Abstract
Background
Dementia is an increasingly significant public health challenge worldwide, with Alzheimer’s disease being the most prevalent form of dementia. The objective of this study was burden of risk factors attributable to Alzheimer’s disease and other dementia and its relationship with the Socio-Demographic Index in Asian countries.
Methods
The present study is a population-based study. The 2021 Global Burden of Disease Study dataset for countries in the Asian continent was used in this study. Age-standardized rate (ASR) for incidence, mortality, prevalence, Disability-Adjusted Life Years (DALY), Years of Life Lost (YLL), Years Lived with Disability (YLD) and Annual Percentage Change (APC) were considered by gender and country. We assessed the trend for all index from 2010 to 2021. In addition, the association between socio-demographic index (SDI) and Alzheimer’s disease incidence and prevalnce was calculated using Pearson correlation analysis.
Results
The results indicated that the number and ASR of four indicators (incidence, prevalence, mortality, DALY, YLL, and YLD) from 1990 to 2021 were higher for women than for men. Metabolic risks and high fasting plasma glucose emerged as the primary risk factors for all four indicators. The percentage change in the risk factor associated with smoking for all four indicators decreased from 1990 to 2021, while the most significant increase was observed in the percentage change related to high body mass index. Additionally, the results demonstrated a positive and significant correlation between the Sociodemographic Index (SDI) and Age-Standardized Incidence Rate (ASIR) (r = 0.284, p = 0.04) as well as Age-Standardized Prevalence Rate (ASPR) (r = 0.281, p = 0.01).
Conclusion
According to the reported results, the burden of disease remains high in most countries. To alleviate this burden, it is essential to prioritize women and the elderly, and to implement more effective prevention and treatment measures.
Keywords: Alzheimer's disease, Dementia, Prevalence, Incidence, Burden of disease
Introduction
Alzheimer’s disease (AD) is the most common type of dementia, affecting mainly older age groups, and its incidence and prevalence increase with age [1]. In 2019, an estimated 57 million people globally were living with dementia, with Alzheimer’s disease being the most common form. The prevalence is projected to rise to 153 million by 2050 [2]. Alzheimer’s and other dementias resulted in 25.3 million years of healthy life lost in 2019, accounting for 1.0% of all years lost [3]. The global prevalence of Alzheimer’s disease in women has been reported to be 1.17 times higher than in men, and the age-standardized mortality rate is also elevated in the female population [4].
Various studies have confirmed modifiable risk factors for Alzheimer’s disease [5–7]. Studies have shown that obesity and overweight are known as a potential risk factor for Alzheimer’s disease and other types of dementia, and these people have a higher risk of developing dementia in older age compared to people of normal weight [8, 9]. High blood sugar, especially in conditions like type 2 diabetes and prediabetes, is known to be a significant risk factor for Alzheimer’s disease and other types of dementia. Research shows that elevated blood sugar levels can have detrimental effects on brain health and increase the risk of cognitive impairment [7, 10]. Research shows that smoking can increase the risk of Alzheimer’s disease and other types of dementia. This association is explained by several mechanisms, including damage to blood vessels, increased inflammation, and oxidative stress [11, 12].
Other factors that can be associated with noncommunicable diseases, including Alzheimer’s disease, include sociodemographic factors. Several studies have examined the association of noncommunicable diseases with socioeconomic indicators [13–15].
The Sociodemographic Index (SDI) is a composite of three key dimensions of income, education, and fertility that indicates the level of development of a country [16, 17]. The SDI can be used in health research to increase understanding of the impact of social and economic contexts on health outcomes. Using the SDI, it can be determined how a combination of factors, such as education and income, affects health outcomes.
Given that the patterns of Alzheimer’s disease and other dementias are not well understood across different countries, this study is essential for providing a more comprehensive understanding of the status of these conditions. The aim of this research is to illuminate the potential factors influencing changes in dementia prevalence over time by examining the relationship between SDI and temporal patterns in DALY, incidence and prevalence of Alzheimer’s disease and other dementias, and to contribute to better planning and delivery of care.
