Risk of Dementia in Nepal: A Cross-Sectional Survey in Mountainous, Hilly, and Lowland Regions

doi:10.21203/rs.3.rs-4669563/v1

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Research Article

Risk of Dementia in Nepal: A Cross-Sectional Survey in Mountainous, Hilly, and Lowland Regions

https://doi.org/10.21203/rs.3.rs-4669563/v1

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Introduction

Globally dementia is a growing public health problem, with over 135,000 people in Nepal living with dementia. Nepal lacks national and community-based data on dementia prevalence. This study aims to determine the dementia risk in Nepal and assess the effects of age, sex, and geographical location on disease prevalence. It also intends to inform policy makers about the burden of dementia, prompting them to plan and prepare appropriate health and social care services for individuals affected by dementia.

Methods

A cross-sectional survey with total 1152 individuals (933 older people, aged 60 and over and 219 carers of 60 years and older people) was conducted to determine the prevalence of dementia risk in three geographical regions of Nepal. The Rowland Universal Dementia Assessment Scale (RUDAS) and Memory First Aid Informant Questionnaire adapted from Community Screening Interview for Dementia (CSI-D) for informant were used to measure cognitive impairment. The study evaluated the overall prevalence of cognitive impairment or risk of dementia and subgroups by region, age group, and sex. Chi-squared tests and multiple logistic regression analyses were conducted to assess the effects.

Results

For the RUDAS test, 53.7% (501) participants had cognitive impairment, with slightly higher rates in women (56.5%) than men (51.7%). For the Memory First Aid Informant Questionnaire/CSI-D for informant, 155 participants had cognitive impairment at a rate of 70.8%, with slightly higher rates in men. Cognitive impairment prevalence increases with age and region, with hilly and mountainous areas and low-lying regions having a greater geographic effect.

Conclusions

There is high risk of dementia in Nepal. The risk is influenced by age and geographical regions, necessitating early diagnosis and tailored interventions for older people and who are residing in higher altitude areas. National-level studies and exploration of factors affecting early dementia diagnosis are needed.

Dementia is a public health problem which requires urgent attention. Globally, the number of elderly people is increasing in proportion to the general population, leading to a corresponding increase in the number of people living with dementia, which is now the 7th leading cause of death worldwide [1]. More than 55 million people around the world are affected by dementia; with about 33 million living in Low- and Middle-Income Countries (LMICs). About 10 million new cases are diagnosed each year worldwide [2]. Correspondingly, the older age population is increasing in Nepal (an LMIC) as elsewhere, where people aged 60 + years old currently comprise about 10% of the total population [3], a 38.2% increase compared to the figure obtained from the previous census of 2011 [4]. It is estimated that over 135,000 people in Nepal may live with dementia, with almost 50% of the population over age of 60 years having some form of memory-related problems [5]. In Nepal, a recent study has determined that nearly 75% of older people living in residential homes in urban areas have dementia symptoms [6] and 93% of older people aged 60 years and above have mild cognitive impairment in one municipality [7]. The situation is compounded in Nepal by a tendency to dismiss symptoms of dementia as part of the normal ageing process, with a general lack of awareness of the symptoms of dementia in the general population [8].

Various factors have been reported to be associated with dementia in the literature; for example, gender, age, education, malnutrition, cardiovascular diseases [9, 10, 11]. Recent literature also has shown women are disproportionately affected by dementia and the prevalence is higher in women than in men [2,11]. Similarly, age is one of the most cited factors to increase the risk of dementia. The prevalence of dementia increases with age, doubling about every 5 years from 60 years until 85 years of age [11]. Similarly, loneliness is also reported to increase risk of dementia [12]. Recently, there have been massive changes in family dynamics in Nepal, with an increasing number of older people living alone or without their immediate family; circumstances that may have triggered older people to suffer from loneliness, depression and contribute poor health outcomes [13] and to increase the risk of dementia.

There are a few Nepalese studies [14,15] in dementia care and management, but there are no national and community-based data indicating the prevalence of dementia in Nepal [16]. Despite government policy availability for older people's health, very limited health facilities are available there. Nearly two-thirds of Nepal’s older adults who rely on primary health care centres (PHCCs) for health services lack basic screening facilities for dementia. Pathak and Gaire highlighted the need for community screening procedures for early identification [14]. The Nepalese health system preparedness in dementia is deprived, and the exact prevalence of dementia is unknown in Nepal. Therefore, this study is the first of its kind in Nepal to estimate the prevalence of cognitive impairment or to assess the risk of dementia associated with geographical location, gender, and age, which is key to ensure adequate public health policy is in place to support people suffering from this condition.

