Commentary on "estimation of newborn risk for child or adolescent obesity: lessons from longitudinal birth cohorts"

Childhood obesity is an increasingly prevalent problem, associated with obesity later in life, and a sequalae of health problems such as metabolic syndrome and an increased risk of coronary heart disease. Poor nutrition and a lack of physical activity are said to be causes of obesity development, with genetic factors and heritability also implicated. However, there are established, identifiable risk factors associated with the future development of obesity, both in childhood, and adolescence. These include parental weight before pregnancy, gestational weight gain, pre-pregnancy maternal smoking, as well as numerous socioeconomic factors.(1-4) Studies have also shown that once obese, children can find it very difficult to lose the excess weight,(5) with long-term management methods having shown poor efficacy.(5) Therefore, preventative strategies are becoming a high priority to battle the ever-increasing epidemic of childhood obesity. This study by Morandi et al.(6) is the first longitudinal study to analyse the predictive properties of early life risk factors for obesity, and propose a subsequent predictive algorithm to identify newborns most at risk of becoming obese in childhood and adolescence. Morandi et al.'s study aimed to develop a clinically useful formula, which could be used to identify the risk of future obesity in newborns, thereby enabling more efficient implementation of prevention strategies.(6) The lifetime Northern Finland Birth Cohort 1986 (NFBC 1986) was used to form predictive equations for both childhood and adolescent obesity, based on established risk factors: parental BMI, birth weight, maternal gestational weight gain, and socioeconomic factors. A genetic score was also created based on 39 BMI/obesity-associated polymorphisms. Validation studies were performed on both a retrospective cohort of children from Veneto, Italy, and a prospective cohort of children from Massachusetts, USA.