Pediatric Original Article

International Journal of Obesity (2012) 36, 950–955; doi:10.1038/ijo.2012.89; published online 5 June 2012

Dietary factors associated with overweight and body adiposity in Finnish children aged 6–8 years: the PANIC Study

A-M Eloranta1,2, V Lindi1, U Schwab3,4, T Tompuri1,5, S Kiiskinen1, H-M Lakka2, T Laitinen5 and T A Lakka1,6

  1. 1Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio, Finland
  2. 2Institute of Public Health and Clinical Nutrition, Public Health, University of Eastern Finland, Kuopio, Finland
  3. 3Institute of Clinical Medicine, Internal Medicine, Kuopio University Hospital, Kuopio, Finland
  4. 4Institute of Public Health and Clinical Nutrition, Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
  5. 5Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
  6. 6Kuopio Research Institute of Exercise Medicine, Kuopio, Finland

Correspondence: Professor TA Lakka, Institute of Biomedicine, Physiology, University of Eastern Finland, PO Box 1627, Kuopio, Fin-70211, Finland. E-mail: timo.lakka@uef.fi

Received 6 September 2011; Revised 17 February 2012; Accepted 22 April 2012
Advance online publication 5 June 2012

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Abstract

Objectives:

 

To investigate the associations of dietary factors with overweight, body fat percentage (BF%), waist circumference (WC) and hip circumference (HC) among children.

Design:

 

Cross-sectional analysis of the Physical Activity and Nutrition in Children (PANIC) Study among 510 children (263 boys, 247 girls) aged 6–8 years from Kuopio, Finland.

Methods:

 

The children’s weight, height, WC and HC were measured. Overweight was defined by International Obesity Task Force body mass index cutoffs. The BF% was measured by dual-energy X-ray absorptiometry, nutrient intakes and meal frequency by 4-day food records and eating behaviour by Children’s Eating Behaviour Questionnaire.

Results:

 

Daily consumption of all the three main meals was inversely associated with overweight (odds ratio (OR) 0.37, 95% confidence interval (CI) 0.18–0.75), BF% (β −0.12, P=0.012), WC (β −0.16, P=0.002) and HC (β −0.15, P=0.002). Enjoyment of food, food responsiveness and emotional overeating were directly associated with overweight (OR 1.57, 95% CI 1.04–2.35; OR 4.68, 95% CI 2.90–7.54; OR 2.60, 95% CI 1.52–4.45, respectively), BF% (β 0.13, P=0.004; β 0.30, P<0.001; β 0.09, P=0.035, respectively), WC (β 0.14, P=0.003; β 0.40, P<0.001; β 0.19, P<0.001, respectively) and HC (β 0.15, P=0.001; β 0.38, P<0.001; β 0.15, P=0.001, respectively). Satiety responsiveness was inversely associated with overweight (OR 0.42, 95% CI 0.26–0.67), BF% (β −0.20, P<0.001), WC (β −0.26, P<0.001) and HC (β −0.26, P<0.001). Slowness in eating was inversely associated with overweight (OR 0.61, 95% CI 0.41–0.92), WC (β −0.16, P=0.001) and HC (β −0.17, P<0.001). Protein intake was directly associated with BF% (β 0.11, P=0.017), WC (β 0.11, P=0.020) and HC (β 0.13, P=0.008).

Conclusions:

 

Promoting regular consumption of main meals and healthy eating behaviours should be emphasized in the prevention of overweight among children. More research is needed on the association of protein-rich foods with body adiposity in children.

Keywords:

children; overweight; diet; protein; meal pattern; eating behaviour

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Introduction

The prevalence of overweight and obesity among children and adolescents has increased rapidly since 1980s in most developed countries1, 2 including Finland.3, 4 To prevent overweight effectively, the early identification of children at an increased risk of overweight is essential. However, evidence on risk factors behind childhood overweight and obesity remains limited.

