Using public health data to inform building practice

At the International WELL Building Institute™ (IWBI™), we see buildings as a platform for public health intervention. Recognizing the importance of a data-driven approach, IWBI not only integrates public health data but also supports other public health initiatives. In rolling out the WELL country briefs and feature ranking tables, we want to highlight some of the ways that the WELL Building Standard™ (WELL™) uses public health data and how projects can use this data to inform their project health goals.

The history of public health and buildings

Since the mid-1800s, public health professionals have recognized the intersection between the environment and human health, beginning with the risk reduction approach in the Victorian Sanitation and Healthy Cities Movement^1,2. In the early 20th century, advances in drugs and surgery led to the health as individual behavior approach and discussions about the connection between the environment and human health faded into the background. At this point in time, health was viewed as a function of individual lifestyle choices and not the environment as a whole³.

In the 1980s, researchers in the U.S., U.K. and northern Europe began to challenge the health as an individual behavior approach. Their work on the impact of natural landscapes on health outcomes led to the health-promoting environment approach^4,5. However, they quickly began to realize that telling people to eat right and exercise more was not very useful when there were numerous barriers to doing so, such as a lack of safe or convenient walkways, or access to healthy foods. This realization led to the socio-ecological approach, which encourages the incorporation of human and environmental factors when searching for public health solutions⁶.

WELL brings a holistic, socio-ecological approach to building design, policy and operations. This comprehensive focus on well-being ensures that we are creating spaces that help people thrive.

WELL country briefs and feature rankings: Linking public health data to building level design, policy and operations.

Apart from the risk reduction approach, there hasn’t been much public health research published on building-level health outcomes. Most population-level health trend data and risks don’t address buildings - where we spend over 90% of our time. And while WELL is a global standard, we recognize that trends in population health vary by location. In order to accurately address public health concerns, we need to deploy strategies on a local-scale and understand how these interventions may impact larger public health issues.

IWBI addresses this gap in the WELL country briefs and feature rankings. The WELL country briefs link WELL v2™ pilot features to national health data on mortality and disability rates from diseases and injuries that arise due to major risk factors. This data is part of the Global Burden of Disease Study (GBD) from the Institute for Health Metrics and Evaluation (IHME) at the University of Washington. The feature rankings table is a recommended list of features that project teams should consider prioritizing based on their potential impact on human health, according to national-level data as measured by the GBD. By connecting WELL v2 features to the largest and most comprehensive dataset used by policymakers worldwide, we can help project teams build WELL v2 scorecards that address relevant national health issues.

Check out our recent webinar to learn how your project might use the WELL country briefs and feature rankings to inform your project health goals: View the recording.

It is also important to note that national-level data trends may differ from local or building-level trends. The use of national-level data is a major first step for developing regional customization pathways within WELL.

Interested in learning more?

Explore our frequently asked questions

What is the Institute for Health Metrics and Evaluation (IHME)?

Institute for Health Metrics and Evaluation, or IHME, is an independent population health research center at the University of Washington. It provides rigorous and comparable measurements of the world’s most important health problems and evaluates strategies used to address them.

What is the Global Burden of Disease Study (GBD)?
The Global Burden of Disease study (GBD) is a systematic effort to quantify the magnitude of health loss due to diseases, injuries, and risk factors by age, sex and geography - in every country in the world. It is an approach to global descriptive epidemiology, that uses the best quality global public health data available to date.

What is included in the WELL country briefs?

• An introduction to WELL, the GBD, the IHME and key health metrics used in the GBD.
• An explanation of the methodology behind linking features in WELL v2 to modifiable risk factors (MRFs) in the GBD.
• A country-specific summary that identifies top modifiable risk factors (MRFs) and their associated health burden and a list of features in WELL v2 that address the top 10 MRFs.
• A feature ranking table with ordinal ranks of all WELL v2 features based on their potential impact on human health.
• Caveats to the WELL feature ranking methodology.
• Glossary of key terms.

What are the feature rankings?
Feature ranking are recommendations of which features project teams should prioritize based on their potential impact on human health, according to national-level data from the GBD. Features are ranked based on how much health loss (as measured in Disability-Adjusted Life Years, DALYs) is associated with the MRFs that the features address. In other words, features that address top-ranked MRFs (as measured by the GBD) in a country may potentially have a greater impact on health than features that address MRFs that are lower ranked.

Only WELL features that have been linked to modifiable risk factors in the GBD are included in the ordinal feature rankings. This does not mean that other WELL features do not have an impact on health and well-being, or that they are not evidence-based. It simply means that they are not currently included in the GBD database.

When would I use the WELL country briefs?
Projects that wish to address nationally-important health issues, as measured by the GBD, will want to refer to the WELL country briefs. This may be of particular interest to projects that want to apply for state or national funding, link to larger health issues, or understand the long-term health impacts of short- and medium-term interventions included in the WELL Building Standard.

What if my country isn’t listed?
If your country is not listed, you can explore one of the five socio-demographic index (SDI) groups that your country falls under.

Why are some WELL features not linked to GBD data? Does this mean they don’t have a health impact?

Only WELL features that have been linked to modifiable risk factors in the GBD are included in the ordinal feature rankings. This does not mean that other WELL features do not have an impact on health and well-being, or that they are not evidence-based. It simply means that they are not linked to a modifiable risk factor that is currently in the GBD database (see table 1).  Many cutting-edge interventions have only been studied at a local building level, and thus they do not have datasets at the GBD. For example, there is solid research on the impact of daylight on circadian rhythms, or access to nature on mental health, but these are not currently measured by many of the datasets that the GBD draws upon (such as census data).

My local health issues don’t match the national ones. What data should I use when deciding which features to pursue in my WELL project?
Local health data and other factors should always be used, if available, over national-level data. We see the WELL country briefs as a first step in systematically linking WELL features to public health data.

Looking at the country health data on IHME’s website, I see some differences in the top MRFs and their associated burden when compared to the graphs in the country briefs for the same country and year. Why is that?
Estimates by the GBD change each year. For example, a data update in September 2018 that released 2017 data also changed the data slightly for each year from 1990 to 2016. Updates to data models are made based on new data sources. These improvements in data modeling are applied to the entire time series (1990 to the most recent year) each time a new round of GBD is published.

Citations

1. Ashton, J., The Origins of Healthy Cities, in Healthy Cities, J. Ashton, Editor. 1992, Open University Press: Milton Keynes and Philadelphia. p. 1-12.
2. Hancock, T., The Evolution, Impact and Significance of the Healthy Cities/Healthy Communities Movement. Journal of Public Health Policy, 1993. 14 Spring: p. 5-18.
3. Petersen, A., The ‘Healthy’ city, expertise, and the regulation of space. Health & Place, 1996. 2(3): p. 157-164.<
4. Kaplan, R.S.K., The Experience of Nature: A Psychological Perspective. 1989, New York: Cambridge University Press. 340.
5. Ulrich, R.S., Human Responses to Vegetation and Landscapes. Landscape and Urban Planning, 1986. 13: p. 29-44.
6. County Health Rankings, Our Approach: County Health Rankings and Roadmaps. 2011, Robert Wood Johnson Foundation.