3 EVIDENT CHILDREN

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3 EVIDENT CHILDREN
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  ORIGINAL ARTICLE Eating patterns and overweight in 9- to 10-year-oldchildren in Telemark County, Norway: across-sectional study IM Oellingrath 1 , MV Svendsen 2 and AL Brantsæter 3 1  Faculty of Health and Social Studies, Department of Health Studies, Telemark University College, Porsgrunn, Norway;  2 Telemark Hospital, Skien, Norway and   3  Department of Food Safety and Nutrition, Norwegian Institute of Public Health, Oslo, Norway  Background/Objectives:  Increasing prevalence of overweight in children is a growing health problem. The aim of this studywas to describe the eating patterns of 9- to 10-year-old schoolchildren, and to investigate the relationship between overweightand eating patterns. Subjects/Methods:  We recruited 1045 children for a cross-sectional study in Telemark County, Norway. The children’s food,snacking and meal frequencies were reported by their parents using a retrospective food frequency questionnaire. Height andweight were measured by health professionals, and body mass index categories were calculated using international standardcutoff points (International Obesity Task Force values). Complete data were obtained for 924 children. Four distinct eatingpatterns were identified using principal component analysis. We used multiple logistic regression and calculated odds ratios(ORs) with 95% confidence intervals (CIs) for being overweight, and adjusted for parental characteristics and physical activitylevels of the children (aORs). Results:  Parental characteristics and physical activity were associated with both obesity and eating patterns. Children adheringto a ‘junk/convenient’ eating pattern had a significantly lower likelihood of being overweight (aOR: 0.6; 95% CI: 0.4, 0.9),whereas children adhering to a ‘varied Norwegian’ or a ‘dieting’ eating pattern had a significantly higher likelihood of beingoverweight (respective values: aOR: 2.1; 95% CI: 1.3, 3.2; aOR: 2.2; 95% CI: 1.4, 3.4). No association with overweight was seenfor a ‘snacking pattern’. Conclusions:  The main finding was that, although family characteristics influenced both the prevalence of overweight andoverall dietary behaviour, independent associations were evident between eating patterns and overweight, indicating parentalmodification of the diets of overweight children. European Journal of Clinical Nutrition  (2010)  64,  1272–1279; doi:10.1038/ejcn.2010.152; published online 18 August 2010 Keywords:  dietary behaviour; principal component analysis; eating patterns; overweight; schoolchildren; dieting Introduction Increasing prevalence of overweight in children is a growinghealth problem worldwide. In Norway, a particular increasehas been observed among young schoolchildren (Andersen et al ., 2005). The main dietary risk factors in relation toweight gain and obesity are energy-dense foods (high infat and/or high in sugar) and low-fibre diets (World HealthOrganization, 2003). However, it has been difficult todemonstrate a consistent relationship between children’sbody mass index (BMI) and total energy intake or otherdietary factors in observational studies (Alexy  et al ., 2004;Reilly  et al ., 2005). A nationwide, cross-sectional study of Norwegian children found no association between over-weight and total energy intake or percentage of energygained from fat. Rather, an inverse relationship was reportedbetween intake of sweets and overweight (Andersen  et al .,2005). The same tendency was observed in a study onchildren from six other European countries ( Janssen  et al .,2005; Magnusson  et al ., 2005). A comprehensive review of studies examining the relationship between dietary intakes,eating behaviour and childhood obesity concluded thatmore research is needed, particularly in the form of studiesthat explore the joint effect of multiple dietary behaviour(Newby, 2007). Received 13 November 2009; revised 22 April 2010; accepted 24 June 2010;published online 18 August 2010Correspondence: Dr IM Oellingrath, Faculty of Health and Social Studies,Department of Health Studies, Telemark University College, Kjølnes ring 56,Porsgrunn, NO-3901, Norway.E-mail: inger.m.oellingrath@hit.no European Journal of Clinical Nutrition (2010) 64,  1272–1279 & 2010 Macmillan Publishers Limited All rights reserved 0954-3007/10 www.nature.com/ejcn  Construction of dietary patterns is an increasingly populartechnique for describing overall dietary