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      Foods, Fortificants, and Supplements: Where Do Americans Get Their Nutrients? 1 2 3

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          Abstract

          Limited data are available on the source of usual nutrient intakes in the United States. This analysis aimed to assess contributions of micronutrients to usual intakes derived from all sources (naturally occurring, fortified and enriched, and dietary supplements) and to compare usual intakes to the Dietary Reference Intake for U.S. residents aged ≥2 y according to NHANES 2003–2006 ( n = 16,110). We used the National Cancer Institute method to assess usual intakes of 19 micronutrients by source. Only a small percentage of the population had total usual intakes (from dietary intakes and supplements) below the estimated average requirement (EAR) for the following: vitamin B-6 (8%), folate (8%), zinc (8%), thiamin, riboflavin, niacin, vitamin B-12, phosphorus, iron, copper, and selenium (<6% for all). However, more of the population had total usual intakes below the EAR for vitamins A, C, D, and E (34, 25, 70, and 60%, respectively), calcium (38%), and magnesium (45%). Only 3 and 35% had total usual intakes of potassium and vitamin K, respectively, greater than the adequate intake. Enrichment and/or fortification largely contributed to intakes of vitamins A, C, and D, thiamin, iron, and folate. Dietary supplements further reduced the percentage of the population consuming less than the EAR for all nutrients. The percentage of the population with total intakes greater than the tolerable upper intake level (UL) was very low for most nutrients, whereas 10.3 and 8.4% of the population had intakes greater than the UL for niacin and zinc, respectively. Without enrichment and/or fortification and supplementation, many Americans did not achieve the recommended micronutrient intake levels set forth in the Dietary Reference Intake.

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          Estimating the energy gap among US children: a counterfactual approach.

          Our goal was to quantify the magnitude of energy imbalance responsible for the increase in body weight among US children during the periods 1988-1994 and 1999-2002. We adopted a counterfactual approach to estimate weight gains in excess of normal growth and the implicit "energy gap"--the daily imbalance between energy intake and expenditure. On the basis of Centers for Disease Control and Prevention growth charts, we constructed weight, height, and BMI percentile distributions for cohorts 2 to 4 and 5 to 7 years of age in the 1988-1994 National Health and Nutrition Examination Survey (N = 5000). Under the counterfactual "normal-growth-only" scenario, we assumed that these percentile distributions remained the same as the cohort aged 10 years. Under this assumption, we projected the weight and height distributions for this cohort at 12 to 14 and 15 to 17 years of age on the basis of their baseline weight-for-age and stature-for-age percentiles. We compared these distributions with those for corresponding age groups in the 1999-2002 National Health and Nutrition Examination Survey (N = 3091) approximately 10 years after the 1988-1994 National Health and Nutrition Examination Survey. We calculated differences between the counterfactual and observed weight distributions and translated this difference into the estimated average energy gap, adjusting for increased total energy expenditure attributable to weight gain. In addition, we estimated the average excess weight accumulated among overweight adolescents in the 1999-2002 National Health and Nutrition Examination Survey, validating our counterfactual assumptions by analyzing longitudinal data from the National Longitudinal Survey of Youth and Bogalusa Heart Study. Compared with the counterfactual scenario, boys and girls who were aged 2 to 7 in the 1988-1994 National Health and Nutrition Examination Survey gained, on average, an excess of 0.43 kg/year over the 10-year period. Assuming that 3500 kcal leads to an average of 1-lb weight gain as fat, our results suggest that a reduction in the energy gap of 110-165 kcal/day could have prevented this increase. Among overweight adolescents aged 12 to 17 in 1999-2002, results indicate an average energy imbalance ranging from 678 to 1017 kcal/day because of an excess of 26.5 kg accumulated over 10 years. Quantifying the energy imbalance responsible for recent changes in weight distribution among children can provide salient targets for population intervention. Consistent behavioral changes averaging 110 to 165 kcal/day may be sufficient to counterbalance the energy gap. Changes in excess dietary intake (eg, eliminating one sugar-sweetened beverage at 150 kcal per can) may be easier to attain than increases in physical activity levels (eg, a 30-kg boy replacing sitting for 1.9 hours with 1.9 hours walking for an extra 150 kcal). Youth at higher levels of weight gain will likely need changes in multiple behaviors and environments to close the energy gap.
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            Energy imbalance underlying the development of childhood obesity.

