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Open Access Research article

Sociodemographic Correlates of Eye Care Provider Visits in the 2006–2009 Behavioral Risk Factor Surveillance Survey

Alberto J Caban-Martinez1*, Evelyn P Davila1, Byron L Lam2, Kristopher L Arheart1, Kathryn E McCollister1, Cristina A Fernandez1, Manuel A Ocasio1 and David J Lee1

Author Affiliations

1 Department of Epidemiology & Public Health, University of Miami, Miller School of Medicine, Clinical Research Building, Room 1075, 1120 N.W. 14th Street, 10th Floor (R-669), Miami, FL, 33136, USA

2 Department of Ophthalmology, Miller School of Medicine, University of Miami, Miami, FL, USA

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BMC Research Notes 2012, 5:253  doi:10.1186/1756-0500-5-253


The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1756-0500/5/253


Received:30 December 2011
Accepted:9 May 2012
Published:23 May 2012

© 2012 Caban-Martinez et al.; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Research has suggested that adults 40 years old and over are not following eye care visit recommendations. In the United States, the proportion of older adults is expected to increase drastically in the coming years. This has important implications for population ocular disease burden, given the relationship between older age and the development of many ocular diseases and conditions. Understanding individual level determinants of vision health could support the development of tailored vision health campaigns and interventions among our growing older population. Thus, we assessed correlates of eye care visits among participants of the Behavior Risk Factor Surveillance System (BRFSS) survey. We pooled and analyzed 2006–2009 BRFSS data from 16 States (N = 118,075). We assessed for the proportion of survey respondents 40 years of age and older reporting having visited an eye care provider within the past two years, two or more years ago, or never by socio-demographic characteristics.

Results

Nearly 80% of respondents reported an eye care visit within the previous two years. Using the ‘never visits’ as the referent category, the groups with greater odds of having an ocular visit within the past two years included those: greater than 70 years of age (OR = 6.8 [95% confidence interval = 3.7–12.6]), with college degree (5.2[3.0–8.8]), reporting an eye disease, (4.74[1.1–21.2]), diagnosed with diabetes (3.5[1.7–7.5]), of female gender (2.9[2.1–3.9]), with general health insurance (2.7[1.8–3.9]), with eye provider insurance coverage (2.1[1.5–3.0]), with high blood pressure (1.5[1.1–2.2]), and with moderate to extreme near vision difficulties (1.42[1.11–2.08]).

Conclusion

We found significant variation by socio-demographic characteristics and some variation in state-level estimates in this study. The present findings suggest that there remains compliance gaps of screening guidelines among select socio-demographic sub-groups, as well as provide evidence and support to the CDC’s Vision Health Initiative. This data further suggests that there remains a need for ocular educational campaigns in select socio-demographic subgroups and possibly policy changes to enhance insurance coverage.

Keywords:
Vision Health; Eye Care; Older Adults; Epidemiology; National Survey

Background

The proportion of persons older than 40 years old in the United States is expected to increase drastically in the coming years [1]. This has important implications for population ocular disease burden, given the relationship between older age and the development of many ocular diseases and conditions [2]. Among older adults, impaired visual acuity is generally associated with negative health outcomes, such as decreased functional capacity and quality of life, sometimes impinging on the ability to live an autonomous life [3-6]. Impaired visual acuity has also been associated with an inability to perform both basic and instrumental activities of daily living, including work, driving safely or obtaining a driver’s license, and even an increase risk of falls and other accidental injuries [7-11]. Older adults may also be unaware of impaired vision, given the relatively insidious development of vision change symptoms over time. Therefore, periodic screening eye exams are paramount to identifying vision changes, preventing the progression of visual disorders and rendering appropriate vision care that improves quality of life and functional capacity in our adult populations [12].

