This indicator measures the number of people that have been diagnosed with dementia as a proportion of the number who are estimated to have the condition.

Purpose

This indicator aims to capture the quality of life of people with dementia. It measures the extent of diagnosis for people with dementia by estimating the proportion of the population that has been diagnosed with the disease.

Current version updated: Feb-16

Next version due: To be confirmed

The Brain Health Data Pilot (BHDP) project aims to be a shared database (like a library) of information for scientists studying brain health, especially for diseases like dementia, which affects about 900,000 people in the UK. Its main feature is a huge collection of brain images linked to routinely collected health records, both from NHS Scotland, which will help scientists learn more about dementia and other brain diseases. What is special about this database is that it will get better over time – as scientists use it and add their discoveries, it becomes more valuable.

This dataset is a subset of the Scottish Accident and Emergency data for use with the BHDP project.

Accident and Emergency Statistics. The A&E datamart was established in June 2007 to monitor the compliance of each NHS Board against the 4 hour wait standard. In July 2010 the A&E data mart was extended further to collect items such as diagnosis, several injury fields and an alcohol involved flag, which will be used to identify whether the patient’s alcohol consumption was a factor in the attendance. The collection of the new fields has been driven by a variety of SG policy decisions and interest from a number of organisations. Although there is now the facility to submit these additional fields, they are still under development and ISD are working with the NHS Boards to support data collection and quality. There are two types of data submitted to the A&E datamart: episode and aggregate level data. All hospitals with Emergency Departments submit episode level data containing a detailed record for each patient attendance. Some smaller sites with minor injury units or community hospitals only submit aggregate files containing monthly summary attendance and compliance figures only. This is because they do not have the information systems and support to enable collection of detailed patient based information. Sites that submit episode level data account for around 94% of all attendances at A&E.

Care Homes provide a residential setting for people that require 24 hour care. The majority of Care Homes provide services for older people, but some offer services to Children and those with Mental or Sensory Impairments.

All Care Homes in the UK are registered, inspected and listed by the relevant authority, which in England and Wales is currently the Care Quality Commission (CQC) There are two main categories of care home; those which provide only personal care and those which also provide nursing care. In addition, some Care Homes provide specialist care, eg for Dementia or Terminal Illness

Care Homes are often run by groups. In these instances we provide the group name and details and record a link from each home to its parent organisation, but we list each home as separate entities due to each having their own considerations/services.

Type of ownership:

The database details the type of ownership of the Homes

Private Homes run by individuals, partnerships and public and private limited companies.

Voluntary Homes that are run by Charities such as The Leonard Cheshire Foundation or Mencap.

Public Homes that are run by Local Authorities and NHS Trusts

Number of beds:

We list the number of Beds for each organisation. The average size of home is approximately 20 beds, whilst only 10% have more than 50 beds. There are almost 3,000 homes with five or fewer beds. These usually provide very specific types of care, including provision for Care in the Community and, if privately owned, should not normally be regarded as commercial undertakings.

The English Longitudinal Study of Ageing (ELSA) is a longitudinal survey of ageing and quality of life among older people that explores the dynamic relationships between health and functioning, social networks and participation, and economic position as people plan for, move into and progress beyond retirement. The main objectives of ELSA are to:

• construct waves of accessible and well-documented panel data;
• provide these data in a convenient and timely fashion to the scientific and policy research community;
• describe health trajectories, disability and healthy life expectancy in a representative sample of the English population aged 50 and over;
• examine the relationship between economic position and health;
• investigate the determinants of economic position in older age;
• describe the timing of retirement and post-retirement labour market activity; and
• understand the relationships between social support, household structure and the transfer of assets.

Further information may be found on the "https://www.elsa-project.ac.uk/"> ELSA project website, the or Natcen Social Research: ELSA web pages.

Wave 11 data has been deposited - May 2025

For the 45th edition (May 2025) ELSA Wave 11 core and pension grid data and documentation were deposited. Users should note this dataset version does not contain the survey weights. A version with the survey weights along with IFS and financial derived datasets will be deposited in due course. In the meantime, more information about the data collection or the data collected during this wave of ELSA can be found in the Wave 11 Technical Report or the User Guide.

