In this sample, childhood obesity was significantly negatively associated with parental reports of psychological adjustment. It is important to stress that, overall, adjusted BMI accounted for only a very small fraction of the variance in reported psychological health. This indicated that childhood BMI accounts for an almost negligible amount of the variance in parentally reported child psychological adjustment across the entire adjusted weight range. Nevertheless, the tentatively modelled curvilinear relationship between weight/reported exercise and mental health strongly suggested the presence of threshold effects. These were indeed evidenced by the results of the analysis once both BMI and SDQ scores were dichotomised. In particular the risk of an emotional disorder was independently increased by obesity. Whilst higher externalising symptom factor scores were associated with obesity, the risk of exceeding the screening thresholds for Conduct Disorder were only weakly increased, once adjusted for the influence of potentially confounding variables. This apparent discrepancy is most likely to be due to the externalising factor including items from both the SDQ peer problems and hyperactivity symptoms subscales as well as the five items that make up the original Conduct Problems subscale. Thus the externalising factor represented a broader construct than that captured by the traditionally used SDQ Conduct Problems subscale. Indeed, it may be the potential difficulties in peer relationships that the externalising factor scores are detecting in children classified as obese. It is not clear why there is a trend for poorer adjustment at lower standardised BMIs. However, feeding and eating difficulties, resulting in an underweight child, may be associated with a number of psychiatric disorders, including autism spectrum disorders  and, by definition, anorexia nervosa. Moreover, low weight and failure-to-thrive may also be a marker of an adverse home environment, resulting in an increased risk of psychological problems .
Comparison with Previous Findings
This sample of children had, on average, higher BMIs than those used to derive normative values in 1990  reflecting the overall trend for increased obesity rates over the last two decades. As the IOTF recommended cut-offs for overweight and obesity were employed the rates presently reported will be lower than those already described in the HSE 2007 report, which utilised normative data from the UK only . Our observation of higher rates of obesity in girls compared to boys under 10 years is a trend that has been observed in health survey data since the mid 1990s .
Our finding of an independent association between obesity and internalising (emotional) difficulties is echoed by findings from a smaller, mainly non-White multiethnic sample of 11-14 year olds from East London. In the survey by Viner and colleagues, 17% of those of White British ethnicity (N = 267) who were classified as obese scored above screening threshold for self-reported SDQ total difficulties compared to 9% of ideal weight children of the same ethnic group . Overall differences in SDQ total difficulties scores remained significant even after controlling for gender, age and socioeconomic status. A significant, independent association with depression and chronic obesity was observed in boys (but not girls) in an all-white sample of 9-16 year olds (N = 991) drawn from the US-based Great Smoky Mountains study. The authors reported that boys with depression were 1.7 times more likely to be chronically obese than non-depressed boys after controlling for SES and age .
However, the above findings stand in contrast to those reported by several previous studies; one Dutch survey of 614 children aged 13-14 reported a statistically significant relationship between obesity and only the peer problems/prosocial behaviour subscale scores of the self-report version of the SDQ, once age, gender and educational status had been adjusted for . A separate survey of 4,320 London-based school students age 11-12 years utilised the self-report SDQ and reported only a small ( < 1 point on the SDQ) though statistically significant (p=.01) trend for the SDQ Emotional Symptoms subscale score to be raised in obese and overweight children compared to ideal weight peers . The authors attempted to control for the effect of potential confounding variables by sub-group analysis according to ethnicity, socioeconomic group (based on Townsend scores) and gender. As in our study, the authors concluded that there was no evidence that socioeconomic status was a moderating variable, although a sub-group analysis may have lacked power to detect a difference, should it have existed. Ethnicity and gender were highlighted as potential moderating factors with the closest association between obesity status SDQ total scores being observed in the subgroup of girls of white ethnicity (mean score of 12.1 [obese] vs 13.4 [ideal weight]). The lack of association between overweight, as opposed to obesity, and poor mental health observed in our cohort of British children echo the findings from a community-based survey of 2,341 French children aged 6-11 years . This latter study found no association with Conduct Problems or Emotional Symptoms SDQ scores and weight exceeding the 85th centile once sociodemographic and lifestyle (including physical activity levels) were adjusted for. These findings, along with the curvilinear relationship between adjusted BMI and emotional symptoms reported by the present study, strongly suggest the presence of a threshold effect of childhood BMI on psychological wellbeing. Thus, we would hypothesise that the risk of significant emotional problems would rapidly increase in children with BMI z-scores exceeding approximately 2.0 (i.e. exceeding the 97th centile). As with existing studies, BMI explained only around 2% of the variance in SDQ scores. Nevertheless, taking a categorical approach, obesity would appear to be associated with a clinically significant risk of poor psychological adjustment, at least in terms of emotional difficulties due to the potential threshold effects outlined above. In addition, it must be noted that the SDQ was developed as a screen for mental health problems in young people and the instrument may be less useful as a metric of wellbeing. However, the variation in published findings are unlikely to be wholly explained by the different measures employed. Rather, there may be genuine differences in the relationship between childhood obesity and wellbeing as a result of both cultural and cohort effects which require further exploration. The choice of potential mediating/confounding variables may also shape the final results.
This is not the first study to observe some relationship between BMI and externalising problems in children. Indeed, findings from both a British cohort reported higher rates of externalising problems in obese boys aged 3-5 years . Moreover, a study of a North American cohort of children of both sexes reported that children with externalising behaviour problems at 2 years old had significantly higher BMIs when followed-up at age 12 years . However, overall, the association of behavioural problems with obesity seems less consistent than that with emotional difficulties, as echoed by the present findings.