The American Academy of Ophthalmology (AAO) and the American Optometric Association (AOA) recommend comprehensive eye examinations by ophthalmologists or optometrists for adults with no signs or risk factors to be conducted as a baseline at the age 40 years [13-15]. Current recommendations by the AOA suggest that 40 to 54 year olds without risk factors should be examined every two to four years, those age 55 to 64 every one to three years, and those over 65 every one to two years. In addition, they recommend that any patient at higher risk for developing disease, based on ocular, medical, or family history should have periodic examinations determined by their individual risk and eye care provider. Understanding the distribution of eye and vision conditions, as well as the sociodemographic correlates of adults who visit eye care providers, may inform eye care efforts and allow for tailored eye care intervention efforts. Therefore we: 1) Examine sociodemographic correlates of eye care provider visits among adults 40 and older; 2) Describe the strength of the association between sociodemographic characteristics associated with eye care provider visit; and 3) Provide state-level prevalence estimates of eye care provider visits.

Methods and Materials

Study Population and Data Source

The Behavioral Risk Factor Surveillance System (BRFSS), developed by the Centers for Disease Control and Prevention (CDC), is an ongoing, state-based, random-digit-dialed telephone survey that collects information on health risk behaviors, preventive health practices, and health care access primarily related to chronic disease and injury among a non-institutionalized, civilian adult population aged 18 years and older [16]. This state-administered survey is comprised of an annual set of core health-related questions asked in all 50 states, the District of Columbia, Guam, Puerto Rico, and the Virgin Islands States, as well as a set of optional modules with specific health-related questions that are fielded by the state, based on priorities and financial resources.

Beginning in 2006, the optional Visual Impairment and Access to Eye Care module was included in the survey to assess prevalence of self-reported visual impairment, eye disease, eye injury, and lack of eye care insurance and eye examination among persons aged 40 years and older. Details about its purpose, sampling methods, data collection, and reporting are available elsewhere [16].

We pooled data from the 2006–2009 BRFSS for all adults aged 40 years and older participating in the Visual Impairment and Access to Eye Care module administered by the following States: Alabama, Alaska, Connecticut, Florida, Georgia, Indiana, Iowa, Missouri, New Mexico, New York, North Carolina, Ohio, Tennessee, Texas, West Virginia and Wyoming (N = 118,075). The median survey cooperation rate from 2006–2009 ranged from 72.1% to 75.0% [16].

Measures

Dependent variable: Eye Care Provider Visit

Participants were asked “When was the last time you had your eyes examined by any doctor or eye care provider?” and responded either within the past month, within the past year, within the past 2 years, 2 or more years ago, or never. We grouped respondents into three outcomes 1) having visited an eye care provider within the past two years, 2) two or more years ago, or 3) never.

Independent variables

Age was categorized into four age groups: 40–49, 50–59, 60–69, and > 70 years old. Additional sociodemographic covariates included: gender, race/ethnicity (grouped as white non-Hispanic, black non-Hispanic, other non-Hispanic, and Hispanic), highest educational attainment (categorized as those reporting less than a high school diploma, a high school diploma, attending some college, or having graduated from college), marital status (categorized as being married/living with a partner, widowed/divorced/separated, or being single).

Participants were also classified based on general health insurance coverage (yes or no), and eye care provider insurance coverage (yes or no). Body mass index (BMI) was based on reported height and weight and was categorized as: (1) neither overweight nor obese [< 25 kg/m2]; (2) overweight [25–29.9 kg/m2]; or (3) obese [> = 30 kg/m2]. Participants were also classified as diabetic or hypertensive if they indicated they were told by a health care professional that they had these conditions.

Survey participants reported on far vision difficulties (categorized as dichotomous “little to none” or “moderate to extreme”), near vision difficulties (also categorized as a dichotomous “little to none” versus “moderate to extreme”), and their eye disease status based on the respondents affirmation to either having been told by a doctor they had cataracts, glaucoma, or age-related macular degeneration (categorized into yes or no if the respondent indicated they had any of the listed ocular diseases).

Statistical Analyses

We analyzed data from individuals who had visited an eye care provider within the past two years, two or more years ago, or never. Prevalence estimates for eye care provider visits and the proportion of participants categorized by frequency of eye care visits across a number of socio-demographic and health-related characteristics are presented in Table 1. Specific state-level prevalence estimates of eye care provider visits are presented in Table 2. A polychotomous logistic regression model with adjustment for survey design tested the association between categories of eye care provider visit frequency and age groups controlling for select socio-demographic characteristics (Table 3).

