Newborns who are heavier than average and gain weight rapidly in the first six months of life face a heightened chance of obesity by the time they are old enough for kindergarten, according to a study published on March 4, 2016, in The Journal of Pediatrics.
This conclusion emerged from an obesity-risk algorithm developed by UCSF researchers, who evaluated demographic data, body measurements and nutrition patterns of Latino children in the San Francisco Bay Area. The researchers recruited and tracked pregnant Latina women and their offspring at UCSF Medical Center and Zuckerberg San Francisco General Hospital and Trauma Center. Of the 166 children followed, they found that 56 -- almost one third -- were obese at age 5, based on the definition of the Centers for Disease Control and Prevention.
“Many recent studies have focused on single risk factors, such as maternal smoking or infant weight gain to predict the risk of obesity,” said lead author Jacob Robson, MD, formerly of the UCSF Department of Pediatrics, Division of Pediatric Gastroenterology, Hepatology and Nutrition and currently assistant professor of pediatrics at the University of Utah, Primary Children’s Hospital. “But targeting single risk factors may be inefficient and ineffective because the development of childhood obesity is a complex interaction of genetic, environmental and socioeconomic factors.”
The researchers listed 10 known predictors of childhood obesity and used data from the children and their mothers to make a logistic regression model, a statistical analysis that predicts an outcome based on established factors.
Pre-Pregnancy Weight Also a Factor
The researchers discovered that the leading determinants of childhood obesity were higher-than-average birth weight and amount of weight gained at 6 months of age. Higher pre-pregnancy body mass index was the most important maternal predictor of obesity at age 5. Factors that had a modest impact on reducing the chance of obesity were breastfeeding and deferring solids until the infant was 6 months old, and older maternal age.
Using the algorithm, researchers found that among those infants whose risk score was ranked below the 25th percentile, 94 percent were in the normal weight range at age 5. In contrast, 61 percent of those whose risk score was categorized above the 75th percentile were obese by age 5. “The obesity rate was 32 percent for this group of 5-year-olds,” said Robson. “The algorithm has a high rate of accuracy in picking out which infants to worry about based on the presence and absence of certain factors.”
While the study focused on the children of Latino women in San Francisco, the algorithm could be applied to other vulnerable populations, said senior author Janet Wojcicki, PhD, associate professor in the UCSF Department of Pediatrics, Division of Pediatric Gastroenterology, Hepatology and Nutrition. “Our recommendation would be to test our tool in other high-risk populations -- African American, American Indian, Alaskan Native -- that likely have the same risk factors for early obesity.”
“Prognostic modeling, in which multiple risk factors are combined to estimate an individual’s risk has been underutilized in childhood obesity prediction,” said Robson. “A childhood obesity risk score like the one we developed derived from the presence or absence of known prenatal and postnatal risk factors could provide a simple filter for directing low-risk infants to routine weight monitoring, while reserving intensive prevention resources for those at high risk.
Pop-Up Message Could Alert Doctor to Patient’s Risk
“Longitudinal data show that once a child becomes obese, it is likely to persist into adolescence and adulthood. Using the obesity-risk tool at the six-month visit would enable doctors to intervene early and most importantly prevent problems with weight and nutrition before they develop,” said Wojcicki.
“As electronic records become standard practice, childhood obesity risk scoring has the potential for immediate and impactful applications,’’ said Wojcicki. “Most electronic medical records can generate a risk score from risk factor data entered into the record. A pop-up message could alert providers to their patients’ obesity risk score and whether intervention is indicated. This could serve as an important tool for busy providers who may fail to classify patients in the appropriate weight category, or may miss rapid infant growth if it is within the normal weight range.”
Childhood obesity has more than doubled in children and quadrupled in adolescents in the past 30 years, according to 2011 figures from the CDC’s National Center for Health Statistics. Obese children and adolescents are at higher risk for cardiovascular disease, diabetes, liver inflammation, bone and joint disorders, sleep apnea, and social and psychological problems.
The research was supported by grants from the National Institutes of Health, and funding from the NASPGHAN Foundation and Hellman Family Foundation.
Co-authors are Sofia Verstraete, MD, and Melvin Heyman, MD, of the UCSF Department of Pediatrics, Division of Pediatric Gastroenterology, Hepatology and Nutrition; and Stephen Shiboski, PhD, of the UCSF Department of Epidemiology and Biostatistics.
UC San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It includes top-ranked graduate schools of dentistry, medicine, nursing and pharmacy; a graduate division with nationally renowned programs in basic, biomedical, translational and population sciences; and a preeminent biomedical research enterprise. It also includes UCSF Health, which comprises top-ranked hospitals, UCSF Medical Center and UCSF Benioff Children’s Hospitals in San Francisco and Oakland – and other partner and affiliated hospitals and healthcare providers throughout the Bay Area.