Association between Cardiovascular and Musculoskeletal Health in Firefighters

Firefighters’ cardiovascular health and musculoskeletal health were found to be significantly associated, particularly blood lipid concentrations in relation to musculoskeletal injuries and discomfort. These results highlight the, possible, association between cardiovascular and musculoskeletal health which may be significant contributors to early retirement due to cardiovascular and musculoskeletal deterioration.

Objective

The aim of the study is to determine the association between cardiovascular health (CVH) and musculoskeletal health in firefighters.

Methods

This cross-sectional study involved 309 full-time firefighters aged 20 to 65 years. Cardiovascular health encompassed cardiovascular disease risk factors, risk scores, CVH metrics, and heart rate variability. Musculoskeletal health was assessed using two validated questionnaires.

Results

Increasing age (P = 0.004), body mass index (P < 0.001), body fat percentage (P < 0.001), diastolic blood pressure (P = 0.003), total cholesterol (P = 0.006), and Framingham risk score (P = 0.011) increased the risk of reporting musculoskeletal injuries (MSIs). Obesity (P = 0.018), hypertension (P = 0.034), and dyslipidemia (P = 0.005) increased the risk of reporting MSIs. Musculoskeletal discomfort was associated with total cholesterol (P = 0.0.34) and low-density lipoprotein (P = 0.014).

Conclusions

Adverse cardiovascular disease risk profile was associated with MSIs and musculoskeletal discomfort in firefighters. Firefighters should maintain an ideal CVH profile, especially as they age.

LEARNING OUTCOMES

After completing this research article, the learner will be better able to:

• Outline and discuss the association between cardiovascular health and musculoskeletal health among firefighters in the City of Cape Town Fire and Rescue Service.

• Outline the cardiovascular health parameters contributing most significantly to musculoskeletal injuries and musculoskeletal discomfort in firefighters.

• Differentiate the impact sociodemographic factors, such as age, sex, and years of experience, have on cardiovascular health in relation to musculoskeletal health in firefighters.

• Suggest ways to improve the cardiovascular and musculoskeletal parameters of firefighters to improve cardiovascular health and prevent work-related musculoskeletal injuries and discomfort.

Firefighting is a physically strenuous and hazardous occupation that involves firefighters placing themselves in life-threatening situations, where they are often exposed to hazardous chemicals and fumes and high temperatures.^1–3 During physically intense duty–related activity, firefighters often reach or even exceed their maximum age-predicted heart rates,^2,4 with many activities requiring forceful repetitive muscular contractions. This necessitates that firefighters maintain good cardiovascular and musculoskeletal health to assist in performing their duties with sufficient speed and efficiency.⁵

Studies have indicated that an alarming number of firefighters have several cardiovascular disease (CVD) risk factors and poor cardiovascular health (CVH) metrics, which significantly predisposes them to sustaining a sudden cardiac event while on active duty.^6–9 In addition, firefighters often sustain musculoskeletal injuries (MSIs) while performing fire suppression and other emergency duties.^10–13 Furthermore, many firefighters have mild-to-severe musculoskeletal discomfort (MSD), which limits their ability to perform their duties effectively.^14,15 Previous studies have shown that CVD risk factors and CVH metrics, such as obesity, aging, cigarette smoking, and physical activity, are related to MSIs and MSDs in firefighters.^15–17 In addition, it has been reported that with an increase in body mass index (BMI), firefighters are more susceptible to lower limb injuries, particularly those related to the knees and ankles, due to an increase in nonfunctional weight, commonly associated with high-fat mass.^11–13,18 Aging has been shown to be associated with reduced bone mineral density, connective tissue health, and skeletal muscle size and strength, compounding the negative effect of increased body mass on musculoskeletal health.^10,13 The association between other CVD risk factors, such as diabetes, dyslipidemia and hypertension, and musculoskeletal health (MSH), has been understudied in firefighters. However, studies in the general population have indicated that connective tissues, such as those found in the musculotendinous junctions, may respond similarly to vascular tissue, being susceptible to atherosclerotic lesions and predisposed to injury.^19,20 Moreover, the high blood glucose and cholesterol concentrations contribute to a proinflammatory state that may diminish tissue recovery and prolong the inflammatory responses.¹⁹ These inflammatory responses affect the autonomic nervous system function resulting in depressed heart rate variability (HRV).^21,22 Furthermore, a bidirectional relationship may exist between musculoskeletal health and CVH, as pain, discomfort, or injury may lead to a decrease in physical activity, leading to obesity, elevated blood pressure, and blood lipids.^23–25

Determining the association between CVH and MSH in firefighters may provide novel findings on the possible associations that may exist in this occupational population. Understanding the association may help better understand what is presumed to be a bidirectional relationship between CVH and MSH and lead to new theories about potential mediators of this relationship. Furthermore, because CVD risk factors are more often measured, these parameters may provide insight into the risk of injury. Firefighters are often required to exert maximum effort for extended durations, which may increase the risk of sudden cardiac events^1,2,26 and predisposes them to severe MSIs.^27–29 The establishment of an association between CVH and musculoskeletal health may assist in reducing the likelihood of morbidity and mortality commonly seen in this population. Therefore, the aim of this study was to determine the association between CVH and MSH in firefighters.

METHODS

Study Design and Population

This cross-sectional study used data on MSH (MSIs and MSD) and CVH (CVD risk factors, CVD risk score, HRV, CVH index) from a cohort of firefighters. Full-time male and female firefighters between the ages of 20 to 65 years from the City of Cape Town Fire and Rescue Service, South Africa, were included, after written informed consent. The study was approved by the Biomedical Research Ethics (BM21/10/9) Committee of the University of the Western Cape (South Africa). Approval was granted by the Chief Fire Officer, as well as the research and the Department of Policy and Strategy research branch of the City of Cape Town.

Sampling and Participant Recruitment

The City of Cape Town Fire and Rescue Service employs approximately 1000 full-time firefighters and using the finite population sample size calculation, a minimum sample size of 278 was needed to ensure the precision and the statistical power of the results. Firefighters excluded were those on administrative duty, on sick leave, employed part-time, or on a seasonal basis.

Data collection took place during the City of Cape Town Fire and Rescue Services annual physical fitness assessment, where firefighters from all 96 platoons (32 fire stations) were selected, using random systematic sampling. Using the sampling interval calculation, every third firefighter was recruited. In the instance where the selected participant declined to participate, the next participant was recruited. More specifically, for each day of testing, five to six platoons would be called to participate in the annual physical ability test. Each of the 96 platoons consisted of 8 to 12 firefighters.

Data Collection

A researcher-generated data collection sheet was used to record the sociodemographic, lifestyle, CVH, and musculoskeletal health information, as well as descriptive physical measures. The musculoskeletal health section was based on the Nordic Musculoskeletal Questionnaire³⁰ and Cornell Musculoskeletal Discomfort Questionnaire,³¹ and physical activity habits were gathered using the International Physical Activity Questionnaire,³² which has been shown to be reliable in a South African population.

