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- Title
Suboptimal iron status and associated dietary patterns and practices in premenopausal women living in Auckland, New Zealand.
- Authors
Beck, Kathryn; Kruger, Rozanne; Conlon, Cathryn; Heath, Anne-Louise; Matthys, Christophe; Coad, Jane; Stonehouse, Welma
- Abstract
Purpose: To investigate associations between dietary patterns and suboptimal iron status in premenopausal women living in Auckland, New Zealand. Methods: Premenopausal women ( n = 375; 18-44 years) were included in this cross-sectional analysis. Suboptimal iron status was defined as serum ferritin <20 μg/L. Participants completed a 144-item iron food frequency questionnaire (FeFFQ) and a questionnaire on dietary practices to assess dietary intake over the past month. Factor analysis was used to determine dietary patterns from the FeFFQ. Logistic regression was used to determine associations between these dietary patterns and iron status. Results: Seven dietary patterns were identified: refined carbohydrate and fat; Asian; healthy snacks; meat and vegetable; high tea and coffee; bread and crackers; and milk and yoghurt. Logistic regression suggested that following a 'meat and vegetable' dietary pattern reduced the risk of suboptimal iron status by 41 % (95 % CI: 18, 58 %; P = 0.002) and following a 'milk and yoghurt' pattern increased the risk of suboptimal iron status by 50 % (95 % CI: 15, 96 %; P = 0.003). Conclusions: These results suggest that dietary patterns characterized by either a low intake of meat and vegetables or a high intake of milk and yoghurt are associated with an increased risk of suboptimal iron status. Dietary pattern analysis is a novel and potentially powerful tool for investigating the relationship between diet and iron status.
- Subjects
NEW Zealand; CHI-squared test; CONFIDENCE intervals; EPIDEMIOLOGY; FACTOR analysis; FOOD; FOOD habits; IRON; QUESTIONNAIRES; RESEARCH funding; T-test (Statistics); U-statistics; WOMEN'S health; PERIMENOPAUSE; LOGISTIC regression analysis; DATA analysis; BODY mass index; CROSS-sectional method; DATA analysis software; DESCRIPTIVE statistics
- Publication
European Journal of Nutrition, 2013, Vol 52, Issue 2, p467
- ISSN
1436-6207
- Publication type
Article
- DOI
10.1007/s00394-012-0348-y