New perspectives for understanding the developmental trajectory of metabolic syndrome and obesity

Open Access
Ventura, Alison Kate
Graduate Program:
Human Development and Family Studies
Doctor of Philosophy
Document Type:
Date of Defense:
April 28, 2008
Committee Members:
  • Leann L Birch, Committee Chair
  • Eric Loken, Committee Chair
  • Susan Mc Hale, Committee Member
  • Elizabeth Susman, Committee Member
  • obesity
  • metabolic syndrome
  • girls
  • prevention
  • latent profile analysis
  • growth mixture models
  • familial influences
Developmental frameworks and person-centered approaches have the potential to broaden our understanding of the nature and development of health status and disease risk in children. Few studies examining the etiology of metabolic syndrome and obesity during childhood have adopted these frameworks and approaches. The present research aims to address these limitations and provide new information about the development of obesity and metabolic syndrome across childhood and adolescence. Data used in the present research were from a longitudinal study of 197 girls and their parents, followed from daughters’ ages 5 to 15 years. In the first study, we used a latent profile approach to identify a metabolic syndrome risk typology based on girls’ values for six metabolic syndrome indicators. Statistical support was strongest for a four group solution: 1) Lower MetS Risk, 2) Dyslipidemia Risk, 3) Hypertension Risk, and 4) Higher MetS Risk. Examination of the antecedents of this risk typology revealed girls in the Higher MetS Risk group consumed significantly more sweetened beverages across ages 5 to 13 years and girls in the Dyslipidemia Risk group had the lowest levels of physical activity. These findings illustrate ways to identify girls at higher risk for chronic disease and point to potential opportunities for intervention during childhood to prevent the development of metabolic syndrome. In the second study, we used a growth mixture model approach to identify latent growth trajectories for girls’ patterns of BMI change across ages 5 to 15 years. Statistical support was strongest for four patterns of BMI change: 1) Upward Percentile Crossing (UPC); 2) Delayed Downward Percentile Crossing (DDPC); 3) 60th Percentile Tracking (60PT) and 4) 50th Percentile Tracking (50PT). Diet and physical activity patterns did not predict BMI trajectories, but girls in the UPC group had more overweight mothers, were breastfed for a shorter duration, under-reported dietary intake to a greater degree and presented the worst metabolic outcomes. These findings suggest future research is needed to explore factors other than self-reported diet and activity patterns that may distinguish among differing trajectories of childhood weight status. In the third study, we explored the maternal and psychosocial correlates of heterogeneity for girls’ BMI trajectories. Our findings illustrated that girls exhibiting an upward percentile crossing trajectory developed in a distinct ecology compared to other girls in our sample, characterized by a combination of higher maternal weight status, weight concern, and higher levels of maternal restriction of daughter’s diet, and more encouragement of daughter’s weight loss. Overall, the results of the present research illustrate that girls do not follow a single pathway toward metabolic and weight status outcomes and the psychosocial influences associated with these pathways are multifactorial. Both mothers and daughters should be targeted for childhood obesity and metabolic syndrome prevention and intervention efforts, and our findings suggest several modifiable behaviors that may serve as successful targets for these efforts.