Effect of Animal Protein Intake on Meeting Recommendations for Nutrient Intake among US Adults, What We Eat in America, NHANES 2015-2018.

Background: Replacing some animal sources of protein with plant foods is encouraged. Nutrient intake may reflect changes in the protein source. The adequacy of habitual nutrient intake among US adults has not been evaluated by the level of animal protein (AP) intake. Objectives: The objective of this study was to compare food consumption and nutrient intake and adequacy among quintiles of percent AP intake. Methods: Dietary intake data of adults 19+ y (N = 9706) from What We Eat in America, National Health and Nutrition Examination Survey 2015-2018 were used. Proportions of protein from animal and plant sources were estimated from ingredients in the Food and Nutrient Database for Dietary Studies 2015-2018, and then applied to dietary intakes. Intakes were classified by Q of percent AP. Food intake was described using the United States Department of Agriculture Food Patterns components. Usual nutrient intakes were estimated using the National Cancer Institute Method and compared with age and gender-specific Dietary Reference Intakes (DRIs). Comparisons between quintiles were made using t-tests. Results were considered significant at P < 0.01. Results: Total protein intake was higher as the Q of AP intake increased. Among the higher quintiles of percent AP, <1% did not meet their DRIs for protein than 17% in Q1 and 5% in Q2 (P < 0.01). In quintiles with lower compared with higher percent AP, there were significantly higher percentages not meeting DRIs for vitamins A, B12, choline, zinc, and calcium but meeting recommendations for folate, vitamin C, saturated fat, cholesterol, and fiber (P < 0.01). Among all quintiles, over one-third did not meet DRIs for fiber, vitamins A, C, D, E, K, choline, calcium, and potassium. Conclusions: Replacing protein from animal sources with plant foods may result in lower intakes of protein and some nutrients but a better intake of dietary components associated with reducing chronic disease risk. The current intake of US adults indicates dietary improvements are needed, regardless of protein source.

Diet Quality and Food Intakes samong US Adults by Level of Animal Protein Intake, What We Eat in America, NHANES 2015-2018.

Background: Dietary recommendations encourage consuming protein from a variety of plant and animal sources. Evaluating the diet of US adults by level of animal protein (AP) intake can inform dietary assessment and nutrition education. Objectives: The objective of this cross-sectional study was to estimate percentage of total protein intake from animal sources by US adults to compare diet quality, and intake from USDA Food Patterns (FP) groups by quintiles of AP. Methods: One day dietary intake data from adults 20+ y (N = 9566) in What We Eat in America (WWEIA), NHANES 2015-2018 were used. Proportions of total protein intake from animal and plant sources and the USDA FP groups were estimated from the ingredients in the Food and Nutrient Database for Dietary Studies 2015-2018, then applied to the dietary intakes. The 2015 Healthy Eating Index (HEI) was used as an indicator of diet quality. The USDA FP groups were used to describe the contribution of animal and plant foods to total protein intake. Data were analyzed by quintile (Q) of AP protein intake; comparisons were made using pairwise t-tests with adjustments for covariates using survey sample weights. Results were considered significant at P <0.001. Results: Total mean protein intakes ranged from 62 (Q1) to 104 g (Q5) (all comparisons P <0.001). Total HEI score (possible 100) of Q1 was slightly higher (54.2) (P <0.001) compared with Q1-Q4 (range: 48.0-50.3), which did not differ significantly from each other. Contributions of plant FP components to total protein intake of Q1 to Q5, respectively, were 15% to 1% from nuts/seeds, legumes, and soy products combined; 35 to 10% from grains. The contribution of animal FP components were 19-66% from meat/poultry/seafood, 14-19% dairy, and 3-5% eggs. Conclusions: The intake of foods considered to be good sources of plant protein was low. The overall diet quality of all adults was suboptimal regardless of plant protein intake.

Diet Quality of Frequent Fast-Food Consumers on a Non-Fast Food Intake Day Is Similar to a Day with Fast Food, What We Eat in America, NHANES 2013-2016.

