Vitamin D status and skin cancer risk independent of time outdoors : 11-year prospective study in and Australian community

Vitamin D may have anti-skin cancer effects, but population-based evidence is lacking. We therefore assessed associations between vitamin D status and skin cancer risk in an Australian subtropical community. We analyzed prospective skin cancer incidence for 11 years following baseline assessment of serum 25(OH)-vitamin D in 1,191 adults (average age 54 years) and used multivariable logistic regression analysis to adjust risk estimates for age, sex, detailed assessments of usual time spent outdoors, phenotypic characteristics, and other possible confounders. Participants with serum 25(OH)-vitamin D concentrations above 75 nmol  l(-1) versus those below 75 nmol  l(-1) more often developed basal cell carcinoma (odds ratio (OR)=1.51 (95% confidence interval (CI): 1.10-2.07, P=0.01) and melanoma (OR=2.71 (95% CI: 0.98-7.48, P=0.05)). Squamous cell carcinoma incidence tended to be lower in persons with serum 25(OH)-vitamin D concentrations above 75 nmol  l(-1) compared with those below 75 nmol  l(-1) (OR=0.67 (95% CI: 0.44-1.03, P=0.07)). Vitamin D status was not associated with skin cancer incidence when participants were classified as above or below 50 nmol  l(-1) 25(OH)-vitamin D. Our findings do not indicate that the carcinogenicity of high sun exposure can be counteracted by high vitamin D status. High sun exposure is to be avoided as a means to achieve high vitamin D status.

Exercise-recruited NK cells display exercise-associated eHSP-70

It is hypothesized that increased plasma or serum concentrations of extracellular heat shock proteins (eHSP) serve as a danger signal to the innate immune system. Cellular binding of eHSP leads to activation of NK cells and monocytes, as measured by their increased cytokine production, mitotic division and killing capacity. We examined whether eHSP binds to NK lymphocytes in vivo in athletes performing endurance exercise in the heat. Eighteen trained male runners ran at 70% VO2max at 35 degrees C and 40% relative humidity. Venous blood collected before, after and 1.5 h after exercise was analysed for leukocyte distribution, phenotype and eHSP70. NK cell-enriched samples were examined for co-localization of CD94 and eHSP70 expression. Plasma eHSP-70 concentration was measured by ELISA. Subjects ran for approximately 50 min, which elicited a reversible leukocytosis. NK cell count increased 83% (p < 0.01) immediately after exercise, then decreased to 66% of the resting level 1.5 h after exercise (p < 0.05). Plasma eHSP concentration increased 167% after exercise and remained elevated (by up to 71%) 1.5 h after exercise (p < 0.01). eHSP was expressed on both NK cells and monocytes at all times; the count of NK cells positive for eHSP doubled from 0.04 +/- 0.02 10(9)/L (mean +/- SD) to 0.08 +/- 0.06 10(9)/L after exercise. In summary, exercise in the heat increased free plasma eHSP concentration, and the eHSP co-localized with CD94 on NK cells. These data confirm the link between exercise and activation of the innate immune system.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

A leap into foodservice satisfaction in the private acute care setting

Monitoring foodservice satisfaction is a risk management strategy for malnutrition in the acute care sector, as low satisfaction may be associated with poor intake. This study aimed to investigate the relationship between age and foodservice satisfaction in the private acute care setting. Patient satisfaction was assessed using a validated tool, the Acute Care Hospital Foodservice Patient Satisfaction Questionnaire for data collected 2008–2010 (n = 779) at a private hospital, Brisbane. Age was grouped into three categories; <50 years, 51–70 years and >70 years. Fisher’s exact test assessed independence of categorical responses and age group; ANOVA or Kruskal–Wallis test was used for continuous variables. Dichotomised responses were analysed using logistic regression and odds ratios (95% confidence interval, p < 0.05). Overall foodservice satisfaction (5 point scale) was high (≥4 out of 5) and was independent of age group (p = 0.377). There was an increasing trend with age in mean satisfaction scores for individual dimensions of foodservice; food quality (p < 0.001), meal service quality (p < 0.001), staff service issues (p < 0.001) and physical environment (p < 0.001). A preference for being able to choose different sized meals (59.8% > 70 years vs 40.6% ≤50 years; p < 0.001) and response to ‘the foods are just the right temperature’ (55.3% >70 years vs 35.9% ≤50 years; p < 0.001) was dependent on age. For the food quality dimension, based on dichotomised responses (satisfied or not), the odds of satisfaction was higher for >70 years (OR = 5.0, 95% CI: 1.8–13.8; <50 years referent). These results suggest that dimensions of foodservice satisfaction are associated with age and can assist foodservices to meet varying generational expectations of clients.

