Socio-demographic and behavioural correlates of oral hygiene status and oral health related quality of life, the Limpopo-Arusha school health project (LASH): a cross-sectional study.

Abstract

Promoting oral health of adolescents is important for improvement of oral health globally. This study used baseline-data from LASH-project targeting secondary students to; 1) assess frequency of poor oral hygiene status and oral impacts on daily performances, OIDP, by socio-demographic and behavioural characteristics, 2) examine whether socio-economic and behavioural correlates of oral hygiene status and OIDP differed by gender and 3) examine whether socio-demographic disparity in oral health was explained by oral health-related behaviours.
Cross-sectional study was conducted in 2009 using one-stage cluster sampling design. Total of 2412 students (mean age 15.2 yr) completed self-administered questionnaires, whereas 1077 (mean age 14.9 yr) underwent dental-examination. Bivariate analyses were conducted using cross-tabulations and chi-square statistics. Multiple variable analyses were conducted using stepwise standardized logistic regression (SLR) with odds ratios and 95% Confidence intervals (CI).
44.8% presented with fair to poor OHIS and 48.2% reported any OIDP. Older students, those from low socio-economic status families, had parents who couldn't afford dental care and had low educational-level reported oral impacts, poor oral hygiene, irregular toothbrushing, less dental attendance and fewer intakes of sugar-sweetened drinks more frequently than their counterparts. Stepwise logistic regression revealed that reporting any OIDP was independently associated with; older age-groups, parents do not afford dental care, smoking experience, no dental visits and fewer intakes of sugar-sweetened soft drinks. Behavioural factors accounted partly for association between low family SES and OIDP. Low family SES, no dental attendance and smoking experience were most important in males. Low family SES and fewer intakes of sugar-sweetened soft drinks were the most important correlates in females. Socio-behavioural factors associated with higher odds ratios for poor OHIS were; older age, belonging to the poorest household category and having parents who did not afford dental care across both genders.
Disparities in oral hygiene status and OIDP existed in relation to age, affording dental care, smoking and intake of sugar sweetened soft drinks. Gender differences should be considered in intervention studies, and modifiable behaviours have some relevance in reducing social disparity in oral health.

Full text

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RESEARCH ARTICLEOpen Access
Socio-demographic and behavioural correlates of
oral hygiene status and oral health related quality
of life, the Limpopo - Arusha school health
project (LASH): A cross-sectional study
Hawa S Mbawalla1,2,3*, Joyce R Masalu3, Anne N Åstrøm1,2
Abstract
Background: Promoting oral health of adolescents is important for improvement of oral health globally. This study
used baseline-data from LASH-project targeting secondary students to; 1) assess frequency of poor oral hygiene
status and oral impacts on daily performances, OIDP, by socio-demographic and behavioural characteristics,
2) examine whether socio-economic and behavioural correlates of oral hygiene status and OIDP differed by gender
and 3) examine whether socio-demographic disparity in oral health was explained by oral health-related behaviours.
Methods: Cross-sectional study was conducted in 2009 using one-stage cluster sampling design. Total of 2412
students (mean age 15.2 yr) completed self-administered questionnaires, whereas 1077 (mean age 14.9 yr)
underwent dental-examination. Bivariate analyses were conducted using cross-tabulations and chi-square statistics.
Multiple variable analyses were conducted using stepwise standardized logistic regression (SLR) with odds ratios
and 95% Confidence intervals (CI).
Results: 44.8% presented with fair to poor OHIS and 48.2% reported any OIDP. Older students, those from low
socio-economic status families, had parents who couldn’t afford dental care and had low educational-level
reported oral impacts, poor oral hygiene, irregular toothbrushing, less dental attendance and fewer intakes of
sugar-sweetened drinks more frequently than their counterparts. Stepwise logistic regression revealed that
reporting any OIDP was independently associated with; older age-groups, parents do not afford dental care,
smoking experience, no dental visits and fewer intakes of sugar-sweetened soft drinks. Behavioural factors
accounted partly for association between low family SES and OIDP. Low family SES, no dental attendance and
smoking experience were most important in males. Low family SES and fewer intakes of sugar-sweetened soft
drinks were the most important correlates in females.
Socio-behavioural factors associated with higher odds ratios for poor OHIS were; older age, belonging to the poor-
est household category and having parents who did not afford dental care across both genders.
Conclusion: Disparities in oral hygiene status and OIDP existed in relation to age, affording dental care, smoking
and intake of sugar sweetened soft drinks. Gender differences should be considered in intervention studies, and
modifiable behaviours have some relevance in reducing social disparity in oral health.
