Predicting dental caries outcomes in young adults using machine learning approach.

OBJECTIVES: To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques. METHODS: This study was conducted using the Iowa Fluoride Study dataset. The predictor variables - sex, mother's education, family income, composite socio-economic status (SES), caries experience at ages 9, 13, and 17, and the cumulative estimates of risk and protective factors, including fluoride, dietary, and behavioral variables from ages 5-9, 9-13, 13-17, and 17-23 were used to predict the age 23 D2+MFS count. The following machine learning models (LASSO regression, generalized boosting machines (GBM), negative binomial (NegGLM), and extreme gradient boosting models (XGBOOST)) were compared under 5-fold cross validation with nested resampling techniques. RESULTS: The prevalence of cavitated level caries experience at age 23 (mean D2+MFS count) was 4.75. The predictive analysis found LASSO to be the best performing model (compared to GBM, NegGLM, and XGBOOST), with a root mean square error (RMSE) of 0.70, and coefficient of determination (R2) of 0.44. After dichotomization of the predicted and observed values of the LASSO regression, the classification results showed accuracy, precision, recall, and ROC AUC of 83.7%, 85.9%, 93.1%, 68.2%, respectively. Previous caries experience at age 13 and age 17 and sugar-sweetened beverages intakes at age 13 and age 17 were found to be the four most important predictors of cavitated caries count at age 23. CONCLUSION: Our machine learning model showed high accuracy and precision in the prediction of caries in young adults from a longitudinally-obtained predictor variables. Our model could, in the future, after further development and validation with other diverse population data, be used by public health specialists and policy-makers as a screening tool to identify the risk of caries in young adults and apply more targeted interventions. However, data from a more diverse population are needed to improve the quality and generalizability of caries prediction.

Predictors of survival of large non-occlusal non-incisal glass-ionomer restorations in older adults.

PURPOSE: This study aimed to investigate the predictors of survival of non-occlusal non-incisal glass-ionomer restorations as a surrogate for root surface restorations among older adults. METHODS: In a retrospective cohort analysis using the University of Iowa College of Dentistry electronic dental records, we included 721 patients aged 65+ who received 2+ surface non-occlusal non-incisal glass ionomer restorations placed from January 2005 - December 2011. Restorations were followed until September 2017 or until they were deemed to have failed. RESULTS: At baseline, participants' mean age was 77.6 ± 8.2 years, and 45.8% were females. Most patients were self-pay (65.2%). Most restorations were placed by residents and dental students (82.7%) and included only two surfaces (95.6%). About half (49.1%) failed during follow-up, with a median survival time of 3.7 years. The time ratio for lower incisors compared to other teeth was 0.6 (p = .006), for three-and-four-surface restorations compared to two was 0.7 (p = .007), for faculty as providers compared to residents and students was 1.4 (p = .039), and for the Geriatric & Special Needs Clinic compared to others was 0.8 (p = .013). Time ratios less than one indicate association with shorter durations for restorations, and time ratios greater than one indicate association with longer durations for restorations. CONCLUSION: Tooth type, number of restored surfaces, provider type, and clinic were all significant factors associated with survival of these restorations.

Using machine learning algorithms to investigate factors associated with complete edentulism among older adults in the United States.

AIMS: Edentulism is an incapacitating condition, and its prevalence is unequal among different population groups in the United States (US) despite its declining prevalence. This study aimed to investigate the current prevalence, apply Machine Learning (ML) Algorithms to investigate factors associated with complete tooth loss among older US adults, and compare the performance of the models. METHODS: The cross-sectional 2020 Behavioral Risk Factor Surveillance System (BRFSS) data was used to evaluate the prevalence and factors associated with edentulism. ML models were developed to identify factors associated with edentulism utilizing seven ML algorithms. The performance of these models was compared using the area under the receiver operating characteristic curve (AUC). RESULTS: An overall prevalence of 11.9% was reported. The AdaBoost algorithm (AUC = 84.9%) showed the best performance. Analysis showed that the last dental visit, educational attainment, smoking, difficulty walking, and general health status were among the top factors associated with complete edentulism. CONCLUSION: Findings from our study support the declining prevalence of complete edentulism in older adults in the US and show that it is possible to develop a high-performing ML model to investigate the most important factors associated with edentulism using nationally representative data.

