Physical activity in New Zealand preschoolers: amount, associations, and accounts

Improving physical activity (PA) participation is a public health priority in developed and developing countries to curb the substantial and growing prevalence of lifestyle-related diseases. Early childhood may be an especially important time to encourage PA; however, there is a paucity of research in this area. The aim of this research was to contribute to the limited body of work in PA in early childhood by investigating PA measurement approaches in young children and applying this knowledge to determine socio-environmental associations of preschool PA. An initial literature review provided the background for the thesis and determined the approaches taken in the ensuing chapters. A second literature review provided a detailed critique of research specific to PA measurement in early childhood to further inform the empirical studies. Information for the empirical chapters was drawn from three research projects: two studies were completed that assessed tools for objectively measuring PA in young children (pedometers and accelerometers), and these studies informed a final project to quantify associates of PA in a sample of preschool-aged children. Novel and important findings from the preliminary studies were that pedometer accuracy for measuring free-living PA and walking in children aged 3-5 years was poor, especially for pedometers worn at the back of the child, or during slow walking. Furthermore, when investigating the utility of accelerometers (more complex and frequently adopted tools) to quantify PA intensity in preschoolers, their application and use of commonly employed thresholds resulted in systematic underestimation of PA intensity and poor agreement (=0.09) when compared with a direct observation criterion measure. Application of existing accelerometer thresholds to classify PA intensity in preschoolers was therefore likely to yield biased estimates. Given the dearth of robust alternatives, a novel approach was developed to calculate individual activity rates from the raw accelerometer data. To account for over-dispersion in accelerometer counts, daily average activity rates per second were derived for each participant using negative binomial generalised estimating equation (GEE) models with a first-order autoregressive (AR1) correlation structure. These rates were assumed to be exchangeable between days and normally distributed. Potential socio-environmental associates of children’s activity rates and body size were thus assessed using normal GEE models with exchangeable correlation structures. Parental PA and child age were independently and significantly associated with child activity rates (P≤0.04). No relationships between child body size and PA or television (TV) exposure were found. Common approaches to PA measurement and data consideration were challenged in this research and novel robust methods devised utilising contemporary statistical methods. Accelerometer data can be successfully reduced to individual activity rates to mitigate current issues related to objective PA quantification with preschoolers. Parental involvement in preschool PA interventions is worthy of further investigation, and younger children may stand to benefit more from increased activity. Further exploration of the complex interactions between PA, exposure to media, and health outcomes in preschool-aged children is warranted

Linking GPS and travel diary data using sequence alignment in a study of children's independent mobility

<p>Abstract</p> <p>Background</p> <p>Global positioning systems (<b>GPS</b>) are increasingly being used in health research to determine the location of study participants. Combining GPS data with data collected via travel/activity diaries allows researchers to assess where people travel in conjunction with data about trip purpose and accompaniment. However, linking GPS and diary data is problematic and to date the only method has been to match the two datasets manually, which is time consuming and unlikely to be practical for larger data sets. This paper assesses the feasibility of a new sequence alignment method of linking GPS and travel diary data in comparison with the manual matching method.</p> <p>Methods</p> <p>GPS and travel diary data obtained from a study of children's independent mobility were linked using sequence alignment algorithms to test the proof of concept. Travel diaries were assessed for quality by counting the number of errors and inconsistencies in each participant's set of diaries. The success of the sequence alignment method was compared for higher versus lower quality travel diaries, and for accompanied versus unaccompanied trips. Time taken and percentage of trips matched were compared for the sequence alignment method and the manual method.</p> <p>Results</p> <p>The sequence alignment method matched 61.9% of all trips. Higher quality travel diaries were associated with higher match rates in both the sequence alignment and manual matching methods. The sequence alignment method performed almost as well as the manual method and was an order of magnitude faster. However, the sequence alignment method was less successful at fully matching trips and at matching unaccompanied trips.</p> <p>Conclusions</p> <p>Sequence alignment is a promising method of linking GPS and travel diary data in large population datasets, especially if limitations in the trip detection algorithm are addressed.</p

Phrenic nerve injury secondary to extracorporeal membrane oxygenation in pregancy: A case report