Health conditions research with ELSA - June 2021

The ELSA Data team have found some issues with historical data measuring health conditions. If you are intending to do any analysis looking at the following health conditions, then please read the ELSA User Guide or if you still have questions contact elsadata@natcen.ac.uk for advice on how you should approach your analysis. The affected conditions are: eye conditions (glaucoma; diabetic eye disease; macular degeneration; cataract), CVD conditions (high blood pressure; angina; heart attack; Congestive Heart Failure; heart murmur; abnormal heart rhythm; diabetes; stroke; high cholesterol; other heart trouble) and chronic health conditions (chronic lung disease; asthma; arthritis; osteoporosis; cancer; Parkinson's Disease; emotional, nervous or psychiatric problems; Alzheimer's Disease; dementia; malignant blood disorder; multiple sclerosis or motor neurone disease).

For information on obtaining data from ELSA that are not held at the UKDS, see the ELSA Genetic data access and Accessing ELSA data webpages.

Wave 10 Health data
Users should note that in Wave 10, the health section of the ELSA questionnaire has been revised and all respondents were asked anew about their health conditions, rather than following the prior approach of asking those who had taken part in the past waves to confirm previously recorded conditions. Due to this reason, the health conditions feed-forward data was not archived for Wave 10, as was done in previous waves.

Harmonized dataset:

Users of the Harmonized dataset who prefer to use the Stata version will need access to Stata MP software, as the version G3 file contains 11,779 variables (the limit for the standard Stata 'Intercooled' version is 2,047).

ELSA COVID-19 study:
A separate ad-hoc study conducted with ELSA respondents, measuring the socio-economic effects/psychological impact of the lockdown on the aged 50+ population of England, is also available under SN 8688, English Longitudinal Study of Ageing COVID-19 Study.

The IDEAL programme is a longitudinal cohort study of people with dementia (PwD) and primary carers (Carers) across Great Britain, led by the Centre for Research in Ageing and Cognitive Health (REACH) at the University of Exeter. The data in this archive relate to the first part of the programme (Waves 1 to 3), which took place between March 2014 and December 2019. The aim of the IDEAL programme is to identify what helps people to live well or makes it difficult to live well in the context of having dementia or caring for a person with dementia, and to understand what ‘living well’ means from the perspective of PwD and Carers. IDEAL conceptualised living well as including satisfaction with life, psychological well-being, and quality of life. The research questions that were central to the development of the programme are as follows: 1. How do capitals, assets and resources, and adaptation in response to dementia-related and other challenges, influence the ability to live well for PwD and Carers, and what are the reciprocal influences between PwD and Carers factors? 2. How do changes over time in capitals, assets and resources, dementia-related and other challenges, and adaptation affect evaluations of living well for PwD and Carers? 3. What do PwD and Carers believe helps or hinders the possibility of living well, and what factors are particularly important to them as regards being able to live well with dementia? At Baseline (Wave 1), data from 1547 PwD and 1283 Carers were included in the programme. Participants were interviewed again at 12 months (Wave 2; 1190 PwD and 992 Carers) and 24 months (Wave 3; 856 PwD and 760 Carers). Interviews were carried out in participants’ own homes. Researchers were NHS staff working from one of 29 research sites across Great Britain. Completed surveys were returned to North Wales Organisation for Randomised Trials in Health (NWORTH) for data entry and dataset production.

