Annals
Established in 1927 by the American College of Physicians
:
Advanced search
box Article
 arrow  Table of Contents                
space
 arrow  Abstract of this article Free
space
 arrow  PDF of this article
(PDFs free after 6 months)
space
 arrow  Figures/Tables List
space
 arrow  Related articles in Annals
space
box Services
 arrow 
pier article
Related Clinical
Content
space
 arrow  Send comment/rapid response letter
space
 arrow  Published comments/rapid response letters
space
 arrow  Notify a friend about this article
space
 arrow  Alert me when this article is cited
space
 arrow  Add to Personal Archive
space
 arrow  Download to Citation Manager
space
 arrow  ACP Search                        
space
 arrow  Get Permissions
space
box PubMed
Articles in PubMed by Author:
  arrow  Wilper, A. P.
space
  arrow  Himmelstein, D. U.
space
 arrow  PubMed                        
space

ARTICLE

A National Study of Chronic Disease Prevalence and Access to Care in Uninsured U.S. Adults

right arrow Andrew P. Wilper, MD, MPH; Steffie Woolhandler, MD, MPH; Karen E. Lasser, MD, MPH; Danny McCormick, MD, MPH; David H. Bor, MD; and David U. Himmelstein, MD

5 August 2008 | Volume 149 Issue 3 | Pages 170-176

Background: No recent national studies have assessed chronic illness prevalence or access to care among persons without insurance in the United States.

Objective: To compare reports of chronic conditions and access to care among U.S. adults, by self-reported insurance status.

Design: Population-based survey.

Setting: National Health and Nutritional Examination Survey (1999–2004).

Participants: 12 486 patients age 18 to 64 years.

Measurements: Estimates of national rates of cardiovascular disease, hypertension, diabetes, hypercholesterolemia, active asthma or chronic obstructive pulmonary disease, previous cancer, and measures of access to care.

Results: On the basis of National Health and Nutrition Examination Survey (1999–2004) responses, an estimated 11.4 million (95% CI, 9.8 million to 13.0 million) working-age Americans with chronic conditions were uninsured, including 16.1% (CI, 12.6% to 19.6%) of the 7.8 million with cardiovascular disease, 15.5% (CI, 13.4% to 17.6%) of the 38.2 million with hypertension, and 16.6% (CI, 13.2% to 20.0%) of the 8.5 million with diabetes. After the authors controlled for age, sex, and race or ethnicity, chronically ill patients without insurance were more likely than those with coverage to have not visited a health professional (22.6% vs. 6.2%) and to not have a standard site for care (26.1% vs. 6.2%) but more likely to identify their standard site for care as an emergency department (7.1% vs. 1.1%) (P <0.001 for all comparisons).

Limitation: The study was cross-sectional and used self-reported insurance and disease status.

Conclusion: Millions of U.S. working-age adults with chronic conditions do not have insurance and have poorer access to medical care than their insured counterparts.



Editors' Notes
space
up arrowTop
dotEditors' Notes
down arrowMethods
down arrowResults
down arrowDiscussion
down arrowAuthor & Article Info
down arrowReferences

Context

  • Although many Americans lack health insurance, some policymakers claim that persons without insurance are largely healthy. However, the rates of chronic illness among those without insurance have not been well documented.

Contribution

  • By using data from the National Health and Nutrition Examination Survey (1999–2004), this study estimates that more than 11 million working-age Americans with cardiovascular disease, hypertension, diabetes, dyslipidemia, obstructive lung disease, or previous cancer do not have health insurance. Individuals without health insurance were more likely than those with insurance to report problems with access to health care.

Implication

  • Many uninsured Americans have health conditions that require ongoing care.

—The Editors

 

The number of Americans without insurance increased from 31 million in 1987 to 47 million in 2006 (1, 2). Policymakers, including President George W. Bush, have cited the youthfulness and presumed health of those without insurance (3–5), and some have argued that the predicament of uninsured persons is often voluntary and rarely consequential (6).

