Prevalence and determinants of childhood overweight and obesity in European countries: pooled analysis of the existing surveys within the IDEFICS Consortium

Abstract

Objective:

To pool and analyse, according to standardized criteria and using harmonized variables, the existing databases of surveys on childhood overweight and obesity carried out from 1995 to 2005 in different European countries by research groups participating in the IDEFICS project.

Methods:

Detailed information from seven surveys in five European countries was collected. A common database was built after harmonization of the single studies regarding sample size and age distribution. Variables were critically reviewed and harmonized according to a common protocol. On the pooled database, descriptive comparative analyses on the prevalence of overweight/obesity and association analyses of these conditions with perinatal, parental and environmental factors were performed.

Results:

Starting from total number of 74 871 children, data of 18 626 children were included in the common database (Belgium, n=1766; Cyprus, n=5540; Estonia, n=583; Italy, n=4480 and Sweden, n=6257). After the exclusion of children outside the defined age ranges (4–5 and 9–11 years), the analysis was conducted on 1738 younger and 12 923 older children. Relevant differences in the prevalence of overweight/obesity were observed between countries in both age groups, the highest values being observed in Italy. Age- and gender-related associations between the risk of obesity/overweight and perinatal, parental and environmental factors were observed. An increased risk of high blood pressure in overweight/obese children was consistently observed.

Conclusions:

The results of this collaborative work of European research centres, although providing potentially useful findings, confirmed that the validity of comparisons between communities depends critically on the comparability of the survey methods. To monitor the current epidemic of childhood obesity and develop appropriate prevention strategies, a coordinated European approach is needed to collect homogeneous sets of epidemiological data.

Introduction

The prevalence of pediatric obesity has increased at an alarming speed in Europe as well as in other developed countries1, 2, 3, 4 and it now represents a well-recognized public health problem.3 In addition, the negative health consequences of pediatric obesity, such as metabolic risk factors and type 2 diabetes, already constitute important public health concerns that will likely increase in the future.5 Although several studies on the prevalence of pediatric obesity have been conducted in Europe, most of which have involved national or regional cross-sectional surveys,4, 6 at present intra- and inter- country comparisons of the prevalence of childhood obesity are very difficult to estimate because of the different definitions and cut-off criteria used to define overweight and obesity.2 Furthermore, the limited sample size of many studies conducted at local level hampers the possibility to reliably assess lifestyle and nutritional determinants of overweight and obesity and to evaluate the effects of the prevention programmes. In particular, although the available epidemiological data on the prevalence of adult obesity in European countries were recently systematically summarized,7 less systematic data exist for pediatric obesity, besides those collected and timely updated by the International Obesity Task Force (IOTF) (http://www.iotf.org/database/Childhoodandadolescentoverweightineurope.htm).4, 6

The aim of the present study was to pool and analyse, according to standardized criteria and using harmonized variables, the existing databases of surveys on childhood overweight and obesity carried out from 1995 to 2005 in different European countries by research groups participating in the IDEFICS project (http://www.idefics.eu).8, 9

To the best of our knowledge, this is the first attempt to build up a common database from raw data—collected in different countries with somewhat different instruments—to obtain comparable information not only on ‘hard’ end points such as the prevalence of overweight/obesity, but also on known determinants of body fat accumulation, such as birthweight, meal frequency, parental education. The results of this analysis could be also useful as starting points to evaluate national trends of overweight/obesity when they will be compared with the data that are currently collected within the IDEFICS study, particularly for those European countries where no data on temporal trends are available.4

Owing to the considerable effort performed during the past decade to obtain comparable criteria to define body mass index (BMI) categories across age strata in childhood,10, 11 standardized instruments are now available to evaluate prevalence and trends of overweight and obesity and compare them within and between countries.

