Article Text
Abstract
Objective To review risk factors associated with acute respiratory illness (ARill) in athletes, including non-infectious ARill and suspected or confirmed acute respiratory infections (ARinf).
Design Systematic review.
Data sources Electronic databases: PubMed-Medline, EbscoHost and Web of Science.
Eligibility criteria Original research articles published between January 1990 and July 2020 in English were searched for prospective and retrospective full text studies that reported quantitative data on risk factors associated with ARill/ARinf in athletes, at any level of performance (elite/non-elite), aged 15–65 years.
Results 48 studies (n=19 390 athletes) were included in the study. Risk factors associated with ARill/ARinf were: increased training monotony, endurance training programmes, lack of tapering, training during winter or at altitude, international travel and vitamin D deficits. Low tear-(SIgA) and salivary-(IgA) were immune biomarkers associated with ARill/ARinf.
Conclusions Modifiable training and environmental risk factors could be considered by sports coaches and athletes to reduce the risk of ARill/ARinf. Clinicians working with athletes can consider assessing and treating specific nutritional deficiencies such as vitamin D. More research regarding the role and clinical application of measuring immune biomarkers in athletes at high risk of ARill/ARinf is warranted.
PROSPERO registration number CRD42020160928.
- athletes
- risk factor
- respiratory system
- infection
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Introduction
Acute respiratory illnesses (ARill), especially respiratory tract infections (ARinf), are the most common illnesses affecting athletes.1 2 At major events, such as Olympic and Paralympic Games, ARinf have been reported to be common among elite athletes, and can cause absence from both training and competition.3–5 Exercise during ARinf may increase the risk of serious health complications, such as myocarditis.6 In the general population, adults typically experience 2–4 ARill per year.7 8
Few studies have addressed the risk factors for ARill and ARinf in athletic cohorts. To date studies have not attempted to differentiate between ARill that can include both non-infective or infective causes, and suspected or confirmed ARinf. Non-infective causes of ARill can mimic symptoms of infections. These may be due to allergies or airway inflammation caused by factors such as pollution, chemical irritants and exposure to cold or dry air. As ARill and ARinf are common medical complaints in athletes, it is important for clinicians and training staff to understand the types and magnitude of risk factors predisposing athletes to ARill and/or ARinf.
Risk factors associated with ARill and ARinf can be categorised broadly into individual athlete factors (age, gender, medical history and co-morbidities), sport (type and level of participation), training and competition factors, nutritional factors, environmental factors (season, air temperature, pollution, altitude), exposure factors (international travel, household exposure, personal hygiene, physical distancing, crowded and indoor environments), and immune/haematological risk factors and biomarkers. Cross-sectional studies of athletes indicate that individuals with high training loads have a greater frequency of ARill.9 10 Longitudinal studies of athletes report an increased incidence of ARill during periods of intense training or competition.11–13 Elite athletes may be predisposed to ARinf during periods of increased physical and mental stressors which may suppress both innate and adaptive immunity.14–18 Individual studies have reported that strenuous exercise-induced immunosuppression, mental stress, nutritional restrictions, air travel, human crowding, housing with other athletes, low temperature with low humidity, and competition all potentially increase the risk for ARinf, especially during the winter season when respiratory viruses are more prevalent.4 12 18 No previous systematic review has been conducted that highlights important risk factors for ARill and ARinf in athletes.
The aim of this study was to conduct a systematic review of risk factors associated with general (undiagnosed) ARill and ARinf (suspected or confirmed by laboratory identification of the pathogen) in athletes.
Methods
Protocol and registration
A protocol was developed according to guidelines outlined in the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.19 The PRISMA checklist is presented in online supplemental file S1.
Supplemental material
Study selection and eligibility criteria
Eligibility criteria were established and agreed on by all authors based on the concepts of population and outcome. Studies that met the following criteria were considered eligible for inclusion in this systematic review:
Participants, male and female, who are athletes at any level (recreational to elite) or military populations engaged in training, aged 15–65 years old.