* Correspondence: hawa.mbawalla@student.uib.no
1Department of Clinical Dentistry, Community Dentistry, University of Bergen,
Bergen, Norway
Full list of author information is available at the end of the article
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Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
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Background
Promoting oral health of adolescents through health pro-
moting schools has been prioritized by the World Health
Organization (WHO) for the improvement of oral health
globally [1]. Adolescents are in particular need for oral
health promoting programs [2]. Poor oral hygiene in terms
of increasing accumulation of plaque and calculus with
increasing age have been reported among children and
adolescents in both developed- and developing countries
[2,3]. This situation might lead to periodontal problems
later in adult life. In Tanzania, the Ministry of Health
Policy guidelines have outlined periodontal problems to
account for 80% of all oral diseases in the population [4].
Poor oral hygiene in the general Tanzanian population
aged 15 years and above is very common (65-99%) with
prevalence of gingivitis ranging from 80-90% [5,6]. Accord-
ing to Kerosuo et al [7], a substantial proportion of school
students aged 12-18 years and, girls less seriously than
boys, presents with sign of gingivitis. In contrast, Kikwilu
[8] found a low prevalence of gingivitis and good oral
hygiene status among school children in Morogoro.
Appropriate use of inter-dental measures, fluorides, den-
tal services and tooth brushing, restricted frequency sugar
intake and avoidance of tobacco consumption contributes
to the prevention and control of oral diseases [1].
A recently published national report considering 13-15
years old Tanzanian adolescents showed that about 90%
reported daily tooth brushing, whereas the prevalence of
adolescents confirming daily intake of sugar products
remained at a moderate level [9,10]. Studies have yielded
lifetime prevalence rates of tobacco use, ranging from
0.4% to 12% in female- and male adolescents, respectively
[9]. Other studies from East Africa focusing adolescents
and young adults have reported similar results with
respect to oral health enhancing- and oral health detri-
mental behaviours [11,12].
Untreated oral diseases might lead to dental pain, dys-
function and problems with daily activities [11,13]. To
date, oral health related quality of life, OHRQoL,
pertaining, to the child- and adolescent populations of
Sub-Saharan Africa have been given little attention in
the literature. Few studies have assessed the socio-beha-
vioural distribution of OHRQoL and its relationship
with clinical indicators of oral hygiene status has yet to
be investigated in younger age groups. Instruments are
now available for measuring OHRQoL in school-aged
children. The Child-OIDP was developed and tested
among Thai schoolchildren aged 11-12 yr [14]. It has
been found to be a reliable and valid instrument when
applied for instance to children and adolescents in Tan-
zania, France and UK [11,13,15,16].
Socio-economic status has a profound effect on health-
and health behaviours [17]. However, inequality in health
and oral health has not been focused to the same extent
in adolescents as in adults [18,19]. Evidently, the lower
the material standard of living as measured by income,
social class and social network- and support, the worse
the level of oral health, whatever the measures used,
being they clinical or self-reported oral health indicators
[17]. The World Health Organization (WHO) Interna-
tional Collaborative studies (ICS-I or II), have demon-
strated a social gradient in adolescents’ caries experience
and periodontal status across high-and low income coun-
tries and various oral health care service systems [20].
Moreover, social disparities in adolescents’ oral health
behaviours have been demonstrated in developing coun-
tries and elsewhere, with oral health detrimental
behaviours being most common in subjects of lower
socio-economic status [20]. In Tanzania, previous studies
have not given any clear-cut conclusion regarding the
relationship between social status and indicators for oral
health among children and adolescents.
Owing to scarce resources within the Tanzanian
health care sector, it is important to select preventive
strategies requiring few resources. It is evident, that oral
health interventions through school can improve oral
health and oral health related behaviour among adoles-
cents [21]. Youth is believed to be an important period
for learning and maintaining health related activities
that may carry over into adulthood [22]. Although the
Tanzanian oral health policy gives priority to children
and adolescents as target groups for health care services,
the oral health status and associated life style patterns of
this age group are not well documented.
This study uses baseline data from a cluster rando-
mized trial, integrating oral health into a health promot-
ing school programme (LASH), to describe patterns of
oral health status and oral health behaviours among sec-
ondary school students in Arusha, northern Tanzania.
The aims were; 1) to assess the frequency of poor oral
hygiene status and oral impacts on daily performances,
OIDP, by socio-demographic- and behavioural indica-
tors, 2) to examine whether socio-economic and beha-
vioural correlates of oral hygiene status and OIDP
differed by gender and 3) to examine whether socio-
demographic disparity in oral health outcomes was
explained by oral health behaviours. It was hypothesized
that, socio-demographic factors influence oral health
outcomes directly or indirectly through oral health
related behaviours.
