Produção Nacional
Revisado por pares
Effect of Body Mass Index on Left Ventricular Mass in Career Male Firefighters
2016; Elsevier BV; Volume: 118; Issue: 11 Linguagem: Inglês
10.1016/j.amjcard.2016.08.058
ISSN1879-1913
AutoresMaria Korre, Luiz Guilherme Grossi Porto, Andrea Farioli, Justin Yang, David C. Christiani, Costas A. Christophi, David A. Lombardi, Richard J. Kovacs, Ronald Mastouri, Siddique Abbasi, Michael L. Steigner, Steven Moffatt, Denise L. Smith, Stefanos N. Kales,
Tópico(s)Non-Invasive Vital Sign Monitoring
ResumoLeft ventricular (LV) mass is a strong predictor of cardiovascular disease (CVD) events; increased LV mass is common among US firefighters and plays a major role in firefighter sudden cardiac death. We aim to identify significant predictors of LV mass among firefighters. Cross-sectional study of 400 career male firefighters selected by an enriched randomization strategy. Weighted analyses were performed based on the total number of risk factors per subject with inverse probability weighting. LV mass was assessed by echocardiography (ECHO) and cardiac magnetic resonance, and normalized (indexed) for height. CVD risk parameters included vital signs at rest, body mass index (BMI)–defined obesity, obstructive sleep apnea risk, low cardiorespiratory fitness, and physical activity. Linear regression models were performed. In multivariate analyses, BMI was the only consistent significant independent predictor of LV mass indexes (all, p <0.001). A 1-unit decrease in BMI was associated with 1-unit (g/m1.7) reduction of LV mass/height1.7 after adjustment for age, obstructive sleep apnea risk, and cardiorespiratory fitness. In conclusion, after height-indexing ECHO-measured and cardiac magnetic resonance–measured LV mass, BMI was found to be a major driver of LV mass among firefighters. Our findings taken together with previous research suggest that reducing obesity will improve CVD risk profiles and decrease on-duty CVD and sudden cardiac death events in the fire service. Our results may also support targeted noninvasive screening for LV hypertrophy with ECHO among obese firefighters. Left ventricular (LV) mass is a strong predictor of cardiovascular disease (CVD) events; increased LV mass is common among US firefighters and plays a major role in firefighter sudden cardiac death. We aim to identify significant predictors of LV mass among firefighters. Cross-sectional study of 400 career male firefighters selected by an enriched randomization strategy. Weighted analyses were performed based on the total number of risk factors per subject with inverse probability weighting. LV mass was assessed by echocardiography (ECHO) and cardiac magnetic resonance, and normalized (indexed) for height. CVD risk parameters included vital signs at rest, body mass index (BMI)–defined obesity, obstructive sleep apnea risk, low cardiorespiratory fitness, and physical activity. Linear regression models were performed. In multivariate analyses, BMI was the only consistent significant independent predictor of LV mass indexes (all, p <0.001). A 1-unit decrease in BMI was associated with 1-unit (g/m1.7) reduction of LV mass/height1.7 after adjustment for age, obstructive sleep apnea risk, and cardiorespiratory fitness. In conclusion, after height-indexing ECHO-measured and cardiac magnetic resonance–measured LV mass, BMI was found to be a major driver of LV mass among firefighters. Our findings taken together with previous research suggest that reducing obesity will improve CVD risk profiles and decrease on-duty CVD and sudden cardiac death events in the fire service. Our results may also support targeted noninvasive screening for LV hypertrophy with ECHO among obese firefighters. Despite the critical prognostic significance of left ventricular (LV) mass,1Levy D. Garrison R.J. Savage D.D. Kannel W.B. Castelli W.P. Prognostic implications of echocardiographically determined left ventricular mass in the Framingham Heart Study.N Engl J Med. 1990; 322: 1561-1566Crossref PubMed Scopus (4963) Google Scholar, 2Haider A.W. Larson M.G. Benjamin E.J. Levy D. Increased left ventricular mass and hypertrophy are associated with increased risk for sudden death.J Am Coll Cardiol. 