Predicting Dental Caries Outcomes in Young Adults Using Machine Learning Approach.

OBJECTIVES: To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques. METHODS: This study was conducted using the Iowa Fluoride Study dataset. The predictor variables - sex, mother's education, family income, composite socio-economic status (SES), caries experience at ages 9, 13, and 17, and the cumulative estimates of risk and protective factors, including fluoride, dietary, and behavioral variables from ages 5-9, 9-13, 13-17, and 17-23 were used to predict the age 23 D2+MFS count. The following machine learning models (LASSO regression, generalized boosting machines (GBM), negative binomial (NegGLM), and extreme gradient boosting models (XGBOOST)) were compared under 5-fold cross validation with nested resampling techniques. RESULTS: The prevalence of cavitated level caries experience at age 23 (mean D2+MFS count) was 4.75. The predictive analysis found LASSO to be the best performing model (compared to GBM, NegGLM, and XGBOOST), with a root mean square error (RMSE) of 0.70, and coefficient of determination (R2) of 0.44. After dichotomization of the predicted and observed values of the LASSO regression, the classification results showed accuracy, precision, recall, and ROC AUC of 83.7%, 85.9%, 93.1%, 68.2%, respectively. Previous caries experience at age 13 and age 17 and sugar-sweetened beverages intakes at age 13 and age 17 were found to be the four most important predictors of cavitated caries count at age 23. CONCLUSION: Our machine learning model showed high accuracy and precision in the prediction of caries in young adults from a longitudinally-obtained predictor variables. Our model could, in the future, after further development and validation with other diverse population data, be used by public health specialists and policy-makers as a screening tool to identify the risk of caries in young adults and apply more targeted interventions. However, data from a more diverse population are needed to improve the quality and generalizability of caries prediction.

Dental caries incidence and associated factors in young adults.

OBJECTIVES: To assess the caries incidence from late adolescence to early adulthood and to identify the factors associated with caries incidence. METHODS: This is a secondary analysis of longitudinal caries data of young adults aged 17-23 from the Iowa Fluoride Study cohort. The inclusion criteria required completion of dental exams at both ages 17 and 23 and having cumulative exposure (AUC) variables data for at least 8 out of the 11 time periods between ages 17 and 23. Mean imputation was used to handle the missing explanatory variable data. Multiple linear regressions were conducted using a generalized linear model to assess the effects of sociodemographic and behavioral/dietary variables on the age 17-23 adjusted cavitated caries (D2+ MFS) increment (AdjCI17-23 ). Multicollinearity was assessed using the variance inflation factor (VIF) and the final model was selected based on the Akaike Information Criterion (AIC) using backward selection and the net effects calculated. RESULTS: The mean AdjCI17-23 was 2.08 (SD = 4.02). The net effects (main effect plus interactions) of higher composite socioeconomic status, higher combined daily fluoride intake, higher frequency of milk intake, lower amount of sugar-sweetened beverages intake, and lower age 17 dental caries counts were associated with lower mean AdjCI17-23 . CONCLUSION: The incidence of caries from age 17 to 23 in this study was low. This study suggests and reinforces the need to continue to advocate for caries preventive strategies such as fluoride use, encouraging milk intake, and reducing sugar-sweetened beverage intakes.

Trajectories of Dental Caries From Childhood to Young Adulthood: Unsupervised Machine Learning Approach.

