DEVELOPING PREDICTION EQUATIONS FOR FAT FREE LEAN IN THE PRESENCE OF AN UNKNOWN AMOUNT OF PROPORTIONAL MEASUREMENT ERROR

Published prediction equations for fat-free lean mass are widely used by producers for carcass evaluation. These regression equations are commonly derived under the assumption that the predictors are measured without error. In practice, however, it is known that some predictors, such as backfat and loin muscle depth, are measured imperfectly with variance that is proportional to the mean. Failure to account for these measurement errors will cause bias in the estimated equation. In this paper, we describe an empirical Bayes approach, using technical replicates, to accurately estimate the regression relationship in the presence of proportional measurement error. We demonstrate, via simulation studies, that this Bayesian approach dramatically improves the accuracy of the estimated equation in comparison to the fit from Ordinary Least Squares regression

DEVELOPING PREDICTION EQUATIONS FOR CARCASS LEAN MASS IN THE PRESCENCE OF PROPORTIONAL MEASUREMENT ERROR

Published prediction equations for carcass lean mass are widely used by commercial pork producers for carcass valuation. These regression equations have been derived under the assumption that the predictors, such as back fat depth, are measured without error. In practice, however, it is known that these measurements are imperfect, with a variance that is proportional to the mean. In this paper, we consider both a linear and quadratic true relationship and compare regression fits among two methods that account for this error versus simply ignoring the additional error. We show that biased estimates of the relationship result if measurement error is ignored. Between our version of regression calibration and a Bayesian model approach, the Bayesian inference approach produced the least biased predictions. The benefits of our Bayesian approach also increased with an increase in the measurement error

A Longitudinal Examination of the Impact of Major Life Events on Physical Activity

Background: Despite promotion of physical activity guidelines, less than one third of U.S. adults are sufficiently active and an even larger number of older adults fail to meet guidelines. To address this major public health issue, it is essential to broadly consider determinants of physical activity. Aims: This study explores how physical activity behavior is impacted by the experience of major life events and considers the stress experienced due to these events across the life course. Methods: Nationally representative panel data from the American’s Changing Lives survey (1986-2012) was used to analyze a growth model with age-based trajectories to examine the relationship between major life events and physical activity overall and separately by gender and race. Results: In the overall sample, retiring was associated with greater physical activity at baseline. As respondents aged, entering into retirement was associated with decreased physical activity, while a parent or friend dying were associated with greater physical activity. Differences by gender and race were also seen over time. Conclusions: Results show that when considering physical activity trajectories, experiencing these major life events is not always detrimental, and in some cases may be beneficial. Considering these impacts is important in planning effective health promotion interventions to increase and promote maintenance of physical activity, while paying attention to specific differences by gender and race

The Complexity of Determining Whether a Nursing Home Transfer Is Avoidable at Time of Transfer

Objectives To describe the relationship between nursing facility resident risk conditions and signs and symptoms at time of acute transfer and diagnosis of conditions associated with potentially avoidable acute transfers (pneumonia, urinary tract infection, congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) or asthma, dehydration, pressure sores). Design As part of a demonstration project to reduce potentially avoidable hospital transfers, Optimizing Patient Transfers, Impacting Medical Quality, Improving Symptoms: Transforming Institutional Care (OPTIMISTIC) project clinical staff collected data on residents who transferred to the emergency department (ED) or hospital. Cross‐tabulations were used to identify associations between risk conditions or symptoms and hospital diagnoses or death. Mixed‐effects logistic regression models were used to describe the significance of risk conditions, signs, or symptoms as predictors of potentially avoidable hospital diagnoses or death. Setting Indiana nursing facilities (N=19). Participants Long‐stay nursing facility residents (N=1,174), who experienced 1,931 acute transfers from November 2014 to July 2016. Measurements Participant symptoms, transfers, risk factors, and hospital diagnoses. Results We found that 44% of acute transfers were associated with 1 of 6 potentially avoidable diagnoses. Symptoms before transfer did not discriminate well among hospital diagnoses. Symptoms mapped into multiple diagnoses and most hospital diagnoses had multiple associated symptoms. For example, more than two‐thirds of acute transfers of residents with a history of CHF and COPD were for reasons other than exacerbations of those two conditions. Conclusion Although it is widely recognized that many transfers of nursing facility residents are potentially avoidable, determining “avoidability” at time of transfer is complex. Symptoms and risk conditions were only weakly predictive of hospital diagnoses

Management of Immediate Post- Endovascular Aortic Aneurysm Repair Type Ia Endoleaks and Late Outcomes