1998; 32: 1454-1459Abstract Full Text Full Text PDF PubMed Scopus (644) Google Scholar, 3Armstrong A.C. Gidding S. Gjesdal O. Wu C. Bluemke D.A. Lima J.A. LV mass assessed by echocardiography and CMR, cardiovascular outcomes, and medical practice.JACC Cardiovasc Imaging. 2012; 5: 837-848Abstract Full Text Full Text PDF PubMed Scopus (217) Google Scholar its measurement and role in clinical practice have yet to be established.4Gidding S.S. Controversies in the assessment of left ventricular mass.Hypertension. 2010; 56: 26-28Crossref PubMed Scopus (20) Google Scholar Echocardiography (ECHO) and cardiac magnetic resonance (CMR) are the 2 most commonly used imaging methods for the assessment of LV mass. Although, CMR is considered the gold standard for assessing LV mass, ECHO is a well validated, noninvasive method that is more widely used in clinical practice.5Bottini P.B. Carr A.A. Prisant L.M. Flickinger F.W. Allison J.D. Gottdiener J.S. Magnetic resonance imaging compared to echocardiography to assess left ventricular mass in the hypertensive patient.Am J Hypertens. 1995; 8: 221-228Crossref PubMed Scopus (311) Google Scholar In addition to considering different imaging methods, disagreement exists as to the most appropriate method of indexing LV mass to body size parameters.3Armstrong A.C. Gidding S. Gjesdal O. Wu C. Bluemke D.A. Lima J.A. LV mass assessed by echocardiography and CMR, cardiovascular outcomes, and medical practice.JACC Cardiovasc Imaging. 2012; 5: 837-848Abstract Full Text Full Text PDF PubMed Scopus (217) Google Scholar Current evidence suggests indexing by height to the allometric powers of 1.7 and 2.7 are the most accurate normalization techniques.4Gidding S.S. Controversies in the assessment of left ventricular mass.Hypertension. 2010; 56: 26-28Crossref PubMed Scopus (20) Google Scholar, 6Chirinos J.A. Segers P. De Buyzere M.L. Kronmal R.A. Raja M.W. De Bacquer D. Claessens T. Gillebert T.C. St John-Sutton M. Rietzschel E.R. Left ventricular mass: allometric scaling, normative values, effect of obesity, and prognostic performance.Hypertension. 2010; 56: 91-98Crossref PubMed Scopus (199) Google Scholar, 7Cuspidi C. Meani S. Negri F. Giudici V. Valerio C. Sala C. Zanchetti A. Mancia G. Indexation of left ventricular mass to body surface area and height to allometric power of 2.7: is the difference limited to obese hypertensives?.J Hum Hypertens. 2009; 23: 728-734Crossref PubMed Scopus (70) Google Scholar This study identifies the most important predictors of LV mass after indexing for height among career male firefighters as assessed by both ECHO and CMR. Male career firefighters, aged 18 years and older were recruited from the Indianapolis Fire Department. Eligible firefighters had a recorded fire department–sponsored medical examination in the last 2 years that included a submaximal exercise tolerance test and had no restrictions on duty. From those eligible, we selected a total of 400 participants, using an "enriched" randomization strategy based on age at randomization, obesity, hypertension, and cardiorespiratory fitness status at last examination, where a larger number of higher risk participants could be selected. Thus, we randomly selected 100 participants from the entire eligible population; 75 low-risk participants (age <40, nonobese, free of hypertension, and high cardiorespiratory fitness) and 225 higher risk participants (at least 2 of the following: age ≥40 years, obese, hypertension, or low cardiorespiratory fitness) for further LV hypertrophy/cardiomegaly screening and imaging tests. Obesity was defined by standard criteria (body mass index [BMI] ≥30 