Methods
Sampling procedure
A cross sectional study was performed in Arusha, north-
ern Tanzania, focusing secondary school students. In
this study area, fluoride concentration in drinking water
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has been estimated to amount to 3.6 mg fluoride/l
drinking water and dental fluorosis is recognized to be
endemic [23]. A total of 59 public secondary schools
were listed of which 31 schools fulfilled the inclusion
criteria of being public schools and having student
enrolment of more than 200 students. A sample size of
2000 students was estimated to be satisfactory; assuming
that the percentage of students expected to have oral
impacts on daily performance was 30%, using an abso-
lute precision (d) of 0.02 and 95% confidence interval
(CI) [24]. A one staged stratified cluster design was uti-
lized with secondary school as the primary sampling
unit. Secondary schools (n = 31) in the Arusha munici-
pality, Arusha and Meru council were stratified into
rural and urban schools, the latter being those within 10
km from Arusha town centre. A total of 11 urban
schools (N = 7533 in form I and II) and 20 rural schools
(N = 9141 in form I and II) constituted the sampling
frame. In the first stage, 10 schools were selected by
simple random sampling from rural (k = 10/20) and
urban (k = 10/11) schools using an unequal sampling
fraction. All available students in Form I and II in the
selected urban (1487 out of a total of 4933) and rural
(1501 out of a total of 3338) schools were invited to
participate in the study. Totals of 1163 and 1249 stu-
dents in urban and rural schools were subsequently
included into the study. The total participation rate was
80.7%. This selection procedure provided a non-self
weighted sample of secondary school students in the
area. A total of 1077 out of 1331 (participation rate
80.9%) participants enrolled in a random sub sample of
10 schools (5 urban and 5 rural) consented to undergo
a full mouth clinical oral examination. The clinical oral
examination was conducted in three consecutive days
starting from the same day as the main questionnaire
survey. Reasons for non-participation in the clinical
examination were mainly due to loss of identification
numbers for matching purposes, absence from school
on the day of examination and dental fear. Parents and
students gave written informed consent to participate
both in the main questionnaire survey and the clinical
examination. Permission to conduct the study was
granted by the school authorities and ministries of Edu-
cation and Health. Ethical clearance was obtained from
Muhimbili University of Health and Allied Sciences
(MUHAS) and from the National Institute for Medical
Research (NIMR) in Tanzania. Ethical approval and
research clearance were obtained from the National
Committees for research Ethics in Norway and from the
Norwegian Social science Data Service.
Questionnaire
The questionnaire, including 165 questions, was initially
constructed in English and translated into Kiswahili, the
national language and subsequently back-translated into
English by independent translators qualified in English
and Kiswahili [Additional file 1]. Following a pilot test,
some modifications in terms of clarification and simplifi-
cation of wording were done. The questionnaires were
completed by students in classroom setting under super-
vision by trained research assistants. Socio-demographic
factors were assessed in terms of age, gender, place of
residence, father’s and mother’s education, household
socio-economic status (perceived affluence of my house-
hold) and household wealth index. Household wealth
index was assessed according to a standard approach in
equity analysis [25]. Durable household assets indicative
of family wealth (i.e. bicycle, motorcycle, car, TV) were
recorded as (1) “available and in working condition” or
(0) “not available and/or not in working condition.”
These assets were analyzed using principal components
analysis. The first component resulting from this analy-
sis was used to categorize households into four approxi-
mate quartiles of wealth ranging from the 1stpoorest
quartile to the least poor 4thquartile. Oral health
related behaviours were assessed in terms of tooth
brushing, (e.g. how “frequently do you brush your
teeth”) dental attendance within the past 2 years, smok-
ing and intake of sugar sweetened soft drinks. Socio-
demographic and behavioural characteristics and the
number of subjects according to categories are summar-
ized in Table 1. Oral health related quality of life was
measured using a Kiswahili version [11,13] of the eight
item Child OIDP inventory (e.g. During the previous 3
months how often have problems with your teeth and
mouth caused you any difficulty with; eating, speaking,
cleaning teeth, smiling, sleeping, emotional balance,
study and social contact). Each item was scored 0-3
where (0) never, (1) once or twice a month, (2) once or
twice a week, (3) every day/nearly every day. A Child-
OIDP simple count (SC) score (range 0-8) was con-
structed by summing the dichotomized frequency items
of (1) affected and (0) not affected. Internal consistency
reliability (standardized item alpha) of 0.85 agrees with
those obtained previously in Tanzania [11,13]. The inter
item correlations ranged from 0.31 (difficulty with carry-
ing out major school work or social role and difficulty
eating and enjoying food) to 0.55 (difficulty with sleep-
ing and relaxing and difficulty with speaking and pro-
nouncing clearly).
