PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Soc Sci Med. Author manuscript; available in PMC Nov 1, 2011.
Published in final edited form as:
PMCID: PMC2954891
NIHMSID: NIHMS236525
Social Inequalities in Childhood Dental Caries: The Convergent Roles of Stress, Bacteria and Disadvantage
W. Thomas Boyce, Pamela K Den Besten, DDS, Juliet Stamperdahl, PhD, Ling Zhan, DDS, PhD, Yebin Jiang, PhD, Nancy E Adler, PhD, and John D Featherstone, PhD
Pamela K Den Besten, University of California, San Francisco;
Corresponding Author: W. Thomas Boyce, University of British Columbia Vancouver, BC CANADA, tom.boyce/at/ubc.ca
The studies reported here examines stress-related psychobiological processes that might account for the high, disproportionate rates of dental caries, the most common chronic disease of childhood, among children growing up in low socioeconomic status (SES) families. In two 2004 – 2006 studies of kindergarten children from varying socioeconomic backgrounds in the San Francisco Bay Area of California (Ns = 94 and 38), we performed detailed dental examinations to count decayed, missing or filled dental surfaces and microtomography to assess the thickness and density of microanatomic dental compartments in exfoliated, deciduous teeth (i.e., the shed, primary dentition). Cross-sectional, multivariate associations were examined between these measures and SES-related risk factors, including household education, financial stressors, basal and reactive salivary cortisol secretion, and the number of oral cariogenic bacteria. We hypothesized that family stressors and stress-related changes in oral biology might explain, fully or in part, the known socioeconomic disparities in dental health. We found that nearly half of the five-year-old children studied had dental caries. Low SES, higher basal salivary cortisol secretion, and larger numbers of cariogenic bacteria were each significantly and independently associated with caries, and higher salivary cortisol reactivity was associated with thinner, softer enamel surfaces in exfoliated teeth. The highest rates of dental pathology were found among children with the combination of elevated salivary cortisol expression and high counts of cariogenic bacteria. The socioeconomic partitioning of childhood dental caries may thus involve social and psychobiological pathways through which lower SES is associated with higher numbers of cariogenic bacteria and higher levels of stress-associated salivary cortisol. This convergence of psychosocial, infectious and stress-related biological processes appears to be implicated in the production of greater cariogenic bacterial growth and in the conferral of an increased physical vulnerability of the developing dentition.
Keywords: Dental caries, socioeconomic status, stress, vulnerability, USA, children, psychobiological
Dental caries is a preventable infectious disease in which bacterial fermentation of dietary carbohydrates in plaque reduces organic acids that erode the mineralized tissue of teeth (Selwitz, Ismail, & Pitts, 2007). Caries constitutes the single most common chronic disease of childhood, affecting as many as 40-50% of U.S. and British children (Pitts, Boyles, Nugent, Thomas, & Pine, 2004, 2007) and 60-90% of children worldwide between the ages of 2 and 11 years (Centers for Disease Control and Prevention, 2006; Donahue, Waddell, Plough, Del Aguila, & Garland, 2005; Edelstein, 2006). The disease accrues an annual U.S. treatment cost of at least $4.5 billion (Aligne, Moss, Auinger, & Weitzman, 2003) and, if fully treated within the developing world, would cost between US$1600-3500 per 1000 children, a figure easily exceeding the total available public health budgets in resource-poor countries (Yee & Sheiham, 2002). Childhood caries has been linked to slowed somatic growth (Nicolau, Marcenes, Allison, & Sheiham, 2005) and diminished quality of life (World Health Organization, 2003), to a variety of acute and chronic medical conditions (Loesche, 2007), and, through inflammatory mediators, to the development of cardiovascular disease, the leading cause of adult mortality (Ford, Yamazaki, & Seymour, 2007; Joshipura, Pitiphat, Hung, Willett, Colditz, & Douglass, 2006). Such evidence for longer term developmental, psychological and medical sequelae of childhood caries is also consistent with emerging findings that chronic adult diseases are often traceable to the conditions and exposures of early life (Barker, 1990; Kuh & Ben-Shlomo, 2004; Shonkoff, Boyce, & McEwen, 2009).
Socioeconomic and racial disparities occur in the incidence and severity of childhood dental caries in virtually every country of the world (Centers for Disease Control and Prevention, 2006; Edelstein, 2006; Hobdell, Oliveira, Bautista, Myburgh, Lalloo, Narendran et al., 2003). The disproportionate rates of caries found among poor and minority children affect both concurrent and future oral health, with trajectories of early caries tracking into adult life (Broadbent, Thomson, & Poulton, 2008). Nearly twice the proportion of U.S. children with family incomes less than the federal poverty level (FPL) show decay of the primary or permanent dentition (55%), compared to those whose family incomes are greater than 200% of the FPL (31%). Approximately one quarter of U.S. children sustain 80% of the tooth decay found within the childhood population at large (Kaste, Selwitz, Oldakowski, Brunelle, Winn, & Brown, 1996). Identifying factors that contribute to social and racial disparities in childhood dental caries could thus affect global health care costs, aid in addressing more general societal inequalities in health and disease, and shed new light on the etiologies of chronic psychological and biomedical disorders in adult life.
A recently issued report by the WHO Commission on the Social Determinants of Health marshals evidence for worldwide socioeconomic and racial disparities in physical and mental disease and calls for the closure of societal gaps in health, especially child health, within a generation's time (Commission on Social Determinants of Health, 2008; Irwin, Siddiqi, & Hertzman, 2007). With recognition of the global pandemic of childhood dental caries (e.g., Edelstein, 2006; Petersen, 2005), causal mechanisms by which socioeconomic status (SES) is linked to dental health have been the focus of new interest and study. Earlier acquisition of oral cariogenic bacteria (Angulo, Pivel, Zinemanas, Jorysz, & Krasse, 1994), greater intake of dietary carbohydrates (Touger-Decker & van Loveren, 2003), exposures to environmental toxins, such as lead (Moss, Lanphear, & Auinger, 1999) and tobacco smoke (Aligne et al., 2003), differences in enamel calcification (Seow, 1998), lack of fluoridated water (Centers for Disease Control and Prevention, 2002), and inaccessibility of dental health care (Seale & Casamassimo, 2003) have all been explored as possible sources of the excessive caries incidence found among low income children.