On the time spent preparing grant proposals : an observational study of Australian researchers

Objective: To estimate the time spent by the researchers for preparing grant proposals, and to examine whether spending more time increase the chances of success. Design: Observational study. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant proposals in March 2012. Main outcome measures: Total researcher time spent preparing proposals; funding success as predicted by the time spent. Results: The NHMRC received 3727 proposals of which 3570 were reviewed and 731 (21%) were funded. Among our 285 participants who submitted 632 proposals, 21% were successful. Preparing a new proposal took an average of 38 working days of researcher time and a resubmitted proposal took 28 working days, an overall average of 34 days per proposal. An estimated 550 working years of researchers' time (95% CI 513 to 589) was spent preparing the 3727 proposals, which translates into annual salary costs of AU$66 million. More time spent preparing a proposal did not increase the chances of success for the lead researcher (prevalence ratio (PR) of success for 10 day increase=0.91, 95% credible interval 0.78 to 1.04) or other researchers (PR=0.89, 95% CI 0.67 to 1.17). Conclusions: Considerable time is spent preparing NHMRC Project Grant proposals. As success rates are historically 20–25%, much of this time has no immediate benefit to either the researcher or society, and there are large opportunity costs in lost research output. The application process could be shortened so that only information relevant for peer review, not administration, is collected. This would have little impact on the quality of peer review and the time saved could be reinvested into research.

Meal induced thermogenesis and appetite : methodological issues and responses to energy restriction

