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Radiographic alveolar bone loss and risk factors in a predoctoral clinic population

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Radiographic alveolar bone loss and risk factors in a predoctoral clinic population

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i

RADIOGRAPHIC ALVEOLAR BONE LOSS AND RISK FACTORS IN A PREDOCTORAL
CLINIC POPULATION

by

Julianna Ko, DDS

A Thesis Presented to the
FACULTY OF THE USC HERMAN OSTROW SCHOOL OF DENTISTRY
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfilment of the
Requirements for the Degree
MASTER OF SCIENCE
(BIOMEDICAL IMPLANTS AND TISSUE ENGINEERING)
August 2022

Copyright 2022 Julianna Ko

ii
Table of Contents

List of Tables ................................................................................................................................. iii
List of Figures ................................................................................................................................ iv
Abstract ............................................................................................................................................v
Introduction ......................................................................................................................................1
Chapter 1: Materials and Methods ...................................................................................................4
Study Population ............................................................................................................4
Inclusion and Exclusion Criteria ....................................................................................5
Measurements ................................................................................................................6
Predictors .......................................................................................................................6
Statistical Analyses ........................................................................................................8
Chapter 2: Results ............................................................................................................................9
Patient Characteristics ....................................................................................................9
Chapter 3: Discussion ....................................................................................................................14
Chapter 4: Conclusion ....................................................................................................................20
References ......................................................................................................................................21
Figures ...........................................................................................................................................27

iii
List of Tables
Table 1. Characteristics of predoctoral clinic population
Table 2. Adjusted multivariable model for age, group, sex, and disease presence
Table 3. Associations between RBL and age groups, sex, and SRMC

iv
List of Figures
Figure 1: Computed Dental Radiography (CDR) DICOM toolbar with “Measure” tab highlighted
Figure 2: Example of linear measurements used to determine radiographic bone loss in CDR
software
Figure 3. Prevalence of RBL by sex, smoking status, and SRMC
Figure 4. Associations between age and SMRC with radiographic bone loss

v
Abstract

Objectives:
To determine 1) the prevalence of RBL among Herman Ostrow School of Dentistry pre-doctoral
patients 2) which age groups had greater RBL prevalence and 3) associations between RBL and
sex, smoking status, and self-reported medical conditions (SRMC).

Materials and Methods: 1073 patients (ages 15-64) from the Herman Ostrow School of Dentistry
predoctoral clinic were reviewed and divided into ten age cohorts. Patients with RBL had at least
one site ≥2.5mm from the cemento-enamel junction to the alveolar crest on posterior interproximal
radiographs.

Results: An overall RBL prevalence of 37.1% was observed. In a multivariable logistic
regression model that controlled for sex and medical comorbidities, age was significantly
associated with increased RBL in the following age groups: 40-44, 45-49, 50-54, 55-59, 60-64.
RBL was significantly decreased in patients under the age of 24 (age groups 20-24, 15-19).
Males were significantly associated with increased RBL compared to females (OR=1.532, 95%
1.105-2.123). Of SRMC, cancer was significantly associated with increased RBL (OR=4.717,
95% 1.342-16.579).

Conclusion: Our results suggest that patients above 40 years of age, male patients, and patients
with current or historic cancer status have increased risk for RBL.

1

Introduction
Periodontitis is a chronic, multifactorial inflammatory disease of the soft and hard tissues
surrounding teeth mediated by host response to bacterial plaque (Eke et al., 2016). Due to its
cumulative, chronic nature, periodontal disease has been associated with increasing age
(Albander et al., 1999). Periodontitis is significantly more prevalent in adults 70-81 years of age
compared to adults 50-59 years of age (Demmer et al., 2012). The most recent CDC report states
that 47.2% of adults over 30 years of age have periodontal disease, and that the prevalence of
periodontal disease increases to 70.1% in adults 65 years and older (Eke et al., 2016).

