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Purpose Our aim was to identify dietary patterns that are associated with bone mineral density (BMD) against a background of relatively high dairy intake in elderly Dutch subjects. Methods Participants were 55 years of age and older (n = 5144) who were enrolled in The Rotterdam Study, a population-based prospective cohort study. Baseline intake of 28 pre-defined food groups was determined using a validated food frequency questionnaire. Dietary patterns were identified using principal component analysis. BMD was measured using dual-energy X-ray absorptiometry at baseline and at three subsequent visits (between 1993 and 2004). Linear mixed modelling was used to longitudinally analyse associations of adherence to each pattern with repeatedly measured BMD (both in Z scores). Results After adjustment for confounders, two dietary patterns were associated with high BMD: a “Traditional” pattern, characterized by high intake of potatoes, meat and fat (β = 0.06; 95 % CI 0.03, 0.09) and a “Health conscious” pattern, characterized by high intake of fruits, vegetables, poultry and fish (β = 0.06; 95 % CI 0.04, 0.08). The “Processed” pattern, characterized by high intake of processed meat and alcohol, was associated with low BMD (β = −0.03; 95 % CI −0.06, −0.01). Associations of adherence to the “Health conscious” and “Processed” pattern with BMD were independent of body weight and height, whereas the association between adherence to the “Traditional” pattern with BMD was not. Conclusions Against a background of high dairy intake and independent of anthropometrics, a “Health conscious” dietary pattern may have benefits for BMD, whereas a “Processed” dietary pattern may pose a risk for low BMD. Electronic supplementary material The online version of this article (doi:10.1007/s00394-016-1297-7) contains supplementary material, which is available to authorized users.

Background: Evidence on the association between dietary patterns, measures of hip bone geometry, and subsequent fracture risk are scarce. Objective: The objective of this study was to evaluate whether dietary patterns that explain most variation in bone mineral density (BMD) and hip bone geometry are associated with fracture risk. Design: We included 4028 subjects aged $55 y from the Rotterdam study. Intake of 28 food groups was assessed with the use of foodfrequency questionnaires. BMD, bone width, section modulus (SM; reflecting bending strength) and cortical buckling ratio (BR; reflecting bone instability) were measured with the use of dual-energy X-ray absorptiometry. BMD and geometry-specific dietary patterns were identified with the use of reduced rank regression. Fracture data were reported by general practitioners (median follow-up 14.8 y). Results: We identified 4 dietary patterns. Of the 4, we named 2 patterns "fruit, vegetables, and dairy" and "sweets, animal fat, and low meat," respectively. These 2 patterns were used for further analysis. Independently of confounders, adherence to the fruit, vegetables, and dairy pattern was associated with high BMD, high SM, low BR, and low risk of fractures [HR (95% CI) for osteoporotic fractures: 0.90 (0.83, 0.96); for hip fractures: 0.85 (0.81, 0.89) per z score of dietary pattern adherence]. Adherence to the sweets, animal fat, and low meat pattern was associated with high bone width, high SM, high BR, and high risk of fractures [HR (95% CI) for osteoporotic fractures: 1.08 (1.00, 1.06); for hip fractures: 1.06 (1.02, 1.12) per z score]. Conclusion: The fruit, vegetables, and dairy pattern might be associated with lower fracture risk because of high BMD, high bending strength, and more stable bones. The sweets, animal fat, and low meat pattern might be associated with higher fracture risk because of widened, unstable bones, independently of BMD. Dietary recommendations associated with bone geometry in addition to BMD might influence risk of fractures.

