Studies of the off-field behaviours of sportspeople : are sponsors' objectives at risk?

The research reported here addresses the problem of athlete off-field behaviours as they influence sports’ sponsors, particularly the achievement of sponsorship objectives. The question arises because of incidents of sponsorship contract cancellation following news-media reporting of athletes’ off-field behaviours. Two studies are used to investigate the research question; the first establishes the content of news-media reports, and the second tests the effects of news’ reports on athlete, team and sponsor evaluations using an experimental design. Key assumptions of the research are that sponsorship objectives are principally consumer-based and mediated. Models of sponsorship argue that sponsors aim to reach and influence consumers through sponsees. Assuming this pathway exists is central to sponsorship activities. A corollary is that other mediators, in this case the news-media, may also communicate (uncontrollable) messages such that a consumer audience may be told of negative news that may then be associated with the sponsor. When sponsors cancel contracts it is assumed that their goal is to control the links between their brand and a negative referent. Balance theory is used to discuss the potential effects of negative off-field behaviours of athletes on sponsor’s objectives. Heider’s balance theory (1958) explains that individuals prefer to evaluate linked individuals or entities consistently. In the sponsorship context this presents the possibility that a negative evaluation of the athlete’s behaviour will contribute to correspondingly negative evaluations of the athlete’s team and sponsors. A content analysis (Study 1) was used to survey the types of athlete off-field behaviours commonly reported in a newspaper. In order to provide a local context for the research, articles from the Courier Mail were sampled and teams in the National Rugby League (NRL) competition were the focus of the research. The study identified nearly 2000 articles referring to the NRL competition; 258 of those refer to off-field incidents involving athletes. The various types of behaviours reported include assault, sexual assault allegations, driving under the influence of alcohol, illicit drug use, breaches of club rules, and positive off-field activities (i.e., charitable activities). An experiment (Study 2) tested three news’ article stimuli developed from the behaviours identified in Study 1 in a between-subjects design. A measure of Identification with the Team was used as a covariate variable in the Multivariate Analysis of Covariance analysis. Social identity theory suggests that when an individual identifies with a group, their attitudes and behaviours towards both in- and out-group members are modified. Use of Identification with the Team as a covariate acknowledges that respondents will evaluate behaviours differently according to the attribution of those behaviours to an in- or out-group member. Findings of the research suggest that the news’ article stimuli have significant, large effects on evaluations of athlete off-field behaviour and athlete Likability. Consistent with pretest results, charitable fundraising is regarded as extremely positive; the athlete, correspondingly, is likable. Assault is evaluated as extremely negative, and the athlete as unlikable. DUI scores reveal that the athlete’s behaviour is very negative; however, the athlete’s likability was evaluated as neutral. Treatment group does not produce any significant effects on team or sponsor variables. This research also finds that Identification with the Team has significant, large effects on team variables (Attitude toward the Brand and Corporate Image). Identification also has a significant large effect on athlete Likability, but not on Attitude toward the Act. Identification with the Team does not produce any significant effects on sponsor variables. The results of this research suggest that sponsor’s consumer-based objectives are not threatened by newspaper reports linking athlete off-field behaviour with their brand. Evaluations of sponsor variables (Attitude toward the Sponsor’s Brand and Corporate Image) were consistently positive. Variance in that data, however, cannot be attributed to experimental stimuli or Identification with the Team. These results argue that respondents may regard sponsorships, in principle, as good. Although it is good news for sponsors that negative evaluations of athletes will not produce correspondingly negative evaluations of consumer-based sponsorship objectives, the results indicate problems for sponsorship managers. The failure of Identification with the Team to explain sponsor variable variance indicates that the sponsor has not been evaluated as a linked entity in a relationship with the sporting team and athlete in this research. This result argues that the sponsee-mediated affective communication path that sponsors aim use to communicate with desirable publics is not necessarily a path available to them.

The role of human capital in economic growth revisited

Benhabib and Spiegel (1994) examine the role of human capital in the development process empirically using a theory-driven specification rather than the standard production function approach. While they find evidence of a positive impact of human capital on income growth, their result is not robust to the inclusion of inequality as an additional covariate. Using an alternate dataset and different measures of inequality, we find robust support for the hypothesis that human capital matters even when we account for the adverse effect of income inequality on growth.