            To develop a model based on empirical data and human energetics to predict the total energy cost of weight gain and obligatory increase in energy intake and/or decrease in physical activity level associated with weight gain in children and adolescents. One-year changes in weight and body composition and basal metabolic rate (BMR) were measured in 488 Hispanic children and adolescents. Fat-free mass (FFM) and fat mass (FM) were measured by DXA and BMR by calorimetry. Model specifications include the following: body mass (BM) = FFM + FM, each with a specific energy content, cff (1.07 kcal/g FFM) and cf (9.25 kcal/g FM), basal energy expenditure (EE), kff and kf, and energetic conversion efficiency, eff (0.42) for FFM and ef (0.85) for FM. Total energy cost of weight gain is equal to the sum of energy storage, EE associated with increased BM, conversion energy (CE), and diet-induced EE (DIEE). Sex- and Tanner stage-specific values are indicated for the basal EE of FFM (kff) and the fat fraction in added tissue (fr). Total energy cost of weight gain is partitioned into energy storage (24% to 36%), increase in EE (40% to 57%), CE (8% to 13%), and DIEE (10%). Observed median (10th to 90th percentile) weight gain of 6.1 kg/yr (2.4 to 11.4 kg/yr) corresponds at physical activity level (PAL) = 1.5, 1.75, and 2.0 to a total energy cost of weight gain of 244 (93 to 448 kcal/d), 267 (101 to 485 kcal/d), and 290 kcal/d (110 to 527 kcal/d), respectively, and to a total energy intake of 2695 (1890 to 3730), 3127 (2191 to 4335), and 3551 (2487 to 4930) kcal/d, respectively. If weight gain is caused by a change in PAL alone and PAL(0) = 1.5 at baseline t = 0, the model indicates a drop in PAL of 0.22 (0.08 to 0.34) units, which is equivalent to 60 (18 to 105) min/d of walking at 2.5 mph. Halting the development or progression of childhood obesity, as observed in these Hispanic children and adolescents, by counteracting its total energy costs will require a sizable decrease in energy intake and/or reciprocal increase in physical activity.
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              Estimating the effects of energy imbalance on changes in body weight in children.

              Estimating changes in weight from changes in energy balance is important for predicting the effect of obesity prevention interventions. The objective was to develop and validate an equation for predicting the mean weight of a population of children in response to a change in total energy intake (TEI) or total energy expenditure (TEE). In 963 children with a mean (+/-SD) age of 8.1 +/- 2.8 y (range: 4-18 y) and weight of 31.5 +/- 17.6 kg, TEE was measured by using doubly labeled water. Log weight (dependent variable) and log TEE (independent variable) were analyzed in a linear regression model with height, age, and sex as covariates. It was assumed that points of dynamic balance, called "settling points," occur for populations wherein energy is in balance (TEE = TEI), weight is stable (ignoring growth), and energy flux (EnFlux) equals TEE. TEE (or EnFlux) explained 74% of the variance in weight. The unstandardized regression coefficient was 0.45 (95% CI: 0.38, 0.51; R(2) = 0.86) after including covariates. Conversion into proportional changes (time(1) to time(2)) gave the equation (weight(2)/weight(1)) = (EnFlux(2)/EnFlux(1))(0.45). In 3 longitudinal studies (n = 212; mean follow-up of 3.4 y), the equation predicted the mean follow-up measured weight to within 0.5%. The relation of EnFlux with weight was positive, which implied that a high TEI (rather than low physical activity and low TEE) was the main determinant of high body weight. Two populations of children with a 10% difference in mean EnFlux would have a 4.5% difference in mean weight.
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                Author and article information

                Journal
                J Nutr
                nutrition
                nutrition
                The Journal of Nutrition
                American Society for Nutrition
                0022-3166
                1541-6100
                October 2011
                24 August 2011
                24 August 2011
                : 141
                : 10
                : 1847-1854
                Affiliations
                [4 ]Nutrition Impact LLC, Battle Creek, MI
                [5 ]Food and Nutrition Database Research, Inc., Okemos, MI
                [6 ]Office of Dietary Supplements, Bethesda, MD
                [7 ]Jean Mayer USDA Human Nutrition Research Center on Aging, and Schools of Medicine and Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
                Author notes
                [2]

                Author disclosures: V. L. Fulgoni III, D. R. Keast, R. L. Bailey, and J. Dwyer, no conflicts of interest.

                [* ]To whom correspondence should be addressed. E-mail: vic3rd@ 123456aol.com .
                Article
                142257
                10.3945/jn.111.142257
                3174857
                21865568
                b97d0276-d545-49f5-b719-104c8b6ec5c5
                © 2011 American Society for Nutrition

                This is a free access article, distributed under terms ( http://www.nutrition.org/publications/guidelines-and-policies/license/) which permit unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 March 2011
                : 2 May 2011
                : 17 July 2011
                Categories
                Nutrient Requirements and Optimal Nutrition

                Nutrition & Dietetics
                Nutrition & Dietetics

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