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Original Contribution |

Association of Health Literacy With Diabetes Outcomes FREE

Dean Schillinger, MD; Kevin Grumbach, MD; John Piette, PhD; Frances Wang, MS; Dennis Osmond, PhD; Carolyn Daher, MPH; Jorge Palacios, MA; Gabriela Diaz Sullivan, MD; Andrew B. Bindman, MD
[+] Author Affiliations

Author Affiliations: University of California, San Francisco, Primary Care Research Center, San Francisco General Hospital (Drs Schillinger, Osmond, Sullivan, and Bindman, Mss Wang and Daher, and Mr Palacios); University of California, San Francisco, Department of Family and Community Medicine (Dr Grumbach); and Center for Practice Management and Outcomes Research, VA Ann Arbor Health Care System, and the University of Michigan School of Medicine, Ann Arbor (Dr Piette). Ms Daher is now with the Johns Hopkins School of Public Health, Baltimore, Md.


JAMA. 2002;288(4):475-482. doi:10.1001/jama.288.4.475.
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Context Health literacy is a measure of patients' ability to read, comprehend, and act on medical instructions. Poor health literacy is common among racial and ethnic minorities, elderly persons, and patients with chronic conditions, particularly in public-sector settings. Little is known about the extent to which health literacy affects clinical health outcomes.

Objectives To examine the association between health literacy and diabetes outcomes among patients with type 2 diabetes.

Design, Setting, and Participants Cross-sectional observational study of 408 English- and Spanish-speaking patients who were older than 30 years and had type 2 diabetes identified from the clinical database of 2 primary care clinics of a university-affiliated public hospital in San Francisco, Calif. Participants were enrolled and completed questionnaires between June and December 2000. We assessed patients' health literacy by using the short-form Test of Functional Health Literacy in Adults (s-TOFHLA) in English or Spanish.

Main Outcome Measures Most recent hemoglobin A1c (HbA1c) level. Patients were classified as having tight glycemic control if their HbA1c was in the lowest quartile and poor control if it was in the highest quartile. We also measured the presence of self-reported diabetes complications.

Results After adjusting for patients' sociodemographic characteristics, depressive symptoms, social support, treatment regimen, and years with diabetes, for each 1-point decrement in s-TOFHLA score, the HbA1c value increased by 0.02 (P = .02). Patients with inadequate health literacy were less likely than patients with adequate health literacy to achieve tight glycemic control (HbA1c ≤7.2%; adjusted odds ratio [OR], 0.57; 95% confidence interval [CI], 0.32-1.00; P = .05) and were more likely to have poor glycemic control (HbA1c ≥9.5%; adjusted OR, 2.03; 95% CI, 1.11-3.73; P = .02) and to report having retinopathy (adjusted OR, 2.33; 95% CI, 1.19-4.57; P = .01).

Conclusions Among primary care patients with type 2 diabetes, inadequate health literacy is independently associated with worse glycemic control and higher rates of retinopathy. Inadequate health literacy may contribute to the disproportionate burden of diabetes-related problems among disadvantaged populations. Efforts should focus on developing and evaluating interventions to improve diabetes outcomes among patients with inadequate health literacy.

Figures in this Article

Health literacy is a constellation of skills, including the ability to perform basic reading and numerical tasks required to function in the health care environment.1 Patients with poor health literacy levels have difficulties that range from reading labels on a pill bottle and interpreting blood sugar values or dosing schedules to comprehending appointment slips, educational brochures, or informed-consent documents. Patients with poor health literacy not only have limitations in reading but also may have difficulties processing oral communication and conceptualizing risk.2,3 In the context of a health care system in which scientific advances and market forces place greater technical and self-management demands on patients, poor health literacy may be a particularly important barrier to chronic-disease care.

Poor health literacy is more common among patients who have low educational attainment and among immigrants, older patients, and racial and ethnic minorities.1 Research has shown that poor health literacy is most prevalent in public hospitals but is also common among the elderly in private-sector settings. A recent study of Medicare managed care enrollees demonstrated that more than one third had poor health literacy.4 Poor health literacy is common among patients with chronic medical conditions, such as type 2 diabetes, asthma, AIDS (acquired immunodeficiency syndrome), and hypertension.59

A growing body of research demonstrates that poor health literacy is independently associated with poor self-rated health10 and higher use of services.11,12 A study among patients with hypertension and diabetes demonstrated a nonstatistically significant relationship between inadequate health literacy and poor blood pressure and glycemic control, although the study was not powered to detect a difference.8 Although it is unclear to what extent health literacy is merely associated with or causally related to outcomes, there are reasons to believe that poor health literacy may directly contribute to poor outcomes. Patients with poor health literacy have greater difficulties naming their medications and describing their indications,13 more frequently hold health beliefs that interfere with adherence,7 and are more likely to have poor understanding of their condition and its management.5,8,9

