Association between consumption of nonessential energy-dense food and body mass index among Mexican school-aged children: A prospective cohort study

Association between consumption of nonessential energy-dense food and body mass index among Mexican school-aged children: A prospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association between consumption of nonessential energy-dense food and body mass index among Mexican school-aged children: A prospective cohort study Tonatiuh Barrientos-Gutiérrez, Daniel Illescas-Zárte, Carolina Batis, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2833950/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Jun, 2024 Read the published version in International Journal of Obesity → Version 1 posted 13 You are reading this latest preprint version Abstract BACKGROUND/OBJECTIVES: Obesity prevalence in Mexican children has increased rapidly and is among the highest in the world. We aimed to estimate the longitudinal association between nonessential energy-dense food (NEDF) consumption and body mass index (BMI) in school-aged children 5 to 11 years, using a cohort study with 6 years of follow-up. SUBJECTS/METHODS: We studied the offspring of women in the Prenatal omega-3 fatty acid supplementation, child growth, and development (POSGRAD) cohort study. NEDF were classified into four main groups: chips and popcorn, sweet bakery products, non-cereal based sweets, and ready-to-eat cereals. We fitted fixed effects models to assess the association between change in 418.6 kJ (100 kcal) of NEDF consumption and changes in BMI. RESULTS: Between 5 and 11 years, children increased their consumption of NEDF by 225 kJ/day (53.9 kcal/day). In fully adjusted models, we found that change in total NEDF was not associated with change in children’s BMI (0.033 kg/m 2 , [p=0.246]). However, BMI increased 0.078 kg/m 2 for every 418.6 kJ/day (100 kcal/day) of sweet bakery products (p=0.035) in fully adjusted models. For chips and popcorn, BMI increased 0.208 kg/m 2 (p=0.035), yet, the association was attenuated after adjustment (p=0.303). CONCLUSIONS: Changes in total NEDF consumption were not associated with changes in BMI in children. However, increases in the consumption of sweet bakery products were associated with BMI gain. NEDF are widely recognized as providing poor nutrition yet, their impact in Mexican children BMI seems to be heterogeneous. Health sciences/Medical research/Epidemiology Health sciences/Health care/Nutrition Figures Figure 1 Introduction In the last four decades, the prevalence of obesity in children has increased in developing countries from 8.3–13.2% [ 1 ]. In Mexico, the prevalence of obesity in school-aged children has increased rapidly from 9.0% in 1999 to 18.6% in 2021 [ 1 – 4 ]. Childhood obesity has been linked to lower quality of life, higher risk of non-communicable diseases in adulthood, such as hypertension, dyslipidemia, type-2 diabetes, and premature death [ 5 – 8 ]. The hypothesis is that a low-quality diet, rich in nonessential energy-dense food (NEDF), often termed “junk food”, “discretionary food” or “processed food”, is a key factor for weight gain and obesity [ 9 – 11 ]. NEDF could be a critical risk factor for obesity in children and adolescents in Mexico as they displace healthy foods [ 12 ], are high in sugar, refined grains, unhealthy fats [ 10 , 13 ], and have a high glycemic index [ 12 ]. NEDF consumption, defined in previous studies as energy-dense food without a cut-off point or > 13% of total energy from added sugars and/or saturated fat is high in Mexico, particularly among school-aged children living in big cities [ 10 , 14 , 15 ], who on average consume 21% of their total daily energy requirement from NEDF, with 50% of this consumed at school [ 14 , 15 ]. School-aged children are particularly vulnerable to NEDF consumption due to targeted marketing and advertisement to young children as well as misleading nutritional information [ 16 , 17 ]. Increased access to NEDF in this age group was large due to high availability in elementary schools and school-aged children have not fully developed their cognitive capacity of resistance towards these foods, and are less able to avoid or reduce their consumption [ 18 ]. Although NEDF might play a critical role as a risk factor for childhood obesity, due to their low diet quality and high intake among children, evidence of the effect of NEDF is limited. One of the main limitations is the lack of a consistent definition or classification of NEDF. Moreover, longitudinal studies of the effect of several NEDF classifications to weight gain in children are scarce and with mixed results [ 19 – 23 ]. Some of the limitations identified in those studies may be small samples sizes, short follow-ups, and limited information on changes in NEDF consumption over time, which could explain the lack of consistent findings. Further evidence on the potential link between NEDF consumption and weight gain in children is needed, to understand the impact of these food group in child wellbeing and health. Our aim was to estimate the longitudinal association of the change in NEDF consumption over time and changes in body mass index of school-aged children 5 to 11 years of age, using a cohort study with 6 years of follow-up. Methods Study design and population We studied the offspring of women in the ongoing POSGRAD (Prenatal omega-3 fatty acid supplementation and child growth and development) study a double-blind, randomized, controlled trial in which women were supplemented with DHA or placebo from mid-pregnancy to parturition. The original study included 978 live births between June 2005 and June 2007 to 973 women who remained in the study as previously described [ 24 ]. Mother-child pairs have been followed prospectively. All children in the cohort had access to the Mexican Social Security Institute in Cuernavaca, Mexico, which provides services to formal employees and their families. Study variables Outcome variables Weight and height were measured twice by trained personnel using standardized procedures [ 25 ]; the average of both measurements was used. Weight with light clothes or a hospital gown was measured to the nearest of 100 g using a digital step-up scale (SECA 803). Height was measured without shoes, hat, hairclips, headbands or other items that could obstruct the procedure using a portable stadiometer (SECA 213). Then we obtained body mass index (weight (kg) /height (mts) 2 , BMI) and calculated z-scores based on the WHO growth reference [ 26 , 27 ]. Exposure variables Dietary intake was evaluated at the three waves. At baseline a 24-hour recall (24HR) questionnaire was applied by a trained interviewer to the person in the household who prepared the meals (frequently the mother); for waves 2 and 3 the same 24HR standardized method were applied but through an automated software previously used in a National Survey [ 28 ]. This is a method which capture more accurate information of the interviewees through 5 iterative steps that complement each other for memory improvement in food intake and thus, reducing under-reporting [ 29 ]. During the interview, children participated in the report of their diet, complementing, and validating their mothers’ report and in some cases adding missing food, correcting the size of a portion or removing the food reported by the adult. 24HR were performed from Sunday to Friday. To increase the accuracy of portions size, we used standardized food replicas, images of products, spoons, and cups of different sizes. Dietary information was collected as follows: 1) individual foods, 2) custom recipes (recipe reported and described in detail by the participant), and 3) standard recipes (set of ingredients in a documented and standard recipe when unknown to the subject). For our analysis all the recipes were disaggregated into their ingredients (with exception of beverages) to facilitate identifying all NEDF in recipes, (e.g. chips, puffed wheat snacks, candies, chocolate, sweets, others). To address outliers in food items, we identify those when the reported amount was > 4 SD from the mean for the same food and age group to minimize their influence in total diet and analysis. We identify less than 0.1% as outliers and were truncated at the highest value (median + four SD) to minimize their influence in total diet and analysis. We did not identify implausible reporters by using the ratio for total energy intake to estimated energy requirement out of the interval between − 3 and + 3 SD in each wave. After the first stage of data cleaning and processing, energy, nutrients and added sugar from food were obtained with the Mexican Food Database in its 18.1.1version that include 1978 different foods including standardized recipes, and labeling information from some processed products [ 30 ]. Total NEDF was classified using the definition by the Ministry of Finance and Public Credit and Ministry of Health of Mexico in 2014 [ 31 ], which considers two criteria: an energy density of > 1151 kJ/100g (275 kcal/100g) and to be classified as "nonessential foods”. NEDF were classified in four groups according to nutrition composition and consumption patterns: 1) Chips and popcorn, 2) Sweet bakery products, 3) Non-cereal based sweets and, 4) Ready-to-eat cereals. Subgroups of these principal groups were constructed to obtain more homogenous groups as presented in Table 1 . We excluded salty seeds or other seed products from the first group because there is solid evidence that seeds are associated with weight lost and are considered a healthy food [ 32 – 34 ]; they were included in the tax because of their high sodium content but our outcome of interest was weight gain and not sodium-related outcomes. Also, we classified beverages into the following food groups: plain water, sugar-sweetened beverages (regular soda, homemade fruit water with added sugar, sweetened milk, coffee or tea with sugar, fruit drinks and sport beverages), 100%-fruit juice, and milk without sugar. Table 1 Classification of nonessential energy dense food. Main groups of NEDF 1 Subgroups of NEDF 1 Food examples Chips and popcorn Fried potato, flour and corn chips, packaged fried pork skin, ready-to-eat popcorn, microwave popcorn. Sweet bakery products Whole grain with added sugar Bars, enriched bread and cookies made with whole grain flour but all with added sugar. Sweet bread Sweet cookies, sweet bread, energy bars and cereal bars. Pie and cakes All kinds of pies and cakes. Non-cereal based sweets Cocoa and other sweet products Cocoa, raisin, plum and legumes covered with chocolate and gums with or without sugar. Sweets Strawberry, vanilla or chocolate powder, condensed milk, fruit preserves, candies, marshmallows, jam, jellies, “dulce de leche” or “cajeta”, hazelnut spread, caramels, ice cream, ice-pops, popsicle. Ready-to-eat cereals All the pre-prepared and ready-to-eat cereal with added sugar. 