Oral clinical examination
Clinical oral examination was carried out by one trained
and calibrated dentist (HSM) assisted by dental assistant
for recording the results. Cotton rolls were used to con-
trol saliva. Plaque and calculus were assessed under field
conditions with adolescents sitting in a regular (non-
dental) chair, using natural light, probes and mouth
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mirror. Oral hygiene was assessed using the Simplified
Oral Hygiene Index (OHIS) recognized to be a useful
index for evaluation of dental health education in public
school systems [26]. Plaque was assessed on 6 index
teeth in terms of (0) no debris present, (1) soft debris
covering more than one third of the tooth surface, (2)
soft debris covering more than one third but not more
than two thirds of the tooth surface and (3) soft debris
Table 1 Frequency distribution of socio-economic and oral health-related behaviours in the main survey and clinical
sub-study
VariableMain questionnaire survey (N = 2412)Clinical sub-study (N = 1077)
Age
12-15 years
16-21 years
Sex
Male
Female
Residence
Urban
Rural
Mother’s education:
Low (primary school and below)
High (secondary school and above)
Father’s education:
Low (primary school and below)
High (secondary school and above)
Wealth index:
1stquartile (Most poor)
2ndquartile
3rdquartile
4thquartile (Least poor)
Family SES
High
Moderate/Low
Tooth brushing
Not regularly
Regularly
Parents afford dental care
Yes
No
Dental visit past 2 years
Yes
No
Sugar-sweetened soft drinks intake
Never
At least on weekly basis
Tried smoking
Yes
No
Having Oral impact on Daily performance (OIDP)
OIDP = 0 (no impact)
OIDP > 0 (has impacts
Oral hygiene status
Good oral hygiene (OHI-S ≤ 1)
Poor oral hygiene (OHI-S > 1)
% (n)
60.6 (1395)
39.4 (907)
% (n)
69.8 (752)
30.2 (325)
47.9 (1154)
52.1 (1256)
46,6 (502)
53,4 (575)
48.2 (1163)
51.8 (1249)
49.1 (529)
50.9 (548)
65.0 (1247)
35.0 (672)
68.7 (590)
31.3 (269)
54.7 (938)
45.3 (778)
57.7 (445)
42.3 (326)
22.9 (517)
29.2 (661)
23.0 (521)
24.9 (562)
23.1 (233)
33.7 (340)
21.5 (217)
23.1 (219)
76.5 (1827)
23.5 (560)
77.5 (825)
22.5 (239)
23.5 (562)
76.5 (1833)
25.5 (273)
74.5 (796)
48.1 (1143)
51.9 (1234)
49.9 (530)
50.1 (532)
12.6 (299)
87.4 (2081)
11.3 (120)
88.7 (943)
46.8 (1116)
53.2 (1267)
45.8 (485)
54.2 (575)
5.8 (138)
94.2 (2261)
5.6 (60
94.4 (1009)
51.8 (1204)
48.2 (1122)
49.3 (509)
50.7 (524)
55.2 (594)
44.8 (483)
(The total numbers in the different categories do not add up to 2,412 in the main questionnaire survey and to 1,077 in the clinical sub study due to missing
values)
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covering more than two thirds of the tooth surface.
Calculus was assessed on 6 index teeth and recorded as
(0) no calculus present, (1) supra-gingival calculus cov-
ering not more than one third of the tooth surface, (2)
supra-gingival calculus covering more than one third
but not more than two thirds of the tooth surface, (3)
supra-gingival calculus covering more than two thirds of
the tooth surface. For each individual the debris- and
calculus scores of each index tooth were totalled and
divided by the number of teeth assessed (range 0-3).
The oral hygiene index (OHIS) was constructed by sum-
marizing the debris and calculus scores (range 0-6). For
analysis, OHIS scores were dichotomized into 0 = good
oral hygiene (OHIS ≤ 1) and 1 = poor oral hygiene
(OHIS > 1).
Statistical analysis
Statistical Package for Social Sciences (SPSS) version 15.0
was used for data analysis. Cluster effect was adjusted for
using STATA 10.0. Bivariate analyses were conducted
using cross-tabulations and chi-square statistics. Multiple
variable analyses were conducted using stepwise standar-
dized logistic regression (SLR) with odds ratios and 95%
Confidence intervals (CI). The logistic regression analyses
were guided by Petersen’s [20] risk factor model for oral
diseases, suggesting that socio-environmental factors
influence behavioural-and attitudinal factors, which again
impact on clinical- and subjective oral health outcomes.
To examine whether oral health related behaviours
accounted for socio-demographic disparities in oral
health status, the approach suggested by Baron and
Kenny was adopted [27]. Reduction in ORs for the socio-
demographic variables from step I to step II after having
included oral health behaviours into the model, was
interpreted as evidence of mediation of effects, given that
socio-demographic characteristics varied systematically
with oral health outcomes and oral health behaviours
and that the relationship between oral health outcomes
and oral health behaviours were statistically significant.
