A Study on Work-Related Injuries and Its Association with Sleep Quality and Other Related Factors Among Firefighters in the District of Kollam, Kerala

Abstract

Background:

Firefighters perform high-risk, physically demanding duties with irregular hours and disrupted sleep, increasing injury risk. This study assessed the burden of work-related injuries and their association with sleep quality among firefighters in Kollam, Kerala.

Methodology:

An institution-based cross-sectional study was conducted from September 2024 to November 2025 among 106 firefighters from all 11 Fire and Rescue stations, selected by simple random sampling. Data were collected through face-to-face interviews using a pre-tested structured questionnaire and analyzed using Microsoft Excel 2021 and JAMOVI 2.5.4.

Result:

Among 106 male firefighters (median age 39; IQR 37–43), 76.4% were married, 62.3% graduates, and 70.8% upper socioeconomic class. Alcohol use (29.2%), and smoking (17%) were reported; all used personal protective equipment (PPE) and 66% had normal body mass index (BMI). Participants worked ≥72 hours weekly with daily physical training. Weekly hazardous exposure was reported by 41.5% and related health problems by 53.8%. Work-related injuries occurred in 39.6%, mostly mild (61.9%) and limb-related (50%), commonly during fire and rescue operations, with fatigue as the leading contributor (40.5%). Poor sleep quality (55.7%) showed a significant association with injury (P < 0.001).

Conclusion:

Work-related injuries are common among firefighters and are strongly associated with poor sleep quality. Optimizing duty schedules, strengthening workplace safety, and promoting sleep health may help reduce injuries.

INTRODUCTION

Firefighters are routinely exposed to extreme heat, toxic gases, structural collapse, hazardous materials, and intense physical exertion, placing them at high risk of fatal and non-fatal work-related injuries.[1] Their duties involve long shifts, night work, and unpredictable emergencies that impair sleep and increase injury risk.[2] In India, firefighters respond to fires, road accidents, chemical spills, and rescues, facing greater occupational hazards than most professions. The World Health Organization-International Labor Organization (WHO-ILO) identifies long work hours and hazardous exposures as major drivers of occupational injuries.[1]

Sleep disturbance is common among firefighters, affecting 37%–61% globally due to shift work, exhaustion, and incident-related stress.[3,4,5] Poor sleep impairs alertness, reaction time, and decision-making, increasing injuries and burnout.[6] Studies from South Korea and southern India report higher fatigue and injury risk among sleep-deprived and night-shift firefighters.[7,8] The Pittsburgh Sleep Quality Index is a validated tool for assessing subjective sleep quality.[9,10] Despite the burden of insomnia in India, research among first responders remains limited.[3,11] Sleep deficiency is a major public health concern affecting workplace performance and injury risk, yet Indian evidence on firefighter injuries, and sleep remains limited, constraining context-specific policy.

Firefighters in Kerala, particularly in Kollam, operate in high-demand urban, industrial, coastal, and disaster settings requiring sustained vigilance and physical effort. No Kerala study has examined work-related injuries or their association with sleep quality; this study therefore assessed injury burden and its relationship with sleep to inform occupational safety interventions.

MATERIALS AND METHODS

An institution-based cross-sectional study was conducted from September 2024 to November 2025 among firefighters in Kollam district, Kerala (map-Figure 1). Kollam has coastal and hilly terrains with expanding urban and industrial areas prone to fire incidents. All 11 Kerala Fire and Rescue Service stations were included to represent diverse geographic and functional settings. Firefighters aged 18–60 years with ≥12 months of field service were included, while those on long-term medical leave or administrative duty were excluded. Sample size was calculated using a 48.7%,[12] prevalence of poor sleep quality, 95% confidence level, 10% absolute precision, and 10% non-response rate, yielding a final sample of 106. Eligible firefighters were selected by simple random sampling using a computer-generated list, and all provided consent.

Figure 1.

Administrative map of Kollam district. © Kerala State Planning Board. Adapted from: District Map of Kerala [Internet]. Available from: https://www.ecostat.kerala.gov.in/storage/documents/44.pdf (Accessed 12 Nov 2025).

Data were collected via face-to-face interviews using a pre-tested, validated structured questionnaire covering sociodemographic, occupational, behavioral, morbidity, and injury details. Chronotype was assessed using the 19-item Morningness–Eveningness Questionnaire (16–86),[13] and sleep quality using the Pittsburgh Sleep Quality Index (global score 0–21; higher scores indicate poorer sleep).[10]

Work-related injuries in the previous 12 months were self-reported. The questionnaire was translated, back-translated, expert-validated, and pilot-tested among eight firefighters from a neighboring district. Data were analyzed using Microsoft Excel 2021 and JAMOVI 2.5.4. Normality was assessed with the Shapiro–Wilk test. Categorical variables were summarized as frequencies and percentages, associations tested using Chi-square or Fisher’s exact test, and variables with P ≤ 0.25 in univariate logistic regression entered multivariable models after assessing multicollinearity. Model fit was evaluated using Hosmer–Lemeshow and Cox and Snell and Nagelkerke R² (P < 0.05).