Objective: To determine the dental caries trajectories over the life course (from age 9 to 23) using an unsupervised machine learning approach. Methods: This is a longitudinal study of caries trajectories over a life course using data from 1,382 individuals from the Iowa Fluoride Study birth cohort. The trajectory analysis of caries in the permanent dentition at ages 9, 13, 17 and 23 was performed using the unsupervised machine learning algorithm known as K-means for Longitudinal Data (KmL), a k-means based clustering algorithm implemented in R specifically designed for analyzing longitudinal data. The trajectory grouping was performed by assessing the distances of the individual trajectories from the centroid and the prediction of the "best" partition was performed based on the Calinsky & Harabatz criterion. The number of cluster partitions assessed was 2 to 6. The number of re-runs with different starting conditions for each number of clusters was 20. Results: The trajectory analysis identified three trajectory groups with 70.5%, 21.1%, and 8.4% of participants in the low, medium, and high caries trajectory groups, respectively. The mean D2+MFS counts of the low caries trajectory groups at ages 9, 13, 17, and 23 were 0.23, 0.37, 1.10, and 1.56, respectively. The mean D2+MFS counts of the medium caries trajectory groups at ages 9, 13, 17, and 23 were 0.92, 2.09, 6.24, and 9.55, respectively. The mean D2+MFS counts of the high caries trajectory groups at ages 9, 13, 17, and 23 were 1.49, 4.80, 12.91, and 22.52, respectively. There were steeper increases in the D2+MFS scores of the three trajectory groups between age 13 and 17, with less steep but also strongly positive slopes from age 17 to 23, suggesting that the period from age 13 to 17 is the highest risk period. Conclusion: There was an increase in the trajectory slopes after age 13 which might be due to changes in risk factors. The next step in this study will be to identify those factors that predict trajectory group membership by modeling their relationships using supervised machine learning techniques.

Triad multisystem phenotype with high risk for developing temporomandibular disorders-characteristics and potential pathophysiology results from the Orofacial Pain: Prospective Evaluation and Risk Assessment dataset.

ABSTRACT: A multisystem phenotype with the Triad of bodily pain, psychological distress, and sleep disturbance was found to have high risk for developing initial onset of painful temporomandibular disorders (TMDs) in the multicenter Orofacial Pain: Prospective Evaluation and Risk Assessment dataset. In this study, we systemically examined phenotypic characteristics and explored potential pathophysiology in quantitative sensory testing and autonomic nervous system domains in this multisystem Triad phenotype. Secondary analysis was performed on 1199 non-Triad and 154 Triad TMD-free Orofacial Pain: Prospective Evaluation and Risk Assessment enrollees at baseline. Results indicated that before developing TMDs, the Triad phenotype demonstrated both orofacial and systemic signs and symptoms that can only be captured through multisystem assessment. In addition, we found significantly lower resting heart rate variability and higher resting heart rate in the Triad phenotype as compared with the non-Triad group. However, pain sensitivity measured by quantitative sensory testing was not different between groups. These findings highlight the importance of whole-person multisystem assessment at the stage before developing complex pain conditions, such as TMDs, and suggest that, in addition to a "tissue damage monitor," pain should be considered in a broader context, such as a component within a "distress monitoring system" at the whole-person level when multisystem issues copresent. Therefore, the presence or absence of multisystem issues may carry critical information when searching for disease mechanisms and developing mechanism-based intervention and prevention strategies for TMDs and related pain conditions. Cardiovascular autonomic function should be further researched when multisystem issues copresent before developing TMDs.

Development and validation of a nursing home mortality index to identify nursing home residents nearing the end of life in dental clinics.

BACKGROUND: Nursing home (NH) residents seek care at dental offices, yet many of them are at the end of life. The uncertain life expectancy further complicates the care of NH residents. This study aimed to develop and validate a Nursing Home Mortality Index (NHMI) to identify NH residents in the last year of life. METHODS: Logistic modeling was used to develop predictive models for death within 1 year after initial appointment by utilizing the new patient examination data and mortality data of 903 Minnesota NH residents. The final model was selected based on areas under the curve (AUC) and then validated using data from 586 Iowa NH residents. Based on the final model, the NHMI was developed with the estimated 1-year mortality for the low, medium and high risk group. RESULTS: One-year mortalities were 21% and 26% in the development and validation cohorts, respectively. Predictors included age, gender, communication capacity, physical mobility, congestive heart failure, peripheral vascular disease, cancer, cerebrovascular disease, chronic renal disease and liver disease. AUCs for the development and validation models were 0.73 and 0.68, respectively. For the validation cohort, the sensitivity and specificity were 0.79 and 0.53, respectively. The estimated 1-year mortality risks for three risk groups were 0%-10%, 11%-19%, and ≥20%, respectively CONCLUSION: The high mortality rate of NH residents following a dental exam highlighted a need to incorporate patients' prognoses in treatment planning along with normative needs and patients' preferences. The NHMI provides a practical way to guide treatment decisions for end-of-life NH residents.

