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Certain Grain Food Patterns Are Associated with Improved 2015 Dietary Guidelines Shortfall Nutrient Intakes, Diet Quality, and Lower Body Weight in US Adults: Results from the National Health and Nutrition Examination Survey, 2005-2010

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Objective: The goal of this study was to identify commonly consumed grain food patterns in US adults (≥19 years old; N = 14,384) and compare nutrient intakes, with focus on 2015-2020 Dietary Guidelines’ shortfall nutrients, diet quality, and health parameters of those consuming various grain food patterns to those not consuming grains. Methods: This study conducted secondary analyses of the National Health and Nutrition Examination Survey, 2005-2010. Cluster analysis was used and identified 8 grain patterns: 1) no consumption of main grain groups, 2) crackers and salty snacks, 3) yeast breads and rolls, 4) cakes, cookies, and pies, 5) cereals, 6) pasta, cooked cereals and rice, 7) quick breads, and 8) mixed grains. Results: Adults consuming “cereals”, “pasta, cooked cereals and rice”, and “mixed grains” had a better diet quality compared to no grains. Consuming many, but not all, of the grain food patterns resulted in less saturated fat and lower added sugars. Adults consuming “cereals”, “pasta, cooked cereals and rice” and “quick breads” had greater dietary fiber intake vs. no grains group. Calcium intake was increased in the cereals group, while magnesium intake was greater in adults consuming “cereals” and “pasta, cooked cereals and rice” vs. no grains. Vitamin D (D2 + D3) intake was higher in adults consuming “cereals”, “pasta, cooked cereals and rice”, and “mixed grains” vs. no grain group. Adults consuming “pasta, cooked cereals and rice” had lower body weights (79.1 ± 0.7 vs. 82.5 ± 1.2 kg; P = 0.009) and waist circumference (95.2 ± 0.6 vs. 98.2 ± 1.0 cm; P = 0.004) in comparison to those consuming no grains. Conclusions: Certain grain food patterns are associated with greater 2015-2020 Dietary Guidelines’ shortfall nutrients, better diet quality and lower body weights in adults. Additionally, certain grain food patterns are associated with lower intake of nutrients to limit, including saturated fat and added sugars.
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Food and Nutrition Sciences, 2016, 7, 772-781
Published Online July 2016 in SciRes. http://www.scirp.org/journal/fns
http://dx.doi.org/10.4236/fns.2016.79078
How to cite this paper: Papanikolaou, Y. and Fulgoni III, V.L. (2016) Certain Grain Food Patterns Are Associated with Im-
proved 2015 Dietary Guidelines Shortfall Nutrient Intakes, Diet Quality, and Lower Body Weight in US Adults: Results from
the National Health and Nutrition Examination Survey, 2005-2010. Food and Nutrition Sciences, 7, 772-781.
http://dx.doi.org/10.4236/fns.2016.79078
Certain Grain Food Patterns Are Associated
with Improved 2015 Dietary Guidelines
Shortfall Nutrient Intakes, Diet Quality, and
Lower Body Weight in US Adults: Results
from the National Health and Nutrition
Examination Survey, 2005-2010
Yanni Papanikolaou1*, Victor L. Fulgoni III2
1Nutritional Strategies Inc., Paris, ON, Canada
2Nutrition Impact, LLC, Battle Creek, MI, USA
Received 11 May 2016; accepted 22 July 2016; published 25 July 2016
Copyright © 2016 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/
Abstract
Objective: The goal of this study was to identify commonly consumed grain food patterns in US
adults (≥19 years old; N = 14,384) and compare nutrient intakes, with focus on 2015-2020 Dietary
Guidelinesshortfall nutrients, diet quality, and health parameters of those consuming various
grain food patterns to those not consuming grains. Methods: This study conducted secondary ana-
lyses of the National Health and Nutrition Examination Survey, 2005-2010. Cluster analysis was
used and identified 8 grain patterns: 1) no consumption of main grain groups, 2) crackers and
salty snacks, 3) yeast breads and rolls, 4) cakes, cookies, and pies, 5) cereals, 6) pasta, cooked ce-
reals and rice, 7) quick breads, and 8) mixed grains. Results: Adults consuming “cereals”, “pasta,
cooked cereals and rice”, and “mixed grains” had a better diet quality compared to no grains. Con-
suming many, but not all, of the grain food patterns resulted in less saturated fat and lower added
sugars. Adults consuming “cereals”, “pasta, cooked cereals and rice” and “quick breads” had
greater dietary fiber intake vs. no grains group. Calcium intake was increased in the cereals group,
while magnesium intake was greater in adults consuming “cereals” and “pasta, cooked cereals and
rice” vs. no grains. Vitamin D (D2 + D3) intake was higher in adults consuming cereals, pasta,
cooked cereals and rice, and mixed grainsvs. no grain group. Adults consuming pasta, cooked
cereals and ricehad lower body weights (79.1 ± 0.7 vs. 82.5 ± 1.2 kg; P = 0.009) and waist cir-
cumference (95.2 ± 0.6 vs. 98.2 ± 1.0 cm; P = 0.004) in comparison to those consuming no grains.
*Corresponding author.
Y. Papanikolaou, V. L. Fulgoni III
773
Conclusions: Certain grain food patterns are associated with greater 2015-2020 Dietary Guide-
linesshortfall nutrients, better diet quality and lower body weights in adults. Additionally, certain
grain food patterns are associated with lower intake of nutrients to limit, including saturated fat
and added sugars.
Keywords
NHANES, Grain Food Patterns, Nutrient Intakes, Diet Quality, Body Weight
1. Introduction
The 2015-2020 Dietary Guidelines for Americans (2015-2020 Dietary Guidelines) policy report identified that a
healthy dietary pattern is higher in fruits, vegetables, whole grains, low- and non-fat dairy, seafood, legumes,
and nuts; moderate in alcohol for adults; and lower in red and processed meat, sugar-sweetened foods and beve-
rages and refined grains [1]. Furthermore, in comparison to recommended United States Department of Agri-
culture (USDA) food patterns, the majority of US adults and children have low intakes of select food groups that
are key contributors to shortfall nutrients, including vegetables, fruits, whole grains, and dairy products, while
intake of refined grains and added sugars remains higher than recommended [1]. However, a variety of grain-
based food products, of which include refined grains, are sources for several shortfall nutrients identified by the
2015-2020 Dietary Guidelines [1], including dietary fiber, folate, iron, and magnesium. With mandatory folic
acid fortification commencing in 1998 by the Food and Drug Administration [2], specific grain foods became
leading sources for folate; breads, rolls, and crackers are the largest contributor of total folate to the US diet,
contributing nearly 16% of total intake, which exceeds contribution of folate from vegetables [3]. Similarly, us-
ing data from the National Health and Nutrition Examination Survey (NHANES) 2003-2006, researchers have
reported that fortification substantially contributes nutrient adequacy for children and adolescents in the US,
without excessive intakes for most vitamins and minerals [4].
While certain grain food products are rich in nutrients to limit in the diet, including added sugar, total and sa-
turated fat [5] [6], grain foods can contribute positive nutrients to the diet, of which include dietary fiber, iron,
magnesium, and B vitamins (thiamin, riboflavin, niacin and folate). A 2003-2006 NHANES analysis examining
food sources of energy and nutrients in adults showed that while four of the top ten ranking foods for calorie
contribution to the total diet were grain foods, the top ten ranking food sources of dietary fiber included five
grain-based productsyeast breads and rolls ranked as the top source of dietary fiber to the diet of US adults,
contributing 10.9% of total dietary fiber [7]. Similarly, researchers have demonstrated that half of the top ten
greatest contributors of calories also contribute 10% or more of the total dietary fiber and micronutrients to the
US diet. Indeed, while three of the top 10 sources of energy provided no nutritional value, the remaining sources
of energy, including milk, beef, poultry, cheese and baked goods were significant contributors of nutrients of
concern and other essential nutrients, and thus, eliminating these foods from food patterns could potentially have
inadvertent effects on diet quality in the US population [6].
While 2015-2020 Dietary Guidelines identify several healthy dietary food patterns, and encourage increased
whole grain consumption and reduced refined grain intake, at present, there are no data that evaluate the associ-
ation of different grain food patterns on nutrient and health-related outcomes in adults. As such, the objective of
the current analyses was to isolate the most commonly consumed grain food patterns in US adults and compare
nutrient intakes, diet quality, and health parameters of those consuming various grain food patterns to those not
consuming main grain foods using data from several National Health and Nutrition Examination Survey
(NHANES) 2005-2010 datasets. The hypothesis for the present analysis was that certain grain food patterns can
significantly contribute positive nutrients, while concurrently lowering nutrients to limit in the diet. Additionally,
we hypothesized that certain grain food patterns would be associated with improved measures on health para-
meters including body weight and overweight or obesity-related outcomes.
2. Subjects and Methods
Data were obtained from What We Eat in America, the dietary intake component of NHANES. NHANES is a
Y. Papanikolaou, V. L. Fulgoni III
774
government-directed program led by the Center for Disease Control and Prevention in collaboration with USDA.
Written informed consent was obtained for all participants or proxies, and the survey protocol was approved by
the Research Ethics Review Board at the National Center for Health Statistics. Data from the current NHANES
analysis are released every two years; for this study three data releases were used, namely 2005-2006, 2007-
2008, and 2009-2010 [8] [9].
Data from the first 24-hr dietary recall in NHANES were used, which was an in-person conducted assessment
with trained specialists using the best methods developed to date (i.e., the multiple pass method was developed
and validated, at least in adults, by the USDA), with all foods and beverages consumed in the last 24 hour period
recorded. USDA’s Food and Nutrient Database for Dietary Studies, 3.0, 4.1, and 5.0 was used to code dietary
intake data and calculate nutrient intakes [10]-[12].
To develop patterns of grain consumption we used cluster analyses which is a statistical procedure that ana-
lyses large data sets to develop various patterns while trying to maximize differences among the patterns. We
used the USDA food coding system to define categories of grain foods [12].