Results
Sample profiles
A total of 2412 out of 2988 eligible secondary school stu-
dents completed structured questionnaires at school
(mean age 15.3 years SD 1.3, response rate 80.7%) and
47.9% were boys. A total of 1077 of 1331 eligible students
underwent a full mouth clinical examination providing a
response rate of 80.9%, (mean age 14.98 years SD 1.4)
and 46.6% were boys. Table 1 gives the percentage distri-
bution of participants’ socio-demographics, and oral
health related behaviours in the main study group and
the clinical sub sample. To assess whether the clinical
sub sample (n = 1077) was representative of the study
group as a whole a comparison was made with the 1335
students who participated in the questionnaire survey,
only. Statistically significant differences were observed
between the two samples as the questionnaire only parti-
cipants had more frequently mothers with high education
(31.3% versus 38.0%, p < 0.05), fathers with high educa-
tion (47.8% versus 42.3%, p < 0.05) and belonged most
frequently to the least poor category of the wealth index
(.27.4% versus 21.7%, p < 0.05). When a reanalysis was
performed with questionnaire variables considering the
restricted sample size of 1077 participants only, the find-
ings presented in this paper was essentially unchanged.
Test retest reliability
Duplicate clinical examination including 25 randomly
selected students gave Kappa statistics of 0.783 for cal-
culus score and 0.669 for OHIS score [28].
Socio-demographic distribution of oral health
related behaviours
As shown in Table 1, the majority in both samples
brushed their teeth on a daily basis (76.5% and 74.5%)
and had not visited a dentist during the past 2 years
(87.4% and 88.7%). Only about 5% reported that they
had tried cigarettes and about 50% reported intake of
sugar sweetened soft drinks on a weekly basis. Pupils
with highly educated mothers, younger students,
females, those who belonged to the least poor wealth
category and high socio-economic status, SES, families
presented with intake of sugar sweetened soft drinks
more frequently than their counterparts in the opposite
groups (p < 0.05) [Additional file 2]. Urban residents,
those having parents with high education, belonging to
the least poor wealth category and having high SES
family status performed regular tooth brushing and den-
tal attendance more frequently than their counterparts
in the opposite groups. Finally, older students and males
reported smoking more frequently than younger stu-
dents and females.
Oral hygiene status and OIDP by socio-behavioural
characteristics
Totals of 44.8% had fair to poor oral hygiene (OHIS > 1)
whereas 81.1%, 74% and 33% had at least one tooth with
plaque, calculus and bleeding, respectively. The mean
OHIS score was 1.1, SD 0.8 range (0-4, good-bad) corre-
sponding to a clinical level of fairly good oral hygiene.
Totals of 48.2% (in the main sample) and 50.7% (clinical
sub sample) reported at least one oral impact on daily
performances (OIDP > 0). The most frequently reported
impacts were eating problems (36.8%) and problems
tooth cleaning (28.9%), whereas the least frequently
reported impacts were problems speaking (14.5%) and
problems school work (9.9%). Totals of 45.4% versus
58.0% of students having good (OHIS ≤ 1) and poor
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(OHIS > 1) oral hygiene reported any oral impact on
daily performances. Table 2 depicts the overall differ-
ences in frequency of students having poor oral hygiene
(OHIS > 1) and any oral impact (OIDP > 0) by socio-
demographic and behavioural characteristics. As shown,
the frequency of oral impacts were higher in older than
younger age groups, higher in subjects having father and
mother with low education, higher in subjects from low
SES families and in those having parents that could not
afford dental care. The frequency of having any oral
impacts also increased significantly in relation to
decreased level of tooth brushing, decreased intake of
sugar sweetened soft drinks, increased dental visiting
and increased smoking experience. The frequency of
having poor oral hygiene increased significantly in rela-
tion to increased age, being a male, having father with
lower level of education, being in the most poor cate-
gory of the household category and having parents that
could not afford dental care index and in relation to not
performing regular tooth brushing (p < 0.05).