Despite such evidence for multiple causal pathways in the social partitioning of childhood caries, a widespread assumption is that low SES and minority group parents, preoccupied with the exigencies of disadvantaged lives, are less attentive to the dental hygiene of their children (see, for example, Skeie, Riordan, Klock, & Espelid, 2006) and that disparities in dental health are principally attributable to parental neglect of hygienic practices. There is limited evidence, however, that parental inattention to dental hygiene plays a causal role in oral health inequalities (Milgrom, Riedy, Weinstein, Tanner, Manibusan, & Bruss, 2000). Further, stressors and adversities—factors that could also contribute to dental health through activation of stress-responsive, immune-regulatory neuroendocrine systems—are also disproportionately present in the lives of low income families (Evans, Gonnella, Marcynyszyn, Gentile, & Salpekar, 2005; Lupien, King, Meaney, & McEwen, 2000). While there is agreement that social, economic and environmental factors are key determinants of dental disease, there has been little study of the psychosocial and biological pathways through which socially partitioned adversities might undermine oral health during the childhood years (Newton & Bower, 2005). The studies reported here, in two samples of five-year-old, kindergarten children, examined the possible convergence of psychosocial, infectious and stress-associated biological processes—i.e., family financial stressors, the number of oral cariogenic bacteria, hypothalamic-pituitary-adrenocortical (HPA) axis activation, and the physical vulnerability of deciduous teeth—that could act as mechanisms linking SES and dental caries. The Committee for the Protection of Human Subjects at the University of California, Berkeley and the Committee on Human Research at the University of California, San Francisco reviewed and approved the recruitment plan and measurement procedures for both studies reported here.
Sample and Methods
Kindergarten children participating in a longitudinal study of social status, biological responses to adversity, and child health and development (the Peers and Wellness Study (PAWS); N = 338, in three successive cohorts (2003 – 2005), approximately equal in size) were enrolled in a dental health sub-study. The sub-sample, recruited during the 2004 – 2005 school year from the 98 children in the second cohort, comprised 94 children (96%) who ranged in age from 5.2 to 6.5 years (37 girls, 57 boys; 40 white, 48 non-white, 6 mixed), attended seven classrooms in three East San Francisco Bay Area, California public schools, and were not absent from school on the day that Study 1 procedures took place (see sub-study flow chart, Figure 1). The subsample did not differ from the larger, longitudinal study sample on socioeconomic status (F = .37, p = NS). Fifty-three children (56%) attended a morning class from 8:30 AM – 12:00 noon, and 41 (44%) attended an afternoon class from 12:00 noon – 3:30 PM. Because measurement of salivary cortisol was a component of the study protocol, children taking medications such as human growth hormone and exogenous glucocorticoids were excluded from the sample.
Figure 1
Figure 1
Flow diagram of study participation—Studies 1 and 2 (Ns = 94 and 38)
Socioeconomic Status (SES)
SES was indexed using parent-reported highest household education level (1 = some grade school; 2 = completed grade school; 3 = some high school; 4 = completed high school; 5 = some college or 2-year degree; 6 = 4-year college graduate; 7 = some graduate or professional school; 8 = graduate or professional degree).
Family Financial Stressors
Financial stress was assessed with four parent-report items derived from Essex et al. (Essex, Klein, Cho, & Kalin, 2002) that measured, on a 1-5 scale, parents’ concerns about money problems, difficulty paying bills, lack of discretionary income, and limited opportunities due to financial constraints (α = .81).
Basal Salivary Cortisol Secretion
For both morning and afternoon students, saliva for cortisol assays was collected in school two times per day, in the first and last 20 minutes of class, at the same time on each of three consecutive school days. Children had not ingested solids or liquids in the 30 minutes prior to saliva collections. Salivary cortisol levels closely correspond to plasma free cortisol and are reliable across sampling days (Kirschbaum & Hellhammer, 1994). Samples were collected using cotton rolls that children chewed for 20-30 seconds and then deposited into salivette tubes (Sarstedt, Nümbrecht, Germany) that were frozen at -7° C until shipped to the University of Dresden. After thawing, samples were mixed and centrifuged 10 min at 2000 – 3000 × g to remove particulate material. Cortisol was assayed using a commercial immunoassay with chemiluminescence detection (Cortisol Luminescence Immunoassay; IBL-Hamburg, Hamburg, Germany) for which the detection limit was 0.41 nmol/L. The mean interassay and intra-assay variations were 8.5% and 6.1%, respectively. To normalize cortisol distributions, raw values were log10-transformed. The mean cortisol values and collection times were computed across the six collections, and the area under the curve with respect to ground was calculated using the method described by Pruessner et al (Pruessner, Kirschbaum, Meinlschmid, & Hellhammer, 2003). Finally, the area under the curve was adjusted for class time to control for the circadian patterning of cortisol secretion. The resulting variable indexed children's mean basal level of HPA activation during class time, averaged over three school days.
Salivary Cortisol Reactivity
During a week different from that in which basal cortisol samples were collected, children's HPA reactivity to standardized challenges was assessed in a quiet, secluded room in the child's school, using a previously described stress reactivity protocol for middle childhood (Alkon, Goldstein, Smider, Essex, Kupfer, & Boyce, 2003). Children completed four standardized social, cognitive, sensory and emotional challenges, and at the beginning and end of the reactivity protocol, saliva was collected for cortisol assays, using the same methods described above for basal cortisol secretion. Standardized residual reactivity scores were computed by regressing post-protocol cortisol values on pre-protocol, baseline values.
Cariogenic Bacteria
Oral cariogenic bacteria were sampled using a cotton-tipped applicator swabbed over the buccal mucosa, gingival margin, tongue and tooth surfaces. The tip was then placed in a sterile tube containing 2 mL of phosphate buffered saline (PBS). Samples were stored on ice, transferred to the laboratory, and within 24 hours of collection were processed for microbiological assays. Bacteria were suspended in the PBS by vortexing for 1 minute, followed by serial dilutions of 1:10, 1:100 and 1:1000 with PBS. The diluted samples were plated (0.1 mL per plate) on Mitis Salivarius Sucrose Bacitricin agar for mutans streptococci (MS) and on Tomato Juice-Rogosa agar for lactobacillus species (LB). Plates were incubated anaerobically in 85% N2, 10% H2, & 5% CO2 at 37°C for 72 hours. The lower limit of detection for MS and LB is 10 CFU/ml (logMS=1.0). Bacteria were counted on plates appropriately diluted to show defined colonies. The sum of log10-transformed counts of MS and LB was computed as the number of oral cariogenic bacteria.
