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Regional and International Differences in Health and Longevity at Older Ages (R03)

Sector: Manufacturing (Industrial) • Location: United States of America

Source: Grants.gov

Project
Archived

This Funding Opportunity Announcement (FOA) encourages Small Grant (R03) applications from institutions/organizations proposing to advance knowledge on the reasons behind the divergent trends that have been observed in health and longevity at older ages, both across industrialized nations and across geographical areas in the United States. This FOA is intended to capitalize on provocative finding

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The project “Regional and International Differences in Health and Longevity at Older Ages (R03)” is an infrastructure initiative in the Manufacturing (Industrial) sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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archived

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Description

Description

This Funding Opportunity Announcement (FOA) encourages Small Grant (R03) applications from institutions/organizations proposing to advance knowledge on the reasons behind the divergent trends that have been observed in health and longevity at older ages, both across industrialized nations and across geographical areas in the United States. This FOA is intended to capitalize on provocative findings in the literature which have been insufficiently understood and addressed. This FOA is also intended to capitalize on NIAs investment in the development of cross-nationally comparable datasets that can be harnessed to study these research questions; these include the Health and Retirement Study (HRS), the English Longitudinal Study on Ageing (ELSA), the Survey of Health, Ageing and Retirement in Europe (SHARE), and the Human Mortality Data Base. Applications proposing secondary analysis, calibration of measures across studies, development of innovative survey measures, and linkages to administrative sources are encouraged. Applications are not restricted to projects using the NIA-supported datasets above and may propose research using any relevant data.

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Source reliability

High

Data quality score

100%

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