All socio-demographic and behavioural variables that
were statistically significantly associated with OIDP and
OHIS in unadjusted analyses (Table 2) were included
into stepwise, logistic regression models. Table 3 depicts
adjusted ORs and 95% CI for OIDP by socio-demo-
graphics and oral health behaviours. Age, mother’s edu-
cation, father’s education and family SES were entered
in the first step, providing a model fit of Nagelkerke’s R2
= 0.043, Model Chi-Square 45.87 df = 6 p < 0.001. Age,
parents’ affording dental care and family SES were sta-
tistically significant correlates of OIDP in the first step
of the model. Entering behavioural variables in the sec-
ond step, improved the fit of the model to Nagelkerke’s
R2= 0.064, Model chi square = 68.81, df = 10, p <
0.001. In the final model, affording dental care and age
were the only socio-demographic variables that main-
tained statistical significance whereas family SES did
not. Older students, parents who did not afford dental
care and smokers were more likely to report impacts
whereas non dental attendees and those who consumed
sugar sweetened soft drinks were less likely to report
oral impacts as compared with their counterparts in the
opposite groups. Statistically significant two way interac-
tions were identified for gender × parents’ affording
dental care (p < 0.05) and gender × dental attendance
(p < 0.05). Stratified logistic regression analyses revealed
that parent affording dental care (OR = 1.6, 95% CI 1.2-
2.4), dental attendance (OR = 0.4, 95% CI 0.3-0.8) and
smoking (OR = 2.6, 95% CI 1.4-5.1) were significant cor-
relates of OIDP in males, whereas family SES (OR = 1.7,
95% CI 1.1-2.7), parents affording dental care (OR = 1.6,
95% CI 1.2-2.3) and intake of sugar sweetened soft
drinks (OR = 0.7, 95% CI 0.4-0.9) were significant corre-
lates of OIDP in females. As depicted in Table 4, socio-
demographics in terms of age, sex, family wealth index
and parents’ affording dental care were entered in the
first step and provided a model fit in terms of Nagelk-
erke’s R2of 0.058, Model chi square 38.73, df 6, p <
0.001. All socio-demographic variables remained statisti-
cally significantly associated with OHIS in the first step
of the models. Entering tooth brushing into the second
Table 2 Distribution of Oral hygiene status and OIDP
according to socio-demographic and oral health related
behaviours
VariableOHI-S > 1
% (n)‡
OIDP > 0
% (n)‡
Age
12-15 yr
16-21 yr
Sex
Male
Female
Place of residence
Urban
Rural
Mother’s education
Low
High
Father’s education
Low
High
Wealth index
1stquartile (Most poor)
2ndquartile
3rdquartile
4thquartile (least poor)
Parents afford care
Yes
No
Family SES
High
Moderate/Low
Tooth brushing
Not regularly
Regularly
Ever tried smoking
No
Yes
Dental visit last 2 years
Yes
No
Sugar sweetened soft drink intake
Never
At least on weekly basis
40.3 (255)
50.3 (197)**
45.1 (607)
53.3 (466)**
51.2 (257)
39.3 (226)**
49.8 (551)
46.8 (570)
43.3 (229)
46.4 (254)
48.4 (545)
48.0 (577)
47.1 (278)
38.7 (104)*
51.2 (615)
44.2 (292)*
50.6 (225)
39.3 (128)**
51.8 (466)
44.2 (332)**
52.8 (123)
47.4 (161)
44.7 (97)
32.9 (72)**
52.2 (262)
48.4 (306)
49.7 (251)
43.9 (239)
40.0 (212)
49.6 (264)**
41.1 (456)
54.7 (649)**
42.7 (352)
52.7 (126)
44.8 (791)
59.6 (319)**
51.6 (141)
42.6 (339)*
54.5 (294)
46.4 (836)*
41.7 (25)
45.0 (454)
47.7 (1041)
57.9 (77)*
38.3 (46)
45.5 (429)
56.1 (162)
47.2 (949)*
48.0 (233)
42.3 (243)
53.4 (574)
43.7 8546)**
**p < 0.001.
*p < 0.05.
‡Frequency of those having OHI-S score >1 and OIDP scores >0, respectively.
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step improved the model fit to Nagelkerke’s R20.059,
Model chi square 39.30, df 8, p < 0.001. In the final
model all socio-demographics, except parents’ affording
dental care, maintained significant associations with the
OHIS score. No statistically significant two way interac-
tion was observed with OHIS.
Discussion
This study reported upon the socio-demographic- and
behavioural frequency distribution of oral hygiene status
and OIDP in a deprived population of adolescents
attending secondary schools examined whether the
socio-demographic and -behavioural distribution of oral
health outcomes differed between males and females
and assessed to what extent oral health related beha-
viours accounted for socio-economic disparity in oral
health outcomes. The factors shown to be statistically
significantly and independently associated with higher
odds ratios of OIDP included; older age groups, low
family SES and parents not affording dental care in
addition to smoking experience, no dental visits and
fewer intake of sugar sweetened soft drinks. The factors
associated with higher odds ratios for poor oral hygiene
were older age groups, males and belonging to the poor-
est category of the household index. Using a stratified
approach by gender allowed estimation of a wider range
of socio-behavioural disparities with respect to the oral
health outcomes investigated. Thus, family SES and
intake of sugar sweetened soft drinks were more impor-
tant correlates of OIDP in females than in males,
whereas smoking and dental attendance patterns were
most pronounced in males. All socio-behavioural corre-
lates of poor oral hygiene status seemed to be equally
important in males and females.