Dental Caries
A pediatric dentist, blind to other study data, completed detailed, school-based dental examinations, in well-lighted conditions, with the child in a supine position. Visual and tactile examination using a dental mirror and explorer produced counts of decayed, missing and filled dental surfaces of the primary (dmfs) and secondary teeth (DMFS), identified according to WHO criteria (Petersen, Bourgeois, Bratthall, & Ogawa, 2005). Although assessing the reliability of caries detection was not feasible within the context of the current study, other work indicates that the presence of caries is detected and rated with a between-observers reliability of 0.60-0.80 (see e.g., Ismail, Sohn, Tellez, Amaya, Sen, Hasson, et al., 2007). For the purposes of this report, ∑DMFS is used to refer to the sum of dmfs and DMFS counts.
Statistics
Four of the five independent variables (SES, Family Financial Stressors, Basal Salivary Cortisol, Salivary Cortisol Reactivity, and Cariogenic Bacteria) had missing values, ranging in proportion from 1-12%, which were imputed using linear regression within the Stata/MP 11 single imputation procedure (StataCorp). Distributions of independent and dependent (Dental Caries) measures were examined, and Pearson correlation coefficients were computed to assess univariate associations. Predictor and outcome distributions violated the normality assumptions of ordinary least-squares (OLS) regression, and, though the outcome was a count variable with non-negative, integer values, its distribution also violated assumptions of regular Poisson regression, due to the overdispersion of its values and the failure of its mean to approximate the variance. Due to such overdispersion and the large number of zeroes contained in the outcome distribution, zero-inflated Poisson (ZIP) regression (StataCorp) was used to estimate the direct and interactive associations of predictor variables with ∑DMFS (Gardner, Mulvey, & Shaw, 1995), with each predictor centered at its mean. The Vuong statistic was used to confirm that the fit of the ZIP regression model significantly exceeded that of the Poisson model. ZIP regression accurately models the multivariate predictors of a dependent measure with a high rate of zero values by apportioning outcome variance to two component distributions: a Poisson model that computes its count dimension; and a logistic model that computes the “zero, not zero” aspect of the outcome (Atkins & Gallop, 2007). Where a significant interaction was found, the moderator effect was probed using scatter plots of ∑DMFS by one interaction component variable (e.g., Cariogenic Bacteria), with data points divided at the 75th percentile into low and high sub-samples on the second component variable (e.g., the bottom 75% and top 25% on Basal Salivary Cortisol Secretion).
In this relatively well-educated East Bay Area sample, the mean of the highest household education level approached ‘some graduate or professional school’, with a range of ‘some grade school’ to ‘graduate or professional degree’ (mean = 6.7, SD = 1.4, range 1-8). Four percent of parents had only a high school education or less, 17% had some college or a two-year degree, 22% were college graduates, and 57% had at least some professional or graduate education beyond college. Despite relatively high education levels on average, nearly 16% of study households had incomes less the federal poverty level for a family of four. Family Financial Stressors were rated an average of 2.4 on the 1-5 point scale (5 corresponding to the highest level of stress), with mean scores ranging from 1 to 5. The mean raw, pre- and post-school salivary cortisol levels were 7.9 nmol/L (SD = 4.4; range = 2.4 - 25) and 4.7 nmol/L (SD = 4.8; range = 1.0 - 40.1 ), respectively. The mean pre- and post-stress reactivity protocol cortisol levels were 5.0 nmol/L (SD = 4.6; range = 1.2 - 36.0) and 4.3 nmol/L (SD = 3.3; range = 1.1 - 26.8). Approximately one third of children (34%) showed an increase in salivary cortisol over the course of the reactivity protocol. Oral MS counts averaged 50,964 CFU/mL and ranged from none to 2,500,000 CFU/mL. Oral LB averaged 7,372 CFU/mL, with a range of none to 70,000 CFU/mL. No oral Cariogenic Bacteria of either species were found in a subset of 42 children (45%). As shown in Figure 1, the 94 study children had a positively skewed distribution of ∑DMFS, with a mean of 4.3 surfaces with lesions (SD = 7.7; range = 0-38). Forty-four children (47%) had at least one caries lesion, while 50 (53%) had none. All reported analyses were also run using a count of decayed, missing and filled teeth (i.e., ΣDMFT), rather than dental surfaces. Resulting associations were comparable in direction and magnitude, but the stronger predictions were derived from the ΣDMFS analyses. Only the latter results are thus presented here.
Table 1 displays Pearson correlation coefficients among independent and dependent variables. SES was significantly and inversely associated with Family Financial Stressors, Basal Salivary Cortisol Secretion, Cariogenic Bacteria, and Dental Caries. Basal Salivary Cortisol Secretion was positively associated with Family Financial Stressors and Dental Caries, and Cariogenic Bacteria was strongly linked to Dental Caries. Because Salivary Cortisol Reactivity was unrelated to Dental Caries in the Study 1 sub-sample, this variable was omitted from further analysis.
Table 1
Table 1
Bivariate Associations Among Independent Variables (1-5) and Dental Caries (6)—Study 1 (Pearson Correlation Coefficients, N = 94 children)
SES, Family Financial Stressors, Basal Salivary Cortisol Secretion, and Cariogenic Bacteria were sequentially entered as predictors of ∑DMFS counts in the Poisson component of the computed ZIP regression models (Table 2). Basal Salivary Cortisol and Cariogenic Bacteria were the strongest bivariate predictors of Dental Caries, and from a theoretical perspective, salivary cortisol could plausibly suppress mucosal immunity against cariogenic bacteria. In light of these considerations, an interaction term for these two predictor variables was entered as a final step in the computed Poisson model. In addition, because those children with no oral pathogens accounted substantially for the large numbers of zeroes among ∑DMFS scores, Cariogenic Bacteria counts were used to predict the presence or absence of ∑DMFS in the models’ logistic component. In the step at which each variable entered the model, SES, Basal Salivary Cortisol Secretion and Cariogenic Bacteria bore strong, independent associations with counts of Dental Caries. The coefficient for SES was -0.16, corresponding to an exponentiated odds ratio of .85 or a 15% decrease in the number of caries for every one unit increase in SES. Similarly, the coefficients for Basal Salivary Cortisol Secretion and Cariogenic Bacteria were 0.19 and 0.12, corresponding to odds ratios of 1.21 and 1.13 or 21% and 13% increases in caries for each one log10 unit increase in cortisol secretion and counts of oral bacteria. Further, the coefficient for SES diminished by half when Cariogenic Bacteria was added to Model 4, indicating that the SES - Dental Caries association was partially mediated by the number of Cariogenic Bacteria.
