Lifestyle interventions for type 2 diabetes management among migrants and ethnic minorities living in industrialized countries : a systematic review and meta-analyses

The objective of this systematic review was to determine the effectiveness of lifestyle interventions to improve the management of type 2 diabetes mellitus (T2DM) among migrants and ethnic minorities. Major searched databases included MEDLINE (via PubMed), EMBASE (via Ovid) and CINAHL. The selection of studies and data extraction followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. In the meta-analysis, significant heterogeneity was detected among the studies (I 2 >50%), and hence a random effects model was used. Subgroup analyses were performed to compare the effect of lifestyle interventions according to intervention approaches (peer-led vs community health workers (CHWs)-led). A total of 17 studies were included in this review which used interventions delivered by CHWs or peer supporters or combination of both. The majority of the studies assessed effectiveness of key primary (hemoglobin (HbA1c), lipids, fasting plasma glucose) and secondary outcomes (weight, body mass index, blood pressure, physical activity, alcohol consumption, tobacco smoking, food habits and healthcare utilization). Meta-analyses showed lifestyle interventions were associated with a small but statistically significant reduction in HbA1c level (-0.18%; 95% CI-0.32% to-0.04%, p=0.031). In subgroup analyses, the peer-led interventions showed relatively better HbA1c improvement than CHW-led interventions, but the difference was not statistically significant (p=0.379). Seven studies presented intervention costs, which ranged from US$131 to US$461 per participant per year. We conclude that lifestyle interventions using either CHWs or peer supporters or a combination of both have shown modest effectiveness for T2DM management among migrants of different background and origin and ethnic minorities. The evidence base is promising in terms of developing culturally appropriate, clinically sound and cost-effective intervention approaches to respond to the growing and diverse migrants and ethnic minorities affected by diabetes worldwide

Non-native contrasts in Tongan loans

We present three case studies of marginal contrasts in Tongan loans from English, working with data from three speakers. Although Tongan lacks contrasts in stress or in CC vs. CVC sequences, secondary stress in loans is contrastive, and is sensitive to whether a vowel has a correspondent in the English source word; vowel deletion is also sensitive to whether a vowel is epenthetic as compared to the English source; and final vowel length is sensitive to whether the penultimate vowel is epenthetic, and if not, whether it corresponds to a stressed or unstressed vowel in the English source. We provide an analysis in the multilevel model of Boersma (1998) and Boersma & Hamann (2009), and show that the loan patterns can be captured using only constraints that plausibly are needed for native-word phonology, including constraints that reflect perceptual strategies

Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models.

BACKGROUND: Stillbirth prevention is an international priority - risk prediction models could individualise care and reduce unnecessary intervention, but their use requires evaluation. OBJECTIVES: To identify risk prediction models for stillbirth, and assess their potential accuracy and clinical benefit in practice. SEARCH STRATEGY: MEDLINE, Embase, DH-DATA and AMED databases were searched from inception to June 2019 using terms relevant to stillbirth, perinatal mortality and prediction models. The search was compliant with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. SELECTION CRITERIA: Studies developing and/or validating prediction models for risk of stillbirth developed for application during pregnancy. DATA COLLECTION AND ANALYSIS: Study screening and data extraction were conducted in duplicate, using the CHARMS checklist. Risk of bias was appraised using the PROBAST tool. RESULTS: The search identified 2751 citations. Fourteen studies reporting development of 69 models were included. Variables consistently included were: ethnicity, body mass index, uterine artery Doppler, pregnancy-associated plasma protein and placental growth factor. For almost all models there were significant concerns about risk of bias. Apparent model performance (i.e. in the development dataset) was highest in models developed for use later in pregnancy and including maternal characteristics, and ultrasound and biochemical variables, but few were internally validated and none were externally validated. CONCLUSIONS: Almost all models identified were at high risk of bias. There are first-trimester models of possible clinical benefit in early risk stratification; these require validation and clinical evaluation. There were few later pregnancy models but, if validated, these could be most relevant to individualised discussions around timing of birth. TWEETABLE ABSTRACT: Prediction models using maternal factors, blood tests and ultrasound could individualise stillbirth prevention, but existing models are at high risk of bias.The authors are collaborators in the IPPIC (International Prediction of Pregnancy Complications) stillbirth project, funded by Sands (the Stillbirth and Neonatal Death Society)

Influence of landscape characteristics on retention of expandable radiocollars on young ungulates

