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Pre-pregnancy BMI, gestational weight gain and body image are associated with dietary under-reporting in pregnant Japanese women.

Mie Shiraishi | Megumi Haruna | Masayo Matsuzaki | Ryoko Murayama | Satoshi Sasaki
Journal of nutritional science | 2018

Dietary under-reporting is a common problem when using self-reported dietary assessment tools. However, there are few studies regarding under-reporting during pregnancy. This study aimed to explore the demographic and psychosocial characteristics related to dietary under-reporting in pregnant Japanese women. A cross-sectional study was conducted between 2010 and 2011 at a university hospital in Tokyo, Japan. Nutrient intake was assessed using a self-administered Diet History Questionnaire (DHQ), which had questions about the consumption frequency and portion size of selected food items. The 24-h urinary excretion levels of urea N and K were used as the dietary protein and K intake reference values, respectively. Under-reporting of protein and K was defined as the bottom 25 % of the reporting accuracy (the ratio of reported intake on the DHQ to the estimated intake based on urinary excretion). Under-reporters were defined as participants who under-reported both protein and K intake. Multiple logistic regression analysis was performed to examine the factors associated with under-reporters. Of 271 healthy women at 19-23 weeks of gestation, thirty-five participants (12·9 %) were identified as under-reporters. Under-reporters had a lower pre-pregnancy BMI (adjusted OR (AOR) = 0·81) and lower gestational weight gain (AOR = 0·82); they also reported managing their gestational weight gain with the aim to return to their pre-pregnancy weight soon after childbirth (AOR = 2·99). Healthcare professionals should consider the potential for dietary under-reporting and the possible related factors when assessing the dietary intakes of pregnant Japanese women using self-administered questionnaires.

Pubmed ID: 29686861

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RRID:SCR_009181

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)

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