Open Access

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

  • Alberto J Caban-Martinez1Email author,
  • Evelyn P Davila1,
  • Byron L Lam2,
  • Kristopher L Arheart1,
  • Kathryn E McCollister1,
  • Cristina A Fernandez1,
  • Manuel A Ocasio1 and
  • David J Lee1
BMC Research Notes20125:253

DOI: 10.1186/1756-0500-5-253

Received: 30 December 2011

Accepted: 9 May 2012

Published: 23 May 2012

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 [36]. 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 [711]. 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 [1315]. 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)†

 

WITHIN THE PAST TWO YEARS

2 OR MORE YEARS AGO

NEVER

Demographics

Sample N

Estimated Annual Population

Percent ±  Standard Error

Sample N

Estimated Annual Population

Percent ±  Standard Error

Sample N

Estimated Annual Population

Percent ±  Standard Error

Total

95,007

42,657,170

79.5 ± 0.2

21,483

9,942,174

18.8 ± 0.2

1,585

950,723

1.8 ± 0.1

Age

         

40-49 years old

18,899

12,295,708

29.2 ± 0.3

6,478

4,183,454

42.1 ± 0.7

823

602,806

63.4 ± 2.2

50-59 years old

24,971

11,798,975

28.0 ± 0.3

6,693

2,969,638

29.9 ± 0.6

483

257,826

27.1 ± 2.1

60-69 years old

23,189

8,419,706

20.0 ± 0.2

4,809

1,692,169

17.0 ± 0.5

181

62,891

6.6 ± 0.8

> 70 years old

26,888

9,615,336

22.8 ± 0.2

3,306

109,691

11.0 ± 0.4

86

27,200

2.9 ± 0.7

Gender

         

Male

33,350

19,293,135

45.2 ± 0.3

9051

5,281,995

52.6 ± 0.7

866

586,433

61.1 ± 2.3

Female

61,657

23,364,035

54.8 ± 0.3

12,432

4,761,838

47.4 ± 0.7

719

372,763

38.9 ± 2.3

Race/Ethnicity

         

White, Non-Hispanic

76,740

32,311,744

76.5 ± 0.3

16,923

7,483,135

75.2 ± 0.6

1,019

508,326

53.9 ± 2.4

Black, Non-Hispanic

9,951

4,178,925

9.9 ± 0.2

2,362

986,422

9.9 ± 0.4

207

92,745

9.8 ± 1.1

Other, Non-Hispanic

2,936

1,863,621

4.4 ± 0.1

771

511,119

5.1 ± 0.4

85

59,147

6.3 ± 1.0

Hispanic

4,389

3,864,274

9.2 ± 0.3

1,210

966,198

9.7 ± 0.5

250

283,682

30.1 ± 2.5

Marital Status

         

Married/Living with Partner

54,074

29,522,056

69.4 ± 0.3

11,413

6,656,542

66.5 ± 0.6

904

690,728

72.2 ± 1.8

Widowed, Divorced or Separated

34,502

10,699,810

25.2 ± 0.3

8,046

2,521,895

25.2 ± 0.5

502

183,293

19.2 ± 1.5

Single

6,054

2,294,113

5.4 ± 0.1

1,948

833,994

8.3 ± 0.3

175

82,020

8.6 ± 1.1

Education

         

Less than High School

10,220

4,249,803

10.0 ± 0.2

3291

1,461,052

14.6 ± 0.5

439

302,500

31.6 ± 2.4

High School Diploma

30,293

12,127,596

28.5 ± 0.3

7632

3,265,457

32.6 ± 0.6

610

309,840

32.3 ± 2.0

Attended College

24,703

11,109,821

26.1 ± 0.3

5329

2,429,357

24.2 ± 0.6

271

162,584

17.0 ± 1.9

Graduated from College

29,570

15,051,606

35.4 ± 0.3

5182

2,865,158

28.6 ± 0.7

262

182,904

19.1 ± 1.9

Body Mass Index

         

Normal Weight

30,432

13,540,061

33.1 ± 0.3

6754

3,129,859

32.4 ± 0.7

523

310,752

35.8 ± 2.4

Overweight

34,287

15,936,469

38.9 ± 0.3

7624

3,650,659

37.8 ± 0.7

527

312,445

36.0 ± 2.3

Obese

26,140

15,936,469

28.0 ± 0.3

6213

2,881,679

29.8 ± 0.7

432

245,332

28.2 ± 2.2

Eye Insurance Status

         

