In an era where data drives decision-making, understanding and addressing social equity requires more than good intentions – it demands evidence. From transportation planners to public health officials, professionals across sectors are increasingly turning to specialized datasets to identify disparities, allocate resources fairly, and ensure that vulnerable communities aren't left behind.
Social equity means ensuring that everyone has access to the same opportunities, resources, and protections, regardless of their income, race, or where they live. But achieving this goal requires first understanding where inequities exist. The right data can illuminate patterns of disadvantage that might otherwise remain invisible, helping policymakers and advocates target interventions where they're needed most.
Here are five critical datasets that are transforming how we approach social equity in America.
1. Location Affordability Index (LAI)
When we think about housing affordability, we often focus solely on rent or mortgage payments. But the Location Affordability Index takes a more comprehensive approach by examining the combined cost of housing and transportation – often the two largest expenses for low- and moderate-income households.
This dataset reveals a crucial insight: a neighborhood with cheap housing isn't necessarily affordable if residents must spend hundreds of dollars monthly on transportation to reach jobs, schools, and services. This phenomenon creates what researchers call "poverty traps," where families are financially strained despite lower housing costs.
For social equity analysis, the LAI is invaluable in several contexts. It helps identify suburban areas where inadequate public transit forces residents to own and maintain vehicles, creating a hidden cost burden. This is particularly important for carless or low-income residents who face limited job access and economic mobility when forced to choose between unaffordable housing in transit-rich areas or high transportation costs in transit-poor areas.
The dataset also supports sustainable development by helping policymakers make strategic investments that address both housing and transportation affordability simultaneously. Rather than building affordable housing in isolated locations, planners can use LAI data to prioritize areas where residents will truly benefit from reduced combined living costs.
Additionally, the LAI plays a critical role in Fair Housing assessments. Under Affirmatively Furthering Fair Housing (AFFH) requirements, jurisdictions must demonstrate that they're promoting housing choice and opportunity. The LAI provides evidence of the true affordability landscape across regions, ensuring that subsidized housing is placed in high-opportunity areas where transportation costs won't negate housing savings.
2. Social Vulnerability Index (SVI)
Not all communities are equally equipped to withstand disasters, public health emergencies, or economic shocks. The Social Vulnerability Index, developed by the CDC and the Agency for Toxic Substances and Disease Registry (ATSDR), uses Census data to identify communities most likely to suffer adverse effects when crises strike.
The SVI examines factors including poverty rates, elderly populations, linguistic isolation, crowded housing, and vehicle access. By combining these variables, it creates a comprehensive picture of community resilience – or lack thereof. This makes it the cornerstone of disaster equity planning.
For emergency preparedness, the SVI allows planners to pre-allocate resources before disasters occur. Rather than scrambling during a crisis, communities can identify in advance which neighborhoods need cooling centers during heat waves, which populations require language-specific emergency materials, and where transportation assistance for evacuation will be most critical. This proactive approach ensures that vulnerable residents receive support when they need it most.
The dataset proved its value during the COVID-19 pandemic, when public health officials used SVI data to prioritize vaccine distribution and outreach efforts. Communities with high proportions of elderly residents, crowded housing conditions, and limited healthcare access received targeted interventions, helping to reduce disparities in pandemic impacts.
Infrastructure investment decisions also benefit from SVI analysis. When agencies apply for resilience grants or plan flood mitigation projects, the SVI provides evidence of where social factors compound physical environmental risks. A low-income neighborhood with limited vehicle access faces far greater danger from flooding than a wealthy area with high car ownership, even if both face similar flood risk. Social equity demands that these compounding vulnerabilities inform resource allocation.
3. Fatality Analysis Reporting System (FARS)
Traffic safety might not seem like a social equity issue at first glance, but the data tells a different story. The Fatality Analysis Reporting System (FARS) provides comprehensive data on fatal motor vehicle crashes, and when analyzed through an equity lens, it reveals stark disparities in who dies on American roads.
Pedestrian and cyclist fatalities occur disproportionately in low-income and minority neighborhoods. This isn't because residents in these areas are less careful – it's because the infrastructure is less safe. Decades of underinvestment have left many neighborhoods without adequate crosswalks, traffic calming measures, dedicated bike lanes, or appropriate speed limit enforcement.
