Sleep duration and quality among Indian anaesthesiologists: A nationwide cross-sectional survey

Abstract

Background and Aims:

Poor sleep can adversely affect well-being, cognitive function, and decision-making. Anaesthesiologists face unique occupational challenges (irregular shifts, on-call duties, and high stress), which exacerbate sleep disturbances. This study aimed to assess the prevalence of poor sleep among Indian anaesthesiologists and identify associated risk factors.

Methods:

A cross-sectional online survey was conducted among Indian anaesthesiologists. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), while data on sleep duration, demographics, work patterns, personal habits, stress, and comorbidities were collected. Bivariate and multivariate logistic regression analyses were performed to identify factors independently associated with short sleep (<7 hours) and poor sleep quality (PSQI >5).

Results:

Out of 728 respondents, more than 60% reported short sleep (<7 hours) and more than 50% reported poor sleep quality (PSQI >5). Independent predictors of poor sleep included female gender, more than three night shifts or on-call duties per month, sedentary lifestyle, high home stress, and presence of self-reported sleep disorders. Respondents emphasised the impact of irregular hours, work–life imbalance, and the need for systematic interventions.

Conclusion:

Poor sleep quality is highly prevalent among Indian anaesthesiologists and is driven by both occupational and personal factors. Structured work schedules and shift patterns and emphasis on lifestyle and stress may improve sleep health and reduce patient risks.

INTRODUCTION

Sleep is a fundamental physiological requirement, with at least 7 hours of regular sleep recommended for adults to maintain physical and cognitive well-being.[1] Insufficient or poor-quality sleep can cause acute effects (irritability, impaired attention, delayed reaction time) and chronic effects (impaired immunity, cardiovascular diseases, etc.).[1] Recent surveys indicate worsening sleep health, described as a “global sleep crisis”.[2]

Anaesthesiologists are particularly vulnerable due to long and irregular working hours, frequent night shifts, and emergency workload, which contribute to stress, burnout, and insufficient sleep.[3,4] Sleep deprivation in this group may impair cognitive performance and reaction time, potentially affecting patient safety.

Although anaesthesiologists’ sleep quality and associated risk factors have been studied internationally,[3,5] there is a lack of data specific to Indian anaesthesia professionals, who number nearly 50,000.

To our knowledge, contemporary nationwide data on sleep quality and its occupational correlates among Indian anaesthesiologists remain limited. Existing literature primarily comes from Western contexts, with differing workloads, shift structures, and support systems.

The primary objective of this study was to assess the prevalence of poor sleep quality among Indian anaesthesiologists using validated tools such as the Pittsburgh Sleep Quality Index (PSQI).[6] The secondary objectives were to identify occupational and personal risk factors associated with poor sleep quality.

METHODS

This cross-sectional, questionnaire-based observational study included anaesthesiologists working in India with ≥1 year of clinical experience. The ≥1-year threshold was chosen to ensure adequate exposure to routine anaesthesia duties, night shifts, and on-call responsibilities. Anaesthesiologists not currently in clinical practice or suffering from depression/anxiety/panic disorder were excluded from the study.

Ethical approval was obtained from the institutional ethics committee (96/MERB/2025; 31/7/2025). The study was prospectively registered with the Clinical Trials Registry-India (CTRI/2025/08/092416; 5/8/2025). Data were collected in August 2025 via an anonymous online questionnaire distributed through emails and professional anaesthesia groups, with one response permitted per email address. Approximately 3600 anaesthesiologists from all over the country were invited to participate in the survey, out of which 790 responded (response rate approximately 21%). Three reminders were issued to improve participation. Despite the modest response rate, the final sample substantially exceeded the pre-specified minimum sample size required for prevalence estimation and regression modelling. Nationwide responses were obtained to ensure diverse representation. All items were mandatory except the optional comments, ensuring complete datasets.

Participation was voluntary with implied informed consent at survey entry. No personal identifiers were collected. Exit was permitted at any stage of the survey. Data were stored on a secure restricted-access cloud drive.

The questionnaire was developed in three stages:

1. Item generation – Based on a validated tool, that is, PSQI, along with a focussed literature review and expert inputs.

2. Expert review – By five anaesthesiologists with >5 years’ experience.

3. Pilot testing – With 10 anaesthesiologists, followed by refinement for clarity.

The final questionnaire comprised 27 questions (with two additional questions for respondents reporting a diagnosed or suspected sleep disorder):

Part I: Demographics (age, gender) and professional details (experience, workplace, working hours, night shifts, Sunday duties, and on-call frequency).

Night shift, Sunday duties, and on-calls frequency were recorded as self-reported categories (0, 1–3, and >3 night shifts per month), reflecting increasing levels of occupational circadian disruption.

Part II: Lifestyle characteristics (physical activity, caffeine intake, smoking and alcohol) and stress at work and home.

Physical activity was categorised as sedentary (little or no exercise), moderately active (physical activity 2–3 times/week), and very active (physical activity >3 times/week).

