Midlife Cognitive Ability, Education, and Tooth Loss in Older Danes

Projecting trends in the disease burden of adult edentulism in China between 2020 and 2030: a systematic study based on the global burden of disease

Purpose

This study was based on the Global Burden of Disease (GBD) database and aimed to analyze the trend of disease burden for complete edentulism in Chinese adults between 1990 and 2030, and to provide valuable information for the development of more effective management and preventive measures.

Methods

Data on Chinese adults with complete edentulism from 1990 to 2019 was analyzed using GHDx data. Descriptive analyses were used to analyze changes in the prevalence and burden of complete edentulism, gender and age distribution between 1990 and 2019. In addition, we used an autoregressive integrated moving average (ARIMA) model to predict the trend of disease burden for Chinese adults with complete edentulism between 2020 and 2030.

Results

The incidence, prevalence, and rate of YLDs in adults with complete edentulism in China showed an increasing trend from 1990 to 2019. In 2019, the incidence was 251.20 per 100,000, the prevalence was 4512.78 per 100,000, and the YLDs were 123.44 per 100,000, marking increases of 20.58, 94.18, and 93.12% from 1990. Males experienced a higher increase than females. However, the standardized rates decreased over the same period. The ARIMA model predicts a subsequent upward and then downward trend for all indicators between 2019 and 2030, except for the standardized incidence rate which remained essentially unchanged. Specifically, the incidence is predicted to decrease from 388.93 to 314.40 per 100,000, prevalence from 4512.78 to 3049.70 per 100,000, and YLDs from 123.44 to 103.44 per 100,000. The standardized prevalence and YLDs rates are also expected to decrease.

Conclusion

The burden of complete edentulism in China is projected to show an increasing trend from 2020 to 2022 and a decreasing trend from 2023 to 2030. Despite the decline in the burden of disease associated with complete edentulism in China, many problems remain to be solved.

Poor oral health and dementia risk under time-varying confounding: A cohort study based on marginal structural models

BACKGROUND

Bidirectional association between oral health, including tooth loss and oral hypofunction, and cognitive impairment can induce time-varying confounding in association with dementia. This study aimed to investigate the association between oral health and the development of dementia among older adults, considering cognitive impairment as a time-varying confounder.

METHODS

This nine-year follow-up cohort study targeted independent older adults aged ≥65 years who participated in the Japan Gerontological Evaluation Study. The exposure variables were self-reported poor oral health (≤19 remaining teeth, edentulousness, chewing difficulty, swallowing problems, and xerostomia), which were assessed in 2010 and 2013. The outcome variable was the incidence of dementia between 2013 and 2019, which was obtained from the municipalities' administrative database. Furthermore, in 2010 and 2013, we considered cognitive impairment as a time-varying confounder and treated it based on a marginal structural model (MSM), including possible baseline confounders. Oral health and cognitive impairment were assessed using the items of Kihon checklist. We employed a Cox proportional hazards model with a stabilized inverse probability weight and estimated hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

Among 37,556 participants (mean age: 72.8 years [1 SD = 5.5], males: 46.8%), the dementia incidence rate was 2.2/100 person-year. The proportions of those with ≤19 remaining teeth, edentulousness, chewing difficulty, swallowing problems, and xerostomia were 61.3%, 11.0%, 24.4%, 14.7%, and 19.2%, respectively. From the regression analysis based on MSM, ≤19 remaining teeth (HR = 1.12, 95% CI = 1.03-1.23), edentulousness (HR = 1.20, 95% CI = 1.09-1.32), chewing difficulty (HR = 1.11, 95% CI = 1.02-1.21), and xerostomia (HR = 1.10, 95% CI = 1.01-1.20) were significantly associated with an increased risk of dementia; however, swallowing problems were not significantly associated with dementia onset (p > 0.05).

CONCLUSIONS

Even after considering time-varying confounding by cognitive function at baseline and follow-up, we observed significant associations between poor oral health and increased risk of dementia among older adults.

Investigating the causal effect of cognition on the self-reported loss of functional dentition using marginal structural models: The Panel on Health and Ageing of Singaporean Elderly study

AIM

To assess the effect of cognition on the loss of functional dentition.

MATERIALS AND METHODS

We used data from the three waves of the Panel on Health and Ageing of Singaporean Elderly study (n = 4990 at baseline, 774 complete cases analysed) over 6 years (2009-2015). The outcome was the loss of functional dentition (<21 teeth). The exposure was cognitive impairment, while baseline confounders included age, sex, education, and ethnicity. Time-varying confounders included income, living arrangements, smoking, diabetes, depressive symptoms, cardiovascular disease, and body mass index. We used marginal structural mean models with inverse probability treatment weighted.

RESULTS

The mean age of the participants was 70.2 years at baseline. The proportion of participants with loss of functional dentition increased from 74.6% to 89.9% over 6 years. Women, ethnic Chinese, less educated, smokers, people with diabetes, and individuals with depression had a higher proportion of loss of functional dentition than their counterparts. Loss of functional dentition was 1.8 times higher (odds ratio 1.80; 95% confidence interval 0.88-3.69) among those with cognitive impairment after taking well-known confounders into account.

