Individual risk factors associated with exertional heat illness: A systematic review

What is the topic of this review? Exertional heat illness (EHI) remains a persistent problem for athletes and individuals. This threat remains despite numerous athletic position statements and occupational guidance policies. This review explores primary evidence that demonstrates a direct association between ‘known’ risk factors and EHI. What advances does it highlight? Primary evidence to support ‘known’ risk factors associated with EHI is not comprehensive. Furthermore, it is not evident that single individual factors predispose individuals to greater risk. In fact, the evidence indicates that EHI can manifest in non‐hostile compensable environments when a combination of risk factors is prevalent.

Surgeon General, 2019). It is of further concern in military situations where the combination of intense physical work coupled with overmotivation and peer pressure may render individuals more susceptible to succumb to EHI (Rav-Acha, Hadad, Epstein, Heled, & Moran, 2004).
Exertional heat illness is noted to be a recurring problem in military training that results in loss of manpower and training effectiveness (Carter et al., 2005). Moore et al. (2015) documents that risk factors for EHI are potentially modifiable; therefore, prospective awareness is crucial to reducing heat-related morbidity. Moore et al. (2015) suggest that, for example, overweight individuals are thought to be at disproportionate risk of heat illness and can be identified by assessment of body composition, which is reported routinely in the UK Armed Forces.
Healthy weight-management strategies could then be deployed to reduce the number of personnel at risk.
Traditional risk factors for EHI have been identified and can be categorized as those attributable to the environment (hot and humid conditions, lack of acclimatization to heat, cumulative effect of heat exposure on repeated days, and inappropriate clothing), behavioural (disrupted sleep patterns, inadequate hydration, poor nutrition and certain medications) and physical factors (low physical fitness levels, being overweight/obese, experiencing high metabolic loads and underlying medical conditions; Armstrong et al., 2007;Casa et al., 2012;Epstein, 1990;Rav-Acha et al., 2004). Other risk factors, such as a history of EHI, sweat gland dysfunction, sunburn and sex have also been reported (Armstrong et al., 2007;Epstein, Shapiro, & Brill, 1983;Gifford et al., 2019;Lim, Kok, Bin Ali, Chong, & Tey, 2016).
To date, numerous position statements and policy documents have been published to provide occupational guidance and advice for athletes and individuals working in hot environments (Armstrong et al., 2007;Casa, Armstrong, & Hillman, 2003, Casa, DeMartini, Bergeron, Csillan & Eichner, 2015Webber et al., 2016). However, despite clear guidance and understanding of EHI, the incidence of EHI remains high (Armed Forces Health Surveillance Center, 2016; Bouchama & Knochel, 2002). The persistent high incidence of EHI might reflect a disregard, lack of knowledge or lack of understanding of the guidance, or it might indicate that the current guidance requires evaluation and possible amendment. Joint Services Publication (JSP) documents are an authoritative set of instructional and regulatory guidelines with defence-wide applicability owned by the UK Government and Ministry of Defence. JSP 539 (Military Headquarters of the Surgeon General, 2019) provides practical guidance on preventative measures to reduce the risk of heat illness to as low as is practicably possible. However, it is essential to ensure that best practice to support risk mitigation is evidence based.

Purpose
The objective of this systematic review was to explore the literature and evaluate the scientific evidence purporting a link between identified risk factors and EHI. The review also aimed to investigate whether there is sufficient evidence to support other, less well-known,

New Findings
• What is the topic of this review?
Exertional heat illness (EHI) remains a persistent problem for athletes and individuals. This threat remains despite numerous athletic position statements and occupational guidance policies. This review explores primary evidence that demonstrates a direct association between 'known' risk factors and EHI.
• What advances does it highlight?
Primary evidence to support 'known' risk factors associated with EHI is not comprehensive. Furthermore, it is not evident that single individual factors predispose individuals to greater risk. In fact, the evidence indicates that EHI can manifest in non-hostile compensable environments when a combination of risk factors is prevalent.
additional risk factors that might be considered by risk managers when assessing the risk of EHI.

PROSPERO registration
The systematic review was registered with PROSPERO international prospective register of systematic reviews (CRD42018111447).

Inclusion/exclusion criteria
The following inclusion and exclusion criteria were applied.

Population
We included studies that reported adult and adolescent data from males and females, ranging from young post-pubertal adults (>16 years of age) to an upper age limit of 65 years.
We excluded studies not reporting a source population, not stating the population size or not stating case rates (n per N population per year, n/N/year).

Phenomenon of interest
We included studies that reported EHI with a valid measure of core temperature.
We excluded studies where subjects were deemed to have impaired thermoregulation for medical reasons.

Context
We included studies from any country or any setting.

Outcomes
We included studies in which the incidence of EHI was established and risk/ratios documented.
We excluded studies where no incidence of EHI and risk coexisted.

Study design
We included cross-sectional, case-control, cohort, randomized control trial and observational studies.
Only studies published in English were reviewed, with no date restriction.

Data extraction
Data were extracted from all eligible studies into a standardized template using the following headings: Author(s) and year; source population and location; sample; date of study; the nature of the exposure outcome and International Classification of Disease Coding

Quality assessment
The QualSyst quality assessment tool from the 'Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields' (Alberta Heritage Foundation for Medical Research) was used. QualSyst produces a score based on eight criteria, including the appropriateness of the study design and research question, definition of outcomes and exposure, reporting of bias and confounding, and sufficient reporting of results and limitations.
Criteria were scored as 'yes' (2), 'partial' (1), 'no' (0) and not applicable (NA). The overall QualSyst score was calculated as the sum of ratings of applicable criteria divided by the maximum scores of applicable criteria. The quality of a paper relative to its QualSyst score was defined by Lee, Packer, Tang, and Girdler (2008)

Data analysis
The heterogeneity of the included studies and the diverse range of risk factors reported meant that a meta-analysis was not possible.
As such, the characteristics of included studies were evaluated descriptively and findings summarized narratively in order to identify the evidenced risk factor(s). The evidenced risk factors were considered in accordance with those presented in JSP 539 (Military Headquarters of the Surgeon General, 2019), pertaining to lifestyle, health and work constraints.

Literature search
Database searches yielded 10,110 records. After the removal of duplicates, 8898 articles remained. Of these 8898 articles, 8765 were excluded after a process of screening the titles, abstracts or both against the study inclusion and exclusion criteria. After full-text assessments of the remaining 133 articles, 93 were excluded because these articles did not meet the inclusion criteria [n = 41 failed to report EHI, n = 24 did not include risk factor incidence, n = 9 presented no EHI and no risk factor, n = 4 full-text articles could not be obtained despite requests to the British Library and several Military libraries (Malhotra & Venkatasawy, 1974;Ping, Chai, & Thomas, 1978;Stallones, Gauld, Dodge, & Lammers, 1957;and Yarger, Cronau, & Goldman, 1968), n = 10 were the wrong type of study, n = 4 were the wrong population sample and n = 1 was a military report that included data in a peer-reviewed publication]. Backward and forward citation searching and assessment of reference lists for the remaining 40 articles resulted in an additional two articles being included and therefore 42 includes in total. The PRISMA diagram in the Supporting Information ( Figure S1) represents a flow chart of the study selection process.

Factors pertaining to lifestyle
Of the 42 studies identified, the majority of risk factors were categorized as those associated with the lifestyle of military personnel.  Rosenberg, Pentel, Pond, Benowitz, & Olson, 1986) and the use of caffeine and protein supplements (Abriat et al., 2014;Armstrong et al., 1990).

Factors pertaining to work constraints
Eight studies were sourced that were able to confirm primary evidence to support individual risk factors, which increased EHI risk from factors personnel (Epstein et al., 1999;O'Donnell, 1975). The majority of included studies also reported risk factors associated with lifestyle, as outlined in Table 1. Thus, the primary level of evidence indicated that lifestyle and health risk factors cannot be viewed in isolation.

Other factors
Of the 42 articles included in the narrative analysis, only 22 demonstrated a clear association between factors pertaining to lifestyle, health and work constraints (Table 1). Twenty-eight of the 42 highlighted other factors that presented a risk of EHI (Table 2).

DISCUSSION
The purpose of this systematic review was to summarize and assess the primary evidence identifying causation between risk factors and EHI. A comprehensive search yielded 42 articles, and the overall study quality ranged from adequate to strong; most scores could have been improved had confounding been controlled or taken into account. The heterogeneity of published studies addressing EHI risk,
Heat illness continues to pose a significant risk to athletic, military and other occupational populations. As such, expansive and up-todate reviews of risk factors will provide important knowledge for the development of effective heat illness mitigation strategies to minimize this risk. Field-based detection before multiple-organ failure is challenging, and medical triage to screen the risk is crucial to prevent fatalities (Rav-Acha et al., 2004).
The findings from this review support the contention that there is wide variation in how humans tolerate heat. In some instances, there is primary evidence to identify that an individual risk factor has caused an individual to succumb to EHI. Synthesis of the findings provides evidence that the majority of EHI is attributable to intrinsic factors pertaining to lifestyle.
Although some of the included studies provided specific support for an increased risk of individuals to develop EHI, it would be prudent to state that associations were evident in individuals who typically presented with low levels of physical fitness combined with high body mass index (BMI)/body fat composition measurement (BCM). Bedno et al. (2014) suggested a five-to eightfold increase risk odds ratio when low physical fitness is combined with obesity, but data to support the risk between the US military classification of 'excess body fat' and being 'unfit' is lacking. However, caution must be exercised when interpreting these associations, because low levels of physical fitness were established from the failing of occupational fitness tests. Therefore, the real risk of EHI from low physical fitness and high BMI/BCM remains unclear. Furthermore, it could be hypothesized that the higher rate of heat illness in females (Armed Forces Health Surveillance Center, 2009Center, , 2010Center, , 2011Center, , 2012Center, , 2013Center, , 2014Center, , 2015Center, , 2016Center, , 2017) is a result of physical factors, such as high BMI/BCM, coupled with lower levels of fitness. However, incidence rates of heat stroke were, in fact, higher in males (Armed Forces Health Surveillance Center, 2009; this is most likely to be attributable to behavioural sex differences, such as over-motivation and higher sustained levels of metabolic load (Rav-Acha et al., 2004).

Contemporary thoughts
The general literature proposes that climate and the lack of acclimatization are the leading risk factors for EHI (Bergeron et al., 2005;Bouchama & Knochel, 2002;Casa et al., 2015). JSP 539 (Military Headquarters of the Surgeon General, 2019) specifies that 8 days should be provided for heat acclimatization and that inadequate time coupled with operational activity that is strenuous will manifest in heat illness peaks in the first few days (Moore et al., 2015). However, the majority of EHI evidenced from this review occurred in temperate climates at lower recorded wet-bulb globe temperatures, suggesting that high environmental temperature is not necessarily a prerequisite for EHS. Furthermore, although it is acknowledged that rapid deployment of troops can further exacerbate risk, it is evident that EHI risk remains after initial deployment. Abriat et al. (2014) identified that the median time from arrival to development of EHS overseas was 60 days with median climatic conditions of 22 • C (interquartile range, 17-25 • C), 80% relative humidity (interquartile range, 67-85%).
As training continues, improvements in physical conditioning will be likely to ensue in response to an increased volume of training, which will probably lead to residual fatigue, diminished levels of intramuscular glycogen and cellular energy depletion (Alosco et al., 2012 having what was deemed to be an excellent conditioned status. More recent work has started to explore the notion of an acute elevated inflammatory status alongside impaired thermoregulation arising from exercise-induced muscle damage. This could explain the risk of EHI associated with increased volume loads and strenuous activity (Dolci et al., 2015;Fortes et al., 2013). Personnel might use NSAIDs to alleviate inflammation, further exacerbating the risk (Nelson et al., 2018b) and highlighting the complex interplay of risk factors.
A contemporary approach to assessment of risk can be made in line with the paradigm of Minard from the early 1960s (Minard et al., 1961)