Impact of the COVID-19 pandemic on the mental health of frontline healthcare workers in a highly affected region in Brazil.

BACKGROUND: The COVID-19 pandemic had a major impact on the mental health of healthcare workers (HCWs), especially in low and middle-income countries, which had to face additional political, social, and economic challenges. We thus aimed to assess the prevalence of mental health outcomes and the associated factors in HCWs treating COVID-19 patients in one of the most affected regions in Brazil. METHODS: We used the Respondent-Driven Sampling method to assess the risks of COVID-19 infection and symptoms of mental disorders in nurses, nursing technicians, and physicians who worked on the frontline in the metropolitan region of Recife. 865 healthcare workers completed a survey regarding sociodemographic data, work-related risks, and symptoms of mental disorders - SRQ-20 for common mental disorders (CMD); AUDIT-C for problematic alcohol use; GAD-7 for anxiety; PHQ-9 for depression; PCL-5 for post-traumatic stress disorder (PTSD). Gile's successive sampling estimator was used to produce the weighted estimates by professional category. A Poisson regression model with robust variance was used to analyze factors associated with a positive screening for CMD. We will present the results of a cross-sectional analysis of the mental health outcomes after the first peak of COVID-19 - from August 2020 to February 2021. RESULTS: The prevalence ratios for a positive screening for CMD were 34.9% (95% CI: 27.8-41.9) in nurses, 28.6% (95% CI: 21.3-36.0) in physicians, and 26.6% (95% CI: 16.8-36.5) in nursing technicians. Nurses presented a higher prevalence of depressive symptoms (23%). Positive screening for problematic alcohol use (10.5 to14.0%), anxiety (10.4 to 13.3%), and PTSD (3.3 to 4.4%) were similar between the professional categories. The main factors associated with CMD in nurses and physicians were related to an intrinsic susceptibility to mental illness, such as previous or family history of psychiatric disorder, and female sex. Among nurse technicians, work-related factors, such as accidents with biological material, presented the strongest association with CMD. CONCLUSION: The mental health of HCWs fighting COVID-19 in Recife was severely affected. It is crucial that healthcare services provide adequate working conditions and psychological support, investing in programs to promote and protect HCWs mental health.

Modeling the impact of child vaccination (5-11 y) on overall COVID-19 related hospitalizations and mortality in a context of omicron variant predominance and different vaccination coverage paces in Brazil.

Background: Developing countries have experienced significant COVID-19 disease burden. With the emergence of new variants, particularly omicron, the disease burden in children has increased. When the first COVID-19 vaccine was approved for use in children aged 5-11 years of age, very few countries recommended vaccination due to limited risk-benefit evidence for vaccination of this population. In Brazil, ranking second in the global COVID-19 death toll, the childhood COVID-19 disease burden increased significantly in early 2022. This prompted a risk-benefit assessment of the introduction and scaling-up of COVID-19 vaccination of children. Methods: To estimate the potential impact of vaccinating children aged 5-11 years with mRNA-based COVID-19 vaccine in the context of omicron dominance, we developed a discrete-time SEIR-like model stratified in age groups, considering a three-month time horizon. We considered three scenarios: No vaccination, slow, and maximum vaccination paces. In each scenario, we estimated the potential reduction in total COVID-19 cases, hospitalizations, deaths, hospitalization costs, and potential years of life lost, considering the absence of vaccination as the base-case scenario. Findings: We estimated that vaccinating at a maximum pace could prevent, between mid-January and April 2022, about 26,000 COVID-19 hospitalizations, and 4200 deaths in all age groups; of which 5400 hospitalizations and 410 deaths in children aged 5-11 years. Continuing vaccination at a slow/current pace would prevent 1450 deaths and 9700 COVID-19 hospitalizations in all age groups in this same time period; of which 180 deaths and 2390 hospitalizations in children only. Interpretation: Maximum vaccination of children results in a significant reduction of COVID-19 hospitalizations and deaths and should be enforced in developing countries with significant disease incidence in children. Funding: This manuscript was funded by the Brazilian Council for Scientific and Technology Development (CNPq - Process # 402834/2020-8).

Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil.

We simulate the impact of school reopening during the COVID-19 pandemic in three major urban centers in Brazil to identify the epidemiological indicators and the best timing for the return of in-school activities and the effect of contact tracing as a mitigation measure. Our goal is to offer guidelines for evidence-based policymaking. We implement an extended SEIR model stratified by age and considering contact networks in different settings - school, home, work, and community, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening, and also estimate the number of hospitalization and deaths averted by the implementation of contact tracing. Reopening schools results in a non-linear increase in reported COVID-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects in reducing the total number of hospitalizations and deaths. Policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. While contact tracing strategies prevent new infections within school environments, they alone are not sufficient to avoid significant impacts on community transmission.

Modelling optimal vaccination strategies against COVID-19 in a context of Gamma variant predominance in Brazil.

INTRODUCTION: Brazil experienced moments of collapse in its health system throughout 2021, driven by the emergence of variants of concern (VOC) combined with an inefficient initial vaccination strategy against Covid-19. OBJECTIVES: To support decision-makers in formulating COVID-19 immunization policy in the context of limited vaccine availability and evolving variants over time, we evaluate optimal strategies for Covid-19 vaccination in Brazil in 2021, when vaccination was rolled out during Gamma variant predominance. METHODS: Using a discrete-time epidemic model we estimate Covid-19 deaths averted, considering the currently Covid-19 vaccine products and doses available in Brazil; vaccine coverage by target population; and vaccine effectiveness estimates. We evaluated a 5-month time horizon, from early August to the end of December 2021. Optimal vaccination strategies compared the outcomes in terms of averted deaths when varying dose intervals from 8 to 12 weeks, and choosing the minimum coverage levels per age group required prior to expanding vaccination to younger target populations. We also estimated dose availability required over time to allow the implementation of optimal strategies. RESULTS: To maximize the number of averted deaths, vaccine coverage of at least 80 % should be reached in older age groups before starting vaccination into subsequent younger age groups. When evaluating varying dose intervals for AZD1222, reducing the dose interval from 12 to 8 weeks for the primary schedule would result in fewer COVID-19 deaths, but this can only be implemented if accompanied by an increase in vaccine supply of at least 50 % over the coming six-months in Brazil. CONCLUSION: Covid-19 immunization strategies should be tailored to local vaccine product availability and supply over time, circulating variants of concern, and vaccine coverage in target population groups. Modelling can provide valuable and timely evidence to support the implementation of vaccination strategies considering the local context, yet following international and regional technical evidence-based guidance.

PSS Health: como calcular tamanho de amostra para testar relações de variáveis com um desfecho binário / PSS Health: how to calculate the sample size to test variables relationships with a binary outcome

Dando continuidade à série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa, esta edição apresenta um passo a passo de como realizar o cálculo para tamanho de amostra e de quais informações são necessárias para testar relações estatísticas entre variáveis e um desfecho binário: comparação de proporções entre grupos independentes (dois ou mais), comparação de duas proporções dependentes e regressão logística. Todos os exemplos também são ilustrados e disponibilizados em vídeos no canal da Unidade de Bioestatística.

Following the series of articles that aim to guide the user in using the PSS Health tool for planning research, this issue presents a step-by-step guide on how to perform the sample size calculation and what information is needed to test statistical relationships between variables and a binary outcome: comparison of proportions between independent groups (two or more), comparison of two dependent proportions, and logistic regression. All examples are also illustrated and available in videos on the Biostatistics Unit's channel.

PSS Health: como calcular tamanho de amostra para testes de comparação de médias de dois grupos / PSS Health: how to calculate sample sizes for mean comparison tests between two groups

Dando continuidade à série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa, esta edição apresenta um passo a passo de como realizar o cálculo e de quais informações são necessárias para comparar médias: de dois grupos dependentes ou independentes, de dois grupos independentes com duas medidas repetidas (deltas), e com duas ou mais medidas repetidas. Todos os exemplos também são ilustrados e disponibilizados em vídeos no canal da Unidade de Bioestatística.

