Socioeconomic factors in adolescents’ oral health: are they mediated by oral hygiene behaviors or preventive interventions?

Polk DE, Weyant RJ, Manz MC. Socioeconomic factors in adolescents’ oral health: are they mediated by oral hygiene behaviors or preventive interventions? Community Dent Oral Epidemiol 2010; 38: 1–9. © 2009 John Wiley & Sons A/STo determine whether there is a socioeconomic status (SES) disparity in caries experience (i.e., DMFT) in an adolescent sample from Pennsylvania and to determine whether differences in oral hygiene behaviors and preventive interventions account for this disparity.A cross-sectional clinical assessment was conducted on a representative sample of 9th grade and 11th grade students across Pennsylvania. These students also completed a brief questionnaire regarding their oral hygiene behaviors. From this group of students, a random subsample of 530 parents completed a questionnaire assessing SES, fluoride exposure, and recency of receipt of dental services. DMFT was examined at two thresholds of severity: simple prevalence (DMFT > 0) and severe caries (DMFT > 3).Using structural equation modeling, we found that lower SES was associated with higher prevalence of DMFT and higher prevalence of severe caries. Although lower SES was associated with lower rates of brushing, less use of sealants, and less recent receipt of dental services, these oral health behaviors and preventive interventions did not account for the disparities in DMFT defined by SES.There is an SES gradient in caries experience in adolescents in Pennsylvania. Disparities in caries experience, however, cannot be accounted for by SES-associated differences in brushing, flossing, sealant use, fluoride exposure, or recency of use of dental services. To facilitate the design of preventive interventions, future research should determine the pathways through which SES-associated disparities occur.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78657/1/j.1600-0528.2009.00499.x.pd

Is there an Appalachian disparity in dental caries in Pennsylvania schoolchildren?

ObjectivesTo determine whether there is an Appalachian disparity in caries prevalence or extent in children living in Pennsylvania.MethodsWe conducted a cross‐sectional clinical assessment of caries in a sample representing 1st, 3rd, 9th, and 11th grade students across Pennsylvania. We used logistic regression and zero‐inflated negative binomial regression controlling for age to examine the association of residence in an Appalachian county with caries prevalence and extent in the primary and permanent dentitions.ResultsCompared with children living outside Appalachia, more children living in Appalachia had a dft >0 (OR = 1.37, 95% CI = 1.07–1.76) and more had a DMFT >0 (OR = 1.32, 95% CI = 1.06–1.64). In addition, compared with children living outside Appalachia, children living in Appalachia had a greater primary but not permanent caries extent (IRR = 1.10, 95% CI = 1.01–1.19).ConclusionsWe found Appalachian disparities in caries prevalence in both the primary and permanent dentitions and an Appalachian disparity in caries extent in the primary dentition. None of the disparities was moderated by age. This suggests that the search for the mechanism or mechanisms for the Appalachian disparities should focus on differential exposures to risk factors occurring prior to and at the start of elementary school.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110608/1/cdoe12135.pd

Effects of Smoking and Genotype on the PSR Index of Periodontal Disease in Adults Aged 18–49

Studies have found both genetic and environmental influences on chronic periodontitis. The purpose of this study was to examine the relationships among previously identified genetic variants, smoking status, and two periodontal disease-related phenotypes (PSR1 and PSR2) in 625 Caucasian adults (aged 18–49 years). The PSR Index was used to classify participants as affected or unaffected under the PSR1 and PSR2 phenotype definitions. Using logistic regression, we found that the form of the relationship varied by single nucleotide polymorphism (SNP): For rs10457525 and rs12630931, the effects of smoking and genotype on risk were additive; whereas for rs10457526 and rs733048, smoking was not independently associated with affected status once genotype was taken into consideration. In contrast, smoking moderated the relationships of rs3870371 and rs733048 with affected status such that former and never smokers with select genotypes were at increased genetic risk. Thus, for several groups, knowledge of genotype may refine the risk prediction over that which can be determined by knowledge of smoking status alone. Future studies should replicate these findings. These findings provide the foundation for the exploration of novel pathways by which periodontitis may occur

Genome-Wide Association Study of Periodontal Health Measured by Probing Depth in Adults Ages 18−49 years

The etiology of chronic periodontitis clearly includes a heritable component. Our purpose was to perform a small exploratory genome-wide association study in adults ages 18–49 years to nominate genes associated with periodontal disease−related phenotypes for future consideration. Full-mouth periodontal pocket depth probing was performed on participants (N = 673), with affected status defined as two or more sextants with probing depths of 5.5 mm or greater. Two variations of this phenotype that differed in how missing teeth were treated were used in analysis. More than 1.2 million genetic markers across the genome were genotyped or imputed and tested for genetic association. We identified ten suggestive loci (p-value ≤ 1E-5), including genes/loci that have been previously implicated in chronic periodontitis: LAMA2, HAS2, CDH2, ESR1, and the genomic region on chromosome 14q21-22 between SOS2 and NIN. Moreover, we nominated novel loci not previously implicated in chronic periodontitis or related pathways, including the regions 3p22 near OSBPL10 (a lipid receptor implicated in hyperlipidemia), 4p15 near HSP90AB2P (a heat shock pseudogene), 11p15 near GVINP1 (a GTPase pseudogene), 14q31 near SEL1L (an intracellular transporter), and 18q12 in FHOD3 (an actin cytoskeleton regulator). Replication of these results in additional samples is needed. This is one of the first research efforts to identify genetic polymorphisms associated with chronic periodontitis-related phenotypes by the genome-wide association study approach. Though small, efforts such this are needed in order to nominate novel genes and generate new hypotheses for exploration and testing in future studies