Living well with dementia, whether as a person with dementia or primary (usually family) carer, can be understood as optimising satisfaction with life, reaching one’s potential for well-being, and experiencing the best possible quality of life (QoL). Enabling people with dementia (PwD) and carers to live well with dementia is a key UK policy objective, but policy recommendations do not tell us how this can be achieved. The IDEAL programme, led by the Centre for Research in Ageing and Cognitive Health (REACH) at the University of Exeter, aims to understand what ‘living well’ means from the perspective of people with dementia and carers and how this changes over time, and to identify how best to enable people with dementia and carers to live well. The first phase of IDEAL, funded by ESRC and NIHR, was conducted between 2014 and 2019, and focused on a longitudinal cohort study in which people with mild-to-moderate dementia were recruited, where possible with an accompanying carer, from memory services in 29 NHS sites throughout Great Britain and through the online Join Dementia Research portal. Participants were assessed at three yearly intervals (Waves 1, 2 and 3) by clinical research network staff. At Wave 1, the cohort comprised 1547 people with dementia and 1283 carers. At Wave 2, 1190 people with dementia and 992 carers remained in the study, and at Wave 3 856 people with dementia and 760 carers contributed. Participants were interviewed in their own homes and completed measures reflecting their ability to live well (quality of life, satisfaction with life, and well-being), and a range of social, psychological, physical, environmental and economic factors potentially associated with ability to live well. Carers, where available, provided information about both the person with dementia and their own experiences. Completed surveys were returned to the North Wales Organisation for Randomised Trials in Health (NWORTH) for data entry and dataset production. From the main cohort a smaller group of 20 people with dementia whose ability to live well improved or declined over the first year of the study was identified, and these individuals and their carers were interviewed in more depth in years 2 and 3. Involvement of people with dementia and carers was integral to developing and conducting the IDEAL programme and ensuring its relevance. The ongoing second phase of IDEAL, funded as an Alzheimer’s Society Centre of Excellence, involves continued follow up of the cohort participants alongside additional work focused on inclusion of ‘seldom heard’ groups.

The Brain Health Data Pilot (BHDP) project aims to be a shared database (like a library) of information for scientists studying brain health, especially for diseases like dementia, which affects about 900,000 people in the UK. Its main feature is a huge collection of brain images linked to routinely collected health records, both from NHS Scotland, which will help scientists learn more about dementia and other brain diseases. What is special about this database is that it will get better over time – as scientists use it and add their discoveries, it becomes more valuable.

This dataset is a subset of the Prescribing Information System (PIS) data for use with the BHDP project.

The information is supplied by Practitioner & Counter Fraud Services Division (P&CFS) who is responsible for the processing and pricing of all prescriptions dispensed in Scotland. These data are augmented with information on prescriptions written in Scotland that were dispensed elsewhere in the United Kingdom. GP’s write the vast majority of these prescriptions, with the remainder written by other authorised prescribers such as nurses and dentists. Also included in the dataset are prescriptions written in hospitals that are dispensed in the community. Note that prescriptions dispensed within hospitals are not included. Data includes CHI number, prescriber and dispenser details for community prescribing, costs and drug information. Data on practices (e.g. list size), organisational structures (e.g. practices within Community Health Partnerships (CHPs) and NHS Boards), prescribable items (e.g. manufacturer, formulation code, strength) are also included. Around 100 million data items are loaded per annum.

This is a subset of National Records of Scotland (NRS) - Deaths dataset for use in the Brain Health Data Pilot (BHDP) project.

The Brain Health Data Pilot (BHDP) project aims to be a shared database (like a library) of information for scientists studying brain health, especially for diseases like dementia, which affects about 900,000 people in the UK. Its main feature is a huge collection of brain images linked to routinely collected health records, both from NHS Scotland, which will help scientists learn more about dementia and other brain diseases. What is special about this database is that it will get better over time – as scientists use it and add their discoveries, it becomes more valuable.