1 NEDF, Nonessential energy-dense food. Covariates A socioeconomic index was calculated at baseline using a questionnaire administered to the head of household that included sanitation and household characteristics and assets. Using this information, we generated an index using principal components analysis. Maternal BMI was calculated using measured weight and height; maternal formal education was categorized as less than secondary school, secondary school, and high school or higher. Marital status was categorized as single (single, separated, divorced or widower participants) and marriage or free union (participants in marriage or living together with a couple). Maternal age was obtain using birth date, while children’s sex was obtained from the birth certificate. Physical activity and sedentary activities . Physical activity and sedentary activities were assessed at 7 and 11 years old, using a validated semi-quantitative questionary based on the Youth Activity Questionnaire developed and validated by Hernández et al [ 35 ]. Physical activity included: playing soccer, volleyball, cycling, skating or skateboarding, basketball, dancing, swimming, walking, taking care of pets, cleaning the house, playing games at home or in the school, among others. Sedentary activities included: time spend watching television, playing videogames, reading ,and doing homework and was defined using the time doing this activity during weekdays and weekends. Available responses included: “0 h”, “ 6 h” and responses were scored “0 h”, “0.25 h”, “1.25 h”, “3 h”, “5 h”, and “6 h”, respectively. Items from physical activity and sedentary activities were added to obtain the total minutes in a week and then per day. Statistical methods Children’s age and sex and mother’s age, education, marital status, and BMI were described at baseline. We evaluated trends across the three cohort waves using grams, joules (calories), percent total energy of NEDF and its subgroups and for BMI. As physical activity and sedentary behavior was just measure at 7 and 11 years, we assumed no change from 5 to 7 years old, imputing for age 5 the same values of age 7. Then we test for trend for dietetic, anthropometric and physical activity variables across 5, 7 and 11 years using an extension of the Wilcoxon rank-sum test created for this purpose. Fixed effect models were used to assess the association between within-individual change in NEDF consumption and the change in BMI. Fixed effect models considered the nesting structure of data waves nested within children, using age as time of observation [ 36 ]. Energy from NEDF and its subgroups was rescaled to produce coefficients relative to 418.6 kJ (100 kcal) change. We ran three different models for each main exposure variable. The first model was unadjusted, the second model was controlled by change in joules different from the main exposure (joules/day) [ 37 ] and the third was adjusted by model 2, plus change in physical activity (min/day) and change in tv watching (min/day). Some sensitivity analyses were performed to assess the robustness of the results. First, in the fixed effect model we changed the adjustment of change in energy different from NEDF for those dietary groups that are closely related with change of BMI, like sugar-sweeten beverages, 100% fruit juice, milk, fruits, dairy food, meat and eggs and processed meet. Second, we left the raw value of the detected dietary outliers to understand their influence in our results. Finally, we changed our model from fixed to a random effects model to estimate the association between BMI and NEDF consumption using the confounders that change in time and without changing in time. All statistical analyses were performed in STATA® Version 13 [ 38 ]. Results The baseline wave was conducted when children were 5 years old (between 2010 and 2011), with the first follow-up at 7 years (between 2012 and 2013) and second at 11 years (between 2015 and 2016). The study sample consisted of 797 at baseline, 682 at 7 years and 439 at 11 years old. Reasons for follow-up losses are presented in the flowchart (Fig. 1). Table 2 presents the characteristics of children and their mothers participating in our study. At baseline there were 797 children and 47% were female. Of them, 85.9% were followed to second (7 years) and 70.7% to the third wave (11 years). Children’s mothers were on average 31.4 years old and majority of them (78.7%) had less than high school, were not single, and overweight. Table 2 Descriptive characteristics of children and their mothers in the POSGRAD 1 study at baseline. Demographic characteristics Baseline (n = 797) Children age (mean ± SD) Years 4.91 ± 0.28 Children sex (n/%) Male 424 (53) Female 373 (47) Mother's age (mean ± SD) 31.3 ± 4.8 Mother's education (n/%) Less than secondary school 303 (38.1) Secondary and high school 323 (40.6) More than high school 170 (21.3) Mother's civil status (n/%) Single 72 (9.0) Married or free union 725 (91.0) Mother's BMI (mean ± SD) 26.15 ± 4.3 Normal weight (n/%) 342 (42.9) Overweight or obese (n/%) 455 (57.9) 1 POSGRAD , Prenatal omega-3 fatty acid supplementation and child growth and development. SD, standar deviation. Children contributed with 1885 data points, which represents and average of 2.4 visits per child over a mean of 6.1 years of follow-up. Table 3 presents the longitudinal change in body weight, BMI, other anthropometric and physical indicators. Mean BMI increased in the first period 1.0 ± 1.46 kg/m 2 and 4.07 ± 2.9 kg/m 2 in the second; this represents an increase of 0.56 ± 0.96 in BMI z-score and 24.2% increase in the proportion of overweight and obesity from baseline to the third wave. Table 3 Mean change in anthropometric measurements, nutritional status and physical activity in children from baseline to 7 and 11 years old. ∆ from baseline to Baseline (n = 797) 7 years (n = 682) 11 years (n = 439) Weight (kg) 18.3 ± 2.9 2 6.30 ± 2.95 23.46 ± 8.4 Height (cm) 108.3 ± 4.4 2 13.17 ± 1.9 37.09 ± 4.2 Body mass index (kg/m 2 ) 15.5 ± 1.7 2 1.00 ± 1.46 4.07 ± 2.9 Height for age, z score -0.39 ± 0.9 2 0.25 ± 0.24 0.48 ± 0.54 Body mass index for age , z score 0.11 ± 1.1 2 0.30 ± 0.69 0.56 ± 0.96 Underweight (n/%) 9 (1.1) 10 (1.5) 16 (3.7) Normal weight (n/%) 639 (80.2) 465 (68.2) 335 (53.5) Overweight (n/%) 101 (12.7) 114 (16.7) 107 (24.4) Obesity (n/%) 48 (6.0) 93 (13.6) 81 (18.5) Physical activity (min/day) 1 ND 74.9 ± 46.3 2 -12.6 ± 57.1 Total sedentary activities (min/day) 1 ND 252.4 ± 104.8 2 39.25 ± 143.9 TV ND 115.5 ± 65.4 2 -16.5 ± 82.2 Other sedentary activities ND 137.02 ± 68.6 2 55.8 ± 110.2 Results are presented in means change and standard deviation, unless it specifies different. 1 n=677 at 7 years and n = 399 at 11 years old. ND, No data. Test for trend across 5, 7 and 11 years old. 2 p value < 0.001. Mean total caloric intake at baseline was 6086.4 kJ (1454 kcal), 19.6% of those joules were NEDF. At baseline 95% of children consumed NEDF in the previous day of assessment, 92% by age 7, and 88% by age 11 (data not shown). At baseline, beverage energy intake represented 20% of the total caloric intake; 5.6% of milk, 14.2% of sugar sweetened beverages and a minimal proportion from juice, tea without sugar and other beverages (Supplemental table 1 ). Table 4 presents baseline and change levels of NEDFL consumption in joules (calories), grams and percentage of total energy consumption to 7 and 11 years old. All sweet bakery products, especially sweet bread, were the main contributors to NEDF with 644 kJ/day (154 kcal/day) (10.5% of total caloric intake). Non-cereal based sweets, ready-to-eat cereals, and chips and popcorn represented a total caloric intake of 3.8%, 3.1% and 2.1%, respectively. On average, the amount of NEDF consumption increased 113 ± 1289 kJ/day (27 ± 308 kcal/day) from baseline to the first wave and 226 ± 1536 kJ (54 ± 367 kcal/day) from baseline to the second wave (p = 0.034); nevertheless, total caloric intake decreased by 2.3 and 3.1 percent points, respectively. In all NEDF groups and subgroups, except for ready-to-eat cereals, the amount in grams and caloric intake increased from 5 to 11 years, yet, as a percent of total energy the change was either negative or null. Consumption of chips and popcorn increased in joules [∆ 98 kj/day (∆ 23.4 kcal/day)] and percent total energy (∆ 0.7 pp/wave) from 5 to 11 years old. Sweet bakery consumption increased on average 54 ± 1050 kJ (13 ± 251 kcal) in first period and 129 ± 1213 kJ (31 ± 290 kcal) in the second, mainly due to sweet bread. Table 4 Mean change in grams, joules (calories) and percentage of total calorie intake of nonessential and energy-dense food from baseline to 7 and 11 years old. ∆ from baseline to Baseline (n = 797) 7 years (n = 682) 11 years (n = 439) g kJ (kcal) ptec 1 ∆ g ∆ kJ (kcal) ∆ ptec 1 ∆ g ∆ kJ (kcal) ∆ ptec 1 Total NEDF 73 ± 58 2 1188 ± 925 2 (284 ± 221) 19.6 ± 13 3 6.8 ± 82 111 ± 1289 (26.6 ± 308) -2.3 ± 17 13.7 ± 94 225 ± 1536 (53.9 ± 367) -3.1 ± 18 Chips and ready-to-eat popcorn 6 ± 14 3 133 ± 293 3 (32 ± 70) 2.1 ± 4.8 3 1.1 ± 22 24 ± 468 (5.9 ± 112) -0.1 ± 6.8 5.1 ± 25 97 ± 514 (23.4 ± 123) 0.7 ± 7.3 Sweet bakery products 41 ± 49 644 ± 732 (154 ± 175) 10.5 ± 12 2 3.2 ± 72 53 ± 1054 (12.8 ± 252) -1.3 ± 15 9.3 ± 85 128 ± 1218 (30.8 ± 291) -1.7 ± 15 Whole-cereal with sugar 5 ± 14 87 ± 246 (21 ± 59) 1.4 ± 4.0 0.8 ± 20 12 ± 346 (3.1 ± 82.7) -0.1 ± 5.4 1.4 ± 29 22 ± 493 (5.4 ± 118) -0.21 ± 5.5 Sweet bread 25 ± 37 418.6 ± 623 (100 ± 149) 6.8 ± 9.8 6.9 ± 55 95 ± 895 (22.7 ± 214) 0.0 ± 13 6.1 ± 53 84 ± 866 (20.2 ± 207) -0.7 ± 12 Cake, pie and others 11 ± 35 138 ± 422 (33 ± 101) 2.3 ± 7.4 -4.3 ± 52 -52 ± 632 (-12.6 ± 151) -1.3 ± 9.5 1.9 ± 66 23 ± 799 (5.5 ± 191) -0.8 ± 9.4 Non-cereal based sweets 14 ± 20 2 226 ± 309 2 (54 ± 74) 3.8 ± 4.8 3 0.7 ± 30 5 ± 481 (1.3 ± 115) -0.6 ± 6.7 2.3 ± 35 35 ± 539 (8.6 ± 129) -0.8 ± 7.0 Cocoa and legumes with sugar 0.3 ± 2 3 3 ± 20 3 (0.9 ± 5) 0.1 ± 0.4 3 -0.1 ± 3 -1 ± 46 (-0.3 ± 11) -0.0 ± 0.7 0.3 ± 8.9 3 ± 108 (0.9 ± 26) 0 ± 1.4 Sweets 14 ± 20 2 226 ± 305 2 (54 ± 73) 3.7 ± 4.8 3 0.7 ± 30 5 ± 481 (1.3 ± 115) -0.6 ± 6.7 1.9 ± 34 30 ± 531 (7.3 ± 127) -0.8 ± 6.9 Ready-to-eat cereals 12 ± 24 3 179 ± 376 3 (43 ± 90) 3.1 ± 6.3 3 1.7 ± 38 27 ± 602 (6.6 ± 144) -0.2 ± 8.4 -2.4 ± 35 -36 ± 544 (-8.8 ± 130) -1.2 ± 7.2 Results are presented in means change and standard deviation. Test for trend across 5, 7 and 11 years old. 1 ptec: percentage of total energy consumption. 2 p value < 0.05 3 p value < 0.001 Table 5 includes the unadjusted and adjusted association between BMI change and NEDF change. In the fully adjusted model, the increase in 418.6 kJ/day (100 kcal/day) in total NEDF was associated with a 0.033 kg/m 2 increase in children’s BMI (95% CI: -0.023, 0.090; p = 0.246). The effect across NEDF subgroups was heterogeneous. The effect between sweet bakery products and BMI was 0.061 kg/m 2 in the unadjusted model (95%CI: -0.012, 0.135, p = 0.102), increasing to 0.078 kg/m 2 in the fully adjusted model (95%IC: 0.005, 0.151; p = 0.035). In the stratified subgroups of sweet bakery products, 418.6 kJ/day (100kcal/day) increase of whole grain bread with added sugar (-0.176 kg/m 2 [95%IC: -0.394, 0.041; p = 0.113]) and cake and pie consumption (0.050 kg/m 2 [95%IC: -0.061, 0.162; p = 0.375]) were in the expected direction, although not statistically significant. But 418.6 kJ/day (100 kcal/day) increase in sweet bread was associated with a 0.127 kg/m 2 BMI increase (95%IC: 0.036, 0.218; p = 0.006). Also, in the unadjusted model, 418.6 kJ/day (100kcal/day) increase in chips and popcorn intake was associated with a 0.208 kg/m 2 BMI increase (95%IC: 0.036, 0.380; p = 0.017), being attenuated in the fully adjusted model (0.086 kg/m 2 [95%IC: -0.078, 0.252; p = 0.303]). Coefficients for association between consumption of non-cereal based sweets and ready-to-eat cereals were negatively associated with children’s BMI. Non-cereal based sweets consumption was not significantly associated even in the stratified subgroups of cocoa and other sweets. Ready-to-eat cereals in the unadjusted model was inverse associated with BMI (-0.095 [95%CI: -0.305, -0.152]; p = 0.030) but after dietary and physical activity adjustment the coefficient went lower and p value lost its significance (-0.095 [95%CI: -0.233, 0.043] p = 0.178). Table 5 Mean change in body mass index associated with total change consumption of NEDF and its subgroups in school age children from 5 to 11 years old. Main exposure Model Coefficient 95% CI p Total NEDF 1 0.039 -0.018, 0.098 0.184 2 0.030 -0.025, 0.086 0.282 3 0.033 -0.023, 0.090 0.246 Chips and popcorn 1 0.208 0.036, 0.380 0.017 2 0.160 -0.005, 0.325 0.058 3 0.086 -0.078, 0.252 0.303 Sweet bakery products 1 0.061 -0.012, 0.135 0.102 2 0.096 -0.010, 0.130 0.096 3 0.078 0.005, 0.151 0.035 Whole-grain with added sugar 1 -0.056 -0.252, 0.139 0.569 2 -0.175 -0.365, 0.014 0.070 3 -0.176 -0.394, 0.041 0.113 Sweet bread 1 0.112 -0.017, 0.207 0.020 2 0.123 0.032, 0.214 0.008 3 0.127 0.036, 0.218 0.006 Pie and cakes 1 0.006 -0.109, 0.122 0.911 2 0.024 -0.086, 0.135 0.667 3 0.050 -0.061, 0.162 0.375 Non-cereal based sweets 1 0.031 -0.129, 0.192 0.701 2 0.839 -0.170, 0.138 0.839 3 -0.029 -0.181, 0.123 0.705 Cocoa and other sweet products 1 -0.054 -1.296, 1.187 0.931 2 -0.122 -1.314. 