While age is related to physiologic changes in the periodontium, it is thought that age itself does
not intrinsically contribute to periodontal breakdown (Natto and Al-Zahrani; Peacock and
Carson). Older adults are more likely to have complex medical conditions and histories, and
epidemiological studies have also shown associations between periodontal bone loss and medical
conditions (Natto and Al-Zahrani; Peacock and Carson). Studies have associated periodontal
disease with diabetes, cardiovascular diseases, pulmonary diseases, rheumatoid arthritis,
cognitive impairment/Alzheimer’s disease, and/or certain cancers of the oral cavity (Eke et al,
2016).

Periodontal disease is more commonly found in men than in women (Eke et al, 2016).
Periodontitis has also been more commonly found in smokers: there is a dose dependent
relationship between the severity of periodontal disease and the amount of cigarette smoking
(Tonetti, 1998). Heavy smokers are six to seven times more likely to have alveolar bone loss
(Grossi et al., 1995). Smoking adversely affects the function of polymorphonuclear leukocytes

2
(PMNs), releases inflammatory cytokines involved in periodontal breakdown, and inhibits
human gingival fibroblasts (Grossi et al., 1995).

In the diagnosis of periodontal disease, clinical and radiographs complement each other. Clinical
examinations provide information about bleeding on probing, probing pocket depths, loss of
attachment, mobility, and suppuration (Nyman and Lindhe, 1997), while radiographs provide
information about bone levels, pattern of bone loss, and periapical perio-endo pathologies
(Tugnait et al., 2000).

At the same time, clinical and radiographic evaluations have their limitations. Clinical findings
may be error-prone due to variability in probing methods, non-calibrated examiners, or difficulty
to identifying the cementoenamel junction (CEJ) when assessing clinical attachment loss (CAL)
(American Academy of Periodontology Task Force Report on the Update to the 1999
Classification of Periodontal Diseases and Conditions, 2015; Albandar et al., 1999; Reddy, 1997)
Probing methods can change based on the degree of edema and probing technique (for example,
probing force, angle of the probe, size of the probe and probe calibration between brands) (Zaki
et al., 2015). Clinical measurements may also not take into consideration attachment loss caused
by physical trauma such as tooth extraction, toothbrush abrasion, or orthodontic forces that move
teeth outside of the alveolar process (Baxter, 1967; Heasman et al., 2015; Schropp et al., 2003).

The most commonly used method to assess bone levels is by posterior bitewing radiographs
(Tugnait et al., 2000; Tugnait et al.). While bone levels can be determined by sounding under
local anesthesia or by surgical visualization, posterior bitewing radiographs require the least

3
intervention (Tugnait et al.). Although radiographs do not provide information on clinical signs
of inflammation, they can prove to be more beneficial in measuring attachment loss in situations
where restorations, calculus, or anatomical structures may obscure the CEJ and/or prevent the
periodontal probe from accessing the pocket (Corbet et al., 2009). Studies have shown that
radiographic alveolar bone loss has a moderately positive correlation with clinical attachment
loss (Machtei et al., 1997; Zhang et al., 2018). Radiographic bone loss (RBL) can be used as an
indirect indicator of past or present periodontal disease.

While many studies have demonstrated that periodontal disease is associated with increasing age,
few studies have investigated whether there is a specific age range when people become
susceptible to periodontitis, and whether the association between age and periodontitis is a linear
progression. Understanding susceptible patient demographics for periodontal disease will allow
clinicians to closely monitor certain age groups for periodontal disease and to implement
preventative measures targeted towards those groups.

The aims of our study were to 1) evaluate the prevalence of radiographic alveolar bone loss
(RBL) among patients of various age groups at the Herman Ostrow School of Dentistry pre-
doctoral clinic 2) to determine which age groups had greater prevalence of RBL than others and
3) to determine associations between RBL and sex, smoking, and self-reported medical
conditions (SRMC).

4
Chapter 1: Materials and Methods
Study Population
This cross-sectional retrospective study is a replication of the 2014 study completed at Tufts
University School of Dental Medicine and will be part of a multicenter study with other
universities. The study was approved by University of Southern California Institutional Review
Board (ID # UP-20-00196).

