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Age is a significant risk factor for common noncommunicable diseases, yet the physiological alterations of aging are poorly understood. We were interested in metabolic patterns between cross‐sectional cohorts of different age ranges with particular emphasis on waist circumference. We recruited three cohorts of healthy subjects with different age ranges (adolescents 18–25 years, adults 40–65 years, and older citizens 75–85 years) and stratified these based on waist circumference. Using targeted LC‐MS/MS metabolite profiling, we analyzed 112 analytes in plasma (amino acids, acylcarnitines, and derivatives). We associated age‐related alterations with various anthropometric and functional parameters such as insulin sensitivity and handgrip strength. Strongest age‐dependent increases were found for fatty acid‐derived acylcarnitines. Amino acid‐derived acylcarnitines displayed increased associations with BMI and adiposity. Some essential amino acids changed in opposite directions, being lower at increased age and higher with increasing adiposity. τ‐methylhistidine was elevated in older subjects, especially on an adiposity background, suggesting an increased protein turnover. Both aging and adiposity are associated with impaired insulin sensitivity. Skeletal muscle mass decreased with age and increased with adiposity. Profound differences in the metabolite signatures during healthy aging and elevated waist circumference/body weight were found. Opposite changes in skeletal muscle mass as well as possible differences in insulin signaling (relative insulin deficiency in older subjects versus hyperinsulinemia associated with adiposity), might be underlying origins for the observed metabolite signatures. We describe novel associations between metabolites and anthropometric factors during aging which underlines the complex interplay of aging, insulin resistance, and metabolic health. [ABSTRACT FROM AUTHOR]

Abstract Background The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study. Results Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant’s gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5. Conclusions The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. Video abstract

Background: The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study. Results: Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant's gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5. Conclusions: The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. 1WX6Se-oTN557_1ffiVH2G Video abstract [ABSTRACT FROM AUTHOR]

Nursing home (NH) residents receiving texture-modified diet (TMD) are at risk of inadequate nutritional intake and subsequent malnutrition. It is essential to monitor dietary intake to take corrective actions, if necessary. Plate diagrams (PDs) are widely used to assess dietary intake in institutions but little is known about their validity for TMD. Dietary intake at main meals was assessed by nursing personnel via PDs and scientific personnel via weighing records (WRs). 17 NH residents receiving TMD on a regular basis. Intake from main meals (breakfast, lunch, and dinner) at 48 days was estimated by nursing personnel in quarters of the offered amount [nothing, ¼, ½, ¾, all, all plus second helping (5 4), or I do not know] and by scientific personnel via WRs. PD estimation was multiplied by the energy and protein content of the offered meal determined by WR and compared to WR intake results. Sums of daily PD quarters were drawn against WR intake results. Energy and protein intake from main meals separately and in total per day were highly correlated (r > 0.854, all P <.001). Paired statistics showed no significant differences between assessment methods (P >.05). Mean differences [±standard deviation (SD)] between PD and WR were 13.9 (±68.6) kcal, which is 1.7% of the mean weighed caloric intake, and 0.2 (±3.3) g protein, which is 0.5% of the mean weighed protein intake per day. Daily energy and protein intake from main meals determined by WR varies widely within each category of summed daily intake quarters; for example, a sum of PD quarters of 12 (ie, "all eaten at all meals") showed corresponding WR intake levels from 394.6 to 1368.9 kcal and 16.3 to 63.0 g protein. Energy and protein intake from TMD estimated by PD corresponds very well to WR-determined intake, if the energy and protein content of the offered meals is known. [ABSTRACT FROM AUTHOR]