Descriptive Measures

Stature, Body Mass, and Circumferences

For stature, firefighters were asked to stand barefoot on the level stadiometer base, with the heels together and the heels, buttocks, and upper back touching the stadiometer rod of a portable stadiometer (Seca model 700; Gmbh & Co, Germany). A Tanita© (Tanita©, Tokyo, Japan) BC-1000 Plus bioelectrical impedance analyzer was used to obtain body composition data, which included body mass (weight), fat mass, and body fat percentage (BF%). When taking body mass and BF%, firefighters were requested to wear minimal clothing, stand upright, barefoot, and stationary on the scale. Waist circumference was measured at the point of the belly button.³³ Hip circumference was taken at the level of the greatest posterior protuberance of the buttocks.

Blood Pressure

Blood pressure was measured using the Omron Healthcare, Inc, M6 comfort intelligence (Omron Healthcare Co, Ltd, Hoofddorp, the Netherlands) automatic blood pressure monitor. Firefighters were asked to remain in a quiet seated position for 5 minutes before testing, with the left arm elevated onto the testing table. The midline of the bladder of the blood pressure cuff was placed over the brachial artery to ensure accurate and consistent readings. The participants’ blood pressures were taken thrice, with at least 2-minute intervals between measures. The average of the three measurements was used as the final measurement.

Blood Tests

Total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, and nonfasting blood glucose (NFBG) concentrations were measured using a CardioChek® Plus analyzer (PTS Diagnostics, IN), which has been shown to be accurate and reliable within industry standards.³⁴ The test entailed a finger-prick, wherein the initial blood droplet was wiped off, and a second drop of blood was used for testing purposes.

Classification of CVH Parameters

In the current study, CVH was used as an umbrella term and investigated using several approaches. These approaches included three main subcomponents, those being CVD risk factors, CVH metrics and HRV. The subcomponents of CVD risk factors and CVH metrics have variables that overlap. The CVD risk factors include age, obesity, hypertension, dyslipidemia, diabetes, cigarette smoking, physical inactivity and family history. For CVH, the metrics included BMI, blood pressure, cholesterol, blood glucose, physical inactivity, cigarette smoking, and diet.

Cardiovascular Disease Risk Factors

Age, as a risk factor, was classified as males older than 45 years and females older than 55 years.³³ Obesity was classified as a BMI at or greater than 30 kg·m⁻², and central obesity was classified as a waist circumference more than 94 cm for men and more than 80 cm for women.³³ Hypertension was classified as systolic blood pressure (SBP) ≥140 mm Hg and/or diastolic blood pressure (DBP) ≥90 mm Hg or history of physician diagnosis.³³ Dyslipidemia was defined as a TC ≥5.18 mmol·L or previously confirmed by a physician, and diabetes was defined as random blood glucose ≥11.1 mmol·L or previously confirmed by a physician. Hypertriglyceridemia was classified as a triglyceride ≥1.70 mmol·L. Cigarette smoking was based on cigarette use in the last 6 months.³³ Physical inactivity was based on exercising less than 3 days a week for at least 30 minutes at a moderate intensity.³³ Physical activity was classified into three categories, namely, total low, moderate, and vigorous intensity weekly minutes. Weekly metabolic equivalents were calculated using the method described by the International Physical Activity Questionnaire, using the total minutes of low-, moderate-, vigorous-intensity activity. A positive family history was based on a history of myocardial infarction, coronary revascularization, or sudden cardiac death before 55 years in the father or other first-degree male relative, or before 65 years in the mother or first-degree female relative.³³

Cardiovascular Disease Risk Score

Framingham risk, lifetime, and 10-year atherosclerotic cardiovascular disease (ASCVD) were calculated to assess the cardiovascular risk of firefighters.³⁵ The Framingham risk score was used to assess the risk of coronary artery disease over a 10-year period in firefighters and included six risk factors, namely, age, gender, TC, HDL-C, cigarette smoking and SBP.³⁵ The 10-year ASCVD risk score was used to assess the CVD risk of firefighters older than 40 years, only, and estimated using SBP, DBP, TC, HDL-C, LDL-C, diabetes history, and smoking status.³⁶ For lifetime risk, all previous risk factors were included; however, only firefighters between the ages of 20 to 59 years were included.³⁷

Cardiovascular Health Metrics

The American Heart Association used these seven CVH metrics to classify individuals as having a good index for CVH or a poor index. The CVH index (CVHI) was inversely associated with all-cause mortality and cardiovascular events.^38,39 For this study, CVHI was classified as “poor” if two or fewer CVH metrics were classified as good, classified as “intermediate” if firefighters had three to four metrics classified as good, and classified as “good” if firefighters had five to seven metrics rated as good or ideal. The metrics used for the CVHI included BMI, blood pressure, TC, NFBG, physical activity, cigarette smoking, and diet. These factors had the same cutoff values as the CVD risk factors previously described in the section “cardiovascular disease risk factors.”^38,39 Diet was scored as good if four or five components were good, intermediate 2 to 3 components were good and poor if 0 to 1 components were good. The diet questions were based on the recommendations by the American Heart Association for a healthy diet and included questions on fruit and vegetable intake, a weekly serving of fish, fiber-rich whole grains, salt intake, and sugar intake.^38,39 There were five questions with each question with three questions having a total point score of three points and two questions with a total point score of four points accumulating to a total of 17 points.

Heart Rate Variability

Heart rate variability was measured at rest using the Polar™ (Polar Electro Oy, Kempele, Finland) H10 heart rate monitor. The equipment was moistened with room temperature water and fitted to the center of the participant’s chest, directly in line with the xiphoid process of the sternum. The participant was asked to maintain a quiet seated position for 5 minutes before the measurement was taken. The participant’s HRV was then recorded over a 5-minute period, following the 5-minute rest period, giving a total test time of 10 minutes. The HRV data were analyzed using the Kubio© Software version 3.4.3. The standard deviation of all normal-to-normal (NN) intervals (SDNN), root-mean-square of successive differences (RMSSD), low-frequency (LF), high-frequency (HF) ranges, and the ratio (LF/HF) was used as main outcome measures for HRV for this study.^40,41 The frequency band for LF ranged between 0.04 and 0.15 Hz and ranged between 0.15 and 0.40 for HF.

Classification of Musculoskeletal Health

Musculoskeletal health was subcategorized as MSI and MSD status. For MSI status, firefighters were categorized as those who sustained an injury while on duty during their time in the fire services based on their responses to the Nordic Musculoskeletal Questionnaire. Musculoskeletal discomfort status was classified as those firefighters that reported experiencing MSD in the past week, using the Cornell Musculoskeletal Discomfort Questionnaire.

