American Journal of Epidemiology Advance Access originally published online on October 15, 2008
American Journal of Epidemiology 2008 168(10):1216; doi:10.1093/aje/kwn314
American Journal of Epidemiology © The Author 2008. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.
THE AUTHORS REPLY
Sam Harper1,
John Lynch1,
Stephen C. Meersman2,
Nancy Breen2,
William W. Davis2 and
Marsha E. Reichman2
1 Department of Epidemiology, Biostatistics, and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada H3G 1Y6
2 Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892
We are grateful to Dr. Bhopal for his letter (1) regarding our analysis of summary measures of health inequality (2), and we generally concur with the points he raises. In particular, we agree that while both absolute and relative measures of health inequality provide the most complete picture of social group differences in health, absolute measures have greater utility for understanding the population health burden of health inequalities. Bhopal's suggestion for the presentation of disease patterns (see his Table 1) is useful; however, as the number of ethnic groups increases, using many pairwise comparisons (e.g., standardized mortality ratios) becomes cumbersome, regardless of whether they are measured on the absolute scale or the relative scale. In such cases, summary measures of health inequality are likely to be more practical, especially when monitoring trends in inequality over time.
Appropriate definitions and classifications of ethnic group identity are critical for studies of health inequalities. Unfortunately, data constraints often require tradeoffs between the length of time series data and the specificity of ethnic group categorizations. Because our primary focus was to evaluate summary measures of health inequality as tools for monitoring trends over as long a time period as possible, the categories we used were aggregated to those of US federal guidelines. Hopefully this problem will be mitigated in the future as local and national data systems adapt to increasing ethnic diversity in populations. For example, starting in 2005, the US National Health Interview Survey began oversampling Asian Americans, and the California Health Interview Survey was designed to sample all of the major racial-ethnic groups as well as subgroups. With the large and growing number of racial-ethnic groups measured in US health data, summary measures of health inequality are likely to become useful tools for monitoring secular trends in health inequalities. Understanding the benefits and drawbacks of such tools remains an important challenge.
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ACKNOWLEDGMENTS
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Conflict of interest: none declared.
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References
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- Bhopal R. Re: "An overview of methods for monitoring social disparities in cancer with an example using trends in lung cancer incidence by area-socioeconomic position and race-ethnicity, 1992–2004" [letter]. Am J Epidemiol. In press.
- Harper S, Lynch J, Meersman SC, et al. An overview of methods for monitoring social disparities in cancer with an example using trends in lung cancer incidence by area-socioeconomic position and race-ethnicity, 1992–2004. Am J Epidemiol (2008) 167(8):889–899.[Abstract/Free Full Text]
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