Operational definition

Work related injury: A work-related injury was defined, according to Occupational Safety and Health Administration (2001) standards, as an injury caused or contributed to by an event or exposure in the work environment, or one that significantly aggravated a pre-existing condition.[14]

RESULT

Sociodemographic characteristics

Among 106 firefighters, the median age was 39 years (IQR: 37–43), and all were male. Most were graduates (62.3%), currently married (76.4%), and from nuclear families (55.7%). Based on modified B.G. Prasad’s scale-January 2024,[15] 70.8% belonged to the upper socioeconomic class. Median monthly per capita income was ₹11,666.67 (IQR: ₹8,333.33–15,000).

Behavioral characteristics

Participants showed varied substance use patterns, including tobacco, alcohol, and other substances [Figure 2]. Current smoking was reported by 17.0%, alcohol use by 29.2%, and other substance use by 4.7%. Based on WHO body mass index (BMI) classification, 66% had normal BMI, 32.1% were overweight, and 1.9% were obese.

Figure 2.

Stacked Bar Chart showing the distribution of study participants according to Smoking tobacco, Alcohol use and others (n=106)

Occupational characteristics

Among participants, 40.6% had 6–10 years of service, and the predominant rank was Fire and Rescue Officer (55.7%). Most (80.2%) reported working ≥72 hours per week. All engaged in daily physical training. Personal protective equipment (PPE) use was universal (100%), while 41.5% reported exposure to hazardous substances at least weekly.

Morbidity profile

A considerable proportion of firefighters reported at least one chronic morbidity, commonly hypertension, type 2 diabetes, and dyslipidemia, with some multimorbidity. Other conditions included musculoskeletal disorders, migraine, asthma, hypothyroidism, and varicose veins; detailed proportions are shown in Figure 3.

Figure 3.

Bar chart showing the distribution of participants with co-morbidities among the study participants (n=65)

Chronotype

Based on the Morningness-Eveningness Questionnaire, most firefighters were classified as neither type (52.8%), followed by moderately evening type (18.9%); full distribution is shown in Figure 4.

Figure 4.

Horizontal bar chart showing the distribution of participants according to their chronotype by M-E Questionnaire (n=106)

Work-related injuries

Forty-two participants reported ≥1 work-related injury in the past year. Most injuries were mild (61.9%), followed by moderate (33.3%). Fire accidents were the leading cause (33.3%), followed by animal or human rescue operations (26.2%); scuba/diving and miscellaneous events were less common. Fatigue was the most frequently reported contributing factor (40.5%).

Sleep quality

Sleep quality assessed using the Pittsburgh Sleep Quality Index showed poor sleep (score >5) in 55.7% of firefighters. Daytime dysfunction was prominent, with 56.6% reporting mild-to-severe impairment in daily activities.

Association between work-related injury and sleep quality

Sleep quality showed a significant association with work-related injury (P < 0.001). Injured firefighters were more likely to be poor sleepers [Table 1], and injury characteristics by sleep quality are presented in Table 2.

Table 1.

Cross table showing association between work-related injuries and sleep quality (n=106)

Sleep Quality	Work-related injuries		Total	Chi-square test
	Yes Number (%)	No Number (%)
Poor	34 (32.1)	25 (23.6)	59 (55.7)	χ² = 18.0 (df=1)
Yes	8 (7.5)	39 (36.8)	47 (44.3)	P-value:<0.001
Total	42 (39.6)	64 (60.4)	106 (100%)

Table 2.

