Are the Mascarene frog (Ptychadena mascareniensis) and Brahminy blind snake (Indotyphlops braminus) really alien species in the Seychelles?

This is an accepted manuscript of an article published by the British Herpetological Society in the Herpetological Bulletin on 30/09/2020. The accepted version of the publication may differ from the final published version

Collaborative Research between Aston Research Centre for Healthy Ageing (ARCHA) and the ExtraCare Charitable Trust

Executive Summary A Longitudinal evaluation of the ExtraCare Approach 1.0 Introduction This report consists of a summary of the full findings. Throughout the report the emphasis is on key learning points: what are the implications of the findings and what could be further developed? ExtraCare management have contributed with a brief summary of their responses or plans to emphasise the collaborative nature of this project, to be found in Section 13.0 of the document. Original objectives: We set out with the overall objective of evaluating whether the ExtraCare approach gives positive outcomes for healthy ageing which result in measurable health and social care cost savings. In a longitudinal study, 162 new residents are compared against 39 control participants. We took measures of health, well-being, cognitive ability and mobility at entry, 3, 12 and 18 months. Qualitative data were gathered using focus groups, interviews and case studies. People were additionally invited to keep a diary to record activities. Outcomes also include health and social care usage and costs to contribute to answering the original question. ExtraCare villages and schemes taking part: Fourteen Villages and Schemes took part in the project. 2.0 Numbers of people taking part Initial targets for recruitment of 160 new residents and 25 control participants were slightly exceeded (162 and 33 respectively), although ExtraCare well-being data at baseline was only available for 151 of these. Over the centres used, 17% of new residents took part. By 18 months there were 108 ExtraCare and 29 control participants in the study for the Aston assessments (69 and 29 respectively for well-being data. The attrition is indicated by the difference between initial and final Aston assessments, whereas the difficulties in getting complete well-being (health) data are illustrated by the difference between the final Aston and final well-being data (108-69 = 39 missing well-being assessments). For the crucial 12 month health data (NHS or Care use are measured over 12 months) there are 96 ExtraCare residents (as against 127 residents in the Aston assessments, that is, 31 missing due to missing well-being assessments). There are 666 Aston assessments and 530 well-being assessments across the four time points. For qualitative data we conducted two or three focus groups at eight sites (total of 74 participants). We individually interviewed six residents within 2-5 months of moving into ExtraCare, then at 6 and 18 months after moving in. This was the only longitudinal component of the qualitative work. Three Case studies were conducted which included interviews and observation within the ExtraCare site. We interviewed two managers formally and when on site met with managers and staff groups to discuss general issues. Attrition: 40% of ExtraCare and 29% of Control participants left the study before completion. With our longitudinal design feature of periodically adding in new volunteers with matched duration of residence, this resulted in overall attrition of 29% (33.3% for residents, 6% for controls), comparing favourably with other similar studies. 33% attrition was anticipated in calculations of sample size. Attrition was selective to participants who were less well. Twelve ExtraCare volunteers died during the period (7.4%) and 14 stated their own or partner’s illness as a reason for not continuing. One qualitative interview volunteer died between the second and third meeting. Those lost to sample were no older than those still available at 18 months. Data summary and challenges: There were some challenges with the ExtraCare Well-being Advisors’ data entry throughout the study which did eventually result in some loss of data, resulting in a mismatch between numbers with full Aston data and those with full well-being data, despite our best efforts and those of the Well-being Advisors. One of the most significant issues was gaps and changes in well-being staffing. Additional financial resources were authorised by ExtraCare to ensure that some of the missing assessments could be carried out where there was a longer term staffing vacancy. Nevertheless, there are still sufficient numbers for most of the analyses planned. ExtraCare was already planning a new centrally stored and more user-friendly data base, so any future data will be easier to use for all concerned. Further description of initial sample: ExtraCare participants were significantly older than controls on average, had more chronic illnesses and differed in terms of socio-economic groupings such that there were fewer professional and higher management and more people with unskilled occupational backgrounds. Control group participants perceived their health to be significantly better than did ExtraCare participants at baseline, and had fewer care needs or functional limitations. Cognitive function and emotional well-being differed between the groups at baseline, even controlling for age differences. There were proportionately more men in the ExtraCare sample than in the Control sample (38.3% as compared with 25.8%). 3.0 Summary from the Diary data 57 ExtraCare and 22 control participants agreed at baseline to keep a diary of their activities over the period, down to 35 and 12 respectively by 18 months. Number of activities was categorised broadly into social, physical and intellectual activity types. There was significant increase in activities over the first 3 months in all categories, but then a levelling off or decrease. For the full duration, only social activity increase remained significant. Given our understanding of the benefits of physical, intellectual and social engagement, these findings indicate a need for continued efforts to involve people, support them to get involved, and listen to what they would like in terms of activities. At baseline, there were five people who reported no activities of any nature but there were none at any subsequent time period. 