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Original Investigation | Socioeconomics and Health Services

Socioeconomic Disparity in Use of Eye Care Services Among US Adults With Age-Related Eye Diseases:  National Health Interview Survey, 2002 and 2008 FREE

Xinzhi Zhang, MD, PhD1; Gloria L. Beckles, MD, MSc2; Chiu-Fang Chou, PhD2; Jinan B. Saaddine, MD, MPH2; M. Roy Wilson, MD, MPH1; Paul P. Lee, MD, JD3; Nair Parvathy, MD2; Asel Ryskulova, MD4; Linda S. Geiss, MS2
[+] Author Affiliations
1National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland
2National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
3Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor
4National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland
JAMA Ophthalmol. 2013;131(9):1198-1206. doi:10.1001/jamaophthalmol.2013.4694.
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Published online

Importance  Individuals with age-related eye disease (ARED) need to use eye care services for detection, assessment, and care at regular intervals.

Objective  To explore the association between socioeconomic position (SEP) and use of eye care services among US adults with self-reported ARED during 2002 and 2008.

Design  Data were from the National Health Interview Survey 2002 and 2008. We used multiple logistic regression to estimate predictive margins, controlling for other factors, and we used the slope index of inequality to measure the relationship between SEP and use of eye care services across the entire distributions of poverty-income ratio (PIR) and educational attainment.

Setting  A cross-sectional, nationally representative sample of adults, with prevalence estimates weighted to represent the civilian, noninstitutionalized US population.

Participants  The sample included US participants in the 2002 (n = 3586) and the 2008 (n = 3104) National Health Interview Survey who were at least 40 years old and reported any ARED (age-related macular degeneration, cataract, diabetic retinopathy, or glaucoma).

Main Outcomes and Measures  Use of eye care services; SEP was measured by the PIR and educational attainment.

Results  In 2002, persons with ARED and a PIR of less than 1.50 were significantly less likely than those with a PIR of at least 5 to report visiting an eye care provider (62.7% vs 80.1%; P < .001) or undergoing a dilated eye examination in the past 12 months (64.3% vs 80.4%; P < .001), after adjustment for other factors. Similarly, persons with less than a high school education were less likely than those with at least a college education to report a visit to an eye care provider (62.9% vs 80.8%; P < .001) or dilated eye examination (64.8% vs 81.4%; P < .001). In 2002, the slope index of inequality showed statistically significant differences for eye care provider visits across the levels of education (24.4; P = .006), and in 2008, it showed a significant difference for eye care provider visits across the levels of educational attainment (25.2; P = .049) and PIR (21.8; P = .01).

Conclusions and Relevance  Significant differences in the use of eye care services by SEP persist among US adults with eye diseases.

Age-related eye disease (ARED), particularly age-related macular degeneration, cataract, diabetic retinopathy, and glaucoma, is the most common cause of visual impairment among adults in the United States15 and results in a substantial economic burden to society.6 In 2004, approximately 1 in 28 Americans at least 40 years old reported blindness or low vision even with optical correction.1 Visual impairment often affects the performance of daily activities,7,8 causes falls and injuries,9,10 social isolation and depression,11,12 the loss of productivity,13,14 and, in some cases, even premature death.1518

Advances in the past few decades have made vision loss due to these conditions preventable, treatable, and, in the case of cataracts, even reversible. To benefit from these interventions, however, individuals must have access to eye care. Routine eye examinations are recommended to prevent or delay vision loss caused by ARED, although guidelines vary for the specific disease and stages. Generally, guidelines recommend at least annual eye assessments for individuals diagnosed with these eye conditions.19,20 Given that a large proportion of American adults do not regularly use eye care services owing to personal choice (eg, because of lack of awareness of the importance of eye care) or access issues (eg, because of cost or lack of insurance for vision care),21,22 systematic and ongoing public health attention in vision loss prevention and eye health promotion have been suggested.23

In September 1990, the Department of Health and Human Services announced Healthy People objectives targeted to improve the overall health of all Americans. During the past 2 decades, Healthy People 2000, Healthy People 2010, and Healthy People 2020 have focused on reducing and possibly eliminating health disparities and achieving health equity.2426 During this time, many efforts have been made to assess health disparities in the US population by tracking rates of mortality, morbidity, health-related risk behaviors, and access to preventive care practice by age, sex, race/ethnicity, spoken language, disability status, and geographic location.27,28

Early detection and timely treatment are key elements for persons with ARED to reduce vision loss and prevent blindness. However, persons with low socioeconomic position (SEP) are more likely to experience health disparities and less likely to use high-quality health care than their wealthier counterparts. Although there are significant disparities found in the use of eye care services by important demographic and socioeconomic groups,22 to our knowledge, none of the previous studies have specifically assessed the variance and trends in use of eye care services of Americans with ARED across the levels of SEP. Identifying eye care disparities is the first step toward their elimination. These findings can inform policymakers and provide evidence for Healthy People objectives. Thus, we explored the association between SEP, as measured by income and educational level, and use of eye care services among US adults with ARED, using the most recent comprehensive vision data from the 2008 National Health Interview Survey (NHIS) and comparing observed disparities with those from the 2002 NHIS.

Data Source

The NHIS is an ongoing national survey conducted by the National Center for Health Statistics, part of the Centers for Disease Control and Prevention, to assess the health of the civilian noninstitutionalized population of the United States (http://www.cdc.gov/nchs/nhis.htm). It uses a stratified, cross-sectional, multistage probability sample to derive estimates for the US population through personal household interviews conducted within the 50 states and District of Columbia. The NHIS gathers data on illnesses, injuries, activity limitation, chronic conditions, health insurance coverage, use of health care, and other health topics.29,30 The NHIS collects health and health-related data about every member in every family in each interviewed household. It also collects additional data from each family about 1 randomly selected child (the “sample child,” ≤17 years old) and 1 randomly selected adult (the “sample adult,” ≥18 years old). Data for the sample child are collected by proxy from a knowledgeable adult, and data for the sample adult are self-reported.