BackgroundDementia is a chronic and progressive illness characterized by severe impairment and high dependencies. Under the influence of Chinese traditional culture, 80% of patients with dementia are watched over at home by family caregivers as primary caregivers. However, long-term care brings formidable burdens to them and reduces the quality of their life. It is necessary to find out the influencing factors of caregivers’ burden.MethodsA scoping search was conducted on eight electronic databases from 1 January 2010 to 14 June 2022: PubMed, Embase, the Cochrane Library, Web of Science, China National Knowledge Infrastructure, China VIP Database, China Biomedical Literature Database, and Wanfang Data Knowledge Service Platform. Research articles included in this review discussed the factors affecting Chinese dementia family caregivers’ care burden or stress, and the level of care burden was evaluated by a standardized care burden scale.ResultsA total of 1,888 related articles were found and 23 cross-sectional studies were eventually included. After quality assessment, 12 were of good quality and 11 were of fair quality. A total of 32 factors were identified that were associated with caregiver burden, and the results were grouped into three categories: patient, caregiver, and society. The severity of disease, poor self-care ability, neuropsychiatric symptoms, care time, number of helpers, poor health status, economic stress, poor psychological status, social support, and age were reported in many previous studies.ConclusionIn this review, the factors that affect the caregiver burden for people with dementia were clarified. By identifying these factors, hospitals, decision-makers, and communities can carry out special projects for these populations, provide appropriate assistance, or design corresponding intervention measures to reduce the caregiver burden and improve the quality of care for patients with dementia.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42022347816].

Data collection is from a parallel group, two-arm, multicentre, feasibility, randomised controlled trial to examine the feasibility of conducting a definitive randomised trial comparing the clinical and cost-effectiveness of the PRIDE intervention (a self-management intervention designed to promote living well and enhance independence) offered in addition to usual care to usual care alone for people with mild dementia. This was work package 4 of the Promoting Independence in Dementia Research Programme funded by the ESRC and NIHR Programme for Applied Research.

People with dementia lose much more than just their memory and daily living skills. They can also lose their independence, their dignity and status, their confidence and morale, and their roles both within the family and beyond. They can often be seen as a burden by society, their families and even by themselves, and feel unable to contribute to society, and they lack opportunities to reciprocate by doing things for others. This adds to the stigmatising of people even if they only have mild memory problems. The focus of this study is promoting independence in dementia which could have substantial benefits for the people with dementia, their families, and NHS and social care. This should translate into major economic (eg reduced costs of care) and societal benefits. Dementia is a national priority and this proposal addresses the Prime Minster's commitment to dementia research and the need to improve community support. In the UK over 800,000 older people have dementia costing the nation over £17 billion a year through the provision of health and social care services. Dementia has profound effects on family carers who through their actions save the UK economy over £6 billion a year. This means there is a need both to better understand the impact of social and lifestyle factors on the broader ageing population at risk of dementia, and to promote independence and quality of life for people with dementia. This study aims: (a) to identify how social and lifestyle changes may help reduce risk of developing dementia and disability and to better understand the social consequences of dementia. (b) to develop and evaluate an effective social intervention to support independence and quality of life for people with early stage dementia and their carers. The first aim will be addressed using the information from the English Longitudinal Study of Ageing (ELSA) cohort which has followed up over 10,000 older people biennially over ten years, collecting information about their health, wealth, lifestyle and social activities. Our initial analysis of the data set indicates that the use of email/internet may reduce cognitive decline and that staying physically active can help improve people's daily living skills. We will do further analyses looking at the frequency of dementia amongst older people in the community and the potential impact of changes in lifestyle (eg exercise, use of computers) on how cognitive abilities may change over time. In the next two ELSA surveys (2014 and 2016) we will ask people about their expectations of ageing, including memory loss and dementia, the associated fear and stigma and what would make it more or less likely for them to seek help if needed. We will explore the concerns and expectations people have (eg loss of identity and loss of independence) at the point of referral to memory services, at the point of diagnosis, and for the following two years. We will also investigate their experiences in terms of loss of role and quality of life. The second aim will be investigated by using an in depth consultation with people with dementia and their carers and an appraisal of the scientific evidence to develop an evidence based social intervention designed to promote independence and support lifestyle changes most likely to benefit cognition (eg physical activity, use of computers) delivered by a dementia advice worker. In a large clinical trial of memory services across the UK, the intervention will be evaluated in comparison to usual care to evaluate potential benefits to independence and quality of life.

In the MODEM cohort study, three-hundred and seven people with clinically diagnosed dementia and their carers were recruited on a quota basis to provide equal numbers of people with mild (standardised Mini-Mental State Examination (sMMSE), n = 110), moderate (sMMSE 10–19, n = 100), and severe (sMMSE 0–9, n = 97) cognitive impairment. Participants had a medical diagnosis of dementia made by a specialist mental health service. To be eligible the person with dementia needed to have an identifiable family (or friend) carer or other informant (e.g. a formal/professional carer). There were no exclusion criteria based on comorbidities, age, or type of dementia. The carer was required to self-identify themselves as a carer for the person with dementia. There were no other inclusion or exclusion criteria. Participants were recruited from memory services in Sussex, UK, or self-referral from a national electronic database (Join Dementia Research; https://www.joindementiaresearch.nihr.ac.uk/), community groups, and care homes in the South East of England. People with dementia and their carers were provided with information about the research and invited to participate in the study. A pair of researchers then visited the participants in their home (or another location convenient for the participant). The capacity of the person with dementia was formally assessed by a trained researcher. If the person with dementia did not have capacity to consent, a personal consultee (family member/friend) was identified to advise on whether the person with dementia should take part. For those with capacity, informed consent was obtained. The two researchers then completed a series of measures with the person with dementia and the carer in parallel. For the person with dementia, the following measures were collected: self-reported quality of life (DEMQOL, EQ-5D-3L, CASP-19); proxy-reported quality of life (DEMQOL-Proxy, EQ-5D-3L); severity of cognitive impairment (sMMSE, ADAS-COG); neuropsychiatric symptoms (NPI), depression (Cornell scale); activity limitation (BADLS, OARS); and comorbidities (CCI). Measures collected for the carer were: self-reported measures of quality of life (EQ-5D-3L, SF-12); social isolation (SIS); carer burden (ZCBI); and mental well-being (GHQ). Data were also collected on the use of services and level of help received by formal and unpaid carers and provided by the carer (CSRI) and demographic characteristics of the person with dementia and carer.

Dementia has enormous impacts on health and quality of life for people with the illness, their families and other people who care for them. Many people with dementia need care in many areas of their lives, and use a range of health and social care services, as well as getting support from their unpaid carers. Many people with dementia eventually move into care homes. The costs of caring for people with dementia can therefore be high. As the UK population ages over the coming decades, the number of people with dementia will increase considerably. A big challenge facing the country is how to provide high-quality treatment and support to these individuals in ways that are acceptable to them and at a cost considered by society to be affordable. In England, care and support arrangements are guided by the National Dementia Strategy; there are similar commitments in Scotland, Wales and Northern Ireland. Dementia is now getting unprecedented attention: it is a high priority for government, the NHS and local councils. Our research feeds new evidence into this national debate to help decision-makers at many levels in health and social care systems to meet the needs and respond to the preferences of people with dementia and their carers in ways that make best use of the country's resources. We examined existing data to get a clearer understanding of the links between a number of factors: the characteristics of individuals and families, their dementia-related and other needs for care and support, and the services and treatments that could be available to them. We looked at the effects of care, support and treatments on outcomes for individuals and carers - how those interventions can improve their health and wellbeing - and also on the costs of support. With this information we first made projections of how many people there will be with dementia over the period to 2040, what family or other unpaid support they are likely to have available, and what it will cost to provide care services. Second, we examined whether there are better ways to support people with dementia and their carers by introducing new forms of care and treatment. For this part of the research we relied on previous studies that have examined whether these interventions improve health and wellbeing, and at what cost. We identified those 'new ways' by reviewing previous studies of dementia care and treatment (and also reviewing ways to prevent or delay dementia). We looked for evidence on, e.g.,...

The Brain Health Data Pilot (BHDP) project aims to be a shared database (like a library) of information for scientists studying brain health, especially for diseases like dementia, which affects about 900,000 people in the UK. Its main feature is a huge collection of brain images linked to routinely collected health records, both from NHS Scotland, which will help scientists learn more about dementia and other brain diseases. What is special about this database is that it will get better over time – as scientists use it and add their discoveries, it becomes more valuable.

