A Profile of Smoking and Health in Wales

No abstract available

Assessing the sensitivity of seagrass bed biotopes to pressures associated with marine activities.

This project was commissioned to generate an improved understanding of the sensitivities of seagrass habitats to pressures associated with human activities in the marine environment - to provide an evidence base to facilitate and support management advice for Marine Protected Areas; development of UK marine monitoring and assessment, and conservation advice to offshore marine industries. Seagrass bed habitats are identified as a Priority Marine Feature (PMF) under the Marine (Scotland) Act 2010, they are also included on the OSPAR list of threatened and declining species and habitats, and are a Habitat of Principle Importance (HPI) under the Natural Environment and Rural Communities (NERC) Act 2006, in England and Wales. The purpose of this project was to produce sensitivity assessments with supporting evidence for the HPI, OSPAR and PMF seagrass/Zostera bed habitat definitions, clearly documenting the evidence behind the assessments and any differences between assessments. Nineteen pressures, falling in five categories - biological, hydrological, physical damage, physical loss, and pollution and other chemical changes - were assessed in this report. Assessments were based on the three British seagrasses Zostera marina, Z. noltei and Ruppia maritima. Z. marina var. angustifolia was considered to be a subspecies of Z. marina but it was specified where studies had considered it as a species in its own rights. Where possible other components of the community were investigated but the basis of the assessment focused on seagrass species. To develop each sensitivity assessment, the resistance and resilience of the key elements were assessed against the pressure benchmark using the available evidence. The benchmarks were designed to provide a ‘standard’ level of pressure against which to assess sensitivity. Overall, seagrass beds were highly sensitive to a number of human activities: • penetration or disturbance of the substratum below the surface; • habitat structure changes – removal of substratum; • physical change to another sediment type; • physical loss of habitat; • siltation rate changes including and smothering; and • changes in suspended solids. High sensitivity was recorded for pressures which directly impacted the factors that limit seagrass growth and health such as light availability. Physical pressures that caused mechanical modification of the sediment, and hence damage to roots and leaves, also resulted in high sensitivity. Seagrass beds were assessed as ‘not sensitive’ to microbial pathogens or ‘removal of target species’. These assessments were based on the benchmarks used. Z. marina is known to be sensitive to Labyrinthula zosterae but this was not included in the benchmark used. Similarly, ‘removal of target species’ addresses only the biological effects of removal and not the physical effects of the process used. For example, seagrass beds are probably not sensitive to the removal of scallops found within the bed but are highly sensitive to the effects of dredging for scallops, as assessed under the pressure penetration or disturbance of the substratum below the surface‘. This is also an example of a synergistic effect Assessing the sensitivity of seagrass bed biotopes to pressures associated with marine activities between pressures. Where possible, synergistic effects were highlighted but synergistic and cumulative effects are outside the scope off this study. The report found that no distinct differences in sensitivity exist between the HPI, PMF and OSPAR definitions. Individual biotopes do however have different sensitivities to pressures. These differences were determined by the species affected, the position of the habitat on the shore and the sediment type. For instance evidence showed that beds growing in soft and muddy sand were more vulnerable to physical damage than beds on harder, more compact substratum. Temporal effects can also influence the sensitivity of seagrass beds. On a seasonal time frame, physical damage to roots and leaves occurring in the reproductive season (summer months) will have a greater impact than damage in winter. On a daily basis, the tidal regime could accentuate or attenuate the effects of pressures depending on high and low tide. A variety of factors must therefore be taken into account in order to assess the sensitivity of a particular seagrass habitat at any location. No clear difference in resilience was established across the three seagrass definitions assessed in this report. The resilience of seagrass beds and the ability to recover from human induced pressures is a combination of the environmental conditions of the site, growth rates of the seagrass, the frequency and the intensity of the disturbance. This highlights the importance of considering the species affected as well as the ecology of the seagrass bed, the environmental conditions and the types and nature of activities giving rise to the pressure and the effects of that pressure. For example, pressures that result in sediment modification (e.g. pitting or erosion), sediment change or removal, prolong recovery. Therefore, the resilience of each biotope and habitat definitions is discussed for each pressure. Using a clearly documented, evidence based approach to create sensitivity assessments allows the assessment and any subsequent decision making or management plans to be readily communicated, transparent and justifiable. The assessments can be replicated and updated where new evidence becomes available ensuring the longevity of the sensitivity assessment tool. The evidence review has reduced the uncertainty around assessments previously undertaken in the MB0102 project (Tillin et al 2010) by assigning a single sensitivity score to the pressures as opposed to a range. Finally, as seagrass habitats may also contribute to ecosystem function and the delivery of ecosystem services, understanding the sensitivity of these biotopes may also support assessment and management in regard to these. Whatever objective measures are applied to data to assess sensitivity, the final sensitivity assessment is indicative. The evidence, the benchmarks, the confidence in the assessments and the limitations of the process, require a sense-check by experienced marine ecologists before the outcome is used in management decisions

