Role of appetitive phenotype trajectory groups on child body weight during a family-based treatment for children with overweight or obesity.

ObjectiveEmerging evidence suggests that individual appetitive traits may usefully explain patterns of weight loss in behavioral weight loss treatments for children. The objective of this study was to identify trajectories of child appetitive traits and the impact on child weight changes over time.MethodsSecondary data analyses of a randomized noninferiority trial conducted between 2011 and 2015 evaluated children's appetitive traits and weight loss. Children with overweight and obesity (mean age = 10.4; mean BMI z = 2.0; 67% girls; 32% Hispanic) and their parent (mean age = 42.9; mean BMI = 31.9; 87% women; 31% Hispanic) participated in weight loss programs and completed assessments at baseline, 3, 6,12, and 24 months. Repeated assessments of child appetitive traits, including satiety responsiveness, food responsiveness and emotional eating, were used to identify parsimonious grouping of change trajectories. Linear mixed-effects models were used to identify the impact of group trajectory on child BMIz change over time.ResultsOne hundred fifty children and their parent enrolled in the study. The three-group trajectory model was the most parsimonious and included a high satiety responsive group (HighSR; 47.4%), a high food responsive group (HighFR; 34.6%), and a high emotional eating group (HighEE; 18.0%). Children in all trajectories lost weight at approximately the same rate during treatment, however, only the HighSR group maintained their weight loss during follow-ups, while the HighFR and HighEE groups regained weight (adjusted p-value < 0.05).ConclusionsDistinct trajectories of child appetitive traits were associated with differential weight loss maintenance. Identified high-risk subgroups may suggest opportunities for targeted intervention and maintenance programs

Mortuary practice in sociohistorical and archaeological contexts: Texas, 1821-1870

Historical accounts of mortuary display during the 19th-century and evidence from archaeological investigations at historic cemeteries can contribute substantially to our understanding of related chronological and social-status issues. An inadequate understanding of mortuary practice in Texas circa 1821 to 1870 frustrates assessment of site chronology and status-related interpretations. While there are numerous studies of individual cemeteries, there is, as of yet, no synthesis of historical and archaeological data pertaining to mortuary practices in early Texas. In response to this deficiency, this thesis provides a synthesis of mortuary practices and the availability of related paraphernalia in Texas circa 1821-1870. Data from numerous cemeteries are compiled to establish a chronology for mortuary practices and to develop a seriation of select burial furnishings as an aid in assessing status-related variation in mortuary display. Results of the study, as gleaned from archival and archaeological data, indicate that mortuary display in mid-19th-century Texas is not so much a proxy of wealth, as it is a measure of popular cultural trends and economic contexts. These findings are used to reassess cemetery chronologies and status indices, including several interments at Matagorda Cemetery (1835-present), which serve as case studies

Engaging Empirical Dynamic Modeling to Detect Intrusions in Cyber-Physical Systems

Modern cyber-physical systems require effective intrusion detection systems to ensure adequate critical infrastructure protection. Developing an intrusion detection capability requires an understanding of the behavior of a cyber-physical system and causality of its components. Such an understanding enables the characterization of normal behavior and the identification and reporting of anomalous behavior. This chapter explores a relatively new time series analysis technique, empirical dynamic modeling, that can contribute to system understanding. Specifically, it examines if the technique can adequately describe causality in cyber-physical systems and provides insights into it serving as a foundation for intrusion detection

Generational research: between historical and sociological imaginations

This paper reflects on Julia Brannen’s contribution to the development of theory and methods for intergenerational research. The discussion is contextualised within a contemporary ‘turn to time’ within sociology, involving tensions and synergies between sociological and historical imagination. These questions are informed by a juxtaposition of Brannen’s four-generation study of family change and social historian Angela Davis’s exploration women and the family in England between 1945 and 2000. These two studies give rise to complementary findings, yet have distinctive orientations towards the status and treatment of sources, the role of geography in research design and limits of generalisatio

Exploring and developing a longitudinal cohort study of babies born within Middlesbrough and Redcar and Cleveland:The Lockdown Babies Study: Executive summary

The overarching aim of the research project is to utilise a co-production approach to ascertain the impact of lockdown on parents giving birth during the pandemic, and any perceived impact on their babies, in Middlesbrough and Redcar & Cleveland

Uncertainty of Forest Biomass Estimates in North Temperate Forests Due to Allometry: Implications for Remote Sensing

Estimates of above ground biomass density in forests are crucial for refining global climate models and understanding climate change. Although data from field studies can be aggregated to estimate carbon stocks on global scales, the sparsity of such field data, temporal heterogeneity and methodological variations introduce large errors. Remote sensing measurements from spaceborne sensors are a realistic alternative for global carbon accounting; however, the uncertainty of such measurements is not well known and remains an active area of research. This article describes an effort to collect field data at the Harvard and Howland Forest sites, set in the temperate forests of the Northeastern United States in an attempt to establish ground truth forest biomass for calibration of remote sensing measurements. We present an assessment of the quality of ground truth biomass estimates derived from three different sets of diameter-based allometric equations over the Harvard and Howland Forests to establish the contribution of errors in ground truth data to the error in biomass estimates from remote sensing measurements