Sage Journals: Discover world-class research

Abstract

Social infrastructure (SI) may buffer against suicide risk by improving social cohesion, social support, and information and resource sharing. The authors use an ecological approach to examine the relationship between county-level SI availability and suicide rates among working-age adults (25–64 years) in the United States, a population among which suicide rates are high, rising, and geographically unequal. Mortality data are from the National Vital Statistics System for 2016 to 2019. SI data are from the National Neighborhood Data Archive for 2013 to 2015 and capture the availability of typically free SI (e.g., libraries, community centers) and commercial SI (e.g., coffee shops, diners, entertainment venues). Results from negative binomial models show that suicide rates are significantly lower in counties with more SI availability, net of county demographic, socioeconomic, and health care factors. This relationship held for both typically free and commercial SI. Policy makers should consider strengthening existing and developing new SI as part of a broader strategy to reduce suicide rates in the United States.

Keywords

suicide social infrastructure working-age adults counties United States

Suicide is the sixth leading cause of death among working-age adults (25–64 years) in the United States (Centers for Disease Control and Prevention 2023). A recent report from the National Academies of Sciences, Engineering, and Medicine (Becker, Majmundar, and Harris 2021) concluded that suicide was among the main causes of death driving the recent decline in life expectancy among U.S. working-age adults and the nation’s divergence in life expectancy from other high-income countries. Suicide rates also vary tremendously across the United States, with much higher rates in some places than others (Becker et al. 2021; Kegler, Stone, and Holland 2017; Keyes et al. 2024; Zhang and Monnat 2024). Understanding the factors that contribute to this geographic variation is critical for informing prevention efforts (Brådvik 2018; National Institute of Mental Health 2023). In this study, we examined the relationship between county-level social infrastructure availability (i.e., free, publicly available, and commercial social venues that facilitate the formation and maintenance of social ties, such as libraries, coffee shops, diners, sport facilities, and religious organizations) and suicide rates among U.S. working-age adults.

A multidimensional and multilevel set of factors from the individual level to the macrostructural level contribute to suicide ideation, attempts, and mortality (Becker et al. 2021; Fazel and Runeson 2020). Such factors include mental health, family history of suicide, trauma, adverse childhood experiences, pain, substance use, access to lethal means, inadequate access to health care, unhealthy social relationships, individual and place-level economic disadvantage, lack of social support, various features of the built, physical, and social environments, macroeconomic shocks, and government policies (Anestis and Anestis 2015; Burgard and Kalousova 2015; Fazel and Runeson 2020; Feldmeyer et al. 2022; Kaufman et al. 2020; Keyes et al. 2024; Opoliner et al. 2014; Phillips 2013; Phillips and Nugent 2014; Steele et al. 2018; Steelesmith et al. 2019; Zhang and Monnat 2024).

However, these risk factors can be moderated by place-level cultural mechanisms that can either disrupt or exacerbate their effects (Abrutyn and Mueller 2018). Social support and social capital are among the most endorsed social protective factors (Phillips 2013; Recker and Moore 2016; Smith and Kawachi 2014). Ecological approaches are commonly used to understand how place-level factors, such as community social support and cohesion, shape collective risk for mortality (Feldmeyer et al. 2022; Phillips 2013; Steelesmith et al. 2019). These studies often point to Emile Durkheim’s (1897) work on suicidality (Hood-Williams 1996; Mueller et al. 2021; Smith and Kawachi 2014). Durkheim proposed that social integration and social ties buffer against suicide risk given their role in facilitating social belonging and inclusion, particularly during periods of rapid social change. Social cohesion captures the extent of social bonds within a community (Carrasco and Bilal 2016). Previous work has demonstrated that there is a positive relationship between social cohesion and mental health (Kingsbury et al. 2020; Robinette et al. 2021; Rotenberg, Anderson, and McKenzie 2020). Social cohesion can help shape collective mental health through the development of strong and weak ties, feelings of belonging and connectedness, and mutual cooperation and shared goals (Schiefer and Van der Noll 2017).

Social infrastructure is receiving increased attention for its role in facilitating social cohesion, social support, and the sharing of information and resources and in buffering against social disorganization (Domenech-Abella et al. 2020; Klinenberg 2018; Rhubart, Kowalkowski, and Wincott 2023). Social infrastructure represents the physical places where people can gather to exchange information, build and maintain relationships, and access resources. They are sometimes referred to as “third places” (i.e., social places and activity spaces other than work and home) (Oldenburg 2014), where a wide variety of people can easily and routinely connect with one another, “exchange ideas, have a good time, and build relationships” (Butler and Diaz 2016). Research shows that third places generate social cohesion and neighbor interaction (Williams and Hipp 2019). Free and lost-cost social infrastructure in particular (e.g., coffee shops and libraries ) can facilitate relationship building and resource and information sharing across groups with limited resources, factors that can reduce mental health risks (De Silva et al. 2005; Whitley and McKenzie 2005).

These places may be particularly important for working-age adults, as families and workplaces become more nuclearized and subsequently more isolated from the community (Oldenburg and Brissett 1982). There has been an increase in psychological distress among U.S. working-age adults in recent decades (Blanchflower and Oswald 2020; Case and Deaton 2020; Daly 2022; Gaydosh et al. 2019; Goldman, Glei, and Weinstein 2018; Muennig et al. 2018). Scholars have pointed to various explanations for this trend, including industrial restructuring and wage stagnation, declines in labor force participation and marriage rates, reduced workplace autonomy, flexibility, and creativity, and the rise of remote work as each contributing to a reduced sense of purpose, meaning, and identity among working-age adults (Case and Deaton 2020; Cherlin 2014; Daly 2022; Monnat 2019; Shanahan et al. 2019; Thompson 2019). In the context of these changes to the institutions of work and the family, social infrastructure may offer a critical alterative to achieving purpose, meaning, social connection, and identity, and therefore could be central in buffering against suicide risk.