Effect of Receiving Dental Treatment on mortality among nursing facility residents.

AIM: To assess the association between receipt of different types of dental procedures and mortality among nursing home residents. METHODS AND RESULTS: Between June 2006 and March 2008, 535 nursing home residents received a health screening assessment and were offered comprehensive dental care. Death certificate data were obtained in September 2013 and multivariable regression models were generated to assess the effect of dental procedures delivered after the screening assessment on mortality, adjusting for demographic and health-related covariates. Residents had a mean age of 85.2 years at baseline and approximately 30% were edentulous. About two-thirds received at least one dental procedure, and about 88% had died, between the screening date and the end of follow-up. Among dentate residents, after adjustment for relevant covariates, for each one-unit increase in the number of intervals during which they received at least one preventive dental procedure there was a 13% decrease in mortality (HR = 0.87, 95% CI = 0.78-0.98) at any given time, while for prosthetic dental procedures there was a 16% decrease in mortality (HR = 0.84, 95% CI = 0.72-0.97). Among edentulous residents, only prosthetic procedures were analyzed, and they were not significantly associated with mortality. CONCLUSION: Among dentate institutionalized elderly, receipt of preventive or prosthetic dental procedures was associated with decreased mortality.

Dose-dependent association between xerostomia and number of medications among older adults.

PURPOSE/AIM: To investigate factors associated with self-reported dry mouth (xerostomia) among older adults seeking dental care at a University clinic. MATERIALS AND METHODS: A query was performed in the electronic records database and de-identified data were collected from patients aged 65 + recorded on the date that the initial health history was entered. Among these patients, data about patients' medications, gender, age, BMI, tobacco use, alcohol addiction, diabetes, heart disease, joint replacement, allergies to medications, hypertension, and mental disorders were obtained. Evaluation of potential risk factors for dry mouth was performed using univariate and multivariable logistic regression analyzes (alpha = 0.05). RESULTS: A total of 11,061 subjects were included in the analysis, 51.5% of whom were women. The mean age in years was 74.2 ± 7.0, the median number of medications was 7 (IQR = 4-11), and 38.5% of the participants reported dry mouth. The multivariable logistic regression analysis revealed that the odds of xerostomia for subjects who took 11 +, 7-10, or 4-6 medications were 3.34, 2.07, or 1.38 times those of subjects who had took 0-3 medications, respectively. CONCLUSION: Number of medications showed a strong and dose-dependent association with xerostomia.

Surgery start time and early implant failure: A case-control study.

OBJECTIVE: To evaluate the influence of surgery start time (SST) and other patient- and therapy-related variables on the risk for early implant failure (EIF) in an academic setting. MATERIAL AND METHODS: Data were extracted from the electronic health records of 61 patients who had at least one EIF and 140 age- and gender-matched, randomly selected, non-EIF controls. Bivariate and multivariable analyses were performed to identify relevant associations between EIF and different variables, such as SST. RESULTS: Incidence of EIF was not significantly associated with SST (HR: 1.9 for afternoon implant placement, 95% CI: 0.9-3.9; p = .105). Other factors that were associated with a significantly increased risk for EIF in a multivariable model were pre-placement ridge augmentation (HR: 7.5, 95% CI: 2.2-25.1; p = .001), intra-operative complications (HR: 5.9, 95% CI: 2.2-16.3; p < .001), simultaneous soft tissue grafting (HR: 5.03, 95% CI: 1.3-19.5; p = .020), simultaneous bone grafting (HR: 3.7, 95% CI: 1.6-8.8; p = .002), and placement with sedation (HR: 3.4, 95% CI: 1.5-7.5; p = .002). CONCLUSIONS: While SST was not associated with the occurrence of EIF in our cohort, other variables, such as ridge augmentation prior to implant placement, simultaneous bone or soft tissue grafting, intra-operative complications, implant placement with sedation, and number of implants in the oral cavity, were associated with an increased risk for this adverse event.