Grain foods intake patterns were identified using SAS 9.4 (SAS Institute, Cary, NC, 2013) PROC CLUSTER
using a single 24-hour dietary recall in NHANES 2005-2010 and applying population weights to adjust for the
complex design. Clusters were developed based on the percentage of calories consumed from the grain products
as the centroid for each cluster. Grains from flour and dry mixes, mixed dishes, and meat substitutes were not
included in development of grain clusters. Cluster analyses provides the ability to focus on a particular defined
aspect (e.g. calories from grains) and then forces maximal differences in clusters for assessment.. For these ana-
lyses, the USDA grains products were collapsed into the grain food groupings mentioned above. All food codes
fit in one and only one of the grain foods groupings. The patterns identified by the cluster analysis were then
identified by percent calories within each grain food grouping (only groups that contributed 5% or more of calo-
ries were used to define the clusters) at the centroid of each cluster. Using this method resulted in seven readily
identifiable grain food patterns and a no consumption of main grain groups (i.e., no grains group); creating eight
unique patterns of consumption. With grain foods patterns identified, and using the output from the cluster pro-
cedure, each subject was then placed in the cluster that matched most closely to the pattern of calories across the
food categories.
Adjusted mean values were determined for subjects in each cluster using PROC REGRESS in SUDAAN 11.0
with various sets of covariates. Covariates for analyses of energy intake, Healthy Eating Index (HEI)-2010 and
HEI sub-components [13] were age, gender, ethnicity, poverty income ratio, physical activity (sedentary, mod-
erate or vigorous based on questionnaire responses), current smoking status, and alcohol intake. The HEI pro-
vides a measure of diet quality and conforms to federal dietary guidance and has been predominantly used to
monitor dietary practices of the US population and the low-income subpopulation. Nutrient intakes were also
adjusted for energy intakes. For body weight, body-mass index (BMI), and waist circumference, covariates were
the same as those for energy intake. All other physiological variables had the same covariates but were also ad-
justed for BMI. The main comparison of interest was to compare results between the no grains group (cluster 0)
and all other clusters. To increase the rigor of the analyses, a P-value of P < 0.01 was set for significance in
place of the traditional value of P < 0.05.
3. Results
Eight grain clusters were identified, one of which included isolating a group of adults that did not consume any
of the identified grains (5.8% of the population). The eight clusters were defined as outlined in Table 1, namely:
1) no consumption of main grain groups, 2) crackers and salty snacks, 3) yeast breads and rolls, 4) cakes, coo-
kies, and pies, 5) cereals, 6) pasta, cooked cereal and rice, 7) quick breads, and 8) mixed grains.
3.1. Energy and Nutrient Intakes
Nutrient and energy intakes in the eight grain food patterns are presented in Table 2. In adults, energy intake
was significantly higher in those in all clusters as compared to individuals in the no grains cluster. The higher
energy intake ranged from 340 to 567 kcal/d with mixed grains cluster representing the greatest increase in
kcal/day (Table 2).
When examining nutrients of concern, as outlined by the 2015 DGAC [16], calcium intake was higher in
adults consuming cerealsas compared to those not consuming grain foods, while dietary fiber was higher in
Y. Papanikolaou, V. L. Fulgoni III
775
Table 1. Grain cluster pattern based on percentage of calories from grains in adults ≥19 years old of age using data from NHANES
2005-2010.
Cluster number Grain foods pattern Description
0 No grains 5.8% of the population
1 Crackers and salty snacks (9.4% of the population) with over 73% of grains coming from this grain group;
2 Yeast breads and rolls (22.6% of the population) with over 92% of grains coming from this grain group;
3 Cakes, cookies and pies (4.6% of the population) with over 88% of grains coming from this grain group;
4 Cereals (4.3% of the population) with over 75% of grains coming from this grain group;
5 Pasta, cooked cereals and rice (10.5% of the population) with over 59% of grains coming from this grain group;
6 Quick breads (13.1% of the population) with over 69% of grains coming from this grain group;
7 Mixed grains (29.7% of the population) with almost 50% of grains coming from yeast bread
and rolls but with significant percentages of grains coming from cakes, cookies
and pies (14.5%); crackers and salty snacks (12.5%); and cereals (9.4%).
Table 2. Adjusted Mean (SE) nutrient and energy intake for all grain clusters using NHANES 2005-2010, 19 years of age.
No Grains Cracke rs/Salty
Snacks Yeast Breads
and Rolls Cakes/Cookies/Pies Cereals Pasta/Cooked
Cereals/Rice Quick Breads Mixed Grains
Energy or Nutrient Cluster 0 Clust er 1 Cluster 2 Cluster 3 Clu ster 4 Cluste r 5 Cluster 6 C luster 7
LSM SE LSM
SE P LSM
SE P LSM
SE P LSM
SE P LSM
SE P LSM
SE P LSM
SE P
Energy (kcal) 1715 44.9 2226
43.3
<0.0001
2055
17.7
<0.0001 2244 54.1
<0.0001 2080 51.3
<0.0001 2069
21.4
<0.0001 2247
27.2
<0.0001 2282
23.2
<0.0001
Carbohydrate (g) 247 2.73 257 3.01
0.0184 247 1.58
0.9120 265 3.22
<0.0001 276 2.74
<0.0001 271 2.08
<0.0001 257 2.22
0.0028 264 1.38
<0.0001
Total sugars (g) 125 2.63 112 2.40
0.0007 113 1.84
<0.0001 141 3.57
0.0005 128 2.71
0.3916 115 1.97
0.0005 109 1.50
<0.0001 121 1.33
0.2127
Added Sugar
(tsp eq) 20. 1 0.79 18.1 0.53
0.0268 18.1 0.43
0.0105 24.7 0.93
0.0001 18.5 0.67
0.0927 16.3
0.44
<0.0001 16.9 0.41
0.0001 19.0 0.32
0.2091
Protein (g) 86.1 1.16 78.0 1.18
<0.0001
87.4 0.62
0.2641 76.8 1.37
<0.0001 84.4 1.20
0.2788 86.9
1.27
0.6445 83.9 0.92
0.1550 81.5 0.65
0.0027
Total fat (g) 85.6 0.96 85.2 1.17
0.7599 84.6 0.58
0.2729 82.0 1.05
0.0090 75.1 0.96
<0.0001 74.7
0.70
<0.0001 82.0 0.84
0.0027 80.3 0.48
<0.0001
Total monounsaturated
fatty acids (g) 31.4 0.41 31. 1 0.47
0.5754 30.7 0.26
0.0882 31.3 0.44
0.8863 27.2 0.48
<0.0001 27.1
0.31
<0.0001 30.5 0.35
0.0678 29.3 0.22
<0.0001
Total saturated
fatty acids (g) 28.8 0.49 27. 4 0.43
0.0346 29.0 0.22
0.7347 26.9 0.60
0.0096 25.5 0.50
<0.0001 24.0
0.27
<0.0001 26 0.34
0.0001 26.8 0.18
0.0002
Cholest erol (mg) 322 13.1 259 6.75
0.0002 318 5.37
0.7112 270 9.58
0.0014 224 7.04
<0.0001 269 7.63
0.0016 307 7.89
0.3358 279 4.68
0.0034
Dietary fiber (g) 14.9 0.58 16.4 0.31
0.0142 14.3 0.21
0.3176 14.1 0.46
0.3367 19.4 0.56
<0.0001 18.1
0.37
<0.0001 18.0 0.49
<0.0001 16.2 0.17
0.0285
Calc ium (mg) 939 23.0 937 20.9
0.9385 969 11.0
0.2604 901 36.1
0.3439 1158 33.9
<0.0001 968 17.0
0.2624 942 21.9
0.9224 987 10.6
0.0592
Magnesiu m (mg) 296 7.45 301 3.45
0.4726 285 2.34
0.1488 271 6.68
0.0200 335 6.69
0.0001 341 4.82
<0.0001 308 6.70
0.1749 299 2.31
0.6764
Iron (mg) 12.7 0.21 13.9 0.23
<0.0001
13.8 0.12
<0.0001 13.5 0.29
0.0246 23.9 0.36
<0.0001 17.0
0.29
<0.0001 15.3 0.27
<0.0001 16.6 0.14
<0.0001
Zinc (mg) 12.8 0.79 11.3 0.19
0.0860 11.9 0.13
0.2950 10.7 0.25
0.0120 16.8 0.79
0.0003 12.7
0.43
0.9290 12.4 0.39
0.6851 12.4 0.13
0.6374
Sod ium (mg) 3590 55.9 3763
53.5
0.0187 3710
29.3
0.0437 3270 62.2
0.0003 3376 46.8
0.0036 3747
46.0
0.0386 3668
28.3
0.2201 3604
21.3
0.8104
Pot assium (m g) 2839 65.5 2602
34.0
0.0013 2708
22.5
0.0504 2529 52.9
0.0005 2941 43.2
0.1628 2827
31.4
0.8747 2735
34.8
0.1049 2695
19.7
0.0473
Folate, DFE (mcg) 438 10.0 462 10.5
0.0796 483 6.48
0.0001 467 14.4
0.0448 867 21.8
<0.0001 615 11.9
<0.0001 506 8.65
<0.0001 582 8.41
<0.0001
Ribofla vin
(Vit amin B2) (mg) 2.02 0.04 2.11 0.04
0.1003 2.14 0.02
0.0084 2.01 0.05
0.8633 2.96 0.06
<0.0001 2.23
0.03
0.0006 2.15 0.03
0.0132 2.32 0.02
<0.0001
Thiamin (V itamin B1)
(mg) 1.41 0.03 1.42 0.02
0.8396 1.60 0.02
<0.0001 1.45 0.06
0.5113 2.15 0.04
<0.0001 1.75
0.02
<0.0001 1.63 0.03
<0.0001 1.78 0.03
<0.0001
Total choline (mg) 349 8.08 307 5.16
<0.0001
348 3.24
0.9160 309 7.16
0.0011 314 5.83
0.0003 338 5.16
0.2753 350 5.02
0.9427 328 3.21
0.0271
Vitamin A,
RAE ( mcg) 575 24.9 578 18.2
0.9305 557 16.5
0.5498 593 29.8
0.6365 828 27.1
<0.0001 736 23.7
<0.0001 601 33.8
0.5375 652 10.3
0.0086
Y. Papanikolaou, V. L. Fulgoni III
776
Continued
Vitamin B12 (mcg) 5.10 0.24 4.92 0.19
0.5607 5.43 0.12
0.2090 5.12 0.64
0.9709 8.39 0.21
<0.0001 5.25 0.19
0.5869 5.09 0.14
0.9697 5.59 0.09
0.0656
Vita min B6 (mg ) 1.95 0.06 1.85 0.06
0.2415 1.88 0.02
0.3303 1.77 0.07
0.0340 2.88 0.05
<0.0001 2.23 0.04
0.0008 1.99 0.05
0.5909 2.10 0.02
0.0276
Vita min C (mg) 99.9 6.97 80.2 5.14
0.0277 82.6 1.92
0.0109 76.2 5.07
0.0062 89.7 4.25
0.2309 96.9 3.38
0.6699 83.3 2.77
0.0220 86.2 2.02
0.0694
Vitamin D (D2 + D3)
(mcg) 4.11 0.21 4.15 0.24
0.8750 4.50 0.11
0.0699 4.21 0.22
0.7326 6.80 0.24
<0.0001 5.07 0.16
0.0008 4.38 0.18
0.2589 4.99 0.12
0.0006
Vitamin E as
alpha-tocopherol (mg) 8.02 0.26 7.76 0.19
0.2818 7.39 0.14
0.0176 7.42 0.28
0.1301 8.41 0.39
0.4306 8.08 0.26
0.8833 7.56 0.25
0.1653 7.57 0.12
0.1367
Vitamin K ( mcg) 107 8.08 99.3 6.00
0.3709 89.5 3.43
0.0368 112 8.41
0.6924 91.1 7.12
0.1241 131 8.49
0.0342 111 5.44
0.6689 93.1 2.91
0.1066
NHANES 2005-2010, N = 14,384; LSM = least square mean; SE = standard error; P = P value of difference as compared to cluster 0 (No grains); Covariates
include age, gender, ethnicity, poverty income ratio, physical activity, current smoking status, alcohol and for all variables except Energy, the covariate of
energy (kcal).
