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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56:M55-M62 (2001)
© 2001 The Gerontological Society of America

Self-reported and Clinical Oral Health in Users of VA Health Care

Judith A. Jonesa,b,c, Nancy R. Kressina,c, Avron Spiro, IIId,e, Carolyn W. Randalla,b, Donald R. Millera,c,e, Catherine Hayesf, Lewis Kazisa,c and Raul I. Garciab,e

a The Center for Health Quality, Outcomes, and Economic Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts
b Department of Health Policy and Health Services Research, Boston University Goldman School of Dental Medicine, Massachusetts
c Departments of Health Services, Boston University School of Public Health, Massachusetts
d Departments of Epidemiology and Biostatistics, Boston University School of Public Health, Massachusetts
e Massachusetts' Veterans Epidemiologic Research and Information Center, VA Boston Healthcare System
f Harvard School of Dental Medicine, Boston, Massachusetts

Judith A. Jones, CHQOER (152), VAMC, 200 Springs Road, Bedford, MA 01730 E-mail: judjones{at}bu.edu.

Decision Editor: William B. Ershler, MD


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. This article describes the oral health of users of Veterans Administration (VA) health care using both clinical and self-report measures, and models relationships between these measures and self-perceived oral health.

Methods. We conducted a cross-sectional study of 538 male users of VA outpatient care in the Boston area. Questionnaires assessed self-reported oral health, oral-specific health-related quality of life, health behaviors, and sociodemographic information. Clinical data were collected on oral mucosa status, number of teeth and root tips, dental caries, and periodontal treatment need. We report clinical and self-reported oral health status by age group (era of military service). We regressed models of self-perceived oral health on clinical indices and self-reported measures of the impact of oral health on daily life, adjusting for sociodemographic characteristics and health behavior.

Results. Among those participants aged 65 to 91 years old, 2.8%, 18.7%, and 41.5% rated their oral health as excellent, very good, or good, respectively. Among 50- to 64-year-old men, the corresponding values were 1.4%, 18.5%, and 40.4%, while among those aged 22 to 49 years old, the values were 2.3%, 17%, and 34.1%. Tooth loss was common among users of VA care; 34% of those aged 65–90 years, 28% of those aged 50–64 years, and 8% of those aged 25–49 years had no teeth. Periodontal treatment needs were uniformly high among persons with teeth; mild mucosal change was common, and 10% had root tips. Regression models showed self-perceived oral health was better in persons with more teeth and recent dental treatment, and worse with tooth mobility, coronal decay, and more medical problems. Measures of the impact of oral conditions on daily life added significantly to the amount of explained variance in self-perceived oral health.

Conclusions. Clinical conditions and the impact of oral health on daily life are important determinants of self-perceived oral health.

CURRENT understanding of self-reported oral health draws on conceptual models that describe the effects of health on daily life. Locker (1) adapted the World Health Organization's Classification of Impairments, Disabilities, and Handicaps to oral health. In his view, oral diseases lead to impairments, such as tooth loss and poorly fitting dentures. Oral impairments, in turn, may be related to discomfort (from dentures) or functional limitation (difficulty chewing). Functional limitations and discomfort can, in turn, affect disability (e.g., alteration of diet because of an inability to chew and swallow food). Functional limitations and discomfort can similarly be associated with handicap (e.g., disinterest in eating with others because of embarrassment during meals caused by denture slipping).

Self-perceived health is thought to be the end result of the effects of systemic diseases, disabilities, and limitations of daily activities (2). Gilbert and colleagues (3) presented a conceptual model in which self-rated oral health is the end result of inputs from multiple dimensions (Fig. 1), including clinical oral disease and tissue damage, oral pain and discomfort, oral functional limitation, and oral disadvantage. Although Gilbert and his colleagues (3) explicitly posited a "sequential causal process involving specific antecedents and consequents," we suggest a modification to this model in which oral pain and discomfort, functional limitations, disadvantage and diminished self-rated oral health can occur either contemporaneously or sequentially.