Importantly, social infrastructure helps foster social cohesion that transmits collective benefits beyond specific users of the social infrastructure (Finlay et al. 2019, 2022; Kingsbury et al. 2020). For example, communities with more social infrastructure have more social cohesion and support, civic participation, and access to resources; lower crime rates; improved disaster response; and better average cognitive and physical health (Domenech-Abella et al. 2020; Finlay et al. 2022; Kawachi and Berkman 2000; Klinenberg 2018; Rhubart et al. 2023; Speer, Jackson and Peterson 2001; Walton 2014). However, social infrastructure is not evenly distributed across the United States. For example, counties with higher poverty rates and larger shares of minoritized racial and ethnic groups and some types of rural communities have less social infrastructure (Rhubart et al. 2022). Given the important roles of social support and social cohesion in buffering against suicide risk, geographic disparities in social infrastructure may contribute to geographic disparities in suicide among working-age adults.

In this paper, we draw on Durkheim’s early work and the concept of social cohesion and use an ecological approach to examine the relationship between social infrastructure availability and county-level suicide rates for working-age adults (25–64 years) in the United States for 2016 to 2019. We hypothesize that suicide rates will be lower in counties with more social infrastructure availability.

Materials and Methods

Data Source and Preparation

Our unit of analysis is the county. Counties are the smallest geographic unit for which suicide data are available nationally. Analyses included 3,141 counties. Kalawao County, Hawaii is excluded because mortality data are not available for that county. Mortality data are from the restricted-use death certificate files from the National Vital Statistics System for 2016 to 2019. These data identify causes of death and county of residence from all death certificates filed in the United States. We calculated suicide deaths for U.S. residents ages 25 to 64 years whose underlying cause of death was listed as suicide on the basis of the International Classification of Disease, 10th Revision, codes X60-X84 and Y87.0. We limited our analysis to 2016 to 2019 because this range (1) preceded the coronavirus disease 2019 (COVID-19) pandemic, which dramatically affected mental health as well as the availability and use of social infrastructure and (2) provided a sufficient range of years to prevent annual anomalies, particularly in small-population counties, from biasing the results (Becker et al. 2021; Monnat et al. 2019).

Social infrastructure data are from the National Neighborhood Data Archive (NaNDA) for 2013 to 2015. We chose these years to allow for a lag between exposure to social infrastructure and suicide (Cummings 2012). Although NaNDA social infrastructure data are available at the census tract level, we aggregated the data to the county level for two reasons. First, this approach aligns the social infrastructure data with the county-level suicide data. Second, counties serve as important administrative units that enact policies and deliver services that affect health and mortality.

We computed counts of typically free social infrastructure (i.e., religious organizations, civic organizations, libraries, and social services), commercial social infrastructure (i.e., food and beverage third places; creative, athletic, and entertainment third places; and personal services), and total social infrastructure. These establishments are considered social infrastructure because they are social and activity spaces that facilitate interaction, social cohesion, relationship and trust building, and information and resource sharing (Butler and Diaz 2016; De Silva et al. 2005; Oldenburg 2014; Whitley and McKenzie 2005). These categorizations have been used in prior research (Fraser et al. 2024; Rhubart et al. 2022). The full list of social infrastructure types is shown in Appendix Table A1. We averaged county social infrastructure counts over the period from 2013 to 2015 and used those averages to calculate area-based densities (per 100 square miles) of social infrastructure.

We controlled for the following county-level characteristics that may conflate observed relationships between social infrastructure and suicide rates: percentage Hispanic, percentage non-Hispanic Black, percentage of the population 25 and older with a bachelor’s degree or higher, poverty rate, percentage of people with health insurance, whether the county is designated as a mental health care provider shortage county, whether the county is designated as a primary health care provider shortage county, and metropolitan status. Demographic and socioeconomic covariates are from the American Community Survey 5-year estimates for 2011 to 2015 (U.S. Census Bureau 2016). Data on primary and mental health care provider shortage designations are from the 2015 Social Determinants of Health Database (Agency for Healthcare Research and Quality 2023). Metropolitan status is based on the U.S. Department of Agriculture Economic Research Service’s 2013 rural-urban continuum codes (U.S. Department of Agriculture, Economic Research Service 2020). Counties with rural-urban continuum codes 4 to 9 are defined as nonmetropolitan. Descriptive statistics are shown in Table 1. We also present maps showing the distribution of county-level suicide rates and social infrastructure density (Figures 1 and 2).

Table 1.

Descriptive Statistics.

	Mean	SD	Minimum	Maximum
Suicide deaths (ages 25–64 years)^a	40.33	103.17	0	2,402
Suicide deaths per 100,000 population (ages 25–64 years), age adjusted^a	25.15	14.85	0	279.75
Total social infrastructure (per 100 square miles)^b,c	248.78	2,141.07	0	104,249.90
Typically free social infrastructure (per 100 square miles)^b,c	110.22	769.81	0	34,851.97
Commercial social infrastructure (per 100 square miles)^b,c	140.12	1,392.77	0	69,837.83
Hispanic population (%)^c	8.83	13.50	0	98.71
Non-Hispanic Black population (%)^c	8.88	14.39	0	85.95
Poverty rate (%)^c	16.70	6.59	1.42	53.32
Population aged ≥25 years with a bachelor’s degree or higher (%)^c	20.41	9.02	1.89	78.77
Population with health insurance (%)^c	86.57	5.44	43.71	98.15
Shortage of primary health care providers^d	.86	.35	0	1
Shortage of mental health care providers^d	.91	.29	0	1
Nonmetropolitan^e	.63	.48	0	1

Note: N = 3,141 counties.