Has Eye Insurance

54330

25,760,864

61.5 ± 0.3

7949

4,173,169

43.5 ± 0.7

474

284,942

31.4 ± 2.2

No Eye Insurance

38931

16,118,968

38.5 ± 0.3

12541

5,429,954

56.5 ± 0.7

1,006

622,259

68.6 ± 2.2

Health Insurance Status

         

Has Health Insurance

88290

39,164,162

92.0 ± 0.2

17408

7,948,234

79.3 ± 0.6

1,015

542,122

56.8 ± 2.4

No Health Insurance

6558

3,392,391

8.0 ± 0.2

4019

2,077,566

20.7 ± 0.6

561

412,791

43.2 ± 2.4

Far Vision Difficulties

         

Has Little to None

88,804

40,142,531

95.4 ± 0.1

19767

9,357,790

94.5 ± 0.3

1,491

910,441

96.7 ± 0.8

Has Moderate to Extreme

4,906

1,948,998

4.6 ± 0.1

1392

546,716

5.5 ± 0.3

64

31,301

3.3 ± 0.8

Near Vision Difficulties

         

Has Little to None

82,508

39,234,257

88.4 ±0.2

17049

8,081,003

82.1 ± 0.5

1,188

746,434

80.3 ± 1.7

Has Moderate to Extreme

11,092

4,866,227

11.6 ± 0.2

3973

1,765,173

17.9 ± 0.5

351

183,319

19.7 ± 1.7

Eye Disease Status*

         

Has Cataract

17,228

6,227,833

16.5 ± 0.2

1372

437,948

4.6 ± 0.2

15

2,961

0.3 ± 0.1‡

Has Glaucoma

5,947

2,368,372

5.6 ± 0.1

343

138,714

1.4 ± 0.1

4

3,750

0.4 ± 0.2‡

Has Age-Related Macular Degeneration

5,242

2,093,948

5.0 ± 0.1

454

212,879

2.2 ± 0.2

7

4,056

0.4 ± 0.3‡

Chronic Disease Status*

         

Has Diabetes

15,175

6,141,139

14.7 ± 0.2

2053

781,008

7.9 ± 0.3

76

36,519

3.9 ± 0.8

Has Hypertension

15,665

3,818,886

43.8 ± 0.5

3014

764,411

40.0 ± 0.9

155

47,163

26.6 ± 3.1

† = Differences in sub-total population sample may not add to total due to item non-response or missing.

‡ = Estimate does not meet National Center for Health Statistic’s standard of reliability or precision given the relative standard error was greater than 30%.

* = Sample n refers to the number of persons with the condition; Presented estimates are row percents of the total sample for condition (i.e. cataract, diabetes).

** = States surveyed = Alabama, Alaska, Connecticut, Florida, Georgia, Indiana, Iowa, Missouri, New Mexico, New York, North Carolina, Ohio, Tennessee, Texas, West Virginia, and Wyoming.

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)

 

