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Psychosomatic Medicine 61:508-512 (1999)
© 1999 American Psychosomatic Society

ORIGINAL ARTICLES

Depressive Symptoms Favor Abundant Growth of Salivary Lactobacilli

Sirpa S. Anttila, DDS, Matti L. E. Knuuttila, DDS, PhD and Tero K. Sakki, DDS, PhD

From the Department of Periodontology and Geriatric Dentistry, Institute of Dentistry, University of Oulu (S.S.A., T.K.S.), and Oral and Maxillofacial Department, Oulu University Hospital (M.L.E.K.), Oulu, Finland.

Address reprint requests to: Sirpa S. Anttila, DDS, Institute of Dentistry, University of Oulu, Aapistie 3, FIN-90220 Oulu, Finland.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
OBJECTIVE: The purpose was to study the growth of lactobacilli in subjects with depressive symptoms in the total 55-year-old population of Oulu (a medium-sized town in Finland); 780 people participated.

METHODS: The dental examination included measurements of salivary lactobacillus growth with the Dentocult-LB method; measurements of salivary flow rate, pH, and buffering capacity; and assessment of oral health status. Depressive symptoms were determined with the Zung Self-Rating Depression Scale (ZSDS). Participants were also asked about their health, medication, smoking, and dietary habits.

RESULTS: The prevalence of high lactobacillus counts (>=100,000 CFU/ml) was 22% among women and 31% among men (p = .02). Thirty-seven percent of the subjects with a high rate of depressive symptoms (ZSDS score of >=40) and 23% of those with an ZSDS score of <=39 had high counts of lactobacilli (p = .003). A logistic regression analysis with improvement of goodness of fit was made to confirm the relation between abundant lactobacilli and a high rate of depressive symptoms. After the confounding factors had been added stepwise into the logistic regression model, depressive symptoms were still significantly associated with abundant lactobacillus growth.

CONCLUSIONS: The association between high lactobacillus counts and depressive symptoms suggests that depressed subjects are at risk of having caries and possibly other dental diseases that should be recognized in the treatment of these patients.

Key Words: salivary lactobacilli • dental health • depressive symptoms

Abbreviations: BMDP = biomedical data program; DSM-III =Diagnostic and Statistical Manual of Mental Disorders,third edition; Ig = immunoglobulin; PLR = procedure oflogistic regression; ZSDS = Zung Self-Rating Depression Scale.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Eating disorders are not uncommon among patients with affective disorders (1). Depression is associated with decreased metabolism of serotonin (2), which has been postulated to play a role in macronutrient choice, with reduced serotoninergic activity leading to a preference for carbohydrates (1).

Frequent intake of fermentable carbohydrates favors the growth of lactobacilli (3), a high count of which indicates the presence of risk factors for the development of dental caries (4). The Dentocult-LB dip-slide test (5) has made it possible to determine the salivary lactobacillus count in everyday dental practice, where it can be used to determine the interval between dental checkups or as an educational aid for motivation and dietary counseling (4). High salivary lactobacillus counts have also been found to be associated with a high prevalence of denture stomatitis (6).

Saliva has a major role in preventing bacterial adherence to tissues. A low salivary pH and flow rate (7, 8) and a low buffering capacity (8) may favor the growth of lactobacilli. Various medications may also increase the lactobacillus count by having a detrimental effect on salivary secretion.

Some characteristics connected with depression may, either directly or indirectly, favor the growth of lactobacilli. Such factors include diet, oral health behavior, medication, and disorders of the endocrine and monoamine regulatory mechanisms, some of which may, in turn, contribute to the extent and nature of salivary secretion.

The aim of this study was to analyze the association between depressive symptoms and salivary lactobacillus counts, to determine whether depressive symptoms could alter the ecologic balance in the mouth and thereby impair oral health.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
The population comprised all 1012 inhabitants born in 1935 and living in Oulu, a city of 100,000 inhabitants in northern Finland. Examinations were performed from October 1990 through September 1991. Four people died before the examination, and 780 (77% of those alive) eventually participated in the clinical interviews and examination.

Questionnaires were mailed to each member of the population and checked at the time of the clinical examination, when the subjects were also interviewed. The mailed questionnaire included questions on dietary habits: use of sugar in coffee or tea (no/yes); consumption of sweets, snacks, and soft drinks (daily or 1–2 times per week/occasionally or never); and consumption of vegetables, fruit, and root crops (daily/1–2 times per week or rarely). Questions were based on those used in Finnish national surveys (9). Subjects were interviewed about their smoking habits (nonsmoker or ex-smoker/occasional or regular smoker) and the subjective sensation of oral dryness (never or rarely/sometimes/often).

Dental examinations were performed by two dentists, who recorded the occurrence of caries using the diagnostic criteria recommended by the World Health Organization (10). Interexaminer agreement in caries diagnosis was 99.1%, and {kappa} = 0.77. Intraexaminer agreement was 99.7% and {kappa} = 0.77 for T. K. Sakki; corresponding values for S. S. Anttila were 99.5% and 0.80. Oral hygiene status (good/moderate/poor) was estimated using plaque accumulation on the teeth as the main criterion.

