Neighborhood-Level Social Determinants of Health and Presenting Characteristics for Rhegmatogenous Retinal Detachments

Sally S Ong; Diep Tran; Erik Westlund; Ishrat Ahmed; Gregory B Russell; Anthony Gonzales; James T Handa; Cindy X Cai

doi:10.1001/jamaophthalmol.2024.2889

. 2024 Aug 8;142(9):845–854. doi: 10.1001/jamaophthalmol.2024.2889

Neighborhood-Level Social Determinants of Health and Presenting Characteristics for Rhegmatogenous Retinal Detachments

Sally S Ong ^1,^✉, Diep Tran ², Erik Westlund ³, Ishrat Ahmed ², Gregory B Russell ⁴, Anthony Gonzales ², James T Handa ², Cindy X Cai ^2,^5,^✉

¹Department of Ophthalmology, Wake Forest School of Medicine, Winston-Salem, North Carolina

²Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland

³Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

⁴Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina

⁵Department of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland

Accepted for Publication: June 3, 2024.

Published Online: August 8, 2024. doi:10.1001/jamaophthalmol.2024.2889

^✉

Corresponding Authors: Cindy X. Cai, MD, Wilmer Eye Institute, 1800 Orleans St, Room 711, Baltimore, MD 21287 (ccai6@jhmi.edu); Sally S. Ong, MD, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157 (song@wakehealth.edu).

Author Contributions: Drs Cai and Ong had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Ong, Handa, Cai.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Ong, Russell, Cai.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Westlund, Russell, Cai.

Obtained funding: Handa, Cai.

Administrative, technical, or material support: Ong, Tran, Gonzales.

Supervision: Ong, Handa, Cai.

Conflict of Interest Disclosures: Dr Ong reported receiving advisory board fees from Eyepoint Pharmaceuticals outside the submitted work. Dr Handa reported receiving grants from Research to Prevent Blindness during the conduct of the study and advisory board fees from Character Biosciences Inc, Cirrus Pharmaceuticals, and Seeing Medicines outside the submitted work. Dr Cai reported receiving grants from Regeneron outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported in part by grant K23EY033440 from the National Institutes of Health/National Eye Institute (Dr Cai) and an unrestricted grant from Research to Prevent Blindness to Wilmer Eye Institute.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Meeting Presentation: This study was presented at Vit-Buckle Society Annual Meeting 2023; April 15, 2023; Las Vegas, Nevada, and the American Society for Retina Specialist Annual Meeting 2024; July 17, 2024; Stockholm, Sweden.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We thank Ugochi T. Aguwa, MD (Wills Eye Hospital), Bradley Beatson, MD (USC Roski Eye Institute), Xi Dai, MD (Yale Eye Center), Alex T. Pham, MD (University of Maryland), Yesha S. Shah, MD (Wilmer Eye Institute), and Ashley Zhou, MD (Mayo Clinic), for their assistance with data acquisition. Beyond usual salary, no one received financial compensation for these contributions.

^✉

Corresponding author.

PMCID: PMC11310845 PMID: 39115836

This cohort study investigates the association between neighborhood-level social determinants of health and severity of rhegmatogenous retinal detachments at presentation.

Key Points

Question

Are neighborhood-level social determinants of health (SDOH) associated with severity of rhegmatogenous retinal detachment (RRD) at presentation?

Findings

In this cohort study at a tertiary care academic center including 700 patients, residence in neighborhoods with worse socioeconomic deprivation and higher percentage of workers who drove to work were associated with increased odds of presenting with visual acuity worse than 20/40 and fovea-involving RRD, even after adjusting for multiple individual characteristics.

Meaning

Adverse neighborhood-level SDOH were associated with more severe RRD at presentation, supporting the possibility that some neighborhoods may benefit from policy change or other interventions to promote vision saving care in RRD.

Abstract

Importance

Functional outcomes after repair of rhegmatogenous retinal detachments (RRDs) are highly dependent on baseline visual acuity and foveal status. Adverse social determinants of health (SDOH) can present barriers to timely presentation for repair and limit vision outcomes.

Objective

To evaluate the association between neighborhood-level SDOH with baseline severity (visual acuity and fovea status) of RRD.

Design, Setting, and Participants

This was a retrospective cohort study that included adult patients 18 years and older who underwent primary repair of uncomplicated RRD at the Wilmer Eye Institute from January 2008 to December 2018. Study data were analyzed from December 2023 to April 2024.