Statistical Analysis

The data were analyzed using SPSS® software, version 28 (Chicago, IL). The Shapiro-Wilks test was used to test the distribution of the data, which were shown to be not normally distributed. Then, group comparisons were based on the Kruskal-Wallis test, because of the departure from a normal distribution of many variables. Continuous variables are summarized as the medians and 25th to 75th percentile. Univariable and multivariable logistic regressions were performed to determine the association between CVH parameters, which were treated as the independent variables, and MSH which designated the outcome variable. Cardiovascular health was analyzed using several approaches in logistic regressions, specifically as continuous cardiovascular measures (age, BMI, blood pressure, lipids, glucose, physical activity, HRV, and risk scores), traditional cardiovascular disease risk factors (age, obesity, dyslipidemia, diabetes, hypertension, cigarette smoking, physical inactivity, family history), CVD risk scores (Framingham risk score, lifetime, and 10-year ASCVD risk), CVH metrics (American Heart Association). The selection of exploratory variables was evidence based and selected based on previous research that consistently reported an association between MSIs and MSD in firefighters. Two models were selected to adjust for age and years of experience separately, to reduce collinearity. In model 2, covariates adjusted for included age, sex, and BMI (only nonadiposity-related measure) and in model 3 covariates adjusted for included years of experience, sex, and BMI (only nonadiposity-related measure). Moreover, to ensure collinearity was not present, all covariates had a correlation less than 0.5 and a VIF of less than 5. Variables not following a normal distribution were fractionally ranked and then normalized using the inverse DF, IDF.NORMAL transformation.⁴² A P value less than 0.05 was used to indicate statistical significance.

RESULTS

Table 1 shows the descriptive characteristics of firefighters overall and by sex. The median (IQR) age, height, and weight were 38.0 (18.0) years, 173.1 (9.9) cm, and 81.5 (18.0) kg, respectively. The males were taller (P < 0.001), heavier (P < 0.001), and had a higher BF% (P < 0.001), DBP (P = 0.003), triglyceride concentration (P < 0.001), and CVD risk scores (P < 0.001) when compared with females.

TABLE 1.

Descriptive Characteristics of Firefighters Overall and by Sex

	Total Firefighters		Males		Females
	n	X̃ (p25th–p75th)	n	X̃ (p25th–p75th)	n	X̃ (p25th–p75th)	P
Age, y	309	38.0 (30–48.0)	275	38.0 (30.0–48.0)	34	39.0 (30.0–45.0)	0.786
Years of experience, y	309	14.0 (5.0–22.0)	275	14.0.0 (5.0–23.0)	34	14.0 (5.0–17.3)	0.252
Height, cm	309	173.1 (168.1–177.9)	275	174 (170.5–178.3)	34	162.9 (158.1–167.0)	<0.001**
Weight, kg	309	81.5 (72.5–90.5)	275	82.4 (73.9–91.0)	34	73.2 (63.1–81.0)	<0.001**
BMI, kg·m−2	309	27.1 (24.1–30.4)	275	27.0 (24.2–30.1)	34	28.4 (23.4–31.9)	0.264
Waist circumference, cm	309	93.0 (84.3–101.0)	275	93.5 (85.0–103.0)	34	86.8 (77.8–98.2)	0.002**
BF%, %	309	20.2 (14.9–27.2)	275	19.0 (14.2–24.0)	34	34.3 (27.6–40.8)	<0.001**
SBP, mm Hg	309	137.3 (125.0–145.5)	275	137.5 (126.7–146.7)	34	127.5 (115.7–141.0)	0.003**
DBP, mm Hg	309	81.7 (74.2–90.8)	275	81.7 (74.0–90.5)	34	82.3 (74.2–92.6)	0.710
NFBG, mmol·L−1	309	5.4 (4.9–6.2)	275	5.4 (4.9–6.2)	34	5.4 (4.8–6.1)	0.970
TC, mmol·L−1	309	4.6 (3.9–5.4)	275	4.6 (3.9–5.4)	34	4.8 (3.9–5.4)	0.835
LDL-C, mmol·L−1	309	2.6 (2.1–3.4)	275	2.6 (2.1–3.4)	34	2.8 (2.0–3.3)	0.705
HDL, mmol·L−1	309	1.2 (1.0–1.4)	275	1.2 (1.0–1.4)	34	1.5 (1.3–1.7)	<0.001**
Triglycerides, mmol·L−1	309	1.4 (0.9–2.2)	275	1.5 (0.9–2.2)	34	0.9 (0.7–1.7)	<0.001**
Diet score	309	10.0 (8.0–11.0)	275	9.0 (8.0–11.0)	34	10.0 (9.0–12.0)	0.186
Physical activity level
TLIPAM, min	309	123.0 (60.0–360.0)	275	120 (60.0–300.0)	34	120.0 (75.0–540.0)	0.473
TMIPAM, min	309	420.0 (240.0–660.0)	275	420 (240.0–660.0)	34	360.0 (90.0–540.0)	0.170
TVIPAM, min	309	340.0 (180.0–720.0)	275	310.0 (180.0–720.0)	34	405.0 (150.0–885.0)	0.915
TWMETM	309	2397.0 (1320.0–4416.0)	275	2400.0 (1320.0–4464.0)	34	2080.0 (1320.0–3879.0)	0.663
Cardiovascular disease risk score
Lifetime ASCVD risk score	303	5.5 (2.4–9.9)	275	5.1 (3.2–10.6)	33	0.8 (0.5–1.1)	<0.001**
Framingham risk	309	1.1 (0.2–5.9)	275	0.6 (0.3–6.3)	34	0.2 (0.0–0.5)	<0.001**
ASCVD risk scorea	138	50.0 (39.0–50.0)	123	50.0 (46.0–50.0)	15	39.0 (27.0–39.0)	<0.001**
Heart rate variability
HRV, ms	304	713.5 (628.3–821.5)	270	716.0 (632.0–826.3)	34	690.0 (619.5–817.0)	0.326
SDNN, ms	304	32.5 (21.5–46.5)	270	32.6 (21.7–46.7)	34	28.2 (19.2–44.1)	0.514
RMSSD, ms	304	22.6 (13.8–37.6)	270	22.65 (13.9–37.6)	34	21.9 (12.4–39.0)	0.802
LF, Hz	304	0.09 (0.07–0.11)	270	0.09 (0.07–0.11)	34	0.08 (0.06–0.09)	0.034*
HF, Hz	304	0.18 (0.16–0.22)	270	0.17 (0.16–0.21)	34	0.19 (0.16–0.29)	0.075
LF/HF ratio, Hz	304	2.90 (1.6–5.1)	270	2.9 (1.7–5.5)	34	2.6 (1.4–3.9)	0.089
Musculoskeletal discomfortbc	130	4.8 (3.0–20.0)	112	4.5 (1.5–20.0)	18	9.5 (3.0–20.0)	0.467
Neck	34	3.0 (1.5–6.0)	31	3.0 (1.5–6.0)	3	1.5 (1.5)	0.645
Shoulder	43	4.5 (2.0–10.0)	42	4.5 (2.0–10.0)	1	1.5 (1.5–1.5)	0.186
Upper back	25	5.0 (2.0–6.0)	22	4.3 (1.9–6.0)	3	6.0 (3.0)	0.353
Upper arm	21	3.5 (2.0–6.0)	21	3.5 (1.9–6.0)	0	—	—
Forearm and elbow	24	4.5 (2.0–6.0)	23	3.0 (2.0–6.0)	1	60.0 (60.0–60.0)	0.083
Wrist and hand	32	6.0 (1.5–6.0)	30	6.0 (1.5–6.0)	2	5.8 (1.5)	0.901
Low back	72	3.0 (1.6–6.0)	64	3.0 (1.5–6.0)	8	5.5 (3.0–9.8)	0.353
Hip and buttocks	20	6.0 (2.0–6.0)	18	6.0 (2.0–6.0)	2	20.8 (1.5)	0.947
Thigh	19	3.5 (2.0–6.0)	19	3.5 (2.0–6.0)	0	—	—
Knee	48	3.0 (1.5–6.0)	43	3.0 (1.5–6.0)	5	3.5 (2.3–30.5)	0.246
Lower leg	19	3.5 (2.0–6.0)	18	2.8 (1.9–6.0)	1	10.0 (10.0–10.0)	0.211
Foot and ankle	29	2.0 (1.5–6.0)	25	3.0 (1.5–6.0)	4	1.5 (1.5–2.6)	0.124
Musculoskeletal injuries, n (%)d	130 (42.1)		110 (40.0)		20 (58.8)
Neck, n (%)	10 (3.2)		8 (2.9)		2 (5.9)
Shoulder, n (%)	17 (5.5)		14 (5.1)		3 (8.8)
Upper back, n (%)	7 (2.3)		7 (2.5)		0 (0)
Forearm and elbow, n (%)	3 (0.9)		3 (1.1)		0 (0)
Wrist and hand, n (%)	12 (3.9)		10 (3.6)		2 (5.9)
Lower back, n (%)	24 (7.8)		22 (8.0)		2 (5.9)
Hip and buttocks, n (%)	4 (1.3)		4 (1.5)		0 (0)
Thigh, n (%)	3 (1)		3 (1.1)		0 (0)
Knee, n (%)	31 (10.0)		24 (8.7)		0 (0)
Lower leg, n (%)	1 (0.3)		1 (0.4)		2 (5.9)
Ankle and foot, n (%)	39 (12.6)		31 (11.3)		8 (23.5)