adults consuming “cereals”, “pasta, cooked cereals and rice”, and quick breads”, ranging from 3.1 to 4.5 g/day
of increased fiber consumption as compared to those in the no grains group. Vitamin D was greater in those
consuming cereals”, pasta, cooked cereals and riceand mixed grains”, while potassium was lower in adults
consumingcrackers and salty snacksandcakes, cookies and piesas compared to those not consuming grain
food products.
Regarding nutrients to limit, total saturated fat intake was reduced in all grain patterns examined, except
yeast breads and rollsand crackers and salty snacks(i.e., the range of saturated fat intake was between 1.9
and 4.8 g/day lower; see Table 2) and sodium intake was decreased (213 to 319 mg/day) in adults consuming
cakes, cookies and piesand cerealswhen compared to adults not consuming grain foods. Total sugars were
lower (10.3 to 15.9 g/day) in those consuming crackers and salty snacks”, “yeast breads and rolls”, pasta,
cooked cereals and riceand quick breads”, but significantly higher (16.5 g/d) in adults predominantly con-
suming cakes, cookies and piesas compared to those not consuming grain foods. Added sugars were higher
(4.7 tsp/d) in those consuming cakes, cookies and piesand lower in those consuming pasta, cooked cereals,
and riceand quick breadsgrain patterns (3.8 and 3.1 tsp/d, respectively, see Table 2) in comparison to the no
grains group.
Regarding nutrients added to grain foods, via either enrichment or fortification practices, iron intake was
greater in adults in all grain cluster food patterns examined except for those consuming cakes, cookies and
pies, while those consuming yeast breads and rolls”, cereals”, pasta, cooked cereals and rice, and mixed
grainshad significantly higher intake of thiamin and riboflavin a as compared to adults not consuming grain
foods. Folate was higher (46 to 429 µg/d) in those in all grain food clusters, except crackers and salty snacks
and cakes, cookies and pies”, while zinc intake was higher only in adults consuming cerealscompared to
those in the no grains cluster. Magnesium intakes were significantly greater in adults consuming cerealsand
pasta, cooked cereals and ricepatterns relative to the no grains group (Table 2).
3.2. Healthy Eating Index-2010
Diet quality, as measured by USDA’s Healthy Eating Index-2010 (HEI-2010) is depicted in Table 3. Adults in
the no grain pattern had an HEI score of 46.8 ± 0.9. Adults in three of the grain clusters had significantly higher
scores relative to the no grains food pattern; adults consuming cerealshad a HEI score of 54.7 ± 1.0, while in-
dividuals consuming pasta, cooked cereals and rice”, and mixed grainshad scores of 54.4 ± 0.6 and 49.5 ±
0.3, respectively (Table 3).
When examining the subcomponents of HEI-2010 (Table 3), and focusing on adults in the cracker and salty
snacks, and mixed grainscluster, results showed that those in these grain clusters had significantly lower to-
tal vegetable scores than subjects in the no grains pattern. All clusters examined, with the exception of cereals”,
had lower scores for refined grains as compared to those not consuming grain foods, suggesting that these indi-
viduals consumed greater refined grain products. Adults in the “yeast breads and rollsand pasta, cooked ce-
reals and ricegrain cluster also had significantly lower scores for sodium intake relative to adults not consum-
ing grains, suggesting greater daily sodium intake. The lower HEI-2010 sub-component scores for refined grains
and sodium were more than offset with increased scores for those in the cereal”, pasta, cooked cereals and
Y. Papanikolaou, V. L. Fulgoni III
777
Table 3. Adjusted Mean (SE) total Healthy Eating Index-2010 (HEI) and component scores for all grain clusters using NHANES
2005-2010, 19 years of age.
HEI-2010
component
No grains
Crackers/salty
snacks
Yeast breads
and rolls
Cakes/cookies/
pies
Cereals
Pasta/cooked
cereals/rice
Quick breads Mixed grains
Cluster 0 Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 Cluster 7
LSM SE LSM SE P LSM
SE P LSM
SE P LSM
SE P LSM
SE
P LSM
SE P LSM
SE P
Total
vegetables
3.25 0.10 3.00 0.06 0.0094 3.05 0.04
0.0397 2.98 0.08
0.0236 3.02
0.07
0.0416 3.14
0.05
0.3182 3.14 0.06
0.2508 2.91 0.03
0.0013
Greens and
beans
1.36 0.10 1.16 0.07 0.0747 0.96 0.06
0.0002 1.13 0.12
0.0935 1.18
0.12
0.2801 1.62
0.09
0.0772 1.63 0.08
0.0345 1.09 0.05
0.0128
Total fruit 1.90 0.10 1.96 0.08 0.6105 1.99 0.06
0.4844 1.90 0.08
0.9864 2.24
0.11
0.0281 2.48
0.06
<0.0001
1.95 0.07
0.6589 2.27 0.05
0.0012
Whole fruit 1.72 0.11 1.97 0.07 0.0564 1.84 0.06
0.4080 1.94 0.09
0.1789 2.34
0.11
0.0004 2.39
0.08
<0.0001
1.90 0.08
0.1381 2.21 0.05
0.0001
Whole grains 0.43 0.04 2.26 0.11 <0.0001
1.64 0.07
<0.0001
0.89 0.11
0.0009 3.64
0.18
<0.0001
3.66
0.17
<0.0001
1.82 0.13
<0.0001
2.93 0.09
<0.0001
Dairy 4.78 0.15 5.01 0.12 0.2514 5.16 0.10
0.0582 5.09 0.18
0.2099 6.98
0.17
<0.0001
4.81
0.12
0.8806 4.85 0.12
0.7285 5.36 0.08
0.0009
Total protein
foods
4.10 0.08 3.88 0.06 0.0288 4.39 0.02
0.0008 3.96 0.08
0.1949 3.79
0.08
0.0111 4.31
0.05
0.0216 4.39 0.04
0.0033 4.20 0.03
0.2414
Seafood and
plant protein
1.59 0.11 2.12 0.10 0.0010 1.94 0.06
0.0045 1.70 0.12
0.5214 1.97
0.13
0.0334 2.29
0.08
<0.0001
2.06 0.06
0.0007 2.00 0.06
0.0008
Fatty
acid ratio
4.66 0.21 5.25 0.14 0.0145 4.26 0.07
0.0935 5.04 0.19
0.1516 4.24
0.28
0.1720 5.34
0.11
0.0071 5.39 0.16
0.0065 4.76 0.08
0.6424
Sodium 4.47 0.20 3.75 0.14 0.0101 3.78 0.09
0.0007 5.35 0.14
0.0002 5.04
0.16
0.0226 3.59
0.10
0.0003 3.97 0.08
0.0160 4.24 0.07
0.2665
Refined
grains
7.66 0.17 5.78 0.12 <0.0001
6.24 0.09
<0.0001
7.05 0.17
0.0034 7.32
0.20
0.2037 6.58
0.15
<0.0001
5.00 0.11
<0.0001
6.04 0.08
<0.0001
SoFAAS
calories
10.91 0.37 11.51 0.21 0.1929 11.74
0.20
0.0451 8.08 0.34
<0.0001
12.94
0.36
0.0001
14.18
0.21
<0.0001
11.54
0.21
0.0804 11.51
0.16
0.1391
HEI-2010
total score
46.83 0.86 47.64 0.52 0.4379 46.98
0.40
0.8744 45.09
0.65
0.0835 54.71
1.03
<0.0001
54.37
0.58
<0.0001
47.65
0.53
0.3627 49.51
0.34
0.0020
NHANES 2005-2010, N = 14,384; LSM = least square mean; SE = standard error; P = P value of difference as compared to cluster 0 (no grains); SoFAAS =
solid fat, alcohol, added sugars; covariates include age, gender, ethnicity, poverty income ratio, physical activity, current smoking status, and alcohol.
riceand mixed grainsclusters for whole fruit, while all grain cluster patterns had significantly higher scores
for whole grains as compared to those not consuming grain foods, indicating the contributory value of all grains
in helping to reach whole grain recommendations. Additionally, adults consuming pasta, cooked cereals, and
riceand mixed grainshad significantly higher scores for total fruit, while all grain clusters except cereals
and cakes, cookies and pies”, had greater scores for seafood and plant protein in comparison to adults in the no
grains pattern. Cereals”, and pasta, cooked cereals, and riceclusters also had significantly greater scores for
empty calories (signifying less calories from solid fats, alcohol and added sugars), while those consuming
cakes, cookies and pieshad a greater amount of calories from solid fats, alcohol and added sugars.