For social equity work, FARS data is essential to "Vision Zero" initiatives, which aim to eliminate traffic deaths. By identifying high-crash corridors and analyzing the demographics of victims, planners can direct safety improvements to areas that have historically been neglected. This might mean installing leading pedestrian intervals at intersections, adding protected bike lanes, or redesigning streets to slow traffic in residential areas.
The dataset also enables enforcement equity analysis. Researchers and advocates can examine whether emergency response times differ by neighborhood, whether vehicle safety regulations are enforced equally, and whether road design standards are applied consistently across communities. When FARS data reveals that low-income neighborhoods experience higher fatality rates despite similar or lower traffic volumes, it provides powerful evidence of systemic inequity in transportation infrastructure investment.
4. Food Access Research Atlas
Access to healthy, affordable food is fundamental to health equity, yet millions of Americans live in areas where obtaining nutritious food requires significant time, money, or transportation resources. The USDA's Food Access Research Atlas spatially identifies these "food deserts" – areas of low income and low access to food retailers.
For public health officials working on social equity, this dataset is indispensable. It allows them to map correlations between limited food access and poor health outcomes, including obesity, diabetes, and heart disease, in specific census tracts. This geographic specificity enables targeted nutrition programs, health education initiatives, and community health worker outreach in areas where interventions will have the greatest impact.
The atlas also serves a critical function in economic development. Local governments and nonprofits use this data when applying for Healthy Food Financing Initiatives, which provide funding to develop supermarkets, grocery stores, and farmers' markets in underserved areas. Without the Food Access Research Atlas, it would be far more difficult to demonstrate the scope and location of food access gaps.
Beyond health and economic development, the dataset informs land-use and zoning decisions. Planners can use food access data to incentivize grocery stores and food hubs in low-access areas, revise zoning codes that inadvertently create food deserts, and ensure that new residential developments include plans for food retail. This proactive approach prevents the creation of new food deserts while addressing existing ones.
5. Air Quality System (AQS)
Environmental justice recognizes that pollution burdens fall unequally across communities. The EPA's Air Quality System (AQS) provides ambient air pollution measurements from monitoring stations nationwide, creating the empirical foundation for environmental justice analysis and advocacy.
The AQS dataset measures pollutants including ozone, particulate matter, sulfur dioxide, and nitrogen dioxide. When overlaid with demographic data, patterns emerge: low-income neighborhoods and communities of color often face significantly higher pollution exposure than wealthier, whiter areas. This isn't coincidental – it reflects decades of discriminatory zoning and land-use decisions that concentrated polluting industries, highways, and ports in marginalized communities.
For environmental justice screening, AQS data is essential. It allows regulators to officially designate Environmental Justice communities, which can then receive enhanced regulatory protection, prioritized cleanup funding, and increased community input in permitting decisions. Without reliable pollution monitoring data, these protections would lack an empirical basis.
The health implications are profound. AQS data provides the evidence base linking air pollution exposure to respiratory conditions like asthma and COPD, which are disproportionately prevalent in fence-line communities near industrial facilities. This connection between environmental burdens and health disparities is central to social equity work.
Perhaps most importantly, advocates and regulators use AQS data in permitting processes. When a company proposes building a new facility in an already pollution-burdened area, AQS data demonstrates the cumulative impact. This evidence can challenge permits, push for stricter emission standards, or demand mitigation measures, ensuring that communities already struggling with poor air quality don't shoulder additional burdens.
Access These Social Equity Datasets Through Social Explorer
Understanding social equity requires access to reliable, comprehensive data – and that's exactly what Social Explorer provides. All five of these critical datasets – the Location Affordability Index, Social Vulnerability Index, Fatality Analysis Reporting System, Food Access Research Atlas, and Air Quality System – are readily available through Social Explorer's intuitive mapping software.
Whether you're a researcher, policymaker, advocate, or community organizer, Social Explorer makes it easy to visualize, analyze, and share the data that drives equity-focused decision-making. Ready to explore these datasets and discover insights that can transform your community? Sign up for a free trial today and start turning data into action for social equity.