Oocyte pick up (OPU) coupled with IVP produce over 1 million cattle embryos per year and has been most successful in Bos indicus derived breeds that contain large numbers of antral follicles on their ...ovaries. More recently, this technology has been applied on a large scale to Bos taurus cattle, where hormone manipulation is generally employed to improve the developmental competence of the COCs. Hormone manipulation, and specifically the use of FSH priming before OPU, has been strategically used in the intensively managed dairy cow, where genomic evaluation and juvenile IVP can produce additional significant genetic gains.
•The number of oocytes collected at OPU is determined by the number of antral follicles on the ovary.•FSH priming improves the developmental competence of the oocyte in Bos taurus cattle.•FSH priming is necessary for juvenile in vitro embryo production programs.•FSH priming may not be required in Bos indicus in vitro embryo production programs.
Two-step floating catchment area (2SFCA) techniques are popular for measuring potential geographical accessibility to health care services. This paper proposes methodological enhancements to increase ...the sophistication of the 2SFCA methodology by incorporating both public and private transport modes using dedicated network datasets. The proposed model yields separate accessibility scores for each modal group at each demand point to better reflect the differential accessibility levels experienced by each cohort. An empirical study of primary health care facilities in South Wales, UK, is used to illustrate the approach. Outcomes suggest the bus-riding cohort of each census tract experience much lower accessibility levels than those estimated by an undifferentiated (car-only) model. Car drivers' accessibility may also be misrepresented in an undifferentiated model because they potentially profit from the lower demand placed upon service provision points by bus riders. The ability to specify independent catchment sizes for each cohort in the multi-modal model allows aspects of preparedness to travel to be investigated.
•A sophisticated multi-modal two-step floating catchment area model is described.•Public and private transport modes are modelled using dedicated networks.•Independent accessibility scores are generated for each travelling cohort.•Multi-modal accessibility scores vary substantially compared to single-mode scores.
Gypsies and Travellers have poorer physical and mental health than the general population, but little is known about mental health service use by Gypsy and Traveller children and young people. ...Finding this group in routine electronic health data is challenging, due to limited recording of ethnicity. We assessed the feasibility of using geographical markers combined with linked routine datasets to estimate the mental health service use of children and young people living on Traveller sites.
Welsh Government supplied a list of Traveller site postcodes included in Caravan Counts between 2012 and 2020. Using spatial filtering with data from the Adolescent Mental Health Data Platform (ADP) at Swansea University's SAIL Databank, we created a cohort of Traveller site residents aged 11-25 years old, 2010-2019. ADP algorithms were used to describe health service use, and to estimate incidence and prevalence of common mental disorders (CMD) and self-harm.
Our study found a subgroup of young Gypsies and Travellers (n = 802). We found no significant differences between our cohort and the general population for rates of CMD or self-harm. The rate of non-attendance for psychiatric outpatient follow-up appointments was significantly higher in our cohort. Rates were higher (but not statistically significant) among Gypsies and Travellers for measures suggesting less well-managed care, including emergency department attendance and prescribed CMD medication without follow-up. The small size of the cohort resulted in imprecise estimates with wide confidence intervals, compared with those for the general population.
Gypsies and Travellers are under-represented in routine health datasets, even using geographical markers, which find only those resident in authorised traveller sites. Routine data is increasingly relied upon for needs assessment and service planning, which has policy and practice implications for this underserved group. To address health inequalities effort is required to ensure that health datasets accurately capture ethnicity.
Built environments have been cited as important facilitators of activity and research using geographic information systems (GIS) has emerged as a novel approach in exploring environmental ...determinants. The Active Children Through Individual Vouchers Evaluation Project used GIS to conduct a cross-sectional analysis of how teenager's (aged 13-14) environments impacted on their amount of activity and influences fitness. The ACTIVE Project recruited 270 participants aged 13-14 (year 9) from 7 secondary schools in south Wales, UK. Demographic data and objective measures of accelerometery and fitness were collected from each participant between September and December 2016. Objective data was mapped in a GIS alongside datasets relating to activity provision, active travel routes, public transport stops, main roads and natural resources. This study shows that fitness and physical activity are not correlated. Teenagers who had higher levels of activity also had higher levels of sedentary time/inactivity. Teenagers showed higher amounts of moderate-to-vigorous physical activity if their homes were closer to public transport. However, they were also more active if their schools were further away from public transport and natural resources. Teenagers were fitter if schools were closer to natural resources. Sedentary behaviour, fitness and activity do not cluster in the same teenagers. Policymakers/planning committees need to consider this when designing teenage friendly environments. Access to public transport, active travel, green space and activities that teenagers want, and need could make a significant difference to teenage health.