One tool used for wildlife management is the deployment of radiocollars to gain knowledge of animal populations. Understanding the influence of individual factors (e.g., species, collar characteristics) and landscape characteristics (e.g., forested cover, shrubs, and fencing) on retention of expandable radiocollars for ungulates is important for obtaining empirical data on factors influencing ecology of young-of-the-year ungulates. During 2001–2009, we captured and radiocollared 198 white-tailed deer (Odocoileus virginianus) fawns, 142 pronghorn (Antilocapra americana) fawns, and 73 mule deer (O. hemionus) fawns in South Dakota, Minnesota, and California, USA. We documented 72 (36.4%), 8 (5.6%), and 7 (9.6%) premature (\u3c270 days post-capture) collar losses among white-tailed deer, pronghorn, and mule deer, respectively. Probability of a collar being retained for 270 days was 0.36 (SE = 0.05, 95% CI = 0.27–0.47), 0.91 (SE = 0.03, 95% CI = 0.82–0.96), and 0.87 (SE = 0.05, 95% CI = 0.73–0.94) for white-tailed deer, pronghorn, and mule deer fawns, respectively. Agricultural fencing, which varied among study areas and thus species, seemed to influence collar retention; fencing density was 69% lower in areas where fawns retained collars ( = 1.00 km/km2, SE = 0.1, n = 75) compared with areas where fawns shed collars ( = 3.24 km/km2, SE = 0.1, n = 56) prior to 270 days. Researchers of fawns should consider that radiocollars can be shed prematurely when estimating desired sample size to yield a suitable strength of inference about some natural process of interest

Spatial Ecology of White-Tailed Deer Fawns in the Northern Great Plains: Implications of Loss of Conservation Reserve Program Grasslands

Few studies have evaluated how wildlife, and white-tailed deer (Odocoileus virginianus) in particular, respond to Conservation Reserve Program (CRP) grasslands. We conducted a 3-year study (2007– 2009) to determine the influence of CRP on fawn ecology during a time of declining CRP enrollment. We captured and radiocollared 81 fawn white-tailed deer during 15 May to 15 June 2007–2009 in north-central South Dakota, collected 6,505 locations, and documented 70 summer home ranges. Mean summer home ranges increased temporally during 2007–2009 (P \u3c 0.001) and corresponded to a 41% loss of CRP grasslands in the area (2.3% loss in land cover and approx. 21% loss in cover habitat in the study area) over the duration of the study. Additionally, mean movement between daily locations increased (P \u3c 0.001) from 2007 to 2009. Analysis of covariance models indicated that change in CRP influenced home-range size, and change in CRP and wheat influenced daily movement. Smaller home ranges and reduced movements were associated with greater quantity of CRP available to fawns, and increased movements were associated with more acreage of wheat available to fawns. Fawns shifted resource selection during the summer at a mean age ranging from 48.8 days to 58.6 days, and this shift was associated with height of corn (83–87 cm). During early summer, fawns consistently selected for CRP; selection of wheat progressed temporally from avoidance in 2007 to selection in 2009. During late summer, fawns consistently selected for corn habitat and used CRP at least in proportion to its availability. Reduction in CRP-grasslands seemed to increase fawn home-range size and daily movements and, influenced change in resource selection to wheat. Current legislation mandates continued decrease in CRP enrollment and concomitant increase in the planting of corn for ethanol production. Management of habitat throughout the grasslands of the Northern Great Plains that maximizes cover habitats would provide neonates with adequate cover for protection from predators

Females know better : Sex-biased habitat selection by the European wildcat

Altres ajuts: FCT/UID/BIA/50027/2013Altres ajuts: POCI/01-0145-FEDER-006821The interactions between animals and their environment vary across species, regions, but also with gender. Sex-specific relations between individuals and the ecosystem may entail different behavioral choices and be expressed through different patterns of habitat use. Regardless, only rarely sex-specific traits are addressed in ecological modeling approaches. The European wildcat (Felis silvestris silvestris) is a species of conservation concern in Europe, with a highly fragmented and declining distribution across most of its range. We assessed sex-specific habitat selection patterns for the European wildcat, at the landscape and home range levels, across its Iberian biogeographic distribution using a multipopulation approach. We developed resource selection functions in a use-availability framework using radio-telemetry data from five wildcat populations. At the landscape level, we observed that, while both genders preferentially established home ranges in areas close to broadleaf forests and far from humanized areas, females selected mid-range elevation areas with some topographic complexity, whereas males used lowland areas. At the home range level, both females and males selected areas dominated by scrublands or broadleaf forests, but habitat features were less important at this level. The strength of association to habitat features was higher for females at both spatial levels, suggesting a tendency to select habitats with higher quality that can grant them enhanced access to shelter and feeding resources. Based on our results, we hypothesize that sex-biased behavioral patterns may contribute to the resilience of wildcats' genetic integrity through influencing the directionality of hybridization with domestic cats. Our study provides information about European wildcats' habitat use in an Iberian context, relevant for the implementation of conservation plans, and highlights the ecological relevance of considering sex-related differences in environmental preferences

Predicting the risk of acute kidney injury in primary care: derivation and validation of STRATIFY-AKI

