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      Impact of Masked Replacement of Sugar-Sweetened with Sugar-Free Beverages on Body Weight Increases with Initial BMI: Secondary Analysis of Data from an 18 Month Double–Blind Trial in Children

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          Abstract

          Background

          Substituting sugar-free for sugar-sweetened beverages reduces weight gain. This effect may be more pronounced in children with a high body mass index (BMI) because their sensing of kilocalories might be compromised. We investigated the impact of sugar-free versus sugary drinks separately in children with a higher and a lower initial BMI z score, and predicted caloric intakes and degree of compensation in the two groups.

          Methods and Findings

          This is a secondary, explorative analysis of our double-blind randomized controlled trial (RCT) which showed that replacement of one 250-mL sugary drink per day by a sugar—free drink for 18 months significantly reduced weight gain. In the 477 children who completed the trial, mean initial weights were close to the Dutch average. Only 16% were overweight and 3% obese. Weight changes were expressed as BMI z-score, i.e. as standard deviations of the BMI distribution per age and sex group. We designated the 239 children with an initial BMI z-score below the median as ‘lower BMI’ and the 238 children above the median as ‘higher BMI’. The difference in caloric intake from experimental beverages between treatments was 86 kcal/day both in the lower and in the higher BMI group. We used a multiple linear regression and the coefficient of the interaction term (initial BMI group times treatment), indicated whether children with a lower BMI responded differently from children with a higher BMI. Statistical significance was defined as p ≤ 0.05. Relative to the sugar sweetened beverage, consumption of the sugar—free beverage for 18 months reduced the BMI z-score by 0.05 SD units within the lower BMI group and by 0.21 SD within the higher BMI group. Body weight gain was reduced by 0.62 kg in the lower BMI group and by 1.53 kg in the higher BMI group. Thus the treatment reduced the BMI z-score by 0.16 SD units more in the higher BMI group than in the lower BMI group (p = 0.04; 95% CI -0.31 to -0.01). The impact of the intervention on body weight gain differed by 0.90 kg between BMI groups (p = 0.09; 95% CI -1.95 to 0.14). In addition, we used a physiologically-based model of growth and energy balance to estimate the degree to which children had compensated for the covertly removed sugar kilocalories by increasing their intake of other foods. The model predicts that children with a lower BMI had compensated 65% (95% CI 28 to 102) of the covertly removed sugar kilocalories, whereas children with a higher BMI compensated only 13% (95% CI -37 to 63).

          Conclusions

          The children with a BMI above the median might have a reduced tendency to compensate for changes in caloric intake. Differences in these subconscious compensatory mechanisms may be an important cause of differences in the tendency to gain weight. If further research bears this out, cutting down on the intake of sugar-sweetened drinks may benefit a large proportion of children, especially those who show a tendency to become overweight.

          Trial Registration

          ClinicalTrials.gov NCT00893529

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          Most cited references12

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          Sugar-sweetened beverages and genetic risk of obesity.

          Temporal increases in the consumption of sugar-sweetened beverages have paralleled the rise in obesity prevalence, but whether the intake of such beverages interacts with the genetic predisposition to adiposity is unknown. We analyzed the interaction between genetic predisposition and the intake of sugar-sweetened beverages in relation to body-mass index (BMI; the weight in kilograms divided by the square of the height in meters) and obesity risk in 6934 women from the Nurses' Health Study (NHS) and in 4423 men from the Health Professionals Follow-up Study (HPFS) and also in a replication cohort of 21,740 women from the Women's Genome Health Study (WGHS). The genetic-predisposition score was calculated on the basis of 32 BMI-associated loci. The intake of sugar-sweetened beverages was examined prospectively in relation to BMI. In the NHS and HPFS cohorts, the genetic association with BMI was stronger among participants with higher intake of sugar-sweetened beverages than among those with lower intake. In the combined cohorts, the increases in BMI per increment of 10 risk alleles were 1.00 for an intake of less than one serving per month, 1.12 for one to four servings per month, 1.38 for two to six servings per week, and 1.78 for one or more servings per day (P<0.001 for interaction). For the same categories of intake, the relative risks of incident obesity per increment of 10 risk alleles were 1.19 (95% confidence interval [CI], 0.90 to 1.59), 1.67 (95% CI, 1.28 to 2.16), 1.58 (95% CI, 1.01 to 2.47), and 5.06 (95% CI, 1.66 to 15.5) (P=0.02 for interaction). In the WGHS cohort, the increases in BMI per increment of 10 risk alleles were 1.39, 1.64, 1.90, and 2.53 across the four categories of intake (P=0.001 for interaction); the relative risks for incident obesity were 1.40 (95% CI, 1.19 to 1.64), 1.50 (95% CI, 1.16 to 1.93), 1.54 (95% CI, 1.21 to 1.94), and 3.16 (95% CI, 2.03 to 4.92), respectively (P=0.007 for interaction). The genetic association with adiposity appeared to be more pronounced with greater intake of sugar-sweetened beverages. (Funded by the National Institutes of Health and others.).
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            Increasing caloric contribution from sugar-sweetened beverages and 100% fruit juices among US children and adolescents, 1988-2004.