Part III: Sleep quality assessed using the PSQI.[6] The PSQI has high internal consistency (Cronbach’s alpha coefficient 0.83) and test–retest reliability (r = 0.85).[6,7] The scores range from 0 to 21 with PSQI >5 indicating “poor sleep quality” (sensitivity 89.6%, specificity 86.5%) (P < 0.001).[6]

The PSQI was used due to its established reliability, reproducibility, and widespread use in assessing sleep quality, enabling meaningful comparison with prior literature. It is a validated instrument with established psychometric properties. The remaining study-specific items were developed based on literature review and expert consensus to capture relevant occupational and personal factors. These items were descriptive and exploratory and were pilot-tested for clarity and face validity but were not intended to represent a standalone validated scale. The questionnaire included additional components; however, only variables relevant to sleep duration and sleep quality were analysed in the present study.

The sample size was based on the primary objective: estimating the prevalence of poor sleep (PSQI >5) among Indian anaesthesiologists. Using a prevalence of 57.3% reported among French anaesthesiologists[3]; the following parameters were applied: Expected prevalence (p): 57.3%, confidence level: 95%, Z-value: 1.96, margin of error (d): 5%, and population size: assumed large (no finite correction applied). Using the formula for estimating a single population proportion (n = Z² × p × [1 − p]/d²), the minimum required sample size was calculated to be 376. The actual sample exceeded this number significantly.

Statistical analysis was performed using Jamovi (version 2.6.44). All tests were two-sided (α = 0.05). Categorical variables are reported as counts and percentages, and continuous variables as mean ± standard deviation (SD) or as median with interquartile range (IQR), depending on distribution. Normality was assessed through Q–Q plots and box plots.

Group comparisons for continuous variables used the independent-samples t-test when normality and homogeneity of variances (tested by Levene’s test) were satisfied. If equality of variances was violated, Welch’s t-test was applied. For non-normal distribution, the Mann–Whitney U test was employed. For comparisons involving more than two groups, one-way analysis of variance (ANOVA) was used, followed by Tukey’s honestly significant difference (HSD) post-hoc test. If variance homogeneity was violated, Welch’s ANOVA with Games–Howell post-hoc was used. For skewed data across more than two groups, the Kruskal–Wallis test was performed, with Dwass–Steel–Critchlow–Fligner pairwise tests applied when significant differences were found.

Correlations were assessed using Pearson’s or Spearman’s coefficients as appropriate. Categorical associations were examined using the Chi-square (χ²) test, with Yates’ correction when required.

Variables with bivariate associations at P < 0.20 were considered for multivariable modelling to avoid excluding potentially relevant predictors. Multicollinearity was excluded [variance inflation factors (VIF) <2, tolerances ~1]. Model adequacy was assessed using the likelihood-ratio χ² test, Akaike Information Criterion (AIC), and Nagelkerke’s R².

Calibration and discrimination were evaluated using the Hosmer–Lemeshow test and area under the receiver operating characteristic curve (AUROC), respectively. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) are reported. All P values are precise to three decimals or P < 0.001.

Models were based on 728 participants with adequate outcome events for short sleep duration (number of participants, n = 476) and poor sleep quality (PSQI >5; n = 371). The events-per-variable ratio exceeded recommended thresholds, ensuring statistical stability. Model adequacy was supported by significant likelihood-ratio χ² tests (P < 0.001), stable standard errors, and consistent CIs. Sensitivity analyses involving sequential removal of low-frequency and correlated predictors demonstrated negligible variation in effect estimates, indicating absence of overfitting. Effect sizes were reported to aid interpretation.

Multicollinearity was excluded using VIF and tolerance values. Although some occupational variables were conceptually related, hierarchical and domain-specific evaluations showed independent contributions. Excluding these variables reduced model performance (e.g., a decrease in Nagelkerke R² from 0.36 to 0.32 in the PSQI model), supporting their retention for maintaining construct validity.

A post-hoc sample adequacy assessment for the PSQI model based on recommended criteria for prediction modelling (Nagelkerke R² = 0.36, outcome prevalence = 50.9%, shrinkage = 0.9) indicated a minimum requirement of 649 participants with at least 331 events. The present study exceeded these thresholds (n = 728; 371 events), confirming adequate power and model reliability.

RESULTS

A total of 790 anaesthesiologists participated in the survey. Of these, 728 responses were analysed after excluding 55 respondents with psychological/mood disorder, and seven with inconsistent entries. All entries were complete. Participants’ characteristics are summarised in Table 1.

Table 1.

Descriptive characteristics of respondents stratified by sleep duration and PSQI score categories

