Urban Loneliness Mapped
Loneliness affects a significant number of people in the United States. As a public health risk, loneliness is consistently associated with a variety of adverse health impacts. The literature on loneliness delves into two types: objective loneliness (physical isolation) and subjective loneliness (feeling of isolation), with several measures of these loneliness types including familial, spousal, social, and existential loneliness.1 Interventions on loneliness depend on the unique needs of lonely individuals who live and work within their built environment: the human-made systems that define the boundaries of culture, habit, and daily life. These include the location of amenities like daycare providers, the local government-defined building density and zoning laws, the investment in and use of public parks, regulations on pollution, location of jobs, etc. Long-term fixes to loneliness like developing new public space, changing commute patterns, and expanding access to healthcare are typically out of scope for local community organizations that need to support their residents today.
To support local communities in local, rapid, and affordable interventions on loneliness, we’ve developed a loneliness index that can be used to identify at-risk populations and individuals and focus intervention activities to directly address loneliness.
This index is mapped at the U.S. Census block group level, including more than 218,000 block groups. This level of granularity is critical for understanding the nuanced differences between communities within a neighborhood. This paper focuses on 1) the development of a community-level approach for identifying areas to invest in anti-loneliness measures, and 2) showing how diving deeper than the typical census tract level (of which there are 72,000-plus) can allow for more nuanced investigation of crises like loneliness.
Census block group analysis can empower communities to make deliberate, impactful decisions, which optimize outreach efforts to at-risk populations. We can organize programs for those who live alone (e.g., the Maryland Daily Wellness Check for Seniors). We can work with single parents to integrate their families into community activities to provide safe spaces for children after school (e.g., Teen Nights). We can translate for people with limited English-speaking skills and introduce them to others in the community who speak their native languages (e.g., language events and promotion of specific language books at the public library). We can support strategic carpooling or alter bus routes for those doing super-commutes alone (e.g., the “slug-line” network in Washington D.C.). We can organize supplemental employment, training, and support for basic healthcare for the poor, underemployed, or uninsured (e.g., organizing volunteers to run sign-up drives for healthcare.gov in communities with limited digital skills or internet connectivity).
Yet these local interventions are only useful if the built environment factors that exacerbate loneliness are not insurmountable. We show via highly granular analysis, that even within a census tract, there can be significant variation in our loneliness index. Since census tracts are themselves granular and often used as the unit of measure for a built environment,2 variations of loneliness within them provide evidence that built environment factors can be overcome through local, rapid, and affordable interventions at the census block group level.
Jessica M. Keralis, “Health and the built environment in United States cities: measuring associations using Google Street View-derived indicators of the built environment,” BMC Public Health, vol. 20, no. 215, 2020.
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