Skip to main content

Advertisement

SpringerLink
Log in

Social Determinants of Population Health: A Systems Sciences Approach

  • Social Epidemiology (JM Oakes, Section Editor)
  • Published:
Current Epidemiology Reports Aims and scope Submit manuscript

Abstract

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Berk BB. Macro-micro relationships in Durkheim’s analysis of egoistic suicide. Sociol Theory. 2006;24(1):58–80.

    Article  Google Scholar 

  2. Rose G. The strategy of preventive medicine. The strategy of preventive medicine. 1992.

  3. Beckfield J, Krieger N. Epi + demos + cracy: linking political systems and priorities to the magnitude of health inequities—evidence, gaps, and a research agenda. Epidemiol Rev. 2009;31:152–77. doi:10.1093/epirev/mxp002.

    Article  PubMed  Google Scholar 

  4. Kramer MR, Hogue CR. Is segregation bad for your health? Epidemiol Rev. 2009;31:178–94. doi:10.1093/epirev/mxp001.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Oakes JM, Andrade KE, Biyoow IM, Cowan LT. Twenty years of neighborhood effect research: an assessment. Current Epidemiol Reports. 2015;2(1):80–7. doi:10.1007/s40471-015-0035-7.

    Article  Google Scholar 

  6. Bandura A. Social learning theory. Englewood Cliffs, NJ: Prentice-Hall; 1977.

    Google Scholar 

  7. Bandura A. Social foundations of thought and action: a social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall; 1986.

    Google Scholar 

  8. Latane B. The psychology of social impact theory. Am Psychol. 1981;36(4):343–56.

    Article  Google Scholar 

  9. Page SE. What sociologists should know about complexity. Annu Rev Sociol. 2015;41(1):21–41. doi:10.1146/annurev-soc-073014-112230. This qualitative review outlines existing literature with respect to complexity in the social sciences.

    Article  Google Scholar 

  10. Galea S, Riddle M, Kaplan GA. Causal thinking and complex system approaches in epidemiology. Int J Epidemiol. 2010;39(1):97–106.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Marshall BD, Galea S. Formalizing the role of agent-based modeling in causal inference and epidemiology. Am J Epidemiol. 2014:kwu274. This paper makes a case for agent-based models to be used to simulate counterfactual outcomes in the presence of complexity.

  12. El-Sayed AM, Scarborough P, Seemann L, Galea S. Social network analysis and agent-based modeling in social epidemiology. Epidemiol Perspect Innov. 2012;9(1):1. doi:10.1186/1742-5573-9-1. This qualitative review describes the application of systems science methods in epidemiology, focusing on network analysis and agent-based models.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Butts CT. Social network analysis: a methodological introduction. Asian J Social Psychol. 2008;11(1):13–41. doi:10.1111/j.1467-839X.2007.00241.x.

    Article  Google Scholar 

  14. Speybroeck N, Van Malderen C, Harper S, Muller B, Devleesschauwer B. Simulation models for socioeconomic inequalities in health: a systematic review. Int J Environ Res Public Health. 2013;10(11):5750–80. doi:10.3390/ijerph10115750.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Luke DA, Stamatakis KA. Systems science methods in public health: dynamics, networks, and agents. Annu Rev Public Health. 2012;33:357–76. doi:10.1146/annurev-publhealth-031210-101222.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006;96(3):452–8. doi:10.2105/ajph.2005.062059.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Garnett GP, Anderson RM. Sexually transmitted diseases and sexual behavior: insights from mathematical models. J Infect Dis. 1996;174 Suppl 2:S150–61.

    Article  PubMed  Google Scholar 

  18. Ghani AC, Swinton J, Garnett GP. The role of sexual partnership networks in the epidemiology of gonorrhea. Sex Transm Dis. 1997;24(1):45–56.

    Article  CAS  PubMed  Google Scholar 

  19. Potterat JJ, Rothenberg RB, Muth SQ. Network structural dynamics and infectious disease propagation. Int J STD AIDS. 1999;10(3):182–5.

    Article  CAS  PubMed  Google Scholar 

  20. Rothenberg RB, Potterat JJ, Woodhouse DE, Muth SQ, Darrow WW, Klovdahl AS. Social network dynamics and HIV transmission. AIDS. 1998;12(12):1529–36.

    Article  CAS  PubMed  Google Scholar 

  21. Smith BT, Smith PM, Harper S, Manuel DG, Mustard CA. Reducing social inequalities in health: the role of simulation modelling in chronic disease epidemiology to evaluate the impact of population health interventions. J Epidemiol Community Health. 2014;68(4):384–9. doi:10.1136/jech-2013-202756.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Diez Roux AV. Complex systems thinking and current impasses in health disparities research. Am J Public Health. 2011;101(9):1627–34. doi:10.2105/ajph.2011.300149.

    Article  PubMed  PubMed Central  Google Scholar 

  23. McPherson M, Smith-Lovin L, Cook JM. Birds of a feather: homophily in social networks. Annu Rev Sociol. 2001;27:415–44.

