The impact of change in neighborhood poverty on BMI trajectory of 37,544 New York City youth: a longitudinal study

Longitudinal exposure to neighborhood poverty and obesity risk in emerging adulthood

This study uses data from the longitudinal Panel Study of Income Dynamics data and its Transition to Adulthood (TA) Study (2005-2017), in conjunction with decades of neighborhood-level data from the U.S. decennial census and American Community Survey, to examine the relationship between individuals' neighborhood poverty exposure trajectories in childhood and the likelihood of obesity in emerging adulthood. Latent growth mixture models reveal that exposure to neighborhood poverty differs considerably for white and nonwhite individuals over their childhood life course. Durable exposure to neighborhood poverty confers greater subsequent obesity risks in emerging adulthood than transitory experiences of neighborhood poverty. Racial differences in the changing and persistent trajectories of neighborhood poverty help explain part of the racial differences in obesity risks. Among nonwhites, and compared to consistent nonpoor neighborhood conditions, both durable and transitory neighborhood poverty exposures are significantly associated with higher obesity risks. This study suggests that a theoretical framework that integrates key elements of the life-course perspective is helpful to uncover the individual and structural pathways through which neighborhood histories in poverty shape population health in general.

Quantile Regression of Childhood Growth Trajectories: Obesity Disparities and Evaluation of Public Policy Interventions at the Local Level

Quantile regression applied to child growth trajectories has been proposed in the methodological literature but has only seen limited applications even though it is a promising framework for the evaluation of school-based policy interventions designed to address childhood obesity. Data that could be used to support such assessments, school-based collection of height and weight, has become increasingly common. Three states currently mandate annual collection and several other jurisdictions including California and New York City (NYC) collect BMI as part of physical fitness assessments. This has resulted in the establishment of extremely large databases that share important characteristics including the ability to define longitudinal growth curves by student with high coverage rates. In NYC public schools, starting in 2006, student records have been linked to registry, academic, and attendance data and across years resulting in a longitudinal dataset containing 9 cohorts with 2 million unique children. A high level of demographic and geographic detail allow for analysis of public policy at the local scale. We demonstrate the utility of quantile regression longitudinal growth curve models applied to BMI trajectories as a means of assessing policy interventions. Models consisting solely of age terms yield empirical curves similar to CDC growth charts; covariates modify these curves. Incorporating lag terms yields a distribution of possible growth trajectories and the effect of interventions can be explicitly quantified. We evaluate area-based and individual poverty measures, known strong correlates of child obesity, as a baseline assessment of the modeling framework. We then evaluate the impact of a real intervention (water jet installations). Our results indicate that students with access to water jets have a statistically significant leftward shift in the right tail of the BMI distribution relative to students without access to water jets. The absolute magnitude of the shift is comparable to the difference in BMI associated with student residential exposure to low versus extreme poverty.

The Effect of Neighborhood-level Resources on Children's Physical Development: Trajectories of Body Mass Index and Pubertal Development and the Influence of Child Biological Sex

Growing research substantiates the role of neighborhood disadvantage in contributing to early pubertal maturation and higher body mass index; however, previous studies in this area have design limitations. Specifically, many studies have been cross-sectional, have used singular indicators of neighborhood disadvantage (e.g., poverty), and have provided mixed findings about the role of biological sex. The present study addresses these gaps by examining how neighborhood resources (spanning educational, health/environmental, and social/economic domains) predict trajectories of pubertal maturation and body mass index using longitudinal multi-wave data. Furthermore, multigroup analyses assessed how these associations may differ by child biological sex. Participants in this study (n = 505; 54% male) were assessed every 3 years at age 9 (M = 9.17, SD = 0.39), age 12 (M = 12.63, SD = 0.43), and age 15 (M = 15.23, SD = 0.37). Approximately 12% of the sample identified as Hispanic, and 11% as non-White. Using multigroup latent growth analyses, the study examined how neighborhood resources predicted trajectories of pubertal maturation and body mass index using multi-wave data across middle childhood through mid-adolescence. The findings suggested that greater neighborhood resources were cross-sectionally associated with lower pubertal development and predicted slower trajectories across time. Although all girls in the study eventually progressed through pubertal development, girls in lower resourced neighborhoods experienced a much earlier onset of puberty. Additionally, greater neighborhood resources predicted lower BMI both cross sectionally and longitudinally. Specifically, higher resourced neighborhoods were protective against obesity risk for both boys and girls across mid-childhood through mid-adolescence. In sum, the study highlights the role of broader neighborhood factors on early maturity risk for female children, and obesity risk for children regardless of biological sex.

Associations of family income with cognition and brain structure in USA children: prevention implications

Poverty, as assessed by several socioeconomic (SES) factors, has been linked to worse cognitive performance and reduced cortical brain volumes in children. However, the relative contributions of the various SES factors on brain development and the mediating effects between cognition and brain morphometry have not been investigated. Here we used cross-sectional data from the ABCD Study to evaluate associations among various SES and demographic factors, brain morphometrics, and cognition and their reproducibility in two independent subsamples of 3892 children. Among the SES factors, family income (FI) best explained individual differences in cognitive test scores (stronger for crystallized than for fluid cognition), cortical volume (CV), and thickness (CT). Other SES factors that showed significant associations with cognition and brain morphometrics included parental education and neighborhood deprivation, but when controlling for FI, their effect sizes were negligible and their regional brain patterns were not reproducible. Mediation analyses showed that cognitive scores, which we used as surrogate markers of the children's level of cognitive stimulation, partially mediated the association of FI and CT, whereas the mediations of brain morphometrics on the association of FI and cognition were not significant. These results suggest that lack of supportive/educational stimulation in children from low-income families might drive the reduced CV and CT. Thus, strategies to enhance parental supportive stimulation and the quality of education for children in low-income families could help counteract the negative effects of poverty on children's brain development.

Associations of community, famliy and early individual factors with body mass index z-scores trajectories among Chinese children and adolescents

The prevalence of childhood overweight and obesity is increasing. This study aimed to examine trajectories of BMI z-scores among Chinese children and the potential determinants including early individual, family and community factors. Group-based trajectory modeling was employed to identify BMI z-scores trajectories of children aged 2-18 years using the five waves data (2010, 2012, 2014, 2016, and 2018) of the China Family Panel Studies (CFPS). Multivariate logistic regression was conducted to determine the association between early individual, family, community factors and BMI z-scores trajectories of children. We identified three trajectories for boys and girls, named Class 1 as "not-overweight", Class 2 as "persistent rapid descending but overweight during pre-school age", and Class 3 as "rapid rising up to school age and then become-overweight" class. Macrosomia (OR 1.772; 95% CI 1.188-2.644) and being a single child (OR 2.038; 95% CI 1.453-2.859) were more likely to belong in Class 3 among boys. Girls living in the advantaged communities (OR 1.539; 95% CI 1.052-2.252), rural-living (OR 1.558; 95% CI 1.133-2.142) and with none social integration (OR 1.496; 95% CI 1.07-2.091) were more likely to belong in Class 2. There are heterogeneous BMI z-scores trajectories of children aged 2-18, and pre-school age is a critical window that could predict the long-term growth patterns. BMI z-scores trends need to be monitored during pre-school age, focusing on those at higher risk of later overweight obesity status, and targeted interventions at the early individual, family, community levels are essential.