Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

Oral health of the elderly with Alzheimer's disease

Objective: The objective of this study was to describe the oral health of elderly people diagnosed with Alzheimer's disease (AD). Study Design: Thirty elderly subjects with AD (mild, moderate, and severe) and 30 without AD (controls) were included in the study. Volunteer-reported oral health data were collected using the General Oral Health Assessment Index (GOHAI). Demographic and oral characteristics were assessed, including the number of natural teeth; number of decayed, missing, and filled teeth (DMTF); oral health index (OHI); removable prosthesis conditions; and oral pathologies. Results: GOHAI values were similar for both groups. Compared with the controls, the subjects with AD had a higher age, DMTF, OHI, and number of oral pathologies and a lower educational level and number of natural teeth. Conclusions: Elderly subjects with AD had poorer oral health than those without the disease. Despite the positive self-perception of their oral health, the oral health of subjects with AD tended to decline as their disease progressed. © 2012 Elsevier Inc.

Reform to health system financing in Chile

Includes bibliography

Comparison of methods in oral health education from the perspective of adolescents.

To investigate whether teenagers' knowledge about oral health is influenced by educational methods and to verify the most effective method according to their perception. The study was performed in Araçatuba, São Paulo State, Brazil, with 127 teenagers from a vocational school. It was realised in 3 steps: 1. An evaluation of knowledge about oral health using a self-applied questionnaire. 2. An application of educational methods, where the students were divided into two groups (A and B). Group A participated in three educational activities that involved lectures, individual demonstration, and participatory activity. Group B was divided into three subgroups (B1, B2, B3) and each of them participated in only one of the methods. 3. The acquired knowledge was evaluated. Group A created a focus group to give their opinion about strategies. With regards to knowledge after the application of the different methods in all groups, there was a statistically significant difference concerning periodontitis, gingivitis and herpes. In group A, after the three activities, and in group B2 after the individual demonstration, an association was found between 'healthy teeth' and 'general health' (P = 0.004 and P = 0.022, respectively). After the individual demonstration, an association was shown between variables of acquired knowledge about 'harmful diet' and 'dental caries' (P = 0.002) as well as 'good diet' and 'prevention of oral diseases' (P = 0.032). The favourite method was individual demonstration, due to the contact with educational materials, followed by participatory activity because it encouraged learning in a more dynamic way. Educational methods influenced knowledge about oral health, with individual demonstration proving to be the most effective method for acquiring knowledge. In the adolescents' view, the participatory activity was the preferred method.

Right to health in Latin America: beyond universalization

Incluye bibliografía.

Artificial Immune Systems with Negative Selection Applied to Health Monitoring of Aeronautical Structures

In this paper we present a system for aircraft structural health monitoring based on artificial immune systems with negative selection. Inspired by a biological process, the principle of discrimination proper/non-proper, identifies and characterizes the signs of structural failure. The main application of this method is to assist in the inspection of aircraft structures, to detect and characterize flaws and decision making in order to avoid disasters. We proposed a model of an aluminum beam to perform the tests of the method. The results obtained by this method are excellent, showing robustness and accuracy.

Case study of children of referrals to health services: an individualizing design?

Nowadays education for all is recommended as an international action. However in Brazil one can observe homogeneous practices for a heterogeneous public. When the student has learning difficulties, there seems to be an attempt to normalization and pathologization by the means of referral, many times being indiscriminate, to health services. This case study aimed to analyze records of pedagogical strategies to meet the students educational needs before sending them to health services. Two records sent to a multidisciplinary team of a Regional Specialty Clinic (ARE) in a city of the state of São Paulo/Brazil, were used. The results reflect that the records of the educators do not show the pedagogical strategies used with the students and that the education system still seeks homogeneous classes, devaluating the diversity present in its context.