Exposures

The census block group of patient home addresses were matched to multiple neighborhood-level SDOH including the Area Deprivation Index (ADI), per capita income, percentage of renters, percentage of rent burden, percentage of people using a food assistance program, percentage of uninsured individuals, mode of transportation to work, distance to the nearest transit stop, total road density, National Walkability Index, Index of Medical Underservice score, and aggregate cost of medical care.

Main Outcomes and Measures

Odds of presenting with vision worse than 20/40 or fovea-involving RRD using multivariable logistic regression adjusting for age, sex, race and ethnicity, and insurance.

Results

A total of 700 patients (mean [SD] age, 57.9 [12.4] years; 432 male [61.7%]) were included. Every decile increase in ADI, indicating more socioeconomic disadvantage, was associated with an increased odds of presenting with worse visual acuity and fovea-involving RRD (odds ratio [OR], 1.14; 95% CI, 1.04-1.24; P = .004 and OR, 1.13; 95% CI, 1.04-1.22; P = .005, respectively). Each $1000 increase in per capita income was associated with lower odds of presenting with worse vision (OR, 0.99; 95% CI, 0.98-0.99; P = .001). Every 1% increase in percentage of workers who drove to work was associated with an increased odds of presenting with worse vision and fovea-involving RRD (OR, 1.02; 95% CI, 1.01-1.03; P = .005 and OR, 1.01; 95% CI, 1.00-1.03; P = .04, respectively).

Conclusions and Relevance

Results of this cohort study suggest that patients with a residence in neighborhoods with more socioeconomic deprivation or a higher percentage of workers who drove to work were more likely to present with more severe RRD even after accounting for multiple individual-level characteristics. These findings support consideration of public policy changes to address the barriers faced by patients residing in certain neighborhoods who seek prompt surgical intervention for RRD to reduce health disparities in RRD outcomes.

Introduction

Rhegmatogenous retinal detachment (RRD) is the most common RD with an incidence of 6.3 to 17.9 per 100 000 persons.¹ With advances in vitreoretinal surgery techniques, reattachment rates have improved.^2,3 Although anatomic success is associated with superior postoperative visual acuity, functional outcomes after retinal reattachment remain variable⁴ due to preoperative and intraoperative factors.^5,6 Of these, baseline visual acuity and fovea status are the strongest and most consistent factors that predict final vision.⁷ Preclinical and clinical studies have shown that subfoveal fluid can cause irreversible retinal anoxia and photoreceptor death.^8,9 Thus, foveal detachment and its duration affect central visual acuity. These factors present later in disease and can dampen final visual outcomes despite successful anatomic reattachment.

The identification and resolution of barriers for early RRD repair are likely to improve functional outcomes. Social determinants of health (SDOH) are now recognized as important contributors to vision outcomes in several eye diseases including glaucoma,¹⁰ diabetic retinopathy,¹¹ age-related macular degeneration,¹² and cataracts¹³ but have yet to be thoroughly explored in RRDs. SDOH refer to the conditions of the environments in which people are born, live, work, play, worship, and age¹⁴ and are grouped into 5 domains: economic stability, education access and quality, social and community context, neighborhood and built environment, and health care access and quality.^14,15 Neighborhood-level SDOH, including median household income, have previously been associated with RRD severity.¹⁶ A detailed investigation of neighborhood-level SDOH across multiple domains in RRD is lacking, especially in the US.

Identification of critical neighborhood-level SDOH associated with RRD severity can be used to expand health policies to connect vulnerable populations to the social services they need to achieve better health outcomes. Our study evaluated the association of multiple neighborhood-level SDOH indicators with baseline severity (visual acuity and fovea status) of primary RRD repaired at a single academic institution in the US.

Methods

Patients

This retrospective cohort study included adult patients 18 years and older who underwent primary repair of uncomplicated RRD at the Wilmer Eye Institute, an academic tertiary care center, between January 1, 2008, to December 31, 2018, with at least 1 year of follow-up. This is the same cohort studied in prior publications by our group, and details of patient identification have been previously described.^4,17 For patients who had 2 qualifying eyes, the eye with the worse visual acuity was chosen. If both eyes had the same visual acuity, 1 eye was chosen at random. This study was approved by the Johns Hopkins Institute Review Board (IRB00198544), and the need for informed consent was waived given that this was secondary research. The study also adhered to the Declarations of Helsinki. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

Neighborhood-Level SDOH

Patient addresses were geocoded using the 12-digit Federal Information Processing Standards (FIPS) code based on the 2019 US Census Bureau TIGER/Line Shapefiles.¹⁸ The 12-digit FIPS code describes the census block group, which is the smallest geographic area for which US census data are reported and generally contains 600 to 3000 people.¹⁹ Addresses that could not be matched on the street level were geocoded using the US Census Bureau Geocoder.²⁰ Patient addresses that were post office boxes, located outside of the US, or could not be geocoded on the street level were excluded from the analysis. The 12-digit FIPS code was used to link to multiple neighborhood-level SDOH measures.