Following the series of articles aiming to guide users in using the PSS Health tool for research planning, this issue presents a step-by-step guide on how to calculate and what information is needed to compare means between 2 dependent or independent groups, 2 independent groups with 2 repeated measures (deltas), and 2 independent groups with 2 or more repeated measures. All examples are accompanied by figures and available in video on the Biostatistics Unit's channel.

PSS Health: como calcular tamanho de amostra para estimar média, proporção e correlação / PSS Health: how to calculate a sample size to estimate means, proportions, and correlations

A ferramenta PSS Health (Power and Sample Size for Health Researchers) foi desenvolvida com o propósito de facilitar o cálculo do tamanho amostral e do poder de testes de hipóteses para diferentes objetivos de estudo, usando interface amigável e terminologia comum à área da saúde. Este é o primeiro de uma série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa. Neste artigo, se ensina como utilizar o PSS Health quando o objetivo principal do estudo é estimar uma média, estimar uma proporção (prevalência ou incidência) ou estimar uma correlação. São disponibilizados vídeos demonstrando o uso da ferramenta em cada um dos contextos citados. (AU)

The PSS Health (Power and Sample Size for Health Researchers) tool was developed with the purpose of facilitating the calculation of sample size and power of hypothesis tests for different study objectives, based on a user-friendly interface and common health care terminology. This is the first in a series of articles intending to guide the user in how to use the PSS Health tool for planning a research project. This article teaches how to use PSS Health when the main objective of the study is to estimate means, proportions (prevalence or incidence), or correlations. Videos showing how to use the tool in each of the mentioned contexts are available. (AU)

Diet quality index for Brazilian adolescents: the ERICA study.

PURPOSE: This study aimed to assess the dietary patterns of adolescents using a food-based diet quality index and their compliance with a healthy dietary guideline METHODS: Participants included 71,553 Brazilian adolescents (12-17 years old) from the Study of Cardiovascular Risks in Adolescents (ERICA), a cross-sectional school-based multicenter study.. Dietary intake was measured by one 24-h recall. A second recall was collected in a random subsample (~ 10%) to correct within-person variability. The Diet Quality Index for Adolescents adapted for Brazilians (DQIA-BR) was used to measure the overall quality of the dietary intake. The National Cancer Institute method was applied to estimate usual dietary intake. The DQIA-BR and the distribution of its components (quality, diversity, and equilibrium) were analyzed according to sex, geographical area, and type of school RESULTS: The mean (SD) DQIA-BR scores were 14.8% (6.1%) for females and 19.0% (6.3%) for males. All analyzed strata revealed low scores of DQIA-BR and its components. The median usual intake was five to sevenfold below the recommendations for vegetables and fruits and approximately twofold below the recommendations for dairy. The highest DQIA-BR mean scores were found in the northern region [17.0% (6.4%), females; 20.7% (6.3%), males]. Adolescents in both types of schools had relatively similar median intakes of snacks (~ 85 g) and sugared drinks (~ 600 ml) CONCLUSIONS: The overall diet quality of Brazilian adolescents is inadequate based on evaluated parameters in all regions and socioeconomic backgrounds.

Power and sample size for health researchers: uma ferramenta para cálculo de tamanho amostral e poder do teste voltado a pesquisadores da área da saúde / Power and sample size for health researchers: a tool for calculating sample size and statistical power designed for health researchers