Because relatively little is known regarding the impact of poor health literacy on clinical outcomes, we investigated the association between health literacy and diabetes outcomes among patients cared for in the clinics of a public hospital. We selected type 2 diabetes because it is one of the most common diseases in the United States, affecting more than 16 million people and 18% of all people 65 years of age and older.14 Despite high rates of health care access and use for most patients with type 2 diabetes, outcomes are frequently unsatisfactory for reasons that are often unclear.15 Isolating the independent contribution of health literacy toward diabetes outcomes may have important clinical implications for the care of individual patients. Since type 2 diabetes disproportionately affects ethnic minorities and those of lower socioeconomic status,16 understanding the association between health literacy and diabetes outcomes may have strategic implications for the reduction of racial, ethnic, and socioeconomic disparities in diabetes care called for in Healthy People 2010.17

Setting and Study Participants

The study took place in 2 primary care clinics (a family practice and a general internal medicine clinic) at San Francisco General Hospital, the public hospital of the city and county of San Francisco. Patients in these clinics receive care from University of California, San Francisco, attending faculty and residents. Primary care physicians treat more than 90% of type 2 diabetes patients at San Francisco General Hospital; the remainder receive services exclusively from specialists or from the emergency department sporadically. The primary care clinics have diabetes educators who attempt to consult with every patient for individual sessions. During the study, there was no disease-management system in place.

Potential subjects were identified by querying the hospital system's computerized clinical and administrative database, an enterprise data warehouse. The San Francisco General Hospital database captures laboratory, radiology, billing and use, and demographic information for all patients who used the public health care system of the city and county of San Francisco within 3 years before the start of the study. Patients were eligible if, according to the database, they were older than 30 years, were registered as speaking English or Spanish, and had type 2 diabetes, controlled or uncontrolled, with or without complications (all International Classification of Diseases, Ninth Revision [ICD-9] codes of 250._0 or 250._2). Participants had to have had a database-recorded visit with a primary care physician in 1 of the clinics in the prior 12 months and at least 1 additional visit to the same physician within the prior 6 months. We excluded patients with any documented billing diagnosis of end-stage renal disease, psychotic disorder, dementia, or blindness (conditions that may interfere with accurate health literacy measurement).18

To ensure that our database-generated list of patients accurately reflected eligibility criteria, we also provided primary care physicians (n = 89) with a list of eligible patients generated from the database and asked them to indicate additional patients meeting criteria for exclusion.

Between June and December 2000, bilingual research assistants attempted to enroll all eligible patients who attended a clinic appointment. Patients who stated that they were fluent in English or Spanish were asked to participate in a study of patient-physician communication and diabetes care and were offered $5.00 for their participation. Written consent, oral consent, or both were obtained from patients before enrollment. To facilitate comprehension of the study and consent process, the consent form was written at a fifth-grade level; in addition, research assistants read an abbreviated version to all patients.

Patients who agreed to participate first had their visual acuity tested with a pocket vision screener (Rosenbaum, Granham-Field Surgical Co Inc, New York, NY); patients with corrected vision of 20/50 or worse were excluded. Patients were then administered an abbreviated version of the short-form Test of Functional Health Literacy in Adults (s-TOFHLA, 14-point font),19 a reliable and validated instrument used to assess a patient's health literacy level.18 Research assistants also orally administered a questionnaire regarding demographic information (race/ethnicity, income, and education), health-related habits (current alcohol, tobacco, and illicit drug use), social support, depressive symptoms, current diabetes treatment (use of diet, oral hypoglycemic agents, and insulin), receipt of diabetes education, length of time with diagnosed diabetes, and the presence of diabetes complications. The protocol was approved by the Human Subjects Committee of the University of California, San Francisco.

Measures

To measure health literacy, we used the abbreviated form of the s-TOFHLA, Spanish or English version.19 The abbreviated s-TOFHLA is a 36-item timed reading comprehension test that uses the modified Cloze procedure20; every fifth to seventh word in a passage is omitted, and 4 multiple-choice options are provided. The abbreviated s-TOFHLA contains 2 health care passages, the first selected from instructions for preparation for an upper gastrointestinal tract radiograph series (Gunning-Fog Index readability grade 4.321) and the second from the patient's "Rights and Responsibilities" section of a Medicaid application (Gunning-Fog Index readability grade 10.4). The abbreviated s-TOFHLA is scored on a scale of 0 to 36. Using established convention, we categorized patients as having inadequate health literacy if the s-TOFHLA score was 0 to 16, marginal health literacy if it was 17 to 22, and adequate health literacy if it was 23 to 36. Patients with inadequate health literacy often misread simple materials, such as prescription bottles, appointment slips, or nutrition labels; patients with marginal health literacy frequently have trouble with more complex materials, such as an educational brochure or informed-consent document.22

Because social support and depression may affect patients' glycemic control,23 we assessed both domains in the patient interview. We measured diabetes-related social support by using 8 questions adapted from the Diabetes Care Profile24 social-support scale that asks patients to rate the extent to which family or friends support their diabetes self-care. We measured depressive symptoms by using the Center for Epidemiologic Studies Depression Scale-10,25 a 10-item questionnaire that has been used extensively in type 2 diabetes research23 and asks patients how frequently they have had symptoms of depression in the prior month. We measured diabetes-related conditions by asking patients whether they had ever been told by a physician that they had a condition considered to be a complication of diabetes, including retinopathy (diabetic eye disease), nephropathy (kidney disease or protein in the urine), lower extremity amputation (amputation of a toe, foot, part of a leg, or entire leg), ischemic heart disease (blocked arteries in the heart, angina, or heart attack), or cerebrovascular disease (stroke).26 Most questions in the patient survey had been translated into Spanish. For those that we modified or that had never been translated, we performed translation and back-translated until we attained concordance in meaning between English and Spanish versions.

We obtained patients' most current hemoglobin A1c (HbA1c) values by querying the San Francisco General Hospital database for data preceding the interview. The San Francisco General Hospital clinical laboratory is a University of California, San Francisco–administered facility that uses ion-exchange chromatography (HPLC:Diastat Hemoglobin A1c program, BioRad Laboratories, Hercules, Calif) to measure HbA1c (normal range, 4.9%-6.7%). To validate patients' self-report of diabetes complications, we queried the database for billing diagnoses corresponding to diabetic retinopathy (ICD-9 codes 250.50, 250.52, 362.01, 362.02, and 362.89). We reasoned that a billing diagnosis of retinopathy would be the most accurate means to validate self-reported diabetes complications, given the regularity with which retinopathy screening is carried out and the consistency with which an accompanying billing diagnosis is entered. In contrast, a billing diagnosis of stroke, for example, would likely be recorded only if the event occurred within the 3-year span of the San Francisco General Hospital database. We also obtained patients' insurance information and the name of their primary care physician from the database.

Statistical Analysis

To determine the contribution of health literacy to glycemic control across the entire range of s-TOFHLA scores, we analyzed health literacy as a continuous variable. To correct for the nonnormal distribution of HbA1c data, we used the log transformation of the HbA1c data. Regression analysis was used to measure the association between s-TOFHLA score and HbA1c after other potentially confounding patient characteristics were controlled. We included any variables that were significant at P<.20 in bivariate analysis and also included variables that we had hypothesized would affect glycemic control. Specifically, we performed multivariate linear regression, controlling for differences in patients' characteristics, including age, race/ethnicity, sex, education, language, insurance, depressive symptoms, social support, diabetes education, treatment regimen, and diabetes duration. To facilitate interpretation of these results, all displayed coefficients reflect non–log-transformed (raw) HbA1c values. To address the theoretical concern that low s-TOFHLA scores may result from undetected cognitive problems in patients with high HbA1c or higher rates of diabetes complications, we repeated the analysis after excluding patients with self-reported stroke.

Because patients are often categorized clinically by their degree of glycemic control, we created cutoffs to define tight control and poor control according to the 25th and 75th percentiles of HbA1c distribution for the study sample. These cutoffs were the same for the raw HbA1c and log-transformed HbA1c data. Logistic regression was used to assess the independent effect of health literacy level on the extent of patients' glycemic control after adjustment for the same potential confounders. We also used multivariate regression models to determine the independent effect of health literacy on the risk of diabetes complications (present vs absent) but adjusted for additional clinical predictors known to be related to the outcome.27 We included a term for hypertension (obtained by querying the San Francisco General Hospital database for ICD-9 codes 401, 401.1, and 401.9) in the model for retinopathy and nephropathy and terms for hypertension and smoking in the model for lower extremity amputation, coronary artery disease, and cerebrovascular disease. The SEs for all model coefficients were adjusted for the clustering of patients within physician by using generalized estimating equations.28 All statistical analyses were performed with SAS version 8 (SAS Institute Inc, Cary, NC).

Eight hundred fifty-eight patients were identified by the San Francisco General Hospital clinical database as potentially eligible for the study. Of these, 142 were ineligible because their primary care physicians informed us that the patients were not in their panel (n = 10), did not have type 2 diabetes (n = 25), did not speak English or Spanish fluently (n = 28), had moved out of the area (n = 35), had a psychiatric condition, eg, dementia, psychosis, or mental retardation (n = 23), or had died (n = 1). An additional 20 patients were identified as ineligible by physicians who stated no reason. Of the 716 remaining eligible patients, 261 did not make a primary care visit during the enrollment period. All remaining 455 patients were approached at a clinic appointment. Of these, 36 patients refused to participate. An additional 17 patients were excluded because they were too ill to participate (n = 9), were acutely intoxicated (n = 2), or had poor visual acuity (≥20/50; n = 6). Four hundred thirteen patients completed the questionnaire. For 408 of the 413 patients, at least 1 HbA1c value was available in the San Francisco General Hospital database; these patients composed our study sample. Patients who refused to participate and patients who were not interviewed by virtue of not attending a clinic appointment during the enrollment period were more likely than study subjects to be younger and male but were not different in terms of sex, race/ethnicity, and language.