In 2002 and 2008, the NHIS questionnaires included supplementary questions sponsored by the National Eye Institute to evaluate vision health and eye care in the United States and monitor progress toward meeting Healthy People 2010 objectives. We used NHIS data from these 2 years to assess the use of eye care services (visiting an eye care provider or undergoing a dilated eye examination) among subjects with ARED, including self-reported age-related macular degeneration, cataract, diabetic retinopathy, and glaucoma. We restricted our study to US adults at least 40 years old because subjects with self-reported ARED (other than possibly diabetic retinopathy) are markedly infrequent in younger age groups.1 The numbers of sample adults and those with self-reported ARED, respectively, were 18 577 and 3586 for the 2002 NHIS and 13 714 and 3104 for the 2008 NHIS.

Measurements

For this study, the recommended follow-up period for visiting an eye care provider or undergoing a dilated eye examination was defined according to the recommended follow-up period stated in disease-specific guidelines from the American Academy of Ophthalmology and the American Optometric Association.19,20 Although the recommended frequency of comprehensive eye examination including dilation varies by disease and stage of progression and between guidelines from the American Academy of Ophthalmology and the American Optometric Association, in general, at least 1 dilated eye examination is recommended every year. Patients with ARED who responded either “less than 1 month” or “1 to 12 months” to the question “When was the last time you had an eye exam in which the pupils were dilated?” were categorized as having undergone a dilated eye examination in the past 12 months. Another indicator used to measure use of eye care service was visits to an eye care provider in the past 12 months. Subjects categorized as reporting a visit to an eye care provider were those who answered yes to the question, “During the past 12 months … have you seen or talked to any of the following health care providers about your own health? … An optometrist, ophthalmologist, or eye doctor (someone who prescribes eyeglasses).” These 2 measures were selected because they comprise an effective measure of access to eye care.

The main independent variables of interest were poverty-income ratio (PIR) and educational attainment, both of which are commonly used as measures to assess the influence of socioeconomic circumstances on health.31 The imputed income files of NHIS 2002 and 2008 were used for income analysis as recommended by the National Center for Health Statistics. The PIR is an index that compares the family income with the poverty threshold established by the Census Bureau; it depends on the size of the family and is adjusted for inflation every year.32 A score of 1 is the federal poverty threshold, and family income less than 1 is categorized as below poverty. The PIR was categorized in quartiles (<1.50, 1.50 to <3.00, 3.00 to <5.00, and ≥5.00). Educational attainment was categorized as less than high school, high school or General Education Development, some college or associate degree, and college or above. Other covariates included age (40-59, 60-79, or ≥80 years), sex (male or female), race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, or other), and a yes/no covariate for health insurance status at the time of the interview.

Statistical Analysis

All analyses were performed using SAS statistical software, version 9.2 (SAS Institute Inc), with survey software SUDAAN (RTI International) to account for the complex sample design of the NHIS when calculating variance estimates. We used Pearson χ2 tests to compare sociodemographic characteristics of NHIS survey participants in 2002 vs 2008 and t tests to compare the use of eye care services (ie, eye care visits and dilated eye examinations) among adults (≥40 years old) with self-reported ARED in NHIS 2002 vs NHIS 2008 after stratification by income and education subgroups. All tests of significance were 2 tailed, and differences were considered statistically significant at P < .05.

Logistic regression was used to study the association of PIR levels and education groups with use of eye care services after controlling for other factors (age [continuous], sex, race/ethnicity, and health insurance). The dichotomous dependent variables were whether or not the participant had seen an eye care provider in the past 12 months and whether or not he or she had undergone a dilated pupil examination in the past 12 months. The model included PIR quartile or educational levels and the year of the survey, and the 2-way interaction between year and PIR (or educational level) were tested. Taylor linearization was used to calculate predictive margins and their 95% CIs.33 The predictive marginal probabilities within the strata of the socioeconomic indicators were compared by measuring the difference between the highest and lowest levels in PIR and educational categories for each year (2002 and 2008). The difference between 2002 and 2008 was calculated by analyzing the interaction between the survey years and PIR or education groups.

The slope index of inequality (SII) was calculated by using Microsoft Excel software (Microsoft Office Professional Plus 2010, version 14.0.6129.5000; Microsoft Corporation) to analyze the linear change in the use of eye care services over the ordinal levels of PIR or education.34 The SII is defined as the gap in visits to eye care providers and dilated eye examinations between the lowest and the highest SEP, based on the linear relationship between the use of eye care services and SEP across the whole study population. It provides the linear regression coefficient that indicates the absolute change in the proportion of subjects using eye care across the entire distributions of PIR and educational categories.35

Table 1 shows the population characteristics of adults at least 40 years old with self-reported ARED, 3586 participants in 2002 and 3104 in 2008. Cataract was the most common self-reported ARED in this age group, followed by glaucoma, macular degeneration, and diabetic retinopathy.36 There were no statistically significant differences between 2002 and 2008 in the racial/ethnic or sex composition of the population with self-reported ARED. The percentage of participants at least 80 years old was 27.5% in 2008 and 24.1% in 2002. Approximately 22.1% of respondents reported a PIR of at least 5 in 2008 compared with 17.2% in 2002, indicating that the higher-SEP proportion of the NHIS population with ARED grew during these 6 years. Of these respondents with ARED, 20.7% had at least a college education in 2008 compared with 16.5% in 2002. In both 2002 and 2008, approximately 3% of persons with ARED reported not having health insurance.