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  		Figure 1. Multidimensional conceptual model of oral health (from Gilbert and colleagues [3]).

 
We examined the self-reported and clinical correlates of oral health (assessed by self-report and clinical exam) in veterans who are users of Veterans Administration (VA) outpatient care using Gilbert and colleagues' model to study relationships between clinical and self-perceived oral health. As with Gilbert and colleagues, we posit that persons with poorer clinical oral conditions will have poorer self-rated oral health. Further, we examined whether oral pain and discomfort, oral functional limitations, and oral disadvantage are associated with self-rated oral health. Finally, we hypothesize that positive health behaviors and fewer medical comorbidities are associated with better self-rated oral health.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Sample
Male veterans (n = 538) were enrolled in a cross-sectional study of clinical and self-reported oral problems and their effects on self-perceived oral health between December 1995 and May 1997. The institutional review boards of the participating VA facilities approved the study.

The sample was recruited from participants in the Veterans Health Study (VHS), a longitudinal observational study of the health and functional status in 2425 male veterans who used care in four VA outpatient clinics in the greater Boston area (4)(5). Details of the VHS recruitment process have been published previously (4)(5). Briefly, male veterans who attended the clinics between August 1993 and March 1996 (n = 7780) were eligible if their last visit was within the previous 12 months. Of these, 4137 provided contact information and read and signed informed consent, and 2425 recruited for the VHS.

VHS participants who had any study visits between December 1995 and March 1997 (n = 2228) were queried as to whether they would be willing to participate in the current study. Persons who responded positively were asked to complete a dental screening form and 538 (24%) participated in the current dental study.

Outcome Measure
Our primary outcome of interest was a single-item, 5-point global self-rating of oral status (OH1, ranging from 1 = excellent to 5 = poor) used previously by Gilbert and colleagues (3) and Atchison and Dolan (6) and collected by questionnaire during the dental study visit.

Explanatory Variables
Questionnaire data from two sources were used in this study. The VHS questionnaire administered prior to the study visit (within the previous 3 years) included the 12-item Geriatric Oral Health Assessment Index (GOHAI), developed by Atchison and Dolan (6). The GOHAI assesses oral functional status; worry or concern; ability to eat, chew, and swallow; pain or discomfort; and social functioning related to oral health.

During the same visit in which the dental examinations were conducted, all participants completed a second questionnaire to assess self-reported oral health and the effects of oral conditions on daily life (Oral Quality of Life, or OQOL). The questionnaire included the 3-item Oral Health-related Quality of Life (OHQOL) scale, which assessed how often problems with teeth or gums affected daily or social activities, or caused a person to avoid conversations because of how he or she looked (7), and the 49-item Oral Health Impact Profile (OHIP) developed by Slade and Spencer (8). The OHIP is based on a conceptual framework of oral disease and its functional and psychosocial consequences. The OHIP's 49 items are divided into seven subscales: functional limitation, pain, psychological discomfort, physical disability, psychological disability, social disability and disadvantage. Together, the OHQOL, GOHAI, and OHIP contain items assessing oral pain and discomfort, oral functional limitations, and oral disadvantage (the middle three boxes in Gilbert and colleagues' model shown in Fig. 1). The metrics used for OHQOL, GOHAI, and OHIP are described in the proceedings of the conference on "Measuring Oral Health and Quality of Life" (9). Because the metrics of the scales are not directly comparable, each was converted to a 0 to 100 metric with 0 representing poor oral health and 100, excellent health. For the OHQOL and GOHAI, the conversion formula was [(score – minimum possible score)/(maximum possible – minimum possible score)] · 100. For the OHIP, the formula was 100 – some of the new OHIP · 100/43 (43 rather than 49 is used because we omitted six items, including three denture- and three tooth-related items that did not apply to all participants). (Further details of the scoring are available from author JAJ.) Oral health behaviors included self-reports of time since last dental visit (<1 year, 1–2 years, 2–5 years, and 5+ years) and the reason for last visit (10).

