Professor Receives $700K NIH Grant to Examine Link between Green Space and Dementias.
Professor Receives $700K NIH Grant to Examine Link between Green Space and Dementias
Marcia Pescador Jimenez, assistant professor of epidemiology, will study how exposure to trees, grass, and other greenery may affect hypertension and other risk factors for Alzheimer’s disease and related dementias.
Physical inactivity, depression, and hypertension are all risk factors for Alzheimer’s disease and related dementias (ADRD), which affect more than 6 million older adults in the US and are expected to affect at least 13 million people by 2050.
Current research suggests that exposure to green space—i.e. trees, plants, grass, and other greenery—may produce mental health benefits that can mitigate these risk factors and possibly lower the risk of ADRD among older adults. But few studies have produced solid evidence of a direct link between green space and ADRD.
Now, thanks to a new grant from the National Institute on Aging, a School of Public Health researcher aims to close this gap.
Marcia Pescador Jimenez, assistant professor of epidemiology, has received a three-year $738,310 grant from NIH and NIA to investigate the direct and indirect effects of green space on neurodegenerative diseases. Pescador Jimenez joined SPH last September from Harvard T.H. Chan School of Public Health to continue pursuing her research interests in urban environmental influences on cardiovascular health, neurodegenerative diseases, and racial disparities in health.
“My goal with this project is to identify specific features of green space and the urban environment that will shed light on pathways to Alzheimer’s Disease and related dementias, cognitive decline, physical activity, depression, and hypertension,” says Pescador Jimenez, who is principal investigator of the three-year study. “With the long-term goal of reducing the risk of ADRD, this project will use state-of-the-art methods to better measure geographic determinants of ADRD, as well as the mechanisms through which they affect health and health disparities.”
Most data measures of green space are limited by satellite images and cannot identify specific features of greenery that may affect health. By applying deep learning algorithms to nationwide Google Street View images from 2007 to 2018, Pescador Jimenez will be able to capture precise, ground-view measures of green space exposure that will reveal any causal links between green space and the noted health conditions.
“Deep learning algorithms have enabled us to predict for instance, whether a given pixel in any image in any location is a tree, grass, a flower with 80 to 90-percent accuracy,” she says. “Deep learning combined with Google Street View images provide novel exposure assessments of the geographic context from a ground-based view as participants experience it. Thus, we can get measure for instance, the percentage of trees that a person sees outside their house.”
Pescador Jimenez hopes her findings will inform urban public health interventions that support healthy aging and reduce racial disparities, as well as advance research on deep learning and objective measurements of the urban environment.
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