Strategic use of the Internet by small- and medium-sized companies: an exploratory study
In: Information economics and policy, Band 14, Heft 1, S. 75-93
ISSN: 0167-6245
8 Ergebnisse
Sortierung:
In: Information economics and policy, Band 14, Heft 1, S. 75-93
ISSN: 0167-6245
In: The Journal of sex research, S. 1-13
ISSN: 1559-8519
In: American journal of health promotion, Band 30, Heft 6, S. 465-474
ISSN: 2168-6602
Purpose: To examine the mediating effect of vitality in the relationship between healthy lifestyle characteristics and health-care and productivity-related costs. Design: Observational prospective cohort study with 2 measurements. Online questionnaires were filled out in 2013 (T0) and 2014 (T1). Setting: A random sample of a Dutch online interview panel was obtained. Subjects: Data of 4231 Dutch adults who had complete data at T0 and T1 were used in the present study. Participants were representative for the Dutch adult population in terms of age, gender, and having chronic disease(s). Measures: Healthy Lifestyle Index (HLI), vitality, and health-care and productivity-related costs. The HLI consisted of the sum of 6 healthy lifestyle characteristics, including a healthy BMI (yes/no), meeting physical activity, fruit, vegetable, and alcohol consumption guidelines (yes/no), and smoking status (yes: non or former smoker/no: current smoker). Health-care and productivity-related costs were measured using a utilization questionnaire. Analysis: Linear regression analysis. Results: The HLI was related to vitality. In addition, vitality was related to health-care costs and productivity-related costs. Furthermore, vitality was found to transmit 28.4% of the effect of HLI on health-care costs and 39.4% of the effect of HLI on productivity-related costs. Conclusion: Lifestyle was related to vitality and vitality to health-care and productivity-related costs. Vitality mediated the relationship between lifestyle and health-care and productivity-related costs. Therefore, we recommend to sustain and improve both vitality and lifestyle.
In: Journal of Developmental and Life-Course Criminology, Band 9, Heft 3, S. 455-482
ISSN: 2199-465X
AbstractCrime victimization is associated with a more unfavorable health profile. We examined associations of victimization of property, violence, and sexual crime with mental health indices for depression, anxiety, and loneliness and explore their etiology in Dutch twin families. The data were collected from adult twins, their parents, siblings, spouses, and offspring participating in longitudinal survey studies of the Netherlands Twin Register (N = 19,867). First, we tested if there is an association between victimization and loneliness, anxiety, and depression at the population level. Second, discordant twin pairs were identified, where one twin was a crime victim and the cotwin was not. This design allows controlling for confounding by shared environment and genetic factors. Third, a longitudinal comparison was made of pre- and post-victimization data in victims, their family members, and unrelated individuals. At the population level, victimization was associated with increased depression, anxiety, and loneliness, except for property crime, which was not associated with depression and anxiety. The associations were strongest for violent and sexual crimes. Within discordant twin pairs, no significant differences were found between the victimized and non-victimized twins. These results confirm that crime victimization is associated with adverse mental health outcomes and loneliness, with the strength of this association differing per type of crime. There is no strong evidence that the relationship between victimization and mental health or loneliness follows a simple causal model, as the relationship can be partly explained by genetic and shared environmental confounding. These results also suggest that victims of sexual and violent crimes may already experience more mental health problems before victimization than non-victims, and that individuals with more mental health problems and loneliness are at increased risk of becoming a victim.
In: Journal of Developmental and Life-Course Criminology
ISSN: 2199-465X
Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell type-specific regulatory component of a set of EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to 20 publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology. ; C.E.B. was supported by a PhD fellowship from the EU-FP7 project EpiTrain (316758). J.H. was supported by the UCL Cancer Institute Research Trust. V.K.R. was supported by BLUEPRINT (282510). K.D. was funded as a HSST trainee by NHS Health Education England. M.F. was supported by the BHF Cambridge Centre of Excellence (RE/13/6/30180). Research in W.H.O.'s laboratory was supported by EU-FP7 project BLUEPRINT (282510) and by program grants from the National Institute for Health Research (NIHR, http://www.nihr.ac.uk) and the British Heart Foundation under numbers RP-PG-0310-1002 and RG/09/12/28096 (https://www.bhf.org.uk/). W.H.O.'s laboratory receives funding from NHS Blood and Transplant for facilities. We gratefully acknowledge the participation of all NIHR Cambridge BioResource volunteers. We thank the Cambridge BioResource staff for their help with volunteer recruitment. We thank members of the Cambridge BioResource SAB and Management Committee for their support of our study and the National Institute for Health Research Cambridge Biomedical Research Centre for funding. R.S. and his group were supported by the European Union in the framework of the BLUEPRINT Project (HEALTH-F5-2011-282510) and the German Ministry of Science and Education (BMBF) in the framework of the MMML-MYC-SYS project (036166B). We thank Deborah Winter (Weizmann Institute) for supplying a set of microglial enhancers from Lavin et al. (2014). Research in S.B.'s laboratory was supported by the Wellcome Trust (99148), Royal Society Wolfson Research Merit Award (WM100023), and EU-FP7 projects EpiTrain (316758), EPIGENESYS (257082), and BLUEPRINT (282510).