Reporting on self-reported and/or physician diagnosed ARill, as well as clinically diagnosed and laboratory confirmed ARinf.
Reporting ARill during training, events/tournaments, multistage events and directly after an event.
Prior to the search strategy implementation it was agreed across all International Olympic Committee consensus groups that journal articles with full-text original prospective and/or retrospective studies published in English between 1 January 1990 and 31 July 2020 will be included.
Studies reporting factor/s predisposing athletes to ARill.
Exclusion criteria were set as studies:
Conducted with a heterogeneous sample (ie, mixed sample of athletic and non-athletic populations) without reporting individual group findings separately.
Available as an abstract only (ie, conference presentations), qualitative or case series, discussion paper, commentary or literature review.
Not available in English.
While asthma and allergy can be independent risk factors associated with ARill, it should be noted they were not included in this review, which has a focus on infections as a cause of ARill.
Search strategy
Researchers systematically searched three electronic databases: PubMed-Medline, EBSCOhost and Web of Science. Medical subject heading (MeSH) terms included: upper respiratory tract infection* OR upper respiratory illness* OR upper respiratory symptom* AND athlet* AND risk factors, and relevant exclusions (see online supplemental file S1). A secondary search of the reference lists of included articles and hand searching in Google Scholar were performed. Further articles the authors were aware of relating to the topic were added to the search results. Duplicate articles were removed from the combined searches. Article screening and selection utilised the online tool CADIMA.20 The articles were then screened independently by three reviewers (LK, JG-E and KM). Full texts of articles were retrieved, and a second independent screening was undertaken by four independent reviewers (LK, JG-E, KM, MG). Any conflicts were resolved through discussion and consensus between reviewers.
Data extraction
Data were extracted for each study independently and agreed by consensus (WD, MM, MG, JF, KM, MS, MB, JG-E, ME, LK). Extracted data included: Participant details (number, age, gender), study design, level of sport performance (elite/professional to non-elite/amateur), sport type, tournament or non-tournament and statistical measures of significance for risk ratios, prevalence ratios. Data related to risk factor/s and biomarkers associated with ARill and ARinf were grouped into the following main categories: (1) demographics (age, gender), (2) sport (type and level of participation), (3) training and competition factors, (4) nutritional factors, (5) environmental/exposure factors (season, altitude, international travel, household exposure) and (6) immune/haematological risk factors and biomarkers.
Criteria and definitions
The criteria and definitions of risk factor, odds ratio, risk, risk ratio/relative risk and level of athletic performance are outlined in online supplemental file S2.
Supplemental material
Definitions and classification of subgroups of ARill
The methods used to diagnose ARill/ARinf in each study were classified as follows: (1) self-reported symptoms of ARill only, (2) self-reported symptoms but with an algorithm validated for ARinf, (3) self-reported symptoms of an ARinf reviewed by a physician, but without clinical or laboratory evaluation, (4) clinical diagnosis of an ARinf by a physician, based on history and clinical examination, (5) diagnosis of ARinf by a physician that was confirmed by laboratory investigation to identify a specific pathogen. Studies were classified by the five methods of diagnosis and included in one of the main and subgroups of ARill, based on a pathological classification (online supplemental file S2).
ARill, including ARinf, frequently present with both upper and lower respiratory tract symptoms/signs and it is not always possible to clearly distinguish between these anatomical regions when classifying ARill. A limitation of this anatomical classification is that several pathogens that cause predominantly upper ARinf can, in some cases, present with lower respiratory and/or systemic symptoms. A clear distinction was made in many studies, hence the anatomical classification was assessed in this review according to the following classifications:
Upper (ARill or ARinf): Studies where the predominant symptoms, signs, or confirmed pathology was mainly related to the upper respiratory tract (ie, above the larynx), or if the study specifically referred to athletes with upper ARill or ARinf. A few studies referred to ARinf with non-specific terms such as ‘influenza’, ‘influenza symptoms’, ‘common cold’, ‘symptoms suggestive of influenza’, ‘influenza symptoms’ or ‘influenza like’. Studies referring to these clinical syndromes were also included in this broad anatomical classification because they are caused by pathogens that all present with predominantly upper respiratory tract symptoms.7 21–23 Notably, this includes the influenza viruses, which predominantly present with upper respiratory tract symptoms24 and are listed as a cause of upper respiratory tract infections.7 21 22
Lower (ARill or ARinf): Studies where the predominant symptoms were below the larynx (including chest symptoms ie, cough, chest pain), or if the diagnosis specifically referred to lower respiratory illness (tracheal, bronchial or lung pathology, eg, pneumonia).
