Shan Xuan Lim1, Marjorelee T Colega2, M Na'im M Ayob2, Sian M Robinson3,4, Keith M Godfrey5,6, Jonathan Y Bernard2,7, Yung Seng Lee2,8,9, Kok Hian Tan10,11, Fabian Yap10,12,13, Lynette Pc Shek2,8,9, Yap Seng Chong2,14, Johan G Eriksson2,14,15,16, Jerry Ky Chan10,17, Shiao Yng Chan2,14, Mary Ff Chong1,2. 1. Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore. 2. Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore. 3. AGE Research Group, Newcastle University Institute for Translational and Clinical Research, Newcastle upon Tyne, UK. 4. NIHR Newcastle Biomedical Research Centre, Newcastle University and Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne, UK. 5. Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK. 6. NIHR Southampton Biomedical Research Centre, University Hospital Southampton, NHS Foundation Trust, Southampton, UK. 7. Université de Paris, Centre for Research in Epidemiology and StatisticS (CRESS), Inserm, INRAE, Paris, France. 8. Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 9. Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore, Singapore. 10. Duke-NUS Medical School, Singapore, Singapore. 11. Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore. 12. Department of Paediatrics, KK Women's and Children's Hospital, Singapore, Singapore. 13. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. 14. Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 15. Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland. 16. Folkhälsan Research Center, University of Helsinki, Helsinki, Finland. 17. Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
Abstract
OBJECTIVE: To identify a posteriori dietary patterns among women planning pregnancy and assess the reproducibility of these patterns in a subsample using two dietary assessment methods. DESIGN: A semi-quantitative FFQ was administered to women enrolled in the Singapore PREconception Study of long-Term maternal and child Outcomes study. Dietary patterns from the FFQ were identified using exploratory factor analysis (EFA). In a subsample of women (n 289), 3-d food diaries (3DFD) were also completed and analysed. Reproducibility of the identified patterns was assessed using confirmatory factor analysis (CFA) in the subsample, and goodness of fit of the CFA models was examined using several fit indices. Subsequently, EFA was conducted in the subsample and dietary patterns of the FFQ and the 3DFD were compared. SETTING: Singapore. PARTICIPANTS: 1007 women planning pregnancy (18-45 years). RESULTS: Three dietary patterns were identified from the FFQ: the 'Fish, Poultry/Meat and Noodles' pattern was characterised by higher intakes of fish, poultry/meat and noodles in soup; 'Fast Food and Sweetened Beverages' pattern was characterised by higher intakes of fast food, sweetened beverages and fried snacks; 'Bread, Legumes and Dairy' pattern was characterised by higher intakes of buns/ethnic breads, nuts/legumes and dairy products. The comparative fit indices from the CFA models were 0·79 and 0·34 for the FFQ and 3DFD of the subsample, respectively. In the subsample, three similar patterns were identified in the FFQ while only two for the 3DFD. CONCLUSIONS: Dietary patterns from the FFQ are reproducible within this cohort, providing a basis for future investigations on diet and health outcomes.
OBJECTIVE: To identify a posteriori dietary patterns among women planning pregnancy and assess the reproducibility of these patterns in a subsample using two dietary assessment methods. DESIGN: A semi-quantitative FFQ was administered to women enrolled in the Singapore PREconception Study of long-Term maternal and child Outcomes study. Dietary patterns from the FFQ were identified using exploratory factor analysis (EFA). In a subsample of women (n 289), 3-d food diaries (3DFD) were also completed and analysed. Reproducibility of the identified patterns was assessed using confirmatory factor analysis (CFA) in the subsample, and goodness of fit of the CFA models was examined using several fit indices. Subsequently, EFA was conducted in the subsample and dietary patterns of the FFQ and the 3DFD were compared. SETTING: Singapore. PARTICIPANTS: 1007 women planning pregnancy (18-45 years). RESULTS: Three dietary patterns were identified from the FFQ: the 'Fish, Poultry/Meat and Noodles' pattern was characterised by higher intakes of fish, poultry/meat and noodles in soup; 'Fast Food and Sweetened Beverages' pattern was characterised by higher intakes of fast food, sweetened beverages and fried snacks; 'Bread, Legumes and Dairy' pattern was characterised by higher intakes of buns/ethnic breads, nuts/legumes and dairy products. The comparative fit indices from the CFA models were 0·79 and 0·34 for the FFQ and 3DFD of the subsample, respectively. In the subsample, three similar patterns were identified in the FFQ while only two for the 3DFD. CONCLUSIONS: Dietary patterns from the FFQ are reproducible within this cohort, providing a basis for future investigations on diet and health outcomes.
Entities:
Keywords:
A posteriori; Confirmatory factor analysis; Dietary patterns; FFQ
Authors: Shan Xuan Lim; See Ling Loy; Marjorelee T Colega; Jun Shi Lai; Keith M Godfrey; Yung Seng Lee; Kok Hian Tan; Fabian Yap; Lynette Pei-Chi Shek; Yap Seng Chong; Johan G Eriksson; Jerry Kok Yen Chan; Shiao-Yng Chan; Mary Foong-Fong Chong Journal: Am J Clin Nutr Date: 2022-02-09 Impact factor: 8.472