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International Journal of Oral Health and Medical Research | ISSN 2395-7387 | JULY-AUGUST 2016 | VOL 3 | ISSUE 2
8
ORIGINAL RESEARCH
Nagaland T et al.: Personality traits, tooth loss and OHRQoL
Correspondence to:
Dr.
Nagaland T,
Public Health Dentistry, V S Dental
College and Hospital Bengaluru, Karnataka.
Contact Us: www.ijohmr.com
Is There an Association of Self-Esteem and
Negative Affectivity with Oral Health Related
Quality of Life in Patients with Tooth Loss? :
A Hospital Based Study
Nagaland T1, Sushi Kadanakuppe2, Rekha Raju3
Context:
Introduction: To meaningfully interpret the oral health-related quality of life measures, the association of personality
traits must be investigated. Aim: To determine the association of self esteem and negative affectivity with oral health
related quality of life in patients with tooth loss. Methodology: OHRQoL measured by the Oral Health Impact Profile
14 (OHIP-14), self-esteem measured by the Rosenberg Self-Esteem Scale (RSES), Negative affectivity (NA) measured
by the Eysenck Personality Inventory Questionnaire (EPI-Q), global oral rating of oral comfort and controlling
variables like gender, age, number of teeth, experience of wearing Removable Partial Denture (RPD), Complete
Denture (CD), location of missing teeth and zone of missing teeth were collected from 91 patients with tooth loss,
signed in for treatment with RPD and CD. Results: Pearson correlation test showed the association of negative
affectivity on oral health related quality of life and the result was statistically significant. In the multivariate analysis,
the controlling variables alone explained 22.7% of the variance in the OHIP-14 score, while the addition of EPI-Q score
and RSES score individually, and both together explained additionally 10.2%, 0.1%, and 12.5% respectively. For each
unit increase in EPI-Q score and RSES score, the OHIP-14 score increased 1.97 times and 0.34 times. Conclusion:
Negative affectivity was found to influence OHRQoL. This indicates the possibility to explain some of the impact of
tooth loss on OHRQoL based on personality traits.
KEYWORDS: Behavioural Science, Personality Traits, Tooth Loss, OHRQoL
AA
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Edentulism, either partial or complete is a debilitating,
and irreversible condition described as ―final marker of
disease burden on oral health.1‖ There are many variables
affecting the quality of life out of which tooth loss is one
of the premier factors. The loss of one or more teeth can
have profound effects on an individual‘s oral health and
quality of life. A lot of measures have been introduced to
measure and describe the oral health-related quality of
life (OHRQoL).2 Interpretation of these measures must be
carried out not only with regard to the psychometric
properties such as validity and reliability, but contextual
factors must also be included in the interpretation.3
Factors such as age, gender, dental status variables, socio-
economic status, self-reported oral health, dental
attendance, and personality traits might influence
patient‘s assessment.4 To interpret the OHRQoL
measures meaningfully, it is necessary to understand the
influence of personality traits on them.5 It is especially
interesting if the OHRQoL measures are used to guide
clinical decisions3; by investigating the influence, that is a
mediating role, of personality traits on OHRQOL in
patients with tooth loss, the clinician could take it into
account the treatment planning and could better inform
the patient of the impact of tooth loss.
In the case of tooth loss, the indication for treatment is
impaired function, which can be determined only by
incorporating the patient in the decision making.6
Without clarifying the patient‘s need before treatment, a
potential for treatment failure occurs.7 Not all teeth need
to be replaced, and a high prevalence of RPDs or CDs are
not accepted by patients.8 This implies that use of
OHRQoL measures in this patient group is highly
indicated. It is not known, however, if differences in
personality traits influence the impact of tooth loss in
patients with partial/complete tooth loss about to receive
an denture.
Negative affectivity (NA) is a personality variable that
involves the experience of negative emotions (such as
anger, contempt, disgust, guilt, and fear, and
nervousness) and poor self-concept.9 More complaints
and more diffuse and widespread complaints have been
found in patients with high NA compared to persons with
How to cite this article:
Nagaland T, Kadanakuppe S, Raju R. Is There an Association of Self-Esteem and Negative Affectivity with Oral Health Related Quality of Life in
Patients with Tooth Loss? : A Hospital Based Study. Int J Oral Health Med Res 2016;3(2):8-12.