BASE
This is the final version of the article. Available from Springer Nature via the DOI in this record. ; Raw data were submitted to the European Genome-phenome Archive (EGA) under accession EGAS00001001077. ; X-chromosome inactivation (XCI), i.e., the inactivation of one of the female X chromosomes, restores equal expression of X-chromosomal genes between females and males. However, ~10% of genes show variable degrees of escape from XCI between females, although little is known about the causes of variable XCI. Using a discovery data-set of 1867 females and 1398 males and a replication sample of 3351 females, we show that genetic variation at three autosomal loci is associated with female-specific changes in X-chromosome methylation. Through cis-eQTL expression analysis, we map these loci to the genes SMCHD1/METTL4, TRIM6/HBG2, and ZSCAN9. Low-expression alleles of the loci are predominantly associated with mild hypomethylation of CpG islands near genes known to variably escape XCI, implicating the autosomal genes in variable XCI. Together, these results suggest a genetic basis for variable escape from XCI and highlight the potential of a population genomics approach to identify genes involved in XCI. ; This research was financially supported by several institutions: BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO, numbers 184.021.007 and 184.033.111); the UK Medical Research Council; Wellcome (www.wellcome.ac.uk; [grant number 102215/2/13/2 to ALSPAC]); the University of Bristol to ALSPAC; the UK Economic and Social Research Council (www.esrc.ac.uk; [ES/N000498/1] to CR); the UK Medical Research Council (www.mrc.ac.uk; grant numbers [MC_UU_12013/1, MC_UU_12013/2 to JLM, CR]); the Helmholtz Zentrum München – German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria; the Munich Center of Health Sciences (MC-Health), Ludwig-Maximilians-Universität, as part of LMUinnovativ; the Wellcome Trust, Medical Research Council, European Union (EU), and the National Institute for Health Research (NIHR)- funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London.
BASE
16 páginas, 5 figuras ; Genetic discoveries of Alzheimer's disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer's disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer's disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer's disease. ; The present work has been performed as part of the doctoral program of I. de Rojas at the Universitat de Barcelona (Barcelona, Spain) supported by national grant from the Instituto de Salud Carlos III FI20/00215. The Genome Research @ Fundació ACE project (GR@ACE) is supported by Grifols SA, Fundación bancaria "La Caixa", Fundació ACE, and CIBERNED. A.R. and M.B. receive support from the European Union/EFPIA Innovative Medicines Initiative Joint undertaking ADAPTED and MOPEAD projects (grant numbers 115975 and 115985, respectively). M.B. and A.R. are also supported by national grants PI13/02434, PI16/01861, PI17/01474, PI19/01240 and PI19/01301. Acción Estratégica en Salud is integrated into the Spanish National R + D + I Plan and funded by ISCIII (Instituto de Salud Carlos III)—Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER—"Una manera de hacer Europa"). Some control samples and data from patients included in this study were provided in part by the National DNA Bank Carlos III (www.bancoadn.org, University of Salamanca, Spain) and Hospital Universitario Virgen de Valme (Sevilla, Spain); they were processed following standard operating procedures with the appropriate approval of the Ethical and Scientific Committee. Amsterdam dementia Cohort (ADC): Research of the Alzheimer center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. The Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting VUmc fonds. The clinical database structure was developed with funding from Stichting Dioraphte. Genotyping of the Dutch case-control samples was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). 100-Plus study: We are grateful for the collaborative efforts of all participating centenarians and their family members and/or relations. This work was supported by Stichting Alzheimer Nederland (WE09.2014-03), Stichting Diorapthe, horstingstuit foundation, Memorabel (ZonMW project number 733050814, 733050512) and Stichting VUmc Fonds. Genotyping of the 100-Plus Study was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND FP-829-029 (ZonMW project number 733051061). Longitudinal Aging Study Amsterdam (LASA) is largely supported by a grant from the Netherlands Ministry of Health, Welfare and Sports, Directorate of Long-Term Care. The authors are grateful to all LASA participants, the fieldwork team and all researchers for their ongoing commitment to the study. This work was supported by a grant (European Alzheimer DNA BioBank, EADB) from the EU Joint Program—Neurodegenerative Disease Research (JPND) and also funded by Inserm, Institut Pasteur de Lille, the Lille Métropole Communauté Urbaine, the French government's LABEX DISTALZ program (development of innovative strategies for a transdisciplinary approach to AD). Genotyping of the German case-control samples was performed in the context of EADB (European Alzheimer DNA biobank) funded by the JPco-fuND (German Federal Ministry of Education and Research, BMBF: 01ED1619A). Full acknowledgments for the studies that contributed data can be found in the Supplementary Note. We thank the numerous participants, researchers, and staff from many studies who collected and contributed to the data. We thank the International Genomics of Alzheimer's Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i–Select chips was funded by the French National Foundation on AD and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant n° 503480), Alzheimer's Research UK (Grant n° 503176), the Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIA/NHLBI grants AG049505, AG058589, HL105756 and AGES contract N01–AG–12100, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer's Association grant ADGC–10–196728. This research has been conducted using the UK Biobank public resource obtained through the University of Edinburg Data Share (https://datashare.is.ed.ac.uk/handle/10283/3364). ; Peer reviewed
BASE