Previous studies have shown that in addition to strong genetic susceptibility, some early life factors, such as a high birth weight, a rapid weight gain during the first year of life and formula feeding instead of breast feeding, are associated with an increased risk of childhood overweight and obesity.5, 6 Moreover, family background factors such as parental overweight and a low Socio–economic status, as well as early lifestyle factors such as short duration of sleep or sedentary behaviour have been reported to be associated with an increased prevalence of overweight and obesity among children.7, 8, 9 The role of dietary factors in the development of childhood overweight and obesity remains poorly understood.10, 11 The results on the associations of energy intake and the nutrient composition of diet with overweight are controversial.12, 13, 14, 15, 16 On the other hand, various eating patterns, such as a high consumption of low-quality food, sugar-sweetened soft drinks, snacks and sweets, and unfavourable meal patterns, such as a low number of daily meals and skipping breakfast, have been related to overweight in children.17, 18, 19 Moreover, some adverse eating behaviours, such as emotional overeating and food responsiveness, have been associated with childhood overweight in recent studies.20, 21, 22, 23

Current evidence on the role of dietary factors in the development of overweight and obesity among children is not only limited, but also inconsistent. More research is therefore needed to identify children who are at an increased risk of overweight and obesity owing to specific dietary risk factors in order to develop effective prevention approaches for childhood overweight and obesity. The objective of the present study was to investigate the associations of eating frequency, eating behaviour and the intake of various nutrients with overweight, body fat percentage and waist and hip circumferences in primary school children aged 6–8 years.

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Methods

Study design and study population

The present analyses are based on the cross-sectional baseline data of the Physical Activity and Nutrition in Children (PANIC) Study, which is a 2-year diet and exercise-intervention study in a population sample of primary-school children from the city of Kuopio, Finland. Altogether 736 children who started the first grade in primary schools of Kuopio in 2007–2009 were invited to participate in the baseline examinations that were conducted between October 2007 and November 2009. Each child attended the baseline examinations in the year they started the first grade at the age of 6–8 years. Of 736 invited children, 512 (70%) participated in the baseline examinations.

A total of 510 children had a reliable measurement of body height, weight as well as waist and hip circumferences. Complete data were available on body composition for 493 children, on nutrient intake and eating frequency for 422 children and on eating behaviour for 480 children.

The study protocol was approved by the Research Ethics Committee of the Hospital District of Northern Savo. All participating children and their parents gave their informed written consent.

Assessments

Assessment of body composition
 

Trained research staff measured the body height, and waist and hip circumferences three times to an accuracy of 0.1cm. The mean of the nearest two values was used for the analyses. Body height was measured by a wall-mounted stadiometer in the Frankfurt plane without shoes. Waist circumference was measured after expiration at mid-distance between the bottom of the rib cage and the top of the iliac crest with an unstretchable measuring tape. Hip circumference was measured at the level of the great trochanters. Body weight was measured to an accuracy of 100g using the same calibrated InBody 720 device (Biospace, Seoul, Korea), after overnight fasting, empty-bladdered and standing in light underwear. Body mass index (BMI) was calculated as body weight (kg) divided by body height (m) squared. Z-scores for height, weight and BMI were calculated by a calculator that uses age- and sex- specific British growth-reference data from 1990,24, 25 as national references were not available at the time of the baseline examinations. The prevalences of overweight and obesity were assessed using the age- and sex- specific BMI cutoffs by the International Obesity Task Force (IOTF).26 Body fat mass and body fat percentage were measured by a dual energy X-ray absorptiometry (DXA) method with the same Lunar DXA device (Lunar Prodigy Advance; GE Medical Systems, Madison, WI, USA), empty-bladdered and lying in light clothing with all metal objects removed.

Assessment of diets
 

Nutrient intakes and eating frequency were assessed by food records on four consecutive days. Records of 2 weekdays and 2 weekend days (99.5% of subjects) and 3 weekdays and 1 weekend day (0.5% of subjects) were included in the analyses. Parents were instructed to record all food and drinks using household measures (e.g. tablespoons, decilitres, centimetres), and asked their child about food eaten outside their home. Schools and afternoon nurseries were asked for the menus and details on the food served to the children, for example, cooking fat. Food records were checked and completed, if needed by a clinical nutritionist, when the parents returned the records. For details in portion sizes, a picture-booklet of portion sizes was used. The intakes of total energy, fat, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, carbohydrates, sucrose, protein and fibre were calculated. The intakes were analysed as nutrient densities divided by the standard deviation of each nutrient (MJ/SD, E%/SD or g/MJ/SD) to be able to compare the magnitude of the associations. The meals were defined by the nutritionists according to the recorded time and the type of food for each child, individually taking into account the meal pattern of the child. If the definition of a meal was not clear, the nutritionist asked the family for details of the eating occasion. Breakfast, lunch and dinner were classified as main meals, and all eating and drinking occasions between the main meals were classified as snacks. The food records were analysed using The Micro Nutrica dietary analysis software (version 2.5, The Social Insurance Institution of Finland) based on Finnish analyses and international food composition tables.27

