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Social support and burden among caregivers of patients with dementia in Malaysia

Choo WY, Low WY, Karina R, Poi PJ, Ebenezer E, Prince MJ

Asia Pac J Public Health, 2003;15(1):23-9.
PMID: 14620494 DOI: 10.1177/101053950301500105

This study aims to examine selected factors of dementia patients and their caregivers that were associated with the burden of family caregivers. This cross sectional study involves face-to-face interview with family caregivers of patients with dementia. Participants were recruited through convenient sampling from geriatric and psychiatry outpatient clinics from three government hospitals, one university hospital, one rural health centre and Alzheimer Disease caregivers' support groups. 70 caregivers took part in the study. Measures included patient and caregiver demographic variables and caregiver burden using the Zarit Burden Interview (ZBI). Caregiver burden was found to be significantly associated with both ethnicity and informal support. Chinese caregivers were found to have a higher level of burden compared to Indians and Malays. Informal support, in particular assistance from family members, was significantly associated with a lower burden perceived by the caregivers. However, the study shows that formal support such as assistance from maids and private nurses did not alleviate the burden of caregivers. Results highlighted the importance of improving the coping skills in burdened caregivers particularly among family members with dementia relatives. Interventions should be designed for specific needs of caregivers of different ethnicities.
Fulltext Prediction of dementia risk in low-income and middle-income countries (the 10/66 Study): an independent external validation of existing models

Stephan BCM, Pakpahan E, Siervo M, Licher S, Muniz-Terrera G, Mohan D, et al.

Lancet Glob Health, 2020 Apr;8(4):e524-e535.
PMID: 32199121 DOI: 10.1016/S2214-109X(20)30062-0

BACKGROUND: To date, dementia prediction models have been exclusively developed and tested in high-income countries (HICs). However, most people with dementia live in low-income and middle-income countries (LMICs), where dementia risk prediction research is almost non-existent and the ability of current models to predict dementia is unknown. This study investigated whether dementia prediction models developed in HICs are applicable to LMICs.
METHODS: Data were from the 10/66 Study. Individuals aged 65 years or older and without dementia at baseline were selected from China, Cuba, the Dominican Republic, Mexico, Peru, Puerto Rico, and Venezuela. Dementia incidence was assessed over 3-5 years, with diagnosis according to the 10/66 Study diagnostic algorithm. Discrimination and calibration were tested for five models: the Cardiovascular Risk Factors, Aging and Dementia risk score (CAIDE); the Study on Aging, Cognition and Dementia (AgeCoDe) model; the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI); the Brief Dementia Screening Indicator (BDSI); and the Rotterdam Study Basic Dementia Risk Model (BDRM). Models were tested with use of Cox regression. The discriminative accuracy of each model was assessed using Harrell's concordance (c)-statistic, with a value of 0·70 or higher considered to indicate acceptable discriminative ability. Calibration (model fit) was assessed statistically using the Grønnesby and Borgan test.
FINDINGS: 11 143 individuals without baseline dementia and with available follow-up data were included in the analysis. During follow-up (mean 3·8 years [SD 1·3]), 1069 people progressed to dementia across all sites (incidence rate 24·9 cases per 1000 person-years). Performance of the models varied. Across countries, the discriminative ability of the CAIDE (0·52≤c≤0·63) and AgeCoDe (0·57≤c≤0·74) models was poor. By contrast, the ANU-ADRI (0·66≤c≤0·78), BDSI (0·62≤c≤0·78), and BDRM (0·66≤c≤0·78) models showed similar levels of discriminative ability to those of the development cohorts. All models showed good calibration, especially at low and intermediate levels of predicted risk. The models validated best in Peru and poorest in the Dominican Republic and China.
INTERPRETATION: Not all dementia prediction models developed in HICs can be simply extrapolated to LMICs. Further work defining what number and which combination of risk variables works best for predicting risk of dementia in LMICs is needed. However, models that transport well could be used immediately for dementia prevention research and targeted risk reduction in LMICs.
FUNDING: National Institute for Health Research, Wellcome Trust, WHO, US Alzheimer's Association, and European Research Council.
Fulltext Reducing the Risk of Cognitive Decline and Dementia: WHO Recommendations

Chowdhary N, Barbui C, Anstey KJ, Kivipelto M, Barbera M, Peters R, et al.

Front Neurol, 2021;12:765584.
PMID: 35082745 DOI: 10.3389/fneur.2021.765584

With population ageing worldwide, dementia poses one of the greatest global challenges for health and social care in the 21st century. In 2019, around 55 million people were affected by dementia, with the majority living in low- and middle-income countries. Dementia leads to increased costs for governments, communities, families and individuals. Dementia is overwhelming for the family and caregivers of the person with dementia, who are the cornerstone of care and support systems throughout the world. To assist countries in addressing the global burden of dementia, the World Health Organisation (WHO) developed the Global Action Plan on the Public Health Response to Dementia 2017-2025. It proposes actions to be taken by governments, civil society, and other global and regional partners across seven action areas, one of which is dementia risk reduction. This paper is based on WHO Guidelines on risk reduction of cognitive decline and dementia and presents recommendations on evidence-based, multisectoral interventions for reducing dementia risks, considerations for their implementation and policy actions. These global evidence-informed recommendations were developed by WHO, following a rigorous guideline development methodology and involved a panel of academicians and clinicians with multidisciplinary expertise and representing geographical diversity. The recommendations are considered under three broad headings: lifestyle and behaviour interventions, interventions for physical health conditions and specific interventions. By supporting health and social care professionals, particularly by improving their capacity to provide gender and culturally appropriate interventions to the general population, the risk of developing dementia can be potentially reduced, or its progression delayed.

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