223 research outputs found
Towards "improved standards in the science of nutrition" through the establishment of Federation of European Nutrition Societies Working Groups
No full textPre-pregnancy dietary micronutrient adequacy is associated with lower risk of developing gestational diabetes in Australian women
No full textEvidence 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.</p
Pre-pregnancy dietary carbohydrate quantity and quality, and risk of developing gestational diabetes: the Australian Longitudinal Study on Women's Health
No full textCarbohydrate 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
Genetic variants in lipid metabolism are independently associated with multiple features of the metabolic syndrome
No full textAbstract Background Our objective was to find single nucleotide polymorphisms (SNPs), within transcriptional pathways of glucose and lipid metabolism, which are related to multiple features of the metabolic syndrome (MetS). Methods 373 SNPs were measured in 3575 subjects of the Doetinchem cohort. Prevalence of MetS features, i.e. hyperglycemia, abdominal obesity, decreased HDL-cholesterol levels and hypertension, were measured twice in 6 years. Associations between the SNPs and the individual MetS features were analyzed by log-linear models. For SNPs related to multiple MetS features (P Results Two SNPs, CETP Ile405Val and APOE Cys112Arg, were associated with both the prevalence of low HDL-cholesterol level (Ile405Val P = Cys112Arg P = 0.001) and with the prevalence of abdominal obesity (Ile405Val P = 0.007; Cys112Arg P = 0.007). For both SNPs, the association with HDL-cholesterol was partly independent of the association with abdominal obesity and vice versa. Conclusion Two SNPs, mainly known for their role in lipid metabolism, were associated with two MetS features i.e., low HDL-cholesterol concentration, as well as, independent of this association, abdominal obesity. These SNPs may help to explain why low HDL-cholesterol levels and abdominal obesity frequently co-occur.</p
Nutritional Factors and the Etiology of Non-Insulin-Dependent Diabetes mellitus: An Epidemiological Overview
No full textCorrection to : Evaluating ‘Power 4 a Healthy Pregnancy’ (P4HP) – protocol for a cluster randomized controlled trial and process evaluation to empower pregnant women towards improved diet quality
No full textThe original publication of this article [1] contained several errors in the author names. The incorrect and correct author names are listed in this correction article. The original article has been updated
Dietary Fibre May Mitigate Sarcopenia Risk: Findings from the NU-AGE Cohort of Older European Adults
No full textSarcopenia is characterised by a progressive loss of skeletal muscle mass and physical function as well as related metabolic disturbances. While fibre-rich diets can influence metabolic health outcomes, the impact on skeletal muscle mass and function is yet to be determined, and the moderating effects by physical activity (PA) need to be considered. The aim of the present study was to examine links between fibre intake, skeletal muscle mass and physical function in a cohort of older adults from the NU-AGE study. In 981 older adults (71 ± 4 years, 58% female), physical function was assessed using the short-physical performance battery test and handgrip strength. Skeletal muscle mass index (SMI) was derived using dual-energy X-ray absorptiometry (DXA). Dietary fibre intake (FI) was assessed by 7-day food record and PA was objectively determined by accelerometery. General linear models accounting for covariates including PA level, protein intake and metabolic syndrome (MetS) were used. Women above the median FI had significantly higher SMI compared to those below, which remained in fully adjusted models (24.7 ± 0.2% vs. 24.2 ± 0.1%, p = 0.011, η2p = 0.012). In men, the same association was only evident in those without MetS (above median FI: 32.4 ± 0.3% vs. below median FI: 31.3 ± 0.3%, p = 0.005, η2p = 0.035). There was no significant impact of FI on physical function outcomes. The findings from this study suggest a beneficial impact of FI on skeletal muscle mass in older adults. Importantly, this impact is independent of adherence to guidelines for protein intake and PA, which further strengthens the potential role of dietary fibre in preventing sarcopenia. Further experimental work is warranted in order to elucidate the mechanisms underpinning the action of dietary fibre on the regulation of muscle mass
Corrigendum: The PERSonalized Glucose Optimization Through Nutritional Intervention (PERSON) Study: Rationale, Design and Preliminary Screening Results
No full text[This corrects the article DOI: 10.3389/fnut.2021.694568.].Copyright © 2022 Gijbels, Trouwborst, Jardon, Hul, Siebelink, Bowser, Yildiz, Wanders, Erdos, Thijssen, Feskens, Goossens, Afman and Blaak.In the original article, there was a mistake in Supplementary Tables 3 and 4. Some numbers in these tables were incorrect. The corrected tables Supplementary Tables 3 and 4 appear below. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated
Trend in age at menarche and its association with body weight, body mass index and non-communicable disease prevalence in Indonesia : evidence from the Indonesian Family Life Survey (IFLS)
No full textBackground: In western countries, age at menarche (AAM) is nowadays lower than a century ago, coinciding with increased Body Mass Index (BMI) and prevalence of non-communicable diseases (NCD). This study aimed to determine the time trend in AAM, and its association with BMI and NCD prevalence at later age, in Indonesia. Methods: We used secondary data of 15,744 women aged 15–65 years from the Indonesian Family Life Survey (IFLS) conducted in the period 1993 to 2015. Multiple linear regression was applied to determine the association of AAM with BMI, and Poisson regression with robust variance for investigating the association of AAM with NCD prevalence ratios. Models were adjusted for age, and effect modification by wealth status, living area, and region was investigated. Results: AAM has significantly declined from 14.4 (SD:2.1) years of age in the 1940s to 13.4 y (SD:1.5) in the 1990s. AAM was inversely associated with BMI (β: − 0.30 kg/m2, 95%CI: − 0.37, − 0.22) and body weight (β: − 0.67 kg, 95%CI: − 0.75, − 0.54), but was not associated with height. After adjustment for age, AAM was not associated with NCD, i.e. hypertension, type 2 diabetes mellitus, liver diseases, asthma, chronic lung diseases, cardiovascular diseases, stroke, cancer, or arthritis. Including BMI in the models did not change the results. Conclusions: From the 1940s to 1990s, AAM has declined with 1 year in Indonesia. Women with earlier AAM had higher BMI and body weight at later age, but AAM was not associated with NCD prevalence in later life in the Indonesian population. Further longitudinal research is needed to disentangle the direction of causality of the associations
Using enhanced regression calibration to combine dietary intake estimates from 24 h recall and FFQ reduces bias in diet-disease associations
No full text<p>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 (); (iii) average of FFQ and ({\\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.</p
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