Validity and Reproducibility of a Food Frequency Questionnaire for Pregnant Finnish Women

Objective: To validate a new food-frequency questionnaire (FFQ) for measuring the intake of fruit, vegetables and tea reported by women participating in the Norwegian Mother and Child Cohort Study (MoBa). Design: Intake of fruits, vegetables and tea estimated by the FFQ was compared with urinary flavonoid excretion, plasma carotenoid concentration and intake measured by a 4-day weighed food diary (FD). The triangular method was applied to calculate FFQ validity coefficients using two independent biomarkers. Setting and subjects: One hundred and nineteen women participating in MoBa. Results: The FFQ estimate of fruit intake was significantly correlated with urine phloretin (r ¼ 0.33), citrus fruit/juice with urine hesperetin (r ¼ 0.44), cooked vegetables with plasma a-carotene (r ¼ 0.37), and tea with urine kaempferol (r ¼ 0.41) (P , 0.01 for all). On average, 60% of the participants fell into the same or adjacent quintiles when classified by FFQ and biomarkers. Significant correlations between the FFQ and FD were found for fruit (r ¼ 0.39), vegetables (r ¼ 0.34), juices (r ¼ 0.50) and tea (r ¼ 0.53). The FFQ validity coefficient was 0.65 for citrus fruit/juice and 0.59 for cooked vegetables as calculated by the triangular method.Conclusions: The validation study shows that the MoBa FFQ can be used to estimate fruit, juice, vegetable and tea intake in pregnant Norwegian women, and to rank individuals within the distribution.

Section: Discussionsupporting

confidence: 71%

Urine flavonoids and plasma carotenoids in the validation of fruit, vegetable and tea intake during pregnancy in the Norwegian Mother and Child Cohort Study (MoBa)

Brantsæter

Haugen

Rasmussen³

et al. 2007

“…A high proportion of study participants ($70 %) were categorized into the same or adjacent quartiles for estimated energy, carbohydrate, Ca, K, fibre, Zn, cholesterol, vitamin A, riboflavin, niacin, vitamin C, vitamin E and folic acid in both gestational periods. In a study involving Finnish pregnant women, Erkkola et al (15) found estimated nutrient intakes measured by an FFQ to be 30-40 % higher than mean values calculated using food records. According to Robinson et al (11) , higher consumption reported by FFQ may result from the bigger portions used in the FFQ or be due to overreporting of intake frequency.…”

Section: Discussionmentioning

confidence: 96%

Relative validation of a quantitative FFQ for use in Brazilian pregnant women

Barbieri

Nishimura

Crivellenti

et al. 2012

Objective: To evaluate the ability of an FFQ, designed for use in Brazilian pregnant women, to estimate nutrient intakes during pregnancy. Design: A prospective study was conducted among 103 pregnant women attended by the Brazilian national health-care service. Food intake during pregnancy was evaluated by three 24 h dietary recalls (24hR), one per trimester of pregnancy, and also by two FFQ. The FFQ with eighty-five food items included questions about frequency of intake and portion sizes during two periods: the first 24 weeks of pregnancy and the pregnancy period as a whole. Deattenuated Pearson's correlation coefficients and joint classification into quartiles of nutrient intake were applied. Setting: Ribeirão Preto, São Paulo State, Brazil. Subjects: One hundred and three pregnant women, aged 18-35 years. Results: Acceptable correlation coefficients (r . 0?35) were found for Ca, K, Zn, Mg, fibre, vitamin C, niacin and folic acid for intake for the first 24 weeks; and for energy, lipids, protein, carbohydrate, Fe, K, Zn, fibre, vitamin B 6 , riboflavin and niacin for the gestational period as a whole. A high proportion of study participants ($70 %) were categorized into the same or adjacent quartiles for estimated energy, carbohydrate, Ca, K, fibre, Zn, cholesterol, vitamin A, riboflavin, niacin, vitamin C, vitamin E and folic acid. Gross misclassification ranged from 2?3 % (dietary fibre) to 12?5 % (vitamin A, thiamin and SFA). Conclusions: The FFQ is a useful tool for assessing categories of nutrient intake during pregnancy, since a high proportion of women were classified into the same or adjacent quartiles. Keywords FFQ Pregnant women Validation studiesInadequate maternal diet is a relevant risk factor for complications during pregnancy (1,2) , impaired fetal development (3) and may also be linked to higher risk of chronic diseases during childhood (4) and adult life (5) .The FFQ is a method widely used in epidemiological studies aimed at categorizing individuals into different levels of consumption and determining their relationships with health outcomes (6,7) . The FFQ's ability to assess dietary intake of pregnant women is due to the fact this method spans a longer time frame, thus allowing the detection of changes in dietary intake during each trimester of pregnancy (8)(9)(10)(11) .Validation studies of FFQ for use in pregnant women have shown that nutrient estimates using this method exhibit high levels of agreement with intake estimates using the 24 h dietary recall (24hR) (12)(13)(14) or daily records (DR) (15,16) , suggesting a good accuracy of the FFQ for assessing dietary intake in this population group. Since 24hR and FFQ might have correlated errors, related to memory and estimation of portion size, the use of multiple DR or weighed records as the reference method is recommended. Nevertheless, when literacy or motivation of participants is low, the 24hR might be applied as the reference measure of nutrient intake (6) .In an earlier study, an FFQ was developed for use in pregnant women ...

