Integrating crime prevention into urban design and planning

Purpose: This paper aims to understand the delivery of Crime Prevention Through Environmental Design (CPTED) across Europe—from European-wide procedures, through national schemes to effective local strategies. Methodology: The findings come from a review of published literature and reports, case studies and site visits conducted primarily during COST Action TU1203 (2013–16). Findings: Innovative approaches and methods to integrate crime prevention into urban design, planning and management have been generated by multi-agency partnerships and collaborations at European, national and city levels. Methods and procedures developed by the European Committee for Standardization (CEN) Working Group on “Crime Prevention through Urban Planning and Building Design” are pioneering. However, findings show that implementation is best achieved at a local level using methods and procedures tailored to the specific context. Practical and research implications: In-depth research is required to appreciate subtle differences between local approaches and conceptual models developed to better understand approaches and methods. In addition, practitioners and academics working to prevent crime benefit from participation in focused, multi-agency collaborations that, importantly, facilitate visits to urban developments, discussions with local stakeholders responsible for delivery ‘on the ground’ and structured and sustained exploration of innovations and challenges. Originality / value: The authors hope that this paper will contribute to developing a new direction for CPTED practice and research that builds on significant progress in creating safer environments over previous decades

Harnessing Whole Genome Polygenic Risk Scores to Stratify Individuals Based on Cardiometabolic Risk Factors and Biomarkers at Age 10 in the Lifecourse - Brief Report

In this study, we investigated the capability of polygenic risk scores to stratify a cohort of young individuals into risk deciles based on 10 different cardiovascular traits and circulating biomarkers. METHODS: We first conducted large-scale genome-wide association studies using data on adults (mean age 56.5 years) enrolled in the UK Biobank study (n=393 193 to n=461 460). Traits and biomarkers analyzed were body mass index, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, apolipoprotein B, apolipoprotein A-I, C-reactive protein and vitamin D. Findings were then leveraged to build whole genome polygenic risk scores in participants from the Avon Longitudinal Study of Parents and Children (mean age, 9.9 years) which were used to stratify this cohort into deciles in turn and analyzed against their respective traits. RESULTS: For each of the 10 different traits assessed, we found strong evidence of an incremental trend across deciles (all P<0.0001). Large differences were identified when comparing top and bottom deciles; for example, using the apolipoprotein B polygenic risk scores there was a mean difference of 13.2 mg/dL for this established risk factor of coronary heart disease in later life. CONCLUSIONS: Although the use of polygenic prediction in a clinical setting may currently be premature, our findings suggest they are becoming increasingly powerful as a means of predicting complex trait variation at an early stage in the lifecourse

Predictors of psychological well-being among treatment seeking transgender individuals

Research has yet to identify specific predictors of poor psychological well-being and quality of life in transgender people. This study aimed first to explore the predictive value of five factors known to be associated with poor psychological well-being in cis- and transgender people; age, self-esteem, victimisation, interpersonal problems, and body dissatisfaction. Second, to investigate the mediatory role of self-esteem and social support. Two hundred and eight participants (104 transgender and 104 cisgender controls), matched by age and gender, completed measures of these predictor variables, along with general psychopathology and functional quality of life. The results indicate that in the transgender group, greater psychopathology and greater depression were predicted by younger age (psychopathology only), lower self-esteem, greater body dissatisfaction, and greater interpersonal problems. In the cisgender group, only lower self-esteem and greater interpersonal problems were significant predictors of these factors. For quality of life, lower self-esteem and greater interpersonal problems were significant predictors of low quality of life in both groups. Self-esteem but not social support mediated the above relationships. Overall, self-esteem and interpersonal problems appear to be crucial factors that influence well-being. Those providing treatment to transgender people should pay more attention to these areas

The long-term impact of folic acid in pregnancy on offspring DNA methylation : follow-up of the Aberdeen folic acid supplementation trial (AFAST)