Materials and methods

Description of the existing studies

We identified seven existing surveys conducted by the partners of the IDEFICS Consortium that were carried out in five European countries (Table 1). In particular, the studies available were conducted in Belgium,12 Cyprus (three separate surveys, indicated as Cyprus A,13 Cyprus B,14 and Cyprus C15, and unpublished data provided by M Tornaritis), Estonia,16 Italy17, 18 and Sweden.19 Details of each single study were reported in previously published papers.12, 13, 14, 15, 16, 17, 18, 19 In all the previous surveys, approval of the local ethical committee was obtained. In Cyprus, approval for the studies was granted by the Ministry of Health and Ministry Education and Culture. The total number of children participating in these surveys was 74 871 (38 336 boys, 36 535 girls). The majority of only the studies (six out of seven) were cross-sectional and only the Cyprus studies may be considered country-representative, whereas the Belgian study is representative of only the Flanders region of Belgium. All the studies were conducted between 1995 and 2005 in school settings, nearly all of them in primary public schools, with the exception of two studies (Cyprus A and Estonia) involving both primary and secondary schools.

Table 1 Summary data of the seven previous surveys included in the pooled analysis

Sample sizes varied largely among the seven studies, ranging from 1129 children and adolescents in the cohort in Estonia to 55 919 children in the Cyprus C study. In addition, a substantial heterogeneity in the age ranges was observed. The mean age varied from 4.5 years in the Belgian study to 14.6 years in the Estonian cohort study, whereas the overall age range was between 2 years in Cyprus to 18 years in Cyprus and Estonia. The gender distribution was balanced in each study and thus also in the pooled sample with about 51.2% boys and 48.8% girls.

After summarizing the characteristics of these surveys, the next step was to assess the variables available in the different studies.

The major end points, that is, overweight and obesity, were assessed in all studies by measuring the BMI of the children. In six out of seven studies, height and weight were measured directly with comparable procedures and BMI was calculated as weight in kilograms divided by height in squared metres. In the Belgian study, BMI was calculated based on weight and height reported by the parents, but no systematic bias is expected for the pooled analyses because of the rather small sample of Belgian survey. With regard to other anthropometric measurements, waist circumference was measured at umbilical level in five studies (Cyprus A, B and C, Italy and Sweden), whereas it was measured midway between iliac crest and the lowest rib in the Estonian study. Hip circumference was also measured in five out of seven studies using comparable methods. Fat distribution pattern was assessed by measurement of skinfold thickness (triceps) in three studies (Cyprus A and C, Estonia).

Blood pressure was measured in three studies using a standard mercury sphygmomanometer (Cyprus A and C, Italy), whereas in the Estonian study an automatic device was used.

Dietary habits of the children were assessed in four studies (Belgium, Cyprus C, Estonia and Italy). A 24 h recall was used in two studies (Belgium, three 24 h recalls carried out repeatedly, and Cyprus C), whereas in the Estonian and the Italian studies dietary intake was evaluated by means of a food frequency questionnaire.

Physical activity was assessed in four studies, although with different instruments. In Belgium and Italy, physical activity of the children was assessed by a parental questionnaire, whereas the Cyprus C study evaluated physical fitness of participating children with the standardized Eurofit test battery, and in Estonia physical activity was measured by accelerometer, recorded for 3 days for at least 10 h per day. Data on sedentary behaviour such as number of hours spent watching television, playing video games were not systematically assessed across the studies.

Other relevant variables, such as parental overweight/obesity, family income and/or education, number of meals/breakfast habits, birthweight, breastfeeding and definition of pubertal status, were collected in most studies, although using somewhat different instruments. Reported parental BMI was available in four studies (Cyprus A and B, Italy and Sweden), as well as categorical family income and/or education.

Breakfast habit was directly investigated in two studies (Cyprus B and Italy), whereas it was obtained from the 24 h dietary recalls in the Belgium and Cyprus C studies. Birthweight was reported by parents in four studies (Cyprus A, B and C, Italy). For three of those studies (Cyprus A and B, Italy) parents also reported weeks of gestation at birth. Data of breastfeeding were available for three studies (Belgium, Estonia and Italy).

Pooling of existing surveys

The initial examination of information sent by each centre to the centralized statistics unit showed that the sample size of the Cyprus C survey was disproportionately larger than that of the other surveys. Thus, taking into account that this survey may be considered as country-representative, a gender- and age-stratified randomized sample was extracted from it to balance out the heterogeneity in sample sizes. Pooling this random sample from Cyprus C with the remaining data sets, the pooled database now included 18 626 children (Belgium=1766; Cyprus=5540; Estonia=583; Italy=4480 and Sweden=6257).

The investigation of the age distribution in the pooled database still revealed a relevant heterogeneity across the five countries, thus hampering stratification of age by 1-year intervals. For this reason, two homogeneous age groups were defined: 4- and 5-year-old children from three countries, n=1738 (Italy, Cyprus and Belgium) and 9- to 11-year-old children from four countries, n=12923 (Italy, Estonia, Cyprus and Sweden).

Standardization and harmonization of variables

Based on a first inspection of the variables measured in each study, a set of variables not requiring further harmonization was identified: gender, age, height, weight, waist and hip circumferences, blood pressure, birthweight and parental BMI. All of these variables were not available for all centres. For centres where these variables had been measured, the measurement instruments were sufficiently standardized among centres to allow their inclusion in the common database.

Body mass index categories were age- and gender-stratified according to the methods proposed by Cole and colleagues,10, 11 which provide the following BMI categories: thin (BMI below 18.5 in adults), normal weight (BMI between 18.5 and 25 in adults), overweight (BMI between 25 and 30 in adults) and obese (BMI above 30 in adults).

Other variables were measured in each study using different instruments and scales and were harmonized according to the lowest common level of agreement. Parental education was dichotomized according to the International Standard Classification of Education (ISCED, http://www.unesco.org/education/information/nfsunesco/doc/isced_1997.htm): ISCED Level 1–2 (primary education/lower secondary education) and ISCED Levels 3–6 (higher secondary education/post-secondary education, non-university education/university education/postgraduate studies). Physical activity was also dichotomized (child practices sport: yes/no). With regard to smoking status of the parents, the lowest common level of agreement was current smokers (smoking status: yes) and former/never smokers (smoking status: no). Breastfeeding (ever/never) and breakfast habits (yes/no) were also categorized into two categories.

Statistical analysis

For descriptive analyses, country-, age- and gender-specific means and 95% confidence intervals (CI) of BMI, waist, hip, waist/hip, waist/height20 and blood pressure are calculated (only 9–11 year children). Age- and gender-specific prevalence of overweight and obesity are calculated in each country and in the whole sample. Multiple logistic regression models are used to estimate age- and gender-specific odds ratios (OR) and 95% confidence limits of the outcome variable (overweight/obesity) in each country, according to modifying factors. The binary outcome variable distinguishes between obese and overweight children (=1) and normal weight and thin children (=0) according to the age- and gender-specific definition by Cole and colleagues.10, 11 The following (categorized) variables are accounted for in the multiple logistic regression: birthweight, breastfeeding, breakfast habit, physical activity, parental BMI, parental education level and parental smoking habit. To adjust for age effects within both age groups, we include one additional dummy variable for children's age (reference: 4-year-old children) in the younger age group and two additional dummies for 10- and 11-year-old children in the older age group (reference: 9-year-old children). For each centre the analyses were performed based on complete cases data. The association between overweight/obesity and high blood pressure defined according to the criteria of the National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents21 was assessed in the older age group (9–11 years) by age- and gender-adjusted logistic regression.

Results

Categories of BMI for younger and older boys and girls in each country and in the combined sample are shown in Figure 1 a and b. Higher prevalence of overweight and obesity was observed in Italian children in both age groups together with a quite lower prevalence of thinner children as compared to the other countries. The lowest prevalence of overweight and obesity was observed in Estonia, with almost no cases of obesity. Interestingly, in the Cyprus sample an increase of the prevalence of both overweight and obesity was observed with the increasing age.

Figure 1
figure1

(a and b) Categories of body mass index (BMI) for younger and older boys and girls in each country and in the combined sample. Thin, white bars; normal weight, grey bars; overweight, hatched bars; obesity, black bars.