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

A flexible Bayesian model for describing temporal variability of N2O emissions from an Australian pasture

Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Differences in physical activity between black and white girls living in rural and urban areas

This study examined the relationship of race and rural/urban setting to physical, behavioral, psychosocial, and environmental factors associated with physical activity. Subjects included 1,668 eighth-grade girls from 31 middle schools: 933 from urban settings, and 735 from rural settings. Forty-six percent of urban girls and 59% of rural girls were Black. One-way and two-way ANOVAs with school as a covariate were used to analyze the data. Results indicated that most differences were associated with race rather than setting. Black girls were less active than White girls, reporting significantly fewer 30-minute blocks of both vigorous and moderate-to-vigorous physical activity. Black girls also spent more time watching television, and had higher BMIs and greater prevalence of overweight than White girls. However, enjoyment of physical education and family involvement in physical activity were greater among Black girls titan White girls. Rural White girls and urban Black girls had more favorable attitudes toward physical activity. Access to sports equipment, perceived safety of neighborhood, and physical activity self-efficacy were higher in White girls than Black girls.

Using the Gini coefficient with BIOLOG substrate utilisation data to provide an alternative quantitative measure for comparing bacterial soil communities

A measure quantifying unequal use of carbon sources, the Gini coefficient (G), has been developed to allow comparisons of the observed functional diversity of bacterial soil communities. This approach was applied to the analysis of substrate utilisation data obtained from using BIOLOG microtiter plates in a study which compared decomposition processes in two contrasting plant substrates in two different soils. The relevance of applying the Gini coefficient as a measure of observed functional diversity, for soil bacterial communities is evaluated against the Shannon index (H) and average well colour development (AWCD), a measure of the total microbial activity. Correlation analysis and analysis of variance of the experimental data show that the Gini coefficient, the Shannon index and AWCD provided similar information when used in isolation. However, analyses based on the Gini coefficient and the Shannon index, when total activity on the microtiter plates was maintained constant (i.e. AWCD as a covariate), indicate that additional information about the distribution of carbon sources being utilised can be obtained. We demonstrate that the Lorenz curve and its measure of inequality, the Gini coefficient, provides not only comparable information to AWCD and the Shannon index but when used together with AWCD encompasses measures of total microbial activity and absorbance inequality across all the carbon sources. This information is especially relevant for comparing the observed functional diversity of soil microbial communities.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

The effect of previous hamstring strain injuries on the change in eccentric hamstring strength during preseason training in elite Australian footballers

Background Hamstring strain injuries (HSIs) are the most common injury type in Australian football and the rate of recurrence has been consistently high for a number of years. Long lasting neuromuscular inhibition has been noted in previously injured athletes but it is not known if this influences athletes adaptive response to training. Purpose To determine if elite Australian footballers with a prior unilateral HSI (previously injured group) display lesser improvements in eccentric hamstring strength during pre-season training compared to athletes without a history of HSI (control group). Study design Prospective cohort study. Methods Ninety-nine elite Australian footballers participated (17 with a history of unilateral HSI in the previous 12 month period). Eccentric hamstring strength was assessed at the start and end of pre-season training using an instrumented Nordic hamstring device. Change in eccentric strength across preseason was determine in absolute terms and normalised to start of preseason strength. Start of preseason strength was used as a covariate to control for differences in starting strength. Results The left and right limbs in the control group showed no difference in absolute or relative change (left limb absolute change, 60.7±72.9N; relative change, 1.28±0.34; right limb absolute change, 48.6±83.8N; relative change, 1.24±0.43) . Similarly, the injured and uninjured limbs from the previously injured group showed no difference for either absolute or relative measures of change (injured limb absolute change, 13.1±57.7N; relative change, 1.07±0.18; uninjured limb absolute change, 14.7±54.0N; relative change, 1.07±0.22N). The previously injured group displayed a significantly lesser increase in eccentric hamstring strength across the preseason (absolute change, 13.9±55.0; relative change, 1.07±0.20) compared to the control group (absolute change, 54.6±78.5; relative change, 1.26±0.39) for both absolute and relative measures (p < 0.001), even after controlling for differences in start of pre-season eccentric hamstring strength, which had a significant effect on strength improvement. Conclusion Elite Australian footballers with a unilateral HSI history displayed lesser improvements in eccentric hamstring strength across preseason training. The smaller improvements were not restricted to the previously injured limb as the contralateral limb also displayed similarly small improvements in eccentric strength. Whether this is the cause of or the result of injury remains to be seen, but it has the potential to contribute to the risk of hamstring strain re-injury.