4.0 Summary from the Qualitative data The aim of the qualitative arm of this study was to try to understand residents’ perspectives and experiences of daily life in ExtraCare. We approached the data with openness and regarded participants as experts of their own experience. It is important to emphasise that whether residents’ accounts of life in ExtraCare are ‘true’ or not, they are real to them and can tell us important things about perceptions and feelings. As well as gaining accounts from residents we also met with managers and conducted observations when visiting each of the eight sites in our sample. Sample description: We aimed to gather data from a range of residents and staff. A total of 144 people (131 ExtraCare residents) took part in the qualitative components of the study. Of the 6 focus group resident participants, 83 were in villages and 48 in schemes. Of the six interview participants, three were in receipt of care or social support, one had private care, one was cared for by his wife, and one had no care. All reported at least one significant health concern. Overview of findings: The focus groups generated some rich data around how ExtraCare had changed over time but also whether initial expectations were maintained. We focus on three areas which have shown to be consistent areas of concern to residents of ExtraCare taking part in focus groups and interviews: 1. connectivity in and beyond ExtraCare; 2. perceptions of change in ExtraCare; 3. negotiating transitions and increasing needs. • Volunteering was experienced positively by some as a way of connecting to others in the ExtraCare community, or as a “new lease of life”; for some it was something they felt unable to do and therefore marginalised them from the ‘able’ residents. • Some residents retained connections from the wider community and were able to maintain friendships; others struggled to meet people and felt lonely within the ExtraCare community. • There was a feeling of change at ExtraCare among residents who had lived there a long time. Some of this was financial but other aspects were about a perceived culture shift in the organisation. • Residents’ sense of well-being may come from experiential activities, i.e. finding enjoyment in other people’s activities or through reading or watching television. • Domiciliary care provided can be experienced as a boost of independence to set one free to do activities one enjoys rather than worrying about the mundane activities of everyday life. • Some residents expressed reticence to seek care perhaps through guilt around their own sense of duty to care for a spouse or through embarrassment or pride. • Seeking care was perceived by some as letting go of one’s independence. Identity: There were less obvious subjective changes (or changes at the level of identity) in which residents sought to maintain inclusion in mainstream ExtraCare life and be seen as independent and self-sufficient, but were perhaps struggling to do so. This may not be consciously registered, but some perceptions of changes and decline in ExtraCare raised may relate to transitions in identity and subjectivity. However, in some locations during the period there were changes in provision of care due to Local Authority changing contracting arrangements. Some complaints may be well founded, of course, but there is also a need to listen to residents’ complaints (against ExtraCare management and against other residents) as markers of difficult transitions, requiring emotional support. 5.0 Changes across time in the key psychological and functional measures The most dramatic differences occurred in the early months after moving in, detailed in previous reports. Now there are data at four time points, we can use growth curve modelling to examine effects of time. The analyses employed a set of complex statistical controls for attrition, age differences and in some circumstances for ceiling effects (healthy people having no reported problems on some measures, e.g. Activities of Daily Living measures). As such, great care has been taken to ensure the reliability of findings. Effects over time which were different to control group changes (that is, ExtraCare effects): There were significant continuous improvements across the period in depression, perceived health, memory and autobiographical memory, in a way that was significantly different from the way the measure changed over time for the control group. Positive Effects over time which were not significantly different from control group changes: These are changes that we need to know about but which are not unique to ExtraCare residents. This was the case for: anxiety, communication limitations and fluency (executive function). Variables which varied with age in the control group but not for the residents: This was the case for: Instrumental Activities of Daily living (IADL) and Social Function limitations. ExtraCare may be reducing the normally expected change in function with increasing age. This is also a feature of the fact that decisions to move into ExtraCare are usually needs related, rather than age related. The two most important implications are that: • some factors can be changed: decline is not inevitable and improvement is possible even in variables that commonly decline with increasing age, given a supportive environment; • Age itself is less important than health in terms of determining need for support and potential decline 6.0 Well-being data Comparisons here are focussed on Baseline to 12 month data. Social care costs: 19% of the sample were in receipt of care at both time points. ExtraCare costs an average of £427.98 less per person per annum than comparative local authority charges. This difference is greater at higher levels of care, and varies according to local authority costs in each location. For the people who were in the sample at both time points, the difference reduced from £414.61 to £363.77. Savings for the more expensive levels of care increase over time. NHS Costs – Comparing EC and Control Participants: Total NHS costs were estimated for each participant, including practice and district nurse, GP and outpatient appointments as well as admissions. Average ExtraCare resident NHS costs reduced by 47% over 12 months. Control NHS costs reduced by 14.1%. BUT when you control for the fact that the more poorly are the people who left the sample this is a 38% reduction, (still a significant reduction). This equates to an average saving of £1114.94 per person per year. In using this figure to scale up for the whole population, it should be borne in mind that this is probably a maximum, e.g. we did not assess people who do not have capacity to consent, and we may surmise that many very poorly people do not take part at all. Costs for these people may not have shown reductions to the same extent. Health profile Medications, illnesses and lifestyle: ExtraCare participants took more prescribed medications than did controls and had a significantly greater number of chronic illnesses at baseline. However, this was related to the age difference in the samples, rather than any other difference between the groups. There were subtle differences in prevalence of specific co-morbidities, and the control group fared better throughout in terms of lifestyle factors (exercise, consumption of fruit and vegetables). Over the 18 month period, both groups showed improvements in blood pressure. There were reductions in BMI and Waist circumference between baseline and 18 months in ExtraCare residents while these remained unchanged in control group. There was a significant initial increase in number of prescribed medications for the ExtraCare group perhaps as well-being support resulted in new diagnoses, but this then remained stable. A reduction in polypharmacy was anticipated, given the use of medication review, but this did not clearly occur. There was no significant change in number of co-morbidities. Healthcare use: GP visits and ExtraCare drop-in clinics: After 12 months GP usage (planned) by ExtraCare residents in the sample had decreased by 46%. No such reduction was seen in 8 emergency appointment data. We investigated the hypothesis that this may be because residents use the well-being drop-in clinic as a substitute for booking routine GP appointments, given that well-being drop-in appointments steadily increased over