The patient’s block group was matched to the 2019 Area Deprivation Index (ADI), an indicator originally created by the Health Resources & Services Administration and updated by Kind et al²¹ to measure the socioeconomic deprivation of a neighborhood. The ADI is reported as the national percentile rank of a block group ranging from 1 to 100, with higher percentiles indicating more socioeconomic disadvantage. The ADI is calculated from 17 indicators of education, employment, housing quality, and poverty measures drawn from the US Census American Community Survey (ACS [PolicyMap Inc]) to measure economic stability, transportation, housing, and health care access.²² Measures from the 2018 US Census ACS 5-year data included per capita income, percentage of renters, percentage of rent burden, percentage of individuals using a food assistance program, and percentage of individuals who are uninsured. We chose variables that were not already represented in the ADI. Additional neighborhood-level SDOH were obtained from PolicyMap Inc, including mode of transportation to work (percentage of workers who: drove to work in 2017-2021, commuted to work using public transit in 2017-2021, commuted to work by bicycle in 2017-2021, commuted to work by walking in 2017-2021, worked from home in 2017-2021, and commuted to work using another means of transportation in 2017-2021), mean number of cars per household, distance to the nearest transit stop in 2021, total road network density in 2021 (calculated by dividing the number of roadway links from intersection to intersection by the land area of the block group), and National Walkability Index in 2021 (range 1-20 with higher values indicating more walkability).^23,24,25 Other measures included Index of Medical Underservice (IMU) score in 2022 (with a score of 0 indicating areas of highest need and 100 indicating the least need), and aggregate cost of medical care in 2019.²⁵

Dependent Variables and Other Characteristics at Baseline

The first dependent variable examined was the best-recorded visual acuity at presentation whether better than or equal to 20/40 (≥20/40) or worse than 20/40 (<20/40). The second dependent variable was whether the fovea was spared or involved at presentation of RRD. Fovea status was determined based on manual chart review of the operative note. If information about fovea status from the operative note was equivocal or missing, then the clinic note was reviewed.

Other baseline characteristics included age at presentation, sex, race and ethnicity, and insurance. Date of birth, sex, and insurance were entered into the electronic health record during patient registration after verification using a valid government issued photograph identification and insurance card. Sex and race and ethnicity were self-reported. Race and ethnicity information was extracted from the electronic health record and was categorized as previously described²⁶ as follows: non-Hispanic Black, Hispanic, non-Hispanic White, and other, which included Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, other, unknown, choose not to disclose, unable to obtain, or 2 or more races.

Statistical Analysis

Descriptive statistics were calculated including mean, median, and IQR. The association of each baseline characteristic and neighborhood-level SDOH with presenting visual acuity and fovea status were investigated with 2-sample t tests and χ² tests. Separate univariable logistic regression models of the association between each neighborhood-level SDOH with the dependent variables of interest (presenting visual acuity and fovea status) were constructed. Multivariable logistic regression models were also constructed adjusting for age (<50 or ≥50 years), sex (male or female), race and ethnicity (non-Hispanic Black, Hispanic, non-Hispanic White, or other), and insurance (public, private, none). The predicted probabilities of presenting with vision worse than 20/40 or fovea-involving RRD were calculated using the multivariable model. All tests performed were 2-sided, and a P value <.05 was considered statistically significant. P values were not adjusted for multiple comparisons. All analyses were performed from December 2023 to April 2024 using Stata, version 18 (StataCorp), and Python, version 3.8.5 (Python Software Foundation).

Results

A total of 700 patients (mean [SD] age, 57.9 [12.4] years; 268 female [38.3%]; 432 male [61.7%]) from 19 different states were included in the study (Figure 1). Patients self-identified with the following races and ethnicities: 81 non-Hispanic Black (11.6%), 8 Hispanic (1.1%), 547 non-Hispanic White (78.1%), and 64 other (9.2%). A total of 373 patients (53.2%) had private insurance (Table 1). More patients (430 [61.4%]) presented with vision worse than 20/40, although most (478 [68.3%]) patients had fovea-sparing RRD (Table 2 and Table 3).

Table 1. Baseline Characteristics (Demographic Characteristics and Neighborhood-Level Social Determinants of Health) of Patients With Rhegmatogenous Retinal Detachments Evaluated at the Wilmer Eye Institute (N =700).