Introduction: Nutritional habits and requirements are changing over the lifespan, but the dynamics of nutritional issues and the diet-health relationship in the major stages of the human life cycle are not sufficiently understood. A human phenotyping research platform for nutrition studies was established to recruit and phenotype selected population groups across different stages of life. The project is the backbone of the highly interdisciplinary enable competence cluster of nutrition research aiming to identify dietary determinants of a healthy life throughout the lifespan and to develop healthier and tasty convenience foods with high consumer acceptance.Methods: The phenotyping program included anthropometry, body composition analysis, assessment of energy metabolism, health and functional status, multisensory perception, metabolic phenotyping, lifestyle, sociodemography, chronobiology, and assessment of dietary intake including food preferences and aversions.Results: In total, 503 healthy volunteers at four defined phases of life including 3–5-year old children (n = 44), young adults aged 18–25 years (n = 94), adults aged 40–65 years (“middle agers,” n = 205), and older adults aged 75–85 years (n = 160) were recruited and comprehensively phenotyped. Plasma, serum, buffy coat, urine, feces and saliva samples were collected and stored at −80°C. Significant differences in anthropometric and metabolic parameters between the four groups were found. A major finding was the decrease in fat-free mass and the concomitant increase in % body fat in both sexes across the adult lifespan.Conclusions: The dataset will provide novel information on differences in diet-related parameters over the lifespan and is available for targeted analyses. We expect that this novel platform approach will have implications for the development of innovative food products tailored to promote healthy eating throughout life.Trial registration: DRKS, DRKS00009797. Registered on 20 January 2016, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&_ID=DRKS00009797.

Purpose: Inter-individual metabolic differences may be a reason for previously inconsistent results in diet–diabetes associations. We aimed to investigate associations between dietary intake and diabetes for metabolically homogeneous subgroups ('metabotypes') in a large cross-sectional study. Methods: We used data of 1517 adults aged 38–87 years from the German population-based KORA FF4 study (2013/2014). Dietary intake was estimated based on the combination of a food frequency questionnaire and multiple 24-h food lists. Glucose tolerance status was classified based on an oral glucose tolerance test in participants without a previous diabetes diagnosis using American Diabetes Association criteria. Logistic regression was applied to examine the associations between dietary intake and diabetes for two distinct metabotypes, which were identified based on 16 biochemical and anthropometric parameters. Results: A low intake of fruits and a high intake of total meat, processed meat and sugar-sweetened beverages (SSB) were significantly associated with diabetes in the total study population. Stratified by metabotype, associations with diabetes remained significant for intake of total meat (OR 1.67, 95% CI 1.04–2.67) and processed meat (OR 2.23, 95% CI 1.24–4.04) in the metabotypes with rather favorable metabolic characteristics, and for intake of fruits (OR 0.83, 95% CI 0.68–0.99) and SSB (OR:1.21, 95% CI 1.09–1.35) in the more unfavorable metabotype. However, only the association between SSB intake and diabetes differed significantly by metabotype (p value for interaction = 0.01). Conclusions: Our findings suggest an influence of metabolic characteristics on diet–diabetes associations, which may help to explain inconsistent previous results. The causality of the observed associations needs to be confirmed in prospective and intervention studies. [ABSTRACT FROM AUTHOR]

This proof-of-concept study investigated the effects of an innovative nutrition concept, comprising texture modification, enrichment, and reshaping, on dietary intake and nutritional status of 16 nursing home residents with chewing and/or swallowing problems (mean age 86.5 ± 7.4 years) in a pre-test post-test design. During 6 weeks with usual texture-modified diet (P1) energy and protein intake were constant. After the implementation of the innovative diet, daily energy intake increased by 204.2 (median) [interquartile range 95.8–444.4] kcal (P = 0.011), and protein intake by 18.3 [9.9–26.3] g (P < 0.001) and remained constant during the following 6 weeks (P2). Body weight decreased during P1 (–0.5 [–1.4 to 0.2] kg), and increased during P2 (+1.1 [0.0 to 1.7] kg, P = 0.004). The present nutrition concept turned out to be a promising strategy for nutritional management of chewing and/or swallowing problems, however, the effects need to be confirmed in larger studies. [ABSTRACT FROM AUTHOR]

Dyslipidemia is a major risk factor for cardiovascular disease, the leading cause of preventable death worldwide. As a result, a full understanding of the factors influencing dyslipidemia is urgently necessary. Bile acids have been recognized as regulators of lipid metabolism, and neutral sterols may influence serum lipid levels. Therefore, this analysis was conducted to better understand the relationship between bile acids, neutral sterols, and dyslipidemia. We examined cross-sectional associations between selected fecal metabolites and serum lipids or markers of dyslipidemia in 1387 participants of the KORA FF4 study using linear and logistic regression models. We found positive associations between fecal bile acids and serum high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-c), total cholesterol, triglycerides and markers of dyslipidemia, though associations were seen most consistently with triglycerides and hypertriglyceridemia. We also found positive associations between fecal cholesterol and serum LDL-c, total cholesterol, triglycerides, hypertriglyceridemia and high serum total cholesterol, though only associations with triglycerides or hypertriglyceridemia remained significant after applying the Bonferroni correction. Unexpectedly, several fecal plant sterols were positively associated with serum lipids and the associated markers of dyslipidemia. However, many of these associations were no longer statistically significant after adjusting for multiple testing. Our results provide insight into the role that bile acids may play in the development or progression of dyslipidemia. However, further confirmation of these results is warranted. Longitudinal and experimental studies are necessary to clarify the mechanisms behind these associations and to determine causality. Image 1 • Fecal bile acids are positively associated with serum lipids and dyslipidemia. • Associations are most consistent with serum triglycerides or hypertriglyceridemia. • Elevated fecal bile acids may be a response to the development of dyslipidemia. [ABSTRACT FROM AUTHOR]