BACKGROUND: Folate and vitamin B-12 are essential micronutrients involved in the donation of methyl groups in cellular metabolism. However, associations between intake of these nutrients and genome-wide DNA methylation levels have not been studied comprehensively in humans.OBJECTIVE: The aim of this study was to assess whether folate and/or vitamin B-12 intake are asssociated with genome-wide changes in DNA methylation in leukocytes.METHODS: A large-scale epigenome-wide association study of folate and vitamin B-12 intake was performed on DNA from 5841 participants from 10 cohorts using Illumina 450k arrays. Folate and vitamin B-12 intakes were calculated from food-frequency questionnaires (FFQs). Continuous and categorical (low compared with high intake) linear regression mixed models were applied per cohort, controlling for confounders. A meta-analysis was performed to identify significant differentially methylated positions (DMPs) and regions (DMRs), and a pathway analysis was performed on the DMR annotated genes.RESULTS: The categorical model resulted in 6 DMPs, which are all negatively associated with folate intake, annotated to FAM64A, WRAP73, FRMD8, CUX1, and LCN8 genes, which have a role in cellular processes including centrosome localization, cell proliferation, and tumorigenesis. Regional analysis showed 74 folate-associated DMRs, of which 73 were negatively associated with folate intake. The most significant folate-associated DMR was a 400-base pair (bp) spanning region annotated to the LGALS3BP gene. In the categorical model, vitamin B-12 intake was associated with 29 DMRs annotated to 48 genes, of which the most significant was a 1100-bp spanning region annotated to the calcium-binding tyrosine phosphorylation-regulated gene (CABYR). Vitamin B-12 intake was not associated with DMPs.CONCLUSIONS: We identified novel epigenetic loci that are associated with folate and vitamin B-12 intake. Interestingly, we found a negative association between folate and DNA methylation. Replication of these methylation loci is necessary in future studies.

Short self-reported sleep duration is associated with dietary intake and this association may partly mediate the link between short sleep and metabolic abnormalities. Subjective sleep measures, however, may be inaccurate and biased. The objective of this study was to evaluate the associations between actigraphic measures of sleep fragmentation, efficiency and duration and energy and macronutrient intakes. We used data from a subgroup of 439 participants of the population-based cohort, Rotterdam Study. Sleep was assessed using 7-day actigraphy and sleep diaries, and dietary data with a validated food frequency questionnaire. We assessed the associations of actigraphic sleep parameters with dietary intake using multivariable linear regression models. Higher sleep fragmentation was associated with 4.19 g lower carbohydrate intake per standard deviation of fragmentation {beta [95% confidence interval (CI) = -4.19 (-8.0, -0.3)]; P = 0.03}. Each additional percentage increase in sleep efficiency was associated with 11.1 kcal lower energy intake [beta (95% CI) = -11.1 (-20.6, -1.7); P = 0.02]. Furthermore, very short sleep duration (= 6.5 to

Background Dietary contribution to acid-base balance in early life may influence subsequent bone mineralization. Previous studies reported inconsistent results regarding the associations between dietary acid load and bone mass. Objective We examined the associations of dietary acid load in early life with bone health in childhood. Design In a prospective, multiethnic, population-based cohort study of 2850 children, we estimated dietary acid load as dietary potential renal acid load (dPRAL), based on dietary intakes of calcium, magnesium, phosphorus, potassium, and protein, and as a protein intake to potassium intake ratio (Pro:K) at 1 y of age and in a subgroup at 2 y of age : Bone mineral density, bone mineral content (BMC), area-adjusted BMC, and bone area were assessed by dual-energy X-ray absorptiometry at the median age of 6 y. Data were analyzed by using multivariable linear regression models. Results After adjusting for relevant maternal and child factors, dietary acid load estimated as either dPRAL or Pro:K ratio was not consistently associated with childhood bone health. Associations did not differ by sex, ethnicity, weight status, or vitamin D supplementation. Only in those children with high protein intake in our population (i.e., >42 g/d), a 1-unit increase in dPRAL (mEq/d) was inversely associated with BMC (difference: -0.32 g; 95% CI: -0.64, -0.01 g). Conclusions Dietary acid load in early life was not consistently associated with bone health in childhood. Further research is needed to explore the extent to which dietary acid load in later childhood may affect current and future bone health.