Independent Variable		Number of Respondents
		Total *(n)		†Sleep Duration (<7 hours) *(n, %)		‡PSQI (>5) *(n, %)
Age (years)
25-35		213		146 (68.5%)		143 (67.1%)
36-50		354		226 (63.8%)		161 (45.5%)
51-65		131		86 (65.6%)		59 (45.0%)
>65		30		18 (60.0%)		8 (26.7%)
Gender
Male		408		249 (61.0%)		174 (42.6%)
Female		320		227 (70.9%)		197 (61.6%)
Workplace
Freelancing		103		66 (64.1%)		42 (40.8%)
Government Medical College		151		101 (66.9%)		91 (60.3%)
Non-teaching Government Hospital		33		20 (60.6%)		12 (36.4%)
Private Medical College		88		68 (77.3%)		60 (68.2%)
Non-teaching Private Hospital		109		62 (56.9%)		56 (51.4%)
Teaching Private Hospital		157		106 (67.5%)		70 (44.6%)
Multiple Workplaces		83		51 (61.4%)		38 (45.8%)
Others		4		2 (50.0%)		2 (50.0%)
Total Professional Experience
≤5 years		165		128 (77.6%)		119 (72.1%)
6–10 years		138		78 (56.5%)		68 (49.3%)
11–20 years		209		131 (62.7%)		89 (42.6%)
>20 years		216		139 (64.4%)		95 (44.0%)
Primary Work Area
Anaesthesia only		353		233 (66.0%)		159 (45.0%)
ICU only		15		7 (46.7%)		7 (46.7%)
Both Anaesthesia and ICU		350		231 (66.0%)		199 (56.9%)
Others		10		5 (50.0%)		6 (60.0%)
Sunday Duties
None		210		125 (59.5%)		79 (37.6%)
1–3 times/month		463		310 (67.0%)		258 (55.7%)
>3 times/month		55		41 (74.5%)		34 (61.8%)
Night Shifts
None		320		196 (61.3%)		120 (37.5%)
1–3 times/month		193		128 (66.3%)		108 (56.0%)
>3 times/month		215		152 (70.7%)		143 (66.5%)
On-Call Duties
None		182		112 (61.5%)		96 (52.7%)
1–3 times/month		262		151 (57.6%)		116 (44.3%)
>3 times/month		284		213 (75.0%)		159 (56.0%)
Working Hours/week
<40 hours		59		35 (59.3%)		23 (39.0%)
40–50 hours		223		137 (61.4%)		101 (45.3%)
51–55 hours		129		90 (69.8%)		74 (57.4%)
56–60 hours		132		86 (65.2%)		71 (53.8%)
>60 hours		185		128 (69.2%)		102 (55.1%)
Physical Activity
Sedentary		186		134 (72.0%)		116 (62.4%)
Moderately Active		337		215 (63.8%)		175 (51.9%)
Very Active		205		127 (62.0%)		80 (39.0%)
Tea/Coffee Consumption
None		73		48 (65.8%)		33 (45.2%)
1–2 cups/day		357		211 (59.1%)		162 (45.4%)
3–4 cups/day		246		178 (72.4%)		140 (56.9%)
>4 cups/day		52		39 (75.0%)		36 (69.2%)
Alcohol Consumption
Never		390		260 (66.7%)		184 (47.2%)
< once a month		182		120 (65.9%)		99 (54.4%)
1–3 times/month		102		64 (62.7%)		62 (60.8%)
>4 times/month		54		32 (59.3%)		26 (48.1%)
Smoking
Never smoked		606		399 (65.8%)		310 (51.2%)
Quit >6 months back		49		34 (69.4%)		20 (40.8%)
Quit <6 months back		10		4 (40.0%)		4 (40.0%)
Current smokers		63		39 (61.9%)		37 (58.7%)
Existence of Comorbidities
Yes		295		193 (65.4%)		158 (53.6%)
No		433		283 (65.4%)		213 (49.2%)
Existence of Sleep Disorder
Yes		128		100 (78.1%)		104 (81.3%)
No		600		376 (62.7%)		267 (44.5%)

*Data are presented as number (n) or number (n) and percentage (%). ^†Sleep duration is self-reported average sleep hours per night. ^‡PSQI: Pittsburgh Sleep Quality Index; defined as poor sleep quality if PSQI >5. ^§Percentages represent row-wise percentages. ICU: Intensive care unit; n: Number of respondents

Poor sleep quality (PSQI >5) was observed in 50.9% of respondents. Variables significantly associated with continuous PSQI scores are presented in Table 2. For clinical interpretation, PSQI was dichotomised at the established cut-off (>5 indicating poor sleep quality) [Table 3].

Table 2.

Factors independently associated with Pittsburgh Sleep Quality Index (PSQI) score after bivariate logistic regression of continuous PSQI Score (n=728)

