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Few studies have derived data-driven dietary patterns in youth in the United States (US). This study examined data-driven dietary patterns and their associations with BMI measures in predominantly low-income, racial/ethnic minority US youth. Data were from baseline assessments of the four Childhood Obesity Prevention and Treatment Research (COPTR) Consortium trials: NET-Works (N=534; 2–4-year-olds), GROW (N=610; 3–5-year-olds), GOALS (N=241; 7–11-year-olds), and IMPACT (N=360; 10–13-year-olds). Weight and height were measured. Children/adult proxies completed 3 24-hour dietary recalls. Dietary patterns were derived for each site from 24 food/beverage groups using k-means cluster analysis. Multivariable linear regression models examined associations of dietary patterns with BMI and percentage of the 95(th) BMI percentile. Healthy (produce and whole grains) and Unhealthy (fried food, savory snacks, and desserts) patterns were found in NET-Works and GROW. GROW additionally had a dairy and sugar-sweetened beverage based pattern. GOALS had a similar Healthy pattern and a pattern resembling a traditional Mexican diet. Associations between dietary patterns and BMI were only observed in IMPACT. In IMPACT, youth in the Sandwich (cold cuts, refined grains, cheese, and miscellaneous [e.g., condiments]) compared to Mixed (whole grains and desserts) cluster had significantly higher BMI [β=0.99 (95% CI: 0.01, 1.97)] and percentage of the 95(th) BMI percentile [β=4.17 (95% CI: 0.11, 8.24)]. Healthy and Unhealthy patterns were the most common dietary patterns in COPTR youth, but diets may differ according to age, race/ethnicity, or geographic location. Public health messages focused on healthy dietary substitutions may help youth mimic a dietary pattern associated with lower BMI.

Supplemental material, COPTR_Taxonomy_Online_Supplementary_File for Applying the Behavior Change Technique Taxonomy to Four Multicomponent Childhood Obesity Interventions by Meghan M. JaKa, Caroline Wood, Sara Veblen-Mortenson, Shirley M. Moore, Donna Matheson, June Stevens, Lou Atkins, Susan Michie, Clara Adegbite-Adeniyi, Oluwatomisin Olayinka, Eli K. Po’e, Alethea M. Kelly, Holly Nicastro, Shrikant I. Bangdiwala, Shari L. Barkin, Charlotte Pratt, Thomas N. Robinson and Nancy E. Sherwood in Western Journal of Nursing Research

Background Individual variability in response to multiple modalities of obesity treatment is well documented yet our understanding of why some individuals respond while others do not is limited. The etiology of this variability is multi-factorial, but at present we lack a comprehensive evidence base to identify which factors or combination of factors influence treatment response. Objectives This paper provides an overview and rationale of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, which aims to advance understanding of individual variability in response to adult obesity treatment. We provide an integrated model for how factors in the behavioral, biological, environmental, and psychosocial domains may influence obesity treatment responses and identify a core set of measures to be used consistently across adult weight loss trials. This paper provides the foundation for four companion papers that describe the core measures in detail. Significance The accumulation of data on factors across the four ADOPT domains can inform the design and delivery of effective, tailored obesity treatments. ADOPT provides a framework for how obesity researchers collectively can generate this evidence base and is a first step in an ongoing process that can be refined as the science advances.

