Author
NICKLAS, THERESA - Children'S Nutrition Research Center (CNRC) | |
O'NEIL, CAROL - LSU Agcenter | |
FULGONI III, VICTOR - Nutrition Impact, Llc |
Submitted to: Journal of Nutrition
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 9/15/2014 Publication Date: 12/3/2014 Citation: Nicklas, T.A., O'Neil, C.E., Fulgoni III, V.L. 2014. Differing statistical approaches affect the relation between egg consumption, adiposity, and cardiovascular risk factors in adults. Journal of Nutrition. 145(1):170S-176S. Interpretive Summary: Associations between food patterns and adiposity are poorly understood. Two statistical approaches were used to examine the potential association between egg consumption and adiposity. The relation between egg consumption and cardiovascular risk factors varied considerably depending on the statistical approach and the covariates used in the analyses. All traditional dietary analyses in epidemiology share one strong but incorrect assumption: that exposures, such as foods or nutrients, were measured with great accuracy. Care needs to be taken with data interpretation of diet and health risk factors and the choice of statistical approaches because these epidemiologic studies are used to generate hypotheses. More studies are needed to develop statistical methods that reduce bias when evaluating dietary hypotheses in more detail. A number of methods are being explored, yet they are usually complicated and will not provide a simple solution. Technical Abstract: Associations between food patterns and adiposity are poorly understood. Two statistical approaches were used to examine the potential association between egg consumption and adiposity. Two statistical approaches were used to examine the potential association between egg consumption and adiposity. Participants (n = 18,987) aged >/=19 years of age were from the 2001–2008 National Health and Nutrition Examination Survey who provided 24-hour diet recall data, body mass index and waist circumference –determined adiposity measures, and blood pressure, circulating insulin, glucose, and lipid concentrations were considered cardiovascular risk factors. Covariate-adjusted least-squares means +/- standard errors were generated. The first statistical approach categorized participants into egg consumers or nonconsumers. Consumers had higher mean body mass index (in kg/m2; 28.7 +/- 0.19; P = 0.006) and waist circumference (98.26 +/- 0.43 cm; P = 0.002) than did nonconsumers (28.26 +/- 0.10 and 96.9 +/- 0.23 cm, respectively). Second, cluster analysis identified 8 distinct egg consumption patterns (explaining 39.5% of the variance in percentage of energy within the food categories).Only 2 egg patterns [egg/meat, poultry, fish/ grains/vegetables and egg/meat, poultry,fish/ grains], consumed by =2% of the population, drove the association (compared with the no-egg pattern) between egg consumption and body mass index and waist circumference. Another analysis controlled for the standard covariates and the other food groups consumed with eggs in those 2 egg patterns. Only the egg/meat, poultry, fish/other-grains pattern remained associated with body mass index and waist circumference (both P = 0.0063). The pattern analyses identified associations between an egg pattern (egg/meat, poultry, fish/other grains/potatoes/other beverages) and diastolic blood pressure and serum lipoprotein cholesterol (both P = 0.0063). A final analysis was conducted by adding percentage of energy from fast foods and medication use for diabetes to the covariates. The association between the egg/meat, poultry, fish/grains pattern and body mass index and the egg/meat, poultry, fish/potatoes/other beverages and diastolic blood pressure and lipoprotein cholesterol disappeared. Care needs to be taken with data interpretation of diet and health risk factors and the choice of statistical analyses and covariates used in the analyses because these studies are typically used to generate hypotheses. Additional studies are needed to better understand these relations. |