1.069 0.840 3 -0.131 -1.284,1.022 0.824 Sweets 1 0.028 -0.133, 0.1912 0.729 2 -0.016 -0.172, 0.139 0.834 3 -0.029 -0.183, 0.123 0.702 Ready-to-eat cereals 1 -0.160 -0.305, -0.152 0.030 2 -0.107 -0.247, 0.032 0.131 3 -0.095 -0.233, 0.043 0.178 NEDF, nonessential and energy-dense food. Coefficients are presented in units of change of 418.6 kJ/ (100 kcal/day). Fixed effects models: Model 1 (n = 724), unadjusted; Model 2 (n = 724): adjusted by change in joules different from the main exposure [kJ/day (kcal/day)); Model 3 (n = 602): adjusted by model 2 + change in physical activity (min/day) and change in tv watching (min/day). In further sensitivity analyses, adjustment for those dietary groups that are closely related with change of BMI (Supplemental table 2) and not truncating outlier truncation, did not change results of the models. In the random effect analysis, we found a similar pattern of association, with weaker coefficients for most of the outcomes. Chips and popcorn, sweet bakery products and sweet bread were associated for each 418.6 kJ/day (100kcal/day) increase in consumption with a 0.128 kg/m 2 (95%IC: 0.006, 0.250; p = 0.039), 0.055 kg/m 2 (95%IC: 0.018, 0.108; p = 0.043) and 0.070 kg/m 2 (95%IC: 0.006, 0.135; p = 0.032) BMI increase, respectively (Supplemental table 3). Discussion We aimed to estimate the association between changes in NEDF consumption and BMI change in school-age children. Over an average of 6.1 years of follow-up children increased their NEDF consumption by 225 kJ (53.9 kcal), yet, we did not observe an association between NEDF increases and BMI increase (0.033 kg/m2, [p = 0.246]). However, in fully adjusted models BMI increased 0.078 kg/m 2 for every 418.6 kJ/day (100 kcal/day) of sweet bakery products intake (p = 0.035). Increases in the consumption of chips and popcorn were associated with a 0.208 kg/m 2 increase in BMI in unadjusted models; however, this association was attenuated in fully-adjusted models. Changes in the consumption of other food groups within the NEDF classification did not show an association with changes in BMI. Few efforts have been made to estimate the association between NEDF consumption and weight in school-aged children. Some cross-sectional studies have described a positive association between NEDF and weight gain [ 12 , 39 ], however, the few longitudinal studies available have shown mixed results. In two studies, the first under five years of age and the second with a mean age of 16 years, children’s weight tended to decrease with higher levels of consumption of NEDF [ 19 , 20 ]. A positive association was observed in a study of 961 children 5 to 12 years of age, that defined dietary patterns rich in high-energy and low-nutrient-density foods as exposure [ 21 ] with 2.5 years follow-up. Similarly, Phillips, et al, found a non-significative result that children’s weight tend to increase with more joules (calories) from NEDF consumption in a cohort of 166 non-overweight school-aged girls followed for seven years [ 22 ], both of these cohort studies used mixed-effect models which can not control for time-invariant confounders as effectively as fixed effects models. Our study is unique in that we are assessing the impact of changes in NEDF consumption and changes in BMI; under this approach we did not detect an association between NEDF and BMI overall, but we did identify a significant association with the consumption of sweet bakery products. The association between sweet bakery product consumption and weight gain has been reported in two other prospective studies. Phillips et al. , in a girls’ cohort study with an average follow-up of seven years, found an increment of z-score in BMI (0.003; p = 0.11), with more intake of cookies, pies, cakes, brownies, chocolate candy, nonchocolate candy, ice cream, milkshakes sherbet, potato chips and corn chips [ 22 ]. The non-significant result for potato chips and popcorn un our study could be explained by a lack of power to detect the effect due to a small sample size and the small number of energy-dense foods included in the food frequency questionary. In the preset study we identified more than 90 different types of NEDF in children’s diet. Also, in a prospective cohort study with more than 120 thousand adults followed for 20 years the consumption of one serving of potato chips per day or refined grains (including sweet bakery products) was associated with increment in body weight of 0.77 kg and 0.25 kg in a 4-year period, to each food product, respectively [ 34 ]. Negative associations between chips and bakery and BMI have also been reported. Field et al ., in a cohort of children and adolescents with three years of follow-up found a reduction of 0.006 in BMI z-score (p < 0.05) among those eating energy-dense foods; however, this association became non-significant after adjusting for dieting status and maternal overweight [ 23 ]. In our study we found that eating ready-to-eat cereals was marginally associated with a BMI reduction of -0.098 kg/m 2 for every 418.6 kJ/day (100 kcal/day). Consumption of ready-to-eat cereals has been related to a healthy dietary pattern in children [ 40 ] and this include more consumption of vitamins and minerals, less of saturated fat and cholesterol, but also, with a higher intake of added sugar [ 40 , 41 ]. Negative associations between ready-to-eat cereals and BMI, have also been reported in longitudinal analyses [ 42 , 43 ]. However, ready-to-eat cereals comprises many different products, and their nutritional impact will depend on the composition of the cereal, and the food consumed with them (such as fruit or milk); our study, as well as all previous studies available could be confounded by these characteristics. Even though ready-to-eat cereals may be associated with weight lost in children, children consuming a non-high fiber cereal, had worse type 2 diabetes risk profile than children consuming a high fiber cereal in a longitudinal study [ 44 ]. There are three different explanations for the association between sweet bakery products consumption and weight gain. First, sweet bakery products tend to be high in added sugar, saturated fat and of course high quantities of energy in small portions of food [ 10 ] and may promote excess energy intake without control over the joules (calories) consumed. In a recent crossover trial, adults were randomized to receive an ultra-processed (generally energy-dense food) or unprocessed diet for a period of 2 weeks. Participants in the ultra-processed diet increased 0.8 kg and those in the unprocessed diet reduced 1.1 kg. Those in the ultra-processed diet consumed 2126 kJ/day (508 kcal/day) more than the other group, mainly by fats and carbohydrates [ 45 ]. Second, many sweet bakery products are high in refined carbohydrates and starches and may induce stronger insulin secretion. This promotes less satiating signals, increasing subsequent hunger feelings [ 46 ] and suppresses the release of fatty acids from adipose tissue into circulation, while keeping glucose and fatty acids away from the oxidation process to store them in the adipose tissue [ 47 ]. Third, a diet rich in energy-dense food is associated with less protein consumption in children and according with the “protein leverage hypothesis” this may be related to the disturbance of the appetite system through increased postprandial hunger and reduced postprandial satiety [ 48 ]. Strengths of this study include the prospective cohort design, including three measurements of anthropometric and dietary information, large sample size and the approach analysis with the possibility to assess the change in change effect. Our study also has some important limitations that must be taken into account to interpret our results. First, at each wave we had one dietary evaluation, instead of two or more 24-hour recalls, which may not reflect usual NEDF consumption. Second, we lost 14.1% of the sample in the first period and 29.3% in the second; however, baseline socioeconomic index, children sex at baseline, age and maternal education, and overweight status were no different between children lost and those who stayed in the cohort. In summary, our results showed that consumption of NEDF overall was not associated with BMI in children. However, NEDF subgroups such as sweet bakery products and, possibly, chips and popcorn, showed an association with BMI. The longer-term effect of NEDF consumption in school-aged children on BMI requires further studies with bigger samples, better follow-up, and the use of an objective measure of adipose tissue in order to obtain more reliable results. Decreasing the consumption of NEDF is a key step to improve dietary quality and prevent obesity, aligned with the WHO 25x25 goals [ 49 ] and the Sustainable Development Goals [ 50 ]. In Mexico, a strategy to reduce NEDF consumption is in place, limiting access to these foods in elementary schools [ 51 ], restricting food marketing to children on television and public areas [ 52 ], and implementing an 8% tax to all NEDF [ 31 ]. However, further public health efforts need to be directed to reduce the consumption of NEDF, particularly early on in life. Abbreviations BMI, body mass index; NEDF, nonessential energy-dense food; POSGRAD, Prenatal omega-3 fatty acid supplementation, child growth, and development; 24HR, 24-hour recall. Declarations AUTHOR CONTRIBUTIONS DI-Z conceived the design research, performed the computations and was the major contributor in writing the manuscript. BS, SG, MD and TB-G, assist the statistical analysis and contributed to writing the manuscript. BV-A, RS-I and RI contributed to the follow-up of the cohort and supervised the cleaning and processing data. RS-I derived the nonessential energy-dense food database. All authors read and approved the final manuscript. FUNDING Primary funding for the study came from the National Institute of Public Health and from National Institutes of Health Grant Number R01DK108148. COMPETING INTERESTS The authors declare that they have no competing interests. ETHICS APPROVAL AND CONSENT TO PARTICIPATE The protocol was approved by the Ethics, Biosafety, and Research Committees’ of the National Institute of Public Health of Mexico and the Emory University. Parental signed consent and children’s informed consent were obtained at each wave of the study. This investigation conformed to all principles outlined in the Declaration of Helsinki. ADDITIONAL INFORMATION Supplementary information, the online version contains supplementary material available at DATA AVAILABILITY STATEMENT The datasets used during the current study are available from the corresponding author on reasonable request. References Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766-81. Bentham J, Di Cesare M, Bilano V, Bixby H, Zhou B, Stevens GA, et al. Worldwide trends in body-mass index, underweight, overweight, and measurement studies in 128.9 million children, adolescents, and adults. Lancet. 2017;319:2627-42. Hernández-Cordero S, Cuevas-Nasu L, Morales-Ruán M, Humarán IM-G, Ávila-Arcos M, Rivera-Dommarco J. Overweight and obesity in Mexican children and adolescents during the last 25 years. Nutr Diabetes. 2017;7:e247. 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Ultra-processed food consumption and adiposity trajectories in a Brazilian cohort of adolescents: ELANA study. Nutr Diabetes. 2018;8:28. Durão C, Severo M, Oliveira A, Moreira P, Guerra A, Barros H, et al. Evaluating the effect of energy-dense foods consumption on preschool children’s body mass index: a prospective analysis from 2 to 4 years of age. . Eur J Nutr. 2015;54:835-43. Shroff MR, Perng W, Baylin A, Mora-Plazas M, Marin C, Villamor E. Adherence to a snacking dietary pattern and soda intake are related to the development of adiposity: a prospective study in school-age children. Public Health Nutr. 2014;17:1507-13. Phillips SM, Bandini LG, Naumova EN, Cyr H, Colclough S, Dietz WH, et al. Energy‐dense snack food intake in adolescence: longitudinal relationship to weight and fatness. . Obes Res. 2004;12:461-72. Field AE, Austin SB, Gillman MW, Rosner B, Rockett HR, Colditz GA. Snack food intake does not predict weight change among children and adolescents. Int J Obes. 2004;28:1210-16. Gonzalez-Casanova I, Stein AD, Hao W, Garcia-Feregrino R, Barraza-Villarreal A, Romieu I, et al. Prenatal Supplementation with Docosahexaenoic Acid Has No Effect on Growth through 60 Months of Age–3. J Nutr. 2015;145:1330-4. Lohman T, Roche A, Martorell R. Anthropometric Standardization Reference Manual Abridged Edition: Human Kinetics Books; 1991. Available from: http://books.google.com.mx/books?id=wgd9QgAACAAJ. World Health Organization. WHO AnthroPlus for personal computers manual: software for assessing growth of the world’s children and adolescents. Geneva: WHO. 2009). Available from: https://www.who.int/growthref/tools/en/. De Onis M. WHO child growth standards: Methods and development - Length/Height-for-age, Weight-for-age, Weight-for-length, Weight-for-height and Body mass index-for-age 2006). Available from: https://www.who.int/childgrowth/standards/Technical_report.pdf?ua=1. Angulo-Estrada JS, Espinosa-Montero J, Gaytan-Colin MA, González-de-Cossío-Martínez T, Gutiérrez JP, Barrera LH, et al. Programa de Cómputo: Rec24Hrs. 5 Pasos (R24H5). Cuernavaca, Morelos: Instituto Nacional de Salud Pública; 2013. Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am J Clin Nutr. 2003;77:1171-8. Ramírez Silva I, Barragán-Vázquez S, Rodríguez-Ramírez S, Rivera-Dommarco J, Mejía-Rodríguez F, Barquera-Cervera S, et al. Base de alimentos de México (BAM): Compilación de la composición de los alimentos frecuentemente consumidos en el país. 2019. Congreso de los Estados Unidos Mexicanos. Ley del Impuesto Especial sobre Producción y Servicios Mexico2014 [Available from: http://www.diputados.gob.mx/LeyesBiblio/pdf/78_241219.pdf. Bitok E, Sabate J. Nuts and Cardiovascular Disease. Prog Cardiovasc Dis. 2018;61:33-7. Kris-Etherton PM, Hu FB, Ros E, Sabaté J. The role of tree nuts and peanuts in the prevention of coronary heart disease: multiple potential mechanisms. J Nutr. 2008;138:1746S-51S. Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB. Changes in diet and lifestyle and long-term weight gain in women and men. . New Eng J Med. 2011;364:2392-404. Hernández B, Gortmaker SL, Laird NM, Colditz GA, Parra-Cabrera S, Peterson KE. Validez y reproducibilidad de un cuestionario de actividad e inactividad física para escolares de la ciudad de México. Salud Publica Mex. 2000;42:315-23. Singer JD, Willett JB. Applied longitudinal data analysis: Modeling change and event occurrence: Oxford university press; 2003. Hu FB, Stampfer MJ, Rimm E, Ascherio A, Rosner BA, Spiegelman D, et al. Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements. Am J Epidemiol. 1999;149:531-40. StataCorp L. Stata 13: College Station: StataCorp LP; 2014 [Available from: https://www.stata.com/company/. Juul F, Martinez-Steele E, Parekh N, Monteiro CA, Chang VW. Ultra-processed food consumption and excess weight among US adults. Br J Nutr. 2018;120:90-100. Priebe MG, McMonagle JR. Effects of ready-to-eat-cereals on key nutritional and health outcomes: A systematic review. PLoS One. 2016;11:e0164931. Michels N, De Henauw S, Beghin L, Cuenca-García M, Gonzalez-Gross M, Hallstrom L, et al. Ready-to-eat cereals improve nutrient, milk and fruit intake at breakfast in European adolescents. Eur J Nutr. 2016;55:771-9. Frantzen LB, Treviño RP, Echon RM, Garcia-Dominic O, DiMarco N. Association between frequency of ready-to-eat cereal consumption, nutrient intakes, and body mass index in fourth-to sixth-grade low-income minority children. J Acad Nutr Diet. 2013;113:511-9. Kuriyan R, Lokesh DP, D'souza N, Priscilla DJ, Peris CH, Selvam S, et al. Portion controlled ready-to-eat meal replacement is associated with short term weight loss: a randomised controlled trial. Asia Pac J Clin Nutr. 2017;26:1055- 65. Donin AS, Nightingale CM, Owen CG, Rudnicka AR, Perkin MR, Jebb SA, et al. Regular breakfast consumption and type 2 diabetes risk markers in 9-to 10-year-old children in the child heart and health study in England (CHASE): a cross-sectional analysis. PLoS medicine. 2014;11:e1001703. Hall KD. Ultra-processed diets cause excess calorie intake and weight gain: A one-month inpatient randomized controlled trial of ad libitum food intake. Cell Metab. 2019;30:67-77.e3. Bornet FR, Jardy-Gennetier A-E, Jacquet N, Stowell J. Glycaemic response to foods: impact on satiety and long-term weight regulation. Appetite. 2007;49:535-53. Hall KD. A review of the carbohydrate–insulin model of obesity. Eur J Clin Nutr. 2017;71:323-6. Simpson S, Raubenheimer D. Obesity: the protein leverage hypothesis. Obes Rev. 2005;6:133-42. World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013-2020. Geneva: World Health Organization. 2015. Buse K, Hawkes S. Health in the sustainable development goals: ready for a paradigm shift? Global Health. 2015;11:13. Secretaría de Salud. Acuerdo Nacional para la Salud Alimentaria. Estrategia contra el sobrepeso y la obesidad. México: Secretaría de Salud; 2010. Consejo de autoregulación y ética publicitariar. Código PABI. Código de autoregulación de publicidad de alimentos y bebidas no alcohólicas dirigida al público infantil. Ciudad de México: CONAR; 2012. 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In Mexico, the prevalence of obesity in school-aged children has increased rapidly from 9.0% in 1999 to 18.6% in 2021 [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Childhood obesity has been linked to lower quality of life, higher risk of non-communicable diseases in adulthood, such as hypertension, dyslipidemia, type-2 diabetes, and premature death [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The hypothesis is that a low-quality diet, rich in nonessential energy-dense food (NEDF), often termed \u0026ldquo;junk food\u0026rdquo;, \u0026ldquo;discretionary food\u0026rdquo; or \u0026ldquo;processed food\u0026rdquo;, is a key factor for weight gain and obesity [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. NEDF could be a critical risk factor for obesity in children and adolescents in Mexico as they displace healthy foods [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], are high in sugar, refined grains, unhealthy fats [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and have a high glycemic index [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNEDF consumption, defined in previous studies as energy-dense food without a cut-off point or \u0026gt;\u0026thinsp;13% of total energy from added sugars and/or saturated fat is high in Mexico, particularly among school-aged children living in big cities [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], who on average consume 21% of their total daily energy requirement from NEDF, with 50% of this consumed at school [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. School-aged children are particularly vulnerable to NEDF consumption due to targeted marketing and advertisement to young children as well as misleading nutritional information [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Increased access to NEDF in this age group was large due to high availability in elementary schools and school-aged children have not fully developed their cognitive capacity of resistance towards these foods, and are less able to avoid or reduce their consumption [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough NEDF might play a critical role as a risk factor for childhood obesity, due to their low diet quality and high intake among children, evidence of the effect of NEDF is limited. One of the main limitations is the lack of a consistent definition or classification of NEDF. Moreover, longitudinal studies of the effect of several NEDF classifications to weight gain in children are scarce and with mixed results [\u003cspan additionalcitationids=\"CR20 CR21 CR22\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Some of the limitations identified in those studies may be small samples sizes, short follow-ups, and limited information on changes in NEDF consumption over time, which could explain the lack of consistent findings. Further evidence on the potential link between NEDF consumption and weight gain in children is needed, to understand the impact of these food group in child wellbeing and health. Our aim was to estimate the longitudinal association of the change in NEDF consumption over time and changes in body mass index of school-aged children 5 to 11 years of age, using a cohort study with 6 years of follow-up.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eWe studied the offspring of women in the ongoing POSGRAD (Prenatal omega-3 fatty acid supplementation and child growth and development) study a double-blind, randomized, controlled trial in which women were supplemented with DHA or placebo from mid-pregnancy to parturition. The original study included 978 live births between June 2005 and June 2007 to 973 women who remained in the study as previously described [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Mother-child pairs have been followed prospectively. All children in the cohort had access to the Mexican Social Security Institute in Cuernavaca, Mexico, which provides services to formal employees and their families.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eStudy variables\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section4\"\u003e \u003ch2\u003eOutcome variables\u003c/h2\u003e \u003cp\u003eWeight and height were measured twice by trained personnel using standardized procedures [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; the average of both measurements was used. Weight with light clothes or a hospital gown was measured to the nearest of 100 g using a digital step-up scale (SECA 803). Height was measured without shoes, hat, hairclips, headbands or other items that could obstruct the procedure using a portable stadiometer (SECA 213). Then we obtained body mass index (weight\u003csub\u003e(kg)\u003c/sub\u003e/height\u003csub\u003e(mts)\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e, BMI) and calculated z-scores based on the WHO growth reference [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e\u003cem\u003eExposure variables\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eDietary intake was evaluated at the three waves. At baseline a 24-hour recall (24HR) questionnaire was applied by a trained interviewer to the person in the household who prepared the meals (frequently the mother); for waves 2 and 3 the same 24HR standardized method were applied but through an automated software previously used in a National Survey [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This is a method which capture more accurate information of the interviewees through 5 iterative steps that complement each other for memory improvement in food intake and thus, reducing under-reporting [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. During the interview, children participated in the report of their diet, complementing, and validating their mothers\u0026rsquo; report and in some cases adding missing food, correcting the size of a portion or removing the food reported by the adult. 24HR were performed from Sunday to Friday. To increase the accuracy of portions size, we used standardized food replicas, images of products, spoons, and cups of different sizes. Dietary information was collected as follows: 1) individual foods, 2) custom recipes (recipe reported and described in detail by the participant), and 3) standard recipes (set of ingredients in a documented and standard recipe when unknown to the subject). For our analysis all the recipes were disaggregated into their ingredients (with exception of beverages) to facilitate identifying all NEDF in recipes, (e.g. chips, puffed wheat snacks, candies, chocolate, sweets, others).\u003c/p\u003e \u003cp\u003eTo address outliers in food items, we identify those when the reported amount was \u0026gt;\u0026thinsp;4 SD from the mean for the same food and age group to minimize their influence in total diet and analysis. We identify less than 0.1% as outliers and were truncated at the highest value (median\u0026thinsp;+\u0026thinsp;four SD) to minimize their influence in total diet and analysis. We did not identify implausible reporters by using the ratio for total energy intake to estimated energy requirement out of the interval between \u0026minus;\u0026thinsp;3 and +\u0026thinsp;3 SD in each wave. After the first stage of data cleaning and processing, energy, nutrients and added sugar from food were obtained with the Mexican Food Database in its 18.1.1version that include 1978 different foods including standardized recipes, and labeling information from some processed products [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTotal NEDF was classified using the definition by the Ministry of Finance and Public Credit and Ministry of Health of Mexico in 2014 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], which considers two criteria: an energy density of \u0026gt;\u0026thinsp;1151 kJ/100g (275 kcal/100g) and to be classified as \"nonessential foods\u0026rdquo;. NEDF were classified in four groups according to nutrition composition and consumption patterns: 1) Chips and popcorn, 2) Sweet bakery products, 3) Non-cereal based sweets and, 4) Ready-to-eat cereals. Subgroups of these principal groups were constructed to obtain more homogenous groups as presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. We excluded salty seeds or other seed products from the first group because there is solid evidence that seeds are associated with weight lost and are considered a healthy food [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]; they were included in the tax because of their high sodium content but our outcome of interest was weight gain and not sodium-related outcomes. Also, we classified beverages into the following food groups: plain water, sugar-sweetened beverages (regular soda, homemade fruit water with added sugar, sweetened milk, coffee or tea with sugar, fruit drinks and sport beverages), 100%-fruit juice, and milk without sugar.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of nonessential energy dense food.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain groups of NEDF\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubgroups of NEDF\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFood examples\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChips and popcorn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFried potato, flour and corn chips, packaged fried pork skin, ready-to-eat popcorn, microwave popcorn.