal protein, cis monounsaturated fatty acids, polyunsaturated fatty acids (PUFAs), or carbohydrates was significantly associated with higher IHD risks (HR per 5% of energy: 1.27-1.37). Slightly lower IHD risks were observed for higher intakes of the sum of butyric (4: Conclusions:In this Dutch population, higher SFA intake was not associated with higher IHD risks. The lower IHD risk observed did not depend on the substituting macronutrient but appeared to be driven mainly by the sums of butyric through capric acid, the sum of pentadecylic and margaric acid, myristic acid, and SFAs from dairy sources. Residual confounding by cholesterol-lowering therapy and trans fat or limited variation in SFA and PUFA intake may explain our findings. Analyses need to be repeated in populations with larger differences in SFA intake and different SFA food sources.Am J Clin Nutr 2016;103:356-65.

OBJECTIVETo investigate the relationship among A1C, fasting plasma glucose (FPG), and 2-h postload plasma glucose in the Dutch general population and to evaluate the results of using A1C for screening and diagnosis of diabetes.RESEARCH DESIGN AND METHODSIn 2006–2007, 2,753 participants of the New Hoorn Study, aged 40–65 years, who were randomly selected from the population of Hoorn, the Netherlands, underwent an oral glucose tolerance test (OGTT). Glucose status (normal glucose metabolism [NGM], intermediate hyperglycemia, newly diagnosed diabetes, and known diabetes) was defined by the 2006 World Health Organization criteria. Spearman correlations were used to investigate the agreement between markers of hyperglycemia, and a receiver operating characteristic (ROC) curve was calculated to evaluate the use of A1C to identify newly diagnosed diabetes.RESULTSIn the total population, the correlations between fasting plasma glucose and A1C and between 2-h postload plasma glucose and A1C were 0.46 and 0.33, respectively. In patients with known diabetes, these correlations were 0.71 and 0.79. An A1C level of ≥5.8%, representing 12% of the population, had the highest combination of sensitivity (72%) and specificity (91%) for identifying newly diagnosed diabetes. This cutoff point would identify 72% of the patients with newly diagnosed diabetes and include 30% of the individuals with intermediate hyperglycemia.CONCLUSIONSIn patients with known diabetes, correlations between glucose and A1C are strong; however, moderate correlations were found in the general population. In addition, based on the diagnostic properties of A1C defined by ROC curve analysis, the advantage of A1C compared with OGTT for the diagnosis of diabetes is limited.