Adherence to a food group-based dietary guideline and incidence of prediabetes and type 2 diabetes.

PURPOSE: In this study, we investigated the association between adherence to the Dutch Healthy Diet index 2015 (DHD15-index) and incidence of prediabetes (preT2D) and Type 2 Diabetes (T2D) in a representative sample for the general Dutch population. METHODS: Two prospective cohort studies, The Hoorn and The New Hoorn Study, were used for data analyses. In total, data from 2951 participants without diabetes at baseline (mean age 56.5 ± 7.5 years; 49.6% male) were harmonized. Baseline dietary intake was assessed with validated Food Frequency Questionnaires and adherence to the DHD15-index was calculated (range 0-130). PreT2D and T2D were classified according to the WHO criteria 2011. Poisson regression was used to estimate prevalence ratios between participant scores on the DHD15-index and preT2D and T2D, adjusted for follow-up duration, energy intake, socio-demographic, and lifestyle factors. Change in fasting plasma glucose levels (mmol/L) over follow-up was analysed using linear regression analyses, additionally adjusted for baseline value. RESULTS: During a mean follow-up of 6.3 ± 0.7 years, 837 participants developed preT2D and 321 participants developed T2D. The highest adherence to the DHD15-index was significantly associated with lower T2D incidence [model 3, PRT3vsT1: 0.70 (0.53; 0.92), ptrend = 0.01]. The highest adherence to the DHD15-index pointed towards a lower incidence of preT2D [PRT3vsT1: 0.87 (0.74; 1.03), ptrend = 0.11]. Higher adherence to the DHD15-index was not associated with change in fasting plasma glucose levels [ß10point: - 0.012 (- 0.034; 0.009)mmol/L]. CONCLUSION: The present study showed that the highest compared to the lowest adherence to the DHD15-index was associated with a lower T2D incidence, and pointed towards a lower incidence of preT2D. These results support the benefits of adhering to the guidelines in T2D prevention.

Using enhanced regression calibration to combine dietary intake estimates from 24 h recall and FFQ reduces bias in diet-disease associations.

OBJECTIVE: To illustrate the impact of combining 24 h recall (24hR) and FFQ estimates using regression calibration (RC) and enhanced regression calibration (ERC) on diet-disease associations. SETTING: Wageningen area, the Netherlands, 2011-2013. DESIGN: Five approaches for obtaining self-reported dietary intake estimates of protein and K were compared: (i) uncorrected FFQ intakes (FFQ); (ii) uncorrected average of two 24hR ( $\overline {\rm R}$ ); (iii) average of FFQ and $\overline {\rm R}$ ( ${\overline {\rm F}}\,\overline {\rm R}}$ ); (iv) RC from regression of 24hR v. FFQ; and (v) ERC by adding individual random effects to the RC approach. Empirical attenuation factors (AF) were derived by regression of urinary biomarker measurements v. the resulting intake estimates. PARTICIPANTS: Data of 236 individuals collected within the National Dietary Assessment Reference Database. RESULTS: Both FFQ and 24hR dietary intake estimates were measured with substantial error. Using statistical techniques to correct for measurement error (i.e. RC and ERC) reduced bias in diet-disease associations as indicated by their AF approaching 1 (RC 1·14, ERC 0·95 for protein; RC 1·28, ERC 1·34 for K). The larger sd and narrower 95% CI of AF obtained with ERC compared with RC indicated that using ERC has more power than using RC. However, the difference in AF between RC and ERC was not statistically significant, indicating no significantly better de-attenuation by using ERC compared with RC. AF larger than 1, observed for the ERC for K, indicated possible overcorrection. CONCLUSIONS: Our study highlights the potential of combining FFQ and 24hR data. Using RC and ERC resulted in less biased associations for protein and K.

Changes in Micronutrient Intake and Status, Diet Quality and Glucose Tolerance from Preconception to the Second Trimester of Pregnancy.