The prolongation of length of stay because of Clostridium difficile infection

Background Clostridium difficile infection (CDI) possibly extends hospital length of stay (LOS); however, the current evidence does not account for the time-dependent bias, ie, when infection is incorrectly analyzed as a baseline covariate. The aim of this study was to determine whether CDI increases LOS after managing this bias. Methods We examined the estimated extra LOS because of CDI using a multistate model. Data from all persons hospitalized >48 hours over 4 years in a tertiary hospital in Australia were analyzed. Persons with health care-associated CDIs were identified. Cox proportional hazards models were applied together with multistate modeling. Results One hundred fifty-eight of 58,942 admissions examined had CDI. The mean extra LOS because of infection was 0.9 days (95% confidence interval: −1.8 to 3.6 days, P = .51) when a multistate model was applied. The hazard of discharge was lower in persons who had CDI (adjusted hazard ratio, 0.42; P < .001) when a Cox proportional hazard model was applied. Conclusion This study is the first to use multistate models to determine the extra LOS because of CDI. Results suggest CDI does not significantly contribute to hospital LOS, contradicting findings published elsewhere. Conversely, when methods prone to result in time-dependent bias were applied to the data, the hazard of discharge significantly increased. These findings contribute to discussion on methods used to evaluate LOS and health care-associated infections.

Adult total wellness: group differences based on sitting time and physical activity level

Background An increasing body of evidence associates a high level of sitting time with poor health outcomes. The benefits of moderate to vigorous-intensity physical activities to various aspects of health are now well documented; however, individuals may engage in moderate-intensity physical activity for at least 30 minutes on five or more days of the week and still exhibit a high level of sitting time. This purpose of this study was to examine differences in total wellness among adults relative to high/low levels of sitting time combined with insufficient/sufficient physical activity (PA). The construct of total wellness incorporates a holistic approach to the body, mind and spirit components of life, an approach which may be more encompassing than some definitions of health. Methods Data were obtained from 226 adult respondents (27 ± 6 years), including 116 (51%) males and 110 (49%) females. Total PA and total sitting time were assessed with the International Physical Activity Questionnaire (IPAQ) (short-version). The Wellness Evaluation of Lifestyle Inventory was used to assess total wellness. An analysis of covariance (ANCOVA) was utilised to assess the effects of the sitting time/physical activity group on total wellness. A covariate was included to partial out the effects of age, sex and work status (student or employed). Cross-tabulations were used to show associations between the IPAQ derived high/low levels of sitting time with insufficient/sufficient PA and the three total wellness groups (i.e. high level of wellness, moderate wellness and wellness development needed). Results The majority of the participants were located in the high total sitting time and sufficient PA group. There were statistical differences among the IPAQ groups for total wellness [F (2,220) = 32.5 (p <0.001)]. A Chi-square test revealed a significant difference in the distribution of the IPAQ categories within the classification of wellness [χ2 (N = 226) = 54.5, p < .001]. One-hundred percent (100%) of participants who self-rated as high total sitting time/insufficient PA were found in the wellness development needed group. In contrast, 72% of participants who were located in the low total sitting time/sufficient PA group were situated in the moderate wellness group. Conclusion Many participants who meet the physical activity guidelines, in this sample, sit for longer periods of time than the median Australian sitting time. An understanding of the effects of the enhanced PA and reduced sitting time on total wellness can add to the development of public health initiatives. Keywords: IPAQ; The Wellness Evaluation of Lifestyle (WEL); Sedentary lifestyle

Serum vitamin D levels are lower in Australian children and adolescents with type 1 diabetes than in children without diabetes