Sociodemographic information, general health behaviors, and general health status were assessed via questionnaires administered by the VHS prior to the dental examination. A medical history interview was used to ascertain status on two conditions we expected to be related to oral health: diabetes and arthritis. This interview also provided information for the comorbidity index, a count-based measure (sum) of the number of comorbid medical (possible = 30) and mental (possible = 6) conditions (11) developed in the VHS. Because we considered diabetes and arthritis separately, the comorbidity index could range from 0 to 34. Smoking was also assessed from this questionnaire. Responses included current, former, and never. Current problems with alcohol were assessed using the "CAGE," which inquiries whether (i) the participant ever cut down on drinking, (ii) people had been annoyed about the participant's drinking, (iii) had the participant ever felt guilty about their drinking, or (iv) did the participant ever have a drink first thing in the morning (eye opener) to steady their nerves or get rid of a hangover (12). Positive answers to two or more CAGE questions in addition to the use of alcohol in the last year were considered a positive indicator for current problems with alcohol.

Clinical Variables
A trained dental hygienist conducted a brief (10–12 min) clinical examination. Interexaminer reliability between a calibrating examiner and the study examiner remained high throughout the study (13) with the percentage of agreement on clinical parameters ranging from 87% to 100% during the study and generally exceeding 93%. We assessed oral mucosa (14) at seven sites in the mouth. Each site received an ordinal score ranging from 0, indicating normal mucosa, to 3, indicating severe (ulcerative) changes or other gross abnormalities. From these, we computed per-person means and high scores. We used the Community Periodontal Index of Treatment Needs (CPITN) to assess periodontal treatment need (15). Measures were taken from 10 index teeth. Each tooth received a score of 0–4, with 0 indicating health and 4 indicating severe disease. The worst scores from each sextant of the mouth were summed and divided by the number of sextants yielding a per-person mean; the worst score per person was also recorded. Coronal caries was scored as in National Institute of Dental Research protocols for their National Survey of Oral Health in Adults (16). Their procedures were modified, as in the VA Dental Longitudinal Study (17), to reflect three levels of decay. For this study, we used decay at level 2, decay that breaks the surface but does not clinically appear to involve the pulp. On pits and fissures, this means that "an explorer catches after insertion with moderate to firm pressure and either softness at the base, opacity adjacent to the area or softened enamel which can be scraped away by the explorer"(16). We also used an index developed by Hayes and Katz (18) that measures root caries and restorations on only eight tooth surfaces. The resulting score is a percentage of the eight root surfaces (with at least 1 mm of recession) that have decay (D + DF)/(D + F + DF + S) or decay plus fillings (D + DF + F)/(D + F + DF + S). (Note: D = decayed, F = filled, and S = sound tooth surfaces.) Root tips were counted as such if they were present without any coronal walls. Root tips could be counted as decayed or sound in the coronal caries count but not in the root caries since the cementoenamel junction was missing on these teeth. Teeth were considered mobile if there was movement greater than 1 mm in any direction.

Analyses
All analyses were performed using SAS software (version 6.12; SAS, Inc., Cary, NC). Previous work showed that age distribution in the VHS was trimodal, with distinct patterns of health and functional status in each group (4)(5). These differences were related to selection into the VA health care system as a function of era of military service and the VA enrollment process. Thus, the youngest group of veterans using VA health care had substantially higher prevalences of mental illnesses, such as depression and problems with alcohol, than the other two groups, although physical illnesses were more prevalent in the oldest age group (4)(5). Accordingly, our descriptive and subsequent analyses were stratified by three age groups: 22–49, 50–64, and 65+ years, roughly corresponding to era of military service (i.e., 22–49 years [Vietnam through Bosnia], 50–64 years [Korea], and 65+ years [World War II]).

