Latent class analysis is useful to classify pregnant women into dietary patterns

Journal of Nutrition

Volumn 140, Issue 12, 2010, Pages 2253-2259

  Sotres Alvarez, Daniela ^a   Herring, Amy H ^a,b   Siega Riz, Anna Maria ^a,b  

^a University of North Carolina at Chapel Hill   (United States)

^b UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALCOHOL; ALPHA CAROTENE; ALPHA TOCOPHEROL; ASCORBIC ACID; BETA CAROTENE; CALCIUM; CHOLESTEROL; FOLIC ACID; IRON; OMEGA 3 FATTY ACID; RETINOL; VITAMIN D; YOGHURT; ZINC;

ADOLESCENT; ADULT; APPLE; ARTICLE; CALORIC INTAKE; CHICKEN; CLASSIFICATION; COFFEE; COHORT ANALYSIS; CONFIRMATORY FACTOR ANALYSIS; DIET SUPPLEMENTATION; DIETARY INTAKE; EXPLORATORY FACTOR ANALYSIS; FEMALE; FISH; FOOD INTAKE; HUMAN; ICE CREAM; INTERMETHOD COMPARISON; LATENT CLASS ANALYSIS; MAJOR CLINICAL STUDY; MATERNAL NUTRITION; MILK; MULTIVARIATE ANALYSIS; NULLIPARA; NUTRITIONAL ASSESSMENT; PEAR; PREGNANCY; PREGNANT WOMAN; SCORING SYSTEM; SPINACH; TOMATO;

DIET; FEMALE; HUMANS; PREGNANCY; PRINCIPAL COMPONENT ANALYSIS;

EID: 78649614726     PISSN: 00223166     EISSN: 15416100     Source Type: Journal    
DOI: 10.3945/jn.110.124909     Document Type: Article

References (22)

1. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002;13:3-9.
2. Newby PK, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev. 2004;62:177-203.
3. Kant AK. Dietary patterns and health outcomes. J Am Diet Assoc. 2004;104:615-35.
4. Moeller SM, Reedy J, Millen AE, Dixon LB, Newby PK, Tucker KL, Krebs-Smith SM, Guenther PM. Dietary Patterns: Challenges and Opportunities in Dietary Patterns Research: an Experimental Biology Workshop, April 1, 2006. J Am Diet Assoc. 2007;107:1233-39.
5. Everitt B, Landau S, Leese M. Cluster analysis. Leese M, editor. London, New York: Arnold; Oxford University Press; 2001.
6. Rabe-Hesketh S, Skrondal A. Classical latent variable models for medical research. Stat Methods Med Res. 2007;17:5-32.
7. Hoffman K, Schulze MB, Boeing H, Altenburg HP. Dietary patterns: report of an international workshop. Public Health Nutr. 2002;5:89-90.
8. Fahey MT, Thane CW, Bramwell GD, Coward WA. Conditional Gaussian mixture modelling for dietary pattern analysis. J R Stat Soc Ser A Stat Soc. 2007;170:149-66.
9. Hagenaars JA, McCutcheon AL. Applied latent class analysis. Hagenaars JA, McCutcheon AL, editors. Cambridge, New York: Cambridge University Press; 2002.
10. Padmadas SS, Dias JG, Willekens FJ. Disentangling women's responses on complex dietary intake patterns from an indian cross-sectional survey: a latent class analysis. Public Health Nutr. 2006;9:204-11.
11. Knudsen VK, Orozova-Bekkevold IM, Mikkelsen TB, Wolff S, Olsen SF. Major dietary patterns in pregnancy and fetal growth. Eur J Clin Nutr. 2008;62:463-70.
12. Block G, Thompson FE, Hartman AM, Larkin FA, Guire KE. Comparison of two dietary questionnaires validated against multiple dietary records collected during a 1-year period. J Am Diet Assoc. 1992;92:686-93.
13. Skrondal A, Rabe-Hesketh S. Generalized latent variable modeling: multilevel, longitudinal, and structural equation models. Boca Raton (FL): Chapman & Hall/CRC; 2004.
14. SAS Institute Inc. SAS system for windows. Cary (NC): SAS Institute; 2002-2003;9.1.
15. Lanza ST, Collins LM, Lemmon DR, Schafer JL. PROC LCA: A SAS procedure for latent class analysis. Struct Equ Modeling. 2007;14:671.
16. Muthén LK, Muthén BO. Mplus user's guide. Fifth Edition. Los Angeles (CA): Muthén & Muthén. 1998-2006;5.1.
17. Tseng M, Breslow RA, DeVellis RF, Ziegler RG. Dietary patterns and prostate cancer risk in the national health and nutrition examination survey epidemiological follow-up study cohort. Cancer Epidemiol Biomarkers Prev. 2004;13:71-7.
18. Costacou T, Bamia C, Ferrari P, Riboli E, Trichopoulos D, Trichopoulou A. Tracing the Mediterranean diet through principal components and cluster analyses in the greek population. Eur J Clin Nutr. 2003;57:1378-85.
19. Newby PK, Muller D, Tucker KL. Associations of empirically derived eating patterns with plasma lipid biomarkers: a comparison of factor and cluster analysis methods. Am J Clin Nutr. 2004;80:759-67.
20. Muthen B, Shedden K. Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics. 1999;55:463-9.
21. Muthen B. Beyond SEM: general latent variable modeling. Behaviormetrika. 2002;29:81-117.
22. Muthen B. Should substance use disorders be considered as categorical or dimensional? Addiction. 2006;101 Suppl 1:6-16.