    Article  Google Scholar 

  24. Wiens JJ, Graham CH. Niche conservatism: integrating evolution, ecology, and conservation biology. Annu Rev Ecol Syst. 2005;36:519–39.

    Article  Google Scholar 

  25. Vandermeer JH. Niche theory. Annu Rev Ecol Syst. 1972;3:107–32.

    Article  Google Scholar 

  26. Loureiro ML, Hine S. Discovering niche markets: a comparison of consumers willingness to pay for local (Colorado grown), organic, and GMO-free products. J Agric Appl Econ. 2002;34(3):477–88.

    Google Scholar 

  27. Gruenewald PJ. The spatial ecology of alcohol problems: niche theory and assortative drinking. Addiction. 2007;102(6):870–8. doi:10.1111/j.1360-0443.2007.01856.x.

    Article  PubMed  Google Scholar 

  28. Gorman DM, Mezic J, Mezic I, Gruenewald PJ. Agent-based modeling of drinking behavior: a preliminary model and potential applications to theory and practice. Am J Public Health. 2006;96(11):2055–60. doi:10.2105/ajph.2005.063289.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Tchetgen Tchetgen EJ, VanderWeele T. On causal inference in the presence of interference. Stat Methods Med Res. 2010;21(1):55–75.

    Article  PubMed  Google Scholar 

  30. Yang Y, Diez-Roux A, Evenson KR, Colabianchi N. Examining the impact of the walking school bus with an agent-based model. Am J Public Health. 2014;104(7):1196–203. doi:10.2105/ajph.2014.301896. This paper presents evidence from an agent-based model on factors that influence intervention effects in the presence of interference among units.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Yang Y, Diez-Roux AV. Using an agent-based model to simulate children’s active travel to school. Int J Behav Nutr Phys Act. 2013;10:67. doi:10.1186/1479-5868-10-67.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Yang Y, Diez Roux AV, Auchincloss AH, Rodriguez DA, Brown DG. Exploring walking differences by socioeconomic status using a spatial agent-based model. Health Place. 2012;18(1):96–9. doi:10.1016/j.healthplace.2011.08.010.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Yang Y, Auchincloss AH, Rodriguez DA, Brown DG, Riolo R, Diez-Roux AV. Modeling spatial segregation and travel cost influences on utilitarian walking: towards policy intervention. Comput Environ Urban Syst. 2015;51:59–69. doi:10.1016/j.compenvurbsys.2015.01.007.

    Article  PubMed  Google Scholar 

  34. Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. N Engl J Med. 2007;357(4):370–9. doi:10.1056/NEJMsa066082.

    Article  CAS  PubMed  Google Scholar 

  35. Fowler JH, Christakis NA. Estimating peer effects on health in social networks: a response to Cohen-Cole and Fletcher; and Trogdon, Nonnemaker, and Pais. J Health Econ. 2008;27(5):1400–5. doi:10.1016/j.jhealeco.2008.07.001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Marshall BD, Friedman SR, Monteiro JF, Paczkowski M, Tempalski B, Pouget ER, et al. Prevention and treatment produced large decreases in HIV incidence in a model of people who inject drugs. Health Aff (Millwood). 2014;33(3):401–9. doi:10.1377/hlthaff.2013.0824. This paper is a model for investigating time lags using agent-based models.

    Article  Google Scholar 

  37. Krieger N. Epidemiology and the web of causation: has anyone seen the spider? Soc Sci Med. 1994;39(7):887–903.

    Article  CAS  PubMed  Google Scholar 

  38. Susser M, Susser E. Choosing a future for epidemiology: II. From black box to Chinese boxes and eco-epidemiology. Am J Public Health. 1996;86(5):674–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. McMichael AJ. Prisoners of the proximate: loosening the constraints on epidemiology in an age of change. Am J Epidemiol. 1999;149(10):887–97.

    Article  CAS  PubMed  Google Scholar 

  40. Cerda M, Tracy M, Ahern J, Galea S. Addressing population health and health inequalities: the role of fundamental causes. Am J Public Health. 2014;104 Suppl 4:S609–19. doi:10.2105/ajph.2014.302055.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Centers for disease control NCfHS. Underlying cause of death 1999-2013 on CDC WONDER online database, released, 2015. Data are from the Multiple Cause of Death File, 1999-2013, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. 2015.

  42. Sampson RJ, Raudenbush SW, Earls F. Neighborhoods and violent crime: a multilevel study of collective efficacy. Science. 1997;227(5328):918–24.

    Article  Google Scholar 

  43. Link BG, Phelan J. Social conditions as fundamental causes of disease. J Health Soc Behav. 1995;Spec No:80-94.

  44. Ladyman J, Lambert J, Wiesner K. What is a complex system? European J Philosphy Sci. 2013;3(1):33–67.

    Article  Google Scholar 

  45. Schelling TC. Dynamic models of segregation. J Math Sociol. 1971;1:143–86.

    Article  Google Scholar 

  46. Yang Y, Diez Roux AV, Auchincloss AH, Rodriguez DA, Brown DG. A spatial agent-based model for the simulation of adults’ daily walking within a city. Am J Prev Med. 2011;40(3):353–61. doi:10.1016/j.amepre.2010.11.017.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Auchincloss AH, Riolo RL, Brown DG, Cook J, Diez Roux AV. An agent-based model of income inequalities in diet in the context of residential segregation. Am J Prev Med. 2011;40(3):303–11. doi:10.1016/j.amepre.2010.10.033.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Story M, Kaphingst KM, Robinson-O’Brien R, Glanz K. Creating healthy food and eating environments: policy and environmental approaches. Annu Rev Public Health. 2008;29:253–72. doi:10.1146/annurev.publhealth.29.020907.090926.

    Article  PubMed  Google Scholar 

  49. Leonard T, McKillop C, Carson JA, Shuval K. Neighborhood effects on food consumption. J Behav Exp Econ. 2014;51:99–113. doi:10.1016/j.socec.2014.04.002.

    Article  Google Scholar 

  50. Cerda M, Tracy M, Keyes KM, Galea S. To treat or to prevent? Reducing the population burden of violence-related post-traumatic stress disorder. Epidemiology. 2015;26(5):681–9. doi:10.1097/ede.0000000000000350. This paper presents agent-based model that compares the effectiveness of two potential interventions on population health. It offers important substantive insight and introduces the role that these models can have in future policy decisions.

    Article  PubMed  Google Scholar 

  51. Wilson DP, Blower SM. Designing equitable antiretroviral allocation strategies in resource-constrained countries. PLoS Med. 2005;2(2):e50. doi:10.1371/journal.pmed.0020050.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Verguet S. Efficient and equitable HIV prevention: a case study of male circumcision in South Africa. Cost Eff Resource Allocation : C/E. 2013;11(1):1. doi:10.1186/1478-7547-11-1.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Matsumoto M, Ogawa T, Kashima S, Takeuchi K. The impact of rural hospital closures on equity of commuting time for haemodialysis patients: simulation analysis using the capacity-distance model. Int J Health Geogr. 2012;11:28. doi:10.1186/1476-072x-11-28.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Blok DJ, de Vlas SJ, Bakker R, van Lenthe FJ. Reducing income inequalities in food consumption: explorations with an agent-based model. Am J Prev Med. 2015;49(4):605–13. doi:10.1016/j.amepre.2015.03.042.

    Article  PubMed  Google Scholar 

  55. Mahamoud A, Roche B, Homer J. Modelling the social determinants of health and simulating short-term and long-term intervention impacts for the city of Toronto. Canada Soc Sci Med. 2013;93:247–55. doi:10.1016/j.socscimed.2012.06.036.

    Article  PubMed  Google Scholar 

  56. Dray A, Perez P, Moore D, Dietze P, Bammer G, Jenkinson R, et al. Are drug detection dogs and mass-media campaigns likely to be effective policy responses to psychostimulant use and related harm? Results from an agent-based simulation model. Int J Drug Policy. 2012;23(2):148–53. doi:10.1016/j.drugpo.2011.05.018.

    Article  PubMed  Google Scholar 

  57. Marshall BD, Paczkowski MM, Seemann L, Tempalski B, Pouget ER, Galea S, et al. A complex systems approach to evaluate HIV prevention in metropolitan areas: preliminary implications for combination intervention strategies. PLoS One. 2012;7(9):e44833. doi:10.1371/journal.pone.0044833.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. El-Sayed AM, Seemann L, Scarborough P, Galea S. Are network-based interventions a useful antiobesity strategy? An application of simulation models for causal inference in epidemiology. Am J Epidemiol. 2013;178(2):287–95. doi:10.1093/aje/kws455.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Soerjomataram I, Barendregt JJ, Gartner C, Kunst A, Moller H, Avendano M. Reducing inequalities in lung cancer incidence through smoking policies. Lung Cancer. 2011;73(3):268–73. doi:10.1016/j.lungcan.2011.01.009.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by research grants from the US National Institute on Drug Abuse of the National Institute of Health (grant number T32DA031099). The sponsoring agency had no further role in the study design and analysis, the writing of the report, or the decision to submit the paper for publication.

Author information

Authors and Affiliations

  1. Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W. 168th Street, Room 1513, New York, NY, 10032-3727, USA

    David S. Fink & Katherine M. Keyes

  2. Department of Emergency Medicine, University of California, Davis, CA, USA

    Magdalena Cerdá

Authors
  1. David S. Fink
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katherine M. Keyes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Magdalena Cerdá
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David S. Fink.

Ethics declarations

Conflicts of Interest

David S. Fink, Katherine M. Keyes, and Magdalena Cerdá declare no conflict of interest.

Human and Animal Rights and Informed Consent

All studies by DS Fink involving animal and/or human subjects were performed after approval by the appropriate institutional review boards. When required, written informed consent was obtained from all participants.

Additional information

This article is part of the Topical Collection on Social Epidemiology

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fink, D.S., Keyes, K.M. & Cerdá, M. Social Determinants of Population Health: A Systems Sciences Approach. Curr Epidemiol Rep 3, 98–105 (2016). https://doi.org/10.1007/s40471-016-0066-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40471-016-0066-8

Keywords

Search

Navigation