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835 Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Periodicals Publicacoes Tecnicas on 10/20/16 For personal use only. ARTICLE Associations between added sugar (solid vs. liquid) intakes, diet quality, and adiposity indicators in Canadian children JiaWei Wang, Lei Shang, Kelly Light, Jennifer O’Loughlin, Gilles Paradis, and Katherine Gray-Donald Abstract: Little is known about the influence of different forms of added sugar intake on diet quality or their association with obesity among youth. Dietary intake was assessed by three 24-h recalls in 613 Canadian children (aged 8–10 years). Added sugars (mean of 3-day intakes) were categorized according to source (solid or liquid). Dietary intake and the Canadian Healthy Eating Index (« HEI-C ») were compared across tertiles of solid and liquid added sugars separately as were adiposity indicators (body mass index (BMI), fat mass (dual-energy X-ray absorptiometry), and waist circumference). Cross-sectional associations were examined in linear regression models adjusting for age, sex, energy intake, and physical activity (7-day accelerometer). Added sugar contributed 12% of total energy intake (204 kcal) on average, of which 78% was from solid sources. Higher consumption of added sugars from either solid or liquid source was associated with higher total energy, lower intake of micronutrients, vegetables and fruit, and lower HEI-C score. Additionally liquid sources were associated with lower intake of dairy products. A 10-g higher consumption of added sugars from liquid sources was associated with 0.4 serving/day lower of vegetables and fruit, 0.4-kg/m2 higher BMI, a 0.5-kg higher fat mass, and a 0.9-cm higher waist circumference whereas the associations of added sugars from solid sources and adiposity indicators tended to be negative. In conclusion, higher consumption of added sugar from either solid or liquid sources was associated with lower overall diet quality. Adiposity indicators were only positively associated with added sugars from liquid sources. Key words: added sugars, diet quality, obesity, children, Healthy Eating Index. Résumé : Il y a peu d’études au sujet de l’influence de l’ajout de sucre sous diverses formes sur la qualité du régime alimentaire et de sa relation avec l’obésité chez les jeunes. On évalue l’apport alimentaire au moyen de trois carnets de rappel de 24 h chez 613 enfants canadiens (âgé de 8–10 ans). On classifie l’ajout de sucres (moyenne de l’apport durant 3 jours) en fonction de la source : liquide ou solide. On compare l’apport alimentaire et l’Indice de saine alimentation au Canada (« HEI-C ») en fonction des tertiles de sucres ajoutés sous forme liquide ou solide et on compare aussi les indicateurs de l’obésité (indice de masse corporelle (IMC), masse adipeuse, absorptiométrie à rayons X en double énergie) et le tour de taille. On examine les relations transversales au moyen de modèles de régression linéaire ajustés selon l’âge, le sexe, l’apport alimentaire et l’activité physique (accélérométrie durant 7 jours). Le sucre ajouté compte en moyenne pour 12 % de l’apport énergétique total (204 kcal) et 78 % provient d’aliments solides. Une consommation plus élevée de sucres ajoutés provenant de sources liquides ou solides est associée à un plus grand apport énergétique total, à un plus faible apport de micronutriments, de fruits et légumes et à un résultat plus faible à l’HEI-C. De plus, les sources liquides de sucres sont associées à un plus faible apport en produits laitiers. Une consommation supplémentaire de 10 g de sucres de sources liquides est associée à une diminution de 0,4 portion par jour de fruits et légumes, à un IMC supérieur de 0,4 kg/m2, à 0,5 g de plus de masse adipeuse et à 0,9 cm de plus de tour de taille; par contre, les associations entre les sucres ajoutés de sources solides et les indicateurs de l’adiposité présentent une tendance négative. En conclusion, une plus forte consommation de sucres ajoutés de sources liquides ou solides est associée à une plus faible qualité globale de l’alimentation. Les indicateurs de l’adiposité sont les seules variables positivement associées aux sucres ajoutés de sources liquides. [Traduit par la Rédaction] Mots-clés : sucres ajoutés, qualité de l’alimentation, obésité, enfants, indice de saine alimentation. Introduction A healthy diet is essential for normal growth in children and adolescents, and helps prevent obesity and related chronic diseases (Committee on