Methods
The present study is a cross-sectional descriptive analysis. Its aim is to examine temporal patterns in incidence, mortality, prevalence, DALY, YLL and YLD of Alzheimer’s disease and other dementias from 1990 to 2021 in Asian countries. The study is based on the GBD 2021 estimates, which provide a systematic scientific assessment of published data on the incidence, prevalence, and mortality of a comprehensive list of diseases and injuries. All data, software code, and methodological guidelines are publicly accessible on the GBD website (https://www.healthdata.org/research-analysis/gbd). The GBD synthesizes existing knowledge regarding the levels and patterns of various health outcomes, a wide range of risk factors, and health system responses using a rules-based approach. GBD data are primarily sourced from censuses, surveys, hospital records, and administrative records. The study adheres to the Guidelines for Reporting Accurate and Transparent Health Estimates (GATHER) in a standardized manner that allows for replication [14, 15, 18]. Data were extracted by sex, age group, and country. Estimates were based on prevalence, incidence, mortality, DALY, YLL, and YLD data were extracted from the GBD Outcomes Tool. Methods for estimating rates can be found on the GBD Outcomes Tool website. In this study, ADOD was also assessed by risk factors, as there was sufficient evidence linking high body mass index, high fasting glucose, and smoking to the outcomes analyzed.
Definitions
Alzheimer’s disease and other dementias
Dementia was defined according to the Diagnostic and Statistical Manual of Mental Disorders III, IV, or V, or ICD-10 (International Classification of Diseases – 10th Edition). The diagnosis was accomplished using clinical records, algorithm criteria, National Institute on Aging Alzheimer’s disease criteria, 10/66 algorithm criteria, and general practitioner records. The ICD codes for ADOD are as follows: 290, 291.2, 291.8, 294, and 331 for the 9th revision (ICD-9) and F00, F01, F02, F03, G30, and G31 for the 10th revision (ICD-10) [19].
Disability-adjusted life years (DALY)
The DALY (Disability-Adjusted Life Years) index is used to assess the overall burden of disease, injury, and disability in a population. DALY represents the healthy years of life lost due to premature death and disability. In essence, one DALY is equivalent to the loss of one year of healthy life [20].
Years of life lost (YLL)
YLL is the years of healthy life lost due to premature death, calculated by subtracting the age of death from the life expectancy for a person at that age [20].
Years lived with disability (YLD)
YLD are the number of years a person lives with reduced quality of life and disability due to a disease. By multiplying the prevalence of a disease by the disability weight, we can obtain a YLD that can indicate the impact of the disease on a person’s quality of life [20].
High body-mass index
High BMI for adults (aged 20 + years) and using the thresholds of the International Obesity Task Force for children (aged < 20 years) defined as BMI ≥ 25 kg/m² was established [21].
Fasting plasma glucose (FPG)
Fasting plasma glucose (FPG) was measured as a continuous variable in mmol/L. Fasting plasma glucose (FPG) was measured as the average FPG in a population, and high FPG was defined as any level above the exposure level. The minimum risk (TMREL: theoretical minimum-risk exposure level) which is 4.8–5.4 mmol/liter was defined. TMREL is defined as the level of exposure that minimizes the risk of disease at the population level [20].
Smoking
The definition of smoking in GBD 2021 is the current use of any tobacco products or former smokers who have quit all tobacco products for at least six months [20].
Data analysis
Age-standardized rates (ASR; rates per 100,000) for incidence (ASIR), prevalence (ASPR), mortality (ASMR), and DALY were estimated using a global age structure from 2021, stratified by year, sex, age, and municipality levels. The association between ASIR and ASPR of ADOD and SDI was assessed by Pearson correlation analysis and plotted using a scatter plot. All analyzes were performed using stata-17 and p < 0.05 was considered statistically significant.
Results
From 1990 to 2021, the number of mortality, incidence, prevalence, DALY, YLD, and YLL increased steadily across all gender groups in Asia (Fig. 1). When the counts were converted to age-standardized rates, and the effects of age were adjusted, the trend of change was almost constant(Fig. 2). Across gender groups, the number and age-standardized rates of all measures were higher for women than for men.