Table Graphic Jump LocationTable 1.  Selected Population Characteristics in US Adults With Age-Related Eye Diseasesa

Table 2 displays the weighted crude and age-adjusted prevalence of eye care provider visits and dilated eye examinations by PIR and educational levels. In 2002 and 2008, persons with higher PIR were more likely than those with lower income to visit an eye care provider (trend P = .04 for 2002 and .03 for 2008). We did not find a similar trend for dilated eye examination. In 2002, persons with less education were less likely than their counterparts to visit an eye care provider or undergo a dilated eye examination (trend P = .048 and .003, respectively). We did not find statistically significant trends for visits to eye care providers or dilated eye examinations by educational level in 2008. Among respondents with a PIR between 3.00 and less than 5.00, the age-adjusted prevalence for visits to eye care providers was lower in 2008 than in 2002 (67.0% vs 78.1%; P = .04), as was the prevalence for dilated eye examinations (67.4% vs 78.7%; P = .04). Likewise, among those with less than a high school education, the age-adjusted prevalence for eye care provider visits decreased from 56.7% in 2002 to 44.0% in 2008 (P = .04).

Table Graphic Jump LocationTable 2.  Crude and Age-Adjusted Prevalence of Eye Care Use Among US Adults With Age-Related Eye Disease by Socioeconomic Positiona

Table 3 shows the multivariate-adjusted prevalence for having seen an eye care provider in the past 12 months or having undergone a dilated eye examination in the past 12 months by PIR and educational levels among US adults with ARED in 2002 and 2008. In 2002 and 2008, persons with the lowest family income (PIR, <1.5) were significantly less likely than those with the highest family income (PIR, ≥5.0) to have visited an eye care provider in the past 12 months, after adjustment for other factors (both P < .001). The SII indicated that the percentage of the population with recent eye care visits increased from the lowest to the highest PIR level by a mean of 24.1 percentage points in 2002 and 21.8 percentage points in 2008. In 2002 and 2008, persons with less than a high school education were significantly less likely than those with at least a college education to have visited an eye care provider in the past 12 months (both P < .001). The SII for eye care visit by educational level (lowest vs highest) was 24.4 percentage points in 2002 and 25.2 percentage points in 2008. Similarly, in 2002 and 2008, persons with a PIR less than 1.5 were significantly less likely than those with a PIR of at least 5 to have undergone a dilated eye examination in the past 12 months (both P < .001). The SII for dilated eye examination by PIR was 20.4 percentage points in 2002 and 22.9 percentage points in 2008. In 2002 and 2008, persons with less than a high school education were significantly less likely than those with at least a college education to have undergone a dilated eye examination in the past 12 months (both P < .001). The SII for dilated eye examination by educational level was 20.9 percentage points in 2002 and 18.0 percentage points in 2008. After controlling for other factors, we found no statistically significant changes from 2002 to 2008 in the use of eye care services by SEP.

Table Graphic Jump LocationTable 3.  Multivariate-Adjusted Prevalence of Eye Care Use Among US Adults With Age-Related Eye Diseases by Socioeconomic Positiona

Additional stratified analyses revealed significant differences in the use of eye care services by SEP among persons with age-related macular degeneration, cataract, or glaucoma (Table 4). These differences did not change from 2002 to 2008. Among persons with diabetic retinopathy, the difference in prevalence of recent dilated eye examination between the lowest and highest income levels did not change significantly between 2002 and 2008 (P = .54), but the differences between the lowest and highest educational levels did (P = .04).

Table Graphic Jump LocationTable 4.  Multivariate-Adjusted Prevalence of Recent Dilated Eye Examination Among US Adults by Socioeconomic Position and Eye Diseasea

In this study, we found considerable differences in the use of eye care services by SEP; such use decreased progressively with increasing socioeconomic disadvantage. This finding adds to the general literature on the strong influence of socioeconomic circumstance on an individual’s health status.37 Moreover, a close analysis of the association between the use of eye care services and SEP showed that the inequalities in use, between the extremes of the income and education distributions and averaged across the cumulative distributions of the population, were sustained from 2002 to 2008.

Our findings are, unsurprisingly, consistent with the summary of the recent National Healthcare Disparities Report prepared by the Agency for Healthcare Research and Quality,38 which concludes that although quality is improving, access and disparities are not improving. Despite the efforts of the Healthcare Research and Quality Act of 199939 and the focus of Healthy People on eliminating health disparities, we observed persistent socioeconomic disparities in eye care, as was also revealed in other areas by the Healthy People 2010 midcourse review.40

Health disparities may appear when there are differences in health outcomes based on individual-level characteristics such as sex, race/ethnicity, SEP, spoken language, disability status, and geographic location. To reduce vision loss and promote eye health, individuals with ARED need to access the health care system for detection, assessment, and care at regular intervals. Many issues affect the use of eye care services, including an individual’s ability to pay for the services, accessibility of eye care professionals and facilities, vision and eye care insurance coverage, high insurance deductibles, provider and patient education, and beliefs about health.41 However, we found that eye care in the United States is suboptimal, especially among low-SEP groups. This calls for continued efforts to improve access to and use of eye care services among socioeconomically disadvantaged groups.