Table 1. Socio-Demographic Characteristics and Frequency of Reported Eye Care Provider Visit of Adults (≥ age 40)- The 2006–2009 Behavioral Risk Factor Surveillance Survey** (N = 118,075)†

Table 2. State Level Estimates of Frequency of Reporting Eye Care Provider Visit for adults (≥ age 40 years)- The 2006–2009 Behavioral Risk Factor Surveillance Survey (N = 118,075)

Table 3. Polytomous logistic regression for Predictors of Visiting Eye Care Provider for adults (≥ age 40 years)- The 2006–2009 Behavioral Risk Factor Surveillance Survey* (N = 118,075)

All analyses were performed using SPSS 17 Complex Samples for Survey Analysis (SPSS Inc., Chicago, IL, 2008) to account for multiple stages of sampling, stratification, and clustering. An alpha level of 0.05 was considered statistically significant. All analyses in this study were weighted according to the standard procedures for analyzing sample survey data [16]. For pooled prevalence estimates, sample weights were adjusted to account for the aggregation of data over multiple survey years for each state by dividing the original weight by the number of years a state was included in the study period (i.e. Alabama, Georgia, Indiana, Iowa, Missouri, New York, North Carolina, Ohio, Tennessee) [16]. The study protocol was approved by the University of Miami’s Institutional Review Board.

Results

The study population represented an estimated 53.6 million U.S. adults annually from 2006–2009. The prevalence of visiting an eye care provider within the past two years, two or more years ago, or never by sociodemographic characteristics, are presented in Table 1. Overall, 79% (representing an estimated annual 42.6 million U.S. adults 40 years of age of older among all 16 States surveyed) reported visiting an eye care provider within the previous two years, 19% reported two or more years ago, and 2% reported that they had never seen an eye care provider. Over 40% of those who reported visiting an eye care provider two or more years ago were 40 to 49 years old. Over 63% of those who reported never having been to an eye provider fell into this age category, indicating that adults in this age range were less likely to be compliant with screening recommendations. State-level estimates varied slightly across eye care provider visit interval category (Table 2). Respondents residing in Connecticut (82.0% ± 0.8) and New York (82.0% ± 0.5) had the highest prevalence for visiting an eye care provider within the past two years, while respondents from Missouri (73.4% ± 1.0) and New Mexico (75.5% ± 0.8) had the lowest.

Eye care visit within the past two years

In the polytomous multiple logistic regression (See Table 3), using the never visits as the referent category, the strongest associations with report of an ocular visit within the past two years was being greater than 70 years of age relative to 40–49 years (OR = 6.8 [95% confidence interval = 3.7–12.6]), having graduated from college relative to those who did not complete high school (5.2 [3.0–8.8]), having an eye condition (e.g. cataract, glaucoma, and/or age-related macular degeneration) relative to no eye condition (4.74 [1.1–21.2]), having diabetes (3.5 [1.7–7.5]), being female (2.9 [2.1–3.9]), having general health insurance (2.7 [1.8–3.9]), having the availability of eye provider health insurance coverage (2.1 [1.5–3.0]), having high blood pressure (1.5 [1.1–2.2]), and having moderate to extreme near vision difficulties relative to little to moderate difficulties (1.42 [1.11–2.08]).

Eye care visit greater than two years ago

Using the never visits as the referent category, the strongest associations with report of an ocular visit greater than two years ago was being greater than 70 years of age relative to 40–49 years (OR = 3.1 [1.7–5.8]), having graduated from college relative to those who did not complete high school (2.4 [1.4–4.0]), having diabetes (2.2 [1.1–4.8]), being female (2.2 [1.6–3.0]), having general health insurance (1.8 [1.2–2.6]), and having high blood pressure (1.6 [1.1–2.3]).

Discussion

We found significant variation by socio-demographic characteristics and some variation in state-level estimates. Correlates of visiting an eye care provider included: being older (e.g. 70 years of age or older), being female, having higher educational attainment, having general health and eye care insurance, being diagnosed with diabetes or high blood pressure, reporting an eye condition such as cataract, glaucoma, or age-related macular degeneration, and having near vision difficulties. To our knowledge, no previous studies have used multistate-level data to test the association between sociodemographic characteristics and report of eye care provider visit. Our findings are consistent with studies from the Los Angeles Latino Eye Study, which reported that select socio-demographic characteristics are strongly associated with more frequent eye care provider visits among Latinos, for example: age, educational attainment, general health and eye insurance status, and co-morbidities [17].

A visit to an eye care provider within the past two years in this study was associated with a number of variables in our multivariable analysis. Among predisposing variables, older age, female gender, and more education were independently associated with greater use of provider eye care service. These results are consistent with previous research showing that women and older individuals are more likely to use vision health services than their male and younger counterparts [18]. Previous literature has also shown that education is associated with greater use of eye care [18]. Nonetheless, these relatively strong independent variables for eye care, such as the social predisposing variable (education) and the enabling variable (insurance status), suggested that the least educated and uninsured were also the least likely to use eye care services. These groups deserve focused attention in any interventions designed to increase eye care utilization rates in these socio-demographic subgroups.

Other factors correlated with greater odds of visiting an eye care provider within the past two years included: having primary ocular disease such as cataract, glaucoma, or age-related macular degeneration, (although the 95% confidence interval for this estimate was large rates (1.06–22.22)). These findings are also similar to results from the Blue Mountains Eye Study in Australia, which included clinical eye examinations [19]; they reported that blue mountain participants with a history of diabetes, hypertension or with any major eye pathology, including moderate to severe myopia, were significantly more likely to have seen an ophthalmologist in the past 2 years. We found that general health and eye insurance were important enabling variables, therefore, we conducted a stepwise regression analyses to identify indicators of eye care for the subgroup of participants with general health and vision insurance. Significant indicators of eye care in the past 24 months (P < 0.05) were: (1) Having a larger number of chronic conditions, (2) Having near vision difficulties, (3) Having a higher level of education, (4) Being of female gender, and (5) Being of older age.

We found some variation in state-level estimates of eye care provider visits. Among respondents attending an eye care provider visit within the past two years, adults from Connecticut and New York had the highest estimates for visiting an eye care provider, while respondents from Missouri and New Mexico had the lowest. Studies suggest that state variation in health care visits is driven by underlying economic and demographic factors, such as the employment makeup in the state (e.g., firm size, industry and occupation, and the degree of unionization), eligibility requirements for public programs such as Medicaid, and the demographic/socioeconomic composition of state residents [20-22]. State variation in employer-sponsored coverage appears to be driven, in part, by employee characteristics, such as industry and length of time spent with an employer, and local labor market characteristics, such as state-level unionization [23]. Given that general health and eye care insurance were associated with report of recent eye care visits, all findings consistent were with those reported by Zhang et al. [24], and variations in economic and labor mixes in the each state could be driving the observed differences.

Strengths and Limitations

This study adds to the literature by being the first to describe the association between eye care provider visits and socio-demographic characteristics using recent population-based data across multiple US states. We were also able to identify the contributions of several important variables (e.g., health and eye insurance status) to these relationships. Although the BRFSS data have been found to provide valid and reliable estimates as compared with the national household surveys [25], our study has several limitations. First, the cross-sectional design does not allow for causal inferences. Since BRFSS is a telephone based survey, there is the possibility of non-response bias. In addition, the survey used for this study was based on self-reported data and data on the type and quality of health care visits were not available. Studies have shown that self-reported data, particularly of less socially desirable behaviors, are subject to limitations of underreporting and recall bias.

