ABSTRACT
OBJECTIVES: Poor sleep quality has been linked to adverse health outcomes. It is important to understand factors contributing to sleep quality. Previous research has suggested increased cognition and education duration have a protective effect on sleep quality in old age. This study aimed to assess the hypothesis that age-11 intelligence quotient and highest achieved education level are associated with subjective sleep quality at age 60. METHODS: Participants are members of the Newcastle Thousand Families Study birth cohort, all born in 1947. Data included a calculated intelligence quotient score based on participant's 11-plus exam results, highest achieved education level, social class at ages 25 and 50 and global Pittsburgh Sleep Quality Index (PSQI) at age 60. Multivariable regression analysis was used to investigate effect sizes of variables on global PSQI, which formed the basis of a path analysis model. RESULTS: After excluding participants with incomplete data, and those who had been diagnosed with sleep apnea, 251 participants were included in the path analysis model. Education level was associated with global PSQI (R=-0.653; 95% CI -1.161, -0.145; P = .012) but age-11 intelligence quotient was not. While a similar association was seen for women in the stratified analysis, no such associations were seen for men. CONCLUSIONS: The results of this study show an inverse relationship between education level, but not childhood intelligence quotient, and sleep quality in later life, in women only. Future research is needed to examine the mechanism underlying this relationship.
ABSTRACT
Spatial statistical models are commonly used in geographical scenarios to ensure spatial variation is captured effectively. However, spatial models and cluster algorithms can be complicated and expensive. One of these algorithms is geographically weighted regression (GWR) which was proposed in the geography literature to allow relationships in a regression model to vary over space. In contrast to traditional linear regression models, which have constant regression coefficients over space, regression coefficients are estimated locally at spatially referenced data points with GWR. The motivation for the adaption of GWR is the idea that a set of constant regression coefficients cannot adequately capture spatially varying relationships between covariates and an outcome variable. GWR has been applied widely in diverse fields, such as ecology, forestry, epidemiology, neurology and astronomy. While frequentist GWR gives us point estimates and confidence intervals, Bayesian GWR enriches our understanding by including prior knowledge and providing probability distributions for parameters and predictions of interest. This paper pursues three main objectives. First, it introduces covariate effect clustering by integrating a Bayesian geographically weighted regression (BGWR) with a post-processing step that includes Gaussian mixture model and the Dirichlet process mixture model. Second, this paper examines situations in which a particular covariate holds significant importance in one region but not in another in the Bayesian framework. Lastly, it addresses computational challenges in existing BGWR, leading to enhancements in Markov chain Monte Carlo estimation suitable for large spatial datasets. The efficacy of the proposed method is demonstrated using simulated data and is further validated in a case study examining children's development domains in Queensland, Australia, using data provided by Children's Health Queensland and Australia's Early Development Census.
ABSTRACT
In the field of population health research, understanding the similarities between geographical areas and quantifying their shared effects on health outcomes is crucial. In this paper, we synthesise a number of existing methods to create a new approach that specifically addresses this goal. The approach is called a Bayesian spatial Dirichlet process clustered heterogeneous regression model. This non-parametric framework allows for inference on the number of clusters and the clustering configurations, while simultaneously estimating the parameters for each cluster. We demonstrate the efficacy of the proposed algorithm using simulated data and further apply it to analyse influential factors affecting children's health development domains in Queensland. The study provides valuable insights into the contributions of regional similarities in education and demographics to health outcomes, aiding targeted interventions and policy design.
Subject(s)
Algorithms , Bayes Theorem , Humans , Cluster Analysis , Queensland , ChildABSTRACT
This study aimed to better understand the vulnerability of children in their first year of school, aged between 5 years 5 months and 6 years 6 months, based on five health and development domains. Identification of subgroups of children within these domains can lead to more targeted policies to reduce these vulnerabilities. The focus of this study was to determine clusters of geographical regions with high and low proportions of vulnerable children in Queensland, Australia. This was achieved by carrying out a K-means analysis on data from the Australian Early Development Census and the Australian Bureau of Statistics. The clusters were then compared with respect to their geographic locations and risk factor profiles. The results are made publicly available via an interactive dashboard application developed in R Shiny.