*Indicates statistical significance <0.05.

**Indicates statistical significance <0.01.

^aThe ASCVD risk score calculated for firefighters older than 40 years, only.

^bMusculoskeletal discomfort did not include injury data.

^cIndicates that only firefighters reported experiencing musculoskeletal discomfort.

^dIndicates only firefighters who reported a musculoskeletal injury.

X̃, median; BF%, body fat percentage; BMI, body mass index; DBP, diastolic blood pressure; HDL, high-density lipoprotein; HF, high frequency; HRV, heart rate variability; LDL-C, low-density lipoprotein; LF, low frequency; LF/HF, low- and high-frequency ratio; NFBG, nonfasting blood glucose; p_25th–p_75th, 25th percentile to 75th percentile; RMSSD, root-mean-square of successive differences; SBP, systolic blood pressure; SDNN, standard deviation of all normal-to-normal; TC, total cholesterol; TLIPAM, total low-intensity physical activity minutes; TMIPAM, total moderate-intensity physical activity minutes; TVIPAM, total vigorous-intensity physical activity minutes; TWMETM, total weekly metabolic equivalent minute.

Table 2 describes the CVH values for firefighters with and without MSI or MSD. Never-injured firefighters were younger (P = 0.002), had fewer years of experience (P < 0.001), and weighed less (P = 0.008). In addition, BMI (P = 0.002), waist circumference (P = 0.008), BF% (P < 0.001), SBP (P = 0.035), DBP (P = 0.001), TC (P = 0.004), LDL-C (P = 0.009), triglycerides (P = 0.042), Framingham risk score (P = 0.002), and LF range (p 0.042) was different between injured and noninjured firefighters. Total cholesterol (P = 0.034), LDL-C (P = 0.009), SDNN (P = 0.006), and RMSSD (P = 0.004) were significantly different between firefighters experiencing musculoskeletal discomfort and those without.

TABLE 2.