Fig. 1.
The trend of all-age number of all six measures for Alzheimer’s disease and other dementia in Asia from 1990 to 2021. (Source: Global Burden of Disease 2021)
Fig. 2.
The trend of age standardize rate of all six measures for Alzheimer’s disease and other dementia in Asia from 1990 to 2021. (Source: Global Burden of Disease 2021)
For each of the six measures, changes in all-age counts and age-standardized rates in Asia were recorded between 1990 and 2021. Further details on each measure for Alzheimer’s disease and other dementias are provided below.
Mortality, incidence and prevalence
Mortality, incidence and prevalence have all increased during the years 1990 to 2021 studied here: in 2021, the number of deaths was 1026.9 (267.2, 2615.5), the incidence 5508.5(4818.6, 6284.9), and the prevalence 31857.0(27609.3, 36564.1). The estimated number of deaths in Asia from Alzheimer’s disease and other dementias has increased from 258.4 (62.0, 683.8) in 1990 to 1026.9(267.2, 2615.5) in 2021. The age-standardized mortality rate increased by 6.9% over the 30 years. The number of deaths in Asia has been steadily increasing. When age-standardized, the mortality rate continued to increase. The estimated incidence rate increased from 1597.9(1824.1, 2392.8) to 5508.5(2684.9, 4818.6) between 1990 and 2021, while the age-standardized incidence rate increased by 11%. Both the crude prevalence and the age-standardized prevalence also increased steadily. Similar to the increasing incidence rate, both the incidence and the age-standardized prevalence rate were continuously increasing. The estimated prevalence increased from 9090.6 (7888.1, 10340.2) to 31857.0 (27609.3, 36564.1), and the age-standardized prevalence rate increased by 13%. A steady and increasing trend in prevalence was observed (Table 1).
Table 1.
All-age number and age-standardized rate of all measures for alzheimer’s disease and other dementia and percentage changes by gender in asia, 1990 and 2021. (Source: global burden of disease 2021)
| All-age number in thousand (95% UI) | Age standardized rate per 100,000 (95% UI) | |||||
|---|---|---|---|---|---|---|
| 1990 | 2021 | APC 1990–2021 | 1990 | 2021 | APC 1990–2021 | |
| Death | ||||||
| Total |
258.4 (62.0, 683.8) |
1026.9 (267.2, 2615.5) |
297.34 (261.1, 352.2) |
23.9 (5.8, 64.2) |
25.6 (6.8, 65.6) |
6.9 (-1.4, 19.6) |
| Female |
170.5 (41.4, 448.3) |
690.8 (184.9, 1751.0) |
305.1 (257.7, 375.8) |
27.5 (6.7, 72.2) |
28.8 (7.7, 72.9) |
4.7 (-5.9, 19.5) |
| Male |
87.9 (20.4, 244.8) |
336.0 (81.6, 912.1) |
282.2 (239.1, 338.1) |
18.5 (4.5, 51.8) |
20.5 (5.1, 55.4) |
10.7 (0.8, 24.0) |
| Incidence | ||||||
| Total |
1597.9 (1392.8, 1824.1) |
5508.5 (4818.6, 6284.9) |
244.7 (234.1, 255.0) |
109.0 (95.5, 124.2) |
121.1 (105.7, 137.9) |
11.0 (8.8, 12.7) |
| Female |
616.0 (533.6, 707.0) |
3431.0 (3013.5, 3901.7) |
249.4 (239.5, 260.1) |
122.2 (107.4, 138.6) |
135.7 (119.1, 154.5) |
11.0 (8.9, 12.8) |
