ABOUT
PRECEDE.
How can PRECEDE help you create healthier spaces?
Learn
PRECEDE provides educational resources on public health factors that can influence community health and well-being.
Explore
PRECEDE consolidates data from the U.S. Census Bureau, the Environmental Protection Agency, the Centers for Health and Disease Prevention, and other key sources—so you don’t have to seek information on multiple websites.
Act
PRECEDE is more than a diagnostic tool: It aims to centralize the growing body of research on the built environment’s impact on health to provide recommendations that help tailor your design response.
About the Grant
In 2022, a team of researchers and designers from Perkins&Will were awarded the American Society of Interior Design Foundation Transform Grant. This $30,000 award with matching funds from Perkins&Will provided the resources to transform a pilot project into a tool to share with the greater design industry. Designing equitable spaces requires transparency and shared research across disciplines and spatial scales.
With the first version complete, the research team is eagerly seeking partners to deepen PRECEDE’s focus on disability inclusion and mental health as well as increase strategies for architecture and urban design. Different building types, geographies, populations will require different tailored solutions. With further research, we hope to fill these gaps.
Limitations
This tool is designed to be a conversation starter.
- PRECEDE cannot replace authentic community engagement. It does not represent the full spectrum of occupant needs and sensitivities. Findings from PRECEDE must be supplemented with historical context and community voice.
- Data is limited to what is regularly collected and publicly available. Strategies do not capture all emerging trends or best practices and should not replace local regulations, policies or health guidance.
- PRECEDE highlights key environmental factors and strategies that may be applied globally, but the Explore tool is limited to data collected in the United States.
Key Considerations when Interpreting Public Health Information
Public health data provides useful estimates.
Measured over politically defined areas for standardized measurement, public health data does not capture small local variations or specific indoor environments.
For example, within a census tract there can be diverse communities, age groups, topography, or building types. If a census tract shows average levels of air pollution, it could be due to one part of the community being exposed to high levels of air pollution from traffic when the other part of the community is buffered by trees and has low levels of air pollution. Therefore, it is important to always validate the results with the community.
Data is influenced by the sample collected.
Health outcomes and census data aims to be a representative sample of the community, but collection efforts can miss sensitive or vulnerable populations such as unhoused people, indigenous communities, individuals with disabilities, children, or pregnant people. Some voices may be underrepresented and bias the findings.
For example, for English language learners they may be less likely to access healthcare, feel comfortable completing English surveys, or be underrepresented due to citizenship status. Therefore, self-reported surveys may underestimate the prevalence of health outcomes for this community.
Missing data or low values can mean different things.
It can be due to poor response rate, low number of people experiencing the health outcome of interest or protecting privacy. For example, data collection during periods of environmental or personal distress (e.g. COVID, displacement due to extreme weather) may limit the number of people who report their information.
Special care and consideration are necessary depending on your population of interest.
Data collections and methods may not be as inclusive as they should be to accurately capture diverse voices required to advance design equity. Individuals with disabilities face discrimination, stigma and lack of recognition, and during the data collection process it can limit our understanding of their lived experience and how the built environment can best respond.