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Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2006-1714
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The Journal of Clinical Endocrinology & Metabolism Vol. 92, No. 2 517-522
Copyright © 2007 by The Endocrine Society

Increasing Body Mass Index z-Score Is Continuously Associated with Complications of Overweight in Children, Even in the Healthy Weight Range

Lana M. Bell, Sue Byrne, Alisha Thompson, Nirubasini Ratnam, Eve Blair, Max Bulsara, Timothy W. Jones and Elizabeth A. Davis

Telethon Institute for Child Health Research, Center for Child Health Research (L.M.B., S.B., A.T., N.R., E.B., M.B., T.W.J., E.A.D.), Schools of Psychology (S.B.) and Population Health (M.B.), University of Western Australia, Crawley, Western Australia 6009, Australia; and Department of Endocrinology and Diabetes (L.M.B., A.T., T.W.J., E.A.D.), Princess Margaret Hospital, Subiaco, Western Australia 6008, Australia

Address all correspondence and requests for reprints to: Dr. E. A. Davis, Princess Margaret Hospital, Roberts Road, Subiaco, Western Australia 6008, Australia. E-mail: Elizabeth.davis{at}health.wa.gov.au.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: Overweight/obesity in children is increasing. Incidence data for medical complications use arbitrary cutoff values for categories of overweight and obesity. Continuous relationships are seldom reported.

Objectives: The objective of this study is to report relationships of child body mass index (BMI) z-score as a continuous variable with the medical complications of overweight.

Design: This study is a part of the larger, prospective cohort Growth and Development Study.

Setting: Children were recruited from the community through randomly selected primary schools. Overweight children seeking treatment were recruited through tertiary centers.

Participants: Children aged 6–13 yr were community-recruited normal weight (n = 73), community-recruited overweight (n = 53), and overweight treatment-seeking (n = 51). Medical history, family history, and symptoms of complications of overweight were collected by interview, and physical examination was performed. Investigations included oral glucose tolerance tests, fasting lipids, and liver function tests.

Main Outcome Measure: Adjusted regression was used to model each complication of obesity with age- and sex-specific child BMI z-scores entered as a continuous dependent variable.

Results: Adjusted logistic regression showed the proportion of children with musculoskeletal pain, obstructive sleep apnea symptoms, headaches, depression, anxiety, bullying, and acanthosis nigricans increased with child BMI z-score. Adjusted linear regression showed BMI z-score was significantly related to systolic and diastolic blood pressure, insulin during oral glucose tolerance test, total cholesterol, high-density lipoprotein, triglycerides, and alanine aminotransferase.

Conclusion: Child’s BMI z-score is independently related to complications of overweight and obesity in a linear or curvilinear fashion. Children’s risks of most complications increase across the entire range of BMI values and are not defined by thresholds.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
THE CONTINUING GLOBAL increase in overweight and obesity is reported in both pediatric and adult populations. Childhood obesity is associated with significant long-term medical consequences, including hyperinsulinism, type 2 diabetes (T2DM), hypertension, orthopedic complications, obstructive sleep apnea (OSA), cardiovascular disease, dyslipidemia, and hepatic steatosis (1, 2, 3). Childhood obesity also frequently persists into adulthood, with up to 80% of obese children reported to become obese adults (4). However, the age of onset and natural history of childhood obesity and its complications are not well defined.

Because a child’s body mass index (BMI) changes with age, measures of BMI alone are inappropriate for comparisons of overweight and obesity among groups of children. Unlike adults in whom BMI values can be compared directly, if BMI is to be used as a surrogate measure of adiposity in children, it must be adjusted for age and gender. Most studies have categorized the adjusted value as normal, overweight, or obese, but an alternative is to use the age- and gender-specific BMI z-score, which provides a continuous variable.

Most analyses of the complications of childhood overweight and obesity have categorized both child’s weight (e.g. "obese" or "overweight") and the complications (e.g."presence" or "absence") using arbitrary, percentile-based criteria (5, 6, 7). Data about the risks and prevalence of comorbidities in childhood in different populations are emerging, usually reported as relative risks of comorbidities for children in overweight or obese categories, compared with normal weight (6, 8, 9, 10, 11, 12).

Category-based risks assessment is clinically useful and, perhaps for this reason, there is little published material examining continuous relationships between increasing BMI z-score and the complications of overweight (7, 13, 14). The tacit assumption of linear relationships between BMI z-score and complications is seldom tested (15). Some studies approach a continuous analysis by using smaller categories and BMI percentile groups, and have suggested that these relationships may not be linear (6, 14). The aim of this study was to examine relationships between child BMI z-scores as a continuous measure of overweight and the adverse consequences of overweight. This approach allows the exploration of the form of the relationships or identification of any threshold effects between increasing BMI z-score and complications. There are implications for public health and health education; a threshold effect would suggest targeting the children above BMI thresholds, whereas a continuous effect would suggest a population-based approach for all children to decrease the future disease burden.

