Measuring Intermediary Determinants of Early Childhood Health: A Composite Index Comparing Colombian Departments

In recent years there has been growing interest in composite indicators as an efficient tool of analysis and a method of prioritizing policies. This paper presents a composite index of intermediary determinants of child health using a multivariate statistical approach. The index shows how specific determinants of child health vary across Colombian departments (administrative subdivisions). We used data collected from the 2010 Colombian Demographic and Health Survey (DHS) for 32 departments and the capital city, Bogotá. Adapting the conceptual framework of Commission on Social Determinants of Health (CSDH), five dimensions related to child health are represented in the index: material circumstances, behavioural factors, psychosocial factors, biological factors and the health system. In order to generate the weight of the variables, and taking into account the discrete nature of the data, principal component analysis (PCA) using polychoric correlations was employed in constructing the index. From this method five principal components were selected. The index was estimated using a weighted average of the retained components. A hierarchical cluster analysis was also carried out. The results show that the biggest differences in intermediary determinants of child health are associated with health care before and during delivery.

Measuring early childhood health : a composite index comparing Colombian departments

This paper presents a composite index of early childhood health using a multivariate statistical approach. The index shows how child health varies across Colombian departments, -administrative subdivisions-. In recent years there has been growing interest in composite indicators as an efficient analysis tool and a way of prioritizing policies. These indicators not only enable multi-dimensional phenomena to be simplified but also make it easier to measure, visualize, monitor and compare a country’s performance in particular issues. We used data collected from the Colombian Demographic and Health Survey, DHS, for 32 departments and the capital city, Bogotá, in 2005 and 2010. The variables included in the index provide a measure of three dimensions related to child health: health status, health determinants and the health system. In order to generate the weight of the variables and take into account the discrete nature of the data, we employed a principal component analysis, PCA, using polychoric correlation. From this method, five principal components were selected. The index was estimated using a weighted average of the components retained. A hierarchical cluster analysis was also carried out. We observed that the departments ranking in the lowest positions are located on the Colombian periphery. They are departments with low per capita incomes and they present critical social indicators. The results suggest that the regional disparities in child health may be associated with differences in parental characteristics, household conditions and economic development levels, which makes clear the importance of context in the study of child health in Colombia.

The unfathomable secret remains: a reverse engineering study of SEO factors on Google's search engine

The vast majority of users don’t seek results beyond the second page offered by the search engine, so if a site fails to be among the top 20 (second page), it says that this page does not have good SEO and, therefore, is not visible to the user. The overall objective of this project is to conduct a study to discover the factors that determine (or not) the positioning of websites in a search engine.

Approximation to the theory of affinities to manage the problems of the groupping process

New economic and enterprise needs have increased the interest and utility of the methods of the grouping process based on the theory of uncertainty. A fuzzy grouping (clustering) process is a key phase of knowledge acquisition and reduction complexity regarding different groups of objects. Here, we considered some elements of the theory of affinities and uncertain pretopology that form a significant support tool for a fuzzy clustering process. A Galois lattice is introduced in order to provide a clearer vision of the results. We made an homogeneous grouping process of the economic regions of Russian Federation and Ukraine. The obtained results gave us a large panorama of a regional economic situation of two countries as well as the key guidelines for the decision-making. The mathematical method is very sensible to any changes the regional economy can have. We gave an alternative method of the grouping process under uncertainty.

Functional diversity of macrophyte communities within and between Pyrenean lakes

Submersed vegetation is a common feature in about 70% Pyrene an high mountain (>1500 m a.s.l.) lakes. Isoetids and soft-water elodeids are common elements of this underw ater flora and can form distinct vegetation units (i.e. patches of vegetation dominated by different species) within complex mosaics of vegetation in shallow waters (<7 m). Since is oetids exert a strong influence on sediment biogeochemistry due to high radial oxygen loss, we examined the small scale characteristics of the lake environment (water and sediment) associated to vegetation patches in order to ascertain potential functional differences among them. To do so, we characterised the species composition and biomass of the main vegetation units from 11 lakes, defined plant communities based on biomass data, and then related each community with sediment properties (redox and dissolved nutrient concentration in the pore water) and water nutrient concentration within plant canopy. We also characterised lake water and sediment in areas without vegetation as a reference. A total of twenty-one vegetation units were identified, ranging from one to five per lake. A cluster analysis on biomass species composition suggested seven different macrophyte communities that were named after the most dominant species:Nitella sp.,Potamogeton praelongus, Myriophyllum alterniflorum, Sparganium angustifolium , Isoetes echinospora,Isoetes lacustris and Carex rostrata . Coupling between macrophyte communities and their immediate environment (overlying water and sediment) was manifested mainly as variation in sediment redox conditions and the dominant form of inorganic nitrogen in pore-water. These effects depended on the specific compositi on of the community, and on the allocation between above- and belowground biomass, and could be predicted with a model relating the average and standard deviation of sediment redox potential from 0 down to -20 cm, across macrophyte communities. Differences in pore-water total dissolved phosphorus were related to the trophic state of the lakes. There was no correlation between sediment and water column dissolved nutrients. However, nitrate concentrations tended to be lower in the water overlaying isoetid communities, in apparent contradiction to the patterns of dissolved nitrates in the pore-water. These tendencies were robust even when comparing the water over laying communities within the same lake, thus pointing towards a potential effect of isoetids in reducing dissolved nitrogen in the lakes.

Environmental factors, spatial variation, and specific requirements of Chironomidae in Mediterranean reference streams

Chironomidae spatial distribution was investigated at 63 near-pristine sites in 22 catchments of the Iberian Mediterranean coast. We used partial redundancy analysis to study Chironomidae community responses to a number of environmental factors acting at several spatial scales. The percentage of variation explained by local factors (23.3%) was higher than that explained by geographical (8.5%) or regional factors(8%). Catchment area, longitude, pH, % siliceous rocks in the catchment, and altitude were the best predictors of Chironomidae assemblages. We used a k-means cluster analysis to classified sites into 3 major groups based on Chironomidae assemblages. These groups were explained mainly by longitudinal zonation and geographical position, and were defined as 1) siliceous headwater streams, 2) mid-altitude streams with small catchment areas, and 3) medium-sized calcareous streams. Distinct species assemblages with associated indicator taxa were established for each stream category using IndVal analysis. Species responses to previously identified key environmental variables were determined, and optima and tolerances were established by weighted average regression. Distinct ecological requirements were observed among genera and among species of the same genus. Some genera were restricted to headwater systems (e.g., Diamesa), whereas others (e.g., Eukiefferiella) had wider ecological preferences but with distinct distributions among congenerics. In the present period of climate change, optima and tolerances of species might be a useful tool to predict responses of different species to changes in significant environmental variables, such as temperature and hydrology.