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Predicting Early Emergence of Childhood Obesity in Underserved Preschoolers
William J Heerman1, Evan C Sommer1, James C Slaughter2
1Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN.
Insights
Childhood obesity risk factors include child age, baseline BMI, and parental BMI. Early family-centered interventions are crucial for prevention, especially for overweight children.
Area of Science:
- Pediatrics
- Public Health
- Obesity Research
Background:
- Childhood obesity is a growing concern, particularly in low-income minority populations.
- Identifying early risk factors is crucial for effective prevention strategies.
Purpose of the Study:
- To determine the magnitude of risk factors contributing to childhood obesity.
- To identify predictors of obesity in low-income minority children aged 3-5 years.
Main Methods:
- Prospective cohort analysis of 605 parent-child pairs over 3 years.
- Measured height, weight, and calculated Body Mass Index (BMI) percentiles.
- Used multivariable logistic regression to identify obesity predictors.
Main Results:
- 24% of normal weight children and 55% of overweight children became obese within 36 months.
- Child age at enrollment, baseline child BMI, and parent baseline BMI were significant predictors.
- Higher baseline BMI in children and parents increased obesity risk.
Conclusions:
- Childhood obesity risk is influenced by family factors, including parental BMI.
- Child overweight status is a strong predictor of future obesity.
- Family-centered obesity prevention starting in early childhood is recommended.
Objective:
To determine the magnitude of risk of factors that contribute to the emergence of childhood obesity among low-income minority children.
Study Design:
We conducted a prospective cohort analysis of parent-child pairs with children aged 3-5 years who were nonobese (n = 605 pairs) who participated in a 3-year randomized controlled trial of a healthy lifestyle behavioral intervention. After baseline, height and weight were measured 5 times over 3 years to calculate body mass index (BMI) percentiles and classify children as normal, overweight, or obese. Multivariable logistic regression was used to estimate the odds of obesity after 36 months. Predictors included age, sex, birth weight, gestational age, months of breastfeeding, ethnicity, baseline child BMI, energy intake, physical activity, food security, parent baseline BMI, and parental depression.
Results:
Among this predominantly low-income minority population, 66% (398/605) of children were normal weight at baseline and 34% (n = 207/605) were overweight. Among normal weight children at baseline, 24% (85/359) were obese after 36 months; among overweight children at baseline, 55% (n = 103/186) were obese after 36 months. Age at enrollment (OR 2.11, 95% CI 1.64-2.72), child baseline BMI (OR 3.37, 95% CI 2.51-4.54), and parent baseline BMI (OR for a 6-unit change 1.36, 95% CI 1.09-1.70) were significantly associated with the odds of becoming obese for children.
Conclusions:
The combination of child age, parent BMI, and child overweight as predictors of child obesity suggest a paradigm of family-centered obesity prevention beginning in early childhood, emphasizing the relevance of child overweight as a phenotype highly predictive of child obesity.
Trial Registration:
Clinicaltrials.gov: NCT01316653.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

