Dementia Diagnosis and Epidemiology in Older Adults

Dementia encompasses a group of neurodegenerative conditions characterised by progressive impairment in memory, executive function and daily living skills. In older populations, diagnosis typically relies on a combination of clinical assessment, neuropsychological testing, neuroimaging and increasingly on biomarker analysis. Epidemiological surveillance utilises both cohort studies and routine healthcare data to estimate incidence and prevalence, uncover risk factors such as age, genetics and vascular comorbidities, and to map geographic and socioeconomic disparities. Despite growing awareness, mild cognitive impairment (MCI)—the prodromal phase of many dementias—remains under-detected, delaying access to emerging interventions. Advances in digital health, notably natural language processing and machine learning, have enabled automated screening of electronic health records to flag early cognitive decline. Large administrative datasets linking primary care, hospital admissions and long-term care records now permit population-level detection of epidemiological trends, identification of under-served groups and assessment of dementia’s impact on outcomes in other clinical contexts, such as perioperative mortality. Global strategies emphasise equitable diagnostic pathways, standardisation of criteria and data sharing to inform public health planning and to optimise early intervention.

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Dementia Diagnosis and Epidemiology in Older Adults publication trend

The graph below shows the total number of articles in dementia diagnosis and epidemiology in older adults across all publications each year (not limited to Nature Index journals).

Technical terms

Mild cognitive impairment (MCI): A transitional stage of measurable cognitive decline not severe enough to interfere significantly with daily life.

Natural language processing (NLP): Computational techniques for extracting clinically relevant information from unstructured text in health records.

Electronic health record (EHR): Digital repository of a patient’s medical history, diagnoses and treatments maintained by healthcare providers.

Incidence: The number of new cases of a condition arising in a defined population over a specified time period.

Prevalence: The total number of individuals with a condition in a population at a given point in time.

Sensitivity: The proportion of true positive cases correctly identified by a diagnostic test.

Specificity: The proportion of true negative cases correctly identified by a diagnostic test.

Area under the receiver operating characteristic curve (AUC): A summary measure of diagnostic accuracy that reflects the trade-off between sensitivity and specificity across thresholds.

References

1. Natural language processing of electronic health records for early detection of cognitive decline: a systematic review. npj Digital Medicine (2025).
2. Expected and diagnosed rates of mild cognitive impairment and dementia in the U.S. Medicare population: observational analysis. Alzheimer's Research & Therapy (2023).
3. Association of neurocognitive disorders with morbidity and mortality in older adults undergoing major surgery in the USA: a retrospective, population-based, cohort study. The Lancet Healthy Longevity (2023).