Identification of the factors associated with outcomes in a condition management programme

<p>Background: A requirement of the Government’s Pathways to Work (PtW) agenda was to introduce a Condition Management Programme (CMP). The aim of the present study was to identify the differences between those who engaged and made progress in this telephone-based biopsychosocial intervention, in terms of their health, and those who did not and to determine the client and practitioner characteristics and programme elements associated with success in a programme aimed at improving health.</p> <p>Methods: Data were obtained from the CMP electronic spreadsheets and clients paper-based case records. CMP standard practice was that questionnaires were administered during the pre- and post-assessment phases over the telephone. Each client’s record contains their socio-demographic data, their primary health condition, as well as the pre- and post-intervention scores of the health assessment tool administered. Univariate and multivariate statistical analysis was used to investigate the relationships between the database variables. Clients were included in the study if their records were available for analysis from July 2006 to December 2007.</p> <p> Results: On average there were 112 referrals per month, totalling 2016 referrals during the evaluation period. The majority (62.8%) of clients had a mental-health condition. Successful completion of the programme was 28.5% (575 “completers”; 144 “discharges”). Several factors, such as age, health condition, mode of contact, and practitioner characteristics, were significant determinants of participation and completion of the programme. The results showed that completion of the CMP was associated with a better mental-health status, by reducing the number of clients that were either anxious, depressed or both, before undertaking the programme, from 74% to 32.5%.</p> <p>Conclusions: Our findings showed that an individual's characteristics are associated with success in the programme, defined as completing the intervention and demonstrating an improved health status. This study provides some evidence that the systematic evaluation of such programmes and interventions could identify ways in which they could be improved.</p&gt

Effects of increased body mass index on employment status:a Mendelian randomisation study

Background: The obesity epidemic may have substantial implications for the global workforce, including causal effects on employment, but clear evidence is lacking. Obesity may prevent people from being in paid work through poor health or through social discrimination. We studied genetic variants robustly associated with body mass index (BMI) to investigate its causal effects on employment. Dataset/methods: White UK ethnicity participants of working age (men 40–64 years, women 40–59 years), with suitable genetic data were selected in the UK Biobank study (N = 230,791). Employment status was categorised in two ways: first, contrasting being in paid employment with any other status; and second, contrasting being in paid employment with sickness/disability, unemployment, early retirement and caring for home/family. Socioeconomic indicators also investigated were hours worked, household income, educational attainment and Townsend deprivation index (TDI). We conducted observational and two-sample Mendelian randomisation (MR) analyses to investigate the effect of increased BMI on employment-related outcomes. Results: Regressions showed BMI associated with all the employment-related outcomes investigated. MR analyses provided evidence for higher BMI causing increased risk of sickness/disability (OR 1.08, 95% CI 1.04, 1.11, per 1 Kg/m2 BMI increase) and decreased caring for home/family (OR 0.96, 95% CI 0.93, 0.99), higher TDI (Beta 0.038, 95% CI 0.018, 0.059), and lower household income (OR 0.98, 95% CI 0.96, 0.99). In contrast, MR provided evidence for no causal effect of BMI on unemployment, early retirement, non-employment, hours worked or educational attainment. There was little evidence for causal effects differing by sex or age. Robustness tests yielded consistent results. Discussion: BMI appears to exert a causal effect on employment status, largely by affecting an individual’s health rather than through increased unemployment arising from social discrimination. The obesity epidemic may be contributing to increased worklessness and therefore could impose a substantial societal burden

Prospective Environmental Life Cycle Assessment of Nanosilver T-Shirts

A cradle-to-grave life cycle assessment (LCA) is performed to compare nanosilver T-shirts with conventional T-shirts with and without biocidal treatment. For nanosilver production and textile incorporation, we investigate two processes: flame spray pyrolysis (FSP) and plasma polymerization with silver co-sputtering (PlaSpu). Prospective environmental impacts due to increased nanosilver T-shirt commercialization are estimated with six scenarios. Results show significant differences in environmental burdens between nanoparticle production technologies: The "cradle-to-gate" climate footprint of the production of a nanosilver T-shirt is 2.70 kg of CO2-equiv (FSP) and 7.67-166 kg of CO2-equiv (PlaSpu, varying maturity stages). Production of conventional T-shirts with and without the biocide triclosan has emissions of 2.55 kg of CO2-equiv (contribution from triclosan insignificant). Consumer behavior considerably affects the environmental impacts during the use phase. Lower washing frequencies can compensate for the increased climate footprint of FSP nanosilver T-shirt production. The toxic releases from washing and disposal in the life cycle of T-shirts appear to be of minor relevance. By contrast, the production phase may be rather significant due to toxic silver emissions at the mining site if high silver quantities are require

Are ethnic inequalities in COVID-19 outcomes mediated by occupation risk? Analyses of a 2-year record linked national cohort study in Scotland

This study investigated the extent to which ethnic inequalities in severe COVID-19 (i.e. hospitalization or deaths) are mediated through occupational risk differences. We used a population-based cohort study linking the 2011 Scottish Census to health records. We included all individuals aged 30-64 years and living in Scotland on 1 March 2020. The study period was from 1 March 2020 to 17 April 2022. Self-reported ethnicity was taken from the Census. We derived occupational risk of SARS-COV-2 infection using the 3-digit Standard Occupational Classification (SOC2010). We estimated hazard ratios (HRs) of total effects and controlled direct effects of ethnicity on severe COVID-19 mediated by occupational risk using marginal structural Cox models and subsequent proportional change. For aggregated ethnic groups, Non-White groups experienced a higher risk of severe COVID-19 (HR 1.6; 95% CI 1.4-1.8) compared to White group (all White ethnic groups) which increased to (1.7; 1.4-2.1) after accounting for occupational risk, representing a 6.0% change. For disaggregated ethnic groups, risks for South Asian (2.0; 1.8-2.3), African, Caribbean, or Black (1.3; 0.9-1.7) and Other ethnic groups (1.1; 0.9-1.3) were higher compared to White Scottish. After accounting for occupational risk, estimated risk of severe COVID-19 remained elevated for South Asian (1.8; 1.2-2.3), African Caribbean or Black (1.4; 0.8-2.1) and Other ethnic group (1.7; 1.1-2.3) representing a reduction of 11.8% and increases of 16.4% and 59.0%, respectively. Our findings suggest that ethnic inequalities in severe COVID-19 were impacted by differences in occupational risk

A New Method to Address Unmet Needs for Extracting Individual Cell Migration Features from a Large Number of Cells Embedded in 3D Volumes

Background: In vitro cell observation has been widely used by biologists and pharmacologists for screening molecule-induced effects on cancer cells. Computer-assisted time-lapse microscopy enables automated live cell imaging in vitro, enabling cell behavior characterization through image analysis, in particular regarding cell migration. In this context, 3D cell assays in transparent matrix gels have been developed to provide more realistic in vitro 3D environments for monitoring cell migration (fundamentally different from cell motility behavior observed in 2D), which is related to the spread of cancer and metastases. Methodology/Principal Findings: In this paper we propose an improved automated tracking method that is designed to robustly and individually follow a large number of unlabeled cells observed under phase-contrast microscopy in 3D gels. The method automatically detects and tracks individual cells across a sequence of acquired volumes, using a template matching filtering method that in turn allows for robust detection and mean-shift tracking. The robustness of the method results from detecting and managing the cases where two cell (mean-shift) trackers converge to the same point. The resulting trajectories quantify cell migration through statistical analysis of 3D trajectory descriptors. We manually validated the method and observed efficient cell detection and a low tracking error rate (6%). We also applied the method in a real biological experiment where the pro-migratory effects of hyaluronic acid (HA) were analyzed on brain cancer cells. Using collagen gels with increased HA proportions, we were able to evidence a dose-response effect on cell migration abilities. Conclusions/Significance: The developed method enables biomedical researchers to automatically and robustly quantify the pro- or anti-migratory effects of different experimental conditions on unlabeled cell cultures in a 3D environment. © 2011 Adanja et al.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Effect modification and interaction between ethnicity and socioeconomic factors in severe COVID-19: analyses of linked national data for Scotland

Objective Minority ethnic groups disproportionately experienced adverse COVID-19 outcomes, partly a consequence of disproportionate exposure to socioeconomic disadvantage and high-risk occupations. We examined whether minority ethnic groups were also disproportionately vulnerable to the consequences of socioeconomic disadvantage and high-risk occupations in Scotland. Design We investigated effect modification and interaction between area deprivation, education and occupational risk and ethnicity (assessed as both a binary white vs non-white variable and a multi-category variable) in relation to severe COVID-19 (hospitalisation or death). We used electronic health records linked to the 2011 census and Cox proportional hazards models, adjusting for age, sex and health board. We were principally concerned with additive interactions as a measure of vulnerability, estimated as the relative excess risk due to interaction (RERI). Results Analyses considered 3 730 837 individuals aged ≥16 years (with narrower age ranges for analyses focused on education and occupation). Severe COVID-19 risk was typically higher for minority ethnic groups and disadvantaged socioeconomic groups, but additive interactions were not consistent. For example, non-white ethnicity and highest deprivation level experienced elevated risk ((HR=2.7, 95% CI: 2.4, 3.2) compared with the white least deprived group. Additive interaction was not present (RERI=-0.1, 95% CI: -0.4, 0.2), this risk being less than the sum of risks of white ethnicity/highest deprivation level (HR=2.4, 95% CI: 2.3, 2.5) and non-white ethnicity/lowest deprivation level (1.4, 95% CI: 1.2, 1.7). Similarly, non-white ethnicity/no degree education (HR=2.5, 95% CI: 2.2, 2.7; RERI=-0.1, 95% CI: -0.4, 0.2) and non-white ethnicity/high-risk occupation (RERI=0.3, 95% CI: -0.2, 0.8) did not experience greater than additive risk. No clear evidence of effect modification was identified when using the multicategory ethnicity variable or on the multiplicative scale either. Conclusion We found no definitive evidence that minority ethnic groups were more vulnerable to the effect of social disadvantage on the risk of severe COVID-19

Investigating the contribution of socio-economic position to ethnic inequalities in severe COVID-19 outcomes: population-based mediation analyses of national linked Scottish data

We quantified the extent to which socio-economic position (SEP) contributed to ethnic inequalities in severe COVID-19 outcomes (hospitalization or death) in Scotland. We used linked 2011 Scottish Census and health records to assess whether ethnic inequalities were mediated by different SEP measures: area deprivation, educational status, household composition, and multigenerational household. We considered disaggregated ethnicities 'White Scottish', 'White British or Irish', 'Other White', 'South Asian', 'African, Caribbean, or Black', and 'Other'. We applied marginal structural models to estimate causal pathways. Of the 3 297 205 individuals analysed, 38 213 (1.2%) had severe COVID-19 outcomes. South Asians had elevated risk of severe COVID-19 compared to White Scottish (hazard ratio: 1.7; 95% confidence interval: 1.5-1.9), while White British or Irish (hazard ratio: 0.7; confidence interval: 0.6-08) and other White (hazard ratio: 0.8; confidence interval: 0.7-0.9) had reduced risk. When holding area deprivation constant, the risk of severe COVID-19 declined by 16.5% for South Asians and 49.2% for White British or Irish; but increased for other White (75.4%). When holding education constant, the risk of severe COVID-19 reduced by 24.8% for White British or Irish and 20.6% for other White; but increased by 74.6% for South Asians. Only a slight change in risk was observed for the South Asians after holding household size and multigenerational household constant. Risk estimates for African, Caribbean or Black, and other groups were underpowered. SEP measures differed substantially in the extent to which they mediated ethnic inequalities in severe COVID-19. This highlights the necessity of addressing multiple dimensions of SEP that drive ethnic inequalities

Evaluation of a national smoke-free prisons policy using medication dispensing: an interrupted time-series analysis

Background Internationally, smoking prevalence among people in prison custody (ie, people on remand awaiting trial, awaiting sentencing, or serving a custodial sentence) is high. In Scotland, all prisons implemented a comprehensive smoke-free policy in 2018 after a 16-month anticipatory period. In this study, we aimed to use data on medication dispensing to assess the impact of this policy on cessation support, health outcomes, and potential unintended consequences among people in prison custody. Methods We did an interrupted time-series analysis using dispensing data for 44 660 individuals incarcerated in 14 closed prisons in Scotland between March 30, 2014, and Nov 30, 2019. We estimated changes in dispensing rates associated with the policy announcement (July 17, 2017) and full implementation (Nov 30, 2018) using seasonal autoregressive integrated moving average models. Medication categories of primary interest were treatments for nicotine dependence (as an indicator of smoking cessation or abstinence attempts), acute smoking-associated illnesses, and mental health (antidepressants). We included antiepileptic medications as a negative control. Findings A 44% step increase in dispensing of treatments for nicotine dependence was observed at implementation (2250 items per 1000 people in custody per fortnight, 95% CI 1875 to 2624) due primarily to a 42% increase in dispensing of nicotine replacement therapy (2109 items per 1000 people in custody per fortnight, 1701 to 2516). A 9% step decrease in dispensing for smoking-related illnesses was observed at implementation, largely accounted for by respiratory medications (−646 items per 1000 people in custody per fortnight, −1111 to −181). No changes associated with announcement or implementation were observed for mental health dispensing or antiepileptic medications (control). Interpretation Smoke-free prison policies might improve respiratory health among people in custody and encourage smoking abstinence or cessation without apparent short-term adverse effects on mental health dispensing