The Growth and Development Study is a prospective cohort study of Western Australian primary school children (aged 6–13 yr) that seeks to determine the causes and consequences of childhood overweight and obesity. This report presents an analysis based on the continuous predictor of BMI z-score measured during a medical evaluation of children involved in the study in 2004.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Recruitment

This study is part of the larger Growth and Development Study, which has recruited a large cohort of children and will follow them longitudinally with the aim of identifying biological, psychosocial, and environmental factors that predict the development and persistence of overweight and obesity in children. It has been approved by the Princess Margaret Hospital Ethics Committee.

Participants were recruited into the study two ways. All children aged 6–13 yr seeking treatment for overweight/obesity at a tertiary pediatric hospital outpatient department were approached (n = 51), and 100% consented to participate in the study. Nontreatment seeking children were recruited from primary schools. To identify overweight and obese children, four primary schools in the Perth metropolitan area were selected at random by computer software. All children with parental consent who were present at the selected schools during the site visit were weighed and measured. All measures were taken in triplicate with the mean score recorded. BMI (weight/height2) was calculated for each child. Children were classified as overweight or obese using the Cole et al. (16) age- and gender-specific overweight and obese cutoffs of BMI for children. All families with children classified as overweight or obese (n = 75) were approached and 53 (71%) consented to participate. In each class, a similar number of children who were not overweight were also approached (n = 92) and 73 (79%) consented to participate. Additional criteria for participation were that at least one parent agreed to participate and that parent had sufficient English to complete the interviews. Siblings of participating children were also invited to participate.

Participating children and a parent attended for an assessment interview and physical examination. Exclusion criteria included obesity secondary to a known medical condition and treatment with medication known to affect body weight, e.g. stimulant medication.

Assessment

The children of all consenting families had a comprehensive medical assessment by the same pediatric fellow (L.M.B.). A structured interview recorded demographic parameters, the child’s medical and birth history, the child’s reported symptoms of complications of overweight, and family history. Specific complications asked about included musculoskeletal pain, symptoms of OSA, enuresis, headache, and psychological issues. Distractor questions about specific health issues not expected to be a complication of obesity, such as tonsillitis, allergies, and asthma were also asked. Height and weight together with waist and hip circumference were measured. A full physical examination and pubertal assessment were performed, looking specifically for complications of overweight such as hypertension, acanthosis nigricans (AN), pain and range of joint movement, gynecomastia, hirsutism, and acne. The participating parent’s height and weight were measured (>99% were mothers), and the nonparticipating parent’s height and weight was reported. Investigations included an oral glucose tolerance test (OGTT) with blood glucose, insulin, and C-peptide levels measured at all time points, fasting lipid profile, and liver function tests.

Measurements

Weight was measured (in kilograms to two decimal places) in light clothing without shoes using a digital balance scale. Height was measured with a wall-mounted Holtain stadiometer (to the nearest millimeter) using the stretch technique. BMI was calculated as weight/height2 and expressed as kilograms per square meters. Waist and hip circumference were measured using a standard tape measure to the nearest 0.5 cm. Systolic (SBP) and diastolic (DBP) blood pressure were measured in the seated position with a Critikon Dinamap 8262-H4139 and an appropriately sized cuff on the right arm. These values were obtained as the average of three measurements. OGTT were carried out after an overnight fast (1.75 g of oral glucose solution per kilogram of body weight, maximum 75 g).

Plasma glucose was measured using the colorimetric method (VITROS GLU; Ortho-Clinical Diagnostics, Rochester, NY). Plasma insulin was determined by chemiluminescent immunometric assay (IMMUNLITE 2000; Diamond Diagnostics, Holliston, MA). Cholesterol, low-density lipoprotein (LDL), high density lipoprotein (HDL), triglycerides (TG), and alanine aminotransferase (ALT) were all were measured by colorimetric method (VITROS CHOL and VITROS 250, Ortho-Clinical Diagnostics).

Statistical analysis

Analysis was performed with the SPSS statistical package (SPSS, Chicago, IL) and Stata 8.0 (StataCorp. 2003 Stata Statistical Software: Release 8.0; Stata Corporation, College Station, TX). A P value of 0.05 or less was considered statistically significant.

Categorical variables were used to indicate the presence or absence of reported comorbidities, and for the examination finding of AN. Adjusted logistic regression was used to model binary outcomes with odds ratios and 95% confidence intervals reported.