Food Marketing and the Diets of Children and Youth 2006). Although Canadian youth consume adequate amounts of most nutrients, insufficient intake of some essential micronutrients is still evident. For example, the prevalence of inadequate vitamin A, magnesium, zinc, and phosphorus ranges between 10%–30%, and even as high as 67% for calcium among Canadian youth aged 9 to 13 years (Health Canada 2012). Childhood obesity has become a major public health concern around Received 21 October 2014. Accepted 15 March 2015. J.W. Wang* and K. Light. School of Dietetics and Human Nutrition, McGill University, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada. L. Shang. School of Dietetics and Human Nutrition, McGill University, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada; Department of Health Statistics, Faculty of Preventive Medicine, Fourth Military Medical University, Xi’an, 710032 China. J. O’Loughlin. Department of Social and Preventive Medicine, University of Montreal, Montreal, QC H3C 3J7, Canada; University of Montreal Hospital Research Centre (CRCHUM), Montreal, QC H2X 0A9, Canada. G. Paradis. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 1A2, Canada. K. Gray-Donald. School of Dietetics and Human Nutrition, McGill University, Ste-Anne-de-Bellevue, QC H9X 3V9, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 1A2, Canada. Corresponding author: Katherine Gray-Donald (e-mail: [email protected]). *Present address: Department of Applied Human Nutrition, Mount Saint Vincent University, Halifax, NS B3M 2J6, Canada. Appl. Physiol. Nutr. Metab. 40: 835–841 (2015) dx.doi.org/10.1139/apnm-2014-0447 Published at www.nrcresearchpress.com/apnm on 14 April 2015. Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Periodicals Publicacoes Tecnicas on 10/20/16 For personal use only. 836 the world. In Canada, 8.0% of children aged 6 to 11 years and 9.4% of adolescents aged 12–17 years are classified as obese (age- and sex-specific body mass index (BMI) ≥95th percentile) (Roberts et al. 2012). In recent decades, diets across the world are sweetening, with dramatic increases in the consumption of added sugars (Popkin and Nielsen 2003). American children aged 9 to 13 years consumed as high as 419 kcal of added sugar per day (National Cancer Institute 2014). Based on the data from 2004 Canadian Community Health Survey, boys aged 9 to 13 years consumed 620 kcal of total sugars per day (which contributed 25.3% of their daily calories), while teenage boys aged 14 to 18 years consumed the highest amount of total sugars among all age groups (688 kcal/day), with regular soft drinks as their primary source (Langlois and Garriguet 2011). Although recent United States data show declines in the consumption of added sugars, the average intake remains high in youth (Welsh et al. 2011). Added sugars are defined as caloric sweeteners added in the processing or preparation of foods and beverages (Johnson et al. 2009). More than 60% of daily added sugar intake comes from solid food (Langlois and Garriguet 2011), and the top sources include grain-based desserts, dairy desserts, candies, and ready-to-eat cereals (National Cancer Institute 2014). Sugar-sweetened beverages (SSB) are the main liquid source of added sugars in youths’ diet in North America (Guthrie and Morton 2000; Garriguet 2008a). Flavoured milk is the other liquid source of added sugars that is particularly prevalent among school-aged youth. Among New York City public schools in 2009, chocolate milk accounted for approximately 60% of total milk purchased (Centers for Disease Control and Prevention (CDC) 2010). There is evidence in some (Øverby et al. 2004; Joyce and Gibney 2008) but not all (Gibson 1993; Forshee and Storey 2001; Johnson et al. 2007; Rennie and Livingstone 2007) studies that higher intake of added sugars reduces micronutrient intake, displaces nutrient-dense foods, and is associated with obesity and weight gain in youth. Forshee et al., using data from the Continuing Survey of Food Intake by Individuals (1994–1996), reported that the role of added sugars in the diet quality of children and adolescents is inconsistent and small (Forshee and Storey 2001). In addition, a longitudinal study of 1203 British children reported no association between SSB consumption at age 5 or 7 years and total fat mass at 9 years (Johnson et al. 2007). Previous studies relating added sugars to dietary intake and health outcomes generally study added sugars overall or only from liquid food sources (i.e., SSB