Extracorporeal membrane oxygenation (ECMO) is used to provide acute respiratory and/or hemodynamic support to patients with severe, refractory respiratory failure. Phrenic nerve injury with subsequent hemidiaphragm paralysis should be included in the differential diagnosis of pregnant women with persistent hypoxia after ECMO cannulation

Measuring Haptic Experience: Elaborating the HX model with scale development

If an author previously posted their submitted version of the article in any of the following locations, he or she will need to replace the submitted version with the accepted version and add the IEEE copyright notice (© 2021 IEEE). When the article is published, the posted version should be updated with a full citation to the original IEEE publication, including DOI. No other changes may be made to the accepted article.Designers increasingly employ haptic feedback with the aim to improve user experience (UX). Designers and researchers currently use qualitative methods or demos for feedback, but neither approach scales to large studies or remote work. We build upon the recent Haptic Experience (HX) model and report on progress towards measuring the five constructs for designing haptic experiences: Harmony, Expressivity, Autotelics, Immersion, and Realism. We describe initial findings from scale development, specifically, from item generation (N=23) and exploratory factor analysis (N=261). Our results provide initial evidence that vibrotactile experiences are effectively modeled by five factors, enriched description of each factor, and guidelines for quantitatively measuring HX.NSERC Discovery Gran

Associations between the neighbourhood built environment and out of school physical activity and active travel : An examination from the Kids in the City study

This study's aim was to examine selected objectively-measured and child specific built environment attributes in relation to proportion of out-of-school time spent in moderate-to-vigorous physical activity (%MVPA) and active travel in a group of ethnically and socio-economically diverse children (n=236) living in Auckland, New Zealand. Street connectivity and distance to school were related to the proportion of trips made by active modes. Ratio of high speed to low speed roads and improved streetscape for active travel were related to %MVPA on weekdays only. Inconsistent results were found for destination accessibility. Local destinations (particularly schools) along a safe street network may be important for encouraging children's activity behaviours

Impact of measured and simulated tundra snowpack properties on heat transfer

Snowpack microstructure controls the transfer of heat to, as well as the temperature of, the underlying soils. In situ measurements of snow and soil properties from four field campaigns during two winters (March and November 2018, January and March 2019) were compared to an ensemble of CLM5.0 (Community Land Model) simulations, at Trail Valley Creek, Northwest Territories, Canada. Snow micropenetrometer profiles allowed for snowpack density and thermal conductivity to be derived at higher vertical resolution (1.25 mm) and a larger sample size (n=1050) compared to traditional snowpit observations (3 cm vertical resolution; n=115). Comparing measurements with simulations shows CLM overestimated snow thermal conductivity by a factor of 3, leading to a cold bias in wintertime soil temperatures (RMSE=5.8 ∘C). Two different approaches were taken to reduce this bias: alternative parameterisations of snow thermal conductivity and the application of a correction factor. All the evaluated parameterisations of snow thermal conductivity improved simulations of wintertime soil temperatures, with that of Sturm et al. (1997) having the greatest impact (RMSE=2.5 ∘C). The required correction factor is strongly related to snow depth () and thus differs between the two snow seasons, limiting the applicability of such an approach. Improving simulated snow properties and the corresponding heat flux is important, as wintertime soil temperatures are an important control on subnivean soil respiration and hence impact Arctic winter carbon fluxes and budgets

Simulating net ecosystem exchange under seasonal snow cover at an Arctic tundra site

Estimates of winter (snow-covered non-growing season) CO2 fluxes across the Arctic region vary by a factor of 3.5, with considerable variation between measured and simulated fluxes. Measurements of snow properties, soil temperatures, and net ecosystem exchange (NEE) at Trail Valley Creek, NWT, Canada, allowed for the evaluation of simulated winter NEE in a tundra environment with the Community Land Model (CLM5.0). Default CLM5.0 parameterisations did not adequately simulate winter NEE in this tundra environment, with near-zero NEE (< 0.01 gCm^-2d^-1) simulated between November and mid-May. In contrast, measured NEE was broadly positive (indicating net CO2 release) from snow-cover onset until late April. Changes to the parameterisation of snow thermal conductivity, required to correct for a cold soil temperature bias, reduced the duration for which no NEE was simulated. Parameter sensitivity analysis revealed the critical role of the minimum soil moisture threshold of decomposition (Ψmin) in regulating winter soil respiration. The default value of this parameter (Ψmin) was too high, preventing simulation of soil respiration for the vast majority of the snow-covered season. In addition, the default rate of change of soil respiration with temperature (Q10) was too low, further contributing to poor model performance during winter. As Ψmin and Q10 had opposing effects on the magnitude of simulated winter soil respiration, larger negative values of Ψmin and larger positive values of Q10 are required to simulate wintertime NEE more adequately.Natural Environment Research CouncilPeer Reviewe