Chronic illnesses, such as diabetes mellitus, coronary artery disease, and hypertension, are highly prevalent in the United States. Modern therapies for these conditions extend life and minimize disabling complications (7–11).

Fragmentary data suggest that lack of health insurance may worsen care of chronic illness. A medically indigent population in California had deterioration in blood pressure control and self-reported health status after their Medicaid coverage was discontinued (12). Persons without health insurance may be more likely to skip medications, use the emergency department, and be hospitalized (13, 14). Outcomes are worse among uninsured patients with breast cancer (15). Among a cohort of persons age 55 to 64 years, not having coverage increased death rates and the cost of care after age 65 years (16, 17). Lack of coverage has been correlated with undiagnosed and uncontrolled hypertension, elevated cholesterol levels, stroke, and death (18, 19). However, to our knowledge, no study has drawn a more complete picture of the burden of chronic physical illness in the uninsured population in the United States as a whole.

We analyzed interview data from a nationally representative sample of working-age Americans to explore the relationship of common chronic illnesses to health insurance and access to care.


Methods
space
up arrowTop
up arrowEditors' Notes
dotMethods
down arrowResults
down arrowDiscussion
down arrowAuthor & Article Info
down arrowReferences

Data Source

To evaluate individuals age 18 to 64 years in the United States, we used 6 years of data (1999–2004) from the continuous NHANES (National Health and Nutrition Examination Survey), which is conducted during 2-year intervals. The National Center for Health Statistics conducts NHANES, which is designed to assess the health and nutrition status of the noninstitutionalized U.S. population. The survey is conducted in English and Spanish and includes interviews, physical examinations, and laboratory testing. Because almost all persons older than age 64 years are eligible for Medicare, we excluded participants in this age group.

We compiled 3 cycles of data in order to bolster sample size. We created a final 6-year weight by assigning two-thirds weight to individuals surveyed during 1999 to 2002 and by assigning one-third weight to individuals surveyed from 2003 to 2004 (20). The weights used in NHANES adjust for the complex survey design, nonresponse, oversampling of low-income individuals and minorities, and poststratification to yield nationally representative estimates. All analyses account for the survey's complex design (that is, weights, stratification, and clustering).

Staff members for NHANES interview respondents in their homes about demographic variables (including health insurance), medical conditions, and 3 measures of access to care, which include having a place to go when sick or in need of medical advice, having a standard site of medical care, and the number of visits to a physician or health care professional in the past 12 months. Details about the NHANES methods are available elsewhere (21).

From 1999 to 2004, NHANES selected 38 086 persons for the sample; 31 126 of those participated in interviews. At the time of the interview, 12 712 were age 18 to 64 years and 12 486 reported health insurance status (Figure).


Figure 1
View larger version (53K):
[in this window]
[in a new window]

 
Figure. Study flow diagram.

NHANES = National Health and Nutrition Examination Survey.

 

We included conditions in our study on the basis of 2 criteria: a diagnosis that would probably require a need for medical care follow-up and robust data on the condition (collected by NHANES). We used questionnaire data to classify participants as having cardiovascular disease (CVD), obstructive pulmonary disease, or cancer. We considered a person to have CVD if they reported coronary heart disease, angina or angina pectoris, heart attack, heart failure, or stroke. We classified participants confirming active asthma, chronic bronchitis, or a history of emphysema as having active obstructive pulmonary disease. We considered participants to have had previous cancer if they reported any previous cancer (other than nonmelanoma skin cancer).

To establish rates of diabetes, hypertension, and hypercholesterolemia, we combined questionnaire data on previous diagnoses with that on current medication use. For instance, we considered participants to have diabetes if a physician had informed them that they had "sugar diabetes" or if they were receiving insulin or an oral hypoglycemic drug.