| Male |
981.8 (859.5, 1117.1) |
2077.4 (1784.7, 2392.1) |
237.2 (225.1, 246.7) |
91.8 (79.7, 105.2) |
102.6 (88.5, 117.7) |
11.6 (8.9, 13.6) |
| Prevalence | ||||||
| Total |
9090.6 (7888.1, 10340.2) |
31857.0 (27609.3, 36564.1) |
250.4 (239.7, 260.5) |
624.5 (544.7, 713.5) |
706.2 (610.7, 812.2) |
13.0 (10.8, 14.8) |
| Female |
5572.3 (4845.2, 6355.1) |
20012.0 (17369.9, 22900.5) |
259.1 (248.3, 269.6) |
701.5 (611.8, 799.5) |
795.0 (687.5, 911.9) |
13.3 (11.2, 15.1) |
| Male |
3518.2 (3015.4, 4019.2) |
11844.9 (10076.6, 13577.6) |
236.6 (224.5, 247.2) |
520.9 (452.8, 597.7) |
586.4 (503.0, 678.1) |
12.5 (9.4, 14.5) |
| DALY | ||||||
| Total |
5726.84 (2671.1, 12706.7) |
20017.63 (9585.6, 42792.4) |
249.5 (222.1, 277.8) |
428.6 (194.9, 935.1) |
460.4 (218.2, 981.0) |
7.4 (-0.08, 15.7) |
| Female |
3633.5 (1708.5, 7928.1) |
12956.0 (6192.3,27341.5) |
256.5 (221.5, 293.7) |
491.6 (225.9, 1060.0) |
522.3 (250.0, 1100.8) |
6.2 (-3.1, 16.7) |
| Male |
2093.3 (965.3, 4756.6) |
7061.5 (3318.3, 15605.5) |
237.3 (208.3, 272.1) |
339.7 (152.5, 760.4) |
372.4 (170.5, 822.7) |
9.6 (0.3, 20.1) |
| YLD | ||||||
| Total |
1817.2 (1241.0, 2408.9) |
6471.3 (4462.4, 8567.4) |
256.1 (244.5, 267.4) |
127.8 (87.8, 168.0) |
144.7 (99.6, 191.1) |
13.2 (11.2, 14.9) |
| Female |
1153.5 (788.6, 1536.3) |
4202.7 (2869.1, 5590.8) |
264.3 (252.3, 276.0) |
147.7 9101.3, 196.8) |
167.4 (114.1, 222.6) |
13.3 (11.3, 15.0) |
| Male |
663.6 (456.7, 865.1) |
2268.6 (1565.4, 3000.1) |
241.8 (229.7, 253.7) |
101.0 969.4, 132.0) |
114.1 (78.6,151.1) |
12.9 (10.1, 14.9) |
| YLL | ||||||
| Total |
3909.6 (901.5, 10696.2 |
13546.2 (3398.1, 35907.4) |
246.4 (241.4, 293.5) |
300.7 (71.8, 786.8) |
315.7 (80.9, 815.8) |
4.9 (-3.9, 17.5) |
| Female |
2479.9 (583.8, 6681.1) |
8753.2 (2254.0, 23032.4) |
252.9 (208.8, 315.4) |
343.9 (82.6, 896.4) |
354.8 (92.0, 923.1) |
3.1 (-8.0, 18.4) |
| Male |
2479.9 (583.8, 6681.1) |
4792.9 (1149.3, 13342.8) |
235.2 (191.5, 290.0) |
238.7 (56.3, 647.3) |
258.2 (62.5, 697.0) |
4.9 (-3.9, 17.5) |
DALY, YLD and YLL
Over the past three decades, the number of DALY, YLD and YLL has increased by 249.5%, 256.1% and 246.4% at all ages, respectively. The number of DALY increased from 5726.84 (2671.1, 12706.7) in 1990 to 20017.63(9585.6, 42792.4) in 2021. The age-standardized DALY rate increased by 4.7% from 1990 to 2021. In addition, the crude number of YLD followed a similar pattern, increasing from 1817.2(1241.0, 2408.9) in 1990 to 6471.3(4462.4, 8567.4) in 2021. The age-standardized YLD rate increased by 13.2% from 1990 to 2021, and similarly, the number of YLL increased from 3909.6 (901.5, 10696.2) in 1990 to 13546.2(3398.1, 35907.4) in 2021, a change of 246.4%. The standardized YLL rates increased by 4.9% from 1990 to 2019. The comparison between 1990 and 2021 and the percentage of changes during these years for each of the four indicators are shown in Table 2, broken down by Asian country (Table 1).