Funding This work was supported by the NIHR Bristol Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. R.C.R., G.C.S., N.K., T.G., G.D.S. and C.L.R. work in a unit that receives funds from the University of Bristol and the UK Medical Research Council (MC_UU_12013/1, MC_UU_12013/2 and MC_UU_12013/8). This work was also supported by CRUK (grant number C18281/A19169) and the ESRC (grant number ES/N000498/1). C.M.T. is supported by a Wellcome Trust Career Re-entry Fellowship (grant number 104077/Z/14/Z).Peer reviewedPublisher PD

Alcohol intake and cardiovascular risk factors:A Mendelian randomisation study

Mendelian randomisation studies from Asia suggest detrimental influences of alcohol on cardiovascular risk factors, but such associations are observed mainly in men. The absence of associations of genetic variants (e.g. rs671 in ALDH2) with such risk factors in women – who drank little in these populations – provides evidence that the observations are not due to genetic pleiotropy. Here, we present a Mendelian randomisation study in a South Korean population (3,365 men and 3,787 women) that 1) provides robust evidence that alcohol consumption adversely affects several cardiovascular disease risk factors, including blood pressure, waist to hip ratio, fasting blood glucose and triglyceride levels. Alcohol also increases HDL cholesterol and lowers LDL cholesterol. Our study also 2) replicates sex differences in associations which suggests pleiotropy does not underlie the associations, 3) provides further evidence that association is not due to pleiotropy by showing null effects in male non-drinkers, and 4) illustrates a way to measure population-level association where alcohol intake is stratified by sex. In conclusion, population-level instrumental variable estimation (utilizing interaction of rs671 in ALDH2 and sex as an instrument) strengthens causal inference regarding the largely adverse influence of alcohol intake on cardiovascular health in an Asian population

Best (but oft-forgotten) practices:the design, analysis, and interpretation of Mendelian randomization studies

Mendelian randomization (MR) is an increasingly important tool for appraising causality in observational epidemiology. The technique exploits the principle that genotypes are not generally susceptible to reverse causation bias and confounding, reflecting their fixed nature and Mendel’s first and second laws of inheritance. The approach is, however, subject to important limitations and assumptions that, if unaddressed or compounded by poor study design, can lead to erroneous conclusions. Nevertheless, the advent of 2-sample approaches (in which exposure and outcome are measured in separate samples) and the increasing availability of open-access data from large consortia of genome-wide association studies and population biobanks mean that the approach is likely to become routine practice in evidence synthesis and causal inference research. In this article we provide an overview of the design, analysis, and interpretation of MR studies, with a special emphasis on assumptions and limitations. We also consider different analytic strategies for strengthening causal inference. Although impossible to prove causality with any single approach, MR is a highly cost-effective strategy for prioritizing intervention targets for disease prevention and for strengthening the evidence base for public health policy

Association between breastfeeding and DNA methylation over the life course:findings from the Avon Longitudinal Study of Parents and Children (ALSPAC)

Background: Breastfeeding is associated with short and long-term health benefits. Long-term effects might be mediated by epigenetic mechanisms, yet the literature on this topic is scarce. We performed the first epigenome-wide association study of infant feeding, comparing breastfed vs non-breastfed children. We measured DNA methylation in children from peripheral blood collected in childhood (age 7 years, N = 640) and adolescence (age 15&ndash;17 years, N = 709) within the Accessible Resource for Integrated Epigenomic Studies (ARIES) project, part of the larger Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Cord blood methylation (N = 702) was used as a negative control for potential pre-natal residual confounding. Results: Two differentially-methylated sites presented directionally-consistent associations with breastfeeding at ages 7 and 15&ndash;17 years, but not at birth. Twelve differentially-methylated regions in relation to breastfeeding were identified, and for three of them there was evidence of directional concordance between ages 7 and 15&ndash;17 years, but not between birth and age 7 years. Conclusions: Our findings indicate that DNA methylation in childhood and adolescence may be predicted by breastfeeding, but further studies with sufficiently large samples for replication are required to identify robust associations