Rural-urban disparities in the prevalence of mild cognitive impairment and dementia in Taiwan: A door-to-door nationwide study

Sources of perceived social support and cognitive function among older adults: a longitudinal study in rural China

Background

Studies have shown the positive impact of perceived social support on cognitive function among older adults in rural areas. However, existing studies often overlook the impact of different support sources. This study aimed to explore the relationship between the diverse sources of perceived social support and cognitive function.

Methods

Participants were drawn from the Guizhou Rural Older Adults' Health Study (HSRO) in China. We included 791 participants who participated in a baseline survey in 2019 and a 3-year follow-up survey. Perceived social support was investigated from the six main sources (friend, relative, children, spouse, sibling, and neighbor). Hierarchical linear regression models were used to observe the effects of diverse sources of perceived social support and their combinations on cognitive function.

Results

Cognitive function was positively associated with perceived support from children, friends, and neighbors. A positive association was found between cognitive function and increases in each additional source [β = 0.75 (95%CI: 0.51, 0.98), p < 0.001]. Older adults who perceived support from both children and friends showed better cognitive function [β = 2.53 (95%CI: 1.35, 3.72), p < 0.001]. The perception of support from spouse, siblings, and relatives did not show a statistically significant association with cognitive function among older adults in rural areas.

Conclusion

This study found that the association between different sources of perceived social support and cognitive function was varied. This study provides scientific evidence that personalized support strategies may benefit in promoting cognitive health in rural older adults.

Disparities in structural brain imaging in older adults from rural communities in Southern Nevada

Introduction

Identifying the associations between rural-living or neighborhood disadvantage and neurobiology may clarify rural-urban disparities in older adults with cognitive impairment related to Alzheimer's disease.

Methods

We examined rural-urban differences and neighborhood disadvantages in brain cortical thickness (CT) measures among 71 rural and 87 urban-dwelling older adults. Analysis of covariance was used to test each FreeSurfer-derived CT measures' associations with rural-urban living, clinical impairment status, and their interactions. Post-hoc linear regressions were used to test the association between CT measures and neighborhood disadvantage index.

Results

Rural-dwelling older adults had thinner cortices in temporal and inferior frontal regions compared to urban participants, especially among clinically normal participants, where the thinner temporal cortex further correlated with higher neighborhood disadvantage. Conversely, rural participants had thicker cortices in superior frontal, parietal and occipital regions.

Discussion

Our results suggest a complex interplay between community contexts and neurobiology. For memory-related regions, rural-living and neighborhood disadvantage might be negatively associated with subjects' brain structures.

Combining the AD8 and MMSE for community-based dementia screening

BACKGROUND

This study aimed to determine whether a cognitive test the Mini-Mental State Examination (MMSE) and the Ascertain Dementia 8 (AD8) instrument applied in combination could improve the accuracy of dementia detection in a community setting.

METHODS

Study participants were recruited from a community-based integrated screening program in Tainan, Taiwan. Participants completed the AD8 and were administered the Chinese version of the MMSE by psychologists. In addition, the presence of dementia was determined by neurologists based on the 2011 National Institute on Aging-Alzheimer's Association guidelines. Logistic regression analysis determined whether the combination of these two tests provided any additional information for dementia detection than either test alone. Receiver operating characteristic (ROC) curve analyses were conducted to explore the performances of different screening modalities in detecting dementia.

RESULT

In total, 282 participants with an average age of 69.31 ± 10.27 years were enrolled. The prevalence of dementia among participants aged ≥65 years was 9.29 %. The sensitivity and specificity of the AD8 applied alone for detecting dementia were 64.71 % and 87.89 %, respectively, and of the MMSE applied alone, after adjusting for education level, were 41.18 % and 84.50 %, respectively. Using a cutoff score of 21 for the MMSE resulted in sensitivity of 77.78 % and specificity of 73.58 %. The AD8 and MMSE when combined in parallel yielded 88.89 % sensitivity and 70.16 % specificity. The serial use of the AD8 followed by the MMSE yielded 50 % sensitivity and 93.02 % specificity. Except for when an MMSE cutoff value of 26 was applied, the sensitivity of all examined modalities was poor and specificity was moderate for detecting mild cognitive impairment. ROC curve analysis revealed that the parallel application of the MMSE and AD8 (area under the ROC curve [AUC]: 82.3 % [75.1 %-89.4 %]) resulted in better dementia detection accuracy than the AD8 alone (AUC: 73.3 % [60.7 %-85.9 %]), the MMSE alone (AUC: 77.4 % [67.6 %-87.3 %]), or serial test administration (AUC: 67.6 % [53.4 %-81.8 %]).

CONCLUSION

This study successfully demonstrated that the MMSE and AD8 combination for dementia screening could improve detection accuracy in a community setting.