Aim

The main aims of this study are to determine the prevalence of cognitive impairment or risk of dementia in Nepal, and assess the effects of age, sex and geographical location on disease prevalence.

The specific objectives of the study are to:

compare the prevalences in three geographic regions (hilly, mountainous and low-lying) of Nepal.
determine the prevalence of cognitive impairment / risk of dementia in males and females; and those in different age groups (defined in bands of 5 years from age 60).
conduct logistic regression analyses to assess the effect of these factors on prevalence.
inform policy makers around dementia burden to provide appropriate health and social care services for people living with dementia.

This study employed a cross-sectional research design using a community-based survey from three geographical regions (Humla: mountainous region); Kavrepalachowk: hilly region) and Siraha: low-lying region) in Nepal. Stratified random sampling was utilised to select the study sites by region and the participants for better representation of the subgroups of the population and improved precision of estimates [17, 18].

A sample size of 334 in each geographic region was calculated to produce a two-sided 95% confidence interval with a width equal to 5%. Hence the study was designed to survey a minimum of 1002 individuals (both men and women) aged 60 + to determine the prevalence of dementia in the three regions of analysis.

The study used the translated Rowland Universal Dementia Assessment Scale (RUDAS) tool to assess cognitive impairment in people from all backgrounds [19]. We used a version of the RUDAS tool translated into Nepalese by Alzheimer’s and Related Dementias Society, piloted on two individuals aged 60 + years as it was not widely used and validated. We had to reword certain items for relevance in the wider context of Nepal. The Memory First Aid Informant Questionnaire (see Appendix 1) adapted from the Community Screening Interview for Dementia (CSI-D) for informants [20], as part of Memory First Aid programme in Nepal by Alzheimer’s and Related Dementias Society team was also used. This instrument was used to collect data about performance in everyday living from individuals who were not capable of providing this information themselves, and responses from carers were entered into the survey by enumerators. The Memory First Aid Informant Questionnaire/CSI-D for informants was used to interview family members on behalf of individuals who were not able to respond to the RUDAS tool. A Computer Assisted Personal Interview (CAPI) was utilised in the study, which included an option to complete questions from the Memory First Aid Informant Questionnaire/ CSI-D for informants and RUDAS instruments. KoboToolbox, a digital tool for the collection of quantitative data [21], was used as a data collection toolbox. All data were collected by the trained enumerators. Due to the state of cognitive impairment of research participants and the literacy challenges among many individuals, the enumerators completed the survey face-to-face, filling in responses given by participants.

Statistical analysis

The samples of patients who responded directly, and of carers responding on behalf of patients, were summarised descriptively. For both samples, the overall prevalence of cognitive impairment was evaluated for the whole sample, and for subgroups defined by region (categorised as low-lying, hilly or mountainous) age group (categorised as 60–64 years, 65–69 years, 70–74 years and 75 + years) and sex. For the sample self-completed by patients, cognitive impairment was diagnosed by a score of 22 or less in the RUDAS test. For data gathered from carers via survey enumerators, cognitive impairment was diagnosed by a score of 6 or more in the Memory First Aid Informant Questionnaire /CSI-D for informants test.

For both samples, chi-squared tests were conducted on the data to assess the significance of the age, region and sex factors in uncontrolled analyses. The magnitude of effects observed was quantified using the φ statistic. Multiple logistic regression analyses were conducted to assess the controlled effects of age, sex and region; reporting p-values, odds ratios and associated 95% confidence intervals (CIs).

Ethical considerations

The ethical approval from University of Huddersfield (SREIC/2021/090) and Nepal Health Research Council (Ref: 1303) was obtained prior to the study. Informed verbal and written consent from all participants were obtained prior to data collection. All participants were ensured that confidentiality, data protection, anonymity would be maintained. They were also explained that they have a right to withdraw from the study without any effect and the participation was voluntary.

Analysis of patient self-completing (RUDAS) data

Data was collected from 933 individuals (549 male) aged 60 years and over from three regions of Nepal: Humla (mountainous region); Kavrepalachowk (hilly region) and Siraha (low-lying region). The sample is summarised in Table 1 below.