Characteristic	No./total No. (%)	Mean (SD)	Median (IQR)
Demographic characteristics
Age, y^a	700/700 (100)	57.9 (12.4)	59.0 (51.5-66.0)
Sex^b
Female	268/700 (38.3)	NA	NA
Male	432/700 (61.7)	NA	NA
Race and ethnicity^b
Non-Hispanic Black	81/700 (11.6)	NA	NA
Hispanic	8/700 (1.1)	NA	NA
Non-Hispanic White	547/700 (78.1)	NA	NA
Other^c	64/700 (9.2)	NA	NA
Insurance^b
Private	373/700 (53.2)	NA	NA
Public	293/700 (41.9)	NA	NA
None	34/700 (4.9)	NA	NA
Neighborhood-level characteristics
Area Deprivation Index, national percentile rank^a (n = 700)	NA	27.2 (20.2)	22.0 (12.0-38.0)
Per capita income, $^a (n = 695)		48 203 (20 595)	44 210 (33 623-57 923)
Workers who drove to work in 2017-2021 (%)^a (n = 582)		79.0 (12.8)	81.2 (72.5-88.1)
Workers who commuted to work using public transit in 2017-2021 (%)^a (n = 582)		4.6 (7.3)	1.7 (0-6.1)
Workers who commuted to work by bicycle in 2017-2021 (%)^a (n = 582)		0.2 (0.9)	0
Workers who commuted to work by walking in 2017-2021 (%)^a (n = 582)		1.8 (4.0)	0 (0-2.0)
People who worked from home in 2017-2021 (%)^a (n = 582)		13.2 (9.0)	13.0 (6.3-18.7)
People who commuted to work using other transport 2017-2021 (%)^a (n = 582)		0.9 (2.1)	0 (0-0.8)
Mean No. cars per household (n = 414)		1.8 (0.5)	1.9 (1.5-2.2)
Distance to nearest transit stop in 2021, m^a (n = 327)		522.2 (294.4)	470.7 (295.1-730.9)
Total road network density in 2021 (No. per square mile)^a (n =695)		14.8 (9.6)	13.9 (6.7-20.6)
National walkability index in 2021 (score)^a (n = 695)		9.8 (4.2)	9.3 (6.2-13.3)
Index of Medical Underservice score, as of 2022^a (n = 146)		58.2 (7.1)	60.1 (56.1-61.3)
Aggregate cost of medical care in 2019, $^a (n = 695)		40 800 000 (16 800 000)	38 300 000 (29 000 000-50 500 000)
Percentage uninsured (%)^a (n = 695)		3.8 (4.2)	2.6 (1.1-5.1)
Percentage renter (%)^a (n = 695)		23.2 (23.1)	15.1 (6.1-33.8)
Percentage rent burden (%)^a (n = 657)		40.8 (26.7)	40.3 (23.3-57.5)
Percentage using food assistance program (%)^a (n = 695)		8.3 (10.8)	4.7 (1.6-10.1)

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Abbreviation: NA, not applicable.

^{^a}

Continuous variable.

^{^b}

Categorical variable.

^{^c}

Other race and ethnicity includes Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, other, unknown, choose not to disclose, unable to obtain, or 2 or more races.

Table 2. Association of Presenting Visual Acuity (VA) Better Than or Equal to 20/40 or Worse Than 20/40 With Demographic Characteristics and Neighborhood-Level Social Determinants of Health.