and/or flavoured milk) (Johnson et al. 2009; Kynde et al. 2010). Because most added sugars are from solid food sources, the importance of examining their role as well as SSB is recognized in a recent statement by the American Heart Association (Johnson et al. 2009). The present study was undertaken in a sample of Canadian children at risk of obesity in that at least one of their biological parents was obese. We studied the association of added sugar intake from solid and liquid food sources on overall diet quality and the associations between these 2 forms of added sugars and adiposity indicators. Materials and methods Study population This study is a secondary data analysis of 630 children aged 8 to 10 years at baseline (2005–2008) participating in the QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) study. Methods for this study have been described in detail elsewhere (Lambert et al. 2012; Wang et al. 2013, 2014). Data were collected during a clinic visit followed by telephone contacts. The study was conducted according to the guidelines laid down in the TriCouncil Statement on Ethical Conduct of Research and all procedures involving human subjects were approved by the ethics review boards at Centre Hospitalier Universitaire Sainte-Justine Appl. Physiol. Nutr. Metab. Vol. 40, 2015 and Laval University. Written informed consent was obtained from parents and assent was obtained from the children. Dietary assessment Within 8–12 weeks after the clinic visit, children’s dietary assessment on 2 weekdays and 1 weekend day was performed by a registered dietitian through telephone interview. In all, 613 out of 630 children completed three 24-h dietary recalls. In this study, the United States Department of Agriculture (USDA) Database for the Added Sugars Content of Selected Foods (USDA 2006) was used as the main data source for added sugars. Values of added sugars for each food item were entered into CANDAT nutrient analysis software version 8.0 (Godin London Inc., London, Ont., Canada). All further dietary analyses, including food group creation and nutrient calculation, were undertaken using CANDAT, which bases food composition data on the Canadian Nutrition File version 2007b and 2010 (Health Canada 2010). All food items were categorized by sources of added sugar into 24 food groups. Solid sources included added sugar from the following food groups: dairy and egg products; spices and herbs; fats and oils; poultry products; soups, sauces, and gravies; sausages and luncheon meats; ready-to-eat cereals; fruits; pork products; vegetables and vegetable products; nuts and seeds; beef products; fish and shellfish products; legumes and legume products; lamb, veal, and game; baked products; sweets; cereals, grains and pasta; fast foods; mixed dishes; and other snack foods. Liquid sources included SSB and flavoured milk (Wang et al. 2014). The Healthy Eating Index (HEI) is a measure of overall diet quality that assesses conformance to the Dietary Guidelines for Americans (Guenther et al. 2013). In Canada, a similar index of HEI-C 2009 (Woodruff and Hanning 2010) was adapted based on the latest dietary recommendation, Eating Well with Canada’s Food Guide (Katamay et al. 2007). This HEI-C 2009 directly listed the scoring scheme for 9- to 13-year-old youth, which includes 9 components with a continuous score assigned to each component, for a maximum score of 100. One of its components, “other foods” (10% of total score), mainly comprises foods rich in added sugars or solid fats, which contribute excess calories and may displace nutrient-dense foods from the diet. An overall higher score indicates closer conformity with Canada’s Food Guide, and a “good diet” is defined as HEI-C score ≥80 points (Glanville and McIntyre 2006). Adiposity assessment Height, measured using a stadiometer with participants standing against a wall and looking straight ahead, was recorded to the nearest millimetre during maximal inspiration. Weight was measured to the nearest 0.1 kg using an electronic scale, with participants wearing light indoor clothing and no shoes. BMI was calculated as weight (kg)/height (m2) and age- and sex-specific BMI z scores were determined using the growth charts published by the United States CDC (Ogden et al. 2002). Dual-energy X-ray absorptiometry (DXA) (Prodigy Bone Densitometer System, DF+14664, GE Lunar Corp., USA) was used to assess fat mass. Waist circumference was measured using a standard tape at the middistance between the last floating rib and the