Table 1: descriptive summary of sample (RUDAS/patient self-completers)

Variable

Frequency (valid %)

Region

Mountainous

Hilly

Low-lying

367 (39.3%)

238 (25.5%)

328 (35.2%)

Sex

Female

Male

384 (41.2%)

549 (58.8%)

Age group

60-64 years

65-69 years

70-74 years

75+ years

298 (31.9%)

241 (25.8%)

204 (21.9%)

190 (20.4%)

Under the assumption that prevalence of cognitive impairment was diagnosed by a score of 22 or less in the RUDAS test, 501 participants (53.7%) were classified as having cognitive impairment (95% confidence interval 50.5% to 56.9%).

Slightly higher prevalences of cognitive impairment were revealed in females than males. Prevalence of cognitive impairment by gender, with associated 95% confidence intervals (CIs), is summarised in Table 2 and Figure 1.

Table 2: prevalence of cognitive impairment and associated 95% CIs, by gender

Gender	Prevalence	95% CI for prevalence
Males	248/549; 51.7%	(47.6%, 55.9%)
Females	217/385; 56.5%	(51.6%, 61.5%)

The gender effect was not statistically significant at the 5% significance level (χ²₍₁₎=2.08; p=0.150).

A strong age effect was observed, with prevalence of cognitive impairment increasing monotonically in age. Prevalence of cognitive impairment by age group, with associated 95% confidence intervals (CIs), is summarised in Table 3 and Figure 2.

Table 3: prevalence of cognitive impairment and associated 95% CIs, by age group

Age group	Prevalence	95% CI for prevalence
60-64 years	131/298; 44.0%	(38.3%, 49.6%)
65-69 years	110/241; 45.6%	(39.3%, 51.9%)
70-74 years	126/204; 61.8%	(55.1%, 68.4%)
75+ years	134/190; 70.5%	(64.0%, 77.0%)

The age effect was significant (χ²₍₃₎=44.6; p<0.001) and large in effect (φ=0.219).

A strong geographic effect was also observed, with prevalence of cognitive impairment increasing with higher altitudes. Prevalence of cognitive impairment by region is summarised in Table 4 and Figure 3.

Table 4: prevalence of cognitive impairment and associated 95% CIs, by region

Region	Prevalence	95% CI for prevalence
Kavrepalanchowk (hilly)	110/238; 46.2%	(39.9%, 52.6%)
Humla (mountainous)	247/361; 67.3%	(62.5%, 72.1%)
Tarai (low-lying)	75/328; 22.9%	(18.3%, 27.4%)

The geographic effect was significant (χ²₍₂₎=137.6; p<0.001) and very large in effect (φ=0.384).

A multiple logistic regression conducted on the data revealed that in a controlled model, compared to the reference category of age 50-64 years; all age groups were significantly associated with the prevalence of cognitive impairment (p=0.043 for age 65-69, p<0.001 for other age groups); compared to the reference category of low-lying region, both hilly and mountainous regions were significantly associated with the prevalence of cognitive impairment (p<0.001 in all cases); and sex was significantly associated with cognitive impairment (p<0.001). Model parameters are summarised in Table 5.

Table 5: logistic regression parameters (RUDAS/patient self-completers)

Variable

p-value

Odds ratio

95% CI for OR

Sex

Female (reference)

Male

<0.001

1.83

(1.34, 2.49)

Age group

60-64 years (reference)

65-69 years

70-74 years

75+ years

0.043

<0.001

1.49

3.17

6.41

(1.01, 2.19)

(2.07, 4.83)

(4.05, 10.2)

Region

Low-lying (reference)

Hilly

Mountainous

<0.001

3.13

11.8

(2.13, 4.61)

(7.97, 17.6)

Analysis of carers’ data (Memory First Aid Informant Questionnaire/CSI-D for informant)

Data was collected from carers of 219 older people (102 male) aged 60 years and over from the same three regions of Nepal utilised in the collection of data directly from older people.

The sample is summarised in Table 6 below.