Chairside risk assessment for first-onset temporomandibular disorders: Result from the Orofacial Pain: Prospective Evaluation and Risk Assessment data set.

BACKGROUND: Temporomandibular disorders (TMD) risk assessment is difficult in general dentistry owing to the complexity of multifactorial risk contributions and the lack of standardized education. The authors explored a health history-based chairside risk assessment. METHODS: Secondary data analysis was performed on the Orofacial Pain: Prospective Evaluation and Risk Assessment data set. Potential demographic, systemic, and local risk contributors were conceptualized into 10 risk categories. Multivariate Cox proportional hazards modeling with backward selection was applied. Variables with P values < .05 were kept in each successive model. RESULTS: The analysis included data from 2,737 participants. The final model indicated that people with any psychological conditions, pain disorders, sleep disorders, or orofacial symptoms were at elevated risks of developing first-onset TMD. Results of post hoc analysis showed the coexistence of conditions from multiple body systems conferred greater risk of developing TMD. CONCLUSIONS: Coexisting conditions and symptoms from multiple body systems substantially increase the risk of developing TMD pain. Therefore, multisystem risk assessment and interprofessional collaborations are important for the prevention of TMD. PRACTICAL IMPLICATIONS: Dentists should include psychological conditions, pain disorders, sleep disorders, and orofacial symptoms when assessing patients' risk of developing TMD pain.

Factors associated with the counts of selected oral microorganisms in nursing home residents.

PURPOSE/AIM: To analyze potential factors associated with levels of selected oral pathogens, as well as total aerobic bacterial species, among nursing home residents. MATERIALS AND METHODS: Nursing home residents were divided into three groups (G1 included people with teeth but no dentures, G2 included people with teeth and dentures, and G3 included people with no teeth and with dentures). All participants had microbiological samples collected from their oral cavity and dentures. Counts of total aerobic bacterial species, Porphyromonas gingivalis, Fusobacterium nucleatum, Actinomyces viscosus, Aggregatibacter actinomycetemcomitans, and Candida albicans were compared among groups using the Wilcoxon rank sum test. A multivariate analysis was also performed to control other available covariates. RESULTS: Bivariate analysis revealed significant differences among the groups, and multivariate analysis showed that sex, the presence of natural teeth, denture wearing, oral hygiene indices, and systemic health conditions were associated with bacterial and Candida albicans log counts. CONCLUSIONS: Presence of natural teeth and denture wearing, as well as oral hygiene, sex and systemic health conditions were associated with bacterial and Candida albicans log counts among nursing home residents.

Structuring, reuse and analysis of electronic dental data using the Oral Health and Disease Ontology.

