ESTRUTURADO DE MIX DE POLPAS DE UMBU E JAMELÃO

Dentre as técnicas de processamento, a estruturação de polpa de frutas representa uma inovação na área de alimentos, com resultados bastante promissores (CARVALHO et al., 2008). Alimento estruturado ou “designed food” ou “engineered food”, são delineados de acordo com um planejamento, geralmente empregando-se matérias-primas de baixo custo, oriundas de frutas que se encontram fora de classificação para comercialização in natura ou excedentes de produção durante o período de safra, em muitos casos, utilizando-se hidrocolóides (FIZMAN, 1992 apud GRIZOTTO et al., 2005). Os hidrocolóides como alginato, pectina e gelatina, irão atuar como agentes de união, facilitando o corte e retendo umidade, contribuindo para a melhoria da textura (GRIZOTTO et al., 2005).O presente trabalho tem como objetivos estudar o efeito da massa de pectina, alginato e gelatina na formulação do estruturado a partir de um mix de polpa de umbu e jamelão: um produto inovador para ser comercializado pelos agricultores aumentando assim sua renda

EFEITO DA CONCENTRAÇÃO DE POLPA DE ABACAXI (ANANAS MILL) NA PRODUÇÃO DE HIDROMEL

O abacaxi ou ananás pertence à família Bromeliaceae e gênero Ananas Mill. Esse gênero é vastamente distribuído nas regiões tropicais por intermédio da espécie Ananas comosus (L.) Merr., a qual abrange todas as cultivares plantadas de abacaxi (Giacomelli, 1981). O abacaxi destaca-se pelo valor energético, devido à sua alta composição de açúcares, e valor nutritivo pela presença de sais minerais (cálcio, fósforo, magnésio, potássio, sódio, cobre e iodo) e de vitaminas (C, A, B1 , B2 e Niacina). No entanto, apresenta teor proteico e de gordura inferiores a 0,5% (Franco, 1989) e apresenta excelente qualidade sensorial decorrente do sabor e aroma característicos (Botrel et al., 1994 apud Antoniolli et al.,2005). O hidromel é uma bebida fermentada a partir do mel, água e leveduras, com teor alcoólico entre 4 e 14% (v/v) que pode ser suplementado com ácido cítrico, ervas, especiarias, polpas ou suco de frutas. A produção de hidromel ainda ocorre de maneira empírica e artesanal, demonstrando a necessidade de pesquisas que visem o aprimoramento do processo de fabricação, considerando desde a seleção do agente da fermentação, formulação do mosto, estudo dos parâmetros fermentativos, bem como a definição de padrões de identidade e qualidade do produto final (Sroka, Tuzynski, 2007; Gupta, Sharma, 2009). Diante disso, o presente trabalho tem como objetivo estudar o processo fermentativo de obtenção de hidromel em função da concentração de polpa de abacaxi por Saccharomyces cerevisiae

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions

Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: a pooled analysis of population-based surveys