Spatiotemporal modelling techniques allow one to predict injury across time and space. However, such methods have been underutilised in injury studies. This study demonstrates the use of statistical ...spatiotemporal modelling in identifying areas of significantly high injury risk, and areas witnessing significantly increasing risk over time.
We performed a retrospective review of hospitalised major trauma patients from the Victorian State Trauma Registry, Australia, between 2007 and 2019. Geographical locations of injury events were mapped to the 79 local government areas (LGAs) in the state. We employed Bayesian spatiotemporal models to quantify spatial and temporal patterns, and analysed the results across a range of geographical remoteness and socioeconomic levels.
There were 31,317 major trauma patients included. For major trauma overall, we observed substantial spatial variation in injury incidence and a significant 2.1% increase in injury incidence per year. Area-specific risk of injury by motor vehicle collision was higher in regional areas relative to metropolitan areas, while risk of injury by low fall was higher in metropolitan areas. Significant temporal increases were observed in injury by low fall, and the greatest increases were observed in the most disadvantaged LGAs.
These findings can be used to inform injury prevention initiatives, which could be designed to target areas with relatively high injury risk and with significantly increasing injury risk over time. Our finding that the greatest year-on-year increases in injury incidence were observed in the most disadvantaged areas highlights the need for a greater emphasis on reducing inequities in injury.
Children growing up in poverty are less likely to achieve in school and more likely to experience mental health problems. This study examined factors in the local area that can help a child overcome ...the negative impact of poverty.
A longitudinal record linkage retrospective cohort study.
This study included 159,131 children who lived in Wales and completed their age 16 exams (Key Stage 4 (KS4)) between 2009 and 2016. Free School Meal (FSM) provision was used as an indicator of household-level deprivation. Area-level deprivation was measured using the Welsh Index of Multiple Deprivation (WIMD) 2011. An encrypted unique Anonymous Linking Field was used to link the children with their health- and educational records.
The outcome variable ‘Profile to Leave Poverty’ (PLP) was constructed based on successful completion of age 16 exams, no mental health condition, no substance and alcohol misuse records in routine data. Logistic regression with stepwise model selection was used to investigate the association between local area deprivation and the outcome variable.
22% of children on FSM achieved PLP compared to 54.9% of non-FSM children. FSM Children from least deprived areas were significantly more likely to achieve PLP (adjusted odds ratio (aOR) - 2.20 (1.93, 2.51)) than FSM children from most deprived areas. FSM children, living in areas with higher community safety, higher relative income, higher access to services, were more likely to achieve PLP than their peers.
The findings indicate that community-level improvements such as increasing safety, connectivity and employment might help in child's education attainment, mental health and reduce risk taking behaviours.
•This novel study indicates the positive effect of community development measures to build resilience of children in poverty.•Anonymously linked, routine health and education data are used to build a nationally representative cohort of children.•Child’s resilience profile is developed based on child’s educational attainment, mental health, risk-taking behaviours.
Inaccurately modelled environmental exposures may have important implications for evidence-based policy targeting health promoting or hazardous facilities. Travel routes modelled using GIS generally ...use shortest network distances or Euclidean buffers to represent journeys with corresponding built-environment exposures calculated along these routes. These methods, however, are an unreliable proxy for calculating child built-environment exposures as child route choice is more complex than shortest network routes.
We hypothesised that a GIS model informed by characteristics of the built-environment known to influence child route choice could be developed to more accurately model exposures. Using GPS-derived walking commutes to and from school we used logistic regression models to highlight built-environment features important in child route choice (e.g. road type, traffic light count). We then recalculated walking commute routes using a weighted network to incorporate built-environment features. Multilevel regression analyses were used to validate exposure predictions to the retail food environment along the different routing methods.
Children chose routes with more traffic lights and residential roads compared to the modelled shortest network routes. Compared to standard shortest network routes, the GPS-informed weighted network enabled GIS-based walking commutes to be derived with more than three times greater accuracy (38%) for the route to school and more than 12 times greater accuracy (92%) for the route home.
This research advocates using weighted GIS networks to accurately reflect child walking journeys to school. The improved accuracy in route modelling has in turn improved estimates of children's exposures to potentially hazardous features in the environment. Further research is needed to explore if the built-environment features are important internationally. Route and corresponding exposure estimates can be scaled to the population level which will contribute to a better understanding of built-environment exposures on child health and contribute to mobility-based child health policy.
Routine monitoring of Body Mass Index (BMI) in general practice, and via national surveillance programmes, is essential for the identification, prevention, and management of unhealthy childhood ...weight. We examined and compared the presence and representativeness of children and young people's (CYPs) BMI recorded in two routinely collected administrative datasets: general practice electronic health records (GP-BMI) and the Child Measurement Programme for Wales (CMP-BMI), which measures height and weight in 4-5-year-old school children. We also assessed the feasibility of combining GP-BMI and CMP-BMI data for longitudinal analyses.
We accessed de-identified population-level GP-BMI data for calendar years 2011 to 2019 for 246,817 CYP, and CMP-BMI measures for 222,772 CYP, held within the Secure Anonymised Information Linkage Databank. We examined the proportion of CYP in Wales with at least one GP-BMI record, its distribution by child socio-demographic characteristics, and trends over time. We compared GP-BMI and CMP-BMI distributions. We quantified the proportion of children with a CMP-BMI measure and a follow-up GP-BMI recorded at an older age and explored the representativeness of these measures.
We identified a GP-BMI record in 246,817 (41%) CYP, present in a higher proportion of females (54.2%), infants (20.7%) and adolescents. There was no difference in the deprivation profile of those with a GP-BMI measurement. 31,521 CYP with a CMP-BMI had at least one follow-up GP-BMI; those with a CMP-BMI considered underweight or very overweight were 87% and 70% more likely to have at least one follow-up GP-BMI record respectively compared to those with a healthy weight, as were males and CYP living in the most deprived areas of Wales.
Records of childhood weight status extracted from general practice are not representative of the population and are biased with respect to weight status. Linkage of information from the national programme to GP records has the potential to enhance discussions around healthy weight at the point of care but does not provide a representative estimate of population level weight trajectories, essential to provide insights into factors determining a healthy weight gain across the early life course. A second CMP measurement is required in Wales.
Physical housing and household composition have an important role in the lives of individuals and drive health and social outcomes, and inequalities. Most methods to understand housing composition ...are based on survey or census data, and there is currently no reproducible methodology for creating population-level household composition measures using linked administrative data.
Using existing, and more recent enhancements to the address-data linkage methods in the SAIL Databank using Residential Anonymised Linking Fields we linked individuals to properties using the anonymised Welsh Demographic Service data in the SAIL Databank. We defined households, household size, and household composition measures based on adult to child relationships, and age differences between residents to create relative age measures.
Two relative age-based algorithms were developed and returned similar results when applied to population and household-level data, describing household composition for 3.1 million individuals within 1.2 million households in Wales. Developed methods describe binary, and count level generational household composition measures.
Improved residential anonymised linkage field methods in SAIL have led to improved property-level data linkage, allowing the design and application of household composition measures that assign individuals to shared residences and allow the description of household composition across Wales. The reproducible methods create longitudinal, household-level composition measures at a population-level using linked administrative data. Such measures are important to help understand more detail about an individual's home and area environment and how that may affect the health and wellbeing of the individual, other residents, and potentially into the wider community.
Accurate simulations of the atmospheric transport and dispersion (AT&D) of hazardous airborne materials rely heavily on the source term parameters necessary to characterize the initial release and ...meteorological conditions that drive the downwind dispersion. In many cases the source parameters are not known and consequently based on rudimentary assumptions. This is particularly true of accidental releases and the intentional releases associated with terrorist incidents. When available, meteorological observations are often not representative of the conditions at the location of the release and the use of these non-representative meteorological conditions can result in significant errors in the hazard assessments downwind of the sensors, even when the other source parameters are accurately characterized. Here, we describe a computationally efficient methodology to characterize both the release source parameters and the low-level winds (eg. winds near the surface) required to produce a refined downwind hazard. This methodology, known as the Variational Iterative Refinement Source Term Estimation (STE) Algorithm (VIRSA), consists of a combination of modeling systems. These systems include a back-trajectory based source inversion method, a forward Gaussian puff dispersion model, a variational refinement algorithm that uses both a simple forward AT&D model that is a surrogate for the more complex Gaussian puff model and a formal adjoint of this surrogate model. The back-trajectory based method is used to calculate a “first guess” source estimate based on the available observations of the airborne contaminant plume and atmospheric conditions. The variational refinement algorithm is then used to iteratively refine the first guess STE parameters and meteorological variables. The algorithm has been evaluated across a wide range of scenarios of varying complexity. It has been shown to improve the source parameters for location by several hundred percent (normalized by the distance from source to the closest sampler), and improve mass estimates by several orders of magnitude. Furthermore, it also has the ability to operate in scenarios with inconsistencies between the wind and airborne contaminant sensor observations and adjust the wind to provide a better match between the hazard prediction and the observations.
•Methodology for rapid source parameter estimation of hazardous airborne materials releases.•Computationally efficient algorithm to determine release source parameters and low-level winds.•Tested in relevant environments and deployed in DoD operational emergency response tools.
PDF