Data on changes in dietary intake and related blood parameters throughout pregnancy are scarce; moreover, few studies have examined their association with glucose homeostasis. Therefore, we monitored intake of folate, vitamin B6, vitamin B12, vitamin D and iron, their status markers, and diet quality from preconception to the second trimester of pregnancy, and we examined whether these dietary factors were associated with glucose homeostasis during pregnancy. We included 105 women aged 18⁻40 years with a desire to get pregnancy or who were already <24 weeks pregnant. Women at increased gestational diabetes (GDM) risk were oversampled. Measurements were scheduled at preconception (n = 67), and 12 (n =53) and 24 weeks of pregnancy (n =66), including a fasting venipuncture, 75-grams oral glucose tolerance test, and completion of a validated food frequency questionnaire. Changes in micronutrient intake and status, and associations between dietary factors and glucose homeostasis, were examined using adjusted repeated measures mixed models. Micronutrient intake of folate, vitamin B6 and vitamin D and related status markers significantly changed throughout pregnancy, which was predominantly due to changes in the intake of supplements. Micronutrient intake or status levels were not associated with glucose homeostasis, except for iron intake (FE µg/day) with fasting glucose (ß = -0.069 mmol/L, p = 0.013) and HbA1c (ß = -0.4843 mmol, p = 0.002). Diet quality was inversely associated with fasting glucose (ß = -0.006 mmol/L for each DHD15-index point, p = 0.017). It was shown that micronutrient intakes and their status markers significantly changed during pregnancy. Only iron intake and diet quality were inversely associated with glucose homeostasis.

Pre-pregnancy dietary micronutrient adequacy is associated with lower risk of developing gestational diabetes in Australian women.

Evidence on pre-pregnancy dietary micronutrient intake in relation to gestational diabetes (GDM) development is limited. Therefore, we examined the prevalence of inadequate micronutrient intake before pregnancy and the association between pre-pregnancy dietary micronutrient adequacy, i.e. meeting micronutrient intake recommendations for a range of micronutrients, and risk of developing GDM in an Australian population. We hypothesized that women with an overall higher micronutrient adequacy would have a lower risk of developing GDM. We used data from the prospective Australian Longitudinal Study on Women's Health cohort, in which 3607 women, aged 25-30 years at baseline in 2003 and without diabetes, were followed-up until 2015. Diet was assessed with a validated 101-item food frequency questionnaire. The Micronutrient Adequacy Ratio (MAR) was calculated as the micronutrient intake divided by its recommended dietary intake averaged over 13 micronutrients. Multivariable regression models with generalized estimating equations were used to estimate relative risks (RR) and 95% confidence intervals (95% CI). In 6263 pregnancies, 285 cases of GDM were documented (4.6%). High prevalences of inadequate dietary micronutrient intake were observed for calcium (47.9%), folate (80.8%), magnesium (52.5%), potassium (63.8%) and vitamin E (78.6%), indicating suboptimal pre-pregnancy micronutrient intakes. Inadequate intakes of individual micronutrients were not associated with risk of developing GDM. However, women in the highest quartile of the MAR had a 39% lower risk of developing GDM compared to women in the lowest quartile (RR 0.61, 95% CI 0.43-0.86, p for trend 0.01). These results highlight the importance of adequate pre-pregnancy micronutrient intake.

Supplement Use and Dietary Sources of Folate, Vitamin D, and n-3 Fatty Acids during Preconception: The GLIMP2 Study.

