Subclinical hyperthyroidism and dementia: the Sao Paulo Ageing & Health Study (SPAH)

Background: Several epidemiologic studies have shown a possible association between thyroid function and cognitive decline. Our aim was to evaluate the association of subclinical hyperthyroidism and dementia in a population sample of older people Methods: A cross-sectional study - Sao Paulo Ageing & Health Study (SPAH) - in a population sample of low-income elderly people >= 65 years-old to evaluate presence of subclinical thyroid disease as a risk factor for dementia. Thyroid function was assessed using thyrotropic hormone and free-thyroxine as well as routine use of thyroid hormones or antithyroid medications. Cases of dementia were assessed using a harmonized one-phase dementia diagnostic procedure by the ""10/66 Dementia Research Group"" including Alzheimer's disease and vascular dementia. Logistic regression models were used to test a possible association between subclinical hyperthyroidism and dementia. Results and discussion: Prevalence of dementia and of subclinical hyperthyroidism were respectively of 4.4% and 3.0%. After age adjustment, we found an association of subclinical hyperthyroidism and any type of dementia and vascular dementia (Odds Ratio, 4.1, 95% Confidence Interval [95% CI] 1.3-13.1, and 5.3 95% CI, 1.1-26.4; respectively). Analyzing data by gender, we found an association of subclinical hyperthyroidism with dementia and Alzheimer's disease only for men (OR, 8.0; 95% CI, 1.5-43.4; OR, 12.4; 95% CI, 1.2-128.4; respectively). No women with subclinical hypothyroidism presented Alzheimer's disease in the sample. Conclusion: The results suggest a consistent association among people with subclinical hyperthyroidism and dementia.

Oral Health Promotion Through an Online Training Program for Medical Students

The objective of this study was to compare the impact on knowledge and counseling skills of face-to-face and Internet-based oral health training programs on medical students. Participants consisted of 148 (82 percent) of the 180 invited students attending their fifth academic year at the Faculty of Medicine, University of Sao Paulo, Brasil, in 2007. The interventions took place during a three-month training period in the clinical Center for Health Promotion, which comprised part of a clerkship in Internal Medicine. The students were divided into four groups: 1) Control Group (Control), with basic intervention; 2) Brochure Group (Br), with basic intervention plus complete brochure with oral health themes; 3) Cybertutor Group (Cy), with basic intervention plus access to an Internet-based training program about oral health themes; and 4) Cybertutor + Contact Group (Cy+C), the same as Cy plus brief proactive contact with a tutor. The impact of these interventions on student knowledge was measured with pre- and post assessments, and student skills in asking and counseling about oral health were assessed with an objective structured clinical examination (OSCE). Multivariate logistic regression models were applied to identify the odds ratios of scoring above Control's medians on the final assessment and the OSCE. In the results, Cy+C performed significantly better than Control on both the final assessment (OR 9.4; 95% CI 2.7-32.8) and the OSCE (OR 5.6; 95% CI 1.9-16.3) and outperformed all the other groups. The Cy+C group showed the most significant increase in knowledge and the best skills in asking and counseling about oral health.

Urban air pollution and chronic obstructive pulmonary disease-related emergency department visits

Background: Patients with chronic obstructive pulmonary disease (COPD) can have recurrent disease exacerbations triggered by several factors, including air pollution. Visits to the emergency respiratory department can be a direct result of short-term exposure to air pollution. The aim of this study was to investigate the relationship between the daily number of COPD emergency department visits and the daily environmental air concentrations of PM(10), SO(2), NO(2), CO and O(3) in the City of Sao Paulo, Brazil. Methods: The sample data were collected between 2001 and 2003 and are categorised by gender and age. Generalised linear Poisson regression models were adopted to control for both short-and long-term seasonal changes as well as for temperature and relative humidity. The non-linear dependencies were controlled using a natural cubic spline function. Third-degree polynomial distributed lag models were adopted to estimate both lag structures and the cumulative effects of air pollutants. Results: PM(10) and SO(2) readings showed both acute and lagged effects on COPD emergency department visits. Interquartile range increases in their concentration (28.3 mg/m(3) and 7.8 mg/m(3), respectively) were associated with a cumulative 6-day increase of 19% and 16% in COPD admissions, respectively. An effect on women was observed at lag 0, and among the elderly the lag period was noted to be longer. Increases in CO concentration showed impacts in the female and elderly groups. NO(2) and O(3) presented mild effects on the elderly and in women, respectively. Conclusion: These results indicate that air pollution affects health in a gender-and age-specific manner and should be considered a relevant risk factor that exacerbates COPD in urban environments.

