R. Li1,†, J. Qi2,†, Y. Yang1, Y. Wu1, P. Yin2, M. Zhou2, Z. Qian3, M.H. LeBaige3, S.E. McMillin4, H. Guo2, H. Lin1
1. Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China; 2. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; 3. Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, Missouri, United States; 4. School of Social Work, College for Public Health and Social Justice, Saint Louis University, Saint Louis, Missouri, United States. † Rui Li and Jinlei Qi are joint first authors
Corresponding Author: Haoyan Guo, PhD, National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China, Email: email@example.com; Hualiang Lin, PhD, School of Public Health, Sun Yat-sen University, No. 74, 2nd Yat-sen Road, Yuexiu District, Guangzhou, 510080, P. R. China, Email: firstname.lastname@example.org
J Prev Alz Dis 2021;
Published online December 10, 2021, http://dx.doi.org/10.14283/jpad.2021.69
Background: Updated information on the burden of Alzheimer’s disease and other forms of dementia are of great importance for evidence-based health care planning. However, such an estimate has been lacking in Chinese populations at both national and provincial levels.
Objective: To estimate the temporal trends and the attributable burdens of selected risk factors of Alzheimer’s disease and other forms of dementia in China.
Design, Setting, and Participants: This is an observational description of the Global Burden of Diseases Study 2019 (GBD 2019). Data on incidence, mortality, prevalence, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) of Alzheimer’s disease and other forms of dementia were derived from the GBD 2019 study at both national and provincial levels in China.
Measurements: Six indicators were used: incidence, mortality, prevalence, DALYs, YLLs, and YLDs. Absolute numbers in detail by age, sex, region, and age-standardized rates (with 95% uncertainty intervals) were calculated.
Results: There were notable increasing trends in the number of deaths (247·9%), incidence (264·8%), prevalence (296·5%), DALYs (228·1%), YLDs (308·7%) and YLLs (201·7%) from 1990 to 2019, respectively. The corresponding age-standardized rates increased by 6·2%, 19·3%, 33·6%, 10·7%, 33·4% and 3·1%. Smoking, high body mass index, high fasting plasma glucose levels, and metabolic risks were the four leading risk factors. Higher burden was observed among females versus males and in the more developed regions.
Conclusions: The disease burden in China were increasing substantially. Regional differences of the disease burden are accompanied by discrepancies of economic level and geographical location, as well as different levels of exposure to risk factors. Targeted prevention and control strategies are urgently needed to reduce the disease burden.
Key words: Dementia, Alzheimer’s disease, disease burden, risk factors, China.
Abbreviations: AD: Alzheimer’s disease; GBD: Global Burden of Diseases Study; DALYs: disability-adjusted life years; YLDs: years lived with disability; YLLs: years of life lost; CI: confidence interval; UI: uncertainty interval; CRA: comparative risk assessment; PAF: population-attributable fractions; TMREL: theoretical minimum level of exposure.
Dementia is a major cause of disability and life-long dependency among older adults throughout the globe, affecting memory, cognitive abilities, and behavior, ultimately, interfering with the patient’s ability to perform daily activities (1). The most common form of dementia is Alzheimer’s disease (AD), which accounts for about 60 to 70% of all dementia cases (2). In 2015, more than 50 million people living with dementia cost of more than US $1 trillion worldwide. Further, it is estimated that the global economic cost for dementia will be US $2·54 trillion in 2030 and US $9·12 trillion in 2050 (3). AD and other forms of dementia ranked as the 7th leading cause of death as well, profoundly affecting the end-of-life experience for patients(4). As a consequence of progressively aging population, the number of cases of dementia, including AD, will rise in the coming decades (5).
One recent study reported that the prevalence of dementia was 5·60% (3·50 to 7·60) for individuals aged 65 years or older in China(6). Another study estimated that 9·5 million people aged 60 or above were living with dementia in China (for a prevalence of 5·3%) (7). The incidence of dementia for those older than 65 years ranged from 17·7 to 24·0 per 1,000 person years (8). However, an updated comparison of risk factors and more precise understanding of the disease burden of Alzheimer’s disease and other types of dementia in China were scarce at both national and provincial levels.
We addressed this gap by conducting a detailed analysis of disease burden through examining incidence, prevalence, death, DALYs, YLDs and YLLs as well as analyzing corresponding risk factors of Alzheimer’s disease and other dementia at both national and provincial levels. The results of this study will provide vital information and background for intervention studies that aim to reduce the disease burden of Alzheimer’s disease and other dementia in China.
Overview of GBD 2019
The Global Burden of Diseases Study 2019 (GBD 2019) provides a systematic and comprehensive assessment for a mutually exclusive and collectively exhaustive list of diseases and injuries at global, national, and subnational levels from 1990 to 2019 (9). The data sources include field surveys, censuses, vital statistics, and other health-related data sources to reach their conclusions, while the methods have been described elsewhere (10, 11). The overall disease burden of Alzheimer’s disease and dementia and corresponding attributable risk factors were estimated yearly for the years of 1990,2019. Thus, we used the data in GBD 2019 to estimate the trends of the disease burden in China in six normalized epidemiological measures: incidence, mortality, prevalence, DALYs, YLDs and YLLs.
All the data were stratified according to province or location (options included 22 provinces, five autonomous regions, four cities, and two special administrative regions including Hong Kong and Macao), gender (male, female, and both) and age (age from 5 years to 94 years were split into new data points for each 5-year age groups; there were other age groups for all ages, and age-standardized). To further explore the regional differences of these indicators, we performed K-means cluster analysis by considering the annual results of these six measures simultaneously from 1990 to 2019.
Dementia is a broad term used to classify a particular group of symptoms. It is a clinical syndrome caused by neurodegeneration and is defined by evidence of difficulties with memory, language, problem-solving, thinking skills, and emotional functions that significantly affect a person’s ability to perform everyday activities (12, 13). While AD, vascular dementia, Lewy body, and frontotemporal dementia are the most common underlying pathologies, the distinctions between different forms of dementia are often not hard boundaries and mixed forms often coexist (14).
In accordance with the International Classification of Diseases, 10th Revision (ICD-10), dementia is defined as any one of the following codes: F00, F01, F02, F03, G30 and G31. And the diagnostic criteria for dementia or “major neurocognitive disorder” in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) require a significant cognitive decline in at least one of the following cognitive domains: learning and memory, complex attention, executive function, language, perceptual-motor ability, including praxis and gnosis, and social cognition (15). In our study, we adopt these international definitions for dementia and Alzheimer’s disease accordingly.
Measures of Disease Burden
In this study, we used six indicators (including incidence, mortality, prevalence, DALYs, YLDs and YLLs) to reflect the disease burden of dementia. Mortality was estimated using data from the Chinese Center for Disease Control and Prevention’s death reporting system and the disease surveillance points system. Prevalence is the number of actual existing cases, while incidence is defined as the number of new cases of dementia. Both prevalence and incidence were population-based estimates using extensive population-representative data including scientific reports and health system administrative surveys.
DALYs is a composite measure of disease burden and is calculated as the sum of YLDs and YLLs in order to serve as a summary of the effects of dementia on both the quantity (premature mortality) and quality of life (disability). YLLs represents the years of life lost in the form of premature mortality due to Alzheimer’s disease and other dementia in the population. This measure is estimated by taking the number of deaths multiplied by the standard life expectancy at the age at which the death occurred. To estimate YLD in a time period, the number of incident cases in the period is multiplied by the disease average duration and a weighted factor reflecting the disease severity on a numerical scale from 0 (perfect health) to 1 (deceased) (16). The point estimates and 95% confidence intervals (95% CIs) of these indicators were calculated from the mean of 1,000 draw values through the GBD modelling process (9-11). We also present 95% uncertainty intervals (95% UIs) for every metric based on the values ordered 2·5th and 97·5th out of 1,000 draws of the posterior distribution. Age-standardized estimates were performed using a global age structure from 2019 (9). All the measures above were stratified by year, province, age, and sex.
K-means cluster analyses were conducted on standardized values of different indicators to demonstrate the discrepancy of geographical distribution (17). Concretely, we used Z-score values of age-standardized rate of deaths, incidence, prevalence, DALYs, YLDs, and YLLs from 1990 to 2019 and then implemented the K-means clustering method. For the convenience of results presentation, we limited the final number of clustering subgroups to 5. The index values of different measures of each region were preliminarily clustered, and the groups with similar characteristics were combined until there was a significant difference between groups. Finally, according to the influence of regional differences on the burden of disease, the main subgroups of geographical distributions were analyzed and summarized. The Kruskal-Wallis test was used to compare the differences between cluster subgroups(18).
Attributable Risk Factors
Both attributable number and attributable age-standardized rate of death, DALYs, YLDs and YLLs were estimated for the following 5 categories of risk factors: all risk factors, smoking, a high body mass index, high fasting plasma glucose levels, and metabolic risks. Attributable number of selected risk factors were estimated according to a comparative risk assessment (CRA) (19). Population-attributable fractions (PAF) were also calculated. PAF calculations utilized relative risk data, exposure data, and a theoretical minimum level of exposure (TMREL), which is the level at which the risk of health outcomes is lowest. Attributable burden was calculated by multiplying the cause measure in question by the PAF(9, 10).
All the analyses were performed with R software (version 3·6·2) and SPSS version 25·0.
From 1990 to 2019, the number of deaths, incidence, prevalence, DALYs, YLDs and YLLs increased steadily in all gender groups at both national and provincial levels. However, once counts were converted to age-standardized rates, removing the effects of population growth and aging, there were not clearly consistent changes in overall health since they varied differently. As for different gender groups, the number of all the measures for females were higher than for males, while the age-standardized rates of all the measures were the highest in female, followed by both and male in any given year (Table 1, Figure 1, Figure 2, and Table A.1). The age group older than 65 accounted for more than 75% of the total number of these measures in every year without exception, this proportion increasing annually. Further, although there was not enough evidence showing a younger age trend, the age group younger than 65 also accounted for a considerable percentage of the total (Figure A.1). When considering both age and gender, the proportions for all indicators were about equal in younger age groups, but the gap in burden between females and males widened significantly in older age groups. The oldest age group, in fact, 95 years or older, exhibited the majority of cases reported for women (Figure A.2, A.3). For all six measures, changes in the all-age number and age-standardized rates were captured at provincial levels in year 1990 and 2019 (Table A.2 to A.7). More detailed descriptions of each measure for Alzheimer’s disease and other dementia are given below.
Abbreviation: UI, uncertainty interval; DALYs, disability-adjusted life years; YLDs, years lived with disability; YLLs, years of life lost.
(A) Deaths; (B) incidence; (C) prevalence; (D) DALYs; (E) YLDs; (F) YLLs.
(A) Mortality rate; (B) incidence rate; (C) prevalence rate; (D) DALYs rate; (E) YLDs rate; (F) YLLs rate.
Mortality, Incidence and Prevalence
Over the past three decades studied here, mortality, incidence and prevalence all increased: mortality by 247·9% (95% UI: 181·3% to 339·2%), incidence by 264·8% (250·5% to 279·1%), and prevalence by 296·5% (281·5% to 311·5%) (Table 1).
The estimated number of deaths nationwide in China from Alzheimer’s disease and other dementia had increased from 0·09 million (0·02 to 0·26) in 1990 to 0·32 million (0·08 to 0·84) in 2019 for those aged 40 years or older. The age-standardized mortality rate increased by 6·2% (-9·4% to 27·7%) during these 30 years (Table 1, Table A.1). The number of deaths steadily increased at the provincial level as well among all provinces. However, when standardized by age, mortality rate changed differently, there were both increases and decreases. The estimated incidence number had increased from 0·51 million (0·44 to 0·60) to 1·80 million (1·52 to 2·08) between 1990 and 2019, while the age-standardized incidence rate increased by 19·3% (16·2% to 22·3%) during these 30 years. At the provincial level, both raw and age-standardized incidence increased steadily. Similar to the increasing tread of incidence, both the number and the age-standardized prevalence rate were rising constantly. The estimated prevalence number increased from 3·35 million (2·80 to 3·89) to 13·14 million (11·02 to 15·30), and the age-standardized prevalence rate increased by 33·6% (30·2% to 36·9%). A steady, increasing trend in the prevalence rate was seen in almost all provinces of China.