We then used a series of age-stratified ordinary least squares regressions to examine the associations between self-perceived oral health, or OH1, and oral conditions and the impact of oral conditions on daily life, controlling for sociodemographic factors, health behaviors, and medical comorbidities. Initially, OH1 was regressed on sociodemographic variables, health behaviors, medical comorbidities, and only two clinical oral variables available from all participants (i.e., oral mucosa score and dentition group). Sociodemographic factors included age, education, race (white, nonwhite), employment status (employed, not employed), and marital status (married, not married). Health behaviors included recency of use of dental care (<1 year, >=1 year), reason for last visit, and smoking status (current, former, never). Medical comorbidities included problems with alcohol, diabetes and arthritis, and the summary comorbidity index (11). In our calculation of the comorbidity index, the total possible score was 34 rather than 36 because arthritis and diabetes were considered separately. Number of teeth was divided into five groups: (i) no teeth, (ii) 1–10 teeth, (iii) 11–20 teeth, (iv) 21–24 teeth, and (v) 25+ teeth, based on differences in functional status according to these groupings found in previous work from the VA Dental Longitudinal study (19). Mucosal status (worst score per person) was included in the first models. For each age group, we used stepwise regression to identify candidate variables for inclusion in the first model. We retained all variables associated with self-rated oral health at p <= .15 in any age group for the final multivariable regressions in the first models. For the second set of age-specific models, we retained dentition status, dental visit in last year, marriage status, diabetes status, and the comorbidity index. To these, we added tooth-related measures (i.e., coronal caries [at level 2 as a continuous variable], root caries [continuous], periodontal treatment need [categorical variable from 0 to 4] and mobile teeth [continuous]). Because edentulous persons did not have any teeth, they were omitted from this second (and also the third) set of analyses. For the second set of models, we present data from the regressions, which included all variables with beta estimates significant at p <= .15 in any age group. For the third set of models, we again retained all variables previously found to be significant predictors of self-rated oral health and added, one at a time, the oral quality of life scores (OHQOL, GOHAI, OHIP) into the models. The second and third sets of analyses were restricted to only those men with complete data for both sets of models. Beta coefficients estimated in these models correspond to the change in self-rated oral health corresponding to a one-level change in the explanatory variable.


   Results
Top
 Abstract
 Methods
 Results
Discussion
 References
 
The mean age in our sample was 62 years, and almost all participants (92%) were white. Most had finished high school, with an average of 12.5 years of education. The mean income of our sample was just under $20,000. Twenty-one percent of the participants were current smokers, and 56% were former smokers.

Comparison With the VHS
Participants in this study (n = 538) were similar to the other participants in the VHS (n = 1887) with respect to age, race, education, income, and marital status. The present sample had fewer current smokers (21% vs 28%). Because smoking is generally associated with poorer oral health (20), less tobacco use among participants in our sample may indicate that they actually have better oral health than the rest of the VHS sample.

Self-reported oral health by age is shown in Fig. 2. Almost two thirds (63%) of those aged 65–91 years, half (53.4%) of those aged 22–49 years, and 60.3% of those aged 50–64 years rated their oral health as good or better.



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  		Figure 2. Self-rated oral health by age group (in percentages).

 
Mean scores for self-reported oral health and oral-specific quality of life instruments (i.e., OHQOL, GOHAI, and OHIP) by age group are shown in Table 1 . In general, older veterans had slightly better self-reported oral health and oral quality of life. To permit comparisons among the measures, self-reported oral health and oral-specific quality of life scores were rescored to a standard 0 to 100 metric, with higher scores indicating better oral health (Table 2 ). The oral-specific health-related quality- of-life instruments (OHQOL, GOHAI, OHIP) are skewed toward the higher end of the scale; the single-item self-reported oral health is more symmetrically distributed.


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  		Table 1. Mean of Self-reported Oral Health Indices by Age Group (Raw Scores)

 

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  		Table 2. Mean of Self-reported Oral Health Indices by Age Group (Scores Using 0 to 100 Metric)

 
Clinical oral health conditions by age group (era of service) are shown in Table 3 . Mean oral mucosa scores averaged 0.6 to 0.7, consistent with mild changes. Worst mucosa scores per person were ~1.9; on average, participants had one area of moderate mucosal damage. The percentage of the sample with any teeth was 92% in the 22–49-year-old group, 72% in the 50–64-year-old group, and 66% in the 65–90-year-old group of participants. Among persons with teeth, mean number of teeth was lower in older age groups. These patterns of tooth loss parallel those in the general population. The percentage of the sample with mobile teeth was higher in the older two groups (61% and 55%) relative to the youngest age group (35%). Ten percent of the participants overall had root tips. The mean of the per-person average of the periodontal treatment need (CPITN) scores approximated 2, indicating the presence of calculus was common, and that participants needed to get their teeth cleaned. The mean of the worst periodontal score per person approximated 3, indicating that, on average, participants had at least one area of the mouth that needed periodontal scaling and root planing.