Patient charts were initially screened by the Informational Technology (IT) team at Herman
Ostrow School of Dentistry at University of Southern California (Figure 1). The IT team
performed a database search of up to 2000 patients seen within pre-doctoral clinics from January
1, 2010 to April 20, 2021, searching backwards from the most recent date until 2000 patient
records were collected. Qualifying patients were between 15-64 years old, with comprehensive
oral examinations and radiographs (either full mouth series or interproximal radiographs)
completed within 3 months of each other. The 3-month time period between the comprehensive
oral examination and the radiograph was to account for patients who were unable to obtain
complete radiographs at the time of examination. The radiographs were collected digitally on
axiUm via CDR (Computed Dental Radiography) DICOM
®
software and had to include four
posterior horizontal or vertical interproximal radiographs.

5
The patients were divided into ten age cohorts consisting of five-year increments (15-19, 20-24,
25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64 years old). There were at least 100
patients (approximately 50 males and 50 females) per cohort, for up to 1073 qualifying records.
The age of each patient was determined to be the age at the time of their comprehensive oral
examination.

Three pre-doctoral students (JH, SB, EL), and one post-doctoral periodontal resident (JK)
collected data from each patient chart.

Inclusion and Exclusion Criteria
For patients to qualify, they had to 1) fall within the age range of 15-64 years 2) have
comprehensive oral examinations (D0150) and interproximal radiographs completed within a 3-
month period 3) have diagnostic horizontal or vertical interproximal radiographs that showed the
cemento-enamel junction (CEJ) and alveolar crestal bone and 4) have at least 8 posterior teeth,
with at least two teeth adjacent to each other in each quadrant. Third molars were included if
they were fully erupted, in occlusion, and radiographically visible. Radiographs were considered
diagnostic when the CEJ and alveolar crest could be identified.

Patients were excluded from the study if they did not meet the above criteria. Sites that were
excluded from measurements were: nonfunctional third molars (partially erupted or impacted),
teeth without proximal or opposing occlusal contacts, all implants, teeth with dental restorations
that obliterated the CEJ, and natural tooth surfaces adjacent to an edentulous site or an implant.

6
Measurements
A calibrated investigator (JK) reviewed all digital posterior interproximal radiographs using
Computed Dental Radiography (CDR) DICOM
®
Version 5.4 for Windows. Posterior
interproximal bone levels were measured from the cemento-enamel junction (CEJ) to the most
coronal portion of the crestal lamina dura of the alveolar crest, using the “Measure” tool within
CDR DICOM
®
(Figures 2, 3).

No clinical attachment loss, or health, is generally consistent with 0.4 and 1.9mm distance from
the cemento-enamel junction to alveolar bone (Hausmann et al., 1991; Tugnait et al., 2000).
Previous studies have used more than 2mm from the cemento-enamel junction as evidence of
bone loss (Fukuda et al., 2008; Gjermo et al., 1984; Grossi et al., 1995; Hansen et al., 1984).
Our study used ≥2.5mm as the threshold measurement for defining radiographic alveolar bone
loss to account for variations in radiographic angulations that may overestimate radiographic
alveolar bone loss.

Predictors
Completed examinations from axiUm
®
were used to collect information about patient sex, BMI,
tobacco use, and self-reported medical conditions (SRMC). SRMC were categorized as:
• Pulmonary (Respiratory) Conditions: orthopnea, asthma, bronchitis, emphysema,
chronic obstructive sleep disorder, sleep apnea, tuberculosis
• Cardiac Conditions: angina, myocardial infarction, rheumatic fever, heart murmur,
TIA, prosthetic heart valve, endocarditis, hypertrophic cardiomyopathy, valvular