Table 2
Table 2
Zero-Inflated Poisson Regression Models Predicting ΣDMFS—Study 1 (N = 94 children)
The interaction of Basal Salivary Cortisol x Cariogenic Bacteria was also a significant predictor of ∑DMFS scores. This interaction was inspected using a scatterplot of the two component variables predicting ∑DMFS (Figure 2). The highest number of Dental Caries was identified among children with the combination of high Basal Salivary Cortisol Secretion and high Cariogenic Bacteria counts, and the coefficient for the interaction was 0.23, corresponding to an odds ratio of 1.26. The ZIP logistic regression component revealed, at each model level, significant effects of Cariogenic Bacteria on the presence or absence of Dental Caries. To examine the possibility that the prior exfoliation of primary teeth could have biased ∑DMFS scores and confounded the identified associations, regression analyses were repeated using counts of only decayed or filled (but not missing) dental surfaces (DFS) as the dependent variable; coefficients for both the Poisson and logistic portions of these models were virtually unchanged from those derived for ∑DMFS scores. In addition, the Vuong statistic for the final model was significant, indicating that the zero-inflated model fit the observed data better than an ordinary Poisson regression (z = 3.74 - 5.41, p < .001).
Figure 2
Figure 2
Interaction of Basal Salivary Cortisol Secretion and Cariogenic Bacteria Predicting ∑DMFS— Study 1 (N = 94 children)
Multivariate regression models thus indicated that: a) lower SES, higher Basal Salivary Cortisol Secretion, and higher counts of Cariogenic Bacteria predicted the number of caries lesions; b) children with the highest number of Dental Caries were those with the combination of high Salivary Cortisol Secretion, high Cariogenic Bacteria, low SES and high Family Financial Stressors; and c) counts of Cariogenic Bacteria were a significant predictor of the binary presence or absence of Caries.
Study 2: Salivary cortisol and the dental microanatomy of exfoliated teeth
Sample and Methods
To examine associations among salivary cortisol and the thickness and density of dental tissue compartments, a second sub-sample of children was recruited during their first grade year, from 2004 - 2006. This sub-sample comprised 38 children ranging in age from 5.9 to 6.8 years (17 girls and 21 boys), recruited from all three PAWS cohorts, and consisting of children who lost a tooth during the 9 months of the first grade academic year and from whom we were able to collect the tooth for analysis (see sub-study flow chart, Figure 1). Again the subsample did not differ from the larger, longitudinal study sample on socioeconomic status (F = .91, p = NS). During their kindergarten year, when basal and reactive cortisol levels were assessed, 18 children (47%) had attended a morning class and 20 (53%) an afternoon class. Children taking medications that could result in erroneous measures of salivary cortisol were excluded from the sample.
Independent Variables
SES, Family Financial Stressors, Basal Salivary Cortisol Secretion, and Salivary Cortisol Reactivity were measured using the methods described for Study 1.
Dental Compartment Thickness and Density
Exfoliated primary mandibular incisors were collected from the children. Parents/guardians were instructed to call the project coordinator for tooth collection immediately after the tooth fell out. The teeth were then transferred to sterile water with 0.1% thymol, sterilized by overnight gamma radiation, and stored at 4°C.
A single investigator (YJ), blind to other study data, measured the thickness and density of the enamel and dentin compartments by scanning with a microtomography (μCT) scanner (Scanco Medical AG, Bassersdorf, Switzerland). A small x-ray tube with a micro focal spot was used as a source, and the detector consisted of a linear CCD-array. A scout view scan was obtained first, followed by automatic positioning, measurement, and offline reconstruction (see Jiang, Zhao, Mitlak, Wang, Genant, & Eriksen, 2003). Images with isotropic resolution of 21 μm were obtained with 70 KVp and 85 μA. For subsequent image analyses, a subset of the original μCT section, containing entirely enamel and readily distinguished from dentin by obvious differences in mineral density, was selected. Enamel data were thresholded into binary data sets, and enamel tissue was segmented from non-enamel in gray-scale images with a fixed thresholding procedure. Boundaries between enamel and dentin and between dentin and pulp cavity were manually traced to measure the thickness and density of the two layers.
Statistics
Preliminary analyses duplicated those of Study 1. OLS regression was used to estimate the direct and interactive associations of independent variables with dental compartment measures. Each predictor variable was centered at its mean, and where a significant interaction was found, the moderator effect was probed using scatter plots as in Study 1.
In the Study 2 sub-sample, the mean of the highest household education level and the standardized Family Financial Stressors score were closely comparable to those of Study 1. The mean raw, pre- and post-school salivary cortisol levels were 9.3 nmol/L (SD = 4.9; range = 3.2 - 25) and 4.9 nmol/L (SD = 3.3; range = 2.4 - 22.6), respectively. The mean pre- and post-stress reactivity protocol cortisol levels were 5.3 nmol/L (SD = 2.6; range 1.7 - 15.7) and 4.2 nmol/L (SD = 2.1; range = 1.5 - 11.3). Again, approximately one third of children (37%) showed an increase in salivary cortisol during the reactivity protocol. The thickness and density of the enamel and dentin layers were normally distributed, with a mean Enamel Thickness of 0.25 mm (SD = 0.04; range 0.15 – 0.33) and a mean Enamel Density of 1,894 mg hydroxyapatite/cm3 (SD = 39.5; range = 1,796 - 1,961). Dentin Thickness and Density had means of 1.05 mm (SD = 0.14; range = 0.80 - 1.44) and 1,090 mg hydroxyapatite/cm3 (SD = 25.7; range = 1,032 - 1,137), respectively. Compartment thicknesses were comparable to but slightly lower than those previously observed using standard radiography (Hall, Lindauer, Tufekci, & Shroff, 2007), differences possibly attributable to variation in measurement technique and tooth selection. Eighteen of the 38 children provided a second exfoliated primary tooth, allowing an examination of the between-teeth reliability of the microtomographic measures in this subset. The intraclass correlation coefficients between tooth 1 and tooth 2, for measures of compartment thickness and density, ranged from .63 to .97 (all p ≤ .001), indicating a high level of measurement reliability.