The study participants were ethnically diverse, had low income and educational attainment, and were predominantly uninsured or publicly insured (Table 1). Most patients were treated with oral hypoglycemic agents either alone or with insulin. The mean abbreviated s-TOFHLA score was 21 (range, 0-36). Thirty-eight percent of patients had inadequate health literacy (s-TOFHLA score, 0-16), and 13% had marginal health literacy (s-TOFHLA score, 17-22). Patients with inadequate health literacy were more likely than patients with adequate health literacy (s-TOFHLA, 23-36) to be older, female, nonwhite, and Spanish-speaking, to have Medicare coverage, to have received only some high school education or less, and to have had diabetes longer.

Table Graphic Jump LocationTable 1. Characteristics of Patients Stratified by Health Literacy Level

The mean HbA1c for the study population was 8.5%. Ninety-eight percent of HbA1c results were obtained within 1 year of the interview date; median length of time between HbA1c and interview date was 90 days. We found no relationship between HbA1c values and the length of time between the date that HbA1c was obtained and the interview date. Table 2 shows the bivariate relationships between predictors of glycemic control and patients' most recent HbA1c value, accounting for the clustering of patients within physician. The s-TOFHLA score, education, insurance, years with diabetes, and diabetes treatment regimen were all associated with HbA1c. After adjustment for age, race/ethnicity, sex, education, language, insurance, depressive symptoms, social support, receipt of diabetes education, treatment regimen, and years with diabetes, only the s-TOFHLA score, insurance status, and treatment regimen were independently associated with HbA1c (Table 2). For each 1-point decrement in s-TOFHLA score, the HbA1c value increased by 0.02 (P = .02); the entire 36-point range of the abbreviated s-TOFHLA score accounted for 0.72 percentage point of HbA1c percentage. Repeating the analysis after excluding patients who reported a history of stroke (n = 46) did not alter the relationship between s-TOFHLA score and HbA1c (–0.02; P = .04). We assessed interactions between significant variables, but none were significant at P<.05.

Table Graphic Jump LocationTable 2. Relationship Between Patient Characteristics and Hemoglobin A1c Levels

The 25th percentile cut point for HbA1c was 7.2% (tight glycemic control), and the 75th percentile cut point for HbA1c was 9.5% (poor glycemic control). Twenty percent of patients with inadequate health literacy had tight glycemic control, whereas 33% of patients with adequate health literacy had tight glycemic control (Figure 1) (unadjusted odds ratio [OR], 0.51; 95% confidence interval [CI], 0.32-0.79; P = .003). Thirty percent of patients with inadequate health literacy had poor glycemic control, whereas 20% of patients with adequate health literacy had poor glycemic control (unadjusted OR, 1.70; 95% CI, 1.09-2.65; P = .02). After confounders were adjusted, patients with inadequate health literacy were less likely than patients with adequate health literacy to achieve tight control (adjusted OR, 0.57; 95% CI, 0.32-1.00; P = .05) and were more likely than patients with adequate health literacy to have poor control (adjusted OR, 2.03; 95% CI, 1.11-3.73; P = .02).

Figure. Health Literacy Level and Glycemic Control by Hemoglobin A1C (HbA1C) Quartile
Graphic Jump Location
See "Methods" for definition of health literacy levels.

Thirty-six percent of patients with inadequate health literacy and 19% of patients with adequate health literacy reported that they had retinopathy (unadjusted OR, 2.44; 95% CI, 1.50-3.96; P<.001). After confounders were adjusted, patients with inadequate health literacy were more likely to report retinopathy (adjusted OR, 2.33; 95% CI, 1.19-4.57; P = .01) (Table 3). When the analysis was repeated with billing diagnoses of retinopathy instead of self-reported retinopathy, the results were similar (unadjusted OR, 2.68; 95% CI, 1.57-4.60; P<.001). The extent of the associations between health literacy and other self-reported diabetes complications, including nephropathy, lower extremity amputation, cerebrovascular disease, and cardiovascular disease, was similar to that of retinopathy but in most cases did not reach statistical significance (Table 3).

Table Graphic Jump LocationTable 3. Adjusted Odds of Self-reported Diabetes Complications for Patients With Inadequate vs Adequate Health Literacy*

Our study demonstrates that, among patients who have type 2 diabetes and access to primary care physicians in public hospital clinics, health literacy was independently associated with glycemic control. Inadequate health literacy was an independent predictor of poor glycemic control and was associated with a lower likelihood of achieving tight control. In addition, inadequate health literacy was associated with a higher prevalence of retinopathy and other self-reported complications of diabetes. The results of our study are consistent with those of a smaller study in which a trend of worse control of blood glucose levels with worse health literacy was noted.8

The association between health literacy and glycemic control that we observed is significant from a clinical and public health perspective. The proportion of patients with tight glycemic control vs poor control is routinely used as a quality-of-care indicator for diabetes.29 Glycosylated hemoglobin is an objective clinical end point that has been linked to health care use and costs30 and disabling and life-threatening conditions.31,32 Studies have demonstrated that there is a curvilinear relationship between HbA1c and microvascular complications and that a decrease in HbA1c of 1 percentage point (from 9.0% to 8.1%, for example) results in a halving of the risk of retinopathy.3133 Consistent with this body of research, our study showed that the worse glycemic control experienced by patients with inadequate health literacy was reflected in a higher prevalence of retinopathy. When compared with patients with adequate health literacy, patients with inadequate health literacy had 2 times the odds of having retinopathy, even after adjustment for patient sociodemographics, diabetes education, treatment regimen, and duration of diabetes.

From the public health perspective, health literacy may represent an important variable explaining the prevalence of poor health outcomes among patients with type 2 diabetes,15 as well as some of the socioeconomic, racial, and ethnic disparities in diabetes outcomes in the United States.17,34 A considerable proportion of patients with type 2 diabetes is likely to have poor health literacy. In the United States, nearly 80% of patients with type 2 diabetes have completed only high school or less compared with 40% of the general population.16 In our sample, 66% of patients with a high school education or less had inadequate or marginal health literacy. Because of its higher prevalence in racial and ethnic minorities,1 poor health literacy may represent an important variable contributing to high rates of diabetes complications, such as diabetic retinopathy and blindness, end-stage renal disease, and lower extremity amputations among racial and ethnic minorities.3540

Our study has a number of limitations. First, its cross-sectional design did not allow us to ascertain whether inadequate health literacy was causally associated with poor diabetes outcomes. It is possible that health literacy is simply a marker for other factors, such as health-seeking behavior or psychological makeup, or that other factors, such as multiple comorbidities or obesity, represent unmeasured confounders. A recent study among public-hospital patients with type 2 diabetes demonstrated no relationship between medical comorbidities, body mass index, and degree of glycemic control.41 Although we hypothesized that health literacy predicted diabetes glycemic control, theoretically, our findings could be a result of poor glycemic control or higher rates of complications (such as stroke) leading to lower scores on the s-TOFHLA. In designing our study, we attempted to minimize this possibility by excluding patients who were too ill to participate or had dementia. To further address this concern, we reanalyzed the association between s-TOFHLA score and glycemic control in all study patients, excluding those with a history of stroke, and found the same relationship as in the entire sample. Because our study involved patients receiving ongoing medical care, we cannot determine the degree to which the association between inadequate health literacy and diabetes outcomes was a result of events occurring before or after clinical presentation. Community-based studies have demonstrated that one third to one half of patients with type 2 diabetes are undiagnosed.42,43 Although our models controlled for self-reported duration of diabetes, it is possible that patients with inadequate health literacy were less likely to recognize signs and symptoms of diabetes, presented to care later, and therefore were more likely to experience diabetes complications.

Our study does not elucidate mechanisms whereby inadequate health literacy may result in worse diabetes outcomes. Diabetes care requires that a host of concepts and skills be conveyed by a team of health care providers and successfully carried out by the patient. The diabetes self-management regimen is one of the most challenging of any for chronic illness. Patients often must perform self-monitoring of blood glucose, manage multiple medications, visit multiple providers, maintain foot hygiene, adhere to diet and meal plans, and engage in an exercise program. Patients also must be able to identify when they are having problems across these functions and effectively problem-solve to divert crises, so diabetes outcomes may be especially sensitive to problems in communication, empowerment, and self-management.44 The determinants of the quality of diabetes care are multiple and complex, with inputs and interactions at the patient, provider, health system, and family and community levels.4548 Poor health literacy probably impedes successful communication across many levels. For example, patients with poor health literacy have lower levels of diabetes-related knowledge and are less likely to correctly interpret or act on self-monitoring results even after adjustment for exposure to diabetes education.8 Providers may fail to successfully transmit the technical skills or behavioral motivation necessary to perform and maintain self-care activities or respond to abnormal results.49 Health systems may fail to provide tailored, systematic support to patients and clinicians.50 Although studies have demonstrated the positive impact of diabetes education,51 in our study standard diabetes education did not eliminate health literacy–related disparities in diabetes outcomes.

Our study has a number of important implications. From the public health standpoint, our findings can inform strategic plans to address the growing diabetes epidemic.52 To prevent diabetes, reduce its economic burden, and improve the quality of life for all persons who have or are at risk for diabetes,52 public health messages and health care system interventions should target patients with poor health literacy. For health care professionals, the prevalence of poor health literacy and the strength and consistency of the association between health literacy and diabetes outcomes that we observed should serve as a call to action. Development of strategies to communicate more effectively with patients who have poor health literacy are needed at the patient-clinician level49,53 and the patient-system level50,54 and should be based on a deeper understanding of the needs and competencies of patients with poor health literacy. Research to develop effective office-based communication strategies and efforts to more widely apply chronic-disease management programs for patients with poor health literacy should be supported.

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Tull ES, Roseman JM, Stern MP, Mitchell BD, Fujimoto WY, Gohdes D. Diabetes in special populations. In: Harris MI, Cowie CC, Reiber G, Boyko E, Stern M, Bennett P, eds. Diabetes in America. 2nd ed. Washington, DC: US Government Printing Office; 1995:613-683. Publication 95-1468.
Haffner SM, Fong D, Stern MP.  et al.  Diabetic retinopathy in Mexican Americans and non-Hispanic whites.  Diabetes.1988;37:878-884.
Harris MI, Klein R, Cowie CC, Rowland M, Byrd-Holt DD. Is the risk of diabetic retinopathy greater in non-Hispanic blacks and Mexican Americans than in non-Hispanic whites with type 2 diabetes? a US population study.  Diabetes Care.1998;21:1230-1235.
Cowie CC, Port FK, Wolfe RA, Savage PJ, Moll PP, Hawthorne VM. Disparities in incidence of diabetic end-stage renal disease according to race and type of diabetes.  N Engl J Med.1989;321:1074-1079.
Bild DE, Selby JV, Sinnock P, Browner WS, Braveman P, Showstack JA. Lower-extremity amputation in people with diabetes: epidemiology and prevention.  Diabetes Care.1989;12:24-31.
Lavery LA, Ashry HR, van Houtum W, Pugh JA, Harkless LB, Basu S. Variation in the incidence and proportion of diabetes-related amputations in minorities.  Diabetes Care.1996;19:48-52.
El-Kebbi IM, Ziemer DC, Cook CB, Miller CD, Gallina DL, Phillips LS. Comorbidity and glycemic control in patients with type 2 diabetes.  Arch Intern Med.2001;161:1295-1300.
Hadden WC, Harris MI. Prevalence of diagnosed diabetes, undiagnosed diabetes, and impaired glucose tolerance in adults 20-74 years of age.  Vital Health Stat 11.1987;237:1-55.
Flegal KM, Ezzati TM, Harris MI.  et al.  Prevalence of diabetes in Mexican Americans, Cubans, and Puerto Ricans from the Hispanic Health and Nutrition Examination Survey, 1982-1984.  Diabetes Care.1991;14:628-638.
Anderson RM, Funnell MM. Compliance and adherence are dysfunctional concepts in diabetes care.  Diabetes Educ.2000;26:597-604.
Von Korff M, Gruman J, Schaefer J, Curry SJ, Wagner EH. Collaborative management of chronic illness.  Ann Intern Med.1997;127:1097-1102.
Glasgow RE, Hampson SE, Strycker LA, Ruggiero L. Personal-model beliefs and social-environmental barriers related to diabetes self-management.  Diabetes Care.1997;20:556-561.
McCulloch DK, Price MJD, Hindmarsh M, Wagner EH. Improvement in diabetes care using an integrated population-based approach in a primary care setting.  Dis Manage.2000;3:75-82.
Fisher L, Chesla CA, Bartz RJ.  et al.  The family and type 2 diabetes: a framework for intervention.  Diabetes Educ.1998;24:599-607.
Schillinger D, Piette J, Wang F.  et al.  Closing the loop: missed opportunities in communicating with patients who have low functional health literacy.  Arch Intern Med.In press.
Schillinger D. Improving the quality of chronic disease management for populations with low functional health literacy: a call to action.  Dis Manage.2001;4:103-109.
Elasy TA, Ellis SE, Brown A, Pichert JW. A taxonomy for diabetes educational interventions.  Patient Educ Couns.2001;43:121-127.
 Diabetes. In: Healthy People 2010 [Office of Disease Prevention and Health Promotion, US Department of Health and Human Services Web site]. Available at: http://www.health.gov/healthypeople/document. Accessibility verified May 24, 2002.
Doak CC, Doak LG, Friedell GH, Meade CD. Improving comprehension for cancer patients with low literacy skills: strategies for clinicians.  CA Cancer J Clin.1998;48:151-162.
 Strategies for reducing morbidity and mortality from diabetes through health-care system interventions and diabetes self-management education in community settings: a report on recommendations of the Task Force on Community Preventive Services.  MMWR Morb Mortal Wkly Rep.2001;50(RR-16):1-15.

Figures

Figure. Health Literacy Level and Glycemic Control by Hemoglobin A1C (HbA1C) Quartile
Graphic Jump Location
See "Methods" for definition of health literacy levels.

Tables

Table Graphic Jump LocationTable 1. Characteristics of Patients Stratified by Health Literacy Level
Table Graphic Jump LocationTable 2. Relationship Between Patient Characteristics and Hemoglobin A1c Levels
Table Graphic Jump LocationTable 3. Adjusted Odds of Self-reported Diabetes Complications for Patients With Inadequate vs Adequate Health Literacy*

References

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Doak CC, Doak LG, Root JH. Teaching Patients With Low Literacy SkillsPhiladelphia, Pa: JB Lippincott; 1996.
Mayeaux Jr EJ, Murphy PW, Arnold C, Davis TC, Jackson RH, Sentell T. Improving patient education for patients with low literacy skills.  Am Fam Physician.1996;53:205-211.
Gazmararian JA, Baker DW, Williams MV.  et al.  Health literacy among Medicare enrollees in a managed care organization.  JAMA.1999;281:545-551.
Kalichman SC, Rompa D. Functional health literacy is associated with health status and health-related knowledge in people living with HIV-AIDS.  J Acquir Immune Defic Syndr.2000;25:337-344.
Kalichman SC, Benotsch E, Suarez T, Catz S, Miller J, Rompa D. Health literacy and health-related knowledge among persons living with HIV/AIDS.  Am J Prev Med.2000;18:325-331.
Kalichman SC, Ramachandran B, Catz S. Adherence to combination antiretroviral therapies in HIV patients of low health literacy.  J Gen Intern Med.1999;14:267-273.
Williams MV, Baker DW, Parker RM, Nurss JR. Relationship of functional health literacy to patients' knowledge of their chronic disease: a study of patients with hypertension and diabetes.  Arch Intern Med.1998;158:166-172.
Williams MV, Baker DW, Honig EG, Lee TM, Nowlan A. Inadequate literacy is a barrier to asthma knowledge and self-care.  Chest.1998;114:1008-1015.
Weiss BD, Hart G, McGee DL, D'Estelle S. Health status of illiterate adults: relation between literacy and health status among persons with low literacy skills.  J Am Board Fam Pract.1992;5:257-264.
Baker DW, Parker RM, Williams MV, Clark WS, Nurss J. The relationship of patient reading ability to self-reported health and use of health services.  Am J Public Health.1997;87:1027-1030.
Baker DW, Parker RM, Williams MV, Clark WS. Health literacy and the risk of hospital admission.  J Gen Intern Med.1998;13:791-798.
Williams MV, Parker RM, Baker DW, Coates W, Nurss J. The impact of inadequate functional health literacy on patients' understanding of diagnosis, prescribed medications, and compliance [abstract].  Acad Emerg Med.1995;2:386.
 National Diabetes Fact Sheet . Atlanta, Ga: Centers for Disease Control and Prevention; 2000.
Harris MI. Health care and health status and outcomes for patients with type 2 diabetes.  Diabetes Care.2000;23:754-758.
Cowie CC, Eberhardt MS. Sociodemographic characteristics of persons with diabetes. In: Harris MI, Cowie CC, Reiber G, Boyko E, Stern M, Bennett P, eds. Diabetes in America. 2nd ed. Washington, DC: US Government Printing Office; 1995:85-116. Publication 95-1468.
 Diabetes. In: Healthy People 2010. Washington, DC: Office of Disease Prevention and Health Promotion, US Dept of Health and Human Services; 2001.
Parker RM, Baker DW, Williams MV, Nurss JR. The test of functional health literacy in adults: a new instrument for measuring patients' literacy skills.  J Gen Intern Med.1995;10:537-541.
Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to measure functional health literacy.  Patient Educ Couns.1999;38:33-42.
Taylor WL. Cloze procedure: a new tool for measuring readability.  Journal Q.1953;30:415-433.
Gunning R. The Technique of Clear WritingNew York, NY: McGraw-Hill; 1968.
Williams MV, Parker RM, Baker DW.  et al.  Inadequate functional health literacy among patients at two public hospitals.  JAMA.1995;274:1677-1682.
Lustman PJ, Anderson RJ, Freedland KE, de Groot M, Carney RM, Clouse RE. Depression and poor glycemic control: a meta-analytic review of the literature.  Diabetes Care.2000;23:934-942.
Fitzgerald JT, Davis WK, Connell CM, Hess GE, Funnell MM, Hiss RG. Development and validation of the Diabetes Care Profile.  Eval Health Prof.1996;19:208-230.
Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale).  Am J Prev Med.1994;10:77-84.
Michigan Diabetes Research and Training Center.  Survey instruments. Available at: http://www.med.umich.edu/mdrtc/survey/index.html. Accessibility verified May 24, 2002.
Leahy JL, Clark NG, Cefalu WT. Medical Management of Diabetes MellitusNew York, NY: Marcel Dekker; 2000.
Burton P, Gurrin L, Sly P. Extending the simple linear regression model to account for correlated responses: an introduction to generalized estimating equations and multi-level mixed modelling.  Stat Med.1998;17:1261-1291.
Fleming BB, Greenfield S, Engelgau MM, Pogach LM, Clauser SB, Parrott MA. The Diabetes Quality Improvement Project: moving science into health policy to gain an edge on the diabetes epidemic.  Diabetes Care.2001;24:1815-1820.
Wagner EH, Sandhu N, Newton KM, McCulloch DK, Ramsey SD, Grothaus LC. Effect of improved glycemic control on health care costs and utilization.  JAMA.2001;285:182-189.
The Diabetes Control and Complications Trial Research Group.  The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus.  N Engl J Med.1993;329:977-986.
UK Prospective Diabetes Study (UKPDS) Group.  Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33).  Lancet.1998;352:837-853.
Klein R, Klein BE, Moss SE, Cruickshanks KJ. The Wisconsin Epidemiologic Study of diabetic retinopathy, XIV: ten-year incidence and progression of diabetic retinopathy.  Arch Ophthalmol.1994;112:1217-1228.
Harris MI, Cowie CC, Reiber G, Boyko E, Stern M, Bennett P. Diabetes in America2nd ed. Washington, DC: US Government Printing Office; 1995. Publication 95-1468.
Tull ES, Roseman JM, Stern MP, Mitchell BD, Fujimoto WY, Gohdes D. Diabetes in special populations. In: Harris MI, Cowie CC, Reiber G, Boyko E, Stern M, Bennett P, eds. Diabetes in America. 2nd ed. Washington, DC: US Government Printing Office; 1995:613-683. Publication 95-1468.
Haffner SM, Fong D, Stern MP.  et al.  Diabetic retinopathy in Mexican Americans and non-Hispanic whites.  Diabetes.1988;37:878-884.
Harris MI, Klein R, Cowie CC, Rowland M, Byrd-Holt DD. Is the risk of diabetic retinopathy greater in non-Hispanic blacks and Mexican Americans than in non-Hispanic whites with type 2 diabetes? a US population study.  Diabetes Care.1998;21:1230-1235.
Cowie CC, Port FK, Wolfe RA, Savage PJ, Moll PP, Hawthorne VM. Disparities in incidence of diabetic end-stage renal disease according to race and type of diabetes.  N Engl J Med.1989;321:1074-1079.
Bild DE, Selby JV, Sinnock P, Browner WS, Braveman P, Showstack JA. Lower-extremity amputation in people with diabetes: epidemiology and prevention.  Diabetes Care.1989;12:24-31.
Lavery LA, Ashry HR, van Houtum W, Pugh JA, Harkless LB, Basu S. Variation in the incidence and proportion of diabetes-related amputations in minorities.  Diabetes Care.1996;19:48-52.
El-Kebbi IM, Ziemer DC, Cook CB, Miller CD, Gallina DL, Phillips LS. Comorbidity and glycemic control in patients with type 2 diabetes.  Arch Intern Med.2001;161:1295-1300.
Hadden WC, Harris MI. Prevalence of diagnosed diabetes, undiagnosed diabetes, and impaired glucose tolerance in adults 20-74 years of age.  Vital Health Stat 11.1987;237:1-55.
Flegal KM, Ezzati TM, Harris MI.  et al.  Prevalence of diabetes in Mexican Americans, Cubans, and Puerto Ricans from the Hispanic Health and Nutrition Examination Survey, 1982-1984.  Diabetes Care.1991;14:628-638.
Anderson RM, Funnell MM. Compliance and adherence are dysfunctional concepts in diabetes care.  Diabetes Educ.2000;26:597-604.
Von Korff M, Gruman J, Schaefer J, Curry SJ, Wagner EH. Collaborative management of chronic illness.  Ann Intern Med.1997;127:1097-1102.
Glasgow RE, Hampson SE, Strycker LA, Ruggiero L. Personal-model beliefs and social-environmental barriers related to diabetes self-management.  Diabetes Care.1997;20:556-561.
McCulloch DK, Price MJD, Hindmarsh M, Wagner EH. Improvement in diabetes care using an integrated population-based approach in a primary care setting.  Dis Manage.2000;3:75-82.
Fisher L, Chesla CA, Bartz RJ.  et al.  The family and type 2 diabetes: a framework for intervention.  Diabetes Educ.1998;24:599-607.
Schillinger D, Piette J, Wang F.  et al.  Closing the loop: missed opportunities in communicating with patients who have low functional health literacy.  Arch Intern Med.In press.
Schillinger D. Improving the quality of chronic disease management for populations with low functional health literacy: a call to action.  Dis Manage.2001;4:103-109.
Elasy TA, Ellis SE, Brown A, Pichert JW. A taxonomy for diabetes educational interventions.  Patient Educ Couns.2001;43:121-127.
 Diabetes. In: Healthy People 2010 [Office of Disease Prevention and Health Promotion, US Department of Health and Human Services Web site]. Available at: http://www.health.gov/healthypeople/document. Accessibility verified May 24, 2002.
Doak CC, Doak LG, Friedell GH, Meade CD. Improving comprehension for cancer patients with low literacy skills: strategies for clinicians.  CA Cancer J Clin.1998;48:151-162.
 Strategies for reducing morbidity and mortality from diabetes through health-care system interventions and diabetes self-management education in community settings: a report on recommendations of the Task Force on Community Preventive Services.  MMWR Morb Mortal Wkly Rep.2001;50(RR-16):1-15.
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