the period. At baseline, number of dropins and number of planned GP visits was significantly positively correlated – the more a person visited their GP, the more they visited the drop-in clinic too. At 12 months, this relationship had gone completely. Drop-ins increased and GP visits reduced over time. Despite this, the relationship does not become negative which would have been definitive evidence that drop-ins are directly replacing GP visits. That is, it is not the case that the more a person visited the drop-in centre, the less they visited their GP. The change is not necessarily reflecting individual level changes, just in the group as a whole. Planned and unplanned hospital admissions and length of stay: The average number of planned admissions to hospital reduced for ExtraCare participants by 12 months by 31% (no change for control participants). The large variance and small effect size means that this was NOT a statistically reliable change. Number of unplanned admissions did not change for either group. Together, these findings support the Drop-in clinic model: (i) Availability of local, accessible, relatively informal health support, particularly for ongoing dayto-day chronic illness care, that does not need an appointment (a drop-in service), can have a significant effect on reducing GP usage, giving potential cost savings. (ii) Communities where homes are accessible, care support is readily available and existing care needs understood may result in reduced length of stays in hospital. Duration of unplanned hospital stays: This reduced from a median of 5-7 days at baseline, to 1-2 days thereafter. This was not related to increase in number of Drop-ins. 7.0 Frailty Frailty is defined as a state of high vulnerability for adverse health outcomes when exposed to a stressor, that is, an absence of resilience. Frailty is related to morbidity and mortality, and utilisation of healthcare. Crucially, frailty, and especially pre-frail states, are malleable. The Frailty Profile: We constructed a frailty measure for this population at each assessment to compare longitudinally, using a frailty profile concept (Rockwood et al, 2006). People were categorised into frail, pre-frail and not frail based on published criteria. ExtraCare residents were frailer than controls throughout. Initial improvements in frailty did not continue over the full period, although the initial improvements may have delayed decline. Nevertheless, a focus on interventions to prevent or reduce frailty could be further developed and evaluated using such an indicator. Frail Participants: Of the 44 residents categorised as frail at baseline, 22 remained in the sample 18 months later, 14 (63.6%) remained categorised as frail with 8 returning to a pre-frail or not frail state. One control participant was categorised as frail at baseline, returning to a not frail state by 18 months. Pre-frail residents: Given that the “pre-frail” is used to indicate people at risk of becoming frail, it is important to know if this occurred for ExtraCare residents. Of the 62 people designated as prefrail at Baseline, 42 were still in the sample at 18 months and 8 (19%) had returned to a not frail state, with 4.7% being designated as frail at 12 months. Ten control participants were categorised as pre-frail at Baseline. Of the 8 remaining at 18 months, all were still in the same category. Putting it together: Frailty and Costs. As indicated in Section 5, NHS costs in total reduced significantly. The reduction for the frail residents was the most striking: for those in the sample at 9 baseline and follow-up, this changed from an average of £3274.21to £1588.04 average per person. That is, a 51.5% drop. Use of this figure needs to bear in mind that the frailest within this group are those who have died or dropped out of the study. Reductions in social care costs over time were much smaller (£2-300 per person on average). Care costs for frail participants are much higher than for pre-frail participants. A frail participant’s average annual care costs were £4720.96 at the 12 month point, as compared to £61.40 for a prefrail resident (given that most pre-frail residents are on zero care). This underlines the importance of strategies to intervene in pre-frailty to reduce the likelihood of it becoming frail. Physical versus cognitive frailty: In order to determine the source of impacts more precisely, we produced a separate cognitive and physical frailty profile. The data showed that cognitive and physical frailty predict care level jumps from one level to the next differently, with cognitive frailty having a more even influence. The main predictor of higher levels was cognitive frailty (although modelling was not possible with the small numbers on care). 8.0 Modelling: What predicts change? Which measures are useful for predicting decline in independence outcomes? IADL: Change in ACE-R (overall cognitive function) and change in frailty: e.g. for every one point increase in ACE-R, it became less likely that IADL would decline. This did not differ by group. Functional Limitations Profile: Baseline age and increase in Depression: e.g. for every one point increase in depressive symptoms, people were 1.36 times more likely to have increases in functional limitations. A focus on rehabilitation and improvement of cognitive function and on treatment or prevention of depression will have important direct effects on independent function and quality of life, and therefore on need for further care and support. Which measures are particularly useful for predicting Care level? Care Level: Frailty, IADL and ADL (a more basic independence measure), and ability to stand up from a chair (time taken or inability). Given that IADL can be impacted by change in its underlying predictors, rehabilitative focus on these predictors would then have an impact on care needed. However, good linguistic ability was also an important predictor of Care Level. Once frailty, IADL and ADL, and sit-to-stand was taken into account, language had an opposite effect – people with higher language ability were more likely to have higher care levels, suggesting that those who could communicate well and understand information may be more likely to get the care they need. Poorer linguistic abilities seem to result in people being less likely to get care, even in the context of frailty. This has important implications for an advocacy role for frail people in helping them get the care they need. This issue reduces from Baseline onwards, validating ExtraCare’s support, but it does still have an effect. Which measures are particularly useful for predicting well-being outcomes? The main predictor of improvement in depression, perceived health and autobiographical memory in the total sample is which group a person is in, the ExtraCare residents or the control group, whereby living in ExtraCare predicts improvements in these wellbeing measures. Depression/mood improvement: change in cognitive function; change in anxiety e.g.an increase in anxiety of one point reduced the chance of mood improving (people were ¾ as likely to 10 improve on mood if their anxiety increased). Number of chronic illnesses was marginally significant (p<0.01) again reducing the chance of improvement in mood as numbers of illnesses increased and should also be borne in mind. Given that we generally an overall improvement in mood for ExtraCare