iliac crest at the end of a normal expiration. Physical activity assessment To obtain objective measures of physical activity, children wore a uniaxial activity monitor (Actigraph LLC, Pensacola, Fla., USA) for a 7-day period following the clinic visit. The accelerometer was worn for a mean of 13.4 h daily and recorded as counts per minute (Corder et al. 2007). Being consistent with current procedures used by the Canadian Health Measures Survey (Colley et al. 2011), days were excluded when the accelerometer was worn for less than 10 h and data from subjects who had worn the accelerometers for less than 4 days were excluded. Ninety-seven percent of Published by NRC Research Press Wang et al. Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Periodicals Publicacoes Tecnicas on 10/20/16 For personal use only. children had more than 4 days of accelerometer data, which has been shown to ensure adequate reliability (Puyau et al. 2002). Actigraph accelerometers have been validated against activitybased energy expenditure assessed by doubly labelled water in 9-year-old children (r = 0.58) (Ekelund et al. 2001). Statistical analysis The calculated mean intake values from 3 recalls were used in the analyses. The distribution of added sugars from solid and liquid food sources was described as the percentage of total added sugars. Participants were categorized according to tertile based on the grams of added sugars consumed from solid or liquid food sources. Daily average intake of nutrients (total energy, percentage of energy from protein, fat and carbohydrate, calcium, vitamins A and D), 2 food groups (milk and dairy products, vegetables and fruit) and total HEI-C scores were compared across tertile of added sugars from solid and liquid food sources separately using ANOVA. 2 tests were used to compare the percentage of consuming a good diet across added sugar tertiles. Post hoc multiple comparisons were performed using Duncan and Dunnett’s T3 for equal and unequal variances, respectively. All nutrients and food groups were adjusted for total energy by expressing quantities per 1000 kcal of intake. Multivariate linear regression analyses were used to study the associations between added sugar consumption (10 g) from solid and liquid food sources, respectively, and outcome variables of vegetables and fruit, BMI, fat mass, and waist circumference after adjustment for age, sex, energy intake, and physical activity. All conditions of linear regression analyses have been met (e.g., independence, linearity, and normality). Residual plot analysis was used as a sensitivity analysis for the regression models. Bonferroni correction (Gelman et al. 2012) was also used for adjusting the multiple comparisons (P < 0.004). Regression calibration (Spiegelman et al. 1997; Hardin et al. 2003) was used to adjust for within-person variation and potential measurement errors by including added sugar intake on 3 individual days. All statistical analyses were conducted using STATA version 11.0 (StataCorp LP, College Station, Tex., USA). Results The demographic and dietary characteristics of QUALITY participants were listed in Table 1. They consumed 51 g/day of added sugars on average, which provided 12% of total energy intake (204 kcal). Overall, 78% of added sugars came from solid food sources O the top 4 sources were sweets (contributed 29% of added sugars), baked products (25%), ready-to-eat cereal (6%), and other snack foods (4%). The other 22% of added sugars came from liquid sources (SSB and flavoured milk). Compared with children in the lowest tertile of added sugars from solid food sources (Table 2), those in the highest tertile had statistically significantly higher intakes of total energy and percentage of energy from carbohydrate, as well as lower intakes of % energy from protein, phosphorus, and magnesium. In addition, higher consumption of added sugars from solid food sources was associated with a lower intake of vegetables and fruit, lower total HEI-C scores, and a lower percentage of participants with a good diet. No statistically significant differences were detected for other nutrients or for milk and dairy products. Compared with children in the lowest tertile of added sugars from liquid food sources (Table 3), those in the highest tertile had significantly higher intakes of total energy and percentage of energy from carbohydrate, as well as significantly lower intakes of percentage of energy from protein, calcium, phosphorous, magnesium, and vitamins A and D. In