INTRODUCTION
1-Post Graduate student, Public Health Dentistry, V S Dental College and Hospital
Bengaluru, Karnataka. 2- Senior Lecturer, Public Health Dentistry, V S Dental College and
Hospital Bengaluru, Karnataka. 3- Professor and Head of the Department, Public Health
Dentistry, V S Dental College and Hospital Bengaluru, Karnataka.
ABSTRACT
International Journal of Oral Health and Medical Research | ISSN 2395-7387 | JULY-AUGUST 2016 | VOL 3 | ISSUE 2
9
ORIGINAL RESEARCH
Nagaland T et al.: Personality traits, tooth loss and OHRQoL
low NA.10 As the complaints in patients with partial tooth
loss are the primary basis for treatment, it would be
highly relevant to include NA in the interpretation of
OHRQoL in this patient group.
Another personality trait important for quality of life is
self-esteem.5 The impact of oral treatments on self-
esteem has been investigated to some extent 11, whereas
the influence of self esteem on OHRQoL in patients with
partial tooth loss has not been described. In medicine,
self-esteem has been reported to be an important factor to
be considered when predicting the outcome of health
treatments.12 Self-esteem has further been said to be
captured by OHRQoL measures13 and was therefore also
thought to be a relevant personality trait to include in this
study.
The overall purpose of this study was to determine the
association of negative affectivity and self esteem with
OHRQoL in patients with tooth loss about to receive a
denture.
The present cross sectional study was conducted in May
and June 2015 among the subjects with tooth loss of
either sex signed in for treatment with Removable Partial
Denture AND/OR Complete Denture attending the
Department of Prosthodontics at Vokkaligara Sangha
Dental college and Hospital, Bengaluru. Ethical clearance
was obtained from institution review board of V.S Dental
College and Hospital. Informed consent was obtained
from study participants. If patients were presenting with
acute pain, profound carious lesions, periodontal
treatment, temporomandibular joint treatment and
patients who were not voluntarily interested to participate
in the study are excluded.
Finally, a total of 91 study participants were included in
the study based on convenience. The required sample size
to detect a correlation coefficient of -0.31 at the
significance level of 5% (α = 0.05) and power 90% (β =
0.1) is Sample size, N = {(1.64+1.28)/-0.31}2 + 3 =
91.54 ~ 91.
Rosenberg’s self-esteem scale: The Rosenberg Self-
esteem Scale14 (RSES) consisted of 10 items regarding
self-esteem, each item was rated on a 4-point response
scale, 1 being ‗strongly agree‘ and 4 being ‗strongly
disagree.‘ Five items were positively worded (item
1,3,4,7,10), and 5 were negatively worded (item
2,5,6,8,9). The scores for the positively worded items
were in the analysis inversed so that a score of 1
(‗strongly agree‘) was set to 4. The addition of the item
scores gave an overall score from 10-40 with a higher
score indicating higher self-esteem.
Eysenck Personality Inventory Questionnaire:
Negative affectivity (NA) was measured by the Eysenck
Personality Inventory Questionnaire (EPI-Q)15, which
consisted of nine questions regarding affection with
dichotomous answers(yes/no). A point was given each
time a question was answered ‗yes‘ giving a final score
for each participant between 0 and 9 and a higher score
indicating higher NA.
OHIP-14 Questionnaire: The Oral Health Impact
Profile (OHIP-14) questionnaire a shorter version of the
original tool which comprises of 49 questions (developed
in Australia by Slade and Spencer in 1994)16, is one of
the most technically sophisticated instruments for
assessing OHRQoL.17 The participants answered how
often each problem had occurred during the past month
on a scale with six choices and according to scores: (5)
All the time, (4) very often, (3) fairly often, (2)
sometimes, (1) seldom, (0) never. The overall OHIP-14
score (0-28) was calculated by adding the 14 answers for
each participant. The final OHIP-14 scores were
categorized as follows: 0-no impact, 1-3—low impact, 4-
6—medium impact, 7-10—negative impact, 11-16—high
negative impact 18.