Table 3 displays correlation coefficients among independent and dependent variables. SES was significantly and inversely associated with Basal Salivary Cortisol Secretion, indicating that children from more highly educated families had lower levels of tonic HPA activation. Basal Salivary Cortisol Secretion was unrelated, however, to any Dental Compartment measure. Unexpectedly, SES was also inversely and significantly associated with Enamel Thickness and Enamel Density, suggesting that children from lower SES families had thicker and less vulnerable dental enamel. Because prior observations have suggested that individuals of African ancestry have phenotypically thicker dental enamel (Hall, et al., 2007; Harris, Hicks, & Barcroft, 2001), this unanticipated finding was explored by jointly examining the child's ethnicity (African-American v other) and SES in relation to Enamel Thickness. Analysis of variance showed that African-American children had significantly greater Enamel Thickness (0.27 mm v 0.24 mm, F = 3.97, p < .05) and that, after adjustment for ethnicity, the significant association with SES disappeared. Finally and as shown in Figure 3 for Enamel Thickness and Density, Salivary Cortisol Reactivity was inversely and significantly or borderline significantly associated with three of the four Dental Compartment measures. Because Basal Salivary Cortisol Secretion was unrelated to outcomes and its associations with Dentin measures were generally smaller in magnitude, these variables were omitted from further analysis.
Table 3
Table 3
Bivariate Associations Among Independent Variables (1-4) and Dental Compartment Thickness and Density (5-8)—Study 2 (Pearson Correlation Coefficients, N = 38 children)
Figure 3
Figure 3
Enamel Thickness and Density by Salivary Cortisol Reactivity— Study 2 (N = 38 children)
OLS linear regression models were next sequentially computed to assess SES, Family Financial Stressors, and Salivary Cortisol Reactivity as predictors of Enamel Thickness and Density (Table 4). Because SES and Salivary Cortisol Reactivity had the strongest bivariate associations with Enamel Thickness and Density, a SES × Salivary Cortisol Reactivity interaction term was entered in the final regression model. Within the series of regression models, SES and Salivary Cortisol Reactivity again bore strong, independent associations with Enamel Thickness and Density. In Model 4, with the entry of the interaction term, the relation of SES to Enamel Thickness and Density substantially diminished, suggesting that SES effects were partially mediated by the significant interaction between SES and Salivary Cortisol Reactivity. As shown in Figure 4, higher SES children showed little difference in Enamel Thickness by Salivary Cortisol Reactivity, while among low SES children, lower Salivary Cortisol Reactivity was associated with higher Enamel Thickness.
Table 4
Table 4
Linear Regression Models Predicting Dental Compartment Thickness and Density—Study 2 (N = 38 children)
Figure 4
Figure 4
Interaction of SES and Salivary Cortisol Reactivity Predicting Enamel Thickness— Study 2 (N = 38 children)
Study 2 multivariate analyses thus indicated that: a) lower SES was associated with higher Enamel Thickness and Density, an unexpected association possibly related to differences in enamel structure among low SES, African-American children; b) higher Salivary Cortisol Reactivity was associated with lower Enamel Thickness and Density; and c) the children with the highest Enamel Thickness were those with the combination of low SES and low Cortisol Reactivity.
General Discussion
The studies reported here yielded five principal findings: a) approximately half of the children had developed dental caries by five years of age; b) low family SES was associated with financial stress, basal activation of the child's hypothalamic-pituitary-adrenocortical (HPA) axis, and higher counts of oral cariogenic bacteria; c) cariogenic bacteria and salivary cortisol secretion were both independently associated with the presence of caries; d) the highest risk of dental caries was among children with high levels of both salivary cortisol and cariogenic bacteria; and e) cortisol reactivity to stress was associated with thinner, softer, and thus more vulnerable enamel surfaces. Low SES was also associated with thicker and more dense dental enamel, especially among those with low cortisol reactivity, a finding perhaps accounted for, fully or in part, by structural differences in enamel among African-American children.
Taken together, these findings advance a conceptual model of social and psychobiological influences on caries incidence with two biologically plausible and distinct but interactive pathways (see Figure 5). First, children from lower SES families acquired cariogenic oral bacteria at levels significantly higher than their higher SES peers. Counts of oral mutans streptococci (MS) and Lactobacillus species (LB) were strongly linked to SES and substantially mediated the SES-caries association. Second, higher levels of basal salivary cortisol secretion and cortisol reactivity to stress may compromise dental health by undermining protective, local defenses and microanatomical structures. Exaggerated basal HPA activation was associated with risk to the dentition through interactions with the presence of cariogenic bacteria, and cortisol reactivity was linked to risk through changes in the physical properties of dental enamel. Importantly, the strongest risk factor for development of dental caries was the joint presence of heightened expression of salivary cortisol and high levels of cariogenic bacteria. To our knowledge, these are the first studies to implicate conjoint, interactive roles of oral bacteria and salivary cortisol in the pathogenesis of childhood dental caries.
Figure 5
Figure 5
Conceptual Model of the Social Partitioning of Childhood Dental Caries
Both cariogenic pathways are consistent with a number of prior observations. First, low SES has been identified as a risk factor for early colonization with cariogenic bacteria (e.g., Li, Caufield, Dasanayake, Wiener, & Vermund, 2005), and transmission within the first year of life is associated with the development of caries in early childhood (Alaluusua & Renkonen, 1983). Such transmission may be either vertical, between mother and child (Lapirattanakul, Nakano, Nomura, Hamada, Nakagawa, & Ooshima, 2008), or horizontal, among peers and playmates (Doméjean-Orliaguet, et al., In press, 2010). Further, mediation of the SES-caries association by cariogenic bacteria counts is concordant with reports that MS and LB are necessary pathogenic elements in the production of caries and that mucosal vaccines against oral pathogens are capable of caries prevention (Smith, 2003). An innate salivary defense against colonization utilizes mechanical rinsing, buffering, antimicrobial peptides, and bacterial aggregation and clearance (Tao, Jurevic, Coulton, Tsutsui, Roberts, Kimball et al., 2005). The first line of defense, however, is immunologic (Walker, 2004). Production of secretory immunoglobulin A (sIgA) in saliva begins by one month of age (Smith, 2003), and the capacity of sIgA antibody to recognize specific bacterial antigens plays a critical role in the modulation and control of infection with cariogenic organisms (Nogueira, Alves, Napimoga, Smith, & Mattos-Graner, 2005).