Fracture incidence needs to be evaluated over time to assess the impact of the enlarging population burden of fractures (due to increase in lifespan) and the efficacy of fracture prevention strategies. Therefore, we aimed to evaluate the association of femoral neck bone mineral density (FN-BMD) measured using dual-energy X-ray absorptiometry (DXA) at baseline with fracture risk over a long follow-up time period. Incident non-vertebral fractures were assessed in 14,613 individuals participating in the Rotterdam Study with up to 20 years of follow-up. During a mean follow-up of 10.7 ± 6.2 years, 2971 (20.3%) participants had at least one incident non-vertebral fracture. The risk for any non-vertebral fracture was 1.37 (95% Confidence Interval (CI): 1.25-1.49) and 1.42 (95%CI: 1.35-1.50) for men and women, respectively. The majority (79% in men and 75% in women) of all fractures occurred among participants a normal or osteopenic T-score. The incidence rates per 1000 person-years for the most common fractures were 5.3 [95%CI: 5.0-5.7] for hip, 4.9 [95%CI: 4.6-5.3] for wrist and 2.3 [95%CI: 2.0-2.5] for humerus. To examine the predictive ability of BMD through follow-up time we determined fracture hazard ratios (HR) per standard deviation decrease in femoral neck BMD across five year bins. No differences were observed, with a HR of 2.5 (95%CI: 2.0-3.1) after the first 5 years, and of 1.9 (95%CI: 1.1-3.3) after 20 years. To assess secular trends in fracture incidence at all skeletal sites we compared participants at an age of 70-80 years across two time periods: 1989-2001 (n = 2481, 60% women) and 2001-2013 (n = 2936, 58% women) and found no statistically significant difference (p 0.05) between fracture incidence rates (i.e., incidence of non-vertebral fractures of 26.4 per 1000 PY [95%CI: 24.4-28.5]) between 1989 and 2001, and of 25.4 per 1000 PY [95%CI: 23.0-28.0] between 2001 and 2013. In conclusion, BMD is still predictive of future fracture over a long period of time. While no secular changes in fractures rates seem to be observed after a decade, the majority of fractures still occur above the osteoporosis threshold, emphasizing the need to improve the screening of osteopenic patients.

Purpose To examine the strength and independence of associations between three major socio-economic indicators (income, education and occupation) and diet quality (DQ) at baseline and after 20-year follow-up. Methods Cross-sectional and longitudinal analyses using data collected in the Rotterdam Study, a prospective population-based cohort. Participants were categorised according to socio-economic indicators (education, occupation and household income) measured at baseline (1989–1993). Participants aged 55 years or older were included (n = 5434). DQ was assessed at baseline (1989–1993) and after 20 years (2009–2011) and quantified using the Dutch Healthy Diet Index, reflecting adherence to the Dutch guidelines for a healthy diet; scores can range from 0 (no adherence) to 80 (optimal adherence). Linear regression models were adjusted for sex, age, smoking status, BMI, physical activity level, total energy intake and mutually adjusted for the other socio-economic indicators. Results At baseline, scores on the Dutch Healthy Diet Index were 2.29 points higher for participants with the highest level of education than for those with the lowest level (95%CI = 1.23–3.36); in addition, they were more likely to have a higher DQ at follow-up (β = 3.10, 95%CI = 0.71–5.50), after adjustment for baseline DQ. In contrast, higher income was associated with lower DQ at follow-up (β = −1.92, 95%CI = −3.67, −0.17), whereas occupational status was not associated with DQ at baseline or at follow-up. Conclusion In our cohort of Dutch participants, a high level of education was the most pronounced socio-economic indicator of high DQ at baseline and at follow-up. Our results highlight that different socio-economic indicators influence DQ in different ways.

Objective— We assessed whether the association between dietary saturated fatty acids (SFA) and incident coronary heart disease (CHD) depends on the food source, the carbon chain length of SFA, and the substituting macronutrient. Approach and Results— From the Rotterdam Study, 4722 men and women (≥55 years) were included. Baseline (1990–1993) SFA intake was assessed using a validated food frequency questionnaire. CHD (nonfatal myocardial infarction and fatal CHD) was ascertained by medical records. Using multivariable Cox regression analysis, we calculated CHD risks for higher intakes of total SFA, SFA from specific food sources, SFA differing in carbon chain length, and substituting other macronutrients instead of SFA. During a median follow-up of 16.3 years, 659 CHD events occurred. Total SFA intake was not associated with CHD risk (hazard ratio [HR] per 5 en%, 1.13; 95% confidence interval, 0.94–1.22), and neither was SFA from specific food sources. A higher CHD risk was observed for palmitic acid (16:0) intake (HR SD , 1.26; 95% confidence interval, 1.05–1.15) but not for SFA with other chain lengths. Except for a higher CHD risk for substitution of SFA with animal protein (HR 5en% , 1.24; 95% confidence interval, 1.01–1.51), substitution with other macronutrients was not associated with CHD. Conclusions— In this Dutch population, we observed that a higher intake of palmitic acid, which accounts for ≈50% of the total SFA intake, was associated with a higher CHD risk, as was substitution of total SFA with animal protein. Nevertheless, we found no association between total SFA intake and CHD risk, which did not differ by food source.

