Do measures of country-level safety predict individual-level health outcomes?

Kimberly R. More, Adele Quigley-McBride, Alexa S. Clerke, Curt More

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Health is not only a result of biological conditions, but of psychological, economic, and social circumstances. Both proximal factors, which impact daily life, and distal factors, which are further removed from everyday life, can influence a person's wellbeing. However, traditionally these distal factors have been overlooked in public discourse and government policy. 

Objective: In the present study we examined whether measures of country-level safety predict the health of their residents. Additionally, we examined whether socioeconomic status (SES; approximated by income) interacts with other proximal factors to predict health. 

Methods: Participants were 81,415 individuals residing in 58 countries. Multilevel modeling was used to determine the influence of distal and proximal factors on health. 

Results: Findings indicated that both country-level safety and SES predict health regardless of the country of residence. Additionally, SES interacted with other proximal variables (e.g., life satisfaction and access to food) to predict health. 

Conclusions: In addition to everyday living conditions, health is contingent upon circumstances that do not directly impact daily life. This indicates that preventive measures are needed to secure the health of individuals impacted not only by negative proximal factors, but negative distal factors as well. In light of these findings, more translational research is needed to highlight the importance of the biopsychosocial model of health to both policymakers and the public. In this article, we suggest two research avenues relating to country-level safety that could provide specific recommendations for policy change.

Original languageEnglish
Pages (from-to)128-138
Number of pages11
JournalSocial Science and Medicine
Volume225
DOIs
Publication statusPublished - Mar 2019

Keywords

  • Global health
  • Multilevel analysis
  • Population health
  • Social determinants of health
  • Subjective health

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