kg/m2). Hypertension was considered present if blood pressure at rest is ≥140/90 mm Hg. Low cardiorespiratory fitness was defined as the bottom tertile, as measured by the recorded treadmill time and the estimated maximal VO2 during the last exercise test. Those selected were included in the study if they had no contraindication to CMR and signed informed consent to participate. LV mass was assessed by both ECHO and CMR imaging. First, a transthoracic cardiac echocardiogram was done as a simple 2-dimensional study with limited m-mode recordings. An abbreviated CMR was performed as "function only" immediately after the ECHO. Images were obtained using a retrospectively electrocardiogram gated steady-state free precession cine sequence. In this fashion, a contiguous short-axis stack of 8-mm slices was obtained parallel to the atrioventricular groove to cover the entire length of the LV. Then, manual tracing of end-diastolic epicardial and endocardial borders was performed. Standard long-axis views were also obtained including horizontal long-axis, vertical long-axis, and 3-chamber views, facilitating the interpretation of ventricular function. Board certified specialists performed clinical interpretation of imaging. LV mass indexes were derived by dividing LV mass in grams with height to the allometric powers of 1.7 and 2.7 (in meters1.7 and meters2.7, respectively). Height was measured in the standing position with a clinic stadiometer. Body weight was measured with bare feet and in light clothes on a calibrated scale. BMI was calculated as the weight in kilograms divided by the square of height in meters. Blood pressure was measured using an appropriately sized cuff with the subject in the seated position. Heart rate and blood pressure were obtained in a resting state from the physical examination (and were not measured before the exercise test). Medical examination data were further supplemented by a preimaging questionnaire, which collected comprehensive information on smoking status, a history of heart rhythm problems, family history of cardiac problems, and moderate to vigorous physical activity level in minutes per week. Obstructive sleep apnea risk was assessed using the validated Berlin Questionnaire.8Webber M.P. Lee R. Soo J. Gustave J. Hall C.B. Kelly K. Prezant D. Prevalence and incidence of high risk for obstructive sleep apnea in World Trade Center-exposed rescue/recovery workers.Sleep Breath. 2011; 15: 283-294Crossref PubMed Scopus (55) Google Scholar We performed a weighted analysis so as to account for our enriched randomization sampling strategy. Weights were calculated based on the total number of risk factors per subject with the technique of inverse probability weighting. Baseline characteristics were described using the mean (SD) in the case of quantitative variables and the frequency (%) for categorical variables. The effects of the different independent variables on the LV mass indexes were assessed with the use of linear regression models. Any independent variables that were significant in the univariate regression models were included in the multivariate regression models. In the multivariate analysis, we followed the backward stepwise elimination process with a removal criterion of alpha = 0.20. Then, considering the predictors that resulted from the backward elimination process and variables that we knew a priori to be important clinical predictors, we constructed the final multivariate regression models. The interaction effects between BMI with obstructive sleep apnea risk and age were also assessed in these models. Collinearity was evaluated using the variance inflation factor. Analyses were performed using SPSS, version 21.0 (IBM, Armonk, New York). A p value of <0.05 was considered statistically significant, and all tests performed were 2 sided. Of the 400 firefighters, we excluded 7 participants with missing measurements of LV mass, assessed by CMR. Baseline