            We sought to document increases in caloric contributions from sugar-sweetened beverages and 100% fruit juice among US youth during 1988-2004. We analyzed 24-hour dietary recalls from children and adolescents (aged 2-19) in 2 nationally representative population surveys: National Health and Nutrition Examination Survey III (1988-1994, N = 9882) and National Health and Nutrition Examination Survey 1999-2004 (N = 10 962). We estimated trends in caloric contribution, type, and location of sugar-sweetened beverages and 100% fruit juice consumed. Per-capita daily caloric contribution from sugar-sweetened beverages and 100% fruit juice increased from 242 kcal/day (1 kcal = 4.2 kJ) in 1988-1994 to 270 kcal/day in 1999-2004; sugar-sweetened beverage intake increased from 204 to 224 kcal/day and 100% fruit juice increased from 38 to 48 kcal/day. The largest increases occurred among children aged 6 to 11 years ( approximately 20% increase). There was no change in per-capita consumption among white adolescents but significant increases among black and Mexican American youths. On average, respondents aged 2 to 5, 6 to 11, and 12 to 19 years who had sugar-sweetened beverages on the surveyed day in 1999-2004 consumed 176, 229, and 356 kcal/day, respectively. Soda contributed approximately 67% of all sugar-sweetened beverage calories among the adolescents, whereas fruit drinks provided more than half of the sugar-sweetened beverage calories consumed by preschool-aged children. Fruit juice drinkers consumed, on average, 148 (ages 2-5), 136 (ages 6-11), and 184 (ages 12-19) kcal/day. On a typical weekday, 55% to 70% of all sugar-sweetened beverage calories were consumed in the home environment, and 7% to 15% occurred in schools. Children and adolescents today derive 10% to 15% of total calories from sugar-sweetened beverages and 100% fruit juice. Our analysis indicates increasing consumption in all ages. Schools are a limited source for sugar-sweetened beverages, suggesting that initiatives to restrict sugar-sweetened beverage sales in schools may have an only marginal impact on overall consumption. Pediatricians' awareness of these trends is critical for helping children and parents target suboptimal dietary patterns that may contribute to excess calories and obesity.
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              Why obese children cannot resist food: the role of impulsivity.

              Facing the undesirable health consequences of being obese, an important question is why some people are not able to resist eating to excess. It is theorized that increased impulsivity at least partly underlies the inability to control eating behaviour; being more impulsive is supposed to make it more difficult to resist food intake. Thirty-three obese children in a residential setting and 31 lean control children are tested. Impulsivity is measured with two behavioural measures (inhibitory control and sensitivity to reward) and questionnaires. Results show that the obese children in treatment were more sensitive to reward and showed less inhibitory control than normal weight children. In addition, the obese children with eating binges were more impulsive than the obese children without eating binges. Most interesting finding was that the children that were the least effective in inhibiting responses, lost less weight in the residential treatment program. To conclude: impulsivity is a personality characteristic that potentially has crucial consequences for the development and maintenance, as well as treatment of obesity.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 July 2016
                2016
                : 11
                : 7
                : e0159771
                Affiliations
                [1 ]Department of Health Sciences, EMGO Institute for Health and Care Research, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
                [2 ]Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States of America
                Vanderbilt University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MBK MRO. Performed the experiments: JCR. Analyzed the data: JCR LDJK CCC KDH. Contributed reagents/materials/analysis tools: JCR CCC KDH. Wrote the paper: MRO JCR LDJK CCC KDH MBK.

                Article
                PONE-D-15-32182
                10.1371/journal.pone.0159771
                4957753
                27447721
                7def8d7f-274f-4caf-956a-b592accf9b1e

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 22 July 2015
                : 6 July 2016
                Page count
                Figures: 3, Tables: 2, Pages: 14
                Funding
                Funded by: Netherlands heart foundation
                Award ID: 2008B096
                Award Recipient :
                Funded by: Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NL), ZonMw
                Award ID: 120520010
                Award Recipient :
                This work was funded by the Netherlands Heart Foundation ( https://www.hartstichting.nl/), grant number 2008B096, funding recipient: MBK; and the Netherlands Organization for Health Research and Development ( http://www.zonmw.nl/en/), grant number 120520010, funding recipient: MBK. CCC and KDH were supported by the Intramural Research Program of the National Institutes of Health, National Institute of Diabetes & Digestive & Kidney Diseases. MBK was supported by an Academy Professorship of the Royal Netherlands Academy of Arts and Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Biology and Life Sciences
                Nutrition
                Diet
                Beverages
                Medicine and Health Sciences
                Nutrition
                Diet
                Beverages
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Body Mass Index
                Medicine and Health Sciences
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                Body Weight
                Weight Gain
                Medicine and Health Sciences
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                Social Sciences
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                All relevant data are within the paper and its Supporting Information files, see Table S6 of the Supplementary Appendix.

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