CONCLUSIONS

After accounting for the time-varying exposure and confounding evidence, the association between cognition and functional dentition among the elderly in Singapore remains uncertain.

Relationship between Cognition, Depression, and Oral health status in Older adults: A longitudinal cross-lagged analysis

BACKGROUND

The world's population is aging increasingly, and older adults' physical and mental health needs to be prioritized. Although several studies have explored the relationship between cognition, depression, and oral health in older adults, the exact nature and direction of this relationship are poorly understood. Moreover, most studies to date have been cross-sectional, with fewer longitudinal studies. The current longitudinal study explored the relationship between cognition, depression, and oral health in older adults.

METHODS

We used data from two waves (2018, 2020) of the Korean Longitudinal Study of Aging, which included 4543 older adults aged 60 years and older. General socio-demographic characteristics were analyzed using descriptive analysis, and study variables were described using t-tests. Generalized Estimating Equations (GEE) and cross-lagged models were used to examine the longitudinal associations between cognition, depression, and oral health.

RESULTS

The GEE results suggested that better cognition and less depression over time were associated with better oral health in older adults. Cross-lagged models further validated the effect of depression on oral health over time.

LIMITATIONS

The directionality of the influence of cognition on oral health could not be determined.

CONCLUSIONS

Although there were several limitations, our study provided novel ideas for verifying the effects of cognition and depression on oral health in older adults.

Spatiotemporal trends of disease burden of edentulism from 1990 to 2019: A global, regional, and national analysis

Background

Understanding the spatiotemporal trends in disease burden of edentulism is critical to reducing disease burden of edentulism and deploying medical resources. We assessed the changing patterns of disease burden of edentulism at global, regional, and national levels from 1990 to 2019.

Methods

Data on incident cases, prevalent cases, disability-adjusted life years (DALYs), and age-standardized rates (ASRs) of edentulism were extracted from the Global Burden of Disease 2019 Study. We calculated the estimated annual percentage change (EAPC) to quantify spatiotemporal trends in the ASRs of edentulism.

Results

In 2019, the number of prevalent cases and DALYs of edentulism were 35.2 and 9.6 million, and the ASPR and ASDR were 43.12/1,000 and 1.18/1,000, with EAPCs of -0.18 [95% confidence interval (CI): -0.28, -0.09] and -0.16[95% CI: -0.26, -0.07] from 1990 to 2019, respectively. Females and the elderly had a higher burden of edentulism. Although the ASPR, ASDR, and ASIR in the high SDI, high-middle SDI, and middle SDI regions showed a decreasing or stable trend, the absolute disease burdens of edentulism in these regions were still high. Although the absolute disease burdens of low SDI and low-middle SDI were low, their ASPR and ASDR showed an upward trend. In countries with high initial disease burden or high SDI, ASPR, ASDR, and ASIR showed stable or declining trends.

Conclusion

The absolute disease burden due to edentulism was increasing in many countries and regions. Countries should reduce the disease burden caused by edentulism by adopting measures including the prevention and treatment of dental caries and periodontal disease.

Systematic Review of the Literature on Dental Caries and Periodontal Disease in Socio-Economically Disadvantaged Individuals

Dental caries and periodontal disease represent a health problem and a social cost for the entire population, and in particular for socio-economically disadvantaged individuals who are less resistant to disease. The aim of this review is to estimate the prevalence and severity of the two dental pathologies, caries and periodontal disease, in the different classes of socio-economically disadvantaged subjects and to understand which of them are most affected. A systematic search of the literature was performed in MEDLINE (via PubMed), EMBASE and Web of Science after establishing a suitable search strategy for each database, using keywords related to socio-economically vulnerable classes and health outcomes. Socio-economically disadvantaged individuals are more susceptible to tooth decay and periodontal disease (with relative tooth loss) than non-vulnerable people. Additionally, when multiple vulnerabilities are combined in the same subject, these oral diseases worsen. There is no type of vulnerability more affected by caries and periodontitis than others, since overall they all have severe disease indices. The data from this systematic literature review might be useful for health policy makers looking to allocate more resources and services to socially disadvantaged individuals, resulting in making them more resilient to oral disease due to their social marginalization.

Predictors of tooth loss: A machine learning approach

Introduction

Little is understood about the socioeconomic predictors of tooth loss, a condition that can negatively impact individual’s quality of life. The goal of this study is to develop a machine-learning algorithm to predict complete and incremental tooth loss among adults and to compare the predictive performance of these models.

Methods

We used data from the National Health and Nutrition Examination Survey from 2011 to 2014. We developed multiple machine-learning algorithms and assessed their predictive performances by examining the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values.

