Understanding Place-Based Health Inequalities in Mid-Life (R01 Clinical Trial Not Allowed)
Sector: Government • Location: United States of America
Source: Grants.gov
This Funding Opportunity Announcement (FOA) RFA supports secondary data analyses and/or data collection/enhancements to existing datasets to address the role of place (e.g., countries, U.S. Census regions, states, counties, neighborhoods, and locations across the urban-rural continuum) in health in order to uncover actionable knowledge to address disparities by geography and other factors such as
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | archived |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | This Funding Opportunity Announcement (FOA) RFA supports secondary data analyses and/or data collection/enhancements to existing datasets to address the role of place (e.g., countries, U.S. Census regions, states, counties, neighborhoods, and locations across the urban-rural continuum) in health in order to uncover actionable knowledge to address disparities by geography and other factors such as race and ethnicity. Secondary data analyses appropriate to this FOA include those that: 1) clarify social, economic, behavioral, and ?institutional (e.g., federal to local government policies/programs, firm/industry practices, etc.) explanations for place-based health disparities (levels and trends) and/or 2) examine intersections between place and sociodemographic characteristics (e.g., gender, race, ethnicity, etc.) to better understand and address processes driving other ?health disparities. Analytic approaches that utilize quasi-experimental and other methods that yield causal estimates are preferred, though mixed methods projects that inform mechanistic insights and/or data enhancements are also appropriate. Multilevel analyses that enable the joint and synergistic examination of macro-, meso-, and individual-level factors are also encouraged. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