Nas próximas edições da seção de Bioestatística da revistaClinical & Biomedical Researchuma nova série de artigos será publicada abordando um assunto de grande importância ao planejar uma pesquisa: o tamanho de amostra mínimo necessário para atingir os objetivos do estudo. Nessa série será apresentado como calcular o tamanho de uma amostra usando a ferramenta PSSHealth(Power and Sample Size for Health Researchers), construído em linguagem R por meio do pacote Shiny, para diferentes tipos e objetivos de estudo, direcionado à pesquisadores da área da saúde, utilizando termos e conceitos comumente utilizados nesta área. Além disso, o pacote fornece uma sugestão de texto com as informações consideradas no cálculo, e como devem ser descritas, com a finalidade de minimizar problemas de interpretação por parte dos pesquisadores. Neste primeiro artigo será apresentada essa ferramenta desenvolvida pela Unidade de Bioestatística do Grupo de Pesquisa e Pós-Graduação do Hospital de Clínicas de Porto Alegre, que permite calcular não apenas o tamanho de amostra, mas também o poder de um teste de hipóteses. (AU)

In the next issues ofClinical and Biomedical Research, the Biostatistics section will introduce a new series of articles addressing a very important subject for research planning: the minimum sample size to achieve the aim of a study. This series will show how to calculate sample size using PSS Health (Power and Sample Size for Health Researchers). This tool was built using R language through the Shiny package. It can be used for different types of study and is designed for health researchers by using terms and concepts commonly used in this area. PSS Health also suggests a text with information considered in the calculation to minimize problems of interpretation by the researchers. In this first article, a general overview of PSS Health will be presented. This tool, which was developed by the Research and Graduate Group Biostatistics Unit of the Hospital de Clínicas de Porto Alegre, is useful not only to calculate sample size but also to determine power of a hypothesis test. (AU)

Equívocos estatísticos: perguntas que você sempre quis fazer, mas nunca teve coragem / Statistical misconceptions: questions you've always wanted to ask, but never dared

Este artigo visa elucidar algumas dúvidas enfrentadas ou equívocos estatísticos cometidos por pesquisadores de diversas áreas. São explanados os temas: "tradução não é validação", "análise fatorial exploratória ou confirmatória", "nem todo estudo com dois grupos tem delineamento caso-controle", "teste ou ajuste de Bonferroni", "tamanho de amostra para teste de hipóteses e/ou para intervalo de confiança", e "testes ou dados paramétricos". A abordagem é realizada em uma linguagem acessível ao público leigo, utilizando exemplos e sugerindo referências para aprofundar o conhecimento.(AU)

This article aims to answer some questions and elucidate statistical misconceptions of researchers from different fields. The following topics are addressed: "translation is not validation", "exploratory or confirmatory factor analysis", "not every study with two groups is a case-control study", "Bonferroni test or adjustment", "sample size for testing hypotheses and/or for confidence intervals", and "parametric data or tests". The topics are explained in lay terms, using examples and suggesting references to advance knowledge.(AU)

Performance of the Gail and Tyrer-Cuzick breast cancer risk assessment models in women screened in a primary care setting with the FHS-7 questionnaire.

Breast cancer (BC) risk assessment models base their estimations on different aspects of a woman's personal and familial history. The Gail and Tyrer-Cuzick models are the most commonly used, and BC risks assigned by them vary considerably especially concerning familial history. In this study, our aim was to compare the Gail and Tyrer-Cuzick models after initial screening for familial history of cancer in primary care using the FHS-7 questionnaire. We compared 846 unrelated women with at least one positive answer to any of the seven FHS-7 questions (positive group) and 892 unrelated women that answered negatively (negative group). Concordance between BC risk estimates was compared by Bland-Altman graphics. Mean BC risk estimates were higher using the Tyrer-Cuzick Model in women from the positive group, while women from the negative group had higher BC risk estimates using the Gail model. With increasing estimates, discordance also increased, mainly in the FHS-7 positive group. Our results show that in women with a familial history of cancer, the Gail model underestimates risk and the Tyrer-Cuzick seems to be more appropriate. FHS-7 can be a useful tool for the identification of women with higher breast cancer risks in the primary care setting.

