GENERAL INFORMATION

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

2. Author Information
	A. Principal Investigator Contact Information
		Name: Dr Lauren H Baker 
		Institution: University of Hertfordshire 
		Address: Centre for Research in Psychology and Sports, School of Health, Medicine and Life Sciences, University of Hertfordshire, 			Hertfordshire, UK 
		Email: L.baker5@herts.ac.uk

	B. Associate or Co-investigator Contact Information
		Name: Dr Terun Desai
		Institution: University College London
		Address: Institute of Sport, Exercise & Health, Division of Surgery & Interventional Science, University College London, London, UK
		Email: t.desai@ucl.ac.uk

	B. Associate or Co-investigator Contact Information
		Name: Dr Jonathan Sinclair
		Institution: University of Central Lancashire
		Address: Research Centre for Applied Sport, Physical Activity and Performance, School of Sport & Health Sciences, Faculty of Allied Health 		and Wellbeing, University of Central Lancashire, Lancashire, UK
		Email: jksinclair@lancashire.ac.uk
	
	B. Associate or Co-investigator Contact Information
		Name: Dr Amy Wells
		Institution: University of Hertfordshire
		Address: Centre for Research in Psychology and Sports, School of Health, Medicine and Life Sciences, University of Hertfordshire, 			Hertfordshire, UK 
		Email: a.v.wells@herts.ac.uk
	

3. Date of data collection August 2017 to June 2018

4. Geographic location of data collection England 

5. Information about funding sources that supported the collection of the data: This research was solely funded by the University of Hertfordshire, with an internal Early Career/ Returning to Research grant for A.W. Those that provided the internal grant had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No external financial support was gained.


SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: CC-BY

2. Links to publications that cite or use the data: Currently under review in PLOS One

3. Links to other publicly accessible locations of the data: none

4. Links/relationships to ancillary data sets: none 

5. Was data derived from another source? no
	A. If yes, list source(s): 

6. Recommended citation for this dataset: Baker, L.H, Desai, T., Sinclair, J., and Wells, A.V. (2026). Sleep Inadequacy and the Relationship with Mucosal Immunity and Upper Respiratory Symptoms in Elite Swimmers: A Longitudinal Study Leading into the Commonwealth Games. https://...
 

DATA & FILE OVERVIEW

1. File List: 

There is 1 file that contains an anonymised dataset. 
 

3. Additional related data collected that was not included in the current data package: N/A


4. Are there multiple versions of the dataset? No
	


METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: 

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. 

2. Methods for processing the data: 

Data was compiled using Microsoft Excel and evaluated using both SPSS software (version 26.0; SPSS Lead Technologies Inc, Chicago, IL) and GraphPad Prism 8.0 (GraphPad Software, Inc., San Diego, CA). Results were presented as mean ± SD, and significance was accepted at the p ≤ 0.05 level. Repeated measures correlations were used to determine relationships between self-reported sleep parameters, URS and salivary IgA. Data was reported as rrm and its 95% confidence interval (95% CI). The strength of the relationship was determined using the standard correlation coefficient interpretation scale used elsewhere[23] classified as no relationship (0), weak (0.1-0.3), moderate (0.4-0.6), strong (0.7-0.9), and perfect (1.0). Repeated measures analysis of variance (ANOVA) with post-hoc Bonferroni adjustment measured differences in measures of URS and sleep parameters between training loads. Greenhouse-Geisser correction was applied upon violation of Mauchly’s test of sphericity for ANOVAs (p < .05). For ANOVA analyses, Partial Eta-Squared ( ) was used to report effect sizes which were classified as small (0.01-0.08), moderate (0.09-0.25) and large (>0.25). 


3. Instrument- or software-specific information needed to interpret the data: 
Excel (Microsoft software package, California, USA),  R Foundation for Statistical Computing (version 2023.12.1+40) and SPSS v27

4. Standards and calibration information, if appropriate: N/A

5. Environmental/experimental conditions: All participants were listed as adult elite international swimmers within British Swimming. 

6. Describe any quality-assurance procedures performed on the data: N/A

7. People involved with sample collection, processing, analysis and/or submission: 
Dr Lauren Baker


DATA-SPECIFIC INFORMATION FOR: DataSet_Sleep

1. Number of variables: 9 variables 
2. Number of cases/rows: 20 cases (rows)

3. Variable List: (Sleep Score, Sleep – National Recommendation, Sleep – Fatigue, Illness Score, Number of URS, Objective Night-Time Sleep, Objective Napping, IgA, training load). Each variable is provided as a separate worksheet within the Excel file. Individual worksheets contain their own internal variables and observations.

4. Missing data codes: 
There are no missing data codes, the cells are just blank.

5. Specialized formats or other abbreviations used: 
N/A