Age of type 2 diabetes onset as a risk factor for dementia: A 13-year retrospective cohort study

AIMS

To examine whether age at type 2 diabetes onset is an independent predictor of dementia risk.

METHODS

Retrospective cohort drawn from healthcare administrative records of all inhabitants within Romagna's catchment area, Italy, with an estimated onset of type 2 diabetes in 2008-2017 and aged ≥ 55, with follow-up until 2020. Time to dementia or censoring was estimated with the Kaplan-Meier method, using diabetes onset as the time origin. Age groups were compared with the log-rank test. Multivariable competing-risks analysis was used to assess predictors of dementia.

RESULTS

In patients aged ≥ 75 years, dementia-free survival (DFS) declined to below 90 % within five years and linearly decreased to 68.8 % until the end of follow-up. In contrast, DFS for those aged 55-64 years showed a marginal decrease, reaching 97.4 % after 13 years. Competing-risks regression showed that individuals aged ≥ 75 and 65-74 had a significantly higher risk of dementia compared to those aged 55-64 years. Having more comorbidities at diabetes onset and initial treatment with ≥ 2 antidiabetics were clinical predictors.

CONCLUSIONS

Later age at onset of diabetes is strongly associated with dementia. A better understanding of the diabetes-dementia relationship is needed to inform strategies for promoting specific healthcare pathways.

Association between drinking water sources and cognitive functioning in Chinese older adults residing in rural areas

OBJECTIVES

To explore the association between drinking water sources and cognitive functioning among older adults residing in rural China.

METHODS

Data were extracted from the 2008-2018 Chinese Longitudinal Healthy Longevity Survey. Drinking water sources were categorized according to whether purification measures were employed. The Chinese version of the Mini-Mental State Examination was used for cognitive functioning assessment, and the score of <24 was considered as having cognitive dysfunction. Cox regression analyses were conducted to derive hazard ratios (HRs) and 95% confidence intervals (CIs) for the effects of various drinking water sources, changes in such sources, and its interaction with exercise on cognition dysfunction.

RESULTS

We included 2304 respondents aged 79.67 ± 10.02 years; of them, 1084 (44.49%) were men. Our adjusted model revealed that respondents consistently drinking tap water were 21% less likely to experience cognitive dysfunction compared with those drinking untreated water (HR = 0.79, 95% CI: 0.70-0.90). Respondents transitioning from natural to tap water showed were 33% less likely to experience cognitive dysfunction (HR = 0.67, 95% CI: 0.58-0.78). Moreover, the HR (95% CI) for the interaction between drinking tap water and exercising was 0.86 (0.75-1.00) when compared with that between drinking untreated water and not exercising. All results adjusted for age, occupation, exercise, and body mass index.

CONCLUSIONS

Prolonged tap water consumption and switching from untreated water to tap water were associated with a decreased risk of cognitive dysfunction in older individuals. Additionally, exercising and drinking tap water was synergistically associated with the low incidence of cognitive dysfunction. These findings demonstrate the importance of prioritizing drinking water health in rural areas, indicating that purified tap water can enhance cognitive function among older adults.

Associations between frailty and mild cognitive impairment in older adults: Evidence from rural Chiang Mai Province

Thailand entered an aged society phase in 2000, with mild cognitive impairment (MCI) and frailty becoming prevalent among the older adult population. However, no studies have yet examined these issues specifically within rural communities. This study aims to explore the relationship between frailty and MCI among older adults in rural Thailand. It was a cross-sectional study conducted between December 2022 and June 2023. A questionnaire was administered by trained village health volunteers. The survey targeted older adults aged 60 years and above, residing in rural Chiang Mai, Thailand, with those having a history of dementia, depression, and brain injury being excluded from participation. Nine hundred eighty-four participants among the older adults were available for analysis. The mean age was 69.8 (SD 7.9) with 62.2% females (n = 612). The median frequency of exercise was three days (0-7). The prevalence of MCI and frailty among rural older adults in the community was 35.6% (n = 350) and 8% (n = 79), respectively. There were four factors associated with an increased risk of MCI, including age (aOR = 1.07, 95% CI 1.04-1.09, p < 0.001), smoking cigarettes (aOR 1.95, 95% CI 1.27-2.98, p = 0.002), feelings of loneliness (aOR 1.43, 95% CI 1.01-2.03, p = 0.043), and the presence of frailty (aOR 1.92, 95% CI 1.10-3.35, p = 0.022). There were two factors associated with a lower risk of MCI: a higher education level (aOR 0.90, 95% CI 0.86-0.94, p <0.001) and engaging in frequent exercise (aOR 0.9, 95% CI 0.86-0.95, p < 0.001). Frailty exhibited an association with an elevated risk of MCI among older adults in rural communities. Enhancing screening through health volunteers and primary healthcare professionals, coupled with bolstering community-driven health promotion initiatives, becomes imperative.

Long-term exposure to fine particulate matter constituents and cognitive impairment among older adults: An 18-year Chinese nationwide cohort study

BACKGROUND

Although growing evidence has shown independent links of long-term exposure to fine particulate matter (PM2.5) with cognitive impairment, the effects of its constituents remain unclear. This study aims to explore the associations of long-term exposure to ambient PM2.5 constituents' mixture with cognitive impairment in Chinese older adults, and to further identify the main contributor.

METHODS

15,274 adults ≥ 65 years old were recruited by the Chinese Longitudinal Healthy Longevity Study (CLHLS) and followed up through 7 waves during 2000-2018. Concentrations of ambient PM2.5 and its constituents (i.e., black carbon [BC], organic matter [OM], ammonium [NH4+], sulfate [SO42-], and nitrate [NO3-]) were estimated by satellite retrievals and machine learning models. Quantile-based g-computation model was employed to assess the joint effects of a mixture of 5 PM2.5 constituents and their relative contributions to cognitive impairment. Analyses stratified by age group, sex, residence (urban vs. rural), and region (north vs. south) were performed to identify vulnerable populations.

RESULTS

During the average 3.03 follow-up visits (89,296.9 person-years), 4294 (28.1%) participants had developed cognitive impairment. The adjusted hazard ratio [HR] (95% confidence interval [CI]) for cognitive impairment for every quartile increase in mixture exposure to 5 PM2.5 constituents was 1.08 (1.05-1.11). BC held the largest index weight (0.69) in the positive direction in the qg-computation model, followed by OM (0.31). Subgroup analyses suggested stronger associations in younger old adults and rural residents.

CONCLUSION

Long-term exposure to ambient PM2.5, particularly its constituents BC and OM, is associated with an elevated risk of cognitive impairment onset among Chinese older adults.

Sarcopenia and diabetes-induced dementia risk

This study aimed to investigate whether sarcopenia independently increases the risk of diabetes-induced dementia in elderly individuals diagnosed with type 2 diabetes mellitus. The study cohort consisted of a large sample of elderly individuals aged 60 years and above, who were diagnosed with type 2 diabetes mellitus between 2008 and 2018. To minimize potential bias and achieve covariate balance between the sarcopenia and non-sarcopenia groups, we employed propensity score matching. Various statistical analyses, including Cox regression models to assess dementia risk and associations, competing risk analysis to account for mortality and Poisson regression analysis for incidence rates, were used. Before propensity score matching, the study included 406 573 elderly type 2 diabetes mellitus patients, with 20 674 in the sarcopenia group. Following propensity score matching, the analysis included a total of 41 294 individuals, with 20 647 in the sarcopenia group and 20 647 in the non-sarcopenia group. Prior to propensity score matching, elderly type 2 diabetes mellitus patients with sarcopenia exhibited a significantly higher risk of dementia (adjusted hazard ratio: 1.12, 95% confidence interval: 1.07-1.17). After propensity score matching, the risk remained significant (adjusted hazard ratio: 1.14, 95% confidence interval: 1.07-1.21). Incidence rates of dementia were notably higher in the sarcopenia group both before and after propensity score matching, underscoring the importance of sarcopenia as an independent risk factor. Our study highlights sarcopenia as an independent risk factor for diabetes-induced dementia in elderly type 2 diabetes mellitus patients. Advanced age, female gender, lower income levels, rural residency, higher adapted diabetes complication severity index and Charlson Comorbidity Index scores and various comorbidities were associated with increased dementia risk. Notably, the use of statins was linked to a reduced risk of dementia. This research underscores the need to identify and address modifiable risk factors for dementia in elderly type 2 diabetes mellitus patients, offering valuable insights for targeted interventions and healthcare policies.

Identification of high likelihood of dementia in population-based surveys using unsupervised clustering: a longitudinal analysis

BACKGROUND

Dementia is defined as a cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognition and daily function over time. We used unsupervised machine learning and longitudinal data to identify transition to probable dementia.

METHODS

Multiple Factor Analysis was applied to longitudinal function and cognitive data of 15,278 baseline participants (aged 50 years and more) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) (waves 1, 2 and 4-7, between 2004 and 2017). Hierarchical Clustering on Principal Components discriminated three clusters at each wave. We estimated probable or "Likely Dementia" prevalence by sex and age, and assessed whether dementia risk factors increased the risk of being assigned probable dementia status using multistate models. Next, we compared the "Likely Dementia" cluster with self-reported dementia status and replicated our findings in the English Longitudinal Study of Ageing (ELSA) cohort (waves 1-9, between 2002 and 2019, 7840 participants at baseline).

RESULTS

Our algorithm identified a higher number of probable dementia cases compared with self-reported cases and showed good discriminative power across all waves (AUC ranged from 0.754 [0.722-0.787] to 0.830 [0.800-0.861]). "Likely Dementia" status was more prevalent in older people, displayed a 2:1 female/male ratio, and was associated with nine factors that increased risk of transition to dementia: low education, hearing loss, hypertension, drinking, smoking, depression, social isolation, physical inactivity, diabetes, and obesity. Results were replicated in ELSA cohort with good accuracy.

CONCLUSIONS

Machine learning clustering can be used to study dementia determinants and outcomes in longitudinal population ageing surveys in which dementia clinical diagnosis is lacking.

Digital oral health biomarkers for early detection of cognitive decline

BACKGROUND

Oral health could influence cognitive function by stimulating brain activity and blood flow. The quantified oral status from oral inflammation, frailty and masticatory performance were rarely applied to the cognitive function screening. We aimed to adopt non-invasive digital biomarkers to quantify oral health and employ machine learning algorithms to detect cognitive decline in the community.

METHODS

We conducted a prospective case-control study to recruit 196 participants between 50 and 80 years old from Puzi Hospital (Chiayi County, Taiwan) between December 01, 2021, and December 31, 2022, including 163 with normal cognitive function and 33 with cognitive decline. Demographics, daily interactions, electronically stored medical records, masticatory ability, plaque index, oral diadochokinesis (ODK), periodontal status, and digital oral health indicators were collected. Cognitive function was classified, and confirmed mild cognitive impairment diagnoses were used for sensitivity analysis.

RESULTS

The cognitive decline group significantly differed in ODK rate (P = 0.003) and acidity from SILL-Ha (P = 0.04). Younger age, increased social interactions, fewer cariogenic bacteria, high leukocytes, and high buffering capacity led to lower risk of cognitive decline. Patients with slow ODK, high plaque index, variance of hue (VOH) from bicolor chewing gum, and acidity had increased risk of cognitive decline. The prediction model area under the curve was 0.86 and was 0.99 for the sensitivity analysis.

CONCLUSIONS

A digital oral health biomarker approach is feasible for tracing cognitive function. When maintaining oral hygiene and oral health, cognitive status can be assessed simultaneously and early monitoring of cognitive status can prevent disease burden in the future.

Cognitive aging in rural communities: preliminary memory characterization of a community cohort from Southern Nevada

Introduction

Rural-dwelling older adults face unique health challenges that may increase risk for Alzheimer's disease and dementia but are underrepresented in aging research. Here, we present an initial characterization of a rural community cohort compared to an urban cohort from the same region.

Methods

Adults over age 50 living in a non-metropolitan area are clinically characterized using the Uniform Data Set, enriched with additional measures of verbal and non-verbal memory measures. Neighborhood disadvantage is also assessed. Clinical and cognitive differences between cohorts were explored after stratifying by cognitive impairment.

Results

Between group comparisons found that rural-dwellers demonstrated better verbal memory than urban-dwellers on primary indices of learning, recall, and recognition, with small to medium effects in overall comparisons. When stratified by impairment, rural-urban differences were notably larger among cognitively normal individuals. Within-group comparisons found that the magnitude of impairment between cognitively normal and impaired groups was greater among rural-dwellers compared to urban-dwellers. No differences in non-verbal memory or overall clinical status were found, and there were no effects of neighborhood disadvantage on any cognitive measure.

Discussion

Living in a rural community presents a complex set of contextual factors that for some, may increase risk for dementia. In this study, we found small to moderate memory advantages for rural-dwellers, leaving open the possibility that late-life rural living may be advantageous for some and promote resilience. Additional prospective research is critically needed to better understand the factors that influence aging outcomes in this underrepresented population.

Demoralization syndrome and its impact factors among cancer patients in China

PURPOSE

This study aimed to investigate the status of demoralization syndrome among cancer patients and explore the key factors influencing demoralization syndrome.

METHOD

Cross-sectional study design of cancer patients in Xiamen, China. Patients completed the Mandarin version of the Perceived Social Support Scale, Patient-Reported Outcome Measures, The Anderson Symptom Inventory, and the Demoralization Scale.

FINDINGS

187/199 (94%) of patients completed questionnaires. This study found that almost half of the cancer patients in Xiamen, China experience moderate to high levels of demoralization syndrome. Furthermore, the findings indicated that the family residence (Large Urban: b = 2.73, p = 0.02), average monthly income (b=-3.05, p = 0.03), source of income, religiousness (b = 1.37, p = 0.04) and financial toxicity (b = 3.3, p < 0.001), and social support (b = 1.02; p < 0.001) are the influencing factors of cancer patients' demoralization syndrome.

CONCLUSION

These findings emphasize the importance of addressing psychological distress and providing adequate social and financial support for cancer patients to maintain their morale and overall well-being.

Charting the Next Road Map for CSF Biomarkers in Alzheimer's Disease and Related Dementias

Clinical prediction of underlying pathologic substrates in people with Alzheimer's disease (AD) dementia or related dementia syndromes (ADRD) has limited accuracy. Etiologic biomarkers - including cerebrospinal fluid (CSF) levels of AD proteins and cerebral amyloid PET imaging - have greatly modernized disease-modifying clinical trials in AD, but their integration into medical practice has been slow. Beyond core CSF AD biomarkers (including beta-amyloid 1-42, total tau, and tau phosphorylated at threonine 181), novel biomarkers have been interrogated in single- and multi-centered studies with uneven rigor. Here, we review early expectations for ideal AD/ADRD biomarkers, assess these goals' future applicability, and propose study designs and performance thresholds for meeting these ideals with a focus on CSF biomarkers. We further propose three new characteristics: equity (oversampling of diverse populations in the design and testing of biomarkers), access (reasonable availability to 80% of people at risk for disease, along with pre- and post-biomarker processes), and reliability (thorough evaluation of pre-analytical and analytical factors influencing measurements and performance). Finally, we urge biomarker scientists to balance the desire and evidence for a biomarker to reflect its namesake function, indulge data- as well as theory-driven associations, re-visit the subset of rigorously measured CSF biomarkers in large datasets (such as Alzheimer's disease neuroimaging initiative), and resist the temptation to favor ease over fail-safe in the development phase. This shift from discovery to application, and from suspended disbelief to cogent ingenuity, should allow the AD/ADRD biomarker field to live up to its billing during the next phase of neurodegenerative disease research.

Rural-Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45

Background and Objectives

Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural-urban disparities in multimorbidity.

Research Design and Methods

Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011-2018), linked with the full-coverage particulate matter 2.5 (PM2.5) concentration data set (2000-2018) and temperature records (2000-2018). Air pollution was assessed by the moving average of PM2.5 concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural-urban disparities in multimorbidity related to temperature and PM2.5 exposure.

Results

We found the higher PM2.5 concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural-urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM2.5-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM2.5 exposure, but PM2.5 exposure or temperature is not associated with the rate of multimorbidity increase with age.

Discussion and Implications

Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural-urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals.

The factors associated with cognitive function among community-dwelling older adults in Taiwan

BACKGROUND

This research aimed to investigate the associations of anthropometric measurements, physiological parameters, chronic disease comorbidities, and social and lifestyle factors with cognitive function amongst community-dwelling older adults in Taiwan.

METHODS

This was an observational, cross-sectional study involving 4,578 participants at least 65 years old, recruited between January 2008 and December 2018 from the Annual Geriatric Health Examinations Program. Cognitive function was assessed using the short portable mental state questionnaire (SPMSQ). Multivariable logistic regression was done to analyze the factors associated with cognitive impairment.

RESULTS

Among the 4,578 participants, 103 people (2.3%) with cognitive impairment were identified. Associated factors were age (odds ratio (OR) = 1.16, 95% confidence interval (CI) = 1.13,1.20), male gender (OR = 0.39, 95% CI = 0.21,0.72), diabetes mellitus (DM) (OR = 1.70, 95% CI = 1.03, 2.82), hyperlipidemia (OR = 0.47, 95% CI = 0.25, 0.89), exercise (OR = 0.44, 95% CI = 0.34, 0.56), albumin (OR = 0.37, 95% CI = 0.15, 0.88), and high-density lipoprotein (HDL) (OR = 0.98, 95% CI = 0.97, 1.00). Whereas waistline, alcohol intake in recent six months, and hemoglobin was not significantly associated with cognitive impairment (all p > 0.05).

CONCLUSIONS

Our findings suggested that people with older age and a history of DM had a higher risk of cognitive impairment. Male gender, a history of hyperlipidemia, exercise, a high albumin level, and a high HDL level seemed to be associated with a lower risk of cognitive impairment amongst older adults.

Identification of High Likelihood of Dementia in Population-Based Surveys using Unsupervised Clustering: a Longitudinal Analysis

Background

Dementia is defined by cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognitive and function over time. We used unsupervised machine learning and longitudinal data to identify transition to probable dementia.

Methods

Multiple Factor Analysis was applied to longitudinal function and cognitive data of 15,278 baseline participants (aged 50 years and more) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) (waves 1, 2 and 4-7, between 2004 and 2017). Hierarchical Clustering on Principal Components discriminated three clusters at each wave. We estimated probable or "Likely Dementia" prevalence by sex and age, and assessed whether dementia risk factors increased the risk of being assigned probable dementia status using multistate models. Next, we compared the "Likely Dementia" cluster with self-reported dementia status and replicated our findings in the English Longitudinal Study of Ageing (ELSA) cohort (waves 1-9, between 2002 and 2019, 7,840 participants at baseline).

Findings

Our algorithm identified a higher number of probable dementia cases compared with self-reported cases and showed good discriminative power across all waves (AUC ranged from 0.754 [0.722-0.787] to 0.830 [0.800-0.861]). "Likely Dementia" status was more prevalent in older people, displayed a 2:1 female/male ratio and was associated with nine factors that increased risk of transition to dementia: low education, hearing loss, hypertension, drinking, smoking, depression, social isolation, physical inactivity, diabetes, and obesity. Results were replicated in ELSA cohort with good accuracy.

Interpretation

Machine learning clustering can be used to study dementia determinants and outcomes in longitudinal population ageing surveys in which dementia clinical diagnosis is lacking.

Mortality of Alzheimer's Disease and Other Dementias in China: Past and Future Decades

Objectives: This study aimed to explore the distribution features and trends of dementia mortality in China from 2011 to 2020 and make a prediction for the next decade. Methods: Mortality-relevant data were gathered from the Chinese Center for Disease Control and Prevention's Disease Surveillance Points system. Joinpoint regression was applied to evaluate the trends. Results: Crude Mortality Rate (CMR) of AD and other dementias increased from 3.7 per 100,000 to 6.2 per 100,000 in 2011-2020, with an Average Annual Percent Change (AAPC) of 5.3% (95% CI 4.4%-6.3%). Age-Standardized Mortality Rate (ASMR) slightly decreased from 5.0 per 100,000 to 4.1 per 100,000 in 2011-2020, with AAPC of -0.4% (95% CI -2.5%-1.8%). CMR will increase to 9.66 per 100,000 while ASMR will decline to 3.42 per 100,000 in the following decade. Conclusion: The upward trend in CMR and downward trend in ASMR suggested the further development of population aging and dementia mortality in the past and future decades. In China, there were gender, urban-rural, regional and age differences.

Education, neighborhood environment, and cognitive decline: Findings from two prospective cohort studies of older adults in China

INTRODUCTION

The impacts of education on cognitive decline across different neighborhood environments (NEs) have rarely been studied.

METHODS

We investigated and compared the associations between educational attainment and cognitive decline using data of 1286 participants from the Taizhou Imaging Study (TIS) and the Shanghai Aging Study (SAS).

RESULTS

Compared with low-educated participants, in TIS with disadvantaged NE, high-educated participants manifested a significantly slower decline in global cognition (.062 Z score per year, P < .001), memory (.054 Z score per year, P < .05), and attention (.065 Z score per year, P < .01), whereas in SAS with advanced NE, highly educated individuals exhibited a slower decline only in attention (.028 Z score per year, P < .05).

DISCUSSION

We observed the additive effect of educational attainment and NE on cognitive decline in older adults. Education is especially important for maintaining cognitive health in a disadvantaged environment.

Prevalence and correlates of suspected dementia in older adults receiving primary healthcare in Wuhan, China: A multicenter cross-sectional survey

Background

Integrating the management of dementia into primary healthcare is a cost-effective way to reduce the burden of dementia but the clinical epidemiology of dementia in primary healthcare settings remains unclear. This study investigated the prevalence and correlates of suspected dementia in Chinese older adults receiving primary healthcare.

Methods

In this multicenter cross-sectional survey, a total of 773 older adults (≥65 years) were consecutively recruited from seven urban and six rural primary care clinics in Wuhan, China, and interviewed with the validated Chinese version of the Brief Community Screening Instrument for Dementia (BCSI-D). Participants with suspected dementia were those who were screened positive on the BCSI-D.

Results

The prevalence of suspected dementia in older primary healthcare adults was 26.8%. Factors significantly associated with suspected dementia were female sex (OR = 1.95, P < 0.001), age-group of 75+ (OR = 1.68, P = 0.004), poor financial status (OR = 4.79, P < 0.001), rural residence (OR = 1.47, P = 0.032), no regular physical exercise (OR = 1.74, P = 0.002), and stroke and other cerebrovascular diseases (OR = 1.97, P = 0.015).

Conclusions

Chinese older adults receiving primary healthcare are at high risk of suspected dementia. Screening and intervention efforts for dementia in primary healthcare settings may be more useful to target older adults who are women, are 75 years and above, have poor economic status, are rural residents, have no exercise habit, and suffer from cerebrovascular diseases.