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  		Table 3. Oral Health Conditions, Coronal Caries, and Root Caries by Age

 
Coronal decayed surfaces (DS) and the D component (D/DFS, the percentage of caries that was unfilled) for coronal caries were stable across age groups (Table 3 ). As expected, modified root caries index scores (RCI_D) were greater in the older age groups. Restored plus filled root surfaces (RCI_DF), as a percentage of total exposed root surfaces, were also greater in the older age groups. For RCI_DF, mean scores in the 22–49-year-old (10%) and the 50–64-year-old age groups (15%) were significantly different (p < .05, using the Duncan test) from those aged 65+ years (22%). Among those aged greater than 65 years, the trend of an increased percentage continued, but was not significant (65–74 years, 18%; 75–84 years, 33%; 85+ years, 42%).

Use of Dental Care
Two thirds (63.5%) of the 22–49-year-old group had seen a dentist in the last year, compared with only 43% of the 50–64-year-old and half (49%) of the 65–90-year-old participants. However, when recency of dental care use by age group and dentition status is examined (Table 4 ), the proportion of dentate veterans who had seen a dentist in the past 2 years is consistent across the age groups. The reason for the last dental visit, by age, is also shown in Table 4 . Although only 6% of the oldest age group and 7% of the 50–64-year-old participants had used emergency care as the main reason for the last visit, this was the case for 16% of those in the youngest age group. In contrast, 40% of the youngest veterans cited routine exam and cleaning as the reason for their last visit, versus 29% of the middle-aged group and 36% of the oldest age group. The frequency of denture care as a reason for the last visit increased with age.


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  		Table 4. Reasons for and Time of Last Visit by Dentition Status and/or Age Group (in percentages)

 
Regression Models
We regressed the OH1, controlling for sociodemographic variables, health behaviors, and medical comorbidities, on mucosal status and dentition group to examine their associations with self-perceived oral health. In the models examining all participants, use of care in the last year was consistently associated with better self-rated oral health (Table 5 ). For the second set of analyses conducted only in dentate men, we dropped periodontal treatment need, diabetes, and marital status, because they did not contribute any explanatory power to the models. Among the dentate in the youngest age group, more coronal caries was related to worse oral health, although the percentage of root surfaces that were decayed or filled (indicating more root caries plus treatment for it) was related to better self-rated oral health. As hypothesized, more teeth and a visit in the last year were associated with better self-rated oral health, while the number of comorbidities and tooth mobility were associated with worse self-rated oral health. Also consistent with our hypothesis, when elements of oral pain, discomfort, functional limitation and disadvantage are added to the models with the OHQOL, GOHAI, and OHIP, the final multivariable models explain substantially more variance than without these dimensions, with improvements in R2 ranging from 3% to 19%. Because parameter estimates did not vary substantially between models, including the OHQOL, GOHAI, and OHIP, they were listed for OHQOL, but not listed for GOHAI and OHIP, and are available on request from the first author.


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  		Table 5. Regression of Self-reported Oral Health by Age Group

 

   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
References
 
This study describes self-rated oral health in a sample of VA patients and demonstrates its value as a measure of oral health in that associations with clinical and other patient measures were observed as predicted by the conceptual model (3). Self-rated oral health was related to dentition status, coronal caries, mobile teeth, and use of dental care, as well as overall illness burden as measured by comorbid medical conditions. The finding that disease burden (comorbidity index) is related to self-reported oral health in VHS participants with a high illness burden (multiple medical problems) and poor health-related quality of life (4)(5) is especially important. This finding is consistent with our previous work (21) that suggests that self-reported oral health is also related to functional status. Our work is consistent with Gilbert and colleagues' in that, as hypothesized, the impact of oral conditions on daily life (as measured by the OHQOL, GOHAI, and OHIP) add significant explanatory power to models that explain variance in self-perceived oral health. Further, our work extends that of Gilbert and colleagues in that it suggests that although oral disease and tissue damage temporally precede other elements of the model, oral pain and discomfort, functional limitations, and disadvantage need not necessarily precede self-rated oral health, but can occur with self-perceived oral health at a single point in time.

One strength of our study is that we report on clinical and self-reported oral health among users of VA health care. The oral health of these veterans is important because the U.S. Department of Veterans Affairs operates one of the largest health care systems in the nation, providing 35.8 million outpatient visits annually (22). Previous work showed that the general health and functional status of users of VA ambulatory care are substantially worse than non-VA populations (4)(5). Further, users of VA care also report worse oral health than other samples of older adults (21)(23). However, few data are available that describe the relationships between veterans' clinical and self-reported oral health.

Of special note is that self-reported oral health-related quality of life as measured by the GOHAI and OHIP is better among older VA patients than in the younger ones. This finding contrasts with the observed age-associated decrements in clinical oral health status (number of teeth, mobility, and dental caries). A plausible explanation may be related to selection effects that overlap with era of service. Patient characteristics (or selection effects) in VA facilities seem to operate differently than elsewhere, such that younger VA patients must meet economic or disease criteria to be enrolled in VA health care. As a result, they present with different characteristics that can affect self-reported oral health. For example, the youngest age group has a higher prevalence of mental disorders, including depression. Previous work (24) (also N.R. Kressin, A. Spiro, K. A. Atchinson, L. Kazis, and J.A. Jones, unpublished data, 2000) found that poorer OQOL is associated with depression. Alternatively, the self-report measures may reflect an acclimatization or acceptance among older veterans of their declines in oral health. Perhaps clinical determinants of self-reported oral health that do not seem to vary with age moderate the effects of those variables that do. Some of the clinical parameters (i.e., root tips, periodontal treatment need, mucosal scores, and coronal decayed teeth) were remarkably stable over the three age groups. These data also suggest that the surviving teeth have a threshold level of disease, beyond which terminal intervention (extraction) occurs.

The practical value of self-reported oral health measures is still largely undeveloped (21)(25)(26). At present, these measures can be used as broad assessments of treatment need or to estimate population—level effects of oral conditions on daily life. In the future, they may be used to assess and monitor improvements in the oral health status of society. In this study, we found that self-report of oral health was related to clinical oral disease (and thus need for care). Used in this way, self-report measures may provide an estimate of resources needed to care for a specific population. However, further work is needed to examine the sensitivity and specificity of patient-based measures in identifying persons who need care. Measures that can predict how much care a population needs would also be useful, especially in large health care systems such as VA and managed care organizations. Future work should examine whether interventions that improve self-perceived oral health also positively influence overall health and functional status.

A major limitation of this study and others like it is that the data are cross-sectional. Longitudinal studies that link baseline self-reported oral health and quality-of-life measures to subsequent use of care are needed. Finally, self-reported measures of oral health will be useful to measure the impact of care provided on an individual level, in populations, and in studies of the effectiveness of alternative dental treatments in clinical trials.


   Acknowledgments
 
The authors gratefully acknowledge the programming support of Ms. Usree Kirtania and Ms. Yao Meng. Dr. Jones and Dr. Garcia are the recipients of Department of Veterans Affairs Health Services Research and Development Career Development Awards. This research was funded by the Department of Veterans Affairs Health Services Research and Development Service (IIR93.025, SDR 91-0061, HFP92-002, and HFP91-012). The views expressed in this article are those of the authors and do not necessarily represent those of the Department of Veterans Affairs.

Received September 10, 1999

Accepted March 30, 2000


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

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