Rating of Oral Comfort: To further investigate the
influence of NA and self-esteem on OHRQoL, the current
oral comfort was rated on a 5-point response scale from
1=‘very poor‘ to 5=‘very good‘. For analytical purposes,
the ratings were divided into the groups (i) good oral
comfort (score 4 and 5), (ii) ok oral comfort (score 3) and
(iii) poor oral comfort (score 1 and 2).
Controlling variables: After oral examination and
history takings, the controlling variables considered in the
study were age, gender, the number of teeth, the
experience of wearing RPD, CD(yes/no), the location of
missing teeth to be replaced (one jaw or both), and zone
of missing teeth to be replaced (masticatory or
masticatory/aesthetic). The aesthetic zone was defined as
incisors, canines, and 1st premolars in the upper jaw and
incisors and canines in the lower jaw. The upper 2nd
premolars/lower both premolars, and 1st and 2nd molars of
both the jaws were defined as masticatory zone in the
case of partial tooth loss. In patients with complete tooth
loss, their experience of wearing of CD (yes/no) and
location of missing teeth to be replaced (one jaw or both)
were taken into consideration.
Statistical analysis: Data analysis was carried out using
SPSS software version 20.0 (SPSS Inc., Chicago, IL,
USA). The correlations above 0.40 were considered
acceptable with 5% significance. Descriptive statistics
was used to calculate the distribution of participants
according to controlling variables and the distribution of
the OHIP-14, EPIQ and RSES scores. The influence of
gender, the experience of wearing RPD, location of
missing teeth and zone of missing teeth was calculated
using ANOVA. Student‘s t-tests were used to investigate
the difference in EPI-Q and RSES score between
participants with the good and poor rating of oral
comfort. The differences were clinically evaluated by
comparing them to the needed difference calculated from
the parameter estimates. Pearson‘s correlation was used
to test the correlation between EPI-Q score and RSES
score
The amount of variance in OHIP-14 score explained by
the EPI-Q score and RSES score was calculated using
MATERIALS AND METHODS
International Journal of Oral Health and Medical Research | ISSN 2395-7387 | JULY-AUGUST 2016 | VOL 3 | ISSUE 2
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ORIGINAL RESEARCH
Nagaland T et al.: Personality traits, tooth loss and OHRQoL
general linear models to create four multivariate models
from which the R-squared value was used: Controlling
variables were included in the first model, followed by
EPI-Q score in second, RSES score in third, both EPI-Q
and RSES scores in the fourth and final model. Parameter
estimates were derived from the final model to quantify
the influence of the personality traits on the OHIP-14
score.
Distributions: The distribution of OHIP-14, EPI-Q, and
RSES scores, as well as the distribution of the
participants according to age, gender, number of teeth,
location, and zone of missing teeth are presented in Table
1.
Distributions
N=91
OHIP-14 score
(Mean)
EPIQ (Mean)
RSES (Mean)
Age (Mean)
Gender
Male
Female
Number of teeth (Range)
Location of missing teeth
One jaw
Both
Zone of missing teeth
Aesthetic
Masticatory
16.25 (2-33)
4.38 (2-7)
20.8 (13-28)
58.2 (32-78)
56
35
13.53 (0-30)
17
74
78
87
Rating of oral comfort: The mean RSES scores in
participants reporting good, ok and poor oral comfort was
20.50, 20.67, and 20.75; EPI-Q scores 4.50, 4.61 and
3.75; the mean OHIP-14 scores 10.75, 18.61 and 17.17
respectively. The difference in EPI-Q score between
participants reporting good oral comfort and participants
reporting poor oral comfort was not significant. The
difference in RSES score between participants reporting
good oral comfort and participants reporting poor oral
comfort was not significant. The difference in OHIP-14
score between participants reporting good oral comfort
and participants reporting poor oral comfort was not
significant.
Correlation analysis: The correlation analysis of the
independent variables with the controlling variables is
shown in Table 2. Among the variables, A weak positive
association was found between age and oral health
quality of life with a significance of P=0.001. A weak
positive association was found between negative
affectivity and type of denture wearing with the oral
health related quality of life which was significant. A
little or no association was found between socioeconomic
status and self esteem which was clinically significant. A
significant result was found between negative affectivity
and self esteem (P=0.004), and negative affectivity and
oral health quality of life (P=0.000) with a weak positive
association. A little association was found between self
esteem and negative affectivity, and the result was
significant.