Anthropometric variables and blood pressure in older boys and girls stratified by age are reported in Table 2a and b. These data are not reported for the younger children, because of the small size of the available samples and the lack of some relevant variables in this age group. Italian boys and girls showed higher age-specific values of BMI, body circumferences, waist/hip and waist/height ratios as compared with the other countries, whereas the higher age-specific values of both systolic and diastolic blood pressure were observed in both girls and boys belonging to the Cyprus population.

Table 2 Anthropometric variables and blood pressure for boys of 9–11 years

The estimates of the risk of obesity/overweight associated with perinatal, parental and environmental factors are presented in Tables 3 and 4 (younger and older children respectively). A number of age- and gender-related associations were observed. Their interpretation should be particularly cautious in younger children because of the relatively small sample sizes and/or lack of data. In particular, a significantly higher risk of overweight/obesity was associated with birthweight higher than 3500 g in both younger and older girls. Skipping breakfast was apparently a risk factor for overweight/obesity in boys, although only in some cases statistical significance was attained. The effect of parental (mother and/or father) overweight/obesity on offspring overweight/obesity could only be confirmed in older children, whereas inconsistent associations were observed with the parental education status. In some countries, parental smoking (mother and/or father) habit was associated with overweight/obesity in their children, particularly in the Italian sample.

Table 3 OR and 95% CI of overweight/obesity for selected risk factors obtained from logistic regressions for children of 4–5 years
Table 4 OR and 95% CI of overweight/obesity for selected risk factors obtained from logistic regressions for children of 9–11 years

The risk of high blood pressure associated with overweight/obesity was only investigated for the older age group. The age- and gender-adjusted analysis showed a significant and comparable increased risk of high blood pressure in the obese/overweight children of the three countries where blood pressure data were available (Cyprus OR 4.59, 95% CI 3.87–5.44; Italy, OR 3.69, 95% CI 2.48–5.51; Estonia, OR 3.89, 95% CI 1.52–9.93).

Discussion

Research centres being members of the IDEFICS Consortium made available—as part of the research programme implemented within the Consortium—raw data of surveys of childhood overweight/obesity conducted in the period 1995–2005 in five European countries.12, 13, 14, 15, 16, 17, 18, 19 Data were cleaned and harmonized and resulted in a common database composed of homogeneously measured variables collected in children of two age ranges (4–5 and 9–11 years). Only surveys using BMI as criterion for the assessment of overweight/obesity were included. Owing to the international framework of the analysis, internationally-based criteria for overweight/obesity10 and thinness11 were preferred to national reference data. The IOTF criteria provide a set of BMI thresholds equivalent to BMIs of 25 and 30 at age 18, adjusted for gender and for children's ages down to 2 years old.10

At the very beginning of the pooling process, a large heterogeneity both in sample size and in age range became apparent, which was solved on the one side by randomly extracting a sample from the largest survey (Cyprus C) and on the other side by excluding children outside the two age ranges of younger (4–5 years) and older (9–11 years) children. The inspection of measured anthropometric variables resulted in enough homogeneity of the measurement instruments to allow their direct inclusion into the common data set. Other variables, mainly those obtained from questionnaires, were collected according to different instruments in the different surveys. However, having raw data available, we were able to define dichotomous variables to be used in the analyses, although reducing the chance to detect discriminating effects, because of the reduced number of possible categories.

The main results of our analysis may be summarized as follows. First, active collaboration among the involved European research centres enabled us to build a unique database of information on childhood overweight/obesity, including perinatal, parental and environmental factors and to analyse it according to a unique strategy. Second, the available data, no matter how imperfect, allowed us to compare prevalence pattern of overweight/obesity according to gender, age and geographical origin. Importantly, these data confirmed the already known North–South gradient of overweight/obesity in Europe.4, 7 The analysis of modifying factors, such as birthweight, parental obesity, and education level and parental smoking habit, suggested that these factors should always be assessed taking age and gender specificities into account. Finally, a relevant finding of the present analysis is that the already described association of overweight/obesity with high blood pressure22, 23, 24 was present with a similar strength in all surveys under investigation.

