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An analysis of studies incorporating data from almost 30 million people has highlighted the role that air pollution-including that coming from car exhaust emissions – plays in increased risk of dementia.

Dementias such as Alzheimer’s disease are estimated to affect more than 57.4 million people worldwide, a number that is expected to almost triple to 152.8 million cases by 2050. The impacts on the individuals, families and caregivers and society at large are immense.

While there are some indications that the prevalence of dementia is decreasing in Europe and North America, suggesting that it may be possible to reduce the risk of the disease at a population level, elsewhere the picture is less promising.

Air pollution has recently been identified as a risk factor for dementia, with several studies pointing the finger at a number of pollutants. However, the strength of evidence and ability to determine a causal effect has been varied.

In a paper published today in The Lancet Planetary Health, a team led by researchers at the Medical Research Council (MRC) Epidemiology Unit, University of Cambridge, carried out a systematic review and meta-analysis of existing scientific literature to examine this link further. This approach allowed them to bring together studies that on their own may not provide sufficient evidence, and which sometimes disagree with each other, to provide more robust overarching conclusions.

In total, the researchers included 51 studies, including data from more than 29 million participants, mostly from high-income countries. Of these, 34 papers were included in the meta-analysis: 15 originated in North America, 10 in Europe, seven in Asia, and two in Australia.

The researchers found a positive and statistically-significant association between three types of air pollutant and dementia. These were:

• Particulate matter with a diameter of 2.5 microns or less (PM2.5), a pollutant made up of tiny particles small enough that they can be inhaled deep into the lungs. These particles come from several sources, including vehicle emissions, power plants, industrial processes, wood burning stoves and fireplaces, and construction dust. They also form in the atmosphere because of complex chemical reactions involving other pollutants such as sulphur dioxide and nitrogen oxides. The particles can stay in the air for a long time and travel a long way from where they were produced.

• Nitrogen dioxide (NO2), one of the key pollutants that arise from burning fossil fuels. It is found in vehicle exhaust, especially diesel exhaust, and industrial emissions, as well as those from gas stoves and heaters. Exposure to high concentrations of nitrogen dioxide can irritate the respiratory system, worsening and inducing conditions like asthma and reducing lung function.
• Soot, from sources such as vehicle exhaust emissions and burning wood. It can trap heat and affect the climate. When inhaled, it can penetrate deep into the lungs, aggravating respiratory diseases and increasing the risk of heart problems.

According to the researchers, for every 10 micrograms per cubic meter (μg/m³) of PM2.5, an individual’s relative risk of dementia would increase by 17%. The average roadside measurement for PM2.5 in Central London in 2023 was 10 μg/m³.

For every 10 μg/m3 of NO2, the relative risk increased by 3%. The average roadside measurement for NO2 in Central London in 2023 was 33 µg/m³.

For each 1 μg/m³ of soot as found in PM2.5, the relative risk increased by 13%. Across the UK, annual mean soot concentrations measured at select roadside locations in 2023 were 0.93 μg/m³ in London, 1.51 μg/m³ in Birmingham and 0.65 μg/m³ Glasgow.

Senior author Dr Haneen Khreis from the MRC Epidemiology Unit said: “Epidemiological evidence plays a crucial role in allowing us to determine whether or not air pollution increases the risk of dementia and by how much. Our work provides further evidence to support the observation that long-term exposure to outdoor air pollution is a risk factor for the onset of dementia in previously healthy adults.

“Tackling air pollution can deliver long-term health, social, climate, and economic benefits. It can reduce the immense burden on patients, families, and caregivers, while easing pressure on overstretched healthcare systems.”

Several mechanisms have been proposed to explain how air pollution may cause dementia, primarily involving inflammation in the brain and oxidative stress (a chemical process in the body that can cause damage to cells, proteins, and DNA). Both oxidative stress and inflammation play a well-established role in the onset and progression of dementia. Air pollution is thought to trigger these processes through direct entry to the brain or via the same mechanisms underlying lung and cardiovascular diseases. Air pollution can also enter circulation from the lungs and travel to solid organs, initiating local and wide-spread inflammation.

