Pediatric Highlight

International Journal of Obesity (2005) 29, 373–380. doi:10.1038/sj.ijo.0802914

Social class, parental education, and obesity prevalence in a study of six-year-old children in Germany

A Lamerz1, J Kuepper-Nybelen2, C Wehle1, N Bruning1, G Trost-Brinkhues3, H Brenner2, J Hebebrand4 and B Herpertz-Dahlmann1

  1. 1Department of Child and Adolescent Psychiatry, University Hospital Aachen, Neuenhofer Weg 21, Aachen, Germany
  2. 2Department of Epidemiology, German Center for Research on Ageing, University of Heidelberg, Bergheimerstr. 20, Heidelberg, Germany
  3. 3Public Health Service, Vereinsstr. 25, Aachen, Germany
  4. 4Clinical Research Group, Department of Child and Adolescent Psychiatry, Phillips University of Marburg, Hans-Sachs-Str. 6, Marburg, Germany

Correspondence: Dr A Lamerz, University Hospital Aachen, Department of Child and Adolescent Psychiatry, Neuenhofer Weg 21, D-52074 Aachen, Germany. E-mail:

Received 11 May 2004; Revised 30 November 2004; Accepted 24 January 2005.





To assess the association between socioeconomic status (SES) and childhood obesity, and which factor in particular stands out in relation to obesity.



When 2020 children attended their obligatory health exam prior to school entry in the City of Aachen, Germany, 1979 parents (97.9%) filled out a questionnaire on their child's weight development and on indicators of their family's SES in a cross-sectional survey. In addition, standardized measures of weight and height were taken. More detailed information on several different SES variables, such as parental education, occupation, income, family constellation, single parenthood, and the location and size of the family residence was obtained by personal interviews in a subsample of all native German speaking children with a BMIgreater than or equal to85th percentile, defined as cases (n=146), and with a BMI between the 40th and 60th percentile, defined as controls (n=221).



The indicators of parental education were most strongly associated with children's obesity. There was a strong dose–response relationship between a composed index of social class and obesity. Children of the lowest social status had a more than three-fold risk to be obese than children of the highest social status in the screening population (OR: 3.29, CI: 1.92–5.63).



The findings established a strong relationship between parental years of education and childhood obesity. Prevention and treatment programs should endeavor to better target undereducated parents and their young children at high risk.


children, socioeconomic status, cross-sectional survey, case–control study, overweight



The prevalence of obesity is on the rise in all industrialized countries and has become a global epidemic.1 In a national representative study in the Netherlands in 1996, over 20% of 6 y olds exceeded the 90th body mass index (BMI) percentile identified in a national representative study in 1980.2 A recent study demonstrated that German preschool children have gained a higher BMI during the last 30 y;3 a similar trend has also been observed in other regions of the world.4, 5, 6, 7 The mechanism underlying the secular trend towards increasing BMI seemingly affected children in the upper weight range more than those in the lower range.3 Several risk factors for the development of obesity, such as familial patterns of obesity, have been well identified.8 Socioeconomic status (SES) has been described as inversely related to obesity in adulthood.9, 10, 11, 12 A systematic review of the literature on childhood predictors of adult obesity identified nine studies that investigated the effect of social class and subsequent obesity in childhood and 12 studies that spanned the period from childhood to adulthood. Of these 12 studies, all but one showed an inverse relationship, a lower risk of fatness associated with higher social group. Of the nine studies limited to childhood, five showed an inverse relationship and one showed an inverse relationship only in girls but not in boys.11, 13 The inverse relationship between SES and obesity in adults was more distinct and consistent in women than in men, independent of the variable that defined SES.14, 15, 16

However, SES is not a generally defined factor; instead, it is a crude summary measure of variables. Unfortunately, most studies define social class only by either one or two variables. The German study by Langnase et al9 on social class differences in overweight children, for example, defined the measure of social class only by parental school education. The two reviews on SES and obesity found little consensus about conceptualizing and measuring SES.9, 11 The most frequently used indicators for SES were income or education and less often occupation.16

The aim of the present epidemiological study was to assess the association between SES and childhood obesity and to provide differentiated evidence on which particular socioeconomic factors are most significantly associated with obesity. The obligatory school health examination offered the opportunity to investigate the complete age-group of children living in the City of Aachen, making selection bias very unlikely. We collected data on several different factors, such as the parental education, their occupation, their income, family constellation, single parenthood, and the location and size of the family residence. Better identification of these factors should help to establish more precisely targeted prevention programs.



Study design and study population

Aachen, Germany, is a city of 254 000 inhabitants on the border to the Netherlands and Belgium. All children in Aachen who attended the obligatory school entrance health examination for the 2002/2003 school year and who were born between 1 July 1995 and 30 June 1996 were asked to participate in a voluntary cross-sectional survey on obesity in childhood. The enrollment took place in cooperation with the Aachen Public Health Service between December 2001 and July 2002.