An intervention to promote self-management, independence and self-efficacy in people with early-stage dementia : the Journeying through Dementia RCT

Background There are few effective interventions for dementia. Aim To determine the clinical effectiveness and cost-effectiveness of an intervention to promote self-management, independence and self-efficacy in people with early-stage dementia. Objectives To undertake a randomised controlled trial of the Journeying through Dementia intervention compared with usual care, conduct an internal pilot testing feasibility, assess intervention delivery fidelity and undertake a qualitative exploration of participants’ experiences. Design A pragmatic two-arm individually randomised trial analysed by intention to treat. Participants A total of 480 people diagnosed with mild dementia, with capacity to make informed decisions, living in the community and not participating in other studies, and 350 supporters whom they identified, from 13 locations in England, took part. Intervention Those randomised to the Journeying through Dementia intervention (n = 241) were invited to take part in 12 weekly facilitated groups and four one-to-one sessions delivered in the community by secondary care staff, in addition to their usual care. The control group (n = 239) received usual care. Usual care included drug treatment, needs assessment and referral to appropriate services. Usual care at each site was recorded. Main outcome measures The primary outcome was Dementia-Related Quality of Life score at 8 months post randomisation, with higher scores representing higher quality of life. Secondary outcomes included resource use, psychological well-being, self-management, instrumental activities of daily living and health-related quality of life. Randomisation and blinding Participants were randomised in a 1 : 1 ratio. Staff conducting outcome assessments were blinded. Data sources Outcome measures were administered in participants’ homes at baseline and at 8 and 12 months post randomisation. Interviews were conducted with participants, participating carers and interventionalists. Results The mean Dementia-Related Quality of Life score at 8 months was 93.3 (standard deviation 13.0) in the intervention arm (n = 191) and 91.9 (standard deviation 14.6) in the control arm (n = 197), with a difference in means of 0.9 (95% confidence interval –1.2 to 3.0; p = 0.380) after adjustment for covariates. This effect size (0.9) was less than the 4 points defined as clinically meaningful. For other outcomes, a difference was found only for Diener’s Flourishing Scale (adjusted mean difference 1.2, 95% confidence interval 0.1 to 2.3), in favour of the intervention (i.e. in a positive direction). The Journeying through Dementia intervention cost £608 more than usual care (95% confidence interval £105 to £1179) and had negligible difference in quality-adjusted life-years (–0.003, 95% confidence interval –0.044 to 0.038). Therefore, the Journeying through Dementia intervention had a mean incremental cost per quality-adjusted life-year of –£202,857 (95% confidence interval –£534,733 to £483,739); however, there is considerable uncertainty around this. Assessed fidelity was good. Interviewed participants described receiving some benefit and a minority benefited greatly. However, negative aspects were also raised by a minority. Seventeen per cent of participants in the intervention arm and 15% of participants in the control arm experienced at least one serious adverse event. None of the serious adverse events were classified as related to the intervention. Limitations Study limitations include recruitment of an active population, delivery challenges and limitations of existing outcome measures. Conclusions The Journeying through Dementia programme is not clinically effective, is unlikely to be cost-effective and cannot be recommended in its existing format. Future work Research should focus on the creation of new outcome measures to assess well-being in dementia and on using elements of the intervention, such as enabling enactment in the community. Trial registration This trial is registered as ISRCTN17993825

The limitations of in vitro experimentation in understanding biofilms and chronic infection

We have become increasingly aware that during infection, pathogenic bacteria often grow in multi- cellular biofilms which are often highly resistant to antibacterial strategies. In order to understand how biofilms form and contribute to infection, in vitro biofilm systems such as microtitre plate as- says and flow cells, have been heavily used by many research groups around the world. Whilst these methods have greatly increased our understanding of the biology of biofilms, it is becoming increasingly apparent that many of our in vitro methods do not accurately represent in vivo conditions. Here we present a systematic review of the most widely used in vitro biofilm systems, and we discuss why they are not always representative of the in vivo biofilms found in chronic infections. We present examples of methods that will help us to bridge the gap between in vitro and in vivo biofilm work, so that our bench-side data can ultimately be used to improve bedside treatment

Psychology and aggression

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68264/2/10.1177_002200275900300301.pd

Analysis of shared heritability in common disorders of the brain

Paroxysmal Cerebral Disorder

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens