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Chin Med J (Engl)
Chin Med J (Engl)
CM9
Chinese Medical Journal
0366-6999
2542-5641
Lippincott Williams & Wilkins Hagerstown, MD

39118213
CMJ-2024-055
10.1097/CM9.0000000000003241
00010
3
Rapid Report
A comprehensive index to evaluate cognitive health at the population scale
Lu Yuanyuan 1
Mao Fan 2
Yin Peng 3
Chang Jie 4
Zhao Zhenping 5
Yang Kun 4
Qin Qi 1
Zhou Maigeng 6
Tang Yi 1
Gao Ting
1 Department of Neurology and Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing 100050, China
2 Department on Obesity and Metabolic Diseases Control and Prevention, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
3 Department on Vital Registry and Mortality Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
4 National Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, Beijing 100050, China
5 Department on Risk Factors Surveillance, National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
6 National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
Correspondence to: Maigeng Zhou, National Centre for Chronic and Non-communicable Disease Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing 100050, China E-Mail: zhoumaigeng@ncncd.chinacdc.cn;
Yi Tang, Department of Neurology and Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing 100050, China E-Mail: tangyi@xwhosp.org
09 8 2024
20 9 2024
137 18 22332235
06 1 2024
Copyright © 2024 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license.
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

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pmcCognitive health is a major determinant of human survival and quality of life. As an increasing proportion of the global population reaches old age (defined as 60 years and older), dementia has become a public health and social care priority.[1] China contains about 15.07 million people with dementia, accounting for 25% of the world’s total dementia population.[2] Due to a relatively high proportion of individuals reaching old age, China is expected to have the sharpest increase in dementia cases of any country over the next few decades, causing ever-greater social and economic impacts.

The 2020 Report of the Lancet Commission stated that modifiable dementia risk factors and other appropriate interventions could delay or prevent the onset of about 40% of dementia cases worldwide.[3] Because there is no cure for dementia, many national strategies currently emphasize early prevention, detection, and management of cognitive disorders before they reach the threshold for classification as dementia. In the Global Action Plan on the Public Health Response to Dementia 2017–2025, the World Health Organization (WHO) encouraged actions that substantially improve dementia diagnoses, treatment, and support, aiming to reduce premature mortality from dementia by 25% as of 2025.[4]

Guidelines and strategies such as those released by the WHO are undoubtedly critical in minimizing dementia cases. However, many barriers to implementation remain, hindering progress in dementia prevention and control, particularly in low- and middle-income countries (LMICs). Indeed, progress toward the WHO target was so limited that there were proposals for the effort to be extended to 2029. Barriers to the implementation of these strategies include insufficient medical resources, regional resource imbalances, ambiguous intervention priorities, inadequately detailed guidance, and untimely policy adjustment due to a lack of dynamic intervention outcome evaluations.

To address these unmet needs, medical institutions including the National Center for Neurological Disorders, the National Center for Chronic and Non-communicable Disease Control and Prevention, the Chinese Center for Disease Control and Prevention (CDC), and health administration departments here jointly established the China Brain Cognitive Health Index (BCHI) based on a comprehensive set of representative data collected from Chinese officials. We then applied the BCHI to evaluate strategies for dementia prevention and management throughout China.

The China BCHI was constructed based on literature review, expert panel discussion, and two rounds of Delphi expert consultation [Supplementary Figure 1, http://links.lww.com/CM9/C101]. A literature review was first performed to establish potential indicators and descriptions for preliminary evaluation.[3,5] A total of 48 indicators were initially proposed by the research team. The relevant indicators were incorporated into a candidate indicator pool, from which each indicator was classified into one of four dimensions: prevalence and disease burden of dementia; risk factor exposure levels; risk factor prevention and control; or diagnosis and treatment of dementia. A second-level and third-level classification scheme was also established to form indicator subcategories.

The Delphi method was then used to assess the indicators, with 29 external experts selecting indicators based on principles such as importance, measurability, and accessibility. Collectively, the experts were highly trained in multiple disciplines and academic fields, including staff from the Chinese CDC and the Provincial CDC, physicians engaged in dementia diagnosis and treatment in grade A tertiary hospitals, and university professionals. After two rounds of Delphi expert consultation [Supplementary Figure 2, http://links.lww.com/CM9/C101], the China BCHI system was constructed, containing 36 indicators classified into four dimensions [Supplementary Table 1, http://links.lww.com/CM9/C101].

The weight of each indicator was determined through the analytical hierarchy process (AHP). In the AHP evaluation, a total of 16 judgment matrices were developed based on the “tree” structure of the indicator classification system. These matrices were completed by 10 senior experts specializing in the prevention or treatment of dementia. The weight of each indicator and dimension was calculated for each expert based on their judgment matrices. The average weight of each indicator and dimension (calculated from the scores of the 10 experts) was used as the final weight for that indicator or dimension. AHP results at the dimension level gave the highest weight to risk factor prevention and control (0.3382), followed by diagnosis and treatment of dementia (0.3250), then the prevalence and burden of dementia (0.1894); the lowest weight was given to risk factor exposure levels (0.1474). The third-level indicators with the five highest weights were prevalence of Alzheimer’s disease and other types of dementia (A01) (0.0704), disability-adjusted life years for those with Alzheimer’s disease and other types of dementia (A03) (0.0697), successful smoking cessation rate (C01) (0.0577), proportion of hospitals with ancillary examinations to assess cognitive impairment (D06) (0.0534), and mortality rates for Alzheimer’s disease and other types of dementia (A02) (0.0493); the third-level indicators with the five lowest weights were prevalence of dyslipidemia (B11) (0.0044), prevalence of obesity (B08) (0.0063), prevalence of cardiovascular disease (B12) (0.0073), prevalence of hypertension (B09) (0.0074), and prevalence of diabetes (B10) (0.0081) [Supplementary Table 2, http://links.lww.com/CM9/C101].

With the indicators and weights established, we collected the available relevant scientific and authoritative data at the sub-national level from national surveys, research projects, statistical yearbooks, and national societies, associations, and registers to calculate BCHI values for the country as a whole and for the provincial level administrative divisions (PLADs). The data covers 31 PLADs except for Taiwan, Hong Kong, and Macau. A total of six sources were selected for collection of original data relating to each indicator: the provincial burden of disease study, the national census, surveillance of chronic disease and risk factors in China (CDRFS), the China Health and Retirement Longitudinal Study (CHARLS), the China Health Statistics Yearbook, and the cognitive center construction project [Supplementary Table 1, http://links.lww.com/CM9/C101]. The scores of the 31 PLADs were calculated. PLADs were classified into three categories for each BCHI indicator: best-performing, moderately performing, and worst-performing [Supplementary Figure 3, http://links.lww.com/CM9/C101]. We next used all of the selected indicators to calculate BCHI for each of the 31 PLADs. Beijing had the highest score (61.31); this was far higher than the second- and third-highest-scoring PLADs, Jiangsu (51.48) and Hubei (50.87). The three lowest-scoring PLADs were Hebei (41.61), Guangxi (43.40), and Jilin (43.82). The average score across the 31 PLADs was 47.39, and a total of 18 PLADs (58%) scored lower than the average [Supplementary Table 3, http://links.lww.com/CM9/C101]. The sub-national rankings of BCHI secondary indicators are shown in Supplementary Table 4, http://links.lww.com/CM9/C101. This study was conducted from February 1 to May 20, 2023.

BCHI is a comprehensive index system to evaluate cognitive health across China and in specific PLADs, which providing a critical foundation for guiding national health strategies and informing optimal healthcare resource allocation. Three primary concerns guided the development of the BCHI. The primary concern was to ensure that the developed tool could be used to comprehensively evaluate multiple factors related to dementia prevention and treatment. Numerous attributes influence dementia risks, but there has been no comprehensive monitoring of these factors on a national scale. Incorporating 36 indicators distributed over four essential dimensions from preexisting data, the BCHI represents a novel system that enables a comprehensive, quantitative evaluation not only of general cognitive health but also of numerous individual features associated with dementia prevention and management.

The second concern guiding the development of the BCHI was the role of prevention. The BCHI placed a weight of 33.82%, the highest weight of the four dimensions, on risk factor prevention and control. This reflects the large body of evidence demonstrating the efficacy of strengthening modifiable dementia risk factor management in maintaining cognitive health.[4] Reflecting the paramount importance of specific risk factor mitigation efforts such as smoking cessation, hypertension control, and treatment of hearing impairments in preventing dementia, these factors were given some of the highest weights of any indicators (5.77%, 4.90%, and 4.46%, respectively) in the BCHI.

The third concern in developing the BCHI was the foundational role of a cognitive health monitoring system in guiding national health strategies. A monitoring system is pivotal to public health, providing necessary information to implement national policies and programs for non-communicable diseases (NCDs) and assisting in the evaluation of such interventions. A study by the WHO revealed that national-level cognitive health monitoring efforts remain underdeveloped throughout the world, with significant regional variations in monitoring capacities.[1] Notably, the BCHI could facilitate spatial comparisons by enabling assessments at PLAD-level resolution. For example, Beijing had the highest BCHI score of all 31 PLADs and also showed good performance in several aspects of dementia risk factor prevention, risk factor control, diagnosis, and treatment. However, indicators related to risk factor exposure (including rates of alcohol consumption, current smoking rates, and the prevalence of dyslipidemia) had relatively low scores across all 31 PLADs. Our study thus highlighted these factors as areas for targeted improvement in Beijing. Furthermore, for each of the 31 PLADs, the BCHI could be used to effectively identify barriers in implementing control measures, facilitating local establishment of priorities for improvement and the elimination of PLAD-specific health inequities.

Importantly, the BCHI enables direct analysis of temporal trends in cognitive health. All of the data used in constructing the BCHI were collected from stable sources that are expected to be continually updated over the next several years. By monitoring BCHI scores over time, policymakers can assess the efficiency of government policies, guiding the allocation of investments in medical resources related to cognitive health. The establishment of a dedicated national BCHI calculation and monitoring system will provide policymakers, health providers, and researchers with necessary evidence to develop programs and policy interventions for cognitive health and will support evaluation of these interventions.

Some limitations of the BCHI should be noted. First, although we included many high-quality data sources to develop a comprehensive index, some unmeasured but important indicators were not included due to a lack of available data. These included indicators related to patient treatments (e.g., the proportion of patients with a specific condition receiving pharmaceutical treatments), genetic risk, prevention and control of other risk factors (e.g., depression, sleep disorder, and brain injury), and access to social support among elderly people with dementia (e.g., local abundance of care facilities). Additional studies will be conducted to monitor these important indicators and the BCHI will be updated to include these factors. Second, data for two relevant indicators (health literacy levels among the elderly and the proportion of first-level hospitals with memory clinics) could not be obtained in time for inclusion in the BCHI; an update of the BCHI will include these data. Third, the data sources used in this study were representative at the PLAD level, with the exception of CHARLS. Data from CHARLS were incorporated into the BCHI because they included important indicators that were not available from any other data source. In addition, CHARLS data did not cover all 31 PLADs. These limitations may have influenced inter-PLAD comparability of indicators obtained from CHARLS data.

In conclusion, we here introduce the BCHI, a comprehensive cognitive health evaluation system. The BCHI was applied to the 31 PLADs in China, identifying current strengths and areas for improvement in the prevention and control of dementia. Analysis of four dimensions encompassing 36 indicators contributed to an advanced understanding of cognitive health among Chinese residents in a clear, intuitive manner. Continued updates to BCHI scores will reveal temporal changes in cognitive health and validate the efficacy of strategies and interventions targeting dementia. The BCHI will allow researchers and policymakers to prioritize key interventions for the prevention and control of dementia in China. Importantly, it also serves as an invaluable model for other LMICs to effectively monitor and target specific factors associated with cognitive health at the population scale in their own countries, promoting increased quality of life and reduced disease burden throughout the world.

Funding

This study was supported by grants from the National Key Research and Development Program of China (No. 2022YFC3602600), the National Natural Science Foundation of China (Nos. 82220108009, 81970996), and STI2030-Major Projects (No. 2021ZD0201801).

Supplementary Material

Yuanyuan Lu and Fan Mao contributed equally to this work.

How to cite this article: Lu YY, Mao F, Yin P, Chang J, Zhao ZP, Yang K, Qin Q, Zhou MG, Tang Y. A comprehensive index to evaluate cognitive health at the population scale. Chin Med J 2024;137:2233–2235. doi: 10.1097/CM9.0000000000003241
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