Vitamin D is synthesised in the skin through the action of UVB radiation (sunlight), and 25-hydroxy vitamin D (25OHD) measured in serum as a marker of vitamin D status. Several studies, mostly conducted in high latitudes, have shown an association between type 1 diabetes mellitus (T1DM) and low serum 25OHD. We conducted a case-control study to determine whether, in a sub-tropical environment with abundant sunlight (latitude 27.5°S), children with T1DM have lower serum vitamin D than children without diabetes. Fifty-six children with T1DM (14 newly diagnosed) and 46 unrelated control children participated in the study. Serum 25OHD, 1,25-dihydroxy vitamin D (1,25(OH)2D) and selected biochemical indices were measured. Vitamin D receptor (VDR) polymorphisms Taq1, Fok1, and Apa1 were genotyped. Fitzpatrick skin classification, self-reported daily hours of outdoor exposure, and mean UV index over the 35d prior to blood collection were recorded. Serum 25OHD was lower in children with T1DM (n=56) than in controls (n=46) [mean (95%CI)=78.7 (71.8-85.6) nmol/L vs. 91.4 (83.5-98.7) nmol/L, p=0.02]. T1DM children had lower self-reported outdoor exposure and mean UV exposure, but no significant difference in distribution of VDR polymorphisms. 25OHD remained lower in children with T1DM after covariate adjustment. Children newly diagnosed with T1DM had lower 1,25(OH)2D [median (IQR)=89 (68-122) pmol/L] than controls [121 (108-159) pmol/L, p=0.03], or children with established diabetes [137 (113-153) pmol/L, p=0.01]. Children with T1DM have lower 25OHD than controls, even in an environment of abundant sunlight. Whether low vitamin D is a risk factor or consequence of T1DM is unknown. © 2012 John Wiley & Sons A/S.

Common variants in the region around Osterix are associated with bone mineral density and growth in childhood

Peak bone mass achieved in adolescence is a determinant of bone mass in later life. In order to identify genetic variants affecting bone mineral density (BMD), we performed a genome-wide association study of BMD and related traits in 1518 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). We compared results with a scan of 134 adults with high or low hip BMD. We identified associations with BMD in an area of chromosome 12 containing the Osterix (SP7) locus, a transcription factor responsible for regulating osteoblast differentiation (ALSPAC: P = 5.8 × 10-4; Australia: P = 3.7 × 10-4). This region has previously shown evidence of association with adult hip and lumbar spine BMD in an Icelandic population, as well as nominal association in a UK population. A meta-analysis of these existing studies revealed strong association between SNPs in the Osterix region and adult lumbar spine BMD (P = 9.9 × 10-11). In light of these findings, we genotyped a further 3692 individuals from ALSPAC who had whole body BMD and confirmed the association in children as well (P = 5.4 × 10-5). Moreover, all SNPs were related to height in ALSPAC children, but not weight or body mass index, and when height was included as a covariate in the regression equation, the association with total body BMD was attenuated. We conclude that genetic variants in the region of Osterix are associated with BMD in children and adults probably through primary effects on growth.

Site and gender specificity of inheritance of bone mineral density

Differences in genetic control of BMD by skeletal sites and genders were examined by complex segregation analysis in 816 members of 147 families with probands with extreme low BMD. Spine BMD correlated more strongly in male-male comparisons and hip BMD in female-female comparisons, consistent with gender- and site-specificity of BMD heritability. Introduction: Evidence from studies in animals and humans suggests that the genetic control of bone mineral density (BMD) may differ at different skeletal sites and between genders. This question has important implications for the design and interpretation of genetic studies of osteoporosis. Methods: We examined the genetic profile of 147 families with 816 individuals recruited through probands with extreme low BMD (T-score < −2.5, Z-score < −2.0). Complex segregation analysis was performed using the Pedigree Analysis Package. BMD was measured by DXA at both lumbar spine (L1-L4) and femoral neck. Results: Complex segregation analysis excluded purely monogenic and environmental models of segregation of lumbar spine and femoral neck BMD in these families. Pure polygenic models were excluded at the lumbar spine when menopausal status was considered as a covariate, but not at the femoral neck. Mendelian models with a residual polygenic component were not excluded. These models were consistent with the presence of a rare Mendelian genotype of prevalence 3–19 %, causing high BMD at the hip and spine in these families, with additional polygenic effects. Total heritability range at the lumbar spine was 61–67 % and at the femoral neck was 44–67 %. Significant differences in correlation of femoral neck and lumbar spine BMD were observed between male and female relative pairs, with male-male comparisons exhibiting stronger lumbar spine BMD correlation than femoral neck, and female-female comparisons having greater femoral neck BMD correlation than lumbar spine. These findings remained true for parent-offspring correlations when menopausal status was taken into account. The recurrence risk ratio for siblings of probands of a Z-score < −2.0 was 5.4 at the lumbar spine and 5.9 at the femoral neck. Conclusions: These findings support gender- and site-specificity of the inheritance of BMD. These results should be considered in the design and interpretation of genetic studies of osteoporosis.