Continuous outcome variables were used for child’s BMI, blood pressure, and all blood test results. Adjusted linear regression was used to model each of these outcomes separately. Age- and sex-specific BMI z-scores were used as a continuous dependant variable for each model [calculated from the 2000 Centers for Disease Control and Prevention Growth Reference, USA (17, 18)]. Age and sex-specific blood pressure z-scores were used for age analysis of blood pressure (19). Insulin levels were not normally distributed and were log transformed. The Socio-Economic Indexes for Areas index of relative advantage/disadvantage derived from 2001 data from the Australian Bureau of Statistics was used at the level of Census District (smallest assessment level comprising approximately 200 households) to adjust for relative socioeconomic status (SES). For all models, the best fitting regression line (considering all squares, cubes, and interactions) has been fitted.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
A total of 177 children were recruited from the community- and hospital-based arms of the study in 2004, 91 (51.4%) female, 86 (48.5%) male.

Demographics and anthropometry

Demographic and anthropometric parameters are shown in Table 1Go. As children were recruited at different ages, parental age at child’s birth was used. Self-identified ethnicity was given as Australian Peoples (Australian Bureau of Statistics classification) for 87% of children; 3% identified as Australian Aboriginal, and 10% as other ethnicity. The median number of people per household was four, and 19.8% of children came from single-parent families. Apart from a marginal difference in SES, there were no significant differences found in any parameter due to the method of recruitment of subjects (community vs. clinic). SES was controlled for in all analyses.


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  		TABLE 1. Demographic and anthropometric parameters of the cohort (n = 177)

 
SES, parents’ ages, birth data (gestation and birth weight), family structure, and mothers’ (measured) and fathers’ (reported) BMI were entered into the model for child’s BMI z-score. Only maternal and paternal BMI remained significantly associated with child’s BMI z-score. For every unit increase in maternal BMI, child BMI z-score increased by 0.073 (P < 0.001), and for every increase in reported paternal BMI, child BMI z-score increased by 0.095 (P < 0.001). Figure 1Go shows each parent’s BMI plotted against their child’s BMI z-score, with the adjusted regression line plotted (model R-square 0.330). Many parents of normal weight children are overweight or obese.


Figure 1
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  		FIG. 1. Parental BMI and child BMI z-scores. Scatter plot and linear regression equation lines.

 
Dichotomously categorized complications

The relationships between child’s BMI z-score and each of the dichotomously categorized complications of obesity (musculoskeletal pain, OSA, headache, teasing/bullying, anxiety, depression, and enuresis), as well as health issues independent of obesity, were investigated. BMI z-score was not related to child’s history of asthma, tonsillitis, otitis media, grommet insertion, eczema, or allergy (inhalational or ingested). After controlling for SES, parents’ ages, parents’ own history (of musculoskeletal pain/OSA/headache, etc.), child’s age, and sex there was a positive relationship between BMI z-score and a number of complications, and all were statistically significant except for anxiety and enuresis (see Table 2Go). The odds ratios were greatest for the psychological complications of overweight and obesity (depression, bullying, and teasing).


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  		TABLE 2. Odds ratios for reported symptoms of overweight by BMI score

 
AN was present in 10.7% of children, and for each unitary increase in BMI z-score, the adjusted odds ratio for AN consistently increased by 11.54 (P = 0.002). For positive paternal history of T2DM, the adjusted odds ratio for AN was 13.09 (P = 0.010).

Continuously categorized complications

Both SBP and DBP z-scores increased in a linear relationship with BMI z-score (P ≤ 0.001 and P = 0.021, respectively; see Fig. 2Go, A and B). The increase in SBP per unit increase in BMI z-score was greater than that of DBP.


Figure 2
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  		FIG. 2. A–H, Comorbidities and complications of overweight and child BMI z-score. Each assessed separately, adjusted for child’s BMI z-score, age, sex, SES, mother’s and father’s ages, and each parent’s own history of these complications (linear regression).

 
Fasting blood tests and OGTTs were successfully completed in 146 (82.5%) children. Regression analysis was used to separately assess each test result with increases in child BMI z-score. Adjustment was made for parental history of T2DM and dyslipidemia, and child’s age, sex, SES, presence of AN, waist to hip ratio, and SBP and DBP z-scores. The coefficient of child BMI z-score and/or the square of child BMI z-score remained statistically significant in the model (P ≤ 0.05) for insulin at all time points, blood glucose level at time 120 min, and fasting c-peptide. Linearly, each unit increase in child BMI z-score increased the log of the fasting insulin by 0.050 (95% confidence interval between 0.002 and 0.093) (model R-square 0.234; see Fig. 2CGo). The log of insulin concentration at both 60 and 120 min of the OGTT was curvilinearly related to BMI z-score (P = 0.02, R-square 0.256 and P = 0.03, R-square 0.217), as was fasting c-peptide (P = 0.005, R-square 0.406) suggesting more rapid increases at the extremes of BMI z-score. BMI z-score did not remain significant in the model for fasting or 60 min blood glucose level.

