Skip Navigation Links
Centers for Disease Control and Prevention
 CDC Home Search Health Topics A-Z

Preventing Chronic Disease: Public Health Research, Practice and Policy

View Current Issue
Issue Archive
Archivo de números en español








Emerging Infectious Diseases Journal
MMWR


 Home 

Volume 1: No. 2, April 2004

COMMENTARY
State-based Diabetes Surveillance Among Minority Populations


TABLE OF CONTENTS


Print this article Print this article
E-mail this article E-mail this article:



Send feedback to editors Send feedback to editors
Download this article as a PDF Download this article as a PDF (132K)

You will need Adobe Acrobat Reader to view PDF files.


Navigate This Article
Author Information
References


Jay Desai, MPH

Suggested citation for this article: Desai J. State-based diabetes surveillance among minority populations. Prev Chronic Dis [serial online] 2004 Apr [date cited]. Available from: URL: http://www.cdc.gov/pcd/issues/2004/
apr/03_0030.htm
.

The elimination of health disparities in the United States is a national priority and overriding goal for Healthy People 2010 (HP 2010). Surveillance of health indicators among minority populations is essential to eliminating disparities. Surveillance is critical for program planning, policy making, evaluating population-based strategies, and tracking progress toward national and state objectives.

The U.S. public health field has made steady progress in diabetes surveillance over the past decade, but there is much room for improvement (1). In this issue, Burrows et al report the findings and recommendations of an expert panel on the feasibility of using current surveys for diabetes surveillance among minority populations (2). The expert panel, convened by the Division of Diabetes Translation at the Centers for Disease Control and Prevention, found existing surveys insufficient for diabetes survey surveillance among minority populations, and, given the realities of finite resources, the panel recommended modifying and expanding existing survey systems to improve this capacity.

Many initiatives to eliminate racial and ethnic disparities are underway at the state and local levels; therefore, surveillance systems are needed at these levels. In an analysis of the capacity of states to measure HP 2010 objectives, Land found that only 56% of the objectives could be measured at the state level and 33% at the county level (3). At the state level, diabetes fared better than most other focus areas (e.g., heart disease, cancer, environmental health, immunization and infectious disease, maternal and child health) because 12 of the 14 objectives could be measured. However, if we extend this analysis to race and ethnicity objectives, only 3 diabetes mortality indicators are measurable. These HP 2010 measurable objectives are the framework for setting the U.S. health agenda and for guiding state and local health activities. Yet they cannot be used among minority populations at the state and local levels because they are not currently measurable.

The Behavioral Risk Factor Surveillance System (BRFSS) is a cornerstone of diabetes surveillance at the state level. It is used for tracking the prevalence of diabetes, risk factors for diabetes and its complications (e.g., physical inactivity, obesity), and preventive care practices among people with diabetes (e.g., adult vaccination, eye exams). Of the surveys listed by Burrows et al, the BRFSS is the only one conducted among all 50 states in a systematic, ongoing way. Unfortunately, the BRFSS remains inadequate for diabetes surveillance among minority populations. In 2000, the median state BRFSS sample size for all persons diagnosed with diabetes was 211. Thus, few states had sufficient respondents with diabetes to estimate risk factors and preventive care practices among minority populations with diabetes.

Another issue for states is the ability to establish long-term resources to conduct and maintain health surveillance among minority populations. For example, in 2001, the Minnesota Department of Health (MDH) began a multimillion-dollar initiative to eliminate health disparities: diabetes was one of 8 health priority areas. Part of the statute establishing the initiative specifies that "[t]he commissioner [of health] shall enhance current data tools to ensure a statewide assessment of risk behaviors associated with the eight health disparity priority areas. The statewide assessment must be used to establish a baseline to measure the effect of activities funded." This is an important statement because it recognizes the need to improve statewide surveillance among minority populations. But, despite the statutory requirement to improve surveillance, the legislature mandated that all funds be distributed in grants to communities and to the MDH for oversight and programmatic support. No funds were made available for statewide improvement in surveillance systems among minority populations.

Emerging minority populations within states, such as the Somali and the Hmong in Minnesota, pose additional diabetes surveillance challenges. Health surveillance data on these populations are almost nonexistent. Furthermore, new methods designed to overcome language and cultural barriers may be required for identifying and tracking diabetes indicators among these populations; traditional methods such as telephone surveys may not be feasible.