DALYs, YLDs and YLLs
Over the past three decades, the number of all-age DALYs, YLDs and YLLs increased by 228·1% (174·0% to 298·3%), 308·7% (290·0% to 328·0%), and 201·7% (136·9% to 292·5%) respectively (Table 1).
The number of DALYs increased from 1·85 million (0·76 to 4·32) in 1990 to 5·98 million (2·68 to 13·10) in 2019. The national age-standardized DALYs rates increased by 10·7% (-4·9% to 29·5%) from 1990 to 2019, but the provincial rate changed differently, while almost all provinces had seen increased rates with a few exceptions. Further, the raw number of YLDs followed a similar pattern, increasing from 0·46 million (0·33 to 0·63) in 1990 to 1·86 million (1·31 to 2·52) in 2019, for an overall change of 308·7% (290·0% to 328·0%). The national age-standardized YLDs rates increased by 33·4% (29·7% to 37·1%) from 1990 to 2019, and the provincial rates increased steadily. Likewise, the number of YLLs increased from 1·38 million (0·32 to 3·81) in 1990 to 4·11 million (0·97 to 11·43) in 2019, with a change of 201·7% (136·9% to 292·5%). The national age-standardized YLLs rates increased by 3·1% (-14·7% to 26·7%) from 1990 to 2019, but the direction of changes in rates across provinces were not consistent. The relative proportions of YLDs and YLLs throughout these years remained basically the same (Figure A.4).
Geographical Distribution of Disease Burden
The detailed geographical distribution of all measures was shown in Supplementary Tables A.2 to A.8 and Figures A.5 to A.10. For each region in different clusters, Regions 5 had the greatest burden of disease as reflected by corresponding indicators. For example, Hebei had been seen in the subgroup of Regions 5 frequently whenever clustered by the age-standardized rate of incidence, prevalence, DALYs or even YLDs, which means condition there was more serious compared with other provinces and more attentions and controls were needed to improve the situation (Table A.8).
On a national scale, the burden of disease showed some east-west and north-south differences, but these trends were not extremely concentrated. Some provinces clearly fell into these regions with a severe burden of disease, such as Hebei, Tianjin, Zhejiang, Guangdong and Jilin, while others were much lighter, such as Guizhou, Inner Mongolia, Liaoning and Tibet. Although the largest disease burden was often seen in provinces with more developed economies, there were exceptions, such as Beijing and Hong Kong in our study.
Attributable Burden by Selected Risk Factors
Attributable number and attributable age-standardized rate of mortalities, DALYs, YLDs and YLLs were estimated in different gender groups in 2019 for the 5 risk factors examined here as shown in Table 2. Comparisons were made nationally between 1990 and 2019 (Table A.9). The attributable number of DALYs for dementia including all risk factors was 1·89 million (95% CI: 0·76 to 4·54). For deaths, it was 0·09 million (0·02 to 0·28). For YDLs, it was 0·59 million (0·36 to 0·91), and 1·31 million (0·28 to 3·89) for YLLs. These results were regardless of gender. The attributable age-standardized rates were 109·8 (44·1 to 263·8), 6·3 (1·3 to 18·8), 34·0 (20·2 to 52·2), 75·8 (16·2 to 227·1) per 100,000 in 2019, respectively. Of these four subtypes of all risk factors, smoking was the leading risk factor of all the four indicators in both attributable number or attributable age-standardized rate while not including gender. This pattern was consistent in men, but metabolic risks were the most important indicator in women. A noteworthy fact was that the trend was basically the same among men and both genders in different age groups as for attributable number of deaths, DALYs, YLDs and YLLs in 2019 (Figure 3). Smoking was still the leading risk factors for disease burden of Alzheimer’s disease and other dementia in male older than 40 years old, although this influence slightly decreased as they got older. Moreover, the hazard of metabolic risks increased year by year. Smoking was the major risk factor only in the younger age groups for male and both but was then superseded by metabolic risks in the older groups for all genders. In females, metabolic risks were the major risk factor throughout all age groups. As for geographical distribution, the attributable number values for each risk factor were almost universally the largest in Shandong, with a few exceptions. Meanwhile, Tianjin was one of the regions with the most notable attributable risk values when considering age-standardized rates. Smoking and metabolic risks remained the two leading risk factors in all provinces from 1990 to 2019 (Table A.10 to A.17).