7
damage, congenital heart disease, mitral valve prolapse, cardiac regurgitation, cardiac
pacemaker, cardiac transplant
• Endocrine Conditions: hyper/hypo-thyroidism, thyroiditis, benign thyroid tumor,
hyper/hype-parathyroidism, Addison’s Disease, Cushing’s syndrome
• Cancer: bladder, breast, cervix, colon, liver, lung, oropharyngeal, ovarian, prostate,
rectal, skin, stomach, thyroid, uterine, kidney
• Blood Disorders: idiopathic thrombocytopenic purpura, Von Willebrand’s Disease,
hemophilia A/B, coumadin/heparin use
• Psychological Conditions: anxiety, depression, mood disorders
o Anxiety: Phobias, panic attack
o Depression: depression, manic depression
o Mood: bipolar, schizophrenia, PTSD, psychosis
Specific SRMC that would have otherwise belonged the previous categories were grouped as
separate conditions on their own, as they have been frequently associated with periodontitis and
RBL in the literature:
• Diabetes (Type 1 and 2)
• Joint problems and replacement therapy
• Osteoporosis/osteopenia
• Hypertension
• Atherosclerosis
• Allergies (hay fever, sinusitis, seasonal allergies)
Patients who reported no medical conditions were labeled as having “no known diseases” (NKD).

8
Statistical Analyses
Descriptive statistics were calculated for all variables of interest. Continuous measures were
summarized using means and standard deviations whereas categorical measures were
summarized using counts and percentages. The primary outcome of bone loss was analyzed
using a logistic regression model. Prior to analysis the predictor variables of interest were
assessed for multicollinearity using tolerance statistics (a tolerance value <0.4 was used as the
benchmark). In the case of multicollinearity, only one member of a correlated set was retained in
the multivariable model. The smoking variables were found to be correlated and therefore only
one of them (smoked in the past yes/no) was kept in the model. Presence of disease (yes/no) was
correlated with the individual disease variables and therefore removed from the model. Separate
models were run: one including all non-correlated variables of interest and a second including
only those variables found to be significant (p<0.05) in bivariate analyses. Model estimates were
displayed using odds ratios and their associated 95% confidence intervals. All analyses were
carried out using SAS Version 9.4 (SAS Institute, Cary, NC, USA).

9
Chapter 2: Results
Patient Characteristics
The sample size of this study was 1073 patients, with 535 (49.86%) males and 538 (50.14%)
females. The mean ± SD age of the patients was 39.35 ± 14.14 years (Table 1). The percentage
of RBL was 37.1%, and the percentage of subjects without bone loss was 62.91%. The mean ±
SD age of patients with RBL was 50.78 ± 13.77 years (Table 1). Bivariate analysis shows that
sex was statistically significant for differences in RBL, with males having greater bone loss than
females (41% vs 34%, p = 0.02) (Table 1).

Table 1. Characteristics of predoctoral clinic population

Variable

Radiographic bone loss -
Yes, n/N
(weighted percent)
‡

Radiographic bone loss-
No, n/N (weighted
percent)
‡

P value

Smoking status

398/1073 (37.1) 675/1073 (62.9)
Present smoker 35/90 (38.9) 55/90 (61.1) 0.71
Past smoker 26/86 (30.2) 60/86 (69.8) 0.16
Never smoker 338/912 (37.1 574/912 (62.9)
Sex
Male 217/535 (40.6) 318/535 (59.4) 0.02
Female 181/538 (33.6) 357/538 (66.4)
Mean age±SD, years 50.78±13.77 32.27±14.19
Self-reported medical conditions

Prediabetes 23/29 (79.3) 6/29 (20.7) <0.0001
Diabetes 73/102 (71.6) 29/102 (28.4) <0.0001
High cholesterol 54/90 (60.0) 36/90 (40.0) <0.0001
Hemophilia 8/9 (88.9) 1/9 (11.1) 0.0012
Anemia 18/50 (36.0) 32/50 (64.0) 0.87
Cardiac conditions

39/68 (57.3) 29/68 (42.7) 0.0004
Respiratory conditions 63/128 (49.2) 65/128 (50.8) 0.0025
Hypertension 52/86 (60.5) 34/86 (39.5) <0.0001
Joint replacement 15/19 (79.0) 4/19 (21.1) 0.0001
Arthritis 20/26 (77.0) 6/26 (23.1) <0.0001
Autoimmune 10/19 (52.6) 9/19 (47.4) 0.16
Hay fever 20/38 (52.6) 18/38 (47.4) 0.04
Anxiety 47/137 (34.3) 90/137 (65.7) 0.47
Mood swings 17/23 (73.9) 6/23 (26.1) 0.0002
Depression 32/91 (35.1) 59/91 (64.8) 0.69
Osteoporosis 3/7 (42.9) 4/7 (57.1) 0.75
Cancer 21/25 (84.0) 4/25 (16.0) <0.0001
No known disease 140/515 (27.2) 375/515 (72.8)
Values that are statistically significant (2-sided P-value ≤ 0.05) are bolded
1