Differences between CVH and Musculoskeletal Health in Firefighters

	Injured			Never Injured		Musculoskeletal Discomfort		Without Discomfort
	n	X̃ (p25th–p75th)	n	X̃ (p25th–p75th)	P	n	X̃ (p25th–p75th)	n	X̃ (p25th–p75th)	P
Age, y	130	42.0 (32.0–49.0)	178	36.0 (29.0–46.0)	0.002**	130	39.0 (32.0–46.5)	179	37.0 (29.0–48.0)	0.478
Years of experience, y	130	17.0 (7.0–25.0)	178	11.0 (4.0–19.0)	<0.001**	130	15.0 (6.8–22.3)	179	13.0 (5.0–22.0)	0.219
Height, cm	130	172.9 (167.5–178.0)	178	173.5 (169.0–177.9)	0.765	130	173.0 (168.4–178.0)	179	173.3 (168.0–177.9)	0.707
Weight, kg	130	82.4 (74.0–95.9)	178	80.8 (72.1–87.5)	0.008**	130	80.7 (71.9–91.6)	179	82.0 (73.0–90.1)	0.942
BMI, kg·m−2	130	27.6 (25.1–31.7)	178	26.8 (23.9–29.6)	0.002**	130	27.0 (24.5–31.1)	179	27.2 (23.9–30.2)	0.469
WC, cm	130	95.0 (86.9–104.3)	178	90.8 (83.0–100.0)	0.008**	130	93.5 (84.0–101.0)	179	91.5 (84.5–101.5)	0.770
BF%, %	130	22.1 (16.7–28.3)	178	18.3 (13.7–24.7)	<0.001**	130	21.3 (14.9–28.5)	179	19.5 (14.6–25.9)	0.118
SBP, mm Hg	130	140.0 (128.3–146.0)	178	134.5 (123.2–145.1)	0.035*	130	139.0 (128.4–145.4)	179	136.3 (124.3–146.0)	0.200
DBP, mm Hg	130	85.0 (77.5–92.4)	178	79.7 (72.5–88.5)	0.001**	130	81.8 (73.7–91.1)	179	81.7 (74.7–90.0)	0.853
NFBG, mmol·L−1	130	5.4 (4.9–6.1)	178	5.4 (4.9–6.2)	0.999	130	5.4 (4.8–6.1)	179	5.4 (5.0–6.3)	0.183
TC, mmol·L−1	130	4.9 (4.1–5.6)	178	4.4 (3.8–5.2)	0.004**	130	4.8 (4.1–5.6)	179	4.5 (3.9–5.2)	0.034*
LDL-C, mmol·L−1	130	2.8 (2.2–3.5)	178	2.5 (2.0–3.2)	0.030*	130	2.8 (2.3–3.5)	179	2.5 (1.9–3.3)	0.009**
HDL-C, mmol·L−1	130	1.2 (1.0–1.4)	178	1.2 (1.0–1.4)	0.690	130	1.2 (1.0–1.4)	179	1.2 (1.1–1.4)	0.939
Triglycerides, mmol·L−1	130	1.6 (0.9–2.2)	178	1.3 (0.9–1.4)	0.042*	130	1.4 (0.8–2.2)	179	1.4 (0.9–2.2)	0.482
Diet score	130	10.0 (8.0–11.0)	178	10.0 (8.8–11.0)	0.961	130	10.0 (9.0–11.0)	179	10.0 (8.0–11.0)	0.358
TLIPAM, min	130	120.0 (60.0–345.0)	178	145.0 (62.5–360.0)	0.372	130	130.0 (60.0–360.0)	179	120.0 (60.0–360.0)	0.512
TMIPAM, min	130	360.0 (240.0–660.0)	178	480.0 (215.0–660.0)	0.281	130	380.0 (210.0–630.0)	179	480.0 (240.0–700.0)	0.463
TVIPAM, min	130	240.0 (180.0–720.0)	178	360.0 (180.0–720.0)	0.004**	130	360 (180.0–720.0)	179	320.0 (180.0–720.0)	0.060
TWMETM, MET·Min	130	2080.0 (1202.5–3699.0)	178	2580.0 (1578.0–5310.0)	0.589	130	2080.0 (2607)	179	2655.0 (1440.0–4986)	0.474
Cardiovascular disease risk score
Lifetime ASCVD risk score	129	50.0 (46–50.0)	175	50.0 (36.0–50.0)	0.365	129	50.0 (42.5–50.0)	175	46.0 (36.0–50.0)	0.284
Framingham risk score	129	2.6 (0.5–6.8)	180	0.8 (0.1–5.2)	0.002**	130	2.0 (0.5–5.9)	179	0.7 (0.1–5.9)	0.203
ASCVD risk scorea	70	5.3 (2.5–9.9)	67	5.5 (2.3–9.8)	0.973	63	4.9 (2.3–8.0)	75	6.2 (2.6–10.6)	0.058
Heart rate variability
Heart rate variability, ms	128	723.0 (637.0–825.0)	176	708.5 (612.0–820.5)	0.293	128	722.5 (647.0–829.0)	175	701.0 (610.5–817.8)	0.054
SDNN, ms	128	29.8 (21.5–44.9)	176	33.2 (20.4–48.1)	0.450	128	35.0 (23.9–49.6)	175	29.4 (19.0–43.5)	0.006**
RMSSD, ms	128	22.0 (13.9–35.6)	176	22.9 (13.8–40.2)	0.897	128	27.2 (16.2–41.8)	175	21.2 (12.3–35.0)	0.004**
LF, Hz	128	0.09 (0.06–0.10)	176	0.09 (0.07–0.11)	0.041*	128	0.09 (0.07–0.10)	175	0.09 (0.07–0.11)	0.489
HF, Hz	128	0.17 (0.16–0.22)	176	0.18 (0.16–0.22)	0.664	128	0.18 (0.16–0.21)	175	0.18 (0.16–0.22)	0.336
LF/HF ratio, Hz	128	2.9 (1.6–5.1)	176	2.8 (1.7–5.4)	0.688	128	2.6 (1.5–4.5)	175	2.9 (1.8–5.4)	0.075

*Indicates statistical significance <0.05.

**Indicates statistical significance <0.01.

^aThe ASCVD risk score calculated for firefighters older than 40 years, only.

X̃, median; ASCVD, atherosclerotic cardiovascular disease; BMI, body mass index; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; HF, high frequency; LDL-C, low-density lipoprotein; LF, low frequency; LF/HF, low- and high-frequency ratio; NFBG, nonfasting blood glucose; p_25th–p_75th, 25th percentile to 75th percentile; RMSSD, root-mean-square of successive differences; SBP, systolic blood pressure; SDNN, standard deviation of all normal-to-normal; TC, total cholesterol; TLIPAM, total low-intensity physical activity minutes; TMIPAM, total moderate-intensity physical activity minutes; TVIPAM, total vigorous-intensity physical activity minutes; TWMETM, total weekly metabolic equivalent minute; WC, waist circumference.

Table 3 describes the association between CVH (CVD risk factors, risk score, CVH metrics, and HRV) and MSI status in firefighters. For every 1-year increase in age and years of experience and firefighters that were of female sex, increased the risk of MSI by a factor of 1.03 (P = 0.004), 1.04 (P < 0.001), and 2.19 (P = 0.033), respectively. A 1-unit increase in BMI and BF% and TC was associated with an increase in the risk of MSI by a factor of 1.09 (P < 0.001), 1.05 (P < 0.001), and 1.27 (P = 0.011), respectively. In the multivariate analysis, after adjustment for years of experience and BMI, the female sex was associated with a risk of MSI that was 2.30 greater compared with males (P = 0.031). In addition, as BMI and BF% increased by 1 kg·m⁻² and 1%, the risk of MSI increased by a factor of 1.07 (P = 0.023) and 1.03 (P = 0.044), respectively. Obesity and a high BF% increased the risk of MSI by a factor of 1.84 (P = 0.018) and 1.95 (P = 0.034), respectively. Hypertension, dyslipidemia and hypertriglyceridemia increased the risk of MSI by a factor of 1.64 (P = 0.034), 1.98 (P = 0.005), and 1.81 (P = 0.013), respectively. In addition, poor CVHI increased the risk of MSI by a factor of 1.62 (P = 0.049) and a good CVHI decreased the risk of MSI by a factor of 0.41 (P = 0.037).

TABLE 3.

Association between CVH and Musculoskeletal Injuries in Firefighters

	Univariable Modelsa		Multivariable Modelsb
	Model 1		Model 2c		Model 3d
	OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)	P
Intercept (null model)	−0.341
General characteristics e
Age, y	1.03 (1.01–1.06)	0.004**	—	—	0.99 (0.94–1.04)	0.538
Sex (females)	2.19 (1.06–4.53)	0.033*	2.11 (0.99–4.47)	0.051	2.30 (1.08–4.90)	0.031*
Years of experience, y	1.04 (1.02–1.06)	<0.001**	1.04 (0.99–1.09)	0.100	—	—
CVH parameterse
BMI, kg·m−2f	1.09 (1.04–1.15)	<0.001**	1.07 (1.02–1.13)	0.012*	1.07 (1.01–1.13)	0.023*
Waist circumference, cmf	1.03 (1.01–1.04)	0.006**	1.02 (0.99–1.04)	0.090	0.99 (0.95–1.03)	0.532
BF%, %f	1.05 (1.02–1.07)	<0.001**	1.03 (1.00–1.06)	0.046*	1.03 (1.00–1.06)	0.030
SBP, mm Hg	1.01 (0.99–1.03)	0.067	—	—	—	—
DBP, mm Hg	1.03 (1.01–1.05)	0.003**	1.02 (0.99–1.04)	0.125	1.02 (0.99–1.04)	0.135
NFBG, mmol·L−1	1.01 (0.86–1.18)	0.941	—	—	—	—
TC, mmol·L−1	1.28 (1.07–1.54)	0.009**	1.18 (0.97–1.44)	0.094	1.17 (0.96–1.42)	0.119
LDL-C, mmol·L−1	1.23 (0.99–1.53)	0.056	—	—	—	—
HDL, mmol·L−1	1.14 (0.63–2.05)	0.676	—	—	—	—
Triglycerides, mmol·L−1	1.21 (0.98–1.49)	0.077	—	—	—	—
Diet score	1.01 (0.91–1.13)	0.841	—	—	—	—
Framingham risk score	1.27 (1.06–1.53)	0.011*	1.05 (0.97–1.13)	0.238	1.03 (0.96–1.10)	0.446
Weekly MET minutes	0.69 (0.39–1.21)	0.197	—	—	—	—
Heart rate variability e
Heart rate variability, ms	1.00 (0.99–1.00)	0.421	—	—	—	—
SDNN, ms	0.99 (0.99–1.01)	0.512	—	—	—	—
RMSSD, ms	1.00 (0.99–1.01)	1.000	—	—	—	—
LF, Hz	0.00 (0.00–1.47)	0.061	—	—	—	—
HF, Hz	0.50 (0.01–19.49)	0.714	—	—	—	—
LF/HF ratio, Hz	0.99 (0.94–1.04)	0.694	—	—	—	—
CVD risk factors and CV health metricsg
Age	0.71 (0.44–1.17)	0.179	—	—	—	—
Obesityf	1.84 (1.11–3.04)	0.018*	0.67 (0.29–1.54)	0.343	0.67 (0.29–1.56)	0.358
Central obesityf	1.45 (0.92–2.28)	0.112	—	—	—	—
High BF%f	1.95 (1.17–3.23)	0.010*	1.02 (0.52–1.00)	0.953	1.02 (0.52–1.99)	0.964
Hypertension	1.64 (1.04–2.59)	0.034*	1.01 (0.99–1.03)	0.320	1.01 (0.99–1.03)	0.340
Diabetes	1.09 (0.39–3.03)	0.855	—	—	—	—
Dyslipidemia	1.98 (1.23–3.18)	0.005**	1.56 (0.93–2.59)	0.091	1.49 (0.89–2.49)	0.126
High LDL-C	1.56 (0.94–2.57)	0.085	—	—	—	—
High HDL-C	0.85 (0.49–1.49)	0.569	—	—	—	—
Hypertriglyceridemia	1.81 (1.14–2.88)	0.013*	1.62 (0.97–2.69)	0.063	1.61 (0.97–2.68)	0.067
Physical inactivity	1.29 (0.79–2.08)	0.299	—	—	—	—
Cigarette smoking	1.13 (0.71–1.82)	0.608	—	—	—	—
Diet	1.14 (0.68–1.89)	0.615	—	—	—	—
Family history	1.68 (0.96–2.95)	0.068	—	—	—	—
Poor CVH index	1.62 (1.00–2.62)	0.049*	1.26 (0.75–2.14)	0.383	1.25 (0.74–2.13)	0.403
Good CVH index	0.41 (0.18–0.95)	0.037*	0.45 (0.17–1.19)	0.108	0.44 (0.16–1.15)	0.093

*Indicates statistical significance <0.05.

**Indicates statistical significance <0.01.

^aUnivariable models using binary logistic regression.

^bEvidence-based explanatory variables reported to be significantly related to musculoskeletal injuries were entered into the same multivariable model.

^cCovariates: age, sex, BMI.

^dCovariates: years of experience, sex, BMI.

^eContinuous variables.

^fBody mass index removed from model.

^gDichotomous categorical variables indicating positive CVD risk factors and poor CVH metrics.

BF%, body fat percentage; BMI, body mass index; CI, confidence interval; CVH, cardiovascular health; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; HF, high frequency; LDL-C, low-density lipoprotein cholesterol; LF, low frequency; LF/HF, low- and high-frequency ratio; MET, metabolic equivalents; NFBG, nonfasting blood glucose; OR, odds ratio; RMSSD, root mean square of successive differences; SBP, systolic blood pressure; SDNN, standard deviation of all normal-to-normal; TC, total cholesterol.

Table 4 presents the association between CVH (CVD risk factors, risk score, CVH metrics, and HRV) and MSD in firefighters. Univariable analysis indicated that every 1-unit increase in TC and LDL-C increased the odds of MSD by a factor of 1.22 (P = 0.034) and 1.32 (P = 0.014), respectively. Every 1-unit increase in SDNN and RMSSD increased the odds of MSD by a factor of 1.02 (P = 0.010) and 1.01 (P = 0.008), respectively. In the multivariable analyses, after adjustment for age, sex and BMI, for every 1-unit increase in TC and LDL-C, the odds of MSD increased by a factor of 1.22 (P = 0.044) and 1.32 (P = 0.018), respectively, and after adjustment for years of experience, sex and BMI, every 1-unit increase in LDL-C, the odds of MSD increased by a factor of 1.03 (P = 0.028). Similarly, after adjustment for age, sex, and BMI, the odds of MSD increased by a factor of 1.02 (P = 0.002) and 1.02 (P = 0.002), for every 1-unit increase in SDNN and RMSSD, respectively, and after adjustment for years of experience, sex, and BMI, every 1 unit increase in SDNN and RMSSD increased the odds of MSD by a factor of 1.02 (P = 0.001) and 1.02 (P = 0.001), respectively.

TABLE 4.

