Google Maps can reveal which areas have highest heart disease risk

By Imogen Howse via SWNS

Google Street View has been used to reveal which areas of cities and towns have the highest heart disease risk.

Researchers used the technology to study more than half a million images of urban environments across the United States – studying cities such as Detroit, Cleveland, Brownsville, Fremont, Bellevue, and Denver.

They analyzed the presence of features like buildings, green spaces, and roads in each neighborhood, and assessed whether they have any influence on coronary artery disease in the people who live there.

Results, published in the European Heart Journal, revealed that these factors can predict the variation in the risk of coronary heart disease from one "built" area to another with 63 percent accuracy.

Neighborhoods with green spaces were associated with a lower risk of coronary artery disease, as were areas where roads were "walkable."

Meanwhile, neighborhoods with poorly paved roads and a lack of access to green spaces were associated with a higher risk of coronary artery disease.

The research team said that this could be linked to residents lacking the space or environment for exercise.

They also said that their findings could help urban planners adapt their towns and cities to make them healthier places to live.

The study was led by Prof Sadeer Al-Kindi and Prof Sanjay Rajagopalan from University Hospitals Harrington Heart & Vascular Institute and Case Western Reserve University, USA, and Dr. Zhuo Chen, a post-doctoral fellow in Prof Rajagopalan’s lab.

Prof Al-Kindi said: “We have always been interested in how the environment, both the built and natural environment, influences cardiovascular disease.

“Here in America, they say that zip code is a better predictor of heart disease than even personal measures of health.

“However, to investigate how the environment influences large populations in multiple cities is no easy task.

“Hence, we used machine vision-based approaches to assess the links between the built environment and coronary heart disease prevalence in US cities.”

Professor Sadeer Al-Kindi, who co-led the study, added: “We’ve shown that we can use computer vision approaches to help identify environmental factors influencing cardiovascular disease risk.

“For instance, features like green space and walkable roads were associated with lower risk, while other features, such as poorly paved roads, were associated with higher risk.

“This could play a role in guiding heart-healthy urban planning.”

He added that this will become even more important as more of the world’s population moves to urban environments.

“With upcoming challenges including climate change and a shifting demographic, where close to 70 percent of the world’s population will live in urban environments, there is a compelling need to understand urban environments at scale,” said Prof. Rajagopalan added.

“Using computer vision approaches that can provide exquisite detail at an unparalleled level will be crucial for this.”