Cross table showing relation between work-related injuries characteristics with sleep quality (n=106)

Work-related injuries (in last 1 year)	Category	Sleep Quality		Total	P-value
		Poor Sleep	Good Sleep
Number of Injuries	1 time	26 (61.9%)	8 (19.05%)	34 (80.95%)	<0.001
	2 times	5 (11.9%)	0	5 (11.9%)
	>3 times	3 (7.15%)	0	3 (7.15%)
Severity of injuries	Mild	19 (45.23%)	7 (1.67%)	26 (61.90%)	<0.001
	Moderate	13 (30.95%)	1 (2.38%)	14 (33.33%)
	severe	2 (4.76%)	0	2 (4.76%)
Body parts injured	Head/neck	4 (9.52%)	2 (4.76%)	6 (14.28%)	<0.001
	Limbs	19 (45.23%)	2 (4.76%)	21 (50%)
	Trunk	1 (2.38%)	3 (7.15%)	4 (9.52%)
	Multiple sites	10 (23.81%)	1 (2.38%)	11 (26.19%)
Injuries event	Animal/human rescue	11 (26.19%)	0	11 (26.19%)	<0.001
	Fire accidents	10 (23.81%)	4 (9.52%)	14 (33.33%)
	Scuba/diving	4 (9.52%)	0	4 (9.52%)
	Others	9 (21.42%)	4 (9.52%)	13 (30.95%)
Type of injuries	Cut injury/fracture	18 (42.85%)	1 (2.38%)	19 (45.23%)	<0.001
	Burns	7 (16.67%)	3 (7.15%)	10 (23.81%)
	Others	9 (21.42%)	4 (9.52%)	13 (30.95%)
Factors leading to injuries	Equipment failure	4 (9.52%)	0	4 (9.52%)	<0.001
	Lack of training	5 (11.9%)	2 (4.76%)	7 (16.67%)
	Fatigue	15 (35.71%)	2 (4.76%)	17 (40.47%)
	Others	10 (23.81%)	4 (9.52%)	14 (33.33%)

*Significant at P<0.05

Factors associated with work-related injury

Multivariate analysis identified poor sleep quality as the strongest predictor of work-related injury, with nearly 10-fold higher odds among poor sleepers (AOR = 9.796, 95% CI: 3.01–31.82, P < 0.001). Work-related health problems or hazardous exposures were also significant (AOR = 5.465, 95% CI: 1.55–19.29, P = 0.008). Alcohol use increased injury odds by over two times (AOR = 2.251, 95% CI: 1.25–4.06, P = 0.007), and increasing age showed a significant association (AOR = 2.504, 95% CI: 1.09–5.07, P = 0.031). Evening chronotype showed higher but non-significant odds of injury (AOR = 1.897, 95% CI: 0.97–3.72, P = 0.062). BMI, smoking, marital status, years of service, duty hours, rank, comorbidities, and other sociodemographic or occupational variables were not significantly associated after adjustment (P > 0.05) [Table 3]. The multivariate model demonstrated good fit and overall significance (Hosmer–Lemeshow P > 0.05; Nagelkerke R² =0.456; model P < 0.01) [Table 4].

Table 3.

Logistic regression analysis of factors associated with Work-Related Injuries (n=106)

Variables	Univariate		Multivariate
	Unadjusted OR (95% CI)	P-value	Adjusted OR (95% CI)	P-value
PSQI-sleep quality	6.63 (2.64-16.63)	<0.001	9.796 (3.01-31.82)	<.001*
Health problems-hazard	2.04 (0.92–4.54)	0.081	5.465 (1.548–19.29)	0.008*
Alcohol	1.709 (1.12–2.60)	0.013	2.251 (1.25–4.06)	0.007*
Age	1.08 (0.78–1.48)	0.654	2.504 (1.09–5.07)	0.031*
M-E Q Impression	1.307 (0.87–1.97)	0.203	1.897 (0.97–3.72)	0.062
Marriage	0.919 (0.60–1.41)	0.696	1.105 (0.44–2.79)	0.832
Education	1.206 (0.79–1.85)	0.391	1.755 (0.89–3.48)	0.108
Family type	0.942 (0.43–2.06)	0.88	1.382 (0.46–4.16)	0.564
Children	0.783 (0.38–1.63)	0.513	0.515 (0.13–1.97)	0.333
Cohabitation	0.931 (0.44–1.97)	0.851	0.971 (0.17–5.54)	0.973
Percapita income	1.57 (0.73–3.39)	0.251	0.936 (0.29–3.75)	0.912
Smoking	0.972 (0.59–1.62)	0.914	1.344 (0.64–2.82)	0.435
Other substance	1.441 (0.63–3.29)	0.386	1.400 (0.49–3.96)	0.525
BMI	0.95 (0.80–1.13)	0.551	0.966 (0.76–1.22)	0.774
Years of service	0.911 (0.64–1.30)	0.609	0.628 (0.27–1.44)	0.272
Current rank	1.1 (0.81–1.50)	0.546	1.229 (0.75–2.00)	0.408
Weekly duty	0.751 (0.30–1.91)	0.546	0.632 (0.15–2.58)	0.523
Co-morbidities	0.812 (0.36–1.82)	0.612	0.862 (0.10–7.21)	0.891
Co-morbidities details	0.952 (0.79–1.15)	0.608	1.193 (0.72–1.97)	0.495

*Significant at P<0.05. BMI=Body mass index

Table 4.

