Nutrient density

Abstract: Previous cohort studies of fat intake and risk of coronary heart disease (CHD) have been inconsistent, probably due in part to methodological differences and various limitations, including inadequate dietary assessment and incomplete adjustment for total energy intake. The authors analyzed repeated assessment of diet from the Nurses' Health Study to examine the associations between intakes of four major types of fat (saturated, monounsaturated, polyunsaturated, and trans fats) and risk of CHD during 14 years of follow-up (1980-1994) by using alternative methods for energy adjustment. In particular, the authors compared four risk models for energy adjustment: the standard multivariate model, the energy-partition model, the nutrient residual model, and the multivariate nutrient density model. Within each model, the authors compared four different approaches for analyzing repeated dietary measurements: baseline diet only, the most recent diet, and two different algorithms for calculating cumulative average diets. The substantive results were consistent across all models; that is, higher intakes of saturated and trans fats were associated with increased risk of CHD, while higher intakes of monounsaturated and polyunsaturated fats were associated with reduced risk. When nutrients were considered as continuous variables, the four energy-adjustment methods yielded similar associationS. However, the interpretation of the relative risks differed across models. In addition, within each model, the methods using the cumulative averages in general yielded stronger associations than did those using either only baseline diet or the most recent diet. When the nutrients were categorized according to quintiles, the residual and the nutrient density models, which gave similar results, yielded statistically more significant tests for linear trend than did the standard and the partition models.

Abstract: Ranking and/or classifying foods based on their nutrient composition is known as nutrient profiling. Nutrition quality indices need to be tested and validated against quality of the total diet. A family of nutrient-rich foods (NRF) indices were validated against the Healthy Eating Index (HEI), an accepted measure of diet quality. All foods consumed by participants in NHANES 1999-2002 studies were scored using NRFn.3 (where n = 6-15) indices based on unweighted sums, means, and ratios of percent daily values (DV) for nutrients to encourage (n) and for nutrients to limit (LIM) (3). Individual food scores were calculated based on 100 kcal (418 kJ) and FDA serving sizes [reference amounts customarily consumed (RACC)]. Energy-weighted food-based scores per person were then regressed against HEI, adjusting for gender, age, and ethnicity. The measure of index performance was the percentage of variation in HEI (R2) explained by each NRF score. NRF indices based on both nutrients to encourage and LIM performed better than indices based on LIM only. Maximum variance in HEI was explained using 6 or 9 nutrients to encourage; index performance actually declined with the inclusion of additional vitamins and minerals. NRF indices based on 100 kcal (418 kJ) performed similarly to indices based on RACC. Algorithms based on sums or means of nutrient DV performed better than ratio-based scores. The NRF9.3 index, based on 9 nutrients to encourage and 3 LIM per RACC and per 100 kcal, explained the highest percentage of variation from HEI and could be readily expected to rank foods based on nutrient density.