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Purpose: Few data are available on sleep characteristics of elite track-and-field athletes. Our study aimed to assess (1) differences in sleep between sexes and among different track-and-field disciplines, (2) the effect of individualized sleep-hygiene strategies on athletes' sleep parameters, and (3) daytime nap characteristics in track-and-field athletes. Methods: Sleep characteristics of 16 elite Olympic-level track-and-field athletes (male: n = 8; female: n = 8) were assessed during the preseason period, at baseline (T0), and during the in-season period, after the adoption of individualized sleep-hygiene strategies (T1). Sleep parameters were objectively monitored by actigraphy for a minimum of 10 days, for each athlete, at both T0 and T1. A total of 702 nights were analyzed (T0 = 425; T1 = 277). Results: Female athletes displayed better sleep efficiency (88.69 [87.69–89.68] vs 91.72 [90.99–92.45]; P =.003, effect size [ES]: 0.44), lower sleep latency (18.99 [15.97–22.00] vs 6.99 [5.65–8.32]; P <.001, ES: 0.65), higher total sleep time (07:03 [06:56–07:11] vs 07:18 [07:10–07:26]; P =.030, ES: 0.26), earlier bedtime (00:24 [00:16–00:32] vs 00:13 [00:04–00:22]; P =.027, ES: 0.18), and lower nap frequency (P <.001) than male athletes. Long-distance runners had earlier bedtime (00:10 [00:03–00:38] vs 00:36 [00:26–00:46]; P <.001, ES: 0.41) and wake-up time (07:41 [07:36–07:46] vs 08:18 [08:07–08:30]; P <.001, ES: 0.61), higher nap frequency, but lower sleep efficiency (88.79 [87.80–89.77] vs 91.67 [90.95–92.38]; P =.013, ES: 0.44), and longer sleep latency (18.89 [15.94–21.84] vs 6.69 [5.33–8.06]; P <.001, ES: 0.67) than athletes of short-term disciplines. Furthermore, sleep-hygiene strategies had a positive impact on athletes' total sleep time (429.2 [423.5–434.8] vs 451.4 [444.2–458.6]; P <.001, ES: 0.37) and sleep latency (14.33 [12.34–16.32] vs 10.67 [8.66–12.68]; P =.017, ES: 0.19). Conclusions: Sleep quality and quantity were suboptimal at baseline in Olympic-level track-and-field athletes. Large differences were observed in sleep characteristics between sexes and among different track-and-field disciplines. Given the positive effect of individualized sleep-hygiene strategies on athlete's sleep, coaches should implement sleep education sessions in the daily routine of top-level athletes. [ABSTRACT FROM AUTHOR]

High fish consumption may be associated with lower inflammation, suppressing atherosclerotic CVD (ASCVD). Long sleep duration, as well as short sleep, may contribute to inflammation, thus facilitating ASCVD. This study investigated the overall association between fish consumption, sleep duration and leucocytes count. We conducted a cross-sectional study between April 2019 and March 2020 with a cohort of 8947 apparently healthy participants with no history of ASCVD (average age, 46·9 ± 12·3 years and 59 % males). The average frequency of fish consumption and sleep duration were 2·13 ± 1·26 d/week and 6·0 ± 0·97 h/d. Multivariate linear regression analysis revealed that increased fish consumption was an independent determinant of sleep duration (β = 0·084, P < 0·0001). Additionally, habitual aerobic exercise (β = 0·059, P < 0·0001) or cigarette smoking (β = −0·051, P < 0·0001) and homoeostasis model assessment-insulin resistance (HOMA-IR) (β = −0·039, P = 0·01) were independent determinants of sleep duration. Furthermore, multivariate linear regression analysis identified fish consumption as an independent determinant of leucocytes count (β = −0·091, P < 0·0001). However, a significant U-shaped curve was found between leucocytes count and sleep duration, with 6–7 h of sleep as the low value (P = 0·015). Higher fish consumption may be associated with a lower leucocytes count in the presence of adequate sleep duration and healthy lifestyle behaviors. However, long sleep duration was also related to increased inflammation, even in populations with high fish consumption. Further studies are needed to clarify the causality between these factors. [ABSTRACT FROM AUTHOR]