Because income and educational level are important social determinants of health,42 social policy as well as health care policy may be needed to further address and eliminate SEP-related health disparities. Higher incomes or educational levels are probably associated with better health status, outcomes, and access to care.35,43,44 Special attention to the persistent disparities in eye care in the United States is warranted, especially because our findings suggest a great need among persons with critical clinical conditions (ie, ARED). To make matters worse, the country has experienced an economic slowdown in recent years, which may further reduce the use of eye care services and widen existing disparities in access to health care. The economic slowdown in the United States was initially manifested by its effect on the stock, credit, and housing markets and later compounded by the loss of employment. Because most Americans obtain health insurance coverage through their employment benefits, the loss of employment often affects their (and their families’) access to health care. Individuals with ARED tend to be older and require regular eye examinations including dilation and hence would be more affected if services were needed but not affordable. A survey revealed that 36% of Americans had limited their visits to medical care providers because of the recession.45 Among all missed visits, the most commonly cited were visits to dentists (63%), primary care physicians (59%), and eye care providers (52%).

Not surprisingly, we found that adults with at least a high school education were relatively more likely to use eye care services than those with less education. A 2005 study indicated that “no reason to go” is the major reason for persons not to see an eye care professional46; this emphasizes the importance of health awareness education to improve the use of eye care services. Interestingly, among persons with diabetic retinopathy, the absolute disparity between the lowest and highest educational levels disappeared in 2008, even though there was a 27–percentage point difference in 2002. Although the conclusion still needs to be confirmed with additional evidence from other national or local data, this finding suggests that it may be possible to reduce or eliminate a health disparity due to SEP by efforts to alter the distribution of health and health care knowledge in the population, in addition to ensuring that health care services are accessible.

To reduce vision-related morbidity and mortality, access to and use of effective and appropriate eye care is important. Under the current health care financing and delivery system, it is necessary to address both health insurance and employment status to better enhance the likelihood that everyone will have “potential” access.41 It is also important for public health agencies to monitor changes in realized access (ie, use of health care services, outcomes, and satisfaction) to ensure that persons actually enter the health care system in spite of education, language, or geographic barriers.

We used data from the NHIS, a large, complex in-person population survey. As an ongoing survey, it allows us to obtain population-based national estimates to observe changes over time and the potential impact of societal transformation. Such national survey data can be used to assess and monitor disparities in the use of eye care services in the United States. However, most federal administrative and claims data contain varying levels of information on SEP status, and frequently a large proportion of SEP data are missing. Such nonresponse bias may result in underestimated or overestimated findings on disparities. However, our use of imputed income data helped correct for the bias and resulted in lower standard errors.47 It is also important to note that the absolute differences in use found in some groups could be lower than the SII, suggesting that the SII, as the gap in health outcome between the lowest and the highest SEP based on a robust statistical model, could provide a better and gradient estimate that represents the whole distribution across the overall population.

However, our analyses have several limitations. First, because of data limitations, our study did not account for other factors associated with income and education that may have influenced the use of health care services (eg, geographic locations). Second, both the use of eye care services and socioeconomic variables were self-reported, and results are subject to social desirability bias. Although there remains some disagreement between self-report and medical records on the use of eye care services,48,49 subjective judgments on access questions are suggested to be valid.50 Moreover, the survey results from the NHIS are generally considered valid and reliable.51,52 Although our study was restricted to adults at least 40 years old, findings from another study suggest that there are also disparities by SEP in the use of eye care services among children.53 Finally, the NHIS does not include institutionalized individuals, and information related to other minority populations, such as Asian Americans and American Indians, were limited owing to 2002 and 2008 NHIS sample sizes.

In conclusion, health promotion and risk reduction efforts in the past have been focused primarily on racial and ethnic disparities in health and health care. Our current study has demonstrated that there are significant differences by SEP in the use of eye care services among US adults with ARED. There is a need for increased awareness about the relationship between social circumstances and ARED and for more research to determine how income and educational inequalities affect health-seeking behavior at the community and individual level over time. Appropriate and timely public health interventions targeted at adults with low levels of education and income may effectively reduce this continuing disparity in eye care.

Section Editor: Paul P. Lee, MD.

Submitted for Publication: January 31, 2013; final revision received April 2, 2013; accepted April 4, 2013.

Corresponding Author: Xinzhi Zhang, MD, PhD, Division of Data Management and Scientific Reporting, National Institute on Minority Health and Health Disparities, National Institutes of Health, 6707 Democracy Blvd, Ste 800, Bethesda, MD 20892 (xinzhi.zhang@nih.gov).

Published Online: July 18, 2013. doi:10.1001/jamaophthalmol.2013.4694.

Author Contributions: Drs Zhang, Beckles, Chou, Saaddine, Parvathy, and Ryskulova and Ms Geiss had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Zhang, Chou, Saaddine, Parvathy, Ryskulova.

Acquisition of data: Chou, Parvathy.

Analysis and interpretation of data: Chou, Zhang, Beckles, Wilson, Lee, Parvathy, Ryskulova, Geiss.

Drafting of the manuscript: Zhang, Parvathy.

Critical revision of the manuscript for important intellectual content: Zhang, Beckles, Chou, Saaddine, Wilson, Lee, Ryskulova, Geiss.

Statistical analysis: Zhang, Chou, Parvathy, Ryskulova.

Administrative, technical, and material support: Zhang, Beckles, Wilson, Geiss.

Study supervision: Saaddine.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by the National Center for Health Statistics, Centers for Disease Control and Prevention.

Role of the Sponsors: The National Center for Health Statistics designs and conducts the NHIS but was not involved in the analysis or interpretation of the study results or in the preparation of the manuscript. The Division of Diabetes Translation was involved in the design and conduct of the study; in the collection, analysis, and interpretation of the data; and in the preparation, review, and approval of this article before submission.

Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the National Institutes of Health or the Centers for Disease Control and Prevention.

Additional Contributions: We thank the NHIS participants, without whom this study would not be possible.