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSweet bakery products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhole grain with added sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBars, enriched bread and cookies made with whole grain flour but all with added sugar.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweet bread\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSweet cookies, sweet bread, energy bars and cereal bars.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePie and cakes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll kinds of pies and cakes.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNon-cereal based sweets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCocoa and other sweet products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCocoa, raisin, plum and legumes covered with chocolate and gums with or without sugar.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrawberry, vanilla or chocolate powder, condensed milk, fruit preserves, candies, marshmallows, jam, jellies, \u0026ldquo;dulce de leche\u0026rdquo; or \u0026ldquo;cajeta\u0026rdquo;, hazelnut spread, caramels, ice cream, ice-pops, popsicle.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReady-to-eat cereals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll the pre-prepared and ready-to-eat cereal with added sugar.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003eNEDF, Nonessential energy-dense food.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eA \u003cem\u003esocioeconomic index\u003c/em\u003e was calculated at baseline using a questionnaire administered to the head of household that included sanitation and household characteristics and assets. Using this information, we generated an index using principal components analysis. \u003cem\u003eMaternal BMI\u003c/em\u003e was calculated using measured weight and height; \u003cem\u003ematernal formal education\u003c/em\u003e was categorized as less than secondary school, secondary school, and high school or higher. \u003cem\u003eMarital status\u003c/em\u003e was categorized as single (single, separated, divorced or widower participants) and marriage or free union (participants in marriage or living together with a couple). \u003cem\u003eMaternal age\u003c/em\u003e was obtain using birth date, while children\u0026rsquo;s \u003cem\u003esex\u003c/em\u003e was obtained from the birth certificate.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePhysical activity and sedentary activities\u003c/em\u003e. Physical activity and sedentary activities were assessed at 7 and 11 years old, using a validated semi-quantitative questionary based on the Youth Activity Questionnaire developed and validated by Hern\u0026aacute;ndez et al [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Physical activity included: playing soccer, volleyball, cycling, skating or skateboarding, basketball, dancing, swimming, walking, taking care of pets, cleaning the house, playing games at home or in the school, among others. Sedentary activities included: time spend watching television, playing videogames, reading ,and doing homework and was defined using the time doing this activity during weekdays and weekends. Available responses included: \u0026ldquo;0 h\u0026rdquo;, \u0026ldquo;\u0026lt;0.5 h\u0026rdquo;, \u0026ldquo;0.5\u0026ndash;2 h\u0026rdquo;, \u0026ldquo;2\u0026ndash;4 h\u0026rdquo;, \u0026ldquo;4\u0026ndash;6 h\u0026rdquo;, \u0026ldquo;\u0026gt; 6 h\u0026rdquo; and responses were scored \u0026ldquo;0 h\u0026rdquo;, \u0026ldquo;0.25 h\u0026rdquo;, \u0026ldquo;1.25 h\u0026rdquo;, \u0026ldquo;3 h\u0026rdquo;, \u0026ldquo;5 h\u0026rdquo;, and \u0026ldquo;6 h\u0026rdquo;, respectively. Items from physical activity and sedentary activities were added to obtain the total minutes in a week and then per day.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003eChildren\u0026rsquo;s age and sex and mother\u0026rsquo;s age, education, marital status, and BMI were described at baseline. We evaluated trends across the three cohort waves using grams, joules (calories), percent total energy of NEDF and its subgroups and for BMI. As physical activity and sedentary behavior was just measure at 7 and 11 years, we assumed no change from 5 to 7 years old, imputing for age 5 the same values of age 7. Then we test for trend for dietetic, anthropometric and physical activity variables across 5, 7 and 11 years using an extension of the Wilcoxon rank-sum test created for this purpose. Fixed effect models were used to assess the association between within-individual change in NEDF consumption and the change in BMI. Fixed effect models considered the nesting structure of data waves nested within children, using age as time of observation [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Energy from NEDF and its subgroups was rescaled to produce coefficients relative to 418.6 kJ (100 kcal) change. We ran three different models for each main exposure variable. The first model was unadjusted, the second model was controlled by change in joules different from the main exposure (joules/day) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and the third was adjusted by model 2, plus change in physical activity (min/day) and change in tv watching (min/day).\u003c/p\u003e \u003cp\u003eSome sensitivity analyses were performed to assess the robustness of the results. First, in the fixed effect model we changed the adjustment of change in energy different from NEDF for those dietary groups that are closely related with change of BMI, like sugar-sweeten beverages, 100% fruit juice, milk, fruits, dairy food, meat and eggs and processed meet. Second, we left the raw value of the detected dietary outliers to understand their influence in our results. Finally, we changed our model from fixed to a random effects model to estimate the association between BMI and NEDF consumption using the confounders that change in time and without changing in time. All statistical analyses were performed in STATA\u0026reg; Version 13 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe baseline wave was conducted when children were 5 years old (between 2010 and 2011), with the first follow-up at 7 years (between 2012 and 2013) and second at 11 years (between 2015 and 2016). The study sample consisted of 797 at baseline, 682 at 7 years and 439 at 11 years old. Reasons for follow-up losses are presented in the flowchart (Fig.\u0026nbsp;1). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the characteristics of children and their mothers participating in our study. At baseline there were 797 children and 47% were female. Of them, 85.9% were followed to second (7 years) and 70.7% to the third wave (11 years). Children\u0026rsquo;s mothers were on average 31.4 years old and majority of them (78.7%) had less than high school, were not single, and overweight.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive characteristics of children and their mothers in the POSGRAD\u003csup\u003e1\u003c/sup\u003e study at baseline.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline (n\u0026thinsp;=\u0026thinsp;797)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildren age (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChildren sex (n/%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e424 (53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e373 (47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's age (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's education (n/%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLess than secondary school\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e303 (38.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSecondary and high school\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e323 (40.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMore than high school\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170 (21.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's civil status (n/%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (9.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried or free union\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e725 (91.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMother's BMI (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.15\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight (n/%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e342 (42.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight or obese (n/%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e455 (57.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003cb\u003ePOSGRAD\u003c/b\u003e, Prenatal omega-3 fatty acid supplementation and child growth and development.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSD, standar deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eChildren contributed with 1885 data points, which represents and average of 2.4 visits per child over a mean of 6.1 years of follow-up. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the longitudinal change in body weight, BMI, other anthropometric and physical indicators. Mean BMI increased in the first period 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46 kg/m\u003csup\u003e2\u003c/sup\u003e and 4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9 kg/m\u003csup\u003e2\u003c/sup\u003e in the second; this represents an increase of 0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96 in BMI z-score and 24.2% increase in the proportion of overweight and obesity from baseline to the third wave.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean change in anthropometric measurements, nutritional status and physical activity in children from baseline to 7 and 11 years old.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e∆ from baseline to\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline (n\u0026thinsp;=\u0026thinsp;797)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 years (n\u0026thinsp;=\u0026thinsp;682)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 years (n\u0026thinsp;=\u0026thinsp;439)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeight (kg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.46\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeight (cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeight for age, z score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass index for age\u003c/b\u003e, \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ez\u003c/span\u003e\u003cb\u003escore\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight (n/%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (3.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight (n/%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e639 (80.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e465 (68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e335 (53.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight (n/%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (24.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity (n/%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81 (18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity (min/day)\u003c/b\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.9\u0026thinsp;\u0026plusmn;\u0026thinsp;46.3\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;57.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal sedentary activities (min/day)\u003c/b\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e252.4\u0026thinsp;\u0026plusmn;\u0026thinsp;104.8\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.25\u0026thinsp;\u0026plusmn;\u0026thinsp;143.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115.5\u0026thinsp;\u0026plusmn;\u0026thinsp;65.4\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-16.5\u0026thinsp;\u0026plusmn;\u0026thinsp;82.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther sedentary activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137.02\u0026thinsp;\u0026plusmn;\u0026thinsp;68.6\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.8\u0026thinsp;\u0026plusmn;\u0026thinsp;110.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eResults are presented in means change and standard deviation, unless it specifies different.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e1\u003c/sup\u003en=677 at 7 years and n\u0026thinsp;=\u0026thinsp;399 at 11 years old.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eND, No data.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eTest for trend across 5, 7 and 11 years old.