RESUMO
In this research article, we propose a class of models for positive and zero responses by means of a zero-augmented mixed regression model. Under this class, we are particularly interested in studying positive responses whose distribution accommodates skewness. At the same time, responses can be zero, and therefore, we justify the use of a zero-augmented mixture model. We model the mean of the positive response in a logarithmic scale and the mixture probability in a logit scale, both as a function of fixed and random effects. Moreover, the random effects link the two random components through their joint distribution and incorporate within-subject correlation because of the repeated measurements and between-subject heterogeneity. A Markov chain Monte Carlo algorithm is tailored to obtain Bayesian posterior distributions of the unknown quantities of interest, and Bayesian case-deletion influence diagnostics based on the q-divergence measure is performed. We apply the proposed method to a dataset from a 24 hour dietary recall study conducted in the city of São Paulo and present a simulation study to evaluate the performance of the proposed methods.
Assuntos
Dieta/estatística & dados numéricos , Modelos Estatísticos , Algoritmos , Teorema de Bayes , Brasil , Simulação por Computador , Humanos , Funções Verossimilhança , Modelos Lineares , Cadeias de Markov , Rememoração Mental , Método de Monte Carlo , Distribuição de PoissonRESUMO
BACKGROUND & AIMS: Metabolic syndrome (MetS) is a cluster of interrelated risk factors for type 2 diabetes mellitus, and cardiovascular disease, with underlying inflammatory pathophysiology. Genetic variations and diet are well-known risk factor for MetS, but the interaction between these two factors is less explored. The aim of the study was to evaluate the influence of interaction between SNP of inflammatory genes (encoding interleukin (IL)-6, IL-1ß and IL-10) and plasma fatty acids on the odds of MetS, in a population-based cross-sectional study. METHODS: Among participants of the Health Survey - São Paulo, 301 adults (19-59 y) from whom a blood sample was collected were included. Individuals with and without MetS were compared according to their plasma inflammatory biomarkers, fatty acid profile, and genotype frequency of the IL1B (rs16944, rs1143623, rs1143627, rs1143634 and rs1143643), IL6 (rs1800795, rs1800796 and rs1800797) and IL10 (rs1554286, rs1800871, rs1800872, rs1800890 and rs3024490) genes SNP. The influence of gene-fatty acids interaction on MetS risk was investigated. RESULTS: IL6 gene SNP rs1800795 G allele was associated with higher odds for MetS (OR = 1.88; p = 0.017). Gene-fatty acid interaction was found between the IL1B gene SNP rs116944 and stearic acid (p inter = 0.043), and between rs1143634 and EPA (p inter = 0.017). For the IL10 gene SNP rs1800896, an interaction was found for arachidonic acid (p inter = 0.007) and estimated D5D activity (p inter = 0.019). CONCLUSION: The IL6 gene SNP rs1800795 G allele is associated with increased odds for MetS. Plasma fatty acid profile interacts with the IL1B and IL10 gene variants to modulate the odds for MetS. This and other interactions of risk factors can account for the unexplained heritability of MetS, and their elucidation can lead to new strategies for genome-customized prevention of MetS.