Similarly, we defined participants as hypertensive if they reported being told by a medical professional that they had high blood pressure or if they were taking an antihypertensive medication. We identified antihypertensive drugs by using the U.S. Food and Drug Administration National Drug Code Directory Formulation Data File and Drug Class Data File for 1999 to 2002 and the Lexicon Plus proprietary database (Cerner Multum, Denver, Colorado) for 2003 to 2004. A 5-member panel of board-certified internists reviewed a list of antihypertensive medications and determined which drugs were usually prescribed for hypertension (for example, hydrochlorothiazide) and others that have several uses (for example, diltiazem). We did a sensitivity analysis defining hypertension with and without inclusion of the multiuse drugs and ultimately excluded these drugs because they had little effect on our results.

We defined participants as hypercholesterolemic if they reported that a health professional had informed them that they had high cholesterol or they were taking a statin, a bile acid sequestrant, or ezetimibe.

Next, we counted the number of chronic conditions that each respondent had and determined the proportion who reported having no health insurance. The NHANES determined participants' self-reported insurance status on the basis of a single question: "Are you covered by health insurance or some other kind of health care plan? Include health insurance obtained through employment or purchased directly as well as government programs like Medicare and Medicaid that provide medical care or help pay medical bills." We excluded nonrespondents (1.8% of nonelderly adults). Individuals reporting insurance coverage who answered questions about insurance type—including private insurance, Medicare, Medicaid or Children's Health Insurance Program, other government insurance, or any single service plan (that is, paying for only 1 type of service, such as nursing home or dental care)—and not having insurance in the past year. The Appendix Table shows a complete list of the survey questions.


View this table:
[in this window]
[in a new window]

 
Appendix Table. Survey Questions Used to Establish Study Variables*{webonly}

 

Statistical Analysis

We used NHANES interview weights to produce national estimates. To account for the complex sample design, we used SAS software, version 9.1 (SAS Institute, Cary, North Carolina); PROC SURVEYFREQ (SAS Institute) to generate percentages and chi-square tests; and the PROC RLOGIST procedure (SUDAAN, version 9.0.3, Research Triangle Institute, Research Triangle Park, North Carolina) for multiple logistic regression.

We stratified participants with each chronic medical condition by the presence of self-reported health insurance. By using logistic regression, we first tested the validity of combining several survey years by examining whether year of participation predicted health insurance status. We evaluated the relationship between having any of the 6 chronic conditions (CVD, hypertension, obstructive pulmonary disease, diabetes, previous cancer, or hypercholesterolemia) and the likelihood of having health insurance, controlling for age, sex, and race or ethnicity (defined as non-Hispanic white, non-Hispanic black, Hispanic, and other). In subsidiary analyses, we controlled for annual household income. Income data were missing for 8.7% of participants; these individuals were less likely to have insurance than those who reported income (25.7% vs. 20.8%; chi-square, 9.95; P = 0.002).

We then used multiple logistic regression to produce predictive margins adjusted for age, sex, and race or ethnicity to determine whether health insurance status was associated with differences in measures of access to care. In a subsidiary analysis, we controlled for income. Predictive margins are a type of direct standardization that average predicted values from logistic regression models across the covariate distribution in the sample. We analyzed subsamples to produce predictive margins, such that these results reflect only the subsamples studied (that is, they compare access measures only among those with CVD). Estimates in the insured group could be interpreted as the average predicted outcome if every individual in the sample had insurance; estimates in the uninsured group could be interpreted as the average predicted outcome if every individual in the sample did not have insurance (22).

Role of the Funding Source

This study was funded by a Health Service Administration National Research Service Award and approved by the institutional review board at Cambridge Health Alliance. The funding source had no role in the design, conduct, or presentation of this study.