addition, higher consumption of added sugars from liquid food sources was associated with lower intakes of the 2 food groups (milk and dairy products, vegetables and fruit) and lower total HEI-C scores and a lower percentage of participants with a good diet. 837 Table 1. Dietary sources of added sugars among Quebec Adiposity and Lifestyle Investigation in Youth cohort participants at baseline (N = 613). Mean Basic Age (y) Boys (%) BMI (kg/m2) BMI z score ≥ BMI 85th percentile (%) Total fat mass (kg) Waist circumference (cm) Physical activity (counts/min) Diet Total energy (kcal) Total HEI-C score (maximum 100) Total added sugars (g) Solid sourcesa (g) Sweets (g) Baked products (g) Ready-to-eat cereal (g) Other snack foods (g) Liquid sources (g) SSB (g) Flavoured milk (g) SD 9.6 54.4 19.5 0.7 41.9 11.0 67.5 587 0.9 O 4.3 1.1 O 7.6 12.2 186 1675 76 51 40 15 13 2.8 2.0 11 10 1.0 391 11 25 22 14 14 4.1 3.4 12 12 2.9 Note: BMI, body mass index; HEI-C, Healthy eating index Canada (2009; Woodruff and Hanning 2010); SSB, sugarsweetened beverage. aOnly top four solid sources of added sugars were listed. The multivariate linear regression models (Table 4) indicate that each additional 10 g of added sugars from solid sources was associated with a 0.3 servings/day lower of vegetables and fruit. A negative association was detected between consumption of added sugars from solid food sources and total fat mass, while a trend of negative association was observed with BMI and waist circumference as well. Consumption of each additional 10 g of added sugars from liquid food sources was associated with 0.4 serving/day of lower vegetables and fruit, a 0.4-kg/m2 higher BMI, a 0.5-kg greater fat mass, and a 0.9-cm higher waist circumference, respectively. Discussion The present study examined added sugars from both solid and liquid food sources in a sample of Canadian children at risk of obesity. The results suggest that higher consumption of added sugars from either solid or liquid food sources was associated with higher energy intake and lower overall diet quality. Higher consumption of added sugars from liquid food sources was also associated with lower intake of milk and dairy products (and related nutrients including calcium and vitamins A and D). Positive associations with adiposity indicators were observed with consumption of added sugars from liquid food sources only. Previous studies of added sugar have focused mainly on its liquid food sources (e.g., SSB). As solid food sources also contribute a significant amount of added sugars (e.g., more than 60% among Canadian youth (Langlois and Garriguet 2011)) and the lack of studies examining the potential differences of consuming added sugars from solid versus liquid foods, this partition of sugars was of particular interest. To date, the only other study in youth that examined dietary intake and its association with consuming added sugar from different food sources reported that consumption of pre-sweetened cereals increased the likelihood of reaching Dietary Reference Intakes for some essential shortfall micronutrients (calcium, folate, and iron), whereas consumption of SSB, candies, sweets, and sweetened grains decreased the likelihood of meeting the recommended levels for these nutrients (Frary et al. 2004). Our study combined all solid food sources of added sugars and found that similar to liquid sources, a higher consumption of Published by NRC Research Press 838 Appl. Physiol. Nutr. Metab. Vol. 40, 2015 Table 2. Daily nutrient and food intake by tertile of added sugar from solid food sources, among Quebec Adiposity and Lifestyle Investigation in Youth cohort participants (N = 613). Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Periodicals Publicacoes Tecnicas on 10/20/16 For personal use only. 1st tertile Total added sugars (g) Energy (kcal) % Energy from protein % Energy from fat % Energy from carbohydrate Calcium (mg/1000 kcal) Phosphorus (mg/1000 kcal) Magnesium (mg/1000 kcal) Vitamin A (g/1000 kcal) Vitamin D (g/1000 kcal) Milk and dairy products (g/1000 kcal) Vegetables and fruit (g/1000 kcal) Total HEI-C score (maximum 100) Good diet (≥80 score, %) 2nd tertile 3rd tertile Mean SD Mean SD Mean SD P 31.8a 1437a 17.6c 32.1 51.5a 525b 673c 143b 193 3.7 178 269c 79c 50.2c 15.4 308 3.9 5.2 6.9 161 136 29 96 2.5 124 138 10 O 47.1b 1654b 15.8b 32.0 53.6b 508ab 648b 140b 197 3.7 173 243b 76b 37.2b 12.7 306 3.0 5.2 6.1 148 129 29 93 2.4 120 121 10 O 74.4c 1939c 14.3a 32.5 54.7b 492a 611a 132a 201 3.3 163 199a 73a 26.6a 24.4 378 2.4 4.4 5.6 142 121 29 80 1.9 105 106 11 O <0.001 <0.001 <0.001 0.507 <0.001 0.077 <0.001 <0.001 0.643 0.128 0.400 <0.001 <0.001 <0.001 Note: Different lowercase letters in the same row indicate statistically significant difference among groups using ANOVA (P < 0.05) and the letters a, b, c are marked from the lowest to the highest value. HEI-C, Healthy eating index - Canada (2009; Woodruff and Hanning 2010). Table 3. Daily nutrient and food intake by tertile of added sugars from liquid food sources, among Quebec Adiposity and Lifestyle Investigation in Youth cohort participants (N = 613). 