Conclusion

Published recommendations by professional organizations for screening and comprehensive eye examinations by ophthalmologists and optometrist have existed for many years [13-15]. However, the present findings suggest that there remain compliance gaps for these screening guidelines among select socio-demographic sub-groups, as well as provide evidence and support to the CDC’s Vision Health Initiative [26]. Impaired vision in aging adults may not be recognized or may remain unreported because vision changes can be relatively subtle, progress slowly over time, or occur in persons with cognitive dysfunction or other co-morbidities. However, even mildly impaired visual acuity can be associated with decreased quality of life and functional capacity and increase the likelihood of accidents and related injuries [3-6]. Vision screening interventions and services targeted at at-risk subgroups such as the uninsured are needed to address population vision health.

Competing interests

The authors declare that they have no competing interests

Authors’ contributions

AJCM: conceived the study, participated in its design, coordination, performed statistical analyses, and co-drafted the manuscript. EPD: participated in the design of the study, performed statistical analysis and helped with the manuscript draft. BLL: participated in the design of the study, performed statistical analysis and helped with the manuscript draft. KLA: participated in the design of the study, performed statistical analysis and helped with the manuscript draft. KEM: participated in analysis of the study results and helped with the manuscript draft CAF: participated in analysis of the study results and helped with the manuscript draft. MAO: participated in analysis of the study results and helped with the manuscript draft DJL: conceived the study, participated in its design, coordination, performed statistical analyses, and co-drafted the manuscript. All authors read and approved the final manuscript.

Funding

Support for this study was provided by National Eye Institute grant (R21-EY019096).

Acknowledgements

We thank the staff and participants of the U.S. Behavior Risk Factor Surveillance System.

Availability of supporting data

“The data set supporting the results of this article is available from the Behavioral Risk Factor Surveillance System coordinated by the National Center for Chronic Disease Prevention and Health Promotion in the United States Center for Disease Control and Prevention, [http://www.cdc.gov/brfss/technical_infodata/surveydata.htm].”

References

  1. National Center for Health Statistics Health: United States, 2009 With Chartbook. Hyattsville, MD; 2010.

    http://www.cdc.gov/nchs/fastats/lifexpec.htm webcite. Accessed May 15, 2012

    OpenURL

  2. Congdon N, O’Colmain B, Klaver CC, Klein R, Muñoz B, Friedman DS, Kempen J, Taylor HR, Mitchell P, 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 Abstract | Publisher Full Text OpenURL

  3. Haymes SA, Johnston AW, Heyes AD: Relationship between vision impairment and ability to perform activities of daily living.

    Ophthalmic Physiol Opt. 2002, 22(2):79-91. PubMed Abstract | Publisher Full Text OpenURL

  4. Klein BE, Moss SE, Klein R, Lee KE, Cruickshanks KJ: Associations of visual function with physical outcomes and limitations 5 years later in an older population: The Beaver Dam Eye Study.

    Ophthalmology 2003, 110(4):644-650. PubMed Abstract | Publisher Full Text OpenURL

  5. Rubin GS, Roche KB, Prasada-Rao P, Fried LP: Visual Impairment and disability in older adults.

    Optom Vis Sci 1994, 71(12):750-760. PubMed Abstract | Publisher Full Text OpenURL

  6. West SK, Munoz B, Rubin GS, Schein OD, Bandeen-Roche K, Zeger S, German S, Fried LP: Function and visual impairment in a population-based study of older adults. The SEE project. Salisbury Eye Evaluation.

    Invest Ophthalmol Vis Sci. 1997, 38(1):72-82. PubMed Abstract | Publisher Full Text OpenURL

  7. 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 Abstract OpenURL

  8. Lord SR, Dayhew J: Visual risk factors for falls in older people.

    J Am Geriatr Soc 2001, 49(5):508-515. PubMed Abstract | Publisher Full Text OpenURL

  9. McGwin G, Chapman V, Owsley C: Visual risk factors for driving difficulty among older drivers.

    Accid Anal Prev 2000, 32(6):735-744. PubMed Abstract | Publisher Full Text OpenURL

  10. Owsley C, Stalvey B, Wells J, Sloane ME: Older drivers and cataract: driving habits and crash risk.

    J Gerontol A Biol Sci Med Sci. 1999, 54(4):M203-M211. PubMed Abstract | Publisher Full Text OpenURL

  11. Sims RV, Owsley C, Allman RM, Ball K, Smoot TM: A preliminary assessment of the medical and functional factors associated with vehicle crashes by older adults.

