Coping religioso, resiliência e qualidade de vida de pessoas com HIV/AIDS

Tese (doutorado)—Universidade de Brasília, Instituto de Psicologia, Programa de Pós-Graduação em Processos de Desenvolvimento Humano e Saúde, 2016.

The importance of organizational commitment to knowledge management

In recent years, Knowledge Management (KM) has assumed great importance in the literature on business and management. However, we still have so little understanding of the human issues in KM processes. Thus, this research aims to contribute to analysing the importance of Organizational Commitment (OC) to KM. First, we used the Cardoso (2003) Knowledge Management Questionnaire (QGC) that embraces all organizational activities around knowledge processes and distinguishes four dimensions of KM. Secondly we applied the Quijano, Masip, Navarro and Aubert (1997) questionnaire (ASH-ICI) that distinguishes two types of commitment (personal and instrumental) into four dimensions. These two questionnaires were applied with 300 employees in the Portuguese industrial ceramics sector. Through multiple regression analysis we found that levels of organizational commitment are statistically important to KM dimensions. Furthermore, our analysis indicates that personal commitment is more important than need commitment. These results are discussed and Organizational Behaviour specialists and Work and Organizational psychologists are challenged to assume more responsibility and an active role in KM studies and practices and to explore human issues in this field.

Urinary schistosomiasis among preschool children in Malengachanzi, Nkhotakota District, Malawi: Prevalence and risk factors

Aim: This study was designed to determine the prevalence of and risk factors for schistosomiasis among a group of preschool children in Malawi. Schistosomiasis burden among preschoolers in Malawi is not well documented in the literature. Methods: This study used field research (in the form of a snail survey), laboratory work (urinalysis and microscopy for parasite identification), and questionnaireguided interviews to determine the prevalence of and risk factors for urinary schistosomiasis among children, aged between 6 and 60 months, in Malengachanzi, Nkhotakota District, Malawi. Results: Urinary schistosomiasis prevalence among preschool children was 13%. Of the factors evaluated, only age (P = 0.027) was statistically significantly associated with urinary schistosomiasis risk. Four-year-old preschool children were five times more likely to contract urinary schistosomiasis than two-year-old children (odds ratio [OR] = 5.255; 95% confidence interval [CI] = 1.014-27.237; P = 0.048). Increased contact with infested water among older children likely explains much of their increased risk. Infestation was evidenced by the presence of infected Bulinus globosus snails in the water contact points surveyed. Multiple regression analysis showed that visiting water contact sites daily (OR = 0.898, 95% CI = 0.185-4.350, P = 0.894), bathing in these sites (OR = 9.462, 95% CI = 0.036-0.00, P = 0.430) and lack of knowledge, among caregivers, regarding the causes of urinary schistosomiasis (OR = 0.235, 95% CI = 0.005-1.102, P = 0.066) posed statistically insignificant risk increases for preschoolers contracting urinary schistosomiasis. Conclusions: Urinary schistosomiasis was prevalent among preschool children in Malengachanzi, Nkhotakota District. Contact with infested water puts these children and the general population at risk of infection and reinfection. Inclusion of preschool children in treatment programmes should be considered imperative, along with safe treatment guidelines. To prevent infection, the population in the area should be provided with health education and safe alternative water sources.

