12 research outputs found

    Avaliação de programa de prevenção de obesidade em adolescentes de escolas públicas

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    OBJETIVO: Avaliar os efeitos de um programa de prevenção de obesidade sobre práticas alimentares de adolescentes de escolas públicas. MÉTODOS: Intervenção com 331 estudantes de 11 a 17 anos de 5º e 6º anos de duas escolas públicas estaduais de Niterói, RJ, em 2005. As escolas foram classificadas em escola de intervenção (EI) e escola de controle (EC) para comparação. Práticas alimentares foram abordadas em questionários auto-respondidos antes e após o período de intervenção: consumo de fast food, consumo de refrigerantes, substituição de refeições por lanches, consumo de frutas, verduras e legumes e tipo de alimentação consumida nos intervalos das aulas. Testes qui-quadrado e McNemar foram aplicados para comparar proporções, considerando valor de p < 0,05. RESULTADOS: Na linha de base participaram 185 estudantes da EI (82,2% dos elegíveis) e 146 estudantes da EC (70,5% dos elegíveis). Na fase pós-intervenção houve perda de 10,3% dos adolescentes da EI e 27,4% da EC. Não se observaram mudanças significativas nas práticas alimentares na EC. Na EI aumentou a proporção de estudantes que relataram não consumir lanches vendidos por ambulantes (de 36,7% para 50,6%; p = 0,02) e dos jovens que relataram não substituir almoço (de 44,5% para 65,2%; p < 0,01) e jantar (de 38,4% para 54,3%; p < 0,01) por lanches. A principal mudança favorável foi a redução na freqüência de consumo de lanches fast food na EI comparada à EC (72,7% vs 54,4%; p = 0,001). CONCLUSÕES: Mudanças favoráveis nas práticas alimentares dos adolescentes foram encontradas e estimulam a implantação de programas dessa natureza; contudo, intervenções de maior duração precisam ser implementadas e avaliadas quanto a sua efetividade

    Membranous nephropathy and cerebellar degeneration with anti-GAD antibodies in type 2 diabetes mellitus

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    Aims: To study the potential pathogenic significance of the coexistence of membranous nephropathy, cerebellar degeneration and anti-glutamic acid decarboxylase (GAD) autoantibodies in patients with diabetes. Methods: We performed a direct immunocytochemistry on human kidney slides, electron microscopy on human kidney biopsy, direct immunofluorescence on human kidney biopsy. Baboon and rat kidney cell lines were fractionated and subjected to western blotting with antibodies to GAD. Results: In this patient we demonstrate the presence of autoantibodies to GAD, which is highly enriched in podocytes plasma membrane and tubular cells of the kidney as well as sub-endothelial IgG and complement C3 deposits in the glomerular basement membrane (GBM). Conclusions: We hypothesize the existence in this patient of a common autoimmune pathogenic mechanism with GAD as the autoantigenic determinant, underlying cerebellar degeneration and membranous nephropathy

