Sleep Inadequacy and the Relationship with Mucosal Immunity and Upper Respiratory Symptoms in Elite Swimmers: A Longitudinal Study Leading into the Commonwealth Games

A total of 23 elite swimmers were recruited between 21/08/2017 and 31/09/2017; however, nine did not complete the eight-month observation due to retiring during the study (n = 4) or because they did not train on the chosen analysis day due to university commitments (n = 5). Therefore, 14 elite national and international swimmers were included. Swimmers were within two training groups: sprint (43%) and middle-distance/distance (57%). A total of 10 swim sessions a week were programmed: five early morning sessions and five afternoon/evening sessions (plus S&C sessions). Prior to study commencement, swimmers provided written fully informed consent and health screens. Ethical approval was granted for human investigation by The University of Hertfordshire, Health Science Engineering & Technology ECDA (Ethics protocol number: aLMS/PGR/UH/02940(1,2,3)). Patients and the public were not involved in design, conduct or reporting of this research, in any way.

Self-reported sleep data was obtained alongside URS data weekly using an adaption of the Australian Institute of Sport (AIS) monthly illness log. Self-perceived sleep quality was monitored by ranking on a scale of 1-10 (1 = poor, 10 = excellent) each week. Moreover, swimmers were asked how many times they thought they had met the NR of 7-9 hours and how many times they had awoken feeling fatigued each week. This sleep data was compared to relative salivary IgA (normalised to each individual's healthy mean), URS, and coach derived training loads of which the methodology has been previously defined[21]. To assess sleep-wake patterns, a wrist-worn activity monitor GT3X+ (ActiGraph, Florida, USA) was worn around the non-dominant wrist during night-time sleep and napping periods only. This was removed when swimmers arose from bed in the morning, or after napping, and swimmers completed daily sleep diaries, which were used to assist in identifying bedtime and wake time for later analysis. Parameters recorded included latency (mins), sleep efficiency (SE; %), total time in bed (TTIB; min), total sleep time (TST; min), wake after sleep onset (WASO; min), number of awakenings, and average time awake (min). Actigraphy data was used to determine objective sleep-wake patterns for different training intensity periods (low, moderate, high training loads and into competition). Actigraphy data was processed using ActiLife software (version 6.13) and individual sleep data reports created by this software were provided to swimmers at the cessation of the study.