General (upper/lower) (ARill or ARinf): Studies where there were no data to distinguish between upper or lower respiratory tract ARill or ARinf, and could include upper, lower or both.
Measures of outcome and determination of strength of association
Risk factors and biomarkers reported in the studies for undiagnosed ARill and suspected and confirmed ARinf, were listed by category of risk and strength of each association evaluated. There was significant heterogeneity in outcome variables reported (eg, relative risk or % athletes affected, single or confounders analysis). As a result, a four level metric was developed to classify the type and strength of an association between a risk factor and ARill or ARinf as follows: no association (0, 00 or 000), some association (+), good association (++) or strong association (+++). A risk factor association was rated as weak evidence ‘no association’ when a simple analysis was performed, such as any of the following statistical tests: descriptive analysis, Pearson’s correlation analysis or grouping t-student’s analysis (0). Good evidence for ‘no association’ was rated as (00) when the study performed a multivariable analysis without mentioning the confounding variables that were taken into account, while stronger evidence for ‘no association’ was reported as (000) that is, when the study documented a multivariable model analysis taking confounding factors into account (eg, sex, age, season and level of performance). A risk factor association was rated as ‘some’ association (+) if a study documented some form of single statistical analysis. ‘Good’ association (++) was attributed if the study used a statistical analysis which accounted for confounding factors. A risk-factor association was rated as ‘strong’ (+++) if the study documented a multivariable model analysis taking confounding factors into account.
Quality assessment and risk of bias
Studies were reviewed for the quality assessment and risk of bias using a modified Downs and Black tool.25 This was conducted by seven reviewers (LK, JG-E, MB, WD, MB, KM and MG) independently scoring the articles and then discussing differences to reach a consensus score for each article. The same reviewers determined the level of evidence using the Oxford Centre for Evidence Based Medicine (OCEBM, 2009).26 The articles fell into two main categories: Observational studies of the prevalence of symptoms of ARill; or Interventional studies where the incidence of ARill was determined in response to the intervention, with or without control groups. The OCEBM level of evidence was graded using the criteria for a Symptom Prevalence Study for the observational studies based on the degree of follow-up for prospective studies as level 1b for good follow-up, level 2b for retrospective studies and level 3b for non-consecutive cohort studies. The intervention studies were graded using the Therapy/Prevention studies criteria of level 1b for randomised control trials (RCTs) with narrow confidence intervals and level 2b for the non-RCT studies.
Results
Study selection
Four hundred and sixty-one (461) studies were identified in the search. The study selection process and reasons for excluding studies is summarised in figure 1. Eighty-four full-text articles were assessed for eligibility, 36 were excluded and 48 were included. The characteristics of the 48 studies are presented in online supplemental file S3, and the quality assessment in online supplemental file S4. The 48 studies had a total of 19 390 (range: 9–12594) participants. Studies were conducted across 17 sports and 5 performance levels: only elite/professional athletes (n=26; 54.2%); only recreational/trained/competitive athletes (n=16; 33.3%); mixed levels (n=6; 12.5%).
Supplemental material
Supplemental material
Number of studies by pathological and anatomical classification of ARill
The pathological and anatomical classifications of ARill for each study are provided in table 1. Of the 48 studies, 40 (83.3%) reported upper ARill, 8 (16.7%) reported general ARill, with no studies reporting lower ARill only. Seventeen (35.5%) studies reported undiagnosed ARill. Of the 31 (64.5%) studies classified as ARinf, 26 (54%) were suspected infections and five (10.4%) were confirmed ARinf.
