Associations of Longitudinal BMI-Percentile Classification Patterns in Early Childhood with Neighborhood-Level Social Determinants of Health.

Background: Understanding social determinants of health (SDOH) that may be risk factors for childhood obesity is important to developing targeted interventions to prevent obesity. Prior studies have examined these risk factors, mostly examining obesity as a static outcome variable. Methods: We extracted electronic health record data from 2012 to 2019 for a children's health system that includes two hospitals and wide network of outpatient clinics spanning five East Coast states in the United States. Using data-driven and algorithmic clustering, we have identified distinct BMI-percentile classification groups in children from 0 to 7 years of age. We used two separate algorithmic clustering methods to confirm the robustness of the identified clusters. We used multinomial logistic regression to examine the associations between clusters and 27 neighborhood SDOHs and compared positive and negative SDOH characteristics separately. Results: From the cohort of 36,910 children, five BMI-percentile classification groups emerged: always having obesity ( n = 429; 1.16%), overweight most of the time ( n = 15,006; 40.65%), increasing BMI percentile ( n = 9,060; 24.54%), decreasing BMI percentile ( n = 5,058; 13.70%), and always normal weight ( n = 7,357; 19.89%). Compared to children in the decreasing BMI percentile and always normal weight groups, children in the other three groups were more likely to live in neighborhoods with higher poverty, unemployment, crowded households, single-parent households, and lower preschool enrollment. Conclusions: Neighborhood-level SDOH factors have significant associations with children's BMI-percentile classification and changes in classification. This highlights the need to develop tailored obesity interventions for different groups to address the barriers faced by communities that can impact the weight and health of children living within them.