    age: Observational data from the ICON audit

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    Purpose: To investigate age-related differences in outcomes of critically ill patients with sepsis around the world.Methods: We performed a secondary analysis of data from the prospective ICON audit, in which all adult ( >16 years ) patients admitted to participating ICUs between May 8 and 18, 2012, were included, except admissions for routine postoperative observation. For this sub-analysis, the 10,012 patients with completed age data were included. They were divided into five age groups - 80 years. Sepsis was defined as infection plus at least one organ failure.Results: A total of 2963 patients had sepsis, with similar proportions across the age groups (80 = 30.9%). Hospital mortality increased with age and in patients >80 years was almost twice that of patients 70 years was independently associated with increased risk of dying.Conclusions: The odds for death in ICU patients with sepsis increased with age with the maximal rate of increase occurring between the ages of 71 and 77 years. (C) 2019 Elsevier Inc. 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J.] Joondalup Hlth Campus, Joondalup, WA, Australia.[Kilminster, M.] Lismore Base Hosp, Lismore, NSW, Australia.[Sturgess, D.] Mater Adult Hosp, South Brisbane, Qld, Australia.[Ziegenfuss, M.] Prince Charles Hosp, Brisbane, Qld, Australia.[O'Connor, S.] Royal Adelaide Hosp, Adelaide, SA, Australia.[Lipman, J.] Royal Brisbane & Womens Hosp, Brisbane, Qld, Australia.[Campbell, L.] Royal Darwin Hosp, Tiwi, NT, Australia.[Mcallister, R.] Royal Hobart Hosp, Hobart, Tas, Australia.[Roberts, B.] Sir Charles Gairdner Hosp, Nedlands, WA, Australia.[Williams, P.] Queen Elizabeth Hosp, Woodville, SA, Australia.[Parke, R.] Auckland Dist Hlth Board, Auckland, New Zealand.[Seigne, P.] Christchurch Hosp, Christchurch, New Zealand.[Freebairn, R.] Hawkes Bay Hosp, Hastings, New Zealand.[Nistor, D.] Palmerston North Hosp, Midcent Hlth, Palmerston North, New Zealand.[Oxley, C.] Middlemore Hosp, Auckland, New Zealand.[Young, P.] Wellington Hosp, Wellington, New Zealand.[Valentini, R.] Cemic, Buenos Aires, DF, Argentina.[Wainsztein, N.] Fleni, Buenos Aires, DF, Argentina.[Comignani, P.] Hosp Aleman, Buenos Aires, DF, Argentina.[Casaretto, M.] Hosp Cent San Isidro, Buenos Aires, DF, Argentina.[Sutton, G.] Hosp Fernandez, Buenos Aires, DF, Argentina.[Villegas, P.] Hosp Francisco Lopez Lima Area Programa Gen Roca, Gen Roca, Argentina.[Galletti, C.] Sanatorio Allende, Cordoba, Argentina.[Neira, J.] Sanatorio Trinidad Palermo, Buenos Aires, DF, Argentina.[Rovira, D.] Sanatorio Julio Corzo Rosario, Rosario, Santa Fe, Argentina.[Hidalgo, J.] Karl Heusner Mem Hosp, Belize City, Belize.[Hidalgo, J.] Belize Healthcare Partner, Belize City, Belize.[Sandi, F.] Hosp Obrero 1, La Paz, Bolivia.[Caser, E.] Cias Unimed Vitoria, Vitoria, ES, Brazil.[Thompson, M.] Evangelical Hosp Cachoeiro De Itapemirim, Cachoeiro De Itapemirim, Brazil.[D'agostino Dias, M.] Hosp 9 Julho, Sao Paulo, Brazil.[Fontes, L.] Hosp Alcides Carneiro, Petropolis, Brazil.[Lunardi, M.] Hosp Clin Luzia De Pinho Melo, Mogi Das Cruzes, Brazil.[Youssef, N.] Hosp Nacoes Curitiba, Curitiba, Parana, Brazil.[Lobo, S.] Hosp Base Famerp, Sao Jose Do Rio Preto, Brazil.[Silva, R.] Hosp Clin Niteroi, Niteroi, RJ, Brazil.[Sales Jr, J.] Hosp Clin Padre Miguel, Rio De Janeiro, Brazil.[Madeira Campos Melo, L.] Hosp Terapia Intens, Sao Paulo, Brazil.[Oliveira, M.] Hosp Trabalhador, Curitiba, Parana, Brazil.[Fonte, M.] Hosp Esperanza, Olinda, PE, Brazil.[Grion, C.] Hosp Evangel Londrina, Londrina, Brazil.[Feijo, C.] Hosp Geral Fortaleza, Fortaleza, Ceara, Brazil.[Rezende, V] Hosp Geral Roraima, Boa Vista, Brazil.[Assuncao, M.] Hosp Israelita Albert Einstein, Sao Paulo, Brazil.[Neves, A.] Hosp Mater Dei, Belo Horizonte, MG, Brazil.[Gusman, P.; Dalcomune, D.] Hosp Meridional, Cariacica, ES, Brazil.[Teixeira, C.] Hosp Moinhos Vento, Porto Alegre, RS, Brazil.[Kaefer, K.] Hosp Municipal Ruth Cardoso, Balneario, Brazil.[Maia, I] Hosp Nereu Ramos, Florianopolis, SC, Brazil.[Souza Dantas, V] Hosp Pasteur, Rio De Janeiro, Brazil.[Costa Filho, R.] Hosp Pro Cardiaco, Rio De Janeiro, Brazil.[Amorim, F.] Hosp Reg Samambaia, Brasilia, DF, Brazil.[Assef, M.] Hosp Reg Hans Dieter Schmidt, Joinville, Brazil.[Schiavetto, P.] Hosp Santa Casa Campo Mourao, Campo Mourao, PR, Brazil.[Houly, J.] Hosp Santa Paula, Sao Paulo, SP, Brazil.[Houly, J.] Hosp Santapaula, Sao Paulo, Brazil.[Bianchi, F.] Hosp Sao Jose Avai, Itaperuna, RJ, Brazil.[Dias, F.] Hosp Sao Lucas Pucrs, Porto Alegre, RS, Brazil.[Avila, C.] Hosp Sao Vicente Paula, Rio De Janeiro, RJ, Brazil.[Gomez, J.] Hosp Sao Vicente Paulo, Rio De Janeiro, Brazil.[Rego, L.] Hosp Saude Mulher, Belem, Para, Brazil.[Castro, P.] Hosp Tacchini, Bento Goncalves, RS, Brazil.[Passos, J.] Hosp Unimed Costa Do Sol Macae Rj, Macae, RJ, Brazil.[Mendes, C.] Hosp Univ Ufpb Joao Pessoa, Joao Pessoa, Paraiba, Brazil.[Grion, C.] Hosp Univ Londrina, Londrina, Brazil.[Colozza Mecatti, G.] Hosp Univ Sao Francisco, Braganca Paulista, SP, Brazil.[Ferrreira, M.] Santa Casa Caridade Diamantina, Diamantina, MG, Brazil.[Irineu, V] Santa Casa Misericordia Tatui, Tatui, Brazil.[Guerreiro, M.] Sao Francisco de Paula Hosp, Sao Francisco De Paula, RS, Brazil.[Ugarte, S.] Clin Indisa, Providencia, Chile.[Tomicic, V] Clin Las Lilas, Providencia, Chile.[Godoy, C.] Hosp Carlos Van Buren, Valparaiso, Chile.[Samaniego, W.] Hosp Trabajador Santiago, Santiago, Chile.[Escamilla, I] Hosp El Pino, San Bernardo, Chile.[Escamilla, I] Hosp Mutual De Seguridad, Santiago, Chile.[Castro Castro, L.] Ctr Med Imbanaco, Valle Del Cauca, Colombia.[Libreros Duque, G.] Clin Colombia Cali, Cali, Colombia.[Diaz-Guio, D.] Clin Del Cafe, Armenia, Colombia.[Benitez, F.] Clin La Estancia SA, Popayan, Colombia.[Guerra Urrego, A.] Clin Medellin, Medellin, Colombia.[Buitrago, R.] Fdn Clin Shaio, Bogota, Colombia.[Ortiz, G.] Hosp Santa Clara, Bogota, Colomb

    Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

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    Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing
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