Table 6: descriptive summary of sample (Memory First Aid Informant Questionnaire/CSI-D- for informant /carer completion)

Variable

Frequency (valid %)

Region

Mountainous

Hilly

Low-lying

22 (10.0%)

136 (62.1%)

61 (27.9%)

Sex

Female

Male

117 (53.4%)

102 (46.6%)

Age group

60-64 years

65-69 years

70-74 years

75+ years

32 (14.6%)

50 (22.8%)

67 (30.6%)

70 (32.0%)

Under the assumption that prevalence of cognitive impairment was diagnosed by a score of 6 or more in the CSID for informant test, 155 participants (70.8%) were classified as having cognitive impairment (95% confidence interval 64.8% to 76.8%).

Slightly higher prevalences were revealed in males than females. Prevalence of cognitive impairment in males and females is summarised in Table 7 and Figure 4.

Table 7: cognitive impairment by gender (CSI-D for informant/carer completion)

Gender	Prevalence	95% CI for prevalence
Males	78/102; 76.5%	(70.9%, 82.1%)
Females	77/117; 65.8%	(59.5%, 72.1%)

The gender effect was not statistically significant at the 5% significance level (χ²₍₁₎=2.99; p=0.084).

Table 8: prevalence of cognitive impairment and associated 95% CIs, by age group

Age group	Prevalence	95% CI for prevalence
60-64 years	8/32; 25.0%	(19.3%, 30.7%)
65-69 years	32/50; 64.0%	(57.6%, 70.4%)
70-74 years	52/67; 77.6%	(72.1%, 83.1%)
75+ years	63/70; 90.0%	(86.0%, 94.0%)

The age effect was significant (χ²₍₃₎=47.6; p<0.001) and very large in effect (φ=0.466). The main effect can be seen to be a step change in prevalence between the youngest and second-youngest age groups (Figure 3).

A strong geographic effect was observed, with prevalence of cognitive impairment increasing with higher altitudes. Prevalence of cognitive impairment by geographical region is summarised in Table 9 and Figure 6.

Table 9: prevalence of cognitive impairment and associated 95% CIs, by region

Region	Prevalence	95% CI for prevalence
Kavrepalanchowk (hilly)	114/136; 83.8%	(78.9%, 88.7%)
Humla (mountainous)	19/22; 86.4%	(81.8%, 90.9%)
Tarai (low-lying)	22/61; 36.1%	(29.7%, 42.4%)

The geographic effect was significant (χ²₍₂₎=49.3; p<0.001) and very large in effect (φ=0.475).

A multiple logistic regression conducted on the data revealed that in a controlled model, compared to the reference category of age 50-64 years; all age groups were significantly associated with the prevalence of cognitive impairment (p=0.020 for age 65-69, p<0.001 for other age groups); compared to the reference category of low-lying region, both hilly and mountainous regions were significantly associated with the prevalence of cognitive impairment (p<0.001 in all cases). Sex was not significantly associated with CSI (p=0.721). Model parameters are summarised in Table 3.

Table 10: logistic regression parameters (Memory First Aid Informant Questionnaire/CSI-D for informant/carer completers)

Variable

p-value

Odds ratio

95% CI for OR

Sex

Female (reference)

Male

0.721

1.15

(0.536, 2.46)

Age group

60-64 years (reference)

65-69 years

70-74 years

75+ years

0.020

<0.001

3.72

7.65

23.6

(1.23, 11.3)

(2.49, 23.5)

(6.73, 82.7)

Region

Low-lying (reference)

Hilly

Mountainous

<0.001

8.37

11.5

(3.81, 18.4)

(2.56, 51.4)

This study was conducted with 1152 individuals (including 933 individuals aged 60 and older, and 219 carers of 60 years and older) to determine the prevalence of cognitive impairment or risk of dementia in Nepal. It compared the prevalence of cognitive impairment across different age groups, males, and females and three geographic regions of Nepal: Humla (mountainous region); Kavrepalachowk (hilly region) and Siraha (low-lying region).