Results
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
dotResults
down arrowDiscussion
down arrowAuthor & Article Info
down arrowReferences

Demographic Characteristics and Health Insurance Status

A total of 12 486 nonelderly adults who participated in NHANES also reported their health insurance status. Of those interviewed, 50.9% (95% CI, 50.0% to 51.9%) were women, 68.4% (CI, 65.0%, to 71.9%) were non-Hispanic white, 11.6% (CI, 9.5% to 13.7%) were non-Hispanic black, 8.3% (CI, 6.5% to 10.1%) were Mexican American, 6.2% (CI, 3.9% to 8.4%) were other Hispanic, and 5.4% (CI, 4.4% to 6.5%) were other race or ethnicity (Table 1).


View this table:
[in this window]
[in a new window]

 
Table 1. Demographic Characteristics and Self-Reported Insurance Status of U.S. Adults Age 18 to 64 Years*

 

On the basis of the responses from NHANES, we estimate that 20.8% of nonelderly adults in the United States did not have insurance (36.4 million [CI, 40.0 million to 33.1 million]), a figure consistent with estimates from the U.S. Census Bureau (23–25). Among those reporting insurance coverage, 87.9% (CI, 86.7% to 89.1%) were covered by private insurance, 3.2% (CI, 2.4% to 3.9%) by Medicare, 6.7% (CI, 5.8% to 7.7%) by Medicaid or Children's Health Insurance Program, and 4.9% (CI, 4.0% to 5.9%) by other government insurance.

Prevalence of Chronic Conditions

An estimated 11.4 million working-age Americans with chronic conditions were uninsured, including 16.1% of the 7.8 million with CVD, 15.5% of the 38.2 million with hypertension, and more than 16.6% of the 8.5 million with diabetes. Among persons without insurance, 31.3% (CI, 28.7% to 34.0%) had at least 1 of the 6 chronic illnesses, a rate less than that of those with insurance (45.4% [CI, 43.6% to 47.1%]), presumably reflecting the lower average age of persons without insurance. After adjusting for sex, age, and race or ethnicity, this difference narrowed substantially to 38.0% (CI, 35.0% to 41.1) versus 43.5% (CI, 41.5% to 45.5%) (Table 2).


View this table:
[in this window]
[in a new window]

 
Table 2. Prevalence of 6 Chronic Conditions, by Self-Reported Insurance Status, among U.S. Adults Age 18 to 64 Years*

 

Comorbid Conditions

Comorbid conditions were common. We estimate that nearly 1 in 5 nonelderly adults (17.5%) had a history of at least 2 chronic conditions, whereas 6.0% had 3 or more (Table 3).


View this table:
[in this window]
[in a new window]

 
Table 3. Prevalence of Any of 6 Chronic Conditions and Self-Reported Insurance Status among U.S Adults Age 18 to 64 Years*

 

Likelihood of Having Insurance

After age, race or ethnicity, sex, and income were controlled for, persons with a chronic illness were statistically significantly more likely than other Americans to have health insurance (81.6% [CI, 79.6% to 83.6%) vs. 77.1 [75.1% to 79.1%]; P <0.001).

National Estimates of Access to Care and 12-Month Utilization for Chronically Ill Americans

After sex, race or ethnicity, and age were controlled for, chronically ill persons without insurance were more likely than those with insurance to have not visited a health professional in the past year (22.6% vs. 6.2%) and to not have a standard site for care (26.1% vs. 6.2%) but more likely to identify a standard site for care as an emergency department (7.1% vs. 1.1%). Further adjustment for income did not alter these findings. The remaining results in Table 4 estimate access measures for the subgroup in each row.


View this table:
[in this window]
[in a new window]

 
Table 4. Indicators of Poor Access to Care among U.S. Adults Age 18 to 64 Years, and Predictive Margins*

 


Discussion
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
up arrowResults
dotDiscussion
down arrowAuthor & Article Info
down arrowReferences

Chronic illness is common among persons without insurance. We identified individuals without insurance who had a previous diagnosis of cardiovascular disease (1.3 million), hypertension (5.9 million), diabetes (1.4 million), hypercholesterolemia (4.0 million), active asthma or chronic obstructive pulmonary disease (3.5 million), and previous cancer (1.1 million). We estimate that nearly one third of nonelderly U.S. adults without insurance (that is, 11.4 million individuals) had at least 1 chronic condition. These findings counter notions that persons without insurance are a largely healthy population with little need for ongoing medical care.

On the basis of NHANES responses, access to health care seems to be systematically worse for persons without insurance than for those with coverage. Chronically ill persons without insurance are less likely to have visited a physician in the past 12 months or have a standard source of care but are more likely to report using an emergency department as a standard site for care. Even after sociodemographic confounders were controlled for, persons without insurance were 4 to 6 times more likely to have each of these 3 access problems. Many of these individuals probably cannot obtain standard medical care to control chronic conditions because they do not have health insurance.

Why do so many working-age Americans lack health insurance? The decreasing size of many U.S. companies, the increasing role of service sector jobs, and the decline in manufacturing jobs have steadily eroded employer-sponsored coverage. Increasing premiums discourage companies from offering coverage; discourage uptake among workers required to pay a share of premium costs; and make insurance particularly unaffordable for self-employed persons, especially if they have a chronic illness (26).

Persons without insurance are typically less affluent than those who have it and face substantially higher costs in both absolute and relative terms when using health care. Low-cost or free services, if available, may be at locations, times, or settings that discourage uptake. These barriers lead to diminished access to care that negatively affects health-related outcomes, an effect that may be pronounced among individuals with chronic disease (27).

A MEDLINE search of studies published in English until January 2008 shows that many researchers have analyzed the health effects of not having insurance (12–19). To our knowledge, only 1 study has examined the burden of chronic conditions among the uninsured population as a whole (28). Compared with data from the Behavior Risk Factor Surveillance System, our results suggest an increase in the proportion of patients who had hypertension (≥34%), diabetes (≥51%), and hypercholesterolemia (≥49%) and were uninsured from 1997 to 1998. However, these increases should be interpreted with caution, given the different survey methodologies.

Our study has several limitations. We could not verify self-reported insurance status. However, our estimate of those without insurance is virtually identical to that generated from the Current Population Survey, the standard source for rates of coverage in the United States. The NHANES' exclusion of individuals who do not speak English or Spanish may lead to an underestimate of the number of persons without insurance. Because NHANES does not review medical records, recall bias may cause understatement of the overall prevalence of diagnosed disease. Persons without insurance may be less likely to recall a previous diagnosis because of longer intervals between their visits with health care professionals. However, in our experience, most cognitively intact patients react strongly to new diagnoses, such as diabetes, and are likely to remember them.

Our results probably underestimate the health problems of persons without insurance because those without insurance are less likely to be aware of their illnesses (18). We could not analyze depression or other chronic mental health conditions because NHANES does not query participants about them. Finally, we could not include health insurance plan details (that is, cost sharing) and duration of coverage.

Given the limited access to care among those without insurance, undiagnosed conditions in this population may be common. Future research should evaluate rates of undiagnosed illness and disease control among persons without insurance. Research should also determine whether extending health insurance to chronically ill persons reduces use of the emergency department as a standard site for care. Most important, research and advocacy should focus on ways to expand health insurance coverage.

Substantial proportions of persons with and without insurance have a history of at least 1 of the conditions identified in our study. Among chronically ill persons, lack of health insurance is strongly associated with poor measures of access to care. For some of the 11.4 million uninsured Americans with serious chronic conditions, access to care seems to be unobtainable; many may face early disability and death as a result.

Treatment of the chronic conditions we studied has become both the standard of care (10, 29–31) and a national priority (32). The benefits of treatment are so clear that studies evaluating new treatments of these conditions are ethically bound to provide control participants with standard therapies. The same ethical consideration has not been extended to those without insurance.