Modelagem estatística: perguntas que você sempre quis fazer, mas nunca teve coragem / Statistical modeling: questions you have always wanted to ask but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas dos pesquisadores do Hospital de Clínicas de Porto Alegre sobre estatística, este quarto artigo se propõe a responder às principais dúvidas levantadas sobre modelagem estatística. São discutidas questões referentes à classificação de variáveis em independentes e dependentes, diferenças entre correlação, associação e regressão, os principais tipos de regressão e quais etapas são necessárias na construção de modelos. Os conceitos são abordados numa linguagem acessível ao público leigo e diversas referências são sugeridas para os curiosos em relação ao tema. (AU)

Continuing the series of articles "Questions you have always wanted to ask but never had the courage to," which aims to answer the most common questions of researchers at Hospital de Clínicas de Porto Alegre regarding statistics and to suggest references for a better understanding, this forth article addresses the topic of statistical modeling. Questions about classification of variables as dependent or independent, differences between correlation, association and regression, types of regression and steps for statistical modeling are discussed. The concepts are explained in plain language for lay readers and several references are suggested for those curious about the topic. (AU)

Bioestatística e epidemiologia: perguntas que você sempre quis fazer, mas nunca teve coragem / Biostatistics and epidemiology: questions you always wanted to ask but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas estatísticas levantadas por pesquisadores da área da saúde, este terceiro artigo aborda o contexto epidemiológico. Neste contexto, foram diferenciadas as principais medidas como prevalência, incidência, Odds Ratio (OR), Risco Relativo (RR), Razão de Prevalência (RP) e Hazard Ratio (HR), foi esclarecido o uso de análises por intenção de tratar e análise por protocolo, e também discutidos alguns dos termos comumente utilizados e pouco compreendidos como tipo de amostra, nível de evidência, relevância clínica e estatística, entre outros. (AU)

Continuing the series of articles "Questions you always wanted to ask but never had the courage to," which aims to answer key statistical questions raised by health researchers and suggest references for a better understanding, this third article addresses the epidemiological context. In this context, important measures such as prevalence, incidence, odds ratio (OR), relative risk (RR), prevalence ratio (PR) and hazard ratio (HR) were differentiated; the use of intention-to-treat analysis and per-protocol analysis was clarified; and some terms commonly used and poorly understood were discussed, such as type of sample, level of evidence, clinical and statistical relevance, among others. (AU)

Electronic Version of the EQ-5D Quality-of-Life Questionnaire: Adaptation to a Brazilian Population Sample.

OBJECTIVES: To assess the measurement equivalence of the original paper version of an adapted tablet version of the EuroQol five-dimensional questionnaire (EQ-5D). METHODS: A randomly selected sample of 509 individuals aged 18 to 64 years from the general population responded to the EQ-5D at two time points separated by a minimum interval of 24 hours and were allocated to one of the following groups: test-retest group (tablet-tablet) or crossover group (paper-tablet and tablet-paper). Agreement between methods was determined using the intraclass correlation coefficient (ICC) and the κ coefficient. RESULTS: In the crossover group, the following ICC values were obtained: 0.76 (confidence interval [CI] 0.58-0.89) for EQ-5D scores and 0.77 (CI 0.68-0.84) for visual analogue scale in subjects responding first to the tablet version; 0.83 (CI 0.75-0.89) for EQ-5D scores and 0.75 (CI 0.67-0.85) for visual analogue scale in subjects responding first to the paper version. In the test-retest group, the ICC was 0.85 (CI 0.73-0.91) for EQ-5D scores and 0.79 (CI 0.66-0.87) for visual analogue scale. The κ values were higher than 0.69 in this group. The internal consistencies of the paper and tablet methods were similar. CONCLUSIONS: The paper and tablet versions of the EQ-5D are equivalent. Test-retest and crossover agreement was high and the acceptability of the methods was similar among individuals.

The progression rate of spinocerebellar ataxia type 2 changes with stage of disease.