Correction: This article was corrected online October 9, 2013, for an incorrect term in Methods and a sentence was added to table note “a” in Table 3.

Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States. Arch Ophthalmol. 2004;122(4):477-485.
PubMed   |  Link to Article
Congdon  N, Vingerling  JR, Klein  BE,  et al; Eye Diseases Prevalence Research Group.  Prevalence of cataract and pseudophakia/aphakia among adults in the United States. Arch Ophthalmol. 2004;122(4):487-494.
PubMed   |  Link to Article
Friedman  DS, Wolfs  RC, O’Colmain  BJ,  et al; Eye Diseases Prevalence Research Group.  Prevalence of open-angle glaucoma among adults in the United States. Arch Ophthalmol. 2004;122(4):532-538.
PubMed   |  Link to Article
Zhang  X, Saaddine  JB, Chou  CF,  et al.  Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656.
PubMed   |  Link to Article
Klein  R, Chou  CF, Klein  BE, Zhang  X, Meuer  SM, Saaddine  JB.  Prevalence of age-related macular degeneration in the US population. Arch Ophthalmol. 2011;129(1):75-80.
PubMed   |  Link to Article
Rein  DB, Zhang  P, Wirth  KE,  et al.  The economic burden of major adult visual disorders in the United States. Arch Ophthalmol. 2006;124(12):1754-1760.
PubMed   |  Link to Article
Vu  HT, Keeffe  JE, McCarty  CA, Taylor  HR.  Impact of unilateral and bilateral vision loss on quality of life. Br J Ophthalmol. 2005;89(3):360-363.
PubMed   |  Link to Article
West  SK, Munoz  B, Rubin  GS,  et al; SEE Project Team.  Function and visual impairment in a population-based study of older adults: the SEE project. Invest Ophthalmol Vis Sci. 1997;38(1):72-82.
PubMed
Ivers  RQ, Cumming  RG, Mitchell  P, Attebo  K.  Visual impairment and falls in older adults: the Blue Mountains Eye Study. J Am Geriatr Soc. 1998;46(1):58-64.
PubMed
Ivers  RQ, Norton  R, Cumming  RG, Butler  M, Campbell  AJ.  Visual impairment and risk of hip fracture. Am J Epidemiol. 2000;152(7):633-639.
PubMed   |  Link to Article
Bazargan  M, Hamm-Baugh  VP.  The relationship between chronic illness and depression in a community of urban black elderly persons. J Gerontol B Psychol Sci Soc Sci. 1995;50(2):S119-S127.
PubMed   |  Link to Article
Rovner  BW, Ganguli  M.  Depression and disability associated with impaired vision: the MoVies Project. J Am Geriatr Soc. 1998;46(5):617-619.
PubMed
Fryback  DG, Dasbach  EJ, Klein  R,  et al.  The Beaver Dam Health Outcomes Study: initial catalog of health-state quality factors. Med Decis Making. 1993;13(2):89-102.
PubMed   |  Link to Article
Sharma  S, Brown  GC, Brown  MM,  et al.  Converting visual acuity to utilities. Can J Ophthalmol. 2000;35(5):267-272.
PubMed
Cugati  S, Cumming  RG, Smith  W, Burlutsky  G, Mitchell  P, Wang  JJ.  Visual impairment, age-related macular degeneration, cataract, and long-term mortality: the Blue Mountains Eye Study. Arch Ophthalmol. 2007;125(7):917-924.
PubMed   |  Link to Article
Klein  R, Klein  BE, Moss  SE.  Age-related eye disease and survival: the Beaver Dam Eye Study. Arch Ophthalmol. 1995;113(3):333-339.
PubMed   |  Link to Article
Lee  DJ, Gómez-Marín  O, Lam  BL, Zheng  DD, Caban  A.  Visual impairment and morbidity in community-residing adults: the National Health Interview Survey 1986-1996. Ophthalmic Epidemiol. 2005;12(1):13-17.
PubMed   |  Link to Article
McCarty  CA, Nanjan  MB, Taylor  HR.  Vision impairment predicts 5 year mortality. Br J Ophthalmol. 2001;85(3):322-326.
PubMed   |  Link to Article
American Academy of Ophthalmology. Preferred practice pattern guidelines: comprehensive adult medical eye evaluation, October 2010. http://one.aao.org/CE/PracticeGuidelines/PPP_Content.aspx?cid=64e9df91-dd10-4317-8142-6a87eee7f517. Accessed April 2, 2012.
American Optometric Association. Optometric clinical practice guideline: comprehensive adult eye and vision examination. 2nd ed. http://www.aoa.org/documents/CPG-1.pdf. Published 2005. Accessed April 2, 2013.
Zhang  X, Lee  PP, Thompson  TJ,  et al.  Health insurance coverage and use of eye care services. Arch Ophthalmol. 2008;126(8):1121-1126.
PubMed   |  Link to Article
Zhang  X, Saaddine  JB, Lee  PP,  et al.  Eye care in the United States: do we deliver to high-risk people who can benefit most from it? Arch Ophthalmol. 2007;125(3):411-418.
PubMed   |  Link to Article
Centers for Disease Control and Prevention. Vision Health Initiative: improving the nation's vision health: a coordinated public health approach, 2006. http://www.cdc.gov/visionhealth/pdf/improving_nations_vision_health.pdf. Accessed April 2, 2013.
US Department of Health and Human Services. Healthy People 2010: Understanding and Improving Health.2nd ed. Washington, DC: US Government Printing Office; 2000.
Koh  HK, Piotrowski  JJ, Kumanyika  S, Fielding  JE.  Healthy People: a 2020 vision for the social determinants approach. Health Educ Behav.2011;38(6):551-557.
PubMed   |  Link to Article
US Department of Health and Human Services. Healthy People 2000: National Health Promotion and Disease Prevention Objectives. Rockville, MD: Office of Disease Prevention and Health Promotion; 1991.
Koh  HK.  A 2020 vision for healthy people. N Engl J Med. 2010;362(18):1653-1656.
PubMed   |  Link to Article
US Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Healthy People 2020. http://www.healthypeople.gov/2020/default.aspx. Accessed April 2, 2013.
National Center for Health Statistics. National Health Interview Survey (NHIS). Hyattsville, MD: US Government Printing Office; 2002.
National Center for Health Statistics. 2008 National Health Interview Survey (NHIS): public use data release.ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHIS/2008/srvydesc.pdf. Accessed January 31, 2013.
Beckles  GL, Truman  BI; Centers for Disease Control and Prevention (CDC).  Education and income—United States, 2005 and 2009. MMWR Surveill Summ. 2011;60(suppl):13-17.
PubMed
US Census Bureau. Current population survey: definitions, 2004. http://www.census.gov/cps/about/cpsdef.html. Accessed April 2, 2013.
Korn  EL, Graubard  BI. Analysis of Health Surveys. New York, NY: Wiley; 1999.
Low  A, Low  A.  Measuring the gap: quantifying and comparing local health inequalities. J Public Health (Oxf). 2004;26(4):388-395.
PubMed   |  Link to Article
Kanjilal  S, Gregg  EW, Cheng  YJ,  et al.  Socioeconomic status and trends in disparities in 4 major risk factors for cardiovascular disease among US adults, 1971-2002. Arch Intern Med. 2006;166(21):2348-2355.
PubMed   |  Link to Article
Ryskulova  A, Turczyn  K, Makuc  DM, Cotch  MF, Klein  RJ, Janiszewski  R.  Self-reported age-related eye diseases and visual impairment in the United States: results of the 2002 National Health Interview Survey. Am J Public Health. 2008;98(3):454-461.
PubMed   |  Link to Article
Wilkinson RG, Marmot MG. Social determinants of health: the solid facts. http://site.ebrary.com/lib/alltitles/docDetail.action?docID=10047454. Published 2003. Accessed April 2, 2013.
Agency for Healthcare Research and Quality. 2011 National Healthcare Quality & Disparities Reports. Rockville, MD: Department of Health and Human Services; 2011.
Healthcare Research and Quality Act of 1999. 42 USC 299 §902(g), §913(b)(2) (2012).
US Department of Health and Human Services (HHS). Healthy People 2010 Midcourse Review. Washington, DC: US Government Printing Office; 2006.
Zhang  X, Andersen  R, Saaddine  JB, Beckles  GL, Duenas  MR, Lee  PP.  Measuring access to eye care: a public health perspective. Ophthalmic Epidemiol. 2008;15(6):418-425.
PubMed   |  Link to Article
Marmot  MG, Wilkinson  RG. Social Determinants of Health. New York, NY: Oxford University Press; 1999.
Heck  KE, Parker  JD.  Family structure, socioeconomic status, and access to health care for children. Health Serv Res. 2002;37(1):173-186.
PubMed
Wilensky  GR, Satcher  D.  Don’t forget about the social determinants of health. Health Aff (Millwood). 2009;28(2):w194-w198.
PubMed   |  Link to Article
American Optometric Association. Recession cutting into doctor visits, according to new consumer survey. http://pennsylvania.aoa.org/x13606.xml. Published September 29, 2009. Accessed April 2, 2013.
Bailey  RN, Indian  RW, Zhang  X, Geiss  LS, Duenas  MR, Saaddine  JB; Centers for Disease Control and Prevention.  Visual impairment and eye care among older adults—five states, 2005. MMWR Morb Mortal Wkly Rep. 2006;55(49):1321-1325.
PubMed
Schenker  N, Raghunathan  TE, Chiu  P-L, Makuc  DM, Zhang  G, Cohen  AJ.  Multiple imputation of missing income data in the National Health Interview Survey. J Am Stat Assoc.2006;101(475):924-933.
Link to Article
Beckles  GL, Williamson  DF, Brown  AF,  et al.  Agreement between self-reports and medical records was only fair in a cross-sectional study of performance of annual eye examinations among adults with diabetes in managed care. Med Care. 2007;45(9):876-883.
PubMed   |  Link to Article
MacLennan  PA, McGwin  G  Jr, Searcey  K, Owsley  C.  Medical record validation of self-reported eye diseases and eye care utilization among older adults. Curr Eye Res. 2013;38(1):1-8.
PubMed   |  Link to Article
Neumann  PJ, Palmer  JA, Nadler  E, Fang  C, Ubel  P.  Cancer therapy costs influence treatment: a national survey of oncologists. Health Aff (Millwood). 2010;29(1):196-202.
PubMed   |  Link to Article
National Center for Health Statistics.  National Health Interview Survey: research for the 1995-2004 redesign. Vital Health Stat 2.1999;(126):1-119.
PubMed
National Center for Health Statistics.  Design and estimation for the National Health Interview Survey, 1995-2004. Vital Health Stat 2. 2000;(130):1-31.
PubMed
Zhang  X, Elliott  MN, Saaddine  JB,  et al.  Unmet eye care needs among U.S. 5th-grade students. Am J Prev Med. 2012;43(1):55-58.
PubMed   |  Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1.  Selected Population Characteristics in US Adults With Age-Related Eye Diseasesa
Table Graphic Jump LocationTable 2.  Crude and Age-Adjusted Prevalence of Eye Care Use Among US Adults With Age-Related Eye Disease by Socioeconomic Positiona
Table Graphic Jump LocationTable 3.  Multivariate-Adjusted Prevalence of Eye Care Use Among US Adults With Age-Related Eye Diseases by Socioeconomic Positiona
Table Graphic Jump LocationTable 4.  Multivariate-Adjusted Prevalence of Recent Dilated Eye Examination Among US Adults by Socioeconomic Position and Eye Diseasea