3.3. Physiological Variables
In adults, body weight and waist circumference were significantly lower (3.5 kg and 3.0 cm, respectively) in
those in the pasta, cooked cereals, and ricecluster pattern relative to adults in the no grain cluster (body
weights: 79.1 ± 0.7 vs. 82.5 ± 1.2 kg, P = 0.009; waist circumference: 95.2 ± 0.6 vs. 98.2 ± 1.0 cm; P = 0.004)
(Table 4).
Red blood cell folate was higher in those consuming cereals(an increase of 76.6 ng/ml RBC) and mixed
grains(an increase of 32.5 ng/ml RBC) while serum folate was higher in those in the cakes, cookies, and pies”,
ereals”, and mixed grainsgrain food patterns (range of increase was 2.0 to 4.7 ng/ml) relative to adults in the
no grain group. HDL cholesterol was significantly lower (a decrease of 3.1 mg/dL) in the cerealscluster as
compared to the no grains cluster, while no differences were seen with LDL-cholesterol across clusters versus
the no grains group. There were no differences observed for plasma glucose, plasma insulin, total cholesterol
and triglycerides for adults in all clusters when compared to the no grains cluster pattern (Table 4).
4. Discussion
This is the first study that has identified various grain food patterns in US adults and documented links between
Y. Papanikolaou, V. L. Fulgoni III
778
Table 4. Adjusted Mean (SE) physiological variables for all grain clusters using NHANES 2005-2010, 19 years of age.
No Grains Cracke rs/Salty
Snacks Yeast Breads
and Rolls Cakes/Cookies/Pies Cereals Pasta/Cooked
Cereals/Rice Quick Breads Mixed Grains
Variable N Cluste r 0 Cluster 1 Cluster 2 Clust er 3 Cluster 4 Cluster 5 Clu ster 6 Cluste r 7
LSM
SE LSM
SE P LSM
SE P LSM
SE P LSM
SE P LSM SE P LSM SE P LSM
SE P
Body Mass
Index (kg/m2) 14,202
28.6 0.38 28.4 0.22 0.5913 29.1 0.19 0.1629 28.6 0.40 0.9171 28.8 0.34 0.7933 27.7 0.26
0.0176 29.3 0.23 0.1272
28.4 0.14
0.4520
Folate, RBC
(ng/mL RBC) 13,558
433 10.3 444 9.34 0.3839 442 7.64 0.3559 457 11.81
0.1350 510 14. 9 <0.0001
456 10.0
0.0865 455 11.7 0.0530
466 8.81
0.0026
Folate,
serum (ng/mL) 13,521
16.1 0.50 16.7 0.38 0.3642 16.6 0.26 0.2767 18.1 0.52 0.0026 20.8 0.75 <0.0001
17.4 0.45
0.0321 17.9 0.99 0.1362
18.2 0.27
0.0004
Glucose, plasma
(mg/dL) 6,580 105 1.77 102 0.70 0.2099 105 0.99 0.7552 104 1.30 0.7651 101 1.05 0.0300 102 0.81
0.2420 105 1.13 0.6525
105 0.67
0.9691
HDL-cho lestero l
(mg/dL) 13,513
53.5 0.76 53.5 0.54 0.9556 53.2 0.40 0.6849 53.6 0.68 0.9098 50.4 0.83 0.0097 52.9 0.59
0.5484 52.8 0.55 0.4688
53.0 0.36
0.6029
Insulin (uU/mL) 6,501 13.3 0. 72 11.9 0.33 0.0599 12.1 0.36 0.1380 12.5 0.55 0.3036 12.1 0.53 0.1837 12.2 0.35
0.1500 11.9 0.47 0.1180
11.8 0.23
0.0632
LDL-cho lestero l
(mg/dL) 6,401 115 1.96 115 1.80 0.7635 117 1.30 0.4252 124 3.14 0.0279 118 2.54 0.3347 116 1.76
0.9002 115 1.39 0.9505
114 0.94
0.5067
Tot al cholester ol
(mg/dL) 13,513
201 2.12 195 1.46 0.0292 198 1.19 0.2400 200 2.37 0.8309 194 2.41 0.0260 198 1.49
0.4120 197 1.22 0.1309
197 0.84
0.1441
Triglyceride
(mg/dL) 6,540 137 10.37 132 5.19 0.6662 135 4.45 0.8868 130 6.24 0.6162 137 6.41 0.9931 136 3.99
0.9345 131 5.40 0.6195
133 2.26
0.7700
Waist
Circumference (cm) 13,836
98.2 0.95 97.5 0.51 0.5384 98.9 0.44 0.4109 98.0 0.97 0.8736 97.8 0.94 0.7806 95.2 0.56
0.0044 99.7 0.59 0.1888
97.3 0.34
0.2860
Weight (kg) 14,227
82.5 1.23 81.6 0.60 0.4970 83.5 0.53 0.4319 82.0 1.20 0.7597 82.7 1.14 0.9007 79.1 0.69
0.0093 84.1 0.66 0.2788
81.2 0.42
0.2374
NHANES 2005-2010, N = 14,384; LSM = least square mean; SE = standard error; P = P value of difference as compared to cluster 0 (no grains); Covariates
include age, gender, ethnicity, poverty income ratio, physical activity, current smoking status, and for non-weight-related variables, the model also includes
body mass index.
grain food pattern consumption, nutrient intakes, diet quality and health outcomes. Specifically, certain grain
food patterns are associated with greater nutrient intakes, including higher consumption of shortfall nutrients and
nutrients of public health concern as identified by the 2015-2020 Dietary Guidelines. Further, adults in the “ce-
reals”, pasta, cooked cereals and riceand mixed grainsclusters had improved diet quality as measured by
USDA’s HEI-2010, relative to those not consuming grain food products. The present observational analysis also
found that adults consuming certain grain food patterns have favorable obesity-related outcomes, including low-
er body weight and a reduced waist circumference. Overall, the present data support several grain food patterns
as part of a healthy dietary food pattern, that takes into consideration authoritative recommendations to reduce
total fat, saturated fat and added sugar consumption, while concurrently increasing 2015-2020 Dietary Guide-
linesshortfall nutrients and/or nutrients of concern, including iron, magnesium, dietary fiber, vitamin D, potas-
sium and folate.
Whole grain cereals and breads have been well-documented in the literature for their role in the prevention of
chronic diseases. Regular consumption of whole grain cereals and breads have been linked to lower risk for car-
diovascular disease, type 2 diabetes mellitus, and with certain cancers, as discussed in a recent review [14]. Sim-
ilar to nutrition guidance worldwide, US 2010 dietary recommendations focused on consuming at least half of
all grains as whole grains, which is largely a minimum of 3 ounce equivalents per day for most adults, with
strong encouragement to increase whole grain consumption by replacing refined grains with whole grains [15], a
concept that has been carried forward by the 2015-2020 Dietary Guidelines and the 2015 Dietary Guidelines
Advisory Committee (2015 DGAC) [1] [16]. A recent NHANES analysis reported less than 8% of US adults
consumed at least 3 whole grain ounce equivalents per day, while about 50% of adults consumed >0 and <3
whole grain ounce equivalents per day, and nearly 42% reported not consuming any whole grains [17]. Likewise,
data stemming from What We Eat in America 2007-2010, showed that the estimated percent of the US popula-
tion consuming below established whole grain recommendations is greater than 95% in all children and adults
[16]. Coupled with the under consumption of whole grains, the 2015 DGAC [16] concluded “several nutrients
are under consumed relative to the Estimated Average Requirement or Adequate Intake levels set by the Insti-
tute of Medicinethese shortfall nutrients are vitamin A, vitamin D, vitamin E, vitamin C, folate, calcium,
magnesium, fiber, and potassium”. The 2015 DGAC also identified iron to be a shortfall nutrient for adolescent
Y. Papanikolaou, V. L. Fulgoni III
779
and premenopausal females. Similarly, recent work evaluating diet quality based on Denmark’s food-based die-
tary guidance, identified that while iron intake increased with a better diet quality, mean iron intake in women of
childbearing age across all groups examined were below recommended levels, thus suggesting a diet closely
aligned to Danish recommendations may still leave many women at risk for inadequate intakes of iron [18]. In
the present analyses, iron was significantly higher in adults in all of the grain food patterns examined, while
those consuming six of the seven grain food patterns had significantly greater folate intake, ranging from 46 to
429 µg per day, relative to those not consuming grain foods. Similarly, magnesium intakes were elevated in
adults consuming cerealsand pasta, cooked cereals and riceby 39 and 45 mg per day, respectively, in com-
parison to adults not consuming grains, representing about 10% of the Daily Value established for magnesium
for adults consuming a 2000 kcal diet.
While previous dietary intake research has reported increased intakes of low-fat dairy products, fish, poultry,
rye bread, fruit and vegetables to be associated with a better diet quality and consumption of high-fat dairy
products, red and processed meat, white bread, soft drinks, sweets and cakes to be associated with lower diet
quality scores, the researchers also noted that added sugar intake and fat on bread were greater in the lowest
quartile of the diet quality index and contributed to the high intake of total fat and saturated fat. Collectively, this
may represent a meaningful contribution for the lower diet quality outcome and warrants further investigation
[18]. Our results are aligned with previous observational findings that considered sources of nutrients in the US
diet. When identifying the top food sources of nutrients, including both intrinsic and added to foods via fortifi-
cation, results showed that grain foods represented the top five ranking food sources for folate, such that ready-
to-eat cereals, yeast breads and rolls, pizza, pasta and crackers, popcorn, pretzels, and chips contributed 56.7%
and 54.4% of folate to the diet of children and adolescents, respectively. Similarly, grain foods represented the
top five food sources for iron in the diet of US children and adolescents, with ready-to-eat cereals, yeast breads,
pizza, cakes, cookies, and pies, and crackers, popcorn, pretzels, and chips cumulatively contributing 52.1% and
48.7% of iron [4].