Variable		Groups *(mean±SD)		Test Used/Value		P		Effect Size (95% CI)
Age		—		Pearson’s r=-0.208, df=726		<0.001		r²=0.043 (95% CI: 0.017, 0.072)
Gender		Female – 6.99±3.41; Male – 5.48±2.93		Welch’s t (629)=6.31		<0.001		Cohen’s d=0.48 (95% CI: 0.33, 0.63) → moderate effect
Total Experience		5 years or less (7.52±3.10); 6–10 years (6.09±3.11); 11–20 years (5.76±3.38); >20 years (5.50±2.98)		ANOVA F (3,724)=14.5		<0.001		Overall effect: η²=0.057 (0.045, 0.068) Post-hoc pairwise effects (Tukey): • ≤5 years vs 11–20 years: Cohen’s d=0.54 (0.33, 0.75) → moderate effect • ≤5 years vs 6–10 years: Cohen’s d=0.46 (0.23, 0.69) → small-to-moderate effect • ≤5 years vs >20 years: Cohen’s d=0.67 (0.46, 0.87) → moderate-to-large effect
Workplace		Freelancing (5.48±3.24); Govt. Medical College (6.90±3.28); Multiple (5.90±3.34); Non-teaching Govt. (5.82±3.62); Non-teaching Private (5.95±3.25); Others (6.50±4.12); Private Medical College (7.13±3.26); Teaching Private Hospital (5.61±2.78)		ANOVA F (7,720)=3.86		<0.001		Overall effect: η²=0.036 (0.011, 0.060) Post-hoc pairwise effects (Tukey): • Freelancing vs Government Medical College: Cohen’s d=−0.44 (95% CI: −0.69, −0.18) → small-to-moderate effect • Freelancing vs Private Medical College: Cohen’s d=−0.51 (95% CI: −0.80, −0.22) → moderate effect • Government Medical College vs Teaching Private Hospital: Cohen’s d=0.42 (95% CI: 0.20, 0.65) → small-to-moderate effect • Private Medical College vs Teaching Private Hospital: Cohen’s d=0.51 (95% CI: 0.25, 0.78) → moderate effect
Sunday Duties		None (5.39±3.27); 1–3/month (6.36±3.10); >3/month (7.15±3.75)		ANOVA F (2,725)=9.67		<0.001		Overall effect: η²=0.026 (0.016, 0.035) Post-hoc pairwise effects (Tukey): • None vs 1–3 times/month: Cohen’s d=−0.31 (95% CI: −0.47, −0.14) → small effect • None vs >3 times/month: Cohen’s d=−0.52 (95% CI: −0.82, −0.22) → moderate effect
Night Shifts		None (5.28±2.98); 1–3/month (6.39±3.28); >3/month (7.20±3.23)		Welch’s F (2,424)=25.5		<0.001		Overall effect: η²=0.107 (0.093, 0.120) Post-hoc pairwise effects (Games-Howell): • 1–3 times/month vs >3 times/month: Cohen’s d=−0.25 (95% CI: −0.44, −0.05) → small effect • 1–3 times/month vs None: Cohen’s d=0.36 (95% CI: 0.18, 0.54) → small-to-moderate effect • >3 times/month vs None: Cohen’s d=0.62 (95% CI: 0.45, 0.80) → moderate effect
On-call Duties		None (6.24±3.32); 1–3/month (5.55±2.97); >3/month (6.63±3.34)		Welch’s F (2,440)=8.22		<0.001		Overall effect: η²=0.036 (0.020, 0.051) Post-hoc pairwise effects (Games-Howell): • 1–3 times/month vs >3 times/month: Cohen’s d=−0.34 (95% CI: −0.51, −0.17) → small-to-moderate effect
Physical Activity		Sedentary (7.10±3.38); Moderately active (6.20±3.15); Very active (5.18±2.98)		ANOVA F (2,725)=18.2		<0.001		Overall effect: η²=0.048 (0.038, 0.057) Post-hoc pairwise effects (Tukey): • Moderately active vs Sedentary: Cohen’s d=−0.28 (95% CI: −0.46, −0.10) → small effect • Moderately active vs Very active: Cohen’s d=0.33 (95% CI: 0.16, 0.51) → small-to-moderate effect • Sedentary vs Very active: Cohen’s d=0.60 (95% CI: 0.40, 0.81) → moderate effect
Tea/Coffee Consumption		None (5.92±3.22); 1–2 cups/day (5.80±3.18); 3–4 cups/day (6.44±3.21); >4 cups/day (7.37±3.42)		ANOVA F (3,724)=4.71		0.003		Overall effect: η²=0.019 (0.007, 0.031) Post-hoc pairwise effects (Tukey): • 1–2 cups vs >4 cups: Cohen’s d=−0.49 (95% CI: −0.78, −0.20) → moderate effect
Work Stress		—		Spearman’s ρ=0.297, df=726		<0.001		r²=0.088 (95% CI: 0.051, 0.137)
Home Stress		—		Spearman’s ρ=0.323, df=726		<0.001		r²=0.104 (95% CI: 0.064, 0.154)
Sleep Disorder Existence		No (5.64±2.95); Yes (8.50±3.47)		Welch’s t (169)=-8.69		<0.001		Cohen’s d=-0.94 (95% CI: -1.14, -0.74)
Sleep Duration		—		Pearson’s r=-0.665, df=726		<0.001		r²=0.442 (95% CI: 0.388, 0.490)

*Data are presented as mean±SD. SD: Standard deviation; CI: Confidence interval; df: Degree of freedom; ANOVA: Analysis of variance; Govt: Government

Table 3.