National Vital Statistics System, 2016 to 2019.

National Neighborhood Data Archive, 2013 to 2015.

American Community Survey, 2011 to 2015.

Social Determinants of Health Database, 2015.

U.S. Department of Agriculture Economic Research Service rural-urban continuum codes, 2013.

Figure 1.

County-level distribution of age-adjusted suicide rates among U.S. working-age adults (25–64 years), 2016-2019.

Figure 2.

County-level distribution of total, typically free, and commercial social infrastructure availability, 2013 to 2015: (A) county-level distribution of total social infrastructure availability, 2013 to 2015; (B) county-level distribution of typically free social infrastructure availability, 2013 to 2015; and (C) county-level distribution of commercial social infrastructure availability, 2013 to 2015.

Analytic Strategy

We used negative binomial regression models to predict county-level suicide deaths as a function of social infrastructure. Negative binomial regression accounts for the skewed nature of suicide counts (Carriere, Marshall, and Binkley 2019). We offset suicide deaths using the county population ages 25 to 64 years and included controls for county age distribution (percentage of the population ages 35–44, 45–54, and 55–64 years). Population data are from the Centers for Disease Control and Prevention’s bridged-race population estimates for 2016 to 2019 (U.S. Census Bureau and National Center for Health Statistics 2023). We weighted models with the log of the county population to provide nationally representative estimates and avoid inflating the influence of small population counties (Montez et al. 2022; Pierce and Schott 2020; Venkataramani et al. 2016), and we clustered standard errors at the state level. We standardized all predictor variables to a mean of zero and standard deviation of one to facilitate comparison of coefficients across predictors. We conducted all analyses in Stata/MP 17.0 (StataCorp, College Station, TX). We ran a robustness check using models that used a population-based measure of social infrastructure (number of social infrastructure units per 1,000 population) in lieu of the area-based measure. We discuss the results of this check after presenting our main results.

Results

There were 126,678 suicides among adults ages 25 to 64 years for the period from 2016 to 2019. The average age-adjusted suicide rate across counties was 25 deaths per 100,000 population (Table 1). Suicide rates were comparatively high in the western half of the United States, with lower rates in the northeastern, mid-Atlantic, and southern regions (Figure 1). As can be seen in Figure 2, social infrastructure is unevenly distributed across the United States, with much greater availability in the eastern half of the country and very limited availability in the West (except for counties containing major cities and the Pacific coastal region).

Negative binomial regression results are shown in Table 2. We present incidence rate ratios (IRRs) and 95 percent confidence intervals (CIs). The top panel (model 1) shows results from models that controlled only for county age composition. Suicide rates were significantly lower in counties with more total social infrastructure (IRR = 0.969, 95 percent CI = 0.96–0.98, p < .01), more free social infrastructure (IRR = 0.965, 95 percent CI = 0.95–0.98, p < .01), and more commercial social infrastructure (IRR = 0.972, 95 percent CI = 0.96–0.99, p < .01).

Table 2.

Results from Negative Binomial Regression Models Predicting Relationships between Social Infrastructure Availability and Suicide Deaths among U.S. Working-Age Adults (25–64 Years), 2016 to 2019.

	Suicide Deaths^a
	IRR	95% CI	IRR	95% CI	IRR	95% CI
Model 1
Total social infrastructure (per 100 square miles)^b,c	.969**	(.96–.98)
Typically free social infrastructure (per 100 square miles)^b,c			.965**	(.95–.98)
Commercial social infrastructure (per 100 square miles)^b,c					.972**	(.96–.99)
Model 2
Total social infrastructure (per 100 square miles)^b,c	.983**	(.97–.99)
Typically free social infrastructure (per 100 square miles)^b,c			.980**	(.97–.99)
Commercial social infrastructure (per 100 square miles)^b,c					.984**	(.97–.99)
Covariates
Hispanic population (%)^c	.880**	(.83–.93)	.881**	(.83–.93)	.880**	(.83–.93)
Non-Hispanic Black population (%)^c	.853**	(.83–.88)	.854**	(.83–.88)	.852**	(.83–.88)
Poverty rate (%)^c	1.015	(.98–1.05)	1.016	(.98–1.05)	1.015	(.98–1.05)
Population aged ≥25 years with a bachelor’s degree or higher (%)^c	.939**	(.92–.96)	.940**	(.92–.96)	.939**	(.91–.96)
Population with health insurance (%)^c	.894**	(.86–.93)	.894**	(.86–.93)	.894**	(.86–.93)
Shortage of primary health care providers^d	.988	(.97–1.00)	.988	(.97–1.00)	.988	(.97–1.00)
Shortage of mental health care providers^d	1.007	(1.00–1.02)	1.008	(1.00–1.02)	1.007	(1.00–1.02)
Nonmetropolitan^e	.986	(.97–1.00)	.986	(.97–1.00)	.986	(.97–1.00)

Note: N = 3,141 counties. Models are weighted by the log of the county population and cluster standard error at the state level. Models include the population ages 24 to 64 years as an offset and control for county age distribution. All the predictor variables are z-score standardized. IRR = incidence rate ratio.

National Vital Statistics System, 2016 to 2019.

National Neighborhood Data Archive, 2013 to 2015.

American Community Survey, 2011 to 2015

Social Determinants of Health Database, 2015.

U.S. Department of Agriculture Economic Research Service rural-urban continuum codes, 2013.

p < .01.