The researchers point out that the majority of people included in the published studies were white and living in high-income countries, even though marginalised groups tend to have a higher exposure to air pollution. Given that studies have suggested that reducing air pollution exposure appears to be more beneficial at reducing the risk of early death for marginalised groups, they call for future work to urgently ensure better and more adequate representation across ethnicities and low- and middle-income countries and communities.

Joint first author Clare Rogowski, also from the MRC Epidemiology Unit, said: “Efforts to reduce exposure to these key pollutants are likely to help reduce the burden of dementia on society. Stricter limits for several pollutants are likely to be necessary targeting major contributors such as the transport and industry sectors. Given the extent of air pollution, there is an urgent need for regional, national, and international policy interventions to combat air pollution equitably.”

Further analysis revealed that while exposure to these pollutants increased the risk of Alzheimer’s disease, the effect seemed stronger for vascular dementia, a type of dementia caused by reduced blood flow to the brain. Around 180,000 people in the UK are thought to be affected by this type of dementia. However, as there were only a small number of studies that examined this difference, the researchers did not class it as statistically significant.

Joint first author Dr Christiaan Bredell from the University of Cambridge and North West Anglia NHS Foundation Trust said: “These findings underscore the need for an interdisciplinary approach to dementia prevention. Preventing dementia is not just the responsibility of healthcare: this study strengthens the case that urban planning, transport policy, and environmental regulation all have a significant role to play.”

Reference:

Clare B Best Rogowski, Long-term air pollution exposure and incident dementia: a systematic review and meta-analysis, The Lancet Planetary Health, DOI: 10.1016/S2542-5196(25)00118-4 

The study analyzed data from 930 individuals diagnosed with AMD, categorizing them into two groups: early-onset (before age 65; n=392) and late-onset (after age 85; n=538). To enable standardized comparisons, only comorbidities identified before age 55 were included. The researchers extracted demographic and health information from electronic medical records to construct detailed patient profiles.

Using unsupervised clustering via Uniform Manifold Approximation and Projection (UMAP), the team identified three distinct patient clusters based on comorbidity patterns. Cluster 1 had the highest proportion of early-onset AMD cases (76.09%) and was notably marked by inflammatory joint disorders (60.1%) and hypertension (34.1%). Cluster 2, which also had a high burden of early-onset AMD (69.83%), showed a significant association with hypertension (25.9%). In contrast, Cluster 3 had the lowest rate of early-onset cases (27.02%) and presented minimal or no comorbidities.

To assess predictive potential, the researchers applied machine learning models—including gradient-boosted decision trees and random forests—to comorbidity data. The gradient-boosted decision tree model achieved a prediction accuracy of 75.84%, relying solely on comorbidities to determine the likelihood of early AMD onset.

In analyzing which comorbidities were most predictive, hypertension emerged as the top-ranked factor, followed by dyslipidemia and inflammatory joint disorders. These findings highlight the potential of systemic health factors in influencing the earlier manifestation of AMD.

The study also found that patients with early-onset AMD had a significantly higher average number of comorbid conditions compared to those with late-onset AMD (3.32 ± 0.24 versus 0.16 ± 0.02), indicating a potential role of overall disease burden in accelerating retinal degeneration.

The authors concluded that hypertension, dyslipidemia, and inflammatory joint disorders are strongly associated with early AMD onset. They emphasized the need for ophthalmologists to consider patients’ systemic health profiles during routine evaluations. Integrating comorbidity screening and proactive management may enable earlier diagnosis and personalized interventions to slow disease progression.

This innovative study emphasizes the promise of machine learning in ophthalmology and highlights the importance of interdisciplinary approaches in tackling complex, age-related diseases like AMD.

Reference:

Ethan Wu, Nasiq Hasan, Sharat Chandra Vupparaboina, Jessica Ye Jiang, Joseph DeCicco, Kiran Vupparaboina, Sandeep Bollepalli, José-Alain Sahel, Jay Chhablani; Identifying Key Co-Morbidities for Predicting Early-Onset Age-Related Macular Degeneration Using Machine Learning. Invest. Ophthalmol. Vis. Sci. 2025;66(8):293.