    Am Geriatr Soc. 1998, 46(5):556-561. OpenURL

  12. Congdon NG: Prevention strategies for age related cataract.

    Br J Ophthalmol 2001, 85:516-520. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  13. Chou R, Dana T, Bougatsos C: Screening older adults for impaired visual acuity: a review of the evidence for the U.S. Preventive Services Task Force.

    Ann Intern Med 2009, 151(1):44-58.

    W11-20

    PubMed Abstract | Publisher Full Text OpenURL

  14. American Optometric Association: Optometric Clinical Practice Guideline. Comprehensive Adult Eye and Vision Examination. Second Edition edition. American Optometric Association, St. Louis, Missouri; 2005.

    Available from: http://www.aoa.org/documents/CPG-1.pdf webcite. Last accessed on September 29, 2010

    OpenURL

  15. U.S. Preventive Services Task Force: Screening for impaired visual acuity in older adults: U.S. Preventive Services Task Force recommendation statement.

    Ann Intern Med 2009, 151(1):37-43.

    W10

    PubMed Abstract | Publisher Full Text OpenURL

  16. Centers for Disease Control and Prevention, National Center for Health Statistics. Health, United States, 2009: With chartbook on trends in the health of Americans. Centers for Disease Control and Prevention, Hyattsville, MD; 2009. OpenURL

  17. Fraser-Bell S, Donofrio J, Wu J, Klein R, Azen SP, Varma R: Los Angeles Latino Eye Study Group Sociodemographic factors and age-related macular degeneration in Latinos: the Los Angeles Latino Eye Study.

    Am J Ophthalmol 2005, 139(1):30-38. PubMed Abstract | Publisher Full Text OpenURL

  18. Lee DJ, Lam BL, Arora S, Arheart KL, McCollister KE, Zheng DD, Christ SL, Davila EP: Reported eye care utilization and health insurance status among US adults.

    Arch Ophthalmol 2009, 127(3):303-310. PubMed Abstract | Publisher Full Text OpenURL

  19. Wang JJ, Mitchell P, Smith W: Use of eye care services by older Australians: the Blue Mountains Eye Study.

    Aust N Z J Ophthalmol 1999, 27(5):294-300. PubMed Abstract | Publisher Full Text OpenURL

  20. Brown ER, Wyn R, Teleki S: Disparities in Health Insurance and Access to Care for Residents across U.S. Cities. The Commonwealth Fund and UCLA Center for Health Policy Research, New York; 2000. OpenURL

  21. Fronstin P: Sources of Health Insurance and Characteristics of the Uninsured: Analysis of the March 2007 Current Population Survey. Employee Benefit Research Institute, Washington, DC; 2007. OpenURL

  22. Holahan J: “Variations among States in Health Insurance Coverage and Medical Expenditures: How Much is Too Much?” Assessing the New Federalism Discussion Paper. Urban Institute, Washington, DC; 2002. OpenURL

  23. Shen YC, Zuckerman S: Why is there state variation in employer-sponsored insurance?

    Health Aff (Millwood) 2003, 22(1):241-251. Publisher Full Text OpenURL

  24. Zhang X, Lee PP, Thompson TJ: Health insurance coverage and use of eye care services.

    Arch Ophthalmol 2008, 126(8):1121-1126. PubMed Abstract | Publisher Full Text OpenURL

  25. Nelson DE, Powell-Griner E, Town M, Kovar MG: A comparison of national estimates from the National Health Interview Survey and the Behavioral Risk Factor Surveillance System.

    Am J Public Health 2003, 93:1335-1341. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  26. Centers for Disease Control and Prevention (CDC): Improving the Nation’s Vision Health. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Atlanta, Georgia; 2006.

    Last accessed on March 21, 2011 from http://www.cdc.gov/diabetes/pubs/pdf/vision.pdf webcite

    PubMed Abstract OpenURL