Model fit statistics for the multivariate logistic regression model (n=106)

Model Fit Measures
							Overall Model Test
Model	Deviance	AIC	BIC	R²McF	R²CS	R²N	χ²	df	P-value
1	98.7	143	201	0.306	0.337	0.456	43.6	21	0.003

AIC=Akaike Information Criterion; BIC=Bayesian Information Criterion; R²McF=McFadden R²; R²CS=Cox and Snell R²; R²N=Nagelkerke R²; df=Degrees of freedom; χ² = Chi-square value

DISCUSSION

This study provides an overview of the sociodemographic, behavioral, occupational, and health profile of firefighters and factors influencing occupational safety. The median age of 39 years and all-male composition reflect typical firefighter demographics reported globally.[16] The high proportion of graduates (62.3%) indicates a well-educated workforce capable of adapting to safety protocols and complex operations, consistent with previous studies.[17] Most participants were married (76.4%) and from nuclear families (55.7%), suggesting family support alongside potential work–life stress. A majority belonged to the upper socioeconomic class with stable income, which may improve healthcare access.[15]

Substance use patterns (smoking 17.0%, alcohol 29.2%, other substances 4.7%) are important in a safety-critical occupation. Alcohol use in firefighters is widely reported as a coping response to occupational stress, highlighting the need for mental health and stress-management programmers.[18,19] Most participants had normal BMI (66%), with relatively lower overweight/obesity than global firefighter data,[20,21] possibly due to routine physical training similar to findings in previous studies.[22]

Occupational findings showed a moderately experienced, mid-career workforce, with 80.2% working ≥72 hours weekly. Prolonged duty hours contribute to fatigue, sleep deprivation, and injury risk in emergency services.[23] Despite universal PPE use and daily training, extended shifts may offset protective benefits.[24] Regular hazardous exposure (41.5%) also indicates risk for long-term respiratory and cancer outcomes documented among firefighters.[25]

Chronic morbidities such as hypertension, diabetes, and dyslipidemia, including multimorbidity, reflect the known cardiovascular and metabolic risks of firefighting related to stress, shift work, and exposures.[20] Regular occupational health screening is therefore essential.

Most firefighters had an intermediate chronotype (52.8%). Although not a significant injury predictor, higher odds in non-morning types suggest possible circadian influences needing further study in shift work.[26]

Nearly two-fifths (39.6%) reported work-related injury in the past year, commonly mild or moderate, mainly during fire incidents and rescue operations, consistent with Ethiopian findings.[12] Numerous studies indicate the annual prevalence of work-related injuries among firefighters ranges from 27% to 66%, highlighting the inherently dangerous nature of the profession.[23,27] Fatigue, the leading contributing factor (40.5%), is strongly linked to impaired alertness and injury risk; workers with sleep problems show higher injury likelihood.[28]

Poor sleep quality affected 55.7% of firefighters, comparable to global firefighter estimates and other shift-working professions, with substantial daytime dysfunction.[27,29]

Poor sleep showed a strong association with work-related injury (P < 0.001), with injured firefighters more often poor sleepers. Reduced alertness, slower reaction time, and impaired cognition may underlie this risk. Links with occupational hazards and alcohol use suggest a multifactorial pathway explaining substantial variance (Nagelkerke R² =0.456), supporting targeted sleep health promotion, behavioral risk reduction, and strengthened occupational health monitoring.

Limitations

The cross-sectional design precludes causal inference. Self-reported data may introduce recall or social desirability bias, particularly for alcohol use and health conditions. Conducting the study in a single district may also limit generalizability.

CONCLUSION

Poor sleep quality, alcohol use, and pre-existing health conditions were associated with work-related injuries among firefighters. These findings underscore the need for workplace interventions such as sleep health education, fatigue management, sleep-disorder screening, and support for substance-use reduction and chronic disease care. Longitudinal studies with objective measures are needed to clarify causality and assess intervention effectiveness.

Ethical approval

Ethical approval was obtained from the Institutional Ethics Committee (IEC/2024(3)/92), with permission from the Fire and Rescue Services Department, Government of Kerala. Confidentiality and voluntary participation were ensured.

Conflicts of interest

There are no conflicts of interest.

Appendix

AIC-Akaike Information Criterion

BIC-Bayesian Information Criterion

R²McF -McFadden R²

R²CS -Cox and Snell R²

R²N-Nagelkerke R²

df -Degrees of freedom

χ²- Chi-square value

Funding Statement

Nil.