Association Between Young-Onset Dementia and Risk of Hospitalization for Motor Vehicle Crash Injury in Taiwan

IMPORTANCE

Several studies have suggested that older-onset dementia is associated with an increased risk of motor vehicle crash injury (MVCI). However, evidence of an association between young-onset dementia and the risk of MVCI is insufficient, particularly in Asia.

OBJECTIVE

To investigate the association between young-onset dementia and MVCI-related hospitalization in Taiwan.

DESIGN, SETTING, AND PARTICIPANTS

In this nationwide, population-based cohort study in Taiwan, a cohort of 39 344 patients aged 40 to 64 years with incident dementia diagnosed between 2006 and 2012 was matched 1:1 with a cohort of participants without dementia by age, sex, and index year (initial diagnosis of dementia). Participants were identified from Taiwan's National Health Insurance Research Database (NHIRD). Data were analyzed between March 25 and October 22, 2021.

EXPOSURES

Dementia, defined by International Classification of Diseases, Ninth Revision, Clinical Modification codes.

MAIN OUTCOMES AND MEASURES

Hospitalization for MVCI, determined using linked data from Taiwan's Police-Reported Traffic Accident Registry and the NHIRD from January 1, 2003, to December 31, 2015. Hazard ratios (HRs) for MVCI-related hospitalization were estimated using Cox proportional hazards regression models adjusted for sex, age, salary-based insurance premium, urbanization level, and comorbidities.

RESULTS

Of the 78 688 participants, 47 034 (59.8%) were male; the mean (SD) age was 54.5 (7.4) years. During the 10-year follow-up period, the incidence density of MVCI-related hospitalization was 45.58 per 10 000 person-years (95% CI, 42.77-48.39 per 10 000 person-years) among participants with dementia and 24.10 per 10 000 person-years (95% CI, 22.22-25.99 per 10 000 person-years) among participants without dementia. Compared with participants without dementia, patients with young-onset dementia were at higher risk of MVCI-related hospitalization (adjusted HR [aHR], 1.83; 95% CI, 1.63-2.06), especially those in younger age groups (aged 40-44 years: aHR, 3.54; 95% CI, 2.48-5.07) and within a shorter period (within 1 year of follow-up: aHR, 3.53; 95% CI, 2.50-4.98) after dementia was diagnosed. Patients with young-onset dementia also had a higher risk of being a pedestrian when the crash occurred (aHR, 2.89; 95% CI, 2.04-4.11), having an intracranial or internal injury (aHR, 2.44; 95% CI, 2.02-2.94), and having a severe injury (aHR, 2.90; 95% CI, 2.16-3.89).

CONCLUSIONS AND RELEVANCE

In this retrospective cohort study, patients in Taiwan with a diagnosis of young-onset dementia had a higher risk of MVCI-related hospitalization than did individuals without dementia and the risk varied by age, disease duration, transport mode, injury type, and injury severity. These findings suggest a need for the planning of strategies to prevent transportation crashes among patients with young-onset dementia.

Predicting the long-term cognitive trajectories using machine learning approaches: A Chinese nationwide longitudinal database

OBJECTIVES

This study aimed to explore the long-term cognitive trajectories and its' determinants, and construct prediction models for identifying high-risk populations with unfavorable cognitive trajectories.

METHODS

This study included 3502 older adults aged 65-105 years at their first observations in a 16-year longitudinal cohort study. Cognitive function was measured by the Chinese version Mini Mental State Examination. The heterogeneity of cognitive function was identified through mixed growth model. Machine learning algorithms, namely regularized logistic regression (r-LR), support vector machine (SVM), random forest (RF), and super learner (SL) were used to predict cognitive trajectories. Discrimination and calibration metrics were used for performance evaluation.

RESULTS

Two distinct trajectories were identified according to the changes of MMSE scores: intact cognitive functioning (93.6%), and dementia (6.4%). Older age, female gender, Han ethnicity, having no schooling, rural residents, low-frequency leisure activities, and low baseline BADL score were associated with a rapid decline in cognitive function. r-LR, SVM, and SL performed well in predicting cognitive trajectories (Sensitivity: 0.73, G-mean: 0.65). Age and psychological well-being were key predictors.

CONCLUSION

Two cognitive trajectories were identified among older Chinese, and the identified key factors could be targeted for constructing early risk prediction models.

