Session

Session Description and Learning Objectives

Lecturers

#1

Tue

Jan 4

Introduction and Overview

1.       Appreciate the role that the social determinants of health (SDH) play in health at an individual and community level

2.       Become familiar with the major concepts in SDH research

3.       Develop an appreciation for the unique research methods necessary to study of SDH

4.       Course logistics

Required Readings: None

Shirley A. A. Beresford, PhD & Nicholas L. Smith, PhD

#2

Thu

Jan 6

Causality and Conceptual Models

1.       Describe the basic principles underlying the dominant theories of causality

2.       Apply these principles to SDH research

3.       Distinguish between causal and conceptual models in SDH research

4.       Identify the components of a conceptual model, the corresponding unit of analysis, and the interconnecting pathways

Required Readings: Greenland S, Brumback B. An overview of relations among causal modelling methods. Int J Epidemiol 2002;31:1030-7.

Kaufman JS, Kaufman S, Poole C. Causal inference from randomized trials in social epidemiology. Soc Sci Med 2003;57:2397-409.

Kreiger N. Epidemiology and the web of causation: has anyone seen the spider? Soc Sci Med 1994;39:887-903.

Marmot M. “Multilevel approaches to understanding social determinants.” In Berkman LF, Kawachi I: Social Epidemiology. New York: Oxford University Press, 2000 (pp. 349-67).

Additional Readings: Holland PW. Statistics and Causal Inference. J Am Stat Assoc 1989;81:945-960.

Robins JM. Data, design, and background knowledge in etiologic inference. Epidemiology 2001;12:313-20.

Rothman KJ. Causal Inference. Chestnut Hill, MA : Epidemiology Resources, 1988

NLS

#3

Tue

Jan 11

Major Conceptual Models in SDH Research

1.       Become familiar with the major conceptual models that are currently researched

Required Readings:  

Reiche EM, Nunes SO, Morimoto HK. Stress, depression, the immune system, and cancer. Lancet Oncol. 2004 Oct;5(10):617-25.

Galobardes B, Lynch JW, Davey Smith G. Childhood socioeconomic circumstances and cause-specific mortality in adulthood: systematic review and interpretation. Epidemiol Rev. 2004;26:7-21.

Subramanian SV, Kawachi I. Income inequality and health: what have we learned so far? Epidemiol Rev. 2004;26:78-91.

Szreter S, Woolcock M. Health by association? Social capital, social theory, and the political economy of public health. Int J Epidemiol. 2004 Aug;33(4):650-67.

► Proposal title and specific aims due at the start of class

Ann E. Kurth, CNM, PhD & NLS

#4

Thu

Jan 13

Journal Article Critique #1: Conceptual Models

Steptoe A, Kunz-Ebrecht S, Owen N, Feldman PJ, Rumley A, Lowe GD, Marmot M. Influence of socioeconomic status and job control on plasma fibrinogen responses to acute mental stress. Psychosom Med. 2003 Jan-Feb;65(1):137-44.

Gold R, Kennedy B, Connell F, Kawachi I. Teen births, income inequality, and social capital: developing an understanding of the causal pathway. Health Place. 2002 Jun;8(2):77-83.

SAAB & NLS

#5

Tue

Jan 18

Data Sources

1.       Identify existing data sources available for SDH research

2.       Identify the structure of the data in existing data sets and be able to distinguish between group-level variables that represent contextual factors and those that indirectly estimate individual-level data

3.       Understand limitations and advantages to using multiple data sources to create analytic data sets

Required Readings: Mackenbach JP, Bos V, Anderson O, Cardano M, Costa G, Harding S, Reid A, Hemstrom O, Valkonen T, Kunst AE. Widening socioeconomic inequalities in mortality in six Western European countries. Int J Epidemiol 2003; 32: 830-839.

Additional Readings: Hetzel AM.  “History and Organization of Vital Statistics System.”  National Center for Health Statistics. 1997. pp. 27- 42 & pp. 58-62.

Krieger N. Overcoming the absence of socioeconomic data in medical records: validation and application of census-based methodologies. Am J Public Health 1992;82:703-10.

SAAB

#6

Thu

Jan 20

Selecting a Study Design (part 1)

1.       Identify the primary and unique study designs new to SHD research (unit of analysis; experimental vs. quasi experimental vs. observational; cross-sectional versus prospective/retrospective; ecologic designs)

2.       Be able to chose the best study design to fit the conceptual model or model component to be tested

3.       Be able to chose the best study design to fit the data available for research

4.       Understand the role of randomized studies in SDH research

5.       Become familiar with network modeling designs to capture contextual effects

Required Readings: Campbell DT, Stanley JC. Experimental and Quasi-Experimental Designs for Research. Chicago: R. McNally, 1966 (pp. 34-46).

Diez-Roux AV. Bringing context back into epidemiology: variables and fallacies in multilevel analysis. Am J Public Health. 1998;88:216-22.

Koepsell TD. "Epidemiologic issues in the design of community intervention trials." Chapter 6 in: Brownson RC, Petitti DB. Applied Epidemiology: Theory to Practice. New York: Oxford University Press, 1998 (pp. 177-211).

