Modeling the Importance of Within- and Between-County Effects in an Ecological Study of the Association Between Social Capital and Mental Distress

Modeling the Importance of Within- and Between-County Effects in an Ecological Study of the Association Between Social Capital and Mental Distress

ORIGINAL RESEARCH — Volume 16 — June 13, 2019

Tse-Chuan Yang, PhD1; Stephen A. Matthews, PhD2; Feinuo Sun1; Marina Armendariz3 (View author affiliations)

Suggested citation for this article: Yang T, Matthews SA, Sun F, Armendariz M. Modeling the Importance of Within- and Between-County Effects in an Ecological Study of the Association Between Social Capital and Mental Distress. Prev Chronic Dis 2019;16:180491. DOI: http://dx.doi.org/10.5888/pcd16.180491external icon.

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On This Page

• Abstract
• Introduction
• Methods
• Results
• Discussion
• Acknowledgments
• Author Information
• References
• Tables

Summary

What is already known on this topic?

At the individual level, high levels of social capital are associated with low levels of mental distress.

What is added by this report?

We used ecological data to demonstrate that social capital and prevalence of mental distress are spatially clustered in US counties. We showed that social capital decreases the prevalence of mental distress within a county, but this within-county association is weaker than the between-county association.

What are the implications for public health practice?

Our results suggest that policy interventions to promote population-level mental health should consider broader multi-county contexts and the coordination of actions within the consortia of neighboring counties.

Abstract

Introduction

Levels of mental distress in the United States are a health policy concern. The association between social capital and mental distress is well documented, but evidence comes primarily from individual-level studies. Our objective was to examine this association at the county level with advanced spatial econometric methods and to explore the importance of between-county effects.

Methods

We used County Health Rankings and Roadmaps data for 3,106 counties of the contiguous United States. We used spatial Durbin modeling to assess the direct (within a county) and indirect (between neighboring counties) effects of social capital on mental distress. We also examined the spatial spillover effects from neighboring counties based on higher-order spatial weights matrices.

Results

Counties with the highest prevalence of mental distress were found in regional clusters where levels of social capital were low, including the Black Belt, central/southern Appalachia, on the Mississippi River, and around some Indian Reservations. Most of the association between social capital and mental distress was indirect, from the neighboring counties, although significant direct effects showed the within-county association. Models also confirmed the importance of county-level socioeconomic status.

Conclusion

We found that county social capital is negatively related to mental distress. Counties are not isolated places and are often part of wider labor and housing markets, so understanding spatial dependencies is important in addressing population-level mental distress.