References

Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States. Arch Ophthalmol. 2004;122(4):477-485.
PubMed   |  Link to Article
Congdon  N, Vingerling  JR, Klein  BE,  et al; Eye Diseases Prevalence Research Group.  Prevalence of cataract and pseudophakia/aphakia among adults in the United States. Arch Ophthalmol. 2004;122(4):487-494.
PubMed   |  Link to Article
Friedman  DS, Wolfs  RC, O’Colmain  BJ,  et al; Eye Diseases Prevalence Research Group.  Prevalence of open-angle glaucoma among adults in the United States. Arch Ophthalmol. 2004;122(4):532-538.
PubMed   |  Link to Article
Zhang  X, Saaddine  JB, Chou  CF,  et al.  Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656.
PubMed   |  Link to Article
Klein  R, Chou  CF, Klein  BE, Zhang  X, Meuer  SM, Saaddine  JB.  Prevalence of age-related macular degeneration in the US population. Arch Ophthalmol. 2011;129(1):75-80.
PubMed   |  Link to Article
Rein  DB, Zhang  P, Wirth  KE,  et al.  The economic burden of major adult visual disorders in the United States. Arch Ophthalmol. 2006;124(12):1754-1760.
PubMed   |  Link to Article
Vu  HT, Keeffe  JE, McCarty  CA, Taylor  HR.  Impact of unilateral and bilateral vision loss on quality of life. Br J Ophthalmol. 2005;89(3):360-363.
PubMed   |  Link to Article
West  SK, Munoz  B, Rubin  GS,  et al; SEE Project Team.  Function and visual impairment in a population-based study of older adults: the SEE project. Invest Ophthalmol Vis Sci. 1997;38(1):72-82.
PubMed
Ivers  RQ, Cumming  RG, Mitchell  P, Attebo  K.  Visual impairment and falls in older adults: the Blue Mountains Eye Study. J Am Geriatr Soc. 1998;46(1):58-64.
PubMed
Ivers  RQ, Norton  R, Cumming  RG, Butler  M, Campbell  AJ.  Visual impairment and risk of hip fracture. Am J Epidemiol. 2000;152(7):633-639.
PubMed   |  Link to Article
Bazargan  M, Hamm-Baugh  VP.  The relationship between chronic illness and depression in a community of urban black elderly persons. J Gerontol B Psychol Sci Soc Sci. 1995;50(2):S119-S127.
PubMed   |  Link to Article
Rovner  BW, Ganguli  M.  Depression and disability associated with impaired vision: the MoVies Project. J Am Geriatr Soc. 1998;46(5):617-619.
PubMed
Fryback  DG, Dasbach  EJ, Klein  R,  et al.  The Beaver Dam Health Outcomes Study: initial catalog of health-state quality factors. Med Decis Making. 1993;13(2):89-102.
PubMed   |  Link to Article
Sharma  S, Brown  GC, Brown  MM,  et al.  Converting visual acuity to utilities. Can J Ophthalmol. 2000;35(5):267-272.
PubMed
Cugati  S, Cumming  RG, Smith  W, Burlutsky  G, Mitchell  P, Wang  JJ.  Visual impairment, age-related macular degeneration, cataract, and long-term mortality: the Blue Mountains Eye Study. Arch Ophthalmol. 2007;125(7):917-924.
PubMed   |  Link to Article
Klein  R, Klein  BE, Moss  SE.  Age-related eye disease and survival: the Beaver Dam Eye Study. Arch Ophthalmol. 1995;113(3):333-339.
PubMed   |  Link to Article
Lee  DJ, Gómez-Marín  O, Lam  BL, Zheng  DD, Caban  A.  Visual impairment and morbidity in community-residing adults: the National Health Interview Survey 1986-1996. Ophthalmic Epidemiol. 2005;12(1):13-17.
PubMed   |  Link to Article
McCarty  CA, Nanjan  MB, Taylor  HR.  Vision impairment predicts 5 year mortality. Br J Ophthalmol. 2001;85(3):322-326.
PubMed   |  Link to Article
American Academy of Ophthalmology. Preferred practice pattern guidelines: comprehensive adult medical eye evaluation, October 2010. http://one.aao.org/CE/PracticeGuidelines/PPP_Content.aspx?cid=64e9df91-dd10-4317-8142-6a87eee7f517. Accessed April 2, 2012.
American Optometric Association. Optometric clinical practice guideline: comprehensive adult eye and vision examination. 2nd ed. http://www.aoa.org/documents/CPG-1.pdf. Published 2005. Accessed April 2, 2013.
Zhang  X, Lee  PP, Thompson  TJ,  et al.  Health insurance coverage and use of eye care services. Arch Ophthalmol. 2008;126(8):1121-1126.
PubMed   |  Link to Article
Zhang  X, Saaddine  JB, Lee  PP,  et al.  Eye care in the United States: do we deliver to high-risk people who can benefit most from it? Arch Ophthalmol. 2007;125(3):411-418.
PubMed   |  Link to Article
Centers for Disease Control and Prevention. Vision Health Initiative: improving the nation's vision health: a coordinated public health approach, 2006. http://www.cdc.gov/visionhealth/pdf/improving_nations_vision_health.pdf. Accessed April 2, 2013.
US Department of Health and Human Services. Healthy People 2010: Understanding and Improving Health.2nd ed. Washington, DC: US Government Printing Office; 2000.
Koh  HK, Piotrowski  JJ, Kumanyika  S, Fielding  JE.  Healthy People: a 2020 vision for the social determinants approach. Health Educ Behav.2011;38(6):551-557.
PubMed   |  Link to Article