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e2\u003c/sup\u003e p value\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMean total caloric intake at baseline was 6086.4 kJ (1454 kcal), 19.6% of those joules were NEDF. At baseline 95% of children consumed NEDF in the previous day of assessment, 92% by age 7, and 88% by age 11 (data not shown). At baseline, beverage energy intake represented 20% of the total caloric intake; 5.6% of milk, 14.2% of sugar sweetened beverages and a minimal proportion from juice, tea without sugar and other beverages (Supplemental table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents baseline and change levels of NEDFL consumption in joules (calories), grams and percentage of total energy consumption to 7 and 11 years old. All sweet bakery products, especially sweet bread, were the main contributors to NEDF with 644 kJ/day (154 kcal/day) (10.5% of total caloric intake). Non-cereal based sweets, ready-to-eat cereals, and chips and popcorn represented a total caloric intake of 3.8%, 3.1% and 2.1%, respectively. On average, the amount of NEDF consumption increased 113\u0026thinsp;\u0026plusmn;\u0026thinsp;1289 kJ/day (27\u0026thinsp;\u0026plusmn;\u0026thinsp;308 kcal/day) from baseline to the first wave and 226\u0026thinsp;\u0026plusmn;\u0026thinsp;1536 kJ (54\u0026thinsp;\u0026plusmn;\u0026thinsp;367 kcal/day) from baseline to the second wave (p\u0026thinsp;=\u0026thinsp;0.034); nevertheless, total caloric intake decreased by 2.3 and 3.1 percent points, respectively. In all NEDF groups and subgroups, except for ready-to-eat cereals, the amount in grams and caloric intake increased from 5 to 11 years, yet, as a percent of total energy the change was either negative or null. Consumption of chips and popcorn increased in joules [∆ 98 kj/day (∆ 23.4 kcal/day)] and percent total energy (∆ 0.7 pp/wave) from 5 to 11 years old. Sweet bakery consumption increased on average 54\u0026thinsp;\u0026plusmn;\u0026thinsp;1050 kJ (13\u0026thinsp;\u0026plusmn;\u0026thinsp;251 kcal) in first period and 129\u0026thinsp;\u0026plusmn;\u0026thinsp;1213 kJ (31\u0026thinsp;\u0026plusmn;\u0026thinsp;290 kcal) in the second, mainly due to sweet bread.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean change in grams, joules (calories) and percentage of total calorie intake of nonessential and energy-dense food from baseline to 7 and 11 years old.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c12\" namest=\"c6\"\u003e \u003cp\u003e∆ from baseline to\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBaseline (n\u0026thinsp;=\u0026thinsp;797)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e7 years (n\u0026thinsp;=\u0026thinsp;682)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003e11 years (n\u0026thinsp;=\u0026thinsp;439)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekJ (kcal)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eptec\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e∆ g\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e∆ kJ\u003c/p\u003e \u003cp\u003e(kcal)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e∆ ptec\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e∆ g\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e∆ kJ\u003c/p\u003e \u003cp\u003e(kcal)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e∆ ptec\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal NEDF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e73\u0026thinsp;\u0026plusmn;\u0026thinsp;58\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1188\u0026thinsp;\u0026plusmn;\u0026thinsp;925 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(284\u0026thinsp;\u0026plusmn;\u0026thinsp;221)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e19.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e111\u0026thinsp;\u0026plusmn;\u0026thinsp;1289\u003c/p\u003e \u003cp\u003e(26.6\u0026thinsp;\u0026plusmn;\u0026thinsp;308)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e225\u0026thinsp;\u0026plusmn;\u0026thinsp;1536\u003c/p\u003e \u003cp\u003e(53.9\u0026thinsp;\u0026plusmn;\u0026thinsp;367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChips and ready-to-eat popcorn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133\u0026thinsp;\u0026plusmn;\u0026thinsp;293 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(32\u0026thinsp;\u0026plusmn;\u0026thinsp;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;468\u003c/p\u003e \u003cp\u003e(5.9\u0026thinsp;\u0026plusmn;\u0026thinsp;112)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e97\u0026thinsp;\u0026plusmn;\u0026thinsp;514\u003c/p\u003e \u003cp\u003e(23.4\u0026thinsp;\u0026plusmn;\u0026thinsp;123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSweet bakery products\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e644\u0026thinsp;\u0026plusmn;\u0026thinsp;732\u003c/p\u003e \u003cp\u003e(154\u0026thinsp;\u0026plusmn;\u0026thinsp;175)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e10.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;1054\u003c/p\u003e \u003cp\u003e(12.8\u0026thinsp;\u0026plusmn;\u0026thinsp;252)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e128\u0026thinsp;\u0026plusmn;\u0026thinsp;1218\u003c/p\u003e \u003cp\u003e(30.8\u0026thinsp;\u0026plusmn;\u0026thinsp;291)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhole-cereal with sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87\u0026thinsp;\u0026plusmn;\u0026thinsp;246\u003c/p\u003e \u003cp\u003e(21\u0026thinsp;\u0026plusmn;\u0026thinsp;59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;346\u003c/p\u003e \u003cp\u003e(3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;82.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;493\u003c/p\u003e \u003cp\u003e(5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSweet bread\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e418.6\u0026thinsp;\u0026plusmn;\u0026thinsp;623\u003c/p\u003e \u003cp\u003e(100\u0026thinsp;\u0026plusmn;\u0026thinsp;149)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95\u0026thinsp;\u0026plusmn;\u0026thinsp;895\u003c/p\u003e \u003cp\u003e(22.7\u0026thinsp;\u0026plusmn;\u0026thinsp;214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e84\u0026thinsp;\u0026plusmn;\u0026thinsp;866\u003c/p\u003e \u003cp\u003e(20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;207)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCake, pie and others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138\u0026thinsp;\u0026plusmn;\u0026thinsp;422\u003c/p\u003e \u003cp\u003e(33\u0026thinsp;\u0026plusmn;\u0026thinsp;101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e-4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-52\u0026thinsp;\u0026plusmn;\u0026thinsp;632\u003c/p\u003e \u003cp\u003e(-12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;151)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;799\u003c/p\u003e \u003cp\u003e(5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-cereal based sweets\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226\u0026thinsp;\u0026plusmn;\u0026thinsp;309 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(54\u0026thinsp;\u0026plusmn;\u0026thinsp;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;481\u003c/p\u003e \u003cp\u003e(1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;539\u003c/p\u003e \u003cp\u003e(8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCocoa and legumes with sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;20 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e-0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1\u0026thinsp;\u0026plusmn;\u0026thinsp;46\u003c/p\u003e \u003cp\u003e(-0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;108\u003c/p\u003e \u003cp\u003e(0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSweets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226\u0026thinsp;\u0026plusmn;\u0026thinsp;305 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(54\u0026thinsp;\u0026plusmn;\u0026thinsp;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;481\u003c/p\u003e \u003cp\u003e(1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;531\u003c/p\u003e \u003cp\u003e(7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;127)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReady-to-eat cereals\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;24\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179\u0026thinsp;\u0026plusmn;\u0026thinsp;376 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(43\u0026thinsp;\u0026plusmn;\u0026thinsp;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3 \u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;602\u003c/p\u003e \u003cp\u003e(6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e-0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c10\"\u003e \u003cp\u003e-2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-36\u0026thinsp;\u0026plusmn;\u0026thinsp;544\u003c/p\u003e \u003cp\u003e(-8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;130)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c12\"\u003e \u003cp\u003e-1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eResults are presented in means change and standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eTest for trend across 5, 7 and 11 years old.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003e1\u003c/sup\u003e ptec: percentage of total energy consumption.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003e2\u003c/sup\u003ep value\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003e3\u003c/sup\u003e p value\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e includes the unadjusted and adjusted association between BMI change and NEDF change. In the fully adjusted model, the increase in 418.6 kJ/day (100 kcal/day) in total NEDF was associated with a 0.033 kg/m\u003csup\u003e2\u003c/sup\u003e increase in children\u0026rsquo;s BMI (95% CI: -0.023, 0.090; p\u0026thinsp;=\u0026thinsp;0.246). The effect across NEDF subgroups was heterogeneous. The effect between sweet bakery products and BMI was 0.061 kg/m\u003csup\u003e2\u003c/sup\u003e in the unadjusted model (95%CI: -0.012, 0.135, p\u0026thinsp;=\u0026thinsp;0.102), increasing to 0.078 kg/m\u003csup\u003e2\u003c/sup\u003e in the fully adjusted model (95%IC: 0.005, 0.151; p\u0026thinsp;=\u0026thinsp;0.035). In the stratified subgroups of sweet bakery products, 418.6 kJ/day (100kcal/day) increase of whole grain bread with added sugar (-0.176 kg/m\u003csup\u003e2\u003c/sup\u003e [95%IC: -0.394, 0.041; p\u0026thinsp;=\u0026thinsp;0.113]) and cake and pie consumption (0.050 kg/m\u003csup\u003e2\u003c/sup\u003e [95%IC: -0.061, 0.162; p\u0026thinsp;=\u0026thinsp;0.375]) were in the expected direction, although not statistically significant. But 418.6 kJ/day (100 kcal/day) increase in sweet bread was associated with a 0.127 kg/m\u003csup\u003e2\u003c/sup\u003e BMI increase (95%IC: 0.036, 0.218; p\u0026thinsp;=\u0026thinsp;0.006). Also, in the unadjusted model, 418.6 kJ/day (100kcal/day) increase in chips and popcorn intake was associated with a 0.208 kg/m\u003csup\u003e2\u003c/sup\u003e BMI increase (95%IC: 0.036, 0.380; p\u0026thinsp;=\u0026thinsp;0.017), being attenuated in the fully adjusted model (0.086 kg/m\u003csup\u003e2\u003c/sup\u003e [95%IC: -0.078, 0.252; p\u0026thinsp;=\u0026thinsp;0.303]). Coefficients for association between consumption of non-cereal based sweets and ready-to-eat cereals were negatively associated with children\u0026rsquo;s BMI. Non-cereal based sweets consumption was not significantly associated even in the stratified subgroups of cocoa and other sweets. Ready-to-eat cereals in the unadjusted model was inverse associated with BMI (-0.095 [95%CI: -0.305, -0.152]; p\u0026thinsp;=\u0026thinsp;0.030) but after dietary and physical activity adjustment the coefficient went lower and p value lost its significance (-0.095 [95%CI: -0.233, 0.043] p\u0026thinsp;=\u0026thinsp;0.178).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean change in body mass index associated with total change consumption of NEDF and its subgroups in school age children from 5 to 11 years old.