This is a subset of the Mental Health Inpatient and Day Case - Scottish Morbidity Record (SMR04) dataset for use in the Brain Health Data Pilot (BHDP) project.

The dataset contains a wide variety of information such as patient characteristics, mental health diagnosis, length of stay, destination on discharge, whether they are admitted under Mental Health Legislation and any previous psychiatric care. Patient identifiers such as name, date of birth, Community Health Index number, NHS number, and postcode are included together with a wide variety of geographical measures. This includes the Scottish Index of Multiple Deprivation and Carstairs measures, census output area, NHS Board, Electoral Ward and Parliamentary constituency.

Legacy unique identifier: P01754

The Brain Health Data Pilot (BHDP) project aims to be a shared database (like a library) of information for scientists studying brain health, especially for diseases like dementia, which affects about 900,000 people in the UK. Its main feature is a huge collection of brain images linked to routinely collected health records, both from NHS Scotland, which will help scientists learn more about dementia and other brain diseases. What is special about this database is that it will get better over time – as scientists use it and add their discoveries, it becomes more valuable.

This is a subset of the Outpatient Appointment and Attendances (SMR00) dataset for use in the Brain Health Data Pilot (BHDP) project.

An SMR00 is generated for outpatients receiving care in the specialties listed when:

-they attend a medical consultant outpatient clinic; -they meet with a consultant or senior member of his/her team outwith an outpatient clinic session (including the patient's home). -they attend a clinic run by a nurse or an AHP identified as the Health Care Professional Responsible for Care for that clinic and who has legal and clinical responsibility for that patient.

The dataset is generally fully complete and ready for analysis three month preceding the current date. So for example at the end of August, data is available until the end of May.

The Brain Health Data Pilot (BHDP) project aims to be a shared database (like a library) of information for scientists studying brain health, especially for diseases like dementia, which affects about 900,000 people in the UK. Its main feature is a huge collection of brain images linked to routinely collected health records, both from NHS Scotland, which will help scientists learn more about dementia and other brain diseases. What is special about this database is that it will get better over time – as scientists use it and add their discoveries, it becomes more valuable.

This is a subset of the Scottish Cancer Registry (SMR06) dataset for use in the Brain Health Data Pilot (BHDP) project.

The registry began in 1958 collecting personal, demographic and diagnosis information (such as site, histology, behaviour, histological confirmation and hospital of diagnosis) from cancer patients. In 1997, a new electronic cancer recording system was launched and at this point the registry was extended to include extra information on tumour stage (for breast, cervical and colorectal cancer), tumour grade and treatment information. A wide variety of geographical data is also included in the dataset including Scottish Index of Multiple Deprivation and Carstairs measures, census output area, NHS Board, Electoral Ward and Parliamentary constituency.

This dataset provides Census 2021 estimates that classify usual residents in Northern Ireland by long-term condition: frequent periods of confusion or memory loss, and by broad age bands. The estimates are as at census day, 21 March 2021.

The census collected information on the usually resident population of Northern Ireland on census day (21 March 2021). Initial contact letters or questionnaire packs were delivered to every household and communal establishment, and residents were asked to complete online or return the questionnaire with information as correct on census day. Special arrangements were made to enumerate special groups such as students, members of the Travellers Community, HM Forces personnel etc. The Census Coverage Survey (an independent doorstep survey) followed between 12 May and 29 June 2021 and was used to adjust the census counts for under-enumeration.

Data are available for Northern Ireland and the 11 Local Government Districts.

This forms part of Camden’s Joint Strategic Needs Assessment, focussing on the demographics of our population. This data shows breakdowns of Camden’s population by health conditions, age and sex, and by Camden ward, as supplementary information of the 2015 Camden population segmentation profile (https://opendata.camden.gov.uk/Health/Camden-Demographics-Population-Segmentation-2015/v6fr-wght). It provides the number of people, percentage of the whole population (prevalence) and Camden average for each breakdown. It only focuses on the population aged 18 and over and doesn’t show breakdowns for those diagnosed with learning disability or those aged under 65 who are diagnosed with dementia due to small numbers.

