Health and Equity Data to Teach the Next Generation of Public Health Leaders.

The COVID-19 pandemic restructured university learning environments while also underscoring the need for granular local health data. We describe how the University of Memphis School of Public Health used the City Health Dashboard, an online resource providing data at the city and neighborhood level for more than 35 measures of health outcomes, health drivers, and health equity for all US cities with populations >50 000, to enrich students' learning of applying data to community health policy. By facilitating students' engagement with population needs, assets, and capacities that affect communities' health-key components of the master of public health accreditation process-the Dashboard supports in-person and virtual learning at undergraduate and graduate levels and is recommended as a novel and rigorous data source for public health trainees.

Building Public Health Surveillance 3.0: Emerging Timely Measures of Physical, Economic, and Social Environmental Conditions Affecting Health.

In response to rapidly changing societal conditions stemming from the COVID-19 pandemic, we summarize data sources with potential to produce timely and spatially granular measures of physical, economic, and social conditions relevant to public health surveillance, and we briefly describe emerging analytic methods to improve small-area estimation. To inform this article, we reviewed published systematic review articles set in the United States from 2015 to 2020 and conducted unstructured interviews with senior content experts in public heath practice, academia, and industry. We identified a modest number of data sources with high potential for generating timely and spatially granular measures of physical, economic, and social determinants of health. We also summarized modeling and machine-learning techniques useful to support development of time-sensitive surveillance measures that may be critical for responding to future major events such as the COVID-19 pandemic. (Am J Public Health. 2022;112(10):1436-1445. https://doi.org/10.2105/AJPH.2022.306917).

Health and Health Determinant Metrics for Cities: A Comparison of County and City-Level Data.

We evaluated whether using county-level data to characterize public health measures in cities biases the characterization of city populations. We compared 4 public health and sociodemographic measures in 447 US cities (percent of children living in poverty, percent of non-Hispanic Black population, age-adjusted cardiovascular disease mortality, life expectancy at birth) to the same measures calculated for counties that contain those cities. We found substantial and highly variable city-county differences within and across metrics, which suggests that use of county data to proxy city measures could hamper accurate allocation of public health resources and appreciation of the urgency of public health needs in specific locales.

City-Level Measures of Health, Health Determinants, and Equity to Foster Population Health Improvement: The City Health Dashboard.

OBJECTIVES: To support efforts to improve urban population health, we created a City Health Dashboard with area-specific data on health status, determinants of health, and equity at city and subcity (census tract) levels. METHODS: We developed a Web-based resource that includes 37 metrics across 5 domains: social and economic factors, physical environment, health behaviors, health outcomes, and clinical care. For the largest 500 US cities, the Dashboard presents metrics calculated to the city level and, where possible, subcity level from multiple data sources, including national health surveys, vital statistics, federal administrative data, and state education data sets. RESULTS: Iterative input from city partners shaped Dashboard development, ensuring that measures can be compared across user-selected cities and linked to evidence-based policies to spur action. Reports from early deployment indicate that the Dashboard fills an important need for city- and subcity-level data, fostering more granular understanding of health and its drivers and supporting associated priority-setting. CONCLUSIONS: By providing accessible city-level data on health and its determinants, the City Health Dashboard complements local surveillance efforts and supports urban population health improvement on a national scale.

Community change and resident needs: Designing a Participatory Action Research study in Metropolitan Boston.

The health implications of urban development, particularly in rapidly changing, low-income urban neighborhoods, are poorly understood. We describe the Healthy Neighborhoods Study (HNS), a Participatory Action Research study examining the relationship between neighborhood change and population health in nine Massachusetts neighborhoods. Baseline data from the HNS survey show that social factors, specifically income insecurity, food insecurity, social support, experiencing discrimination, expecting to move, connectedness to the neighborhood, and local housing construction that participants believed would improve their lives, identified by a network of 45 Resident Researchers exhibited robust associations with self-rated and mental health. Resident-derived insights into relationships between neighborhoods and health may provide a powerful mechanism for residents to drive change in their communities.