Genetic load and adaptive potential of a recovered avian species that narrowly avoided extinction

High genetic diversity is often a good predictor of long-term population viability, yet some species persevere despite having low genetic diversity. Here we study the genomic erosion of the Seychelles paradise flycatcher (Terpsiphone corvina), a species that narrowly avoided extinction after having declined to 28 individuals in the 1960s. The species recovered unassisted to over 250 individuals in the 1990s and was downlisted from Critically Endangered to Vulnerable in the IUCN Red List in 2020. By comparing historical, pre-bottleneck (130+ years old) and modern genomes, we uncovered a 10-fold loss of genetic diversity. The genome shows signs of historical inbreeding during the bottleneck in the 1960s, but low levels of recent inbreeding after the demographic recovery. We show that the proportion of severely deleterious mutations has reduced in modern individuals, but mildly deleterious mutations have remained unchanged. Computer simulations suggest that the Seychelles paradise flycatcher avoided extinction and recovered due to its long-term small Ne. This reduced the masked load and made the species more resilient to inbreeding. However, we also show that the chronically small Ne and the severe bottleneck resulted in very low genetic diversity in the modern population. Our simulations show this is likely to reduce the species’ adaptive potential when faced with environmental change, thereby compromising its long-term population viability. In light of rapid global rates of population decline, our work highlights the importance of considering genomic erosion and computer modelling in conservation assessment