Consistent with many previous studies of child- and
adolescents populations in sub Saharan Africa, this
study revealed a moderate frequency (prevalence/occur-
rence) of poor oral hygiene status, high rates of daily
tooth brushing, low rates of smoking and moderate
intake of sugar sweetened soft drinks [9-13]. These
Table 3 OIDP regressed on socio-demographic characteristics and oral health behaviours
VariableStep 1:
Socio-demographics‡
OR (95% CI)
Step 2:
Socio-demographics and behavioural factors§
OR (95% CI)
Age
12-15 yr
16-21 yr
Mother’s education:
Low
High
Father’s education:
Low
High
Family SES
High
Moderate/Low
Parents afford dental care
yes
No
Tooth brushing
Not regularly
Regularly
Ever tried smoking
No
yes
Dental visit past 2 yr
Yes
No
Sugar sweetened soft drink intake
Never
At least on weekly basis
1
1.2 (1.0-1.5)
1
1.2 (1.0-1.5)
1
0.9 (0.7-1.2)
1
0.9 (0.7-1.2)
1
0.9 (0.7-1.2)
1
0.9 (0.7-1.2)
1
1.3(1.0-1.7)
1
1.2 (0.9-1.6)
1
1.6 (1.3-2.0)
1
1.6 (1.3-2.0)
1
0.8 (0.6-1.1)
1
2.0 (1.2-3.4)
1
0.6 (0.4-0.8)
1
0.7 (0.6-0.9)
‡Adjusted Odds ratios (ORs) and 95% Confidence interval (CI) for having at least one OIDP according to socio-demographic characteristics.
§Adjusted Odds ratios (ORs) and 95% Confidence interval (CI) for having at least one OIDP according to Socio-demographics and oral health behaviours.
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figures indicate that there is a room for improving oral
self care, diet and access to and utilization of dental ser-
vices. Moreover, about half of the students (48%-50%)
reported experience with any OIDP during the past 3
months. This rate is higher than those reported pre-
viously among similar age groups in Tanzania, but lower
than the prevalence rate identified among secondary
school students in Uganda and other non-industrialized
countries [11,13,29,30]. Problems with eating and clean-
ing teeth were the most commonly reported impair-
ments, a finding which is consistent with those of other
populations using both the adult-and child version of
the OIDP inventory [11,13,29,31].
In spite of its considerable floor effect indicating that
half of the students investigated did not experience oral
impacts, the OIDP inventory exhibited sufficient discri-
minatory properties suggesting that it is suitable for
detecting group differences in cross-sectional studies.
Observed OIDP differences across socio-demographic-
and behavioural factors were statistically significant both
in unadjusted and adjusted analyses and across males
and females. In general, these findings confirm the social
gradient observed in oral health and oral health related
behaviours of adolescent-and adult populations, globally
[17,20,32]. Notably, students who had seen a dentist
during the previous 2 years reported oral impacts more
frequently than students who had not visited a dentist.
Similar findings have been reported previously, and
might be attributed to symptomatic dental attendance
patterns rather than an unexpected response to dental
treatment [33]. The social gradient in adolescents’ sugar
consumption was opposite that observed in industria-
lized countries being highest in the socially affluent
groups of young people. This finding is consistent with
evidence suggesting that commercialized sugar products
have become highly preferred in low income countries,
particularly by the higher socio-economic status groups
[34]. Students who reported fewer intake of sugar swee-
tened soft drinks were more likely than their counter-
parts to report any impact on daily performances. This
might be a reflection of their lower socio-economic
status. It is also probably that reduced consumption
follows oral impacts in terms of problems eating and
cleaning, rather than sugar consumption having advan-
tageous consequences for oral health.
The present findings, suggesting a similar social gradi-
ent in oral health behaviours and OIDP and the fact
that dental attendance, tooth brushing and intake of
sugar sweetened soft drinks varied systematically with
OIDP, suggests a contribution of oral health behaviours
to social disparities in oral health among the students
investigated [35-38]. According to the results depicted
in Table 3 and 4, this study suggests that individual
behavioural factors might lessen social disparity in oral
Table 4 Oral hygiene (OHI-S) regressed on socio-demographic factors and oral health behaviours
Variable Step 1:
Socio-demographics‡
OR (95% CI)
Step 2:
Socio-demographics and toothbrushing§
OR (95% CI)
Age
12-15 yr
16-21 yr
Sex
Male
Female
Father’s education
Low
High
Family wealth
1st quartile (most poor)
2nd
3rd
4th (least poor)
Parents afford dental care
yes
No
Tooth brushing
No
Yes
1
1.3 (1.0-1.9) 1.3 (1.0-1.8)
1
0.6 (0.4-0.8)
1
0.6 (0.4-0.9)
1
0.7 (0.5-1.2)
1
0.7 (0.5-1.2)
1
0.8 (0.6-1.2)
0.7 (0.5-1.2)
0.5 (0.3-0.9)
1
0.8 (0.6-1.2)
0.8 (0.5-1.2)
0.5 (0.2-0.7)
1
1.2 (1.0-1.6)
1
1.2 (0.9-1.6)
1
0.9 (0.6-1.3)
‡Adjusted Odds ratios (OR) and 95% confidence interval (CI) for having poor oral hygiene (OHIS > 1) according to socio-demographic factors
§Adjusted Odds ratios (OR) and 95% confidence interval (CI) for having poor oral hygiene (OHIS > 1) according to socio-demographic factors and tooth brushing
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hygiene status and OHRQoL among adolescents but do
not seem to remove it completely. Attempts to explain
and describe socio-economic differences in oral health
status have mainly focused on adults in industrialized
countries, with the commonly held view that poor oral
health is explained by personal neglect not always being
supported [35-38]. Consistent with the findings in this
study, a multilevel analysis of adolescents from 33
industrialized countries revealed that behavioural factors
accounted partly for the socio-economic differences in
self reported health status [19]. These results appear to
imply that preventive programs should focus unhealthy
behaviours of adolescents in the poorest socio-economic
status groups.