10
Of the 1073 records reviewed, 90 patients (8.39%) identified as current smokers, 86 identified as
past smokers (8.01%), and 912 patients (85%) identified as never smokers (Table 1). RBL was
39% in current smokers, 30% in past smokers, and 37% in never smokers. RBL was not found to
be significantly different in current smokers (p=0.71) or past smokers (p=0.16) compared to
never smokers (Table 1).

In the bivariate analysis, SRMC that were statistically significant for RBL compared to no
disease were prediabetes (p<0.0001), diabetes (p<0.0001), high cholesterol (p<0.0001),
hemophilia (p=0.0012), cardiac problems (p=0.0004), respiratory disease (p=0.0025), high blood
pressure (p<0.0001), joint replacement (p=0.0001), arthritis (p<0.0001), hay fever (p=0.04),
mood swings (p=0.0002), and cancer (p<0.0001) (Table 1).

In the first multivariable model including all non-correlated variables of interest (age group, sex,
and no disease), age group (p<0.0001) and sex (p=0.01) were found to be significant, but disease
presence (p=0.48) was not (Table 2).

11
In the second multivariable model including only those variables found to be significant in
bivariate analyses (p<0.05) (Table 1), age group (p<0.0001), sex (p=0.02), and cancer (p=0.01)
were statistically significant for RBL, but other categories were not (Table 3).

12
Table 3. Associations between RBL and age groups, sex, and SRMC

In both multivariable models, males had significantly higher odds ratios than females for RBL
Table 2, Table 3). Positive associations of bone loss were found to occur starting with age cohort

13
35-39 and continuing in higher age cohorts. Significantly higher odds ratios in the multivariable
model ranged from 4.65 (40-44 age cohort) to 32.9 (60-64 age cohort), and significantly lower
odds ratios ranged from 0.06 (15-19 age cohort) to 0.31 (20-24 age cohort).

14
Chapter 3: Discussion
Using posterior interproximal radiographs, this study evaluated radiographic bone loss and its
associations with patient age, sex, smoking status, and SRMC. Like previous studies, our study
found that RBL was associated with increasing age and males. Our study differed from other
studies in not finding statistically significant associations between RBL and smoking habits, and
RBL and certain SRMCs when adjusting for age and sex.

An overall RBL prevalence of 37.1% was observed in this study. One study using NHANES data
from 1988-1994 reported a 53.1% prevalence of periodontitis in 9689 patients aged 30-90
(Albandar et al., 1999). The 2009-2012 National Health and Nutrition Examination Survey
(NHANES) representing about 141 million adults in the United States reported a prevalence of
45.9% in adults 30 years and older based on full mouth periodontal examinations (Eke et al.,
2016). Severe periodontitis was most prevalent among smokers and adults 65 years or older, and
had significant co-occurrence with diabetes and increasing number of missing teeth (Eke et al.,
2016). The difference in RBL prevalence between our study (37.1%) and the NHANES study
(53.1%) could be explained by the differences in mean ages of the study populations. The
NHANES study did not include patients younger than 30 years old and included patients older
than 65 years old. The mean age of their study (51 years old) was higher than the age of our
study (39 years old).