1st tertile Total added sugars (g) Energy (kcal) % Energy from protein % Energy from fat % Energy from carbohydrate Calcium (mg/1000 kcal) Phosphorus (mg/1000 kcal) Magnesium (mg/1000 kcal) Vitamin A (g/1000 kcal) Vitamin D (g/1000 kcal) Milk and dairy products (g/1000 kcal) Vegetables and fruit (g/1000 kcal) Total HEI-C score (maximum 100) Good diet (≥80 score, %) 2nd tertile 3rd tertile Mean SD Mean SD Mean SD P 38.4a 1644a 16.6b 32.3 52.5a 543b 682b 1488c 214b 3.9b 199b 266b 78b 46.9b 19.8 401 3.3 5.0 5.9 164 142 316 101 2.6 132 130 10 O 48.5b 1633a 16.2b 32.6 52.6a 504a 635a 1368b 190a 3.6ab 165a 233a 75a 33.8a 25.8 366 3.7 5.2 6.9 135 116 280 83 2.1 104 122 10 O 66.4c 1754b 14.9a 31.7 54.7b 477a 614a 1311a 187a 3.3a 148a 211a 74a 34.0a 21.7 394 3.1 4.6 6.1 145 124 255 82 2.0 105 117 11 O <0.001 0.003 <0.001 0.232 <0.001 <0.001 <0.001 <0.001 0.004 0.023 <0.001 <0.001 <0.001 0.007 Note: Different lowercase letters in the same row indicate statistically significant difference among groups using ANOVA (P < 0.05) and the letters a, b, c are marked from the lowest to the highest value. HEI-C, Healthy eating index - Canada (2009; Woodruff and Hanning 2010). Table 4. Multivariate linear regression analyses of the association between added sugars (liquid vs. solid) and vegetables and fruit and adiposity among Quebec Adiposity and Lifestyle Investigation in Youth cohort participants. Indicators* Vegetables and fruit (servings/d) Solid added sugars (10 g) Liquid added sugars (10 g) BMI (kg/m2) Solid added sugars (10 g) Liquid added sugars (10 g) Total fat mass (kg) Solid added sugars (10 g) Liquid added sugars (10 g) Waist circumference (cm) Solid added sugars (10 g) Liquid added sugars (10 g) N  coefficient 95% CI P 613 613 −0.28 −0.38 −0.38 to −0.18 −0.51 to −0.24 <0.001 <0.001 525 525 −0.18 0.40 −0.37 to 0.02 0.11 to 0.69 0.084 0.007 522 522 −0.39 0.52 −0.74 to −0.05 0.02 to 1.03 0.041 0.025 525 525 −0.55 0.87 −1.10 to 0.01 0.06 to 1.68 0.052 0.035 Note: BMI, body mass index; CI, confidence interval; HEI-C, Healthy eating index - Canada (2009; Woodruff and Hanning 2010). *Covariates included age, sex, energy intake, and physical activity. solid added sugars was associated with a lower overall diet quality, lower percentage of energy from protein as well as lower intake of micronutrients and vegetables and fruit. While specific food vehicles, such as fortified breakfast cereal, may contribute positively to overall diet, a small proportion of added sugar came from breakfast cereals in our study. In addition, our results indicated that those children with higher added sugar intake also consumed more energy overall but with decreased nutrient density. In addition, our findings are consistent with previous studies (Tordoff and Alleva 1990; Harnack et al. 1999; Rodriguez-Artalejo Published by NRC Research Press Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Periodicals Publicacoes Tecnicas on 10/20/16 For personal use only. Wang et al. et al. 2003; Vartanian et al. 2007; Libuda et al. 2009; Collison et al. 2010), showing that higher consumption of added sugar from liquid sources (mainly SSB) is linked to higher energy intake, lower consumption of essential micronutrients, and lower overall diet quality in youth. A cross-sectional analysis of 1112 Spanish children aged 6 to 7 years suggested that higher consumption of SSB was associated with higher energy intake, lower consumption of milk, calcium, and lower HEI score (Rodriguez-Artalejo et al. 2003). Another analysis of dietary data from 7156 three-day weighed records in 1069 German youth aged 2 to 19 years found that SSB consumption was associated with decreased micronutrient intakes (i.e., calcium and folate) as well as protein intake and total diet quality (Libuda et al. 2009). A recent analyses of over 9400 youth aged 10 to 19 years indicated a higher intake of SSB is associated with poor dietary