Eating behaviours were assessed by the validated Children’s Eating Behaviour Questionnaire28 using an official version translated into Finnish. The parents answered the questionnaire on behalf of their child. The 35 questions of the questionnaire represented eight categories of eating behaviour, including food approach (enjoyment of food, food responsiveness, emotional overeating, desire to drink) and food avoidance (satiety responsiveness, slowness in eating, emotional undereating, food fussiness). Each question offered response options from never to always on a 1–5 Likert scale, and the means of responses of each category were calculated and used in the analyses.

Other assessments
 

Time spent in physical activity and screen time were assessed by the PANIC Physical Activity Questionnaire filled out by the parents. Questions regarding time spent in structured physical activity, unstructured physical activity, commuting to and from school, physical education and physical activity during breaks at school were asked, and the total daily amount of physical activity was calculated in hours per day. Total daily screen time including watching TV, using a computer and playing mobile games was calculated in hours per day. The total annual income of the household was asked by a structured questionnaire from both parents and coded into three categories (less than or equal to30000 euro/y, 30001–60000 euro/y and >60000 euro/y). If the household income categories of the parents were different owing to separation, the higher category of the parents was used in the analyses.

Statistical analyses

Statistical analyses were performed using the SPSS statistical analysis software (v. 17.0 for Windows, SPSS Inc., Chicago, IL, USA). t-test for independent samples, Mann–Whitney’s U-test and Pearson’s χ2-test were used to examine differences in the basic characteristics between sexes. Logistic regression analysis was used to model the associations of dietary factors with the risk of being overweight or obese. Because of high collinearity between dietary factors, each dietary factor was entered in the model separately. Linear regression analysis was used to model the associations of dietary factors with body fat percentage as well as waist and hip circumferences. Continuous variables were logarithmically transformed when appropriate. All regression analyses were adjusted for confounding variables (sex, age, total daily time of physical activity, total daily screen time and parental income level). All associations were considered statistically significant if the P-value was <0.05.

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Results

Characteristics

Of all 510 children, 263 (52%) were boys and 247 (48%) were girls. Table 1 presents characteristics of the boys and girls. Altogether 11.0% of the boys and 15.4% of the girls were overweight or obese.


Eating frequency, risk of overweight or obesity and body composition

Children who ate all three main meals (breakfast, lunch and dinner) daily had a 63% lower risk of being overweight or obese than those who did not eat all of them daily (Table 2). Eating all main meals daily was also associated with a lower body fat percentage (Table 3) and smaller waist and hip circumferences (Table 4). Further adjustment for the number of snacks did not affect the associations of eating all main meals with overweight, body fat percentage, waist circumference or hip circumference. The number of snacks was not statistically significantly associated with overweight or obesity (Table 2), body fat percentage (Table 3), waist circumference or hip circumference (Table 4). Higher energy intake from dinner was associated with a lower risk of being overweight or obese, but energy intake from breakfast, lunch or snacks or from all main meals together was not related to the risk of having overweight or obesity.




Eating behaviour, risk of overweight or obesity and body composition

Scores in enjoyment of food, food responsiveness and emotional overeating were directly associated with the prevalence of overweight or obesity (Table 2), body fat percentage (Table 3) and waist and hip circumferences (Table 4). Satiety responsiveness was associated with a decreased risk of being overweight or obese (Table 2) and a decreased body fat percentage (Table 3), and waist and hip circumferences (Table 4). Slowness in eating was also inversely associated with the risk of overweight or obesity (Table 2) and waist and hip circumferences (Table 4). Desire to drink, food fussiness and emotional undereating were not associated with overweight or obesity, body fat percentage, waist circumference or hip circumference.