Cancer is a leading cause of death worldwide, with cancer deaths expected to continue to rise, necessitating new prevention and treatment strategies. Bioactive food components like Brassica-derived 3,3'-diindolylmethane (DIM) are a promising area of study for cancer prevention and treatment. Due to its efficacy, availability, low cost, and low toxicity, DIM is currently in use as a treatment for recurrent respiratory papillomatosis and is in clinical trials for the prevention and treatment of prostate and cervical cancers.DIM's anticancer activities include induction of cell cycle arrest and apoptosis, inhibition of angiogenesis, and immune activation. Though some mechanisms for these activities in various cancer cells have been uncovered, it is clear that DIM works through multiple pathways. More research is necessary to determine the full extent of DIM's effects and to identify specific cellular targets of DIM. This dissertation focuses on DIM's effects on the signaling pathways of two specific pathways, HGF/c-Met/Akt and p38 MAPK.Akt signaling is frequently dysregulated in breast cancer. Although it has been reported that DIM inhibits Akt signaling in breast cancer cells, the mechanism(s) for this action, as well as the kinetics and effects of lower, physiologically relevant concentrations of DIM, have remained unknown. In chapter 2 we demonstrate that physiologically relevant concentrations of DIM inhibit short- and long-term activation of Akt in the highly invasive MDA-MB-231 breast cancer cells. DIM also selectively inhibits HGF-induced Akt activation, which is one novel mechanism by which DIM inhibits Akt. In addition, DIM inhibits cell cycle progression and in vitro metastasis and induced apoptosis, which are all consistent with Akt inhibition. The roles of specific upstream activators of the Akt pathway, including c-Met, in this activity have not been investigated. In chapter 3, we demonstrate that DIM inhibits motility and proliferation of MDA-MB-231 breast cancer cells downstream of HGF, and that DIM promotes ligand-dependent degradation of c-Met and inhibits c-Met activation.Even with its strong inhibition by DIM, the Akt pathway is just one of several signaling pathways modified by DIM. DIM also exerts some of its anti-cancer effects by activating the p38 pathway. DIM activates p38 in various cancer cells, including breast cancer cells, and that p38 activation as well as regulation of expression of various genes have been shown to play a role in DIM's effects in breast cancer cells. However, the connection between these two effects has not been reported. In chapter 4 we demonstrate through gene expression profiling that 25 μM DIM for 4 hours regulates the expression of over 400 genes in MDA-MB-231 cells. We also show that DIM activates p38 under physiologically relevant conditions and this activation is partly responsible for DIM-induced up regulation of several genes and for DIM's induction of apoptosis. Future experiments should focus on determining a specific mechanism by which DIM inhibits c-Met and should establish the relationship between c-Met inhibition and Akt inhibition, as well as between c-Met/Akt inhibition and cell cycle progression, proliferation, apoptosis, and motility in MDA-MB-231 breast cancer cells. The results of the gene expression profiling study also provide many opportunities for follow up experiments. In summary, DIM is a promising anti-breast cancer compound that exerts its effects in part by inhibiting the HGF/c-Met/Akt pathway and by activating the p38 pathway.

BACKGROUND: The influence of community characteristics on the effectiveness of childhood obesity prevention efforts is not well understood. OBJECTIVE: Examine the interaction of community characteristics with the relationship between community programs and policies (CPPs) and dietary intake. METHODS: An observational study of 5138 children in grades K-8 in 130 U.S. communities was conducted in 2013–2015. Key informant interviews identified and characterized CPPs. CPP scores were generated for the number of target behaviors (CPP-Behav) and the number of behavior change strategies (CPP-Strat) addressed by all CPPs and CPPs with nutrition goals over the prior 6 years in each community. Dietary intake was assessed by dietary screener and included intake of: sugar from sugar-sweetened beverages; energy-dense foods; fruits and vegetables; whole grains; and fiber. Multivariate statistical models assessed the interactions between U.S. region, urbanicity, community-level income, and community-level race/ethnicity and CPP scores in relation to dietary intake. RESULTS: CPP-Strat was positively associated with healthier dietary intakes in the Northeast and West, and in high Hispanic communities; the reverse was true in the South, and in high African American and low-income communities. The CPP-Behav was positively associated with healthier dietary intakes in the South and rural areas, and the reverse was true in the West. CONCLUSION: The relationships between CPP index scores and dietary intake were most strongly influenced by region and urbanicity and to a lesser extent by community-level race/ethnicity and income. Findings suggest that different considerations may be needed for childhood obesity prevention efforts in communities with different characteristics.