BACKGROUND—Post-endovascular aortic aneurysm repair (EVAR) endoleaks and the need for reintervention are challenging. Additional endovascular treatment is advised for type Ia endoleaks detected on post-EVAR completion angiogram. This study analyzed management and late outcomes of these endoleaks. STUDY DESIGN—This was a retrospective review of prospectively collected data from EVAR patients during a 10-year period. All post-EVAR type Ia endoleaks on completion angiogram were identified (group A) and their early (30-day) and late outcomes were compared with outcomes of patients without endoleaks (group B). Kaplan-Meier analysis was used for survival analysis, sac expansion, late type Ia endoleak, and reintervention. RESULTS—Seventy-one of 565 (12.6%) patients had immediate post-EVAR type Ia endoleak. Early intervention (proximal aortic cuffs and/or stenting) was used in 56 of 71 (79%) in group A vs 31 of 494 (6%) in group B (p \u3c 0.0001). Late type Ia endoleak was noted in 9 patients (13%) in group A at a mean follow-up of 28 months vs 10 patients (2%) in group B at a mean follow-up of 32 months (p \u3c 0.0001). Late sac expansion and reintervention rates were 9% and 10% for group A vs 5% and 3% for group B (p = 0.2698 and p = 0.0198), respectively. Freedom rates from late type Ia endoleaks at 1, 3, and 5 years for group A were 88%, 85%, and 80% vs 98%, 98%, and 96% for group B (p \u3c 0.001); and for late intervention, were 94%, 92%, and 77% for group A, and 99%, 97%, and 95% for group B (p = 0.007), respectively. Survival rates were similar. CONCLUSIONS—Immediate post-EVAR type Ia endoleaks are associated with higher rates of early interventions, late endoleaks and reintervention, which will necessitate strict post-EVAR surveillance

Integrating physical and economic data into experimental water accounts for the United States: Lessons and opportunities

Water management increasingly involves tradeoffs, making its accounting highly relevant in our interconnected world. Physical and economic data about water in many nations are becoming more widely integrated through application of the System of Environmental-Economic Accounts for Water (SEEA-Water), which enables the tracking of linkages between water and the economy. We present the first national and subnational SEEA-Water accounts for the United States. We compile accounts for water: (1) physical supply and use, (2) productivity, (3) quality, and (4) emissions for roughly the years 2000 to 2015. Total U.S. water use declined by 22% from 2000 to 2015, falling in 44 states though groundwater use increased in 21 states. Water-use reductions, combined with economic growth, led to increases in water productivity for the overall national economy (65%), mining (99%), and agriculture (68%). Surface-water quality trends were most evident at regional levels, and differed by waterquality constituent and region. This work provides (1) a baseline of recent historical water resource trends and their value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.This work was conducted as a part of the “Accounting for U.S. Ecosystem Services at National and Subnational Scales” working group supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation (grant DBI-1052875) and the U.S. Geological Survey (USGS) John Wesley Powell Center for Analysis and Synthesis (grant GX16EW00ECSV00). We thank members of the working group for constructive discussions of the scope and content of U.S. water accounts and reviews of this manuscript. We thank the following individuals for assistance with data access and interpretation: Cheryl Dieter, Carey Johnston, John Lovelace, Molly Maupin, Gary Rowe, and Lori Sprague. Support for Bagstad and Ancona’s time was provided by the USGS Land Change Science Program

Division of Credit Modeling for Team Sports with an Emphasis on NCAA Volleyball

Assessing player contribution in team sports has direct application to setting lineups and constructing team rosters. It also plays a big role in fan engagement, providing media content for talk show debates and opinion articles. Traditionally collected player contribution metrics have focused on a single aspect of game play and, as a result, haven’t captured the full contribution of a player. More recent metrics have been developed to more fully capture total contribution, placing players on a common basis of comparison. This dissertation proposes a general framework known as Division of Credit modeling for team sports. The purpose of which is to develop data driven approaches to value player contribution based on the apportioning of value from play outcomes. Many of its subcomponents can be found in the sports literature, but are presented here as a cohesive framework and applied directly to National Collegiate Athletic Association Women’s Volleyball. Volleyball is a generally underexplored sport in the literature for player evaluation, but has the necessary elements for a Division of Credit metric to make it a prime example. Models are presented to value contribution based on player presence, similar to the adjusted plus/minus, and to value contribution based on player action grades, a more thorough approach. The work concludes by describing extensions of these models to football

Individual Health Outcomes Secondary to a Nurse-Led Coalition Based Health Promotion Program for Underserved Diverse Populations

This study describes the impact of various levels of participation in a nurse-led coalition-based wellness program on participant outcomes related to body mass index, blood pressure, diabetes risk and lifestyle behaviors in a Midwest rural county

A Lost Opportunity: Recovering the End of Major League Baseball's 1994 Strike Shortened Season

The 1994 Major League Baseball (MLB) Season ended prematurely when the players went on strike on August 12th, due to a labor disagreement with team owners. This paper describes the model estimation for predicting the runs scored in each of the unplayed games and gives the results of 1,000 simulations. Of particular interest are the Cleveland Indians and the Montreal Expos. The Expos were on pace to have the best season in franchise history (and the best record in the league), while the Indians were poised to begin a very successful run that could have ended the city's World Championship drought dating from 1948

A Lost Opportunity: Recovering the End of Major League Baseball's 1994 Strike Shortened Season

The 1994 Major League Baseball (MLB) Season ended prematurely when the players went on strike on August 12th, due to a labor disagreement with team owners. This paper describes the model estimation for predicting the runs scored in each of the unplayed games and gives the results of 1,000 simulations. Of particular interest are the Cleveland Indians and the Montreal Expos. The Expos were on pace to have the best season in franchise history (and the best record in the league), while the Indians were poised to begin a very successful run that could have ended the city's World Championship drought dating from 1948