Assuntos
Ácidos Graxos/sangue , Interleucina-10/genética , Interleucina-1beta/genética , Interleucina-6/genética , Síndrome Metabólica/sangue , Síndrome Metabólica/genética , Adulto , Estudos Transversais , Ácidos Graxos/genética , Feminino , Predisposição Genética para Doença , Humanos , Interleucina-10/sangue , Interleucina-1beta/sangue , Interleucina-6/sangue , Masculino , Pessoa de Meia-Idade , Fatores de RiscoRESUMO
Introdução. A COVID-19 impactou a garantia de uma alimentação adequada e saudável, inclusive entre universitários, que parecem constituir um grupo suscetível à Insegurança Alimentar (IA). Objetivo. Verificar a associação entre IA e marcadores de consumo alimentar em universitários durante a pandemia de COVID-19. Materiais e métodos. Estudo transversal com 5407 estudantes de instituições de ensino superior de todas as regiões do Brasil. Os dados foram coletados entre agosto/2020 e fevereiro/2021. O consumo alimentar foi avaliado por marcadores de alimentação saudável utilizados num inquérito nacional de saúde (VIGITEL). Os níveis de IA foram classificados pela Escala Brasileira de Insegurança Alimentar em Segurança Alimentar (SA) e IA leve, moderada e grave. A associação entre IA e marcadores de consumo foi avaliada por meio de regressão logística, considerando frequência semanal de consumo < 3 dias e ≥ 3 dias. Resultados. 37% dos universitários estavam em algum grau de IA. Verificou-se maior chance de baixa frequência de consumo de feijão (OR 1,81), verduras e legumes (OR 4,76), frutas (OR 3,99), lácteos (OR 3,98) e carnes (OR 3,41), e maiores chances de maior consumo de frango (OR 1,14) e ovos (OR 2,04) entre aqueles em IA (p<0,05). Em sua maioria, os valores foram mais expressivos quanto maior o grau de IA. Conclusões. Maiores níveis de IA mostraram-se associados a uma menor chance de consumo alimentar saudável por universitários. Instituições de ensino superior podem executar papéis importantes no combate e assistência à IA nessa população(AU)
Introduction. COVID-19 has impacted access to an adequate and healthy diet, including university students, who seem to constitute a group susceptible to Food Insecurity (FI). Objective. To verify the association between FI and food consumption markers in university students during the COVID-19 pandemic. Materials and Methods. We conducted a cross- sectional study with 5407 students from higher education institutions from all regions of Brazil. Data were collected between August/2020 and February/2021. We evaluated food consumption using the healthy eating markers from a Brazilian national health survey (VIGITEL). We classified the FI levels according to the Brazilian Food Insecurity Scale into Food Security (FS) and mild, moderate, and severe FI. We evaluated the association between FI and consumption markers using logistic regression, considering the weekly frequency of consumption of < 3 days and ≥ 3 days. Results. 37% of the university students had in some degree of FI. We found a greater chance of lower frequency of consumption of beans (OR 1.81), vegetables (OR 4.76), fruits (OR 3.99), dairy products (OR 3.98), and meat (OR 3. 41), and greater chances of increased consumption of chicken (OR 1.14) and eggs (OR 2.04) among those in FI (p<0.05). Overall, the values were more expressive the higher the degree of FI. Conclusions. Higher FI levels were associated with a lower chance of healthy food consumption in university students. Higher education institutions can play a relevant role in addressing and administering the FI in this population(AU)
Assuntos
Humanos , Masculino , Feminino , Adolescente , Adulto , Ingestão de Alimentos , Insegurança AlimentarRESUMO
SCOPE: Interactions between adiponectin genetic variants and plasma fatty acid profile can modulate plasma inflammatory biomarker concentration and the risk for metabolic diseases. The aim of this study was to investigate the interaction between single nucleotide polymorphisms of the adiponectin gene and plasma fatty acid profile in modulating the odds for systemic inflammation in a cross-sectional population-based study. METHODS AND RESULTS: Inflammatory patterns comprised 11 inflammatory biomarkers. Among participants of the Health Survey of São Paulo, 262 adults (19-59 years) met the inclusion criteria. Anthropometric parameters, blood pressure, plasma inflammatory biomarker concentration, and fatty acid profile were measured and five single nucleotide polymorphisms of the adiponectin gene (rs2241766, rs1501299, rs16861209, rs17300539, and rs266729) genotyped. Individuals in the upper 50th percentile for plasma araquidonic acid, n-3 highly unsaturated fatty acid and estimated delta-5-desaturase activity, had reduced odds of being in the inflammatory cluster (OR (95% CI) = 0.55 (0.32-0.95), 0.50 (0.28-0.88) and 0.48 (0.28-0.83), respectively). Gene-plasma fatty acid profile interaction was found between rs2241766 and n-3 (p = 0.019), rs16861209 and araquidonic acid and docosapentaenoic acid (p = 0.044, p = 0.037, respectively), and rs17300539 and saturated fatty acid (p = 0.019). CONCLUSION: Plasma fatty acid profile can interact with adiponectin gene variants to modulate the risk for systemic inflammatory state.