Air pollution and health: bridging the gap from sources to health outcomes: conference summary

Air Pollution and Health: Bridging the Gap from Sources to Health Outcomes, an international specialty conference sponsored by the American Association for Aerosol Research, was held to address key uncertainties in our understanding of adverse health effects related to air pollution and to integrate and disseminate results from recent scientific studies that cut across a range of air pollution-related disciplines. The Conference addressed the science of air pollution and health within a multipollutant framework (herein "multipollutant" refers to gases and particulate matter mass, components, and physical properties), focusing on five key science areas: sources, atmospheric sciences, exposure, dose, and health effects. Eight key policy-relevant science questions integrated across various parts of the five science areas and a ninth question regarding findings that provide policy-relevant insights served as the framework for the meeting. Results synthesized from this Conference provide new evidence, reaffirm past findings, and offer guidance for future research efforts that will continue to incrementally advance the science required for reducing uncertainties in linking sources, air pollutants, human exposure, and health effects. This paper summarizes the Conference findings organized around the science questions. A number of key points emerged from the Conference findings. First, there is a need for greater focus on multipollutant science and management approaches that include more direct studies of the mixture of pollutants from sources with an emphasis on health studies at ambient concentrations. Further, a number of research groups reaffirmed a need for better understanding of biological mechanisms and apparent associations of various health effects with components of particulate matter (PM), such as elemental carbon, certain organic species, ultrafine particles, and certain trace elements such as Ni, V, and Fe(II), as well as some gaseous pollutants. Although much debate continues in this area, generation of reactive oxygen species induced by these and other species present in air pollution and the resulting oxidative stress and inflammation were reiterated as key pathways leading to respiratory and cardiovascular outcomes. The Conference also underscored significant advances in understanding the susceptibility of populations, including the role of genetics and epigenetics and the influence of socioeconomic and other confounding factors and their synergistic interactions with air pollutants. Participants also pointed out that short-and long-term intervention episodes that reduce pollution from sources and improve air quality continue to indicate that when pollution decreases so do reported adverse health effects. In the limited number of cases where specific sources or PM2.5 species were included in investigations, specific species are often associated with the decrease in effects. Other recent advances for improved exposure estimates for epidemiological studies included using new technologies such as microsensors combined with cell phone and integrated into real-time communications, hybrid air quality modeling such as combined receptor-and emission-based models, and surface observations used with remote sensing such as satellite data.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

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.

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.

Validity assessment of the Breast Cancer Risk Reduction Health Belief scale.

BACKGROUND: : Women at increased risk of breast cancer (BC) are not widely accepting of chemopreventive interventions, and ethnic minorities are underrepresented in related trials. Furthermore, there is no validated instrument to assess the health-seeking behavior of these women with respect to these interventions. METHODS: : By using constructs from the Health Belief Model, the authors developed and refined, based on pilot data, the Breast Cancer Risk Reduction Health Belief (BCRRHB) scale using a population of 265 women at increased risk of BC who were largely medically underserved, of low socioeconomic status (SES), and ethnic minorities. Construct validity was assessed using principal components analysis with oblique rotation to extract factors, and generate and interpret summary scales. Internal consistency was determined using Cronbach alpha coefficients. RESULTS: : Test-retest reliability for the pilot and final data was calculated to be r = 0.85. Principal components analysis yielded 16 components that explained 64% of the total variance, with communalities ranging from 0.50-0.75. Cronbach alpha coefficients for the extracted factors ranged from 0.45-0.77. CONCLUSIONS: : Evidence suggests that the BCRRHB yields reliable and valid data that allows for the identification of barriers and enhancing factors associated with use of breast cancer chemoprevention in the study population. These findings allow for tailoring treatment plans and intervention strategies to the individual. Future research is needed to validate the scale for use in other female populations. Cancer 2009. (c) 2009 American Cancer Society.

Personality, risky health behavior, and perceived susceptibility to health risks

We examined the relations between personality (Five-Factor Model), risky health behaviours, and perceptions of susceptibility to health risks among 683 university students. The hypothesis was that personality would affect perceptions of susceptibility to health risks in two ways: directly, irrespective of risky health behaviours, and indirectly, through the effects of personality on risky health behaviours. The students were surveyed about smoking, being drunk, drunk driving, risky sexual behaviour, and perceptions of susceptibility to related health risks. In path-analytical models we found the expected direct and indirect effects. The personality dimensions of Agreeableness and Conscientiousness had negative direct effects on perceptions of susceptibility as well as negative indirect effects through risky health behaviours. Neuroticism was the only personality dimension to show positive direct effects on perceptions of susceptibility as well as negative indirect effects.