US Department of Health and Human Services. Healthy People 2000: National Health Promotion and Disease Prevention Objectives. Rockville, MD: Office of Disease Prevention and Health Promotion; 1991.
Koh  HK.  A 2020 vision for healthy people. N Engl J Med. 2010;362(18):1653-1656.
PubMed   |  Link to Article
US Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Healthy People 2020. http://www.healthypeople.gov/2020/default.aspx. Accessed April 2, 2013.
National Center for Health Statistics. National Health Interview Survey (NHIS). Hyattsville, MD: US Government Printing Office; 2002.
National Center for Health Statistics. 2008 National Health Interview Survey (NHIS): public use data release.ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHIS/2008/srvydesc.pdf. Accessed January 31, 2013.
Beckles  GL, Truman  BI; Centers for Disease Control and Prevention (CDC).  Education and income—United States, 2005 and 2009. MMWR Surveill Summ. 2011;60(suppl):13-17.
PubMed
US Census Bureau. Current population survey: definitions, 2004. http://www.census.gov/cps/about/cpsdef.html. Accessed April 2, 2013.
Korn  EL, Graubard  BI. Analysis of Health Surveys. New York, NY: Wiley; 1999.
Low  A, Low  A.  Measuring the gap: quantifying and comparing local health inequalities. J Public Health (Oxf). 2004;26(4):388-395.
PubMed   |  Link to Article
Kanjilal  S, Gregg  EW, Cheng  YJ,  et al.  Socioeconomic status and trends in disparities in 4 major risk factors for cardiovascular disease among US adults, 1971-2002. Arch Intern Med. 2006;166(21):2348-2355.
PubMed   |  Link to Article
Ryskulova  A, Turczyn  K, Makuc  DM, Cotch  MF, Klein  RJ, Janiszewski  R.  Self-reported age-related eye diseases and visual impairment in the United States: results of the 2002 National Health Interview Survey. Am J Public Health. 2008;98(3):454-461.
PubMed   |  Link to Article
Wilkinson RG, Marmot MG. Social determinants of health: the solid facts. http://site.ebrary.com/lib/alltitles/docDetail.action?docID=10047454. Published 2003. Accessed April 2, 2013.
Agency for Healthcare Research and Quality. 2011 National Healthcare Quality & Disparities Reports. Rockville, MD: Department of Health and Human Services; 2011.
Healthcare Research and Quality Act of 1999. 42 USC 299 §902(g), §913(b)(2) (2012).
US Department of Health and Human Services (HHS). Healthy People 2010 Midcourse Review. Washington, DC: US Government Printing Office; 2006.
Zhang  X, Andersen  R, Saaddine  JB, Beckles  GL, Duenas  MR, Lee  PP.  Measuring access to eye care: a public health perspective. Ophthalmic Epidemiol. 2008;15(6):418-425.
PubMed   |  Link to Article
Marmot  MG, Wilkinson  RG. Social Determinants of Health. New York, NY: Oxford University Press; 1999.
Heck  KE, Parker  JD.  Family structure, socioeconomic status, and access to health care for children. Health Serv Res. 2002;37(1):173-186.
PubMed
Wilensky  GR, Satcher  D.  Don’t forget about the social determinants of health. Health Aff (Millwood). 2009;28(2):w194-w198.
PubMed   |  Link to Article
American Optometric Association. Recession cutting into doctor visits, according to new consumer survey. http://pennsylvania.aoa.org/x13606.xml. Published September 29, 2009. Accessed April 2, 2013.
Bailey  RN, Indian  RW, Zhang  X, Geiss  LS, Duenas  MR, Saaddine  JB; Centers for Disease Control and Prevention.  Visual impairment and eye care among older adults—five states, 2005. MMWR Morb Mortal Wkly Rep. 2006;55(49):1321-1325.
PubMed
Schenker  N, Raghunathan  TE, Chiu  P-L, Makuc  DM, Zhang  G, Cohen  AJ.  Multiple imputation of missing income data in the National Health Interview Survey. J Am Stat Assoc.2006;101(475):924-933.
Link to Article
Beckles  GL, Williamson  DF, Brown  AF,  et al.  Agreement between self-reports and medical records was only fair in a cross-sectional study of performance of annual eye examinations among adults with diabetes in managed care. Med Care. 2007;45(9):876-883.
PubMed   |  Link to Article
MacLennan  PA, McGwin  G  Jr, Searcey  K, Owsley  C.  Medical record validation of self-reported eye diseases and eye care utilization among older adults. Curr Eye Res. 2013;38(1):1-8.
PubMed   |  Link to Article
Neumann  PJ, Palmer  JA, Nadler  E, Fang  C, Ubel  P.  Cancer therapy costs influence treatment: a national survey of oncologists. Health Aff (Millwood). 2010;29(1):196-202.
PubMed   |  Link to Article
National Center for Health Statistics.  National Health Interview Survey: research for the 1995-2004 redesign. Vital Health Stat 2.1999;(126):1-119.
PubMed
National Center for Health Statistics.  Design and estimation for the National Health Interview Survey, 1995-2004. Vital Health Stat 2. 2000;(130):1-31.
PubMed
Zhang  X, Elliott  MN, Saaddine  JB,  et al.  Unmet eye care needs among U.S. 5th-grade students. Am J Prev Med. 2012;43(1):55-58.
PubMed   |  Link to Article

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