Antibiotic Therapy for Very Low BirthWeigh Newborns in NICU

Background: Prolonged empiric antibiotics therapy in neonates results in several adverse consequences including widespread antibiotic resistance, late onset sepsis (LOS), necrotizing enterocolitis (NEC), prolonged hospital course (HC) and increase in mortality rates. Objectives: To assess the risk factors and the outcome of prolonged empiric antibiotic therapy in very low birth weight (VLBW) newborns. Materials and Methods: Prospective study in VLBW neonates admitted to NICU and survived > 2 W, from July 2011 - June 2012. All relevant perinatal and postnatal data including duration of antibiotics therapy (Group I < 2W vs Group II > 2W) and outcome up to the time of discharge or death were documented and compared. Results: Out of 145 newborns included in the study, 62 were in group I, and 83 in Group II. Average duration of antibiotic therapy was 14 days (range 3 - 62 days); duration in Group I and Group II was 102.3 vs 25.510.5 days. Hospital stay was 22.311.5 vs 44.3 14.7 days, respectively. Multiple regression analysis revealed following risk factors as significant for prolonged empiric antibiotic therapy: VLBW especially < 1000 g, (P < 0.001), maternal Illness (P = 0.003), chorioamnionitis (P = 0.048), multiple pregnancy (P = 0.03), non-invasive ventilation (P < 0.001) and mechanical ventilation (P < 0.001). Seventy (48.3%) infants developed LOS; 5 with NEC > stage II, 12 (8.3%) newborns died. Infant mortality alone and with LOS/NEC was higher in group II as compared to group I (P < 0.002 and < 0.001 respectively). Conclusions: Prolonged empiric antibiotic therapy caused increasing rates of LOS, NEC, HC and infant mortality

Differences Among Undergraduate and Graduate Nursing Students’ Cultural Competency

This study examined differences in cultural competency levels between undergraduate and graduate nursing students (age, ethnicity, gender, language at home, education level, program standing, program track, diversity encounters, and previous diversity training). Participants were 83% women, aged 20 to 62; 50% Hispanic/Latino; with a Bachelor of Science in Nursing (n = 82) and a Master of Science in Nursing (n = 62). Degrees included high school diplomas, associate/diplomas, bachelors’ degrees in or out of nursing, and medical doctorate degrees from outside the United States. Students spoke English (n = 82) or Spanish (n = 54). The study used a cross-sectional design guided by the three-dimensional cultural competency model. The Cultural Competency Assessment (CCA) tool is composed of two subscales: Cultural Awareness and Sensitivity (CAS) and Culturally Competent Behaviors (CCB). Multiple regressions, Pearson’s correlations, and ANOVAs determined relationships and differences among undergraduate and graduate students. Findings showed significant differences between undergraduate and graduate nursing students in CAS, p <.016. Students of Hispanic/White/European ethnicity scored higher on the CAS, while White/non-Hispanic students scored lower on the CAS, p < .05. One-way ANOVAs revealed cultural competency differences by program standing (grade-point averages), and by program tracks, between Master of Science in Nursing Advanced Registered Nurse Practitioners and both Traditional Bachelor of Science in Nursing and Registered Nurse-Bachelor of Science in Nursing. Univariate analysis revealed that higher cultural competency was associated with having previous diversity training and participation in diversity training as continuing education. After controlling for all predictors, multiple regression analysis found program level, program standing, and diversity training explained a significant amount of variance in overall cultural competency (p = .027; R2 = .18). Continuing education is crucial in achieving students’ cultural competency. Previous diversity training, graduate education, and higher grade-point average were correlated with higher cultural competency levels. However, increased diversity encounters were not associated with higher cultural competency levels.

Traços desadaptativos da personalidade, sintomas depressivos e afectividade positiva e negativa: Uma amostra com estudantes universitários