Dietary intake and requirements in nursing home (NH) residents vary individually, but concepts for individualised interventions are currently lacking. Therefore, we present an individualised modular nutritional intervention concept for NH residents with (risk of) malnutrition and describe its application and acceptability. Three enrichment modules—a sweet and a savoury protein cream (40 g, 125 kcal, 10 g protein) and a protein-energy drink (250 mL, 220 kcal, 22 g protein)—were offered to residents of two German NHs single or in combination in five levels of enrichment from level 0 (no enrichment) to 4 (all enrichment modules) to compensate for individual energy and protein deficiencies. Residents with chewing and/or swallowing difficulties received reshaped instead of usual texture-modified meals. The intervention concept was applied to 55 residents (Mean age of 84 ± 8 years, 76.0% female, 25.5% malnutrition). Despite (risk of) malnutrition, 18.2% received no enrichment (level 0). Level 1 was allocated to 10.9%, level 2 to 27.3%, level 3 to 20.0% and level 4 to 23.6% of the residents. 32.7% received reshaped texture-modified meals (RTMM). Participants consuming RTMM were more often assigned to level 4 than residents receiving usual meals (38.8% vs 16.2%). We proposed and successfully applied an individualised modular nutritional intervention concept to NH residents with (risk of) malnutrition. In the next step, the effects of the concept and its transferability to other NHs need to be demonstrated.

Type 2 diabetes mellitus (T2DM) is a global public health epidemic. Diet and lifestyle changes have been demonstrated as effective measures in managing T2DM and preventing or delaying the progression from prediabetes to diabetes, yet the relationship between diet, prediabetes and diabetes is still not entirely clear. The present study aimed to further elucidate the relationship between diet, diabetes and especially prediabetes. A total of 1542 participants of the cross-sectional, population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013/2014) were included in this analysis. Dietary intake was derived using a method combining information from a FFQ and repeated 24-h food lists. Glucose tolerance status was assessed via oral glucose tolerance tests in all participants without a previous physician-confirmed diagnosis of T2DM, and was classified according to the 2003 American Diabetes Association criteria. Crude and fully adjusted multinomial logistic regression models were fitted to examine associations between diet and prediabetes, undetected diabetes mellitus (UDM) and prevalent T2DM. After adjusting for major covariates, fruit was significantly inversely and total meat, processed meat, sugar-sweetened beverages and moderate alcohol significantly associated with UDM and/or prevalent diabetes. Sex-specific analyses showed that in men, coffee was significantly inversely (OR 0·80; 95% CI 0·67, 0·96) and heavy alcohol significantly (OR 1·84; 95% CI 1·14, 2·95) associated with prediabetes. Our findings on diet and T2DM are consistent with current literature, while our results regarding coffee, heavy alcohol consumption and prediabetes highlight new possible targets for primary prevention of the derangement of glucose homeostasis. [ABSTRACT FROM AUTHOR]

