Local Food Environment and Consumption of Ultra-Processed Foods: Cross-Sectional Data from the Nutritionists' Health Study-NutriHS.

This study aimed to analyze whether community food environments are associated with individual food consumption among nutrition students and newly graduated nutritionists. This cross-sectional study used data from the Nutritionists' Health Study cohort, which included 357 undergraduate nutrition students from the city of Fortaleza, Ceará, Brazil. Exposure to the food environment was defined as the proximity and availability of food outlets within a 500 m buffer from the participants' homes. Food consumption was assessed using a Food Frequency Questionnaire and analyzed according to the NOVA classification. Multi-level linear regression models with fixed effects were used to estimate the presence of food outlets within the buffer and their association with food consumption. The presence of mini-markets in the buffer in the fourth quartile was associated with lower consumption of ultra-processed foods (UPF) when observing socioeconomic and lifestyle conditions (ß = -3.29; 95% CI = -6.39 to -0.19). The presence of bakeries and coffee shops was related to lower consumption of ultra-processed foods among participants when observing socioeconomic conditions (ß = -3.10; 95% CI = -6.18 to -0.02). There was no clear evidence of an association between the type of food outlet and UPF consumption. The community food environment seemed to influence food consumption among study participants, although clearer and more consistent evidence on this subject is needed.

Spatial, spatio-temporal, and origin-destination flow analyses of patients with severe acute respiratory syndrome hospitalized for COVID-19 in Southeastern Brazil, 2020-2021.

Brazil experienced one of the fastest increasing numbers of coronavirus disease (COVID-19) cases worldwide. The Sao Paulo State (SPS) reported a high incidence, particularly in Sao Paulo municipality. This study aimed to identify clusters of incidence and mortality of hospitalized patients with severe acute respiratory syndrome for COVID-19 in the SPS, in 2020-2021, and describe the origin flow pattern of the cases. Cases and mortality risk area clusters were identified through different analyses (spatial clusters, spatio-temporal clusters, and spatial variation in temporal trends) by weighting areas. Ripley's K12-function verified the spatial dependence between the cases and infrastructure. There were 517,935 reported cases, with 152,128 cases resulting in death. Of the 470,441 patients hospitalized and residing in the SPS, 357,526 remained in the original municipality, while 112,915 did not. Cases and death clusters were identified in the Sao Paulo metropolitan region (SPMR) and Baixada Santista region in the first study period, and in the SPMR and the Campinas, Sao Jose do Rio Preto, Barretos, and Sorocaba municipalities during the second period. We highlight the priority areas for control and surveillance actions for COVID-19, which could lead to better outcomes in future outbreaks.

Spatial, spatio-temporal, and origin-destination flow analyses of patients with severe acute respiratory syndrome hospitalized for COVID-19 in Southeastern Brazil, 2020-2021

ABSTRACT Brazil experienced one of the fastest increasing numbers of coronavirus disease (COVID-19) cases worldwide. The Sao Paulo State (SPS) reported a high incidence, particularly in Sao Paulo municipality. This study aimed to identify clusters of incidence and mortality of hospitalized patients with severe acute respiratory syndrome for COVID-19 in the SPS, in 2020-2021, and describe the origin flow pattern of the cases. Cases and mortality risk area clusters were identified through different analyses (spatial clusters, spatio-temporal clusters, and spatial variation in temporal trends) by weighting areas. Ripley's K12-function verified the spatial dependence between the cases and infrastructure. There were 517,935 reported cases, with 152,128 cases resulting in death. Of the 470,441 patients hospitalized and residing in the SPS, 357,526 remained in the original municipality, while 112,915 did not. Cases and death clusters were identified in the Sao Paulo metropolitan region (SPMR) and Baixada Santista region in the first study period, and in the SPMR and the Campinas, Sao Jose do Rio Preto, Barretos, and Sorocaba municipalities during the second period. We highlight the priority areas for control and surveillance actions for COVID-19, which could lead to better outcomes in future outbreaks.

COVID-19 in the state of São Paulo: the evolution of a pandemic. / COVID-19 no estado de São Paulo: a evolução de uma pandemia.