characteristics are summarized in Table 1. The mean age of the study subjects was 45 (8.1) years, their mean BMI was 30 (4.5) kg/m2 and 45% were obese.Table 1Baseline descriptive characteristicsVariablesStudy Sample(N = 393)Study SampleUnweightedAge (years)∗Mean (SD) for continuous variables.47 ± 8.245 ± 8.1Height (cm)∗Mean (SD) for continuous variables.179± 6.4179 ± 6.6Heart rate (bpm)∗Mean (SD) for continuous variables.81 ± 1380 ± 13Body weight (kg)∗Mean (SD) for continuous variables.99 ± 1797 ±17Resting systolic blood pressure (mm Hg)∗Mean (SD) for continuous variables.126 ± 9.7125 ± 9.4Resting diastolic blood pressure (mm Hg)∗Mean (SD) for continuous variables.82 ± 8.181 ± 7.4High risk of obstructive sleep apnea†n (%) for categorical variables.112 (38%)254 (32%)Body mass index (kg/m2)∗Mean (SD) for continuous variables.31 ± 4.630 ± 4.5Smoker†n (%) for categorical variables.50 (13%)135 (13%)History of heart rhythm problems†n (%) for categorical variables.60 (16%)153 (15%)Family history of cardiac problems†n (%) for categorical variables.153 (40%)426 (41%)Age ≥ 40 (years)†n (%) for categorical variables.301 (78%)770 (73%)Body mass index ≥ 30 (kg/m2)†n (%) for categorical variables.260 (56%)474 (45%)Low cardiorespiratory fitness†n (%) for categorical variables.178 (47%)363 (34%)Moderate to vigorous physical activity (min/week)∗Mean (SD) for continuous variables.177 ± 117187 ± 118LV mass by echocardiography (g)∗Mean (SD) for continuous variables.189 ± 38187 ± 37LV mass by cardiac magnetic resonance (g)∗Mean (SD) for continuous variables.139 ± 24138 ± 23LV mass by echocardiography indexed to height1.7 (g/m1.7)∗Mean (SD) for continuous variables.70 ± 1370 ± 13LV mass by echocardiography indexed to height2.7 (g/m2.7)∗Mean (SD) for continuous variables.40 ± 7.639 ± 7.4LV mass by cardiac magnetic resonance indexed to height1.7 (g/m1.7)∗Mean (SD) for continuous variables.52 ± 8.351 ± 8.1LV mass by cardiac magnetic resonance indexed to height2.7 (g/m2.7)∗Mean (SD) for continuous variables.29 ± 4.729 ± 4.6bpm = beats per minute; LV = left ventricular.∗ Mean (SD) for continuous variables.† n (%) for categorical variables. Open table in a new tab bpm = beats per minute; LV = left ventricular. The univariate analyses summarized in Table 2 revealed highly statistically significant associations between both LV mass height indexes, assessed by both ECHO and CMR, with systolic blood pressure at rest, hypertension, high risk of obstructive sleep apnea, low cardiorespiratory fitness, and BMI (all p <0.01). Age, family history of cardiac problems, and physical activity also showed a significant association with both LV mass indexes, when LV mass was based on ECHO measurement (at least p <0.01).Table 2Simple linear regression models of cardiovascular risk factors and LV mass assessed by echocardiography and cardiac magnetic resonance and normalized for height to allometric powers of 1.7 and 2.7 as continuous variableVariablesAssessed by ECHOAssessed by CMRModel 1∗LV mass normalized for height to the allometric power of 1.7.Model 2†LV mass normalized for height to the allometric power of 2.7.Model 3∗Model 4†LV mass normalized for height to the allometric power of 2.7.β (SE)Pβ (SE)pβ (SE)pβ (SE)pAge (years)0.11 (0.1)0.02‡Statistically significant p-values.0.10 (0.0)<0.01‡Statistically significant p-values.0.01 (0.1)0.800.03 (0.0)0.18Heart Rate (bmp)-0.01 (0.03)0.78-0.02 (0.0)0.33-0.02 (0.0)0.34-0.02 (0.0)0.08Resting systolic blood pressure (mmHg)0.13 (0.04)<0.01‡Statistically significant p-values.0.08 (0.0)<0.01‡Statistically significant p-values.0.17 (0.0)<0.01‡Statistically significant p-values.0.10 (0.0)<0.01‡Statistically significant p-values.Resting diastolic blood pressure (mmHg)-0.002 (0.1)0.970.002 (0.0)0.960.14 (0.1)<0.01‡Statistically significant p-values.0.08 (0.0)<0.01‡Statistically significant p-values.High risk of obstructive sleep apnea5.64 (0.99)<0.01‡Statistically significant p-values.3.12 (0.6)<0.01‡Statistically significant p-values.3.90 (0.6)<0.01‡Statistically significant p-values.2.20 (0.3)<0.01‡Statistically significant p-values.Body Mass Index (kg/m2)0.95 (0.1)<0.01‡Statistically significant p-values.0.51 (0.1)<0.01‡Statistically significant p-values.0.86 (0.1)<0.01‡Statistically significant p-values.0.46 (0.0)<0.01‡Statistically significant p-values.Smoker-2.62 (1.2)0.03‡Statistically significant p-values.