# Expanding the Gateway Research Infrastructure on Exposome Studies for the Health and Retirement Study and the Harmonized Cognitive Assessment Protocol International Network of Studies

> **NIH NIH R01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2022 · $2,456,548

## Abstract

Abstract
Building resources to produce widely accessible, (re)usable, and interoperable data from high-value, publicly-
funded cohort studies is one of the National Institute on Aging’s key milestones for the Alzheimer’s disease (AD)
and AD-related dementia (ADRD) research implementation. The Gateway to Global Aging Data (Gateway) is
a data platform developed to harmonize and disseminate data from the Health and Retirement Study and its
international network of studies (HRS-INS) to facilitate longitudinal analyses on aging across 47 countries. Our
overarching goal is to expand the Gateway by incorporating additional environmental characteristics that might
influence cognition and the onset and progression of AD/ADRD, collecting and documenting historical policy
changes in education, harmonizing newly available metadata from two Harmonized Cognitive Assessment
Protocol (HCAP) studies in the Northern Ireland and the Caribbean America (Puerto Rico and Dominican
Republic), and preparing harmonized analytical datafiles for the Gateway Data Enclave. Integrating
environmental characteristics that influence health and behavioral outcomes has been an important aim of the
Gateway. In our parent project, we have or will estimate exposure to fine particulate matter (PM2.5) at a 1-km
resolution for the U.S., England, Ireland, India, China, Mexico, and Chile, using the satellite data together with
ground monitor data. These data are already linked to the HRS, the English Longitudinal Study of Ageing (ELSA),
and the Longitudinal Aging Study in India (LASI). Taking it a step further, we aim to bring in additional open data
sources on environmental measures that might influence health and cognition, such as nitrogen dioxide (NO2),
ozone (O3), ambient air temperature, light pollution, and access to green and blue spaces. Motivated by the rapid
evolution of policies affecting older people across the world, we launched the Gateway Policy Explorer Series.
This series captures historic policies in place at the time of surveys covered in the Gateway. Our work has so far
focused on retirement and long-term care policies, and we aim to expand this work by compiling historical
changes in compulsory schooling laws and policies aimed at affecting the quality of education for the countries
with HCAP data and add this policy area to the Gateway’s Policy Explorer. We will also integrate additional
contextual data on education, such as country-and-year specific learning-adjusted years of schooling from the
World Bank, and other relevant contextual variables, such as country, birth year, sex, and age-specific mortality
from the Human Mortality Database. For rapid dissemination, we have built the Gateway Data Enclave, a new
remote-access, NIA-sponsored Health & Aging Data (HaAD) enclave, for researchers to access data from their
own computers. We propose to construct an exposome analysis datafile for pooled cross-country analysis of
late-life cognition and dementia and their risk...

## Key facts

- **NIH application ID:** 10661375
- **Project number:** 3R01AG030153-17S1
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Sara Adar
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,456,548
- **Award type:** 3
- **Project period:** 2007-05-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10661375

## Citation

> US National Institutes of Health, RePORTER application 10661375, Expanding the Gateway Research Infrastructure on Exposome Studies for the Health and Retirement Study and the Harmonized Cognitive Assessment Protocol International Network of Studies (3R01AG030153-17S1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10661375. Licensed CC0.

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