behaviour in apopulation. The most commonly used method of dietarypattern identification is principal component analysis (PCA),which groups correlated food variables together and therebyidentifies underlying patterns in the data. The use of dietarypatterns enables the study of the associations betweencombinations of foods and certain health conditions, andmay illuminate associations that are not revealed whensingle nutrients or food items are used alone ( Jacques andTucker, 2001; Hu, 2002). Dietary patterns are population specific, and influenced by sociocultural factors and foodavailability (Balder  et al ., 2003). Only a few studies haveidentified distinct dietary patterns in European children andadolescents (North and Emmett, 2000; Aranceta  et al ., 2003;Roos  et al ., 2004; Northstone and Emmett, 2005). Typical dietary patterns of Norwegian schoolchildren have not beendescribed previously.The failure to identify a positive relationship betweenoverweight and unhealthy foods in cross-sectional studieshas been partly explained by changes in dietary habits andfood restrictions due to children’s weight gain (Andersen et al ., 2005; Clark  et al ., 2007). It is not known whether this isa general phenomenon or is dependent on other familycharacteristics. Several studies have linked healthy dietaryhabits among children with high parental education levels(North and Emmett, 2000; Aranceta  et al ., 2003; Roos  et al .,2004; Andersen  et al ., 2005; Northstone and Emmett, 2005). It is likely that dietary modification and restriction of unhealthy food items could be influenced by confounding.To our knowledge, no previous study has examined theassociation between overall dietary behaviour and over-weight among schoolchildren in the light of parentalsociodemographic characteristics.The aim of this study was to describe the eating patternsof 9- to 10-year-old Norwegian schoolchildren, and toinvestigate the relationship between overweight and eatingpatterns and family characteristics. Methods Subjects and study design A descriptive cross-sectional study of fourth-grade pupils(9–10 years old), from primary schools in Telemark County,Norway, was performed from February to April 2007. Allprimary schools in Telemark were invited to participatein the study. Of the 110 invited schools, 70 (64%) agreed toparticipate in the study. The main reason for not participat-ing was the work involving school staff, such as sendinginvitations to parents, handling written consents andquestionnaires, and performing the weight and heightmeasurements of the children. In total, 1477 childrenwere invited to the study. Parents gave written consentfor inclusion of 1045 children, which represented 50%of the county’s fourth-grade pupils. Weight and heightmeasurements were obtained for 955 (91.4%) children. Dataon dietary intake were incomplete for 31 of these, resultingin 924 (88.4%) children for the present analysis.The research protocol was approved by the RegionalCommittee for Ethics in Medical Research and by theNorwegian Data Inspectorate, and informed written consentwas obtained from the parents of all participating children.  Dietary information The children’s food and drink intake was reported by theirparents using a retrospective food frequency questionnaire(FFQ), which asked about habitual daily consumption of 39 food items, 11 types of dinks, 13 snack items and 5 mainmeals during the last 6 months. The questionnaire was basedon a short FFQ developed for use among fourth- and eighth-grade children in Norway, but was modified to includemore dietary questions. The FFQ has not been validatedfor estimating total intakes of energy or nutrients but isappropriate for exploring dietary patterns on the basis of frequencies. The alternative frequencies for food and drinkitems were ‘rarely/never’, ‘1–3 times a month’, ‘1–3 times aweek’, ‘4–6 times a week’, ‘once a day’, ‘twice a day’ and ‘3 ormore times per day’. Meal patterns were registered as thedaily frequencies of five main meals (breakfast, lunch,afternoon meal, dinner and supper), with alternativesranging from ‘rarely/never’ to ‘daily’. The questionsabout snacking between meals had three answer categories:‘never/rarely’, ‘sometimes’ and ‘often/always’. As we usedmeal and snacking events in addition to food consumptionfrequencies as input variables in the PCA, the componentswere denoted as ‘eating patterns’ rather than ‘dietarypatterns’. Other variables In addition to providing dietary information, the parentsanswered questions about their own weight, height, educa-tional level and work situation, family income and theirsubjective opinion regarding their child’s physical activitylevel compared with that of other children of the same age.Parental educational level was divided into three cate-gories: ‘primary and lower secondary education’ (10 years orless), ‘upper secondary education’ (3–4 years of secondaryeducation) and ‘university or university college’.Family income was also divided into three categories:‘both parents  o Norwegian kroner (NOK) 300000’(euro 33909), ‘one parent X NOK 300000’ and ‘both parents X NOK 300000’.Parental work situation was divided into four categories:‘employed’, ‘unemployed/benefit recipient’, ‘housewife/home working’ and ‘others’. ‘Others’ included students,persons on sick leave and persons on a leave of absence.A question categorizing activity by reference to otherchildren was used as an indicator of the children’s physicalactivity level. The question was taken from a battery of  Eating patterns and overweight in schoolchildren IM Oellingrath  et al 1273 European Journal of Clinical Nutrition  validated questions used in a study on children’s activity andinactivity in the Netherlands ( Janz  et al ., 2005), andtranslated into Norwegian for use in this study.Before the main study, the questionnaire was tested on asample of parents. This was followed by qualitative inter-views (Schelling and Streitlien, 2007).  BMI categories The weight and height of the children were measured bypublic health nurses at each school. The children wereweighed wearing light clothing (that is, trousers, T-shirt,socks), using calibrated, electronic scales measuring in 100gincrements. The BMI (kg/m 2 ) of each child was calculated onthe basis of the measurements. Child BMI categories werecalculated using International Obesity Task Force cutoff points (underweight, normal weight, overweight and obese),on the basis of growth curves and BMIs of 17, 25 and 30kg/m 2 at age 18 years (Cole  et al ., 2000, 2007). The cutoff points for9.5-year-old boys and girls were used. Parent BMI categorieswere calculated on the basis of self-reported height andweight and the International Obesity Task Force cutoff points for adults (overweight at BMI X 25kg/m 2 ). Statistical analysis To identify the underlying eating patterns, PCA factoranalysis with varimax rotation was applied to reporteddietary responses. Food and drink frequencies were assignedvalues from 1 for ‘never/rarely’ to 7 for ‘three or more timesdaily’; meal frequencies were assigned values from 1 for‘rarely/never’ to 8 for ‘daily’; and snacking frequencies wereassigned values from 1 to 3. Missing values for a givenvariable were replaced by rarely/never. Respondents wereexcluded from the analysis if answers were missing for morethan 25% of the questions about food and drink items or if answers were missing for more than two questions aboutmeals ( n ¼ 31).PCA constructs new linear factors by grouping togethercorrelated variables. The coefficients defining the factors arecalled factor loadings and are the correlations of each inputvariable with the factors. The number of components chosenfrom the factor analysis was based on the scree plot,eigenvalues and the interpretability of the components(Cattell, 1966). Variables with factor loadings  4 0.25 or o  0.25 were considered to be the most important, provid-ing the best interpretability of each eating pattern. Indivi-duals are given factor scores for each of the patterns. Factorscores are standardized to a mean of zero. Positive factorscores indicate higher consumption of foods, drinks, snacksand meals in that pattern and negative factor scores indicatelow consumption. The factor scores were ranked into tertiles.Differences between group factor scores were testedusing the Mann–Whitney or Kruskall–Wallis test. We usedmultiple logistic regression to calculate odds ratios and 95%confidence intervals (odds ratio (OR) and 95% confidenceinterval (CI)) for overweight in relation to parental char-acteristics, child gender, physical activity level and eatingpatterns. For all tests,  P  o 0.05 was considered significant.The questionnaires were scanned by Eyes and Hands(Readsoft Forms, Helsingborg, Sweden), and all statisticalanalyses were carried out using SPSS version 15. Results Weight and height were obtained for 955 of the 1045participating children (91%)    49.9% boys and 50.1% girls.The distribution between normal weight, overweight andobesity was 736 (80%), 151 (16%) and 37 (4%). We includedthe underweight children in the