How does socio economic position link to health behaviour? Sociological pathways and perspectives for health promotion

Socio economic inequalities in adult health behaviour are consistently observed. Despite a well-documented pattern, social determinants of variations in health behaviour have not been sufficiently clarified. This article therefore presents sociological pathways to explain the existing inequalities in health behaviour. At a micro level, control beliefs have been part of several behavioural theories. We suggest that these beliefs might bridge the gap between sociology and psychology by emphasising their roots in fundamental socio-economic environments. At a meso level, social networks and support have not been explicitly considered as behavioural determinants. This contribution states that these social factors influence health behaviour while being unequally distributed across society. At a macro level, characteristics of the neighbourhood environment influence health behaviour of its residents above and beyond their individual background. Providing further opportunity for policy makers, it is shown that peer and school context equalise inequalities in risky behaviour in adolescence. As a conclusion, factors such as control expectations, social networks, neighbourhood characteristics, and school context should be included as strategies to improve health behaviour in socially disadvantaged people.

Predictors of surgical, general and follow-up complications in lumbar spinal stenosis relative to patient age as emerged from the Spine Tango Registry

Published opinions regarding the outcomes and complications in older patients have a broad spectrum and there is a disagreement whether surgery in older patients entails a higher risk. Therefore this study examines the risk of surgery for lumbar spinal stenosis relative to age in the pooled data set of the Spine Tango registry.

Delayed dispersal as a potential route to cooperative breeding in ambrosia beetles

Abstract  Xyleborini are a species-rich tribe of ambrosia beetles, which are haplodiploid and typically mate among siblings within their natal brood chamber. Several characteristics of this tribe would predict the evolution of higher levels of sociality: high genetic relatedness within galleries due to inbreeding, high costs of dispersal and the potential benefit of cooperation in brood care within the natal gallery (e.g. by fungus gardening, gallery extension, offspring feeding and cleaning). However, information on the social system of these beetles is very limited. We examined the potential for cooperative breeding in Xyleborinus saxeseni by monitoring dispersal in relation to brood size and composition. Results show that adult female offspring delay dispersal despite dispersal opportunities, and apparently some females never disperse. The femalesâ?? decision to stay seems to depend on the presence of eggs and dependent siblings. We found no indication that female offspring reproduce in their natal gallery, as colonies with many mature daughters do not contain more eggs than those with few or no daughters. There is a significant positive relationship between the number of females present and the number of dependent siblings (but not eggs), which suggests that cooperative brood care of female offspring raises colony productivity by improving survival rates of immatures. Our results suggest that cooperative breeding is likely to occur in X. saxeseni and possibly other xyleborine species. We argue that a closer look at sociality within this tribe may yield important information on the factors determining the evolution of cooperative breeding and advanced social organization.

AccessMod 3.0: computing geographic coverage and accessibility to health care services using anisotropic movement of patients

Background Access to health care can be described along four dimensions: geographic accessibility, availability, financial accessibility and acceptability. Geographic accessibility measures how physically accessible resources are for the population, while availability reflects what resources are available and in what amount. Combining these two types of measure into a single index provides a measure of geographic (or spatial) coverage, which is an important measure for assessing the degree of accessibility of a health care network. Results This paper describes the latest version of AccessMod, an extension to the Geographical Information System ArcView 3.×, and provides an example of application of this tool. AccessMod 3 allows one to compute geographic coverage to health care using terrain information and population distribution. Four major types of analysis are available in AccessMod: (1) modeling the coverage of catchment areas linked to an existing health facility network based on travel time, to provide a measure of physical accessibility to health care; (2) modeling geographic coverage according to the availability of services; (3) projecting the coverage of a scaling-up of an existing network; (4) providing information for cost effectiveness analysis when little information about the existing network is available. In addition to integrating travelling time, population distribution and the population coverage capacity specific to each health facility in the network, AccessMod can incorporate the influence of landscape components (e.g. topography, river and road networks, vegetation) that impact travelling time to and from facilities. Topographical constraints can be taken into account through an anisotropic analysis that considers the direction of movement. We provide an example of the application of AccessMod in the southern part of Malawi that shows the influences of the landscape constraints and of the modes of transportation on geographic coverage. Conclusion By incorporating the demand (population) and the supply (capacities of heath care centers), AccessMod provides a unifying tool to efficiently assess the geographic coverage of a network of health care facilities. This tool should be of particular interest to developing countries that have a relatively good geographic information on population distribution, terrain, and health facility locations.