Pretendemos estudar quais os traços desadaptativos de personalidade que se relacionam com os sintomas depressivos, a afectividade positiva e negativa, numa amostra de 187 estudantes universitários, entre os 18 e os 43 anos. Calculámos as correlações entre as escalas de padrões de personalidade e as escalas de padrões graves de personalidade do Inventário Multiaxial clínico de Millon II (MCMI-II) com os sintomas depressivos avaliados pela Escala de Depressão do Centro de Estudos Epidemiológicos e com a afectividade positiva e negativa avaliadas pela Escala de Afectividade Positiva e Afectividade Negativa. Realizámos uma análise da regressão múltipla utilizando as escalas de padrões de personalidade do MCMI-II como predictores e o resultado na CES-O, como variável dependente. Obtivemos uma correlação significativa entre os padrões de personalidade borderline, masoquista, esquizotípico, negativista e evitante e paranóide e os sintomas depressivos. A afectividade negativa apresenta-se também positivamente correlacionada com os padrões dependente e esquizóide. A afectividade positiva correlacionou-se significativa e positivamente com os padrões histriónico e narcisista e negativamente com os padrões esquizóide, esquizotípico, negativista, borderline, evitante e masoquista. Na análise de regressão, o padrão borderline prevê a presença de sintomas depressivos e os padrões sádico e dependente também, mas num sentido negativo. /ABSTRACT: We intendend to study wich personality traits relate to depressiva symptoms, and positive and negative affectivity, in a sample of 187 university students, between 18 and 43 years. We did the correlation between the personality patterns scales and the personality patterns of severe personality with the depressive symptoms measured by the Center for Epidemiologic Studies Depression Scale and the positive and negative affectivity measured by the Positive Affect and Negative Affect Shedule. We did a multiple regression analysis using the personality patterns scale of Millon Clinical Multiaxial lnventory (MCMI-II) as predictors and the result of CES-D, as dependent variable. We obtained a significant correlation between the borderline, masochist, schizotypal, negativistic, avoidant and paranoid personality patterns and the depressive symptoms. Negative affectivity relates also positively with dependent and schizoid patterns. Positive affectivity correlated significant and positively with histrionic and narcissistic personality patterns and negatively with schizoid, schizotypal, negativistic, borderline, avoidant and masochist personality patterns. ln the regression analysis, the borderline pattern predicts the presence of depressive symptoms as well as the sadistic and dependent, but in the negative sense.

Necessidades interpessoais e risco de suicídio numa amostra clínica de idosos

O objetivo desta investigação é testar o contributo das necessidades interpessoais - os sentimentos de não pertença e a perceção de ser um fardo – para o risco de suicídio, avaliado através da ideação suicida. Também se pretende investigar a possível interação entre as necessidades interpessoais e respetivos efeitos quadráticos, controlando o impacto de um conjunto de variáveis que apresentam, muitas vezes, uma correlação significativa com a ideação suicida. Neste estudo participaram 80 utentes idosos em recuperação de uma doença aguda. De acordo com os resultados, os sentimentos de não pertença e a perceção de ser um fardo correlacionam-se com a ideação suicida. No entanto, quando numa análise da regressão múltipla se considera simultaneamente o efeito de ambas as variáveis, apenas os sentimentos de não pertença contribuem significativamente na previsão da ideação suicida. Não se verificaram efeitos de interação nem efeitos quadráticos entre as variáveis necessidades interpessoais; Abstract: “Interpersonal needs and suicide risk in a sample of elderly patients” The aim of this study is to test the contribution of interpersonal needs - thwarted belongingness and perceived burdensomeness - to the risk of suicide, assessed by the presence of suicidal ideation. It also intends to investigate the possible interaction between interpersonal needs and the respective quadratic effects, by controlling the impact of a set of variables which have, many times, a significant correlation with suicidal ideation. In this study participated 80 elderly patients recovering from an acute medical condition. According to the results, thwarted belongingness and perceived burdensomeness are correlated with suicidal ideation. However, when in a multiple regression analysis we considerate simultaneously the effect of both variables, only thwarted belongingness contributes significatively to suicide ideation prediction. No interactions effects or quadratic effects were observed between interpersonal needs variables.

Dimension Reduction of the Explanatory Variables in Multiple Linear Regression

2002 Mathematics Subject Classification: 62J05, 62G35.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Ocular Pulse Amplitude and Doppler Waveform Analysis in Glaucoma Patients

