Research and Forest Recreation

Research on forest management for recreation is described with references to recent work. The need is advanced to study individual perception and the social and physical environment so as to guide the provision of appropriate forest settings for recreation activity

Translation and validation of non-English versions of the Ankylosing Spondylitis Quality of Life (ASQOL) questionnaire

BACKGROUND: The Ankylosing Spondylitis Quality of Life (ASQOL) questionnaire is a unidimensional, disease-specific measure developed in the UK and the Netherlands. This study describes its adaptation into other languages. METHODS: The UK English ASQOL was translated into US English; Canadian French and English; French; German; Italian; Spanish; and Swedish (dual-panel methods). Cognitive debriefing interviews were conducted with AS patients. Psychometric/scaling properties were assessed using data from two Phase III studies of adalimumab. Baseline and Week-2 data were used to assess test-retest reliability. Validity was determined by correlation of ASQOL with SF-36 and BASFI and by discriminative ability of ASQOL based on disease severity. Item response theory (Rasch model) was used to test ASQOL's scaling properties. RESULTS: Cognitive debriefing showed the new ASQOL versions to be clear, relevant and comprehensive. Sample sizes varied, but were sufficient for: psychometric/scaling assessment for US English and Canadian English; psychometric but not scaling analyses for German; and preliminary evidence of these properties for the remaining languages. Test-retest reliability and Cronbach's alpha coefficients were high: US English (0.85, 0.85), Canadian English (0.87, 0.86), and German (0.77, 0.79). Correlations of ASQOL with SF-36 and BASFI for US English, Canadian English, and German measures were moderate, but ASQOL discriminated between patients based on perceived disease severities (p < 0.01). Results were comparable for the other languages. US English and Canadian English exhibited fit to the Rasch model (non-significant p-values: 0.54, 0.68), confirming unidimensionality. CONCLUSION: The ASQOL was successfully translated into all eight languages. Psychometric properties were excellent for US English, Canadian English, and German, and extremely promising for the other languages

Vitamin G: effects of green space on health, well-being, and social safety

BACKGROUND: Looking out on and being in the green elements of the landscape around us seem to affect health, well-being and feelings of social safety. This article discusses the design of a research program on the effects of green space in the living environment on health, well-being and social safety. METHODS/DESIGN: The program consists of three projects at three different scales: at a macro scale using data on the Netherlands as a whole, at an intermediate scale looking into the specific effect of green space in the urban environment, and at micro scale investigating the effects of allotment gardens. The projects are observational studies, combining existing data on land use and health interview survey data, and collecting new data through questionnaires and interviews. Multilevel analysis and GIS techniques will be used to analyze the data. DISCUSSION: Previous (experimental) research in environmental psychology has shown that a natural environment has a positive effect on well-being through restoration of stress and attentional fatigue. Descriptive epidemiological research has shown a positive relationship between the amount of green space in the living environment and physical and mental health and longevity. The program has three aims. First, to document the relationship between the amount and type of green space in people's living environment and their health, well-being, and feelings of safety. Second, to investigate the mechanisms behind this relationship. Mechanisms relate to exposure (leading to stress reduction and attention restoration), healthy behavior and social integration, and selection. Third, to translate the results into policy on the crossroads of spatial planning, public health, and safety. Strong points of our program are: we study several interrelated dependent variables, in different ordinary settings (as opposed to experimental or extreme settings), focusing on different target groups, using appropriate multilevel methods

100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care — Preliminary Report

BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection. METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis. RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives. CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Germline selection shapes human mitochondrial DNA diversity.

Approximately 2.4% of the human mitochondrial DNA (mtDNA) genome exhibits common homoplasmic genetic variation. We analyzed 12,975 whole-genome sequences to show that 45.1% of individuals from 1526 mother-offspring pairs harbor a mixed population of mtDNA (heteroplasmy), but the propensity for maternal transmission differs across the mitochondrial genome. Over one generation, we observed selection both for and against variants in specific genomic regions; known variants were more likely to be transmitted than previously unknown variants. However, new heteroplasmies were more likely to match the nuclear genetic ancestry as opposed to the ancestry of the mitochondrial genome on which the mutations occurred, validating our findings in 40,325 individuals. Thus, human mtDNA at the population level is shaped by selective forces within the female germ line under nuclear genetic control, which ensures consistency between the two independent genetic lineages.NIHR, Wellcome Trust, MRC, Genomics Englan

Public hunting & private land

Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/115503/1/39015003275370.pd