Table 2.
Point estimated and 95% UI attributable number and Age-Standardized rate of risk factors for alzheimer’s disease and other dementia in 2021. (Source: global burden of disease 2021)
| Measures | ||||||
|---|---|---|---|---|---|---|
| Attributable number in thousand (95%UI) | All risk factors | High body-mass index | High fasting plasma glucose | Metabolic risks | Smoking | |
| Mortality | Total | 209.9(24.0, 655.2) | 39.7(-2.4, 186.2) | 143.6(5.7, 448.0) | 175.8(6.6, 589.0) | 40.8(9.6, 113.6) |
| Female | 125.8(8.8, 414.4) | 29.5(-2.3, 137.7) | 94.3(3.8, 294.3) | 118.3(3.9, 399.6) | 9.0(2.0, 24.2) | |
| Male | 84.1(14.4, 249.5) | 10.2(-0.1, 48.8) | 49.3(1.9,156.9) | 57.4(2.7, 193.6) | 31.8(7.6, 90.8) | |
| DALY | Total | 4253.4(813.4, 11022.7) | 850.5(-73.1, 3405.9) | 2761.9(158.9, 7369.3) | 3451.4(218.5, 9821.0) | 958.3(412.3, 2196.5) |
| Female | 2410.1(242.5, 6682.4) | 619.6(-66.3, 2452.9) | 1753.3(101.9, 4673.6) | 2257.2(120.4, 6449.4) | 185.4(78.3, 405.6) | |
| Male | 1843.2(523.1, 4425.1) | 230.9(-6.9, 934.8) | 1008.6(57.0, 2710.3) | 1194.2(98.1, 3396.4) | 772.8(326.4, 1805.8) | |
| YLD | Total | 1375.0(366.1, 2814.0) | 277.1(-29.9, 882.7) | 879.0(76.6, 1925.3) | 1103.8(100.9, 2556.1) | 323.0(196.2, 476.4) |
| Female | 778.1(103.3, 1738.5) | 204.5(-28.3, 651.5) | 560.2(48.6, 1227.0) | 726.6(55.0, 1698.5) | 62.3(36.3, 95.9) | |
| Male | 596.8(248.8, 1044.6) | 72.5(-3.3, 218.4) | 318.8(27.9, 697.1) | 1103.8(100.9, 2556.1) | 260.7(161.1,386.2) | |
| YLL | Total | 2878.4(332.8, 8914.9) | 573.4(-45.6, 2572.6) | 1882.9(75.4, 5947.3) | 2347.5(76.9, 7890.2) | 635.2(151.0, 1802.8) |
| Female | 1632.0(105.0, 5319.3) | 415.1(-41.3, 1836.0) | 1193.0(48.0, 3716.3) | 1530.5(43.8, 5140.0) | 123.0(27.9, 345.6) | |
| Male | 1246.3(209.5, 3628.4) | 158.3(-4.00, 739.2) | 689.8(27.4, 2214.5) | 817.0(36.3, 2798.8) | 512.1(122.9, 1488.6) | |
| Attributable Age Standardized Rate Per 100,000 (95% UI) | ||||||
| Mortality | Total | 5.1(0.5, 15.9) | 0.9(-0.05, 4.5) | 3.5(0.1, 11.2) | 4.3(0.1, 14.7) | 0.9(0.2, 2.6) |
| Female | 5.2(0.3, 17.1) | 1.2(-0.09, 5.6) | 3.9(0.1, 3.9) | 4.9(0.1, 16.7) | 0.3(0.08, 0.9) | |
| Male | 4.9(0.8, 14.9) | 0.6(-0.01, 2.9) | 3.0(0.1, 9.5) | 3.4(0.1,11.8) | 1.7(0.4, 5.02) | |
| DALY | Total | 96.0(18.1, 251.7) | 18.8(1.4, 77.2) | 63.6(3.6, 171.0) | 78.8(5.2, 225.7) | 20.5(8.6, 47.6) |
| Female | 96.6(10.0, 268.2) | 24.4(2.5, 97.7) | 70.7(4.1, 189.4) | 90.5(4.9, 259.5) | 7.3(3.1, 16.1) | |
| Male | 94.2(25.4, 230.5) | 11.5(0.2, 47.6) | 53.6(3.0,142.2) | 62.9(5.3, 177.9) | 37.2(15.2, 87.6) | |
