Variância intrapessoal para ajuste da distribuição de nutrientes em estudos epidemiológicos

Morimoto, Juliana Masami; Marchioni, Dirce Maria Lobo; César, Chester Luiz Galvão; Fisberg, Regina Mara

doi:10.1590/s0034-89102011000300022

Cited by 12 publications

(8 citation statements)

References 5 publications

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“…The best linear unbiased predictor (BLUP) of usual individual added sugars and energy intake was also used. BLUPs were outputted from PC-Side program for further analyses by using complex samples in Stata software 12,13,15,16 . Sugars added to food during processing or at the time of consumption (table sugars) were considered for the analysis.…”

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confidence: 99%

Added sugars: consumption and associated factors among adults and the elderly. São Paulo, Brazil

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Marchioni

César

et al. 2012

Rev. bras. epidemiol.

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Objective: To investigate added sugar intake, main dietary sources and factors associated with excessive intake of added sugar. Methods: A population-based household survey was carried out in São Paulo, the largest city in Brazil. Cluster sampling was performed and the study sample comprised 689 adults and 622 elderly individuals. Dietary intake was estimated based on a 24-hour food recall. Usual nutrient intake was estimated by correcting for the within-person variance of intake using the Iowa State University (ISU) method. Linear regression analysis was conducted to identify factors associated with added sugar intake. Results: Average of energy intake (EI) from added sugars was 9.1% (95% CI: 8.9%; 9.4%) among adults and 8.4% (95% CI: 8.2%; 8.7%) among the elderly (p < 0.05). Average added sugar intake (% EI) was higher among women than among men (p < 0.05). Soft drink was the main source of added sugar among adults, while table sugar was the main source of added sugar among the elderly. Added sugar intake increased with age among adults. Moreover, higher socioeconomic level was associated with added sugar intake in the same group. Conclusions: Added sugar intake is higher among younger adults of higher socioeconomic level. Soft drink and table sugar accounted for more than 50% of the sugar consumed.Keywords: Added sugars. Food intake. Soft drink. Survey. Adults. Elderly. IntroductionThe new dietary pattern is characterized by high intake of energy, saturated fats and sugars and low intake of complex carbohydrates and fibers. This diet plays a role as a predisposing risk factor for chronic diseases 1 . The literature reports untoward effects from added sugar consumption on health, especially when consumed in large amounts. One of the adverse effects from sugar intake is dental caries, especially when associated with other factors such as genetics, poor oral hygiene, number of meals and fluoride exposure. Some studies show that energy from sugars is related to excessive weight gain and dilution of other nutrients [1][2][3] . Sugars can be added to foods during processing or preparation to improve palatability and increase viscosity, texture, color and durability. Added sugars refer to refined sugar, brown sugar, corn and glucose syrups, fructose-based sweeteners, honey and molasses 4 . Based on the World Health Organization (WHO), the Brazilian Food Guide recommends a dietary sugar intake that provides no more than 10% of energy intake (EI) 3,5 . Brazil is the world's largest producer of sugarcane but few surveys have been published on Brazilian dietary sugar intake.T h e Ho u s e h o l d Bu d g e t Su r v e y (2008/2009) showed that consumption of sugars remained at 16.4% of energy intake in the past five years. The maximum of 10% of energy intake from sugars is largely overcome in all socioeconomic levels 6 . The objective of the present study was to investigate the main food sources of added sugars among adults and elderly individuals living in the city of São Paulo and the factors associated with e...

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confidence: 99%

Added sugars: consumption and associated factors among adults and the elderly. São Paulo, Brazil

Bueno

Marchioni

César

et al. 2012

Rev. bras. epidemiol.

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“…When comparing our results with previous works, more than 7 d of data are usually needed to estimate nutrient intake in adults (9)(10)(11)(12)(13)(14)(15) and older children. Fewer records are needed for younger age groups (1,8,21) , which can be attributed to the lower variability of their diets, which are based on a smaller variety of foods than adult diets (5) .…”

Section: Discussionmentioning

confidence: 70%

“…Although several studies have characterised intra and interpersonal variability of nutrient intake in adults (9)(10)(11)(12)(13)(14)(15) , the information available for children is still very limited (5,8,(16)(17)(18)(19)(20)(21)(22)(23)(24)(25) . Such data are especially scarce for Brazil, where only two studies have conducted such assessments (1,3) .…”

