Bad Altitude: Categorizing Elevation Produces Spurious Association With Concussions in the National Football League (NFL)

Limitations of Separating Athletes into High or Low-Risk Groups based on a Cut-Off. A Clinical Commentary

Background

Athlete injury risk assessment and management is an important, yet challenging task for sport and exercise medicine professionals. A common approach to injury risk screening is to stratify athletes into risk groups based on their performance on a test relative to a cut-off threshold. However, one potential reason for ineffective injury prevention efforts is the over-reliance on identifying these 'at-risk' groups using arbitrary cut-offs for these tests and measures. The purpose of this commentary is to discuss the conceptual and technical issues related to the use of a cut-off in both research and clinical practice.

Clinical Question

How can we better assess and interpret clinical tests or measures to enable a more effective injury risk assessment in athletes?

Key Results

Cut-offs typically lack strong biologic plausibility to support them; and are typically derived in a data-driven manner and thus not generalizable to other samples. When a cut-off is used in analyses, information is lost, leading to potentially misleading results and less accurate injury risk prediction. Dichotomizing a continuous variable using a cut-off should be avoided. Using continuous variables on its original scale is advantageous because information is not discarded, outcome prediction accuracy is not lost, and personalized medicine can be facilitated.

Clinical Application

Researchers and clinicians are encouraged to analyze and interpret the results of tests and measures using continuous variables and avoid relying on singular cut-offs to guide decisions. Injury risk can be predicted more accurately when using continuous variables in their natural form. A more accurate risk prediction will facilitate personalized approaches to injury risk mitigation and may lead to a decline in injury rates.

Level of Evidence

5.

Interaction of Surface Type, Temperature, and Week of Season on Concussion Risk in the National Football League: A Bayesian Analysis

BACKGROUND

Artificial turf fields and environmental conditions may influence sports concussion risk, but existing research is limited by uncontrolled confounding factors, limited sample size, and the assumption that risk factors are independent of one another. The purpose of this study was to examine how playing surface, time of season, and game temperature relate to diagnosed concussion risk in the National Football League (NFL).

METHODS

This retrospective cohort study examined data from the 2012 to the 2019 NFL regular season. We fit Bayesian negative binomial regression models to relate how playing surface, game temperature, and week of the season independently related to diagnosed concussion risk and any interactions among these factors.

RESULTS

We identified 1096 diagnosed concussions in 1830 games. There was a >99% probability that concussion risk was reduced on grass surface (median incidence rate ratio [IRR] = 0.78 [95% credible interval: 0.68, 0.89]), >99% probability that concussion risk was lower at higher temperatures (IRR = 0.85 [0.76,0.95] for each 7.9 °C), and >91% probability that concussion risk increased with each week of the season (IRR = 1.02 [1.00,1.04]). There was an >84% probability for a surface × temperature interaction (IRR = 1.01 [0.96, 1.28]) and >75% probability for a surface × week interaction (IRR = 1.02 [0.99, 1.05]).

CONCLUSIONS

Diagnosed concussion risk is increased on artificial turf compared with natural grass, and this is exacerbated in cold weather and, independently, later in the season. The complex interplay between these factors necessitates accounting for multiple factors and their interactions when investigating sports injury risk factors and devising mitigation methods.

Do Climate and Environmental Characteristics Influence Concussion Incidence in Outdoor Contact Sports? A Systematic Review

OBJECTIVE

To obtain a comprehensive understanding of the implications of environmental and climate factors on sport-related concussion incidence in outdoor contact sports.

DATA SOURCES

MEDLINE (via Ovid), Embase (via Elsevier), CINAHL Complete (via EBSCOhost), SPORTDiscus (via EBSCOhost), and Scopus (via Elsevier).

STUDY SELECTION

Studies that report incidence of sport-related concussion, assess data from athletes participating in outdoor contact sports, report on 1 or more climate or environmental factors, and report a diagnosis of concussion performed by a licensed medical professional were included. Reasons for exclusion included no report on extrinsic or environmental factors, no data on sport-related concussion incidence, and self-report of concussion diagnosis.

DATA EXTRACTION

This systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines using 2 reviewers at each phase and a third reviewer for conflict resolution.

DATA SYNTHESIS

A total of 7558 articles were reviewed, and 20 met the inclusion criteria. There was moderate to strong strength of evidence concluding no difference between surface type (grass versus artificial) on sport-related concussion risk. Moderate to strong strength of evidence was found supporting no difference in sport-related concussion incidence based on game location (home versus away). There was no consensus on the effects of altitude or temperature on sport-related concussion incidence. One high-quality study found a decreased risk of sport-related concussion when playing in wet versus dry conditions. Heterogenous populations and data collection methods prevented extraction and meta-analysis.

CONCLUSIONS

Although a consensus on specific environmental and climate factors that influence sport-related concussion incidence was limited, the majority of studies were of high quality and gave insight into opportunities for future investigation. Administrators of large injury surveillance databases should consider including specific environmental and climate factors to provide investigators with robust data sets to better understand potential associations with sport-related concussion.