Common risk factors for dementia vary between rich, poor countries: Study

Prevention strategies for dementia must be adapted to local economic and social conditions rather than relying on a universal global model, according to research published in The Lancet Healthy Longevity. A large-scale analysis, presented on 13 July 2026 at the Alzheimer's Association International Conference in London, evaluated survey data from more than 214,000 individuals across 14 countries. The study, which integrated information collected between 2009 and 2023, highlights that while the risk of cognitive decline is a global concern, the specific factors driving that risk shift significantly depending on a nation's wealth.

The research, led by scientists at the University of Southern California, Brown University, and Johns Hopkins University, compared how 12 modifiable risk factors—such as hearing loss, physical inactivity, depression, and social isolation—manifest across different populations. The findings revealed that demographic disparities are stark. For example, low education impacts 85.6% of older adults in China, while the rate in the United States is 12.0%. Conversely, obesity, indicated by a high body mass index, affects 44.9% of American participants compared to 13.3% of those in India.

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Clustered Risks and Global Patterns

Despite these variations in prevalence, the researchers identified consistent patterns in how these risks group together. Cardiovascular conditions, including hypertension and high cholesterol, frequently co-occur globally. Similar clustering was observed among lifestyle factors, specifically smoking and alcohol consumption. Across all studied regions, more than 50% of individuals were found to have at least two concurrent risk factors.

"I was less surprised by the differences and more surprised by some of the similarities, particularly in the ways these risks are patterned across settings. That has real implications for how we design prevention strategies and interventions, because some things are more consistent across places than we might expect."

Emma Nichols, research scientist at the USC Schaeffer Institute for Public Policy & Government Service

The researchers suggest these patterns provide a practical starting point for public health officials. Nations that currently lack granular local epidemiological data may be able to utilize models from regions with similar socioeconomic development. However, the study cautions that this should only serve as an initial framework. Local data collection remains a necessary step to ensure that public health interventions are suited to the specific social structures and healthcare capacities of a given population.

Integrated Approaches to Health

Because risk factors often occur in clusters, the study suggests that healthcare systems move away from treating individual conditions in isolation. By integrating care, a program designed to address diabetes, for instance, could simultaneously manage related cardiometabolic issues such as high blood pressure and cholesterol. Such an approach aims to address the cumulative nature of risk over an individual's life course.

For individuals, the findings emphasize that dementia is not an unchangeable fate.

"Risk for these late-life outcomes isn't predetermined. These are risk factors you experience over the life course, and you can have an impact on changing your own risk — while also recognising the ways broader societal factors shape that risk, too."

Emma Nichols, research scientist at the USC Schaeffer Institute for Public Policy & Government Service

Future Research Directions

The research team intends to continue broadening the scope of the study. Future efforts are expected to incorporate more consistent collection of biomarkers and a wider array of social data. Work is currently underway to expand the dataset to include nations such as Kenya and Egypt, and researchers aim to investigate additional emerging risk factors, including sleep quality and environmental exposures like air pollution.

Risk Factor	Impact in USA	Impact in Specified Comparison Country
Low Education	12.0%	85.6% (China)
High BMI	44.9%	13.3% (India)