The 2015 DGAC [16] report further states of the shortfall nutrients, calcium, vitamin D, fiber, and potassium
also are classified as nutrients of public health concern because their under consumption has been linked in the
scientific literature to adverse health outcomes”, a principle carried forward from the 2010 Dietary Guidelines
for Americans policy document [19]. The 2015 DGAC [16] also reports that “if whole grains were consumed in
the amounts recommended in the recommended food patterns, whole grains would provide substantial percen-
tages of several key nutrients, such as about 32 percent of dietary fiber, 42% of iron, 35% of folate, 29% of
magnesium and 16% of vitamin A”. While these nutrients levels represent significant contributions from whole
grains, whole grain consumption alone can still leave a gap between consumption and recommendation levels.
The 2005 Dietary Guidelines Advisory Committee reported that refined grains contribute substantial levels of
key nutrients to food patterns, naming folate, iron, calcium, dietary fiber, thiamin, riboflavin and niacin [20].
The committee further acknowledged that including only three ounce equivalents of whole grains daily with no
refined grains in recommended food patterns would lower intake of many key nutrients and potentially place
specific populations at risk for nutrient inadequacy [20]; an argument which led the 2015 DGAC to conclude
that consumption of whole grains with no substitutions would result in nutrient shortfalls [16]. The current anal-
ysis provides data linking different grain food patterns with nutrient intakes and concurrently we observed the
adverse nutrient- and health-related outcomes when grain foods as a whole are eliminated from the diet. In many
of the grain patterns examined, a better nutrient intake profile was observed which demonstrates the important
dietary contributions made by different grain foods and emphasizes the importance of consuming whole and re-
fined grains. Indeed, while some of the grain food clusters contributed nutrients to limit in the diet as identified
by the 2015 DGAC report [16], including saturated fat, added sugars, and sodium, several of the grain food pat-
terns were associated with lower intakes of these nutrients and improved shortfall nutrient intakes and diet qual-
ity. Thus, it is conceivable to rationalize that Americans need more specific dietary guidance about grain con-
sumption rather than simply having two broad categories of recommended intakes that revolve around refined
and whole grains.
The present analysis includes limitations inherent in observational research that deserve recognition. Data for
energy and nutrient intakes, including values reported for diet quality, were obtained using 24-hour dietary re-
calls, which rely on study participant memory. While validated procedures are used to collect the data, recalled
information may be inaccurate and biased from misreporting, memory challenges and other potential measure-
ment errors experienced in epidemiological research involving large datasets [21] [22]. In addition, the current
Y. Papanikolaou, V. L. Fulgoni III
780
evidence, being observational, cannot establish a causal link between the different grain foods patterns examined
and improvements in diet quality, nutrient intakes and other health variables considered. However, a large
strength of the current work stems from the use of NHANES, which is a large continuous survey that examines a
nationally representative sample of about 5,000 individuals yearly by highly-trained medical personnel [8]. Ad-
ditionally we used numerous covariates to adjust data in an attempt to remove potential confounding; however
residual confounding may still exist that could explain some of the results reported.
5. Conclusion
In summary, the consumption of certain grain food patterns in US adults is associated with greater nutrient in-
takes, including higher consumption shortfall nutrients and nutrients of public health concern as identified by the
2015-2020 Dietary Guidelines [17]. Further, adults in the pasta, cooked cereals and rice”, “cereals”, and
“mixed grains” dietary patterns had improved diet quality as measured by USDA’s HEI-2010, when compared
to adults not consuming grain foods. In addition, adults consuming certain grain food patterns have favorable
obesity-related health outcomes, including decreased body weights and a reduced risk of having an elevated
waist circumference. Overall, while some grain food patterns were associated with elevated sodium and added
sugar, the present data also support that several grain food patterns can serve as part of a healthy dietary food
pattern that accounts for 2015 Dietary Guidelines recommendations to reduce total fat, saturated fat and added
sugar consumption, while concurrently increasing intake of shortfall nutrients and/or nutrients of concern, in-
cluding iron, magnesium, dietary fiber, vitamin D, potassium and folate.
Acknowledgements
The current analyses were supported by funding from the Grain Foods Foundation in Washington, DC. YP col-
laborated on the conception and interpretation of the research and drafted the manuscript. VLF directed the con-
ception and design of the research, conducted the analyses and provided interpretation. Both authors approved
the final version of the present manuscript.
References
[1] United States Department of Health and Human Services and United States Department of Agriculture (2015) 2015-
2020 Dietary Guidelines for Americans. 8th Edition, U.S. Government Printing Office, December.
[2] United States Food and Drug Administration (1996) Food Standards: Amendment of Standards of Identity for Enriched
Grain Products to Require Addition of Folic Acid. Federal Register, 61.
http://www.gpo.gov/fdsys/pkg/FR-1996-03-05/pdf/96-5014.pdf
[3] Dietrich, M., et al. (2005) The Effect of Folate Fortification of Cereal-Grain Products on Blood Folate Status, Dietary
Folate Intake, and Dietary Folate Sources among Adult Non-Supplement Users in the United States. Journal of the
American College of Nutrition, 24, 266-274. http://dx.doi.org/10.1080/07315724.2005.10719474
[4] Berner, L.A., et al. (2014) Fortified Foods Are Major Contributors to Nutrient Intakes in Diets of US Children and
Adolescents. Journal of the Academy of Nutrition and Dietetics, 114, 1009-1022.
http://dx.doi.org/10.1016/j.jand.2013.10.012
[5] Reedy, J. and Krebs-Smith, S.M. (2010) Dietary Sources of Energy, Solid Fats, and Added Sugars among Children and
Adolescents in the United States. Journal of the American Dietetic Association, 110, 1477-1484.
http://dx.doi.org/10.1016/j.jada.2010.07.010
[6] Huth, P.J., et al. (2013) Major Food Sources of Calories, Added Sugars, and Saturated Fat and Their Contribution to
Essential Nutrient Intakes in the U.S. Diet: Data from the National Health and Nutrition Examination Survey (2003-
2006). Nutrition Journal, 12. http://dx.doi.org/10.1186/1475-2891-12-116
[7] O’Neil, C.E., et al. (2012) Food Sources of Energy and Nutrients among Adults in the US: NHANES 2003-2006. Nu-
trients, 4, 2097-2120. http://dx.doi.org/10.3390/nu4122097
[8] National Health and Nutrition Examination Survey. Analytic and Reporting Guidelines.
http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/nhanes_analytic_guidelines_dec_2005.pdf
[9] National Health and Nutrition Examination Survey. Analytic Note Regarding 2007-2010 Survey Design Changes and
Combining Data across Other Survey Cycles. http://www.cdc.gov/nchs/data/nhanes/analyticnote_2007-2010.pdf
[10] United States Department of Agriculture (2008) USDA Food and Nutrient Database for Dietary Studies, 3.0. Agricul-
tural Research Service, Food Surveys Research Group, Beltsville.
Y. Papanikolaou, V. L. Fulgoni III
781
[11] United States Department of Agriculture (2010) USDA Food and Nutrient Database for Dietary Studies, 4.1. U.S. De-
partment of Agriculture, Agricultural Research Service, Food Surveys Research Group, Beltsville.
[12] Ahuja, J.K.A., et al. (2012) USDA Food and Nutrient Database for Dietary Studies, 5.0. United States Department of
Agriculture, Agricultural Research Service, Food Surveys Research Group, Beltsville.
[13] Guenther, P.M., et al. (2013) Update of the Healthy Eating Index: HEI-2010. Journal of the Academy of Nutrition and
Dietetics, 113, 569-580. http://dx.doi.org/10.1017/S1368980011002576
[14] Gil, A., et al. (2011) Wholegrain Cereals and Bread: A Duet of the Mediterranean Diet for the Prevention of Chronic
Diseases. Public Health Nutrition, 14, 2316-2322. http://dx.doi.org/10.1017/S1368980011002576
[15] The Secretary of Health and Human Services and Secretary of Agriculture. United States Department of Agriculture
(2010) Scientific Report of the Dietary Guidelines Advisory Committee on the Dietary Guidelines for Americans, 2010.
US Department of Agriculture, Washington DC.
[16] United States Department of Agriculture and United States Department of Health and Human Services (USDA/HHS)
(2015) Scientific Report of the 2015 Dietary Guidelines Advisory Committee: Advisory Report to the Secretary of
Health and Human Services and Secretary of Agriculture. USDA, Agricultural Research Service, Washington DC.
[17] Reicks, M., et al. (2014) Total Dietary Fiber Intakes in the US Population Are Related to Whole Grain Consumption:
Results from the National Health and Nutrition Examination Survey 2009 to 2010. Nutrition Research, 34, 226-234.
http://dx.doi.org/10.1016/j.nutres.2014.01.002
[18] Knudsen, V.K., et al. (2012) Evaluation of Dietary Intake in Danish Adults by Means of an Index Based on Food-
Based Dietary Guidelines. Food & Nutrition Research, 56, 17129. http://dx.doi.org/10.3402/fnr.v56i0.17129
[19] United States Department of Agriculture and United States Department of Health and Human Services (2010) Dietary
Guidelines for Americans, 2010. 7th Edition, U.S. Government Printing Office, December, Washington DC.
[20] The Secretary of Health and Human Services and Secretary of Agriculture. U.S. Department of Agriculture (2005)
Scientific Report of the Dietary Guidelines Advisory Committee on the Dietary Guidelines for Americans, 2005. US
Department of Agriculture, Washington DC.
[21] Dwyer, J., et al. (2003) Members of the Steering Committee; National Health and Nutrition Examination Survey. Col-
lection of Food and Dietary Supplement Intake Data: What We Eat in America-NHANES. Journal of Nutrition, 133,
590S-600S.