choices (more fast foods and less vegetables and fruit) (Collison et al. 2010). Studies examining the association between consumption of added sugars and adiposity indicators in youth remain inconclusive. Over the past 10 years, a large number of observational studies including our own findings using QUALITY data (Wang et al. 2013) report positive associations between SSB consumption and higher risk of adiposity in both youth and adults (Malik et al. 2013). One cross-sectional analysis of nationally representative children aged 2–18 years (n = 10 038) from the Canadian Community Health Survey 2.2 indicated that boys aged 6–11 years whose beverage pattern characterized by soft drink had a higher prevalence of overweight and obesity (odds ratio 2.3) compared with the lower intake group, after adjusting for various confounders. But this beverage-weight association was not found among other age/ sex groups (Danyliw et al. 2012). Several recent studies in youth reported negative findings with consumption of SSB or solid added sugars (from either candy or sweets) or total added sugars. For example, a cross-sectional analysis of 11 181 youth aged 2 to 18 years from the National Health and Nutrition Examination Survey (NHANES) (1999–2004) found that candy consumers were 22% and 26% less likely to be overweight or obese than nonconsumers (O’Neil et al. 2011). In an analysis of 3136 youth aged 6 to 18 years from NHANES (2003–2006), Nicklas et al. (2011) reported no significant associations between intake of total added sugars and adiposity indicators (i.e., BMI z score, waist circumference) with adjustment for age, sex, race, total energy intake, and physical activity. In our study, we found a cross-sectional association between higher added sugar intake from liquid food source and greater adiposity. Because of the cross-sectional design of this study, the direction of the effect of the sugar–adiposity associations is not clear and it could be that some parents limit some foods in heavier children. Added sugar from different solid sources was combined in our study and in future studies one might wish to examine different types of solid foods. There were a small number of trials indicating that the sugar in liquid form generally produces less satiety and incomplete energy compensation than sugar in solid form, and thus contributes to positive energy balance and a higher risk of weight gain (DiMeglio and Mattes 2000; Pan and Hu 2011). But considering the evidence of satiety and energy intake from short-term studies is equivocal, more randomized controlled trials of sufficient size and duration are clearly needed to further explore the potential mechanism between sugar intake (liquid vs. solid) and adiposity (Saris 2003; van Baak and Astrup 2009). The QUALITY cohort study included children at risk of obesity, and had a sizable population of heavy children to study. The results may not be generalizable to the entire population, as youth living in households with an obese parent may have a different food environment, but given the current obesity rates in Canada, this home environment of 1 obese parent is not unusual. The recruitment from schools rather than clinics also helps to enhance the generalizability. The data for this study used measures of three 24-h dietary recalls, several measures of adiposity (includ- 839 ing fat mass measured by DXA), and was able to control for physical activity measured by 7-day accelerometry. The food coding in the dietary recall questionnaire enabled us to adjust for total energy intake, create food groups, and estimate added sugar values from both solid and liquid food sources. Although it is better than single dietary recall, this short-term recall may still limit the reliability on long-term usual intake patterns (Beaton et al. 1979). As a global indicator to evaluate overall diet quality, the HEI-C provided advantages over other methodologies at the population level (Kant 1996; Dubois et al. 2000), although it may be limited by the similar weighting factor (10 points) for each component (except for “vegetables and fruit”, 20 points) (Woodruff and Hanning 2010). Canadian Nutrition File provides data on total sugars only, without distinguishing whether it is intrinsic to the food or added. The estimation of added sugar values was taken from the USDA, which recently removed the Added Sugar Database from its Web site because of constant changes in formulations for a large number of commercial and multi-ingredient foods. Considering