1. Introduction

From the contemporary definitions of health clinical measures have serious limitations. They tell us nothing about functioning of the oral cavity and symptoms such as pain and discomfort. Furthermore, they do not consider the attitudes and behavior of patients, which in turn influence the effectiveness of treatments in oral health [1]. Additional motivation for measuring both negative and positive changes in oral health status has stimulated the development of sociodental indicators to supplement clinical indicators, by adding a social impact dimension [2]. Sociodental indicators are the measures of oral health-related quality of life (OHRQoL) which have been developed from basic conceptual frameworks of role function.

Oral Impacts on Daily Performance (OIDP) is a newly developed indicator that attempts to measure oral impacts that seriously affect the person’s daily life. OIDP was developed in 1996, earlier it was called as Dental Impacts on Daily Life (DIDL) [3]. OIDP was used first among low dental disease Thai population [4], and in 2003 it was used among Tanzanian students [5]. It is based on an explicit conceptual framework, the World Health Organization’s International Classification of Impairments, Disabilities and Handicaps, ICIDH, which has been amended for dentistry by Locker consisting of the following key points; impairments, functional limitations, pain and discomfort and disability and handicap. Impairments refer to immediate biophysical outcomes of disease, commonly assessed by clinical indicators. Functional limitations are concerned with functioning of body parts whereas pain and discomfort refer to the practical aspects of oral conditions in terms of symptoms. Finally, ultimate outcomes of disability and handicap refer to any difficulty in performing activities of daily living and to broader social disadvantages.

The use of oral health-related quality of life indicators and measures of perceived needs has highlighted the large difference between normative and perceived assessments of dental treatment needs, and demonstrated an inconsistent relationship between clinical measures and oral symptoms and impacts. Overall the associations between clinical indicators of normative needs and measures of oral health-related quality of life were weak. However, the associations were better for specific clinical conditions such as missing teeth, particularly anterior teeth [6]. Because of different findings for overall and specific clinical conditions it was worthwhile an attempt to investigate the relationship between oral health-related quality of life using the OIDP scale and specific clinical dental measures for need assessment among students attending various colleges located in Udaipur city, Rajasthan, India.

2. Materials and methods

3. Results

A total of 800 students [males: 536 (67%) and females 264 (33%)] participated in the survey. Majority perceived their present condition of mouth as good (43.8%) to fair (36%). Reported perceived grades did not show any statistical significance between gender (p = 0.053). Merely over half (57.9%) the subjects were satisfied with appearance of their teeth and the difference observed among gender group was not significant (p = 0.322). Overall proportion of subjects accounted with Oral Impacts on Daily Performance was 60%. Though no statistically significant difference was apparent by gender (p = 0.357) OIDP was more in males (68.3%) than females (31.7%).

Corrected item correlation ranged from 0.40 to 0.68 being above the minimum recommended level of 0.20 for inclusion of items in the scale and meeting the stringent criterion of item convergent validity of >0.40. Cronbach’s alpha of the scale was 0.82 with alpha values (if any item being deleted) lower than original value. The present alpha value falls within a recommended minimum of 0.70 [8]. Finally, test–retest reliability was also found to be satisfactory (ICC = 0.91) (Table 1).

Table 2 illustrates at least one oral impact on daily performance in the last six months among 480 (60%) students. Cleaning was the most commonly affected daily performance (24%), followed by eating (12%) and smiling (12%). Impacts affecting carrying out work (1%) and speaking (2%) were uncommon. Overall mean OIDP score was 2.49 ± 3.92, which ranged from 0.06 ± 0.59 (carrying out work) to 1.60 ± 4.49 (cleaning). Among those participants with impacts, 18.3% reported fairly severe and 3.3% very severe intensity. Smiling (33.3%), emotional stability (33.3%) and social contact (28.6%) predominantly contributed to fairly severe effect. Majority (48%) of the study subjects reported effects on one daily performance and the enduring 11% and 1%, had impacts on two and three daily performances respectively.

Table 3 represents bivariate analysis of relationship between oral impacts on daily performance and clinical status. Significant association (p ⩽ 0.05) was observed in oral impacts on daily performances with age, presence of dental fluorosis, oral mucosal conditions, prosthetic need, caries, CPI score and DAI score. No association (p ⩾ 0.05) was found between oral impacts on daily performance and gender, presence of TMJ clicking, loss of attachment, enamel opacities and prosthetic status, respectively.

Multivariate logistic regression considering association between dependent variable (OIDP) and independent variables is shown in Table 4 . All independent variables that demonstrated significant association with OIDP in bivariate analysis (as in Table 3) were analyzed together after controlling for age. Four significant factors for probability of having one or more impact were identified: presence of oral mucosal condition (OR 4.614, 95% CI:1.800–9.633), presence of caries (OR 4.225, 95% CI:3.039–5.873), prosthetic need (OR 0.486, 95% CI:0.267–0.884) and DAI score, ⩾34/<34 (OR 2.735, 95% CI:1.257–5.952).