Factors independently associated with Pittsburgh Sleep Quality Index (PSQI) score categories after bivariate logistic regression (n=728)

Variable		*PSQI ≤5 (Good sleep) †mean±SD or n		*PSQI >5 (Poor sleep) †mean±SD or n		Test Used/Value		P		Effect Size (95% CI)
Age (Mean±SD)		45.3±11.1		40.7±10.5		t (726)=5.76		<0.001		Cohen’s d=0.43 (0.28, 0.57) →moderate effect
Gender n		Male 234; Female 123		Male 174; Female 197		χ² (1)=25.7		<0.001		Phi=0.19 (0.12, 0.26)
Total Experience (n)		≤5 years 46; 6–10 years 70; 11–20 years 120; >20 years 121		≤5 years 119; 6–10 years 68; 11–20 years 89; >20 years 95		χ² (3)=39.8		<0.001		Cramer’s V=0.23 (0.16, 0.29)
Workplace (n)		Freelancing 61; Govt. Medical College 60; Private Medical College 28; Teaching Private 83		Freelancing 42; Govt. Medical College 91; Private Medical College 60; Teaching Private 74		χ² (7)=26.2		<0.001		Cramer’s V=0.19 (0.11, 0.26)
Work Area (n)		Anaesthesia only 194; Both Anaesthesia and ICU 151; ICU only 7; Others 4		Anaesthesia only 159; Both Anaesthesia and ICU 199; ICU only 8; Others 6		χ² (3)=10.3		0.017		Cramer’s V=0.12 (0.04, 0.19)
Sunday Duties (n)		None 131; 1–3/month 205; >3/month 21		None 79; 1–3/month 258; >3/month 34		χ² (2)=21.8		<0.001		Cramer’s V=0.17 (0.09, 0.24)
Night Shifts (n)		None 200; 1–3/month 85; >3/month 72		None 120; 1–3/month 108; >3/month 143		χ² (2)=45.9		<0.001		Cramer’s V=0.25 (0.18, 0.32)
On-call Duties (n)		None 86; 1–3/month 146; >3/month 125		None 96; 1–3/month 116; >3/month 159		χ² (2)=7.79		0.020		Cramer’s V=0.10 (0.02, 0.18)
Working Hours (n)		<40 h 36; 40-50 h 122; 51-55 h 55; 56-60 h 61; >60 h 83		<40 h 23; 40-50 h 101; 51-55 h 74; 56-60 h 71; >60 h 102		χ² (4)=10.1		0.039		Cramer’s V=0.12 (0.04, 0.19)
Physical Activity (n)		Sedentary 70; Moderate 162; Very active 125		Sedentary 116; Moderate 175; Very active 80		χ² (2)=21.5		<0.001		Cramer’s V=0.17 (0.09, 0.24)
Tea/Coffee (n)		>4 cups/day 16; None 40; 1–2 cups 197; 3–4 cups 144		>4 cups/day 36; None 33; 1–2 cups 164; 3–4 cups 102		χ² (3)=15.8		0.001		Cramer’s V=0.15 (0.07, 0.22)
Work Stress (Mean±SD)		4.00±2.28		5.20±2.43		Mann–Whitney U test=47465		<0.001		Rank-biserial correlation (r)=0.28 (0.21, 0.35)
Home Stress (Mean±SD)		3.25±2.01		4.49±2.39		Mann–Whitney U test=445813		<0.001		Rank-biserial correlation (r)=0.31 (0.24, 0.37)
Sleep Disorder Exist. (n)		No 333; Yes 24		No 267; Yes 104		χ² (1)=57.0		<0.001		Cramer’s V=0.28 (0.21, 0.35)
Sleep Duration (Mean±SD)		6.64±0.76		5.66±0.96		Welch’s t-test (699)=15.35		<0.001		Cohen’s d=−0.56 (−0.70, −0.42) →moderate effect

*PSQI ≤5: Good sleep quality; PSQI >5: Poor sleep quality. ^†Data presented as mean±SD or n. ICU: Intensive care unit; SD: Standard deviation; CI: Confidence interval; n: Number of respondents; Govt.: Government

On multivariate analysis [Table 4], female gender and ≤5 years’ experience conferred elevated risk for poor sleep quality (PSQI >5). Compared with freelancers, anaesthesiologists in non-teaching government hospitals had lower odds (OR = 0.32, P = 0.024). Also, working in both operating theatres and intensive care units (ICUs) increased the risk 1.62 times (P = 0.015).

Table 4.

Factors independently associated with poor sleep quality (PSQI >5) after multivariate analysis (n=728)

Independent Variable		*Odds Ratio (95% CI)		P
Gender (Male vs Female)		0.50 (0.34–0.73)		<0.001
Total Experience
6–10 years vs ≤5 years		0.45 (0.25–0.81)		0.007
Workplace
Non-teaching Govt. vs Freelancing		0.32 (0.12–0.86)		0.024
Work Area
Both Anaesthesia and ICU vs Anaesthesia only		1.62 (1.10–2.39)		0.015
Night Shifts
1–3/month vs None		1.74 (1.07–2.83)		0.026
>3/month vs None		2.00 (1.16–3.46)		0.013
Physical Activity
Sedentary vs Very active		1.80 (1.09–2.98)		0.023
Home Stress		1.18 (1.07–1.30)		<0.001
Sleep Disorder (Yes vs No)		5.00 (2.93–8.52)		<0.001

*Odds ratio (OR) with 95% confidence interval (CI) shown. ^†Overall Model test - χ² (36): 228, P: <0.001; Nagelkerke’s R²=0.36. ^‡Model Performance – Accuracy (72.5%); Sensitivity: 73%; Specificity: 72%; Area under curve (AUC): 0.804. ICU: Intensive care unit; n: Number of respondents; vs: Versus

Night shifts emerged as powerful predictors, with moderate exposure (1–3 shifts/month) increasing odds by 74% (OR = 1.74, P = 0.026) and frequent exposure (>3/month) doubling the risk (OR = 2.00, P = 0.013). Sedentary lifestyle almost doubled the risk of poor sleep (OR = 1.80, 95% CI, P = 0.023).