BACKGROUND: Spinocerebellar ataxia type 2 (SCA2) affects several neurological structures, giving rise to multiple symptoms. However, only the natural history of ataxia is well known, as measured during the study duration. We aimed to describe the progression rate of ataxia, by the Scale for the Assessment and Rating of Ataxia (SARA), as well as the progression rate of the overall neurological picture, by the Neurological Examination Score for Spinocerebellar Ataxias (NESSCA), and not only during the study duration but also in a disease duration model. Comparisons between these models might allow us to explore whether progression is linear during the disease duration in SCA2; and to look for potential modifiers. RESULTS: Eighty-eight evaluations were prospectively done on 49 symptomatic subjects; on average (SD), study duration and disease duration models covered 13 (2.16) months and 14 (6.66) years of individuals' life, respectively. SARA progressed 1.75 (CI 95%: 0.92-2.57) versus 0.79 (95% CI 0.45 to 1.14) points/year in the study duration and disease duration models. NESSCA progressed 1.45 (CI 95%: 0.74-2.16) versus 0.41 (95% CI 0.24 to 0.59) points/year in the same models. In order to explain these discrepancies, the progression rates of the study duration model were plotted against disease duration. Then an acceleration was detected after 10 years of disease duration: SARA scores progressed 0.35 before and 2.45 points/year after this deadline (p = 0.013). Age at onset, mutation severity, and presence of amyotrophy, parkinsonism, dystonic manifestations and cognitive decline at baseline did not influence the rate of disease progression. CONCLUSIONS: NESSCA and SARA progression rates were not constant during disease duration in SCA2: early phases of disease were associated with slower progressions. Modelling of future clinical trials on SCA2 should take this phenomenon into account, since disease duration might impact on inclusion criteria, sample size, and study duration. Our database is available online and accessible to future studies aimed to compare the present data with other cohorts.

Estatística descritiva: perguntas que você sempre quis fazer, mas nunca teve coragem / Descriptive statistics: questions you have always wanted to ask, but never had the courage to

A revista do HCPA (Clinical & Biomedical Research) está reabrindo a seção de Bioestatística com o intuito de apresentar artigos explicativos, conceituais ou tutoriais, de modo a elucidar os leitores sobre os mais diversos temas estatísticos. Neste contexto, este artigo será o primeiro de uma série que tem como objetivo responder algumas das questões mais levantadas por pesquisadores da área da saúde. Começando pela Estatística Descritiva, alguns conceitos são esclarecidos e diversas referências são indicadas para o estudo do tema e para análises em SPSS ou R-project. (AU)

The HCPA journal (Clinical & Biomedical Research) is reopening its Biostatistics section with the aim of presenting readers with explanatory, conceptual or tutorial articles on a wide range of statistical topics. In this context, this is the first in a series of articles seeking to answer some of the questions raised by health researchers. Starting with descriptive statistics, some concepts are introduced and several references are indicated for those interested in studying the topic and performing analyses in SPSS or R-project. (AU)

Cancer in Machado-Joseph disease patients-low frequency as a cause of death.

Since polyglutamine diseases have been related to a reduced risk of cancer, we aimed to study the 15 years cumulative incidence of cancer (CIC) (arm 1) and the proportion of cancer as a cause of death (arm 2) in symptomatic carriers of spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD). SCA3/MJD and control individuals from our state were invited to participate. A structured interview was performed. CIC as published by the Brazilian National Institute of Cancer, was used as populational control. Causes of death were obtained from the Public Information System on Mortality. We interviewed 154 SCA3/MJD patients and 80 unrelated controls: CIC was 7/154 (4.5%) and 5/80 (6.3%), respectively. The interim analysis for futility showed that the number of individuals required to detect a significant difference between groups (1938) would be three times larger than the existing local SCA3/MJD population (625), for an absolute risk reduction of 1.8%. Then this study arm was discontinued due to lack of power. In the same period, cancer was a cause of death in 9/101 (8.9%) SCA3/MJD and in 52/202 (26.2%) controls, with an absolute reduction risk of 17.3% (OR 0.27, 95%CI 0.13 to 0.58, p = 0.01). A significant reduction of cancer as cause of death was observed in SCA3/MJD, suggesting a common effect to all polyglutamine diseases.