Abbreviation: CI, confidence interval; DALYs, disability-adjusted life years; YLDs, years lived with disability; YLLs, years of life lost.
(A) Death for both female and male; (B) death for female; (C) death for male; (D) DALYs for both female and male; (E) DALYs for female; (F) DALYs for male; (G) YLDs for both female and male; (H) YLDs for female; (I) YLDs for male; (J) YLLs for both female and male; (K) YLLs for female; (L) YLLs for male.
This population-based nationwide epidemiologic study provided an updated information for disease burden of Alzheimer’s disease and other dementia in China from 1990 to 2019. We found that the number of deaths, incidence, prevalence, DALYs, YLDs and YLLs increased substantially in all gender and age groups at both national and provincial levels from year 1990 to 2019, but the changes of age-standardized rates were not clearly consistent in overall health.
For these 30 years, the absolute number for burden of Alzheimer’s disease and other dementia had increased almost 3·5 times with a ratio of nearly 1·73 between women and men on average. Researches have suggested that this difference may be attributable to hormonal differences and brain development factors between men and women (20). The age-standardized rates of all the measures were highest in females, followed by both genders and males. AD is more prevalent in women, and moreover, mounting evidence from brain imaging, post-mortem analyses, hormone therapy, and genetic testing suggests that AD does indeed affect men and women differently (21).
In our study, the people younger than 65 years old with dementia accounted for a considerable part of the total number of those with dementia. Dementia is often thought of as an illness that only affects seniors, but it can, not uncommonly, exhibit in people younger than 65 years, particularly in the 45 to 64-year age range (22). Dementia is a challenging condition in any case but can have disastrous implications for patients and their families, society, and the economy when it strikes at a young age (23). Nowadays, most people do not have many regular, protective daily habits and live with high levels of stress, poor sleep quality, and other risk factors due to the accelerated pace of life, factors which may also lead to the population suffering from Alzheimer’s disease getting gradually younger. Thus, an early diagnosis of dementia is extremely important. Fortunately, related practical ‘how-to’ guidance, considerations, and tools that can be used by healthcare providers throughout the diagnostic journey have been well summarized and published recently (24).
One recent study had found that the dementia prevalence decreased from the northern, central, and southern regions in China to the lowest rates in Hong Kong and Taiwan, while western China exhibited a particularly high estimate (7). Another report published in 2016 showed, similarly, that the incidence of dementia was higher in northern China than in southern China and in rural areas versus urban areas (25). In our study, the burden of disease showed some east-west and north-south differences, but not especially strong differences. Although more disease burden was often seen in provinces with more developed economics, there were still a few exceptions, such as Beijing and Hong Kong. Environmental risk factors, such as sunshine and Vitamin D intake, air pollution, and access to quality health services, certainly play a role in general health and may subsequently influence one’s risk of dementia and provide a possible explanation for the geographical variation seen in several studies (26, 27). Systematic regional variations in other exposures such as education, smoking, nutrition, diet, general health, and life experiences might also contribute to cognitive health differences later in life. Although we might expect that steadily aging populations, changes to more sedentary lifestyles, and a rise in chronic disease prevalence might all increase the risk of dementia in older populations over time, recent epidemiological studies suggest, to the contrary, that the prevalence of dementia has stabilized or decreased in high-income countries over the past two decades (28). Possible explanations for these trends include improving education systems, better living conditions and lifestyle, and a reduction in chronic conditions and extreme poverty and deprivation (7).
