Knee Injuries in NFL Lineman -- A Correlation with BMI

Knee Injuries in NFL Linemen - Correlation with BMI Dr. Michael Lem, MD; Dr. John Bianchi, DO; Austin Irwin, OMS II; Dr. Robert Farrell, MD; Cole Siegenfeld, OMS II Purpose: Knee injuries are among the most common injuries suffered in the NFL which in turn can decrease a player\u27s playing time in a given season and thus negatively impact future performance. Understanding characteristics like BMI can help modify and identify players at risk for knee injuries. Methods and Study Design: Data collected for this study was extracted from the official NFL database of injuries. Reported knee injuries for offensive and defensive lineman were collected and organized by week during the 2009-2022 seasons; final data was calculated for players with a BMI over 39.95. Pro-football-reference.com was cited for height, weight, career length and draft status. BMI was calculated based on height and weight. Comparisons were made between BMI and game status. Results: Among the players collected, offensive tackles were the most likely to appear on the injury report. Players with a BMI above 40 appeared most commonly as Probable (n=182), followed by Questionable (157), Out (134) then Doubtful (26). The average BMI for the players listed as probable was x=42.4 (SD=2.69); questionable x=41.2 (1.37); doubtful x=41.0 (.856); out x=40.9 (.991). There is a significant difference in the player’s BMI between “probable” game status and both “questionable” (p=.023) and “out” (p\u3c .001). Players with a BMI= +37 appeared as either out or doubtful 30.07% total. Players with a BMI under 37 appeared as either out or doubtful 30.81%. Conclusions: Based on our data, BMI may play a protective role on injury report placement for knee injuries. The abundance of “probable” game status also supports the notion that the injuries studied are lower-grade. More players appear on the injury list towards the end of the season, which may indicate there is a persisting effect to the injuries

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

International Society of Sports Nutrition Position Stand: protein and exercise

Abstract Position statement The International Society of Sports Nutrition (ISSN) provides an objective and critical review related to the intake of protein for healthy, exercising individuals. Based on the current available literature, the position of the Society is as follows: 1) An acute exercise stimulus, particularly resistance exercise, and protein ingestion both stimulate muscle protein synthesis (MPS) and are synergistic when protein consumption occurs before or after resistance exercise. 2) For building muscle mass and for maintaining muscle mass through a positive muscle protein balance, an overall daily protein intake in the range of 1.4–2.0 g protein/kg body weight/day (g/kg/d) is sufficient for most exercising individuals, a value that falls in line within the Acceptable Macronutrient Distribution Range published by the Institute of Medicine for protein. 3) There is novel evidence that suggests higher protein intakes (>3.0 g/kg/d) may have positive effects on body composition in resistance-trained individuals (i.e., promote loss of fat mass). 4) Recommendations regarding the optimal protein intake per serving for athletes to maximize MPS are mixed and are dependent upon age and recent resistance exercise stimuli. General recommendations are 0.25 g of a high-quality protein per kg of body weight, or an absolute dose of 20–40 g. 5) Acute protein doses should strive to contain 700–3000 mg of leucine and/or a higher relative leucine content, in addition to a balanced array of the essential amino acids (EAAs). 6) These protein doses should ideally be evenly distributed, every 3–4 h, across the day. 7) The optimal time period during which to ingest protein is likely a matter of individual tolerance, since benefits are derived from pre- or post-workout ingestion; however, the anabolic effect of exercise is long-lasting (at least 24 h), but likely diminishes with increasing time post-exercise. 8) While it is possible for physically active individuals to obtain their daily protein requirements through the consumption of whole foods, supplementation is a practical way of ensuring intake of adequate protein quality and quantity, while minimizing caloric intake, particularly for athletes who typically complete high volumes of training. 9) Rapidly digested proteins that contain high proportions of essential amino acids (EAAs) and adequate leucine, are most effective in stimulating MPS. 10) Different types and quality of protein can affect amino acid bioavailability following protein supplementation. 11) Athletes should consider focusing on whole food sources of protein that contain all of the EAAs (i.e., it is the EAAs that are required to stimulate MPS). 12) Endurance athletes should focus on achieving adequate carbohydrate intake to promote optimal performance; the addition of protein may help to offset muscle damage and promote recovery. 13) Pre-sleep casein protein intake (30–40 g) provides increases in overnight MPS and metabolic rate without influencing lipolysis