Air Pollution and Mortality in Latin America The Role of Education

Background: People with less education in Europe, Asia, and the United States are at higher risk of mortality associated with daily and longer-term air pollution exposure. We examined whether educational level modified associations between mortality and ambient particulate pollution (PM(10)) in Latin America, using several timescales. Methods: The study population included people who died during 1998-2002 in Mexico City, Mexico; Santiago, Chile; and Sao Paulo, Brazil. We fit city-specific robust Poisson regressions to daily deaths for nonexternal-cause mortality, and then stratified by age, sex, and educational attainment among adults older than age 21 years (none, some primary, some secondary, and high school degree or more). Predictor variables included a natural spline for temporal trend, linear PM(10) and apparent temperature at matching lags, and day-of-week indicators. We evaluated PM(10) for lags 0 and I day, and fit an unconstrained distributed lag model for cumulative 6-day effects. Results: The effects of a 10-mu g/m(3) increment in lag 1 PM(10) on all nonextemal-cause adult mortality were for Mexico City 0.39% (95% confidence interval = 0.131/-0.65%); Sao Paulo 1.04% (0.71%-1.38%); and for Santiago 0.61% (0.40%-0.83%. We found cumulative 6-day effects for adult mortality in Santiago (0.86% [0.48%-1.23%]) and Sao Paulo (1.38% [0.85%-1.91%]), but no consistent gradients by educational status. Conclusions: PM(10) had important short- and intermediate-term effects on mortality in these Latin American cities, but associations did not differ consistently by educational level.

Patient Characteristics as Predictors of Image Quality and Diagnostic Accuracy of MDCT Compared With Conventional Coronary Angiography for Detecting Coronary Artery Stenoses: CORE-64 Multicenter International Trial

OBJECTIVE. The purpose of the study was to investigate patient characteristics associated with image quality and their impact on the diagnostic accuracy of MDCT for the detection of coronary artery stenosis. MATERIALS AND METHODS. Two hundred ninety-one patients with a coronary artery calcification (CAC) score of <= 600 Agatston units (214 men and 77 women; mean age, 59.3 +/- 10.0 years [SD]) were analyzed. An overall image quality score was derived using an ordinal scale. The accuracy of quantitative MDCT to detect significant (>= 50%) stenoses was assessed using quantitative coronary angiography (QCA) per patient and per vessel using a modified 19-segment model. The effect of CAC, obesity, heart rate, and heart rate variability on image quality and accuracy were evaluated by multiple logistic regression. Image quality and accuracy were further analyzed in subgroups of significant predictor variables. Diagnostic analysis was determined for image quality strata using receiver operating characteristic (ROC) curves. RESULTS. Increasing body mass index (BMI) (odds ratio [OR] = 0.89, p < 0.001), increasing heart rate (OR = 0.90, p < 0.001), and the presence of breathing artifact (OR = 4.97, p = 0.001) were associated with poorer image quality whereas sex, CAC score, and heart rate variability were not. Compared with examinations of white patients, studies of black patients had significantly poorer image quality (OR = 0.58, p = 0.04). At a vessel level, CAC score (10 Agatston units) (OR = 1.03, p = 0.012) and patient age (OR = 1.02, p = 0.04) were significantly associated with the diagnostic accuracy of quantitative MDCT compared with QCA. A trend was observed in differences in the areas under the ROC curves across image quality strata at the vessel level (p = 0.08). CONCLUSION. Image quality is significantly associated with patient ethnicity, BMI, mean scan heart rate, and the presence of breathing artifact but not with CAC score at a patient level. At a vessel level, CAC score and age were associated with reduced diagnostic accuracy.