An adequate nutritional status during the preconception period is important, particularly for folate, vitamin D, and n-3 fatty acids (i.e., EPA+DHA). We aimed to determine supplement intake and the main dietary sources of folate, vitamin D, and EPA+DHA using the data of 66 Dutch women aged 18⁻40 years who wished to become pregnant. Additionally, associations of these intakes with their blood levels were examined. Dietary intake was assessed with a validated food frequency questionnaire, and supplement use with a structured questionnaire. 25-hydroxyvitamin D levels were determined in serum and folate and phospholipid EPA+DHA levels in plasma. Partial Spearman's correlations, restricted cubic splines and trend analyses over tertiles of nutrient intakes were performed to examine intake-status associations. A large proportion of women did not meet the Dutch recommended intakes of folate (50%), vitamin D (67%), and EPA+DHA (52%). Vegetables were the main contributor to dietary folate intake (25%), oils and fats to dietary vitamin D intake (39%), and fish to dietary EPA+DHA intake (69%). Fourteen percent of the women had an inadequate folate status and 23% an inadequate vitamin D status. Supplemental folate intake, supplemental and dietary vitamin D intake and dietary EPA+DHA intake were significantly associated with their blood levels. In conclusion, even in our highly educated population, a large proportion did not achieve recommended folate, vitamin D and n-3 fatty acid intakes. Promotion of folate and vitamin D supplement use and fish consumption is needed to improve intakes and blood levels of these nutrients in women who wish to become pregnant.

Pre-pregnancy dietary carbohydrate quantity and quality, and risk of developing gestational diabetes: the Australian Longitudinal Study on Women's Health.

Carbohydrate quantity and quality affect postprandial glucose response, glucose metabolism and risk of type 2 diabetes. The aim of this study was to examine the association of pre-pregnancy dietary carbohydrate quantity and quality with the risk of developing gestational diabetes mellitus (GDM). We used data from the Australian Longitudinal Study on Women's Health that included 3607 women aged 25-30 years without diabetes who were followed up between 2003 and 2015. We examined carbohydrate quantity (total carbohydrate intake and a low-carbohydrate diet (LCD) score) and carbohydrate subtypes indicating quality (fibre, total sugar intake, glycaemic index, glycaemic load and intake of carbohydrate-rich food groups). Relative risks (RR) for development of GDM were estimated using multivariable regression models with generalised estimating equations. During 12 years of follow-up, 285 cases of GDM were documented in 6263 pregnancies (4·6 %). The LCD score, reflecting relatively high fat and protein intake and low carbohydrate intake, was positively associated with GDM risk (RR 1·54; 95 % CI 1·10, 2·15), highest quartile v. lowest quartile). Women in the quartile with highest fibre intake had a 33 % lower risk of GDM (RR 0·67; 95 % CI 0·45, 0·96)). Higher intakes of fruit (0·95 per 50 g/d; 95 % CI 0·90, 0·99) and fruit juice (0·89 per 100 g/d; 95 % CI 0·80, 1·00)) were inversely associated with GDM, whereas cereal intake was associated with a higher risk of GDM (RR 1·05 per 20 g/d; 95 % CI 1·01, 1·07)). Thus, a relatively low carbohydrate and high fat and protein intake may increase the risk of GDM, whereas higher fibre intake could decrease the risk of GDM. It is especially important to take the source of carbohydrates into account.

Does a better adherence to dietary guidelines reduce mortality risk and environmental impact in the Dutch sub-cohort of the European Prospective Investigation into Cancer and Nutrition?

Guidelines for a healthy diet aim to decrease the risk of chronic diseases. It is unclear as to what extent a healthy diet is also an environmentally friendly diet. In the Dutch sub-cohort of the European Prospective Investigation into Cancer and Nutrition, the diet was assessed with a 178-item FFQ of 40 011 participants aged 20-70 years between 1993 and 1997. The WHO's Healthy Diet Indicator (HDI), the Dietary Approaches to Stop Hypertension (DASH) score and the Dutch Healthy Diet index 2015 (DHD15-index) were investigated in relation to greenhouse gas (GHG) emissions, land use and all-cause mortality risk. GHG emissions were associated with HDI scores (-3·7 % per sd increase (95 % CI -3·4, -4·0) for men and -1·9 % (95 % CI -0·4, -3·4) for women), with DASH scores in women only (1·1 % per sd increase, 95 % CI 0·9, 1·3) and with DHD15-index scores (-2·5 % per sd increase (95 % CI -2·2, -2·8) for men and -2·0 % (95 % CI -1·9, -2·2) for women). For all indices, higher scores were associated with less land use (ranging from -1·3 to -3·1 %). Mortality risk decreased with increasing scores for all indices. Per sd increase of the indices, hazard ratios for mortality ranged from 0·88 (95 % CI 0·82, 0·95) to 0·96 (95 % CI 0·92, 0·99). Our results showed that adhering to the WHO and Dutch dietary guidelines will lower the risk of all-cause mortality and moderately lower the environmental impact. The DASH diet was associated with lower mortality and land use, but because of high dairy product consumption in the Netherlands it was also associated with higher GHG emissions.