Background: Antihypertensives reduce the risk of cardiovascular disease but are also associated with harms including acute kidney injury (AKI). Few data exist to guide clinical decision making regarding these risks. Aim: To develop a prediction model estimating the risk of AKI in people potentially indicated for antihypertensive treatment. Design and setting: Observational cohort study using routine primary care data from the Clinical Practice Research Datalink (CPRD) in England. Method: People aged ≥40 years, with at least one blood pressure measurement between 130 mmHg and 179 mmHg were included. Outcomes were admission to hospital or death with AKI within 1, 5, and 10 years. The model was derived with data from CPRD GOLD (n = 1 772 618), using a Fine–Gray competing risks approach, with subsequent recalibration using pseudo-values. External validation used data from CPRD Aurum (n = 3 805 322). Results: The mean age of participants was 59.4 years and 52% were female. The final model consisted of 27 predictors and showed good discrimination at 1, 5, and 10 years (C-statistic for 10-year risk 0.821, 95% confidence interval [CI] = 0.818 to 0.823). There was some overprediction at the highest predicted probabilities (ratio of observed to expected event probability for 10-year risk 0.633, 95% CI = 0.621 to 0.645), affecting patients with the highest risk. Most patients (>95%) had a low 1- to 5-year risk of AKI, and at 10 years only 0.1% of the population had a high AKI and low CVD risk. Conclusion: This clinical prediction model enables GPs to accurately identify patients at high risk of AKI, which will aid treatment decisions. As the vast majority of patients were at low risk, such a model may provide useful reassurance that most antihypertensive treatment is safe and appropriate while flagging the few for whom this is not the case

Habitat use at fine spatial scale: how does patch clustering criteria explain the use of meadows by red deer ?

Large mammalian herbivores are keystone species in different ecosystems. To mediate the effects of large mammalian herbivores on ecosystems, it is crucial to understand their habitat selection pattern. At finer scales, herbivore patch selection depends strongly on plant community traits and therefore its understanding is constrained by patch definition criteria. Our aim was to assess which criteria for patch definition best explained use of meadows by wild, free-ranging, red deer (Cervus elaphus) in a study area in Northeast Portugal. We used two clustering criteria types based on floristic composition and gross forage classes, respectively. For the floristic criteria, phytosociological approach was used to classify plant communities, and its objectivity evaluated with a mathematical clustering of the floristic relevés. Cover of dominant plant species was tested as a proxy for the phytosociological method. For the gross forage classes, the graminoids/forbs ratio and the percentage cover of legumes were used. For assessing deer relative use of meadows we used faecal accumulation rates. Patches clustered according to floristic classification better explained selection of patches by deer. Plant community classifications based on phytosociology, or proxies of this, used for characterizing meadow patches resulted useful to understand herbivore selection pattern at fine scales and thus potentially suitable to assist wildlife management decisions

Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study

Objective To develop and externally validate the STRAtifying Treatments In the multi-morbid Frail elderlY (STRATIFY)-Falls clinical prediction model to identify the risk of hospital admission or death from a fall in patients with an indication for antihypertensive treatment. Design Retrospective cohort study. Setting Primary care data from electronic health records contained within the UK Clinical Practice Research Datalink (CPRD). Participants Patients aged 40 years or older with at least one blood pressure measurement between 130 mm Hg and 179 mm Hg. Main outcome measure First serious fall, defined as hospital admission or death with a primary diagnosis of a fall within 10 years of the index date (12 months after cohort entry). Model development was conducted using a Fine-Gray approach in data from CPRD GOLD, accounting for the competing risk of death from other causes, with subsequent recalibration at one, five, and 10 years using pseudo values. External validation was conducted using data from CPRD Aurum, with performance assessed through calibration curves and the observed to expected ratio, C statistic, and D statistic, pooled across general practices, and clinical utility using decision curve analysis at thresholds around 10%. Results Analysis included 1 772 600 patients (experiencing 62 691 serious falls) from CPRD GOLD used in model development, and 3 805 366 (experiencing 206 956 serious falls) from CPRD Aurum in the external validation. The final model consisted of 24 predictors, including age, sex, ethnicity, alcohol consumption, living in an area of high social deprivation, a history of falls, multiple sclerosis, and prescriptions of antihypertensives, antidepressants, hypnotics, and anxiolytics. Upon external validation, the recalibrated model showed good discrimination, with pooled C statistics of 0.833 (95% confidence interval 0.831 to 0.835) and 0.843 (0.841 to 0.844) at five and 10 years, respectively. Original model calibration was poor on visual inspection and although this was improved with recalibration, under-prediction of risk remained (observed to expected ratio at 10 years 1.839, 95% confidence interval 1.811 to 1.865). Nevertheless, decision curve analysis suggests potential clinical utility, with net benefit larger than other strategies. Conclusions This prediction model uses commonly recorded clinical characteristics and distinguishes well between patients at high and low risk of falls in the next 1-10 years. Although miscalibration was evident on external validation, the model still had potential clinical utility around risk thresholds of 10% and so could be useful in routine clinical practice to help identify those at high risk of falls who might benefit from closer monitoring or early intervention to prevent future falls. Further studies are needed to explore the appropriate thresholds that maximise the model’s clinical utility and cost effectiveness