For the 2020 children who were born in the specified period, 1979 parents (97.9%) agreed to fill out a 42-item screening questionnaire on their SES and the child's weight development. In a pilot study, all questions on the questionnaire were tested and evaluated on a sufficient number of parents in a clinical setting and in focus groups (including those with a low SES) to ensure that the participants of the study would fully understand what was being asked. The screening questionnaire was presented in German; however, one of our Research Assistants was always available at the survey location and was able to explain unclear items to the parents.17 Anthropometric data such as height and weight were collected from all children in a standardized form (measured to the nearest 1 cm and the nearest 100 g in underwear and standing) on a digital scale (Seca column scale 910 with telescopic measuring rod, Hamburg, Germany). The BMI was calculated for all children as it is the simplest and most common used assessment tool for categorizing childhood obesity.18

Within this cross-sectional survey, we conducted a case–control study to obtain more detailed information on a subsample of children, which could not be obtained from all children due to limited resources. All children with a BMI greater than or equal to85th percentile were defined as cases and all children with a BMI between the 40th and 60th percentile were defined as controls (Table 1). In order to categorize the children, the average of the BMI-percentiles of the school entry health exams in Aachen of the years 1998–2000 served as reference percentiles. All children in the case–control study had to speak German as their native language as an inclusion criterion in order to establish a homogenous group with respect to cultural background. German language capacity was evaluated in a standardized interview by the physician from the Public Health Service and in addition by the Research Assistant always present at the location.17 Of all 277 children with a BMI greater than or equal to85th percentile, 97 children (35%) did not speak German as their native language and 34 refused participation (81% response rate). Of all 350 children with a BMI between the 40th and 60th percentile, 73 children (21%) did not speak German as their native language and 56 refused participation (80% response rate).

Variables of SES

All parents who participated in the cross-sectional survey were asked for the following indicators of SES: (1) Years of education of the parent who filled in the questionnaire and his/her partner. (2) Occupation of either parent. (3) Number of people permanently living at home. (4) Living space per person in m2. All parents who further participated in the case–control study underwent standardized interviews by trained interviewers and were asked the following additional questions pertaining to SES: (1) marital status; (2) type of school diploma and higher education; (3) hours of work on weekdays and weekends of either parent; (4) household net-income; and (5) location of home with respect to distinct districts of the City of Aachen.

Statistical analysis

The BMI of each child and its equivalent percentile rank was calculated by a German internet-based reference program (, which uses data obtained from 17 epidemiological studies in Germany, which in total are based on anthropometric data of 17 147 boys and 17 275 girls in the age range of 0–18 y.19 In bivariate analysis we investigated the relationship between socioeconomic factors and obesity within both the screening and the case–control study. In the screening population, children above the 90th percentile of BMI were compared to children below the 90th percentile. In the case–control study, where more detailed data were collected, cases (children above the 85th percentile of BMI) were compared to controls (children between the 40th and the 60th percentile). We conducted multiple logistic regression analyses to assess the independent contribution of each socioeconomic risk factor to childhood obesity. Additional adjustments were made for gender and for the BMI of parents. The multiple regression model was tested for multicollinearity, which was not relevant as the variance inflation factor was below 10 for all variables included in the model. Within the case–control study, a stepwise forward regression was conducted to establish the most influential independent socioeconomic factors associated with obesity.

In addition, socioeconomic variables were summarized in a social strata index. The following most influential variables, each divided into up to four categories, entered the index for the screening population to establish a cumulative risk of social status: parental education according to the German school system (categories: 4 points for less than 9 y and therefore without a graduation degree, 3 points for 9 y, 2 points for 10–12 y, or 1 point for 13 y of education), living space in square meter per person living in the household (categories: 4 points for <20 m2, 3 points for 20–29.99 m2, 2 points for 30–30.99 m2, or 1 point for 40+ m2), and single parenthood (categories: 3 points for 'yes', or 1 point for 'no'). Four social class categories were formed and scored accordingly, with the highest category for SES receiving the lowest score.

We assessed the relation between this social strata index and obesity in the screening population with obesity as the dependent variable and the index categorized in quartiles as the exposure variable. The results are presented as crude and adjusted odds ratios with their 95% confidence intervals.



Study population

The study populations of the cross-sectional survey and the case–control study are presented in Table 1 with regard to basic sociodemographic and anthropometric characteristics. Of the 1979 participants, 1008 (50.9%) were boys and 971 (49.1%) were girls. The mean age of the children was 5.8 y (s.d. 0.4, range 5–7 y). Of the 16.1% non-German children in the cross-sectional survey, 38.8% were of Turkish nationality. The mean weight and height of all children in the cross-sectional survey were 22.3 kg (48th percentile according to German reference population based on Kromeyer-Hauschild et al19) and 118.5 cm (45th percentile according to German reference population based on Kromeyer-Hauschild et al19). The mean BMI was 15.8 kg/m2 (51st percentile according to German reference population based on Kromeyer-Hauschild et al19).