In the present study we did not observe a difference in internalising factor scores according to gender. Given the previously documented excess of depression and anxiety in adolescent females this was initially surprising. However, in the present study the average age of the study sample was only about 10 years and the gender difference in emotional problems may only become apparent in later teenage years. For example, depression is twice as common in adolescent girls compared to boys but this difference is only observed by the age of 15 years . Moreover, higher rates of comorbidity between internalising and externalising difficulties have been reported in pre-pubescent boys  and this also may have contributed to a lack of an observed gender difference.
Study Strengths and Limitations
This was a relatively complete and representative national sample of children where the effects of a number of key sociodemographic variables were able to be controlled for. Moreover, the use of multilevel modelling appropriately adjusted the standard errors of the estimates for the non-independence of observations from children nested within households. However, although there were a very large number of clusters the average number of children nested within families was small at 1.4. Indeed, given this average cluster size and the intraclass correlations for observations nested within families the design effects were relatively small, and the curve in Figure 1 would not appear very different were these not controlled for by the introduction of a random intercept to the model. Nevertheless, given the clearly hierarchical nature of the data and the risk of dependency amongst residuals from observations within each cluster we felt the use of multilevel, rather than single level, modelling was justified. Moreover, this approach provided an opportunity to explore, albeit tentatively, within family effects and cross-level interaction. However, when considering the power of multilevel modelling studies both cluster number and size, as well as the parameters being estimated must be taken into account. When estimating parameters associated with fixed-effects (e.g. the effect of obesity status externalising factor scores) the number of clusters are of prime importance- where fewer than 50 clusters exist parameter estimates may be biased downwards . Therefore it can be assumed that any fixed effects were estimated accurately. However, in this analysis we also introduced a random slope parameter in order to investigate the possibility of cross-level interaction. Again, cluster size is of secondary importance to the number of clusters with a recommendation of at least 100 groups with around 10 individuals in each group . However, in our study average cluster size was considerably lower than this, although the number of clusters was very large. Therefore the parameters associated with potential cross-level interactions may be relatively poorly estimated and we may not have detected a significant effect where one existed. This is a potential limitation of the present study. Nevertheless, our findings were in keeping with that of Drukker et al. who also reported that SES did not appear to be a moderating factor. However, neither the present or these latter findings can be taken as definitive evidence of this as both studies may be subject to low power.
Ideally, more detailed biometrics would have been utilised to derive obesity status. However, the IOTF recommended cut-offs correlate to a moderate to high degree with more sophisticated methods to estimate adiposity . Whilst valid BMIs were obtained, self-reported physical activity levels may be less reliable than more objective based estimates, such as those based on accelerometry or heart rate, although moderate levels of correlation are generally reported . No information on pubertal status was available in this sample. The relatively small numbers of non-white ethnic groups within this survey, whilst reflecting the general population from which the sample was drawn, makes it difficult to draw firm conclusions about ethnic differences. Probably the most significant limitation in this survey was that data on psychological wellbeing was restricted to the parentally reported SDQ, in the absence of the SDQ impact supplement. The use of SDQ internalising and externalising factor scores as the main outcome measure may have been more appropriate than using SDQ subscale scores consisting of only five items each. Moreover, parentally reported SDQ scores may be more sensitive to emotional disturbance than the self-report version of this instrument in 11-15 year olds . Indeed, the use of totalled subscale scores in previous studies could partly explain the failure to report firm associations between obesity and emotional problems in young people. The SDQ is widely used and well validated, but the addition of self-report versions for those children over ten years would have resulted in increased sensitivity for the screening for potentially clinically significant disorders [35, 36]. The exclusion of the impact supplement from the survey pack may have reduced the reliability of the screening thresholds for conduct and emotional disorders as defined by the respective SDQ subscales. Despite this, the relative risks may have remained relatively unchanged as the decreased accuracy would apply to both obese and non-obese children. In addition, we did not have any detailed information of family environment available, although we felt it was important to include family level economic status as this is known to be a risk factor for both childhood obesity  and certain psychological problems .
Directions for Future Research
The conflicting findings from previously published research suggest that further datasets containing relevant measures of wellbeing and biometrics should be utilised in replicating the present analyses. However, in order to model hypothesised underlying mechanisms driving the association further longitudinal data are required. A number of ongoing studies of health and development are potential sources of such information, though it may be that new studies based in mixed qualitative/quantitative methodologies would be more effective in exploring this area and contextualising classes of observed trajectories. There are some indications that in adults poor mental health (and in particular, depression) may precede obesity . There is little longitudinal research published regarding under 18s but the available evidence suggests this predominant direction of causality may also apply to children and adolescents. One US based longitudinal study involving 9,374 adolescents reported no association between obesity and depression at initial assessment. In contrast, at one year follow-up, depression significantly predicted onset of obesity (OR 2.05; 95% CI 1.04 to 4.06) independent of self-esteem ratings, conduct problems, socioeconomic status, gender and parental obesity . A separate cohort study also suggested that childhood depression was a risk factor for obesity in adulthood, at least for women . 'Temperamental Difficulties' were also noted to predict weight gain in a cohort of 138 North American children aged between 4 and 9 . From these scant studies a tentative model could be proposed whereby temperament (largely hereditary in nature), interacting with early environment gives rise to a tendency to dysphoric mood and low self-esteem that increases the risk of over-eating. The reasons for the non-linearity of the relationship between BMI and psychological adjustment require further exploration. It may be that socio-cultural factors are the predominant influence, with children who obviously exceed the normative range of adiposity being at an exponentially increasing risk of adverse experiences, such as peer rejection.