Risk factors and biomarkers associated with ARill and ARinf
Risk factors and biomarkers associated with general (undiagnosed) ARill
The main categories of risk factors and biomarkers associated with general (undiagnosed) ARill, by category of risk and strength of each association are presented in table 2. Risk factors that showed a strong association (+++) with general (undiagnosed) ARill were: being a less competitive athlete, elevated white blood cell and neutrophil counts, and a lower serum Vitamin D concentration. Risk factors for which there was strong evidence for no association (000) with general (undiagnosed) ARill were intensified phase of training, competition phase, detection of IgE antibodies to aero-allergens, and a reduction in salivary flow rate. Of interest is that there was both strong evidence for a positive association (+++) and no association (000) between ARill and increased training load.
Risk factors and biomarkers associated with suspected ARinf
The main categories of risk factors and biomarkers associated with suspected ARinf, by category of risk and strength of each association are presented in table 3. Risk factors that showed a strong association (+++) with suspected ARinf were: increments in training load, endurance training, training monotony, training at altitude, winter season, post international travel, less competitive athletes, having reduced serum Vitamin D concentration, and experiencing prior episodes of respiratory infection. A strong association (+++) was found between lower risk of suspected ARinf and autumn season, as well as the tapering phase of training and increased training intensity. Risk factors for which there was strong evidence for no association (000) with suspected ARinf were: age, gender and household family exposure. Of interest is that there was both strong evidence for a positive association (+++) and no association (000) between suspected ARinf and increased training load, increased speed and strength training, and the competition period.
Risk factors and biomarkers associated with confirmed ARinf
The main categories of risk factors and biomarkers associated with confirmed ARinf, by category of risk and strength of each association are presented in table 4. Risk factors and biomarkers that showed a strong association (+++) with confirmed ARinf were: increasing training intensity, lower salivary-(IgA) (preseason, pretraining and across a season) and reduced tear salivary-(IgA) and secretion rates. The only risk factor where there was strong evidence for no association (000) with suspected ARinf was postseason training salivary-(IgA).
Discussion
The aim of this study was to conduct a systematic review of risk factors associated with general (undiagnosed) ARill and ARinf (suspected or confirmed) in athletes. The 48 studies meeting the eligibility criteria were graded as good or excellent, providing confidence in the quality of the studies. However, the small number of studies assessing each risk factor or biomarker made it difficult to draw firm conclusions for most risk factors. In addition, the differences in the methodologies for classifying respiratory illnesses/infections further impaired comparisons. Further discussion of the review findings now focuses on the evidence for associations between increased risk for ARill/ARinf in athletic populations and risk factors in six main categories.
Demographic factors
The findings of this review show that age and gender were not associated with increased risk of any ARill or ARinf (suspected or confirmed).
Sport type and level of participation
In general, sport type was not strongly associated with increased risk of ARill or ARinf (suspected or confirmed). There was some evidence of increased risk of ARill and ARinf in endurance athletes and runners specifically. There was a lower risk of prolonged ARill (symptom days) for elite athletes.27–29 One study hypothesised that the individual training load threshold, above which the risk of illness increases,30 is lower in national level athletes than in international athletes. Other studies concluded that the differences may relate to underlying genetic predispositions for better resistance to infections31 32 or lower proinflammatory responses to infection that present as a reduced incidence of ARill.32–35 Previous research has suggested that higher-level athletes (top professional or elite) are linked to a better athletic lifestyle (personal, academic or professional schedules; better recovery, sleep quality or nutrition) that reduces the risk of ARill.14 36 37 One possibility, not examined, was that the differences are related to the type of sport rather than the level of performance.
Training and competition risk factors
While each risk factor had studies with conflicting results, the review findings for training factors indicated ARill/ARinf, irrespective of classifications, were mostly associated with increased training intensity, endurance phase training and competition periods, but there was a potential lower risk in the tapering phase of training. There was a higher risk for ARill/ARinf in less competitive level athletes, endurance sports and younger athletes. Training monotony, training in winter, at altitude and after international travel across time zones all increased the risk of ARill/ARinf.