The complex burden of determining prevalence rates of mild cognitive impairment: A systematic review

Mild cognitive impairment (MCI) is a syndrome characterized by a decline in cognitive performance greater than expected for an individual's age and education level, but that does not interfere much with daily life activities. Establishing the prevalence of MCI is very important for both clinical and research fields. In fact, in a certain percentage of cases, MCI represents a prodromal condition for the development of dementia. Accordingly, it is important to identify the characteristics of MCI that allow us to predict the development of dementia. Also, initial detection of cognitive decline can allow the early implementation of prevention programs aimed at counteracting or slowing it down. To this end, it is important to have a clear picture of the prevalence of MCI and, consequently, of the diagnostic criteria used. According to these issues, this systematic review aims to analyze MCI prevalence, exploring the methods for diagnosing MCI that determine its prevalence. The review process was conducted according to the PRISMA statement. Three thousand one hundred twenty-one international articles were screened, and sixty-six were retained. In these studies, which involved 157,035 subjects, the prevalence of MCI ranged from 1.2 to 87%. The review results showed a large heterogeneity among studies due to differences in the subjects' recruitment, the diagnostic criteria, the assessed cognitive domains, and other methodological aspects that account for a higher range of MCI prevalence. This large heterogeneity prevents drawing any firm conclusion about the prevalence of MCI.

Risk of Dementia in Patients Who Underwent Surgery under Neuraxial Anesthesia: A Nationwide Cohort Study

The incidence of dementia in patients with surgery under neuraxial anesthesia and the possibility of surgery under neuraxial anesthesia as a risk factor for dementia were investigated. We performed a retrospective matched cohort study with nationwide, representative cohort sample data of the Korean National Health Insurance Service in South Korea between 1 January 2003, and 31 December 2004. The participants were divided into control (n = 4488) and neuraxial groups (n = 1122) using propensity score matching. After 9 years of follow-up, the corresponding incidences of dementia were 11.5 and 14.8 cases per 1000 person-years. The risk of dementia in the surgery under neuraxial group was 1.44-fold higher (95% confidence interval [95%CI], 1.17-1.76) than that in the control group. In the subgroup analysis of dementia, the risk of Alzheimer's disease in those who underwent surgery under neuraxial anesthesia was 1.48-fold higher (95%CI, 1.17-1.87) than that in those who did not undergo surgery under anesthesia. Our findings suggest that patients who underwent surgery under neuraxial anesthesia had a higher risk of dementia and Alzheimer's disease than those who did not undergo surgery under neuraxial anesthesia.

Burden and correlates of cognitive impairment among hypertensive patients in Tanzania: a cross-sectional study

BACKGROUND

The evolution of cognitive impairment of vascular origin is increasingly becoming a prominent health threat particularly in this era where hypertension is the leading contributor of global disease burden and overall health loss. Hypertension is associated with the alteration of the cerebral microcirculation coupled by unfavorable vascular remodeling with consequential slowing of mental processing speed, reduced abstract reasoning, loss of linguistic abilities, and attention and memory deficits. Owing to the rapidly rising burden of hypertension in Tanzania, we sought to assess the prevalence and correlates of cognitive impairment among hypertensive patients attending a tertiary cardiovascular hospital in Tanzania.

METHODOLOGY

A hospital-based cross-sectional study was conducted at Jakaya Kikwete Cardiac Institute, a tertiary care public teaching hospital in Dar es Salaam, Tanzania between March 2020 and February 2021. A consecutive sampling method was utilized to recruit consented hypertensive outpatients during their scheduled clinic visit. General Practitioner Assessment of Cognition (GPCOG) Score was utilized in the assessment of cognitive functions. All statistical analyses utilized STATA v11.0 software. Pearson Chi square and Student's T-test were used to compare categorical and continuous variables respectively. Logistic regression analyses were used to assess for factors associated with cognitive impairment. Odd ratios with 95% confidence intervals and p-values are reported. All tests were 2-sided and p < 0.05 was used to denote a statistical significance.

RESULTS

A total of 1201 hypertensive patients were enrolled in this study. The mean age was 58.1 years and females constituted nearly two-thirds of the study population. About three quarters had excess body weight, 16.6% had diabetes, 7.7% had history of stroke, 5.7% had heart failure, 16.7% had renal dysfunction, 53.7% had anemia, 27.7% had hypertriglyceridemia, 38.5% had elevated LDL, and 2.4% were HIV-infected. Nearly two-thirds of participants had uncontrolled blood pressure and 8.7% had orthostatic hypotension. Overall, 524 (43.6%) of participants had cognitive impairment. During bivariate analysis in a logistic regression model of 16 characteristics, 14 parameters showed association with cognitive functions. However, after controlling for confounders, multivariate analysis revealed ≤primary education (OR 3.5, 95%CI 2.4-5.2, p < 0.001), unemployed state (OR 1.7, 95%CI 1.2-2.6, p < 0.01), rural habitation (OR 1.8, 95%CI 1.1-2.9, p = 0.01) and renal dysfunction (OR 1.7, 95%CI 1.0-2.7, p = 0.04) to have independent association with cognitive impairment.

CONCLUSION

This present study underscore that cognitive decline is considerably prevalent among individuals with systemic hypertension. In view of this, it is pivotal to incorporate cognitive assessment in routine evaluation of hypertensive patients.