The prevalence of cognitive impairment or risk of dementia in the Memory First Aid Informant Questionnaire/CSI-D for informant, carer-completed survey was 70.8% and the prevalence of cognitive impairment or risk of dementia in older people completing RUDAS survey was 53.7%. The prevalence revealed by the Memory First Aid Informant Questionnaire/CSI-D for informants instrument was similar to that found in a recent study in Nepal, which revealed that 75% of older adults have dementia symptoms using the Cognitive Impairment Test (CIT) tool in residential care homes [6]. About 93.0% was screened for mild cognitive impairment with 115 individuals (60 years and older) using the Montreal Cognitive Assessment (MoCA) [7]. However, the prevalence of cognitive impairment revealed in the current investigation is much higher than found in a recent systematic review focused on global prevalence, using results from 80 studies which revealed a range of 5–41% [22]; and in another national study from China, which found a prevalence rate of 22.2% [23]. It is interesting to note that the prevalence of cognitive impairment is even higher when using different tools in different settings. Therefore, it is important to understand how this prevalence varied with different tools used and context. Further, the high prevalence reported in this study does not mean that most or all people will develop dementia in later life. However, it may indicate a raised risk for onset of dementia. Therefore, comprehensive diagnoses are required after an indication of depression to rule out other possible problems such as delirium and depression (pseudodementia) in this group. Depression is a risk factor for dementia [24] and very common in older people, ranging from 25–60% with depression in the community. This proportion is higher in hospital and residential care homes in Nepal [25, 26]. Context is important to consider in the diagnosis process.

Gender

Results from the RUDAS tool revealed a higher prevalence of cognitive impairment among females than males. Although the difference is not statistically significant, we find that it aligns with previous studies [6,27]. Conversely, results from the CSI-D for informant tool show that prevalence of cognitive impairment or risk of dementia in males is slightly higher (not statistically significant) than in females; inconsistent to a recent study conducted using the CIT tool in care home settings in Nepal, which indicated a higher prevalence in females [6,28]. However overall findings from both tools reveals no significant difference in proportions of cognitive impairment in males and females which is consistent with a previous study [29]; further, it is noteworthy that only few studies have reported significant differences in the prevalence of dementia with respect to gender [30].

Gender-related lifestyle factors may impact on dementia to different extents in males and females in certain cultures; such as higher levels of smoking and alcohol consumption reported among males than in females in the Nepalese community [31, 32]. Alcohol and smoking are known risk factors for dementia and cognitive impairment [31]. There is a need for additional research to understand the impact of gender-related risk factors for cognitive impairment or dementia. Lifestyle-related risk factors can change over time; therefore, a longitudinal cohort study may be useful to understand how gender-related lifestyle factors can impact on the risk of dementia.

Age

The prevalence of cognitive impairment or risk of dementia increases monotonically with age in both samples featured in this study, reflecting a significant age effect. There is evidence in the literature highlighting the increasing risk of dementia with age [33, 34]. Therefore, community-level screening could be one of the best strategies to recognise the risk of dementia as early as possible and it might be beneficial to develop early interventions to reduce the risk. Using new technologies that help to identify biomarkers may be useful in the early diagnosis, prevention, and treatment of cognitive decline [35, 36]. The global action plan for a public health response to dementia in the period 2017–2025 also describes goals and suggested courses of action to help nations handle the expanding global dementia crisis [37]. According to the action plan, universal access to care and support for individuals with dementia and their carers depends on prompt and accurate dementia diagnosis, ideally provided at the primary care level. Literature has suggested being cognitively, physically, and socially active from midlife help to reduce the risk of dementia [31]. The awareness programme should focus on risk factors of dementia, recognising early signs and symptoms of dementia and promoting healthy lifestyles (31 37]. Understanding the significance of cardiovascular risk factors that increase the risk of dementia is also important [9, 35]; as is the ability to recognise early symptoms and signs of dementia; and increasing the people’s knowledge of risk factors associated with dementia, thereby promoting healthy lifestyles and risk reduction behaviour in all.

Geographic region

A noticeable geographic effect was observed in this study, with prevalence of cognitive impairment associated with living at higher altitudes. This could be associated with rurality, as people living in mountainous area may have many challenges in their daily life due to the local terrain and may also face difficulties in accessing care facilities. The aetiology of dementia may have significant socio-environmental contributions, as suggested by regional variations in dementia prevalence [38]. A systematic literature review comprising 51 studies across the world shown that people living in rural areas had higher prevalence of dementia than those in urban areas [38]. Similar findings were noted among Thai and Chinese people living in rural areas, who had higher prevalence of dementia symptoms [23, 39]. The literature suggests that LMICs are not well prepare to care for, and support the anticipated future rise in the number of dementia patients and need for advance care planning [40]. Hence, there is a need to prioritise research in rural and underserved areas, as well as low resource settings areas to further establish the relationship between geographic region and dementia, along with the possible explanation for the differences.