Agreement of dietary fiber and calorie intake values according to the choice of nutrient composition and household measure tables / Concordância dos valores de consumo de fibras alimentares e de calorias diárias de acordo com a escolha da tabela de composição de nutrientes e de medidas caseiras

ABSTRACT Objective: To analyze the variations in the daily intake of dietary fiber and calories according to the different nutrient composition and homemade measure tables. Methods: Five different methods based on different nutrient composition and household measure tables were used to calculate daily calorie and fiber intake, measured using a food frequency questionnaire, of 633 pregnant women receiving care in primary health care units in the Southern region of Brazil; they were selected to participate in a cohort study. The agreement between the five methods was evaluated using the Kappa and weighted Kappa coefficients. The Nutritional Support Table, a Brazilian traditional food composition table and the Brazilian household expenditure survey were used in Method 1. Brazilian Food Composition Table and the Table for the Assessment of Household Measures (Pinheiro) were used in Methods 2 and 3. The average values of all subtypes of food listed in the Brazilian Food Composition Table for each corresponding item in the food frequency questionnaire were calculated in the method 3. The United States Department of Agriculture Food Composition Table and the table complied by Pinheiro were used in Method 4. The Brazilian Food Composition Table and the Brazilian household expenditure survey were used in Method 5. Results: The highest agreement of calorie intake values were found between Methods 2 and 3 (Kappa=0.94; 0.92-0.95), and the lowest agreement was found between Methods 4 and 5 (Kappa=0.46; 0.42-0.50). As for the fiber intake, the highest agreement was found between Methods 2 and 5 (Kappa=0.87; 0.82-0.90), and the lowest agreement was observed between Methods 1 and 4 (Kappa=0.36; 0.3-0.43). Conclusion: Considerable differences were found between the nutritional composition tables. Therefore, the choice of the table can influence the comparability between studies.

RESUMO Objetivo: Analisar a variação no consumo diário de fibras e de calorias de acordo com diferentes tabelas de composição nutricional e de medidas caseiras. Métodos: Cinco métodos baseados em diferentes tabelas de composição nutricional e de medidas caseiras foram utilizados para calcular o consumo diário de calorias e de fibras, aferidos por questionário de frequência alimentar em 633 gestantes atendidas na atenção primária do Sul do Brasil, arroladas para estudo de coorte. A concordância entre os cinco métodos foi avaliada pelo coeficiente Kappa e Kappa Ponderado. A Tabela de Suporte Nutricional e a de medidas caseiras do Estudo Nacional de Despesas Familiares foram usadas no método 1. A Tabela Brasileira de Composição de Alimentos e a Tabela para Avaliação de Consumo Alimentar em Medidas Caseiras (Pinheiro) foram utilizadas pelos métodos 2 e 3, sendo que no método 3 calculou-se a média dos subtipos do alimento encontradas na Tabela Brasileira de Composição de Alimentos correspondente ao item do Questionário de Frequência Alimentar. No método 4, foram utilizadas a Tabela Americana da United States Department of Agriculture e a Pinheiro e, no método 5, a Tabela Brasileira de Composição de Alimentos e a do Estudo Nacional de Despesas Familiares. Resultados: A maior concordância entre valores de calorias ocorreu entre os métodos 2 e 3 (Kappa=0,94; 0,92-0,95) e a menor concordância foi entre os métodos 4 e 5 (Kappa=0,46; 0,42-0,50). Já para os valores de fibras, a melhor concordância foi entre os métodos 2 e 5 (Kappa=0,87; 0,82-0,90) e a menor entre os métodos 1 e 4 (Kappa=0,36; 0,31-0,43). Conclusão: Diferenças encontradas, conforme escolha da tabela de composição nutricional, são relevantes, podendo influenciar a comparabilidade entre estudos.

Contextual and individual factors associated with dissatisfaction with the Brazilian Unified National Health System, 2011-2012.

User satisfaction is known to be related to quality of healthcare. The aim of this study was to evaluate the influence of contextual and individual factors associated with user dissatisfaction with the Brazilian Unified National Health System (SUS). This was a cross-sectional multilevel study. Data were collected via telephone by the ombudsman's office of the SUS. Telephone numbers were randomly selected from a telephone company database. Health services, socioeconomic, and individual demographic variables were evaluated, in addition to information on the municipalities. The outcome variable was dissatisfaction with the SUS. Hierarchical multilevel logistic regression was used, and 18,673 individuals were contacted. Prevalence of dissatisfaction was 63.4% (95%CI: 62.7-64.1). Unmet demand (OR = 3.66), waiting time > 4 hours (OR = 2.82), and number of Primary Healthcare Units (OR = 0.89) were associated statistically with dissatisfaction. Characteristics of the health teams' work process showed a strong association with dissatisfaction.

Contextual and individual factors associated with dissatisfaction with the Brazilian Unified National Health System, 2011-2012 / Fatores contextuais e individuais associados à insatisfação com o Sistema Único de Saúde, 2011-2012 / Factores contextuales e individuales asociados a la insatisfacción con el Sistema Único de Salud brasileño, 2011-2012

Abstract: User satisfaction is known to be related to quality of healthcare. The aim of this study was to evaluate the influence of contextual and individual factors associated with user dissatisfaction with the Brazilian Unified National Health System (SUS). This was a cross-sectional multilevel study. Data were collected via telephone by the ombudsman's office of the SUS. Telephone numbers were randomly selected from a telephone company database. Health services, socioeconomic, and individual demographic variables were evaluated, in addition to information on the municipalities. The outcome variable was dissatisfaction with the SUS. Hierarchical multilevel logistic regression was used, and 18,673 individuals were contacted. Prevalence of dissatisfaction was 63.4% (95%CI: 62.7-64.1). Unmet demand (OR = 3.66), waiting time > 4 hours (OR = 2.82), and number of Primary Healthcare Units (OR = 0.89) were associated statistically with dissatisfaction. Characteristics of the health teams' work process showed a strong association with dissatisfaction.

Resumo: Sabe-se que a satisfação do usuário relaciona-se com a qualidade em saúde. O objetivo foi avaliar a influência de fatores contextuais e individuais associados a insatisfação do usuário com o Sistema Único de Saúde (SUS). Este é um estudo transversal multinível. Os dados foram coletados pela ouvidoria através de contato telefônico. Números de telefone foram selecionados aleatoriamente de um banco de dados de empresas de telefonia. Foram avaliadas variáveis de serviço de saúde, socioeconômicas e demográficas individuais, bem como informações dos municípios. O desfecho foi insatisfação com o SUS. Regressão logística multinível foi utilizada, com uma abordagem hierárquica. 18.673 indivíduos foram contatados. A prevalência de insatisfação foi 63,4% (IC95%: 62,7-64,1). Demanda não resolvida (OR = 3,66), espera > 4 horas (OR = 2,82) e número de unidades básicas de saúde (OR = 0,89) estiveram associados à insatisfação. Características do processo de trabalho das equipes de saúde foram fortemente associadas à insatisfação.

Resumen: Se sabe que la satisfacción del usuario se relaciona con la calidad en salud. El objetivo fue evaluar la influencia de factores contextuales e individuales asociados a la insatisfacción del usuario con el Sistema Único de Salud brasileño (SUS). Este es un estudio transversal multinivel. Los datos fueron recogidos por una auditoría a través de contacto telefónico. Se seleccionaron los números de teléfono aleatoriamente de un banco de datos de empresas de telefonía. Se evaluaron variables de servicio de salud, socioeconómicas y demográficas individuales, así como información de los municipios. El resultado fue insatisfactorio en relación con el SUS. Se utilizó la regresión logística multinivel, con un enfoque jerárquico. 18.673 individuos fueron contactados. La prevalencia de insatisfacción fue de un 63,4% (IC95%: 62,7-64,1). La demanda no resuelta (OR = 3,66), espera > 4 horas (OR = 2,82) y número de unidades básicas de salud (OR = 0,89) estuvieron asociados a la insatisfacción. Características del proceso de trabajo de los equipos de salud estuvieron fuertemente asociadas a la insatisfacción.