Development and evaluation of the Dutch Healthy Diet index 2015.

OBJECTIVE: To update the Dutch Healthy Diet index, a measure of diet quality, to reflect adherence to the Dutch dietary guidelines 2015 and to evaluate against participants' characteristics and nutrient intakes with the score based on 24 h recall (24 hR) data and FFQ data. DESIGN: The Dutch Healthy Diet index 2015 (DHD15-index) consists of fifteen components representing the fifteen food-based Dutch dietary guidelines of 2015. Per component the score ranges between 0 and 10, resulting in a total score between 0 (no adherence) and 150 (complete adherence). SETTING: Wageningen area, the Netherlands, 2011-2013. SUBJECTS: Data of 885 men and women, aged 20-70 years, participating in the longitudinal NQplus study, who filled out two 24 hR and one FFQ, were used. RESULTS: Mean (sd) score of the DHD15-index was 68·7 (16·1) for men and 79·4 (16·0) for women. Significant inverse trends were found between the DHD15-index and BMI, smoking, and intakes of energy, total fat and saturated fat. Positive trends were seen across sex-specific quintiles of the DHD15-index score with energy-adjusted micronutrient intakes. Mean DHD15-index score of the FFQ data was 15·5 points higher compared with 24 hR data, with a correlation coefficient of 0·56 between the scores. Observed trends of the DHD15-index based on FFQ with participant characteristics, macronutrient and energy-adjusted micronutrient intakes were similar to those with the DHD15-index based on 24 hR. CONCLUSIONS: The DHD15-index score assesses adherence to the Dutch dietary guidelines 2015 and indicates diet quality. The DHD15-index score can be based on 24 hR data and on FFQ data.

Lifestyle Changes in Young Adulthood and Middle Age and Risk of Cardiovascular Disease and All-Cause Mortality: The Doetinchem Cohort Study.

BACKGROUND: The associations between overall lifestyle profile and cardiovascular disease (CVD) and death have been mainly investigated in cross-sectional studies. The full benefits of a healthy lifestyle may therefore be underestimated, and the magnitude of benefits associated with changes in lifestyle remains unclear. We quantified the association of changes in lifestyle profiles over 5 years with risk of CVD and all-cause mortality. METHODS AND RESULTS: Lifestyle factors (ie, diet, physical activity, smoking, alcohol consumption) and body mass index were assessed and dichotomized as healthy/unhealthy among 5263 adults ages 26 to 66 in 1993-1997 and 5 years later (1998-2002). Multivariable-adjusted hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were estimated to quantify associations of change in lifestyle with fatal/nonfatal CVD and all-cause mortality that occurred 8 to 15 years after 1998-2002. Independent of baseline lifestyles, each decrement in number of healthy lifestyle factors was, on average, associated with 35% higher risk of CVD (HR, 1.35; 95% CI, 1.12-1.63) and 37% higher risk of all-cause mortality (HR, 1.37; 95% CI, 1.10-1.70); no association was noted with increase in the number of healthy lifestyle factors (P>0.5). Individuals who maintained 4 to 5 healthy lifestyle factors had 2.5 times lower risk of CVD (HR, 0.43; 95% CI, 0.25-0.63) and all-cause mortality (HR, 0.40; 95% CI, 0.22-0.73) than those who maintained only 0 to 1 healthy lifestyle factor. CONCLUSIONS: Our findings suggest that the benefits of healthy lifestyles may be easier lost than gained over a 5-year period. This underscores the need for efforts to promote maintenance of healthy lifestyles throughout the life course.