Socioeconomic factors associated with obesity in the screening population

The frequencies of the various socioeconomic factors of the screening population and their association with being in the 90th percentile or higher of BMI are presented in Table 2. In bivariate analysis comparing children above the 90th percentile of BMI with children below the 90th percentile, the children's obesity was strongly associated with parents' educational level and moderately associated with the living space per person. Specific interaction analyses between all socioeconomic factors listed in Table 2, and gender revealed no significant differences between boys and girls. After adjustment for all other socioeconomic factors in this table as well as for gender and for the parents' BMI, the maternal educational level was the only SES variable independently associated with childhood obesity. Children of mothers with no school degree had an almost three times higher risk to be obese than children of mothers with 13 y of school. Stratified analysis by BMI of the parents revealed that paternal and maternal education was particularly strongly associated with overweight in children in the subsample of both parents being overweight (BMI>25 kg/m2).

Association of social strata index and obesity

The association of social status, measured as a cumulative index of different socioeconomic variables, and obesity is presented in Table 3. Among children with the lowest score (highest SES), 5.2% had a BMIgreater than or equal to90th percentile; among children with the highest score (lowest SES), 15.3% had a BMIgreater than or equal to90th percentile. Children of the lowest social status had a 3.3-fold higher risk to be obese than children of the highest social status.

Socioeconomic factors associated with obesity in the case–control study

In the bivariate analysis of the relationship between several socioeconomic factors and obesity in the case–control study, low education of parents, mothers not pursuing an out of home occupation, and the parents' type of occupation seemed to be associated with children's overweight. Children of parents with nine or fewer years of education had a three-fold higher risk to be obese and fall into the case category than children of parents with 13 y of education. Children of mothers who remained at home had a 1.68 higher risk to fall into the case category, and children of blue-collar working mothers had a 3.98 higher risk. None of the other SES variables listed in Table 4 showed an association with the weight of the child.

The educational level of the father and the type of occupation of the mother remained as independently associated factors with childhood obesity after adding all socioeconomic variables listed in Table 4, gender, and the BMI of the parents in a stepwise regression model. Children of fathers with nine or fewer years of education had a 3.19 higher risk to be obese (95% CI: 1.72–5.94); children of mothers who were self-employed had a 2.76 higher risk to be obese (95% CI: 1.02–7.04); and children of mothers who were blue-collar workers had a 2.59 higher risk to be obese and fall into the case category than children of mothers who were white-collar workers (95% CI: 1.23–5.47). Among the self-employed mothers, 15 (75%) followed 13 y of education and 47% worked more than 4 h per day outside their homes. The effect of assortative mating was tested by calculation of the Spearman correlation between maternal and paternal education in years (r=0.65).



Although several studies have focussed on the association between SES and obesity, this is the first study to not only demonstrate that the association already prevails in early childhood but to also illustrate which socioeconomic factors in particular determine this inverse relationship. Most studies have defined SES by either one or two variables, presuming that the respective variables best describe the crude summary measure of variables defined with the term SES. This study collected a broad range of variables defining SES; however, parental education was the variable most strongly related (in an inverse manner) with childhood obesity. In addition, a social strata index, defining the summary measure of socioeconomic variables into a social status scaling system, revealed a strong inverse dose–response association between social class and childhood obesity.

A limitation of the study is that children's obesity was only defined by BMI percentile. One might argue that there is a considerable variability in findings depending on how or by which index overweight and obesity are defined. Peng et al20 as well as Lobstein and Frelut6 could demonstrate that prevalence of childhood overweight and obesity was dependent on method and assessment criteria, and changed considerably when measuring other variables than BMI (for example, percentage of body fat or skinfold thickness). However, BMI and BMI percentiles are widely respected criteria for defining obesity in children and adults21 and even allow comparisons between different populations.22

Another limitation is that we did not use a longitudinal approach in order to study the association between children's obesity and SES, taking into account secular trends of increasing obesity.3 The social structure of the German society has changed remarkably over the last years with an on average increase of household-income and single-parent households, as well as a rise in the number of families who are dependent upon social welfare.23, 24 Nevertheless, other studies have demonstrated that the inverse relationship between SES and subsequent obesity has been constant over the years in spite of societal changes.25, 26 Obesity may lead to a social decline, and/or a low social class may promote the development of obesity.11 In addition, a longitudinal approach would have limited the study findings because of a much smaller sample size.