Home stress independently predicted poor sleep (OR = 1.18, P < 0.001), while work stress showed borderline effect (P = 0.068). A self-reported sleep disorder was the single strongest determinant (OR = 5.00, P < 0.001).

The average sleep duration was 6.14 ± 0.99 hours, with 476 (65.3%) respondents sleeping for <7 hours and 158 (21.7%) sleeping for <6 hours. Significant bivariate associations with sleep duration are presented in Table 5. In multivariate analysis [Table 6], those with 6–10 years (OR = 0.39, 95% CI: 0.22–0.67, P < 0.001) and 11–20 years (OR = 0.54, 95% CI: 0.31–0.95, P = 0.031) had lower odds of short sleep compared with participants with ≤5 years of experience.

Table 5.

Factors independently associated with sleep duration after bivariate logistic regression (n=728)

Variable		Groups *(mean±SD)		Test Used/Value		P		Effect Size (95% CI)
Gender		Female – 6.00±0.98; Male – 6.24±0.99		t (726)=-3.25		0.001		Cohen’s d=−0.24 (95% CI: −0.39, −0.10) → small effect
Total Experience		5 years or less (5.87±1.03); 6–10 years (6.36±0.95); 11–20 years (6.22±0.97); >20 years (6.12±0.98)		ANOVA F (3, 724)=6.99		<0.001		Overall effect: η²=0.028 (0.010, 0.046) Post-hoc pairwise effects (Tukey): • 5 years or less vs 11–20 years: Cohen’s d=−0.35 (−0.56, −0.15) → small effect • 5 years or less vs 6–10 years: Cohen’s d=−0.49 (−0.72, −0.26) → moderate effect
Work Area		Anaesthesia only: 6.18±0.92; Both Anaesthesia and ICU: 6.07±1.06; ICU only: 6.63±0.61; Others: 6.10±1.43		Welch’s F (3, 28.5)=3.67		0.024		Overall effect: η²=0.279 (0.049, 0.385) Post-hoc pairwise effects (Games-Howell): • Both Anaesthesia and ICU vs ICU only: Cohen’s d=−0.59 (95% CI: −1.09, −0.10) → moderate effect
Night Shifts		None (6.28±0.97); 1–3/month (6.05±1.03); >3/month (6.01±0.99)		ANOVA F (2, 725)=5.83		0.003		Overall effect: η²=0.016 (0.006, 0.025) Post-hoc pairwise effects (Tukey): None vs 1–3 times/month: Cohen’s d=0.23 (0.05, 0.41) → small effect None vs >3 times/month: Cohen’s d=0.28 (0.10, 0.45) → small-to-moderate effect
On-call Duties		None (6.14±1.09); 1–3/month (6.31±0.89); >3/month (5.98±1.00)		ANOVA F (2, 725)=7.76		<0.001		Overall effect: η²=0.021 (0.011, 0.030) Post-hoc pairwise effects (Tukey): • 1–3 times/month vs >3 times/month: Cohen’s d=0.35 (0.18, 0.52) → small-to-moderate effect
Physical Activity		Sedentary (5.97±1.09); Moderately active (6.17±0.96); Very active (6.24±0.95)		ANOVA F (2, 725)=4.17		0.016		Overall effect: η²=0.011 (0.001, 0.021) Post-hoc pairwise effects (Tukey): • Sedentary vs Very active: Cohen’s d=−0.27 (−0.46, −0.07) → small effect
Tea/Coffee Consumption		None (6.19±0.93); 1–2 cups/day (6.27±0.97); 3–4 cups/day (6.02±0.93); >4 cups/day (5.74±1.32)		Welch’s F (3, 158)=5.03		0.002		Overall effect: η²=0.087 (0.034, 0.131) Post-hoc pairwise effects (Games-Howell): • 1–2 cups vs 3–4 cups: Cohen’s d=0.26 (0.10, 0.42) → small effect • 1–2 cups vs >4 cups: Cohen’s d=0.52 (0.22, 0.81) → moderate effect
Work Stress		—		Spearman’s ρ=-0.134, df=726		<0.001		r²=0.018 (95% CI: 0.004, 0.042)
Home Stress		—		Spearman’s ρ=-0.198, df=726		<0.001		r²=0.039 (95% CI: 0.016, 0.071)
Sleep Disorder Existence		No (6.23±0.97); Yes (5.73±1.03)		t (726)=5.19		<0.001		Cohen’s d=0.51 (95% CI: 0.32, 0.70) → moderate effect

*Data are presented as mean±SD. SD: Standard deviation; CI: Confidence interval; ANOVA: Analysis of variance; ICU: Intensive care unit; n: Number of respondents; df: Degree of freedom

Table 6.

Factors independently associated with sleep duration <7 hours after multivariate analysis (n=728)

Independent Variable		*Odds Ratio (95% CI)		P
Total Experience
†6–10 years vs ≤5 years		0.39 (0.22–0.67)		<0.001
†11–20 years vs ≤5 years		0.54 (0.31–0.95)		0.031
On-call Duties
†>3/month vs None		1.79 (1.14–2.81)		0.012
Home Stress		1.11 (1.02–1.22)		0.022
†Sleep Disorder (Yes vs No)		1.96 (1.19–3.21)		0.008

*Odds ratio (OR) with 95% confidence interval (CI) shown. ^†Reference groups: ≤5 years’ experience, no on-call duties, no sleep disorder. ^‡Overall Model fit - χ² (31): 94.9, P: <0.001; Nagelkerke’s R²=0.169. ^§Model Performance – Accuracy (69.8%); Sensitivity: 88%; Specificity: 35.3%; AUC: 0.716. n: Number of respondents; vs: Versus

In occupational load, only frequent on-call duties (>3/month) remained significant (OR = 1.79, 95% CI: 1.14–2.81, P = 0.012). Home stress (OR = 1.11, 95% CI: 1.02–1.22, P = 0.022) and self-reported sleep disorders (OR = 1.96, 95% CI: 1.19–3.21, P = 0.008) were also independent predictors.

Overall, 17.6% anaesthesiologists reported a sleep disorder, the most common being insomnia. However, only 2.7% had sought specialist evaluation.

Free-text comments (n = 172) revealed concerns about irregular working hours, work–life imbalance, personal well-being, and patient safety [Supplementary Table 1]. Suggested coping strategies included strategic napping and self-care, along with institutional measures like regulated duty hours and designated rest periods after night shifts.

Supplementary Table 1.

Thematic summary of optional free-text comments regarding sleep disturbances and coping strategies

Theme *(Number of respondents contributing to each theme)		Description		†Illustrative Quotes
Irregular and Long Working Hours (14 respondents)		A dominant theme is the impact of long, irregular, and unpredictable working hours, including night shifts and on-call duties, which often disrupt sleep patterns and routines. Respondents describe difficulties in maintaining regular sleep schedules, with night duties and emergency calls often cited as major disruptors.		“Working hours to be planned in shifts to maintain adequate work life balance. This would permit people to have time to work as well as have time for themselves and family. This would help people to devote some time for any kind of activity that would improve their quality of life and their own health” “Poor sleep throws everything off balance, be it job or health, mood etc”
Work–Life Balance and Self-Care Challenges (10 respondents)		Several responses state that demanding professional schedules leave insufficient time for family and personal well-being. Sleep deprivation is also seen as a barrier to engaging in meaningful family and leisure activities.		“Inadequate sleep along with erratic hours and long days (12 to 14 hours at work) affects work life balance, self-care and quality of life.” “When self-care routine like yoga, meditation, art are replaced by work it leads to exhaustion and emotional unrest.”
Recognition of Sleep as Essential for Health and Safety (16 respondents)		A recurring perspective is that good sleep is fundamental not just for job performance and patient safety but for overall health, immunity, and emotional resilience. Some mention fear of long-term effects, such as burnout, memory loss, or increased risk of chronic illnesses.		“Poor sleep throws everything off balance, be it job or health, mood etc.” “A full night’s sleep is essential to function normally especially after 50 years age. If one attends 2-3 calls at night should definitely be given 6-8 hours (if possible) rest before resuming work or else patient safety is definitely compromised”
Coping Strategies and Recommendations (4 respondents)		Respondents mention coping strategies, e.g., naps, avoiding large meals, attempting to maintain routines, or consulting health professionals. Some also suggest policy-level changes, like regulated duty hours, designated rest periods after night shifts, and institutional recognition of the problem.		“Avoid heavy lunch to avoid sleepiness during work days” “Small naps whenever possible really rejuvenate” “Always trying to get good sleep. For that, daily morning, I am doing yoga meditation for one hour”
Comments on Unique Personal or Home Circumstances (20 respondents)		Many respondents share personal situations affecting sleep, such as having young children or caregiving responsibilities, further complicating their ability to maintain adequate rest.		“I have a small kid. And that’s the reason for waking up in middle of night sometimes as he gets up” I have a toddler boy of 18 month-old” “Individual circumstances like health and family responsibilities impact sleep”
Emotional and Psychological Effects (9 respondents)		Many note the psychological impact of poor sleep, including anxiety, exhaustion, emotional instability, and frustration. A sense of “vicious cycle” is observed – where sleep deficit worsens stress and stress, in turn, worsens sleep.		“Poor sleep throws everything off balance, be it job or health, mood etc” “Sleep if disturbed causes fatigue and irritability next day leading to exhaustion”

*Number of respondents per theme (n) shown in parentheses. †Illustrative quotes are verbatim responses from survey participants

DISCUSSION

There is growing interest worldwide in the well-being of anaesthesiologists, yet their sleep quality still remains under-explored.[8,9]

This nationwide survey highlights a substantial burden of short sleep duration and poor sleep quality among Indian anaesthesiologists, driven by both occupational workload and modifiable personal factors. The burden of insufficient sleep in this survey exceeded estimates from the general Indian population (~30%) and was comparable to anaesthesiologists in France and Portugal.[3,10,11,12]

In the present survey, self-reported insomnia was far lower than in the general population (18–33%), with only a small proportion seeking specialist advice, suggesting potential self-management among clinicians.[13,14]

Also, as per the findings of the survey, short sleep duration was independently associated with professional experience, frequent on-call duties, home stress, and pre-existing sleep disorders. Predictors of poor sleep quality (PSQI >5) included female gender, professional experience, workplace characteristics, night shifts, physical inactivity, home stress, and sleep disorders. Female anaesthesiologists appeared particularly vulnerable, consistent with established gender differences in sleep architecture and social roles. Recent Indian data also demonstrate a disproportionate burden of domestic responsibilities and limited support systems among female anaesthesiologists, adversely affecting professional roles and career progression, which may partly explain the higher vulnerability observed in our cohort.[2,5,15] On-call duties or night shifts (>3/month) were important contributors, likely reflecting circadian rhythm disruption.[3,16] Nevertheless, prior studies have demonstrated impaired neuro-behavioural performance after night duties.[3,17] These findings support institutional fatigue-mitigation strategies such as regulated duty rosters and protected rest periods.

The current survey revealed a protective association of sleep quality with regular physical activity, consistent with prior evidence.[18] Nonetheless, simple workplace interventions (e.g., brief exercises during breaks) may be beneficial. Home stress also contributed to poor sleep in our study, highlighting the additive impact of personal stressors. Chronic stress can disrupt sleep architecture and reduce overall sleep efficiency,[2,5,12] suggesting that accessible mental-health support may benefit high-risk clinicians.

Pre-existing sleep disorders emerged as the strongest determinant in our study. This finding underscores the importance of targeted screening, early identification, and timely intervention as untreated sleep disorders may further exacerbate occupational fatigue and impair overall well-being in anaesthesiologists.

Several factors, including professional experience, institutional affiliation, and primary work area, were identified as significant predictors in the current study. These findings are presented in the context of existing literature.[3,12,19,20] Early career anaesthesiologists demonstrated higher vulnerability, advocating for tailored support during formative years. Anaesthesiologists in non-teaching government hospitals had significantly lower odds of poor sleep compared to freelancers, reflecting the benefit of structured work schedules.

Anaesthesiologists working in both operating theatres and ICUs had poorer sleep as per our survey findings, reflecting the strain of dual high-intensity responsibilities. Implementing structured shift rotations could help alleviate this burden.

Overall, the findings of this survey likely reflect cumulative circadian disruption from night duties and on-call work, compounded by modifiable lifestyle and stress-related factors. Targeted institutional and individual strategies may help mitigate these disturbances. Poor sleep among anaesthesiologists has implications beyond individual health, contributing to medical errors and adverse patient outcomes.[1,16,21] Notably, India lacks national health policies addressing minimum sleep duration even for the general population.[22]

The limitations of our study include subjective assessment of stress as objective physiological measures were not feasible in this nationwide survey-based study. Secondly, the study relied on self-reported measures, and some potentially relevant variables such as bedtime screen exposure were not included to ensure conciseness and minimise respondent burden. Digital device use is increasingly recognised as a contributor to sleep disturbance and warrants further investigation in future studies. Thirdly, recall bias and night-to-night variability cannot be excluded as sleep duration could not be objectively measured. The voluntary web-based survey design may introduce selection and non-response bias, potentially affecting the representativeness of the findings. Nonetheless, the large sample size and national representation strengthen the generalisability of the findings.

CONCLUSION

This study demonstrates a high prevalence of poor sleep quality (PSQI >5) and short sleep duration (<7 hours) among Indian anaesthesiologists, with significant associations with frequent night duties, on-call responsibilities, sedentary behaviour, and perceived stress. These findings highlight the need for greater awareness of sleep health and consideration of occupational factors contributing to sleep disturbances in this population. Further research is needed to explore potential interventions and long-term implications.

Author contributions

All the authors were involved in making substantial contributions to the conception and design of the survey, interpreting the relevant literature, drafting the article, revising it critically for important intellectual content and giving the final approval of the version to be submitted.

Presentation at conferences/CMEs and abstract publication

The study has not been presented at any conference/CME, and no abstract has been published.

Statement on data sharing

De-identified data may be requested with reasonable justification from the authors (email to the corresponding author) and shall be shared after approval as per the authors’ Institution policy.

Disclosure of use of artificial intelligence (AI)-assistive or generative tools

ChatGPT (OpenAI) was used only for language editing for improving clarity of the manuscript. It was not used for data analysis, interpretation, or generation of scientific content. The authors reviewed and approved the final manuscript and take full responsibility for its content.

Declaration of use of permitted tools

Only standard, widely accepted tools and software were used for data collection, analysis, and manuscript preparation. No unauthorised or prohibited tools were used.

Supplementary material

This article has supplementary material which can be accessed at the following link - https://links.lww.com/IJOA/A92.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.