Location: Human Nutrition Research Center on Aging
Title: Empirically derived dietary fatty acid patterns and metabolic syndrome risk factors: the Boston Puerto Rican Health Study Authors
|Noel, Sabrina -|
|Newby, P -|
Submitted to: Journal of Nutrition
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 12, 2010
Publication Date: October 1, 2010
Citation: Noel, S.E., Newby, P.K., Ordovas, J.M., Tucker, K. 2010. Empirically derived dietary fatty acid patterns and metabolic syndrome risk factors: the Boston Puerto Rican Health Study. Journal of Nutrition. 140(10):1846-1854. Interpretive Summary: The prevalence of metabolic syndrome in the US is on the rise and is particularly high for older adults and certain ethnic groups. Hispanics have the highest reported prevalence of metabolic syndrome and are more likely to be affected by type 2 diabetes than non-Hispanic whites. Puerto Ricans, currently the second largest Hispanic subgroup in the U.S, are burdened by excess chronic health conditions and report poorer health status than other Hispanic groups. We previously showed that Puerto Rican elders in Massachusetts were twice as likely to have type 2 diabetes compared with a representative neighborhood-based sample of non-Hispanic whites and that up to 50% had metabolic syndrome. Lifestyle behaviors such as diet play an important role in the development of metabolic syndrome. Total fat and type of dietary fat consumed have been associated with metabolic syndrome and its components; however, results are inconsistent. A combination of unsaturated fatty acids along with moderate total fat intake may offer the most benefit for several metabolic-related risk factors. There is limited information on the dietary habits of Puerto Ricans living on the US mainland. In this study, we aim to: 1) characterize fatty acid patterns of Boston Puerto Rican adults aged 45-75 years and, 2) examine associations between the fatty acid patterns and metabolic syndrome in this unique population. Using factor analysis to identify dietary fatty acid patterns revealed four unique patterns in this population. Dietary fatty acid patterns were related to several metabolic syndrome components. The n-3 fatty acid/fish pattern was associated with overall lower likelihood of metabolic syndrome. More research is needed to identify the optimal combination of individual fatty acids, given their diverse effects on metabolism.
Technical Abstract: Combinations of fatty acids may affect risk of metabolic syndrome. Puerto Ricans, the second largest US Hispanic subgroup, endure a disproportionate number of chronic conditions compared with other Hispanic groups. We aimed to characterize the fatty acid patterns of 1207 Boston Puerto Rican adults aged 45-75 y, and to examine associations between these patterns and metabolic syndrome. Dietary fatty acids, as percent of total fat, were entered into principle components analysis. Pearson and Spearman correlation coefficients were examined between fatty acid patterns, selected nutrients and for food groups. Associations between metabolic syndrome and its components were examined using logistic regression and general linear models for factor quintiles, respectively. Four patterns emerged as most meaningful: a short and medium chain saturated fatty acid (SFA)/dairy, an n-3/fish, a long chain SFA/oils and a monounsaturated (MUFA)/trans fat pattern. The SFA/dairy pattern was inversely associated with fasting plasma glucose concentrations (P=0.02), but was no longer statistically significant after adjustment for BMI (P=0.11). Factor 3 was negatively related to waist circumference (P=0.008). The n-3/fish pattern was associated with lower likelihood of metabolic syndrome (Q5 vs. Q1- OR: 0.54, 95% CI: 0.34, 0.86). Using factor analysis to identify dietary fatty acid patterns revealed four unique patterns in this population. Dietary fatty acid patterns were related to several metabolic syndrome components. The n-3/fish pattern was associated with overall lower likelihood of metabolic syndrome. More research is needed to identify the optimal combination of individual fatty acids, given their diverse effects on metabolism.