[22] Boeing, H. (2013) Nutritional Epidemiology: New Perspectives for Understanding the Diet-Disease Relationship? Eu-
ropean Journal of Clinical Nutrition, 67, 424-429. http://dx.doi.org/10.1038/ejcn.2013.47
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Background: While dietary recommendations call for greater whole-grain intake and reduced refined grain consumption, there are limited peer-reviewed studies examining the influence of fortified/enriched refined grains on nutrient adequacy. Methods: A modeling analysis using data from National Health and Nutrition Examination Survey (NHANES) 2009–2016 estimated usual daily intake of shortfall nutrients for Dietary Guidelines for Americans (DGA) in the current dietary pattern and when specific percentages of fortified/enriched refined grain foods (bread, ready-to-eat cereals, and all-grained foods) were removed from the diet (19–50-year-old adults, N = 11,169; 51–99-year-old adults, N = 9,641). Results: While American adults are currently falling short of nutrient recommendations, eliminating 25, 50, and 100% of all grains consumed in the US dietary pattern resulted in a greater percentage of adults not meeting recommendations for several shortfall nutrients, including dietary fiber, folate DFE, iron, and magnesium. Removal of all grains led to a reduced energy intake by ~10% in both age groups examined. Currently, ~3.8% of 19–50-year-old adults meet the adequate intake (AI) for dietary fiber. Removal of 25, 50, and 100% of grains from the diet resulted in 2.6 ± 0.3, 1.8 ± 0.2, and 0.7 ± 0.1% of adults exceeded the AI for dietary fiber, respectively. Similarly, 11.0 and 13.8% of younger and older adults, respectively, fall short of folate, DFE recommendations with the current diet. Following the removal of 100% of grains from the diet, 43.4 ± 1.1 and 56.2 ± 1.0%, respectively, were below the estimated average requirement (EAR) for folate DFE. For iron, current dietary pattern consumption shows 8.4% and 0.8% of younger and older adults, respectively, are not meeting iron recommendations, however, removal of 100% of grains from the diet results in nearly 10 and 22% falling short of the EAR. Currently, about 51 and 54% of younger and older adults are below the EAR for magnesium; however, with the removal of 100% of grains, 68 and 73%, respectively, fall below the EAR. Conclusion: Removal of specific refined grains led to an increased percentage of Americans not meeting recommendations for several shortfall nutrients, including dietary fiber, folate, iron, and magnesium.
... Consequently, it is justified to ask whether each food group in this dietary pattern independently contributes to increased risk of obesity, as has been described by DGAC (19), or whether it is possible that the higher risk is not due to refined grain intake but instead is a consequence of "guilt by association" with other foods in the dietary pattern. Previous work examining grain food patterns of consumption by US adults reported that although all grain food patterns were associated with higher daily calories, no significant associations were observed with weight-related outcomes, including BMI and waist circumference, compared with adults not consuming grain foods (3). Nonetheless, adults consuming a grain pattern predominantly composed of pasta, cooked cereals, and rice had significantly lower body weights and smaller waist circumferences compared with adults not consuming grain foods. ...
... Nonetheless, adults consuming a grain pattern predominantly composed of pasta, cooked cereals, and rice had significantly lower body weights and smaller waist circumferences compared with adults not consuming grain foods. Furthermore, these adults had a 27% reduced risk of being overweight or obese and a 31% reduced risk of having an increased waist size (3). A similar analysis that examined associations between grain patterns of consumption and weight-related parameters in children and adolescents also revealed that energy intake was significantly higher for children in several grain patterns. ...
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Although dietary guidance recommends increasing consumption of whole grains and concurrently limiting consumption of refined and/or enriched grain foods, emerging research suggests that certain refined grains may be part of a healthy dietary pattern. A scientific expert panel was convened to review published data since the release of 2015 dietary guidance in defined areas of grain research, which included nutrient intakes, diet quality, enrichment/fortification, and associations with weight-related outcomes. Based on a 1-d roundtable discussion, the expert panel reached consensus that 1) whole grains and refined grains can make meaningful nutrient contributions to dietary patterns, 2) whole and refined grain foods contribute nutrient density, 3) fortification and enrichment of grains remain vital in delivering nutrient adequacy in the American diet, 4) there is inconclusive scientific evidence that refined grain foods are linked to overweight and obesity, and 5) gaps exist in the scientific literature with regard to grain foods and health. Curr Dev Nutr 2020;4:nzaa125.
... Consequently, it is justified to ask whether each food group in this dietary pattern independently contributes to increased risk of obesity, as has been described by DGAC (19), or whether it is possible that the higher risk is not due to refined grain intake but instead is a consequence of "guilt by association" with other foods in the dietary pattern. Previous work examining grain food patterns of consumption by US adults reported that although all grain food patterns were associated with higher daily calories, no significant associations were observed with weight-related outcomes, including BMI and waist circumference, compared with adults not consuming grain foods (3). Nonetheless, adults consuming a grain pattern predominantly composed of pasta, cooked cereals, and rice had significantly lower body weights and smaller waist circumferences compared with adults not consuming grain foods. ...
... Nonetheless, adults consuming a grain pattern predominantly composed of pasta, cooked cereals, and rice had significantly lower body weights and smaller waist circumferences compared with adults not consuming grain foods. Furthermore, these adults had a 27% reduced risk of being overweight or obese and a 31% reduced risk of having an increased waist size (3). A similar analysis that examined associations between grain patterns of consumption and weight-related parameters in children and adolescents also revealed that energy intake was significantly higher for children in several grain patterns. ...
Article
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Although dietary guidance recommends increasing consumption of whole grains and concurrently limiting consumption of refined and/or enriched grain foods, emerging research suggests that certain refined grains may be part of a healthy dietary pattern. A scientific expert panel was convened to review published data since the release of 2015 dietary guidance in defined areas of grain research, which included nutrient intakes, diet quality, enrichment/fortification, and associations with weight-related outcomes. Based on a 1-d roundtable discussion, the expert panel reached consensus that 1) whole grains and refined grains can make meaningful nutrient contributions to dietary patterns, 2) whole and refined grain foods contribute nutrient density, 3) fortification and enrichment of grains remain vital in delivering nutrient adequacy in the American diet, 4) there is inconclusive scientific evidence that refined grain foods are linked to overweight and obesity, and 5) gaps exist in the scientific literature with regard to grain foods and health.
... Nationally representative data from the 2005-2010 US National Health and Nutrition Examination Surveys (NHANES), indicated that consumption of certain groups of GBFs including bread, ready-to-eat cereals, tortillas and rolls and other grain products was significantly associated with greater intakes of dietary fibre, iron, folate, magnesium, thiamin and niacin in US adults ≥ 19 years-old [17]. Moreover, showed that several GBFs dietary patterns, including pasta, cereals, rice, bread, and mixed grain foods, were associated with better diet quality in adults, as measured by Healthy Eating Index-2010 developed in United States Department of Agriculture (USDA). ...
... Similarly, regarding the GBFs consumption patterns among US adults, more than 50% of the population were clustered in the 'yeast bread rolls,' and 'mixed grains', which primarily includes cake and cookies, pies, and salty snacks. Furthermore, in alignment with our results, another study using NHANES data reported the 'no grain' cluster had the lowest energy intake [17]. ...
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In this study, we used the Canadian Community Health Survey-Nutrition (CCHS) 2015 data to examine the consumption patterns of grain-based foods (GBFs) for Canadian adults. We used a k-mean cluster analysis based on the contribution of 21 grain-based foods to total energy intake of adults in Canada to find the dietary patterns of GBFs. Cluster analyses rendered seven dietary patterns including: ‘other bread’, ‘cake and cookies’, ‘pasta’, ‘rice’, ‘mixed’, ‘white bread’, and finally ‘whole wheat and whole-grain bread’. ‘No grain’ and ‘rice’ consumers had lower intakes of dietary fibre, folate, iron and calcium, which are the nutrients of public health concern in Canada. Adults consuming a ‘mixed grain’ dietary pattern had a greater daily intake of calcium, potassium, magnesium, riboflavin, and vitamin B6 than those in the ‘no grain’ dietary pattern. We also observed that a considerable proportion of individuals clustered in the ‘rice’ group are immigrants and belong to households with lower income levels.
... Recent NHANES data in adults showed that some, but not all, grain food patterns were associated with better nutrient intakes, improved diet quality and beneficial obesity-related parameters [7]. While 2015-2020 DGA identify several healthy dietary food patterns, and encourage increased whole grain consumption and reduced refined grain intake, at present, there are no data that evaluate the association of different grain food patterns on nutrient intakes and diet quality outcomes in children and adolescents. ...
... Several, but not all grain food patterns, were associated with improved diet quality compared to adults not consuming main grain groups. Adults consuming pasta, cooked cereals and rice also had lower body weights and smaller waist circumferences when compared to individuals not consuming grain foods [7]. Several nutrients contributed by grain foods naturally or via fortification/enrichment, including folate, calcium, magnesium, fiber and iron are under consumed relative to IOM nutrition standards [17]. ...
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Background The present study identified the most commonly consumed grain food patterns in US children and adolescents (2–18 years-old; N = 8,367) relative to those not consuming grains and compared diet quality and nutrient intakes, with focus on 2015–2020 Dietary Guidelines for Americans (2015–2020 DGA) shortfall nutrients. Methods Cluster analysis using data from the National Health and Nutrition Examination Survey 2005–2010, identified 8 unique grain food patterns: a) no consumption of main grain groups, b) cakes, cookies and pies, c) yeast bread and rolls, d) cereals, e) pasta, cooked cereals and rice, f) crackers and salty snacks, g) pancakes, waffles and French toast and other grains, and h) quick breads. ResultsEnergy intake was higher for all grain cluster patterns examined, except ‘cereals’, compared to no grains. Children and adolescents in the ‘yeast bread and rolls’, ‘cereals’, ‘pasta, cooked cereals and rice’, and ‘crackers and salty snacks’ patterns had a higher diet quality relative to no grains (all p < 0.01). Energy adjusted (EA) dietary fiber intake was greater in five of the seven grain patterns, ranging from 1.8 – 2.8 g more per day (all p < 0.01), as compared to those consuming no grains. All grain patterns, except cakes, cookies and pies had higher EA daily folate relative to children in the no grains pattern (all p < 0.0001). EA total fat was lower in ‘cereals’, ‘pasta, cooked cereals and rice’, and ‘pancakes, waffles, French toast and other grains’ in comparison to the no grains food pattern (all p < 0.01). EA magnesium intakes were greater in children and adolescents consuming ‘yeast bread and rolls’, ‘pasta, cooked cereals and rice’, and ‘quick breads’, while EA iron was higher in all grain patterns relative to no grains (all p < 0.01). EA vitamin D intake was higher only in children consuming ‘cereals’ vs. no grain group (p < 0.0001). There were no significant differences in total or added sugar intake across all grain clusters as compared to no grains. Conclusions Consumption of several, but not all, grain food patterns in children and adolescents were associated with improved 2015–2020 DGA shortfall nutrient intakes and diet quality as compared to those consuming no grains.
