The aim of this study was to investigate the association between cigarette smoking and smoking cessation and the prevalence and incidence of tooth loss in a large cohort study in Germany. We analyzed data of 23,376 participants of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study recruited between 1994 and 1998 from the general population in Potsdam and other parts of Brandenburg, Germany, who had complete data on cigarette smoking, tooth loss, and covariates. Negative binomial regression and tooth-specific logistic regression models were fit to evaluate the association between smoking and the baseline prevalence and incidence of tooth loss during follow-up, respectively. Cigarette smoking was associated with higher prevalence of tooth loss at baseline as well as higher incidence of tooth loss during follow-up. The association between smoking and the incidence of tooth loss was stronger in men than women and stronger in younger versus older individuals. Heavy smoking (≥15 cigarettes/d) was associated with >3 times higher risk of tooth loss in men (odds ratio, 3.6; 95% confidence interval, 3.0, 4.4) and more than twice the risk of tooth loss in women (odds ratio, 2.5; 95% confidence interval, 2.1, 2.9) younger than 50 y when compared with never smokers. Smoking cessation was consistently associated with a reduction in tooth loss risk, with the risk of tooth loss approaching that of never smokers after approximately 10 to 20 y of cessation.

This study adds to the evidence showing that diets rich in polyphenols, and particularly flavonoids, play a role in the prevention of type 2 diabetes. For most associations evidence for nonlinearity was found, suggesting a recommendable amount of intake associated with the lowest risk of type 2 diabetes. Therefore, future studies are warranted in which nonlinear associations are further explored.

BackgroundReports on body mass index (BMI) trajectories from childhood into late adolescence, their determinants, and subsequent cardiometabolic risk markers, particularly among European populations have been few. Moreover, sex-specific investigation is necessary considering the sex difference in BMI, and the sex-specific association between BMI and some cardiometabolic risk markers.MethodsUsing a sample from the DOrtmund Nutritional and Anthropometric Longitudinally Designed study, we explored sex-specific trajectories of the BMI standard deviation score (SDS) from 4 to 18 years of age in 354 males and 335 females by latent (class) growth models. The determinants of trajectory were assessed by logistic regression. We identified cardiometabolic risk markers that were highly associated with BMI SDS trajectory by random forest regression, and finally we used generalized linear models to investigate differences in the identified cardiometabolic risk markers between pairs of trajectories.ResultsWe observed four: ‘low-normal weight’, ‘mid-normal weight’, ‘high-normal weight’, and ‘overweight’, and three: ‘‘low-normal weight’, ‘mid-normal weight’, and ‘high-normal weight’ trajectories in males and females, respectively. Higher maternal prepregnancy BMI was associated with the ‘overweight’ trajectory, and with ‘high-normal weight’ trajectory in both sexes. In addition, employed mothers and first-born status were associated with ‘high-normal weight’ trajectory in females. BMI SDS trajectory was associated with high-density lipoprotein-cholesterol and interleukin-18 (IL-18) in males, and diastolic blood pressure and interleukin-6 (IL-6) in females. However, only males following the ‘overweight’ trajectory had significantly higher IL-18 when compared to their ‘low-normal weight’ counterpart.ConclusionsWe identified sex-specific distinct trajectories of BMI SDS from childhood into late adolescence, higher maternal prepregnancy BMI as a common determinant of the ‘high-normal weight’ and ‘overweight’ trajectories, and ‘overweight’ trajectory being associated with elevated IL-18 in late adolescence–young adulthood. This study emphasizes the role of maternal prepregnancy BMI in overweight, and highlights IL-18 as a cardiometabolic signature of overweight across life.Electronic supplementary materialThe online version of this article (10.1186/s12933-019-0813-5) contains supplementary material, which is available to authorized users.

Background and Purpose It used to be a common practice in the field of nutritional epidemiology to analyze separate nutrients, foods, or food groups. However, in reality, nutrients and foods are consumed in combination. The introduction of dietary patterns (DP) and their analysis has revolutionized this field, making it possible to take into account the synergistic effects of foods and to account for the complex interaction among nutrients and foods. Three approaches of DP analysis exist: (1) the hypothesis-based approach (based on prior knowledge regarding the current understanding of dietary components and their health relation), (2) the exploratory approach (solely relying on dietary intake data), and (3) the hybrid approach (a combination of both approaches). During the recent past, complementary approaches for DP analysis have emerged both conceptually and methodologically. Method We have summarized the recent developments that include incorporating the Treelet transformation method as a complementary exploratory approach in a narrative review. Results Uses, peculiarities, strengths, limitations, and scope of recent developments in DP analysis are outlined. Next, the narrative review gives an overview of the literature that takes into account potential relevant dietary-related factors, specifically the metabolome and the gut microbiome in DP analysis. Then the review deals with the aspect of data processing that is needed prior to DP analysis, particularly when dietary data arise from assessment methods other than the long-established food frequency questionnaire. Lastly, potential opportunities for upcoming DP analysis are summarized in the outlook. Conclusion Biological factors like the metabolome and the microbiome are crucial to understand diet-disease relationships. Therefore, the inclusion of these factors in DP analysis might provide deeper insights.

Tryptophan and tyrosine metabolism has a major effect on human health, and disorders have been associated with the development of several pathologies. Recently, gut microbial metabolism was found to be important for maintaining correct physiology. Here, we describe the development and validation of a UHPLC-ESI-MS/MS method for targeted quantification of 39 metabolites related to tryptophan and tyrosine metabolism, branched chain amino acids and gut-derived metabolites in human plasma and urine. Extraction from plasma was optimised using 96-well plates, shown to be effective in removing phospholipids. Urine was filtered and diluted ten-fold. Metabolites were separated with reverse phase chromatography and detected using triple quadrupole MS. Linear ranges (from ppb to ppm) and correlation coefficients (r2 > 0.990) were established for both matrices independently and the method was shown to be linear for all tested metabolites. At medium spiked concentration, recovery was over 80% in both matrices, while analytical precision was excellent (CV < 15%). Matrix effects were minimal and retention time stability was excellent. The applicability of the methods was tested on biological samples, and metabolite concentrations were found to be in agreement with available data. The method allows the analysis of up to 96 samples per day and was demonstrated to be stable for up to three weeks from acquisition.