Falls Among The Elderly: Risk Factors In A Population-based Study.

The aim of the present study was to identify factors associated with the occurrence of falls among elderly adults in a population-based study (ISACamp 2008). A population-based cross-sectional study was carried out with two-stage cluster sampling. The sample was composed of 1,520 elderly adults living in the urban area of the city of Campinas, São Paulo, Brazil. The occurrence of falls was analyzed based on reports of the main accident occurred in the previous 12 months. Data on socioeconomic/demographic factors and adverse health conditions were tested for possible associations with the outcome. Prevalence ratios (PR) were estimated and adjusted for gender and age using the Poisson multiple regression analysis. Falls were more frequent, after adjustment for gender and age, among female elderly participants (PR = 2.39; 95% confidence interval (95% CI) 1.47 - 3.87), elderly adults (80 years old and older) (PR = 2.50; 95% CI 1.61 - 3.88), widowed (PR = 1.74; 95% CI 1.04 - 2.89) and among elderly adults who had rheumatism/arthritis/arthrosis (PR = 1.58; 95% CI 1.00 - 2.48), osteoporosis (PR = 1.71; 95% CI 1.18 - 2.49), asthma/bronchitis/emphysema (PR = 1,73; 95% CI 1.09 - 2.74), headache (PR = 1.59; 95% CI 1.07 - 2.38), mental common disorder (PR = 1.72; 95% CI 1.12 - 2.64), dizziness (PR = 2.82; 95% CI 1.98 - 4.02), insomnia (PR = 1.75; 95% CI 1.16 - 2.65), use of multiple medications (five or more) (PR = 2.50; 95% CI 1.12 - 5.56) and use of cane/walker (PR = 2.16; 95% CI 1.19 - 3,93). The present study shows segments of the elderly population who are more prone to falls through the identification of factors associated with this outcome. The findings can contribute to the planning of public health policies and programs addressed to the prevention of falls.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

[access To Basic Health Services And Associated Factors: A Population-based Study].

This study sought to identify factors involved in access to the services of a basic health unit. It is a cross-sectional, population-based study involving 101 randomly-selected families residing in the area covered by the health unit. An adult resident of each household was interviewed. The response variable was whether or not the resident frequented the health unit if he/she or anyone in the family required assistance to resolve a health issue. The independent variables investigated were service provision aspects, demographic and socio-economic characteristics, individual habits, morbidities and use of the health unit. In addition to descriptive and univariate analysis, logistic regression was applied in the multivariate analysis. The results show that access to the basic health unit is associated with the treatment received previously (OR = 3,224) with accessibility (OR = 0,146) and micro-area of residence (OR = 10,918). These findings suggest that access is related to the impressions created by the care received at the health unit and is based on experiences with the service, but can also be strongly modulated by individual aspects and factors related to the territory.

Prevalence Of Urinary Incontinence And Its Association With Multimorbidity In Women Aged 50 Years Or Older: A Population-based Study.

To evaluate the prevalence and associated risk factors for urinary incontinence, as well as its association with multimorbidity among Brazilian women aged 50 or over. This was a secondary analysis of a cross-sectional population-based study including 622 women 50 years or older, conducted in the city of Campinas-SP-Brazil. The dependent variable was Urinary Incontinence (UI), defined as any complaint of urine loss. The independent variables were sociodemographic data, health-related habits, self-perception of health and functional capacity evaluation. Statistical analysis was carried out using the Chi-square test and Poisson regression. The mean age of the women was 64. UI was prevalent in 52.3% of these women: Mixed UI (26.6%), Urge UI (13.2%) and Stress UI (12.4%). Factors associated with a higher prevalence of UI were hypertension (OR 1.21, CI 1:01-1:47, P = 0.004), osteoarthritis (OR 1.24, CI 1:03-1:50, P = 0.022), physical activity ≥3 days/week (OR 1.21, CI 1:01-1:44, P = 0.039), BMI ≥ 25 at the time of the interview (OR 1.25, CI 1:04-1:49, P = 0.018), negative self-perception of health (OR 1.23, CI 1:06-1:44 P = 0.007) and limitations in daily living activities (PR 1:56 CI 1:16-2:10, P = 0.004). The prevalence of UI was high. Mixed incontinence was the most frequent type of UI. Many associated factors can be prevented or improved. Thus, health policies targeted at these combined factors could reduce their prevalence rate and possibly decrease the prevalence of UI. Neurourol. Urodynam. © 2014 Wiley Periodicals, Inc.

Factors Associated With The Age Of The Onset Of Diabetes In Women Aged 50 years Or More: A Population-based Study.

