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RESEARCH AND PRACTICE |
Leonard E. Egede and Deyi Zheng are with the Departments of Medicine and of Biometry and Epidemiology, Medical University of South Carolina, Charleston.
Correspondence: Requests for reprints should be sent to Leonard E. Egede, MD, Medical University of South Carolina, Division of General Internal Medicine and Geriatrics, McClennanBanks Adult Primary Care Clinic (4th floor), 326 Calhoun St, PO Box 250100, Charleston, SC 29401 (e-mail: egedel{at}musc.edu).
| ABSTRACT |
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Objectives. This study identified racial/ethnic disparities in influenza vaccination in high-risk adults.
Methods. We analyzed data on influenza vaccination in 7655 adults with high-risk conditions, using data from the 1999 National Health Interview Survey (NHIS). We stratified data by age and used multiple logistic regression to adjust for gender, education, income, employment, and health care access.
Results. After control for covariates, White patients with diabetes, chronic heart conditions, and cancer had a higher prevalence of influenza vaccination than did Black patients with the same conditions. Similarly, White patients with 2 or more high-risk conditions were more likely to receive the influenza vaccine than Black patients with the same conditions.
Conclusions. Significant racial/ethnic differences exist in influenza vaccination of high-risk individuals, and missed vaccination opportunities seem to contribute to the less-than-optimal influenza vaccination coverage in the United States.
| INTRODUCTION |
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Certain segments of the population are particularly at high risk of serious illness and death from influenza and related complications. These high-risk groups include elderly persons, immunocompromised individuals, and people with medical conditions such as diabetes, chronic heart conditions, chronic obstructive pulmonary disease (COPD), and asthma.5 Consequently, the Advisory Committee on Immunization Practices recommends yearly influenza vaccination for all adults aged 65 years and older and for high-risk adults aged 18 to 64 years.5
Evidence exists of substantial current racial/ethnic disparities in the quality of health care in the United States.6 Compared with White Americans, Black Americans appear less likely to receive quality health care for several medical conditions.710 Similar racial/ethnic disparities in vaccination coverage against influenza exist, and studies have shown that Blacks have lower influenza vaccination rates than do Whites.1114 However, few data exist regarding whether racial/ethnic differences exist in influenza vaccination coverage for specific high-risk chronic medical conditions, such as cancer, chronic heart conditions, COPD, and asthma.
This study used nationally representative data to examine the following 2 questions: (1) Do racial/ethnic disparities in influenza vaccination exist among individuals with specific high-risk chronic medical conditions, such as diabetes, chronic heart conditions, COPD, cancer, and asthma? and (2) Should racial/ethnic differences in influenza vaccination exist, do differences in age, gender, household income, education, employment, and access to care adequately explain them?
| METHODS |
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Subjects
The study used civilian noninstitutionalized adults aged 18 years and older in the United States with at least 1 of the following chronic medical conditions: diabetes, chronic heart conditions, COPD, cancer, and asthma (n = 7655).
Data
The NHIS is a national household survey of nonmilitary and noninstitutionalized persons in the United States, sponsored by the National Center for Health Statistics of the Centers for Disease Control and Prevention.15 This analysis used variables from the sample adult core. In the sample adult core, 1 adult per family was randomly selected to respond to a computer-assisted personal interview questionnaire. For the 1999 survey, 30 801 persons aged 18 years and older were interviewed, with a final response rate of 70%. The NHIS sample was selected through the use of a complex sampling design involving stratification, clustering, and multistage sampling with a nonzero probability of selection for each person. We used final weights provided by NHIS to account for unequal probability of selection, nonresponse, and oversampling of certain demographic groups so that weighted estimates in this study can be generalized to the adult civilian population of the United States. Details about the methodology of the 1999 NHIS are available online.16,17
Demographic Variables
We examined data on age, gender, race/ethnicity, education, household income, employment, and marital status. Race/ethnicity was restricted to non-Hispanic Whites and non-Hispanic Blacks; Hispanics and others were excluded in this analysis. Similarly, for analytic purposes, we created dichotomous groups for education (< high school vs
high school), household income (< $20 000 vs
$20 000), employment (employed vs not employed), and marital status (married vs not married).
High-Risk Patients
We defined high-risk patients as individuals with diabetes, chronic heart conditions, COPD, cancer, or asthma per the Centers for Disease Control and Prevention definition.5 Clinical conditions were based on self-report. The diabetes group excluded patients diagnosed during pregnancy, and the chronic heart condition group included patients with coronary heart disease, angina pectoris, myocardial infarction, and congestive heart failure. We created 2 comorbidity categories: people with only 1 high-risk condition and people with 2 or more high-risk conditions.
Clinical and Access-to-Care Variables
Influenza vaccination status was based on self-report. Health status was based on perceived change in physical health in the previous 12 months. We dichotomized responses as "worse" versus "better" or "about the same." Indicators of access to health care included having a usual source of care, having health care coverage, and having contact with a primary care physician in the past 12 months.
Statistical Analyses
We used SAS18 for statistical analyses and SUDAAN19 to generate population estimates weighted to the US population in 1999 and to account for the complex sampling design of the NHIS. We compared demographic, clinical, and access-to-care variables and the proportion of individuals with high-risk medical conditions in Whites and Blacks, using
2 statistics to identify baseline differences. We then calculated the crude prevalence of influenza vaccination for Whites and Blacks, using
2 statistics to determine differences in prevalence estimates by patient characteristics. Finally, we determined the adjusted prevalence of influenza vaccination for each high-risk condition. We chose to adjust for variables that were most likely to influence influenza vaccination coverage, on the basis of previous research. Also, we eliminated variables that did not contribute to the models in our preliminary analyses.
For each high-risk condition, we stratified patients by age and used SUDAAN to obtain the conditional marginal prevalence of influenza vaccination in Whites and Blacks, adjusting for gender, education, household income, employment, and having had a physician checkup within the previous 12 months. We performed a similar analysis for patients with 2 or more high-risk conditions to account for the fact that the clinical categories were not mutually exclusive. The conditional marginal procedure estimates the probability of receiving the influenza vaccine after control for the independent variables. For example, to compare the prevalence of influenza vaccination among Whites with that among Blacks, the conditional marginal procedure computes the probability of receiving the influenza vaccine for both Whites and Blacks after control for other independent variables. This procedure is different from the multiple logistic regression procedure, which designates either Whites or Blacks as the reference and computes odd ratios. The results from the conditional marginal procedure are easier to interpret. Details about the conditional marginal procedure are available in the SUDAAN 8.0 users manual.20
| RESULTS |
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| DISCUSSION |
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Our results concur with the findings of earlier studies that have documented racial/ethnic differences in influenza vaccination in the United States1114,21,22 and suggest that although influenza vaccination coverage has improved over time, racial/ethnic differences have remained unchanged. In addition, our findings contradict the prevailing assumption that differences in socioeconomic status and access to health care between Whites and Blacks23 are responsible for racial/ethnic differences in influenza vaccination. Future studies need to examine the contribution of other factors, such as racial/ethnic differences in the administration of vaccines by health care providers and racial/ethnic differences in the acceptance of vaccines by patients.
We also found that regardless of race/ethnicity, the prevalence of influenza vaccination in younger-aged patients with high-risk conditions was suboptimal. For example, the adjusted prevalence of influenza vaccination ranged from 20% (in Blacks with cancer) to 46% (in Whites with diabetes). The low vaccination coverage in this age group is worrisome, and unless effective strategies that target this group of patients are implemented, it is unlikely that the goal of vaccinating 60% of these patients by the year 201024 will be met. Of particular concern is the low vaccination coverage for younger-aged Black patients. In this group of patients, the highest coverage was 33% (in those with diabetes), which is a far cry from the target of 60% by the year 2010.
The major implication of our findings is that opportunities to administer the influenza vaccine during patientprovider encounters are being missed, particularly for Blacks and for younger-aged patients. In our study, only 46% of high-risk patients with a physician encounter in the past year reported receipt of the influenza vaccine. Similar results have been previously reported. One study found that among people aged 65 years or older with 5 or more physician contacts during the previous 12 months, only 69% of Whites and 44% of Blacks reported receipt of the influenza vaccine.14 Another study found that a significant proportion of generalist and subspecialist physicians failed to strongly recommend influenza and pneumococcal vaccinations to their elderly and high-risk patients.25
These missed vaccination opportunities must be exploited, especially in light of data suggesting that a physicians recommendation strongly influences a patients decision to be vaccinated.2628 It is crucial that healthcare systems adopt and widely implement effective strategies that increase vaccination rates, and that healthcare providers ensure that the influenza vaccine is offered to all patients during the flu season. In addition, creative strategies that target younger adults and minority patients and that also address culture-specific erroneous beliefs about and attitudes toward vaccination are likely to be beneficial.