BACKGROUND: Frequent fast food (FF) consumers may make more healthful food choices at eating occasions without FF. However, it is not clear if poor diet quality of frequent FF consumers is a function of FF consumption or less healthful food choices overall. OBJECTIVE: The objective of this study was to compare diet quality, energy, and nutrient intakes of infrequent FF consumers (INFREQ) with that of frequent FF consumers on an intake day with FF (FREQ-FF) or without FF (FREQ_NO FF). DESIGN: This study is a cross-sectional analysis of 1 day dietary intake data from What We Eat in America, National Health and Nutrition Examination Survey 2013-2016, the dietary intake component of National Health and Nutrition Examination Survey. PARTICIPANTS/SETTING: Participants included adults aged 20 years and older (N = 4,012), who, during the previous 7 days, reported no consumption of FF or pizza (n = 2,142 INFREQ) or reported FF or pizza three or more times and either had FF/pizza (n = 1,455 FREQ_FF) or did not have FF/pizza (n = 415 FREQ_NO FF) on the intake day. MAIN OUTCOME MEASURES: Main outcomes were energy, nutrient density (nutrient intake per 1,000 kcal), and diet quality evaluated using Healthy Eating Index (HEI) 2015. STATISTICAL ANALYSES PERFORMED: Group comparisons were made using t tests. Differences were considered significant at P < 0.001. RESULTS: Compared with INFREQ consumers, FREQ_FF consumers had higher intakes of energy and fat per 1,000 kcal, lower scores for total HEI and most components, and lower nutrient densities of most micronutrients (P < 0.001). HEI component scores of INFREQ consumers for vegetables, fruit, whole grains, and added sugars were higher than FREQ_FF consumers (P < 0.001). Energy intake, most nutrient densities, and total HEI and component scores of FREQ_NO FF consumers were not significantly different from FREQ_FF consumers with the exception of fruit but were different from INFREQ consumers for some nutrients and HEI components. CONCLUSIONS: Results suggest diet quality and nutrient intake of frequent FF consumers on a non-FF intake day is not markedly different from a day with FF.

Late Evening Eating Patterns among US Adults Vary in Their Associations With, and Impact on, Energy Intake and Diet Quality: Evidence from What We Eat in America, National Health and Nutrition Examination Survey 2013-2016.

BACKGROUND: Evening eating has been associated with higher energy intake and lower nutrient density. However, these qualities may not characterize all late evening (LE) eating patterns. OBJECTIVE: We sought to characterize US adults' LE eating patterns on a given day and identify differences, if any, in pattern-specific associations with, and impact on, daily energy intake and total diet quality. DESIGN: LE eating patterns, energy intakes, and Healthy Eating Index (HEI) scores were identified using Day-1 dietary recall data from the cross-sectional National Health and Nutrition Examination Survey 2013-2016. PARTICIPANTS/SETTING: The sample included adults aged ≥ 20 years (n = 9,861). LE reporters were respondents who consumed foods/beverages between 20:00 and 23:59 on the intake day. MAIN OUTCOME MEASURES: Energy intake and HEI-2015 scores by LE status/pattern and the impact of LE consumption on these measures. STATISTICAL ANALYSES: Cluster analysis assigned individuals to LE eating patterns based on the LE energy contribution of food/beverage groups. Regression models estimated energy intake and HEI-2015 scores; estimates were compared between LE reporters and nonreporters. Similarly, LE's contribution to total energy and the difference in total HEI inclusive vs exclusive of LE consumption were estimated and compared among patterns. RESULTS: Among US adults, 64.4% were LE reporters. Eleven LE patterns were identified; the six most prevalent patterns (representing 89% of LE reporters) were further analyzed. Daily energy intake in all prevalent patterns except the fruit pattern exceeded that of nonreporters by ≥ 268 kcal (unadjusted; P < 0.001), varying by pattern. Conversely, total HEI score did not differ from that of nonreporters (51.0) in any pattern except the fruit pattern, where it was higher (57.4, unadjusted; P < 0.001). Generally, LE consumption's impact on energy was high and its impact on HEI scores was low. CONCLUSIONS: Late evening food/beverage consumption is common among US adults, and LE patterns are not monolithic in their associations with, and impact on, total energy intake and dietary quality.

Application of the Database of Flavonoid Values for USDA Food Codes 2007-2010 in Assessing Intake Differences Between the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) Study and What We Eat in America (WWEIA), NHANES.