Multivariate models: The results from the multivariate
models created to explain the variance in OHIP-14 scores
are shown. The addition of EPI-Q score to the first model
of controlling variables (22.7%) explained additional
10.5% of the variance, while the addition of RSES score
to the first model explained additional 0.1% of the the
variance. The addition of both EPI-Q and RSES score
provided a 35.1% increase in R-square.(Table 3)
The parameter estimates from the final model showed
that for each unit increase in EPI-Q, the OHIP-14 score
increased by a statistically significant of 1.97 times, and
for each unit increase in RSES score, the OHIP-14 score
increased by a statistically non significant 0348 units.
Similarly for each unit increase in age, the OHIP-14 score
increased by statistically significant of 0.18 times.
The increase in population with tooth loss was widely
discussed in social implications in different sectors but
particularly in health related sectors. Oral health is one of
the relevant aspects to analyze in social implications of
the tooth loss population. Negative affectivity and self
esteem are one of the personal traits which play a role in
the quality of life including oral health in the population.
So an attempt was made to assess the association of self
esteem and negative affectivity on oral health related
quality of life of patients with tooth loss.
Majority of the study subjects were male (61.5%) which
was similar to the study done by Torres et al. and most of
the participants belonged to 51-60 year age group. Most
of the study participants belonged to middle/lower middle
class. The controlling variables (i.e. age, gender, the
number of teeth, the experience of RDP and CD, location
and zone of missing teeth) were selected as they were
thought to potentially influence the OHIP- 14 score in the
study population.
Baron and Kenny19 explained that ‗a given variable is
said to function as a mediator to an extent when it
accounts for the relation between the predictor and the
criterion.‘ In this study, it was aimed to determine the
association self-esteem and NA on the OHRQoL and
thereby be seen as mediators of the relationship between
tooth loss and OHRQoL. The relationship between
subjective and objective variables is complex, however,
and different methods for investigating such relationships
have been used. Since the main purpose of this study was
to determine the association of the two known personality
traits and the population size was limited, it seemed to be
sufficient using general linear models, which also
allowed for quantification of the influence. This is in line
with Kressin et al3, who used the same method for
investigating the association between NA and OHRQoL.
From the multivariate analyses, it was found that NA had
the greatest single influence of the explaining variables; it
RESULTS
Table 1. Distribution of OHIP-14, EPI-Q AND RSES scores and the
participants according to controlling variables (range)
DISCUSSION
International Journal of Oral Health and Medical Research | ISSN 2395-7387 | JULY-AUGUST 2016 | VOL 3 | ISSUE 2
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ORIGINAL RESEARCH
Nagaland T et al.: Personality traits, tooth loss and OHRQoL
increased the explanation percentage of the variance in
OHIP-14 score by well over half of what the controlling
variables accounted for combined, and the parameter
estimate was highly significant. The direct correlation
with the OHIP-14 score was acceptable. Compared to
other studies correlating NA to the OHIP score, the R-
value of 0.59 found in this study is a little higher:
Brennan et al4 found a correlation of R = 0.36 in a large
random sampled Australian population and Kressin et al.3
found a correlation of R = 0.46 in a large population of
older men. The association of self-esteem in this study
was negative; a large increase in the explanation
percentage was found, but the weak direct correlation
with the OHIP-14 score was found.
Few other studies have investigated the relationship
between self esteem and OHRQoL. As in this study,
Agou et al5 found a low but significant negative
correlation between self-esteem and OHRQoL in a group
of children seeking orthodontic treatment. Along with the
significant relationship of high NA and poor oral comfort
found in this study, this indicates that the personality
traits, in fact, have an association with OHRQoL in the
study population.
The greatest influence on the OHIP-14 score in this study
was found when was accounted for in the multivariate
model, that is, the additional variance was explained
compared to when NA and self-esteem were added alone.
This may be expected as the correlation between NA and
self-esteem, even though, was low. This also makes it
unlikely that collinearity problems occurred. When the
influence of the personality traits was quantified, it was
found that for each unit increase in EPI-Q score and
RSES score, the OHIP-14 score increased by a
statistically significant 1.97 and nonsignificant 0.34 units,
respectively.