PURPOSE: To determine the correlation between ocular blood flow velocities and ocular pulse amplitude (OPA) in glaucoma patients using colour Doppler imaging (CDI) waveform analysis. METHOD: A prospective, observer-masked, case-control study was performed. OPA and blood flow variables from central retinal artery and vein (CRA, CRV), nasal and temporal short posterior ciliary arteries (NPCA, TPCA) and ophthalmic artery (OA) were obtained through dynamic contour tonometry and CDI, respectively. Univariate and multiple regression analyses were performed to explore the correlations between OPA and retrobulbar CDI waveform and systemic cardiovascular parameters (blood pressure, blood pressure amplitude, mean ocular perfusion pressure and peripheral pulse). RESULTS: One hundred and ninety-two patients were included [healthy controls: 55; primary open-angle glaucoma (POAG): 74; normal-tension glaucoma (NTG): 63]. OPA was statistically different between groups (Healthy: 3.17 ± 1.2 mmHg; NTG: 2.58 ± 1.2 mmHg; POAG: 2.60 ± 1.1 mmHg; p < 0.01), but not between the glaucoma groups (p = 0.60). Multiple regression models to explain OPA variance were made for each cohort (healthy: p < 0.001, r = 0.605; NTG: p = 0.003, r = 0.372; POAG: p < 0.001, r = 0.412). OPA was independently associated with retrobulbar CDI parameters in the healthy subjects and POAG patients (healthy CRV resistance index: β = 3.37, CI: 0.16-6.59; healthy NPCA mean systolic/diastolic velocity ratio: β = 1.34, CI: 0.52-2.15; POAG TPCA mean systolic velocity: β = 0.14, CI 0.05-0.23). OPA in the NTG group was associated with diastolic blood pressure and pulse rate (β = -0.04, CI: -0.06 to -0.01; β = -0.04, CI: -0.06 to -0.001, respectively). CONCLUSIONS: Vascular-related models provide a better explanation to OPA variance in healthy individuals than in glaucoma patients. The variables that influence OPA seem to be different in healthy, POAG and NTG patients.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Trabecular bone score (TBS) the new parameter of 2D texture analysis for the evaluation of 3D bone micro architecture status

X-ray is a technology that is used for numerous applications in the medical field. The process of X-ray projection gives a 2-dimension (2D) grey-level texture from a 3- dimension (3D) object. Until now no clear demonstration or correlation has positioned the 2D texture analysis as a valid indirect evaluation of the 3D microarchitecture. TBS is a new texture parameter based on the measure of the experimental variogram. TBS evaluates the variation between 2D image grey-levels. The aim of this study was to evaluate existing correlations between 3D bone microarchitecture parameters - evaluated from μCT reconstructions - and the TBS value, calculated on 2D projected images. 30 dried human cadaveric vertebrae were acquired on a micro-scanner (eXplorer Locus, GE) at isotropic resolution of 93 μm. 3D vertebral body models were used. The following 3D microarchitecture parameters were used: Bone volume fraction (BV/TV), Trabecular thickness (TbTh), trabecular space (TbSp), trabecular number (TbN) and connectivity density (ConnD). 3D/2D projections has been done by taking into account the Beer-Lambert Law at X-ray energy of 50, 100, 150 KeV. TBS was assessed on 2D projected images. Correlations between TBS and the 3D microarchitecture parameters were evaluated using a linear regression analysis. Paired T-test is used to assess the X-ray energy effects on TBS. Multiple linear regressions (backward) were used to evaluate relationships between TBS and 3D microarchitecture parameters using a bootstrap process. BV/TV of the sample ranged from 18.5 to 37.6% with an average value at 28.8%. Correlations' analysis showedthat TBSwere strongly correlatedwith ConnD(0.856≤r≤0.862; p<0.001),with TbN (0.805≤r≤0.810; p<0.001) and negatively with TbSp (−0.714≤r≤−0.726; p<0.001), regardless X-ray energy. Results show that lower TBS values are related to "degraded" microarchitecture, with low ConnD, low TbN and a high TbSp. The opposite is also true. X-ray energy has no effect onTBS neither on the correlations betweenTBS and the 3Dmicroarchitecture parameters. In this study, we demonstrated that TBS was significantly correlated with 3D microarchitecture parameters ConnD and TbN, and negatively with TbSp, no matter what X-ray energy has been used. This article is part of a Special Issue entitled ECTS 2011. Disclosure of interest: None declared.