Author and Article Information
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
up arrowResults
up arrowDiscussion
dotAuthor & Article Info
down arrowReferences

From Cambridge Health Alliance/Harvard Medical School, Cambridge, Massachusetts.

Acknowledgment: The authors thank John Z. Ayanian, MD, and Sarah Hollopeter, MD, for their comments on an earlier draft of the manuscript, and Amy Cohen, Manager of Instructional Computing, Harvard School of Public Health, for her help with statistical software.

Grant Support: By Health Resources and Service Administration National Research Service Award 5T32 HP110011 (Dr. Wilper).

Potential Financial Conflicts of Interest: None disclosed.

Reproducible Research Statement: Study protocol: The NHANES methodology is available from the Centers for Disease Control and Prevention (http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm.) Statistical code and data set: Available from Dr. Wilper (e-mail, awilper{at}hsph.harvard.edu).

Requests for Single Reprints: Andrew P. Wilper, MD, Cambridge Health Alliance/Harvard Medical School, 1493 Cambridge Street, Cambridge, MA 02139; e-mail, awilper{at}hsph.harvard.edu.

Current Author Addresses: Drs. Wilper, Woolhandler, Lasser, McCormick, Bor, and Himmelstein: Cambridge Health Alliance/Harvard Medical School, 1493 Cambridge Street, Cambridge, MA 02144.

Author Contributions: Conception and design: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.H. Bor, D.U. Himmelstein.

Analysis and interpretation of the data: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.U. Himmelstein.

Drafting of the article: A.P. Wilper, S. Woolhandler.

Critical revision of the article for important intellectual content: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.H. Bor, D.U. Himmelstein.

Final approval of the article: A.P. Wilper, S. Woolhandler, K.E. Lasser, D. McCormick, D.H. Bor, D.U. Himmelstein.

Statistical expertise: A.P. Wilper, S. Woolhandler, D.U. Himmelstein.

Obtaining of funding: D.H. Bor.

Administrative, technical, or logistic support: A.P. Wilper.

Collection and assembly of data: A.P. Wilper.


References
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
up arrowResults
up arrowDiscussion
up arrowAuthor & Article Info
dotReferences

1. U.S. Census Bureau. Current Population Survey, 1988 to 2006 Annual Social and Economic Supplements. Historical Health Insurance Tables. Accessed at http://www.census.gov/hhes/www/hlthins/historic/hlthin05/hihistt7.html on 20 December 2007.

2. U.S. Census Bureau. Current Population Survey, 2000 to 2007 Annual Social and Economic Supplements. Historical Health Insurance Tables. Accessed at http://www.census.gov/hhes/www/hlthins/historic/hihistt2.html on 20 December 2007.

3. Economic Report of the President. Transmitted to Congress February 2004. Chapter 10, page 197. Accessed at http://www.gpoaccess.gov/usbudget/fy05/pdf/2004_erp.pdf on 20 December 2007.

4. Cannon MF. "Cover the Uninsured Week"—With Honesty. Washington, DC: Cato Institute; 2004. Accessed at http://www.cato.org/pub_display.php?pub_id=2657 on 15 August 2007.

5. Westerfield DL. Insuring the Uninsured Through Association Health Plans. Washington, DC: National Center for Policy Analysis; 2003. Accessed at http://www.ncpa.org/pub/st/st259/ on 8 August 2007.

6. President Bush Visits Cleveland, Ohio. Accessed at http://www.whitehouse.gov/news/releases/2007/07/20070710-6.html on 8 August 2007.

7. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. 1993;329:977-86. [PMID: 8366922].[Abstract/Free Full Text]

8. Mortality findings for stepped-care and referred-care participants in the hypertension detection and follow-up program, stratified by other risk factors. The Hypertension Detection and Follow-up Program Cooperative Research Group. Prev Med. 1985;14:312-35. [PMID: 2865725].[Medline]

9. Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ. 2000;321:405-12. [PMID: 10938048].[Abstract/Free Full Text]

10. Capewell S, Morrison CE, McMurray JJ. Contribution of modern cardiovascular treatment and risk factor changes to the decline in coronary heart disease mortality in Scotland between 1975 and 1994. Heart. 1999;81:380-6. [PMID: 10092564].[Abstract/Free Full Text]

11. Rahimi AR, Spertus JA, Reid KJ, Bernheim SM, Krumholz HM. Financial barriers to health care and outcomes after acute myocardial infarction. JAMA. 2007;297:1063-72. [PMID: 17356027].[Abstract/Free Full Text]

12. Lurie N, Ward NB, Shapiro MF, Gallego C, Vaghaiwalla R, Brook RH. Termination of Medi-Cal benefits. A follow-up study one year later. N Engl J Med. 1986;314:1266-8. [PMID: 3517642].[Medline]

13. Collins S. Gaps in Health Insurance: An All-American Problem. In: Findings From the Commonwealth Fund Biennial Health Insurance Survey; 2006. Accessed at http://www.cmwf.org/usr_doc/Collins_gapshltins_920.pdf on 20 July 2007.

14. Weissman JS, Gatsonis C, Epstein AM. Rates of avoidable hospitalization by insurance status in Massachusetts and Maryland. JAMA. 1992;268:2388-94. [PMID: 1404795].[Abstract]

15. Ayanian JZ, Kohler BA, Abe T, Epstein AM. The relation between health insurance coverage and clinical outcomes among women with breast cancer. N Engl J Med. 1993;329:326-31. [PMID: 8321261].[Abstract/Free Full Text]

16. McWilliams JM, Zaslavsky AM, Meara E, Ayanian JZ. Health insurance coverage and mortality among the near-elderly. Health Aff (Millwood). 2004;23:223-33. [PMID: 15318584].[Abstract/Free Full Text]

17. McWilliams JM, Meara E, Zaslavsky AM, Ayanian JZ. Use of health services by previously uninsured Medicare beneficiaries. N Engl J Med. 2007;357:143-53. [PMID: 17625126].[Abstract/Free Full Text]

18. Ayanian JZ, Zaslavsky AM, Weissman JS, Schneider EC, Ginsburg JA. Undiagnosed hypertension and hypercholesterolemia among uninsured and insured adults in the Third National Health and Nutrition Examination Survey. Am J Public Health. 2003;93:2051-4. [PMID: 14652333].[Free Full Text]

19. Fowler-Brown A, Corbie-Smith G, Garrett J, Lurie N. Risk of cardiovascular events and death—does insurance matter? J Gen Intern Med. 2007;22:502-7. [PMID: 17372800].[Medline]

20. Analytic and Reporting Guidelines. The National Health and Nutrition Examination Survey (NHANES). 2006. Accessed at http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/nhanes_analytic_guidelines_dec_2005.pdf on 21 March 2008.

21. National Center for Health Statistics, Centers for Disease Control and Prevention (CDC). Survey operations manuals, brochures, and consent documents: 1999-current NHANES. Accessed at http://www.cdc.gov/nchs/about/major/nhanes/currentnhanes.htm on 2 April 2008.

22. Korn EL, Graubard BI. Analysis of Health Surveys. (Wiley Series in Probability and Statistics). New York: Wiley; 1999.

23. U.S. Census Bureau, Center for Population Statistics. Health Insurance Coverage Status and Type of Coverage by Selected Characteristics 2000. Accessed at http://pubdb3.census.gov/macro/032001/health/h01_001.htm on 29 June 2007.

24. U.S. Census Bureau, Center for Population Statistics. Health Insurance Coverage Status and Type of Coverage by Selected Characteristics 2002. Accessed at http://pubdb3.census.gov/macro/032003/health/h01_001.htm on 29 June 2007.

25. U.S. Census Bureau, Center for Population Statistics. Health Insurance Coverage Status and Type of Coverage by Selected Characteristics 2004. Accessed at http://pubdb3.census.gov/macro/032005/health/h01_001.htm on 29 June 2007.