Comparative role of neuropsychological testing in the presurgical evaluation of children with medically intractable epilepsies

In the present study, we evaluated the preoperative demographic, clinical, and neuropsychological variables that could predict postoperative seizure outcome in a group of pediatric epileptic patients. We studied 40 consecutive pediatric patients, ages ranging from 6 to 16 years, that underwent resective surgery for the treatment of medically intractable epilepsy at the Clinical Hospital of RibeirA o pound Preto School of Medicine. We performed ictal electroencephalography (EEG), interictal EEG, magnetic resonance imaging (MRI), and a preoperative neuropsychological assessment in the presurgical workup. The following factors were correlated with seizure outcome: (1) duration of epilepsy, (2) surgery localization, (3) localized Neuropsychological (NPS) Evaluation, (4) ictal EEG, (5) interictal EEG, and (6) MRI. Mental retardation, NPS tests, and the other demographic variables failed to correlate with seizure reduction. The identification of predictor variables of epilepsy surgery outcome could improve the epileptic prognosis and guarantee the children`s full potential development.

Long-Term Outcome and Prognostic Factors of Juvenile Dermatomyositis: A Multinational, Multicenter Study of 490 Patients

Objective. To investigate the long-term outcome and prognostic factors of juvenile dermatomyositis (DM) through a multinational, multicenter study. Methods. Patients consisted of inception cohorts seen between 1980 and 2004 in 27 centers in Europe and Latin America. Predictor variables were sex, continent, ethnicity, onset year, onset age, onset type, onset manifestations, course type, disease duration, and active disease duration. Outcomes were muscle strength/endurance, continued disease activity, cumulative damage, muscle damage, cutaneous damage, calcinosis, lipodystrophy, physical function, and health-related quality of life (HRQOL). Results. A total of 490 patients with a mean disease duration of 7.7 years were included. At the cross-sectional visit, 41.2-52.8% of patients, depending on the instrument used, had reduced muscle strength/endurance, but less than 10% had severe impairment. Persistently active disease was recorded in 41.2-60.5% of the patients, depending on the activity measure used. Sixty-nine percent of the patients had cumulative damage. The frequency of calcinosis and lipodystrophy was 23.6% and 9.7%, respectively. A total of 40.7% of the patients had decreased functional ability, but only 6.5% had major impairment. Only a small fraction had decreased HRQOL. A chronic course, either polycyclic or continuous, consistently predicted a poorer outcome. Mortality rate was 3.1%. Conclusion. This study confirms the marked improvement in functional outcome of juvenile DM when compared with earlier literature. However, many patients had continued disease activity and cumulative damage at followup. A chronic course was the strongest predictor of poor prognosis. These findings highlight the need for treatment strategies that enable a better control of disease activity over time and the reduction of nonreversible damage.

Loss minimization by the predictor-corrector modified barrier approach

This paper presents a new approach, predictor-corrector modified barrier approach (PCMBA), to minimize the active losses in power system planning studies. In the PCMBA, the inequality constraints are transformed into equalities by introducing positive auxiliary variables. which are perturbed by the barrier parameter, and treated by the modified barrier method. The first-order necessary conditions of the Lagrangian function are solved by predictor-corrector Newton`s method. The perturbation of the auxiliary variables results in an expansion of the feasible set of the original problem, reaching the limits of the inequality constraints. The feasibility of the proposed approach is demonstrated using various IEEE test systems and a realistic power system of 2256-bus corresponding to the Brazilian South-Southeastern interconnected system. The results show that the utilization of the predictor-corrector method with the pure modified barrier approach accelerates the convergence of the problem in terms of the number of iterations and computational time. (C) 2008 Elsevier B.V. All rights reserved.

Myocardial Perfusion Imaging Is a Strong Predictor of Death in Women

OBJECTIVES We sought to assess the prognostic value and risk classification improvement using contemporary single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) to predict all-cause mortality. BACKGROUND Myocardial perfusion is a strong estimator of prognosis. Evidence published to date has not established the added prognostic value of SPECT-MPI nor defined an approach to detect improve classification of risk in women from a developing nation. METHODS A total of 2,225 women referred for SPECT-MPI were followed by a mean period of 3.7 +/- 1.4 years. SPECT-MPI results were classified as abnormal on the presence of any perfusion defect. Abnormal scans were further classified as with mild/moderate reversible, severe reversible, partial reversible, or fixed perfusion defects. Risk estimates for incident mortality were categorized as <1%/year, 1% to 2%/year, and >2%/year using Cox proportional hazard models. Risk-adjusted models incorporated clinical risk factors, left ventricular ejection fraction (LVEF), and perfusion variables. RESULTS All-cause death occurred in 139 patients. SPECT-MPI significantly risk stratified the population; patients with abnormal scans had significantly higher death rates compared with patients with normal scans, 13.1% versus 4.0%, respectively (p < 0.001). Cox analysis demonstrated that after adjusting for clinical risk factors and LVEF, SPECT-MPI improved the model discrimination (integrated discrimination index = 0.009; p = 0.02), added significant incremental prognostic information (global chi-square increased from 87.7 to 127.1; p < 0.0001), and improved risk prediction (net reclassification improvement = 0.12; p = 0.005). CONCLUSIONS SPECT-MPI added significant incremental prognostic information to clinical and left ventricular functional variables while enhancing the ability to classify this Brazilian female population into low-and high-risk categories of all-cause mortality. (J Am Coll Cardiol Img 2011;4:880-8) (C) 2011 by the American College of Cardiology Foundation

Anti-mullerian hormone is the best predictor of poor response in ICSI cycles of patients with endometriosis

Purpose: To correlate ovarian reserve (OR) markers with response in assisted reproduction techniques (ART) and determine their ability to predict poor response among patients with endometriosis (EDT). Methods: We evaluated ART cycles of 27 women with EDT and 50 with exclusive male factor. Basal follicle stimulating hormone (FSH) and anti-mullerian hormone (AMH) levels were determined. Ovarian response to gonadotropin stimulation was assessed and correlation coefficients calculated between the variables and reserve markers. Areas under the curve (AUC) determined ability of tests to predict poor response. Results: AMH was significantly correlated with response in both groups and it was the only marker with significant discriminative capacity to predict poor response among EDT (AUC = 0.842; 95% CI: 0.651-0.952) and control group (AUC = 0.869; 95% CI: 0.743-0.947). Conclusion: Infertile patients with endometriosis can benefit from the pre-therapeutic assessment of OR markers. However, regardless of disease presence, only AMH predicts poor response to stimulus.

Validation of body condition score as a predictor of subcutaneous fat in Nelore (Bos indicus) cows

The aim of the present study was to determine the relationship among body weight (BW), body condition score (BCS) and rump fat thickness (RFAT) measured by ultrasonography, and validate the relationship between BCS and RFAT over the time. Two hundred sixty and six Nelore cows had their BW, BCS and RFAT evaluated at five different moments during the production cycle: M1) weaning: M2) parturition, M3) 42 days post-partum; M4) 82 days postpartum and M5) 112 days post-partum. A BCS value was attributed for each cow following a I to 5 points scale. Ultrasonographic images for RFAT measurement were obtained using a 3.5 MHz linear transducer. Images were immediately analyzed as soon as they were formed and frozen. Body condition scores and ultrasound measurements were collected on the same day by a single trained technician. The relationship between BCS and RFAT values was investigated by regression models. The analysis of similarity among the five obtained models was performed using the proc MIXED from SAS and the correlations among variables were analyzed with proc CORR from SAS. The BCS was able to predict RFAT in Nelore cows in all different moments evaluated. Also, it was shown that BCS presented high correlation (r=0.82 to 0.93) and relationship (R(2) = 0.73 to 0.92) with RFAT. However, both BCS and RFAT showed low correlation (r=0.37 to 0.50) and relationship (R(2) = 0.13 to 0.25) with BW. The BCS classification by visual method using a 1 to 5 point scale, was able to predict the RFAT in Nelore cows over the time. (C) 2008 Elsevier B.V. All rights reserved.

Analysis of the effects of conical indentation variables on the indentation response of elastic-plastic materials through factorial design of experiment

In this work, the effects of conical indentation variables on the load-depth indentation curves were analyzed using finite element modeling and dimensional analysis. A factorial design 2(6) was used with the aim of quantifying the effects of the mechanical properties of the indented material and of the indenter geometry. Analysis was based on the input variables Y/E, R/h(max), n, theta, E, and h(max). The dimensional variables E and h(max) were used such that each value of dimensionless Y/E was obtained with two different values of E and each value of dimensionless R/h(max) was obtained with two different h(max) values. A set of dimensionless functions was defined to analyze the effect of the input variables: Pi(1) = P(1)/Eh(2), Pi(2) = h(c)/h, Pi(3) = H/Y, Pi(4) = S/Eh(max), Pi(6) = h(max)/h(f) and Pi(7) = W(P)/W(T). These six functions were found to depend only on the dimensionless variables studied (Y/E, R/h(max), n, theta). Another dimension less function, Pi(5) = beta, was not well defined for most of the dimensionless variables and the only variable that provided a significant effect on beta was theta. However, beta showed a strong dependence on the fraction of the data selected to fit the unloading curve, which means that beta is especially Susceptible to the error in the Calculation of the initial unloading slope.

Can type of school be used as an alternative indicator of socioeconomic status in dental caries studies? A cross-sectional study

Background: Despite the importance of collecting individual data of socioeconomic status (SES) in epidemiological oral health surveys with children, this procedure relies on the parents as respondents. Therefore, type of school (public or private schools) could be used as an alternative indicator of SES, instead of collecting data individually. The aim of this study was to evaluate the use of the variable type of school as an indicator of socioeconomic status as a substitute of individual data in an epidemiological survey about dental caries in Brazilian preschool children. Methods: This study followed a cross-sectional design, with a random sample of 411 preschool children aged 1 to 5 years, representative of Catalao, Brazil. A calibrated examiner evaluated the prevalence of dental caries and parents or guardians provided information about several individual socioeconomic indicators by means of a semi-structured questionnaire. A multilevel approach was used to investigate the association among individual socioeconomic variables, as well as the type of school, and the outcome. Results: When all significant variables in the univariate analysis were used in the multiple model, only mother's schooling and household income (individual socioeconomic variables) presented significant associations with presence of dental caries, and the type of school was not significantly associated. However, when the type of school was used alone, children of public school presented significantly higher prevalence of dental caries than those enrolled in private schools. Conclusions: The type of school used as an alternative indicator for socioeconomic status is a feasible predictor for caries experience in epidemiological dental caries studies involving preschool children in Brazilian context.

Depressive symptoms in old age: relations among sociodemographic and self-reported health variables

Background: Depression in old age is a complex multifactorial phenomenon that is influenced by several biopsychosocial variables. Depressive symptoms are associated with the presence of chronic diseases, with being female, with low education and low income levels, and with poor perceived health assessment. In impoverished areas, older adults may have more physical disability, as they may have less access to health services. Therefore, they may be more likely to report depressive symptoms. Methods: Population-based cross-sectional research was undertaken using data from the FIBRA study conducted in Ermelino Matarazzo, a poor subdistrict of the city of Sao Paulo, Brazil. The participants comprised 303 elderly people, aged 65 years and over, who attended a single-session data collection effort carried out at community centers. The protocol comprised sociodemographic and self-reported health variables, and the Geriatric Depression Scale. Results: The majority of the subjects reported five or fewer symptoms of depression (79.21%), reported one or two self-reported chronic diseases (56.86%), declared themselves to have one or two self-reported health problems (46.15%), and had good perceived health assessment (40.27%). The presence of depressive symptoms was associated with a higher number of self-reported health problems, poor perceived health assessment, and lower schooling levels, in the total sample and in analyses including men only. For women, depressive symptoms were associated with the number of self-reported health problems and family income. Conclusion: The presence of health problems, such as falls and memory problems, lower perceived health, and low education (and low family income for women) were associated with a higher presence of depressive symptoms among elderly people in this poor area of Sao Paulo.

Exercise training associated with diet improves heart rate recovery and cardiac autonomic nervous system activity in obese children

The purpose of this study was to test the hypotheses that in obese children: 1) hypocaloric diet (D) improves both heart rate recovery at 1 min (Delta HRR1) cfter an exercise test, and cardiac autonomic nervous system activity (CANSA) in obese children; 2) Diet and exercise training (DET) combined leads to greater improvement in both Delta HRR1 after an exercise test and in CANSA, than D alone. Moreover, we examined the relationships among Delta HRR1, CANSA, cardiorespiratory fitness and anthropometric variables (AV) in obese children submitted to D and to DET. 33 obese children (10 +/- 0.2 years; body mass index (BMI) >95(th) percentile) were divided into 2 groups: D (n = 15; BMI = 31 +/- 1 kg/m(2)) and DET (n = 18; 29 +/- 1 kg/m(2)). All children performed a maximal cardiopulmonary exercise test on a treadmill. The Delta HRR1 was defined as the difference between heart rate at peak and at 1-min post-exercise. CANSA was assessed using power spectral analysis of heart rate variability at rest. The sympathovagal balance (low frequency and high frequency ratio, LF/HF) was measured. After interventions, all obese children showed reduced body weight (P < 0.05). The D group did not improve in terms of peak VO(2), Delta HRR1 or LF/HF ratio (P > 0.05). In contrast, the DET group showed increased peak VO(2) (P = 0.01) and improved Delta HRR1 (Delta HRR1 = 37.3 +/- 2.6; P = 0.01) and LF/HF ratio (P = 0.001). The DET group demonstrated significant relationships among Delta HRR1, peak VO(2) and CANSA (P < 0.05). In conclusion, DET, in contrast to D, promoted improved Delta HRR1 and CANSA in obese children, suggesting a positive influence of increased levels of cardiorespiratory fitness by exercise training on cardiac autonomic activity.

Strength training improves fall-related gait kinematics in the elderly: a randomized controlled trial

Background: Falls are one of the greatest concerns among the elderly. Among a number of strategies proposed to reduce the risk of falls, improving muscle strength has been applied as a successful preventive strategy. Although it has been suggested as a relevant strategy, no studies have analyzed how muscle strength improvements affect the gait pattern. The aim of this study was to determine the effects of a lower limb strength training program on gait kinematics parameters associated with the risk of falls in elderly women. Methods: Twenty seven elderly women were assigned in a balance and randomized order into an experimental (n = 14: age = 61.1 (4.3) years, BMI = 26.4 (2.8) kg m(-2)) and a control (n = 13; age = 61.6 (6.6) years; BMI = 25.9 (3.0) kg m(-2)) group. The EG performed lower limb strength training during 12 weeks (3 days per week), being training load increased weekly. Findings: Primary outcomes were gait kinematics parameters and maximum voluntary isometric contractions at pre- and post-training period. Secondary outcomes were training load improvement weekly and one repetition maximum every two weeks. The I maximal repetition increment ranged from 32% to 97% and was the best predictor of changes in gait parameters (spatial, temporal and angular variables) after training for the experimental group. Z-score analysis revealed that the strength training was effective in reversing age-related changes in gait speed, stride length, cadence and toe clearance, approaching the elderly to reference values for healthy young women. Interpretation: Lower limb strength training improves fall-related gait kinematic parameters. Thus, strength training programs should be recommended to the elderly women in order to change their gait pattern towards young adults. (C) 2009 Elsevier Ltd. All rights reserved.

An exploratory analysis of relationships between socioeconomic, land use, activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the Sao Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (17), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin-destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation ""credits"" for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation ""credits"" for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice). (c) 2010 Elsevier Ltd. All rights reserved.

Approximate algorithms for credal networks with binary variables

This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contain only binary variables. Such networks can represent incomplete or vague beliefs, lack of data, and disagreements among experts; they can also encode models based on belief functions and possibilistic measures. All algorithms for approximate inference in this paper rely on exact inferences in credal networks based on polytrees with binary variables, as these inferences have polynomial complexity. We are inspired by approximate algorithms for Bayesian networks; thus the Loopy 2U algorithm resembles Loopy Belief Propagation, while the Iterated Partial Evaluation and Structured Variational 2U algorithms are, respectively, based on Localized Partial Evaluation and variational techniques. (C) 2007 Elsevier Inc. All rights reserved.