Characteristics and effectiveness of diabetes self-management educational programs targeted to racial/ethnic minority groups: a systematic review, meta-analysis and meta-regression.

BACKGROUND It is not clear to what extent educational programs aimed at promoting diabetes self-management in ethnic minority groups are effective. The aim of this work was to systematically review the effectiveness of educational programs to promote the self-management of racial/ethnic minority groups with type 2 diabetes, and to identify programs' characteristics associated with greater success. METHODS We undertook a systematic literature review. Specific searches were designed and implemented for Medline, EMBASE, CINAHL, ISI Web of Knowledge, Scirus, Current Contents and nine additional sources (from inception to October 2012). We included experimental and quasi-experimental studies assessing the impact of educational programs targeted to racial/ethnic minority groups with type 2 diabetes. We only included interventions conducted in countries members of the OECD. Two reviewers independently screened citations. Structured forms were used to extract information on intervention characteristics, effectiveness, and cost-effectiveness. When possible, we conducted random-effects meta-analyses using standardized mean differences to obtain aggregate estimates of effect size with 95% confidence intervals. Two reviewers independently extracted all the information and critically appraised the studies. RESULTS We identified thirty-seven studies reporting on thirty-nine educational programs. Most of them were conducted in the US, with African American or Latino participants. Most programs obtained some benefits over standard care in improving diabetes knowledge, self-management behaviors and clinical outcomes. A meta-analysis of 20 randomized controlled trials (3,094 patients) indicated that the programs produced a reduction in glycated hemoglobin of -0.31% (95% CI -0.48% to -0.14%). Diabetes knowledge and self-management measures were too heterogeneous to pool. Meta-regressions showed larger reduction in glycated hemoglobin in individual and face to face delivered interventions, as well as in those involving peer educators, including cognitive reframing techniques, and a lower number of teaching methods. The long-term effects remain unknown and cost-effectiveness was rarely estimated. CONCLUSIONS Diabetes self-management educational programs targeted to racial/ethnic minority groups can produce a positive effect on diabetes knowledge and on self-management behavior, ultimately improving glycemic control. Future programs should take into account the key characteristics identified in this review.

A combined analysis of the short-term effects of photochemical air pollutants on mortality within the EMECAM project.

In recent years, some epidemiologic studies have attributed adverse effects of air pollutants on health not only to particles and sulfur dioxide but also to photochemical air pollutants (nitrogen dioxide and ozone). The effects are usually small, leading to some inconsistencies in the results of the studies. Furthermore, the different methodologic approaches of the studies used has made it difficult to derive generic conclusions. We provide here a quantitative summary of the short-term effects of photochemical air pollutants on mortality in seven Spanish cities involved in the EMECAM project, using generalized additive models from analyses of single and multiple pollutants. Nitrogen dioxide and ozone data were provided by seven EMECAM cities (Barcelona, Gijón, Huelva, Madrid, Oviedo, Seville, and Valencia). Mortality indicators included daily total mortality from all causes excluding external causes, daily cardiovascular mortality, and daily respiratory mortality. Individual estimates, obtained from city-specific generalized additive Poisson autoregressive models, were combined by means of fixed effects models and, if significant heterogeneity among local estimates was found, also by random effects models. Significant positive associations were found between daily mortality (all causes and cardiovascular) and NO(2), once the rest of air pollutants were taken into account. A 10 microg/m(3) increase in the 24-hr average 1-day NO(2)level was associated with an increase in the daily number of deaths of 0.43% [95% confidence interval (CI), -0.003-0.86%] for all causes excluding external. In the case of significant relationships, relative risks for cause-specific mortality were nearly twice as much as that for total mortality for all the photochemical pollutants. Ozone was independently related only to cardiovascular daily mortality. No independent statistically significant relationship between photochemical air pollutants and respiratory mortality was found. The results in this study suggest that, given the present levels of photochemical pollutants, people living in Spanish cities are exposed to health risks derived from air pollution.

Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin.

Background/objectives:Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.Subjects/methods:Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.Results:A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6âeuro0/00kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.Conclusions:Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.