Context:The role of uric acid (UA) in skeletal metabolism remains to be unraveled.Objective:We prospectively investigated the association between UA, bone mineral density at the femoral neck (FN-BMD), hip bone geometry parameters, and incident fracture risk and examined whether the associations were modified by age and vitamin C intake.Participants and Setting:Data of 5074 participants of The Rotterdam Study, a prospective population-based cohort.Exposure:Serum UA was assessed at baseline.Main Outcomes and Measures:FN-BMD was measured at baseline, and at second, third, and fourth visits of the Rotterdam Study. Hip bone geometry parameters were measured at baseline and at the second and third visits.Results:Serum UA levels (per SD increase) were positively associated with FN-BMD (β = 0.007 g/cm2; 95% confidence interval [CI] = 0.002–0.01), thicker cortices (β = 0.002 cm; 95% CI = 0.0003–0.002), lower bone width (β = −0.013 cm; 95% CI = −0.23 to −0.003), and lower cortical buckling ratio (β = −0.19; 95% CI = −0.33 to −0.06). The effects of UA on FN-BMD and cortical buckling ratio tended to become stronger over time. Hazard ratios and 95% CIs per SD increase of baseline UA levels for the development of any type of incident fractures, nonvertebral fractures, and osteoporotic fractures were 0.932 (0.86–0.995), 0.924 (0.856–0.998), and 0.905 (0.849–0.982), respectively. These associations were more prominent in older individuals (age, >65 y) and in participants with high intakes of vitamin C (> median).Conclusions:Higher levels of serum UA are associated with higher BMD (at the expense of thicker cortices and narrower bone diameters) and may be a protective factor in bone metabolism. However, interactions with age and vitamin C may be present.

No diet score exists that summarizes the features of a diet that is optimal for bone mineral density (BMD) in the elderly. Our aims were (a) to develop a BMD-Diet Score reflecting a diet that may be beneficial for BMD based on the existing literature, and (b) to examine the association of the BMD-Diet Score and the Healthy Diet Indicator, a score based on guidelines of the World Health Organization, with BMD in Dutch elderly participating in a prospective cohort study, the Rotterdam Study (n = 5144). Baseline dietary intake, assessed using a food frequency questionnaire, was categorized into food groups. Food groups that were consistently associated with BMD in the literature were included in the BMD-Diet Score. BMD was measured repeatedly and was assessed using dual energy X-ray absorptiometry. The BMD-Diet Score considered intake of vegetables, fruits, fish, whole grains, legumes/beans and dairy products as "high-BMD" components and meat and confectionary as "low-BMD" components. After adjustment, the BMD-Diet Score was positively associated with BMD (beta (95% confidence interval) = 0.009 (0.005, 0.012) g/cm(2) per standard deviation). This effect size was approximately three times as large as has been observed for the Healthy Diet Indicator. The food groups included in our BMD-Diet Score could be considered in the development of future dietary guidelines for healthy ageing.

Background Abnormal gestational weight gain is associated with unfavorable pregnancy outcomes. Several risk factors have been identified, but the effect of macronutrient intake during pregnancy on gestational weight gain has not been systematically evaluated in both high-income countries and low- and middle-income countries. Objective We conducted a systematic review of the literature in 8 different databases (until 12 August 2015) to assess whether energy intake and macronutrient intake (i.e., protein, fat, and carbohydrate) during pregnancy were associated with gestational weight gain (following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines). Results Of 7623 identified references, we included 56 articles (46 observational studies and 10 trials, 28 of which were in high-income countries and 28 of which were in low- and middle-income countries). Eleven of the included articles were of high quality (20%). Results of 5 intervention and 7 high-quality observational studies suggested that higher energy intake during pregnancy is associated with higher gestational weight gain (n = 52). Results from observational studies were inconsistent for protein intake (n = 29) and carbohydrate intake (n = 18). Maternal fat intake (n = 25) might be associated with gestational weight gain as suggested by observational studies, although the direction of this association might depend on specific types of fat (e.g., saturated fat). Macronutrient intake was not consistently associated with the prevalence of inadequate or excessive gestational weight gain. Associations were comparable for high-income countries and low- and middle-income countries. Conclusions The current literature provides evidence that energy intake is associated with gestational weight gain, but the roles of individual macronutrients are inconsistent. However, there is a need for higher-quality research because the majority of these studies were of low quality.