Impact of outdoor biomass air pollution on hypertension hospital admissions

Background This study aimed to evaluate the association between the total suspended particles (TSP) generated from burning sugar cane plantations and the incidence of hospital admissions from hypertension in the city of Araraquara. Methods The study was an ecological time-series study. Total daily records of hypertension (ICD 10th I10-15) were obtained from admitted patients of all ages in a hospital in Araraquara, Sao Paulo State, Brazil, from 23 March 2003 to 27 July 2004. The daily concentration of TSP (mu g/m(3)) was obtained using a Handi-Vol sampler placed in downtown Araraquara. The local airport provided daily measures of temperature and humidity. In generalised linear Poisson regression models, the daily number of hospital admissions for hypertension was considered to be the dependent variable and the daily TSP concentration the independent variable. Results TSP presented a lagged effect on hypertension admissions, which was first observed 1 day after a TSP increase and remained almost unchanged for the following 2 days. A 10 mu g/m(3) increase in the TSP 3 day moving average lagged in 1 day led to an increase in hypertension-related hospital admissions during the harvest period (12.5%, 95% CI 5.6% to 19.9%) that was almost 30% higher than during non-harvest periods (9.0%, 95% CI 4.0% to 14.3%). Conclusions Increases in TSP concentrations were associated with hypertension-related hospital admissions. Despite the benefits of reduced air pollution in urban cities achieved by using ethanol produced from sugar cane to power automobiles, areas where the sugar cane is produced and harvested were found to have increased public health risk.

Cardiac arrhythmia emergency room visits and environmental air pollution in Sao Paulo, Brazil

Objectives: Air-pollution exposure has been associated with increased cardiovascular hospital admissions and mortality in time-series studies. We evaluated the relation between air pollutants and emergency room (ER) visits because of cardiac arrhythmia in a cardiology hospital. Methods: In a time-series study, we evaluated the association between the emergency room visits as a result of cardiac arrhythmia and daily variations in SO2, CO, NO2, O-3 and PM10, from January 1998 to August 1999. The cases of arrhythmia were modelled using generalised linear Poisson regression models, controlling for seasonality (short-term and long-term trend), and weather. Results: Interquartile range increases in CO (1.5 ppm), NO2 (49,5 mu g/m(3)) and PM10 (22.2 mu g/m(3)) on the concurrent day were associated with increases of 12.3% (95% CI: 7.6% to 17.2%), 10.4% (95% CI: 5.2% to 15.9%) and 6.7% (95% CI: 1.2% to 12.4%) in arrhythmia ER visits, respectively. PM10, CO and NO2 effects were dose-dependent and gaseous pollutants had thresholds. Only CO effect resisted estimates in models with more than one pollutant. Conclusions: Our results showed that air pollutant effects on arrhythmia are predominantly acute starting at concentrations below air quality standards, and the association with CO and NO2 suggests a relevant role for pollution caused by cars.

Trends in socioeconomic inequalities in cancer mortality in Barcelona: 1992-2003

Background: The objective of this study was to assess trends in cancer mortality by educational level in Barcelona from 1992 to 2003. Methods: The study population comprised Barcelona inhabitants aged 20 years or older. Data on cancer deaths were supplied by the system of information on mortality. Educational level was obtained from the municipal census. Age-standardized rates by educational level were calculated. We also fitted Poisson regression models to estimate the relative index of inequality (RII) and the Slope Index of Inequalities (SII). All were calculated for each sex and period (1992-1994, 1995-1997, 1998-2000, and 2001-2003). Results: Cancer mortality was higher in men and women with lower educational level throughout the study period. Less-schooled men had higher mortality by stomach, mouth and pharynx, oesophagus, larynx and lung cancer. In women, there were educational inequalities for cervix uteri, liver and colon cancer. Inequalities of overall and specific types of cancer mortality remained stable in Barcelona; although a slight reduction was observed for some cancers. Conclusion: This study has identified those cancer types presenting the greatest inequalities between men and women in recent years and shown that in Barcelona there is a stable trend in inequalities in the burden of cancer.

Fatores gravimétricos no Brasil para um modelo anelástico de Terra

Geodetic observations are affected by the disturbing potential of the luni-solar tide. Among those observations, the value of g obtained from gravimetric survey needs correction by the gravimetric factor. This correction is derived from the Numbers of Love, which depend on the adopted model of Earth. Because of this, it is necessary to update the correction since the gravimetric factor widely used in Brazil as delta = 1.20 does not consider local rheological variations and they are latitude dependent. A discrepancy of about 1% between the observed tidal gravimetric factors d of the ""Trans World Tidal Gravity Profiles"" (TWTGP), related to Brussels fundamental station, and those obtained by recent observations reported by Freitas and Ducarme ( 1991). Experiments based on inertial force effects also reveal a variation of about 0.5% in the observed d. A same order of magnitude difference is obtained for an anelastic Earth model when compared with a viscous-elastic model and even when different frequencies of tidal perturbations are considered. In this paper regression models are presented for gravimetric factors for the lunar components O(1) and M(2) in Brazil. These models were obtained from observations performed at stations belonging to the Brazilian segment of the TWTGP.

Espacialização da temperatura do ar anual no estado de Alagoas com diferentes modelos digitais de elevação e resoluções espaciais

The aim of this study was to establish a digital elevation model and its horizontal resolution to interpolate the annual air temperature for the Alagoas State by means of multiple linear regression models. A multiple linear regression model was adjusted to series (11 to 34 years) of annual air temperatures obtained from 28 weather stations in the states of Alagoas, Bahia, Pernambuco and Sergipe, in the Northeast of Brazil, in function of latitude, longitude and altitude. The elevation models SRTM and GTOPO30 were used in the analysis, with original resolutions of 90 and 900 m, respectively. The SRTM was resampled for horizontal resolutions of 125, 250, 500, 750 and 900 m. For spatializing the annual mean air temperature for the state of Alagoas, a multiple linear regression model was used for each elevation and spatial resolution on a grid of the latitude and longitude. In Alagoas, estimates based on SRTM data resulted in a standard error of estimate (0.57 degrees C) and dispersion (r(2) = 0.62) lower than those obtained from GTOPO30 (0.93 degrees C and 0.20). In terms of SRTM resolutions, no significant differences were observed between the standard error (0.55 degrees C; 750 m - 0.58 degrees C; 250m) and dispersion (0.60; 500 m - 0.65; 750 m) estimates. The spatialization of annual air temperature in Alagoas, via multiple regression models applied to SRTM data showed higher concordance than that obtained with the GTOPO30, independent of the spatial resolution.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Definindo a arena política local: sistemas partidários municipais na federação brasileira

This article analyzes the Brazilian political system from the local perspective. Following Cox (1997), we review the problems with electoral coordination that emerge from a given institutional framework. Due to the characteristics of the Brazilian Federal system and its electoral rules, linkage between the three levels of government is not guaranteed a priori, but demands a coordinating effort by the parties' leadership. According to our hypothesis, the parties are capable of coordinating their election strategies at different levels in the party system. Regression models based on two-stage least squares (2SLS) and TOBIT, analyzing a panel of Brazilian municipalities with data from the 1994 and 2000 elections, show that the proportion of votes received by a party in a given election correlates closely with its previous votes in majoritarian elections. Despite institutional incentives, the Brazilian party system shows evidence that it is organized nationally to the extent that it links the competition for votes at the three levels of government (National, State, and Municipal).

Understanding Pain and Quality of Life for Patients With Chronic Venous Ulcers

Aim. To identify the impact of pain on quality of life (QOL) of patients with chronic venous ulcers. Methods. A cross-sectional study was performed on 40 outpatients with chronic venous ulcers who were recruited at one outpatient care center in Sao Paulo, Brazil. WHOQOL-Bref was used to assess QOL, the McGill Pain Questionnarie-Short Form (MPQ) to identify pain characteristics, and an 11-point numerical pain rating scale to measure pain intensity. Kruskall-Wallis or ANOVA test, with post-hoc correction (Tukey test) was applied to compare groups. Multiple linear regression models were used. Results. The mean age of the patients was 67 +/- 11 years (range, 39-95 years), and 26 (65%) were women. The prevalence of pain was 90%, with worst pain mean intensity of 6.2 +/- 3.5. Severe pain was the most prevalent (21 patients, 52.5%). Pain most frequently reported was sensory-discriminative and evaluate in quality. Pain was significantly and negatively correlated with physical (PY), environmental (EV), and overall QOL. Compared to a no-pain group, those with pain had lower overall QOL. On multiple analyses, pain remained as a predictor of overall QOL (beta = -0.73, P = 0.03) and was also predictive of social QOL, whereas pain did not have any impact on physical, emotional, or social relationships QOL (beta = -3.85, P = 0.00) when adjusted for age, number, duration and frequency of wounds, pain dimension (MPQ), partnership, and economic status. Conclusion. To improve QOL of out-patients with chronic venous ulcers, the qualities and the intensity of pain must be considered differently.

Ventilation behavior during upper-body incremental exercise

Pires, FO, Hammond, J, Lima-Silva, AE, Bertuzzi, RCM, and Kiss, MAPDM. Ventilation behavior during upper-body incremental exercise. J Strength Cond Res 25(1): 225-230, 2011-This study tested the ventilation (V(E)) behavior during upper-body incremental exercise by mathematical models that calculate 1 or 2 thresholds and compared the thresholds identified by mathematical models with V-slope, ventilatory equivalent for oxygen uptake (V(E)/(V) over dotO(2)), and ventilatory equivalent for carbon dioxide uptake (V(E)/(V) over dotCO(2)). Fourteen rock climbers underwent an upper-body incremental test on a cycle ergometer with increases of approximately 20 W.min(-1) until exhaustion at a cranking frequency of approximately 90 rpm. The V(E) data were smoothed to 10-second averages for V(E) time plotting. The bisegmental and the 3-segmental linear regression models were calculated from 1 or 2 intercepts that best shared the V(E) curve in 2 or 3 linear segments. The ventilatory threshold(s) was determined mathematically by the intercept(s) obtained by bisegmental and 3-segmental models, by V-slope model, or visually by V(E)/(V) over dotO(2) and V(E)/(V) over dotCO(2). There was no difference between bisegmental (mean square error [MSE] = 35.3 +/- 32.7 l.min(-1)) and 3-segmental (MSE = 44.9 +/- 47.8 l.min(-1)) models in fitted data. There was no difference between ventilatory threshold identified by the bisegmental (28.2 +/- 6.8 ml.kg(-1).min(-1)) and second ventilatory threshold identified by the 3-segmental (30.0 +/- 5.1 ml.kg(-1).min(-1)), V(E)/(V) over dotO(2) (28.8 +/- 5.5 ml.kg(-1).min(-1)), or V-slope (28.5 +/- 5.6 ml.kg(-1).min(-1)). However, the first ventilatory threshold identified by 3-segmental (23.1 +/- 4.9 ml.kg(-1).min(-1)) or by VE/(V) over dotO(2) (24.9 +/- 4.4 ml.kg(-1).min(-1)) was different from these 4. The V(E) behavior during upper-body exercise tends to show only 1 ventilatory threshold. These findings have practical implications because this point is frequently used for aerobic training prescription in healthy subjects, athletes, and in elderly or diseased populations. The ventilatory threshold identified by V(E) curve should be used for aerobic training prescription in healthy subjects and athletes.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

An estimate of biometric parameters in eucalyptus clone plantations in Southern Bahia: an application of the airborne laser scanning (ALS) technology

The application of airborne laser scanning (ALS) technologies in forest inventories has shown great potential to improve the efficiency of forest planning activities. Precise estimates, fast assessment and relatively low complexity can explain the good results in terms of efficiency. The evolution of GPS and inertial measurement technologies, as well as the observed lower assessment costs when these technologies are applied to large scale studies, can explain the increasing dissemination of ALS technologies. The observed good quality of results can be expressed by estimates of volumes and basal area with estimated error below the level of 8.4%, depending on the size of sampled area, the quantity of laser pulses per square meter and the number of control plots. This paper analyzes the potential of an ALS assessment to produce certain forest inventory statistics in plantations of cloned Eucalyptus spp with precision equal of superior to conventional methods. The statistics of interest in this case were: volume, basal area, mean height and dominant trees mean height. The ALS flight for data assessment covered two strips of approximately 2 by 20 Km, in which clouds of points were sampled in circular plots with a radius of 13 m. Plots were sampled in different parts of the strips to cover different stand ages. The clouds of points generated by the ALS assessment: overall height mean, standard error, five percentiles (height under which we can find 10%, 30%, 50%,70% and 90% of the ALS points above ground level in the cloud), and density of points above ground level in each percentile were calculated. The ALS statistics were used in regression models to estimate mean diameter, mean height, mean height of dominant trees, basal area and volume. Conventional forest inventory sample plots provided real data. For volume, an exploratory assessment involving different combinations of ALS statistics allowed for the definition of the most promising relationships and fitting tests based on well known forest biometric models. The models based on ALS statistics that produced the best results involved: the 30% percentile to estimate mean diameter (R(2)=0,88 and MQE%=0,0004); the 10% and 90% percentiles to estimate mean height (R(2)=0,94 and MQE%=0,0003); the 90% percentile to estimate dominant height (R(2)=0,96 and MQE%=0,0003); the 10% percentile and mean height of ALS points to estimate basal area (R(2)=0,92 and MQE%=0,0016); and, to estimate volume, age and the 30% and 90% percentiles (R(2)=0,95 MQE%=0,002). Among the tested forest biometric models, the best fits were provided by the modified Schumacher using age and the 90% percentile, modified Clutter using age, mean height of ALS points and the 70% percentile, and modified Buckman using age, mean height of ALS points and the 10% percentile.