| YLD | Total | 30.2(7.8, 62.2) | 5.9(-0.5, 18.8) | 19.7(1.7, 43.1) | 24.5(2.3, 56.8) | 6.7(4.1, 10.0) |
| Female | 30.8(4.1, 68.9) | 7.9(-1.06, 25.5) | 22.3(1.9, 49.2) | 28.8(2.2, 67.3) | 2.4(1.4, 3.7) | |
| Male | 29.1(11.8, 51.8) | 3.4(0.1, 10.4) | 16.2(1.4, 16.2) | 19.0(2.3, 43.3) | 12.0(7.5, 17.8) | |
| YLL | Total | 65.8(7.6, 204.4) | 12.8(-0.9, 58.9) | 43.8(1.7, 136.5) | 54.2(1.8, 180.1) | 13.7(3.2, 38.3) |
| Female | 65.8(4.3, 213.4) | 16.4(-1.5, 73.8) | 48.3(1.9, 150.6) | 61.7(1.8, 207.0) | 4.9(1.1, 13.7) | |
| Male | 65.0(11.0, 190.1) | 8.0(-0.1, 38.3) | 37.4(1.4, 119.0) | 43.9(2.0, 148.0) | 25.2(5.9, 71.3) | |
Attributable burden by selected risk factors
The attributable number and age-standardized rate of attributable deaths, DALY, YLD, and YLL in different gender groups in 2021 for the 5 risk factors examined here were estimated as shown in Table 2. Regardless of gender (for both sexes), the attributable number of DALY for dementia including all risk factors was 4253.4 (813.4, 11022.7). For mortality 209.9 (24.0, 655.2), YDL 1375.0 (366.1, 2814.0), and for YLL 2878.4(332.8, 8914.9). The age-standardized rates for all risk factors for mortality, DALY, YLD, and YLL were 5.1 (0.5, 15.9), 96.0(18.1, 251.7), 30.2(7.8, 62.2) and 65.8 (7.6, 204.4) per 100,000 in 2021, respectively. Of these four subgroups of all risk factors, Metabolic risks and High fasting plasma glucose were the main risk factors for all four indicators in either the attributable number or the age-standardized rate attributable, while not including gender. This pattern was consistent in men and women (Table 2).
The percentage changes for smoking in all age groups in both men and women for all four mortality indicators, DALY, YLL and YLD, were decreasing over the past three decades (1990–2021). For the other three risk factors (metabolic risks, high blood sugar and high BMI), the percentage changes for both men and women in all age groups for all four indicators were increasing. The largest percentage increase during 1990–2021 was for High Body Mass Index (Fig. 3).
Fig. 3.
Percentage change from risk factors Alzheimer’s disease and other dementia for four measures (Mortality, DALY, YLD and YLL) in During 1990–2021(Source: Global Burden of Disease 2021)
The results of the study showed that there is a positive and significant correlation between the Alzheimer’s ASIR and SDI in Asian countries (r = 0.284, p = 0.04). A positive and significant correlation was also observed between the SDI index and ASPR (r = 0.281, p = 0.01), which indicates that countries with a higher SDI index have higher ASIR and ASPR (Fig. 4).
Fig. 4.
The association between SDI and the ASIR and ASPR of ADOD in 2021. ASIR: Age-standardized incidence rate; ASPR, Age-standardized prevalence rate; SDI: Socio-demographic index. (Source: Global Burden of Disease 2021)
Discussion
The burden of Alzheimer’s disease and other dementias is significantly greater than that of other noncommunicable diseases among older age groups. Due to population growth and aging, along with the absence of definitive treatments, this issue should be a focal point for public health policy and research [3, 20].
The results for all indicators, including incidence, prevalence, mortality, DALYs, YLLs, and Years Lived with Disability (YLDs), indicated that there was no decline in these metrics in Asia from 1990 to 2021. This stagnation may be attributed to several factors, including significant advancements in diagnostic capabilities, increased life expectancy, improved medical care, and enhanced patient survival rates. Additionally, emerging risk factors, along with changes in lifestyle and environmental conditions, may continue to contribute to the incidence and prevalence of Alzheimer’s Disease and Other Dementias (ADOD). Consequently, the substantial burden of dementia on the public health system is likely to persist for the foreseeable future [22].
ASIRs, ASPRs, ASDRs, and DALYs (per 100,000 population) were consistently higher in women than in men during this period. This finding indicates that the disease burden is greater in women than in men. The differences in prevalence patterns between the sexes may be attributed to factors such as reproductive capacity, hormone levels, genetic susceptibility, and mental health [23]. Women are more likely to develop structural and functional disorders of the nervous system [24].
Mental health issues, such as depression, are twice as prevalent in women as in men [25]. The female brain is inherently more vulnerable to Alzheimer’s disease due to the influence of sex hormones [3].
On the other hand, the high life expectancy of women means that a significant proportion of the elderly population is female. This underscores the importance of dementia prevention, treatment, and targeted interventions for women [26].
Our results indicate that age-standardized incidence and prevalence rates are positively and significantly correlated with SDI, which may be attributed to higher life expectancy in regions with a high SDI, which often have a larger elderly population [27].
Regions with a high SDI have better medical services and allocate larger budgets for the care of individuals with dementia. In these areas, mortality rates from this disease are lower, while its prevalence is higher, as risk factors associated with mortality are identified at an early stage [28].
On the other hand, the decline in ASIR and ASPR (per 100,000 population) in certain regions with low Socio-Demographic Index (SDI) levels may be attributed to lower life expectancy in these areas [29].Variations in economic conditions, policies, and cultural factors among countries may also contribute to this complexity, making the interpretation of this issue challenging and necessitating further research.
The pharmacological treatments currently available for Alzheimer’s disease are limited, and there is no effective cure for this condition. Therefore, implementing effective programs to identify and manage its associated risk factors can be beneficial in preventing the progression of the disease [30].
Studies have shown that the incidence of metabolic diseases, such as high systolic blood pressure, elevated BMI, and diabetes, has significantly increased due to changes in lifestyle. Stress is often linked to detrimental lifestyle habits, including smoking, excessive alcohol consumption, and physical inactivity [10].
High-income countries and regions face an elevated risk of obesity, social stress, and insufficient physical activity, which consequently increases the risk of dementia. Additionally, in certain European countries, the incidence of dementia has declined. This reduction may be attributed to effective interventions implemented in recent years that target cardiovascular, metabolic, cognitive, behavioral, and other factors associated with dementia [27].
Screening for risk factors, along with the early detection and treatment of related diseases, can significantly reduce the risk factors associated with Alzheimer’s disease. Consequently, a variety of resources and facilities are essential to enhance the elderly care service system and the healthcare system for older adults.
Improved medical care and support systems may have contributed to the reduction in mortality rates and the increased life expectancy of individuals with dementia. In contrast, the age-standardized incidence and prevalence rates have not decreased, which could be attributed to several factors. There has been a significant increase in awareness and diagnostic capabilities for Alzheimer’s Disease and Other Dementias (ADOD), likely leading to a higher number of diagnoses and contributing to the rise in incidence and prevalence. As people live longer, the absolute number of individuals at risk of developing dementia also increases. With advancements in medical care, individuals with dementia are living longer, which contributes to the higher prevalence, even as mortality rates decline. Additionally, emerging risk factors or changes in lifestyle and environmental conditions may continue to influence the incidence and prevalence of ADOD [22].