Subject(s)
Schools , Vulnerable Populations , Child , Humans , Child, Preschool , Infant , Queensland/epidemiology , Australia , Risk FactorsABSTRACT
Demographic and educational factors are essential, influential factors of early childhood development. This study aimed to investigate spatial patterns in the association between attendance at preschool and children's developmental vulnerabilities in one or more domain(s) in their first year of full-time school at a small area level in Queensland, Australia. This was achieved by applying geographically weighted regression (GWR) followed by K-means clustering of the regression coefficients. Three distinct geographical clusters were found in Queensland using the GWR coefficients. The first cluster covered more than half of the state of Queensland, including the Greater Brisbane region, and displays a strong negative association between developmental vulnerabilities and attendance at preschool. That is, areas with high proportions of preschool attendance tended to have lower proportions of children with at least one developmental vulnerability in the first year of full-time school. Clusters two and three were characterized by stronger negative associations between developmental vulnerabilities, English as the mother language, and geographic remoteness, respectively. This research provides evidence of the need for collaboration between health and education sectors in specific regions of Queensland to update current service provision policies and to ensure holistic and appropriate care is available to support children with developmental vulnerabilities.
Subject(s)
Child Development , Schools , Child, Preschool , Humans , Child , Queensland/epidemiology , Australia , StudentsABSTRACT
The similarity of sensitivity of adult Africanised and European honeybees following acute oral exposure to thiamethoxam has been questioned. Data collated from adult acute contact and oral toxicity testing of a range of thiamethoxam containing products (solo and mixtures) shows that the toxicity of these products to Africanised honeybees can be directly predicted from the toxicity of the active substances to European honeybees. Similarly, the acute contact and oral toxicity of dimethoate to Africanised bees lies within the same range as European honeybees. There are no major differences in the sensitivity of Africanised and European honeybee individuals to thiamethoxam and dimethoate.
Subject(s)
Dimethoate , Insecticides , Bees , Animals , Thiamethoxam/toxicity , Dimethoate/toxicity , Neonicotinoids/toxicity , Thiazoles/toxicity , Toxicity Tests , Insecticides/toxicityABSTRACT
WHAT IS KNOWN ON THE SUBJECT?: Staff working with other people's mental health are in more danger of experiencing high stress at work. These members of staff are more likely to have mental health problems themselves. Previous research has suggested that training these members of staff to deal with their daily stress and become mentally tougher can protect them. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: The findings showed that higher levels of perceived stress and reduced quality of life in mental health workers were related to lower levels of mental toughness. This research provides a detailed understanding of the current issues experienced in a range of different mental health settings, which may contribute to stress and quality of life. The research highlights the importance of protecting staff mental wellbeing, controlling and reducing levels of stress and suggests that one route to doing this is improving mental toughness. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: These findings suggest a need to increase the awareness of and further protect the mental health of staff working in the mentioned settings. Staff working in mental health settings should be provided with information about how to enhance mental toughness and how to reduce stress. This will lead to a better quality of life for mental health staff and in turn improve the quality of care provided. ABSTRACT: Introduction Clinicians working in mental health services are at increased risk of stress at work. Previous work suggests that mental toughness is a protective mechanism for stress in other professions. This has not yet been examined in mental health workers. Aim/Question To examine whether mental toughness predicts perceived stress and quality of life in mental health workers, to develop an understanding of the factors contributing to and techniques used to deal with stress in this population. Method Sixty-two workers completed measures of mental toughness, perceived stress, quality of life and answered questions regarding their personal experience of stress at work. Results Mental toughness was a predictor of stress (F(7, 54) = 10.58, p < .001) and quality of life (F(6, 55) = 7.58, p < .001, F(7, 54) = 7.15, p < .001 and F(7, 54) = 6.81, p < .001, for compassion satisfaction, burnout and secondary traumatic stress, respectively), with particular roles for the interpersonal confidence and control of life components. Qualitative analysis revealed sources of stress for health workers and a variety of stress management techniques to cope with workplace stress. The findings suggested that mental toughness develops in some but not all health workers due to the demands of their role. Discussion The findings provide an insight into stress, quality of life and protective factors for stress in mental health workers and suggest that future research should consider mental toughness training in mental health workers. Implications for Practice There is a need to increase the awareness of factors contributing to stress in mental health workers, such as a lack of resources and staff, and to promote organizational change to improve their professional quality of life. Future research should also explore the potential of mental toughness training in this population.
Subject(s)
Burnout, Professional , Occupational Stress , Humans , Mental Health , Quality of Life , Burnout, Professional/psychology , Occupational Stress/psychology , Health Personnel/psychologyABSTRACT
Plants respond to environmental stresses through controlled stem cell maintenance and meristem activity. One level of gene regulation is RNA alternative splicing. However, the mechanistic link between stress, meristem function and RNA splicing is poorly understood. The MERISTEM-DEFECTIVE (MDF) Arabidopsis gene encodes an SR-related family protein, required for meristem function and leaf vascularization, and is the likely orthologue of the human SART1 and yeast Snu66 splicing factors. MDF is required for the correct splicing and expression of key transcripts associated with root meristem function. We identified RSZ33 and ACC1, both known to regulate cell patterning, as splicing targets required for MDF function in the meristem. MDF expression is modulated by osmotic and cold stress, associated with differential splicing and specific isoform accumulation and shuttling between nucleus and cytosol, and acts in part via a splicing target SR34. We propose a model in which MDF controls splicing in the root meristem to promote stemness and to repress stress response, cell differentiation and cell death pathways.
Subject(s)
Arabidopsis Proteins , Arabidopsis , Humans , Meristem/metabolism , Arabidopsis Proteins/genetics , Arabidopsis Proteins/metabolism , Arabidopsis/metabolism , RNA Splicing/genetics , Cell Differentiation/genetics , Gene Expression Regulation, Plant/genetics , Plant Roots/genetics , Plant Roots/metabolismABSTRACT
During sowing using pneumatic machinery, dust may be abraded from pesticide-treated seed and contaminate adjacent bee-attractive off-crop areas. This study quantified the risk to native bees of dust released during sowing of Brazilian crop seeds treated with a thiamethoxam formulation (Cruiser 350FS). To address toxicity to native bees, adult acute contact LD50 data for thiamethoxam were collated from the literature, a species sensitivity distribution generated, and the HD5 calculated. The LD50 HD5 was used to refine the default safety factor applied to the honeybee acute contact LD50 from 10 to 5.45 for thiamethoxam. Crop-specific abraded dust data (Heubach dust and Heubach AI) were generated for seeds treated with Cruiser 350FS sourced from on-farm and industrial facilities. The mean Heubach dust levels was ranked as cotton = maize > sunflower = soybean > drybean. There was no correlation between the measured residues of thiamethoxam (Heubach AI) and those estimated in dust based on the thiamethoxam content of Cruiser 350FS. A hazard quotient (HQ) for each crop (based on application rate, the default dust deposition factor, and the honeybee contact LD50/10) identified risks during sowing for all crops. Refinement of the application rate with the measured 90th percentile Heubach dust (assuming 100% thiamethoxam) resulted in sowing of industrially treated soybean and on-farm treated cotton being identified as risks. Further refinement using either the measured 90th percentile Heubach AI or the acute contact LD50 (HD5 ) resulted in sowing of all crops treated with Cruiser 350FS as being identified as low risk. Similar high quality seed treatment should be demonstrated for other formulations containing insecticides with high toxicity to bees. Data on dust drift from machinery and crops more representative of those in Brazil may allow further refinement of the default dust deposition value of 17% used in this study. Integr Environ Assess Manag 2023;19:1361-1373. © 2023 SETAC.