... Analyses involving food sources of energy and nutrients in Americans have shown that the grain category is an important contributor of energy and nutrients in the total diet (1,2). Grain foods, relative to energy (kcal), provided greater percentages of the under-consumed nutrients and nutrients of public health concern as defined by the 2015-2020 Dietary Guidelines for Americans (DGA) (3), including dietary fiber, folate, magnesium, calcium, and iron (4)(5)(6)(7)(8)(9). When evaluating subcategories of grain foods, breads, rolls, and tortillas are also meaningful contributors (i.e., ≥10% in the diet) of dietary fiber, thiamin, folate, iron, zinc, and niacin to the American diet (1,2). ...
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Background: Previous research in adults has reported an association between sandwich consumers and increased daily energy, total fat, and sodium intakes and decreased dietary fiber intake. Additionally, sandwich consumers had a lower diet quality, as compared to non-sandwich consumers. However, the research failed to differentiate between the types of sandwiches consumed. Objectives: The purpose of this study was to model different sandwiches, using both whole-grain bread (WGB), enriched-grain bread (EGB), and soft taco tortillas, to examine associations with energy (kcal), nutrient intakes, and diet quality, in comparison to the typically consumed sandwich (control). Methods: Data from the NHANES 2013-2014 was used to complete the analyses in adults ≥19 years old, and USDA food composites were used to create 5 sandwich types, using WGB, EGB, or soft corn tortillas. Results: In the modeling analysis, adults consuming the soft corn tortilla taco had lower energy, as compared to those eating the typical sandwich. Total fat intakes were lower in the WGB and EGB grilled chicken/cheese/vegetable sandwiches and in the soft taco tortilla, in comparison to the control sandwich. Sodium intakes were lower in the WGB and EGB grilled chicken/cheese/vegetable sandwiches and in the soft taco tortilla, in comparison to the typical sandwich consumed. All WGB sandwich models and the soft taco tortilla had greater daily dietary fiber intakes, in comparison to the control sandwich. WGB, EGB, and tortilla sandwiches were also associated with greater intakes of shortfall nutrients. All sandwich models, except EGB with meat/cheese/vegetables, had higher diet qualities, in comparison to the control. Conclusions: The current data support the inclusion of certain WGB and EGB sandwiches/tortillas, within recommended dietary patterns, in American adults, and suggest that ingredients within a sandwich, rather than the just the bread component, can be an important contributor to overall nutrient intakes and nutrients to limit in the diet.
... 18 Diets high in processed carbohydrates result in a significantly lower intake of magnesium. 72 For example, a potato without the skin contains a third less magnesium than one with skin. 43 White bread and cooked white rice contain almost a third less magnesium than their whole-grain counterparts. ...
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The negative health effects of inadequate magnesium intake are well established, but the extent of the problem of deficiency warrants further exploration. This review explores the dietary factors, such as changes in agricultural practices and dietary patterns, that affect magnesium consumption over time and examines the current adequacy of magnesium intake among adults in the United States. Large, cross-sectional, population-based data sets confirm over half the adult population in the United States does not consume adequate amounts of magnesium, although recent population-based studies show a steady and consistent recovery in magnesium consumption over the last several decades. Because there is no simple, rapid, accurate test to determine whole-body magnesium status, continued monitoring of magnesium consumption is essential to determine whether the trend of increasing magnesium consumption will continue. In the meantime, since the clinical consequences of inadequate magnesium status are well established, there are few reasons not to encourage increased magnesium intake in adults, especially since magnesium is found in healthy foods that should be consumed more often and there are no reported cases of hypermagnesemia from food alone.
... Such findings suggest that those consuming breakfast cereal are more likely to be physically active as well, which would account for the higher energy intakes but lower body weights. The consumption of wheatbased foods (both whole and refined grains), such as breads, pastas, breakfast cereals, cookies, and crackers, contributes to body weight maintenance as well as to diet quality, providing a more balanced intake of nutrients (128)(129)(130)(131). ...
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Meeting the growing demand for food over the next 20-30 years will be challenging, mainly because the fastest population growth is occurring in already highly populated developing countries and because producing cereal crops (the main source of nutrients in these countries) requires that serious production constraints, due mainly to the effects of climate change, be overcome. Wheat supplies the most calories and proteins to the global population in the form of diverse wheat-based foods. Wheat-based foods are staples that are major sources of micronutrients that are fundamental for normal development, as well as metabolic and cognitive functioning, from childhood to adulthood. Furthermore, whole grain, wheat-based foods have potential additional health benefits because they contribute fiber and bioactive compounds that can help reduce the risk of chronic conditions, such as cardiovascular disease, type 2 diabetes, and other chronic conditions. In this article, we describe common wheat-based foods consumed globally and regionally, as well as consumption trends for the most important wheat-based foods. Changes in consumption patterns are strongly associated with population shifts from rural to urban areas, which cause changes in both lifestyle and dietary habits. It is recognized that wheat production and wheat-based foods will continue to be important for the well-being of millions of people, especially for low-income farmers and consumers. Finally, we briefly discuss trends in wheat production and supply impacted by potential climate change and outline some important research and development strategies needed to improve grain productivity, grain processing quality, and the nutritional value of wheat-based foods.
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The 2015–2020 Dietary Guidelines for Americans (2015-2020 DGA) maintains recommendations for increased consumption of whole grains while limiting intake of enriched/refined grains. A variety of enriched grains are sources of several shortfall nutrients identified by 2015-2020 DGA, including dietary fiber, folate, iron, and magnesium. The purpose of this study was to determine food sources of energy and nutrients for free-living U.S. adults using data from the National Health and Nutrition Examination Survey, 2009–2012. Analyses of grain food sources were conducted using a single 24-h recall collected in adults ≥19 years of age (n = 10,697). Sources of nutrients contained in all grain foods were determined using United States Department of Agriculture nutrient composition databases and the food grouping scheme for grains (excluding mixed dishes). Mean energy and nutrient intakes from the total diet and from various grain food groups were adjusted for the sample design using appropriate weights. All grains provided 285 ± 5 kcal/day or 14 ± 0.2% kcal/day in the total diet in adult ≥19 years of age. In the total daily diet, the grain category provided 7.2 ± 0.2% (4.9 ± 0.1 g/day) total fat, 5.4 ± 0.2% (1.1 ± 0.03 g/day) saturated fat, 14.6 ± 0.3% (486 ± 9 mg/day) sodium, 7.9 ± 0.2% (7.6 ± 0.2 g/day) total sugar, 22.8 ± 0.4% (3.9 ± 0.1 g/day) dietary fiber, 13.2 ± 0.3% (122 ± 3 mg/day) calcium, 33.6 ± 0.5% (219 ± 4 mcg dietary folate equivalents (DFE)/day) folate, 29.7 ± 0.4% (5.3 ± 0.1 mg/day) iron, and 13.9 ± 0.3% (43.7 ± 1.1 mg/day) magnesium. Individual grain category analyses showed that breads, rolls and tortillas and ready-to-eat cereals provided minimal kcal/day in the total diet in men and women ≥19 years of age. Similarly, breads, rolls and tortillas, and ready-to-eat cereals supplied meaningful contributions of shortfall nutrients, including dietary fiber, folate and iron, while concurrently providing minimal amounts of nutrients to limit. Cumulatively, a variety of grain food groups consumed by American adults contribute to nutrient density in the total diet and have the potential to increase consumption of shortfall nutrients as identified by 2015–2020 DGA, particularly dietary fiber, folate, and iron.
Data
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Documentation and dataset available on Worldwide Web Site: Food Surveys Research Group: http://www.ars.usda.gov/Services/docs.htm?docid=12089
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Whole grain (WG) foods have been shown to reduce chronic disease risk and overweight. Total dietary fiber is associated with WG and its health benefits. The purpose was to determine whether associations exist between WG intake (no-WG intake, 0 ounce equivalent [oz eq]; low, >0-<3 oz eq; high, ≥3 oz eq) and total dietary fiber intake among Americans 2 years and older. One-day food intake data from the US National Health and Nutrition Examination Survey 2009 to 2010 (n = 9042) showed that only 2.9% and 7.7% of children/adolescents (2-18 years) and adults (≥19 years) consumed at least 3 WG oz eq/d, respectively. For children/adolescents and adults, individuals in the high WG intake group were 59 and 76 times more likely to fall in the third fiber tertile, respectively, compared with those with no-WG intake. Total dietary fiber intake from food sources varied by WG intake group for children/adolescents and adults with more total dietary fiber consumed from ready-to-eat (RTE) and hot cereals and yeast breads/rolls in the high WG intake group compared with the no-WG intake group. Major WG sources for children/adolescents and adults included yeast bread/rolls (24% and 27%, respectively), RTE cereals (25% and 20%, respectively), and oatmeal (12% and 21%, respectively). Among those with the highest WG intake, WG RTE cereal with no added bran was the greatest contributor to total dietary fiber compared with other RTE cereal types. Whole grain foods make a substantial contribution to total dietary fiber intake and should be promoted to meet recommendations.