Plate diagrams (PDs) are commonly used to monitor dietary intake in nursing homes (NHs). PD intake estimation of texture-modified diet (TMD) is reliable, but only if the offered portion is determined by weighing records (WRs). Offered portion size is usually individualized in NHs and WRs are impractical for NH routine. Thus, an estimation of offered portion size by PDs seems to be appropriate but its validity is unknown. Further, validity of PDs for intake estimation based on estimated offer (instead of WRs) is unknown. Main meal dietary offer and intake were assessed via PDs and WRs. Seventeen NH residents receiving TMD regularly. Offered portion size and intake of breakfast, lunch, and dinner at 42 days were estimated by nursing personnel via PDs (answer options offered portion size: >standard, standard, ¾, ½, ¼, nothing, I do not know; answer options intake: all plus second helping, all, ¾, ½, ¼, nothing, I do not know). In parallel, scientific personnel weighed all offered food items and leftovers. PD estimation of offered portion size was multiplied by energy and protein content of predefined standard portions. Afterward, PD estimation of intake was multiplied by PD determined energy and protein offer to determine the estimated energy and protein intake. PD determined offer and intake were compared with weighed offer and intake. Seventeen residents (14 female) with a mean [±standard deviation (SD)] age of 87.1 (±7.5) years participated in the study. Nursing personnel overestimated offer and intake. Mean daily differences (±SD) between WR and PD determined offer were −349.0 (±315.7) kcal, P <.001, (−36.3% of mean weighed energy offer) and −15.0 (±12.8) g protein, P <.001, (−42.2% of mean weighed protein offer). Mean daily differences (±SD) between WR and PD determined intake were −283.0 (±299.8) kcal, P <.001, (−35.1% of mean weighed energy intake) and −12.6 (±12.7)g protein, P <.001, (−43.1% of mean weighed protein intake). PD estimation of individualized offered portion size of TMD by nursing staff is not valid and can, thus, not be recommended. The mistake in estimation of offered portion size is continued on intake estimation but does not become larger, which supports the use of PDs for intake estimation but just in case of a WR determined offer. [ABSTRACT FROM AUTHOR]

Dietary intake and requirements in nursing home (NH) residents vary individually, but concepts for individualised interventions are currently lacking. Therefore, we present an individualised modular nutritional intervention concept for NH residents with (risk of) malnutrition and describe its application and acceptability. Three enrichment modules-a sweet and a savoury protein cream (40 g, 125 kcal, 10 g protein) and a protein-energy drink (250 mL, 220 kcal, 22 g protein)-were offered to residents of two German NHs single or in combination in five levels of enrichment from level 0 (no enrichment) to 4 (all enrichment modules) to compensate for individual energy and protein deficiencies. Residents with chewing and/or swallowing difficulties received reshaped instead of usual texture-modified meals. The intervention concept was applied to 55 residents (Mean age of 84 ± 8 years, 76.0% female, 25.5% malnutrition). Despite (risk of) malnutrition, 18.2% received no enrichment (level 0). Level 1 was allocated to 10.9%, level 2 to 27.3%, level 3 to 20.0% and level 4 to 23.6% of the residents. 32.7% received reshaped texture-modified meals (RTMM). Participants consuming RTMM were more often assigned to level 4 than residents receiving usual meals (38.8% vs 16.2%). We proposed and successfully applied an individualised modular nutritional intervention concept to NH residents with (risk of) malnutrition. In the next step, the effects of the concept and its transferability to other NHs need to be demonstrated.

Scope: "Metabotyping" describes the grouping of metabolically similar individuals. We aimed to identify valid metabotypes in a large cohort for targeted dietary intervention, for example, for disease prevention., Methods and Results: We grouped 1729 adults aged 32-77 years of the German population-based KORA F4 study (2006-2008) using k-means cluster analysis based on 34 biochemical and anthropometric parameters. We identified three metabolically distinct clusters showing significantly different biochemical parameter concentrations. Cardiometabolic disease status was determined at baseline in the F4 study and at the 7 year follow-up termed FF4 (2013/2014) to compare disease prevalence and incidence between clusters. Cluster 3 showed the most unfavorable marker profile with the highest prevalence of cardiometabolic diseases. Also, disease incidence was higher in cluster 3 compared to clusters 2 and 1, respectively, for hypertension (41.2%/25.3%/18.2%), type 2 diabetes (28.3%/5.1%/2.0%), hyperuricemia/gout (10.8%/2.3%/0.7%), dyslipidemia (19.2%/18.3%/5.6%), all metabolic (54.5%/36.8%/19.7%), and all cardiovascular (6.3%/5.5%/2.3%) diseases together., Conclusion: Cluster analysis based on an extensive set of biochemical and anthropometric parameters allows the identification of comprehensive metabotypes that were distinctly different in cardiometabolic disease occurrence. As a next step, targeted dietary strategies should be developed with the goal of preventing diseases, especially in cluster 3., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)