Subject(s)
Dust , Insecticides , Bees , Animals , Thiamethoxam/analysis , Dust/analysis , Brazil , Neonicotinoids/toxicity , Insecticides/toxicity , Insecticides/analysis , Seeds/chemistry , Crops, Agricultural , Risk AssessmentABSTRACT
A group education program was developed for clinic patients with rheumatoid arthritis. Teaching methods used included the Arthritis Foundation's handbook, Rheumatoid Arthritis, and a lecture by a rheumatologist. The 20 patients in the study were given a multiple choice test before and after the teaching program to determine their knowledge of arthritis. Results showed group education to be an effective teaching device. It was demonstrated that patients learned from reading the handbook alone, but the combination of reading and lecture was found to be a more effective method. Correlation studies showed that prior to group education, patients had a significant knowledge of their disease which was related to native intelligence, formal education, and socio-economic status, but not to duration of disease or length of clinic attendance. This suggests that future patient education experiments should include a pre-instuction test to document prior knowledge.
Subject(s)
Arthritis, Rheumatoid , Humans , Arthritis, Rheumatoid/therapy , Program EvaluationABSTRACT
Epidemiological studies investigating the association between daily particle exposure and health effects are frequently based on a single monitoring site located in an urban background. Using a central site in epidemiological time-series studies has been established based on the premises of low spatial variability of particles within the areas of interest and hence the adequacy of the central sites to monitor the exposure. This is true to a large extent in relation to larger particles (PM2.5, PM10) that are typically monitored and regulated. However, the distribution of ultrafine particles (UFP), which in cities predominantly originate from traffic, is heterogeneous. With increasing pressure to improve the epidemiology of UFP, an important question to ask is, whether central site monitoring is representative of community exposure to this size fraction of particulate matter; addressing this question is the aim of this paper. To achieve this aim, we measured personal exposure to UFP, expressed as particle number concentration (PNC), using Philips Aerasense Nanotracers (NT) carried by the participants of the study, and condensation particle counters (CPC) or scanning mobility particle sizers (SMPS) at central fixed-site monitoring stations. The measurements were conducted at three locations in Brisbane (Australia), Cassino (Italy) and Accra (Ghana). We then used paired t-tests to compare the average personal and average fixed-site PNC measured over the same 24-h, and hourly, periods. We found that, at all three locations, the 24-h average fixed-site PNC was no different to the personal PNC, when averaged over the study period and all the participants. However, the corresponding hourly averages were significantly different at certain times of the day. These were generally times spent commuting and during cooking and eating at home. Our analysis of the data obtained in Brisbane, showed that maximum personal exposure occurred in the home microenvironment during morning breakfast and evening dinner time. The main source of PNC for personal exposure was from the home-microenvironment. We conclude that the 24-h average PNC from the central-site can be used to estimate the 24-h average personal exposure for a community. However, the hourly average PNC from the central site cannot consistently be used to estimate hourly average personal exposure, mainly because they are affected by very different sources.
Subject(s)
Air Pollutants , Particulate Matter , Child , Humans , Particulate Matter/analysis , Air Pollutants/analysis , Environmental Monitoring , Particle Size , CitiesABSTRACT
This work investigates the application of a tiered risk assessment scheme for soil organisms based on the risk quotient (RQ) and the toxicity exposure ratio (TER). Forty-five pesticides registered in Latin America were chosen and the ecotoxicological endpoints for earthworms, Collembola, and microorganisms were collated. Tier I assessment was made on conservative assumptions in which no refinements were applied. There, 14 pesticides (31%) exceed the RQ regulatory trigger indicating unacceptable risk, whereas 27 (60%) indicate unacceptable risk on the TER approach. In a Tier II evaluation when refinement options such as foliar interception, field half-life, and the dissipation following the peak estimated environmental concentration are considered, eight (18%) pesticides indicate unacceptable risk based on the RQ, and 15 (33%) indicate unacceptable risk based on the TER. A nonmetric multidimensional scaling evaluation was performed to understand the relevant characteristics involved in how each pesticide poses a risk to soil organisms. Based on the outcome of this analysis, we observed that, for a given pesticide, the combination of high persistence, low or no crop interception, and high toxicity are likely to require higher tier risk assessment. Refinement options can consider either or both the exposure and/or the effect side of the framework. Exposure refinements are potentially simpler and can be conducted with data already available to risk assessors, whereas effect refinements involving further testing with the organisms potentially at risk are still under discussion for intermediate and higher tiers. A sensitive, simple, and logical environmental risk assessment framework can be used to adequately identify risks based on the relevant protection goals that, in turn, will help to protect the desired soil multifunctionality of the ecosystem. We encourage academia and industry to further investigate these topics to provide the most scientifically robust and evidence-based information to decision makers. Integr Environ Assess Manag 2023;19:446-460. © 2022 SETAC.
Subject(s)
Pesticides , Pesticides/toxicity , Soil , Ecosystem , Latin America , Risk Assessment/methodsABSTRACT
Plant RNases T2 are involved in several physiological and developmental processes, including inorganic phosphate starvation, senescence, wounding, defense against pathogens, and the self-incompatibility system. Solanaceae RNases form three main clades, one composed exclusively of S-RNases and two that include S-like RNases. We identified several positively selected amino acids located in highly flexible regions of these molecules, mainly close to the B1 and B2 substrate-binding sites in S-like RNases and the hypervariable regions of S-RNases. These differences between S- and S-like RNases in the flexibility of amino acids in substrate-binding regions are essential to understand the RNA-binding process. For example, in the S-like RNase NT, two positively selected amino acid residues (Tyr156 and Asn134) are located at the most flexible sites on the molecular surface. RNase NT is induced in response to tobacco mosaic virus infection; these sites may thus be regions of interaction with pathogen proteins or viral RNA. Differential selective pressures acting on plant ribonucleases have increased amino acid variability and, consequently, structural differences within and among S-like RNases and S-RNases that seem to be essential for these proteins play different functions.
ABSTRACT
AIMS: To achieve expert clinical consensus in the delivery of hydrodilatation for the treatment of primary frozen shoulder to inform clinical practice and the design of an intervention for evaluation. METHODS: We conducted a two-stage, electronic questionnaire-based, modified Delphi survey of shoulder experts in the UK NHS. Round one required positive, negative, or neutral ratings about hydrodilatation. In round two, each participant was reminded of their round one responses and the modal (or 'group') response from all participants. This allowed participants to modify their responses in round two. We proposed respectively mandating or encouraging elements of hydrodilatation with 100% and 90% positive consensus, and respectively disallowing or discouraging with 90% and 80% negative consensus. Other elements would be optional. RESULTS: Between 4 August 2020 and 4 August 2021, shoulder experts from 47 hospitals in the UK completed the study. There were 106 participants (consultant upper limb orthopaedic surgeons, n = 50; consultant radiologists, n = 52; consultant physiotherapist, n = 1; extended scope physiotherapists, n = 3) who completed round one, of whom 97 (92%) completed round two. No elements of hydrodilatation were "mandated" (100% positive rating). Elements that were "encouraged" (≥ 80% positive rating) were the use of image guidance, local anaesthetic, normal saline, and steroids to deliver the injection. Injecting according to patient tolerance, physiotherapy, and home exercises were also "encouraged". No elements were "discouraged" (≥ 80% negative rating) although using hypertonic saline was rated as being "disallowed" (≥ 90% negative rating). CONCLUSION: In the absence of rigorous evidence, our Delphi study allowed us to achieve expert consensus about positive, negative, and neutral ratings of hydrodilatation in the management of frozen shoulder in a hospital setting. This should inform clinical practice and the design of an intervention for evaluation.Cite this article: Bone Jt Open 2022;3(9):701-709.
