Decision trees in epidemiological research

Background: In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. Main text: We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Conclusions: Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation

Parent’s Physical Activity Associated With Preschooler Activity in Underserved Populations

INTRODUCTION: In the U.S., children from low-income families are more likely to be obese. The impact of parent modeling of physical activity (PA) and sedentary behaviors in low-income American ethnic minorities is unclear, and studies examining objective measures of preschooler and parent PA are sparse. METHODS: This cross-sectional study examined 1,003 parent-child pairs who were of low income, largely Latino and African American, and living in one of two geographically disparate metropolitan areas in the U.S. Parents and children wore GT3X/GT3X+ accelerometers for an average of >12 hours/day (7:00am-9:00pm) for 1 week (September 2012 to May 2014). Analysis occurred in 2015-2016. RESULTS: About 75% of children were Latino and >10% were African American. Mean child age was 3.9 years. The majority of children (60%) were normal weight (BMI ≥50th and <85th percentiles), and more than a third were overweight/obese. Children's total PA was 6.03 hours/day, with 1.5 hours spent in moderate to vigorous PA (MVPA). Covariate-adjusted models showed a monotonic, positive association between parent and child minutes of sedentary behavior (β=0.10, 95% CI=0.06, 0.15) and light PA (β=0.06; 95% CI=0.03, 0.09). Child and parent MVPA were positively associated up to 40 minutes/day of parent MVPA, but an inverse association was observed when parental MVPA was beyond 40 minutes/day (p=0.002). CONCLUSIONS: Increasing parental PA and reducing sedentary behavior correlate with increased PA-related behaviors in children. However, more work is needed to understand the impact of high levels of parental MVPA on the MVPA levels of their children

Characterizing Behavior Change Interventions to Improve Pediatric Obesity Prevention Research

University of Minnesota Ph.D. dissertation. September 2016. Major: Epidemiology. Advisors: Nancy Sherwood, Simone French. 1 computer file (PDF); vi, 79 pages.Behavior change interventions to prevent pediatric obesity are critical. The efficacy of these interventions has been modest and reasons for the less-than-desired results are unclear. This dissertation includes three manuscripts aimed at characterizing and identifying effective components within the ‘black box’ of pediatric obesity prevention interventions. The first manuscript assesses the reliability of a standardized method for coding characteristics of an intervention delivered to parents of 5- to 10-year-old children at risk for becoming overweight or obese. The second manuscript evaluates if parents, when given choice in a pediatric obesity prevention intervention, spend time discussing the weight-related behaviors most relevant to their child’s obesity risk. The purpose of the third manuscript is to identify relationships between specific intervention characteristics and study outcomes (i.e., change in child weight-related behaviors and BMI percentile). By using reliable, standardized methods to identify effective intervention characteristics, this dissertation paves the way for future researchers to design more focused interventions, ultimately leading to successful prevention of pediatric obesity

Describing the relationship between occupational and non-occupational physical activity using objective measurement

Objective: Physical inactivity is a major health risk for working adults, yet the interplay between physical activity levels in work and non-work settings is not well understood. The association between occupational physical activity (OPA) and non-occupational physical activity (non-OPA), and associations by sex, were examined in a group of 233 working adults in the Minneapolis, MN metro area between 2010 and 2012. Methods: Accelerometry-measured activity was split into OPA and non-OPA via participant-reported typical work start and end times. Regression models were used to estimate associations. Results: Average weekly OPA was positively associated with non-OPA (B = 0.18, 95% CI: 0.08 to 0.28) and associations were stronger among women than men (Binteraction = −0.39, 95% CI: −0.61 to −0.17). Conclusions: Results suggest that individuals with less physical activity during work also have less physical activity outside of work. Understanding the complexities of the OPA/non-OPA relationship will enable researchers to explore the underlying mechanisms

MOESM1 of Decision trees in epidemiological research

Additional file 1. Regression tree representing the relationship between adjusted residuals for energy intake (adjusted for age, sex, and BMI) and 22 baseline covariate

The dose of behavioral interventions to prevent and treat childhood obesity: a systematic review and meta-regression

Abstract Background A better understanding of the optimal “dose” of behavioral interventions to affect change in weight-related outcomes is a critical topic for childhood obesity intervention research. The objective of this review was to quantify the relationship between dose and outcome in behavioral trials targeting childhood obesity to guide future intervention development. Methods A systematic review and meta-regression included randomized controlled trials published between 1990 and June 2017 that tested a behavioral intervention for obesity among children 2–18 years old. Searches were conducted among PubMed (Web-based), Cumulative Index to Nursing and Allied Health Literature (EBSCO platform), PsycINFO (Ovid platform) and EMBASE (Ovid Platform). Two coders independently reviewed and abstracted each included study. Dose was extracted as intended intervention duration, number of sessions, and length of sessions. Standardized effect sizes were calculated from change in weight-related outcome (e.g., BMI-Z score). Results Of the 258 studies identified, 133 had sufficient data to be included in the meta-regression. Average intended total contact (# sessions x length of sessions) was 27.7 (SD 32.2) hours and average duration was 26.0 (SD 23.4) weeks. When controlling for study covariates, a random-effects meta-regression revealed no significant association between contact hours, intended duration or their interaction and effect size. Conclusions This systematic review identified wide variation in the dose of behavioral interventions to prevent and treat pediatric obesity, but was unable to detect a clear relationship between dose and weight-related outcomes. There is insufficient evidence to provide quantitative guidance for future intervention development. One limitation of this review was the ability to uniformly quantify dose due to a wide range of reporting strategies. Future trials should report dose intended, delivered, and received to facilitate quantitative evaluation of optimal dose. Trial registrations The protocol was registered on PROSPERO (Registration # CRD42016036124 )

Additional file 1: of The dose of behavioral interventions to prevent and treat childhood obesity: a systematic review and meta-regression

Figure S1. Forest plot demonstrating a visual representation of the variability in standardized effect size. Table S1. Dose of behavioral intervention and intervention characteristics by study and a full reference list of all studies reviewed. Table provides details of all articles reviewed in this meta-regression. Table S2. Meta-regression evaluating the relationship between dose and standardized effect size stratified by study characteristics. (PDF 1938 kb