Longitudinal associations between BMI, waist circumference, and cardiometabolic risk in US youth: Monitoring implications

• Published in: Obesity (Silver Spring, Md.) Md.), 2013-03, Vol.21 (3), p.E271-E279
• Main Authors: Jago, R., Mendoza, J. A., Chen, T., Baranowski, T.
• Format: Article
• Language: English
• Subjects: Adolescent; Adults; Automation; Blood Glucose - analysis; Blood Pressure; Body Composition; Body Mass Index; Cardiovascular disease; Cardiovascular Diseases - epidemiology; Cholesterol; Cholesterol, HDL - blood; Cholesterol, LDL - blood; Datasets; Diabetes; Disease prevention; Fasting; Female; Gender; Glucose; Humans; Hypertension; Linear Models; Lipoproteins; Logistic Models; Longitudinal Studies; Male; Metabolism; Methods; Nutrition research; Obesity; Obesity - blood; Overweight - blood; Pediatrics; Randomized Controlled Trials as Topic; Risk Factors; Schools; Students; Studies; Triglycerides; Triglycerides - blood; United States - epidemiology; Waist Circumference - physiology
• ISSN: 1930-7381; 1930-739X
• DOI: 10.1002/oby.20080

Objective: This study examined whether change in body mass index (BMI) or waist circumference (WC) is associated with change in cardiometabolic risk factors and differences between cardiovascular disease specific and diabetes specific risk factors among adolescents. We also sought to examine any differences by gender or baseline body mass status. Design: The article is a longitudinal analysis of pre‐ and post‐data collected in the HEALTHY trial. Participants were 4,603 ethnically diverse adolescents who provided complete data at 6th and 8th grade assessments. Methods: The main outcome measures were percent change in the following cardiometabolic risk factors: fasting triglycerides, systolic and diastolic blood pressure, high density lipoprotein cholesterol, and glucose as well as a clustered metabolic risk score. Main exposures were change in BMI or WC z‐score. Models were run stratified by gender; secondary models were additionally stratified by baseline BMI group (normal, overweight, or obese). Results: Analysis showed that when cardiometabolic risk factors were treated as continuous variables, there was strong evidence (P < 0.001) that change in BMI z‐score was associated with change in the majority of the cardiovascular risk factors, except fasting glucose and the combined risk factor score for both boys and girls. There was some evidence that change in WC z‐score was associated with some cardiovascular risk factors, but change in WC z‐score was consistently associated with changes in fasting glucose. Conclusions: In conclusion, routine monitoring of BMI should be continued by health professionals, but additional information on disease risk may be provided by assessing WC.