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain exposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eTotal NEDF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.018, 0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.025, 0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.023, 0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eChips and popcorn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036, 0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.005, 0.325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.078, 0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSweet bakery products\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.012, 0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.010, 0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005, 0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eWhole-grain with added sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.252, 0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.365, 0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.394, 0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSweet bread\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.017, 0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.032, 0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036, 0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePie and cakes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.109, 0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.086, 0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.061, 0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eNon-cereal based sweets\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.129, 0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.170, 0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.181, 0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCocoa and other sweet products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.296, 1.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.314. 1.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.284,1.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSweets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.133, 0.1912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.172, 0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.183, 0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eReady-to-eat cereals\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.305, -0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.247, 0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.233, 0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNEDF, nonessential and energy-dense food. Coefficients are presented in units of change of 418.6 kJ/ (100 kcal/day).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eFixed effects models: Model 1 (n\u0026thinsp;=\u0026thinsp;724), unadjusted; Model 2 (n\u0026thinsp;=\u0026thinsp;724): adjusted by change in joules different from the main exposure [kJ/day (kcal/day)); Model 3 (n\u0026thinsp;=\u0026thinsp;602): adjusted by model 2\u0026thinsp;+\u0026thinsp;change in physical activity (min/day) and change in tv watching (min/day).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn further sensitivity analyses, adjustment for those dietary groups that are closely related with change of BMI (Supplemental table 2) and not truncating outlier truncation, did not change results of the models. In the random effect analysis, we found a similar pattern of association, with weaker coefficients for most of the outcomes. Chips and popcorn, sweet bakery products and sweet bread were associated for each 418.6 kJ/day (100kcal/day) increase in consumption with a 0.128 kg/m\u003csup\u003e2\u003c/sup\u003e (95%IC: 0.006, 0.250; p\u0026thinsp;=\u0026thinsp;0.039), 0.055 kg/m\u003csup\u003e2\u003c/sup\u003e (95%IC: 0.018, 0.108; p\u0026thinsp;=\u0026thinsp;0.043) and 0.070 kg/m\u003csup\u003e2\u003c/sup\u003e (95%IC: 0.006, 0.135; p\u0026thinsp;=\u0026thinsp;0.032) BMI increase, respectively (Supplemental table 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe aimed to estimate the association between changes in NEDF consumption and BMI change in school-age children. Over an average of 6.1 years of follow-up children increased their NEDF consumption by 225 kJ (53.9 kcal), yet, we did not observe an association between NEDF increases and BMI increase (0.033 kg/m2, [p\u0026thinsp;=\u0026thinsp;0.246]). However, in fully adjusted models BMI increased 0.078 kg/m\u003csup\u003e2\u003c/sup\u003e for every 418.6 kJ/day (100 kcal/day) of sweet bakery products intake (p\u0026thinsp;=\u0026thinsp;0.035). Increases in the consumption of chips and popcorn were associated with a 0.208 kg/m\u003csup\u003e2\u003c/sup\u003e increase in BMI in unadjusted models; however, this association was attenuated in fully-adjusted models. Changes in the consumption of other food groups within the NEDF classification did not show an association with changes in BMI.\u003c/p\u003e \u003cp\u003eFew efforts have been made to estimate the association between NEDF consumption and weight in school-aged children. Some cross-sectional studies have described a positive association between NEDF and weight gain [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], however, the few longitudinal studies available have shown mixed results. In two studies, the first under five years of age and the second with a mean age of 16 years, children\u0026rsquo;s weight tended to decrease with higher levels of consumption of NEDF [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A positive association was observed in a study of 961 children 5 to 12 years of age, that defined dietary patterns rich in high-energy and low-nutrient-density foods as exposure [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] with 2.5 years follow-up. Similarly, Phillips, et al, found a non-significative result that children\u0026rsquo;s weight tend to increase with more joules (calories) from NEDF consumption in a cohort of 166 non-overweight school-aged girls followed for seven years [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], both of these cohort studies used mixed-effect models which can not control for time-invariant confounders as effectively as fixed effects models. Our study is unique in that we are assessing the impact of changes in NEDF consumption and changes in BMI; under this approach we did not detect an association between NEDF and BMI overall, but we did identify a significant association with the consumption of sweet bakery products.\u003c/p\u003e \u003cp\u003eThe association between sweet bakery product consumption and weight gain has been reported in two other prospective studies. Phillips \u003cem\u003eet al.\u003c/em\u003e, in a girls\u0026rsquo; cohort study with an average follow-up of seven years, found an increment of z-score in BMI (0.003; p\u0026thinsp;=\u0026thinsp;0.11), with more intake of cookies, pies, cakes, brownies, chocolate candy, nonchocolate candy, ice cream, milkshakes sherbet, potato chips and corn chips [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The non-significant result for potato chips and popcorn un our study could be explained by a lack of power to detect the effect due to a small sample size and the small number of energy-dense foods included in the food frequency questionary. In the preset study we identified more than 90 different types of NEDF in children\u0026rsquo;s diet. Also, in a prospective cohort study with more than 120 thousand adults followed for 20 years the consumption of one serving of potato chips per day or refined grains (including sweet bakery products) was associated with increment in body weight of 0.77 kg and 0.25 kg in a 4-year period, to each food product, respectively [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Negative associations between chips and bakery and BMI have also been reported. Field \u003cem\u003eet al\u003c/em\u003e., in a cohort of children and adolescents with three years of follow-up found a reduction of 0.006 in BMI z-score (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among those eating energy-dense foods; however, this association became non-significant after adjusting for dieting status and maternal overweight [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study we found that eating ready-to-eat cereals was marginally associated with a BMI reduction of -0.098 kg/m\u003csup\u003e2\u003c/sup\u003e for every 418.6 kJ/day (100 kcal/day). Consumption of ready-to-eat cereals has been related to a healthy dietary pattern in children [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and this include more consumption of vitamins and minerals, less of saturated fat and cholesterol, but also, with a higher intake of added sugar [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Negative associations between ready-to-eat cereals and BMI, have also been reported in longitudinal analyses [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, ready-to-eat cereals comprises many different products, and their nutritional impact will depend on the composition of the cereal, and the food consumed with them (such as fruit or milk); our study, as well as all previous studies available could be confounded by these characteristics. Even though ready-to-eat cereals may be associated with weight lost in children, children consuming a non-high fiber cereal, had worse type 2 diabetes risk profile than children consuming a high fiber cereal in a longitudinal study [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are three different explanations for the association between sweet bakery products consumption and weight gain. First, sweet bakery products tend to be high in added sugar, saturated fat and of course high quantities of energy in small portions of food [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and may promote excess energy intake without control over the joules (calories) consumed. In a recent crossover trial, adults were randomized to receive an ultra-processed (generally energy-dense food) or unprocessed diet for a period of 2 weeks. Participants in the ultra-processed diet increased 0.8 kg and those in the unprocessed diet reduced 1.1 kg. Those in the ultra-processed diet consumed 2126 kJ/day (508 kcal/day) more than the other group, mainly by fats and carbohydrates [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Second, many sweet bakery products are high in refined carbohydrates and starches and may induce stronger insulin secretion. This promotes less satiating signals, increasing subsequent hunger feelings [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and suppresses the release of fatty acids from adipose tissue into circulation, while keeping glucose and fatty acids away from the oxidation process to store them in the adipose tissue [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Third, a diet rich in energy-dense food is associated with less protein consumption in children and according with the \u0026ldquo;protein leverage hypothesis\u0026rdquo; this may be related to the disturbance of the appetite system through increased postprandial hunger and reduced postprandial satiety [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStrengths of this study include the prospective cohort design, including three measurements of anthropometric and dietary information, large sample size and the approach analysis with the possibility to assess the change in change effect. Our study also has some important limitations that must be taken into account to interpret our results. First, at each wave we had one dietary evaluation, instead of two or more 24-hour recalls, which may not reflect usual NEDF consumption. Second, we lost 14.1% of the sample in the first period and 29.3% in the second; however, baseline socioeconomic index, children sex at baseline, age and maternal education, and overweight status were no different between children lost and those who stayed in the cohort.\u003c/p\u003e \u003cp\u003eIn summary, our results showed that consumption of NEDF overall was not associated with BMI in children. However, NEDF subgroups such as sweet bakery products and, possibly, chips and popcorn, showed an association with BMI. The longer-term effect of NEDF consumption in school-aged children on BMI requires further studies with bigger samples, better follow-up, and the use of an objective measure of adipose tissue in order to obtain more reliable results. Decreasing the consumption of NEDF is a key step to improve dietary quality and prevent obesity, aligned with the WHO 25x25 goals [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and the Sustainable Development Goals [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In Mexico, a strategy to reduce NEDF consumption is in place, limiting access to these foods in elementary schools [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], restricting food marketing to children on television and public areas [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], and implementing an 8% tax to all NEDF [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, further public health efforts need to be directed to reduce the consumption of NEDF, particularly early on in life.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI, body mass index; NEDF, nonessential energy-dense food; POSGRAD, Prenatal omega-3 fatty acid supplementation, child growth, and development; 24HR, 24-hour recall.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDI-Z conceived the design research, performed the computations and was the major contributor in writing the manuscript. BS, SG, MD and TB-G, assist the statistical analysis and contributed to writing the manuscript. BV-A, RS-I and RI contributed to the follow-up of the cohort and supervised the cleaning and processing data. RS-I derived the\u0026nbsp;nonessential energy-dense food database. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrimary funding for the study came from the National Institute of Public Health and from \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNational Institutes of Health\u0026nbsp;Grant Number R01DK108148.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS APPROVAL AND CONSENT TO PARTICIPATE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe protocol was approved by the Ethics, Biosafety, and Research Committees\u0026rsquo; of the National Institute of Public Health of Mexico and the Emory University. Parental signed consent and children\u0026rsquo;s informed consent were obtained at each wave of the study. This investigation conformed to all principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eADDITIONAL INFORMATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary information,\u003c/strong\u003e the online version contains supplementary material available at\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNg M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980\u0026ndash;2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766-81.\u003c/li\u003e\n\u003cli\u003eBentham J, Di Cesare M, Bilano V, Bixby H, Zhou B, Stevens GA, et al. Worldwide trends in body-mass index, underweight, overweight, and measurement studies in 128.9 million children, adolescents, and adults. Lancet. 2017;319:2627-42.\u003c/li\u003e\n\u003cli\u003eHern\u0026aacute;ndez-Cordero S, Cuevas-Nasu L, Morales-Ru\u0026aacute;n M, Humar\u0026aacute;n IM-G, \u0026Aacute;vila-Arcos M, Rivera-Dommarco J. Overweight and obesity in Mexican children and adolescents during the last 25 years. Nutr Diabetes. 2017;7:e247.\u003c/li\u003e\n\u003cli\u003eShamah-Levy T, Romero-Mart\u0026iacute;nez M, Barrientos-Guti\u0026eacute;rrez T, Cuevas-Nasu L, Bautista-Arredondo S, Colchero M, et al. Encuesta Nacional de Salud y Nutrici\u0026oacute;n 2021 sobre Covid-19. Resultados nacionales. Cuernavaca, M\u0026eacute;xico: Instituto Nacional de Salud P\u0026uacute;blica; 2022.\u003c/li\u003e\n\u003cli\u003eFranks PW, Hanson RL, Knowler WC, Sievers ML, Bennett PH, Looker HC. Childhood obesity, other cardiovascular risk factors, and premature death. New Eng J Med. 2010;362:485-93.\u003c/li\u003e\n\u003cli\u003eDwyer J. Starting down the right path: nutrition connections with chronic diseases of later life. Am J Clin Nutr. 2006;83:415S-20S.\u003c/li\u003e\n\u003cli\u003eHalldorsson TI, Gunnarsdottir I, Birgisdottir BE, Gudnason V, Aspelund T, Thorsdottir I. Childhood Growth and Adult Hypertension in a Population of High Birth Weight. Hypertension. 2011;58:8-15.\u003c/li\u003e\n\u003cli\u003eReilly JJ, Kelly J. Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review. Int J Obes (Lond). 2011;35:891-8.\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-Pimienta TG, Batis C, Lutter CK, Rivera JA. 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Adherence to a snacking dietary pattern and soda intake are related to the development of adiposity: a prospective study in school-age children. Public Health Nutr. 2014;17:1507-13.\u003c/li\u003e\n\u003cli\u003ePhillips SM, Bandini LG, Naumova EN, Cyr H, Colclough S, Dietz WH, et al. Energy‐dense snack food intake in adolescence: longitudinal relationship to weight and fatness. . Obes Res. 2004;12:461-72.\u003c/li\u003e\n\u003cli\u003eField AE, Austin SB, Gillman MW, Rosner B, Rockett HR, Colditz GA. Snack food intake does not predict weight change among children and adolescents. Int J Obes. 2004;28:1210-16.\u003c/li\u003e\n\u003cli\u003eGonzalez-Casanova I, Stein AD, Hao W, Garcia-Feregrino R, Barraza-Villarreal A, Romieu I, et al. Prenatal Supplementation with Docosahexaenoic Acid Has No Effect on Growth through 60 Months of Age\u0026ndash;3. J Nutr. 2015;145:1330-4.\u003c/li\u003e\n\u003cli\u003eLohman T, Roche A, Martorell R. 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Salud Publica Mex. 2000;42:315-23.\u003c/li\u003e\n\u003cli\u003eSinger JD, Willett JB. Applied longitudinal data analysis: Modeling change and event occurrence: Oxford university press; 2003.\u003c/li\u003e\n\u003cli\u003eHu FB, Stampfer MJ, Rimm E, Ascherio A, Rosner BA, Spiegelman D, et al. Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements. Am J Epidemiol. 1999;149:531-40.\u003c/li\u003e\n\u003cli\u003eStataCorp L. Stata 13: College Station: StataCorp LP; 2014 [Available from: https://www.stata.com/company/.\u003c/li\u003e\n\u003cli\u003eJuul F, Martinez-Steele E, Parekh N, Monteiro CA, Chang VW. Ultra-processed food consumption and excess weight among US adults. Br J Nutr. 2018;120:90-100.\u003c/li\u003e\n\u003cli\u003ePriebe MG, McMonagle JR. Effects of ready-to-eat-cereals on key nutritional and health outcomes: A systematic review. PLoS One. 2016;11:e0164931.\u003c/li\u003e\n\u003cli\u003eMichels N, De Henauw S, Beghin L, Cuenca-Garc\u0026iacute;a M, Gonzalez-Gross M, Hallstrom L, et al. Ready-to-eat cereals improve nutrient, milk and fruit intake at breakfast in European adolescents. Eur J Nutr. 2016;55:771-9.\u003c/li\u003e\n\u003cli\u003eFrantzen LB, Trevi\u0026ntilde;o RP, Echon RM, Garcia-Dominic O, DiMarco N. Association between frequency of ready-to-eat cereal consumption, nutrient intakes, and body mass index in fourth-to sixth-grade low-income minority children. J Acad Nutr Diet. 2013;113:511-9.\u003c/li\u003e\n\u003cli\u003eKuriyan R, Lokesh DP, D\u0026apos;souza N, Priscilla DJ, Peris CH, Selvam S, et al. Portion controlled ready-to-eat meal replacement is associated with short term weight loss: a randomised controlled trial. Asia Pac J Clin Nutr. 2017;26:1055- 65.\u003c/li\u003e\n\u003cli\u003eDonin AS, Nightingale CM, Owen CG, Rudnicka AR, Perkin MR, Jebb SA, et al. Regular breakfast consumption and type 2 diabetes risk markers in 9-to 10-year-old children in the child heart and health study in England (CHASE): a cross-sectional analysis. PLoS medicine. 2014;11:e1001703.\u003c/li\u003e\n\u003cli\u003eHall KD. Ultra-processed diets cause excess calorie intake and weight gain: A one-month inpatient randomized controlled trial of ad libitum food intake. Cell Metab. 2019;30:67-77.e3.\u003c/li\u003e\n\u003cli\u003eBornet FR, Jardy-Gennetier A-E, Jacquet N, Stowell J. Glycaemic response to foods: impact on satiety and long-term weight regulation. Appetite. 2007;49:535-53.\u003c/li\u003e\n\u003cli\u003eHall KD. A review of the carbohydrate\u0026ndash;insulin model of obesity. Eur J Clin Nutr. 2017;71:323-6.\u003c/li\u003e\n\u003cli\u003eSimpson S, Raubenheimer D. Obesity: the protein leverage hypothesis. Obes Rev. 2005;6:133-42.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013-2020. Geneva: World Health Organization. 2015.\u003c/li\u003e\n\u003cli\u003eBuse K, Hawkes S. Health in the sustainable development goals: ready for a paradigm shift? Global Health. 2015;11:13.\u003c/li\u003e\n\u003cli\u003eSecretar\u0026iacute;a de Salud. Acuerdo Nacional para la Salud Alimentaria. Estrategia contra el sobrepeso y la obesidad. M\u0026eacute;xico: Secretar\u0026iacute;a de Salud; 2010.\u003c/li\u003e\n\u003cli\u003eConsejo de autoregulaci\u0026oacute;n y \u0026eacute;tica publicitariar. C\u0026oacute;digo PABI. C\u0026oacute;digo de autoregulaci\u0026oacute;n de publicidad de alimentos y bebidas no alcoh\u0026oacute;licas dirigida al p\u0026uacute;blico infantil. Ciudad de M\u0026eacute;xico: CONAR; 2012.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-obesity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ijo","sideBox":"Learn more about [International Journal of Obesity](http://www.nature.com/ijo/)","snPcode":"41366","submissionUrl":"https://mts-ijo.nature.com/cgi-bin/main.plex","title":"International Journal of Obesity","twitterHandle":"@intjobesity","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-2833950/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2833950/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBACKGROUND/OBJECTIVES: \u003c/strong\u003eObesity prevalence in Mexican children has increased rapidly and is among the highest in the world. We aimed to estimate the longitudinal association between nonessential energy-dense food (NEDF) consumption and body mass index (BMI) in school-aged children 5 to 11 years, using a cohort study with 6 years of follow-up.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSUBJECTS/METHODS: \u003c/strong\u003eWe studied the offspring of women in the Prenatal omega-3 fatty acid supplementation, child growth, and development (POSGRAD) cohort study. NEDF were classified into four main groups: chips and popcorn, sweet bakery products, non-cereal based sweets, and ready-to-eat cereals. We fitted fixed effects models to assess the association between change in 418.6 kJ (100 kcal) of NEDF consumption and changes in BMI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRESULTS: \u003c/strong\u003eBetween 5 and 11 years, children increased their consumption of NEDF by 225 kJ/day (53.9 kcal/day). In fully adjusted models, we found that change in total NEDF was not associated with change in children’s BMI (0.033 kg/m\u003csup\u003e2\u003c/sup\u003e, [p=0.246]). However, BMI increased 0.078 kg/m\u003csup\u003e2\u003c/sup\u003e for every 418.6 kJ/day (100 kcal/day) of sweet bakery products (p=0.035) in fully adjusted models. For chips and popcorn, BMI increased 0.208 kg/m\u003csup\u003e2\u003c/sup\u003e (p=0.035), yet, the association was attenuated after adjustment (p=0.303).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONCLUSIONS: \u003c/strong\u003eChanges in total NEDF consumption were not associated with changes in BMI in children. However, increases in the consumption of sweet bakery products were associated with BMI gain. NEDF are widely recognized as providing poor nutrition yet, their impact in Mexican children BMI seems to be heterogeneous.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Association between consumption of nonessential energy-dense food and body mass index among Mexican school-aged children: A prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-04-26 20:12:49","doi":"10.21203/rs.3.rs-2833950/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2023-11-09T14:39:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2023-11-03T15:02:15+00:00","index":4,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2023-10-19T07:25:18+00:00","index":4,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2023-10-09T05:59:02+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2023-10-02T01:06:05+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2023-09-27T07:51:08+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2023-09-13T09:51:14+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2023-04-24T17:44:07+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2023-04-24T17:28:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-04-21T09:22:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Obesity","date":"2023-04-20T16:12:53+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2023-04-19T10:25:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-04-18T23:18:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-obesity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ijo","sideBox":"Learn more about [International Journal of Obesity](http://www.nature.com/ijo/)","snPcode":"41366","submissionUrl":"https://mts-ijo.nature.com/cgi-bin/main.plex","title":"International Journal of Obesity","twitterHandle":"@intjobesity","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5b76c741-0b26-4b0c-817e-eb7eb2a9d05e","owner":[],"postedDate":"April 26th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":20967905,"name":"Health sciences/Medical research/Epidemiology"},{"id":20967906,"name":"Health sciences/Health care/Nutrition"}],"tags":[],"updatedAt":"2024-06-09T07:05:08+00:00","versionOfRecord":{"articleIdentity":"rs-2833950","link":"https://doi.org/10.1038/s41366-024-01552-0","journal":{"identity":"international-journal-of-obesity","isVorOnly":false,"title":"International Journal of Obesity"},"publishedOn":"2024-06-08 04:00:00","publishedOnDateReadable":"June 8th, 2024"},"versionCreatedAt":"2023-04-26 20:12:49","video":"","vorDoi":"10.1038/s41366-024-01552-0","vorDoiUrl":"https://doi.org/10.1038/s41366-024-01552-0","workflowStages":[]},"version":"v1","identity":"rs-2833950","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2833950","identity":"rs-2833950","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}