The current study provided strong statistical support for 4 distinct risk profiles among a nonclinical sample of non-Hispanic, white adolescent girls and identified developmental and familial antecedents of these MetS risk profiles. The 4 groups included: a higher MetS risk group (14% of the sample); a lower MetS risk group (41% of the sample); a HDL-TG risk group (24% of the sample); and a hypertension risk group (22% of the sample). At 13 years old, these 4 groups also differed in BMI, fat mass, pubertal development, and fitness levels. With respect to developmental antecedents, both the higher MetS risk and the hypertension risk groups had significantly greater increases in weight and fat mass from 5 to 13 years. The higher MetS risk and the hypertension risk groups also diverged from the HDL-TG risk and lower MetS risk groups in family history of obesity and type 2 diabetes. With respect to food intake and physical activity, the higher MetS risk groups had the highest sweetened beverage intakes, and lower MetS risk had the highest fitness levels. No differences were found among groups on indices of sedentary behavior, specifically television viewing and computer time.
Other research has used factor analysis to address the issue of whether MetS is a more useful conceptualization of risk compared with focusing on individual indicators.16,20,32
Cluster analysis has also been used to address this issue by looking for greater-than-chance clustering of dichotomous risk indicators.33
The present approach instead posits an underlying typology and estimates parameters associated with the latent groups. Although this mixture model analysis is similar to factor modeling in accounting for covariation among observed variables by their association with latent variables,34
there are some differences convenient for the purposes of this study. Mixture model analysis provided the opportunity to construct classes of individuals thought to differ qualitatively from one another. It was on the basis of these classifications that differences among the 4 risk groups’ developmental antecedents could then be examined and described.
Longitudinal data on development lifestyle factors provided information on several antecedents of risk classification. Changes in weight and adiposity were developmental antecedents of interest, because weight status, fat mass, and change over time for both of these variables from 5 to 13 years were strong predictors of risk group membership. This is consistent with research showing that overweight and obesity are intricately linked with the prevalence of MetS, its various components, and its consequences later in life.35-39
Before the 1990s, disease statuses, such as type 2 diabetes and CVD, were thought of as adult conditions, for which children were thought to be at very low risk. But, with the reports of dramatic increases in both CVD and type 2 diabetes in children and adolescents,3,5,6,40,41
it has become apparent that susceptibility to and development of these chronic diseases can emerge as early as adolescence. In addition, research has shown that the increased prevalence of type 2 diabetes and CVD in adolescents may be partially attributable to the dramatic increases in overweight in both children and adolescents,10
as well as to patterns of weight change during childhood.42
The present findings reveal that elevated weight status and accelerated change in weight status during middle childhood are predictors of MetS risk at age 13 and may serve as a key signal to clinicians and interventionists aimed at preventing MetS and CVD risk during early childhood.
Several aspects of girls’ families were found to differ across risk groups. Girls classified as having higher risk for MetS and the components of MetS (hypertension and dyslipidemia) were more likely to have a family history of obesity, type 2 diabetes, and gestational diabetes and to have parents who were more overweight. In addition, the lower-risk girls had parents who were more educated, although the mean educational levels of all 4 of the risk groups reflected 2 to 3 years of college education among parents. Similarities within families for the presence of MetS and for traits related to MetS have been attributed to both genetic and shared environment factors.43-46
Thus, although it seems that some girls in the present study may be genetically predisposed to the development of MetS, environmental factors, such as parent education level, were also predictive of risk status. In addition, the difference in parental weight status between the groups is suggestive of both genetic and environmental influences, because overweight parents may be a marker for less healthy parental eating and activity patterns. This supports the “obesegenic family” view,47-49
suggesting that there are certain environments created by parental behaviors that contribute to the development of overweight and comorbidities (ie, MetS) in children.
