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Einleitung
Die Prävalenz der über 80-jährigen bei Ulcus cruris venosum (VLU) beträgt 4-5 %, obwohl diese Altersgruppe nur 1 % der Gesamtbevölkerung ausmacht. Zusätzlich wird bei VLU-Patienten häufig eine Mangelernährung beobachtet. Insbesondere geriatrische Patienten leiden darunter. Dabei ist bekannt, dass Mangelernährung Einfluss auf die Wundheilung und somit auf die Lebensqualität der Patienten hat. Diverse Studien beschreiben erste erfolgreiche ernährungstherapeutische Ansätze für einen beschleunigten Wundheilungsprozess. Allerdings ist die Ernährungstherapie bei VLU-Patienten wenig erforscht. Ziel dieser Arbeit ist es einen Überblick über den ernährungsphysiologischen Einfluss zur VLU zu schaffen, um mögliche Ernährungsinterventionen für geriatrische Patienten zu erhalten.
Diet can influence healthy aging through anti- or proinflammatory effects, partly by modulating the gut microbiome composition. This study investigated the relationships between the Dietary Inflammatory Index (DII), the gut microbiome, and nutritional status in elderly individuals. Methods: This cross-sectional analysis included 114 home-dwelling individuals aged over 70 years. The Energy-adjusted DII (E-DII) was calculated from 3-day food diaries, and blood samples were taken to measure micronutrient status, glucose, and lipid metabolism. Body composition was assessed using bioimpedance, and fecal gut microbiome composition was analyzed through 16S rRNA gene sequencing. The participants were categorized into maintaining an anti-inflammatory diet (AD) and a pro-inflammatory diet (PD) based on the median E-DII score. The associations of E-DII groups with blood markers and microbial diversity and composition were examined using the analysis of covariance, permutational analysis of variance, and multivariate linear models. Results: The AD (n = 57, 76 ± 3.83 years) and PD (n = 57, 75 ± 5.21 years) groups were similar in age but differed in sex distribution, with a higher proportion of females in the AD group (p = 0.02). When compared to the PD group and adjusted for sex, the AD group had a lower body mass index, fat mass, fasting insulin level, HOMA-IR (Homeostasis Model Assessment of Insulin Resistance), fasting triglycerides, and serum uric acid concentration (all p < 0.05), with higher concentrations of high-density lipoprotein, red-blood-cell folate (RBC), and Omega-3 index (all p < 0.05). While the microbial diversity and composition did not differ between the DII groups, folate concentrations were negatively associated with Agathobacter and positively associated with Bacteroides abundance (both q = 0.23). Lower uric acid concentrations were associated with a higher abundance of Bifidobacterium (q = 0.09) and lower abundance of Phocaeicola (q = 0.11). Discussion: The study suggests that following an anti-inflammatory diet is associated with improved nutritional status in the elderly. Dietary blood markers, rather than E-DII, were found to be associated with the gut microbiome, suggesting a potential link between the microbiome and changes in nutritional markers independent of diet. Further studies are needed to explore the causal relationship between dietary inflammatory potential, gut microbiome, and healthy aging.
Studies on nutrition have historically concentrated on food-shortages and over-nutrition. The physiological states of feeling hungry or being satiated and its dynamics in food choices, dietary patterns, and nutritional behavior, have not been the focus of many studies. Currently, visual analytic using easy-to-use tooling offers applicability in a wide-range of disciplines. In this interdisciplinary pilot-study we tested a novel visual analytic software to assess dietary patterns and food choices for greater understanding of nutritional behavior when hungry and when satiated. We developed software toolchain and tested the hypotheses that there is no difference between visual search patterns of dishes 1) when hungry and when satiated and 2) in being vegetarian and non-vegetarian. Results indicate that food choices can be deviant from dietary patterns but correlate slightly with dish-gazing. Further, scene perception probably could vary between being hungry and satiated. Understanding t he complicated relationship between scene perception and nutritional behavioral patterns and scaling up this pilot-study to a full-study using our introduced software approaches is indispensable.