Diet Induced Thermogenesis (DIT) is the energy expended consequent to meal consumption, and reflects the energy required for the processing and digestion of food consumed throughout each day. Although DIT is the total energy expended across a day in digestive processes to a number of meals, most studies measure thermogenesis in response to a single meal (Meal Induced Thermogenesis: MIT) as a representation of an individual’s thermogenic response to acute food ingestion. As a component of energy expenditure, DIT may have a contributing role in weight gain and weight loss. While the evidence is inconsistent, research has tended to reveal a suppressed MIT response in obese compared to lean individuals, which identifies individuals with an efficient storage of food energy, hence a greater tendency for weight gain. Appetite is another factor regulating body weight through its influence on energy intake. Preliminary research has shown a potential link between MIT and postprandial appetite as both are responses to food ingestion and have a similar response dependent upon the macronutrient content of food. There is a growing interest in understanding how both MIT and appetite are modified with changes in diet, activity levels and body size. However, the findings from MIT research have been highly inconsistent, potentially due to the vastly divergent protocols used for its measurement. Therefore, the main theme of this thesis was firstly, to address some of the methodological issues associated with measuring MIT. Additionally this thesis aimed to measure postprandial appetite simultaneously to MIT to test for any relationships between these meal-induced variables and to assess changes that occur in MIT and postprandial appetite during periods of energy restriction (ER) and following weight loss. Two separate studies were conducted to achieve these aims. Based on the increasing prevalence of obesity, it is important to develop accurate methodologies for measuring the components potentially contributing to its development and to understand the variability within these variables. Therefore, the aim of Study One was to establish a protocol for measuring the thermogenic response to a single test meal (MIT), as a representation of DIT across a day. This was done by determining the reproducibility of MIT with a continuous measurement protocol and determining the effect of measurement duration. The benefit of a fixed resting metabolic rate (RMR), which is a single measure of RMR used to calculate each subsequent measure of MIT, compared to separate baseline RMRs, which are separate measures of RMR measured immediately prior to each MIT test meal to calculate each measure of MIT, was also assessed to determine the method with greater reproducibility. Subsidiary aims were to measure postprandial appetite simultaneously to MIT, to determine its reproducibility between days and to assess potential relationships between these two variables. Ten healthy individuals (5 males, 5 females, age = 30.2 ± 7.6 years, BMI = 22.3 ± 1.9 kg/m2, %Fat Mass = 27.6 ± 5.9%) undertook three testing sessions within a 1-4 week time period. During the first visit, participants had their body composition measured using DXA for descriptive purposes, then had an initial 30-minute measure of RMR to familiarise them with the testing and to be used as a fixed baseline for calculating MIT. During the second and third testing sessions, MIT was measured. Measures of RMR and MIT were undertaken using a metabolic cart with a ventilated hood to measure energy expenditure via indirect calorimetry with participants in a semi-reclined position. The procedure on each MIT test day was: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard 576 kcal breakfast (54.3% CHO, 14.3% PRO, 31.4% FAT), comprising muesli, milk toast, butter, jam and juice, and 3) six hours of measuring MIT with two, ten-minute breaks at 3 and 4.5 hours for participants to visit the bathroom. On the MIT test days, pre and post breakfast then at 45-minute intervals, participants rated their subjective appetite, alertness and comfort on visual analogue scales (VAS). Prior to each test, participants were required to be fasted for 12 hours, and have undertaken no high intensity physical activity for the previous 48 hours. Despite no significant group changes in the MIT response between days, individual variability was high with an average between-day CV of 33%, which was not significantly improved by the use of a fixed RMR to 31%. The 95% limits of agreements which ranged from 9.9% of energy intake (%EI) to -10.7%EI with the baseline RMRs and between 9.6%EI to -12.4%EI with the fixed RMR, indicated very large changes relative to the size of the average MIT response (MIT 1: 8.4%EI, 13.3%EI; MIT 2: 8.8%EI, 14.7%EI; baseline and fixed RMRs respectively). After just three hours, the between-day CV with the baseline RMR was 26%, which may indicate an enhanced MIT reproducibility with shorter measurement durations. On average, 76, 89, and 96% of the six-hour MIT response was completed within three, four and five hours, respectively. Strong correlations were found between MIT at each of these time points and the total six-hour MIT (range for correlations r = 0.990 to 0.998; P < 0.01). The reproducibility of the proportion of the six-hour MIT completed at 3, 4 and 5 hours was reproducible (between-day CVs ≤ 8.5%). This indicated the suitability to use shorter durations on repeated occasions and a similar percent of the total response to be completed. There was a lack of strong evidence of any relationship between the magnitude of the MIT response and subjective postprandial appetite. Given a six-hour protocol places a considerable burden on participants, these results suggests that a post-meal measurement period of only three hours is sufficient to produce valid information on the metabolic response to a meal. However while there was no mean change in MIT between test days, individual variability was large. Further research is required to better understand which factors best explain the between-day variability in this physiological measure. With such a high prevalence of obesity, dieting has become a necessity to reduce body weight. However, during periods of ER, metabolic and appetite adaptations can occur which may impede weight loss. Understanding how metabolic and appetite factors change during ER and weight loss is important for designing optimal weight loss protocols. The purpose of Study Two was to measure the changes in the MIT response and subjective postprandial appetite during either continuous (CONT) or intermittent (INT) ER and following post diet energy balance (post-diet EB). Thirty-six obese male participants were randomly assigned to either the CONT (Age = 38.6 ± 7.0 years, weight = 109.8 ± 9.2 kg, % fat mass = 38.2 ± 5.2%) or INT diet groups (Age = 39.1 ± 9.1 years, weight = 107.1 ± 12.5 kg, % fat mass = 39.6 ± 6.8%). The study was divided into three phases: a four-week baseline (BL) phase where participants were provided with a diet to maintain body weight, an ER phase lasting either 16 (CONT) or 30 (INT) weeks, where participants were provided with a diet which supplied 67% of their energy balance requirements to induce weight loss and an eight-week post-diet EB phase, providing a diet to maintain body weight post weight loss. The INT ER phase was delivered as eight, two-week blocks of ER interspersed with two-week blocks designed to achieve weight maintenance. Energy requirements for each phase were predicted based on measured RMR, and adjusted throughout the study to account for changes in RMR. All participants completed MIT and appetite tests during BL and the ER phase. Nine CONT and 15 INT participants completed the post-diet EB MIT and 14 INT and 15 CONT participants completed the post-diet EB appetite tests. The MIT test day protocol was as follows: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard breakfast meal (874 kcal, 53.3% CHO, 14.5% PRO, 32.2% FAT), and 3) three hours of measuring MIT. MIT was calculated as the energy expenditure above the pre-meal RMR. Appetite test days were undertaken on a separate day using the same 576 kcal breakfast used in Study One. VAS were used to assess appetite pre and post breakfast, at one hour post breakfast then a further three times at 45-minute intervals. Appetite ratings were calculated for hunger and fullness as both the intra-meal change in appetite and the AUC. The three-hour MIT response at BL, ER and post-diet EB respectively were 5.4 ± 1.4%EI, 5.1 ± 1.3%EI and 5.0 ± 0.8%EI for the CONT group and 4.4 ± 1.0%EI, 4.7 ± 1.0%EI and 4.8 ± 0.8%EI for the INT group. Compared to BL, neither group had significant changes in their MIT response during ER or post-diet EB. There were no significant time by group interactions (p = 0.17) indicating a similar response to ER and post-diet EB in both groups. Contrary to what was hypothesised, there was a significant increase in postprandial AUC fullness in response to ER in both groups (p < 0.05). However, there were no significant changes in any of the other postprandial hunger or fullness variables. Despite no changes in MIT in both the CONT or INT group in response to ER or post-diet EB and only a minor increase in postprandial AUC fullness, the individual changes in MIT and postprandial appetite in response to ER were large. However those with the greatest MIT changes did not have the greatest changes in postprandial appetite. This study shows that postprandial appetite and MIT are unlikely to be altered during ER and are unlikely to hinder weight loss. Additionally, there were no changes in MIT in response to weight loss, indicating that body weight did not influence the magnitude of the MIT response. There were large individual changes in both variables, however further research is required to determine whether these changes were real compensatory changes to ER or simply between-day variation. Overall, the results of this thesis add to the current literature by showing the large variability of continuous MIT measurements, which make it difficult to compare MIT between groups and in response to diet interventions. This thesis was able to provide evidence to suggest that shorter measures may provide equally valid information about the total MIT response and can therefore be utilised in future research in order to reduce the burden of long measurements durations. This thesis indicates that MIT and postprandial subjective appetite are most likely independent of each other. This thesis also shows that, on average, energy restriction was not associated with compensatory changes in MIT and postprandial appetite that would have impeded weight loss. However, the large inter-individual variability supports the need to examine individual responses in more detail.

