Prevalence and risk factors of radiographic vertebral fracture in Brazilian community-dwelling elderly

The prevalence and risk factors of radiographic vertebral fracture were determined among Brazilian community-dwelling elderly. Vertebral fractures were a common condition in this elderly population, and lower hip bone mineral density was a significant risk factor for vertebral fractures in both genders. The aim of the study was to estimate the prevalence of radiographic vertebral fracture and investigate factors associated with this condition in Brazilian community-dwelling elderly. This cross-sectional study included 943 elderly subjects (561 women and 382 men) living in So Paulo, Brazil. Thoracic and lumbar spine radiographs were obtained, and vertebral fractures were evaluated using Genant`s semiquantitative method. Bone mineral density (BMD) was measured by dual X-ray absorptiometry, and bone biochemical markers were also evaluated. Female and male subjects were analyzed independently, and each gender was divided into two groups based on whether vertebral fractures were present. The prevalence of vertebral fracture was 27.5% (95% CI 23.8-31.1) in women and 31.8% in men (95% CI 27.1-36.5) (P = 0.116). Cox regression analyses using variables that were significant in the univariate analysis showed that age (prevalence ratio = 1.03, 95% CI 1.01-1.06; p = 0.019) and total femur BMD (PR = 0.27, 95% CI 0.08-0.98; p = 0.048) were independent factors in predicting vertebral fracture for the female group. In the male group, Cox regression analyses demonstrated that femoral neck BMD (PR = 0.26, 95% CI 0.07-0.98; p = 0.046) was an independent parameter in predicting vertebral fractures. Our results suggest that radiographic vertebral fractures are common in Brazilian community-dwelling elderly and that a low hip BMD was an important risk factor for this condition in both genders. Age was also significantly correlated with the presence of vertebral fractures in women.

Inexpensive footwear decreases joint loading in elderly women with knee osteoarthritis

Recent literature has highlighted that the flexibility of walking barefoot reduces overload in individuals with knee osteoarthritis (OA). As such, the aim of this study was to evaluate the effects of inexpensive, flexible, non-heeled footwear (Moleca (R)) as compared with a modern heeled shoes and walking barefoot on the knee adduction moment (KAM) during gait in elderly women with and without knee OA. The gait of 45 elderly women between 60 and 70 years of age was evaluated. Twenty-one had knee OR graded 2 or 3 according to Kellgren and Lawrence`s criteria, and 24 who had no OA comprised the control group (CG). The gait conditions were: barefoot, Moleca (R), and modern heeled shoes. Three-dimensional kinematics and ground reaction forces were measured to calculate KAM by inverse dynamics. For both groups, the Moleca (R) provided peak KAM and KAM impulse similar to barefoot walking. For the OA group, the Moleca (R) reduced KAM even more as compared to the barefoot condition during midstance. On the other hand, the modern heeled shoes increased this variable in both groups. Inexpensive, flexible, and non-heeled footwear provided loading on the knee joint similar to a barefoot gait and significant overload decreases in elderly women with and without knee OA, compared to modern heeled shoes. During midstance, the Moleca (R) also allowed greater reduction in the knee joint loads as compared to barefoot gait in elderly women with knee OA, with the further advantage of providing external foot protection during gait. (C) 2011 Elsevier B.V. All rights reserved.

Exercise-associated thermographic changes in young and elderly subjects

This study aimed at evaluating the thermographic changes associated with localized exercise in young and elderly subjects. An exercise protocol using 1 kg load was applied during 3 min to the knee flexors of 14 elderly (67 +/- 5 years) and 15 young (23 +/- 2 years) healthy subjects. The posterior thigh`s skin temperature of the exercised limb and contralateral limb were measured by infrared thermography on pre-exercise, immediately post-exercise, and during the 10-min period post-exercise. Difference (p < 0.01) between elderly and young subjects was observed on pre-exercise temperature. Although differences were not observed between pre-exercise and immediately post-exercise temperature in the exercised limb, thermographic profile displayed heat concentration in exercised areas for both groups. Temperature reduction was only observed for the young group on the 10-min post-exercise (p < 0.05) in the exercised limb (30.7 +/- 1.7 to 30.3 +/- 1.5 degrees C). In contrast, there was a temperature reduction post-exercise (p < 0.01) in the contralateral limb for both groups. These results present new evidences that elderly and young subjects display similar capacity of heat production; however, the elderly subjects presented a lower resting temperature and slower heat dissipation. This work contributes to improve the understanding about temperature changes in elderly subjects and may present implications to the sports and rehabilitation programs.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

Relative entropy measures applied to healthy and pathological voice characterization

Nowadays, noninvasive methods of diagnosis have increased due to demands of the population that requires fast, simple and painless exams. These methods have become possible because of the growth of technology that provides the necessary means of collecting and processing signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this paper is to characterize healthy and pathological voice signals with the aid of relative entropy measures. Phase space reconstruction technique is also used as a way to select interesting regions of the signals. Three groups of samples were used, one from healthy individuals and the other two from people with nodule in the vocal fold and Reinke`s edema. All of them are recordings of sustained vowel /a/ from Brazilian Portuguese. The paper shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Relative entropy is well suited due to its sensibility to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. The results showed that the pathological groups had higher entropy values in accordance with other vocal acoustic parameters presented. This suggests that these techniques may improve and complement the recent voice analysis methods available for clinicians. (C) 2008 Elsevier Inc. All rights reserved.

Influence of education and depressive symptoms on cognitive function in the elderly

Objective: The purpose of the present study was to investigate the influence that education and depression have on the performance of elderly people in neuropsychological tests. Methods: The study was conducted at the Institute of Psychiatry, University of Sao Paulo School of Medicine, Hospital das Clinicas. All of the individuals evaluated were aged 60 or older. The study sample consisted of 59 outpatients with depressive disorders and 51 healthy controls. We stratified the sample by level of education: low = 1-4 years of schooling; high = 5 or more years of schooling. Evaluations consisted of psychiatric assessment, cognitive assessment, laboratory tests and cerebral magnetic resonance imaging. Results: We found that level of education influenced all the measures of cognitive domains investigated (intellectual efficiency, processing speed, attention, executive function and memory) except the Digit Span Forward and Fuld Object Memory Evaluation (immediate and delayed recall), whereas depressive symptoms influenced some measures of memory, attention, executive function and processing speed. Although the combination of a low level of education and depression had a significant negative influence on Stroop Test part B, Trail Making Test part B and Logical Memory (immediate recall), we found no other significant effects of the interaction between level of education and depression. Conclusion: The results of this study underscore the importance of considering the level of education in the analysis of cognitive performance in depressed elderly patients, as well as the relevance of developing new cognitive function tests in which level of education has a reduced impact on the results.