normal weight groupbecause of the small number of individuals involved( n ¼ 5). Overweight and obese children were also combinedinto one group, denoted ‘overweight’ in the analysis. Theincidence of overweight/obesity was 20.6% for boys and20.1% for girls (  P  ¼ 0.851).We extracted four components describing the eatingpatterns of the children, and named each component afterthe nature of the foods, beverages and meals with thehighest factor loadings within it (Table 1). The eigenvaluesfor the four factors were 4.97, 3.56, 2.82 and 2.47,respectively. The first component, ‘snacking’, was character-ized by snack items and sugar-sweetened drinks consumedbetween meals, combined with low breakfast and dinnerfrequency and low intake of water, vegetables and brownbread. The second component, ‘junk/convenient’, wascharacterized by high-fat and high-sugar processed fast foodssuch as French fries, processed pizza, processed meatproducts, sweets, ice cream and soft drinks. The thirdcomponent, ‘varied Norwegian’, was characterized by fooditems typical of a traditional Norwegian diet, such as fish andmeat for dinner, brown bread, regular white or browncheese, lean meat, fish spread, and fruit and vegetables.The last component, ‘dieting’, was characterized by artifi-cially sweetened soft drinks, low fat cheese and fat- andsugar-reduced yoghurt, and was negatively associated withsugar-sweetened soft drinks.Overweight among the children was positively associatedwith paternal and maternal overweight, and inverselyassociated with maternal education and physical activitylevel (Table 2). Paternal and maternal overweight were alsoassociated with higher ‘dieting’ scores, and maternal over-weight with higher ’snacking’ scores (Table 3). Maternaleducational level was associated with lower ‘snacking’scores,and increased physical activity by the child was associatedwith higher ‘varied Norwegian’ scores and lower ‘dieting’scores. Boys had higher ‘snacking’ and ‘junk/convenient’scores, whereas girls had higher ‘varied Norwegian’ and‘dieting’ scores (Table 3).The highest incidence of overweight was observed in thelower tertile of the ‘junk/convenient’ pattern (27%), and theupper tertile of the ‘dieting’ pattern (26%). The lowest Eating patterns and overweight in schoolchildren IM Oellingrath  et al 1274 European Journal of Clinical Nutrition  incidence was observed in the lower tertile of the ‘dieting’pattern (13%) (Table 4).Children ranked in the two upper tertiles of the ‘junk/convenient’ pattern were less likely to be overweight thanthose in the lower tertile. Independently of this, childrenranked in the two upper tertiles of the ‘varied Norwegian’and ‘dieting’ patterns were more likely to be overweight thanthose in the respective lower tertiles (Table 4). Theseassociations remained significant after adjustment for par-ental BMI, maternal education and physical activity level(Model 2, Table 4). No significant associations were seenbetween ‘snacking pattern’ and overweight.The observed associations between pattern-score tertilesand overweight were basically the same for boys and girls,and for stratified parental characteristics (that is, paternalBMI, maternal BMI, maternal education and physical activitylevel). However, statistical significance was only achieved instrata with a sufficient number of participants (data notshown). Discussion The dietary pattern approach has rarely been used toexamine associations between diet and overweight amongchildren. In this cross-sectional study, we found significantdifferences in eating patterns between normal weight andoverweight 9- to 10-year-old Norwegian children, indepen-dent of physical activity level and parental characteristics. Table 1  Structure of the four eating patterns extracted from 924Norwegian 9- to 10-year-old children Interpreted eating patternItems Factor loadings Cumulative variance explained  ‘Snacking’ Sugar-sweetened soft drinks,carbonated (between meals)0.62 7Sugar-sweetened soft drinks,non-carbonated (between meals)0.60Sweets between meals 0.58Milk between meals 0.47Salty snacks between meals 0.46Ice cream between meals 0.43Juice between meals 0.43 Yoghurt between meals 0.43Biscuits, cakes, crackers, etc.between meals0.41 Artificially sweetened soft drinks,carbonated (between meals)0.37Sugar-sweetened soft drinks,non-carbonated0.33 Artificially sweetened soft drinks,non-carbonated, (between meals)0.30 Water    0.35 Vegetables   0.32Breakfast   0.31Pasta   0.28Dinner    0.28Brown bread   0.28‘Junk/ French fries in fast food restaurants 