Flavonoids are polyphenolic plant compounds whose biological activities may promote human health. It is worthwhile to examine whether flavonoid intake varies between populations with differing prevalence of diet-related diseases. This study compared flavonoid intakes in the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study with nationally representative estimates from What We Eat in America (WWEIA), NHANES stratified by sex, age (30-49, 50-64 years), and poverty status (income <125%, >125% of the 2004 HHS Poverty Guidelines). Flavonoid intakes from both surveys were estimated using the Database of Flavonoid Values for USDA Food Codes 2007-2010. Across all subpopulations analyzed, intake of anthocyanidins was lower in HANDLS (p<0.01). Intakes of total flavonoids and all or most flavonoid classes were lower in HANDLS for men overall and in both age groups and for both men and women with poverty status <125%. These findings of lower flavonoid intakes in HANDLS, particularly among men and those with the lowest incomes, suggest that flavonoid intake may be a factor in the high prevalence of diet-related disease in populations represented by HANDLS. This research illustrates how any survey using USDA's food codes can utilize the Flavonoid Database in comparing flavonoid intakes.

Dietary Flavonoid Intakes Are Associated with Race but Not Income in an Urban Population.

Flavonoids are polyphenolic phytochemicals with health-promoting properties, yet knowledge about their intake in at-risk populations is limited. This study sought to estimate intakes of total flavonoids and six flavonoid classes in the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study; determine if differences in intakes exist by race (African American (AA) and White (W)) and income (< or >125% Federal poverty guidelines); and compare intakes to those of a nationally representative population with similar demographic and socioeconomic characteristics. Data transformation normalized the flavonoid intake distributions prior to conducting statistical tests. With the exception of the flavanone class, flavonoid intakes of AAs were significantly lower than those of W (p < 0.01), regardless of other potential mediating factors including sex, age, and income. Total flavonoid intakes in HANDLS did not differ from intakes in the nationally representative study, but anthocyanidin and flavone intakes were lower, and race specific differences were found for several flavonoid classes. These findings imply that benefits attributable to flavonoid consumption may not be experienced equally by AAs and Whites, nor in vulnerable populations such as that represented by HANDLS relative to the U.S. population, and may play a role in observed health disparities.

A New Database Facilitates Characterization of Flavonoid Intake, Sources, and Positive Associations with Diet Quality among US Adults.

BACKGROUND: Epidemiologic studies demonstrate inverse associations between flavonoid intake and chronic disease risk. However, lack of comprehensive databases of the flavonoid content of foods has hindered efforts to fully characterize population intakes and determine associations with diet quality. OBJECTIVES: Using a newly released database of flavonoid values, this study sought to describe intake and sources of total flavonoids and 6 flavonoid classes and identify associations between flavonoid intake and the Healthy Eating Index (HEI) 2010. METHODS: One day of 24-h dietary recall data from adults aged ≥ 20 y (n = 5420) collected in What We Eat in America (WWEIA), NHANES 2007-2008, were analyzed. Flavonoid intakes were calculated using the USDA Flavonoid Values for Survey Foods and Beverages 2007-2008. Regression analyses were conducted to provide adjusted estimates of flavonoid intake, and linear trends in total and component HEI scores by flavonoid intake were assessed using orthogonal polynomial contrasts. All analyses were weighted to be nationally representative. RESULTS: Mean intake of flavonoids was 251 mg/d, with flavan-3-ols accounting for 81% of intake. Non-Hispanic whites had significantly higher (P < 0.001) intakes of total flavonoids (275 mg/d) than non-Hispanic blacks (176 mg/d) and Hispanics (139 mg/d). Tea was the primary source (80%) of flavonoid intake. Regardless of whether the flavonoid contribution of tea was included, total HEI score and component scores for total fruit, whole fruit, total vegetables, greens and beans, seafood and plant proteins, refined grains, and empty calories increased (P < 0.001) across flavonoid intake quartiles. CONCLUSIONS: A new database that permits comprehensive estimation of flavonoid intakes in WWEIA, NHANES 2007-2008; identification of their major food/beverage sources; and determination of associations with dietary quality will lead to advances in research on relations between flavonoid intake and health. Findings suggest that diet quality, as measured by HEI, is positively associated with flavonoid intake.