In a somewhat similar patient group as this, John et al20
estimated the minimally important difference for the
OHIP-14 questionnaire to be between 2 and 9 units.
These estimates can be used to understand the clinically
meaning of the EPI-Q and the RSES. The results further
showed that the reason for the clinical significant
difference in EPI-Q score was related to the association
between poor oral comfort and high NA; a significant
difference in EPI-Q score between participants reporting
poor and ok oral comfort was also seen.
The multivariate analyses showed that the controlling
variables indeed explained some of the variance in the
OHIP-14 score, and the bivariate analyses showed that
the high age span in the study population especially
influenced the OHIP-14 score. It is recognized that the
controlling variables in this study do not encompass all
OHRQoL aspects, and other dental status variables,
socioeconomic status, and dental attendance could
account for additional variance in the OHIP-14 score.
The present study cannot yield conclusive data on
causality because of its cross-sectional design. Even
though the study population was large enough to produce
significant results, the population was selected from a
dental college and hospital, and the results, therefore,
might not be generalized to the entire population. Dental
attendance might account for additional variance in the
OHIP-14 score11. Social desirability bias may also exist.
Correlations
OHIP-
14
CE-A (no.
of teeth
present)
Age
(in
year)
Gender
Socioeconomic
status
Self-
esteem
score
Eysenck
personality
questionnaire
Type of
denture
OHIP-14
Pearson
Correlation
1
-.282**
.357**
.107
-.016
-.021
.445**
.231*
P value
.007*
.001*
.314
.880
.845
.000*
.027*
Self-esteem
score
Pearson
Correlation
-.021
.033
.000
-.099
-.299**
1
-.383**
-.062
P value
.845
.753
.996
.349
.004*
.000*
.558
Eysenck
personality
questionnaire
Pearson
Correlation
.445**
-.092
.088
.155
.133
-.383**
1
.173
P value
.000*
.388
.408
.142
.208
.000*
.101
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Table 2: Correlation between OHIP-14, self esteem and EPIQ with no. of teeth present, age, gender, socioeconomic status, self esteem, EPIQ,
and type of denture wearing.
Multivariate analysis
R2
Explaining percentages of variance in OHIP-14 score
Model 1. Controlling variables
Model 2. Controlling variables+EPI-Q
Model 3. Controlling variables+RSES
Model 4. Controlling variables+EPI-Q+RSES
22.7%
33.2%
22.8%
35.1%
PARAMETER ESTIMATES FROM MODEL 4
Age (in years)
0.186 (0.75)*
Gender
1.078 (1.33)
Socioeconomic status
--0.184 (0.95)
ROC-A
--0.025 (0.81)
CE-A (no. of teeth present)
0.518 (0.44)
CE-CA (aesthetic zone)
0.546 (0.53)
CE-CM (masticatory zone)
0.725 (0.57)
Self-esteem score
0.348 (0.23)
Eysenck personality questionnaire
1.970 (0.50)*
Table 3: Multivariate models explaining the variance in OHIP-14 score and parameter estimates (SE) from the final model.
(Dependent Variable: OHIP-14, *P<0.05)
International Journal of Oral Health and Medical Research | ISSN 2395-7387 | JULY-AUGUST 2016 | VOL 3 | ISSUE 2
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ORIGINAL RESEARCH
Nagaland T et al.: Personality traits, tooth loss and OHRQoL
Longitudinal studies are required to further address a
conclusive data on the causality. The additional variances
that might influence Oral Health Related Quality of Life
can be added. Studies should be done to know the
association of other personality traits such as Openness to
experience, Extraversion, and Agreeableness on
OHRQoL in tooth loss patients.
An association was found between negative affectivity
and oral health quality of life whereas no association was
found between self esteem and oral health quality of life
in the study participants. High negative affectivity was
associated with worse oral health related quality of life. If
OHRQoL measures are used to guide clinical decisions, it
is thus important to determine whether the impact of
tooth loss is in a part of the function of high negative
affectivity. As the negative affectivity was the trait
influencing OHRQoL, it may not clinically indicate
worse oral health but could reflect a person‘s disposition
to view things negatively. The question remains,
however, if these persons benefit from treatment to the
same extent as persons with a more positive attitude.
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REFERENCES
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Conflict of Interest: Nil