OBJECTIVES: To retrospectively describe severe cases of hospitalized patients and deaths related to the COVID-19 epidemic in the state of São Paulo, starting from the date of the first record, with symptoms onset on 02/10/2020 up to 05/20/2021. METHODS: This is a descriptive study carried out using the Influenza Epidemiological Surveillance System (Sistema de Vigilância Epidemiológica da Gripe - SIVEP-Gripe) database. The rates of incidence, mortality, and accumulated incidence in the period were calculated, stratified by age group and Regional Health Department (RHD). In addition, severe cases were geocoded to analyze their spread across the state; and the Effective R, which determines the spread potential of a virus within a population, was calculated. RESULTS: There was a significant increase in severe cases and deaths recorded in the period of one year, with incidence and mortality rates being heterogeneous within the state. The most critical periods regarding the incidence of severe cases occurred between May and July 2020 and between March and April 2021. The RHD in São José do Rio Preto, Expanded São Paulo, and Araçatuba concentrated the highest incidence and mortality rates. Severe cases and deaths were more frequent in men and in the population over 60 years, while the main risk conditions related to deaths were heart disease (59%) and diabetes (42,8%). CONCLUSIONS: These results not only provide a detailed profile for more efficient control action plan, but will also allow the historical understanding of the COVID-19 evolution within the state of São Paulo.

OBJETIVO: Descrever, de forma retrospectiva, os casos graves de pacientes hospitalizados e os óbitos relacionados à epidemia de COVID-19 no estado de São Paulo, desde a data do primeiro registro, com início de sintomas em 10 de fevereiro de 2020 até registros disponíveis em 20 de maio de 2021. MÉTODOS: Trata-se de um estudo descritivo realizado por meio da base de dados do Sistema de Vigilância Epidemiológica da Gripe. Foram calculadas as taxas de incidência, mortalidade e incidência acumulada no período, estratificadas por faixa etária e agrupadas de acordo com cada Departamento Regional de Saúde. Os casos graves foram geocodificados para a análise de seu espalhamento pelo estado e foi calculado o R efetivo, que estima o potencial de propagação de um vírus em uma população. RESULTADOS: Houve aumento significativo dos casos graves e óbitos registrados no período de um ano, e as taxas de incidência e mortalidade foram heterogêneas no estado. Os períodos mais críticos em relação à incidência de casos graves ocorreram entre maio e julho de 2020 e entre março e abril de 2021. Os Departamentos Regionais de Saúde de São José do Rio Preto, Grande São Paulo e Araçatuba concentraram as maiores taxas de incidência e mortalidade. Os casos graves e óbitos foram mais frequentes nos homens e na população acima de 60 anos, e as principais condições de risco relacionadas aos óbitos foram cardiopatia (59%) e diabetes (42,8%). CONCLUSÕES: Espera-se que esses resultados ofereçam embasamento e possam contribuir para uma ação de controle mais eficiente da COVID-19, além de permitir o entendimento histórico de sua evolução no estado.

COVID-19 in the state of São Paulo: the evolution of a pandemic / COVID-19 no estado de São Paulo: a evolução de uma pandemia

OBJECTIVES: To describe retrospectively severe hospitalized cases and deaths related to the COVID-19 epidemic in the state of São Paulo, starting from the date of the first record with symptoms onset on 02/10/2020 up to 05/20/2021 records. METHODS: This is a descriptive study. The data source used was from the Influenza Epidemiological Surveillance System (SIVEP-Gripe). The rates of incidence, mortality and accumulated incidence in the period were calculated, stratified by age group and Regional Health Department (DRS). In addition, severe cases were geocoded to analyze their spread across the state; and the Effective R, which determines the spread potential of a virus within a population, was calculated. RESULTS: There was a significant increase in severe cases and deaths recorded in the period of one year, with incidence and mortality rates being heterogeneous within the state. The most critical periods regarding the incidence of severe cases occurred between May and July 2020 and between March and April 2021. The DRSs in São José do Rio Preto, Grande São Paulo and Araçatuba concentrated the highest incidence and mortality rates. Severe cases and deaths were more frequent in men and in the population over 60 years, while the main risk conditions related to deaths were heart disease (59%) and diabetes (42,8%). CONCLUSIONS: These results not only provide a detailed profile for more efficient control action plan, but will also allow the historical understanding of the COVID-19 evolution within the state of São Paulo.