The present paper suffers from some limitations. First of all, the validity of comparisons between communities critically depends on the comparability of the survey methods. In our case, although it is true for anthropometric and blood pressure measurements, a large heterogeneity in the used instruments could be observed for most variables. Thus, our estimated effects of modifying factors on the risk of overweight/obesity in children might be rather biased. Second, we cannot consider our data as representative of the child population of the participating countries. Only the surveys in Cyprus were based on nationally representative data, whereas the others were conducted as smaller and regional studies. However, it should be mentioned that the principal investigators of much larger and complete analyses of prevalence and trends of both adult and childhood overweight/obesity in Europe were also facing the same problem, mainly due to the limited number of national surveys monitoring overweight/obesity in Europe, and included regional and local surveys in their analyses instead.4, 7

The prevalence data obtained from our analysis could be of value in the near future in filling the gap of information about the trends of childhood overweight/obesity in some European countries.4, 6 In fact, in the most recently published investigation of such trends, no data were reported for Cyprus, Estonia and Italy, because of the lack of prospective comparable cohorts in these countries.4 It should be noted that the surveys currently conducted in the framework of the IDEFICS project8, 9 are collecting data on child health in eight European countries, including Cyprus, Estonia and Italy. These new data, compared with those reported in this paper, will contribute to the temporal assessment of overweight/obesity based on common criteria also in countries not yet considered.

In summary, we explored the possibility to increase, with a collaborative effort, the knowledge in the field of health disorders in children by exploiting already available data. This experiment, although only partly successful, confirmed the need to improve the comparability of the epidemiological methods for the collection of data to face the childhood obesity epidemic in Europe effectively. This could be achieved only by combining resources and increasing collaboration and integration between research centres, public health authorities and stakeholders, as envisaged in European projects such as the IDEFICS study.

Conflict of interest

The authors declare no conflict of interest.

References

  1. 1

    Lobstein T, Baur L, Uauy R, IASO International Obesity Task Force. Obesity in children and young people: a crisis in public health. Obes Rev 2004; 5: 4–104.

    Article  Google Scholar 

  2. 2

    Reilly JJ . Descriptive epidemiology and health consequences of childhood obesity. Best Pract Res Clin Endocrinol Metab 2005; 19: 327–341.

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3

    James WP . The challenge of childhood obesity. Int J Pediatr Obes 2006; 1: 7–10.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. 4

    Jackson-Leach R, Lobstein T . Estimated burden of paediatric obesity and co-morbidities in Europe. Part 1. The increase in the prevalence of child obesity in Europe is itself increasing. Int J Pediatr Obes 2006; 1: 26–32.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5

    Lobstein T, Jackson-Leach R . Estimated burden of paediatric obesity and co-morbidities in Europe. Part 2. Numbers of children with indicators of obesity-related disease. Int J Pediatr Obes 2006; 1: 33–41.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6

    Lobstein T, Frelut ML . Prevalence of overweight among children in Europe. Obes Rev 2003; 4: 195–200.

    CAS  Article  Google Scholar 

  7. 7

    Berghöfer A, Pischon T, Reinhold T, Apovian CM, Sharma AM, Willich SN . Obesity prevalence from a European perspective: a systematic review. BMC Public Health 2008; 8: 200.

    Article  PubMed  PubMed Central  Google Scholar 

  8. 8

    Ahrens W, Bammann K, de Henauw S, Halford J, Palou A, Pigeot I, et al., European Consortium of the IDEFICS Project. Understanding and preventing childhood obesity and related disorders—IDEFICS: a European multilevel epidemiological approach. Nutr Metab Cardiovasc Dis 2006; 16: 302–308.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  9. 9

    Bammann K, Peplies J, Sjöström M, Lissner L, De Henauw S, Galli C, et al., on behalf of the IDEFICS Consortium. Assessment of diet, physical activity and biological, social and environmental factors in a multi-centre European project on diet- and lifestyle-related disorders in children (IDEFICS). J Public Health 2006; 15: 279–289.

