Cai H, Shu XO, Hebert JR, Jin F, Yang G, Liu DK, Gao YT, Zheng W. Variation in nutrient intakes among women in Shanghai, China.
Eur J Clin Nutr 2005;
58:1604-11. [PMID:
15199383 DOI:
10.1038/sj.ejcn.1602013]
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Abstract
BACKGROUND
In 1997, we launched a large population-based cohort study, the Shanghai Women Health Study (SWHS), to investigate diet in relation to cancer risk among 74 943 Chinese women. Simultaneously, a dietary calibration study was conducted among 200 SWHS participants with biweekly 24-h dietary recall (24HDR) over a 1-y period in order to evaluate the validity and reliability of the SWHS food frequency questionnaire (FFQ).
OBJECTIVE
The objectives of the current study were to evaluate the nature and magnitude of variances for intake of 26 nutrients among SWHS participants, and to estimate the number of 24HDR needed for estimate intake of the 26 nutrients examined in the study population.
DESIGN
In all, 1-y biweekly 24HDR collected from 200 healthy, free-living women aged between 40 and 70 y, who participated in the SWHS dietary calibration study, was analyzed by mixed effects model and ratios of within-individual and between-individual dietary intake variances (sigma(w)(2)/sigma(b)(2)) were estimated.
RESULTS
In agreement with reports from studies conducted in the US, we found that within-individual variances were larger than between-individual variances in dietary intake of most nutrients. The sum of all other variation (eg, weekday and weekend, seasonal, interviewer) accounted for less than 5% of total variation. Ratios of within- to between-individual variances (for log transformed data) ranged from 1.05 (carbohydrate) to 2.79 (fat) for macronutrient intake, 1.74 (niacin) to 8.48 (delta-tocopherol) for vitamin intake, and 1.35 (phosphorus) to 5.59 (sodium) for mineral intake.
CONCLUSIONS
The results of this study suggest that within- and between-individual differences in nutrient intake are the major sources of variation in this population of adult Chinese women. Cultural practices as well as seasonal supply and consumption patterns of vegetable intake are likely the major contributors to the variation. Implications of these results are discussed.
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