0.60 13convenient’ Hamburger or kebab 0.56Biscuits, cakes, crackers, etc. 0.51French fries for dinner 0.49 Waffles 0.47Pancakes 0.45Ice cream 0.44Sausages, hot dog 0.44Processed pizza 0.41Biscuits, cakes, crackers, etc.between meals0.34Sugar-sweetened soft drinks,carbonated0.34 White bread 0.34Cereals and breakfast mixturescontaining sugar 0.33Salty snacks 0.32Sweets 0.32Chocolate spread 0.28Processed meat for dinner 0.26Rice 0.25Ice cream between meals 0.25‘Varied Fruits and berries 0.53 17Norwegian’ Vegetables 0.50Fruit yoghurt 0.45Fruits, berries or vegetables betweenmeals0.44 Yoghurt between meals 0.41Fish for dinner 0.40Fat- and sugar-reduced yoghurt 0.36Low-fat meat on sandwich 0.35Fish spread 0.35Juice between meals 0.35Cereals without sugar 0.34 White cheese, full fat 0.34 White cheese, low fat 0.33 Yoghurt with cereal 0.33 Table 1  Continued Interpreted eating patternItems Factor loadings Cumulative variance explained  Processed fish for dinner 0.32Juice 0.31Brown bread 0.30Non-processed meat for dinner 0.29 Water between meals 0.28Brown cheese, full fat 0.27Potatoes 0.27‘Dieting’ Artificially sweetened soft drinks,non-carbonated (between meals)0.66 20 Artificially sweetened soft drinks,non-carbonated0.65 Artificially sweetened soft drinks,carbonated0.63 Artificially sweetened soft drinks,carbonated (between meals)0.54Fat- and sugar-reduced yoghurt 0.29 White cheese, low fat 0.26Sugar-sweetened soft drinks,non-carbonated  0.47Sugar-sweetened soft drinks,carbonated  0.36 Food items, snacks and meals with factor loadings above ± 0.25 are listed. Eating patterns and overweight in schoolchildren IM Oellingrath  et al 1275 European Journal of Clinical Nutrition  No studies have thus far been reported of the dietarypatterns of young Norwegian schoolchildren, and there arefew studies from other European countries (North andEmmett, 2000; Aranceta  et al ., 2003; Northstone andEmmett, 2005, 2008). Differences in dietary assessmentsand the population specificity of dietary patterns make directcomparison difficult (Balder  et al ., 2003), but severalsimilarities can be observed. Most dietary pattern studiesinclude one pattern featuring a mixture of processed andconvenience/junk foods, one pattern featuring high loadings Table 2  Associations (ORs and 95% CIs) between parental characteristics, child gender, parent-reported physical activity and overweight among 924Norwegian 9- to 10-year-old children Characteristics Total Overweight and obese children OR crude (95% CI) OR adjusted  a ( 95% CI  )n  %BMI father  Normal weight 292 39 13 1 1Overweight and obese 510 120 24 2.0 (1.3, 3.0) 1.8 (1.2, 2.7)Missing 122 29 24 2.0 (1.2, 3.5) 1.7 (0.8, 3.7) BMI mother  Normal weight 544 83 15 1 1Overweight and obese 314 93 30 2.3 (1.7, 3.3) 2.2 (1.5, 3.2)Missing 66 12 18 1.2 (0.6, 2.4) 0.9 (0.4, 2.0) Maternal education Primary/lower secondary 138 41 30 1 1Upper secondary 319 65 20 0.6 (0.4, 1.0) 0.6 (0.4, 1.1)University/university college 421 72 17 0.5 (0.3, 0.8) 0.5 (0.3, 0.9)Missing 46 10 22 0.7 (0.3, 1.4) 0.5 (0.2, 1.2) Paternal education Primary/lower secondary 120 25 21 1 1Upper secondary 383 82 21 1.0 (0.6, 1.7) 1.5 (0.8, 2.6)University/university college 317 54 17 0.8 (0.5, 1.3) 1.3 (0.7, 2.4)Missing 104 27 26 1.3 (0.7, 2.5) 1.6 (0.7, 3.6) Family income in Norwegian kroner (NOK) Both parents o NOK 300000 151 32 21 1 1One parent X NOK 300000 421 80 19 0.9 (0.6, 1.4) 1.0 (0.6, 1.7)Both parents X NOK 300000 227 43 19 0.9 (0.5, 1.5) 1.3 (0.7, 2.4)Missing 125 33 26 1.3 (0.8, 2.3) 1.6 (0.7, 3.6) Maternal work  Employed 688 138 20 1 1Unemployed/benefit recipient 42 16 38 2.5 (1.3, 4.7) 1.8 (0.9, 3.7)Housewife 39 5 13 0.6 (0.2, 1.5) 0.4 (0.1, 1.0)Other 89 13 15 0.7 (0.4, 1.3) 0.6 (0.3, 1.1)Missing 66 16 24 1.3 (0.7, 2.3) 1.3 (0.7, 2.6) Paternal work  Employed 773 152 20 1 1Unemployed/benefit recipient 31 8 8 1.4 (0.6, 3.2) 1.0 (0.4, 2.5)Other 40 9 23 1.2 (0.6, 2.5) 1.4 (0.6, 3.3)Missing 80 19 24 1.3 (0.7, 2.2) 0.6 (0.2, 1.5) Child gender  Boy 476 98 21 1 1Girl 448 90 20 1.0 (0.7, 1.3) 1.0 (0.7, 1.4) Physical activity  Less than other children 69 28 41 1 1Same as other children 504 117 23 0.4 (0.3, 0.7) 0.5 (0.3, 0.8)More than other children 346 42 12 0.2 (0.1, 0.4) 0.2 (0.1, 0.4)Missing 5 1 20 0.4 (0.0, 3.5) 0.5 (0.0, 4.7)  Abbreviations: CI, confidence interval; OR, odds ratio. a  Adjusted for all other variables. Eating patterns and overweight in schoolchildren IM Oellingrath  et al 1276 European Journal of Clinical Nutrition
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