Validating the use of census data on education as a measure of socioeconomic status in an occupational cohort

Abstract

Purpose

Adjusting for smoking status or a reliable surrogate [such as socioeconomic status (SES)] is critically important in occupational epidemiology studies when any smoking-related cancer or cardiovascular disease is an outcome of interest. Sometimes, however, data on smoking patterns or individual-level smoking surrogates such as job title, education, pay scale or other measures of SES are not readily available in occupational cohorts.

Methods and materials

To obtain a surrogate measure for missing smoking or individual-level SES data, we demonstrate a method used to obtain and geocode residential address histories which were then linked to area-level SES measures from the United States Census in three test samples and then in a full cohort of workers from the Mound nuclear weapons facility in Dayton, Ohio, USA. The mean educational attainment of the Census Block Group was used to derive a categorical estimate of educational attainment which was compared to self-reported (SR) education available from Mound worker histories using Kappa statistics. Lung cancer mortality patterns between area-derived (AD) and SR education were investigated using Standardized Mortality Ratios (SMR) and Cox Proportional Hazards models with stratification or adjustment by either SR or AD education.

Results

Home address histories were obtained from linkages of individual worker data to online resources. In the test cohorts, mean educational attainment was the Census Block Group measure found to have the largest magnitude association with individual-level SES measures. Among 7251 Mound workers, 5685 (78.4%) had at least one residential address match (mean 4.9 addresses) identified. The SR and AD educational attainment measures were highly correlated (weighted Kappa coefficient 0.10, p < .0001). SMR patterns by SR and AD educational attainment were similar, with steadily decreasing mortality with increased educational attainment by either measure. Cox models for lung cancer using AD education produced similar results as those using SR education as an adjustment factor.

Conclusion

When individual-level SES indicators are not available for statistical adjustment, area-level SES measures can serve as a reliable surrogate when investigating outcomes that are affected by lifestyle factors such as smoking.

Keywords:

• Epidemiology
• database
• lung neoplasms
• modeling

Disclosure statement

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Additional information

Funding

The Million Person Study of Low-Dose Health effects is supported in part by a grant from the U.S. Nuclear Regulatory Commission [NRC-HQ‐60‐14‐G‐0011], grants from the Centers for Disease Control and Prevention [5UE1EH000989, 5NUE1EH001315], grants from the National Aeronautics and Space Administration [NNX15AU88G, 80NSSC17M0016], and grants from the U.S. Department of Energy [Grant No. DE-SC0008944] awarded to the National Council on Radiation Protection and Measurements, which included interagency support from the U.S. Nuclear Regulatory Commission, the U.S. Environmental Protection Agency, and the National Aeronautics and Space Administration; and more recent Grants No. DE-AU0000042 and DE-AU0000046. Contract support was received from the Naval Sea Systems Command [N00024-17-C-4322]. Further, contract support was received by Oak Ridge National Laboratory from the Office of Radiation and Indoor Air, U.S. Environmental Protection Agency, under Interagency Agreement DOE No. 1824 S581‐A1, under contract No. DE-AC05‐00OR22725 with UT-Battelle; and contract support was received by Oak Ridge Associated Universities from the U.S. Department of Energy under contract No. DE-SC0014664.

Notes on contributors

Sarah S. Cohen

Sarah S. Cohen is a Principal Epidemiologist at EpidStat Institute where she directs observational research studies in the areas of pharmacoepidemiology, nutritional epidemiology, and occupational epidemiology as well as leads large data management projects and statistical analyses. She is also an Adjunct Assistant Research Professor of Medicine in the Department of Medicine at Vanderbilt University School of Medicine. She has been a collaborator on the Million Person Study of Low-Dose Health Effects for nearly twenty years, providing analytic support as well as co-authoring numerous publications.

Michael T. Mumma

Michael T. Mumma is the Director of Information Technology at the International Epidemiology Institute and the International Epidemiology Field Station for Vanderbilt University Medical Center. He has over 20 years of experience in data analysis and conducting epidemiologic investigations.

Elizabeth D. Ellis

Elizabeth (Betsy) D. Ellis is a Group Leader in the Health, Energy and the Environment Program at Oak Ridge Associated Universities. She has over 35 year of experience leading occupational epidemiology studies of workers in the nuclear and chemical industries. She serves on an International Commission on Radiological Protection Task Group concerned with the health effects of internal alpha emitters. A major project is contributing to the Million Person Study of Low Dose Health Effects. She is also active in human subject protection in research.

John D. Boice

John D. Boice Jr. is President of the National Council on Radiation Protection and Measurements and Professor of Medicine at Vanderbilt University. He is an international authority on radiation effects and served on the Main Commission of the International Commission on Radiological Protection and on the United Nations Scientific Committee on the Effects of Atomic Radiation. He directs the Million Person Study of Low-Dose Health Effects.