Although the assessment of training intensity/load alone gave mixed results, the review indicates that high intensity training is a significant risk factor in athletes who experience recurrent episodes of ARinf/ARill and altered immune status.10 38 39 Increments in high intensity training, including speed and strength training, were associated with a higher risk of ARinf/ARill in these athletes.38 40 Intense exercise, particularly in endurance sports, can induce significant immune system disturbances.41 42 This review confirms findings of individual studies reporting an increase in ARinf/ARill symptoms during training periods characterised by high loads imposed continuously over several weeks or months.43–45 The accumulation of elevated training loads without adequate recovery may be associated with a chronic depletion of cellular and mucosal immune parameters, which may lower resistance to potential viral43 46 and non-viral pathogens,14 or allow viral reactivation,43 46 thereby partially explaining the higher incidence of ARinf/ARill symptoms.9 45 47 48
Nutritional factors
Vitamin D is an important component for effective immunity.49 50 The review confirmed previous research showing a vitamin D deficit predisposes athletes to longer and more severe ARill, compared with non-deficit athletes.39 40 51 He et al 51 found that vitamin D supplementation reduced the incidence of ARill. Scullion et al 52 found that multivitamin supplementation in an athlete’s diet did not result in fewer ARill in winter compared with summer, and also found that an overload of vitamin D did not reduce the prevalence of ARill in athletes.
Environmental and exposure factors
Seasonality
Seasonal factors are important parameters to consider, as external factors can influence and increase the risk of ARinf/ARill.53–55 This review showed a consistent association of increased ARill with the winter months, supporting the previously established relationship of cold environments with a higher incidence of ARinf/ARill episodes and symptoms.14 51 The exposure to respiratory pathogens is highest in winter, but also significant in autumn and spring.52 56 57 Spring is associated with higher pollen counts that can cause symptoms of ARill in susceptible athletes, causing eosinophilic airway inflammation that is often confused with the symptoms of ARinf.38 39 56 58–61 Cold air can also damage the respiratory epithelium due to airway drying causing airway inflammation.59 62 These findings mirror the seasonal patterns for acute ARill and infections in the general population, as winter is characterised by a surge in viral acute respiratory infections.63
Furthermore, during the colder months selected hormones that regulate immune function and vitamin D concentrations are at their lowest. Recent research indicates that a vitamin D deficit is a predictor of infections,51 but supraphysiological doses of vitamin D do not protect against respiratory infections.64 In the Northern Hemispheres, winter-time is usually characterised by increments in load in certain sports such as skiing, skating and ice hockey, and the intense competition period coincides with the winter season12 13 47 65 which potentially accentuates immune-suppression and increases the risk of infection. A similar pattern is evident in the Southern Hemisphere with swimmers preparing in winter months for major international competitions typically held in the Northern Hemisphere summer.10 66 However, time of year (season) appears to influence infection risk to a lower degree than the impact of training phase/type of sport.
International travel
International travel was shown to be a significant risk factor for ARill/ARinf56 when athletes travelled across >567 and >668 time zones. Svendsen et al 56 noted athletes were five times more likely to report symptoms the day following international air travel. Studies have reported that medical illness (most commonly affecting the respiratory system) affects elite athletes while travelling to international competitions.12 67–69 The reasons for a higher incidence of illness/infection/symptoms during international travel include: drying of respiratory epithelium, close contact with air travellers and exposure to re-circulated air (infections), time-zone changes associated with sleep/circadian rhythm disruption, variation of diet. Other travel factors that can augment the risk of ARill include: exposure to different environmental conditions (temperature, humidity, atmospheric pollution, aeroallergens) or exposure to different strains of pathogenic organisms, and high population density at competition venues.
