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Background: A transition to healthy and sustainable diets has the potential to improve human and planetary health but diets need to meet requirements for nutritional adequacy, health, environmental targets, and be acceptable to consumers.Objective: The objective of this study was to derive a nutritionally adequate and healthy diet that has the least deviation possible from the average observed diet of Danish adults while aiming for a greenhouse gas emission (GHGE) reduction of 31%, corresponding to the GHGE level of the Danish plant-rich diet, which lays the foundation for the current healthy and sustainable food-based dietary guidelines (FBDGs) in Denmark.Methods: With an objective function minimizing the departure from the average observed diet of Danish adults, four diet optimizations were run using quadratic programming, with different combinations of diet constraints: (1) nutrients only (Nutri), (2) nutrients and health-based targets for food amounts (NutriHealth), (3) GHGE only (GHGE), and finally, (4) combined nutrient, health and GHGE constraints (NutriHealthGHGE).Results: The GHGE of the four optimized diets were 3.93 kg CO2-eq (Nutri), 3.77 kg CO2-eq (NutriHealth) and 3.01 kg CO2-eq (GHGE and NutriHealthGHGE), compared to 4.37 kg CO2-eq in the observed diet. The proportion of energy from animal-based foods was 21%–25% in the optimized diets compared to 34% in the observed diet and 18% in the Danish plant-rich diet. Moreover, compared to the average Danish diet, the NutriHealthGHGE diet contained more grains and starches (44 E% vs. 28 E%), nuts (+230%), fatty fish (+89%), eggs (+47%); less cheese (−73%), animal-based fats (−76%), total meat (−42%); and very limited amounts of ruminant meat, soft drinks, and alcoholic beverages (all-90%), while the amounts of legumes and seeds were unchanged. On average, the mathematically optimized NutriHealthGHGE diet showed a smaller deviation from the average Danish diet compared to the Danish plant-rich diet (38% vs. 169%, respectively).Conclusion: The final optimized diet presented in this study represents an alternative way of composing a nutritionally adequate and healthy diet that has the same estimated GHGE as a diet consistent with the climate-friendly FBDGs in Denmark. As this optimized diet may be more acceptable for some consumers, it might help to facilitate the transition toward more healthy and sustainable diets in the Danish population.

Background Kidney involvement in systemic lupus erythematosus (SLE) affects approximately 40% of patients and is associated with increased mortality and morbidity. The risk of renal involvement has primarily been reported as hazard ratios (HR) which may be challenging to interpret on a patient level. Additional data reporting such as absolute risk estimates may strengthen risk stratification and compliance. This study provides absolute risk estimations of risk of new-onset proteinuria among SLE patients. Methods Danish SLE-centres provided clinical data on first time observations of proteinuria and other clinical parameters listed in the 1997 American College of Rheumatology Classification Criteria for SLE. Time from first occurring non-renal manifestation to new-onset proteinuria or censoring defined time at risk. Cox-regression models were used to identify risk factors for new-onset proteinuria and to calculate risk of proteinuria stratified by risk factor debut age, duration and sex. Models were reduced using a backwards elimination process for p>0.01. Potentially relevant interaction covariate terms were added to the model in a forward selection procedure using p

Forekomsten af multisygdom ligger på mellem 22-37 % i den danske befolkning. Forekomsten vil stige med cirka 1,4 % om året de næste 10 år. Multisygdom defineres oftest som forekomsten af to eller flere kroniske sygdomme hos den samme person. I denne rapport benyttes denne definition.Det er velbeskrevet at multisygdom reducerer den sundhedsrelaterede livskvalitet, den fysiskefunktionsevne, og øger risikoen for tidlig død, indlæggelser og generelt højere forbrug i sundhedsvæsenet. Multisygdom udgør en substantiel økonomisk byrde for både sundhedsvæsenet og for samfundet (1). Oftest vil patienter med flere samtidige kroniskesygdomme modtage separat behandling for hver sygdom i det specialeopdelte sundhedsvæsen.Dette fører ofte til fragmenterede sundhedsfaglige indsatser, hvor hverken behandlere ellerpatienten har et samlet overblik over sygdommene og disses behandlinger. Litteraturen omhandlende forekomsten af multisygdom nævner ofte kun, hvor mange kroniskesygdomme den enkelte har – uden at tage højde for de sygdomskombinationer, der typisk forekommer i befolkningen. Vi ved, at multisygdom er forbundet med social ulighed, menikke hvordan uligheden konkret manifesterer sig i termer af de forskellige sygdomskombinationer i dag.Denne rapport beskriver multisygdom og sammenhæng med social ulighed. Rapporten opdeler desuden de multisyge voksne danskere i sygdomsclustre, baseret på deressygdomskombinationer, og undersøger hvorledes uligheden ser ud indenfor disse clustre.

Additional file 1: Supplementary figure S1. The twenty-item Patient Assessment of Chronic Illness Care (PACIC) questionnaire

Additional file 1: Figure S1. Yearly variation of the mean abundance for each country. The abundance (y axis) was calculated as the mean all the observations (log transformed) from each country. Figure S2. QQ-plots of the residuals per month for the Obsoletus ensemble. Figure S3. QQ-plots of the residuals per month for the Pulicaris ensemble. Figure S4. Comparison of the abundance maps for each month using Random Forest (RF) and Interpolations for the Obsoletus ensemble. a Maps from January to June. b maps from July to December. Figure S5. Comparison of the abundance maps for each month using Random Forest (RF) and Interpolations for the Pulicaris ensemble. a Maps from January to June. b Maps from July to December. Figure S6. Comparison of the abundance maps for each month using Random Forest (RF) and Interpolations for Culicoides imicola. a Maps from January to June. b Maps from July to December. Figure S7. At a local scale, interpolation maps produce a smother surface between the farms compared to environmental driven RF, for which the predictions differ between adjacent pixels. The example shown in the figure corresponds to the August maps for the Obsoletus ensemble. Green dots: farms used for training, purple dots: farms within the test set.

In this report we present statistical models that describe the incidence of Coccidiosis parasites in mink in thirty mink farms in Denmark during the period April to October 2016. The dataset was obtained by asking the farmer at each mink farm to select 5 sows and collect a fecal sample from the sows on 16 dates during the period April to October. Once the sows give birth to kits (usually at the end of april), a pooled fecal sample from the kits belonging to each sow was also collected on the same dates as the sows. All the fecal samples were then analysed for presence of two types of Coccidiosis-causing parasites: Eimeria and Isospora. If Eimeria was present, the sample was examined for the presence of three different types of Eimeria, called tyk, tynd and lille. In addition, the fecal sample was classified by the farmer according to a feces score (hereafter F score) ranging from 1 to 5.Various characteristics of the mink and the farms were also included in the dataset, including from which of three feed suppliers the farm obtains the feed, birth date of the kits, litter size, age of the sow. The aim of this project was to use statistical models to investigate which factors can account for the incidence of Eimeria (and its three subtypes), and Isospora, as well as the F score, observed during the study. This means there were 6 response (independent) variables to investigate: Eimeria, tynd, tyk, lille, Isospora and F score.