In the 15-19 age cohort of this study, RBL prevalence was found to be .99%. Previous studies
with comparable radiographic guidelines showed similar findings, ranging between 0.06% and
4.5% (Benn, 1990; Blankenstein et al., 1978; Kronauer et al., 1986). Other studies that have

15
higher prevalence within this age cohort had less stringent criteria for RBL (Hull et al., 1975;
Latcham et al., 1983). Hull et al. (1975) observed RBL in 51.5% of 14 year-old English school
children, but the criteria for bone loss was set as a lower threshold measurement for RBL
(>1.5mm from the CEJ) than the current study (> 2.5mm from CEJ). Our study based our
threshold value on previous studies that have shown RBL between 2-3mm reflects radiographic
bone loss within the population (Aass et al., 1988; Hausmann et al., 1991; Hausmann et al.).

Previous studies have found that older groups have a higher proportion of periodontal diseases
compared to younger age groups (Eke et al., 2012). This is in accordance with our results, which
demonstrate a trend that older age groups have significantly higher odds ratios of radiographic
bone loss than younger age groups. In a multivariable logistic regression model that controlled
for sex (male vs female) and medical comorbidities, age was significantly associated with
increased bone loss in patients older than 40 years, and age was significantly associated with
decreased bone loss in patients under the age of 24 compared to our reference age group 30-34.
There was no significant difference between the reference group compared to the age groups 25-
29 and 35-39. The association between age and bone loss could be associated with the possibility
that osteoblasts are downregulated in older individuals, and there is a decreased response to
mitogens and bone formation stimulators/repairers (Pfeilschifter et al., 1993).

Previous studies have observed that the proportion of males with periodontal disease is
significantly higher than that of females (Eke et al., 2012; Nunn, 2003). This agrees with our
results, which demonstrate that when controlling for age and self-reported medical conditions,
females have significantly lower odds ratios of periodontal diseases compared to males

16
(OR=0.655, 95% 0.471-0.937). Some studies have suggested that estrogen may underlie the
difference between periodontal disease in men and women. One study found that
osteopenic/osteoporotic women taking estrogen supplements had a reduced frequency of clinical
attachment loss and gingival inflammation (Reinhardt et al., 1999). Another study comparing
postmenopausal women taking estrogen supplements to postmenopausal women without found
that the group taking the supplements had significantly less bleeding upon probing (Norderyd et
al., 1993).

In our bivariate analysis examining radiographic bone loss and self-reported medical conditions,
patients with prediabetes, diabetes, high cholesterol, hemophilia, cardiac conditions, respiratory
conditions, hypertension, arthritis, hay fever, mood swings, and cancer had a statistically
significant higher prevalence of radiographic bone loss than patients without these conditions,
with more than two times RBL in weighted percentage (Table 1). This observation is consistent
with previous studies that show strong associations between periodontitis and chronic
inflammatory conditions, assuming that bone loss could be related to periodontitis in older
populations.

In our multivariable analysis controlling for age and sex, however, only cancer had significantly
higher odds ratios of alveolar bone loss than those with no disease (OR=4.717, 95% 1.342-
16.579). Other self-reported medical conditions were not significant. Our multivariable analysis
suggests that age is a stronger predictor for RBL than SRMC and sex alone. This explains why
all SRMC except cancer were no longer significant in the multivariable analysis adjusted for age.
As older individuals are more likely to have multiple chronic inflammatory conditions, they are

17
more likely to have periodontal disease as well. Our study suggests that the strong association
between inflammatory conditions and alveolar bone loss is age-related.

Previous studies have shown that the strongest associations with periodontal disease are diabetes
and smoking. Diabetes is positively associated with attachment loss: a study by Grossi et al.
(1995) found an odds ratio of 2.32 (95% CI: 1.17-4.60). Emrich et al. found type-2 diabetes
subjects within the Pima Indian population had a three-fold increased risk of periodontitis (OR:
2.81, 95% CI: 1.91-4.13) and of alveolar bone loss (OR: 3.43, 95% CI: 2.28-5.16). The
prevalence of diabetics in our study (9.5%) is comparable to that of the national average (9.3%)
(National Diabetes Statistics Report, 2014). Our age-adjusted multivariable model demonstrated
a lower odds ratio for radiographic bone loss than previous studies (OR: 1.328, 95% CI: 0.741-
2.381), which again suggests that age is an effect modifier in risk for bone loss.