Results

The extreme gradient boosting trees presented the highest performance in the prediction of edentulism (AUC = 88.7%; 95%CI: 87.1, 90.2), the absence of a functional dentition (AUC = 88.3% 95%CI: 87.3,89.3) and for predicting missing any tooth (AUC = 83.2%; 95%CI, 82.0, 84.4). Although, as expected, age and routine dental care emerged as strong predictors of tooth loss, the machine learning approach identified additional predictors, including socioeconomic conditions. Indeed, the performance of models incorporating socioeconomic characteristics was better at predicting tooth loss than those relying on clinical dental indicators alone.

Conclusions

Future application of machine-learning algorithm, with longitudinal cohorts, for identification of individuals at risk for tooth loss could assist clinicians to prioritize interventions directed toward the prevention of tooth loss.

Analysis of the relationship between lifestyle habits and glycosylated hemoglobin control based on data from a Health Management Plan

BACKGROUND/OBJECTIVES

Type 2 Diabetes mellitus (T2DM) is a hereditary disease that is also strongly dependent on environmental factors, lifestyles, and dietary habits. This study explored the relationship between lifestyle habits and glycosylated hemoglobin management in T2DM patients to provide empirical outcomes to improve T2DM management and patient health literacy.

SUBJECTS/METHODS

This study enrolled 349 diabetic patients with more than 5 care visits to a Diabetes Mellitus care network under the Health Management Plan led by Taiwan Department of Health (DOH). Based on relevant literature, an Outpatient Record Form of Diabetes Mellitus Care was designed and lipid profile tests were conducted for data collection and analysis.

RESULTS

When modeling the data, the results showed that the odds for HbA1c > 7.5% in T2DM patients duration over 10 years was 3.785 (P = 0.002) times that in patients with disease duration of fewer than 3 years. The odds of HbA1c > 7.5% in illiterate patients was 3.128 (P = 0.039) times that in patients with senior high school education or above. The odds of HbA1c > 7.5% in patients with other chronic illness was 2.207 (P = 0.019) times that in participants without chronic illness. Among 5 beneficial lifestyle habits, the odds of HbA1c > 7.5% in patients with 2 or 3 good habits were 3.243 (P = 0.003) and 3.424 (P = 0.001) times that in patients with more than 3 good habits, respectively.

CONCLUSION

This empirical outcome shows that maintaining a good lifestyle improves T2DM management and patients' knowledge, motivation, and ability to use health information. Patients with longer disease duration, education, or good lifestyle habits had optimal HbA1c management than those in patients who did not. Thus, effective self-management and precaution in daily life and improved health literacy of diabetic patients are necessary to increase the quality of T2DM care.

The Causal Effect of Education on Tooth Loss: Evidence From United Kingdom Schooling Reforms

Associations between education and oral health have frequently been reported, but until now there has been no causal evidence. Exploiting exogenous variation in the duration of schooling due to 1947 and 1972 reforms in mandatory schooling in the United Kingdom, we examined the causal relationship between education and tooth loss in older age. We conducted a cross-sectional study using data from waves 3 (2006-2007), 5 (2010-2011), and 7 (2014-2015) of the English Longitudinal Study of Ageing. We used a 2-stage least squares instrumental variable approach and included 5,667 respondents (average age = 67.8 years; 44.4% were men) in the analyses, of whom 819 (14.5%) had no teeth. The schooling reforms increased the duration of education by an average of 0.624 years (95% confidence interval: 0.412, 0.835). For respondents born within ±6 years of the pivotal cohorts, a 1-year increment of education causally reduced the probability of edentulism by 9.1 (95% confidence interval: 1.5, 16.8) percentage points. The effects were stronger for the 1947 reform than for the 1972 reform. Results were robust to broadening of the cohort bandwidth and functional form of the cohort trend. The findings suggest that investment in education produces improved oral health later in life.

Association between residual teeth number in later life and incidence of dementia: A systematic review and meta-analysis

Background

It has been suggested that tooth loss in later life might increase dementia incidence. The objective of this analysis is to systematically review the current evidence on the relationship between the number of remaining teeth and dementia occurrence in later life.

Methods

A search of multiple databases of scientific literature was conducted with relevant parameters for articles published up to March 25th, 2017. Multiple cohort studies that reported the incidence of dementia and residual teeth in later life were found with observation periods ranging from 2.4 to 32 years. Random-effects pooled odds ratios (OR) and 95% confidence intervals (CI) were estimated to examine whether high residual tooth number in later life was associated with a decreased risk of dementia. Heterogeneity was measured by I². The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was used to assess the overall quality of evidence.

Results

The literature search initially yielded 419 articles and 11 studies (aged 52 to 75 at study enrollment, n = 28,894) were finally included for analysis. Compared to the low residual teeth number group, the high residual teeth number group was associated with a decreased risk of dementia by approximately 50% (pooled OR = 0.483; 95% CI 0.315 to 0.740; p < 0.001; I² = 92.421%). The overall quality of evidence, however, was rated as very low.

Conclusion

Despite limited scientific strength, the current meta-analysis reported that a higher number of residual teeth was associated with having a lower risk of dementia occurrence in later life.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0729-z) contains supplementary material, which is available to authorized users.