The present results should be interpreted in the light of
limitations that include a cross-sectional design, use of
self-reported measures and the fact that the estimates
presented are not weighted using sample weight. Due to
its cross sectional design, the present study cannot
demonstrate causality and longitudinal studies are
needed to identify the direction of the relationships iden-
tified. Another weak aspect is the lack of a measure of
dental fluorosis being endemic in the present study area
and might assumingly impact children’s OHRQoL. Struc-
tured, self-administered questionnaires as applied in this
study have certain limitations with bias due to social
desirability, acquiescence and lack of recall being fre-
quently encountered, particularly in younger age groups
[39]. In spite of a reportedly optimal tooth brushing fre-
quency that might counteract the deleterious effects of
dental plaque and sugary diets, about 80%, 70% and 30%
of the study population presented with plaque, calculus
and gingival bleeding. This finding do indicate that
response inaccuracy due to recall bias and social desir-
ability is a methodological problem that might have con-
fronted the identification of relationships between oral
behaviours and oral health outcomes in this study. How-
ever, most findings were in accordance with expectations.
Moreover, the measures of oral hygiene - and sugar con-
sumption utilized have been applied previously in East
Africa [11-13]. The sugar frequency questionnaire
applied has been found to be acceptable with respect to
classifying adolescents into broad categories of high and
low sugar consumption [12].
Conclusion
Disparities in oral hygiene status and OIDP existed in
relation to age, affording dental care, smoking and
intake of sugar sweetened soft drinks. Gender differ-
ences should be considered in intervention studies, and
modifiable behaviours have some relevance in reducing
social disparity in oral health.
Additional material
Additional file 1: Youth health survey Questionnaire. A self
administered questionnaire used for collection of the information
regarding students’ basic background information and socio-
demographics, oral health related behaviors, Oral Impact on Daily
performance index as measure of oral quality of life for the students’
baseline information. It has questions on: Individual student and his/her
family background, Dietary Behaviors, Oral Health, Tobacco Use and
Health services utilization among other things. The mentioned
questionnaire sections are relevant to the present study, though the
questionnaire had 165 questions.
Additional file 2: Table S5: Socio-demographic distribution of oral
health related behaviours. Table showing percent of the students who
reported to consume sugar sweetened soft drink weekly, daily tooth
brushing, have tried or are smoking and having attended to a dentist in
different socio-demographic groups (N = 2412).
Acknowledgements
This work was in part funded by a grant from the Norwegian Cooperation
Programme for Development, Research and Education (NUFU) and in part
form the Faculty of Medicine and Dentistry, University of Bergen. It was
facilitated by the collaborating institutions: Muhimbili University of Health
and Allied Sciences and Centre for Educational Development in Health,
Arusha, Tanzania, the University of Limpopo, South Africa, and the
Universities of Oslo and Bergen, Norway. The authors acknowledge and
appreciate Arusha municipality, Arusha rural and Meru administrative
councils’ authorities, Muhimbili University of Health and Allied Sciences
(MUHAS), Ministries of Health and Social Welfare and Education in Tanzania,
and REK VEST of Norway for permission to conduct the study. They are
indebted to the study participants, parents and their school administrations
for making this study a reality. Thanks to Mrs. Flora Mrita for her diligent
work during the clinical field work.
Author details
1Department of Clinical Dentistry, Community Dentistry, University of Bergen,
Bergen, Norway.2Centre for International Health, University of Bergen,
Bergen, Norway.3Department of Preventive and Community Dentistry,
School of Dentistry, Muhimbili University of Health and Allied Sciences, Dar
Es Salaam, Tanzania.
Authors’ contributions
HSM: Principle investigator, designed the study, collected data, performed
statistical analyses and writing of the manuscript. ANÅ: Main supervisor,
designed study, guided the statistical analyses. She has been actively
involved in manuscript writing. JRM: Participated in design of study and
provided valuable guidance in data collection. All authors read and
approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Received: 19 July 2010 Accepted: 30 November 2010
Published: 30 November 2010
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Cite this article as: Mbawalla et al.: Socio-demographic and behavioural
correlates of oral hygiene status and oral health related quality of life,
the Limpopo - Arusha school health project (LASH): A cross-sectional
study. BMC Pediatrics 2010 10:87.
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