With respect to lifestyle factors, the only dietary pattern that clearly distinguished the higher-risk group from the other groups was early elevated intake of calorically sweetened beverages across ages 5 to 11 years. Relative to the low MetS risk group, at ages 5, 7, and 9 years, the higher MetS risk group consumed 27%, 45%, and 50% more sweetened beverage servings per day, respectively. This difference would result in an additional 167.36 to 313.80 J per day for the higher MetS risk group over time, which coincides with, and possibly accounts for, the greater weight and weight gain of the higher MetS risk group. For example, the consumption of an additional 50 kJ per day persisting over 4 years, assuming 50% of these additional calories are stored as fat, could result in an additional weight gain of ~10 lb (4.5 kg) over a 4-year period. This estimation is close to the difference in weight gain between ages 5 and 9 years in the high MetS risk group (17.62 kg) and the average weight gain in the other 3 groups (14.3 kg; data not shown). The differences among the groups in their sweetened beverage consumption disappeared by age 11 because of increases in sweetened beverage intake among the other groups. This pattern suggests the possibility that consistently high intake of sweetened beverages early in life may constitute a risk factor for excessive weight gain and increased MetS risk. These findings are consistent with research examining physiologic responses to consuming high glycemic load carbohydrates (eg, sweetened beverages), which has shown that habitual consumption of these foods contributes to the development of insulin resistance, especially when these high intakes are accompanied by the consumption of higher than needed calories on a habitual basis.50
Based on these findings, it is not unreasonable to expect that girls who have been consuming higher amounts of sugar-sweetened beverages from ages 5 to 11 would have greater risk for insulin resistance or MetS. In addition, although a clear consensus on the effect of high intakes of sweetened beverages on weight change and health status has not been reached, children’s consumption of caloric drinks has been shown to predict change in BMI and overweight prevalence.51,52
Thus, epidemiologic data associating childhood sweetened beverage intakes to weight change, as well as data from the current and past studies associating childhood sweetened beverage intakes to MetS risk, suggest that this dietary factor may be an important target for early lifestyle health promotion efforts.
Recently, the definition of MetS and its clinical application have been questioned, with a charge that the label “syndrome” offers no substantive clinical use.16
The critics contend that for a syndrome to have scientific force it must have predictive use greater than that offered by the individual components, must designate a distinct underlying causal process, and must suggest a treatment strategy different from merely treating the individual risk components.16
The present study does not specifically address the clinical status of MetS. To do so, higher risk for adverse health outcomes for the higher MetS risk group would need to be established. Because this was a nonclinical sample of healthy, non-Hispanic, white 13-year-olds, the adverse health outcomes are not yet manifest. Concurrent associations between risk group membership and both higher body fat and BMI were seen, but whether this is reflective of a later morbidity remains to be tested in subsequent analyses using data from later points in development.
What this study does contribute is a novel approach to describing the clustering of the risk factors among a nonclinical sample of girls. This includes an estimate of the mean levels on the indicators associated with the subgroups of the girls in the study and a clear demonstration of developmental patterns showing consistent differences and a steady divergence from age 5 on measures of body weight and adiposity, which are associated with the clustering of the MetS risk indicators. In addition, this study was unique in that group means were estimated by the mixture modeling and not a priori considerations. Previous studies of MetS in adolescents classify individuals based on modified adult values13
; in contrast, the current study allowed the data to determine profiles of MetS risk based on the commonly used indicators.
Limitations of this study include a sample that is relatively small and homogeneous in both ethnicity and gender. Because a sample of non-Hispanic white girls was examined, results cannot be generalized to other ethnicities or to boys. In addition, this study cannot currently assess future MetS risk, because data beyond age 13 have not yet been obtained. Data at future time points on the actual presence of MetS in this sample of adolescent girls are needed to assess the adequacy of the subgroups as indicators of risk and to determine whether the 3 elevated risk groups (HDL-TG, hypertension, and higher MetS) will be associated with distinctly different patterns of comorbidities later in development.
Given the strong statistical support for the model, the similarities between the higher-risk group in this model and the current conceptualization of MetS in adolescents and the various differences in the developmental precursors noted among the risk groups, this study provides support for a multifaceted disease risk trajectory during adolescence. In addition, 1 of the strengths of this study was the ability to use a rich, longitudinal data set to examine developmental antecedents of risk subtypes. This study provided evidence that family history and persistent patterns of elevated sweetened beverage intake, accelerated weight gain, and elevated fat mass accumulation during childhood were predictive of elevated risk for MetS in early adolescence. These developmental antecedents of adolescent MetS risk provide promising targets for preventive interventions.