The results indicated that among the four subgroups of risk factors, metabolic risks and high fasting plasma glucose were the primary contributors. A quantitative meta-analysis of 19 studies demonstrated that individuals with diabetes have a heightened risk of developing dementia compared to healthy individuals [19]. Additionally, 24 longitudinal studies provide evidence of an increased risk of Alzheimer’s disease among those with diabetes [31].
A recent large study conducted in the United States revealed that even in individuals without diabetes, elevated blood glucose levels significantly increase the risk of developing dementia, with the risk escalating alongside rising blood glucose levels [32]. A meta-analysis of case-control studies found that fasting blood glucose levels were higher in patients diagnosed with Alzheimer’s disease compared to control subjects [33]. These findings suggest that glucose metabolism is compromised in individuals with Alzheimer’s disease. Under conditions of elevated blood glucose and reduced insulin receptor sensitivity, the risk of Alzheimer’s disease may rise due to impaired mitochondrial function in nerve cells and an inflammatory response. Additionally, high blood glucose levels can enhance tau protein phosphorylation, leading to neuronal damage [33–35].
The study results indicated that the most significant percentage increase between 1990 and 2021 was associated with a high body mass index.
Studies have shown that obesity is a significant risk factor for Alzheimer’s disease (AD) and other forms of dementia [36–38]. An influential meta-analysis concluded that being overweight or obese during midlife is associated with a higher risk of developing dementia [8]. Furthermore, evidence indicates that the combination of obesity, diabetes, and aging increases susceptibility to dementia [39]. Effective weight management and the adoption of a healthy lifestyle can play a crucial role in reducing the risk of Alzheimer’s disease.
Although obesity is recognized as a risk factor for Alzheimer’s disease, further research is necessary to gain a deeper understanding of this association and to develop effective preventive strategies. It is essential to identify reliable markers to mitigate adverse effects and to initiate comprehensive prevention programs.
A survey conducted in Latin America, China, and India found that individuals with a history of smoking are more likely to develop dementia in these regions [40].
Smoking not only adversely affects physical health but also has harmful consequences for brain health, potentially increasing the risk of Alzheimer’s disease. Quitting smoking is one of the most effective strategies to mitigate this risk. A study revealed that the prevalence of smoking among all age groups, for both men and women, decreased from 1990 to 2021.
In a meta-analysis of 37 longitudinal studies, smoking was found to be associated with an increased risk of Alzheimer’s disease (AD) [12]. The oxidative stress in the brain linked to smoking may promote the production of amyloid or tau pathology [41]. In contrast, never-smokers exhibited an 18% reduced risk of developing Alzheimer’s disease compared to current smokers [42].
Conclusion
The prevalence and incidence of the disease were more severe in areas with a high Socio-Demographic Index (SDI), which warrants increased attention. Women were at a higher risk of developing the disease, an issue that should be addressed in health and prevention interventions. Our findings can inform global health policies and programs that guide resource allocation, emphasizing the need to support specific subgroups and regions. Public health interventions aimed at promoting healthier lives among older populations, particularly women, should be prioritized, taking into account relevant risk factors.
Acknowledgements
The authors would like to thank Global Burden of Disease and their staff for their willingness to provide the data required for this research.
Author contributions
Design: E.G., and K.Sh. Data Collection and/or Processing E.G., V.M., and S.Kh., Analysis or Interpretation: E.G.,K.Sh., and S.Kh., Writing: E.G., V.M., and A.S.
Funding
No additional funding was provided for this study.
Data availability
All the data used in this research were made available to the public at http://ghdx.healthdata.org/gbd-results-tool.
Declarations
Ethics approval and consent to participate
The study was approved by the ethics committee of Lorestan University of Medical Sciences code of ethics IR.LUMS.REC.1399.219.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
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Data Availability Statement
All the data used in this research were made available to the public at http://ghdx.healthdata.org/gbd-results-tool.