Unlike many other studies, our study did not find a statistically significant difference in the
prevalence of radiographic alveolar bone loss between current/former smokers and never-
smokers. It is well established that cigarette smoking is a key risk factor in the development of
inflammatory periodontal diseases (Bergström et al., 2000; Jansson and Lavstedt, 2002; Palmer
et al., 1999). It exerts harmful effects on gingival tissues, immune responses, and healing
potential. In general, many cross-sectional studies have estimated the odds ratio for the risk of
bone loss in smokers to vary between 1.4 (Horning et al., 1992) and 5.5 (Stoltenberg et al., 1993)
Bergstrom et al. (2000) reported smokers to have greatly reduced bone height with increasing
age as compared with non-smokers. The lack of significant association in our study could be due
to a variety of reasons. As the health histories are reported by the patients, cigarette smoking

18
could have been underreported by patients. Additionally, our study’s definition of “current
smoker” or “past smoker” is broad: it includes patients who smoke one to more than ten
cigarettes a day, and includes patients who may have smoked 1 day to more than 10 years.
Studies have shown that the effect of smoking on the severity of periodontal disease is dose-
dependent, related to the number of cigarettes smoked and the years of cigarette smoking. While
smoking one cigarette a day increased attachment loss by 0.5%, smoking 10 cigarettes a day
increased attachment loss by 5% and smoking 20 cigarettes a day increased attachment loss by
10% (Position Paper: Tobacco Use and the Periodontal Patient, 1999). If we had further divided
our definition of current/past smoker into those that smoked less than or greater than 10
cigarettes a day for less than or more than 5-10 years, then we may have found stronger
associations with radiographic bone loss in heavy and long-term smokers.

Further differences between our study and previous studies could possibly be explained by our
study’s limitations. This study uses interproximal posterior radiographs for radiographic bone
loss, which is only part of a comprehensive periodontal evaluation. While some studies have
shown a correlation between radiographic bone loss and clinical attachment loss (Grossi et al.,
1995), while others have shown moderate agreement (Farook et al., 2020). From this study, we
can only assume that the radiographic bone levels are reflective of periodontal disease status.

The use of interproximal posterior radiographs is a limitation itself. Areas can be excluded
because of difficulties in identifying CEJ and/or alveolar crest; only posterior radiographs are
used; buccal and lingual bone levels cannot be definitively measured; deviations from parallel
angulations could reduce the distance between CEJ and alveolar crest (Stoner, 1972).

19
Furthermore, patients that did not have adjacent molars were excluded. As a result, this study did
not include patients who have lost teeth to periodontal disease. As such, the prevalence of
patients with periodontal disease is more likely to be underrepresented in older age groups who
are more likely to have lost teeth.

Another limitation is that the study had small sample populations for some medical conditions.
Our finding that cancer patients have higher odds ratios of developing radiographic bone loss
may not be entirely accurate, as our sample size is 25 patients. We also cannot extrapolate data
from this population and apply it to the entire US population, as population biases occurred with
the selected sample pool living in the southwest and within proximity to Herman Ostrow School
of Dentistry. Potential reporting errors may have occurred using SRMC, as patients could
misreport conditions or social habits.

This retrospective radiographic study will be a part of a multi-center university study, which will
provide a larger sample size and perhaps provide insight into possible geographic variations in
radiographic prevalence of bone loss.

20
Chapter 4: Conclusion
Results of the study corroborate previous studies’ findings that increasing age groups have
higher odds of radiographic bone loss and that males are more likely to have radiographic bone
loss than females. Patients with prediabetes, diabetes, high cholesterol, hemophilia, hypertension,
joint replacement, arthritis, mood swings, and current/historic cancer presented with more than
two times prevalence of RBL in weighted percentage. Our multivariable analysis suggests that
age is a stronger predictor for RBL than SRMC and sex alone. This explains why all SRMC
except cancer were no longer significant in the multivariable analysis adjusted for age. The
strong associations that we found between chronic inflammatory conditions and RBL bone loss
are age-related, although the exact relationship is unknown. Our results emphasize the
importance of oral hygiene education to older age groups, particularly older males and patients
with current/past cancer history.