Investigate factors associated with the onset of diabetes in women aged more than 49 years. Cross-sectional, population-based study using self-reports with 622 women. The dependent variable was the age of occurrence of diabetes using the life table method. Cox multiple regression models were adjusted to analyse the onset of diabetes according to predictor variables. Sociodemographic, clinical and behavioural factors were evaluated. Of the 622 women interviewed, 22.7% had diabetes. The mean age at onset was 56 years. The factors associated with the age of occurrence of diabetes were self-rated health (very good, good) (coefficient=-0.792; SE of the coefficient=0.215; p=0.0001), more than two individuals living in the household (coefficient=0.656, SE of the coefficient=0.223; p=0.003), and body mass index (BMI) (kg/m(2)) at 20-30 years of age (coefficient= 0.056, SE of the coefficient=0.023; p=0.014). Self-rated health considered good or very good was associated with a higher rate of survival without diabetes. Sharing a home with two or more other people and a weight increase at 20-30 years of age was associated with the onset of type 2 diabetes.

Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

[need For Orthodontic Treatment Among Brazilian Adolescents: Evaluation Based On Public Health].

To identify the prevalence and the severity of malocclusions and to analyze factors associated with the need for orthodontic treatment of Brazilian adolescents. This exploratory, cross-sectional study was carried out based on secondary data from the national epidemiological survey on oral health in Brazil (2002-2003). Socio-demographic conditions, self-perception, and the existence and degree of malocclusion, using the Dental Aesthetic Index, were evaluated in 16,833 adolescent Brazilians selected by probabilistic sample by conglomerates. The dependent variable - need orthodontic treatment - was estimated from the severity of malocclusion. The magnitude and direction of the association in bivariate and multivariate analyzes from a Robust Poisson regression was estimated RESULTS: The majority of the adolescents needed orthodontic treatment (53.2%). In the multivariate analysis, the prevalence of the need for orthodontic treatment was larger among females, non-whites, those that perceived a need for treatment, and those that perceived their appearance as normal, bad, or very bad. The need for orthodontic treatment was smaller among those that lived in the Northeast and Central West macro-regions compared to those living in Southeast Brazil and it was also smaller among those that perceived their chewing to be normal or their oral health to be bad or very bad. There was a high prevalence of orthodontic treatment need among adolescents in Brazil and this need was associated with demographic and subjective issues. The high prevalence of orthodontic needs in adolescents is a challenge to the goals of Brazil's universal public health system.

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co) variances with age adequately and larger breeding value accuracies can be expected using this model.

Biaxial strain-induced suppression of spinodal decomposition in GaMnAs and GaCrAs

The thermodynamic properties of the magnetic semiconductors GaMnAs and GaCrAs are studied under biaxial strain. The calculations are based on the projector augmented wave method combined with the generalized quasichemical approach to treat the disorder and composition effects. Considering the influence of biaxial strain, we find a tendency to the suppression of binodal decomposition mainly for GaMnAs under compressive strain. For a substrate with a lattice constant 5% smaller than the one of GaAs, for GaMnAs, the solubility limit increases up to 40%. Thus, the strain can be a useful tool for tailoring magnetic semiconductors to the formation or not of embedded nanoclusters. (C) 2010 American Institute of Physics. [doi:10.1063/1.3448025]

Chemiluminescence-based uphill energy conversion

The conversion of red excitation light into blue emission light (uphill energy conversion) using unstable 1,2-dioxetanes is described. The method is based on 1,2-dioxetane formation by red-light sensitized photooxygenation of adequate alkenes and subsequent blue-light emission due to thermal 1,2-dioxetane cleavage. The energy gain resulting from the chemical energy obtained in the transformation of an alkene into two carbonyl compounds transforms a red-light excitation laser beam into a blue-light chemiluminescence emission, producing thereby a formal anti-Stokes shift of 200-250 nm, opening up a whole spectrum of possible applications.

Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

Reliability-based evaluation of design code provisions for circular concrete-filled steel columns

This paper presents an investigation of design code provisions for steel-concrete composite columns. The study covers the national building codes of United States, Canada and Brazil, and the transnational EUROCODE. The study is based on experimental results of 93 axially loaded concrete-filled tubular steel columns. This includes 36 unpublished, full scale experimental results by the authors and 57 results from the literature. The error of resistance models is determined by comparing experimental results for ultimate loads with code-predicted column resistances. Regression analysis is used to describe the variation of model error with column slenderness and to describe model uncertainty. The paper shows that Canadian and European codes are able to predict mean column resistance, since resistance models of these codes present detailed formulations for concrete confinement by a steel tube. ANSI/AISC and Brazilian codes have limited allowance for concrete confinement, and become very conservative for short columns. Reliability analysis is used to evaluate the safety level of code provisions. Reliability analysis includes model error and other random problem parameters like steel and concrete strengths, and dead and live loads. Design code provisions are evaluated in terms of sufficient and uniform reliability criteria. Results show that the four design codes studied provide uniform reliability, with the Canadian code being best in achieving this goal. This is a result of a well balanced code, both in terms of load combinations and resistance model. The European code is less successful in providing uniform reliability, a consequence of the partial factors used in load combinations. The paper also shows that reliability indexes of columns designed according to European code can be as low as 2.2, which is quite below target reliability levels of EUROCODE. (C) 2009 Elsevier Ltd. All rights reserved.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved