Characteristics Associated with Poor Glycemic Control Among Adults with Self-Reported Diagnosed Diabetes — National Health and Nutrition Examination Survey, United States, 2007–2010

Mohammed K. Ali, MBChB

Kai McKeever Bullard, PhD

Giuseppina Imperatore, MD

Lawrence Barker, PhD

Edward W. Gregg, PhD

Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion

Corresponding author: Mohammed K. Ali, National Center for Chronic Disease Prevention and Health Promotion, CDC, 4770 Buford Hwy NE, MS K-10, Atlanta, GA 30341.Telephone: 770-488-4036; Fax: 770-488-1148; E-mail: ise1@cdc.gov.

Introduction

Nationally representative estimates indicate that 18.8 million adults in the United States have received a diagnosis with diabetes mellitus (1). When glycemic control is not optimized, diabetes imposes additional burdensome care requirements, health-care costs, and high risk of disabling complications, and this has been especially evident in socioeconomically disadvantaged and minority populations (2). For example, higher levels of glycated hemoglobin (A1c) have been associated with increased risk of diabetic retinopathy (3), increased risk of chronic kidney disease (4), and increased risk of cardiovascular disease (5). Reducing A1c levels through combined clinical and effective self-management has demonstrated reduced risk for microvascular complications (6,7). Although the most appropriate target A1c levels to achieve optimal health impact might vary among persons, the majority of adults with diabetes will benefit from reduction of A1c levels to ≤7%; targets for patients with a history of severe hypoglycemia, or with limited life expectancy, or with advanced complications, or with certain comorbid conditions might be higher (8). Nevertheless, an A1c level of 9% constitutes a clearly modifiable, high level of risk that few, if any, persons with diabetes should be exposed to. Accordingly, the Healthy People 2020 objectives (9) include a 10% reduction in the proportion of the diabetes population that has poor glycemic control (A1c >9%) as a target.

This report evaluates the levels of glycemic control achieved among U.S. adults with diagnosed diabetes by demographic, socioeconomic, clinical, and health-care access-related characteristics, and identifies the gaps in glycemic control nationally. These data also serve as a baseline for future evaluations of how ongoing expansions of access to health insurance will affect diabetes care and control.

Methods

To estimate the proportions and characteristics of U.S. adults aged ≥18 years with self-reported diagnosed diabetes experiencing inadequate glycemic control, CDC analyzed pooled data from the 2007–2008 and 2009–2010 cycles of the National Health and Nutrition Examination Surveys (NHANES). These serial cross-sectional surveys use stratified multistage probability cluster sampling to ensure adequate representation of the United States' noninstitutionalized civilian population. NHANES data are collected through household interviews, standardized medical examinations, and blood sample collection in mobile examination centers (10). Overall survey exam response rates were 75.4% (for 2007–2008) and 77.3% (for 2009–2010). This analysis included 1,350 nonpregnant adults aged ≥18 years with self-reported diabetes. Self-reported diagnosed diabetes was defined as a respondent's positive response to the question of whether they had ever been told by a health-care provider or other health professional that they had diabetes other than during pregnancy.

Glycated hemoglobin was measured in all NHANES participants aged ≥12 years from whole blood samples and standardized to reference methods from the Diabetes Control and Complications Trial. In all adult participants with self-reported diagnosed diabetes, the proportion with poor glycemic control (represented by most recent A1c >9.0% reflecting National Diabetes Quality Improvement Alliance indicators) (11) was estimated. Crude estimates of the proportion of adults with poor glycemic control were then calculated, stratifying by demographic (age group, sex, race/ethnicity, and marital status), socioeconomic position (e.g., age group, sex, education, and poverty-income ratio*), clinical (e.g., time since diagnosis of diabetes, and glucose-lowering medication type) and health-care access-related characteristics (e.g., health insurance status,† number of times medical care was received in the previous year,§ and usual source of medical care¶). All estimates were standardized to the age distribution of the population with diagnosed diabetes in NHANES 2009–2010. Multivariable logistic regression was conducted to compute the adjusted prevalence of poor glycemic control (Alc >9.0%) in each category, adjusting for all other exposures (e.g., age and socioeconomic position). Categorical results were deemed statistically significant using the Satterthwaite-adjusted F-test if p<0.05.

Results

During 2007–2010, an estimated 12.9% of U.S. adults with self-reported diagnosed diabetes exhibited poor glycemic control (Table).

