Does a parsimonious measure of complex body mass index trajectories exist?

A novel systematic pipeline for increased predictability and explainability of growth patterns in children using trajectory features

OBJECTIVE

Longitudinal patterns of growth in early childhood are associated with health conditions throughout life. Knowledge of such patterns and the ability to predict them can lead to better prevention and improved health promotion in adulthood. However, growth analyses are characterized by significant variability, and pattern detection is affected by the method applied. Moreover, pattern labelling is typically performed based on ad hoc methods, such as visualizations or clinical experience. Here, we propose a novel pipeline using features extracted from growth trajectories using mathematical, statistical and machine-learning approaches to predict growth patterns and label them in a systematic and unequivocal manner.

METHODS

We extracted mathematical and clinical features from 9577 children growth trajectories embedded with machine-learning predictions of the growth patterns. We experimented with two sets of features (CAnonical Time-series Characteristics and trajectory features specific to growth), developmental periods and six machine-learning classifiers. Clinical experts provided labels for the detected patterns and decision rules were created to associate the features with the labelled patterns. The predictive capacity of the extracted features was validated on two heterogenous populations (The Applied Research Group for Kids and the 2004 Pelotas Birth Cohort, based in Canada and Brazil, respectively).

RESULTS

Features predictive ability measured by accuracy and F1 score was ≥ 80% and ≥ 0.76 respectively in both cohorts. A small number of features (n = 74) was sufficient to distinguish between growth patterns in both cohorts. Slope, intercept of the trajectory, age at peak value, start value and change of the growth measure were among the top identified features.

CONCLUSION

Growth features can be reliably used as predictors of growth patterns and provide an unbiased understanding of growth patterns. They can be used as tool to reduce the effort to repeat analysis and variability concerning anthropometric measures, time points and analytical methods, in the context of the same or similar populations.

Maltreatment experience in childhood and average excess body mass from adolescence to young adulthood

BACKGROUND

Prior studies have suggested maltreatment is a strong predictor of later weight outcomes, such that maltreatment experiences in childhood increase the likelihood of being overweight or obese in adulthood. Estimates of this relationship may be biased due to: 1) inadequate selection of covariates; 2) improper operationalization of child maltreatment; and 3) restricting analyses to cross-sectional outcomes.

OBJECTIVES

Evaluate how latent classes of child maltreatment experiences are associated with a longitudinal BMI measure from adolescence to adulthood.

PARTICIPANTS

Data from the National Longitudinal Study of Adolescent to Adult Health.

METHODS

We evaluated how previously developed latent classes of child maltreatment experiences were associated with average excess BMI from adolescence to adulthood using multivariate linear regression.

RESULTS

In the unadjusted model, individuals in the poly-maltreatment class (b = 0.46, s.e. = 0.20) and individuals who experienced adolescent-onset maltreatment (b = 0.36, s.e. = 0.11) had higher average excess BMI compared to individuals in the no maltreatment class. After adjusting for confounders, the relationship between poly-maltreatment and average excess BMI abated, whereas the relationship between adolescent-onset maltreatment and average excess BMI sustained (b = 0.28, s.e. = 0.11).

CONCLUSIONS

Contrary to previous findings, our analyses suggest the association between maltreatment experiences and longitudinal weight outcomes dissipates after controlling for relevant confounders. We did find a relationship, however, between adolescent-onset maltreatment and average excess BMI from adolescence to adulthood. This suggests the importance of maltreatment timing in the relationship between maltreatment and weight.

Child Maltreatment and Body Mass Index over Time: The Roles of Social Support and Stress Responses

An unhealthy body mass index (BMI) trajectory can exacerbate the burdens associated with child maltreatment. However, we have yet to explain why the relationship between maltreatment and BMI trajectories exists and what allows individuals to attain healthy BMI trajectories despite adversity. Guided by the Transactional Model of Stress and Coping, we evaluated (1) if peer friendship and adult mentors moderate, and (2) if impulsivity and depressive symptoms mediate, the relationship between maltreatment experiences and average excess BMI. We used data from four waves of the National Longitudinal Study of Adolescent to Adult Health (n = 17,696), following adolescents from ages 13-21 (Wave I) to 24-31 years (Wave IV). We did not find evidence of significant moderation or mediation of the maltreatment experience to average excess BMI relationship. However, models did demonstrate a relationship between peer friendship quality and average excess BMI, such that higher quality protected against higher average excess BMI (B = -0.073, s.e. = 0.02, p < 0.001). Age of maltreatment onset was also associated with average excess BMI, such that maltreatment onset in adolescence was associated with a higher average excess BMI (B = 0.275-0.284, s.e. = 0.11, p = 0.01). Although we found no evidence of moderation by social support or mediation by stress responses of the relationship between maltreatment experiences and average excess BMI, peer friendship appears to protect against higher average excess BMI from adolescence to young adulthood for all adolescents. Future public health interventions should consider how to leverage friendship in obesity prevention efforts.