Altitude
It is well established that ascent to high altitude alters physiological and metabolic function and can influence immune function.70 In this review, training at altitude was shown to increase the risk of ARill but not when findings were adjusted for sex, performance level, training phases and season.56 Tiollier et al 71 found no significant differences in mucosal immunity between elite cross-country skiers sleeping at 2500–3500 m above sea level and training at 1200 m for 18 days, compared with a control group living and training at 1200 m. However, the typical cold and dry conditions of training at altitude may present with upper respiratory symptoms due to airway drying and inflammation and be considered a risk factor for non-infective ARill through this effect on respiratory mucosal membranes.72 73
Immune/haematological biomarkers and risk factors
Changes in systemic and mucosal immune parameters have been extensively studied in response to exercise training and competitions at all levels of sports and in many different types of sports. This systematic review of associations between immune parameters with ARinf/ARill revealed only a limited number of studies combining both ARill and exercise/training measures. The major factor affecting the immune response that appears to be associated with a higher risk of upper ARinf/ARill in athletes is a reduction in tear or salivary-(IgA). Salivary-(IgA) is the most studied immune parameter and represents a biomarker for altered mucosal immunity in the respiratory tract. It is well established that low concentrations of salivary-(IgA) at mucosal surfaces is a risk for mucosal infections in the general population.74 Salivary-(IgA) plays a major role in immune defence not only at mucosal surfaces but also in responding to and eliminating pathogens that cross mucosal surfaces.75 76 The studies in this review revealed an association between the appearance of EBV-DNA (viral reactivation) in saliva and the incidence of ARinf/ARill and the time frame for association with low concentrations of salivary-IgA. These biomarkers reflect immune parameters that are known risk factors associated with respiratory illness in the general population and have therefore been evaluated as tools to monitor ARill/ARinf risks in athletic populations known to have exercise-induced alterations in immune function and parameters.4 14 41 42 48 77–80
Regardless of the methodology used for characterising ARinf/ARill, this review found a consistent association between lower concentrations of salivary-(IgA) and tear salivary-(IgA) with an increased incidence of ARinf/ARill, with 83% of studies reporting this association. The majority, but not all studies that assessed secretions rates, also found an increased incidence of ARinf/ARill with reduced secretion rates of salivary-IgA or tear-IgA. It is possible that the one study with the reverse finding of higher salivary-IgA concentrations with increased ARill was sampled during the infective period40 when salivary-IgA would be expected to increase in response to an infection in subjects with a fully functioning immune system.
The cumulative effects of long-term training at high loads and intensity were observed in a decline in immune protection over time. Pretraining or preseason lower salivary-IgA concentrations were shown to be associated with the increase in episodes of ARill/ARinf, symptom duration34 35 and severity in elite swimmers.60 81 A 65% reduction in salivary-IgA concentration was reported 1–2 weeks before the appearance of a suspected ARinf in rugby union players.82 Similarly, in a cohort of elite yacht racing sailors, low individual relative salivary-IgA values (<40% drop) suggested a 48% chance of an ARill within 3 weeks.83 In elite swimmers, an additional infection was observed for each 10% drop (slope) of pretraining salivary-IgA level over time (per month).46 In recreationally active individuals (various sports), low salivary-IgA (<5.5 µg/mL) and reduced secretion rate (>30%) was associated with ARill in the week following a competition.40 The reductions in salivary-IgA concentration and secretion rates may have been the result of increments in training load83 84 or inadequate recovery time between training sessions.80 85
Strengths and limitations
The quality of the studies included in this review and the variables explored as risk factors for ARill/ARinf provides some direction on the topic, specifically for elite/high performance athletes. A strength of this review is that it followed a systematic approach for inclusion and although a meta-analysis could not be performed, studies were reviewed for the quality assessment and risk of bias using a modified Downs and Black tool.25
However, this review has some limitations. First, while a consensus of the research group was used to reduce inclusion/exclusion bias, we acknowledge that the selected criteria may have (to a certain extent) led to selection bias. For example, the inclusion of studies in the English Language might have resulted in language restriction bias. There are other possible biases not considered by the selected appraisal tool in this study, which have the potential to affect study outcomes. For example, measurement bias could result from selected studies reporting self-reported symptoms only, without clinical verification by a physician. Additionally, residual confounding bias could result from studies which did not adequately consider adjustments of the confounders when reporting the strength of association. Further, sparse data bias,86 may have arisen in studies which had fewer participants, subsequently influencing the OR and relative risk outcomes, with considerable upward biases when there were minimal athletes at key combinations of the outcome, exposure and covariates.
Second, the focus on statistically positive findings (p<0.05) may result in researchers losing results reporting some evidence that could be a clinically relevant factor associated with ARill. Third, the differences in methodological design, definitions of ARill/ARinf, outcome measures within diagnostic methodologies and heterogeneity of athletes’ levels of performance and sports codes made it difficult to interpret the magnitude of each risk factor. Also, the approach we adopted might be considered “reductionist’ in the identification and stratification of risk factors. Indeed, there is considerable complexity of these identified risk factors and their interaction with other risk factors for example, the interactions of training variations and dietary changes on immune function. Fourth, only a few studies identified the infections by clinical assessment and confirmed with laboratory diagnosis. Fifth, asthma, atopy and allergy were excluded as a risk factor for ARill. Sixth, this review considered research published only in the English language, such that relevant studies conducted in non-English languages were overlooked.
The broad search strategy provided a degree of confidence that, within the inclusion criteria of risk factors for respiratory infections/illnesses, the studies were of a high level of quality. Interpretation of findings should consider that there are potentially other influences on the risks for ARill/ARinf than those examined. Future studies would need to standardise diagnostic methods, and outcome measurements to allow comparisons between studies, variables and to enable a future meta-analysis.
Summary and conclusions
The review identified several modifiable risk factors that could be considered by sports coaches when preparing training programmes, particularly for athletes who experience recurrent episodes of ARill/ARinf and those at a less competitive level (table 5). Risk factors included increased training monotony, endurance training programmes, lack of tapering, training during winter and at altitude, and international travel. It is also important for clinicians working with athletes to consider vitamin D deficits, particularly those prone to repeated ARill/ARinf. Biomarkers for monitoring athletes at a higher risk of ARill/ARinf included: low tear-SIgA concentration and low salivary-IgA concentrations. While other possible risk factors for ARill/ARinf were identified in this review, conflicting evidence limits conclusions to be draw. Further research in these areas is therefore warranted.
What is already known?
Acute respiratory illnesses (ARill), especially respiratory tract infections, are the most common acute illnesses affecting athletes.
ARill can result in time loss from training and competition.
Individual studies have reported that strenuous exercise-induced immunosuppression, mental stress, nutritional restrictions, air travel, human crowding, housing with other athletes, low temperature with low humidity and competition all potentially increase the risk for ARill.
What are the new findings?
Increased training load, monotony, endurance training programmes, lack of tapering, training during winter and at altitude, and international travel were reported to increase the risk of acute respiratory infections (ARinf).
It is important for clinicians working with athletes to consider vitamin D deficits, particularly those prone to repeated acute respiratory illness (ARill)/ARinf.
Biomarkers for monitoring athletes at a higher risk of ARill/ARinf include low tear-(SIgA) and low salivary-(IgA).
Ethics statements
Patient consent for publication
Ethics approval
This study does not involve human participants.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Twitter @wderman, @goipergormance, @sportsdocaus, @margo.mountjoy
Collaborators a Subgroup of the IOC consensus on “Acute respiratory illness in the athlete”.
Contributors All authors contributed towards the generation of key search terms used to identify relevant articles for this systematic review. Furthermore, (LK, JG-E, KM and MG) were involved in the data extraction and secondary search for articles missed by the search strategy. KM and MG performed the clinical diagnoses of upper ARinf, ARill and URS which were verified by WD and MS. Critical appraisal and OCEBM levels of evidence were performed by LK, JG-E and MG. All authors were involved in the analysis, interpretation and writing of the manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.