The second possible pathway, by which SES was associated with family financial stressors, cortisol secretion, and physical properties of the dental enamel, is similarly consistent with other reports. Low family SES has been linked to a higher burden of acute and chronic adversities of all types, not least financial stressors (Duncan & Brooks-Gunn, 2000; Evans & Schamberg, 2009), and children from low SES families show evidence of heightened HPA activation and reactivity (Cohen, Doyle, & Baum, 2006; Kristenson, Eriksen, Sluiter, Starke, & Ursin, 2004; Lupien et al., 2000). Greater exposure to stressors has also been associated with acceleration in dental disease in rats (Gaspersic, Stiblar-Martincic, & Skaleric, 2002) and with lowered host resistance to periodontitis-related bacteria in humans (Klages, Weber, & Wehrbein, 2005). Although no prior work has examined salivary cortisol secretion and the physical properties of teeth, enamel hypoplasia is known to augment dental caries susceptibility (Hong, Levy, Warren, & Broffitt, 2009), and exposures to therapeutic corticosteroids can induce hypoplasia (Bublitz, Machat, Scharer, Komposch, & Mehls, 1981) and narrow the dental pulp chamber by effecting new dentin formation (Nasstrom, Odselius, & Petersson, 1996).
Finally, the previously unrecognized interaction of cortisol and bacteria in the prediction of caries risk is consistent with prior findings that acute and chronic stressors can impair sIgA production (Deinzer, Kleineidam, Stiller-Winkler, Idel, & Bachg, 2000; Phillips, Carroll, Evans, Bosch, Clow, Hucklebridge et al., 2006), that cortisol is capable of affecting local, mucosal immunity and oral microbial flora (Genco, Ho, Kopman, Grossi, Dunford, & Tedesco, 1998), and that mucosal immune competence affects bacterial colonization and growth (Kamma, Lygidakis, & Nakou, 1998; Nogueira et al., 2005). Secretory IgA plays an important role in regulation of oral microbial ecology (Teeuw, Bosch, Veerman, & Amerongen, 2004), and glucocorticoids can exert immunosuppressive effects through mechanisms such as reductions in circulating lymphocytes, inhibition of immune cell aggregation, down-regulation of chemotaxis and degranulation, and diminution in cytokine production, including IL-1, IL-2, tumor necrosis factor, and interferon gamma (Genco et al., 1998). Collectively, these previous reports undergird our conclusion that the socioeconomic partitioning of childhood dental caries involves the convergent, stress-related processes of increased cortisol secretion and the proliferation of cariogenic bacteria.
Several methodological and design limitations of these studies should be taken into account in weighing the presented findings. First, the study samples, though socioeconomically representative of the larger study from which they were drawn and, more generally, of the East San Francisco Bay Area population, were on average highly educated by national standards; such overrepresentation of high SES families would arguably have operated as a conservative bias, obscuring or diminishing associations between SES and measures of oral health. Second, cross-sectional in design, the studies were incapable, in principle, of establishing causally informative associations. The two-pathway model advanced here, linking SES and caries, should be therefore regarded as a conceptual synthesis of reported findings, rather than as a causal model of caries pathogenesis. Third, several known or suspected oral health risk factors, such as the developmental timing of cariogenic bacteria acquisition, the level of dietary carbohydrates, lead and tobacco smoke exposure, and parental attentiveness to children's dental hygiene were unmeasured in this study. Although the fluoridation of drinking water was also not evaluated, optimal fluoride levels for the East Bay Area are monitored and maintained by the California Department of Public Health. Fourth, although conjectures have been made regarding the possible immunological mediation of the cortisol x bacteria interaction, no immune parameters were measured, and thus no direct test of immune mediation was possible. Finally, the studies employed unselected sub-samples of children from a larger, longitudinal research project, and while the sub-samples did not differ in SES from the larger study sample, they could be unrepresentative in terms of other, unmeasured parameters.
These limitations not withstanding, our analyses yielded substantive, coherent relations between social and psychobiological factors and dental outcomes. They suggest that socioeconomic disparities in stressful experience and HPA activation may contribute to the social partitioning of dental caries through two distinctive pathways: a) a low SES-linked predisposition to larger acquisitions of oral cariogenic bacteria, augmented by higher basal cortisol secretion that could accelerate local bacterial growth and virulence, and b) glucocorticoid effects on mineralized dental tissues, creating physical vulnerabilities to cariogenic bacteria. Such pathways offer a new, heuristic, and biologically plausible account for how early social conditions may interact with systemic and local biological processes to determine short- and long-term disparities in childhood dental health, disparities that may ultimately and critically affect the chronic, more general morbidities of adult life.
Acknowledgements
This research was supported by grant awards R01 MH62320 and R01 MH62320-S1 from the National Institute of Mental Health. Dr. Boyce holds the Sunny Hill Health Centre-BC Leadership Chair in Child Development. His work is also supported by the MacArthur Foundation Research Network on Psychopathology and Development and by the Canadian Institute for Advanced Research. The authors are grateful to Drs. Barry Forer, Bruno Zumbo, and Jelena Obradović for their assistance with this manuscript.
Footnotes
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Contributor Information
Pamela K Den Besten, University of California, San Francisco.
Juliet Stamperdahl, University of California, Berkeley.
Ling Zhan, University of California, San Francisco.
Yebin Jiang, University of Michigan.
Nancy E Adler, University of California, San Francisco.
John D Featherstone, University of California, San Francisco.