Background: Describing the prevalence and trends of cardiometabolic risk factors that are associated with noncommunicable diseases (NCDs) is crucial for monitoring progress, planning prevention, and providing evidence to support policy efforts. We aimed to analyse the transition in body-mass index (BMI), obesity, blood pressure, raised blood pressure, and diabetes in the Americas, between 1980 and 2014. Methods: We did a pooled analysis of population-based studies with data on anthropometric measurements, biomarkers for diabetes, and blood pressure from adults aged 18 years or older. A Bayesian model was used to estimate trends in BMI, raised blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg), and diabetes (fasting plasma glucose ≥7•0 mmol/L, history of diabetes, or diabetes treatment) from 1980 to 2014, in 37 countries and six subregions of the Americas. Findings: 389 population-based surveys from the Americas were available. Comparing prevalence estimates from 2014 with those of 1980, in the non-English speaking Caribbean subregion, the prevalence of obesity increased from 3•9% (95% CI 2•2–6•3) in 1980, to 18•6% (14•3–23•3) in 2014, in men; and from 12•2% (8•2–17•0) in 1980, to 30•5% (25•7–35•5) in 2014, in women. The English-speaking Caribbean subregion had the largest increase in the prevalence of diabetes, from 5•2% (2•1–10•4) in men and 6•4% (2•6–10•4) in women in 1980, to 11•1% (6•4–17•3) in men and 13•6% (8•2–21•0) in women in 2014). Conversely, the prevalence of raised blood pressure has decreased in all subregions; the largest decrease was found in North America from 27•6% (22•3–33•2) in men and 19•9% (15•8–24•4) in women in 1980, to 15•5% (11•1–20•9) in men and 10•7% (7•7–14•5) in women in 2014. Interpretation: Despite the generally high prevalence of cardiometabolic risk factors across the Americas, estimates also showed a high level of heterogeneity in the transition between countries. The increasing prevalence of obesity and diabetes observed over time requires appropriate measures to deal with these public health challenges. Our results support a diversification of health interventions across subregions and countries.Fil: Miranda, J. Jaime. Universidad Peruana Cayetano Heredia; PerúFil: Carrillo-Larco, Rodrigo M.. Imperial College London; Reino UnidoFil: Ferreccio, Catterina. Pontificia Universidad Católica de Chile; ChileFil: Hambleton, Ian R.. The University Of The West Indies; BarbadosFil: Lotufo, Paulo A.. Universidade de Sao Paulo; BrasilFil: Nieto-Martinez, Ramfis. Miami Veterans Affairs Healthcare System; Estados UnidosFil: Zhou, Bin. Imperial College London; Reino UnidoFil: Bentham, James. University Of Kent; Reino UnidoFil: Bixby, Honor. Imperial College London; Reino UnidoFil: Hajifathalian, Kaveh. Cleveland Clinic; Estados UnidosFil: Lu, Yuan. University of Yale; Estados UnidosFil: Taddei, Cristina. Imperial College London; Reino UnidoFil: Abarca-Gomez, Leandra. Caja Costarricense de Seguro Social; Costa RicaFil: Acosta-Cazares, Benjamin. Instituto Mexicano del Seguro Social; MéxicoFil: Aguilar-Salinas, Carlos A.. (Instituto Nacional de Ciencias Médicas y Nutrición; MéxicoFil: Andrade, Dolores S.. Universidad de Cuenca; EcuadorFil: Assunção, Maria Cecilia F.. Universidade Federal de Pelotas; BrasilFil: Barcelo, Alberto. Pan American Health Organization; Estados UnidosFil: Barros, Aluisio J.D.. Universidade Federal de Pelotas; BrasilFil: Barros, Mauro V.G.. Universidade de Pernambuco; BrasilFil: Bata, Iqbal. Dalhousie University Halifax; CanadáFil: Batista, Rosangela L.. Universidade Federal Do Maranhao; BrasilFil: Benet, Mikhail. Cafam University Foundation; ColombiaFil: Bernabe-Ortiz, Antonio. Universidad Peruana Cayetano Heredia; PerúFil: Bettiol, Heloisa. Universidade de Sao Paulo; BrasilFil: Boggia, Jose G.. Universidad de la Republica; UruguayFil: Boissonnet, Carlos P.. Centro de Educación Médica e Investigaciones Clínicas; ArgentinaFil: Brewster, Lizzy M.. University of Amsterdam; Países BajosFil: Cameron, Christine. Canadian Fitness and Lifestyle Research