Intakes of various nutrients, risk of overweight or obesity and body composition

Total energy intake was directly associated with waist circumference and hip circumference (Table 4). When adjusted additionally for body height, however, the associations of total energy intake with waist circumference (standardized regression coefficient 0.02, P=0.730) and hip circumference (standardized regression coefficient 0.00, P=0.933) disappeared. There was a direct association of protein intake as E% with body fat percentage (Table 3), waist circumference and hip circumference (Table 4). Adjustments for energy or other macronutrient intakes did not affect these associations.

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Discussion

The present study in a population sample of Finnish girls and boys aged 6–8 years shows that skipping main meals is associated with an increased risk of having overweight or obesity, increased body fat percentage and higher waist and hip circumferences in children. Emotional overeating, enjoyment of food and food responsiveness were directly associated and satiety responsiveness and slowness in eating were inversely related to these measures of increased body fat. Moreover, protein intake was directly associated with body fat percentage, waist circumference and hip circumference. All these associations were independent of sex, age, physical activity, screen time and parental income.

The results of some previous studies suggest that eating main meals, especially breakfast, is important in the prevention of overweight and obesity in children and adolescents.18, 29, 30 The present observation also emphasizes the role of eating main meals regularly in preventing overweight and obesity among children. However, the present data did not allow us to investigate the independent association of eating breakfast with overweight and obesity, because 96% of the children ate breakfast regularly. Energy obtained from dinner had an inverse association with being overweight or obese. Our finding may indicate that an early dinner may reduce snacking in the afternoons and evenings. Although most primary school children in Finland have a breakfast and a free prepared school lunch, the regularity and composition of a dinner vary more among Finnish families. Moreover, the tradition of two prepared meals at home on weekends has become less common in Finland. An increasing number of families skips or replaces one of the meals with a snack. However, whether the inverse association of energy received from dinner with the risk of being overweight or obese is due to a regular family lifestyle, prepared food, eating with parents or the avoidance of low-quality snacks remains to be clarified.

We found that enjoyment of food, emotional overeating and responsiveness to food were associated with increased body adiposity in children. Moreover, satiety responsiveness and slowness in eating were associated with a reduced risk of having excess body fat. These eating behaviours have also been related to overweight and obesity among children in previous studies.20, 21, 22, 23, 31 We observed no associations of desire to drink, emotional undereating and food fussiness with measures of body adiposity. In previous studies, the results have also been inconsistent.20, 21, 22, 23 Altogether, the present findings suggest that children who have adverse eating behaviours that may result in an unregulated food intake have a higher risk of overweight than those without such problems. Accordingly, an obesogenic environment with unlimited availability of food can be especially harmful for those who have eating behaviours that hinder regulation of food intake and feelings of satiety. Our finding may also be related to the inverse association between the number of main meals and overweight; that is, irregular eating and skipping meals may increase the tendency to be vulnerable to rapid eating, overeating and decreased feelings of satiety. There is some evidence on heritability and tracking of certain eating behaviours.32, 33 Hence, assessing eating behaviour by a short questionnaire could be useful in child health care to identify normal weight children with a susceptibility to overeating and weight gain, and who therefore would benefit most from dietary counselling. Such effective intervention approaches targeted towards children are needed.

We found that protein intake was directly associated with body fat percentage, waist circumference and hip circumference, whereas intakes of other nutrients were not related to measures of adiposity. Previous studies have suggested that a high protein intake during the weaning period and the first years of life predicts a high BMI and a high body fat percentage in later childhood.34, 35, 36 This association could be due to early adiposity rebound as a result of changes in hormonal responses. However, the findings concerning the association of protein intake after weaning period with childhood overweight are controversial.37 One explanation for our finding could be that the sources of protein are often high in fat and sucrose. For example, protein-rich dairy products, such as yoghurts and hot chocolate, have been reported to be one of the most significant sources of sucrose in the diet of 7-year-old Finnish school children.38 A high intake of energy from such foods would predispose to excess body fat. However, further adjustment for energy from fat or carbohydrates did not weaken the association between energy from protein and indicators of body adiposity in the present study. A high protein intake can also indicate other unhealthy dietary choices that could increase body adiposity. For example, replacing vegetables with meat or replacing water as a between-meal drink with a protein-rich drink, such as milk or a milk-based drink, could expose to excess weight gain.

In the present study, total energy intake was not associated with overweight or body adiposity, even when the analyses were adjusted for physical activity. We found linear associations of total energy intake with waist and hip circumferences, but the associations disappeared after controlling for body height. The explanation for this may be that taller children have, on average, higher waist and hip circumferences independently of body adiposity.

The strengths of the present study are the availability of objectively measured weight, height and waist and hip circumferences instead of reported values and the rigorous methods used for assessing diet, eating behaviour and body composition among children.28, 39, 40, 41 Overweight was defined by internationally accepted age and sex specific BMI cut offs,26 which enables the comparison of results with studies conducted in the same age group in other countries. The prevalence of overweight and obesity in the present study sample (12.8%) was slightly lower than that of Finnish first-graders, reported recently by the National Institute for Health and Welfare (16.5%).42 However, children from almost every school of the city of Kuopio, both rural and urban schools, were invited to participate in order to have as socio–economically representative study sample as possible. Moreover, the relatively high participation rate diminishes the nonparticipant bias. It is possible that neither of these study samples completely represent the Finnish population of this age group, or that there is some regional variation in overweight and obesity in Finland. A limitation of our study is the cross-sectional study design that makes it difficult to draw conclusions about a causal relationship between dietary factors and body adiposity.

The results of the present study suggest that promoting regular main meal eating pattern and healthy eating behaviours should be emphasized in the prevention of overweight among children. Together, with the limited and inconsistent previous evidence, our data suggest that more research is needed on the association of protein-rich foods with adiposity in children.

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Conflict of interest

The authors declare no conflict of interest.

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References

  1. Janssen I, Katzmarzyk PT, Boyce WF, Vereecken C, Mulvihill C, Roberts C et al. Comparison of overweight and obesity prevalence in school-aged youth from 34 countries and their relationships with physical activity and dietary patterns. Obes Rev 2005; 6: 123–132. | Article | PubMed | ISI | CAS |
  2. de Onis M, Blossner M, Borghi E. Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr 2010; 92: 1257–1264. | Article | PubMed | ISI | CAS |
  3. Kautiainen S, Rimpela A, Vikat A, Virtanen SM. Secular trends in overweight and obesity among Finnish adolescents in 1977-1999. Int J Obes Relat Metab Disord 2002; 26: 544–552. | Article | PubMed | CAS |
  4. Vuorela N, Saha MT, Salo M. Prevalence of overweight and obesity in 5- and 12-year-old Finnish children in 1986 and 2006. Acta Paediatr 2009; 98: 507–512. | Article | PubMed | ISI |
  5. Arenz S, Ruckerl R, Koletzko B, von Kries R. Breast-feeding and childhood obesity--a systematic review. Int J Obes Relat Metab Disord 2004; 28: 1247–1256. | Article | PubMed | CAS |
  6. Reilly JJ, Armstrong J, Dorosty AR, Emmett PM, Ness A, Rogers I et al. Early life risk factors for obesity in childhood: cohort study. BMJ 2005; 330: 1357. | Article | PubMed | ISI |
  7. Danielzik S, Czerwinski-Mast M, Langnase K, Dilba B, Muller MJ. Parental overweight, socioeconomic status and high birth weight are the major determinants of overweight and obesity in 5-7 y-old children: baseline data of the Kiel Obesity Prevention Study (KOPS). Int J Obes Relat Metab Disord 2004; 28: 1494–1502. | Article | PubMed | CAS |
  8. Must A, Tybor DJ. Physical activity and sedentary behavior: a review of longitudinal studies of weight and adiposity in youth. Int J Obes (Lond) 2005; 29 (Suppl 2): S84–S96. | Article | PubMed |
  9. Kleiser C, Schaffrath Rosario A, Mensink GB, Prinz-Langenohl R, Kurth BM. Potential determinants of obesity among children and adolescents in Germany: results from the cross-sectional KiGGS Study. BMC Public Health 2009; 9: 46. | Article | PubMed |
  10. Rodriguez G, Moreno LA. Is dietary intake able to explain differences in body fatness in children and adolescents? Nutr Metab Cardiovasc Dis 2006; 16: 294–301. | Article | PubMed |
  11. Moreno LA, Rodriguez G. Dietary risk factors for development of childhood obesity. Curr Opin Clin Nutr Metab Care 2007; 10: 336–341. | Article | PubMed | ISI |
  12. Maffeis C, Provera S, Filippi L, Sidoti G, Schena S, Pinelli L et al. Distribution of food intake as a risk factor for childhood obesity. Int J Obes Relat Metab Disord 2000; 24: 75–80. | Article | PubMed | CAS |
  13. Maillard G, Charles MA, Lafay L, Thibult N, Vray M, Borys JM et al. Macronutrient energy intake and adiposity in non obese prepubertal children aged 5-11 y (the Fleurbaix Laventie Ville Sante Study). Int J Obes Relat Metab Disord 2000; 24: 1608–1617. | Article | PubMed | CAS |
  14. Johnson L, Mander AP, Jones LR, Emmett PM, Jebb SA. Energy-dense low-fiber, high-fat dietary pattern is associated with increased fatness in childhood. Am J Clin Nutr 2008; 87: 846–854. | PubMed | CAS |
  15. Wilson TA, Adolph AL, Butte NF. Nutrient adequacy and diet quality in non-overweight and overweight Hispanic children of low socioeconomic status: the Viva la Familia Study. J Am Diet Assoc 2009; 109: 1012–1021. | Article | PubMed |
  16. Elliott SA, Truby H, Lee A, Harper C, Abbott RA, Davies PS. Associations of body mass index and waist circumference with: energy intake and percentage energy from macronutrients, in a cohort of Australian children. Nutr J 2011; 10: 58. | Article | PubMed |
  17. Nicklas TA, Yang SJ, Baranowski T, Zakeri I, Berenson G. Eating patterns and obesity in children. The Bogalusa Heart Study. Am J Prev Med 2003; 25: 9–16. | Article | PubMed | ISI |
  18. Toschke AM, Thorsteinsdottir KH, von Kries R. GME Study Group. Meal frequency, breakfast consumption and childhood obesity. Int J Pediatr Obes 2009; 4: 242–248. | Article | PubMed | ISI |
  19. Sandercock GR, Voss C, Dye L. Associations between habitual school-day breakfast consumption, body mass index, physical activity and cardiorespiratory fitness in English schoolchildren. Eur J Clin Nutr 2010; 64: 1086–1092. | Article | PubMed |
  20. Sleddens EF, Kremers SP, Thijs C. The Children's Eating Behaviour Questionnaire: factorial validity and association with Body Mass Index in Dutch children aged 6-7. Int J Behav Nutr Phys Act 2008; 5: 49. | Article | PubMed |
  21. Viana V, Sinde S, Saxton JC. Children's Eating Behaviour Questionnaire: associations with BMI in Portuguese children. Br J Nutr 2008; 100: 445–450. | Article | PubMed | CAS |
  22. Webber L, Hill C, Saxton J, Van Jaarsveld CH, Wardle J. Eating behaviour and weight in children. Int J Obes (Lond) 2009; 33: 21–28. | Article | PubMed |
  23. Spence JC, Carson V, Casey L, Boule N. Examining behavioural susceptibility to obesity among Canadian pre-school children: the role of eating behaviours. Int J Pediatr Obes 2011; 6: e501–e507. | Article | PubMed |
  24. Cole TJ, Freeman JV, Preece MA. Body mass index reference curves for the UK, 1990. Arch Dis Child 1995; 73: 25–29. | Article | PubMed | ISI | CAS |
  25. Freeman JV, Cole TJ, Chinn S, Jones PR, White EM, Preece MA. Cross sectional stature and weight reference curves for the UK, 1990. Arch Dis Child 1995; 73: 17–24. | Article | PubMed | ISI | CAS |
  26. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000; 320: 1240–1243. | Article | PubMed | ISI | CAS |
  27. Rastas M, Seppänen R, Knuts LR, Hakala P, Karttila V (eds) Nutrient Composition of Foods. The Social Insurance Institution: Helsinki, France, 1997.
  28. Wardle J, Guthrie CA, Sanderson S, Rapoport L. Development of the Children's Eating Behaviour Questionnaire. J Child Psychol Psychiatry 2001; 42: 963–970. | Article | PubMed | ISI | CAS |
  29. de Gouw L, Klepp KI, Vignerova J, Lien N, Steenhuis IH, Wind M. Associations between diet and (in) activity behaviours with overweight and obesity among 10-18-year-old Czech Republic adolescents. Public Health Nutr 2010; 13: 1701–1707. | Article | PubMed |
  30. Lehto R, Ray C, Lahti-Koski M, Roos E. Meal pattern and BMI in 9-11-year-old children in Finland. Public Health Nutr 2011; 14: 1245–1250. | Article | PubMed |
  31. Berkowitz RI, Moore RH, Faith MS, Stallings VA, Kral TV, Stunkard AJ. Identification of an obese eating style in 4-year-old children born at high and low risk for obesity. Obesity (Silver Spring) 2010; 18: 505–512. | Article | PubMed |
  32. Ashcroft J, Semmler C, Carnell S, van Jaarsveld CH, Wardle J. Continuity and stability of eating behaviour traits in children. Eur J Clin Nutr 2008; 62: 985–990. | Article | PubMed | CAS |
  33. Carnell S, Wardle J. Appetitive traits in children. New evidence for associations with weight and a common, obesity-associated genetic variant. Appetite 2009; 53: 260–263. | Article | PubMed | ISI |
  34. Rolland-Cachera MF, Deheeger M, Akrout M, Bellisle F. Influence of macronutrients on adiposity development: a follow up study of nutrition and growth from 10 months to 8 years of age. Int J Obes Relat Metab Disord 1995; 19: 573–578. | PubMed | CAS |
  35. Gunnarsdottir I, Thorsdottir I. Relationship between growth and feeding in infancy and body mass index at the age of 6 years. Int J Obes Relat Metab Disord 2003; 27: 1523–1527. | Article | PubMed | CAS |
  36. Gunther AL, Buyken AE, Kroke A. Protein intake during the period of complementary feeding and early childhood and the association with body mass index and percentage body fat at 7 y of age. Am J Clin Nutr 2007; 85: 1626–1633. | PubMed | ISI |
  37. Newby PK. Are dietary intakes and eating behaviors related to childhood obesity? A comprehensive review of the evidence. J Law Med Ethics 2007; 35: 35–60. | Article | PubMed | ISI | CAS |
  38. Ruottinen S, Niinikoski H, Lagstrom H, Ronnemaa T, Hakanen M, Viikari J et al. High sucrose intake is associated with poor quality of diet and growth between 13 months and 9 years of age: the special Turku Coronary Risk Factor Intervention Project. Pediatrics 2008; 121: e1676–e1685. | Article | PubMed | ISI |
  39. Buzzard M. 24-h dietary recall and food record methods. In: Willett W (ed.) Nutritional Epidemiology. Oxford University Press: New York, 1998. pp 50.
  40. Sopher AB, Thornton JC, Wang J, Pierson RN, Heymsfield SB, Horlick M. Measurement of percentage of body fat in 411 children and adolescents: a comparison of dual-energy X-ray absorptiometry with a four-compartment model. Pediatrics 2004; 113: 1285–1290. | Article | PubMed | ISI |
  41. Carnell S, Wardle J. Measuring behavioural susceptibility to obesity: validation of the child eating behaviour questionnaire. Appetite 2007; 48: 104–113. | Article | PubMed | ISI |
  42. Mäki P, Hakulinen-Viitanen T, Kaikkonen R, Koponen P, Ovaskainen M-L, Sippola R et al. (eds) [Child Health—Results of the LATE-study on growth, development, health, health behavior and growth environment]. In Finnish. National Institute for Health and Welfare (THL): Helsinki, 2010.
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Acknowledgements

We thank all voluntary subjects and their families for participating in the PANIC Study. We are also gratefully indebted to the PANIC Study research team members for their skillful contribution in conducting the study. We gratefully acknowledge MD, PhD David Laaksonen for editing the language of the manuscript, Eila Koski for DXA scans and PhD Marja Kalavainen and PhD Outi Nuutinen for the translation of the Children’s Eating Behaviour Questionnaire into Finnish language. This work has been financially supported by grants from the Ministry of Social Affairs and Health of Finland, the Ministry of Education and Culture of Finland, the University of Eastern Finland, the Finnish Innovation Fund Sitra, the Social Insurance Institution of Finland, the Finnish Cultural Foundation, the Juho Vainio Foundation, the Foundation for Pediatric Research and the Kuopio University Hospital (EVO-funding number 5031343).

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