“…Regarding the assessment of food consumption, the limited ability of the FFQ to estimate real intake, as characterized in a relative validity study comparing FFQ and 24 h dietary recalls (29) , is another limitation. Furthermore, lactating women may overestimate food consumption (51)(52)(53) . Another limitation is the use of reported, rather than measured, pre-pregnancy weight.…”

Section: Discussionmentioning

confidence: 99%

Fibre intake and evolution of BMI: from pre-pregnancy to postpartum

Drehmer

Camey

Nunes

et al. 2012

Objective: To evaluate the effect of fibre intake on the evolution of maternal BMI from pregnancy to postpartum and to identify dietary patterns associated with fibre intake. Design: Cohort study. Food intake was obtained using an FFQ. Focused principal component analysis was used focusing on the variables: postpartum weight retention and total dietary fibre intake. Poisson regression models with robust variance were built in order to measure the effect of fibre intake during the postpartum period on obesity risk. Setting: Primary care clinics in southern Brazil. Subjects: Pregnant women (n 370) were followed until the 5th month postpartum. Results: The highest contribution to fibre intake came from the consumption of beans. Consumption of bread and rice indicated a common Brazilian food pattern along with beans. Participants retained a median of 4?4 (interquartile range 0?6, 7?9) kg of weight gained during pregnancy. Obesity risk, defined as an unfavourable evolution of BMI during pregnancy and postpartum, was present in 189 (55?1 %) women. Individual food items did not have an important effect on weight retention. In Poisson regression adjusting for maternal age, pre-pregnancy BMI and total gestational weight gain, inadequate postpartum fibre intake increased obesity risk by 24 % (relative risk 5 1?24; 95 % CI 1?05, 1?47). Conclusions: Important maternal weight retention occurred in these women. Adequate fibre intake may reduce obesity risk in the period following childbirth. Keywords Postpartum BMI Fibre intake Maternal obesityThe postpartum period appears to be a critical period for obesity development in women of reproductive age due to maternal weight retention determined by a series of interrelated factors (1,2) . Gestational weight gain above the recommendations of the Institute of Medicine (IOM) is considered the most important predictor for postpartum weight retention, increasing the short-, medium-and long-term risk obesity (3)(4)(5)(6)(7)(8) .Among other factors associated with postpartum weight variation, maternal age, parity, social and demographic factors as well as pre-pregnancy nutritional status represent non-modifiable factors or ones that occur before pregnancy (1,2) . Modifiable factors related to lifestyle, such as diet, physical activity, smoking and lactation, and their effects on the postpartum weight evolution, are still relatively underexplored in the literature (9)(10)(11)(12) .Maternal energy intake needs to be increased in both pregnancy and postpartum in order to meet physiological demands. The American Dietetic Association recommends that food intake in pregnancy and the postpartum period should be based on whole grains, fruit and vegetables, aiming at meeting recommended vitamin and mineral contents (13) . Nutritional restriction is discouraged even for obese women in the postpartum period, and methods that emphasize a fast weight loss are not recommended (14) . Approximately 13-20 % of women do not return to their pre-pregnancy weight, showing significant postpartum weig...