The USDA Automated Multiple-Pass Method accurately assesses population sodium intakes.

BACKGROUND: Given current sodium-reduction strategies, accurate and practical methods to monitor sodium intake in the US population are critical. Although the gold standard for estimating sodium intake is the 24-h urine collection, few studies have used this biomarker to evaluate the accuracy of a dietary instrument. OBJECTIVE: Our objective was to compare self-reported dietary intake of sodium with 24-h urinary excretion obtained in the USDA Automated Multiple-Pass Method (AMPM) Validation Study. DESIGN: Subjects were healthy, weight-stable volunteers aged 30-69 y recruited from the Washington, DC, area. Data from 465 subjects who completed at least one 24-h recall and collected a complete 24-h urine sample during the same period were used to assess the validity of sodium intake. Reporting accuracy was calculated as the ratio of reported sodium intake to that estimated from the urinary biomarker (24-h urinary sodium/0.86). Estimations of sodium intake included salt added in cooking but did not include salt added at the table. RESULTS: Overall, the mean (95% CI) reporting accuracy was 0.93 (0.89, 0.97) for men (n = 232) and 0.90 (0.87, 0.94) for women (n = 233). Reporting accuracy was highest for subjects classified as normal weight [body mass index (in kg/m(2)) <25]: 1.06 (1.00, 1.12) for men (n = 84) and 0.99 (0.94, 1.04) for women (n = 115). For women only, reporting accuracy was higher in those aged 50-69 y than in those who were younger. CONCLUSION: Findings from this study suggest that the USDA AMPM is a valid measure for estimating sodium intake in adults at the population or group level.

The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes.

BACKGROUND: The US Department of Agriculture Automated Multiple-Pass Method (AMPM) is used for collecting 24-h dietary recalls in What We Eat In America, the dietary interview component of the National Health and Nutrition Examination Survey. Because the data have important program and policy applications, it is essential that the validity of the method be tested. OBJECTIVE: The accuracy of the AMPM was evaluated by comparing reported energy intake (EI) with total energy expenditure (TEE) by using the doubly labeled water (DLW) technique. DESIGN: The 524 volunteers, aged 30-69 y, included an equal number of men and women recruited from the Washington, DC, area. Each subject was dosed with DLW on the first day of the 2-wk study period; three 24-h recalls were collected during the 2-wk period by using the AMPM. The first recall was conducted in person, and subsequent recalls were over the telephone. RESULTS: Overall, the subjects underreported EI by 11% compared with TEE. Normal-weight subjects [body mass index (in kg/m(2)) < 25] underreported EI by <3%. By using a linear mixed model, 95% CIs were determined for the ratio of EI to TEE. Approximately 78% of men and 74% of women were classified as acceptable energy reporters (within 95% CI of EI:TEE). Both the percentage by which energy was underreported and the percentage of subjects classified as low energy reporters (<95% CI of EI:TEE) were highest for subjects classified as obese (body mass index > 30). CONCLUSIONS: Although the AMPM accurately reported EIs in normal-weight subjects, research is warranted to enhance its accuracy in overweight and obese persons.

The prevalence of arthritis and activity limitation and their predictors in Missouri.

Arthritis and other rheumatic conditions comprise the leading cause of disability in the United States. In 1990, an estimated 16.7% of Missourians had arthritis. By 2020, an estimated 20% of Missourians will have this condition. We examined Missouri's prevalence of self-reported physician-diagnosed arthritis, chronic joint symptoms, and activity limitation due to joint symptoms and their associations with selected predictors (i.e., socio-demographic, access to health care, risk factor, and comorbidity indicators) from Missouri's 1996 Behavioral Risk Factor Surveillance System. We conducted logistic regression analysis to generate Odds Ratios and 95% Confidence Intervals of arthritis and activity limitation across levels of predictors. Analysis indicates arthritis is under-diagnosed in younger individuals and that arthritis and activity limitation due to joint symptoms are significant contributors to functional limitation, enhancing dependency while decreasing the quality of life. As the population ages, arthritis, chronic joint symptoms, and activity limitation will become a larger public health problem.