Strengths and Limitations:

To the best of our knowledge, this is the first study of its kind to compare the prevalence of cognitive impairment or risk of dementia across different geographic locations in Nepal. The findings of this study could help raising awareness about on dementia and prioritise the health and social care demand and preparedness across different geographical regions in Nepal.

This study utilised the most widely used tools, translated in Nepali to measure cognitive impairment [19, 20] although these tools are translated but still to be validated in different context of Nepal. We acknowledge that RUDAS was translated and tested in Kathmandu [41] but we recognise that the adaptation was not entirely appropriate for the wider Nepali context. Therefore, we used a Nepali version translated by professionals working in Demetia care from Alzheimer’s and Related Dementias Society. Some adaptations were further made to the example used in the tools following consultation with a local expert who involved in translation of these Nepali tools to ensure relevancy in the Nepali context: for example, the item 5 on judgement in RUDAS elicits a response to the statement there is no pedestrian crossing and no traffic lights. This statement is inappropriate to Nepali respondents based outside the capital city of Kathmandu, as there are hardly any roads outside Kathmandu with traffic lights and pedestrian crossings. The item was accordingly amended. In the same question, typical examples of traffic found in each of the featured geographical areas were included: for example, yaks, sheep, goats, mules in the mountainous area; rickshaws, horse and cart, buses and cars in the hilly area; and buses, trucks, cars and taxis in the low-lying urban area. Similarly, we amended certain items which had been adapted and translated by the Alzheimer’s and Related Dementias Society team. For example, to an item of the CSI-D for informant tool offering options of methods of eating, we added hand along with spoon as an additional response option, because many Nepalese eat with their hands. Similarly, for question number 23 of the CSI-D for informant tool regarding “difficulty dressing”, a further option of zipper with button was added. It is not considered that any of these amendments have any implications for instrument validity.

This study acknowledges that prevalence may disagree with different scales, as noted in previous studies using various tools. Further research is needed to establish whether the adapted questionnaire from CSI-D for informant, known as Memory First Aid Informant Questionnaire, is appropriate and is interpreted by caregivers in the same way that the RUDAS self-reporting tool is interpreted by participants who record their activity directly using this tool.

The prevalence of cognitive impairment or risk of dementia is high in Nepal, with various factors affecting older people’s cognitive impairment. There is some effect on prevalence of cognitive impairment of age, gender, and geographical location. Therefore, it is important for awareness of dementia and importance of early diagnosis to improve the quality of life of people living with dementia. The significant geographic differences in cognitive impairment calls for tailored interventions and support systems that are specific to each region. This could include establishing specialised dementia care centres and training community healthcare professionals to identify early signs of cognitive decline. Additionally, implementing educational programmes in schools and community centres can help reduce the stigma surrounding dementia and promote a more inclusive society for individuals living with the condition. As diverse data is seen in different countries, there is need for national level prevalence studies and exploration of different factors affecting access to early diagnosis of dementia. Policies implemented to address this issue should prioritise community awareness and early screening and diagnosis to reduce complications from dementia.

Ethics approval and consent to participate: The study protocols were approved by University of Huddersfield (SREIC/2021/090) and Nepal Health Research Council (Reference no. 1303). All participants were fully informed about the study's purpose, benefits, and potential risks prior to participation, and written consent was obtained from all respondents. The study obeyed to the ethical standards defined in the Declaration of Helsinki.

Availability of data and materials: The datasets used and/or analysed during the current study are available from the lead author (BS) on reasonable request.

Consent for publication: Not applicable.

Competing interests: The author declares they have no competing interests.

Funding: University of Huddersfield

Authors' contributions: BS developed the concept and took the lead in the funding application, literature review, analysed and interpreted the data. JS performed statistical analysis and finalised manuscript. BS drafted the initial version. STM supervised and managed the data collection. BS and JS ensured consistency in data analysis and proofread the manuscript. PS provided feedback and supported to finalise the manuscript. PT involved in project development and ethical approvals. All authors read and approved the final manuscript.

Acknowledgements: We are very thankful to all the participants for their time and support. We are grateful to Mr Prabhat Pradhan for providing Nepali translated tools by Alzheimer’s and Related Dementias Society and training to enumerators around dementia with the research team.

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Risk of Dementia in Nepal: A Cross-Sectional Survey in Mountainous, Hilly, and Lowland Regions

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