BACKGROUND: A key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information collected during dental care exposes many of the challenges that confront a wider scale approach. For example, to improve the quality of dental care, we must be able to collect and analyze data about dental procedures from multiple practices. However, a number of challenges make doing so difficult. First, dental electronic health record (EHR) information is often stored in complex relational databases that are poorly documented. Second, there is not a commonly accepted and implemented database schema for dental EHR systems. Third, integrative work that attempts to bridge dentistry and other settings in healthcare is made difficult by the disconnect between representations of medical information within dental and other disciplines' EHR systems. As dentistry increasingly concerns itself with the general health of a patient, for example in increased efforts to monitor heart health and systemic disease, the impact of this disconnect becomes more and more severe. To demonstrate how to address these problems, we have developed the open-source Oral Health and Disease Ontology (OHD) and our instance-based representation as a framework for dental and medical health care information. We envision a time when medical record systems use a common data back end that would make interoperating trivial and obviate the need for a dedicated messaging framework to move data between systems. The OHD is not yet complete. It includes enough to be useful and to demonstrate how it is constructed. We demonstrate its utility in an analysis of longevity of dental restorations. Our first narrow use case provides a prototype, and is intended demonstrate a prospective design for a principled data backend that can be used consistently and encompass both dental and medical information in a single framework. RESULTS: The OHD contains over 1900 classes and 59 relationships. Most of the classes and relationships were imported from existing OBO Foundry ontologies. Using the LSW2 (LISP Semantic Web) software library, we translated data from a dental practice's EHR system into a corresponding Web Ontology Language (OWL) representation based on the OHD framework. The OWL representation was then loaded into a triple store, and as a proof of concept, we addressed a question of clinical relevance - a survival analysis of the longevity of resin filling restorations. We provide queries using SPARQL and statistical analysis code in R to demonstrate how to perform clinical research using a framework such as the OHD, and we compare our results with previous studies. CONCLUSIONS: This proof-of-concept project translated data from a single practice. By using dental practice data, we demonstrate that the OHD and the instance-based approach are sufficient to represent data generated in real-world, routine clinical settings. While the OHD is applicable to integration of data from multiple practices with different dental EHR systems, we intend our work to be understood as a prospective design for EHR data storage that would simplify medical informatics. The system has well-understood semantics because of our use of BFO-based realist ontology and its representation in OWL. The data model is a well-defined web standard.

Predictors of having a dentist among older adults in Iowa.

OBJECTIVES: Oral health plays an important role in the general well-being of older adults, yet older adults experience unique barriers to dental care. In the United States, almost two-thirds of older adults are dentally uninsured - a reflection of the exclusion of dental benefits from Medicare. The aim of this study was to investigate potential predictors of having a dentist among older adults receiving services funded through the Iowa Department on Aging (IDA). METHODS: This was a cross-sectional analysis on a convenience sample (n = 2692) of adults age 65+ who completed a required survey to determine eligibility to receive services from the IDA. Data from questionnaires completed between March and December 2017 were used to generate multivariable logistic regression models that identified predictors of having a dentist. The dependent variable, having a dentist, was gathered by self-report in the survey. Explanatory variables eligible for inclusion in the models included demographic and geographic factors, indicators of access to dental care, and factors related to activities of daily living. RESULTS: Fewer than half (46.2%) of the respondents reported having a dentist. In the final regression model, individuals with dental insurance were more than twice as likely to have a dentist than those without insurance. Conversely, individuals with a tooth/mouth problem and who need help with housekeeping and with transportation were significantly less likely to have a dentist than their counterparts. CONCLUSIONS: These results align with known insurance-related barriers and identify certain activities of daily living that might influence older adults' ability to access care. The finding that individuals with oral health problems were less likely to have a dentist underscores the need to reduce barriers to care for this population.

Self-perceived oral health among institutionalized older adults in Taubate, Brazil.

PURPOSE/AIM: To assess self-perception of oral health among institutionalized older adults in Taubate, Brazil. METHOD AND MATERIALS: Demographics, oral, and systemic health data were collected from a sample of 89 institutionalized older adults. The Geriatric Oral Health Assessment Index (GOHAI) was applied to assess their self-perception of oral health. A linear regression model using GOHAI scores and considering age, BMI, gender, race, dry mouth, denture status, number of teeth, number of comorbid conditions, and number of medications as independent variables was generated. RESULTS: Fifty-five percent were male, with an average age of 75.9 years (±9.1), 43.8% identified as mixed race, and 42.7% as white. The average BMI was 23.9 (±3.8), the average number of comorbid condition was 1.8 (±1.4), and the average number of daily medications was 6.2 (±3.6). The average number of teeth was 3.9 (±7.4), and 57.3% of the participants reported dry mouth sensation; 8.9% presented oral lesions, with denture stomatitis as the most common oral lesion (5.6%). The average GOHAI score was 31.1 (±3.7). Regression analysis showed a negative correlation between BMI and GOHAI scores (P = .032, R2  = 7.2%). CONCLUSIONS: Self-perception of oral health was good and negatively correlated with BMI.