Every One, Every Day

Creative Statement: “There are those who see Planet Earth as a gigantic living being, one that feeds and nurtures humanity and myriad other species – an entity that must be cared for. Then there are those who see it as a rock full of riches to be pilfered heedlessly in a short-term quest for over-abundance. This ‘cradle to grave’ mentality, it would seem, is taking its toll (unless you’re a virulent disbeliever in climate change). Why not, ask artists Priscilla Bracks and Gavin Sade, take a different approach? To this end they have set out on a near impossible task; to visualise the staggering quantity of carbon produced by Australia every year. Their eerie, glowing plastic cube resembles something straight out of Dr Who or The X Files. And, like the best science fiction, it has technical realities at its heart. Every One, Every Day tangibly illustrates our greenhouse gas output – its 27m3 volume is approximately the amount of green-house gas emitted per capita, daily. Every One, Every Dayis lit by an array of LED’s displaying light patterns representing energy use generated by data from the Australian Energy Market. Every One, Every Day was formed from recycled, polyethylene – used milk bottles – ‘lent’ to the artists by a Visy recycling facility. At the end of the Vivid Festival this plastic will be returned to Visy, where it will re-enter the stream of ‘technical nutrients.’ Could we make another world? One that emulates the continuing cycles of nature? One that uses our ‘technical nutrients’ such as plastic and steel in continual cycles, just like a deciduous tree dropping leaves to compost itself and keep it’s roots warm and moist?” (Ashleigh Crawford. Melbourne – April, 2013) Artistic Research Statement: The research focus of this work is on exploring how to represent complex statistics and data at a human scale, and how produce a work where a large percentage of the materials could be recycled. The surface of Every One, Every Day is clad in tiles made from polyethylene, from primarily recycled milk bottles, ‘lent’ to the artists by the Visy recycling facility in Sydney. The tiles will be returned to Visy for recycling. As such the work can be viewed as an intervention in the industrial ecology of polyethylene, and in the process demonstrates how to sustain cycles of technical materials – by taking the output of a recycling facility back to a manufacturer to produce usable materials. In terms of data visualisation, Every One, Every Day takes the form of a cube with a volume of 27 cubic meters. The annual per capita emissions figures for Australia are cited as ranging between 18 to 25 tons. Assuming the lower figure, 18tons per capital annually, the 27 cubic meters represents approximately one day per capita of CO2 emissions – where CO2 is a gas at 15C and 1 atmosphere of pressure. The work also explores real time data visualisation by using an array of 600 controllable LEDs inside the cube. Illumination patterns are derived from a real time data from the Australian Energy Market, using the dispatch interval price and demand graph for New South Wales. The two variables of demand and price are mapped to properties of the illumination - hue, brightness, movement, frequency etc. The research underpinning the project spanned industrial ecology to data visualization and public art practices. The result is that Every One, Every Day is one of the first public artworks that successfully bring together materials, physical form, and real time data representation in a unified whole.