Poor glycemic control was least common among those aged ≥65 years (6.8%) and most common among adults aged 18–39 years (24.2%). The proportion of non-Hispanic blacks (18.7%) and Hispanics (18.8%) with poor glycemic control was greater than the proportion of non-Hispanic whites with poor glycemic control (10.1%). No statistically significant or consistent patterns of association existed between education levels attained, poverty-income ratio group, or sex with poor glycemic control. However, unmarried persons (16.8%) were more likely than married persons (10.3%) to have poor glycemic control. Higher percentages of respondents using insulin therapy alone (20.8%) or combined with other oral glucose-lowering medications (22.3%) exhibited poor glycemic control compared with those reporting no medication use (5.3%) or oral medications only (10.1%). Prevalence of poor glycemic control was highest among the uninsured (28.5%) compared with non-Medicare publicly insured (13.0%), Medicare users (12.6%), and privately insured persons (7.2%). In addition, poor glycemic control was common among those without a usual source of medical care (22.4%) or among those using hospital or emergency departments for their health-care needs (22.9%) compared with 11.2%–15.2% for those accessing clinics or doctors' offices.

In a multivariable analysis controlling for all other sociodemographic, clinical, and economic covariates, adults aged ≥65 years were less likely to have poor glycemic control than young and middle-aged adults (7.3% versus 19.1% and 15.0%, respectively; p = 0.02). After controlling for all covariates, non-Hispanic blacks and Hispanics (17.6% and 16.2%, respectively versus 9.7%; p <0.01) still exhibited higher prevalence of poor glycemic control compared to non-Hispanic white persons. Marital status also was associated with poor glycemic control (married [9.6%] versus not married [16.1%]; p = 0.05). Similarly, independent of all other demographic, socioeconomic, and clinical factors considered, poor glycemic control was more prevalent among the uninsured (20.7%) compared with those on non-Medicare public insurance plans (12.4%), those on Medicare (12.4%), and those with private insurance (9.5%)(p = 0.03). In a sensitivity analysis, in which age was excluded from the multivariable model, these relationships remained significant (p<0.001). The association between usual place of care and poor glycemic control was no longer statistically significant in the multivariable model.

Discussion

Among persons with self-reported diagnosed diabetes, young (aged 18–39 years) and middle-aged adults (aged 40–64 years), non-Hispanic black or Hispanic respondents, those not married, those treated with insulin, and those lacking insurance exhibited substantially higher prevalence of poor glycemic control than their respective comparison groups. Adjusted for all other demographic and socioeconomic covariates considered, poor glycemic control remained persistently more prevalent among young and middle-aged adults, minority groups, those not married, those using insulin, and those with no health insurance coverage, compared with their respective comparison groups. These findings are encouraging because 40.5% of persons with diabetes are aged ≥65 years, and a substantial proportion of them maintain A1c levels of ≤9%. However, the data describe ongoing disparities, especially among high-risk groups that account for a large number (e.g., non-Hispanic black and Hispanic persons comprise up to 30%) of adults with diabetes in the United States.

The sub-optimal glycemic control observed among young persons might reflect less interaction with the health system stemming from the vulnerable period of age-related transition between parents' and independent insurance coverage. This finding also is consistent with 2007 employee benefit data demonstrating that approximately 23%–32% of U.S. youths and young adults were uninsured (12). The association between young adulthood and poor glycemic control was attenuated but was still significant after controlling for demographic and socioeconomic characteristics, suggesting that other barriers to achieving better glycemic control might exist. Future studies are needed to explore this association.

The findings in this report support previous studies demonstrating that social, demographic, and economic exposures are linked closely to health outcomes and might be interconnected (2,13). For example, health insurance status influences the likelihood of having a usual health-care provider. Conceivably, the attenuated relationships between regular access to a provider and glycemic control noted in this analysis might be moderated by health insurance status. Our data confirm the importance of health insurance status because a much smaller proportion of persons with any public or private insurance exhibited poor glycemic control than uninsured persons. These data also support previous findings that outcomes for persons with diabetes are similar in publicly funded and commercially managed health systems (14). Finally, although insulin use was associated with poor glycemic control, this might more accurately reflect type 1 diabetes or more advanced stage of diabetes requiring aggressive therapy, rather than a causal link with poor glycemic control (6,15).

