The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
What's Wrong with Social Epidemiology, and How Can We Make It Better?
Open accessAbstract
It is perhaps ironic that an epidemiologist who has been working in the field of social epidemiology for over a quarter of a century, and who directs a center focused on social epidemiology, should coin a title suggesting that there is something “wrong” with social epidemiology. Perhaps it is even inopportune, as it could provide ammunition to those who believe that the practice of social epidemiology is misguided, unscientific, ideological, or too overreaching (1–3). However, this title was chosen purposely with the hope that identifying some of the critical intellectual, methodological, and empirical lacunae and challenges in social epidemiology might promote continuing development of a social epidemiology that is both scientifically enlightening and useful, productive, and contributory to the public’s health. Indeed, the hope is that the “social” in epidemiology will become so integral a part of epidemiology that the term can be dropped altogether. To assert that all epidemiology is social is not an attempt at intellectual hegemony—that the problems of disease and the distribution of disease in populations over time and space can be understood from a social perspective only or that such information is in some sense more fundamental that other types of information about disease determinants. In the same way that our understanding of the etiology of chronic and infectious diseases benefits from knowledge of the pathobiologic processes involved in such diseases, increased understanding of social factors, broadly considered, may shed light on processes every bit as integral to our understanding of the etiology of those diseases. There is no question that social epidemiology has come of age and that the term “social epidemiology” is being increasingly used to describe examination of the role of a broad array of social factors in the development and progression of many important health problems, and in the natural history of the risk factors for those diseases and conditions. While not all may agree with Geoffrey Rose’s assertion that “the primary determinants of disease are mainly economic and social, and therefore its remedies must also be economic and social” (4, p. 129), there is no question that there has been enormous growth in the study of these economic and social forces on health and disease. Figure 1, which plots growth since 1966 in use of the term “social epidemiology” in article titles, abstracts, and keywords, graphically illustrates this increased interest. Beginning in the early 1980s, growth of such publications increased rapidly, well fit by an exponential curve. In fact, this figure is likely to dramatically underrepresent the growth of social epidemiologists’ interest in the matter; a similar exponential growth pattern has been seen when studies examining socioeconomic position and health (5) and social capital and social relationships (6) were similarly totaled. Other contributions in this volume of Epidemiologic Reviews take up the wide variety of topics that social epidemiologists study. In what follows, I instead touch on a series of issues that highlight some of the critical problems with which social epidemiology must grapple. Many of the issues discussed are not restricted to social epidemiology and have their analogs in other areas of epidemiology. Thus, while the focus of this review is on social epidemiology, it would be misleading to suppose that similar criticisms do not apply to other lines of research. In addition, I want to make it clear that many of the criticisms raised apply to my own work as well as to others’. Because this is an attempt at a form of self-criticism of the field, I do not focus on as extensive citation as other reviews do. Where I do cite the work of others, it should be considered illustrative, not as singling out a particular piece of work. The lessons to be learned hopefully apply to the many. Figures 2, 3, 4, and 5 present a few of the many diagrammatic models that have been used to illustrate recent social epidemiologic approaches to understanding the social determinants of health and health disparities (e.g., Kaplan et al. (7), Marmot (8), House (9), Lynch (10)). These models have many features in common, the most prominent being an emphasis on layered, multilevel understandings; a multiplicity of pathways; and possibilities for reciprocal influences. Such models serve as important metaphors, attempting to portray the component parts of complex processes, their interrelations, and the temporal relations between components. They act as an important caution against the potentially misleading oversimplification that comes from focusing on one level of influence, often the one most proximal to the outcome, and not the flow of information and influence represented by the totality of processes and relations. Similar to a good cartoon, they remove extraneous factors and draw our attention to what is believed to be most critical. While the heuristic utility
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Social Relationships and Health
House, J. S., Landis, K. R., & Umberson, D. (1988) · Science · doi:10.1126/science.3399889 · Cited by 7,073
Unequal treatment: confronting racial and ethnic disparities in health care
(2003) · Choice Reviews Online · doi:10.5860/choice.40-5843 · Cited by 7,043
Sick individuals and sick populations
Rose, G. (2001) · International Journal of Epidemiology · doi:10.1093/ije/30.3.427 · Cited by 3,736
Causal Diagrams for Epidemiologic Research
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00008 · Cited by 3,728
Social capital, income inequality, and mortality.
Kawachi, I., Kennedy, B. P., Lochner, K., & Prothrow-Stith, D. (1997) · American Journal of Public Health · doi:10.2105/ajph.87.9.1491 · Cited by 3,212
Sick individuals and sick populations
ROSE, G. (1985) · International Journal of Epidemiology · doi:10.1093/ije/14.1.32 · Cited by 2,701
THE CONTRIBUTION OF THE SOCIAL ENVIRONMENT TO HOST RESISTANCE1
CASSEL, J. (1976) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a112281 · Cited by 1,816 · cited 1×
“In many respects, John Cassel’s ( 68 ) seminal paper, “The Contribution of the Social Environment to Host Resistance,” was a step in that direction.”
BackgroundNeighborhood of residence and incidence of coronary heart disease
Roux, A. V. D., Merkin, S. S., Arnett, D., Chambless, L., Massing, M., Nieto, F. J., Sorlie, P., Szklo, M., Tyroler, H. A., & Watson, R. L. (2001) · New England Journal of Medicine · doi:10.1056/nejm200107123450205 · Cited by 1,799
US Socioeconomic and Racial Differences in Health: Patterns and Explanations
Williams, D. R., & Collins, C. (1995) · Annual Review of Sociology · doi:10.1146/annurev.so.21.080195.002025 · Cited by 1,718
Social Integration, Social Networks, Social Support, and Health
Berkman, L. F., & Glass, T. (2000) · Social Epidemiology · doi:10.1093/oso/9780195083316.003.0007 · Cited by 1,513
Cited by
The social structural production of HIV risk among injecting drug users
Rhodes, T., Singer, M., Bourgois, P., Friedman, S. R., & Strathdee, S. A. (2005) · Social Science & Medicine · doi:10.1016/j.socscimed.2004.12.024 · Cited by 934
How race becomes biology: Embodiment of social inequality
Gravlee, C. C. (2009) · American Journal of Physical Anthropology · doi:10.1002/ajpa.20983 · Cited by 625
Epidemiology and the people's health: theory and context
(2011) · Choice Reviews Online · doi:10.5860/choice.49-0897 · Cited by 489
Riva, M., Gauvin, L., & Barnett, T. A. (2007) · Journal of Epidemiology and Community Health · doi:10.1136/jech.2006.050740 · Cited by 334
Galea, S., Hall, C., & Kaplan, G. A. (2009) · International Journal of Drug Policy · doi:10.1016/j.drugpo.2008.08.005 · Cited by 124
Self-citation
Metadata
- Authors
- Kaplan, G. A.
- Venue
- Epidemiologic Reviews
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-07-01
- Volume
- 26
- Issue
- 1
- Pages
- 124-135
- ISSN
- 0193-936X (ISSN-L)
- 1478-6729
- OpenAlex
- W2170168913
- Cited by
- 177
- References
- 14
- FWCI
- 8.58
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: What's Wrong with Social Epidemiology, and How Can We Make It Better? https://app.cochat.ai/papers/10.1093/epirev/mxh010
- The paper
- Kaplan, G. A. (2004). What's Wrong with Social Epidemiology, and How Can We Make It Better? Epidemiologic Reviews. https://doi.org/10.1093/epirev/mxh010
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.