The results of this study are subject to some limitations. Bias in recall of influenza vaccine administration is one potential limitation. However, studies have shown that self-report of influenza vaccination is reliable,29 so that our estimates are likely to be reliable. A second potential limitation is misclassification of asthma and COPD that may result from the similarity in these diseases clinical manifestations. We see no obvious reason to expect misclassification of asthma and COPD to differ between Whites and Blacks; therefore, it is unlikely that our estimates would be affected by such misclassification. Finally, our findings cannot be generalized beyond nonmilitary and noninstitutionalized persons, which means that our results may not be applicable to institutionalized patients such as those in nursing homes.
In conclusion, this study documents significant racial/ethnic differences in influenza vaccination of high-risk individuals and the contribution of missed vaccination opportunities to the less-than-optimal prevalence of influenza vaccination in the United States.
| Acknowledgments |
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Note. The contents of this article reflect the personal opinions of the authors and do not represent the official opinion of either the Agency for Health Care Research and Quality or the Centers for Disease Control and Prevention.
Human Participant Protection
This study was approved by the institutional review board of Medical University of South Carolina.
| Footnotes |
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Accepted for publication April 7, 2002.
| References |
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14. Singleton JA, Greby SM, Wooten KG, Walker FJ, Strikas R. Influenza, pneumococcal, and tetanus toxoid vaccination of adultsUnited States, 19931997. MMWR CDC Surveill Summ. 2000;49(SS-9):3962.[Medline]
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16. Data file documentation, National Health Interview Survey, 1999. Hyattsville, Md: National Center for Health Statistics; 2001. Available at: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHIS/1999/Srvydesc.pdf. Accessed June 28, 2002.
17. Data file and documentation, National Health Interview Survey, 1999. Hyattsville, Md: National Center for Health Statistics; 2001. Available at: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHIS/1999/SAMADULT.pdf. Accessed June 28, 2002.
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20. SUDAAN Users Manual. Release 8.0. Research Triangle Park, NC: Research Triangle Institute; 2001.
21. Egede LE, Zheng D. Disparities in influenza and pneumococcal vaccine coverage among adults with diabetes. J Gen Intern Med. 2001;16(suppl 1):128129.
22. Egede LE, Zheng D. Influenza and pneumococcal vaccination coverage among adults with diabetes in 1999. How do minorities compare to whites? Diabetes. 2001;50(suppl 2):A210.
23. Center for Disease Control and Prevention. Influenza and pneumococcal vaccination rates among persons with diabetes mellitusUnited States 1997. MMWR Morb Mortal Wkly Rep. 1999;48(42):961967.[Medline]
24. Healthy People 2010: Understanding and Improving Health. 2nd ed. Washington, DC: US Dept of Health and Human Services; 2000.
25. Nichol KL, Zimmerman R. Generalist and subspecialist physicians knowledge attitudes, and practices regarding influenza and pneumococcal vaccinations for elderly and other high-risk patients. Arch Intern Med. 2001;161:27022708.
26. Centers for Disease Control and Prevention. Local data for local decision makingselected counties, Connecticut, Massachusetts, and New York, 1997. MMWR Morb Mortal Wkly Rep. 1998;47:809813.[Medline]
27. Fiebach NH, Viscoli CM. Patient acceptance of influenza vaccination. Am J Med. 1991;91:393400.[ISI][Medline]
28. Nichol KL, Lofgren RP, Gapinski J. Influenza vaccination. Knowledge, attitudes, and behavior among high-risk outpatients. Arch Intern Med. 1992;152:106110.[Abstract]
29. Mac Donald R, Baken L, Nelson A, Nichol KL. Validation of self-report of influenza and pneumococcal vaccination status in elderly outpatients. Am J Prev Med. 1999;16:173177.[ISI][Medline]
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