These findings also suggest that glycemic control among persons with diagnosed diabetes has steadily improved since 1988– 2002 (16). Healthy People 2020 targets for glycemic control have already been reached for certain subgroups (e.g., whites, the elderly, and those with a high level of education). The findings of this report can be used to track and evaluate the effects of national and state health reforms. The Patient Protection and Affordable Care Act of 2010 (as amended by the Healthcare and Education Reconciliation Act of 2010 and referred to collectively as the Affordable Care Act [ACA]) (17) includes a number of provisions that directly address gaps in diabetes prevention, screening, care, and treatment. The Catalyst to Better Diabetes Care Act of 2009 (ACA §10407) directs the U.S. Department of Health and Human Services and CDC to enhance diabetes surveillance and quality standards across the country. In particular, these agencies were responsible for emphasizing reengineering of vital statistics systems, promoting more accurate classification and collection of diabetes mortality data, preparing biennial national reports that track trends in health outcomes for persons with diabetes and prediabetes that will be made publicly available and that can be used to inform policy and program development, and promoting licensing and certification for providers that care for persons with diabetes. In addition, diabetes is targeted specifically by provisions administering private health insurance wellness and prevention programs (ACA §2717), Medicaid Health Homes for enrollees with chronic conditions (ACA §2703), the Medicaid Incentives to Prevent Chronic Disease program (ACA §4108), and the Medicare Independence at Home Demonstration program (ACA §3024).

More broadly, the Affordable Care Act expands insurance coverage, consumer protections, and access to primary care. The law expands Medicaid to cover persons with incomes up to 133% of the federal poverty level. State-based insurance exchanges** will provide access to health insurance for small employers and to persons and families not eligible for Medicaid or the Children's Health Insurance Program, and federal tax credits will help those living at 100%–400% of the federal poverty level. By 2016, an estimated 95% of the U.S. population will have access to health insurance. Young adults ≥aged 26 years are now eligible to remain on their parents' insurance, and the National Center for Health Statistics reported in December 2011 that 2.5 million additional young adults had been insured. The law also provides for guaranteed issue of insurance, ending denials of coverage for preexisting conditions (diabetes is considered preexisting by certain insurers) and prohibits rescission (dropping coverage), lifetime coverage limits, and limits on emergency department use (12,17).

In the context of these reforms, the findings in this report provide a benchmark for future and more detailed national diabetes report cards that focus on persons affected by diabetes. Increasing access to care through insurance and increasing the proportion of persons with a usual care provider might lead to better diagnosis, treatment, and control of diabetes (18). In addition, future reports might consider evaluations of system- and provider-focused policies and interventions and their impact on diabetes detection and control. The only empirical data associated with a number of national large-scale population-targeted policies and interventions are related to quality improvement strategies (e.g., structured team-based care, reminders, nonphysician health workers, peer support, and provision of feedback to patients) and how this affects efficiency, self-management support, physician responsibilities, and glycemic control (19).

The findings provided in this report are subject to at least four limitations. First, the analyses are cross-sectional, which do not provide information regarding temporal or causal association. Second, detailed analyses were confined to those with diagnosed diabetes because the profile and reasons for poor glycemic control would predictably be different between the groups with diagnosed and undiagnosed disease. For groups with undiagnosed diabetes, poor glycemic control is primarily related to lack of awareness of the condition; the public health solution should focus on better detection. Including persons with undiagnosed diabetes might cause the proportion of the population with poor glycemic control to be overestimated, but to potentially have overestimates or underestimates of the associations between poor control and sociodemographic characteristics. Third, the indicator used (A1c>9.0%) might overestimate poor control in African American persons, among whom A1c might be naturally higher (20). Finally, no attempt was made to disaggregate data regarding persons with type 1 and type 2 diabetes because glucose control guidelines do not differ by type of diabetes mellitus.

Conclusion

Nationally, sociodemographic disparities in glycemic control among persons with self-reported diagnosed diabetes persist. Improvements in access to health care and benefits, quality of care delivery, and patient adherence might be achieved by more extensive translation of innovative, evidence-based system, provider, and patient-level policies and interventions. Routine surveillance also will be imperative to evaluate the intended and unintended impacts of system-level reforms on sociodemographic disparities in health utilization and diabetes control.

Further study is needed to examine the effects of increasing emphasis on evidence-based guidelines and to monitor quality indicators to determine how incentives affect motivation and accountability among health-care providers. Evaluating the implementation of health information technologies (e.g., electronic health records and computerized decision support systems that aim to motivate provider and patient adherence) will be essential in determining whether to extensively promote adoption. Finally, evaluating health system policies (e.g., assessments of the patient-centered medical home, reduction of copayments for essential medications, and other initiatives) will determine the sustainability of each initiative.

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