Kuh D, Ben-Shlomo Y, Lynch J, Hallqvist J, Power C. Life course epidemiology.  J Epidemiol Community Health 2003;57:778-83.

Additional Readings: Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int J Epidemiol 2003;31:285-93.

“Evaluating the Effects of Policies on Health.” In Koepsell TD, Weiss NS. Epidemiologic Methods: Studying the Occurrence of Illness. Oxford; New York: Oxford University Press, 2003.

► Proposal conceptual model due at the start of class

NLS

#7

Tue

Jan 25

Selecting a Study Design (part 2)

Required Readings: See session #6

Thomas D. Koepsell, MD, MPH & NLS

#8

Thu

Jan 27

Measurement Issues

1.       Understand the advantages and limitations of individual and group measures in SDH research

2.       Understand how measures are selected to represent concepts

3.       Become familiar with index measures of exposures and outcomes and how these measures can be constructed and validated

4.       Combining data from various sources

Required Readings: Saunders RP, Pate RR, Felton G, Dowd M, Weinrich MC, Ward DS, Parsons MA, Baranowski T.  Development of questionnaires to measure psychosocial children’s physical activity. Prev Med 1997; 26: 241-247.

Raudenbush SW. “The quantitative assessment of neighborhood social environments.” In Kawachi I and Berkman LF. Neighborhoods and Health. New York, Oxford University Press. 2003. Pp 112-131.

Lynch J, Kaplan G. “Socioeconomic position.” In Berkman LF and Kawachi I. Social Epidemiology. New York, Oxford University Press 2000. pp 13- 35.

Diez Roux AV. The study of group-level factors in epidemiology: rethinking variables, study designs, and analytical approaches. Epidemiol Rev. 2004;26:104-11.

Additional Readings: Gordon D. “Area-based deprivation measures – a U.K. Perspective.” In Kawachi I and Berkman LF. Neighborhoods and Health. New York, Oxford University Press. 2003. Pp 179-207

Mathers CD, Murray CJL, Ezzati M, Gakidou E, Salomon JA, Stein C. Population health metrics: crucial inputs to the development of evidence for health policy. Population Health Metrics 2003; 1:6     http://www/pophealthmetrics/content/1/1/6

Armstrong BK. White E, Saracci R. Principles of exposure measurement in epidemiology. New York, Oxford University Press. 1992; chapter 1: pp1-21.

Krieger N. Comparing individual-based and household-based measures of social class to assess class inequalities in women’s health: methodological study of 684 US women. J Epidemiol Community Health 1999;53:612-23.

SAAB

#9

Tue

Feb 1

Journal Article Critique #2: Study Design and Measurements

Costello EJ, Compton SN, Keeler G, Angold A. Relationships between poverty and psychopathology: a natural experiment. JAMA. 2003;290:2023-9.

Galea S, Ahern J, Vlahov D, Coffin PO, Fuller C, Leon AC, Tardiff K. Income distribution and risk of fatal drug overdose in New York City neighborhoods. Drug Alcohol Depend. 2003;70(2):139-48.

Phillips DP, Liu GC, Kwok K, Jarvinen JR, Zhang W, Abramson IS. The Hound of the Baskervilles effect: natural experiment on the influence of psychological stress on timing of death. BMJ. 2001;323(7327):1443-6.

NLS & SAAB

#10

Thu

Feb 3

Analytic Issues (part 1): Ecologic Data

1.       General issues of ecologic data analyses

2.       Understanding limitations of interpretation when analyzing potentially confounded data

3.       Describe the benefits and drawbacks of using within population sampling to estimate confounding effects of the larger group

Required Readings: D.A. Freedman. “Ecological inference and the ecological fallacy.” International Encyclopedia for the Social and Behavioral Sciences. Elsevier (2001) vol. 6 pp. 4027–30. N. J. Smelser and Paul B. Baltes, eds.

Morgenstern, H. (1998). Ecologic Studies. In Rothman, K.J. and Greenland, S. (Eds.), Modern Epidemiology, Second Edition, pp. 459-480. Lipincott-Raven.

Additional Readings: Greenland, S. (1992). Divergent biases in ecologic and individual-level studies, Stats Med, 11, 1209-23.

Jon Wakefield, PhD & SAAB

#11

Tue

Feb 8

Analytic Issues  (part 2): Ecologic Data Review and Multi-level Data

1.       Review of ecologic data analyses (30 minutes) and provide homework

2.       Introduction to analytic issues of multi-level research

Required Readings: Blakely TA, Woodward AJ.  Ecological effects in multi-level studies.  Journal of Epidemiology and Community Health 2000,54:367-374.

Duncan C, Jones K, Moon G.  Context, composition and heterogeneity: Using multilevel models in health research.  Soc Sci Med 1998, 46:97-117.  (especially pages 97-105; 112-114)

Diez-Roux AV.  A glossary for multilevel analysis.  Journal of Epidemiology and Community Health 2002, 56: 588-594.

Diez-Roux AV.  Multilevel analysis in public health research.  Annual Review of Public Health 2000, 21:171-92.

