Holistic Life-Span Health Outcomes Among Elite Intercollegiate Student–Athletes

Abstract

Context: Competitive sports are recognized as having unique health benefits and risks, and the effect of sports on life-span health among elite athletes has received increasing attention. However, supporting scientific data are sparse and do not represent modern athletes.Objective: To assess holistic life-span health and healthrelated quality-of-life (HRQL) among current and former National Collegiate Athletic Association student-athletes (SAs).Design: Cross-sectional study. Conclusions: The SAs demonstrated significant, clinically meaningful evidence of greater joint health concerns later in life, comparable cardiopulmonary health, and differences in life-span psychosocial health and HRQL profiles compared with NAs. These data provide timely evidence regarding a compelling public issue and highlight the need for further study of life-span health among modern athletes.Key Words: athletes, quality of life, questionnaires, National Collegiate Athletic Association Key PointsCompared with their nonathlete peers, former National Collegiate Athletic Association intercollegiate studentathletes demonstrated a greater risk for joint health concerns later in life, similar life-span cardiopulmonary health, and different age-related profiles of psychosocial health and health-related quality of life. These findings highlight the need for additional research studies and proactive, evidence-based intervention programs addressing holistic, life-span health, and wellness outcomes among modern competitive athletes.

Health-Related Quality of Life in Athletes: A Systematic Review With Meta-Analysis

“…The overall random-effects meta-analysis for all composite or total score comparisons revealed a weak ES of 0.27 (95% CI ¼ 0.14, 0.40; P ,.001; Figure 2). Among the 3 studies 28,33,34 that had data available for analysis using a composite score (PCS or MCS) as the moderator variable, a difference was evident (Q ¼ 4.86, P ¼ .03). The results revealed a weak effect of 0.03 (95% CI ¼À0.32, 0.53; P ¼ .86) for the PCS and a moderate effect of 0.46 (95% CI ¼ 0.31, 0.61; P ¼ .002) for the MCS.…”

“…Two additional studies 10,28 were identified through the hand search, resulting in a total of 8 eligible studies, which were classified into athletes and nonathletes (Table 2) and uninjured and injured athletes (Table 3). Five articles 10,28,30,33,34 met the inclusion criteria for this question. Quality scores ranged from 70.6% to 82.4% with 3 high-quality 10,33,34 (!75%) and 2 moderate-quality 28,30 studies (60%, 74.9%).…”

“…Five articles 10,28,30,33,34 met the inclusion criteria for this question. Quality scores ranged from 70.6% to 82.4% with 3 high-quality 10,33,34 (!75%) and 2 moderate-quality 28,30 studies (60%, 74.9%). The mean mDB score was 76.5% 6 5.9%.…”

“…The mean mDB score was 76.5% 6 5.9%. Four articles 28,30,33,34 provided sufficient data for the calculation of ESs and 95% CIs ( Table 4). The overall random-effects meta-analysis for all composite or total score comparisons revealed a weak ES of 0.27 (95% CI ¼ 0.14, 0.40; P ,.001; Figure 2).…”

“…[25][26][27] Health-related quality of life has become an important component of health surveillance, and the use of PRO instruments enables clinicians to track HRQOL deficits postinjury. 27 Several groups 10,[28][29][30][31][32][33][34] have used generic outcomes such as the Short Form-36 (SF-36), Pediatric Outcomes Data Collection Instrument (PODCI), and Pediatric Quality of Life Inventory (PedsQL) to measure HRQOL in athletes and nonathletes and the effect of sport-related injury on HRQOL. Although the evidence suggests that normative values for athletes differ from the general population 28,30,33,34 and between injured and uninjured athletes, 10,29,31,32 this evidence has not been synthesized.…”