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Even in an era of obesity and dietary excess, numerous shortfall micronutrients have been identified in the diets of US children and adolescents. To help tailor strategies for meeting recommendations, it is important to know what foods contribute greatly to micronutrient intakes. Data are lacking on specific contributions made by added nutrients. Our aims were to examine the impact of fortification on nutrient adequacy and excess among US children and adolescents and to rank food sources of added nutrient intake and compare rankings with those based on total nutrient intake from foods. Data were from 7,250 respondents 2 to 18 years old in the National Health and Nutrition Examination Survey 2003-2006. Datasets were developed that distinguished nutrient sources: intrinsic nutrients in foods; added nutrients in foods; foods (intrinsic plus added nutrients); and total diet (foods plus supplements). The National Cancer Institute method was used to determine usual intakes of micronutrients by source. The impact of fortification on the percentages of children having intakes less than the Estimated Average Requirement and more than the Upper Tolerable Intake Level was assessed by comparing intakes from intrinsic nutrients to intakes from intrinsic plus added nutrients. Specific food sources of micronutrients were determined as sample-weighted mean intakes of total and added nutrients contributed from 56 food groupings. The percentage of intake from each grouping was determined separately for total and added nutrients. Without added nutrients, a high percentage of all children/adolescents had inadequate intakes of numerous micronutrients, with the greatest inadequacy among older girls. Fortification reduced the percentage less than the Estimated Average Requirement for many, although not all, micronutrients without resulting in excessive intakes. Data demonstrated the powerful influence of fortification on food-source rankings. Knowledge about nutrient intakes and sources can help put dietary advice into a practical context. Continued monitoring of top food sources of nutrients and nutrient contributions from fortification will be important.
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The risk of chronic disease cannot be predicted simply by the content of a single nutrient in a food or food group in the diet. The contribution of food sources of calories, added sugars and saturated fat (SFA) to intakes of dietary fiber and micronutrients of public health importance is also relevant to understanding the overall dietary impact of these foods. Identify the top food sources of calories, added sugars and SFA in the U.S. diet and quantify their contribution to fiber and micronutrient intakes. Single 24-hour dietary recalls (Day 1) collected from participants >=2 years (n = 16,822) of the What We Eat in America, National Health and Nutrition Examination Survey (WWEIA/NHANES 2003--2006) were analyzed. All analyses included sample weights to account for the survey design. Calorie and nutrient intakes from foods included contributions from disaggregated food mixtures and tabulated by rank order. No one food category contributes more than 7.2% of calories to the overall U.S. diet, but half of the top 10 contribute 10% or more of total dietary fiber and micronutrients. Three of the top 10 sources of calories and SFA (beef, milk and cheese) contribute 46.3% of the calcium, 49.5% of the vitamin D, 42.3% of the vitamin B12 as well as other essential nutrients to the American diet. On the other hand, foods categorized as desserts, snacks, or beverages, contribute 13.6% of total calories, 83% of added sugar intake, and provide little or no nutritional value. Including food components of disaggregated recipes more accurately estimated the contribution of foods like beef, milk or cheese to overall nutrient intake compared to "as consumed" food categorizations. Some food sources of calories, added sugars and SFA make major contributions to American dietary fiber and micronutrient intakes. Dietary modifications targeting reductions in calories, added sugar, or SFA need to take these key micronutrient sources into account so as not to have the unintended consequence of lowering overall dietary quality.
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Identification of current food sources of energy and nutrients among US adults is needed to help with public health efforts to implement feasible and appropriate dietary recommendations. To determine the food sources of energy and 26 nutrients consumed by US adults the 2003-2006 National Health and Nutrition Examination Survey (NHANES) 24-h recall (Day 1) dietary intake data from a nationally representative sample of adults 19+ years of age (y) (n = 9490) were analyzed. An updated USDA Dietary Source Nutrient Database was developed for NHANES 2003-2006 using current food composition databases. Food grouping included ingredients from disaggregated mixtures. Mean energy and nutrient intakes from food sources were sample-weighted. Percentages of total dietary intake contributed from food sources were ranked. The highest ranked sources of energy and nutrients among adults more than 19 years old were: energy - yeast bread/rolls (7.2%) and cake/cookies/quick bread/pastry/pie (7.2%); protein-poultry (14.4%) and beef (14.0%); total fat - other fats and oils (9.8%); saturated fatty acids - cheese (16.5%) and beef (9.1%); carbohydrate - soft drinks/soda (11.4%) and yeast breads/rolls (10.9%); dietary fiber - yeast breads/rolls (10.9%) and fruit (10.2%); calcium - milk (22.5%) and cheese (21.6%); vitamin D - milk (45.1%) and fish/shellfish (14.4%); and potassium - milk (9.6%) and coffee/tea/other non-alcoholic beverages (8.4%). Knowledge of primary food sources of energy and nutrients can help health professionals design effective strategies to reduce excess energy consumed by US adults and increase the nutrient adequacy of their diets.
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Data on dietary intake and physical activity has been collected from a representative sample of the Danish population from 2003-2008. The aim of the present study was to describe the habitual diet in Denmark and to evaluate the overall diet quality using a diet quality index based on the National Food-Based Dietary Guidelines (FBDG), which consists of seven guidelines regarding diet and one regarding physical activity. Data from the Danish National Survey of Diet and Physical Activity 2003-2008 (n=3354) were included. The diet quality index was constructed based on five of the seven dietary guidelines. Individuals were categorised according to quartiles of the diet quality index, and food and nutrient intakes were estimated in each of the groups. Macronutrient distribution did not meet recommendations in any of the groups, as energy from total fat and especially saturated fat was too high. A high intake of high-fat milk products, fat on bread and processed meat contributed to a high intake of total fat and saturated fat, and sugar-sweetened soft drinks contributed to a high intake of added sugars in the group below the lowest quartile of the diet quality index. Individuals above in the highest quartile had higher intakes of 'healthy foods' such as fish, fruit and vegetables, rye bread, and also a higher consumption of water and wine. Overall, intakes of micronutrients were sufficient in all groups. The diet quality index is a useful tool in assessing food and nutrient intake in individuals with high vs. low degree of compliance towards the dietary guidelines, and provides a valuable tool in future studies investigating variations in dietary intakes with respect to lifestyle, demographic and regional differences in Denmark.
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The promotion of healthy lifestyles is one of the major goals of governments and international agencies all over the world. Wholegrain cereals are rich in nutrients and many phytochemical compounds, with recognised benefits for health, including dietary fibre, a number of phenolic compounds, lignans, vitamins and minerals and other bioactive components. The aim of the present work is to review the fundamental studies that support the consumption of wholegrain cereals and bread to prevent chronic diseases. Descriptive review considering human studies. Subjects included in randomised intervention trials and cohort studies from different countries published up to 2010. Several studies show consistently that subjects who ingest three or more portions of foods per day based on wholegrain cereals have a 20-30 % lower risk of CVD than subjects who ingest low quantities of cereals. This level of protection is not observed with the ingestion of refined cereals, these being even higher than with the intake of fruit and vegetables. Likewise, high intake of wholegrain cereals and their products, such as whole-wheat bread, is associated with a 20-30 % reduction in the risk of type 2 diabetes. Finally, protection against the risk of colorectal cancer and polyps, other cancers of the digestive tract, cancers related to hormones and pancreatic cancer has been associated with the regular consumption of wholegrain cereals and derived products. The regular intake of wholegrain cereals can contribute to reduction of risk factors related to non-communicable chronic diseases.
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Nutritional epidemiology is a subdiscipline of epidemiology and provides specific knowledge to nutritional science. It provides data about the diet-disease relationships that is transformed by Public Health Nutrition into the practise of prevention. The specific contributions of nutritional epidemiology include dietary assessment, description of nutritional exposure and statistical modelling of the diet-disease relationship. In all these areas, substantial progress has been made over the last years and is described in this article. Dietary assessment is moving away from the food frequency questionnaire (FFQ) as main dietary assessment instrument in large-scale epidemiological studies towards the use of short-term quantitative instruments due to the potential of gross measurement errors. Web-based instruments for self-administration are therefore evaluated of being able to replace the costly interviewer conducted 24-h-recalls. Much interest is also directed towards the technique of taking and analysing photographs of all meals ingested, which might improve the dietary assessment in terms of precision. The description of nutritional exposure could greatly benefit from standardisation of the coding of foods across studies in order to improve comparability. For the investigations of bioactive substances as reflecting nutritional intake and status, the investigation of concentration measurements in body fluids as potential biomarkers will benefit from the new high-throughput technologies of mass spectrometry. Statistical modelling of the dietary data and the diet-disease relationships can refer to complex programmes that convert quantitative short-term measurements into habitual intakes of individuals and correct for the errors in the estimates of the diet-disease relationships by taking data from validation studies with biomarkers into account. For dietary data, substitution modelling should be preferred over simple adding modelling. More attention should also be put on the investigation of non-linear relationships. The increasing complexity of the conduct and analysis of nutritional epidemiological studies is calling for a distinct and advanced training programme for the young scientists moving into this area. This will also guarantee that in the future an increasing number of high-level manuscripts will show up in this and other journals in respect of nutritional epidemiological topics.European Journal of Clinical Nutrition advance online publication, 27 February 2013; doi:10.1038/ejcn.2013.47.
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The objective of this research was to identify top dietary sources of energy, solid fats, and added sugars among 2- to 18-year-olds in the United States. Data from the National Health and Nutrition Examination Survey, a cross-sectional study, were used to examine food sources (percentage contribution and mean intake with standard errors) of total energy (data from 2005-2006) and energy from solid fats and added sugars (data from 2003-2004). Differences were investigated by age, sex, race/ethnicity, and family income, and the consumption of empty calories-defined as the sum of energy from solid fats and added sugars-was compared with the corresponding discretionary calorie allowance. The top sources of energy for 2- to 18-year-olds were grain desserts (138 kcal/day), pizza (136 kcal/day), and soda (118 kcal/day). Sugar-sweetened beverages (soda and fruit drinks combined) provided 173 kcal/day. Major contributors varied by age, sex, race/ethnicity, and income. Nearly 40% of total energy consumed (798 of 2,027 kcal/day) by 2- to 18-year-olds were in the form of empty calories (433 kcal from solid fat and 365 kcal from added sugars). Consumption of empty calories far exceeded the corresponding discretionary calorie allowance for all sex-age groups (which range from 8% to 20%). Half of empty calories came from six foods: soda, fruit drinks, dairy desserts, grain desserts, pizza, and whole milk. There is an overlap between the major sources of energy and empty calories: soda, grain desserts, pizza, and whole milk. The landscape of choices available to children and adolescents must change to provide fewer unhealthy foods and more healthy foods with less energy. Identifying top sources of energy and empty calories can provide targets for changes in the marketplace and food environment. However, product reformulation alone is not sufficient-the flow of empty calories into the food supply must be reduced.