-1.3 (0.7)0.05‡Statistically significant p-values.-1.11 (0.77)0.15-0.63 (0.4)0.15History of Heart Rhythm Problems-2.68 (1.2)0.02‡Statistically significant p-values.-1.48 (0.6)0.02‡Statistically significant p-values.-0.98 (0.75)0.19-0.57 (0.4)0.19Family History of cardiac problems3.26 (0.8)<0.01‡Statistically significant p-values.2.01 (0.5)<0.01‡Statistically significant p-values.0.07 (0.6)0.890.24 (0.5)0.44Low cardiorespiratory fitness3.24 (0.8)<0.01‡Statistically significant p-values.1.94 (0.5)<0.01‡Statistically significant p-values.1.53 (0.6)<0.01‡Statistically significant p-values.0.95 (0.3)<0.01‡Statistically significant p-values.Moderate to vigorous Physical Activity (min/week)-0.02 (0.0)<0.01‡Statistically significant p-values.-0.01 (0.0)<0.01‡Statistically significant p-values.-0.002(0.0)0.46-0.001 (0.0)0.28bpm = beats per minute; CMR = cardiac magnetic resonance; ECHO = echocardiography.∗ LV mass normalized for height to the allometric power of 1.7.† LV mass normalized for height to the allometric power of 2.7.‡ Statistically significant p-values. Open table in a new tab bpm = beats per minute; CMR = cardiac magnetic resonance; ECHO = echocardiography. In all 4 models evaluated, namely with LV mass assessed by ECHO or CMR and normalized with height to either 1.7 or 2.7, only BMI was consistently associated with LV mass in a statistically significant fashion (p <0.001) in all multivariate models. Final multivariate regression models showing the associations between the statistically and clinically significant predictors of LV mass are summarized in Table 3. A 1-unit decrease in BMI was associated with 1 unit (g/m1.7) reduction of LV mass/height1.7 after adjustment for age, obstructive sleep apnea risk, and cardiorespiratory fitness.Table 3Multivariate linear regression models of cardiovascular risk factors and LV mass assessed by echocardiography and cardiac magnetic resonance and normalized for height to allometric powers of 1.7 and 2.7 as continuous variableR2Assessed by ECHOAssessed by CMRModel 1∗LV mass normalized for height to the allometric power of 1.7.Model 2†LV mass normalized for height to the allometric power of 2.7.Model 3∗LV mass normalized for height to the allometric power of 1.7.Model 4†LV mass normalized for height to the allometric power of 2.7.0.1340.1250.2390.215β (SE)Pβ (SE)pβ (SE)pβ (SE)pAge (years)0.04 (0.1)0.520.07 (0.0)0.070.02 (0.0)0.560.04 (0.0)0.05High risk of obstructive sleep apnea0.76 (1.1)0.490.36 (0.6)0.570.15 (0.6)0.810.11 (0.4)0.76Body Mass Index (kg/m2)1.01 (0.1)<0.001‡Statistically significant p values.0.55 (0.1)<0.001‡Statistically significant p values.0.83 (0.1)<0.001‡Statistically significant p values.0.45 (0.0)<0.001‡Statistically significant p values.Low cardiorespiratory fitness-0.23 (1.0)0.83-0.34 (0.6)0.57-0.96 (0.6)0.10-0.70 (0.3)0.05CMR = cardiac magnetic resonance; ECHO = echocardiography.∗ LV mass normalized for height to the allometric power of 1.7.† LV mass normalized for height to the allometric power of 2.7.