  • Alaluusua S, Renkonen OV. Streptococcus mutans establishment and dental caries experience in children from 2 to 4 years old. Scandinavian Journal of Dental Research. 1983;91(6):453–457. [PubMed]
  • Aligne CA, Moss ME, Auinger P, Weitzman M. Association of pediatric dental caries with passive smoking. JAMA. 2003;289(10):1258–1264. [PubMed]
  • Alkon A, Goldstein LH, Smider N, Essex M, Kupfer D, Boyce WT. Developmental and contextual influences on autonomic reactivity in young children. Developmental Psychobiology. 2003;42(1):64–78. [PubMed]
  • Angulo M, Pivel L, Zinemanas E, Jorysz E, Krasse B. Dental caries and microbial and salivary conditions in Uruguayan children from two different socioeconomic areas. Acta Odontologica Scandinavica. 1994;52(6):377–383. [PubMed]
  • Atkins DC, Gallop RJ. Rethinking how family researchers model infrequent outcomes: a tutorial on count regression and zero-inflated models. Journal of Family Psychology. 2007;21(4):726–735. [PubMed]
  • Barker DJ. The fetal and infant origins of adult disease. BMJ. 1990;301(6761):1111. [PMC free article] [PubMed]
  • Broadbent JM, Thomson WM, Poulton R. Trajectory patterns of dental caries experience in the permanent dentition to the fourth decade of life. Journal of Dental Research. 2008;87(1):69–72. [PMC free article] [PubMed]
  • Bublitz A, Machat E, Scharer K, Komposch G, Mehls O. Changes in dental development in paediatric patients with chronic kidney disease. Proceedings of the European Dialysis and Transplant Association. 1981;18:517–523. [PubMed]
  • Centers for Disease Control and Prevention Populations receiving optimally fluoridated public drinking water--United States, 2000. MMWR Morbidity and Mortality Weekly Reports. 2002;51(7):144–147. [PubMed]
  • Centers for Disease Control and Prevention Fact Sheet: Surveillance for Dental Caries, Dental Sealants, Tooth Retention, Edentulism and Enamel Fluorosis--United States, 1988-1994 and 1999-2002. 2006. [PubMed]
  • Cohen S, Doyle WJ, Baum A. Socioeconomic status is associated with stress hormones. Psychosomatic Medicine. 2006;68(3):414–420. [PubMed]
  • Commission on Social Determinants of Health Closing the gap in a generation: Health equity through action on the social determinants of health. World Health Organization; Geneva: 2008. [PubMed]
  • Deinzer R, Kleineidam C, Stiller-Winkler R, Idel H, Bachg D. Prolonged reduction of salivary immunoglobulin A (sIgA) after a major academic exam. International Journal of Psychophysiology. 2000;37(3):219–232. [PubMed]
  • Doméjean-Orliaguet S, Zhan L, Denbesten PK, Stamper J, Boyce WT, Featherstone JD. Horizontal transmission of mutans streptococci in children. Journal of Dental Research. 2009 In press. [PMC free article] [PubMed]
  • Donahue GJ, Waddell N, Plough AL, Del Aguila MA, Garland TE. The ABCDs of treating the most prevalent childhood disease. American Journal of Public Health. 2005;95(8):1322–1324. [PubMed]
  • Duncan GJ, Brooks-Gunn J. Family poverty, welfare reform, and child development. Child Development. 2000;71(1):188–196. [PubMed]
  • Edelstein BL. The dental caries pandemic and disparities problem. BMC Oral Health. 2006;6(Suppl 1):S2. [PMC free article] [PubMed]
  • Essex MJ, Klein MH, Cho E, Kalin NH. Maternal stress beginning in infancy may sensitize children to later stress exposure: Effects on cortisol and behavior. Biological Psychiatry. 2002;52:776–784. [PubMed]
  • Evans GW, Gonnella C, Marcynyszyn LA, Gentile L, Salpekar N. The role of chaos in poverty and children's socioemotional adjustment. Psychological Science. 2005;16(7):560–565. [PubMed]
  • Evans GW, Schamberg MA. Childhood poverty, chronic stress, and adult working memory. Proceedings of the National Academy of Sciences U S A. 2009 [PubMed]
  • Ford PJ, Yamazaki K, Seymour GJ. Cardiovascular and oral disease interactions: what is the evidence? Primary Dental Care. 2007;14(2):59–66. [PubMed]
  • Gardner W, Mulvey EP, Shaw EC. Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models. Psychological Bulletin. 1995;118(3):392–404. [PubMed]
  • Gaspersic R, Stiblar-Martincic D, Skaleric U. Influence of restraint stress on ligature-induced periodontitis in rats. European Journal of Oral Sciences. 2002;110(2):125–129. [PubMed]
  • Genco RJ, Ho AW, Kopman J, Grossi SG, Dunford RG, Tedesco LA. Models to evaluate the role of stress in periodontal disease. Annals of Periodontology. 1998;3(1):288–302. [PubMed]
  • Hall NE, Lindauer SJ, Tufekci E, Shroff B. Predictors of variation in mandibular incisor enamel thickness. Journal of the American Dental Association. 2007;138(6):809–815. [PubMed]
  • Harris EF, Hicks JD, Barcroft BD. Tissue contributions to sex and race: Difference in tooth crown size of deciduous molars. American Journal of Physical Anthropology. 2001;115(3):223–237. [PubMed]
  • Hobdell MH, Oliveira ER, Bautista R, Myburgh NG, Lalloo R, Narendran S, et al. Oral diseases and socio-economic status (SES). Britsh Dental Journal. 2003;194(2):91–96. discussion 88. [PubMed]
  • Hong L, Levy SM, Warren JJ, Broffitt B. Association between enamel hypoplasia and dental caries in primary second molars: a cohort study. Caries Research. 2009;43(5):345–353. [PMC free article] [PubMed]
  • Irwin LG, Siddiqi A, Hertzman C. Early Child Development: A Powerful Equalizer. World Health Organization Commission on Social Determinants of Health; Vancouver, BC: 2007.