In Minnesota, one approach used to identify appropriate health indicators for surveillance is participatory research partnerships (PRPs). This approach involves partnerships among African American, African immigrant, American Indian, Hispanic, and Asian immigrant communities to understand health concepts and other cultural issues and to determine appropriate health indicators. The challenge of systematically and regularly monitoring these health indicators remains.

At the state and local levels, expanding the BRFSS or developing new surveys for diabetes surveillance among minority communities will be costly. To expand diabetes surveillance, states must look to alternatives such as health care administrative data (e.g., hospital discharge, Medicare, Medicaid, managed care). Even though such data only pertain to people under medical care, analyzing data already being collected may be the most efficient way of expanding diabetes surveillance among minority populations.

Unfortunately, many hospitals and most managed care organizations do not systematically collect or report race and ethnicity information. The Institute of Medicine, in a report on disparities in health care, has recommended that race and ethnicity, education level, and primary language data all be collected and reported in a standardized way and included in hospital and managed care performance measurement (4). A pilot project among 8 managed care organizations (MCOs) has begun exploring methods for assessing racial and ethnic disparities within their populations. Bierman et al have outlined the importance of using race and ethnicity data by MCOs as well as highlighted potential barriers to collecting racial and ethnic data — barriers such as perceived legal, business, and confidentiality concerns (5,6).

In Minnesota, statutory language was developed to require insurers to provide claims data — and eventually race and ethnicity data — to the MDH for the purpose of public health research and surveillance. Public concerns about data confidentiality curtailed this initiative, even though sophisticated methods for ensuring confidentiality were in place. The MDH continues to garner support from health care providers, MCOs, and other stakeholders and to articulate the purpose, need, and confidentiality safeguards for a statewide medical claims database. Such large-scale efforts, either voluntary or statutory, are underway in many states and can considerably enhance state and local diabetes surveillance among minority populations.

Current state diabetes surveillance systems among minority populations must be improved if we are to make progress toward eliminating racial and ethnic disparities or to know if we are even making progress. Expanding current surveillance surveys, although less expensive than starting new surveys, will require substantial financial resources and long-term commitment. For some populations (recent immigrants, for example) new surveillance methods may be required. The use of alternative surveillance data sources, such as health care administrative data, will have financial ramifications and raise confidentiality concerns. Ultimately, a concerted and committed effort by public health and health care organizations to begin systematically collecting and reporting data on race and ethnicity is needed and will benefit all.

Acknowledgments

I would like to thank David Stroud for his insights and comments in developing this article.

Author Information

Corresponding author: Jay Desai, Minnesota Diabetes Program, Minnesota Department of Health, PO Box 64882, Saint Paul, MN 55101. Telephone: 651-281-9844. E-mail: jay.desai@health.state.mn.us.

Back to top

References

  1. Desai J, Geiss L, Mukhtar Q, Harwell T, Benjamin S, Bell R, et al. Public health surveillance of diabetes in the United States. J Public Health Manag Prac 2003 Nov;Suppl:S44-51.
  2. Burrows NR, Lojo J, Engelgau MM, Geiss LS. Using survey data for diabetes surveillance among minority populations: a report of the Centers for Disease Control and Prevention's expert panel meeting. Prev Chronic Dis [serial online] 2004 Apr. Available from: URL: http://www.cdc.gov/pcd/issues/2004/apr/03_0018.htm.
  3. Land G. Measuring 2010 national objectives and leading indicators at the state and local level. J Public Health Manag Prac 2002;8 (4):9-13.
  4. Smedley BD, Stith AY, Nelson AR, editors. Unequal treatment: confronting racial and ethnic disparities in healthcare. Washington (DC): National Academies Press; 2003. 764 p.
  5. Nerenz DR, Bonham VL, Green-Weir R, Joseph C, Gunter M. Eliminating racial/ethnic disparities in health care: can health plans generate reports? Health Aff 2002 May-Jun;21 (3):259-63.
  6. Bierman AS, Lurie N, Collins KS, Eisenberg JM. Addressing racial and ethnic barriers to effective health care: the need for better data. Health Aff 2002 May-Jun;21 (3):91-102.

Back to top

 



 



The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors’ affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.


 Home 

Privacy Policy | Accessibility

CDC Home | Search | Health Topics A-Z

This page last reviewed March 22, 2013
Centers for Disease Control and Prevention
National Center for Chronic Disease Prevention and Health Promotion
 HHS logoUnited States Department of
Health and Human Services