‡ Statistically significant p values. Open table in a new tab CMR = cardiac magnetic resonance; ECHO = echocardiography. The present cross-sectional study in US firefighters using ECHO and CMR measurements found BMI to be the strongest and most consistent independent predictor of LV mass indexed by height. In simple linear regression models, apart from BMI, the associations were highly statistically significant for high risk of obstructive sleep apnea, systolic blood pressure at rest, and low cardiorespiratory fitness consistently in all 4 models (p <0.01). In multivariate models, however, BMI was the only consistently significant predictor. Therefore, our study clearly supported BMI as a major determinant of LV mass. Given the epidemic level of obesity in the US fire service, it is not surprising that we found BMI to be the strongest predictor of LV mass in this population. This is consistent with the studies, which find obesity to be a risk factor for LV hypertrophy and increased cardiac mass.9Soteriades E.S. Targino M.C. Talias M.A. Hauser R. Kawachi I. Christiani D.C. Kales S.N. Obesity and risk of LVH and ECG abnormalities in US firefighters.J Occup Environ Med. 2011; 53: 867-871Crossref Scopus (17) Google Scholar, 10Soteriades E.S. Smith D.L. Tsismenakis A.J. Baur D.M. Kales S.N. Cardiovascular disease in US firefighters: a systematic review.Cardiol Rev. 2011; 19: 202-215Crossref PubMed Scopus (297) Google Scholar In addition, given that obesity is associated with cardiovascular disease (CVD) risk factor clustering,11Soteriades E.S. Hauser R. Kawachi I. Liarokapis D. Christiani D.C. Kales S.N. Obesity and cardiovascular disease risk factors in firefighters: a prospective cohort study.Obes Res. 2005; 13: 1756-1763Crossref PubMed Scopus (123) Google Scholar, 12Tsismenakis A.J. Christophi C.A. Burress J.W. Kinney A.M. Kim M. Kales S.N. The obesity epidemic and future emergency responders.Obesity (Silver Spring). 2009; 17: 1648-1650Crossref PubMed Scopus (100) Google Scholar it probably explains why other factors such as blood pressure and obstructive sleep apnea risk were weaker predictors because of their association with LV mass may be closely linked to their association or co-morbidity with obesity.13Kales S.N. Tsismenakis A.J. Zhang C. Soteriades E.S. Blood pressure in firefighters, police officers, and other emergency responders.Am J Hypertens. 2009; 22: 11-20Crossref PubMed Scopus (138) Google Scholar Given our previous findings that obesity-associated sudden cardiac death (SCD) among younger firefighters was largely driven by an increased cardiac mass in SCD victims compared with controls,14Yang J. Teehan D. Farioli A. Baur D.M. Smith D. Kales S.N. Sudden cardiac death among firefighters ≤45 years of age in the United States.Am J Cardiol. 2013; 112: 1962-1967Abstract Full Text Full Text PDF PubMed Scopus (76) Google Scholar our results reinforce that decreasing obesity in the fire service will lower the risk of LV hypertrophy and on-duty CVD events, particularly SCD. In agreement with findings that even small reductions on BMI may produce significant beneficial effects on metabolic syndrome and other CVD risk factors,15Mileski K.S. Leitao J.L. Lofrano-Porto A. Grossi Porto L.G. Health-related physical fitness in middle-aged men with and without metabolic syndrome.J Sports Med Phys Fitness. 2015; 55: 223-230Google Scholar, 16Elmer P.J. Obarzanek E. Vollmer W.M. Simons-Morton D. Stevens V.J. Young D.R. Lin P.H. Champagne C. Harsha D.W. Svetkey L.P. Ard J. Brantley P.J. Proschan M.A. Erlinger T.P. Appel L.J. Effects of comprehensive lifestyle modification on diet, weight, physical fitness, and blood pressure control: 18-month results of a randomized trial.Ann Intern Med. 2006; 144: 485-495Crossref PubMed Scopus (477) Google Scholar our results suggest that a 1-unit decrease in BMI will reduce LV mass index by 1 unit (g/m1.7). Our results may also support targeted noninvasive screening for LV hypertrophy with ECHO among obese firefighters. Based on the values of R2 for our final multivariate regression models, we were able to explain 12.5% to 13.4% of the variability of LV mass indexed by height to the allometric powers of 1.7 and 2.7 based on ECHO assessments and 21.5% to 23.9% based on CMR assessments. We were able to explain 10% more of the LV mass variability with the CMR models compared with ECHO ones, irrespective of the indexation technique. This is likely explained by CMR measurements that are more standardized across techniques and institutions and less dependent on operator's skill and experience, acoustic window adequacy, and LV mass geometric assumptions.3Armstrong A.C. Gidding S. Gjesdal O. Wu C. Bluemke D.A. Lima J.A. LV mass assessed by echocardiography and CMR, cardiovascular outcomes, and medical practice.JACC Cardiovasc Imaging. 2012; 5: 837-848Abstract Full Text Full Text PDF PubMed Scopus (217) Google Scholar, 17Celebi A.S. Yalcin H. Yalcin F. Current cardiac imaging techniques for detection of left ventricular mass.Cardiovasc Ultrasound. 2010; 8: 19Crossref Scopus (16) Google Scholar Our study has some modest limitations. Because of its cross-sectional design, we can only demonstrate associations and not causation; however, the findings are consistent with past studies18Mann C.J. Observational research methods. Research design II: cohort, cross sectional, and case-control studies.Emerg Med J. 2003; 20: 54-60Crossref PubMed Scopus (857) Google Scholar and are biologically plausible. In addition, because of the very small number of participating women firefighters in our study, only male participants were included in the present study. Our study also has a number of important strengths. We were able to collect comprehensive data on CVD risk factors from both medical examinations and a screening questionnaire. The BMI was measured during medical examinations, which avoided self-reporting biases. Obstructive sleep apnea risk was assessed by the widely used and validated Berlin Questionnaire, which has high sensitivity and specificity (86% and 77%, respectively) and demonstrates a high yield in public safety occupations.8Webber M.P. Lee R. Soo J. Gustave J. Hall C.B. Kelly K. Prezant D. Prevalence and incidence of high risk for obstructive sleep apnea in World Trade Center-exposed rescue/recovery workers.Sleep Breath. 2011; 15: 283-294Crossref PubMed Scopus (55) Google Scholar, 19Baur D.M. Christophi C.A. Tsismenakis A.J. Cook E.F. Kales S.N. Cardiorespiratory fitness predicts cardiovascular risk profiles in career firefighters.J Occup Environ Med. 2011; 53: 1155-1160Crossref PubMed Scopus (56) Google Scholar Moreover, we used imaging results for LV mass by both ECHO and CMR. Another important strength of our study is that we normalized LV mass by height to 2 different allometric powers, which allowed us to perform a more holistic assessment of its potential predictors. Furthermore, our results were consistent among the imaging methods and the indexing methods, making our findings more robust. Finally, our sample had similar anthropometric characteristics and CVD risk factors to those found in other epidemiologic studies of firefighters.11Soteriades E.S. Hauser R. Kawachi I. Liarokapis D. Christiani D.C. Kales S.N. Obesity and cardiovascular disease risk factors in firefighters: a prospective cohort study.Obes Res. 2005; 13: 1756-1763Crossref PubMed Scopus (123) Google Scholar, 12Tsismenakis A.J. Christophi C.A. Burress J.W. Kinney A.M. Kim M. Kales S.N. The obesity epidemic and future emergency responders.Obesity (Silver Spring). 2009; 17: 1648-1650Crossref PubMed Scopus (100) Google Scholar, 20Kales S.N. Polyhronopoulos G.N. Aldrich J.M. Leitao E.O. Christiani D.C. Correlates of body mass index in hazardous materials firefighters.J Occup Environ Med. 1999; 41: 589-595Crossref PubMed Scopus (54) Google Scholar Therefore, we believe that our results could be generalized to most male career firefighters. The authors would like to thank all the participating firefighters and the Indianapolis Fire Department; the staff and clinical leadership of the clinics who examined the firefighters; Dr. Carol Jisseth Zárate Ardila, MD and Dr. Konstantina Sampani, MD who helped with the data entry. The authors have no conflicts of interest to disclose.
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