Survival analysis of caries incidence in African-American school-aged children.

OBJECTIVES: To conduct an assessment of time-dependent covariates related to dental caries of the permanent dentition among a low socioeconomic status, understudied cohort of children, incorporating time-dependent covariates through the application of extended Cox proportional hazards modeling. METHODS: This study modeled the time to first cavitated dental caries in permanent teeth among school-aged children and assessed factors associated with this event. A cohort of 98 low socioeconomic status African-American children with mean age of 5.85 years at baseline was recruited in Uniontown, Alabama and followed prospectively for 6 years. None of these children had dental caries on permanent teeth at baseline, and oral examinations were performed annually. Caries-free survival curves were generated to describe time to event (having first decayed, filled, or missing permanent surface). Bivariate and multivariable extended Cox hazards modeling was used to assess the relationships between time-dependent and time-independent covariates and time to event. RESULTS: Twenty-eight children (28.6 percent) had their first permanent tooth caries event during the 6-year follow-up. Multivariable results showed that greater consumption of water was associated with lower dental caries hazard, while previous primary tooth caries experience was associated with greater dental caries hazard after adjustment for frequency of consumptions of milk, added-sugar beverages, and 100 percent juice. CONCLUSIONS: There was a global/overall significant caries protective effect of water consumption during the school-age period of child development.

Systemic Health Characteristics and Self-Reported Xerostomia among Nursing Facility Residents in Iowa-US and Sao Paulo-Brazil / Saúde Sistêmica e Xerostomia Auto-Reporada entre Residentes em Instituições de Longa Permanência em Iowa-EUA e São Paulo-Brasil

Objective: To describe and compare potential differences in systemic health characteristics and xerostomia among residents in American and Brazilian nursing facilities (NF). Material and Methods: This secondary analysis used data from a study in NF located in Iowa-USA (n=81) and Sao Paulo (SP)-Brazil (n=119). Recorded data included demographics, medications, comorbid conditions, and self-reported xerostomia. Results: The Iowa group mean age was 82.1 years (±12.9), 60.5% were females, and 100% were white, whereas the SP group mean age was 76.4 years (±8.7), 47.9% females, most participants identified as either white (42.0%) or as more than one race (45.4%). The median number of comorbid conditions and medications in the Iowa were 9 and 12, respectively, as compared to 2 and 6 in SP. Most common comorbidities in Iowa were hypertension, dementia (including Alzheimer), and depression. In SP, they were hypertension, unspecified diabetes mellitus (including type 2), and Parkinson. Most common prescription medications in Iowa were acetaminophen, acetylsalicylic acid, and magnesium hydroxide, while in SP, they were omeprazole, acetylsalicylic acid, and losartan. Xerostomia was reported by 32.1% (Iowa) and 59.7% (SP) of the participants. There was no association between age and dry mouth sensation in either Iowa (p=0.480) or SP (p=0.130) samples. However, there was an association between total medications and dry mouth sensation in Iowa (p=0.040), but not in SP (p=0.075) Conclusions: Iowans presented with higher numbers of comorbidities and prescription medications, however xerostomia was reported in a greater percentage in SP. Xerostomia was associated to higher number of medications in Iowa, but not in SP.(AU)