OBJETIVOS: Descrever, de forma retrospectiva, os casos graves hospitalizados e óbitos relacionados à epidemia de COVID-19 no estado de São Paulo, desde a data do primeiro registro com início de sintomas em 10/02/2020 até registros disponíveis em 20/05/2021. MÉTODOS: Trata-se de um estudo descritivo realizado por meio da base de dados do Sistema de Vigilância Epidemiológica da Gripe (SIVEP-Gripe). Foram calculadas as taxas de incidência, mortalidade e incidência acumulada no período, estratificadas por faixa etária e Departamento Regional de Saúde (DRS). Os casos graves foram geocodificados para análise de seu espalhamento pelo estado e foi calculado o R Efetivo, que estima o potencial de propagação de um vírus dentro de uma população. RESULTADOS: Houve um aumento significativo dos casos graves e óbitos registrados no período de um ano, sendo que as taxas de incidência e mortalidade foram heterogêneas dentro do estado. Os períodos mais críticos em relação à incidência de casos graves ocorreram entre maio e julho de 2020 e entre março e abril de 2021. Os DRS de São José do Rio Preto, Grande São Paulo e Araçatuba concentraram as maiores taxas de incidência e mortalidade. Os casos graves e óbitos foram mais frequentes nos homens e na população acima de 60 anos, e as principais condições de risco relacionadas aos óbitos foram cardiopatia (59%) e diabetes (42,8%). CONCLUSÕES: Espera-se que esses resultados ofereçam embasamento e possam contribuir para uma ação de controle mais eficiente, além de permitir o entendimento histórico da evolução da COVID-19 no estado.

COVID-19 no estado de São Paulo: a evolução de uma pandemia / COVID-19 in the state of São Paulo: the evolution of a pandemic

RESUMO: Objetivo: Descrever, de forma retrospectiva, os casos graves de pacientes hospitalizados e os óbitos relacionados à epidemia de COVID-19 no estado de São Paulo, desde a data do primeiro registro, com início de sintomas em 10 de fevereiro de 2020 até registros disponíveis em 20 de maio de 2021. Métodos: Trata-se de um estudo descritivo realizado por meio da base de dados do Sistema de Vigilância Epidemiológica da Gripe. Foram calculadas as taxas de incidência, mortalidade e incidência acumulada no período, estratificadas por faixa etária e agrupadas de acordo com cada Departamento Regional de Saúde. Os casos graves foram geocodificados para a análise de seu espalhamento pelo estado e foi calculado o R efetivo, que estima o potencial de propagação de um vírus em uma população. Resultados: Houve aumento significativo dos casos graves e óbitos registrados no período de um ano, e as taxas de incidência e mortalidade foram heterogêneas no estado. Os períodos mais críticos em relação à incidência de casos graves ocorreram entre maio e julho de 2020 e entre março e abril de 2021. Os Departamentos Regionais de Saúde de São José do Rio Preto, Grande São Paulo e Araçatuba concentraram as maiores taxas de incidência e mortalidade. Os casos graves e óbitos foram mais frequentes nos homens e na população acima de 60 anos, e as principais condições de risco relacionadas aos óbitos foram cardiopatia (59%) e diabetes (42,8%). Conclusões: Espera-se que esses resultados ofereçam embasamento e possam contribuir para uma ação de controle mais eficiente da COVID-19, além de permitir o entendimento histórico de sua evolução no estado.

ABSTRACT: Objectives: To retrospectively describe severe cases of hospitalized patients and deaths related to the COVID-19 epidemic in the state of São Paulo, starting from the date of the first record, with symptoms onset on 02/10/2020 up to 05/20/2021. Methods: This is a descriptive study carried out using the Influenza Epidemiological Surveillance System (Sistema de Vigilância Epidemiológica da Gripe - SIVEP-Gripe) database. The rates of incidence, mortality, and accumulated incidence in the period were calculated, stratified by age group and Regional Health Department (RHD). In addition, severe cases were geocoded to analyze their spread across the state; and the Effective R, which determines the spread potential of a virus within a population, was calculated. Results: There was a significant increase in severe cases and deaths recorded in the period of one year, with incidence and mortality rates being heterogeneous within the state. The most critical periods regarding the incidence of severe cases occurred between May and July 2020 and between March and April 2021. The RHD in São José do Rio Preto, Expanded São Paulo, and Araçatuba concentrated the highest incidence and mortality rates. Severe cases and deaths were more frequent in men and in the population over 60 years, while the main risk conditions related to deaths were heart disease (59%) and diabetes (42,8%). Conclusions: These results not only provide a detailed profile for more efficient control action plan, but will also allow the historical understanding of the COVID-19 evolution within the state of São Paulo.