The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Individual and collective bodies: using measures of variance and association in contextual epidemiology
Open accessAbstract
Background: Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body’s geographical or cultural limits (eg “neighbourhood”) are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Methods: Critical essay and literature review. Results: The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Conclusions: Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.
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Cites
Neighborhood 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
Partitioning Variation in Multilevel Models
Goldstein, H., Browne, W., & Rasbash, J. (2002) · Understanding Statistics · doi:10.1207/s15328031us0104_02 · Cited by 874
A glossary for social epidemiology
Krieger, N. (2001) · Journal of Epidemiology and Community Health · doi:10.1136/jech.55.10.693 · Cited by 852
Cited by
Intermediate and advanced topics in multilevel logistic regression analysis
Austin, P. C., & Merlo, J. (2017) · Statistics in Medicine · doi:10.1002/sim.7336 · Cited by 649
Self-citationBlock, J. P., Subramanian, S. V., Christakis, N. A., & O’Malley, A. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063217 · Cited by 35
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Metadata
- Authors
- Merlo, J., Ohlsson, H., Lynch, K. F., Chaix, B., & Subramanian, S. V.
- Venue
- Journal of Epidemiology and Community Health
- Publisher
- BMJ
- Published
- 2009-08-06
- Volume
- 63
- Issue
- 12
- Pages
- 1043-1048
- ISSN
- 0141-7681 (ISSN-L)
- 0143-005X
- 1470-2738
- OpenAlex
- W2148156367
- Cited by
- 158
- References
- 3
- FWCI
- 10.57
- Type
- journal article
- Language
- en
- Open access
- green
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