A Late Life Risk Index for Severe Cognitive Impairment in Mexico

Population-level trends in self-reported healthcare utilization among older adults in Mexico with and without cognitive impairment

BACKGROUND

Older adults with cognitive impairment exhibit different patterns of healthcare utilization compared to their cognitively healthy counterparts. Despite extensive research in high-income countries, similar studies in low- and middle-income countries are lacking. This study aims to investigate the population-level patterns in healthcare utilization among older adults with and without cognitive impairment in Mexico.

METHODS

Data came from five waves (2001-2018) of the Mexican Health and Aging Study. We used self-reported measures for one or more over-night hospital stays, doctor visits, visits to homeopathic doctors, and dental visits in the past year; seeing a pharmacist in the past year; and being screened for cholesterol, diabetes, and hypertension in the past two years. Cognitive impairment was defined using a modified version of the Cross Cultural Cognitive Examination that assessed verbal memory, visuospatial and visual scanning. Total sample included 5,673 participants with cognitive impairment and 34,497 without cognitive impairment interviewed between 2001 and 2018. Generalized Estimating Equation models that adjusted for time-varying demographic and health characteristics and included an interaction term between time and cognitive status were used.

RESULTS

For all participants, the risk for one or more overnight hospital stays, doctor visits, and dental visits in the past year, and being screened for diabetes, hypertension, and high cholesterol increased from 2001 to 2012 and leveled off or decreased in 2015 and 2018. Conversely, seeing a homeopathic doctor decreased. Cognitive impairment was associated with higher risk of hospitalization (RR = 1.13, 1.03-1.23) but lower risk of outpatient services (RR = 0.95, 0.93-0.97), cholesterol screening (RR = 0.93, 0.91-0.96), and diabetes screening (RR = 0.95, 0.92-0.97). No significant difference was observed in the use of pharmacists, homeopathic doctors, or folk healers based on cognitive status. Interaction effects indicated participants with cognitive impairment had lower risk for dental visits and hypertension screening but that these trajectories differed over time compared to participants without cognitive impairment.

CONCLUSIONS

We identified distinct population-level trends in self-reported healthcare utilization and differences according to cognitive status, particularly for elective and screening services. These findings highlight the necessity for policy interventions to ensure older adults with cognitive impairment have their healthcare needs met.

What's New in Dementia Risk Prediction Modelling? An Updated Systematic Review

Introduction

Identifying individuals at high risk of dementia is critical to optimized clinical care, formulating effective preventative strategies, and determining eligibility for clinical trials. Since our previous systematic reviews in 2010 and 2015, there has been a surge in dementia risk prediction modelling. The aim of this study was to update our previous reviews to explore, and critically review, new developments in dementia risk modelling.

Methods

MEDLINE, Embase, Scopus, and Web of Science were searched from March 2014 to June 2022. Studies were included if they were population- or community-based cohorts (including electronic health record data), had developed a model for predicting late-life incident dementia, and included model performance indices such as discrimination, calibration, or external validation.

Results

In total, 9,209 articles were identified from the electronic search, of which 74 met the inclusion criteria. We found a substantial increase in the number of new models published from 2014 (>50 new models), including an increase in the number of models developed using machine learning. Over 450 unique predictor (component) variables have been tested. Nineteen studies (26%) undertook external validation of newly developed or existing models, with mixed results. For the first time, models have also been developed in low- and middle-income countries (LMICs) and others validated in racial and ethnic minority groups.

Conclusion

The literature on dementia risk prediction modelling is rapidly evolving with new analytical developments and testing in LMICs. However, it is still challenging to make recommendations about which one model is the most suitable for routine use in a clinical setting. There is an urgent need to develop a suitable, robust, validated risk prediction model in the general population that can be widely implemented in clinical practice to improve dementia prevention.

Multi-domain prognostic models used in middle-aged adults without known cognitive impairment for predicting subsequent dementia

BACKGROUND

Dementia, a global health priority, has no current cure. Around 50 million people worldwide currently live with dementia, and this number is expected to treble by 2050. Some health conditions and lifestyle behaviours can increase or decrease the risk of dementia and are known as 'predictors'. Prognostic models combine such predictors to measure the risk of future dementia. Models that can accurately predict future dementia would help clinicians select high-risk adults in middle age and implement targeted risk reduction.

OBJECTIVES

Our primary objective was to identify multi-domain prognostic models used in middle-aged adults (aged 45 to 65 years) for predicting dementia or cognitive impairment. Eligible multi-domain prognostic models involved two or more of the modifiable dementia predictors identified in a 2020 Lancet Commission report and a 2019 World Health Organization (WHO) report (less education, hearing loss, traumatic brain injury, hypertension, excessive alcohol intake, obesity, smoking, depression, social isolation, physical inactivity, diabetes mellitus, air pollution, poor diet, and cognitive inactivity). Our secondary objectives were to summarise the prognostic models, to appraise their predictive accuracy (discrimination and calibration) as reported in the development and validation studies, and to identify the implications of using dementia prognostic models for the management of people at a higher risk for future dementia.

SEARCH METHODS

We searched MEDLINE, Embase, PsycINFO, CINAHL, and ISI Web of Science Core Collection from inception until 6 June 2022. We performed forwards and backwards citation tracking of included studies using the Web of Science platform.  SELECTION CRITERIA: We included development and validation studies of multi-domain prognostic models. The minimum eligible follow-up was five years. Our primary outcome was an incident clinical diagnosis of dementia based on validated diagnostic criteria, and our secondary outcome was dementia or cognitive impairment determined by any other method.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened the references, extracted data using a template based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS), and assessed risk of bias and applicability of included studies using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). We synthesised the C-statistics of models that had been externally validated in at least three comparable studies.  MAIN RESULTS: We identified 20 eligible studies; eight were development studies and 12 were validation studies. There were 14 unique prognostic models: seven models with validation studies and seven models with development-only studies. The models included a median of nine predictors (range 6 to 34); the median number of modifiable predictors was five (range 2 to 11). The most common modifiable predictors in externally validated models were diabetes, hypertension, smoking, physical activity, and obesity. In development-only models, the most common modifiable predictors were obesity, diabetes, hypertension, and smoking. No models included hearing loss or air pollution as predictors. Nineteen studies had a high risk of bias according to the PROBAST assessment, mainly because of inappropriate analysis methods, particularly lack of reported calibration measures. Applicability concerns were low for 12 studies, as their population, predictors, and outcomes were consistent with those of interest for this review. Applicability concerns were high for nine studies, as they lacked baseline cognitive screening or excluded an age group within the range of 45 to 65 years. Only one model, Cardiovascular Risk Factors, Ageing, and Dementia (CAIDE), had been externally validated in multiple studies, allowing for meta-analysis. The CAIDE model included eight predictors (four modifiable predictors): age, education, sex, systolic blood pressure, body mass index (BMI), total cholesterol, physical activity and APOEƐ4 status. Overall, our confidence in the prediction accuracy of CAIDE was very low; our main reasons for downgrading the certainty of the evidence were high risk of bias across all the studies, high concern of applicability, non-overlapping confidence intervals (CIs), and a high degree of heterogeneity. The summary C-statistic was 0.71 (95% CI 0.66 to 0.76; 3 studies; very low-certainty evidence) for the incident clinical diagnosis of dementia, and 0.67 (95% CI 0.61 to 0.73; 3 studies; very low-certainty evidence) for dementia or cognitive impairment based on cognitive scores. Meta-analysis of calibration measures was not possible, as few studies provided these data.

AUTHORS' CONCLUSIONS

We identified 14 unique multi-domain prognostic models used in middle-aged adults for predicting subsequent dementia. Diabetes, hypertension, obesity, and smoking were the most common modifiable risk factors used as predictors in the models. We performed meta-analyses of C-statistics for one model (CAIDE), but the summary values were unreliable. Owing to lack of data, we were unable to meta-analyse the calibration measures of CAIDE. This review highlights the need for further robust external validations of multi-domain prognostic models for predicting future risk of dementia in middle-aged adults.

Effect of Demographic and Health Dynamics on Cognitive Status in Mexico between 2001 and 2015: Evidence from the Mexican Health and Aging Study

Sources of health disparities such as educational attainment, cardiovascular risk factors, and access to health care affect cognitive impairment among older adults. To examine the extent to which these counteracting changes affect cognitive aging over time among Mexican older adults, we examine how sociodemographic factors, cardiovascular diseases, and their treatment relate to changes in cognitive function of Mexican adults aged 60 and older between 2001 and 2015. Self and proxy respondents were classified as dementia, cognitive impairment no dementia (CIND), and normal cognition. We use logistic regression models to examine the trends in dementia and CIND for men and women aged 60 years or older using pooled national samples of 6822 individuals in 2001 and 10,219 in 2015, and sociodemographic and health variables as covariates. We found higher likelihood of dementia and a lower risk of CIND in 2015 compared to 2001. These results remain after adjusting for sociodemographic factors, cardiovascular diseases, and their treatment. The improvements in educational attainment, treatment of diabetes and hypertension, and better access to health care in 2015 compared to 2001 may not have been enough to counteract the combined effects of aging, rural residence disadvantage, and higher risks of cardiovascular disease among older Mexican adults.

Risk Factors for Incident Dementia Among Older Cubans

Introduction: Little is known about risk factors of dementia in Latin American countries. We aimed to identify socio–demographic, health and lifestyle risk factors of incident dementia in Cuban older adults.

Methods: Data were from 1,846 participants in the Cuban cohort of the 10/66 Dementia Research Group. Participants completed questionnaires, health examinations, and cognitive tests at baseline (2003–2006) and 4.5 years later (2007–2010). Associations between risk factors (baseline) and incident dementia (follow-up) were examined using logistic regression.

Results: Just over 9% of participants developed dementia. Overall, older age and low physical activity were associated with incident dementia. In those 65–74 years of age, depression, stroke and low physical activity were associated with incident dementia. In those ≥75 years of age, low physical activity, never eating fish, and smoking were associated with incident dementia.

Conclusions: Modifiable lifestyle factors play an important role in developing dementia in Cuban older adults. This knowledge opens up opportunities for preventive strategies.

The Mexican Cognitive Aging Ancillary Study (Mex-Cog): Study Design and Methods

OBJECTIVE

Describe the protocol sample and instruments of the Cognitive Aging Ancillary Study in Mexico (Mex-Cog). The study performs an in-depth cognitive assessment in a subsample of older adults of the ongoing Mexican Health and Aging Study (MHAS). The Mex-Cog is part of the Harmonized Cognitive Assessment Protocol (HCAP) design to facilitate cross-national comparisons of the prevalence and trends of dementia in aging populations around the world, funded by the National Institute on Aging (NIA).

METHODS

The study protocol consists of a cognitive assessment instrument for the target subject and an informant questionnaire. All cognitive measures were selected and adapted by a team of experts from different ongoing studies following criteria to warrant reliable and comparable cognitive instruments. The informant questionnaire is from the 10/66 Dementia Study in Mexico.

RESULTS

A total of 2,265 subjects aged 55-104 years participated, representing a 70% response rate. Validity analyses showed the adequacy of the content validity, proper quality-control procedures that sustained data integrity, high reliability, and internal structure.

CONCLUSIONS

The Mex-Cog study provides in-depth cognitive data that enhances the study of cognitive aging in two ways. First, linking to MHAS longitudinal data on cognition, health, genetics, biomarkers, economic resources, health care, family arrangements, and psychosocial factors expands the scope of information on cognitive impairment and dementia among Mexican adults. Second, harmonization with other similar studies around the globe promotes cross-national studies on cognition with comparable data. Mex-Cog data is publicly available at no cost to researchers.

The effect of educational attainment on cognition of older adults: results from the Mexican Health and Aging Study 2001 and 2012

Objective: This paper seeks to document changes in the effect of educational attainment on cognitive function of older adults in Mexico, and measure gender differences using data from two time periods. Methods: The data come from the Mexican Health and Aging Study (MHAS), taking the cross-sections of adults aged 60 years or older interviewed in 2001 and 2012. We perform an OLS regression using standardized z-scores for five individual cognitive domains and for total cognition. Results: Total cognitive scores and educational attainment were higher for men than women in both years. When cognitive components were analyzed separately, women had higher verbal memory and verbal recall scores than men. The gender gap in overall cognition score was smaller in 2012 compared to 2001, while the gender gap in educational attainment was larger in 2012 than in 2001. Even though men had higher educational attainment than women, the effect of educational attainment on cognition was higher for women. Similarly, the difference between total scores for each task for men compared to women decreased between 2012 and 2001, except for verbal learning and verbal recall where the gender difference widened. Conclusions: If younger cohorts of women continue to progressively achieve higher levels of education, the gender gap in old-age cognition should close. Additional work should determine the mechanisms through which added formal education seems to translate into higher cognitive gains for women compared to men.

Combining modifiable risk factors and risk of dementia: a systematic review and meta-analysis

OBJECTIVE

To systematically review the literature relating to the impact of multiple co-occurring modifiable risk factors for cognitive decline and dementia.

DESIGN

A systematic review and meta-analysis of the literature relating to the impact of co-occurring key risk factors for incident cognitive decline and dementia. All abstracts and full text were screened independently by two reviewers and each article assessed for bias using a standard checklist. A fixed effects meta-analysis was undertaken.

DATA SOURCES

Databases Medline, Embase and PsycINFO were searched from 1999 to 2017.

ELIGIBILITY CRITERIA

For inclusion articles were required to report longitudinal data from participants free of cognitive decline at baseline, with formal assessment of cognitive function or dementia during follow-up, and an aim to examine the impact of additive or clustered comorbid risk factor burden in with two or more core modifiable risk factors.

RESULTS

Seventy-nine full-text articles were examined. Twenty-two articles (18 studies) were included reporting data on >40 000 participants. Included studies consistently reported an increased risk associated with greater numbers of intraindividual risk factors or unhealthy behaviours and the opposite for healthy or protective behaviours. A meta-analysis of studies with dementia outcomes resulted in a pooled relative risk for dementia of 1.20 (95% CI 1.04 to 1.39) for one risk factor, 1.65 (95% CI 1.40 to 1.94) for two and 2.21 (95% CI 1.78 to 2.73) for three or more, relative to no risk factors. Limitations include dependence on published results and variations in study outcome, cognitive assessment, length of follow-up and definition of risk factor exposure.

CONCLUSIONS

The strength of the reported associations, the consistency across studies and the suggestion of a dose response supports a need to keep modifiable risk factor exposure to a minimum and to avoid exposure to additional modifiable risks. Further research is needed to establish whether particular combinations of risk factors confer greater risk than others.

PROSPERO REGISTRATION NUMBER

42016052914.