Significant association (p ⩽ 0.05) of difficulty in cleaning teeth performance with oral mucosal condition and CPI was found. Eating performance was significantly (p ⩽ 0.05) associated with dental caries, prosthetic need and oral mucosal condition. Dental fluorosis was significantly associated (p ⩽ 0.05) with all performances except eating, cleaning and sleeping and relaxing. TMJ clicking was not associated with any of the performance activity (Table 5 ).

Multivariate logistic regression analysis with each performance activity of OIDP as outcome variable revealed that clinical indicators of oral disorders accounted for 31.4% (Nagelkerke’s R² = 0.314) and 10% (Nagelkerke’s R² = 0.10) of explainable variance for eating and cleaning respectively (Table 6 ). Participants with caries were more likely to have an impact on cleaning (OR = 2.487) and sleeping and relaxing (OR = 8.996) than those without caries. Similarly participants with oral mucosal conditions were more likely to have an impact on eating (OR = 3.97), cleaning (OR = 2.966) and physical activities (OR = 11.190) than those without oral mucosal conditions. DAI impacted more on cleaning (OR = 2.134), emotional stability (OR = 3.957) and social contact (OR = 3.210).

4. Discussion

Execution of epidemiological studies and dissemination of data such as those of the present study seek to advocate that different strategies need to be planned for improvement of the oral health status of the population. Strategies need to take into account both normative and subjective needs as assessed by professionals and socio-dental indicators respectively. Younger individuals perceive oral health as having a greater impact on their life quality than older people. Indeed, many quality of life indicators in dentistry have focused primarily on older age groups, partly on the assumption that they would have had a lifetime’s experience of oral ill health and thus are likely to perceive oral health as having a greater impact on their quality of life [9]. Therefore the present study had focussed on younger age group.

Oral Impacts on Daily Performance (OIDP) is one of the most widely used sociodental indicators which focus on measuring serious oral impacts on a person’s ability to perform daily activities. The approach provides advantages, not only in terms of being easier to measure the behavioral impacts on performances than the feeling-state dimensions, but also in being short [10]. It has been successfully tested for reliability and validity in adult and elderly populations in different settings [11]. In line with previous studies [12,13], all examined relationships between OIDP scores and subjective oral health measures were statistically significant and showed a clear trend in the expected direction; worst the subjective oral health rating, higher the OIDP scores (p < 0.001).

In our study, about 43.8% subjects perceived their present condition of mouth as ‘good’ and 57.9% of subjects were satisfied with the appearance of teeth which is comparable to the findings of Masalu and Astrom (2003) [5]. Proportion of subjects who reported impacts on daily activities at least once or twice a month ranged from 75% concerning physical activities to 0% regarding carrying out work. Comparable with findings of Masalu and Astrom (2002) [14], 32.3% subjects perceived the impact on eating at least once or twice a month.

An unexpectedly high prevalence of young adults (60%) reported that an oral problem had affected them on at least one daily performance in the 6 months preceding the survey which was higher than the prevalence obtained by Masalu and Astrom (2002) [14] in Tanzania (51%), Astrom et al. (2006) [15] in Norway (18.3%) and Soe et al. (2004) [16] in Myanmar (15.8%). This impact was clearly below those of about 70% observed in western populations with high dental disease levels [17,18]. In the present study, OIDP frequency scores showed a significant difference among age groups with younger age groups reporting more impact. Gift et al. (1996) [19] also reported age as a significant predictor of perceived dental status in US adults aged 17–74 years. On the other hand, Locker and Miller [17,20] found younger Canadians to be as likely as their older counterparts to report impacts of oral diseases.

Apart from methodological differences such as variations in measures of oral health related quality of life that has been used, there are several reasons as to why the prevalence of oral impacts could vary between populations. First, as the prevalence and severity of oral conditions vary among populations in different countries, they may also experience oral impacts related to different aspects of their lives in varying frequencies. Secondly, people of different social, cultural and ethnic groups differ in their perception of what aspects of their oral health will affect their quality of life. Thirdly, values and attitudes toward oral health could strongly influence the reporting of impacts. Individuals who place little value on their teeth are probably less likely to report being self conscious or emotionally disturbed due to their oral health. Fourthly, the phenomenon of “internalization” or “adaptation” by which an individual learns to live with the symptoms could influence the reporting of impacts. For example, an individual who had experienced tooth loss could adapt to such a condition and may respond by learning to live with the symptoms such as difficulty in chewing. As a consequence the symptoms may not have an impact on the individual [21].

Despite the fact that oral impacts were very frequent among Udaipur college students, they were not severe; this population had a mean OIDP score of 2.49 ± 3.92 and almost half of those with impacts had very minor or fairly minor severity of impacts which is in conformity with results obtained by Astrom and Okullo (2003) [2] among students with a mean age of 16.3 years. Around two third participants reported an impact only on 1 or 2 performances. Consistent with results reported in previous OIDP surveys [4,5,22,23], difficulty with eating, cleaning teeth and smiling were the impacts most frequently reported.

