Abstract There is concern that sickle cell trait (SCT) increases risk of exertional collapse, a primary cause of which is heat injury. However, to our knowledge, no population-based studies among active individuals have addressed this, representing a critical evidence gap. We conducted a retrospective cohort study of SCT-tested African-American soldiers who were on active duty in the US Army anytime between January 2011 and December 2014. Using Cox proportional hazards models and adjusting for demographic and medical factors, we observed no significant associations between SCT and either mild heat injury (hazard ratio (HR) = 1.15, 95% confidence interval (CI): 0.84, 1.56; n = 45,999) or heat stroke (HR = 1.11, 95% CI: 0.44, 2.79; n = 46,183). Risk of mild heat injury was substantially higher among soldiers with recent prescriptions for antipsychotic agents (HR = 3.25, 95% CI: 1.33, 7.90). Risk of heat stroke was elevated among those with a prior mild heat injury (HR = 17.7, 95% CI: 8.50, 36.7) and among overweight and obese individuals (HR = 2.91 (95% CI: 1.38, 6.17) and HR = 4.04 (95% CI: 1.72, 9.45), respectively). In a setting where universal precautions are utilized to mitigate risk of exertion-related illnesses, SCT is not associated with either mild heat injury or heat stroke. cohort studies, heat stroke, mild heat injury, military personnel, sickle cell trait There has been vigorous controversy over whether college athletes and military service members should be universally screened for sickle cell trait (SCT) in an effort to protect them against exertional collapse (1–5). Persons with SCT are heterozygous for the sickle cell mutation in the hemoglobin subunit beta gene (HBB), resulting in the presence of wild-type hemoglobin A, as well as hemoglobin S. SCT is most prevalent among persons with African ancestry. An estimated 7.3% of African Americans and 1.6% of Americans overall carry the trait (6). While SCT is largely benign and of no consequence to athletic performance, it has been associated in the literature with an increased risk of exertional sudden death events in both athletes and warfighters (7, 8). While there is speculation on potential risk factors contributing to exertional collapse in this population, the mechanism for this increased risk has yet to be elucidated (9). Proponents of screening suggest that it would alleviate the increased risk of exertional collapse and death reported to be associated with SCT. Potential actions might include increased education of and accommodations for athletes and warriors with SCT (5), although there is no published evidence on the impact of such efforts. Others, however, have expressed concerns about mass SCT screening on ethical grounds and because, until very recently, the literature on the association between SCT and exertional collapse and death had been dominated by case reports and review-type articles (1–4, 10–17). There has been a dearth of current, population-based epidemiologic studies on fully SCT-tested populations to provide adequate evidence to support policy-making (9). In a recent study, we leveraged data on an SCT-tested subset of the US Army population to address this evidence gap (18). In that study, no difference in overall mortality was observed when comparing soldiers with and without SCT, but there was a modest elevation in the risk of exertional rhabdomyolysis associated with SCT. Another critical health event that can precipitate exertional collapse and requires study is heat injury. Heat-related injuries are an important source of morbidity and mortality among athletes and warfighters (17, 19–23). Concern that SCT increases the risk of heat injury has been expressed (1, 16, 17), but no population-based studies of SCT-tested active individuals have been conducted. We therefore utilized a large database of administrative and health data on US Army soldiers to test whether SCT is associated with risk of heat injuries. METHODS We conducted a retrospective cohort study using data from the Stanford Military Data Repository, which includes largely deidentified administrative and health-care records for all persons who were active-duty US Army soldiers between January 2011 and December 2014 (see the Web Appendix, available at https://academic.oup.com/aje). During this time frame, soldiers were subject to doctrinal regulations emphasizing universal precautions, including exercise acclimatization in conjunction with promotion of adequate hydration and appropriate work/rest cycles for a given heat strain, as measured by the wet bulb globe temperature (24). This study was approved by the Stanford University Institutional Review Board and the Defense Health Agency’s Human Research Protection Office. Study population Because SCT is most prevalent among African Americans (6), we limited the eligible study population to SCT-tested soldiers who reported African-American race and were on duty anytime between January 2011 and December 2014 (n = 48,384). Self-reported race was identified using official personnel records. To ensure the capture of incident heat injury events, we utilized 2 sets of eligibility rules supporting dedicated analyses of heat stroke and milder heat injury events. For both of these analyses, all African-American SCT-tested soldiers who were newly enlisted during this time were included in the analyses (n = 12,406). This criterion was based on the policy that substantial prior heat injury is generally a disqualifying condition for service (25). For “experienced” soldiers (i.e., those who entered military service prior to the start of our data set in January 2011), we first utilized a washout process to ensure that any follow-up care we might observe during 2011 for prior heat injury events would not be counted as pertaining to incident heat injuries. Specifically, we excluded experienced soldiers with fewer than 13 months of observed service—that is, those who were discharged from military service for any reason before February 2012 (n = 2,166). This criterion permitted a sufficient screening and exclusion period. The 13th month for experienced soldiers, January 2012, constituted the initial month of time at risk for outcomes. For the heat stroke analysis, only those experienced soldiers with a minimum of 13 months of observed service and no evidence of heat stroke during 2011 were eligible. Those with evidence of mild heat injuries during 2011 were accepted for the heat stroke analysis, as mild heat injury served as a predictor in this analysis. We thus employed a study population for the heat stroke analysis comprised of new and eligible experienced soldiers with a sample size of 46,183. Because heat stroke is ostensibly the most serious type of heat injury, we further limited the study population for the mild heat injury analysis to a subset of the population that was eligible for the heat stroke analysis, as follows. First, experienced soldiers with evidence of either heat stroke or mild heat injury in 2011 were excluded. Second, any soldiers diagnosed with heat stroke prior to or in the same month as an incident mild heat injury were excluded from the mild heat injury analysis. Finally, any soldier experiencing only heat stroke as a heat injury was excluded from the mild heat injury analysis. The last criterion was implemented to be consistent with the Cox modeling requirement that censoring is uninformative. These additional exclusions resulted in a total sample size of 45,999 new and experienced soldiers for the mild heat injury analysis. Measures The outcomes of interest were 1) heat stroke per International Classification of Diseases, Ninth Revision, Clinical Modification, code 992.0 and 2) milder heat injuries collectively identified with International Classification of Diseases, Ninth Revision, Clinical Modification, codes 992.1–992.9. The outcomes were identified using data from the Military Health System Data Repository (Web Appendix), which includes records from in- and outpatient encounters taking place in both military and civilian facilities. SCT was defined by laboratory tests confirming the hemoglobin AS phenotype. Demographic predictors included sex, age, and military pay grade. We used 4 categories for age: ≤22 years, 23–27 years, 28–35 years, and ≥36 years. We employed 7 categories for pay grade: private (E1–E3); specialist or corporal (E4); junior sergeant (E5–E6); senior sergeant (E7–E9); warrant officer (W1–W5); junior officer (O1–O3); and senior officer (O4–O10) (26). Participants’ body mass index (weight (kg)/height (m)2) measures were categorized per standard classifications (27). As only 120 soldiers (0.25% of the total study population) were underweight, we included underweight soldiers, along with those missing body mass index data, with the normal-weight soldiers in the reference group. The most recent body mass index measure for each soldier was employed. To control for physical conditioning, we included a binary variable denoting high scores versus normal or low scores on the most recent Army Physical Fitness Test (28). Information on tobacco use reported at an outpatient encounter during the preceding 6 months was updated monthly. Three binary variables indicated the presence or absence of at least 1 dispensed prescription for statins, antipsychotic agents, or stimulants in each observed month and/or the prior month. Season was modeled with 4 categories and updated monthly: winter (December–February); spring (March–May); summer (June–August); and fall (September–November). Statistical analysis We fitted Cox proportional hazards models, and ties for the total time observed before the outcome were handled using the Breslow method. The model employed was as follows, with the hazard of heat injury modeled as a function of the demographic, health-related, and season-related variables as described above: h(t)=h0(t)exp(β1X1+β2X2+…+βpXp).Time at risk began at the first observed service month for new soldiers and in January 2012 for experienced soldiers due to the aforementioned screening process. For the heat stroke analysis, censoring occurred after the first observed heat stroke event; mild heat injuries did not interrupt observation. For the mild heat injury analysis, censoring occurred after the first observed mild heat injury. Otherwise, censoring occurred at the end of military service, if observed, or in December 2014. Mean observed time was 31.0 person-months per subject, and we observed 119,213 person-years in total. All models included as predictors the main exposure of interest—SCT—plus all of the demographic, military, and health-related variables described above. All statistical analyses were conducted using Stata 14 software (StataCorp LP, College Station, Texas), and all reported P values are 2-sided. RESULTS There were 543 incident cases of mild heat injury and 61 incident cases of heat stroke. Table 1 contrasts the characteristics of soldiers who did and did not experience each incident event in the respective analyses. Table 1. Demographic and Health-Related Characteristics of Active-Duty African-American US Army Soldiers Tested for Sickle Cell Trait, According to the Presence or Absence of Incident Mild Heat Injuriesa and Heat Strokeb, United States, 2011–2014 Characteristicc Mild Heat Injury Analysis (n = 45,999) Heat Stroke Analysis (n = 46,183) Subjects With Mild Heat Injury (n = 543) Subjects Without Mild Heat Injury (n = 45,456) P Valued Subjects With Heat Stroke (n = 61) Subjects Without Heat Stroke (n = 46,122) P Valued No. % No. % No. % No. % Female sex 212 39.0 12,681 27.9 <0.001 11 18.0 12,929 28.0 0.082 Age, yearse 26.0 (6.7) 30.6 (7.6) <0.0001 29.0 (7.6) 30.5 (7.6) 0.12 Had sickle cell trait 45 8.3 3,337 7.3 0.401 5 8.2 3,393 7.4 0.802 Experienced prior mild heat injury N/A N/A N/A 9 14.8 664 1.4 <0.001 Body mass indexe,f 26.0 (3.8) 27.2 (3.9) <0.0001 28.2 (3.6) 27.2 (3.9) 0.045 APFT scoreg ≥270 during the study period 78 14.4 9,847 21.7 <0.001 11 18.0 9,973 21.6 0.496 Self-reported tobacco use at an outpatient encounter in past 6 months 84 15.5 9,271 20.4 0.005 12 19.7 9,436 20.5 0.879 Prescription for specified medication in past 2 months Statins 1 0.2 492 1.1 0.043 1 1.6 498 1.1 0.673 Antipsychotics 5 0.9 313 0.7 0.516 1 1.6 321 0.7 0.376 Stimulants 2 0.4 175 0.4 0.950 1 1.6 178 0.4 0.115 Characteristicc Mild Heat Injury Analysis (n = 45,999) Heat Stroke Analysis (n = 46,183) Subjects With Mild Heat Injury (n = 543) Subjects Without Mild Heat Injury (n = 45,456) P Valued Subjects With Heat Stroke (n = 61) Subjects Without Heat Stroke (n = 46,122) P Valued No. % No. % No. % No. % Female sex 212 39.0 12,681 27.9 <0.001 11 18.0 12,929 28.0 0.082 Age, yearse 26.0 (6.7) 30.6 (7.6) <0.0001 29.0 (7.6) 30.5 (7.6) 0.12 Had sickle cell trait 45 8.3 3,337 7.3 0.401 5 8.2 3,393 7.4 0.802 Experienced prior mild heat injury N/A N/A N/A 9 14.8 664 1.4 <0.001 Body mass indexe,f 26.0 (3.8) 27.2 (3.9) <0.0001 28.2 (3.6) 27.2 (3.9) 0.045 APFT scoreg ≥270 during the study period 78 14.4 9,847 21.7 <0.001 11 18.0 9,973 21.6 0.496 Self-reported tobacco use at an outpatient encounter in past 6 months 84 15.5 9,271 20.4 0.005 12 19.7 9,436 20.5 0.879 Prescription for specified medication in past 2 months Statins 1 0.2 492 1.1 0.043 1 1.6 498 1.1 0.673 Antipsychotics 5 0.9 313 0.7 0.516 1 1.6 321 0.7 0.376 Stimulants 2 0.4 175 0.4 0.950 1 1.6 178 0.4 0.115 Abbreviations: APFT, Army Physical Fitness Test; N/A, not applicable. a Mild heat injuries were defined using International Classification of Diseases, Ninth Revision, Clinical Modification, codes 992.1–992.9 (heat syncope; heat cramps; heat exhaustion, anhydrotic; heat exhaustion due to salt depletion; heat exhaustion, unspecified; heat fatigue, transient; heat edema; other specified heat effects; and unspecified effects of heat and light). b Heat stroke was defined using International Classification of Diseases, Ninth Revision, Clinical Modification, code 992.0. c All time-varying values were as known for each subject in the last observed month before censoring. d χ2 tests were employed to test for distribution differences for all variables other than age and body mass index. Two-sample t tests were employed to test for differences in mean values for age and body mass index. e Values are expressed as mean (standard deviation). f Weight (kg)/height (m)2. g APFT scores are unitless, and higher scores denote better physical performance. Standard scores range from 0 to 300. A minimum score of 180 is ordinarily required to pass. Soldiers attaining a score of 90 or greater in each of the 3 fitness categories (push-ups, sit-ups, and cardiovascular endurance) are awarded recognition for high fitness (28). SCT was present in 7.3% of the study population in the mild heat injury analysis and 7.4% of the study population in the heat stroke analysis (Table 1). SCT was not associated with either mild heat injury (hazard ratio (HR) = 1.15, 95% confidence interval (CI): 0.84, 1.56) or heat stroke (HR = 1.11, 95% CI: 0.44, 2.79) (Table 2). Table 2. Adjusted Hazard Ratios for Demographic and Health-Related Characteristics From Cox Proportional Hazards Modelsa Predicting Mild Heat Injuryb and Heat Strokec Among Active-Duty African-American US Army Soldiers, United States, 2011–2014 Characteristicd Mild Heat Injury Analysis (n = 45,999) (1,415,974 Person-Months) Heat Stroke Analysis (n = 46,183) (1,430,556 Person-Months) HR 95% CI HR 95% CI Sickle cell trait status per laboratory testing Negative 1 Referent 1 Referent Positive 1.15 0.84, 1.56 1.11 0.44, 2.79 Sex Male 1 Referent 1 Referent Female 1.76 1.48, 2.10 0.61 0.31, 1.19 Age category, years ≥36 1 Referent 1 Referent ≤22 1.32 0.84, 2.09 0.77 0.25, 2.43 23–27 1.22 0.80, 1.87 0.65 0.22, 1.89 28–35 0.91 0.63, 1.32 0.92 0.39, 2.14 Mild heat injury previously observed No prior mild heat injury N/A 1.0 Referent Prior mild heat injury N/A 17.7 8.50, 36.7 Body mass indexe category <25 or unknown 1 Referent 1 Referent 25–29.99 0.99 0.82, 1.20 2.91 1.38, 6.17 ≥30 1.13 0.86, 1.49 4.04 1.72, 9.45 APFT scoref <270 or unknown 1 Referent 1 Referent ≥270 0.94 0.73, 1.22 1.05 0.53, 2.08 Self-reported tobacco use at an outpatient encounter in past 6 months No tobacco use 1 Referent 1 Referent Tobacco use 1.16 0.91, 1.48 1.04 0.54, 1.99 Prescription for specified medication in last 2 months No statins 1 Referent 1 Referent Statins 0.58 0.08, 4.18 2.23 0.29, 16.9 No antipsychotics 1 Referent 1 Referent Antipsychotics 3.25 1.33, 7.90 3.67 0.48, 27.8 No stimulants 1 Referent 1 Referent Stimulants 1.67 0.41, 6.73 5.19 0.70, 38.8 Characteristicd Mild Heat Injury Analysis (n = 45,999) (1,415,974 Person-Months) Heat Stroke Analysis (n = 46,183) (1,430,556 Person-Months) HR 95% CI HR 95% CI Sickle cell trait status per laboratory testing Negative 1 Referent 1 Referent Positive 1.15 0.84, 1.56 1.11 0.44, 2.79 Sex Male 1 Referent 1 Referent Female 1.76 1.48, 2.10 0.61 0.31, 1.19 Age category, years ≥36 1 Referent 1 Referent ≤22 1.32 0.84, 2.09 0.77 0.25, 2.43 23–27 1.22 0.80, 1.87 0.65 0.22, 1.89 28–35 0.91 0.63, 1.32 0.92 0.39, 2.14 Mild heat injury previously observed No prior mild heat injury N/A 1.0 Referent Prior mild heat injury N/A 17.7 8.50, 36.7 Body mass indexe category <25 or unknown 1 Referent 1 Referent 25–29.99 0.99 0.82, 1.20 2.91 1.38, 6.17 ≥30 1.13 0.86, 1.49 4.04 1.72, 9.45 APFT scoref <270 or unknown 1 Referent 1 Referent ≥270 0.94 0.73, 1.22 1.05 0.53, 2.08 Self-reported tobacco use at an outpatient encounter in past 6 months No tobacco use 1 Referent 1 Referent Tobacco use 1.16 0.91, 1.48 1.04 0.54, 1.99 Prescription for specified medication in last 2 months No statins 1 Referent 1 Referent Statins 0.58 0.08, 4.18 2.23 0.29, 16.9 No antipsychotics 1 Referent 1 Referent Antipsychotics 3.25 1.33, 7.90 3.67 0.48, 27.8 No stimulants 1 Referent 1 Referent Stimulants 1.67 0.41, 6.73 5.19 0.70, 38.8 Abbreviations: APFT, Army Physical Fitness Test; CI, confidence interval; HR, hazard ratio; N/A, not applicable. a Results in each model were adjusted for all of the variables in the table, as well as for military pay grade, time in military service, and season of the year (categorized as shown in Web Table 1). b Mild heat injuries were defined using International Classification of Diseases, Ninth Revision, Clinical Modification, codes 992.1–992.9 (heat syncope; heat cramps; heat exhaustion, anhydrotic; heat exhaustion due to salt depletion; heat exhaustion, unspecified; heat fatigue, transient; heat edema; other specified heat effects; and unspecified effects of heat and light). c Heat stroke was defined using International Classification of Diseases, Ninth Revision, Clinical Modification, code 992.0. d All time-varying values were as known for each subject in the last observed month before censoring. e Weight (kg)/height (m)2. f APFT scores are unitless, and higher scores denote better physical performance. Standard scores range from 0 to 300. A minimum score of 180 is ordinarily required to pass. Soldiers attaining a score of 90 or greater in each of the 3 fitness categories (push-ups, sit-ups, and cardiovascular endurance) are awarded recognition for high fitness (28). The adjusted hazard of mild heat injury was substantially higher among female and lower-ranking soldiers (Table 2 and Web Table 1). A notable increase in the risk of mild heat injury was also observed in association with use of antipsychotic agents (HR = 3.25, 95% CI: 1.33, 7.90) (Table 2). The hazard of heat stroke was greatly increased among those with prior mild heat injury (HR = 17.7, 95% CI: 8.5, 36.7) and was also notably higher among overweight and obese individuals (HR = 2.91 (95% CI: 1.38, 6.17) and HR = 4.04 (95% CI: 1.72, 9.45), respectively) (Table 2). The hazards of both mild heat injury and heat stroke were strongly elevated in each of the warmer seasons as compared with winter. The greatest elevation was observed in the summer (Web Table 1). DISCUSSION This study provides much-needed evidence on the question of whether SCT increases the risk of heat injury, a key cause of exertional collapse. Leveraging a unique data set on SCT-tested US Army soldiers, we observed no increased risk of either heat stroke or mild heat injury among persons with SCT. These findings add to the body of evidence that, with universal precautions to mitigate risk of exertion-related illnesses (24), SCT does not markedly increase the risk of these outcomes (18). To the best of our knowledge, the prior literature concerning the specific relationship of SCT to heat injury consists only of a case study and a review (16, 17). Very few large, SCT-tested populations with follow-up information about health events exist, making it difficult to estimate the true risk of heat injury associated with SCT. Our study addresses that gap. Since both the exposure and the outcomes considered were relatively rare, our estimates sometimes had large confidence intervals. Because this was the first epidemiologic study of this association, however, we did not have a prior expectation for the magnitude of the association. Our research goal was to test suggestions made in the literature that persons with SCT were at significantly increased risk of heat injury. The lack of statistical significance for the association and the very modest point estimates observed are reassuring. The nature of the relationship between SCT and heat injury is clearly fundamental to decisions regarding screening for SCT. At present in the US Army, there is no special recognition or handling of soldiers with SCT before or during physical activity. Instead, the Army employs universal precautions to reduce the risks of dehydration and heat- and exercise-induced illness among all of its soldiers (24, 28). Such measures have been previously shown to be effective in reducing exercise-related fatality rates among both SCT-positive and SCT-negative individuals (29). Our finding that the risk of heat stroke among persons with a prior mild heat injury was elevated 17-fold is consistent with clinical impressions but has been challenging to study epidemiologically in the past (30, 31). The increased risk of mild heat injury observed among persons in lower pay grades was also noted in a recent report (23) and may reflect associated workload demands. In the same report, female service members were observed to be at increased risk of mild heat injury but at decreased risk for heat stroke, which we also observed, although our finding in the heat stroke model was not statistically significant (P = 0.15). The relationships between heat injury risk and warm seasons and overweight/obesity have been reported previously (20, 32–34). It is important to note that geographic assignments for soldiers are not made differentially on the basis of weight, SCT status, or the other risk factors considered. While different installations have different proportions of military occupational specialties represented, an exploratory analysis showed only slight differences in average body mass index across the top installations (results not shown), indicating an absence of systematic bias in assignment on that basis. The increased hazard of mild heat injury in relation to prescriptions for antipsychotic agents is intriguing, and this finding—along with the observed substantial, albeit nonsignificant, associations with other medications—will be the subject of further investigation utilizing the total Army population. The large but imprecise hazard ratio for stimulants in the heat stroke model indicates the need for a larger sample, but it is particularly worrying given that energy drinks, preworkout supplements, and weight loss supplements are commonly used by soldiers and contain nonprescription stimulants (e.g., caffeine, synephrine) (35, 36). We did not utilize geographic location—or deployment, which is an expected part of the military experience—as covariates in this analysis, since neither would be expected to vary on the basis of SCT. We are examining the relationship of geographic location to heat injury risk in a separate study utilizing the total Army population. Our study possessed a number of strengths, including laboratory confirmation of SCT status for the total study population, electronic capture of clinical diagnoses, and control for a number of known or suspected heat injury risk factors. Some limitations are also worth noting, however. Because the Army has not conducted universal screening for SCT, not all African-American soldiers were available for inclusion in the study. However, our data indicated no substantive demographic or health-related differences between screened and unscreened subjects (results not shown). A second concern could be selection—that those soldiers with SCT who are most prone to heat injury might exit the Army at higher rates, leaving less-susceptible individuals. However, exploratory analyses revealed no difference in the association of SCT with heat injury for new soldiers versus more experienced soldiers (results not shown). Third, it would be interesting to determine whether our results are consistent across racial/ethnic groups. Because SCT is much rarer in ethnic groups other than African Americans in the United States, and because rates of heat injury were relatively low in our population, we were not able to investigate this using our data. Finally, the question of whether our results will generalize fully to other active populations requires further investigation. In summary, our population-based study of African-American soldiers who served during the current climate of universal precautions implemented to mitigate the risk of exertion-related illness found no increased risk of either mild heat injury or heat stroke among soldiers with SCT. ACKNOWLEDGMENTS Author affiliations: Department of Medicine, Division of Primary Care and Population Health, School of Medicine, Stanford University, Stanford, California (D. Alan Nelson, Lianne M. Kurina); and the Consortium for Health and Military Performance (A DoD Center of Excellence), Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland (Patricia A. Deuster, Francis G. O’Connor). The National Heart, Lung, and Blood Institute funded this project in collaboration with the Uniformed Services University of the Health Sciences (interagency agreement A-HL-14-007). All data used in the study were provided under a cooperative agreement with the US Army Medical Command. The views expressed in this paper are those of the authors and do not reflect the views or official policies of the US Government, the Department of Defense, the Defense Health Agency, the Department of the Army, or the Uniformed Services University of the Health Sciences. Conflict of interest: none declared. Abbreviations CI confidence interval HR hazard ratio SCT sickle cell trait REFERENCES 1 Goldsmith JC, Bonham VL, Joiner CH, et al. . Framing the research agenda for sickle cell trait: building on the current understanding of clinical events and their potential implications. Am J Hematol . 2012; 87( 3): 340– 346. Google Scholar CrossRef Search ADS PubMed 2 Grant AM, Parker CS, Jordan LB, et al. . 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American Journal of Epidemiology – Oxford University Press
Published: Mar 1, 2018
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