There is still no cure for dementia, although currently available treatments may alleviate some symptoms (29). Risk for dementia is believed to be caused by complex interactions between age and genetic factors, both factors that cannot be controlled, and lifestyle and comorbidity factors that are, by contrast, amenable to intervention (1). Modifiable risk factors, such as low education level, high blood pressure, type 2 diabetes mellitus, alcohol consumption, smoking, and nutrient deficiency, among others, seem to have a great influence on the disease burden of Alzheimer’s disease and other dementia (1, 30). Limited by incomplete survey data and lack of various types of indicators, we only looked at all risk factors together and smoking, high body-mass index, high fasting plasma glucose, and metabolic risks (such as diabetes and hypertension but no specific subtypes) individually in relation to the burden of disease in our study. The data showed that smoking was still the leading risk factor for disease burden across genders, and this influence slightly decreased as age group increased. Similarly, a newly published overview of reviews (including 86 literature reviews) also suggested that active smoking (versus never smoking) was associated with an increased risk of dementia (31). There are several potential mechanisms through which smoking could directly affect dementia risk, such as the intrinsic carcinogenic and noxious properties of tobacco, and the numerous chemicals contained in cigarettes. Smoking can also indirectly affect the risk via increasing the incidence of coronary heart disease, diabetes mellitus and other metabolic diseases since its effects of vasoconstriction, atherogenesis, thrombogenesis and endothelial dysfunction (32). The hazard of metabolic risks behaved inversely: increasing quickly with age. Noteworthy, too, is that metabolic risks were unquestionably the major risk factor for females of all age groups. Lifestyle factors such as smoking, excessive alcohol use, and poor diet appear to moderately influence dementia risk in both males and females. Sex, as a risk factor that is not typically modifiable, may influence the effectiveness of treatments aimed at targeting modifiable risk factors (33).
This study provides timely information on the incidence, prevalence, mortality, DALYs, YDLs, YLLs and the main risk factors of Alzheimer’s disease and other dementia cases at both national and provincial levels in the Chinese population from 1990 to 2019. The methodology is widely used in GBD studies and has shown its robustness. Admittedly, the present study has several limitations. First, the several unique forms of dementia are not clearly distinguished in the data utilized here, and this fact may influence targeted managements and controls in real-world applications. Second, fully and accurately representing the UIs around our point estimates remains a challenge, particularly in locations with sparse or absent data. Third, specific reasons for regional disease burden differences remain unclear and require more further investigation. Furthermore, a greater focus for future research needs to be directed to identifying data on treatment effects and distributions of severity for major risk factors and their various subtypes for various indicators of disease burden of Alzheimer’s disease and other dementia.
The health burden due to Alzheimer’s disease and other dementia is still substantial and increasing at both national and provincial levels in different gender and age groups yearly. The regional differences may suggest the necessity to allocate health resources and take corresponding control measures depending on the specific factors in the province. More attention should be paid to the management of modifiable risk factors including smoking, high body-mass index, high fasting plasma glucose, and metabolic risks. The effects of age and gender differences need to be taken into account since they may influence the effectiveness of our treatments in targeting modifiable risk factors.
Acknowledgements: The authors would like to appreciate the staff who participated in data collection and management of this study. The authors are also grateful to the National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention for providing the data.
Role of the funding source: This work was supported by the National key Research and Development program of China [2020YFC2008705].
Conflict of Interest Disclosures: Dr Qian reports funding from HRSA, MCH Bureau for the Center of Excellence in Maternal and Child Health Education, Research, and Practice. Dr McMillin reports payment for energy efficiency advocacy consultation from Renew Missouri and funding form Section Chair and Convenor, Social Innovation and Entrepreneurship special interest section of the Society for Social Work and Research. The other authors have nothing to disclose. The funders had no role in the design or conduct of the study; the collection, management, analysis, or interpretation of the data; the preparation, review or approval of the manuscript; or the decision to submit the manuscript for publication. The authors declare no conflicts and competing interests that could have appeared to influence the work reported in this paper.
Authorship Contribution Statement: Rui Li: Formal analysis, writing original draft, writing review & editing. Jinlei Qi: Formal analysis, writing original draft, writing review & editing. Yin Yang: Conceptualization, formal analysis, writing review & editing. Yinglin Wu: Formal analysis, writing review & editing. Peng Yin: Acquisition of data, writing review & editing. Maigeng Zhou: Acquisition of data, writing review & editing. Zhengmin (Min) Qian: Writing review & editing. Stephen Edward McMillin: Writing review & editing. Morgan H. LeBaige: Writing review & editing. Hualiang Lin: Conceptualization, formal analysis, writing original draft, writing – review & editing. Haoyan Guo: Conceptualization, formal analysis, writing original draft, writing review & editing.
Ethical Information: Data were all analyzed anonymously, so ethical approval was not needed.
Data sharing: Data were collected within the collaborative research network of Chinese Center for Disease Control and Prevention under a data sharing agreement and cannot be made publicly available. Researchers can refer to coauthors of this article who work for the Chinese Center for Disease Control and Prevention for more information on accessing the data.
Funding: National key Research and Development program of China [2020YFC2008705].
1. Sacuiu SF. Dementias. Handb Clin Neurol. 2016;138:123-51. DOI: 10.1016/B978-0-12-802973-2.00008-2.
2. World Health Organisation. 2020. Fact sheets: Dementia. September 2020. https://www.who.int/news-room/fact-sheets/detail/dementia. 2020.
3. Pickett J, Brayne C. The scale and profile of global dementia research funding. The Lancet. 2019;394(10212):1888-9. DOI: 10.1016/s0140-6736(19)32599-1.
4. Roden M, Shulman GI. The integrative biology of type 2 diabetes. Nature. 2019;576(7785):51-60. DOI: 10.1038/s41586-019-1797-8.
5. Garre-Olmo J. [Epidemiology of Alzheimer’s disease and other dementias]. Rev Neurol. 2018;66(11):377-86.
6. Huang YQ, Wang Y, Wang H, et al. Prevalence of mental disorders in China: a cross-sectional epidemiological study. Lancet Psychiat. 2019;6(3):211-24. DOI: 10.1016/S2215-0366(18)30511-X.
7. Wu YT, Ali GC, Guerchet M, et al. Prevalence of dementia in mainland China, Hong Kong and Taiwan: an updated systematic review and meta-analysis. Int J Epidemiol. 2018;47(3):709-19. DOI: 10.1093/ije/dyy007.
8. Chen R, Hu Z, Wei L, et al. Incident dementia in a defined older Chinese population. PLoS One. 2011;6(9):e24817. DOI: 10.1371/journal.pone.0024817.
9. Diseases GBD, Injuries C. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1204-22. DOI: 10.1016/S0140-6736(20)30925-9.
10. Zhou M, Wang H, Zeng X, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;394(10204):1145-58. DOI: 10.1016/S0140-6736(19)30427-1.
11. Nichols E, Szoeke CEI, Vollset SE, et al. Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990,2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology. 2019;18(1):88-106. DOI: 10.1016/s1474-4422(18)30403-4.
12. Gottfries CG. Dementia: classification and aspects of treatment. Psychopharmacol Ser. 1988;5:187-95. DOI: 10.1007/978-3-642-73280-5_18.
13. 2020 Alzheimer’s disease facts and figures. Alzheimers Dement. 2020. DOI: 10.1002/alz.12068.
14. Cahill S. WHO’s global action plan on the public health response to dementia: some challenges and opportunities. Aging Ment Health. 2020;24(2):197-9. DOI: 10.1080/13607863.2018.1544213.
15. Battle DE. Diagnostic and Statistical Manual of Mental Disorders (DSM). Codas. 2013;25(2):191-2. DOI: 10.1590/s2317-17822013000200017.
16. Guenther PM, Kirkpatrick SI, Reedy J, et al. The Healthy Eating Index-2010 is a valid and reliable measure of diet quality according to the 2010 Dietary Guidelines for Americans. J Nutr. 2014;144(3):399-407. DOI: 10.3945/jn.113.183079.
17. Steinley D. K-means clustering: a half-century synthesis. Br J Math Stat Psychol. 2006;59(Pt 1):1-34. DOI: 10.1348/000711005X48266.