The bottom panel of Table 2 (model 2) shows the results from the fully adjusted models. Although the social infrastructure coefficients are slightly attenuated relative to model 1, they remain statistically significant. Suicide rates were significantly lower in counties with more total social infrastructure (IRR = 0.983, 95 percent CI = 0.97–0.99, p < .01), free social infrastructure (IRR = 0.980, 95 percent CI = 0.97–0.99, p < .01), and commercial social infrastructure (IRR = 0.984, 95 percent CI = 0.97–0.99, p < .01). Interpreting the IRRs from model 2, 1-SD increases in total social infrastructure, free social infrastructure, and commercial social infrastructure are associated with 1.7 percent, 2.0 percent, and 1.6 percent fewer suicide deaths, holding all other variables constant. Although these percentages may seem small, when we consider that there were 126,678 working-age adult suicides nationally during the study period, a 1.7 percent reduction would have equated to 1,266 fewer lives lost.

In terms of covariates, counties with higher percentages of adults ages 25 and older with a bachelor’s degree, higher percentages of insured residents, and larger relative shares of Black and Hispanic populations had lower suicide rates. The poverty rate, health care provider shortages, and metropolitan status were not statistically significant, net of other covariates.

Results of Robustness Check

In our robustness check using a population-based social infrastructure measure in lieu of the density-based measure (Appendix Table A2), we found that total social infrastructure and commercial social infrastructure were related to fewer suicide deaths in the unadjusted model (model 1) but not in the fully adjusted model (model 2). This implies that the spatial distribution and coverage of social infrastructure at the county level may have a more substantial influence on suicide rates than the actual per-person quantity of infrastructure. Given that we rely on an ecological framework for these analyses that hypothesize that social support and social cohesion are the mechanisms through which social infrastructure availability might shape suicide rates, we argue that geographic availability is a more appropriate measure than per-person quantity. The density-based measure is also used in other studies to measure the availability of social infrastructure (Fraser et al. 2024) and social environment (Moore et al. 2013). In addition, the NaNDA data we used to measure social infrastructure is not able to capture the capacity (size or number of patrons) of these places, thus making per capita measures less reliable.

Discussion

Suicide is a preventable cause of death, and yet suicide rates among working-age adults in the United States are high, rising, geographically disparate, and have contributed to the nation’s stagnation in life expectancy in recent years (Becker et al. 2021). At the individual level, promoting social support and social cohesion are among the main strategies for preventing suicide (Centers for Disease Control and Prevention 2022). At the place level, social infrastructure such as libraries, coffee shops, civic organizations, sports and recreational outlets, religious establishments, and social services are key venues for building trust and social connections, the exchange of support and resources, and cultivating a sense of belonging in the community (Finlay et al. 2019; Zhang and Warner 2024). Related research shows that communities with more third places have higher levels of social cohesion (Williams and Hipp 2019) and that communities with higher levels of connectedness and trust have lower rates of mental health problems (De Silva et al. 2005; Whitley and McKenzie 2005). We build on that research by showing that counties with more social infrastructure had significantly lower average suicide rates among working-age adults from 2016 to 2019, net of county demographic and socioeconomic composition and health care provider availability. This finding held for both typically free social infrastructure and commercial social infrastructure. To our knowledge, this is the first empirical study to identify the role of social infrastructure on county-level suicide rates among working-age adults.

It was beyond the scope of this study (and the data that are available) to identify the specific mechanisms linking social infrastructure to suicide. However, there are several plausible mechanisms. Typically free social infrastructure, such as religious establishments, libraries, and community food services can increase access to resources and support for vulnerable populations who are at risk for suicide and help reduce the stigma associated with seeking help (Klinenberg 2018; O’Sullivan et al. 2013). Commercial social infrastructure, such as coffee shops, sports and recreational facilities, and barbershops, is a source of employment for individuals without college degrees, among whom suicide rates are higher (Phillips and Hempstead 2017). These places also facilitate relationship building, bonding, and the sharing of information (Arnade 2019). Our findings imply that both types of social infrastructure may buffer against the risk factors for suicide among working-age adults, a population that has experienced increases in psychological distress in recent decades (Blanchflower and Oswald 2020; Case and Deaton 2020; Daly 2022; Gaydosh et al. 2019; Goldman et al. 2018; Muennig et al. 2018). In the context of declining marriage rates (home as the first place) and labor force participation rates (work as the second place), social infrastructure (as third places) may be increasingly important for working-age adults to achieve a sense of purpose, meaning, and identity in life.

Our findings underscore the important role of local governments in supporting existing and developing new social infrastructure within the communities they serve. By encouraging cross-agency collaboration, local governments can partner with market-based services and social service agencies to increase the availability, access, and use of spaces that promote social interaction, share information, reduce social isolation, and foster a sense of belonging. In addition to helping reduce suicide rates, building more robust social infrastructure may also help reduce crime (Papachristos et al. 2011), support overall health (Walton 2014), and promote entrepreneurship, community economic development, and upward social mobility (Cabras and Mount 2017; Sharp et al. 2002).

Study Limitations and Directions for Future Research

These results should be considered in relation to some study limitations. First, our analyses are cross-sectional. As such, we cannot determine causality. Second, suicide is among the most commonly misclassified causes of death (Rockett et al. 2022). Our findings may be biased by geographic variation in misclassification if misclassification is more or less likely to occur in places with more or less social infrastructure.

Third, social infrastructure availability does not imply accessibility or use. Different types of social infrastructure may be inaccessible to certain groups, including those who are low income, minoritized racial and ethnic groups, and individuals with disabilities. We made the case in the introduction that social infrastructure transmits collective benefits beyond specific users because it increases overall social cohesion and helps reduce social disorganization (Finlay et al. 2019, 2022; Kingsbury et al. 2020). Nonetheless, given the ecological nature of this study, we cannot connect individual use of social infrastructure to suicide.

