Quedas em idosos assistidos na estratégia saúde da família: frequência e fatores associados

The growth of the elderly population is a global phenomenon and, in Brazil, this transformation is happening in a very rapid rhythm. With the current population aging, this emerging age group will need more health care and attention. One of the characteristics of the population aging is the progressive accumulation of disabilities, which makes it more vulnerable to falls. This study was developed with the purpose of knowing the episode falls in the scope of an elderly population treated at a Family Health Unit. It is a research with cross-sectional nature, and its sample was composed by 121 elderly. The research was approved by the Ethics Committee of HUOL, with Opinion nº 816.022. We applied a questionnaire to the participants, and the results were statistically analyzed by using Chi-square test and Fisher’s exact test to verify the association between variables. In order to perform a multivariate analysis, we used the method of the Binomial Logistic Regression. For both tests, we accepted significance p<0,05 and CI of 95%. The results prove that the majority belongs to the female gender (76,9%); the age group of elderly reaches 88,4% and 11,6% is over-aged; regarding the marital status, 35,3% are married and 29,4% widowed; 92,1% with family income between one and two minimum wages; and 91,8% live with their partners and/or children. Regarding the frequency of falls, we found that 61,2% of the surveyed elderly suffered one or more falls in 2014. As associated factors, it became clear that 73,8% were due to extrinsic factors, 6,4% to intrinsic factors and 21,4% to both factors. As a consequence of the fall, we found that 89,2% have fear of falling again, 37,3% showed anxiety and 13,3% had their ambulation affected. Concerning the exposure to the risk factors, the most prevalent places were: street/avenue (31,0%), pavement (19,0%), living room (14,3%) and courtyard/backyard (10,7%). The study has proven a statistically significant association among female gender (p=0,001), rubble/objects in the backyard (p=0,015) and furniture that may cause accidents (p=0,005). It was evident among the elderly people surveyed, 72.7% receive little information about falls, being a risk factor for falls. We conclude that there is a high frequency of falls in the surveyed elderly, thereby constituting a worrisome data because this event in the elderly population is a serious matter, which raises the need to ensure them a safe environment in their homes and, above all, outside them. The information provided by the Family Health Strategy team are important to avoid these occurrences, which reinforces the need for developing health education activities together with the population as a way to prevent and reduce the occurrence of falls, thereby improving the quality of life of elderly.

Avaliação da aplicabilidade de correlações matemáticas e redes neurais na predição de parâmetros de especificação do diesel

Diesel fuel is one of leading petroleum products marketed in Brazil, and has its quality monitored by specialized laboratories linked to the National Agency of Petroleum, Natural Gas and Biofuels - ANP. The main trial evaluating physicochemical properties of diesel are listed in the resolutions ANP Nº 65 of December 9th, 2011 and Nº 45 of December 20th, 2012 that determine the specification limits for each parameter and methodologies of analysis that should be adopted. However the methods used although quite consolidated, require dedicated equipment with high cost of acquisition and maintenance, as well as technical expertise for completion of these trials. Studies for development of more rapid alternative methods and lower cost have been the focus of many researchers. In this same perspective, this work conducted an assessment of the applicability of existing specialized literature on mathematical equations and artificial neural networks (ANN) for the determination of parameters of specification diesel fuel. 162 samples of diesel with a maximum sulfur content of 50, 500 and 1800 ppm, which were analyzed in a specialized laboratory using ASTM methods recommended by the ANP, with a total of 810 trials were used for this study. Experimental results atmospheric distillation (ASTM D86), and density (ASTM D4052) of diesel samples were used as basic input variables to the equations evaluated. The RNAs were applied to predict the flash point, cetane number and sulfur content (S50, S500, S1800), in which were tested network architectures feed-forward backpropagation and generalized regression varying the parameters of the matrix input in order to determine the set of variables and the best type of network for the prediction of variables of interest. The results obtained by the equations and RNAs were compared with experimental results using the nonparametric Wilcoxon test and Student's t test, at a significance level of 5%, as well as the coefficient of determination and percentage error, an error which was obtained 27, 61% for the flash point using a specific equation. The cetane number was obtained by three equations, and both showed good correlation coefficients, especially equation based on aniline point, with the lowest error of 0,816%. ANNs for predicting the flash point and the index cetane showed quite superior results to those observed with the mathematical equations, respectively, with errors of 2,55% and 0,23%. Among the samples with different sulfur contents, the RNAs were better able to predict the S1800 with error of 1,557%. Generally, networks of the type feedforward proved superior to generalized regression.