By examining relationships between OHRQoL and clinical variables in a single regression model, it was possible to obtain better understanding of combined effects of these variables and to compare the predictive power of each. In regard to temporomandibular joint assessment, TMJ clicking was the only sign observed, prevalence being 1.7% which was lower compared to study conducted by Vojdani et al. (2012) [24]. TMJ clicking was found to be significantly associated with sleeping and relaxing (OR = 6.029) which is in accordance with previous evidence [25].

Results of the present study pointed out a significant impact of oral mucosal conditions on eating, cleaning and physical activities (OR = 3.97, 2.966, 11.190). Comparable results were concluded in another study by Suliman et al. (2012) [26]. Oral lesions can cause discomfort or pain that interferes with mastication, swallowing, and speech, and they can produce symptoms such as halitosis, xerostomia, or oral dysesthesia, which interfere with daily social activities [27].

The presence of developmental defects of enamel did not have any significant impact on any of the performances which is in harmony with the preceding survey [28]. However, fluorosis was almost thrice as likely to report an impact on smiling (OR = 2.836), emotional stability (OR = 2.572) and social contact (OR = 3.156), indicating Udaipur students concern about their dental appearance. This finding was supported by a previous research conducted by Crosato et al. (2005) [29].

Wandera et al. [30] provided confirmation to non significant associations between OIDP and CPI and with regard to individual items, between cleaning teeth (OR = 1.164) performance and clinical periodontal status. The reason behind this could be bleeding gums as perceived by a majority (56.3%) of the students. In another study conducted by Adulyanon (1996) [4], cleaning teeth was impacted chiefly by gum abscess (28.6%), toothache (23.3%) and oral ulcer (12.6%). The present study depicted a non-significant impact of loss of attachment on performances which is in conformity with the results obtained by Needleman et al. (2004) [31]. However, this diverges from findings of Ng and Leung (2006) [32], where a significant impact was observed. Disease does not always negatively affect subjective perceptions of well-being, and when it does; its impact is influenced by nature of the disease as well as expectation, preferences and financial, social and psychological resources [33].

Untreated dental caries were strongly associated with OIDP (OR = 4.225), corroborating with previous studies [34,35]. Reason could be attributed to dental pain resulting from dental caries, a finding observed in a similar study [36]. Cleaning, sleeping and relaxing were most frequently affected performances (OR = 2.487, 8.996) as a consequence of caries substantiated by another study in which sleeping and cleaning performances were associated with pain resulting from tooth decay [37].

Participants with prosthesis were about 2.9 times more likely to report impact on smiling than those without prosthesis. Impact of prosthetic status on daily performances might have resulted from inadequate adaptation, retention or extension of the prosthesis. These significant differences in the experience of oral impacts were expected, because partially edentulous subjects with aforementioned denture deficiencies might experience increased functional difficulties such as eating, speaking, avoiding smiling as well as other psychological and social impacts [3]. Consistent with the odds reported by other researchers [2], the present data revealed a significant impact of tooth loss on eating (OR = 4.246). Loss of posterior teeth is the main cause of chewing deficiency [38].

In accordance with the previous study [39], considering psychosocial impacts of student’s orthodontic status, the present results suggested that malocclusion was significantly associated to OIDP (OR = 2.735), predominantly emotional stability (OR = 3.957), cleaning teeth (OR = 2.314) and social contact (OR = 3.21). Reason could be attributed to facial appearance which plays an important psychosocial role in individual’s life and interpersonal relations. Furthermore, dentofacial esthetics and self-perceptions of occlusal appearance as well as attitudes toward malocclusion and orthodontic treatment are important factors in deciding to seek orthodontic treatment.

Main limitation in our study is its cross-sectional nature which poses problems in relation to hypothesis testing since data on risk factors and outcome are assessed at the same time, but this particular issue does not seem to affect our result. An imbalance in the number of males and females in our study sample may also be a limitation since the impact of oral conditions could be different in relation to sex. Future longitudinal studies are needed to better understand and interpret OHRQoL measures in students; although these are difficult to conduct in developing countries due to financial restraints and lack of population records. Further research is also recommended to assess whether measures of oral health-related quality of life as a patient-centered outcome are sensitive to changes in clinical dental status over time and also at the level of the individual.

In conclusion, a strong and consistent relationship between most of the clinical measures of oral health status and perceived impacts in college students was observed. These findings have significant implications for employment of patient-centered outcome measures as objective clinical parameters of dental diseases in assessment, planning and provision of treatment, and subsequent evaluation of care. Professionals perhaps need to utilize this tool to evaluate if successful therapist-centered outcome co-relates with patient-centered outcome.

Authors contributions

RN contributed with the design, acquisition, analysis and interpretation of data and took part in drafting of the manuscript. MB contributed with the design, analysis and interpretation of data and took part in drafting of the manuscript. SS, HD and GR contributed with drafting of the manuscript, analysis and interpretation of data and revised it critically. All authors listed on the title page have read the manuscript, attest to the validity and legitimacy of the data and its interpretation, and agree to its submission.

Conflict of interest

None declared.

Source of funding

Nil.

Acknowledgements

The authors would like to thank the study participants for their participation and kind cooperation throughout the study.