Fourth, the availability of social infrastructure could vary by place-level ethnoracial composition, socioeconomic composition, and rurality (Fraser et al. 2024; Rhubart et al. 2022). We encourage future research to explore these potential heterogenous associations. Fifth, we focused on working-age adults. Older adults and children may have distinct types and patterns of interaction with their local social and built environments (Nathan et al. 2018), such that the relationship between social infrastructure and suicide may be different in these age groups. Future research should consider the relationship between social infrastructure and suicide in these age groups for which different mechanisms may operate.

Finally, the COVID-19 pandemic highlighted the importance of social relationships and the psychosocial harms associated with reducing social interaction (Banerjee, Kosagisharaf, and Rao 2021). We encourage research that explores how the availability and use of social infrastructure changed during and after the pandemic and how those changes may have influenced suicide rates.

Conclusion

This research highlights the importance of social infrastructure on county-level suicide rates among working-age adults in the United States. We provide evidence that suicide rates are lower in counties with more social infrastructure availability, and this association holds for both typically free social infrastructure and commercial social infrastructure. Our results illustrate the need for policy makers to prioritize the maintenance of existing and development of new social infrastructure as part of a broader strategy to reduce suicide rates in the United States.

Supplemental Material

sj-docx-1-srd-10.1177_23780231241241034 – Supplemental material for Social Infrastructure Availability and Suicide Rates among Working-Age Adults in the United States

Supplemental material, sj-docx-1-srd-10.1177_23780231241241034 for Social Infrastructure Availability and Suicide Rates among Working-Age Adults in the United States by Xue Zhang, Danielle C. Rhubart and Shannon M. Monnat in Socius

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by the Interdisciplinary Network on Rural Population Health and Aging (National Institute on Aging grant R24 AG065159) and the National Institute on Drug Abuse (grant U01 DA055972) and supported by the National Institute on Aging (grants P30 AG066583 and 2R24 AG045061) and the Rural Population Research Network (a Department of Agriculture–funded multistate research network; grant W5001).

ORCID iDs

Xue Zhang

Danielle C. Rhubart

Shannon M. Monnat

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Xue Zhang is a Lerner Postdoctoral Scholar in population health at Syracuse University. She is a social scientist, demographer, and population health scholar who conducts research on geographic differences in demographic structure, public policy, and social determinates of health, with a special interest in rural-urban differences and health disparity. Her most recent research examines governments’ policy response during COVID-19. She is interested in factors related to governments’ policy decision, and the relation between various policies and health outcomes, including physical, mental, psychological health, mortality, and COVID-19 infections and deaths. Her research also examines factors at the individual, community, and policy levels that contribute to a better population health.

Danielle C. Rhubart is an assistant professor of biobehavioral health and demography and director of the Rural Health Disparities Lab. She is trained as a rural sociologist and demographer and studies rural population health and how built and social environments shape health and well-being. She has published 19 peer-reviewed journal articles, including articles in Public Policy and Aging Report, Milbank Quarterly, Population Research and Policy Review, and Rural Sociology. She also has research briefs and reports through the Carsey School of Public Policy (University of New Hampshire), the Lerner Center for Public Health Promotion (Syracuse University), and the Center for Rural Pennsylvania.

Shannon M. Monnat is a professor of sociology, director of the Center for Policy Research, and Lerner Chair in Public Health Promotion and Population Health at Syracuse University. She is a demographer and population health scholar whose research examines trends and geographic differences in health and mortality. She has authored more than 70 peer-reviewed journal articles, as well as numerous book chapters and policy briefs. She has been the principal investigator or coinvestigator on externally funded projects totaling more than $12 million. She currently leads a National Institute on Drug Abuse–funded project to examine the effects of state’s COVID-19 mitigation policies on working-age adult psychological well-being, drug overdose, and suicide and coleads a National Institute on Aging–funded project on how state policies and county economic conditions have jointly contributed to the large and growing geographic disparities in midlife mortality, psychosocial well-being, and health behaviors in the United States.

References

Abrutyn

Seth

Mueller

Anna S.

2018. “Toward a Cultural-Structural Theory of Suicide: Examining Excessive Regulation and Its Discontents.” Sociological Theory 36(1):48–66.

Agency for Healthcare Research and Quality. 2023. “Social Determinants of Health Database.” Retrieved February 13, 2024. https://www.ahrq.gov/sdoh/data-analytics/sdoh-data.html.

Anestis

Michael D.

Anestis

Joye C.

2015. “Suicide Rates and State Laws Regulating Access and Exposure to Handguns.” American Journal of Public Health 105(10):2049–58.

Arnade

Chris

. 2019. Dignity: Seeking Respect in Back Row America. Sentinel.

Banerjee

Debanjan

Kosagisharaf

Jagannatha Rao

Rao

T. S. Sathyanarayana

. 2021. “‘The Dual Pandemic’ of Suicide and COVID-19: A Biopsychosocial Narrative of Risks and Prevention.” Psychiatry Research 295:113577.

Becker

Tara

Majmundar

Malay K.

Harris

Kathleen Mullan

, eds. 2021. “High and Rising Mortality Rates among Working-Age Adults.” Washington, DC: The National Academies Press.

Blanchflower

David G.

Oswald

Andrew J.

2020. “Trends in Extreme Distress in the United States, 1993–2019.” American Journal of Public Health 110(10):1538–44.

Brådvik

Louise

. 2018. “Suicide Risk and Mental Disorders.” International Journal of Environmental Research and Public Health 15(9):2028.

