Toward a new interdisciplinary model to understand Alzheimer’s disease: The interplay between neurobiology and socio-economic factors

• Main Authors: Hyun Jee Han, Clive Shrubsole
• Format: Article
• Language: English
• Published: Edizioni FS 2018-11-01
• Series: Journal of Health and Social Sciences
• Subjects: Neuroinflammation; Alzheimer’s disease; air pollution; PM2.5; eco-politics; education; models
• Online Access: https://journalhss.com/wp-content/uploads/jhss33_243-272.pdf
• ISSN: 2499-2240; 2499-5886

Introduction: In recent years, there has been emerging evidence that air pollution is a chronic source of neuroinflammation, which contributes to Alzheimer’s Disease (AD) and other forms of dementia, which are an increasingly common and devastating illness affecting elderly populations. Aim of this paper is to develop a new, interdisciplinary and theoretical model based on neurobiology, sociology of medicine and eco-political science for a better understanding of the etiopathogenesis of Alzheimer’s disease and other forms of dementia. Methods: We carried out a literature review focusing on the following aspects: 1) The causal relationship between PM2.5 (and air pollution) and AD; 2) Regulations and guidelines about air pollution released by organizations across the world; 3) Differences in PM2.5 and educational levels between More Economically Developed Countries (MEDC) and Less Economically Developed Countries (LEDC); 4) Differences of AD incidence between MEDC and LEDC with regard to their levels of social developments. Results: Our interdisciplinary model depicts a pathway through which specific socio-economic factors (poor residential conditions and geographical sites, low educational levels) and environmental factors (i.e. air pollution exposure) interact to increase the risk of developing Alzheimer’s disease. Discussion: According to our model, socio-economically disadvantaged individuals and communities are likely to be at higher risk for AD, compared to those in better living conditions, due to greater likelihood of living by the lower-price housing areas and greater exposure to air pollution, and low educational levels. This suggests that the lower the socio-economic development, the higher the chance of being exposed to the PM2.5. These combined socio-economic determinants may result in a greater likelihood of developing AD. Conclusion: Although our model does not include other well-recognized causes of AD and needs to be tested by further in-depth epidemiological studies, more holistic and realistic views on the current approaches will allow this field to move forward and lead to an improvement to actionable policies.