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Nutrient intake variability and the number of days needed to estimate usual intake in children aged 13–32 months

et al. 2017

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The number of days of data required to accurately estimate usual nutrient intake of children is not well established. This study aims to calculate the variability and the number of days required to estimate usual nutrient intake in children aged 13-32 months. This cross-sectional study, which is part of the BRISA Project in São Luís, Maranhão, Brazil, involved 231 children from April 2011 to January 2013. Socio-economic and demographic data were collected using a questionnaire, and 3 non-consecutive days of food consumption were collected using a 24-h dietary recall (24HDR) survey. Intrapersonal and interpersonal variability and variance ratio (VR) were obtained for each nutrient using the Multiple Source Method® program (version 1.0.1). The number of days (d) needed was calculated using the formula proposed by Black et al. for different correlation coefficients (r) (i.e. 0·7, 0·8 or 0·9). For the vast majority of nutrients, intrapersonal and interpersonal variability values of <1 were observed, with even smaller intrapersonal variabilities, resulting in low VR (<1). More days were needed to estimate intakes of soluble fibre (12), insoluble fibre (11), total fibre (10), vitamin C (9) and PUFA (7), while fewer days were needed for energy, carbohydrate, SFA, Ca, Fe, P and Zn (all had 2 d for r 0·9). However, most nutrients required one, two or three 24HDR for r 0·7, 0·8 or 0·9.

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“…Estudos apontam que apenas um dia de R24h não representaria a ingestão habitual de um indivíduo devido à elevada variação no consumo de nutrientes 36 . Porém, coletar dados de vários dias de consumo alimentar se torna um procedimento que requer maior tempo de estudo e maior disponibilidade do avaliado 37 . Além disso, a omissão ao relatar o consumo de alguns alimentos, a dificuldade de memória em quantificar as porções e até mesmo a falta de compreensão das perguntas realizadas pelo entrevistador poderia promover um relato impreciso da ingestão energética 38 .…”

Section: Discussionunclassified

Estado nutricional e a estimativa de consumo dos nutrientes em mulheres do programa UCS sênior

2018

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Objetivo: Avaliar o estado nutricional e o consumo dos macro e micronutrientes em mulheres de um programa de extensão.Materiais e Métodos: Estudo transversal que foi realizado com mulheres ≥50 anos. As variáveis analisadas foram: sociodemográficas, antropométricas e consumo alimentar. Correlacionou-se o estado nutricional com o consumo alimentar.Resultados: A partir das 176 mulheres, verificou-se que a média de idade foi 63,2 anos (±7,4). A predominância do nível de escolaridade foi médio completo ou mais (58,5%), excesso de peso (52,3%) e risco muito aumentado para Doenças Cardio Vasculares (DCV) pela Circunferência Abdominal (CA) em 78,4%. A média do consumo de macronutrientes ficou em 57,7% para carboidrato, 17,2% para proteína e 25% para lipídeos. Na correlação entre Índice de Massa Corporal (IMC) com CA, dados demográficos e consumo alimentar, houve associação positiva significativa entre IMC e CA (p<0,001). Também houve associação negativa significativa entre IMC com nível de escolaridade (p=0,041), calorias do café da manhã (p=0,040) e fibras (p=0,008). Já na análise de correlação entre CA com dados demográficos e consumo alimentar, houve associação positiva significativa entre CA com idade (p=0,039) e proteínas, (p=0,011). Também houve associação negativa significativa entre CA com nível de escolaridade (p=0,005) e fibras (p=0,007).Conclusão: Encontrou-se uma elevada prevalência de excesso de peso e a CA como fator de risco para DCV. Correlações entre o estado nutricional e o consumo alimentar também foram demonstradas. A educação nutricional é fundamental para que as mulheres possam adequar a sua alimentação e, consequentemente, melhorar seu estado nutricional.

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Variância intrapessoal para ajuste da distribuição de nutrientes em estudos epidemiológicos

Cited by 12 publications

References 5 publications

Added sugars: consumption and associated factors among adults and the elderly. São Paulo, Brazil

Added sugars: consumption and associated factors among adults and the elderly. São Paulo, Brazil

Nutrient intake variability and the number of days needed to estimate usual intake in children aged 13–32 months

Estado nutricional e a estimativa de consumo dos nutrientes em mulheres do programa UCS sênior

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