    Article  Google Scholar 

  10. 10

    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.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. 11

    Cole TJ, Flegal KM, Nicholls D, Jackson AA . Body mass index cut offs to define thinness in children and adolescents: international survey. BMJ 2007; 335: 194.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12

    Huybrechts I, De Bacquer D, Matthys C, De Backer G, De Henauw S . Validity and reproducibility of a semi-quantitative food-frequency questionnaire for estimating calcium intake in Belgian preschool children. Br J Nutr 2006; 95: 802–816.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13

    Savva SC, Kourides Y, Tornaritis M, Epiphaniou-Savva M, Chadjigeorgiou C, Kafatos A . Obesity in children and adolescents in Cyprus. Prevalence and predisposing factors. Int J Obes Relat Metab Disord 2002; 26: 1036–1045.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14

    Savva SC, Tornaritis M, Chadjigeorgiou C, Kourides YA, Savva ME, Panagi A et al. Prevalence and socio-demographic associations of undernutrition and obesity among preschool children in Cyprus. Eur J Clin Nutr 2005; 59: 1259–1265.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. 15

    Savva SC, Tornaritis MJ, Chadjigeorgiou C, Kourides YA, Siamounki M, Kafatos A . Prevalence of overweight and obesity among 11-year-old children in Cyprus, 1997–2003. Int J Pediatr Obes 2008; 3: 186–192.

    Article  PubMed  PubMed Central  Google Scholar 

  16. 16

    Riddoch C, Edwards D, Page A, Froberg K, Anderssen SA, Wedderkopp N et al. The European Youth Heart Study—cardiovascular disease risk factors in children: rationale, aims, study design and validation of methods. J Phys Act Health 2005; 2: 115–129.

    Article  Google Scholar 

  17. 17

    Barba G, Giacco R, Clemente G, Venezia A, Russo P, Grimaldi C et al. The BRAVO project: screening for childhood obesity in a primary school setting. Nutr Metab Cardiovasc Dis 2001; 11: 103–108.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18

    Barba G, Troiano E, Russo P, Strazzullo P, Siani A . Body mass, fat distribution and blood pressure in Southern Italian children: results of the ARCA project. Nutr Metab Cardiovasc Dis 2006; 16: 239–248.

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19

    Marild S, Bondestam M, Bergstrom R, Ehnberg S, Hollsing A, Bertsson-Wikland K . Prevalence trends of obesity and overweight among 10-year-old children in western Sweden and relationship with parental body mass index. Acta Paediatr 2004; 93: 1588–1595.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  20. 20

    Maffeis C, Banzato C, Talamini G, Obesity Study Group of the Italian Society of Pediatric Endocrinology Diabetology. Waist-to-height ratio, a useful index to identify high metabolic risk in overweight children. J Pediatr 2008; 152: 207–213.

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21

    National High Blood Pressure Education Program Working Group (NHBPEP) on High Blood Pressure in Children and Adolescents. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 2004; 114: 555–576.

    Article  Google Scholar 

  22. 22

    Sorof J, Daniels S . Obesity hypertension in children: a problem of epidemic proportions. Hypertension 2002; 40: 441–447.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. 23

    Couch SC, Daniels SR . Diet and blood pressure in children. Curr Opin Pediatr 2005; 17: 642–647.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24

    Barba G, Casullo C, Dello Russo M, Russo P, Nappo A, Lauria F et al. Gender-related differences in the relationships between blood pressure, age, and body size in prepubertal children. Am J Hypertens 2008; 21: 1007–1010.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was carried out as part of the IDEFICS study (www.idefics.eu). We acknowledge the financial support of the European Community within the Sixth RTD Framework Program Contract No. 016181 (FOOD). The information in this document reflects the author's view and is provided as it is. No guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability.

Author information

Affiliations

Authors

Corresponding author

Correspondence to A Siani.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Pigeot, I., Barba, G., Chadjigeorgiou, C. et al. Prevalence and determinants of childhood overweight and obesity in European countries: pooled analysis of the existing surveys within the IDEFICS Consortium. Int J Obes 33, 1103–1110 (2009). https://doi.org/10.1038/ijo.2009.142

Download citation

Keywords

  • childhood obesity
  • childhood overweight
  • survey
  • Europe
  • blood pressure

Further reading

Search