E Denova-Gutiérrez1, P Clark2,3, K L Tucker4, P Muñoz-Aguirre5, J Salmerón5,6. 1. Hospital Infantil de Mexico Federico Gomez, Ciudad de México, Mexico. 2. Hospital Infantil de Mexico Federico Gomez, Ciudad de México, Mexico. osteoclark@gmail.com. 3. Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, Mexico. osteoclark@gmail.com. 4. Department of Clinical Laboratory and Nutritional Sciences, University of Massachusetts Lowell, Lowell, MA, USA. 5. Unidad de Investigación Epidemiológica y en Servicios de Salud, Instituto Mexicano del Seguro Social, Cuernavaca, México. 6. Centro de Investigación en Salud Poblacional, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, México.
Abstract
UNLABELLED: Several types of nutrients and foods affect bone mineral density (BMD). However, these nutrients occur together in food groups and dietary patterns, and the overall effects of dietary patterns are not yet well known. INTRODUCTION: We evaluated the associations between dietary patterns and BMD among adults participating in the Health Workers Cohort Study. METHODS: In a cross-sectional analysis, we examined 6915 Mexican adults aged 20-80 years. All participants completed a validated self-administered food frequency questionnaire (FFQ) and had total, hip, and spine BMD measurements assessed by dual-energy X-ray absorptiometry (DXA). The FFQ included 116 foods, which were grouped into 22 categories and entered into a factor analysis to derive dietary patterns. RESULTS: Three dietary patterns emerged-a Prudent, a Refined foods, and a Dairy and fish pattern. After adjustment for potential confounders, those in the highest quintile of the Prudent pattern had lower odds (OR) of low spine BMD (OR = 0.80; 95 % CI 0.68, 0.94; P for trend = 0.031) compared to those in the lowest quintile. In contrast, participants in the highest quintile of the Refined foods pattern had greater odds of low total BMD (OR = 1.74; 95 % CI 1.10, 2.76; P for trend = 0.016) than those in the lowest quintile. Finally, participants in the highest quintile of the Dairy and fish dietary pattern had significantly lower likelihood of having low BMD. CONCLUSION: This study identified specific dietary patterns associated with BMD among a Mexican adult population and highlights the importance of promoting food-based prevention strategies for maintaining bone health.
UNLABELLED: Several types of nutrients and foods affect bone mineral density (BMD). However, these nutrients occur together in food groups and dietary patterns, and the overall effects of dietary patterns are not yet well known. INTRODUCTION: We evaluated the associations between dietary patterns and BMD among adults participating in the Health Workers Cohort Study. METHODS: In a cross-sectional analysis, we examined 6915 Mexican adults aged 20-80 years. All participants completed a validated self-administered food frequency questionnaire (FFQ) and had total, hip, and spine BMD measurements assessed by dual-energy X-ray absorptiometry (DXA). The FFQ included 116 foods, which were grouped into 22 categories and entered into a factor analysis to derive dietary patterns. RESULTS: Three dietary patterns emerged-a Prudent, a Refined foods, and a Dairy and fish pattern. After adjustment for potential confounders, those in the highest quintile of the Prudent pattern had lower odds (OR) of low spine BMD (OR = 0.80; 95 % CI 0.68, 0.94; P for trend = 0.031) compared to those in the lowest quintile. In contrast, participants in the highest quintile of the Refined foods pattern had greater odds of low total BMD (OR = 1.74; 95 % CI 1.10, 2.76; P for trend = 0.016) than those in the lowest quintile. Finally, participants in the highest quintile of the Dairy and fish dietary pattern had significantly lower likelihood of having low BMD. CONCLUSION: This study identified specific dietary patterns associated with BMD among a Mexican adult population and highlights the importance of promoting food-based prevention strategies for maintaining bone health.
Entities:
Keywords:
Bone mineral density; Dietary patterns; Factor analysis; Health Workers Cohort Study
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