 |
|
Patterns of Prevalent Major Chronic Disease Among Older Adults in the United States
To the Editor: Older adults with more than 1 chronic disease have worse functional status and self-rated health, use more health care, and die earlier than those with a single disease.1 Because evidence-based medical treatment has usually been directed toward single diseases, understanding specific patterns of multimorbidity may help develop strategies to improve clinical practice. Ignoring concomitant diseases while applying single-disease guidelines may lead to harm.2 The purpose of this study was to estimate patterns of major chronic disease co-occurrence in older adults.
Methods
Data were taken from the National Health and Nutrition Examination Survey (NHANES), a nationally representative study of US noninstitutionalized civilians.3 Data from 3 survey waves (1999-2000, 2001-2002, and 2003-2004) comprised the analytic sample of 4349 individuals aged 65 years or older. We selected 5 disease types with a leading role as a cause of death4 or morbidity5: arthritis, cerebrovascular accident, chronic lower respiratory tract disease, coronary heart disease, and diabetes mellitus. Disease status was ascertained through the question "Has a doctor or other health professional ever told you you had [disease]?" Coronary heart disease included individuals stating they had coronary heart disease, angina, or a myocardial infarction; chronic lower respiratory tract disease included self-reported emphysema, chronic bronchitis, or asthma. Diabetes included participants who had "borderline diabetes" and treatment for or complications of diabetes.
Frequencies were estimated using NHANES sampling weights and masked variance units. Binomial Wald 95% confidence intervals were calculated. Analyses were performed using Stata, release 9.2 (Stata Corp, College Station, Texas).
Results
Prevalence of mutually exclusive disease patterns occurring in all older adults was estimated for women (Table 1) and men (Table 2). While the absence of all diseases and single occurrences of some diseases were the most common patterns, the majority of participants experiencing each disease had at least 1 other coincident disease. The percentage of participants experiencing each disease alone varied from 15.2% to 47.2%.
|
|
|
|
Table 1. Prevalence of Major Chronic Disease Patterns Among Women Aged 65 or Older, NHANES, 1999-2004a
|
|
|
|
|
|
|
Table 2. Prevalence of Major Chronic Disease Patterns Among Men Aged 65 or Older, NHANES, 1999-2004a
|
|
|
Column total frequencies can be used to compute conditional prevalence of disease co-occurrence. As an example, in designing an intervention trial for older adults with chronic lower respiratory tract disease, it may be useful to know what proportion of potential participants also have both diabetes and arthritis. The total disease frequency of chronic lower respiratory tract disease (3 919 100) may be used as the denominator and the sum of the corresponding row frequencies (369 870 + 192 380) as the numerator, for a rough prevalence of 14% in older women (Table 1).
Comment
Single-disease clinical practice guidelines may not be relevant for large proportions of individuals with disease, particularly if the guidelines do not consider drug-drug and drug-disease interactions. Recognizing that some specific combinations of diseases are common may allow strategies targeted to a pattern. For example, older women with arthritis and chronic lower respiratory tract disease may benefit from education on how to optimize physical activity (proper use of analgesics to participate in pulmonary rehabilitation) and avoid medication interactions (avoiding prolonged use of nonsteroidal anti-inflammatory drugs while taking glucocorticoids).
These results must be considered within the study limitations. They are limited to 5 major disease types chosen for their associated morbidity and mortality and, therefore, do not include all types of potentially important multimorbidity patterns. Self-report of diseases may have led to misclassification; however, agreement between self-report and objective disease status has been considered acceptable for these diseases.6 Information bias may affect these results in that patients with a chronic disease have more contact with health care professionals and thereby have more diseases identified. Nevertheless, these findings provide evidence that clinical trials and treatment guidelines that do not appropriately incorporate multimorbidity may fail to address the needs of a majority of older individuals with disease.
Author Contributions: Dr Weiss had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Weiss, Boyd, Leff.
Acquisition of data: Weiss.
Analysis and interpretation of data: Weiss, Boyd, Yu, Wolff, Leff.
Drafting of the manuscript: Weiss.
Critical revision of the manuscript for important intellectual content: Weiss, Boyd, Yu, Wolff, Leff.
Statistical analysis: Weiss, Boyd, Yu.
Obtained funding: Weiss, Boyd.
Administrative, technical, or material support: Wolff, Leff.
Study supervision: Leff.
Financial Disclosures: None reported.
Funding/Support: Dr Weiss was supported by the Hartford Center of Excellence at Johns Hopkins University. Dr Boyd was supported by the Johns Hopkins Bayview Center for Innovative Medicine.
Role of the Sponsors: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.
Additional Contributions: We acknowledge the assistance with data management provided by Michelle Ricks, MS, a paid employee of the Johns Hopkins Center on Aging and Health.
This article was corrected for error in data on 10/4/2007, prior to publication of the correction in print.
Carlos O. Weiss, MD, MHS
cweiss9{at}jhmi.edu
Cynthia M. Boyd, MD, MPH;
Qilu Yu, PhD
Division of Geriatric Medicine and Gerontology
Department of Medicine
Johns Hopkins University School of Medicine
Baltimore, Maryland
Jennifer L. Wolff, PhD
Department of Health Policy and Management
Johns Hopkins Bloomberg School of Public Health
Baltimore, Maryland
Bruce Leff, MD
Division of Geriatric Medicine and Gerontology
Department of Medicine
Johns Hopkins University School of Medicine
Baltimore, Maryland
1. Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van den Bos GA. Causes and consequences of comorbidity: a review. J Clin Epidemiol. 2001;54(7):661-674.
FULL TEXT
|
ISI
| PUBMED
2. Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA. 2005;294(6):716-724.
FREE FULL TEXT
3. National Center for Health Statistics. National Health and Nutrition Examination Survey. http://www.cdc.gov/nchs/nhanes.htm. Accessed February 6, 2007.4. Jemal A, Ward E, Hao Y, Thun M. Trends in the leading causes of death in the United States, 1970-2002. JAMA. 2005;294(10):1255-1259.
FREE FULL TEXT
5. Verbrugge LM, Patrick DL. Seven chronic conditions: their impact on US adults' activity levels and use of medical services. Am J Public Health. 1995;85(2):173-182.
FREE FULL TEXT
6. Simpson CF, Boyd CM, Carlson MC, Griswold ME, Guralnik JM, Fried LP. Agreement between self-report of disease diagnoses and medical record validation in disabled older women: factors that modify agreement. J Am Geriatr Soc. 2004;52(1):123-127.
FULL TEXT
|
ISI
| PUBMED
Letters Section Editor: Robert M. Golub, MD, Senior Editor.
JAMA. 2007;298:1160-1162.
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati  Twitter
What's this?
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
Will Running the Numbers First Violate the Principles of Patient-Centered Care?
Boyd and Leff
ANN INTERN MED 2008;149:838-839.
FULL TEXT
|