  • Ismail AI, Sohn W, Tellez M, Amaya A, Sen A, Hasson H, et al. The International Caries Detection and Assessment System (ICDAS): an integrated system for measuring dental caries. Community Dentistry and Oral Epidemiology. 2007;35(3):170–178. [PubMed]
  • Jiang Y, Zhao JJ, Mitlak BH, Wang O, Genant HK, Eriksen EF. Recombinant human parathyroid hormone (1-34) [teriparatide] improves both cortical and cancellous bone structure. Journal of Bone and Mineral Research. 2003;18(11):1932–1941. [PubMed]
  • Joshipura KJ, Pitiphat W, Hung HC, Willett WC, Colditz GA, Douglass CW. Pulpal inflammation and incidence of coronary heart disease. J Endod. 2006;32(2):99–103. [PubMed]
  • Kamma JJ, Lygidakis NA, Nakou M. Subgingival microflora and treatment in prepubertal periodontitis associated with chronic idiopathic neutropenia. Journal of Clinical Periodontology. 1998;25(9):759–765. [PubMed]
  • Kaste LM, Selwitz RH, Oldakowski RJ, Brunelle JA, Winn DM, Brown LJ. Coronal caries in the primary and permanent dentition of children and adolescents 1-17 years of age: United States, 1988-1991. Journal of Dental Research. 1996;75:631–641. Spec No. [PubMed]
  • Kirschbaum C, Hellhammer DH. Salivary cortisol in psychoneuroendocrine research: recent developments and applications. Psychoneuroendocrinology. 1994;19(4):313–333. [PubMed]
  • Klages U, Weber AG, Wehrbein H. Approximal plaque and gingival sulcus bleeding in routine dental care patients: relations to life stress, somatization and depression. Journal of Clinical Periodontology. 2005;32(6):575–582. [PubMed]
  • Kristenson M, Eriksen HR, Sluiter JK, Starke D, Ursin H. Psychobiological mechanisms of socioeconomic differences in health. Social Science and Medicine. 2004;58(8):1511–1522. [PubMed]
  • Kuh D, Ben-Shlomo Y. A Life Course Approach to Chronic Disease Epidemiology. Oxford University Press; Oxford: 2004. [PubMed]
  • Lapirattanakul J, Nakano K, Nomura R, Hamada S, Nakagawa I, Ooshima T. Demonstration of mother-to-child transmission of Streptococcus mutans using multilocus sequence typing. Caries Research. 2008;42(6):466–474. [PubMed]
  • Li Y, Caufield PW, Dasanayake AP, Wiener HW, Vermund SH. Mode of delivery and other maternal factors influence the acquisition of Streptococcus mutans in infants. Journal of Dental Research. 2005;84(9):806–811. [PubMed]
  • Loesche W. Dental caries and periodontitis: contrasting two infections that have medical implications. Infectious Disease Clinics of North America. 2007;21(2):471–502. vii. [PubMed]
  • Lupien SJ, King S, Meaney MJ, McEwen BS. Child's stress hormone levels correlate with mother's socioeconomic status and depressive state. Biological Psychiatry. 2000;48(10):976–980. [PubMed]
  • Milgrom P, Riedy CA, Weinstein P, Tanner AC, Manibusan L, Bruss J. Dental caries and its relationship to bacterial infection, hypoplasia, diet, and oral hygiene in 6- to 36-month-old children. Community Dentistry and Oral Epidemiology. 2000;28(4):295–306. [PubMed]
  • Moss ME, Lanphear BP, Auinger P. Association of dental caries and blood lead levels. Jama. 1999;281(24):2294–2298. [PubMed]
  • Nasstrom K, Odselius R, Petersson A. Energy dispersive X-ray microanalysis of the dentin in rat molars after corticosteroid treatment. Scanning Microscopy. 1996;10(2):339–346. discussion 346-337. [PubMed]
  • Newton JT, Bower EJ. The social determinants of oral health: new approaches to conceptualizing and researching complex causal networks. Community Dentistry and Oral Epidemiology. 2005;33(1):25–34. [PubMed]
  • Nicolau B, Marcenes W, Allison P, Sheiham A. The life course approach: explaining the association between height and dental caries in Brazilian adolescents. Community Dentistry and Oral Epidemiology. 2005;33(2):93–98. [PubMed]
  • Nogueira RD, Alves AC, Napimoga MH, Smith DJ, Mattos-Graner RO. Characterization of salivary immunoglobulin A responses in children heavily exposed to the oral bacterium Streptococcus mutans: Influence of specific antigen recognition in infection. Infection & Immunity. 2005;73(9):5675–5684. [PMC free article] [PubMed]
  • Petersen PE. Sociobehavioural risk factors in dental caries - international perspectives. Community Dentistry and Oral Epidemiology. 2005;33(4):274–279. [PubMed]
  • Petersen PE, Bourgeois D, Bratthall D, Ogawa H. Oral health information systems--towards measuring progress in oral health promotion and disease prevention. Bulletin of the World Health Organization. 2005;83(9):686–693. [PubMed]
  • Phillips AC, Carroll D, Evans P, Bosch JA, Clow A, Hucklebridge F, et al. Stressful life events are associated with low secretion rates of immunoglobulin A in saliva in the middle aged and elderly. Brain Behavior and Immunity. 2006;20(2):191–197. [PubMed]
  • Pitts N, Boyles J, Nugent Z, Thomas N, Pine C. The dental caries experience of 5-year-old children in Great Britain (2005/6). Surveys co-ordinated by the British Association for the study of community dentistry. Community Dental Health. 2007;24(1):59–63. [PubMed]
  • Pruessner JC, Kirschbaum C, Meinlschmid G, Hellhammer DH. Two formulas for computation of the area under the curve represent measures of total hormone concentration versus time-dependent change. Psychoneuroendocrinology. 2003;28(7):916–931. [PubMed]
  • Seale NS, Casamassimo PS. Access to dental care for children in the United States: a survey of general practitioners. Journal of the American Dental Association. 2003;134(12):1630–1640. [PubMed]
  • Selwitz RH, Ismail AI, Pitts NB. Dental caries. Lancet. 2007;369(9555):51–59. [PubMed]
  • Seow WK. Biological mechanisms of early childhood caries. Community Dentistry and Oral Epidemiology. 1998;26(1 Suppl):8–27. [PubMed]
  • Shonkoff JP, Boyce WT, McEwen BS. Neuroscience, Molecular Biology, and the Childhood Roots of Health Disparities: Building a New Framework for Health Promotion and Disease Prevention. Jama. 2009;301(21):2252–2259. [PubMed]
  • Skeie MS, Riordan PJ, Klock KS, Espelid I. Parental risk attitudes and caries-related behaviours among immigrant and western native children in Oslo. Community Dentistry and Oral Epidemiology. 2006;34(2):103–113. [PubMed]
  • Smith DJ. Caries vaccines for the twenty-first century. Journal of Dental Education. 2003;67(10):1130–1139. [PubMed]
  • Tao R, Jurevic RJ, Coulton KK, Tsutsui MT, Roberts MC, Kimball JR, et al. Salivary antimicrobial peptide expression and dental caries experience in children. Antimicrobial Agents & Chemotherapy. 2005;49(9):3883–3888. [PMC free article] [PubMed]
  • Teeuw W, Bosch JA, Veerman ECI, Amerongen AVN. Neuroendocrine regulation of salivary IgA synthesis and secretion: Implications for oral health. Biological Chemistry. 2004;385:1137–1146. [PubMed]
  • Touger-Decker R, van Loveren C. Sugars and dental caries. American Journal of Clinical Nutrition. 2003;78(4):881S–892S. [PubMed]
  • Walker DM. Oral mucosal immunology: an overview. Annals of the Academy of Medicine Singapore. 2004;33(4 Suppl):27–30. [PubMed]
  • World Health Organization The World Oral Health Report 2003. World Health Organization; Geneva, Switzerland: 2003.
  • Yee R, Sheiham A. The burden of restorative dental treatment for children in Third World countries. International Dental Journal. 2002;52(1):1–9. [PubMed]