Intrinsic factors associated with medial tibial stress syndrome in athletes: A large case-control study

Background. Medial tibial stress syndrome (MTSS) is the most common lower-leg injury in athletes, and is thought to be caused by bony overload. To prevent MTSS, both pathophysiological and aetiological factors specific to MTSS need to be identified. The intrinsic risk factors that contribute to the development of MTSS are still uncertain.Objective. To determine the intrinsic risk factors of MTSS by sampling a large population of athletic MTSS patients and controls.Methods. Athletes with MTSS and control subjects were medically examined in terms of range of motion of the leg joints (hip abduction, adduction, internal and external range of motion; ankle plantar and dorsal flexion; hallux extension and flexion; subtalar inversion and eversion), measures of over-pronation and maximal calf girth.Results. Ninety-seven subjects agreed to participate in the study: 48 MTSS patients and 49 active controls. The following variables were considered: gender, age, body mass index (BMI), hip abduction, hip adduction, internal and external hip range of rotation, ankle plantar and dorsal flexion, hallux flexion and extension, subtalar inversion and eversion, maximal calf girth, standing foot angle and navicular drop test. In multivariate logistic regression analysis, hip abduction (odds ratio (OR) 0.82; 95% confidence interval (CI) 0.72 - 0.94), ankle plantar flexion (OR 0.73; 95% CI 0.61 - 0.87) and subtalar inversion (OR 1.24; 95% CI 1.10 - 1.41) were significantly associated with MTSS. The Nagelkerke R2 for this model was 0.76, indicating that 76% of the variance in the presence of MTSS could be explained by these variables.Conclusion. Decreased hip abduction, decreased ankle plantar flexion and an increased subtalar inversion could be considered risk factors for MTSS

Nestedness of Ectoparasite-Vertebrate Host Networks

Determining the structure of ectoparasite-host networks will enable disease ecologists to better understand and predict the spread of vector-borne diseases. If these networks have consistent properties, then studying the structure of well-understood networks could lead to extrapolation of these properties to others, including those that support emerging pathogens. Borrowing a quantitative measure of network structure from studies of mutualistic relationships between plants and their pollinators, we analyzed 29 ectoparasite-vertebrate host networks—including three derived from molecular bloodmeal analysis of mosquito feeding patterns—using measures of nestedness to identify non-random interactions among species. We found significant nestedness in ectoparasite-vertebrate host lists for habitats ranging from tropical rainforests to polar environments. These networks showed non-random patterns of nesting, and did not differ significantly from published estimates of nestedness from mutualistic networks. Mutualistic and antagonistic networks appear to be organized similarly, with generalized ectoparasites interacting with hosts that attract many ectoparasites and more specialized ectoparasites usually interacting with these same “generalized” hosts. This finding has implications for understanding the network dynamics of vector-born pathogens. We suggest that nestedness (rather than random ectoparasite-host associations) can allow rapid transfer of pathogens throughout a network, and expand upon such concepts as the dilution effect, bridge vectors, and host switching in the context of nested ectoparasite-vertebrate host networks

Optimal foraging and community structure: implications for a guild of generalist grassland herbivores

A particular linear programming model is constructed to predict the diets of each of 14 species of generalist herbivores at the National Bison Range, Montana. The herbivores have body masses ranging over seven orders of magnitude and belonging to two major taxa: insects and mammals. The linear programming model has three feeding constraints: digestive capacity, feeding time and energy requirements. A foraging strategy that maximizes daily energy intake agrees very well with the observed diets. Body size appears to be an underlying determinant of the foraging parameters leading to diet selection. Species that possess digestive capacity and feeding time constraints which approach each other in magnitude have the most generalized diets. The degree that the linear programming models change their diet predictions with a given percent change in parameter values (sensitivity) may reflect the observed ability of the species to vary their diets. In particular, the species which show the most diet variability are those whose diets tend to be balanced between monocots and dicots. The community-ecological parameters of herbivore body-size ranges and species number can possibly be related to foraging behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47765/1/442_2004_Article_BF00377109.pd

What makes for a good job? Evidence using subjective wellbeing data

We study what makes for a good job, by looking at which workplace characteristics are conducive or detrimental to job satisfaction. Using data from 37 countries around the world in the 2015 Work Orientations module of the International Social Survey Programme, we find that having an interesting job and good relationships at work, especially with management, are the strongest positive predictors of how satisfied employees are with their jobs, along with wages. Stressful or dangerous jobs, as well as those that interfere with family life, have the strongest negative correlation with job satisfaction. We discuss implications for firms and other organisations as well as for public policy-makers, and point toward future avenues for research in the area