ABSTRACT
Time series data are often observed in ecological monitoring. Frequently, such data exhibit nonlinear trends over time potentially due to complex relationships between observed and auxiliary variables, and there may also be sudden declines over time due to major disturbances. This poses substantial challenges for modeling such data and also for adaptive monitoring. To address this, we propose methods for finding adaptive designs for monitoring in such settings. This work is motivated by a monitoring program that has been established at Scott Reef; a coral reef off the Western coast of Australia. Data collected for monitoring the health of Scott Reef are considered, and semiparametric and interrupted time series modeling approaches are adopted to describe how these data vary over time. New methods are then proposed that enable adaptive monitoring designs to be found based on such modeling approaches. These methods are then applied to find future monitoring designs at Scott Reef where it was found that future information gain is expected to be similar across a variety of different sites, suggesting that no particular location needs to be prioritized at Scott Reef for the next monitoring phase. In addition, it was found that omitting some sampling sites/reef locations was possible without substantial loss in expected information gain, depending upon the disturbances that were observed. The resulting adaptive designs are used to form recommendations for future monitoring in this region, and for reefs where changes in the current monitoring practices are being sought. As the methods used and developed throughout this study are generic in nature, this research has the potential to improve ecological monitoring more broadly where complex data are being collected over time.
Subject(s)
Soil Pollutants , Soil , Brazil , Risk Assessment , Soil Pollutants/analysis , Soil Pollutants/toxicityABSTRACT
The ban imposed by the European Union on the use of neonicotinoids as sugar beet seed treatments was based on the exposure of bees to residues of neonicotinoids in pollen and nectar of succeeding crops. To address this concern, residues of thiamethoxam (TMX) and clothianidin (CTD) were analyzed in soil collected from fields planted in at least the previous year with thiamethoxam-treated sugar beet seed. This soil monitoring program was conducted at 94 sites across Germany in two separate years. In addition, a succeeding crop study assessed residues in soil, guttation fluid, pollen, and nectar sampled from untreated succeeding crops planted in the season after thiamethoxam seed-treated sugar beet at eight field sites across five countries. The overall mean residues observed in soil monitoring were 8.0 ± 0.5 µg TMX + CTD/kg in the season after the use of treated sugar beet seed. Residue values decreased with increasing time interval between the latest thiamethoxam or clothianidin application before sugar beet drilling and with lower application frequency. Residues were detected in guttation fluid (2.0-37.7 µg TMX/L); however, the risk to pollinators from this route of exposure is likely to be low, based on the reported levels of consumption. Residues of thiamethoxam and clothianidin in pollen and nectar sampled from the succeeding crops were detected at or below the limit of quantification (0.5-1 µg a.i./kg) in 86.7% of pollen and 98.6% of nectar samples and, unlike guttation fluid residues, were not correlated with measured soil residues. Residues in pollen and nectar are lower than reported sublethal adverse effect concentrations in studies with honeybee and bumble bee individuals and colonies fed only thiamethoxam-treated sucrose, and are lower than those reported to result in no effects in honeybees, bumble bees, and solitary bees foraging on seed-treated crops. Integr Environ Assess Manag 2022;18:709-721. © 2021 SYNGENTA. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
Subject(s)
Beta vulgaris , Insecticides , Animals , Bees , Crops, Agricultural , Insecticides/analysis , Insecticides/toxicity , Neonicotinoids/toxicity , Nitro Compounds/toxicity , Oxazines/analysis , Oxazines/toxicity , Plant Nectar/analysis , Plant Nectar/chemistry , Seeds/chemistry , Soil , Sugars/analysis , Thiamethoxam/analysis , VegetablesABSTRACT
Developmental surveillance tools are used to closely monitor the early development of infants and young children. This study provides a novel implementation of a multidimensional item response model, using Bayesian hierarchical priors, to construct developmental profiles for a small sample of children (N = 115) with sparse data collected through an online developmental surveillance tool. The surveillance tool records 348 developmental milestones measured from birth to three years of age, within six functional domains: auditory, hands, movement, speech, tactile, and vision. The profiles were constructed in three steps: (1) the multidimensional item response model, embedded in the Bayesian hierarchical framework, was implemented in order to measure both the latent abilities of the children and attributes of the milestones, while retaining the correlation structure among the latent developmental domains; (2) subsequent hierarchical clustering of the multidimensional ability estimates enabled identification of subgroups of children; and (3) information from the posterior distributions of the item response model parameters and the results of the clustering were used to construct a personalized profile of development for each child. These individual profiles support early identification of, and personalized early interventions for, children with developmental delay.