DNA methylation and body mass index from birth to adolescence : meta-analyses of epigenome-wide association studies

Background DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits. Methods We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment. Results DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P <1.06 x 10(-7), with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth P-enrichment = 1; childhood P-enrichment = 2.00 x 10(-4); adolescence P-enrichment = 2.10 x 10(-7)). Conclusions There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.Peer reviewe

Genetic variants influencing biomarkers of nutrition are not associated with cognitive capability in middle-aged and older adults

Several investigations have observed positive associations between good nutritional status, as indicated by micronutrients, and cognitive measures; however, these associations may not be causal. Genetic polymorphisms that affect nutritional biomarkers may be useful for providing evidence for associations between micronutrients and cognitive measures. As part of the Healthy Ageing across the Life Course (HALCyon) program, men and women aged between 44 and 90 y from 6 UK cohorts were genotyped for polymorphisms associated with circulating concentrations of iron [rs4820268 transmembrane protease, serine 6 (TMPRSS6) and rs1800562 hemochromatosis (HFE)], vitamin B-12 [(rs492602 fucosyltransferase 2 (FUT2)], vitamin D ([rs2282679 group-specific component (GC)] and β-carotene ([rs6564851 beta-carotene 15,15'-monooxygenase 1 (BCMO1)]. Meta-analysis was used to pool within-study effects of the associations between these polymorphisms and the following measures of cognitive capability: word recall, phonemic fluency, semantic fluency, and search speed. Among the several statistical tests conducted, we found little evidence for associations. We found the minor allele of rs1800562 was associated with poorer word recall scores [pooled β on Z-score for carriers vs. noncarriers: -0.05 (95% CI: -0.09, -0.004); P = 0.03, n = 14,105] and poorer word recall scores for the vitamin D-raising allele of rs2282679 [pooled β per T allele: -0.03 (95% CI: -0.05, -0.003); P = 0.03, n = 16,527]. However, there was no evidence for other associations. Our findings provide little evidence to support associations between these genotypes and cognitive capability in older adults. Further investigations are required to elucidate whether the previous positive associations from observational studies between circulating measures of these micronutrients and cognitive performance are due to confounding and reverse causality

Biological Earth observation with animal sensors

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmen-tal change

Seabirds Abstracts

Click on the link to view the abstracts.Ostrich 2007, 78(2): 453–45

Norms of Knowledge: Navigating Epistemic Territory

Communicating with others is not as simple as broadcasting a message; that message must be calibrated to one’s audience. How exactly we are able to formulate an understanding of others’ minds is a quintessential question in philosophy, psychology, and cognitive science, among other fields, but it is a well-established fact that we are especially adept at doing so. Close observation of conversational interaction offers a window into at least some of the tools that enable us to navigate the knowledge states of others and tailor messages to suit particular recipients. This dissertation explores social and moral norms that govern management of relative authority over knowledge in conversational interaction.This dissertation draws on several sources of data, including a corpus of recorded unstructured conversation between close friends, recordings of the collaborative completion of an experimental task by strangers, and survey data from online participants making social judgments about written transcripts. This dissertation presents evidence, across four chapters, that participants in conversation orient to a normative expectation that what one actually knows (epistemic status) will be accurately reflected in how one talks about that knowledge in interaction (epistemic stance), both within an individual (don’t misrepresent your own knowledge) and between individuals (don’t treat others like they know more or less than they actually do). Violations of this norm are sanctionable offences and participants take measures to avoid making violations (Chapter 1), make off-record challenges when violations are suspected (Chapter 2), and admonish and harshly judge parties who have committed obvious violations (Chapters 3 and 4), behavior which both reflects and reinforces the norm