Burgard

Sarah A.

Kalousova

Lucie

. 2015. “Effects of the Great Recession: Health and Well-Being.” Annual Review of Sociology 41:181–201.

10.

Butler

Stuart M.

Diaz

Carmen

. 2016. “‘Third Places’ as Community Builders.” Brookings Institute. Retrieved January 5, 2024. https://www.brookings.edu/articles/third-places-as-community-builders/.

11.

Cabras

Ignazio

Mount

Matthew P.

2017. “How Third Places Foster and Shape Community Cohesion, Economic Development and Social Capital: The Case of Pubs in Rural Ireland.” Journal of Rural Studies 55:71–82.

12.

Carrasco

Maria A.

Bilal

Usama

. 2016. “A Sign of the Times: To Have or to Be? Social Capital or Social Cohesion?” Social Science & Medicine 159:127–31.

13.

Carriere

Danielle E.

Marshall

Maria I.

Binkley

James K.

2019. “Response to Economic Shock: The Impact of Recession on Rural–Urban Suicides in the United States.” Journal of Rural Health 35(2):253–61.

14.

Case

Anne

Deaton

Angus

. 2020. Deaths of Despair and the Future of Capitalism. Princeton, NJ: Princeton University Press.

15.

Centers for Disease Control and Prevention. 2022. “Suicide Prevention Resource for Action.” Retrieved May 30, 2023. https://www.cdc.gov/suicide/resources/prevention.html.

16.

Centers for Disease Control and Prevention. 2023. “Web-Based Injury Statistics Query and Reporting System (WISQARS).” Retrieved January 5, 2024. https://www.cdc.gov/injury/wisqars/index.html.

17.

Cherlin

Andrew J.

2014. Labor’s Love Lost: The Rise and Fall of the Working-Class Family in America. New York: Russell Sage.

18.

Cummings

Neil

. 2012. “Fostering Sustainable Behavior through Design: A Study of the Social, Psychological, and Physical Influences of the Built Environment.” Master’s thesis, University of Massachusetts Amherst. Retrieved June 6, 2023. https://scholarworks.umass.edu/theses/885.

19.

Daly

Michael

. 2022. “Prevalence of Psychological Distress among Working-Age Adults in the United States, 1999–2018.” American Journal of Public Health 112(7):1045–49.

20.

De Silva

Mary J.

McKenzie

Kwame

Harpham

Trudy

Huttly

Sharon R. A.

2005. “Social Capital and Mental Illness: A Systematic Review.” Journal of Epidemiology & Community Health 59(8):619–27.

21.

Domenech-Abella

Joan

Mundo

Jordi

Leonardi

Matilde

Chatterji

Somnath

Tobiasz-Adamczyk

Beata

Koskinen

Seppo

Ayuso-Mateos

Jose Luis

, et al. 2020. “Loneliness and Depression among Older European Adults: The Role of Perceived Neighborhood Built Environment.” Health & Place 62:102280.

22.

Durkheim

Emile

. 1897. Suicide: A Sociological Study. Paris: Alcan.

23.

Fazel

Seena

Runeson

. 2020. “Suicide. Reply.” New England Journal of Medicine 382(21):e66.

24.

Feldmeyer

Ben

Cullen

Francis T.

Sun

Diana

Kulig

Teresa C.

Chouhy

Cecilia

Zidar

Michael

. 2022. “The Community Determinants of Death: Comparing the Macro-level Predictors of Overdose, Homicide, and Suicide Deaths, 2000 to 2015.” Socius. doi:10.1177/23780231221100392.

25.

Finlay

Jessica

Esposito

Michael

Kim

Min Hee

Gomez-Lopez

Iris

Clarke

Philippa

. 2019. “Closure of ‘Third Places’? Exploring Potential Consequences for Collective Health and Wellbeing.” Health & Place 60:102225.

26.

Finlay

Jessica

Esposito

Michael

Langa

Kenneth M.

Judd

Suzanne

Clarke

Philippa

. 2022. “Cognability: An Ecological Theory of Neighborhoods and Cognitive Aging.” Social Science & Medicine 309:115220.

27.

Fraser

Timothy

Feeley

Olivia

Ridge

Andres

Cervini

Ava

Rago

Vincent

Gilmore

Kelly

Worthington

Gianna

, et al. 2024. “How Far I’ll Go: Social Infrastructure Accessibility and Proximity in Urban Neighborhoods.” Landscape and Urban Planning 241:104922.

28.

Gaydosh

Lauren

Hummer

Robert A.

Hargrove

Taylor W.

Halpern

Carolyn T.

Hussey

Jon M.

Whitsel

Eric A.

Dole

Nancy

, et al. 2019. “The Depths of Despair among Us Adults Entering Midlife.” American Journal of Public Health 109(5):774–80.

29.

Goldman

Noreen

Glei

Dana A.

Weinstein

Maxine

. 2018. “Declining Mental Health among Disadvantaged Americans.” Proceedings of the National Academy of Sciences 115(28):7290–95.

30.

Hood-Williams

John

. 1996. “Studying Suicide.” Health & Place 2(3):167–77.

31.

Kaufman

John A.

Salas-Hernández

Leslie K.

Komro

Kelli A.

Livingston

Melvin D.

2020. “Effects of Increased Minimum Wages by Unemployment Rate on Suicide in the USA.” Journal of Epidemiology and Community Health 74(3):219–24.

32.

Kawachi

Ichiro

Berkman

Lisa

. 2000. “Social Cohesion, Social Capital, and Health.” Social Epidemiology 174(7):290–319.

33.

Kegler

Scott R.

Stone

Deborah M.

Holland

Kristin M.