The City of Aachen is a typical German city with respect to the population's age distribution, proportion of non-German nationals, and SES, such as unemployment rates and the proportion of inhabitants receiving welfare payments.23, 24 Two particular strengths of this study were the large number of participating children and the very high participation rates, making selection bias very unlikely. The presented data on height and weight are representative of a German preschooler population, since the equivalent figures closely correspond to the German reference population as described by Kromeyer-Hauschild et al19 (Table 1).

In line with several other studies presented by Parsons et al,11 we found a significant association between a low SES and obesity in preschool children without any difference between boys and girls. Social status scaling in both study populations revealed a clear association between low social status and childhood obesity. The index reveals a cumulative risk of the three different socioeconomic variables that entered the analysis (parental education, living space, and single parenthood), defining social class not only by a single variable but a combination of variables.

In order to establish independently associated factors for the summary measure SES for overweight in children, and in order to present a ranking of those factors, a multiple logistic regression was conducted. Adjustments were made for potential confounding factors as described in the literature, such as gender, parental BMI, education, and employment, living space per person and single parenthood.9, 11, 13, 14, 15, 16, 27 The most important single independently associated factor for a child being in the 90th percentile or higher of BMI in the screening population was maternal education. Obesity was particularly prevalent in children whose mothers had less than 9 y of education. Similar results were found in the case–control population, which included only children with a German mother-tongue. Of all the variables listed, paternal education and type of maternal occupation were the most influential independent factors in a stepwise forward regression for childhood obesity. The fact that maternal education did not turn out to be a significant independent predictor of children's obesity in the case–control study is mainly due to the more limited power given the much smaller sample size. High assortative mating of parental education might explain the similar effect of maternal and paternal education in the two populations.

The relationship of SES to obesity is believed to increase with age;28 however, it is already prevalent as early as 6 y of age. The fact that young children usually spend more time with their mothers than their fathers29 might explain the finding that maternal education in the screening population had a greater influence on childhood obesity than paternal education. Mothers are also generally more responsible for diet intake and upbringing of their children than fathers.30, 31 Nonetheless, nine or less years of education of either of the parents is the highest risk factor for childhood obesity. Blue-collar work is very strongly associated with limited school education, explaining the result of the stepwise regression in the case–control study. However, children of self-employed mothers, in spite of high educational levels, also had a high risk of being obese. Self-employed mothers who work more hours outside their homes might probably spend less time with their children and, hence, will have less control over food intake, eating habits, and physical activity levels of their children. Anderson et al32 showed in their study that it is higher socioeconmic status mothers whose work intensity is particularly deleterious for their children's overweight status.

Obesity is associated with a higher morbidity for a number of chronic diseases such as coronary heart disease, hypertension, and diabetes mellitus, which might increase the risk for inability to work and thus lower income.33 There are several potential explanations for the association between low parental education and childhood obesity.27 Parents with a lower educational level tend to bottle-feed their children more than parents with a higher educational level, because the latter are being better informed about the advantages of breastfeeding.34 Differences in cultural and social norms between parents of high and low education might be another reasonable explanation. Dieting and healthy weight control practices such as reducing high energy and fat intakes and increasing exercise are more common in women of a higher SES.35 In addition, children who attended higher social status schools exhibited more negative attitudes towards obesity.36 A further consideration is the role of the emotional development in early life. Lissau and Sorenson37 could demonstrate that dirty and neglected children had a much greater risk of adult obesity than ordinarily groomed children. Adverse economic circumstances, marital conflict and negative life events seem to be much more frequent in families with a lower SES. These parents might be less involved in the lives of their children, which might then lead to more overeating.38 Childhood socioeconomic conditions have a long-lasting impact on the risk of adult obesity.39 Socially and economically disadvantaged children are likely to remain in their low social class.

The findings of the present study should lead to more accurate targeting of prevention and intervention programs for obesity in childhood, ensuring a better school education for lower social classes, and thus eventually to a lower risk for obesity in the next generation. Preventive community and school-based programs should start early in childhood to overcome social health inequalities.



This representative cross-sectional survey on 1979 children and case–control study on 367 children in the German City of Aachen have convincingly demonstrated that social status is inversely associated with childhood obesity as early as age six. There was a significant relationship between parents' years of education and childhood obesity, and among the many other ascertained SES variables, parental education was the most important SES variable that accounts for the SES-obesity association. Future studies should focus on early childhood obesity and prevention programs should endeavor to better target undereducated parents and their young children at high risk.



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We would like to thank the entire staff of the Aachen Public Health Service and the medical students Sandra Schäfer, Christine Schell and Martina Selzner for their support and cooperation. This study was funded by the German Society for the Advancement of Scientific Research (DFG Grants HE 1809/5-1 and BR 1704/4-1) and by the START-Program of the Medical Faculty, RWTH Aachen, Germany.



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