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Advancing Measurement of Diabetes at the Population Level

  • Diabetes Epidemiology (E Selvin and K Foti, Section Editors)
  • Published:
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Abstract

Purpose

The measurement and estimation of diabetes in populations guides resource allocation, health priorities, and can influence practice and future research. To provide a critical reflection on current diabetes surveillance, we provide in-depth discussion about how upstream determinants, prevalence, incidence, and downstream impacts of diabetes are measured in the USA, and the challenges in obtaining valid, accurate, and precise estimates.

Findings

Current estimates of the burden of diabetes risk are obtained through national surveys, health systems data, registries, and administrative data. Several methodological nuances influence accurate estimates of the population-level burden of diabetes, including biases in selection and response rates, representation of population subgroups, accuracy of reporting of diabetes status, variation in biochemical testing, and definitions of diabetes used by investigators. Technological innovations and analytical approaches (e.g., data linkage to outcomes data like the National Death Index) may help address some, but not all, of these concerns, and additional methodological advances and validation are still needed.

Summary

Current surveillance efforts are imperfect, but measures consistently collected and analyzed over several decades enable useful comparisons over time. In addition, we proposed that focused subsampling, use of technology, data linkages, and innovative sensitivity analyses can substantially advance population-level estimation.

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Acknowledgements

MKA is partially supported by the Georgia Center for Diabetes Translation Research funded by the National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024).

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Authors and Affiliations

  1. Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA

    Mohammed K. Ali, Karen R. Siegel, Michael Laxy & Edward W. Gregg

  2. Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Road, Atlanta, GA, 30322, USA

    Mohammed K. Ali, Karen R. Siegel, Michael Laxy & Edward W. Gregg

  3. Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, GA, USA

    Mohammed K. Ali

  4. Helmholtz Zentrum München, Institute of Health Economics and Health Care Management, Munich, Germany

    Michael Laxy

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  1. Mohammed K. Ali
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Correspondence to Mohammed K. Ali.

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Conflict of Interest

Mohammed K. Ali, Karen R. Siegel, Michael Laxy, and Edward W. Gregg declare that they have no conflict of interest.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

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The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention.

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This article is part of the Topical Collection on Diabetes Epidemiology

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Ali, M.K., Siegel, K.R., Laxy, M. et al. Advancing Measurement of Diabetes at the Population Level. Curr Diab Rep 18, 108 (2018). https://doi.org/10.1007/s11892-018-1088-z

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