Genome-wide association Scan of dental caries in the permanent dentition

Background: Over 90% of adults aged 20 years or older with permanent teeth have suffered from dental caries leading to pain, infection, or even tooth loss. Although caries prevalence has decreased over the past decade, there are still about 23% of dentate adults who have untreated carious lesions in the US. Dental caries is a complex disorder affected by both individual susceptibility and environmental factors. Approximately 35-55% of caries phenotypic variation in the permanent dentition is attributable to genes, though few specific caries genes have been identified. Therefore, we conducted the first genome-wide association study (GWAS) to identify genes affecting susceptibility to caries in adults. Methods: Five independent cohorts were included in this study, totaling more than 7000 participants. For each participant, dental caries was assessed and genetic markers (single nucleotide polymorphisms, SNPs) were genotyped or imputed across the entire genome. Due to the heterogeneity among the five cohorts regarding age, genotyping platform, quality of dental caries assessment, and study design, we first conducted genome-wide association (GWA) analyses on each of the five independent cohorts separately. We then performed three meta-analyses to combine results for: (i) the comparatively younger, Appalachian cohorts (N = 1483) with well-assessed caries phenotype, (ii) the comparatively older, non-Appalachian cohorts (N = 5960) with inferior caries phenotypes, and (iii) all five cohorts (N = 7443). Top ranking genetic loci within and across meta-analyses were scrutinized for biologically plausible roles on caries. Results: Different sets of genes were nominated across the three meta-analyses, especially between the younger and older age cohorts. In general, we identified several suggestive loci (P-value ≤ 10E-05) within or near genes with plausible biological roles for dental caries, including RPS6KA2 and PTK2B, involved in p38-depenedent MAPK signaling, and RHOU and FZD1, involved in the Wnt signaling cascade. Both of these pathways have been implicated in dental caries. ADMTS3 and ISL1 are involved in tooth development, and TLR2 is involved in immune response to oral pathogens. Conclusions: As the first GWAS for dental caries in adults, this study nominated several novel caries genes for future study, which may lead to better understanding of cariogenesis, and ultimately, to improved disease predictions, prevention, and/or treatment

Heritable patterns of tooth decay in the permanent dentition: principal components and factor analyses

<p>Abstract</p> <p>Background</p> <p>Dental caries is the result of a complex interplay among environmental, behavioral, and genetic factors, with distinct patterns of decay likely due to specific etiologies. Therefore, global measures of decay, such as the DMFS index, may not be optimal for identifying risk factors that manifest as specific decay patterns, especially if the risk factors such as genetic susceptibility loci have small individual effects. We used two methods to extract patterns of decay from surface-level caries data in order to generate novel phenotypes with which to explore the genetic regulation of caries.</p> <p>Methods</p> <p>The 128 tooth surfaces of the permanent dentition were scored as carious or not by intra-oral examination for 1,068 participants aged 18 to 75 years from 664 biological families. Principal components analysis (PCA) and factor analysis (FA), two methods of identifying underlying patterns without <it>a priori </it>surface classifications, were applied to our data.</p> <p>Results</p> <p>The three strongest caries patterns identified by PCA recaptured variation represented by DMFS index (correlation, r = 0.97), pit and fissure surface caries (r = 0.95), and smooth surface caries (r = 0.89). However, together, these three patterns explained only 37% of the variability in the data, indicating that <it>a priori </it>caries measures are insufficient for fully quantifying caries variation. In comparison, the first pattern identified by FA was strongly correlated with pit and fissure surface caries (r = 0.81), but other identified patterns, including a second pattern representing caries of the maxillary incisors, were not representative of any previously defined caries indices. Some patterns identified by PCA and FA were heritable (h²= 30-65%, p = 0.043-0.006), whereas other patterns were not, indicating both genetic and non-genetic etiologies of individual decay patterns.</p> <p>Conclusions</p> <p>This study demonstrates the use of decay patterns as novel phenotypes to assist in understanding the multifactorial nature of dental caries.</p

A system dynamics model of clinical decision thresholds for the detection of developmental-behavioral disorders

Abstract Background Clinical decision-making has been conceptualized as a sequence of two separate processes: assessment of patients’ functioning and application of a decision threshold to determine whether the evidence is sufficient to justify a given decision. A range of factors, including use of evidence-based screening instruments, has the potential to influence either or both processes. However, implementation studies seldom specify or assess the mechanism by which screening is hypothesized to influence clinical decision-making, thus limiting their ability to address unexpected findings regarding clinicians’ behavior. Building on prior theory and empirical evidence, we created a system dynamics (SD) model of how physicians’ clinical decisions are influenced by their assessments of patients and by factors that may influence decision thresholds, such as knowledge of past patient outcomes. Using developmental-behavioral disorders as a case example, we then explore how referral decisions may be influenced by changes in context. Specifically, we compare predictions from the SD model to published implementation trials of evidence-based screening to understand physicians’ management of positive screening results and changes in referral rates. We also conduct virtual experiments regarding the influence of a variety of interventions that may influence physicians’ thresholds, including improved access to co-located mental health care and improved feedback systems regarding patient outcomes. Results Results of the SD model were consistent with recent implementation trials. For example, the SD model suggests that if screening improves physicians’ accuracy of assessment without also influencing decision thresholds, then a significant proportion of children with positive screens will not be referred and the effect of screening implementation on referral rates will be modest—results that are consistent with a large proportion of published screening trials. Consistent with prior theory, virtual experiments suggest that physicians’ decision thresholds can be influenced and detection of disabilities improved by increasing access to referral sources and enhancing feedback regarding false negative cases. Conclusions The SD model of clinical decision-making offers a theoretically based framework to improve understanding of physicians’ behavior and the results of screening implementation trials. The SD model is also useful for initial testing of hypothesized strategies to increase detection of under-identified medical conditions