Accelerometer data reduction in adolescents: effects on sample retention and bias

BACKGROUND: Accelerometry is increasingly being recognized as an accurate and reliable method to assess free-living physical activity (PA) in children and adolescents. However, accelerometer data reduction criteria remain inconsistent, and the consequences of excluding participants in for example intervention studies are not well described. In this study, we investigated how different data reduction criteria changed the composition of the adolescent population retained in accelerometer data analysis. METHODS: Accelerometer data (Actigraph GT3X), anthropometric measures and survey data were obtained from 1348 adolescents aged 11-14 years enrolled in the Danish SPACE for physical activity study. Accelerometer data were analysed using different settings for each of the three key data reduction criteria: (1) number of valid days; (2) daily wear time; and (3) non-wear time. The effects of the selected setting on sample retention and PA counts were investigated and compared. Ordinal logistic regression and multilevel mixed-effect linear regression models were used to analyse the impact of differing non-wear time definitions in different subgroups defined by body mass index, age, sex, and self-reported PA and sedentary levels. RESULTS: Increasing the minimum requirements for daily wear time and the number of valid days and applying shorter non-wear definitions, resulted in fewer adolescents retained in the dataset. Moreover, the different settings for non-wear time significantly influenced which participants would be retained in the accelerometer data analyses. Adolescents with a higher BMI (OR:0.93, CI:0.87-0.98, p=0.015) and older adolescents (OR:0.68, CI:0.49-0.95, p=0.025) were more likely to be excluded from analysis using 10 minutes of non-wear compared to longer non-wear time periods. Overweight and older adolescents accumulated more daily non-wear time if the non-wear time setting was short, and the relative difference between groups changed depending on the non-wear setting. Overweight and older adolescents did also accumulate more sedentary time, but this was not significant correlated to the non-wear setting used. CONCLUSIONS: Even small differences in accelerometer data reduction criteria can have substantial impact on sample size and PA and sedentary outcomes. This study highlighted the risk of introducing bias with more overweight and older adolescents excluded from the analysis when using short non-wear time definitions

Intravital Immunofluorescence for Visualizing the Microcirculatory and Immune Microenvironments in the Mouse Ear Dermis

Visualizing the dynamic behaviors of immune cells in living tissue has dramatically increased our understanding of how cells interact with their surroundings, contributing important insights into mechanisms of leukocyte trafficking, tumor cell invasion, and T cell education by dendritic cells, among others. Despite substantial advances with various intravital imaging techniques including two-photon microscopy and the generation of multitudes of reporter mice, there is a growing need to assess cell interactions in the context of specific extracellular matrix composition and microvascular functions, and as well, simpler and more widely accessible methods are needed to image cell behaviors in the context of living tissue physiology. Here we present an antibody-based method for intravital imaging of cell interactions with the blood, lymphatic, and the extracellular matrix compartments of the living dermis while simultaneously assessing capillary permeability and lymphatic drainage function. Using the exposed dorsal ear of the anesthetized mouse and a fluorescence stereomicroscope, such events can be imaged in the context of specific extracellular matrix proteins, or matrix-bound chemokine stores. We developed and optimized the method to minimize tissue damage to the ear, rapidly immunostain for multiple extracellular or cell surface receptors of interest, minimize immunotoxicity with pre-blocking Fc gamma receptors and phototoxicity with extracellular antioxidants, and highlight the major dermal tissue structures with basement membrane markers. We demonstrate differential migration behaviors of bone marrow-derived dendritic cells, blood-circulating leukocytes, and dermal dendritic cells, with the latter entering sparse CCL21-positive areas of pre-collecting lymphatic vessels. This new method allows simultaneous imaging of cells and tissue structures, microvascular function, and extracellular microenvironment in multiple skin locations for 12 hours or more, with the flexibility of immunolabeling in addition to genetic-based fluorescent reporters