2017. “Trends in Suicide by Level of Urbanization—United States, 1999–2015.” Morbidity and Mortality Weekly Report 66(10):270.

34.

Keyes

Katherine M.

Kandula

Sasikiran

Martinez-Ales

Gonzalo

Gimbrone

Catherine

Joseph

Victoria

Monnat

Shannon M.

Rutherford

Caroline

, et al. 2024. “Geographic Variation, Economic Activity, and Labor Market Characteristics in Trajectories of Suicide in the United States, 2008 to 2020.” American Journal of Epidemiology 193(2):256–66.

35.

Kingsbury

Mila

Clayborne

Zahra

Colman

Ian

Kirkbride

James B.

2020. “The Protective Effect of Neighbourhood Social Cohesion on Adolescent Mental Health Following Stressful Life Events.” Psychological Medicine 50(8):1292–9.

36.

Klinenberg

Eric

. 2018. Palaces for the People: How Social Infrastructure Can Help Fight Inequality, Polarization, and the Decline of Civic Life. New York: Crown.

37.

Monnat

Shannon M.

2019. “The Contributions of Socioeconomic and Opioid Supply Factors to US Drug Mortality Rates: Urban-Rural and Within-Rural Differences.” Journal of Rural Studies 68:319–35.

38.

Monnat

Shannon M.

Peters

David J.

Berg

Mark T.

Hochstetler

Andrew

. 2019. “Using Census Data to Understand County-Level Differences in Overall Drug Mortality and Opioid-Related Mortality by Opioid Type.” American Journal of Public Health 109(8):1084–91.

39.

Montez

Jennifer Karas

Mehri

Nader

Monnat

Shannon M.

Beckfield

Jason

Chapman

Derek

Grumbach

Jacob M.

Hayward

Mark D.

, et al. 2022. “U.S. State Policy Contexts and Mortality of Working-Age Adults.” PLoS One 17(10):e0275466.

40.

Moore

Kari

Diez Roux

Ana V.

Auchincloss

Amy

Evenson

Kelly R.

Kaufman

Joel

Mujahid

Mahasin

Williams

Kayleen

. 2013. “Home and Work Neighbourhood Environments in Relation to Body Mass Index: The Multi-ethnic Study of Atherosclerosis (MESA).” Journal of Epidemiology & Community Health 67(10):846–53.

41.

Mueller

Anna S.

Abrutyn

Seth

Pescosolido

Bernice

Diefendorf

Sarah

. 2021. “The Social Roots of Suicide: Theorizing How the External Social World Matters to Suicide and Suicide Prevention.” Frontiers in Psychology 12:621569.

42.

Muennig

Peter A.

Reynolds

Megan

Fink

David S.

Zafari

Zafar

Geronimus

Arline T.

2018. “America’s Declining Well-Being, Health, and Life Expectancy: Not Just a White Problem.” American Journal of Public Health 108(12):1626–31.

43.

Nathan

Andrea

Villanueva

Karen

Rozek

Julianna

Davern

Melanie

Gunn

Lucy

Trapp

Gina

Boulangé

Claire

, et al. 2018. “The Role of the Built Environment on Health across the Life Course: A Call for CollaborACTION.” American Journal of Health Promotion 32(6):1460–68.

44.

National Institute of Mental Health. 2023. “Frequently Asked Questions about Suicide.” Retrieved May 19, 2023. https://www.nimh.nih.gov/health/publications/suicide-faq.

45.

Oldenburg

Ray

. 2014. “Every Community Deserves a Third Place.” The New York Times. Retrieved January 5, 2024. https://www.nytimes.com/roomfordebate/2014/04/13/the-pros-and-cons-of-gentrification/every-community-deserves-a-third-place.

46.

Oldenburg

Ray

Brissett

Dennis

. 1982. “The Third Place.” Qualitative Sociology 5(4):265–84.

47.

Opoliner

April

Azrael

Deborah

Barber

Catherine

Fitzmaurice

Garrett

Miller

Matthew

. 2014. “Explaining Geographic Patterns of Suicide in the US: The Role of Firearms and Antidepressants.” Injury Epidemiology 1(1):1–7.

48.

O’Sullivan

Tracey L.

Kuziemsky

Craig E.

Toal-Sullivan

Darene

Corneil

Wayne

. 2013. “Unraveling the Complexities of Disaster Management: A Framework for Critical Social Infrastructure to Promote Population Health and Resilience.” Social Science & Medicine 93:238–46.

49.

Papachristos

Andrew V.

Smith

Chris M.

Scherer

Mary L.

Fugiero

Melissa A.

2011. “More Coffee, Less Crime? The Relationship between Gentrification and Neighborhood Crime Rates in Chicago, 1991 to 2005.” City & Community 10(3):215–40.

50.

Phillips

Julie A.

2013. “Factors Associated with Temporal and Spatial Patterns in Suicide Rates across US States, 1976–2000.” Demography 50(2):591–614.

51.

Phillips

Julie A.

Hempstead

Katherine

. 2017. “Differences in US Suicide Rates by Educational Attainment, 2000–2014.” American Journal of Preventive Medicine 53(4):e123–30.

52.

Phillips

Julie A.

Nugent

Colleen N.

2014. “Suicide and the Great Recession of 2007–2009: The Role of Economic Factors in the 50 US States.” Social Science & Medicine 116:22–31.

53.

Pierce

Justin R.

Schott

Peter K.

2020. “Trade Liberalization and Mortality: Evidence from US Counties.” American Economic Review: Insights 2(1):47–64.

54.

Recker

Nicholas L.

Moore

Matthew D.

2016. “Durkheim, Social Capital, and Suicide Rates across US Counties.” Health Sociology Review 25(1):78–91.