Salivary lactobacillus counts were measured with the Dentocult-LB method (Orion Diagnostica, Espoo, Finland) according to the manufacturer’s instructions. The lactobacillus count was considered high if the number of microorganisms was at least 100,000 CFU/ml (11, 12). For measurement of unstimulated saliva secretion, subjects spat the freely secreted saliva into a test tube via a funnel. After the unstimulated saliva was collected, the paraffin wax–stimulated salivary flow rate was measured after 1 minute of prestimulation. Collection time was 5 minutes for both measurements, and flow rates were calculated as milliliters per minute. Unstimulated salivary flow rates of <=0.1 ml/min and stimulated flow rates of <=0.7 ml/min were considered low flow rates (13–15). Buffering capacity was measured from stimulated saliva with the Dentobuff strip (Orion Diagnostica) and classified as high (final saliva pH of >=6.0) or low (final saliva pH of <=5.5). Saliva pH was measured with indicator paper and classified as <=7 or >=8.

Illnesses and use of drugs were recorded by physicians. The following diseases (other than depressive disorder) that may be associated with a dry mouth (16) were present in this study population: Sjögren’s syndrome, rheumatoid diseases, sarcoidosis, hypertension, hyperlipidemia, diabetes mellitus, and anxiety disorder. Xerogenic medications included all drugs that, according to the list published by the Finnish Association of Pharmaceutical Chemists (17), may have xerogenic side effects and were available in Finland in 1990. The xerogenic medications were the same as those used in our previous study (18).

Depressive symptoms were determined with the ZSDS, which was completed for 768 subjects (338 men and 430 women). The ZSDS questionnaire includes 20 items (19), each of which contains four reply alternatives. These measure common psychic and somatic symptoms, including the criteria generally used in diagnosing depression. Scores were calculated as total raw sum points on a scale of 20 to 80, using the method described by Zung (19). The validity of the ZSDS has been tested against the diagnosis of major depression based on DSM-III criteria among elderly patients (aged 60 years or more) of medical clinics (20, 21). With a cutoff of 39/40 raw sum points, the sensitivity of the ZSDS ranged from 79% to 100%, and the specificity ranged from 55% to 57%. In a study of Finnish men and women aged 65 years or more, the sensitivity of the ZSDS was 87.4% and the specificity was 61.5% with a cutoff of 39/40 (S.-L. Kivelä, unpublished results). A cutoff of 39/40 was recommended by Zung for studying working-aged populations (22).

Cross-tabulation was used to test the associations between pairs of variables, and the difference was tested using {chi}2 statistics. A logistic regression analysis, a PLR application of the BMDP statistical software, with an improvement of goodness of fit (23) was used to identify variables associated with abundant salivary lactobacillus growth (>=100,000 CFU/ml). Variables were added stepwise, and the improvement of the model was measured by a change of the log likelihood and by the difference of deviance. Depressive symptoms were added to the models last (Table 2) and first (Table 3). We also made models of each variable or variable groups alone before the addition of depressive symptoms to study the influence of each variable on the association between depressive symptoms and lactobacillus growth (data not presented).


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  		Table 2. Improvement of Goodness of Fit of Logistic Regression Model Related to High Lactobacillus Count (>=100,000 CFU/ml) by Adding Variables in a Stepwise Manner (N = 508)
 

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  		Table 3. Improvement of Goodness of Fit of Logistic Regression Model Related to High Lactobacillus Count (>=100,000 CFU/ml) by Adding Variables in a Stepwise Manner (N = 508)
 

   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
The prevalence of high lactobacillus counts (>=100,000 CFU/ml) was 22% in women and 31% in men (p = .02); the prevalence of high depressive symptoms scores (ZSDS >= 40) was 23% and 20%, respectively. Thirty-seven percent of subjects with a high rate of depressive symptoms and 23% of those with ZSDS scores of <=39 had high counts of lactobacilli (p = .003) (Table 1). NS = not significant.


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  		Table 1. Prevalences of High Lactobacillus Counts and High Numbers of Depressive Symptoms in Relation to Individual Explanatory Variables in a Dentate Population
 

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  		Table 1A. —Continued
 
The following variables were associated with high lactobacillus counts in a bivariate analysis: low unstimulated salivary flow rate (p = .054); low pH of unstimulated whole saliva (p = .001); low buffering capacity (p = .003); at least three daily medicines (p = .023); use of a combination of psychopharmacological and other drugs (p = .027); poor oral hygiene (p = .001); smoking (p = .001); use of sugar in coffee or tea (p = .052); minor consumption of vegetables, fruit, and root crops (p = .026); removable dentures (p = .001); and at least one decayed surface (p = .001). The number of daily medications and use of a combination of psychopharmacological and other drugs were the only variables associated with both abundant lactobacillus growth and a high rate of depressive symptoms (Table 1).

To confirm the relation between a high lactobacillus count and a high rate of depressive symptoms, logistic regression models were made using variables that had bivariate associations with lactobacillus count. When depressive symptoms were added into the model last, it still turned out to be significantly associated with abundant lactobacillus growth (p = .011) (Table 2). After controlling for the effect of the other variables, the odds ratio (with 95% confidence limits) for depressive symptoms was 2.0 (1.2–3.3). When depressive symptoms were added to the model first (Table 3), the already-insignificant association between lactobacillus growth and medication was further diminished. We also made models of each variable or variable groups alone before adding the depressive symptoms to study the influence of each variable on the association between depressive symptoms and lactobacillus growth (data not presented). Depressive symptoms significantly improved the model after each variable. However, the significance was slightly weaker after smoking, number of daily medications, combination of psychopharmacological and other drugs, and oral hygiene compared with the other variables.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Our results show that there is an association between salivary lactobacillus count and depressive symptoms even when the most important confounding factors are controlled for (Table 2). Furthermore, in agreement with earlier results, lactobacilli were related to such factors as decreased salivary flow rate and pH (7, 8), low buffering capacity (8), use of removable dentures (24), smoking (25), and open carious lesions (26).

The prevalence of depressive symptoms varies widely because of differences in samples, methods, and classifications. However, depressive symptoms seem to be quite common; summaries of adult population surveys show that one-tenth to one-third of adults suffer from depressive symptoms (27). The Zung rating scale is best used to assess the severity of depression, not as a tool to diagnose clinical depression. Consequently, participants who scored 40 raw sum points or more were considered to have a high rate of depressive symptoms. In this study population, the prevalence of a high rate of depressive symptoms (ZSDS score >= 40) was 23% in women and 20% in men. The proportion of subjects with high salivary lactobacillus counts(>=100,000 CFU/ml) in the same age group has ranged from 14% (28) to 40% (12), and the prevalence in our total population (27%) fell halfway between these figures.

In bivariate analysis, the number of medicines used and the combination of psychopharmacological and other drugs were the only variables associated with both a high lactobacillus count and a high rate of depressive symptoms (Table 1). However, the association between medication and a high lactobacillus count was not supported by the presented logistic models (Tables 2 and 3). When each variable or variable group was added to the model alone before depressive symptoms, smoking, medication, and oral hygiene slightly diminished the significance of the association between depressive symptoms and abundant lactobacillus growth (data not presented). However, even when these other factors were controlled for, the odds ratio for depressive symptoms remained the same (Tables 2 and 3).

A high lactobacillus count can be considered an indicator of a certain type of behavior, or there may be a biological explanation for it. One possible factor connecting lactobacillus growth and depressive symptoms is diet. More frequent consumption of sweets, snacks, or soft drinks by the depressed (Table 1) supports the earlier findings of increased carbohydrate consumption among depressed persons (29), but this influence was not powerful enough to increase lactobacillus counts significantly. The preference for carbohydrates by the depressed may also imply a preference for food with a high glycemic index, such as starch-containing pasta, bread, potatoes, rice, and corn. Cooked starchy food can be used as a source of energy by lactobacilli after salivary amylase has converted the starch into a fermentable form (30). Unfortunately, our analysis of food intake does not warrant further conclusions concerning possible associations.

Depression is often associated with hypercortisolemia (2), which may impair the normal functions of the immune system. The reports on immune alterations in the literature are contradictory, but it seems that such alterations occur mainly in cellular immunity (31). In fact, Bauer et al. (32) did not find differences in IgG, IgM, or IgA titers between patients with major depression and healthy control subjects. Both immune (IgA, IgG, and IgM) and nonimmune defense factors in saliva (33) may affect the growth of salivary lactobacilli. However, there are no data available on the effects of depression on either immune or nonimmune salivary defense factors. Therefore, the possibility that the impairment of immune defenses would account for the overgrowth of salivary lactobacilli cannot be totally excluded.

Saliva and its components can affect salivary lactobacillus growth. Decreased flow rate, pH, and buffering capacity are not, however, enough to explain the association between depressive symptoms and high lactobacillus counts. Mucins are highly glycosylated salivary proteins that protect mucosal surfaces from desiccation and environmental insult (34). Furthermore, they are suggested to have an important role in inhibiting bacterial colonization in the oral cavity (34, 35). It has been suggested that the biosynthesis of mucins is regulated by multiple extrinsic controls and that the mucin structure is controlled by neurotransmitters (34). In our previous study (18) concerning the association between depressive symptoms and the sensation of dry mouth, we hypothesized that the sensation of dry mouth in depressed persons might partly be due to alterations in the regulatory mechanisms contributing to mucin content. The structural heterogeneity of mucins has been suggested to modulate the bacterial clearance–adherence phenomena in the oral cavity (34). It is possible that some biochemical and biological alterations associated with depression might influence the structure of mucins and thereby the amount of salivary lactobacilli.

A high salivary lactobacillus count gives us information of the oral conditions. Abundant lactobacillus growth shows the subject to be at risk for caries and possibly other dental diseases. The association between high lactobacillus counts and depressive symptoms therefore suggests an increased risk of dental diseases among depressed subjects, which should be recognized in their treatment.

Received for publication March 27, 1998.

Revision received March 31, 1999.


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 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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