► Proposal sections A, B, C (optional) and D1-D4 due at the start of class

NLS & SAAB

#12

Thu

Feb 10

Analytic Issues  (part 3): Confounding and Effect Modification with Multi-level Data

1.          General issues of confounding in multi-level research studies

2.          General issues of effect modification in multi-level research studies

Required Readings: See session #11.

► Homework assignment #1 due at the beginning of class

Lianne Sheppard, PhD & SAAB

#13

Tue

Feb 15

Analytic Issues  (part 4): Analyzing Multi-level Data

1.       Understand basic approaches to analyzing multi-level data using hierarchical models

2.       Become familiar with other analytic methods to address multi-level data

Required Readings: See session #12.

Xiao-hua Andrew Zhou, PhD & NLS

#14

Thu

Feb 17

Analytic Issues  (part 5): Multi-level Data Review and Structural Equation Models

1.       Review of multi-level data analysis (30 minutes) and provide homework

2.       General issues of structural equation modeling

Required Readings: Pearl J. Causality: Models, Reasoning, and Inference. “Causality and Structural Models in Social Science and Economics” (Chapter 5), Cambridge: Cambridge University Press, 2000, pp 133-171.

Ken Rice, PhD & NLS

#15

Tue

Feb 22

Journal Article Critique #3: Multi-level Research Studies

Merlo J, Ostergren PO, Hagberg O, Lindstrom M, Lindgren A, Melander A, Rastam L, Berglund G. Diastolic blood pressure and area of residence: multilevel versus ecological analysis of social inequity. J Epidemiol Community Health. 2001;55:791-8.

► Homework assignment #2 due at the beginning of class

NLS & SAAB

#16

Thu

Feb 24

Analytic Issues  (part 6): Longitudinal Data

1.       Understand the general issues of longitudinal data analysis using follow-up data from long-standing cohorts

2.       Identify threats to validity when using longitudinal data

3.       Identify analytic techniques to evaluate robustness of findings

Required Readings:

TBA

Brian G. Leroux, PhD & SAAB

#17

Tue

Mar 1

Analytic Issues  (part 7): Longitudinal Data Review and Survey Data Analysis Modeling

1.         Review of longitudinal data analysis (30 minutes) and provide homework

2.         Understand the special qualities of survey data

3.         Using national survey data to standardize populations

Required Readings: Bierman, AS, Bubolz TA. “Secondary Analysis of Large Survey Databases” in Max, MB, Lynn, J, eds Symptom Research: Methods and Opportunities http://symptomresearch.nih.gov/chapter_20/  (not on e-reserve)

Brogan, DJ. Pitfalls of Using Standard Statistical Software Packages for Sample Survey Data, Encylopedia of Biostatistics. Reprinted at http://www.fas.harvard.edu/~stats/survey-soft/donna_brogan.html (on e-reserve)

Hendricx, J.  The Impact of Weights on Standard Errors. http://www.asc.org.uk/Events/Apr02/Full/Hendrickx.doc (on e-reserve)

Additional Readings: Also look at the NCHS and ICPSR websites

http://www.cdc.gov/nchs 

Thomas Lumley, PhD & NLS

#18

Thu

Mar 3

Journal Article Critique #4: Longitudinal

TBD

► Homework assignment #3 due at the beginning of class

NLS & SAAB

#19

Tue

Mar 8

Interpretation of Research Findings

1.       Interpreting the conceptual model in light of the research findings

2.       Translation of research findings into improved health

3.       Role of epidemiologists and health services researchers in SDH research

Required Readings: Mackenbach JP, Bakker MJ; European Network on Interventions and Policies to Reduce Inequalities in Health.  Tackling socioeconomic inequalities in health: analysis of European experiences. Lancet. 2003;362:1409-14.

Kindig D, Day P, Fox DM, Gibson M, Knickman J, Lomas J, Stoddart G. What new knowledge would help policymakers better balance investments for optimal health outcomes? Health Serv Res. 2003;38:1923-37.

Susser M. Should the epidemiologist be a social scientist or a molecular biologist? Int J Epidemiol. 1999;28:S1019-22.

SAAB & NLS

#20

Thu

Mar 10

Journal Article Critique #5: General Overview

Kramer MS, Goulet L, Lydon J, Seguin L, McNamara H, Dassa C, Platt RW, Chen MF, Gauthier H, Genest J, Kahn S, Libman M, Rozen R, Masse A, Miner L, Asselin G, Benjamin A, Klein J, Koren G. Socio-economic disparities in preterm birth: causal pathways and mechanisms. Paediatr Perinat Epidemiol. 2001;15:104-23.

Hillemeier MM, Lynch J, Harper S, Raghunathan T, Kaplan GA. Relative or absolute standards for child poverty: a state-level analysis of infant and child mortality. Am J Public Health. 2003;93:652-7.

Coulton CJ, Korbin JE, Su M. Neighborhoods and child maltreatment: a multi-level study. Child Abuse Negl. 1999;23:1019-40.

SAAB & NLS

Final

Tue

Mar 15

► Full proposal due at 9:00 am.