Location of residence associated with the likelihood of patient visit to the preoperative assessment clinic

BACKGROUND: Outpatient preoperative assessment clinics were developed to provide an efficient assessment of surgical patients prior to surgery, and have demonstrated benefits to patients and the health care system. However, the centralization of preoperative assessment clinics may introduce geographical barriers to utilization that are dependent on where a patient lives with respect to the location of the preoperative assessment clinic. METHODS: The association between geographical distance from a patient's place of residence to the preoperative assessment clinic, and the likelihood of a patient visit to the clinic prior to surgery, was assessed for all patients undergoing surgery at a tertiary health care centre in a major Canadian city. The odds of attending the preoperative clinic were adjusted for patient characteristics and clinical factors. RESULTS: Patients were less likely to visit the preoperative assessment clinic prior to surgery as distance from the patient's place of residence to the clinic increased (adjusted OR = 0.52, 95% CI 0.44–0.63 for distances between 50–100 km, and OR = 0.26, 95% CI 0.21–0.31 for distances greater than 250 km). This 'distance decay' effect was remarkable for all surgical specialties. CONCLUSION: The present study demonstrates that the likelihood of a patient visiting the preoperative assessment clinic appears to depend on the geographical location of patients' residences. Patients who live closest to the clinic tend to be seen more often than patients who live in rural and remote areas. This observation may have implications for achieving the goals of equitable access, and optimal patient care and resource utilization in a single universal insurer health care system

Under-Five Mortality in High Focus States in India: A District Level Geospatial Analysis

<div><h3>Background</h3><p>This paper examines if, when controlling for biophysical and geographical variables (including rainfall, productivity of agricultural lands, topography/temperature, and market access through road networks), socioeconomic and health care indicators help to explain variations in the under-five mortality rate across districts from nine high focus states in India. The literature on this subject is inconclusive because the survey data, upon which most studies of child mortality rely, rarely include variables that measure these factors. This paper introduces these variables into an analysis of 284 districts from nine high focus states in India.</p> <h3>Methodology/Principal Findings</h3><p>Information on the mortality indicator was accessed from the recently conducted Annual Health Survey of 2011 and other socioeconomic and geographic variables from Census 2011, District Level Household and Facility Survey (2007–08), Department of Economics and Statistics Divisions of the concerned states. Displaying high spatial dependence (spatial autocorrelation) in the mortality indicator (outcome variable) and its possible predictors used in the analysis, the paper uses the Spatial-Error Model in an effort to negate or reduce the spatial dependence in model parameters. The results evince that the coverage gap index (a mixed indicator of district wise coverage of reproductive and child health services), female literacy, urbanization, economic status, the number of newborn care provided in Primary Health Centers in the district transpired as significant correlates of under-five mortality in the nine high focus states in India. The study identifies three clusters with high under-five mortality rate including 30 districts, and advocates urgent attention.</p> <h3>Conclusion</h3><p>Even after controlling the possible biophysical and geographical variables, the study reveals that the health program initiatives have a major role to play in reducing under-five mortality rate in the high focus states in India.</p> </div

Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods

Gibbons CL, Mangen M-JJ, Plaß D, et al. Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods. BMC Public Health. 2014;14(1): 147.Background: Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true' incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting. Methods: Within the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens. Results: MFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-,country-, age-, and sex-specific. Conclusions: When routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence

The evolution of Müllerian mimicry

It is now 130 years since Fritz Müller proposed an evolutionary explanation for the close similarity of co-existing unpalatable prey species, a phenomenon now known as Müllerian mimicry. Müller’s hypothesis was that unpalatable species evolve a similar appearance to reduce the mortality involved in training predators to avoid them, and he backed up his arguments with a mathematical model in which predators attack a fixed number (n) of each distinct unpalatable type in a given season before avoiding them. Here, I review what has since been discovered about Müllerian mimicry and consider in particular its relationship to other forms of mimicry. Müller’s specific model of associative learning involving a “fixed n” in a given season has not been supported, and several experiments now suggest that two distinct unpalatable prey types may be just as easy to learn to avoid as one. Nevertheless, Müller’s general insight that novel unpalatable forms have higher mortality than common unpalatable forms as a result of predation has been well supported by field experiments. From its inception, there has been a heated debate over the nature of the relationship between Müllerian co-mimics that differ in their level of defence. There is now a growing awareness that this relationship can be mediated by many factors, including synergistic effects between co-mimics that differ in their mode of defence, rates of generalisation among warning signals and concomitant changes in prey density as mimicry evolves. I highlight areas for future enquiry, including the possibility of Müllerian mimicry systems based on profitability rather than unprofitability and the co-evolution of defence

The response of plant community diversity to alien invasion: evidence from a sand dune time series

This study examines the process of invasion of coastal dunes in north-eastern Italy along a 60-year time series considering alien attributes (origin, residence time, invasive status, and growth form strategy) and habitat properties (species richness, diversity and evenness, proportion of aliens, and proportion of focal species). Vegetation changes through time were investigated in four sandy coastal habitats, using a fine-scale diachronic approach that compared vegetation data collected by use of the same procedure, in four time periods, from the 1950s to 2011. Our analysis revealed an overall significant decline of species richness over the last six decades. Further, both the average number of species per plot and the mean focal species proportion were proved to be negatively affected by the increasing proportion of alien species at plot level. The severity of the impact, however, was found to be determined by a combination of species attributes, habitat properties, and human disturbance suggesting that alien species should be referred to as ‘‘passengers’’ and not as ‘‘drivers’’ of ecosystem change. Passenger alien species are those which take advantage of disturbances or other changes to which they are adapted but that lead to a decline in native biodiversity. Their spread is facilitated by widespread anthropogenic environmental alterations, which create new, suitable habitats, and ensure human-assisted dispersal, reducing the distinctiveness of plant communities and inducing a process of biotic homogenization

MC1R Genotype and Plumage Colouration in the Zebra Finch (Taeniopygia guttata): Population Structure Generates Artefactual Associations

Hoffman J, Krause ET, Lehmann K, Krüger O. MC1R Genotype and Plumage Colouration in the Zebra Finch (Taeniopygia guttata): Population Structure Generates Artefactual Associations. PLoS ONE. 2014;9(1): e86519.Polymorphisms at the melanocortin-1 receptor (MC1R) gene have been linked to coloration in many vertebrate species. However, the potentially confounding influence of population structure has rarely been controlled for. We explored the role of the MC1R in a model avian system by sequencing the coding region in 162 zebra finches comprising 79 wild type and 83 white individuals from five stocks. Allelic counts differed significantly between the two plumage morphs at multiple segregating sites, but these were mostly synonymous. To provide a control, the birds were genotyped at eight microsatellites and subjected to Bayesian cluster analysis, revealing two distinct groups. We therefore crossed wild type with white individuals and backcrossed the F1s with white birds. No significant associations were detected in the resulting offspring, suggesting that our original findings were a byproduct of genome-wide divergence. Our results are consistent with a previous study that found no association between MC1R polymorphism and plumage coloration in leaf warblers. They also contribute towards a growing body of evidence suggesting that care should be taken to quantify, and where necessary control for, population structure in association studie