Institute; CanadáFil: Cândido, Ana Paula C.. Universidade Federal de Juiz de Fora; BrasilFil: Cardoso, Viviane C.. Universidade de Sao Paulo; BrasilFil: Chan, Queenie. Imperial College London; Reino UnidoFil: Christofaro, Diego G.. Universidade Estadual Paulista; BrasilFil: Confortin, Susana C.. Universidade Federal de Santa Catarina; BrasilFil: Craig, Cora L.. Canadian Fitness and Lifestyle Research Institute; CanadáFil: d'Orsi, Eleonora. Universidade Federal de Santa Catarina; BrasilFil: Delisle, Hélène. University of Montreal; CanadáFil: De Oliveira, Paula Duarte. Universidade Federal de Pelotas; BrasilFil: Dias-da-Costa, Juvenal Soares. Universidade do Vale do Rio Dos Sinos; BrasilFil: Diaz, Alberto Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Escuela Superior de Ciencias de la Salud. Instituto de Investigación en Ciencias de la Salud; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Municipalidad de Tandil. Hospital Municipal Ramón Santamarina; ArgentinaFil: Donoso, Silvana P.. Universidad de Cuenca; EcuadorFil: Elliott, Paul. Imperial College London; Reino UnidoFil: Escobedo-de La Peña, Jorge. Instituto Mexicano del Seguro Social; MéxicoFil: Ferguson, Trevor S.. The University of The West Indies; JamaicaFil: Fernandes, Romulo A.. Universidade Estadual Paulista; BrasilFil: Ferrante, Daniel. Ministerio de Salud; ArgentinaFil: Flores, Eric Monterubio. Instituto Nacional de Salud Pública; MéxicoFil: Francis, Damian K.. The University of The West Indies; JamaicaFil: Do Carmo Franco, Maria. Universidade Federal de Sao Paulo; BrasilFil: Fuchs, Flavio D.. Hospital de Clinicas de Porto Alegre; BrasilFil: Fuchs, Sandra C.. Universidade Federal do Rio Grande do Sul; BrasilFil: Goltzman, David. Université McGill; CanadáFil: Gonçalves, Helen. Universidade Federal de Pelotas; BrasilFil: Gonzalez-Rivas, Juan P.. The Andes Clinic Of Cardio-Metabolic Studies; VenezuelaFil: Gorbea, Mariano Bonet. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Gregor, Ronald D.. Dalhousie University Halifax; CanadáFil: Guerrero, Ramiro. Universidad Icesi; ColombiaFil: Guimaraes, Andre L.. Universidade Estadual de Montes Claros; BrasilFil: Gulliford, Martin C.. King’s College London; Reino UnidoFil: Gutierrez, Laura. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Hernandez Cadena, Leticia. Instituto Nacional de Salud Pública; MéxicoFil: Herrera, Víctor M.. (Universidad Autónoma de Bucaramanga; ColombiaFil: Hopman, Wilma M.. Kingston General Hospital; CanadáFil: Horimoto, Andrea RVR. Instituto do Coração; BrasilFil: Hormiga, Claudia M.. Fundación Oftalmológica de Santander; ColombiaFil: Horta, Bernardo L.. Universidade Federal de Pelotas; BrasilFil: Howitt, Christina. The University of the West Indies; BarbadosFil: Irazola, Wilma E.. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Jiménez-Acosta, Santa Magaly. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Joffres, Michel. Simon Fraser University; CanadáFil: Kolsteren, Patricia. (Institute of Tropical Medicine; BélgicaFil: Landrove, Orlando. Ministerio de Salud Pública; CubaFil: Li, Yanping. Harvard TH Chan School of Public Health; Estados UnidosFil: Lilly, Christa L.. West Virginia University; Estados UnidosFil: Lima-Costa, M. Fernanda. Fundação Oswaldo Cruz; BrasilFil: Louzada Strufaldi, Maria Wany. Universidade Federal de Sao Paulo; BrasilFil: Machado-Coelho, George L. L.. Universidade Federal de Ouro Preto; BrasilFil: Makdisse, Marcia. Hospital Israelita Albert Einstein; BrasilFil: Margozzini, Paula. Pontificia Universidad Católica de Chile; ChileFil: Pruner Marques, Larissa. Universidade Federal de Santa Catarina; BrasilFil: Martorell, Reynaldo. Emory University; Estados UnidosFil: Mascarenhas, Luis. Universidade Federal do Paraná; BrasilFil: Matijasevich, Alicia. Universidade Federal de Sao Paulo; BrasilFil: Mc Donald Posso, Anselmo J.. Gorgas Memorial Institute of Health Studies; PanamáFil: McFarlane, Shelly R.. The University of the West Indies; JamaicaFil: McLean, Scott B.. (Statistics Canada; CanadáFil: Menezes, Ana Maria B.. Universidade Federal de