Association between CVH and Musculoskeletal Discomfort in Firefighters

	Univariable Modelsa		Multivariable Modelsb
	Model 1		Model 2c		Model 3d
	OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)	P
Intercept (null model)	−0.326
General characteristicse
Age, y	1.01 (0.98–1.03)	0.666	—	—	—	—
Sex (females)	1.64 (0.80–3.35)	0.177	—	—	—	—
Years of experience	1.01 (0.99–1.03)	0.290	—	—	—	—
CVH parameterse
BMI, kg·m−2	1.03 (0.98–1.08)	0.280	—	—	—	—
Waist circumference, cm	1.00 (0.99–1.02)	0.657	—	—	—	—
Body fat percentage (%)	1.02 (0.99–1.05)	0.084	—	—	—	—
SBP, mm Hg	1.01 (0.99–1.03)	0.184	—	—	—	—
DBP, mm Hg	1.01 (0.99–1.03)	0.603	—	—	—	—
NFBG, mmol·L−1	0.89 (0.76–1.06)	0.193	—	—	—	—
TC, mmol·L−1 c	1.22 (1.02–1.46)	0.034*	1.22 (1.01–1.48)	0.044*	1.19 (0.99–1.44)	0.070
LDL-C, mmol·L−1 c	1.32 (1.06–1.64)	0.014*	1.32 (1.05–1.66)	0.018*	1.03 (1.03–1.62)	0.028*
HDL-C, mmol·L−1	1.08 (0.59–1.94)	0.810	—	—	—	—
Triglycerides, mmol·L−1	0.90 (0.74–1.11)	0.339	—	—	—	—
Diet score	1.05 (0.94–1.17)	0.382	—	—	—	—
Framingham risk score	1.03 (0.99–1.08)	0.141	—	—	—	—
Weekly MET minutes	0.64 (0.36–1.12)	0.121	—	—	—	—
Heart rate variabilitye
Heart rate variability	1.00 (1.00–1.00)	0.071	—	—	—	—
SDNN c	1.02 (1.00–1.03)	0.010*	1.02 (1.01–1.03)	0.002**	1.02 (1.01–1.03)	0.001**
RMSSD c	1.01 (1.00–1.02)	0.008**	1.02 (1.01–1.03)	0.002**	1.02 (1.01–1.03)	0.001**
LF	0.06 (0.00–437.13)	0.534	—	—	—	—
HF	0.08 (0.00–3.24)	0.182	—	—	—	—
LF/HF ratio	0.95 (0.90–1.01)	0.077	—	—	—	—
CVD risk factors and CV health metricsf
Age	0.87 (0.53–1.43)	0.593	—	—	—	—
Obesity	1.13 (0.68–1.86)	0.640	—	—	—	—
Central obesity	1.12 (0.71–1.76)	0.627	—	—	—	—
High BF%	1.47 (0.89–2.44)	0.132	—	—	—	—
Hypertension	1.14 (0.72–1.79)	0.577	—	—	—	—
Diabetes	0.44 (0.14–1.40)	0.166	—	—	—	—
Dyslipidemia	1.35 (0.84–2.16)	0.215	—	—	—	—
High LDL-C	1.32 (0.80–2.19)	0.275	—	—	—	—
Low HDL-C	1.45 (0.83–2.50)	0.189	—	—	—	—
Hypertriglyceridemia	1.39 (0.88–2.21)	0.160	—	—	—	—
Physical inactivity	1.14 (0.71–1.83)	0.584	—	—	—	—
Cigarette smoking	1.30 (0.81–2.09)	0.271	—	—	—	—
Diet	0.73 (0.44–1.23)	0.241	—	—	—	—
Family history	1.02 (0.59–1.75)	0.957	—	—	—	—
Poor CVH index	1.39 (0.86–2.25)	0.177	—	—	—	—
Good CVH index	0.73 (0.35–1.53)	0.398	—	—	—	—

*Indicates statistical significance <0.05.

**Indicates statistical significance <0.01.

^aUnivariable models using binary logistic regression.

^bEvidence-based explanatory variables reported to be significantly related to musculoskeletal discomfort were entered into the same multivariable model.

^cCovariates: age, sex, BMI.

^dCovariates: years of experience, sex, BMI.

^eContinuous variables.

^fDichotomous categorical variables indicating positive CVD risk factors and poor cardiovascular health metrics.

BF%, body fat percentage; BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; CVH, cardiovascular health; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; HF, high frequency; LDL-C, low-density lipoprotein cholesterol; LF, low frequency; LF/HF, low- and high-frequency ratio; MET, metabolic equivalents; NFBG, nonfasting blood glucose; OR, odds ratio; RMSSD, root-mean-square of successive differences; SBP, systolic blood pressure; SDNN, standard deviation of all normal-to-normal; TC, total cholesterol.

DISCUSSION

The aim of this study was to determine the association between CVH and MSH in firefighters. The results indicated an increase in the odds of firefighters reporting MSIs among those with prevalent CVD risk factors and poor health metrics, particularly related to aging, obesity, hypertension, and dyslipidemia. Previous studies indicated that aging and obesity were significantly related to an increase in injuries in firefighters.^10,11,13,15 This may be due to the progressive deterioration in connective tissue health, which may also be related to a reduction in physical activity levels commonly seen in older firefighters.^10,13,43 In addition, it is likely that older firefighters are more physically inactive²⁴ and thus have a lower cardiorespiratory fitness level,^23,24 predisposing them to injury.¹⁸ This may, somewhat, explain why more physically active firefighters were associated with lower of MSIs in firefighters in previous studies.^10,12,44

The results indicated that both TC and LDL-C were associated with an increase in reporting of MSIs and MSD and that hypertriglyceridemia was associated with reporting of MSIs, only. This positive association between lipid profiles and MSIs is supported by a systematic review conducted by Tilley et al.²⁰ who reported that an increase in TC and LDL-C was related to an increase in the likelihood of reported tendon pathologies.²⁰ The study suggested that tendons respond similarly to arteries regarding their metabolic environments and, as such, are prone to atherosclerotic lesion development due to shear and compression forces, precipitating cholesterol and fatty acid deposition and plaque build-up.²⁰ This, in turn, predisposes the area to injuries, such as sudden tendon rupture.^19,20 In addition, Tilley et al.²⁰ noted that participants with an altered lipid profile reported more MSD than those with normal lipid profiles. In the present study, firefighters used statins as a treatment for their dyslipidemia, which has been associated with increased symptoms of MSD and pain,¹⁷ providing an additional explanation for the association between dyslipidemia and MSD seen in the present study. A study by Squier et al.¹⁹ noted that hypercholesteremia altered Achilles tendon biomechanics and increased the risk for injuries, due to abnormal loading. Altered force distribution, particularly in firefighters who are often required to move in awkward positions,^45,46 may predispose them to injury. Moreover, altered force distribution in tendons may also predispose firefighters to pain and discomfort due to the uneven loading.

Arteries and tendons have a similar collagen makeup,^19,20 and because of this, it is likely that other major CVD risk factors may have a similar effect on the progressive development of atherosclerotic plaque within tendons.⁴⁷ This may provide a hypothetical explanation for DBP increasing the likelihood of MSIs in firefighters, as blood pressure is a significant factor in the development of atherosclerotic plaque in arteries.^48,49 The results of the present study indicated that the Framingham risk score and poor CVHI increased the odds of MSIs by 27% and 62%, respectively. As these risk scores are predictive of risk for atherosclerotic diseases, this relationship may help explain the association between these measures and MSIs.^17,19,20,50 Moreover, several factors included in the Framingham risk score and CVHI were independently associated with an increased likelihood of injury in the current results, making the cumulative CVD risk scores association with MSIs unsurprising. In addition, a good CVHI reduced the odds of MSIs by 41% in firefighters. Healthier and younger firefighters may, overall, have better cardiovascular and musculoskeletal health, likely reducing the likelihood of injury, which has been noted in previous studies.^11–13