ObjectiveNon-pharmacological therapies (NPTs) have received increasing attention from researchers as a category of treatment to improve cognitive impairment in patients with dementia because of their fewer side effects. In this study, photobiomodulation (PBM), enriched environment (EE), exercise therapy (ET), computerized cognitive training (CCT), and cognitive stimulation therapy (CST) were selected to compare the effects of NPTs that improve dementia by quantifying information from randomized controlled trials (RCTs).MethodsWe did a systematic review and network meta-analysis. We searched PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), China National Knowledge Infrastructure Database, Wan Fang Database, Chinese Biomedical Literature Database, Web of Science, and VIP Database from the time of database creation to 1 August 2022. Two investigators independently screened the literature, extracted information, and assessed the RCTs’ quality with the Cochrane Collaboration Network Risk of Bias 2.0. Network meta-analysis was performed using R language (X64 version 4.1.3) and STATA 17.0.ResultsWe identified 1,268 citations and of these included 38 trials comprising 3,412 participants. For improving dementia, the results of the network meta-analysis showed that compared with the control group (CON), PBM (SMD = 0.90, 95% CI: 0.43–1.37), EE (SMD = 0.71, 95% CI: 0.02–1.41), ET (SMD = 0.42, 95% CI: 0.16–0.68), and CST (SMD = 0.36, 95% CI: 0.11–0.62) were significantly different (P < 0.05); There was no significant difference in CCT (SMD = 0.41, 95% CI: −0.07–0.88) (P > 0.05). The ranked results showed that PBM has more potential to be the best intervention (P = 0.90). In addition, there was a significant difference between PBM and CST in improving cognitive function (SMD = 0.54, 95% CI: 0.00; 1.08, P < 0.05).ConclusionIn this study, NPTs have excellent potential to improve cognition in people with dementia, and PBM may have more significant benefits in improving cognition than the other four NPTs.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022363746.

BackgroundDementia is a gradual and ongoing cognitive decline due to damage to nerve cells in the brain. This meta-analysis aimed to assess the potential relationship between regional anesthesia (RA) and the risk of dementia.MethodsElectronic databases including Embase, Medline, Google Scholar, and Cochrane Library were searched for studies investigating the association between RA and dementia risk from inception to March 2022. The primary outcome was the risk of dementia in patients who underwent RA (RA group) and those who received general anesthesia (GA group). Secondary outcomes included identifying other potential risk factors for dementia and comparing dementia risk between individuals receiving RA and those not receiving surgery/anesthesia (placebo group).ResultsEight cohort studies published between 2014 and 2023 were included in this analysis. A meta-analysis of the available data demonstrated no differences in baseline characteristics and morbidities (i.e., age, male proportion, hypertension, diabetes, depression, and severe comorbidities) between the RA and GA groups (all p > 0.05). Initial analysis revealed that the risk of dementia was higher in the GA group than in the RA group (HR = 1.81, 95% CI = 1.29–2.55, p = 0.007, I2 = 99%, five studies). However, when a study featuring a relatively younger population was excluded from the sensitivity analysis, the results showed a similar risk of dementia (HR, 1.17; p = 0.13) between the GA and RA groups. The pooled results revealed no difference in dementia risk between the RA and placebo groups (HR = 1.2, 95% CI = 0.69–2.07, p = 0.52, I2 = 68%, three studies). Sensitivity analysis revealed that the evidence was not stable, suggesting that limited datasets precluded strong conclusions on this outcome. Anxiety, stroke history, hypertension, diabetes, hyperlipidemia, and diabetes are potential predictors of dementia.ConclusionOur results emphasize that, while RA could be protective against dementia risk compared to GA, the association between the type of anesthesia and dementia risk might vary among different age groups. Owing to the significant prevalence of dementia among older people and their surgical needs, further investigations are warranted to clarify the association between dementia risk and regional anesthesia.Systematic review registration: https://www.crd.york.ac.uk/prospero/, CRD42023411324.