Pelotas; BrasilFil: Miquel, Juan Francisco. Pontificia Universidad Católica de Chile; ChileFil: Mohanna, Salim. Universidad Peruana Cayetano Heredia; PerúFil: Monterrubio, Eric A.. Instituto Nacional de Salud Pública; MéxicoFil: Moreira, Leila B.. Universidade Federal do Rio Grande do Sul; BrasilFil: Morejon, Alain. Universidad de Ciencias Médicas; CubaFil: Motta, Jorge. Gorgas Memorial Institute of Public Health; PanamáFil: Neal, William A.. West Virginia University; Estados UnidosFil: Nervi, Flavio. Pontificia Universidad Católica de Chile; ChileFil: Noboa, Oscar A.. Universidad de la República; UruguayFil: Ochoa-Avilés, Angélica M.. Universidad de Cuenca; EcuadorFil: Olinto, Maria Teresa Anselmo. Universidad de Vale do Rio dos Sinos; BrasilFil: Oliveira, Isabel O.. Universidade Federal de Pelotas; BrasilFil: Ono, Lariane M.. Universidade Federal de Santa Catarina; BrasilFil: Ordunez, Pedro. Pan American Health Organization; Estados UnidosFil: Ortiz, Ana P.. Universidad de Puerto Rico; Puerto RicoFil: Otero, Johanna A.. Fundación Oftalmológica de Santander; ColombiaFil: Palloni, Alberto. University of Wisconsin-Madison; Estados UnidosFil: Viana Peixoto, Sergio. Fundação Oswaldo Cruz; BrasilFil: Pereira, Alexandre C.. Instituto do Coração; BrasilFil: Pérez, Cynthia M.. Universidad de Puerto Rico; Puerto RicoFil: Rangel Reina, Daniel A.. Gorgas Memorial Institute of Health Studies; PanamáFil: Ribeiro, Robespierre. Secretaria de Estado de Saúde de Minas Gerais; BrasilFil: Ritti-Dias, Raphael M.. Universidade Nove de Julho; BrasilFil: Rivera, Juan A.. Instituto Nacional de Salud Pública; MéxicoFil: Robitaille, Cynthia. Public Health Agency of Canada; CanadáFil: Rodríguez-Villamizar, Laura A.. Universidad Industrial de Santander; ColombiaFil: Rojas-Martinez, Rosalba. Instituto Nacional de Salud Pública; MéxicoFil: Roy, Joel G. R.. Statistics Canada; CanadáFil: Rubinstein, Adolfo Luis. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Ruiz-Betancourt, Blanca Sandra. Instituto Mexicano del Seguro Social; MéxicoFil: Salazar Martinez, Eduardo. Instituto Nacional de Salud Pública; MéxicoFil: Sánchez-Abanto, José. Instituto Nacional de Salud; PerúFil: Santos , Ina S.. Universidade Federal de Pelotas; BrasilFil: dos Santos, Renata Nunes. Universidade Federal de Sao Paulo; BrasilFil: Scazufca, Marcia. Universidade Federal de Sao Paulo; BrasilFil: Schargrodsky, Herman. Hospital Italiano; ArgentinaFil: Silva, Antonio M.. Universidade Federal do Maranhao; BrasilFil: Santos Silva, Diego Augusto. Universidade Federal de Santa Catarina; BrasilFil: Stein, Aryeh D.. Emory University; Estados UnidosFil: Suárez-Medina, Ramón. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Tarqui-Mamani, Carolina B.. Instituto Nacional de Salud; PerúFil: Tulloch-Reid, Marshall K.. The University of the West Indies; JamaicaFil: Ueda, Peter. Harvard TH Chan School of Public Health; Estados UnidosFil: Ugel, Eunice E.. Universidad Centro-Occidental Lisandro Alvarado; VenezuelaFil: Valdivia, Gonzalo. Pontificia Universidad Católica de Chile; ChileFil: Varona, Patricia. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Velasquez-Melendez, Gustavo. Universidade Federal de Minas Gerais; BrasilFil: Verstraeten, Roosmarijn. Institute of Tropical Medicine; BélgicaFil: Victora, Cesar G.. Universidade Federal de Pelotas; BrasilFil: Wanderley Jr, Rildo S.. Universidade Federal de Pernambuco; BrasilFil: Wang, Ming-Dong. Public Health Agency of Canada; CanadáFil: Wilks, Rainford J.. The University of the West Indies; JamaicaFil: Wong-McClure, Roy A.. Caja Costarricense de Seguro Social; Costa RicaFil: Younger-Coleman, Novie O.. The University of the West Indies; JamaicaFil: Zuñiga Cisneros, Julio. Gorgas Memorial Institute of Public Health; PanamáFil: Danaei, Goodarz. Harvard TH Chan School of Public Health; Estados UnidosFil: Stevens, Gretchen A.. World Health Organization; SuizaFil: Riley, Leanne M.. World Health Organization; SuizaFil: Ezzati, Majid. (Imperial College London; Reino UnidoFil: Di Cesare, Mariachiara. Middlesex University; Reino Unid