WITHIN THE PAST TWO YEARS

2 OR MORE YEARS AGO

NEVER

State Specifics

Sample N

Estimated Annual Population

Percent ±  Standard Error

Sample N

Estimated Annual Population

Percent ±  Standard Error

Sample N

Estimated Annual Population

Percent ±  Standard Error

Alabama

12,484

1,654,872

79.0 ± 0.5

2,870

401,267

19.2 ± 0.4

224

38,015

1.8 ± 0.2

Alaska

2,835

1,947,321

81.6 ± 1.2

628

415,073

17.4 ± 1.2

41‡

25,254

1.1 ±0.4‡

Connecticut

4,026

1,380,228

82.0 ± 0.8

754

292,665

17.4 ± 0.7

35‡

10,970

0.7 ± 0.1‡

Florida

6,624

6,954,837

81.6 ± 0.6

1,310

1,369,507

16.1 ± 0.6

138

193,798

2.3 ± 0.3

Georgia

8,805

2,858,914

78.1 ± 0.5

2,072

741,347

20.2 ± 0.5

153

61,631

1.7 ± 0.2

Indiana

8,350

2,118,487

78.2 ± 0.6

2,102

554,609

20.5 ± 0.5

108

37,246

1.4 ± 0.2

Iowa

7,060

1,092,764

80.8 ± 0.5

1,445

240,577

17.8 ± 0.5

91

19,632

1.5 ± 0.2

Missouri

2,966

1,908,869

73.4 ± 1.0

935

638,409

24.6 ± 0.9

60

52,018

2.0 ± 0.3

New Mexico

3,651

640,405

75.5 ± 0.8

981

185,502

21.9 ± 0.8

96

22,269

2.6 ± 0.3

New York

7,566

6,864,984

82.0 ± 0.5

1,475

1,379,011

16.5 ± 0.5

97

124,990

1.5 ± 0.2

North Carolina

9,876

3,160,247

78.2 ± 0.5

2,262

798,792

19.8 ± 0.5

178

82,470

2.0 ± 0.2

Ohio

3,383

1,996,997

78.8 ± 1.2

787

515,389

20.3 ± 1.1

38‡

23,356

0.9 ± 0.3‡

Tennessee

5,928

2,231,474

80.5 ± 0.7

1,142

477,692

17.2 ± 0.7

129

61,190

2.2 ± 0.3

Texas

3,777

6,950,523

77.7 ± 1.0

893

1,800,936

20.1 ± 1.0

97

189,467

2.1 ± 0.3

West Virginia

2,688

707,781

78.0 ± 0.8

673

185,309

20.4 ± 0.8

45

14,234

1.6 ± 0.2

Wyoming

4,988

188,459

78.9 ± 0.6

1,154

47,743

20.0 ± 0.6

55

2,649

1.1 ± 0.2

‡ = Estimate does not meet National Center for Health Statistic’s standard of reliability or precision given the relative standard error was greater than 30%.

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)

PREDICTORS

OCULAR VISIT WITHIN THE PAST TWO YEARS**

OCULAR VISIT ≥ TWO YEARS**

OR

95% CI

OR

95% CI

Age (ref = 40–49 years old)

1.00

 

1.00

 

50-59 years old

2.18

1.55-3.09

1.57

1.11-2.22

60-69 years old

4.65

2.25-7.85

3.05

1.79-5.17

≥ 70 years old

6.82

3.70-12.57

3.08

1.65-5.76

Gender (ref = male)

1.00

 

1.00

 

Female

2.87

2.12-3.91

2.22

1.62-3.03

Race/Ethnicity (ref = White, Non-Hispanic)

1.00

 

1.00

 

Black, Non-Hispanic

0.74

0.73-1.29

0.64

0.37-1.12

Other, Non-Hispanic

0.90

0.42-1.93

0.72

0.33-1.57

Hispanic

0.91

0.41-2.01

0.54

0.23-1.27

Marital Status (ref = Married, Living with Partner)

1.00

 

1.00

 

Widowed, Divorced or Separated

1.07

0.74-1.57

1.43

0.97-2.09

Single

1.43

0.98-2.09

1.77

0.92-3.42

Education (ref = Less than High School)

1.00

 

1.00

 

High School Diploma

1.89

1.20-2.97

1.25

0.79-1.97

Attended College

3.03

1.81-5.08

1.85

1.10-3.11

Graduated from College

5.16

3.02-8.81

2.35

1.37-4.04

Eye Provider Insurance (ref = No Eye Insurance)

1.00

 

1.00

 

Yes

2.08

1.46-2.95

1.05

0.74-1.50

General Health Insurance (ref = No Health Insurance)

1.00

 

1.00

 

Yes

2.66

1.80-3.93

1.76

1.19-2.61

Diabetes Status (ref = no diabetes)

1.00

 

1.00

 

Yes, has diabetes

3.53

1.66-7.50

2.24

1.06-4.80

High Blood Pressure Status (ref = no high blood pressure)

1.00

 

1.00

 

Yes, has high blood pressure

1.54

1.08-2.20

1.63

1.14-2.34

Far Vision Difficulties (ref = has little to moderate)

1.00

 

1.00

 

Has Moderate to Extreme

1.68

0.74-3.82

1.58

0.69-3.62

Near Vision Difficulties ( ref = has little to moderate)

1.00

 

1.00

 

Has Moderate to Extreme

1.42

1.11-2.08

0.92

0.61-1.40

Eye Disease Status ( ref = has no Eye Disease)

1.00

 

1.00

 

Has eye disease (e.g. cataract, glaucoma, and/or ARMD)

4.74

1.06-21.22

1.80

0.40-8.11

** Reference group = Never.

*Statistically significant findings in bold.

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 [2022]. 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 [1315]. 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 [36]. Vision screening interventions and services targeted at at-risk subgroups such as the uninsured are needed to address population vision health.

Funding

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

Declarations

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].”

Authors’ Affiliations

(1)
Department of Epidemiology & Public Health, University of Miami, Miller School of Medicine, Clinical Research Building
(2)
Department of Ophthalmology, Miller School of Medicine, University of Miami

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Copyright

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

This article is published under license to 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.