55.

Rhubart

Danielle

Kowalkowski

Jennifer

Wincott

Logan

. 2023. “The Built Environment and Social and Emotional Support among Rural Older Adults: The Case for Social Infrastructure and Attention to Ethnoracial Differences.” Rural Sociology 88(3):731–62.

56.

Rhubart

Danielle

Sun

Yue

Pendergrast

Claire

Monnat

Shannon M.

2022. “Sociospatial Disparities in ‘Third Place’ Availability in the United States.” Socius. doi:10.1177/23780231221090301.

57.

Robinette

Jennifer W.

Bostean

Georgiana

Glynn

Laura M.

Douglas

Jason A.

Jenkins

Brooke N.

Gruenewald

Tara L.

Frederick

David A.

2021. “Perceived Neighborhood Cohesion Buffers COVID-19 Impacts on Mental Health in a United States Sample.” Social Science & Medicine 285:114269.

58.

Rockett

Ian R. H.

Jia

Haomiao

Ali

Bina

Banerjee

Aniruddha

Connery

Hilary S.

Nolte

Kurt B.

Miller

Ted

, et al. 2022. “Association of State Social and Environmental Factors with Rates of Self-Injury Mortality and Suicide in the United States.” JAMA Network Open 5(2):e2146591.

59.

Rotenberg

Martin

Anderson

Kelly K.

McKenzie

Kwame

. 2020. “Social Capital and Psychosis: A Scoping Review.” Social Psychiatry and Psychiatric Epidemiology 55:659–71.

60.

Schiefer

David

Van der Noll

Jolanda

. 2017. “The Essentials of Social Cohesion: A Literature Review.” Social Indicators Research 132:579–603.

61.

Shanahan

Lilly

Hill

Sherika N.

Gaydosh

Lauren M.

Steinhoff

Annekatrin

Costello

E. Jane

Dodge

Kenneth A.

Harris

Kathleen Mullan

, et al. 2019. “Does Despair Really Kill? A Roadmap for an Evidence-Based Answer.” American Journal of Public Health 109(6):854–58.

62.

Sharp

Jeff S.

Agnitsch

Kerry

Ryan

Vern

Flora

Jan

. 2002. “Social Infrastructure and Community Economic Development Strategies: The Case of Self-Development and Industrial Recruitment in Rural Iowa.” Journal of Rural Studies 18(4):405–417.

63.

Smith

Nathan Daniel Lucia

Kawachi

Ichiro

. 2014. “State-Level Social Capital and Suicide Mortality in the 50 US States.” Social Science & Medicine 120:269–77.

64.

Speer

Paul W.

Jackson

Courtney B.

Peterson

N. Andrew

. 2001. “The Relationship between Social Cohesion and Empowerment: Support and New Implications for Theory.” Health Education & Behavior 28(6):716–32.

65.

Steele

Ian H.

Thrower

Natasha

Noroian

Paul

Saleh

Fabian M.

2018. “Understanding Suicide across the Lifespan: A United States Perspective of Suicide Risk Factors, Assessment & Management.” Journal of Forensic Sciences 63(1):162–71.

66.

Steelesmith

Danielle L.

Fontanella

Cynthia A.

Campo

John V.

Bridge

Jeffrey A.

Warren

Keith L.

Root

Elisabeth D.

2019. “Contextual Factors Associated with County-Level Suicide Rates in the United States, 1999 to 2016.” JAMA Network Open 2(9):e1910936.

67.

Thompson

Beverly Yuen

. 2019. “The Digital Nomad Lifestyle: (Remote) Work/Leisure Balance, Privilege, and Constructed Community.” International Journal of the Sociology of Leisure 2(1–2):27–42.

68.

U.S. Census Bureau. 2016. “2011-2015 ACS 5-Year Estimates.” Retrieved March 21, 2024. https://www.census.gov/programs-surveys/acs/technical-documentation/table-and-geography-changes/2015/5-year.html.

69.

U.S. Census Bureau and National Center for Health Statistics. 2023. “Bridged-Race Population Estimates.” Retrieved February 1, 2023. https://wonder.cdc.gov/bridged-race-population.html.

70.

U.S. Department of Agriculture, Economic Research Service. 2020. “2013 Rural-Urban Continuum Codes.” Retrieved October 9, 2022. https://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx.

71.

Venkataramani

Atheendar S.

Chatterjee

Paula

Kawachi

Ichiro

Tsai

Alexander C.

2016. “Economic Opportunity, Health Behaviors, and Mortality in the United States.” American Journal of Public Health 106(3):478–84.

72.

Walton

Emily

. 2014. “Vital Places: Facilitators of Behavioral and Social Health Mechanisms in Low-Income Neighborhoods.” Social Science & Medicine 122:1–12.

73.

Whitley

Rob

McKenzie

Kwame

. 2005. “Social Capital and Psychiatry: Review of the Literature.” Harvard Review of Psychiatry 13(2):71–84.

74.

Williams

Seth A.

Hipp

John R.

2019. “How Great and How Good? Third Places, Neighbor Interaction, and Cohesion in the Neighborhood Context.” Social Science Research 77:68–78.

75.

Zhang

Xue

Monnat

Shannon M.

2024. “Geographically Specific Associations between County-Level Socioeconomic and Household Distress and Mortality from Drug Poisoning, Suicide, Alcohol, and Homicide among Working-Age Adults in the United States.” SSM – Population Health 25:101595.

76.

Zhang

Xue

Warner

Mildred E.

2024. “Cross-Agency Collaboration to Address Rural Aging: The Role of County Government.” Journal of Aging & Social Policy 36(2):302–324.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB