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Original Article
ARTICLE IN PRESS
doi:
10.25259/IJASM_34_2025

Perception of oral health and oral health-related quality of life among aviators in the armed forces: A cross-sectional study

Indian Air Force, India.
Author image
Corresponding author: Srihari Krishna Kaushik, Indian Air Force, India. aerodontist@yahoo.com
Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Kaushik SK, Farzand A, Venkatakrishnan H. Perception of oral health and oral health-related quality of life among aviators in the armed forces: A cross-sectional study. Indian J Aerosp Med. doi: 10.25259/IJASM_34_2025

Abstract

Objectives:

Oral health significantly influences functional performance and psychological well-being. Military aviators operate under unique physiological and operational stresses where even minor dental issues can compromise in-flight performance and safety. As evidence regarding oral health-related quality of life (OHRQoL) among military aviators is scarce, this study aimed to assess the perception of oral health and OHRQoL using the Oral Health Impact Profile-14 (OHIP-14) and to evaluate its association with demographic, occupational, and behavioral factors.

Material and Methods:

A cross-sectional study was conducted among 430 military aviators using a structured, self-administered online questionnaire comprising flying attributes, demographic details, oral health awareness and hygiene habits, smoking habits, and the validated OHIP-14 instrument. Descriptive statistics, unpaired t-tests, one-way analysis of variance, and Spearman’s correlation were performed using IBM Statistical Package for the Social Sciences version 26.0, with significance set at p < 0.05.

Results:

Overall OHRQoL among aviators was favorable. Functional limitation (mean = 4.10 ± 1.89) and physical pain (mean = 2.22 ± 1.59) were the most affected domains. Advancing age and longer service duration were significantly associated with higher OHIP scores (p < 0.001). Smokers demonstrated significantly poorer OHRQoL compared to non-smokers (p = 0.047). Strong positive correlations were observed among physical pain, functional limitation, physical disability, and handicap domains.

Conclusion:

Aviators demonstrated favorable OHRQoL; however, functional limitation and physical pain remain key concerns. Age, duration of service, and smoking were major determinants of reduced OHRQoL. Incorporating periodic OHRQoL assessments, smoking cessation counseling, and preventive oral health programs into aeromedical evaluations can enhance dental readiness and operational efficiency in the Armed Forces.

Keywords

Aerospace medicine
Military personnel
Oral health
Pain
Quality of life
Smoking

INTRODUCTION

Oral health is a unique determinant of an individual’s overall quality of life influencing significantly the daily functioning, comfort, and psychosocial wellness. Unlike other clinical disease indicator parameters, the subjective impact of oral conditions on normal routine physiologic functions such as mastication, phonetics, and social interactions is increasingly established through the concept of oral health-related quality of life (OHRQoL).[1] The oral health impact profile (OHIP) is a well-recognized and widely used community oral health tool used to measure OHRQoL. Since the original version was lengthy and complex, the adapted, simpler, and concise version abbreviated 14-item version (OHIP-14) is nowadays more widely used due to greater feasibility retaining robust validity in occupation-based population study models.[2,3]

Military aviators represent a distinct occupational cohort exposed to aviation-specific physiological stresses, circadian rhythms altered due to operational tasks, and high cognitive/motor demands. Even minor dental problems such as sensitivity/pain due to dental decay may impair in-flight performance or trigger temporary grounding, with consequent operational and safety implications. Military and aerospace medicine literature therefore emphasizes proactive dental readiness and periodic dental screening.

Despite this operational imperative, empirical data addressing aviators’ perceptions of their oral health and the resultant effect on OHRQoL remain scarce. Evaluating these among aviators can help identify gaps in oral health awareness, preventive behaviors, and the need for targeted dental interventions. Such assessments using validated instruments like the OHIP-14 can assist in formulating tailored preventive and educational programs, ensuring sustained oral health and mission efficiency. This study, therefore, aims to assess the perception of oral health and OHRQoL among military aviators using the OHIP-14 questionnaire and to explore associations with occupational and behavioral factors.

MATERIAL AND METHODS

A cross-sectional descriptive study was conducted to assess the OHRQoL using OHIP-14 questionnaire among the military aviators across geographic deployment between November 24 and December 24. The study included military aviators aged between 25 and 60 years across services, aircraft streams, and geographic deployment. Aviators who provided informed consent were included in the study. Individuals with a history of recent trauma or surgery, diagnosed with uncontrolled systemic illness, malignancy, and those unwilling to participate were excluded.

Sampling method

Convenience sampling was employed due to wide geographic dispersion, variable operational commitments, and frequent movement of aviators, which limited the feasibility of probability-based sampling. Data were collected using an anonymous online questionnaire distributed through a secure Google Forms link, with a single response permitted per participant.

The sample size was calculated using the formula: n = Z2 × p × (1 − p)/d2 where Z = 1.96 (for 95% confidence), p = 0.5 (anticipated proportion for maximum variability), and d = 0.05 (allowable error). The calculated sample size was 384, which was increased to 430 to account for potential non-responses or incomplete submissions.

Data collection

Data were collected using a structured questionnaire consisting of four sections. The first section included demographic and occupational details (age, years of service, aircraft stream, and flying hours). The second section captured information on self-reported dental problems and treatment history. The third section captured the seven domains (functional limitation, physical pain, psychological discomfort, physical disability, psychological disability, social disability, and handicap) with two items each scored on a five-point Likert scale ranging from never (0) to very often (4). The final section assessed smoking status. A pilot test involving 20 aviators confirmed the clarity and feasibility of the questionnaire; these responses were excluded from the final analysis.

Ethical considerations

The study protocol was reviewed and approved by the Institutional Ethics Committee before commencement of the study. Electronic informed consent was obtained from all participants before submission of responses. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki and applicable national guidelines for biomedical research involving human participants. The study was based on an online questionnaire Google form without any active physical intervention on human subjects or exposure of sensitive information/ confidentiality of the voluntarily participating subjects in anonymity; ethical clearance was waived (Copy of waiver from head of institution enclosed).

Data analysis

The data collected from the participants’ responses to the questionnaire were analyzed using IBM Statistical Package for the Social Sciences statistics software version 26. Individual contribution of each of the seven domains to overall OHRQoL was analyzed. Appropriate tests such as unpaired t-test and analysis of variance were applied to ascertain the significance between baseline characteristics and OHIP components. The inter-relationships among the various OHIP components were examined using the Spearman correlation analysis, with a p < 0.05 considered statistically significant.

RESULTS

The distribution of the respondent subjects based on demographic variables, smoking, dental problem status, and dental treatment status is summarized in Figures 1-4, respectively.

Distribution of respondents by demographic variables. RPA: Remotely piloted aircraft, UAV: Unmanned aerial vehicle.
Figure 1: Distribution of respondents by demographic variables. RPA: Remotely piloted aircraft, UAV: Unmanned aerial vehicle.
Distribution of respondents by smoking status.
Figure 2: Distribution of respondents by smoking status.
Distribution of respondents by dental problem status.
Figure 3: Distribution of respondents by dental problem status.
Distribution of respondents by dental treatment status.
Figure 4: Distribution of respondents by dental treatment status.

Around 64.2% were non-smokers and among those who smoked, the duration of smoking varied considerably.

The domain-wise mean OHIP-14 scores are summarized in Table 1. Among the seven components analyzed, the functional limitation (4.10 ± 1.89) recorded the highest mean score. Psychological disability (mean = 0.53 ± 1.17) and psychological discomfort (mean = 0.32 ± 0.73) had comparatively low scores. Six sigma limits were applied as an exploratory quality assessment framework to identify domains exceeding acceptable variation thresholds. When compared (Lower: 1.34; Mean: 1.61; Upper: 1.89), it was observed that functional limitation and physical pain scores exceeded the upper limit. The remaining domains were within the defined limits [Figure 5].

Table 1: Comparative analysis of OHIP components.
OHIP component scores OHIP score Six sigma limits
Mean SD Lower Mean Upper
Physical pain 2.22 1.59 1.34 1.61 1.89
Functional limitation 4.10 1.89 1.34 1.61 1.89
Physical disability 1.54 1.58 1.34 1.61 1.89
Psychological disability 0.53 1.17 1.34 1.61 1.89
Social disability 0.93 1.42 1.34 1.61 1.89
Handicap 1.66 1.75 1.34 1.61 1.89
Psychological discomfort 0.32 0.73 1.34 1.61 1.89

OHIP: Oral health impact profile, SD: Standard deviation

Six sigma-based comparative distribution of oral health impact profile-14 domains.
Figure 5: Six sigma-based comparative distribution of oral health impact profile-14 domains.

The association between overall OHIP-14 scores and baseline characteristics is presented in Table 2. A statistically significant increase in overall OHIP-14 scores was observed with advancing age (F = 9.62, p < 0.001) and increasing duration of service (F = 8.17, p < 0.001). Smoking status was also significantly associated with higher OHIP-14 scores (t = 1.99, p = 0.047). No significant association was observed between aircraft stream and overall OHRQoL.

Table 2: Correlation of OHIP overall with baseline characteristics.
Baseline characteristics OHIP overall score (%)
Mean SD
Age
  25–30 years 8.51 6.57
  31–35 years 12.02 7.15
  36–40 years 11.84 7.41
  41 years and above 13.01 7.09
  (ANOVA) F=9.62, p<0.001
Number of years of service
  <5 years 7.87 5.90
  6–10 years 10.11 7.26
  11–15 years 12.22 7.07
  16–20 years 12.65 7.18
  21 years and above 13.31 7.22
  (ANOVA) F=8.17, p<0.001
Aircraft stream
  Fighter 11.96 7.01
  Helicopter 10.91 7.28
  RPA/UAV 10.50 7.20
  Transport 11.10 7.58
  (ANOVA) F=0.68, p=0.562
Smoking
  Yes 12.25 7.76
  No 10.81 6.87
  (unpaired t-test) t=1.99, p=0.047

OHIP: Oral health impact profile, SD: Standard deviation, ANOVA: Analysis of variance, RPA: Remotely piloted aircraft, UAV: Unmanned aerial vehicle, p-value significant at 0.05

The relationship between baseline characteristics and individual OHIP-14 domains is detailed in Table 3. Age and years of service showed significant associations with the domains of physical pain, functional limitation, and physical disability (p < 0.001). Smoking status was significantly associated with the psychological disability domain (p = 0.009), while other domain-wise associations were not statistically significant.

Table 3: Association between baseline characteristics and individual OHIP-14 domains.
Baseline characteristics Physical pain Functional limitation Physical disability Psychological disability Social disability Handicap Psychological discomfort
Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD
Age
  25–30 years 1.49 1.44 3.36 2.00 0.99 1.34 0.45 0.98 0.66 1.33 1.36 1.64 0.21 0.62
  31–35 years 2.36 1.52 4.40 1.86 1.68 1.68 0.56 1.34 0.92 1.46 1.80 1.87 0.30 0.72
  36–40 years 2.10 1.51 4.00 1.90 1.66 1.63 0.69 1.27 1.06 1.51 1.91 1.68 0.43 0.83
  41 years and above 2.81 1.55 4.59 1.59 1.87 1.57 0.49 1.13 1.10 1.41 1.68 1.78 0.36 0.77
ANOVA F=17.45, p<0.001 F=11.19, p<0.001 F=7.86, p<0.001 F=0.67, p=0.572 F=2.38, p=0.069 F=1.95, p=0.121 F=1.51, p=0.210
Number of years of service
  <5 years 1.30 1.31 3.31 1.89 0.89 1.30 0.43 1.02 0.54 1.02 1.23 1.61 0.17 0.56
  6–10 years 1.89 1.60 3.81 2.05 1.29 1.58 0.50 1.07 0.77 1.42 1.59 1.84 0.26 0.68
  11–15 years 2.31 1.48 4.29 1.86 1.78 1.57 0.56 1.27 1.09 1.65 1.84 1.70 0.36 0.77
  16–20 years 2.57 1.47 4.37 1.76 1.80 1.59 0.65 1.38 1.06 1.30 1.80 1.74 0.41 0.81
  21 years and above 2.87 1.54 4.60 1.62 1.89 1.60 0.53 1.17 1.13 1.46 1.77 1.79 0.39 0.80
ANOVA F=14.21, p<0.001 F=6.53, p<0.001 F=6.43, p<0.001 F=0.29, p=0.882 F=2.70, p=0.030 F=1.61, p=0.170 F=1.36, p=0.247
Aircraft stream
  Fighter 2.43 1.52 4.24 1.88 1.81 1.63 0.49 1.09 0.86 1.36 1.76 1.73 0.28 0.69
  Helicompter 2.07 1.63 4.03 1.90 1.38 1.51 0.55 1.22 0.95 1.52 1.57 1.75 0.34 0.76
  RPA/UAV 2.21 1.67 3.71 1.54 1.14 1.51 0.43 1.16 1.14 1.29 1.43 1.65 0.43 0.85
  Transport 2.11 1.62 4.05 1.95 1.43 1.59 0.57 1.19 0.96 1.38 1.65 1.84 0.32 0.74
ANOVA F=1.65, p=0.178 F=0.61, p=0.609 F=2.91, p=0.034 F=0.13, p=0.944 F=0.23, p=0.875 F=0.50, p=0.683 F=0.38, p=0.765
Smoking
  Yes 2.36 1.61 4.30 1.75 1.69 1.70 0.73 1.48 1.00 1.52 1.82 1.93 0.36 0.77
  No 2.15 1.58 4.00 1.96 1.48 1.53 0.42 0.93 0.89 1.37 1.58 1.66 0.29 0.71
Unpaired t-test t=1.30, p=0.193 t=1.57, p=0.117 t=1.31, p=0.191 t=2.64, p=0.009 t=0.76, p=0.448 t=1.35, p=0.179 t=1.00, p=0.316

OHIP: Oral health impact profile, SD: Standard deviation, ANOVA: Analysis of variance. p-value significant at 0.05

Spearman’s correlation analysis demonstrated significant positive correlations among multiple OHIP-14 domains [Table 4]. Strong correlations were observed between physical pain and physical disability (p = 0.651), physical pain and functional limitation (p = 0.542), and between physical disability and handicap (p = 0.553), all of which were statistically significant (p < 0.001).

Table 4: Spearman’s correlation between oral health impact profile-14 domains.
Spearman correlations Physical pain Functional limitation Physical disability Psychological disability Social disability Handicap Psychological discomfort
Physical pain
  Rho value 1.000
  p-value
Functional limitation
  Rho-value 0.542 1.000
  p-value <0.001
Physical disability
  Rho-value 0.651 0.477 1.000
  p-value <0.001 <0.001
Psychological disability
  Rho-value 0.329 0.282 0.366 1.000
  p-value <0.001 <0.001 <0.001
Social disability
  Rho-value 0.468 0.280 0.493 0.382 1.000
  p-value <0.001 <0.001 <0.001 <0.001
Handicap
  Rho-value 0.577 0.437 0.553 0.399 0.564 1.000
  p-value <0.001 <0.001 <0.001 <0.001 <0.001
Psychological discomfort
  Rho-value 0.185 0.109 0.114 0.116 0.164 0.117 1.000
  p-value <0.001 0.024 0.018 0.017 0.001 0.015

Bold values represent statistically significant correlations. p-value significant at 0.05

DISCUSSION

The present study evaluated the perception of oral health and its impact on OHRQoL among military aviators using the validated OHIP-14 instrument. The results revealed that functional limitation and physical pain were the most affected domains. This was similar to the study conducted by Singh and Talmale[4] where functional limitation and physical pain recorded the highest mean score. Physical pain contributes largely toward low OHRQoL values. This was in agreement with the studies conducted by Acharya and Sangam,[5] Batista et al.,[6] Dahl et al.,[7] Lu et al.,[8] Montero-Martin et al.,[9] and Papagiannopoulou et al.[10] The results in the study showed a significant relationship between age and OHRQoL, implying that the oral health impact tends to increase with advancing age possibly due to cumulative dental wear, neglect, or systemic influences. This was similar to the study conducted by Li et al.[11] and Pakkhesal et al.[12]

In the present study, smokers exhibited a higher mean OHIP than the non-smokers indicating tobacco use may exacerbate oral health problems, leading to a greater perceived impact on OHRQoL. This was similar to the study conducted by Maida et al.,[13] Astrom et al.,[14] Mbawalla et al.,[15] and Bakri et al.[16] Among all the domains of OHIP, psychological disability recorded the highest when comparing with smokers and non-smokers. This was in contrast to the study conducted by Sagtani et al.[17] where psychological discomfort recorded the highest mean value.

Correlation analysis demonstrated strong interrelationships among physical pain, functional limitation, physical disability, and handicap domains, highlighting the multidimensional nature of oral health impacts. The exploratory use of Six Sigma analysis identified domains with greater variability, offering an additional perspective on areas that may warrant focused preventive and clinical attention. Overall, these findings emphasize the value of comprehensive oral health strategies that address both physical symptoms and their functional implications in military aviators.

In the present study, approximately 15.8% of aviators reported habitual non-productive clenching or bruxism. Although this prevalence was lower than that reported by Kaushik et al.,[18] who observed a prevalence of 51% among aviation personnel, the finding remains clinically relevant in the context of military aviation. Occupational stress, operational fatigue, altered sleep cycles, high cognitive workload, and anxiety associated with flying duties may contribute to parafunctional habits such as clenching and bruxism. These habits can further aggravate temporomandibular discomfort, tooth wear, muscle fatigue, and functional limitation, thereby negatively influencing oral health-related quality of life. The aviation environment therefore presents unique occupational stressors that may predispose aviators to stress-related oral manifestations compared to the general population.

Limitations

The cross-sectional design of the study limits causal interpretation of the observed associations. Data were collected using a self-reported online questionnaire, which may be subject to recall and social desirability bias. Convenience sampling and the operational dispersion of aviators may restrict the generalizability of the findings to all military aviation settings. In addition, certain variables that may influence OHRQoL, such as associated systemic health conditions, dietary habits, stress levels, sleep disturbances, frequency of dental visits, and accessibility to dental care services, were not evaluated in the present study. These factors may act as potential confounders and should be explored in future studies to provide a more comprehensive understanding of oral health determinants among military aviators. Nevertheless, the large sample size and use of a validated instrument provide meaningful insight into oral health-related quality of life among military aviators.

CONCLUSION

Military aviators generally demonstrate good OHRQoL; however, functional limitation and physical pain remain key determinants influencing their perceived oral well-being. Advancing age, longer service duration, and smoking were significantly associated with poorer OHRQoL. Future research may benefit from longitudinal study designs to evaluate temporal changes in OHRQoL throughout different phases of military service and flying exposure. Incorporating OHRQoL assessments, preventive dental strategies, and targeted smoking cessation interventions into periodic medical evaluations can help detect early deterioration in oral health, ensuring sustained readiness, comfort, and mission capability among aviators.

Ethical approval:

The Institutional Review Board has waived ethical approval for this study. The waiver was granted by the Head of the Institution, 92 Base Hospital, on 25 November 2020, due to the anonymous questionnaire-based design of the study, which involved no physical intervention or collection of identifiable personal information.

Declaration of patient consent:

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient has given consent for clinical information to be reported in the journal. The patient understands that the patient’s names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Conflicts of interest:

There are no conflicts of interest.

Use of artificial intelligence (AI)-assisted technology for manuscript preparation:

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

Financial support and sponsorship: Nil.

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