18. Chan Y, Walmsley RP. Learning and understanding the Kruskal-Wallis one-way analysis-of-variance-by-ranks test for differences among three or more independent groups. Phys Ther. 1997;77(12):1755-62. DOI: 10.1093/ptj/77.12.1755.
19. Murray CJ, Ezzati M, Lopez AD, Rodgers A, Vander Hoorn S. Comparative quantification of health risks conceptual framework and methodological issues. Popul Health Metr. 2003;1(1):1. DOI: 10.1186/1478-7954-1-1.
20. Sohn D, Shpanskaya K, Lucas JE, et al. Sex Differences in Cognitive Decline in Subjects with High Likelihood of Mild Cognitive Impairment due to Alzheimer’s disease. Sci Rep. 2018;8(1):7490. DOI: 10.1038/s41598-018-25377-w.
21. Laws KR, Irvine K, Gale TM. Sex differences in cognitive impairment in Alzheimer’s disease. World J Psychiatry. 2016;6(1):54-65. DOI: 10.5498/wjp.v6.i1.54.
22. Withall A, Draper B, Seeher K, Brodaty H. The prevalence and causes of younger onset dementia in Eastern Sydney, Australia. Int Psychogeriatr. 2014;26(12):1955-65. DOI: 10.1017/S1041610214001835.
23. Kvello-Alme M, Brathen G, White LR, Sando SB. The Prevalence and Subtypes of Young Onset Dementia in Central Norway: A Population-Based Study. J Alzheimers Dis. 2019;69(2):479-87. DOI: 10.3233/JAD-181223.
24. Porsteinsson AP, Isaacson RS, Knox S, Sabbagh MN, Rubino I. Diagnosis of Early Alzheimer’s Disease: Clinical Practice in 2021. J Prev Alzheimers Dis. 2021;8(3):371-86. DOI: 10.14283/jpad.2021.23.
25. Yuan J, Zhang Z, Wen H, et al. Incidence of dementia and subtypes: A cohort study in four regions in China. Alzheimers Dement. 2016;12(3):262-71. DOI: 10.1016/j.jalz.2015.02.011.
26. Delgado-Saborit JM, Guercio V, Gowers AM, et al. A critical review of the epidemiological evidence of effects of air pollution on dementia, cognitive function and cognitive decline in adult population. Sci Total Environ. 2021;757:143734. DOI: 10.1016/j.scitotenv.2020.143734.
27. Cao L, Tan L, Wang HF, et al. Dietary Patterns and Risk of Dementia: a Systematic Review and Meta-Analysis of Cohort Studies. Mol Neurobiol. 2016;53(9):6144-54. DOI: 10.1007/s12035-015-9516-4.
28. Roehr S, Pabst A, Luck T, Riedel-Heller SG. Is dementia incidence declining in high-income countries? A systematic review and meta-analysis. Clin Epidemiol. 2018;10:1233-47. DOI: 10.2147/CLEP.S163649.
29. Kumar A, Sidhu J, Goyal A, Tsao JW. Alzheimer Disease. StatPearls. Treasure Island (FL)2021.
30. James BD, Bennett DA. Causes and Patterns of Dementia: An Update in the Era of Redefining Alzheimer’s Disease. Annu Rev Public Health. 2019;40:65-84. DOI: 10.1146/annurev-publhealth-040218-043758.
31. Rochoy M, Rivas V, Chazard E, et al. Factors Associated with Alzheimer’s Disease: An Overview of Reviews. J Prev Alzheimers Dis. 2019;6(2):121-34. DOI: 10.14283/jpad.2019.7.
32. Zhou S, Wang K. Childhood Secondhand Smoke Exposure and Risk of Dementia, Alzheimer’s Disease and Stroke in Adulthood: A Prospective Cohort Study. J Prev Alzheimers Dis. 2021;8(3):345-50. DOI: 10.14283/jpad.2021.10.
33. Podcasy JL, Epperson CN. Considering sex and gender in Alzheimer disease and other dementias. Dialogues Clin Neurosci. 2016;18(4):437-46. DOI: 10.31887/DCNS.2016.18.4/cepperson.