21
References
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10.1902/jop.1999.70.1.13.
American Academy of Periodontology Task Force Report on the Update to the 1999
Classification of Periodontal Diseases and Conditions. (2015). J Periodontol 86, 835-838.
10.1902/jop.2015.157001.
Baxter, D.H. (1967). The effect of orthodontic treatment on alveolar bone adjacent to the
cemento-enamel junction. Angle Orthod. 37, 35-47.
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27

Figure 1. Flow chart for identification of qualifying patient charts and separation into ten age
cohorts
Patient charts screened by IT and study
team (n=2000)
Excluded charts that did not meet
criteria (n=927)
Included charts that had
(n=1073):
• Patients between 15-64 years old
• Comprehensive oral
examinations and radiographs
completed within 3 months of
each other
• Diagnostic interproximal
radiographs with at least 8
posterior teeth (at least 2
adjacent teeth per quadrant)

Qualifying charts divided into ten age
cohorts for analysis:
• 15-19 years old (n=102)
• 20-24 years old (n=105)
• 25-29 years old (n=101)
• 30-34 years old (n=110)
• 40-44 years old (n=103)
• 45-49 years old (n=102)
• 50-54 years old (n=107)
• 55-59 years old (n=102)
• 60-64 years old (n=101)

28

Figure 2: Computed Dental Radiography (CDR) DICOM toolbar with “Measure” tab highlighted

Figure 3: Example of linear measurements used to determine radiographic bone loss in CDR
software

29

Figure 4. Prevalence of RBL by sex, smoking status, and SRMC
0
10
20
30
40
50
60
70
80
90
100
Male
Female
Present smoker
Past smoker
Never smoker
Prediabetes
Diabetes
High Cholesterol
Endocrine
Hemophilia
Anemia
Cardiac
Respiratory
Hypertension
Joint
Arthritis
Autoimmune
Hay fever
Anxiety
Mood
Depression
Osteoporosis
Cancer
No known disease
Prevalence
Prevalence of radiographic bone loss
Presence of RBL Absence of RBL

30

Figure 5. Associations between age and SMRC with radiographic bone loss (values that are
statistically significant (p≤ 0.05) are bolded)

Abstract (if available)

Abstract Objectives: To determine 1) the prevalence of RBL among Herman Ostrow School of Dentistry pre-doctoral patients 2) which age groups had greater RBL prevalence and 3) associations between RBL and sex, smoking status, and self-reported medical conditions (SRMC).
Materials and Methods: 1073 patients (ages 15-64) from the Herman Ostrow School of Dentistry predoctoral clinic were reviewed and divided into ten age cohorts. Patients with RBL had at least one site ≥2.5mm from the cemento-enamel junction to the alveolar crest on posterior interproximal radiographs.
Results: An overall RBL prevalence of 37.1% was observed. In a multivariable logistic regression model that controlled for sex and medical comorbidities, age was significantly associated with increased RBL in the following age groups: 40-44, 45-49, 50-54, 55-59, 60-64. RBL was significantly decreased in patients under the age of 24 (age groups 20-24, 15-19). Males were significantly associated with increased RBL compared to females (OR=1.532, 95% 1.105-2.123). Of SRMC, cancer was significantly associated with increased RBL (OR=4.717, 95% 1.342-16.579).
Conclusion: Our results suggest that patients above 40 years of age, male patients, and patients with current or historic cancer status have increased risk for RBL.

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Asset Metadata

Creator Ko, Julianna (author)

Core Title Radiographic alveolar bone loss and risk factors in a predoctoral clinic population

School School of Dentistry

Degree Master of Science

Degree Program Biomedical Implants and Tissue Engineering

Degree Conferral Date 2022-08

Publication Date 06/30/2022

Defense Date 06/30/2022

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Age,Diabetes,OAI-PMH Harvest,periodontitis,prevalence,radiographic alveolar bone loss,risk factors,self-reported medical conditions,smoking

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Kar, Kian (committee chair), Chen, Casey (committee member), Paine, Michael (committee member)

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