there is no better added sugar database, we and others (Kell et al. 2014) chose to make use of this Added Sugar Database. Although under-reporting is prevalent among self-reports of dietary surveys among both older youth and adult populations (Garriguet 2008b) and particularly “unhealthy” foods rich in fat and/or added sugars are more frequently underestimated (Lafay et al. 2000), estimates of under-reporting are difficult to quantify in younger children. No specific guideline for children was made yet on the recommended consumption level of added sugars. Considering for this potential knowledge gap for youth, our study was designed to provide some preliminary evidence on the relationship between added sugar consumption from solid versus liquid food sources, diet quality, and obesity. Regarding to the potential adverse effects of consuming excessive added sugars on micronutrient dilution and health (Hess et al. 2012), the Beverage Guidance Panel (initiated by Dr. Barry M. Popkin in the United States) has recommended limiting SSB intake for the general population in the United States (Popkin et al. 2006). In fact, more than 30 national and subnational governments have made efforts to restrict the availability of SSB in schools (Hawkes 2010; Mâsse and de Niet 2013), including voluntary actions taken by some beverage companies (Storey 2010). Per capita intake of milk decreased from 605 to 472 mL) per day between 1989 and 2008 in American children (Lasater et al. 2011). Although several recommendations or policies related to the regulation of flavoured milk have been announced, no definite agreement has been reached. Food and Nutrition Service in the United States published Nutrition Standards for School Meals allowing schools to offer flavoured milk if it is fat-free (Food and Nutrition Service 2014). In addition, Recommended Community Strategies published by the CDC require licensed child care facilities in local jurisdictions to ban SSB (including flavoured milk) (Khan et al. 2009), as does the Los Angeles Unified School District Board of Education, which has voted to remove flavoured milk from schools (Los Angeles Unified School District 2011). In conclusion, higher consumption of added sugars from either solid or liquid food sources is linked to a lower diet quality in children. Liquid, but not solid added sugars were positively associated with adiposity indicators. Further longitudinal and clinical trial studies are encouraged, especially for examining added sugars from different solid foods, considering that there is still no recommendation specifically for children and adolescents who are the highest consumers of added sugar. Conflict of interest statement All authors reported with no conflicts of interest. Acknowledgements We are grateful to all the families that participated in the QUALITY cohort. Dr. Marie Lambert (July 1952 – February 2012), pediatric geneticist and researcher, initiated the QUALITY cohort. Her leadPublished by NRC Research Press Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by Periodicals Publicacoes Tecnicas on 10/20/16 For personal use only. 840 ership and devotion to QUALITY will always be remembered and appreciated. Dr. Jennifer O’Loughlin is a Canada Research Chair in the early determinants of adult chronic disease. Dr. Gilles Paradis holds an Applied Public Health Research Chair in chronic diseases prevention. We thank Ms. Louise Johnson-Down for her technical help in data processing and Dr. Danielle St-Arnaud-McKenzie for her critical comments on the manuscript. Financial support: Canadian Agri-Science Clusters Initiative, Canadian Institutes of Health Research, Heart and Stroke Foundation of Canada, and Fonds de la recherche en santé du Québec. All these funders had no role in the design, analysis or writing of this article. Author contributions: J.W.W. and K.G.-D. designed research; J.W.W. conducted research, data analyses and interpretation, and manuscript writing. L.S. contributed to the data interpretation and critical revision; K.L. helped data entry and analyses; J.O., and G.P. contributed on the data acquisition and interpretation and critical revision; K.G.-D. supervised the data analyses and interpretation and critical revision; J.W.W. and K.G.-D. had primary responsibility for final content. All authors read and approved the final version of the paper. References Beaton, G.H., Milner, J., Corey, P., McGuire, V., Cousins, M., Stewart, E., et al. 1979. 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