The relationship between child BMI z-score and ALT showed a linear increase across BMI values. However, for BMI z-score greater than 2.00, a further increase was seen in some individuals. A significant curvilinear relationship was seen with BMI z-score and both HDL (P = 0.021, R-square 0.149) and TG (P = 0.021, R-square 0.226; see Fig. 2Go, F–H). HDL and TG show unfavorable profiles at both, but particularly the upper, extremes of BMI z-score. The relationship between BMI z-score and total cholesterol was statistically significant (P = 0.029, R-square 0.120); however, the association was greater with negative rather than positive BMI z-scores. There was no relationship between BMI z-score and LDL.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
The number of overweight and obese children is increasing worldwide (20, 21, 22). Some reports show the distribution of BMI is increasingly right skewed (23, 24), whereas others suggest a shift across the entire spectrum of childhood BMI (25, 26). With either scenario, increases in obesity-related comorbidities can be expected to follow.

Odds ratios for childhood obesity are known to increase with parental obesity (24, 27, 28). However, no previous studies have reported a continuous adjusted linear relationship between parent BMI and child BMI z-score.

In this report, we have analyzed symptoms, examination findings, and investigation results and all change in a continuous manner with child BMI z-score.

Hypertension, high total cholesterol, low HDL, high LDL, and high TG are recognized risk factors for cardiovascular disease in adults. In children, low HDL and high TG may be more strongly related to BMI (6, 8, 15). This study found a continuous relationship with increasing BMI z-score for these measures. The linear relationship between increasing BMI and blood pressure is comparable to that reported by Sorof and colleagues (7, 13). Higher, earlier effects on SBP ["preponderance of isolated systolic hypertension in early obesity" (7)] are replicated. The curvilinear relationships between HDL, TG, and child BMI z-score demonstrate that changes in BMI z-score at the high end of the spectrum (>2.00) have a greater impact on unfavorable lipid profiles. In the case of HDL, unfavorable profiles are also seen at the low end of the BMI z-score spectrum, but subject numbers here are low. Nonlinear relationships between lipid profiles and BMI percentile were suggested by results from the Bogalusa Heart Study (6), where seven BMI percentile categories were used to approximate a continuous analysis (6, 15, 29). Similarly, findings by Resnicow and Morabia (14) suggest a nonlinear association between total cholesterol and the Rohrer Index (kilograms per cubic meter). These findings suggest that small changes in weight at extremes of BMI may yield large changes in lipid profiles.

Components of the metabolic syndrome (AN, hyperinsulinism, elevated blood glucose level, elevated ALT) have been shown to cluster in overweight/obese children (9, 30, 31, 32, 33) as well as adults. This clustering of risk factors is known to be associated with increased long-term morbidity and mortality in adults (34, 35, 36, 37, 38), but further longitudinal studies are needed to assess this in children. We have shown the components of this syndrome are similarly influenced in a continuous manner by changes in BMI z-score. As a marker for hyperinsulinism, the presence of AN increased with BMI z-score, and this finding is reinforced by the increases in the insulin values at all three time points of the OGTT (after adjustment for family history and AN). However, a subset of children, despite increasing BMI z-scores, maintained normal fasting insulin. Longitudinal studies are needed to assess whether this lack of insulin resistance (and T2DM risk) is maintained lifelong in select groups of individuals. These children may have genetic profiles that protect against the development of insulin resistance. The pattern of interaction of BMI z-score with ALT suggests that a degree of threshold effect may be superimposed on a linear relationship at a BMI z-score greater than 2.00. At this point, some individuals show a further increase in ALT levels. Again, longitudinal studies are needed to follow this group into adulthood for the development of possible liver disease.

These findings have implications for public health measures. Obese and overweight children as young as six may need specialist medical care for the investigation and treatment of complications, but decreasing the BMI of whole populations of children will decrease the future disease burden. The linear association between parental and child BMI reinforces the need for families to be included in management of children’s weight.

Using this novel approach, the risk of comorbidity is seen to increase continuously across the whole spectrum of childhood BMI z-scores. Child’s BMI z-score is independently linearly or curvilinearly related to many medical complications, and most comorbidities are not defined by a simple threshold effect. Even in the "normal" range of BMI this progression of risk is evident.


   Footnotes
 
This work is partly funded by a Raine Priming Grant and a Healthway Project Grant.

The authors have nothing to disclose.

First Published Online November 14, 2006

Abbreviations: ALT, Alanine aminotransferase; AN, acanthosis nigricans; BMI, body mass index; DBP, diastolic blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein; OGTT, oral glucose tolerance test; OSA, obstructive sleep apnoea; SBP, systolic blood pressure; SES, socioeconomic status; T2DM, type 2 diabetes; TG, triglycerides.

Received August 16, 2006.

Accepted November 3, 2006.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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