Objetivo: Descrever e comparar possíveis diferenças nas características de saúde sistêmica e xerostomia entre residentes em instituições de longa permanência (ILP) americanas e brasileiras. Materiais e Métodos: Esta análise utilizou dados de um estudo em ILPs localizadas em Iowa/EUA (n = 81) e São Paulo/Brasil (n = 119). Os dados avaliados incluíram dados demográficos, medicamentos, comorbidades e xerostomia autoreportada. Resultados: A idade média do grupo de Iowa foi de 82,1 anos (± 12,9), 60,5% eram do sexo feminino e 100% eram brancos, enquanto a idade média do grupo SP foi de 76,4 anos (± 8,7), 47,9% do sexo feminino, a maioria dos participantes identificados como brancos ( 42,0%) ou como mais de uma raça (45,4%). A média do número de comorbidades e medicamentos em Iowa foi de 9 e 12, respectivamente, em comparação com 2 e 6 em SP. Comorbidades mais comuns em Iowa foram hipertensão, demência (incluindo Alzheimer) e depressão. Em SP, foram hipertensão, diabetes mellitus (incluindo o tipo 2) e Parkinson. Os medicamentos de prescrição mais comuns em Iowa eram acetaminofeno, ácido acetilsalicílico e hidróxido de magnésio, enquanto em SP, foram omeprazol, ácido acetilsalicílico e losartana. A xerostomia foi reportada por 32,1% dos participantes em Iowa e 59,7% em SP. Não houve associação entre idade e sensação de boca seca nas amostras de Iowa (p = 0,480) ou SP (p = 0,130). No entanto, houve associação entre o total de medicamentos e a sensação de boca seca em Iowa (p= 0,040), mas não em SP (p = 0,075). Conclusões: Os residentes de Iowa apresentaram maior número de comorbidades e prescrição de medicamentos, porém a xerostomia foi relatada em maior percentual em SP. A xerostomia foi associada ao maior número de medicamentos em Iowa, mas não em SP.(AU)

Iowa nursing facility oral hygiene (INFOH) intervention: A clinical and microbiological pilot randomized trial.

PURPOSE/AIM: The aim of this pilot study was to evaluate feasibility and gather initial data for a definitive study to test the clinical and microbiological effectiveness of a nursing facility (NF) customized oral hygiene protocol, intended to be delivered by dental hygienists and NF personnel. MATERIALS AND METHODS: A convenience sample of 8 Eastern Iowa NFs was recruited, and each NF was assigned to one of three intervention groups: (1) control (current oral hygiene practice), (2) educational program only, and (3) educational program plus 1% chlorhexidine varnish monthly application. Demographic information, systemic health data, patient centered data, oral health data, and microbiology samples were collected at baseline and after 6 months. RESULTS: Recruitment response rates were 21% for NFs and 23% for residents. A total of 81 residents were examined at baseline and of those, 49 were examined at 6 months (39.5% attrition). There were no statistically or clinically significant differences among the intervention groups at 6 months for any of the recorded clinical or microbiological outcomes. CONCLUSIONS: Recruitment and retention posed a significant challenge to this trial, even with a relatively short observation period. Results from this pilot study did not encourage further investigation of this customized oral hygiene protocol.

Anterior restoration longevity among nursing facility residents: a 30-year retrospective study.

AIM: To assess factors influencing anterior dental restoration longevity among the institutionalized elderly. METHODS: Among a sample of Eastern Iowa nursing facility dental patients, one anterior restoration placed from 1985 to 2014 was selected at random from each subject. Kaplan-Meier survival curves were generated, with restoration failures defined as subsequent restorative codes involving the same surface; endodontic procedures; or extractions. Bivariate and multivariable Cox proportional hazards modeling were performed. RESULTS: In multivariable analyses, the 1985 to 1999 cohort (n = 496) had longer restoration survival in in females < 75 years old versus males < 75 years old (P = 0.016), males ≥75 years old (P = 0.026) and females ≥75 years old (P = 0.030); one- versus three-surface restorations (P < 0.001); and restorations placed by faculty/residents versus pre-doctoral students (P = 0.009). The 2000 to 2014 cohort (n = 521) had longer restoration survival in females < 75 years old versus males ≥75 years old (P = 0.012) and females ≥75 years old (P = 0.019); residents who paid out-of-pocket versus those on Medicaid (P = 0.019); and composite resin versus glass ionomer cement restorations (P < 0.001). CONCLUSIONS: Knowing how long restorations last, and what factors affect their longevity, could improve treatment planning, informed consent, and communication with residents and caregivers, and also help inform practice guidelines for restorative care among the institutionalized elderly.