Briana J K Stephenson1, Daniela Sotres-Alvarez2, Anna-Maria Siega-Riz3, Yasmin Mossavar-Rahmani4, Martha L Daviglus5, Linda Van Horn6, Amy H Herring7,8,9, Jianwen Cai2. 1. Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA. 2. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 3. Department of Nutrition, School of Public Health and Health Services, University of Massachusetts, Amherst, MA, USA. 4. Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA. 5. Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA. 6. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. 7. Department of Statistical Science, Duke University, Durham, NC, USA. 8. Duke Global Health Institute, Duke University, Durham, NC, USA. 9. Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Abstract
BACKGROUND: Latent class models (LCMs) have been used in exploring dietary behaviors over a wide set of foods and beverages in a given population, but are prone to overgeneralize these habits in the presence of variation by subpopulations. OBJECTIVES: This study aimed to highlight unique dietary consumption differences by both study site and ethnic background of Hispanic/Latino populations in the United States, that otherwise might be missed in a traditional LCM of the overall population. This was achieved using a new model-based clustering method, referred to as robust profile clustering (RPC). METHODS: A total of 11,320 individuals aged 18-74 y from the Hispanic Community Health Study/Study of Latinos (2008-2011) with complete diet data were classified into 9 subpopulations, defined by study site (Bronx, Chicago, Miami, San Diego) and ethnic background. At baseline, dietary intake was ascertained using a food propensity questionnaire. Dietary patterns were derived from 132 food groups using the RPC method to identify patterns of the general Hispanic/Latino population and those specific to an identified subpopulation. Dietary patterns derived from the RPC were compared to those identified from an LCM. RESULTS: The LCM identified 48 shared consumption behaviors of foods and beverages across the entire cohort, whereas significant consumption differences in subpopulations were identified in the RPC model for these same foods. Several foods were common within study site (e.g., chicken, orange juice, milk), ethnic background (e.g., papayas, plantain, coffee), or both (e.g., rice, tomatoes, seafood). Post hoc testing revealed an improved model fit in the RPC model [Deviance Information Criterion DICRPC = 2.3 × 104, DICLCM = 9.5 × 106]. CONCLUSIONS: Dietary pattern behaviors of Hispanics/Latinos in the United States tend to align by ethnic background for some foods and by location for other foods. Consideration of both factors is imperative to better understand their contributions to population health and developing targeted nutrition intervention studies.
BACKGROUND: Latent class models (LCMs) have been used in exploring dietary behaviors over a wide set of foods and beverages in a given population, but are prone to overgeneralize these habits in the presence of variation by subpopulations. OBJECTIVES: This study aimed to highlight unique dietary consumption differences by both study site and ethnic background of Hispanic/Latino populations in the United States, that otherwise might be missed in a traditional LCM of the overall population. This was achieved using a new model-based clustering method, referred to as robust profile clustering (RPC). METHODS: A total of 11,320 individuals aged 18-74 y from the Hispanic Community Health Study/Study of Latinos (2008-2011) with complete diet data were classified into 9 subpopulations, defined by study site (Bronx, Chicago, Miami, San Diego) and ethnic background. At baseline, dietary intake was ascertained using a food propensity questionnaire. Dietary patterns were derived from 132 food groups using the RPC method to identify patterns of the general Hispanic/Latino population and those specific to an identified subpopulation. Dietary patterns derived from the RPC were compared to those identified from an LCM. RESULTS: The LCM identified 48 shared consumption behaviors of foods and beverages across the entire cohort, whereas significant consumption differences in subpopulations were identified in the RPC model for these same foods. Several foods were common within study site (e.g., chicken, orange juice, milk), ethnic background (e.g., papayas, plantain, coffee), or both (e.g., rice, tomatoes, seafood). Post hoc testing revealed an improved model fit in the RPC model [Deviance Information Criterion DICRPC = 2.3 × 104, DICLCM = 9.5 × 106]. CONCLUSIONS: Dietary pattern behaviors of Hispanics/Latinos in the United States tend to align by ethnic background for some foods and by location for other foods. Consideration of both factors is imperative to better understand their contributions to population health and developing targeted nutrition intervention studies.
Authors: Changzheng Yuan; Donna Spiegelman; Eric B Rimm; Bernard A Rosner; Meir J Stampfer; Junaidah B Barnett; Jorge E Chavarro; Amy F Subar; Laura K Sampson; Walter C Willett Journal: Am J Epidemiol Date: 2017-04-01 Impact factor: 4.897
Authors: Paul D Sorlie; Larissa M Avilés-Santa; Sylvia Wassertheil-Smoller; Robert C Kaplan; Martha L Daviglus; Aida L Giachello; Neil Schneiderman; Leopoldo Raij; Gregory Talavera; Matthew Allison; Lisa Lavange; Lloyd E Chambless; Gerardo Heiss Journal: Ann Epidemiol Date: 2010-08 Impact factor: 3.797
Authors: Michael T Fahey; Pietro Ferrari; Nadia Slimani; Jeroen K Vermunt; Ian R White; Kurt Hoffmann; Elisabet Wirfält; Christina Bamia; Mathilde Touvier; Jakob Linseisen; Miguel Rodríguez-Barranco; Rosario Tumino; Eiliv Lund; Kim Overvad; Bas Bueno de Mesquita; Sheila Bingham; Elio Riboli Journal: J Epidemiol Community Health Date: 2011-08-28 Impact factor: 3.710
Authors: Yasmin Mossavar-Rahmani; Molly Jung; Sanjay R Patel; Daniela Sotres-Alvarez; Raanan Arens; Alberto Ramos; Susan Redline; Cheryl L Rock; Linda Van Horn Journal: Appetite Date: 2015-07-16 Impact factor: 3.868