General and abdominal adiposity and hypertension in eight world regions: a pooled analysis of 837 population-based studies with 7·5 million participants

International audienceSummaryBackground Adiposity can be measured using BMI (which is based on weight and height) as well as indices of abdominal adiposity. We examined the association between BMI and waist-to-height ratio (WHtR) within and across populations of different world regions and quantified how well these two metrics discriminate between people with and without hypertension.MethodsWe used data from studies carried out from 1990 to 2023 on BMI, WHtR and hypertension in people aged 20–64 years in representative samples of the general population in eight world regions. We graphically compared the regional distributions of BMI and WHtR, and calculated Pearson’s correlation coefficients between BMI and WHtR within each region. We used mixed-effects linear regression to estimate the extent to which WHtR varies across regions at the same BMI. We graphically examined the prevalence of hypertension and the distribution of people who have hypertension both in relation to BMI and WHtR, and we assessed how closely BMI and WHtR discriminate between participants with and without hypertension using C-statistic and net reclassification improvement (NRI).FindingsThe correlation between BMI and WHtR ranged from 0·76 to 0·89 within different regions. After adjusting for age and BMI, mean WHtR was highest in south Asia for both sexes, followed by Latin America and the Caribbean and the region of central Asia, Middle East and north Africa. Mean WHtR was lowest in central and eastern Europe for both sexes, in the high-income western region for women, and in Oceania for men. Conversely, to achieve an equivalent WHtR, the BMI of the population of south Asia would need to be, on average, 2·79 kg/m² (95% CI 2·31–3·28) lower for women and 1·28 kg/m² (1·02–1·54) lower for men than in the high-income western region. In every region, hypertension prevalence increased with both BMI and WHtR. Models with either of these two adiposity metrics had virtually identical C-statistics and NRIs for every region and sex, with C-statistics ranging from 0·72 to 0·81 and NRIs ranging from 0·34 to 0·57 in different region and sex combinations. When both BMI and WHtR were used, performance improved only slightly compared with using either adiposity measure alone.InterpretationBMI can distinguish young and middle-aged adults with higher versus lower amounts of abdominal adiposity with moderate-to-high accuracy, and both BMI and WHtR distinguish people with or without hypertension. However, at the same BMI level, people in south Asia, Latin America and the Caribbean, and the region of central Asia, Middle East and north Africa, have higher WHtR than in the other regions

Diminishing benefits of urban living for children and adolescents’ growth and development

Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1–6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions