Advertisement

Subclinical Cardiac Dysfunction is Associated with Reduced Cardiorespiratory Fitness and Cardiometabolic Risk Factors in Firefighters

Open AccessPublished:February 05, 2022DOI:https://doi.org/10.1016/j.amjmed.2021.12.025

      Abstract

      Background

      Past studies have documented the ability of cardiopulmonary exercise testing to detect cardiac dysfunction in symptomatic patients with coronary artery disease. Firefighters are at high risk for work-related cardiac events. This observational study investigated the association of subclinical cardiac dysfunction detected by cardiopulmonary exercise testing with modifiable cardiometabolic risk factors in asymptomatic firefighters.

      Methods

      As part of mandatory firefighter medical evaluations, study subjects were assessed at 2 occupational health clinics serving 21 different fire departments. Mixed effects logistic regression analyses were used to estimate odds ratios (ORs) and account for clustering by fire department.

      Results

      Of the 967 male firefighters (ages 20-60 years; 84% non-Hispanic white; 14% on cardiovascular medications), nearly two-thirds (63%) had cardiac dysfunction despite having normal predicted cardiorespiratory fitness (median peak VO2 = 102%). In unadjusted analyses, cardiac dysfunction was significantly associated with advanced age, obesity, diastolic hypertension, high triglycerides, low high-density lipoprotein (HDL) cholesterol, and reduced cardiorespiratory fitness (all P values < .05). After adjusting for age and ethnicity, the odds of having cardiac dysfunction were approximately one-third higher among firefighters with obesity and diastolic hypertension (OR = 1.39, 95% confidence interval [CI] = 1.03-1.87 and OR = 1.36, 95% CI = 1.03-1.80) and more than 5 times higher among firefighters with reduced cardiorespiratory fitness (OR = 5.41, 95% CI = 3.29-8.90).

      Conclusion

      Subclinical cardiac dysfunction detected by cardiopulmonary exercise testing is a common finding in career firefighters and is associated with substantially reduced cardiorespiratory fitness and cardiometabolic risk factors. These individuals should be targeted for aggressive risk factor modification to increase cardiorespiratory fitness as part of an outpatient prevention strategy to improve health and safety.

      Keywords

      Clinical Significance
      • Cardiopulmonary exercise testing (CPET) can detect subclinical cardiac dysfunction in asymptomatic individuals undergoing annual physicals.
      • Subclinical cardiac dysfunction was found in 63% of firefighters and was strongly associated with reduced cardiorespiratory fitness, obesity, and diastolic hypertension.
      • Aggressive risk factor modification in individuals with cardiac dysfunction can improve outpatient strategies for heart disease prevention.

      Introduction

      Cardiovascular disease is the leading cause of mortality in the United States and is of specific concern in firefighters because approximately 50% of duty-related deaths are attributable to cardiac events and 80% of cardiac fatalities occur among those with evidence of coronary artery disease and structurally enlarged hearts.,
      • Smith DL
      • Haller JM
      • Korre M
      • et al.
      The relation of emergency duties to cardiac death among US firefighters.
      Individuals with demand ischemia at high workloads, such as during strenuous firefighting activities may experience myocardial injury, type II myocardial infarction, or arrhythmias resulting in cardiac events and possibly death. In this context, there is a need to identify markers of early disease and to implement accepted therapeutic interventions at an earlier stage to improve job safety and longevity.
      Peak oxygen consumption (Peak VO2) objectively quantifies exercise capacity and is a primary component of cardiorespiratory fitness. It is recognized as the best predictor of all-cause mortality and has been proposed as a vital sign to objectively quantify the functional health of the cardiorespiratory system.
      • Kodama S
      • Saito K
      • Tanaka S
      • et al.
      Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis.
      ,
      • Ross R
      • Blair SN
      • Arena R
      • et al.
      Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign: a scientific statement from the American Heart Association.
      Directly measured cardiorespiratory fitness in healthy men and women reveals an inverse linear relationship with mortality.
      • Imboden MT
      • Harber MP
      • Whaley MH
      • et al.
      Cardiorespiratory fitness and mortality in healthy men and women.
      ,
      • Letnes JM
      • Dalen H
      • Vesterbekkmo EK
      • et al.
      Peak oxygen uptake and incident coronary heart disease in a healthy population: the HUNT Fitness Study.
      In an outcomes study of men and women with coronary heart disease, peak VO2 was a strong predictor of all-cause death with every 1 mlO2·kg−1·min−1 increase in peak VO2 associated with an approximate 15% decrease in mortality.
      • Keteyian SJ
      • Brawner CA
      • Savage PD
      • et al.
      Peak aerobic capacity predicts prognosis in patients with coronary heart disease.
      Cardiopulmonary exercise testing (CPET) is the gold standard for quantifying cardiorespiratory fitness, including peak VO2 as well as for determining the mechanism of exercise limitation (cardiac vs pulmonary vs other).
      • Balady GJ
      • Arena R
      • Sietsema K
      • et al.
      Clinician's Guide to cardiopulmonary exercise testing in adults: a scientific statement from the American Heart Association.
      With enhanced analysis of data from CPET performed on a cycle, inducible myocardial dysfunction caused by coronary artery disease can be assessed.
      • Belardinelli R
      • Lacalaprice F
      • Carle F
      • et al.
      Exercise-induced myocardial ischaemia detected by cardiopulmonary exercise testing.
      ,
      • Chaudhry S
      • Arena R
      • Wasserman K
      • et al.
      Exercise-induced myocardial ischemia detected by cardiopulmonary exercise testing.
      Inducible myocardial dysfunction results from mechanical dysfunction caused by myocardial energy depletion and has been shown to be superior to stress electrocardiogram (ECG) for detecting coronary artery disease in symptomatic patients.
      • Belardinelli R
      • Lacalaprice F
      • Tiano L
      • et al.
      Cardiopulmonary exercise testing is more accurate than ECG-stress testing in diagnosing myocardial ischemia in subjects with chest pain.
      ,
      • Chaudhry S
      • Kumar N
      • Behbahani H
      • et al.
      Abnormal heart-rate response during cardiopulmonary exercise testing identifies cardiac dysfunction in symptomatic patients with non-obstructive coronary artery disease.
      Recent outcomes data reveal that patients with inducible myocardial dysfunction on CPET have a 3-fold increased risk of near-term annualized mortality compared to patients without inducible myocardial dysfunction, independent of cardiorespiratory fitness.

      Mann J, Williams M, Wilson J, et al. Exercise-induced myocardial dysfunction detected by cardiopulmonary exercise testing is associated with increased risk of mortality in major oncological colorectal surgery [e-pub ahead of print]. Br J Anaesth. doi: https://doi.org/10.1016/j.bja.2019.12.043. Accessed July 15, 2020.

      Current US guidelines for firefighters recommend the quantification of cardiorespiratory fitness as part of an annual medical assessment.
      National Fire Protection Association
      NFPA 1582: Standard on Comprehensive Occupational Medical Program for Fire Departments.
      CPET performed to maximal exercise is superior to submaximal tests on a treadmill as it more precisely quantifies cardiorespiratory fitness. The purpose of this cross-sectional, observational study was to investigate the relationship between cardiometabolic risk factors and inducible myocardial dysfunction detected by CPET in a population of asymptomatic career firefighters for whom CPET is part of the annual medical evaluation.

      Methods

      Subjects

      Firefighters were assessed at 2 occupational health clinics serving 21 different fire departments in Arizona and Texas. Eligible study subjects included all consecutive firefighters who underwent mandatory firefighter medical evaluations between January 2018 and August 2020 and for whom medical records were available. All firefighters were asymptomatic and on active duty at the time of their evaluations. Firefighters who did not meet our inclusion criteria (20-60 years of age) or who were missing key demographic or clinical information (n = 257) were excluded from the analysis. For the present investigation, our sample included 967 firefighters. Only male firefighters were included because the number of women in the data set was too small to test for differences due to sex. The study protocol was reviewed and approved by Skidmore Colleges’ institutional review board.

      Data Collection

      Annual occupational medical evaluations were consistent with current guidelines
      National Fire Protection Association
      NFPA 1582: Standard on Comprehensive Occupational Medical Program for Fire Departments.
      and included demographic measurements, standard blood chemistries, lipid panels, medical examinations, and CPET. Blood draws were obtained in the morning after an overnight fast and sent to a commercial laboratory for the determination of blood lipids and chemistries. All CPET equipment, technician training, clinical support, and data analysis were provided by a central laboratory (MET-TEST).
      CPET was performed on an electronically braked cycle ergometer with breath-by-breath gas analysis as previously described.
      • Chaudhry S
      • Arena R
      • Wasserman K
      • et al.
      Exercise-induced myocardial ischemia detected by cardiopulmonary exercise testing.
      Major prognostic variables include measurements of peak VO2, and peak O2-pulse defined as peak VO2 corrected for peak heart rate (VO2/HR). Relative values for peak VO2 and peak O2-pulse were expressed as mlO2·kg−1·min−1 and mL/beat, respectively. These parameters were also expressed relative to predicted values based on age, height, weight, and sex from population studies.
      • Wasserman K
      • Hansen JE
      • Sue DY
      • et al.
      Principles of Exercise Testing and Interpretation: Including Pathophysiology and Clinical Applications.
      Increase of the O2-pulse during exercise has been shown to be a close surrogate for the stroke volume response in a variety of cardiac abnormalities and is a key variable to diagnosing inducible myocardial dysfunction.
      • Evangelista M
      • Boveri S
      • Alfonzetti E
      • et al.
      Abstract 12231: accuracy of methods for stroke volume measures by O2-pulse during gas exchange analysis and clinical implications.
      The change in heart rate to work rate slope (ΔHR-WR slope) is a novel CPET parameter that was calculated as described in a previous publication.
      • Chaudhry S
      • Kumar N
      • Behbahani H
      • et al.
      Abnormal heart-rate response during cardiopulmonary exercise testing identifies cardiac dysfunction in symptomatic patients with non-obstructive coronary artery disease.
      Simultaneous changes in O2-pulse trajectory and ΔHR-WR slope were the primary determinants for identifying inducible myocardial dysfunction. All CPET studies were analyzed per protocols of the central CPET laboratory. Each test with sufficient effort (ie, peak respiratory exchange ratio ≥1.05) was classified as either normal cardiac function or abnormal with inducible myocardial dysfunction as illustrated in Figure 1.
      • Chaudhry S
      • Arena R
      • Bhatt DL
      • et al.
      A practical clinical approach to utilize cardiopulmonary exercise testing in the evaluation and management of coronary artery disease: a primer for cardiologists.
      Figure 1
      Figure 1Classification based on cardiac function. Graphical display of heart rate (top line) and O2-pulse response, which reflects stroke volume (bottom line). Cardiac output is the product of stroke volume and heart rate and plotting both parameters in the same graph allows for assessment of their relative dependence in real time. Data from every test was optimized for averaging, filtering, scaling, and trend analysis prior to classification: (A) Normal cardiac response: The O2-pulse rises from start (6-min mark) to end (15-min mark) in a linear manner to slightly above predicted value (black dot) without plateau. The heart-rate response is linear in early and middle exercise and slows in late exercise as it approaches physiological peak resulting in a negative ΔHR-WR slope (−42%). The mean value of the ΔHR-WR slope was −7% for individuals with normal cardiac function. (B) Abnormal cardiac response - IMD: The O2-pulse response is linear in early and middle exercise but shortly after reaching AT (green dotted line), abruptly slows starting at the IT, then plateaus and is decreasing by the end of exercise. The plateau/decreasing trend in stroke volume reflects the start of mechanical dysfunction at the IT. Heart rate is linear in early and middle exercise but at the IT, abruptly starts to accelerate in an exponential manner to the end of exercise resulting in a highly positive ΔHR-WR slope (+161%). The upper limit of increase in ΔHR-WR slope is +15-20% and represents increased sympathetic discharge to compensate for loss of stroke volume after the IT. Note that heart rate acceleration is independent of oxygen consumption measurement and changes in both parameters occurs near simultaneously. The mean value of ΔHR-WR slope was +61% for individuals with IMD. AT = anaerobic threshold; IT = inducible threshold; IMD = inducible myocardial dysfunction; ΔHR-WR slope = change in heart rate vs work-rate slope.

      Statistical Analysis

      Summary statistics were computed for all variables, including means and standard deviations for quantitative variables and frequencies and proportions for categorical variables. Two-sample t-tests were used to test for mean differences in cardiometabolic risk factors, including CPET-derived measurements, between subjects with and without inducible myocardial dysfunction. Two-sample t-tests were also repeated after stratifying by age (younger than 45 years or 45 years and older) and ethnicity (non-Hispanic whites vs others). Differences between the proportion of younger and older subjects or non-Hispanic whites and others with and without inducible myocardial dysfunction were tested using a standard 2-sample z-test.
      To account for clustering by fire department, we fit mixed effects logistic regression models, with fire department as a random effect, to estimate odds ratios and 95% confidence intervals for the association between each cardiometabolic risk factor and inducible myocardial dysfunction. Age- and ethnicity-adjusted models were also fit to account for the potential confounding effects of age (younger than 45 years or 45 years and older) and ethnicity (non-Hispanic white vs others). To examine whether the association between each cardiometabolic risk factor and inducible myocardial dysfunction differed by age or ethnicity, we also included and tested the significance of an interaction term in each model. To explore whether traditional cardiometabolic risk factors were associated with inducible myocardial dysfunction after accounting for cardiorespiratory fitness, we fit age, ethnicity, and peak VO2 adjusted mixed effects logistic regression models. All statistical tests were 2-sided, and P values< .05 were considered statistically significant. All analyses were conducted using R/RStudio (version 1.3.959).

      Results

      The mean age of the firefighters was 40 years and the majority were non-Hispanic white (84%) with approximately 10% being Hispanic. Demographic and clinical characteristics of the 967 firefighters with and without myocardial dysfunction are summarized in Table 1 and in Supplementary Tables S1, S2, and S3, available online, after stratifying on ethnicity (non-Hispanic whites vs others). Overall, firefighters with inducible myocardial dysfunction were older and heavier with higher blood sugars and triglycerides and lower cardiorespiratory fitness.
      Table 1Characteristics of Firefighters by Myocardial Dysfunction
      Myocardial dysfunction
      NoYesP Value
      Number (proportion)356 (0.37)611 (0.63)-
      Ethnicity (non-Hispanic white)
      Data are number (proportion); P values based on 2-sample z-tests for difference in proportions.
      299 (0.37)515 (0.63).97
      Age (y)39 ± 941 ± 9<.01
      Height (in)71 ± 371 ± 3.66
      Weight (lb)204 ± 31207 ± 34.12
      BMI (kg/m2)28.5 ± 3.829.1 ± 4.3.05
      Body fat (%)18 ± 619 ± 6<.01
      SBP (mm Hg)120 ± 9121 ± 10.12
      DBP (mm Hg)77 ± 778 ± 7.05
      Triglycerides (mg/dL)106 ± 54115 ± 61.02
      Total cholesterol (mg/dL)190 ± 34189 ± 38.85
      LDL (mg/dL)117 ± 30116 ± 33.62
      HDL (mg/dL)52 ± 1351 ± 13.07
      Fasting glucose (mg/dL)94 ± 1496 ± 17.03
      Hemoglobin A1C (%)5.4 ± 0.45.4 ± 0.7.10
      Peak VO2 (mlO2·kg−1·min−1)36 ± 632 ± 6<.01
      Peak VO2 (L/min)3.3 ± 0.53.0 ± 0.5<.01
      Predicted peak VO2 (%)109 ± 15101 ± 15<.01
      Peak O2-pulse (mL/beat)20 ± 319 ± 3<.01
      Predicted peak O2-pulse (%)122 ± 17114 ± 17<.01
      SBP at peak exercise (mm Hg)172 ± 18172 ± 19.99
      DBP at peak exercise (mm Hg)82 ± 1283 ± 12.29
      Resting heart rate (beats per min)73 ± 1375 ± 12.09
      Peak heart rate (beats per min)162 ± 16159 ± 15<.01
      Predicted peak heart rate (%)89 ± 889 ± 7.53
      Heart rate recovery (beats per min)37 ± 1037 ± 14.58
      ΔHR-WR slope (%)−7 ± 3261 ± 59<.01
      BMI = body mass index; DBP = diastolic blood pressure; LDL = low-density lipoprotein cholesterol; HDL = high-density lipoprotein cholesterol; SBP = systolic blood pressure; VO2 = oxygen uptake; ΔHR-WR slope = change in heart rate vs work-rate slope.
      Data are restricted to men 20 to 60 years of age.
      Data are mean ± standard deviation unless indicated otherwise; P values based on 2-sample t-tests for difference in means.
      low asterisk Data are number (proportion); P values based on 2-sample z-tests for difference in proportions.
      Based on dichotomizing cardiometabolic risk factors per threshold values (Table 2), approximately one-third of firefighters (n = 347) were 45 years of age or older, and approximately one-third (n = 325) were obese (body mass index [BMI] >30 kg/m2). Based on national hypertension thresholds, approximately 18% had high systolic blood pressure (≥130 mm Hg) and 48% had high diastolic blood pressure (≥80 mm Hg). Similarly, about one-third had elevated cholesterol (total cholesterol >200 mg/dL−1). Only 2% had blood glucose levels indicative of diabetes (fasting glucose ≥126 mg/dL−1). Fourteen percent of firefighters were on 1 or more cardiovascular medications.
      Table 2Association of CVD Risk Factors with Myocardial Dysfunction
      Number (proportion)Unadjusted OR (95% CI)
      Based on unadjusted mixed effects logistic regression.
      Adjusted OR (95% CI)
      Based on mixed effects logistic regression adjusted for age (≥ 45 y vs <45 y) and ethnicity (non-Hispanic white vs other).
      Ethnicity (non-Hispanic white)814 (0.84)1.01 (0.70-1.46)-
      Age (≥ 45 y)347 (0.36)2.07 (1.54-2.80)-
      Obesity (BMI ≥ 30 kg/m2)325 (0.34)1.52 (1.13-2.03)1.39 (1.03-1.87)
      Systolic hypertension (SBP ≥ 130 mm Hg)169 (0.18)1.22 (0.85-1.75)1.11 (0.77-1.60)
      Diastolic hypertension (DBP ≥ 80 mm Hg)459 (0.48)1.48 (1.12-1.95)1.36 (1.03-1.80)
      High triglycerides (>150 mg/dL)184 (0.19)1.46 (1.03-2.09)1.27 (0.88-1.83)
      High cholesterol (total cholesterol >200 mg/dL)350 (0.36)1.11 (0.84-1.47)1.08 (0.81-1.43)
      High LDL cholesterol (LDL ≥ 130 mg/dL)303 (0.31)1.18 (0.88-1.58)1.15 (0.86-1.55)
      Low HDL cholesterol (HDL <40 mg/dL)177 (0.18)1.51 (1.05-2.16)1.39 (0.97-2.01)
      Hyperglycemia (fasting glucose ≥ 126 mg/dL)20 (0.02)2.55 (0.83-7.82)2.00 (0.64-6.20)
      High hemoglobin A1C (≥5.7 %)174 (0.18)1.29 (0.90-1.84)1.09 (0.75-1.58)
      Low predicted peak VO2 (<90%)162 (0.17)5.23 (3.19-8.57)5.41 (3.29-8.90)
      High resting heart rate (>90 beats per min)94 (0.10)1.14 (0.72-1.81)1.08 (0.68-1.73)
      BMI = body mass index; CI = confidence interval; CVD = cardiovascular disease; DBP = diastolic blood pressure; HDL = high-density lipoprotein cholesterol; LDL = low-density lipoprotein cholesterol; OR = odds ratio; SBP = systolic blood pressure; VO2 = oxygen uptake.
      low asterisk Based on unadjusted mixed effects logistic regression.
      Based on mixed effects logistic regression adjusted for age (≥ 45 y vs <45 y) and ethnicity (non-Hispanic white vs other).
      Nearly two-thirds of firefighters (63%) had evidence of inducible myocardial dysfunction (Table 1), despite having a median percentage of predicted peak VO2 of 102% (or median of 100% and 107% in those with and without inducible myocardial dysfunction, respectively; Figure 2). There was no difference in the prevalence of inducible myocardial dysfunction by ethnicity (Table 1). On average, firefighters with evidence of inducible myocardial dysfunction were slightly but significantly older (41 vs 39 years) and heavier (19% vs 18% bodyfat) than those without inducible myocardial dysfunction (Table 1). Those with inducible myocardial dysfunction also had significantly higher mean triglycerides and fasting glucose levels. Peak VO2, percentage of predicted peak VO2, peak O2-pulse, and percentage of predicted peak O2-pulse were also significantly lower, on average, in those with inducible myocardial dysfunction (Table 1). The change in heart rate-work rate slope (ΔHR-WR slope) is one of the salient diagnostic markers for inducible myocardial dysfunction and had a mean acceleration of +61% in the inducible myocardial dysfunction group and a mean deceleration of −7% in the noninducible myocardial dysfunction group (Table 1).
      Figure 2
      Figure 2Predicted peak VO2 (%) stratified by myocardial dysfunction. VO2 = oxygen uptake.
      Firefighters were stratified by age based on the cutoff value of when age becomes a risk factor for men (<45 y vs ≥45 y); BMI, body fat, and triglyerides were slightly but significantly higher and HDL lower in firefighters with inducible myocardial dysfunction compared with those without among younger but not older firefighters (Table 3). In contrast, fasting glucose levels were significantly higher in firefighters with inducible myocardial dysfunction versus those without among older but not younger firefighters.
      Table 3Characteristics of Firefighters by Age and Myocardial Dysfunction
      Age < 45 yAge ≥ 45 y
      Myocardial dysfunctionMyocardial dysfunction
      NoYesP ValueNoYesP Value
      Number (proportion)
      Data are number (proportion); P values based on 2-sample z-tests for difference in proportion
      258 (0.42)362 (0.58)98 (0.28)249 (0.72)
      Ethnicity (non-Hispanic white)
      Data are number (proportion); P values based on 2-sample z-tests for difference in proportion
      214 (0.42)294 (0.58).6685 (0.28)221 (0.72).73
      Age (y)35 ± 635 ± 6.8550 ± 451 ± 4.04
      Height (in)71 ± 371 ± 3.3771 ± 371 ± 3.45
      Weight (lb)201 ± 32206 ± 35.11210 ± 30210 ± 33.82
      BMI (kg/m2)28.1 ± 3.728.9 ± 4.4.0229.7 ± 3.829.4 ± 4.0.46
      Body fat (%)17 ± 518 ± 6<.0120 ± 620 ± 6.87
      SBP (mm Hg)119 ± 9120 ± 9.65122 ± 10123 ± 11.29
      DBP (mm Hg)76 ± 777 ± 7.7078 ± 779 ± 7.08
      Triglycerides (mg/dL)99 ± 49108 ± 59.04127 ± 62126 ± 63.97
      Total cholesterol (mg/dL)187 ± 32187 ± 37.89197 ± 39193 ± 39.43
      LDL (mg/dL)115 ± 28115 ± 33.92123 ± 33117 ± 34.16
      HDL (mg/dL)53 ± 1350 ± 13<.0150 ± 1351 ± 14.28
      Fasting glucose (mg/dL)93 ± 1393 ± 12.6896 ± 16101 ± 23.02
      Hemoglobin A1C (%)5.3 ± 0.35.3 ± 0.3.445.5 ± 0.55.6 ± 1.0.18
      Peak VO2 (mlO2•kg−1•min−1)37 ± 634 ± 6<.0132 ± 629 ± 6<.01
      Peak VO2 (L/min)3.4 ± 0.53.1 ± 0.5<.013.0 ± 0.52.8 ± 0.5<.01
      Predicted peak VO2 (%)108 ± 1499 ± 14<.01112 ± 16104 ± 16<.01
      Peak O2-pulse (ml/beat)20 ± 319 ± 3<.0120 ± 318 ± 3<.01
      Predicted peak O2-pulse (%)121 ± 17113 ± 17<.01127 ± 18116 ± 18<.01
      SBP at peak exercise (mm Hg)169 ± 17168 ± 16.55178 ± 18176 ± 21.46
      DBP at peak exercise (mm Hg)81 ± 1381 ± 12.7184 ± 1285 ± 12.72
      Resting heart rate (beats per min)74 ± 1375 ± 12.2572 ± 1374 ± 12.12
      Peak heart rate (beats per min)166 ± 13164 ± 13.03151 ± 17152 ± 14.49
      Predicted peak heart rate (%)90 ± 688 ± 6.0389 ± 1090 ± 8.24
      Heart rate recovery (beats per min)38 ± 1038 ± 13.7835 ± 1035 ± 15.69
      ΔHR-WR slope (%)−9 ± 3453 ± 49<.01−2 ± 2573 ± 69<.01
      BMI = body mass index; DBP = diastolic blood pressure; LDL = low-density lipoprotein cholesterol; HDL = high-density lipoprotein cholesterol; SBP = systolic blood pressure; VO2 = oxygen uptake; ΔHR-WR slope = change in heart rate vs work-rate slope.
      Data are restricted to men 20 to 60 years of age.
      Data are mean ± standard deviation unless indicated otherwise; P values based on 2-sample t-tests for difference in means.
      low asterisk Data are number (proportion); P values based on 2-sample z-tests for difference in proportion
      Supplementary Table S1Characteristics of Non-Hispanic White Firefighters by Myocardial Dysfunction
      OverallMyocardial dysfunction
      NoYesP Value
      Number (proportion)814299 (0.37)515 (0.63)
      Age (y)41 ± 939 ± 942 ± 9<.01
      Height (in)71 ± 371 ± 371 ± 3.63
      Weight (lb)207 ± 34204 ± 31208 ± 35.14
      BMI (kg/m2)28.8 ± 4.128.4 ± 3.829.0 ± 4.3.06
      Body fat (%)18 ± 617 ± 519 ± 6<.01
      SBP (mm Hg)121 ± 10120 ± 9121 ± 11.08
      DBP (mm Hg)77 ± 777 ± 778 ± 7.08
      Triglycerides (mg/dL)111 ± 58105 ± 56114 ± 59.03
      Total cholesterol (mg/dL)190 ± 36190 ± 35189 ± 36.70
      LDL (mg/dL)116 ± 32117 ± 30116 ± 32.70
      HDL (mg/dL)51 ± 1353 ± 1451 ± 13.03
      Fasting glucose (mg/dL)95 ± 1594 ± 1596 ± 15.04
      Hemoglobin A1C (%)5.4 ± 0.55.4 ± 0.45.4 ± 0.5.56
      Peak VO2 (mlO2-1-1)34 ± 636 ± 632 ± 6<.01
      Peak VO2 (L/min)3.1 ± 0.53.3 ± 0.53.0 ± 0.5<.01
      Predicted peak VO2 (%)104 ± 15109 ± 15102 ± 15<.01
      Peak O2-pulse (mL/beat)19 ± 320 ± 319 ± 3<.01
      Predicted peak O2-pulse (%)117 ± 18123 ± 17114 ± 18<.01
      SBP at peak exercise (mm Hg)172 ± 19172 ± 18172 ± 19.66
      DBP at peak exercise (mm Hg)82 ± 1282 ± 1383 ± 12.22
      Resting heart rate (beats per min)74 ± 1273 ± 1375 ± 12.09
      Peak heart rate (beats per min)160 ± 15162 ± 15159 ± 14.02
      Predicted peak heart rate (%)89 ± 789 ± 789 ± 7.94
      Heart rate recovery (beats per min)37 ± 1237 ± 1037 ± 13.54
      ΔHR-WR slope (%)37 ± 60−7 ± 3362 ± 58<.01
      BMI = body mass index; DBP = diastolic blood pressure; HDL = high-density lipoprotein cholesterol; LDL = low-density lipoprotein cholesterol; SBP = systolic blood pressure; VO2 = oxygen uptake; ΔHR-WR slope = change in heart rate vs work-rate slope.
      Data are restricted to men 20 to 60 years of age.
      Data are mean ± standard deviation unless indicated otherwise; P values based on 2-sample t-tests for difference in means.
      Supplementary Table S2Characteristics of Hispanic and Nonwhite Firefighters by Myocardial Dysfunction
      OverallMyocardial dysfunction
      NoYesP Value
      Number (proportion)15357 (0.37)96 (0.63)
      Age (y)39 ± 1038 ± 939 ± 10.73
      Height (in)70 ± 370 ± 370 ± 3.96
      Weight (lb)204 ± 31202 ± 32205 ± 31.62
      BMI (kg/m2)29.5 ± 4.029.2 ± 3.729.6 ± 4.2.47
      Body fat (%)20 ± 619 ± 620 ± 6.46
      SBP (mm Hg)120 ± 9121 ± 8120 ± 9.82
      DBP (mm Hg)77 ± 777 ± 678 ± 8.36
      Triglycerides (mg/dL)118 ± 63113 ± 46121 ± 71.44
      Total cholesterol (mg/dL)190 ± 39188 ± 31191 ± 44.72
      LDL (mg/dL)116 ± 35117 ± 28115 ± 39.73
      HDL (mg/dL)51 ± 1350 ± 1251 ± 13.70
      Fasting glucose (mg/dL)99 ± 2397 ± 9100 ± 28.36
      Hemoglobin A1C (%)5.7 ± 1.05.5 ± 0.35.8 ± 1.2.07
      Peak VO2 (mlO2-1-1)33 ± 635 ± 732 ± 6<.01
      Peak VO2 (L/min)3.0 ± 0.53.2 ± 0.52.9 ± 0.5<.01
      Predicted peak VO2 (%)102 ± 15107 ± 1498 ± 14<.01
      Peak O2-pulse (mL/beat)19 ± 320 ± 319 ± 3.02
      Predicted peak O2-pulse (%)117 ± 16122 ± 15114 ± 16<.01
      SBP at peak exercise (mm Hg)169 ± 17172 ± 16168 ± 17.24
      DBP at peak exercise (mm Hg)82 ± 1183 ± 1182 ± 11.77
      Resting heart rate (beats per min)74 ± 1174 ± 1374 ± 11.78
      Peak heart rate (beats per min)158 ± 17161 ± 19157 ± 16.13
      Predicted peak heart rate (%)87 ± 889 ± 987 ± 7.11
      Heart rate recovery (beats per min)39 ± 1539 ± 1138 ± 18.97
      ΔHR-WR slope (%)34 ± 60−6 ± 2658 ± 61<.01
      BMI = body mass index; DBP =diastolic blood pressure; HDL = high-density lipoprotein cholesterol; LDL = low-density lipoprotein cholesterol; SBP = systolic blood pressure; VO2 = oxygen uptake; ΔHR-WR slope = change in heart rate vs work-rate slope.
      Data are restricted to men 20 to 60 years of age.
      Data are mean ± standard deviation unless indicated otherwise; P values based on 2-sample t-tests for difference in means.
      Supplementary Table S3Characteristics of Firefighters by Ethnicity
      OverallNon-Hispanic whiteOthersP Value
      Number (proportion)967814 (0.84)153 (0.16)
      Myocardial dysfunction (yes)
      Data are number (proportion); P values based on 2-sample z-tests for difference in proportions.
      611 (0.63)515 (0.63)96 (0.63).97
      Age (y)40 ± 941 ± 939 ± 10<.01
      Height (in)71 ± 371 ± 370 ± 3<.01
      Weight (lb)206 ± 33207 ± 34204 ± 31.38
      BMI (kg/m2)28.9 ± 4.128.8 ± 4.129.5 ± 4.0.05
      Body fat (%)18 ± 618 ± 620 ± 6<.01
      SBP (mm Hg)121 ± 10121 ± 10120 ± 9.74
      DBP (mm Hg)77 ± 777 ± 777 ± 7.66
      Triglycerides (mg/dL)112 ± 59111 ± 58118 ± 63.20
      Total cholesterol (mg/dL)190 ± 36190 ± 36190 ± 39.97
      LDL (mg/dL)116 ± 32116 ± 32116 ± 35.93
      HDL (mg/dL)51 ± 1351 ± 1351 ± 13.76
      Fasting glucose (mg/dL)96 ± 1695 ± 1599 ± 23<.01
      Hemoglobin A1C (%)5.4 ± 0.65.4 ± 0.55.6 ± 1.0<.01
      Peak VO2 (mlO2-1-1)33 ± 633 ± 633 ± 6.39
      Peak VO2 (L/min)3.1 ± 0.53.1 ± 0.53.0 ± 0.5.06
      Predicted peak VO2 (%)104 ± 15104 ± 15102 ± 15.08
      Peak O2-pulse (mL/beat)19 ± 319 ± 319 ± 3.26
      Predicted peak O2-pulse (%)117 ± 18117 ± 18117 ± 16.99
      SBP at peak exercise (mm Hg)172 ± 18172 ± 19169 ± 17.10
      DBP at peak exercise (mm Hg)82 ± 1282 ± 1282 ± 11.97
      Resting heart rate (beats per min)74 ± 1274 ± 1274 ± 11.57
      Peak heart rate (beats per min)160 ± 15160 ± 15158 ± 17.18
      Predicted peak heart rate (%)89 ± 789 ± 787 ± 8<.01
      Heart rate recovery (beats per min)37 ± 1337 ± 1239 ± 15.11
      ΔHR-WR slope (%)36 ± 6037 ± 6034 ± 60.59
      BMI = body mass index; DBP = diastolic blood pressure; HDL = high-density lipoprotein cholesterol; LDL = low-density lipoprotein cholesterol; SBP = systolic blood pressure; VO2 = oxygen uptake; ΔHR-WR slope change in heart rate vs work-rate slope.
      Data are restricted to men 20 to 60 years of age.
      Data are mean ± standard deviation unless indicated otherwise; P values based on 2-sample t-tests for difference in means.
      low asterisk Data are number (proportion); P values based on 2-sample z-tests for difference in proportions.
      In mixed effects logistic regression models (Table 2), inducible myocardial dysfunction was significantly associated with obesity, diastolic hypertension, and low percentage of predicted peak VO2 before and after adjustment for age and ethnicity. In contrast, inducible myocardial dysfunction was significantly associated with high triglycerides and low HDL cholesterol before but not after adjustment for age and ethnicity. In adjusted models, the odds of inducible myocardial dysfunction were about a third higher among firefighters with obesity and diastolic hypertension (odds ratio [OR] = 1.39, 95% confidence interval [CI] = 1.03-1.87 and OR = 1.36, 95% CI = 1.03-1.80, respectively) and more than 5 times higher among firefighters with low percentage of predicted peak VO2 (OR = 5.41, 95% CI = 3.29-8.90). However, there was a significant interaction between obesity and age consistent with obesity being a significant predictor of inducible myocardial dysfunction in younger but not older firefighters (Table 3).
      In age- and ethnicity-adjusted models, inducible myocardial dysfunction was significantly associated with obesity and diastolic hypertension before and after adjustment for percentage of predicted peak VO2 (Supplementary Table S4, available online). After adjusting for age, ethnicity, and percentage of predicted peak VO2, the odds of having inducible myocardial dysfunction were 51% and 44% higher, respectively, among obese firefighters and those with diastolic hypertension.
      Supplementary Table S4Association of CVD Risk Factors with Myocardial Dysfunction Before and After Adjustment for Percentage of Predicted Peak VO2
      Number (proportion)Unadjusted OR (95% CI)
      Based on mixed effects logistic regression adjusted for age ( ≥45 y vs <45 y) and ethnicity (non-Hispanic white vs other).
      P valueAdjusted OR (95% CI)
      Based on mixed effects logistic regression adjusted for age ( ≥45 y vs <45 y), ethnicity (non-Hispanic white vs other), and percentage of predicted peak VO2.
      P Value
      Obesity (BMI kg/m2)325 (0.34)1.39 (1.03-1.87).031.51 (1.11-2.06)<.01
      Systolic hypertension (SBP mm Hg)169 (0.17)1.11 (0.77-1.60).571.15 (0.79-1.67).47
      Diastolic hypertension (DBP mm Hg)459 (0.48)1.36 (1.03-1.80).031.44 (1.08-1.93).01
      high triglycerides (>150 mg/dL)184 (0.19)1.27 (0.88-1.83).201.12 (0.77-1.62).56
      High cholesterol (total cholesterol >200 mg/dL)350 (0.36)1.08 (0.81-1.43).601.05 (0.78-1.41).75
      High LDL cholesterol (LDL mg/dL)303 (0.31)1.15 (0.86-1.55).341.12 (0.83-1.51).47
      Low HDL cholesterol (HDL <4 0 mg/dL)177 (0.18)1.39 (0.97-2.01).081.23 (0.84-1.78).29
      Hyperglycemia (fasting glucose mg/dL)20 (0.02)2.00 (0.64-6.20).231.59 (0.48-5.28).45
      High hemoglobin A1C (%)174 (0.18)1.09 (0.75-1.58).651.03 (0.70-1.52).87
      Low predicted peak VO2 (<90%)162 (0.17)5.41 (3.29-8.90)<.01
      High resting heart rate (>90 beats per min)94 (0.10)1.08 (0.68-1.73).750.78 (0.48-1.27).32
      BMI = body mass index; CI = confidence interval; DBP = diastolic blood pressure; HDL = high density lipoprotein cholesterol; LDL = low-density lipoprotein cholesterol; OR = odds ratio; SBP = systolic blood pressure; VO2 = oxygen uptake.
      low asterisk Based on mixed effects logistic regression adjusted for age ( ≥45 y vs <45 y) and ethnicity (non-Hispanic white vs other).
      Based on mixed effects logistic regression adjusted for age ( ≥45 y vs <45 y), ethnicity (non-Hispanic white vs other), and percentage of predicted peak VO2.

      Discussion

      To our knowledge, this is the first study to demonstrate that subclinical cardiac dysfunction as evidenced by inducible myocardial dysfunction on CPET is a common finding among asymptomatic career firefighters (63% prevalence). Although cardiorespiratory fitness was well preserved overall with a median peak VO2 of 102% predicted, the absolute mean peak VO2 was 4 mlO2·kg-1·min-1 lower in the group with inducible myocardial dysfunction compared with those without inducible myocardial dysfunction, corresponding to 15%-20% increased risk for cardiovascular mortality.
      • Imboden MT
      • Harber MP
      • Whaley MH
      • et al.
      Cardiorespiratory fitness and mortality in healthy men and women.
      • Letnes JM
      • Dalen H
      • Vesterbekkmo EK
      • et al.
      Peak oxygen uptake and incident coronary heart disease in a healthy population: the HUNT Fitness Study.
      • Keteyian SJ
      • Brawner CA
      • Savage PD
      • et al.
      Peak aerobic capacity predicts prognosis in patients with coronary heart disease.
      Inducible myocardial dysfunction was significantly associated with age but not ethnicity in our predominantly non-Hispanic white sample. On average, firefighters with inducible myocardial dysfunction were older and heavier with higher blood sugars and triglycerides and lower cardiorespiratory fitness. In unadjusted mixed effects logistics regression analyses, inducible myocardial dysfunction was significantly associated with obesity, diastolic hypertension, low HDL, high triglycerides, and low cardiorespiratory fitness. After accounting for age and ethnicity, inducible myocardial dysfunction remained significantly associated with obesity and diastolic hypertension both before and after adjustment for cardiorespiratory fitness.
      Inducible myocardial dysfunction detected by CPET has been attributed to mechanical dysfunction induced by myocardial ATP depletion resulting from the ischemic cascade.
      • Chaudhry S
      • Arena R
      • Bhatt DL
      • et al.
      A practical clinical approach to utilize cardiopulmonary exercise testing in the evaluation and management of coronary artery disease: a primer for cardiologists.
      The compensatory acceleration of heart rate (HR) observed when the rise in O2-pulse (surrogate for stroke volume) abruptly plateaus after the ventilatory anaerobic threshold is the hallmark pathological sign of inducible myocardial dysfunction (Figure 1). Van De Sande et al
      • Van De Sande DAJP
      • Schoots T
      • Hoogsteen J
      • et al.
      O2 pulse patterns in male master athletes with normal and abnormal exercise tests.
      compared asymptomatic individuals with ischemic ECG changes to matched individuals without ECG changes in a population of healthy middle-aged athletes. They found that athletes with ischemic ECG changes had a lower peak VO2 and lower peak O2-pulse with an average 19% increase in the HR slope in late exercise (our inducible myocardial dysfunction group had a mean acceleration of +61%). The nonischemic ECG athletes had an average deceleration of −20% in HR slope during the same period (our noninducible myocardial dysfunction group had a mean deceleration of −7%). Interestingly, peak VO2 in their inducible myocardial dysfunction group was also 4 mlO2·kg-1·min-1 less than those with normal cardiac function, similar in magnitude to our findings. The authors concluded the ischemic ECG changes were likely due to early-stage atherosclerosis and unlikely to represent false positive findings.
      • Van De Sande DAJP
      • Schoots T
      • Hoogsteen J
      • et al.
      O2 pulse patterns in male master athletes with normal and abnormal exercise tests.
      In a recent study based on firefighter autopsies, we found that only 20% of cardiac deaths had evidence of intracoronary thrombi, suggesting that many cardiac events during job-related strenuous activity are likely caused by demand ischemia.
      • Smith DL
      • Haller JM
      • Korre M
      • et al.
      Pathoanatomic findings associated with duty related cardiac death in us firefighters: a case control study.
      The data suggest that inducible myocardial dysfunction in firefighters could be caused by microvascular ischemia. If left untreated, microvascular ischemia can lead to symptomatic nonobstructive and obstructive coronary artery disease, atrial fibrillation, heart failure, and persist as angina after revascularization.
      • Buono MGD
      • Montone RA
      • Camilli M
      • et al.
      Coronary microvascular dysfunction across the spectrum of cardiovascular diseases.
      • Knuuti J
      • Wijns W
      • Saraste A
      • et al.
      2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes: The Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC).
      • Range FT
      • Schäfers M
      • Acil T
      • et al.
      Impaired myocardial perfusion and perfusion reserve associated with increased coronary resistance in persistent idiopathic atrial fibrillation.
      • Taqueti VR
      • Solomon SD
      • Shah AM
      • et al.
      Coronary microvascular dysfunction and future risk of heart failure with preserved ejection fraction.
      In this study, the primary cardiometabolic risk factors associated with inducible myocardial dysfunction were obesity and diastolic hypertension. We recently reported that across all age groups, male firefighters had a higher prevalence of hypertension (based largely on a greater prevalence of elevated diastolic blood pressure) than the general population.
      • Khaja SU
      • Mathias KC
      • Bode ED
      • et al.
      Hypertension in the United States Fire Service.
      We have also shown that firefighters have a concerning prevalence of obesity and hypercholesterolemia and that these risk factors increase over a 5-year period.
      • Soares EMKVK
      • Smith D
      • Grossi Porto LG.
      Worldwide prevalence of obesity among firefighters: a systematic review protocol.
      Asymptomatic obese individuals are recognized to have subclinical cardiac dysfunction that is thought to be linked to endothelial dysfunction and non-endothelium-dependent coronary microvascular dysfunction.
      • Powell-Wiley TM
      • Poirier P
      • Burke LE
      • et al.
      Obesity and cardiovascular disease: a scientific statement from the American Heart Association.
      Obesity is a major driver of metabolic syndrome
      • Grundy SM.
      Metabolic syndrome update.
      and accelerates atherosclerosis even after accounting for the impact of traditional cardiovascular risk factors
      • Powell-Wiley TM
      • Poirier P
      • Burke LE
      • et al.
      Obesity and cardiovascular disease: a scientific statement from the American Heart Association.
      and even in obese individuals considered to be metabolically healthy.
      • Commodore-Mensah Y
      • Lazo M
      • Tang O
      • et al.
      High Burden of subclinical and cardiovascular disease risk in adults with metabolically healthy obesity: the Atherosclerosis Risk in Communities (ARIC) Study.
      ,
      • Zhou Z
      • Macpherson J
      • Gray SR
      • et al.
      Are people with metabolically healthy obesity really healthy? A prospective cohort study of 381, 363 UK Biobank participants.
      Visceral adipose tissue related systemic inflammation, decreased nitric oxide bioavailability, insulin resistance, and oxidized low-density lipoprotein are primary drivers of endothelial dysfunction in obesity.
      • Engin A.
      Endothelial dysfunction in obesity.
      Likewise, the increased hemodynamic load of hypertension has also been linked to endothelial dysfunction regardless of the underlying mechanism.
      • Rizzoni D
      • Porteri E
      • Castellano M
      • et al.
      Endothelial dysfunction in hypertension is independent from the etiology and from vascular structure.
      Obesity has also been linked to abnormalities in non-endothelium-dependent coronary microvasculature involved in regulating myocardial blood flow.
      • Schindler TH
      • Schelbert HR
      • Quercioli A
      • et al.
      Cardiac PET imaging for the detection and monitoring of coronary artery disease and microvascular health.
      ,
      • Taqueti VR
      • Carli MFD.
      Coronary microvascular disease pathogenic mechanisms and therapeutic options.
      Coronary microvascular dysfunction is associated with a higher BMI, is linked to increased microvascular resistance, and provides independent prognostic information for cardiovascular risk in obese patients.
      • Bajaj NS
      • Osborne MT
      • Gupta A
      • et al.
      Coronary microvascular dysfunction and cardiovascular risk in obese patients.
      ,
      • Schindler TH
      • Cardenas J
      • Prior JO
      • et al.
      Relationship between increasing body weight, insulin resistance, inflammation, adipocytokine leptin, and coronary circulatory function.
      Asymptomatic diabetic patients undergoing cardiac magnetic resonance imaging (MRI) have also been shown to have decreased myocardial blood flow from microvascular dysfunction, a finding that was linked to reduced peak VO2.
      • Gulsin GS
      • Henson J
      • Brady EM
      • et al.
      Cardiovascular determinants of aerobic exercise capacity in adults with type 2 diabetes.
      Thus, inducible myocardial dysfunction may be the result of endothelial dysfunction and coronary microvascular dysfunction.
      These findings provide evidence that inducible myocardial dysfunction is a distinct “physiological phenotype” associated with undertreated cardiometabolic risk factors that can result in progressive decrease in cardiorespiratory fitness over time. Because 80% of cardiovascular disease is considered preventable, inducible myocardial dysfunction could help to identify individuals who would benefit from more aggressive risk factor modification with the goal of increasing cardiorespiratory fitness from baseline. The current standard of care is to recommend exercise as the primary treatment modality for individuals with modifiable cardiometabolic risk factors as well as those with established cardiovascular disease. CPET provides individualized exercise prescriptions for precise HR training in the low-, moderate-, and high-intensity zones. Training in the moderate HR zone (corresponding to 40%-60% of measured peak VO2) is safe, well tolerated, and highly efficacious to reverse cardiometabolic risk factors, promote weight loss, improve coronary circulation, and increase cardiorespiratory fitness if performed for the recommended 150 min/wk or more.
      • Riebe D
      • Ehrman J
      • Liguori G.
      American College of Sports Medicine's Guidelines for Exercise Testing and Prescription.
      For individuals not compliant with exercise training or for whom exercise alone may not be sufficient to stop disease progression, intensification with medications proven to reduce cardiovascular mortality should be the next step. Longitudinal changes in cardiorespiratory fitness provides a robust and recognized mechanism to track response to medical therapy on an individualized basis. Serial CPET in a high-risk individual on aggressive lipid-lowering therapy for primary prevention for 3.3 years (without lifestyle changes) revealed a significant reversal of the baseline inducible myocardial dysfunction pattern with a concomitant 2.6 mlO2·kg-1·min-1 increase in peak VO2.
      • Chaudhry S
      • Arena RA
      • Hansen JE
      • et al.
      The utility of cardiopulmonary exercise testing to detect and track early-stage ischemic heart disease.
      In the same individual, nearly complete normalization of inducible myocardial dysfunction and cardiorespiratory fitness was achieved with the addition of exercise to his daily routine.
      • Chaudhry S
      • Arena R
      • Bhatt DL
      • et al.
      A practical clinical approach to utilize cardiopulmonary exercise testing in the evaluation and management of coronary artery disease: a primer for cardiologists.
      Implementing precise, individualized physiological data in this manner can be used to improve cardiovascular health and safety as part of an outpatient heart disease prevention program. The establishment of multidisciplinary cardiometabolic health clinics to accomplish similar goals have been proposed for the general population.
      • Reiter-Brennan C
      • Dzaye O
      • Davis D
      • et al.
      Comprehensive care models for cardiometabolic disease.
      There are several strengths of the current study. We analyzed data from nearly 1000 firefighters from a geographically diverse population including 21 departments from 2 states. Because the annual medical evaluations were mandatory, referral and selection bias were minimized. To improve diagnostic accuracy, the collection, processing, and interpretation of all CPET data were standardized by a central laboratory. Despite these strengths, there were also several limitations. Our sample was a convenience sample, and due to administrative constraints, we were unable to account for smoking, a potentially significant confounder. Fourteen percent of firefighters were also on cardiovascular medications, another potential confounder. There were some small but significant differences between the 967 firefighters included in our analyses and the 257 who were excluded due to missing data. Notably though, there was no evidence that the outcome of interest (inducible myocardial dysfunction) differed between the 2 groups (Supplementary Table S5, available online). Our sample was exclusively male and primarily non-Hispanic white with a well-defined occupational exposure. Thus, these findings may not be generalizable to other populations. Although microvascular ischemia may be the likely mechanism of inducible myocardial dysfunction, validation and further study by other modalities are needed to better characterize this physiological phenotype. Future research should also determine the significance of inducible myocardial dysfunction to predict cardiovascular events and mortality independent of cardiorespiratory fitness.
      Supplementary Table S5Characteristics of Included and Excluded Firefighters
      N
      Number of firefighters with nonmissing values for each variable.
      OverallIncludedExcludedP Value
      Ethnicity (non-Hispanic white)
      Data are number (proportion); P values based on 2-sample z-tests for difference in proportions.
      12241025 (0.84)814 (0.84)211 (0.82).48
      Myocardial dysfunction (yes)
      Data are number (proportion); P values based on 2-sample z-tests for difference in proportions.
      1195769 (0.64)611 (0.63)158 (0.61).67
      Age (y)122440 ± 940 ± 937 ± 9<.01
      Height (in)122471 ± 371 ± 371 ± 3.57
      Weight (lb)1224207 ± 34206 ± 33208 ± 35.34
      BMI (kg/m2)122428.9 ± 4.228.9 ± 4.129.1 ± 4.4.46
      Body fat (%)119119 ± 618 ± 619 ± 6.39
      SBP (mm Hg)1149121 ± 10121 ± 10124 ± 11<.01
      DBP (mm Hg)114977 ± 777 ± 779 ± 8<.01
      Triglycerides (mg/dL)1194111 ± 60112 ± 59107 ± 64.22
      Total cholesterol (mg/dL)1220190 ± 38190 ± 36192 ± 45.40
      LDL (mg/dL)1195116 ± 32116 ± 32114 ± 33.23
      HDL (mg/dL)121751 ± 1351 ± 1349 ± 13.06
      Fasting glucose (mg/dL)121695 ± 1696 ± 1695 ± 15.70
      Hemoglobin A1C (%)11055.4 ± 0.65.4 ± 0.65.5 ± 0.9.55
      Peak VO2 (mlO2-1-1)122333 ± 633 ± 633 ± 7.20
      Peak VO2 (L/min)12243.1 ± 0.53.1 ± 0.53.0 ± 0.6.26
      Predicted peak VO2 (%)1223103 ± 16104 ± 1599 ± 17<.01
      Peak O2-pulse (mL/beat)122419 ± 319 ± 318 ± 4<.01
      Predicted peak O2-pulse (%)1224116 ± 18117 ± 18110 ± 20<.01
      SBP at peak exercise (mm Hg)1224171 ± 19172 ± 18169 ± 22.10
      DBP at peak exercise (mm Hg)122483 ± 1282 ± 1284 ± 11.05
      Resting heart rate (beats per min)122275 ± 1374 ± 1278 ± 13<.01
      Peak heart rate (beats per min)1224161 ± 16160 ± 15165 ± 17<.01
      Predicted peak heart rate (%)122489 ± 889 ± 790 ± 8.04
      Heart rate recovery (beats per min)122237 ± 1337 ± 1337 ± 13.69
      ΔHR-WR slope (%)122434 ± 6036 ± 6025 ± 59<.01
      BMI = body mass index; DBP = diastolic blood pressure; HDL = high-density lipoprotein cholesterol; LDL = low-density lipoprotein cholesterol; SBP = systolic blood pressure; VO2 = oxygen uptake; ΔHR-WR slope = change in heart rate vs work-rate slope.
      Data are restricted to men 20 to 60 years of age.
      Data are mean ± standard deviation unless indicated otherwise; P values based on 2-sample t-tests for difference in means.
      low asterisk Number of firefighters with nonmissing values for each variable.
      Data are number (proportion); P values based on 2-sample z-tests for difference in proportions.

      Conclusion

      Firefighters are an important occupational group that requires adequate cardiorespiratory fitness and cardiovascular health to safely perform high-risk duties. Myocardial ischemia during strenuous firefighting work increases the risk for adverse events and sudden cardiac death. This study found that nearly two-thirds of firefighters have signs of subclinical cardiac dysfunction as evidenced by inducible myocardial dysfunction during CPET. Moreover, inducible myocardial dysfunction was significantly associated with reduced cardiorespiratory fitness and undertreated cardiometabolic risk factors. Aggressive risk factor interventions with exercise and medical therapy have the potential to treat these risk factors with the intent to reverse inducible myocardial dysfunction and increase cardiorespiratory fitness from baseline. Comprehensive cardiovascular disease prevention programs could benefit by using this information to improve the health and safety of career firefighters.

      References

      1. Fahy RF, Molis JL. Firefighter fatalities in the US-2018. Available at:https://www.nfpa.org/News-and-Research/Publications-and-media/NFPA-Journal/2019/July-August-2019/Features/Firefighter-Fatalities#:∼:text=Author(s)%3A%20Rita%20Fahy,Published%20on%20July%201%2C%202019.&text=In%202018%2C%2064%20firefighters%20died,than%2070%20deaths%20per%20year. Accessed July 15, 2020.

        • Smith DL
        • Haller JM
        • Korre M
        • et al.
        The relation of emergency duties to cardiac death among US firefighters.
        Am J Cardiol. 2019; 123: 736-741https://doi.org/10.1016/j.amjcard.2018.11.049
        • Kodama S
        • Saito K
        • Tanaka S
        • et al.
        Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis.
        JAMA. 2009; 301: 2024-2035https://doi.org/10.1001/jama.2009.681
        • Ross R
        • Blair SN
        • Arena R
        • et al.
        Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign: a scientific statement from the American Heart Association.
        Circulation. 2016; 134: e653-e699https://doi.org/10.1161/cir.0000000000000461
        • Imboden MT
        • Harber MP
        • Whaley MH
        • et al.
        Cardiorespiratory fitness and mortality in healthy men and women.
        J Am Coll Cardiol. 2018; 72: 2283-2292https://doi.org/10.1016/j.jacc.2018.08.2166
        • Letnes JM
        • Dalen H
        • Vesterbekkmo EK
        • et al.
        Peak oxygen uptake and incident coronary heart disease in a healthy population: the HUNT Fitness Study.
        Eur Heart J. 2019; 40: 1633-1639https://doi.org/10.1093/eurheartj/ehy708
        • Keteyian SJ
        • Brawner CA
        • Savage PD
        • et al.
        Peak aerobic capacity predicts prognosis in patients with coronary heart disease.
        Am Heart J. 2008; 156: 292-300https://doi.org/10.1016/j.ahj.2008.03.017
        • Balady GJ
        • Arena R
        • Sietsema K
        • et al.
        Clinician's Guide to cardiopulmonary exercise testing in adults: a scientific statement from the American Heart Association.
        Circulation. 2010; 122: 191-225https://doi.org/10.1161/CIR.0b013e3181e52e69
        • Belardinelli R
        • Lacalaprice F
        • Carle F
        • et al.
        Exercise-induced myocardial ischaemia detected by cardiopulmonary exercise testing.
        Eur Heart J. 2003; 24: 1304-1313
        • Chaudhry S
        • Arena R
        • Wasserman K
        • et al.
        Exercise-induced myocardial ischemia detected by cardiopulmonary exercise testing.
        Am J Cardiol. 2009; 103: 615-619https://doi.org/10.1016/j.amjcard.2008.10.034
        • Belardinelli R
        • Lacalaprice F
        • Tiano L
        • et al.
        Cardiopulmonary exercise testing is more accurate than ECG-stress testing in diagnosing myocardial ischemia in subjects with chest pain.
        Int J Cardiol. 2014; 174: 337-342https://doi.org/10.1016/j.ijcard.2014.04.102
        • Chaudhry S
        • Kumar N
        • Behbahani H
        • et al.
        Abnormal heart-rate response during cardiopulmonary exercise testing identifies cardiac dysfunction in symptomatic patients with non-obstructive coronary artery disease.
        Int J Cardiol. 2017; 228: 114-121https://doi.org/10.1016/j.ijcard.2016.11.235
      2. Mann J, Williams M, Wilson J, et al. Exercise-induced myocardial dysfunction detected by cardiopulmonary exercise testing is associated with increased risk of mortality in major oncological colorectal surgery [e-pub ahead of print]. Br J Anaesth. doi: https://doi.org/10.1016/j.bja.2019.12.043. Accessed July 15, 2020.

        • National Fire Protection Association
        NFPA 1582: Standard on Comprehensive Occupational Medical Program for Fire Departments.
        National Fire Protection Association, Technical Committee on Fire Service Occupational Safety and Health, Quincy, MA2018
        • Wasserman K
        • Hansen JE
        • Sue DY
        • et al.
        Principles of Exercise Testing and Interpretation: Including Pathophysiology and Clinical Applications.
        5th ed. Lippincott Williams and Wilkins, Philadelphia, PA2012
        • Evangelista M
        • Boveri S
        • Alfonzetti E
        • et al.
        Abstract 12231: accuracy of methods for stroke volume measures by O2-pulse during gas exchange analysis and clinical implications.
        Circulation. 2019; 140: A12231https://doi.org/10.1161/circ.140.suppl_1.12231
        • Chaudhry S
        • Arena R
        • Bhatt DL
        • et al.
        A practical clinical approach to utilize cardiopulmonary exercise testing in the evaluation and management of coronary artery disease: a primer for cardiologists.
        Curr Opin Cardiol. 2018; 33: 168-177https://doi.org/10.1097/HCO.0000000000000494
        • Van De Sande DAJP
        • Schoots T
        • Hoogsteen J
        • et al.
        O2 pulse patterns in male master athletes with normal and abnormal exercise tests.
        Med Sci Sports Exerc. 2019; 51: 12-18https://doi.org/10.1249/mss.0000000000001772
        • Smith DL
        • Haller JM
        • Korre M
        • et al.
        Pathoanatomic findings associated with duty related cardiac death in us firefighters: a case control study.
        J Am Heart Assoc. 2018; 7e009446https://doi.org/10.1161/JAHA.118.009446
        • Buono MGD
        • Montone RA
        • Camilli M
        • et al.
        Coronary microvascular dysfunction across the spectrum of cardiovascular diseases.
        J Am Coll Cardiol. 2021; 78: 1352-1371https://doi.org/10.1016/j.jacc.2021.07.042
        • Knuuti J
        • Wijns W
        • Saraste A
        • et al.
        2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes: The Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC).
        Eur Heart J. 2020; 41: 407-477https://doi.org/10.1093/eurheartj/ehz425
        • Range FT
        • Schäfers M
        • Acil T
        • et al.
        Impaired myocardial perfusion and perfusion reserve associated with increased coronary resistance in persistent idiopathic atrial fibrillation.
        Eur Heart J. 2007; 28: 2223-2230https://doi.org/10.1093/eurheartj/ehm246
        • Taqueti VR
        • Solomon SD
        • Shah AM
        • et al.
        Coronary microvascular dysfunction and future risk of heart failure with preserved ejection fraction.
        Eur Heart J. 2018; 39: 840-849https://doi.org/10.1093/eurheartj/ehx721
        • Khaja SU
        • Mathias KC
        • Bode ED
        • et al.
        Hypertension in the United States Fire Service.
        Int J Environ Res Public Health. 2021; 18: 5432
        • Soares EMKVK
        • Smith D
        • Grossi Porto LG.
        Worldwide prevalence of obesity among firefighters: a systematic review protocol.
        BMJ Open. 2020; 10e031282https://doi.org/10.1136/bmjopen-2019-031282
        • Powell-Wiley TM
        • Poirier P
        • Burke LE
        • et al.
        Obesity and cardiovascular disease: a scientific statement from the American Heart Association.
        Circulation. 2021; 143: e984-e1010https://doi.org/10.1161/CIR.0000000000000973
        • Grundy SM.
        Metabolic syndrome update.
        Trends Cardiovasc Med. 2016; 26: 364-373https://doi.org/10.1016/j.tcm.2015.10.004
        • Commodore-Mensah Y
        • Lazo M
        • Tang O
        • et al.
        High Burden of subclinical and cardiovascular disease risk in adults with metabolically healthy obesity: the Atherosclerosis Risk in Communities (ARIC) Study.
        Diabetes Care. 2021; 44: 1657-1663https://doi.org/10.2337/dc20-2227
        • Zhou Z
        • Macpherson J
        • Gray SR
        • et al.
        Are people with metabolically healthy obesity really healthy? A prospective cohort study of 381, 363 UK Biobank participants.
        Diabetologia. 2021; 64: 1963-1972https://doi.org/10.1007/s00125-021-05484-6
        • Engin A.
        Endothelial dysfunction in obesity.
        in: Engin AB Engin A Obesity and Lipotoxicity. Springer International Publishing, Cham, Switzerland2017: 345-379
        • Rizzoni D
        • Porteri E
        • Castellano M
        • et al.
        Endothelial dysfunction in hypertension is independent from the etiology and from vascular structure.
        Hypertension. 1998; 31: 335-341https://doi.org/10.1161/01.HYP.31.1.335
        • Schindler TH
        • Schelbert HR
        • Quercioli A
        • et al.
        Cardiac PET imaging for the detection and monitoring of coronary artery disease and microvascular health.
        JACC Cardiovasc Imaging. 2010; 3: 623-640https://doi.org/10.1016/j.jcmg.2010.04.007
        • Taqueti VR
        • Carli MFD.
        Coronary microvascular disease pathogenic mechanisms and therapeutic options.
        J Am Coll Cardiol. 2018; 72: 2625-2641https://doi.org/10.1016/j.jacc.2018.09.042
        • Bajaj NS
        • Osborne MT
        • Gupta A
        • et al.
        Coronary microvascular dysfunction and cardiovascular risk in obese patients.
        J Am Coll Cardiol. 2018; 72: 707-717https://doi.org/10.1016/j.jacc.2018.05.049
        • Schindler TH
        • Cardenas J
        • Prior JO
        • et al.
        Relationship between increasing body weight, insulin resistance, inflammation, adipocytokine leptin, and coronary circulatory function.
        J Am Coll Cardiol. 2006; 47: 1188-1195https://doi.org/10.1016/j.jacc.2005.10.062
        • Gulsin GS
        • Henson J
        • Brady EM
        • et al.
        Cardiovascular determinants of aerobic exercise capacity in adults with type 2 diabetes.
        Diabetes Care. 2020; 43: 2248-2256https://doi.org/10.2337/dc20-0706
        • Riebe D
        • Ehrman J
        • Liguori G.
        American College of Sports Medicine's Guidelines for Exercise Testing and Prescription.
        10th ed. Wolters Kluwer Health, Philadelphia, PA2018
        • Chaudhry S
        • Arena RA
        • Hansen JE
        • et al.
        The utility of cardiopulmonary exercise testing to detect and track early-stage ischemic heart disease.
        Mayo Clin Proc. 2010; 85: 928-932https://doi.org/10.4065/mcp.2010.0183
        • Reiter-Brennan C
        • Dzaye O
        • Davis D
        • et al.
        Comprehensive care models for cardiometabolic disease.
        Curr Cardiol Rep. 2021; 23: 22https://doi.org/10.1007/s11886-021-01450-1