26. Swartz K. Reinsuring Health: Why More Middle-class People Are Uninsured and What Government Can Do. New York: Sage; 2006.

27. Institute of Medicine. Care Without Coverage Too Little, Too Late. Washington, DC: National Academy Pr; 2002.

28. Ayanian JZ, Weissman JS, Schneider EC, Ginsburg JA, Zaslavsky AM. Unmet health needs of uninsured adults in the United States. JAMA. 2000;284:2061-9. [PMID: 11042754].[Abstract/Free Full Text]

29. Baigent C, Keech A, Kearney PM, Blackwell L, Buck G, Pollicino C, et al. Cholesterol Treatment Trialists' (CTT) Collaborators. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins. Lancet. 2005;366:1267-78. [PMID: 16214597].[Medline]

30. Suissa S, Ernst P, Benayoun S, Baltzan M, Cai B. Low-dose inhaled corticosteroids and the prevention of death from asthma. N Engl J Med. 2000;343:332-6. [PMID: 10922423].[Abstract/Free Full Text]

31. Sin DD, McAlister FA, Man SF, Anthonisen NR. Contemporary management of chronic obstructive pulmonary disease: scientific review. JAMA. 2003;290:2301-12. [PMID: 14600189].[Abstract/Free Full Text]

32. Geyman JP. Disease management: panacea, another false hope, or something in between? Ann Fam Med. 2007;5:257-60. [PMID: 17548854].[Abstract/Free Full Text]

33. National Health and Nutrition Examination Survey Codebook for Data Production (1999–2000). The Medical Conditions Section of the SP Questionnaire (MCQ). Person Level Data. Accessed at http://www.cdc.gov/nchs/data/nhanes/frequency/mcq.pdf on 11 June 2008.

34. National Health and Nutrition Examination Survey Codebook for Data Production (2001–2002). The Medical Conditions Section of the SP Questionnaire (MCQ_B). Person Level Data. Accessed at http://www.cdc.gov/nchs/data/nhanes/nhanes_01_02/mcq_b_cbk.pdf on 11 June 2008.

35. National Health and Nutrition Examination Survey Codebook for Data Production (2003–2004). Documentation, Codebook, and Frequencies MEC Questionnaire Component: Medical Conditions Questionnaire Data. Accessed at http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/mcq_c.pdf on 11 June 2008.

Related articles in Annals:

Editorials
Improving Care and Outcomes of Uninsured Persons with Chronic Disease ... Now
Marshall H. Chin
Annals 2008 149: 206-208. [Full Text]  



Rapid Responses:

Read all Rapid Responses

Re: A National Study of Chronic Disease Prevalence and Access to Care in Uninsured U.S. Adults
Tim J. Stocker, et al.
Annals Online, 9 Sep 2008 [Full text]

box Article
 arrow  Table of Contents                
space
 arrow  Abstract of this article Free
space
 arrow  PDF of this article
(PDFs free after 6 months)
space
 arrow  Figures/Tables List
space
 arrow  Related articles in Annals
space
box Services
 arrow 
pier article
Related Clinical
Content
space
 arrow  Send comment/rapid response letter
space
 arrow  Published comments/rapid response letters
space
 arrow  Notify a friend about this article
space
 arrow  Alert me when this article is cited
space
 arrow  Add to Personal Archive
space
 arrow  Download to Citation Manager
space
 arrow  ACP Search                        
space
 arrow  Get Permissions
space
box PubMed
Articles in PubMed by Author:
  arrow  Wilper, A. P.
space
  arrow  Himmelstein, D. U.
space
 arrow  PubMed                        
space


 Home | Current Issue | Past Issues | In the Clinic | ACP Journal Club | CME | Collections | Audio/Video | Mobile | Subscribe | Tools | Help | ACP Online