An augmenting factor to the reporting of MSIs and MSDs may be BMI and BF%, as previous studies have shown that heavier firefighters are particularly susceptible to lower limb injuries,^11,12 and may be a result of the combination of the factors (age, TC, LDL-C, triglycerides) noted in the present study. The increase in nonfunctional mass, commonly seen in obese firefighters, may add additional strain to already susceptible tendons, exacerbating the risk for sudden tendon ruptures considerably.^11–13 In addition, firefighters who are physically inactive, and are required to perform physically strenuous duties, particularly those that are obese with underlying cholesterol issues, may be especially susceptible to sudden tendon sprain.^11–13

We found that increased SDNN and RMSSD were associated with an increased likelihood of MSD in firefighters. Chuang et al.²² noted that a direct relationship between musculoskeletal pain and SDNN and RMSSD existed, where a decreased in MSD caused a subsequent increase in SDNN and RMSSD. However, the current results are in contrast to Chuang et al.,²² where it was found as MSD decreased, SDNN and RMSSD decreased and, in particular, those participants that reported high levels of MSD. Measures of HRV have been reported to be closely linked to various physiological processes, such as stress and discomfort, in firefighters.^41,51–53 Most importantly, HRV, particularly SDNN and RMSSD, have been related to autonomic disturbance and inflammatory responses, similar to those related to musculoskeletal pain and discomfort.^21,22 The conflicting results in the current study compared with the findings of Chuang et al.²² may be related to firefighters that experienced MSD being more vigorously physically active than firefighters without discomfort (360 vs 320 minutes) and the additional physical activity causing chronic inflammation due to the higher workloads; however, this is only speculation. The current results indicated that TC, LDL-C, SDNN, and RMSSD remained significantly associated with MSD after adjustment for covariates. Another possible explanation would be that high LDL-C is a source of oxidative stress within the tendons.^20,22 The oxidative stress, accompanied by inflammation, may present as a reduction in HRV, which is supported by studies that showed reduced symptoms of musculoskeletal pain and discomfort were associated with increased HRV measures, such as N-N intervals, RMSSD, and SDNN.^21,22 The results of the present study showed that firefighters that were never injured were the most vigorously active (360 vs 240 minutes), but also reported the highest musculoskeletal discomfort. Perhaps, firefighters experienced more discomfort due to their higher levels of vigorous activity, which may have been fitter, but also had higher levels of TC and LDL-C concentrations, which has been shown to increase inflammation and pain.^17,22 Moreover, studies have shown that HRV was linked to overtraining and overuse, providing a potential link between HRV and MSH,^54,55 particularly in the firefighter population, which is known to be a physically demanding profession. In this current study, higher levels of vigorous weekly physical activity had a protective effect on the prevalence of MSIs of firefighters, which is not unexpected, given the protective effect of physical activity on musculoskeletal health, which is well documented in firefighters.^5,29 This is in contrast to a previous study in this population, which noted higher weekly physical activity was related to an increase in MSIs.⁵⁶ Nevertheless, physical activity has been reported to be a central factor in reducing the incidence of MSIs and MSDs alike in firefighters.^18,44,57

In the current study, sex was significantly associated with firefighters reporting MSIs, where female firefighters were 2.1 times as likely to report an MSI compared with male firefighters. Nazari et al.⁴³ reported that females were 1.6 times more likely to sustain two or more injuries, compared with male firefighters. Similarly, a study by O’Leary et al.⁵⁸ noted that in military, personal females were at higher risk for musculoskeletal injury compared with males, particularly related to the lower limbs. A recent study noted that reduced lean body mass predisposed males to injury, whereas a higher fat mass predisposed females to injury.⁵⁰ The current results indicated that a significant difference existed between male and female BF%, which could, possibly, explain the association between sex and injuries seen in the current study. In addition, generally, males having more muscle mass, a higher bone mineral density, and relatively stronger connective tissues^59,60 which could further explain why females were more likely to report an MSI. Studies have shown that firefighting PPE has been designed to fit male firefighters more comfortably than female firefighters, likely contributing to the higher injury incidence in female firefighters.^61,62 Moreover, because of discrimination in the fire services, female firefighters may be less likely to ask male firefighters for assistance on physically strenuous tasks increasing the probability of injury in females.⁶¹

Age and years of experience were significantly associated with injuries in firefighters, where every 1-year increase in experience increased the likelihood of injury by 3% and 4%, and approached statistical significance in the adjusted models. However, after adjustment, significance was removed. This was consistent with previous literature, where both aging and years of experience were significantly associated with firefighters sustaining MSIs.^10,13,43 Firefighting is a strenuous occupation that places significant strain on the musculoskeletal system.^10,63 Compounded with age increasing along with experience, firefighters become significantly predisposed to MSIs. Moreover, aging, independently, causes physiological changes that reduce MSH^12,13 and as a result of the attrition in MSH associated with increasing years as a firefighter,^12,13,27 predisposes this population to injury. Previous studies have noted that with the normal wear and tear of firefighting, older firefighters, generally, would have a higher risk of injury, likely as a result of the increase in years of service.^10,13,43

Strengths and Limitations

Strengths of the present study include the application of multilevel modeling to account for the hierarchical nature of the data and the use of objective measures for the CVH components and all tools used were reliable and valid. In addition, this article adds novel information into an area, which has been understudied in firefighters. There are, however, several limitations to the present study. First, this study used a cross-sectional design, which precludes the inference of causal relationships. Second, MSIs and MSD were self-reported. Thirdly, female firefighters were underrepresented, limiting the generalizability to the female firefighter population. Finally, although the study met the minimum required sample size, the number of comparisons made may introduce chance findings.

CONCLUSIONS

Multiple CVD risk factors and CVH metrics were associated with MSIs and MSD in firefighters. Musculoskeletal injuries were significantly higher in aged, obese, hypertensive, and dyslipidemic firefighters. In addition, MSD was significantly higher in firefighters with high TC, LDL-C, SDNN, and RMSSD. Thus, older female firefighters with a higher BF% are most likely to have ever sustained a musculoskeletal line-of-duty injury. In addition, those with elevated blood lipid levels are most likely to have musculoskeletal discomfort. Our results add to the limited research in this topic area, particularly on the potential relationships that exist between CVH, and musculoskeletal health in firefighters. The results of this study add novel information on the associations between CVH and MSH in firefighters, specifically the association between MSIs and MSD and blood lipid and HRV irregularities, providing new insights into risk factors for MSIs in this population. Maintaining one’s CVH may have an added benefit of maintaining MSH in firefighters and that commonly obtained health metrics may provide valuable insight into who is most at risk for MSI and MSD. Therefore, maintenance of an ideal body composition and blood lipid profile is recommended, particularly as firefighters age, as it may have a positive and long-term benefit in maintaining the well-being and ensuring career longevity in firefighters.

Recommendations

Future studies should use a longitudinal study design to establish the causal factors related to MSIs and MSD in firefighters. A more representative sample of female firefighters should be included to increase the generalizability to the female firefighter population.