Demographic characteristic	VA ≥20/40 (n = 270)		VA <20/40 (n = 430)		Mean difference (95% CI)	P value
Demographic characteristic	No./total No. (%)	Mean (SD) [median]	No./total No. (%)	Mean (SD) [median]	Mean difference (95% CI)	P value
Age, y^a	270/270 (100)	55.2 (11.7) [57.0]	430/430 (100)	59.7 (12.5) [60.0]	−4.5 (−6.3 to −2.6)	<.001
Sex^b
Female	168/268 (62.7)	NA	100/268 (37.3)	NA	Reference	.59
Male	262/432 (60.7)	NA	170/432 (39.4)	NA	0.02 (−0.05 to 0.09)	.59
Race and ethnicity^b
Non-Hispanic Black	60/81 (74.1)	NA	21/81 (25.9)	NA	−0.15 (−0.26 to −0.05)	.03
Hispanic	4/8 (50.0)		4/8 (50.0)		−0.09 (−0.26 to 0.44)
Non-Hispanic White	322/547 (58.9)		225/547 (41.1)		Reference
Other^c	44/64 (68.8)		20/64 (31.3)		−0.1 (−0.22 to 0.02)
Insurance^b	208/44.24 (55.8)		165/373 (44.2)
Private	196/33.11 (66.9)	NA	97/293 (33.1)	NA	Reference	.002
Public	26/23.53 (76.5)		8/34 (23.5)		−0.11 (−0.19 to 0.04)
None	168/268 (62.7)		100/268 (37.3)		−0.21 (−0.36 to −0.06)
Neighborhood-level characteristics		Mean (SD) [median]/total No.		Mean (SD) [median]/total No.
Area Deprivation Index, national percentile rank^a	NA	23.9 (19.7) [18.0]/270	NA	29.3 (20.3) [24.0]/430	−5.4 (−8.4 to −2.3)	<.001
Per capita income, $^a		51 886.80 (21 483.80) [48 808.00]/268		45 891.90 (19 693.80) [42 164.00]/427	5994.90 (2873.20 to 9116.60)	<.001
Workers who drove to work in 2017-2021 (%)^a		77.2 (13.5) [79.9]/221		79.9 (12.2) [81.8]/361	−2.7 (−4.8 to −0.6)	.01
Workers who commuted to work using public transit in 2017-2021 (%)^a		5.0 (7.7) [7.7]/221		361.0 (4.4) [1.5]/361	0.6 (−0.6 to 1.9)	.30
Workers who commuted to work by bicycle in 2017-2021 (%)^a		0.3 (0.9) [0]/221		0.2 (0.9) [0]/361	0.1 (−0.1 to 0.2)	.42
Workers who commuted to work by walking in 2017-2021 (%)^a		1.9 (4.0) [0]/2221		1.8 (4.0) [0]/361	0.2 (−0.5 to 0.8)	.65
People who worked from home in 2017-2021 (%)^a		14.3 (8.4) [13.9]/221		12.6 (9.3) [11.6]/361	1.7 (0.2 to 3.2)	.02
People who commuted to work using other transport 2017-2021 (%)^a		1.0 (2.1) [0]/221		0.9 (2.1) [0]/361	0.1 (−0.2 to 0.5)	.55
Mean No. cars per household		1.8 (0.5) [1.9]/153		1.9 (0.5) [1.9]/261	−0.1 (−0.2 to 0.0)	.25
Distance to nearest transit stop in 2021, m^a		495.6 (278.4) [434.5]/123		538.4 (303.1) [496.2]/204	−42.8 (−108.9 to 23.2)	.20
Total road network density in 2021 (No. per square mile)^a		15.0 (9.4) [14.1]/268		14.6 (9.7) [13.9]/427	0.4 (−1.1 to 1.8)	.63
National walkability index in 2021 (score)^a		9.8 (4.3) [9.2]/268		9.9 (4.1) [9.5]/427	−0.1 (−0.7 to 0.6)	.80
Index of Medical Underservice score, as of 2022^a		57.7 (7.2) [58.4]/48		58.5 (7.1) [60.1]/98	−0.8 (−3.3 to 1.7)	.54
Aggregate cost of medical care in 2019, $^a		40 500 000.00 (16 900 000.00) [38 000 000.00]/268		40 900 000.00 (16 700 000.00) [38 400 000.00]/427	−395 277.80 (−2 965 310.00 to 2 174 754.00)	.76
Percentage uninsured (%)^a		3.4 (3.8) [2.3]/268		4.1 (4.3) [2.7]/427	−0.7 (−1.3 to 0.0)	.04
Percentage renter (%)^a		20.9 (21.7) [12.4]/268		24.6 (23.9) [17.0]/427	−3.7 (−7.3 to −0.2)	.04
Percentage rent burden (%)^a		42.5 (27.5) [44.7]/252		39.7 (26.3) [39.3]/405	2.7 (−1.5 to 6.9)	.20
Percentage using food assistance program (%)^a		7.5 (10.6) [4.3]/268		8.8 (10.9) [4.9]/427	−1.3 (−3.0 to 0.3)	.11

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Abbreviation: NA, not applicable.

^{^a}

Continuous variable.

^{^b}

Categorical variable.

^{^c}

Other race and ethnicity includes Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, other, unknown, choose not to disclose, unable to obtain, or 2 or more races.

Table 3. Association of Presenting Fovea Status (Fovea Sparing or Fovea Involving) With Demographic Characteristics and Neighborhood-Level Social Determinants of Health.

Demographic characteristic	Fovea sparing (n = 478)		Fovea involving (n = 222)		Mean difference (95% CI)	P value
Demographic characteristic	No./total No. (%)	Mean (SD) [median]	No./total No. (%)	Mean (SD) [median]	Mean difference (95% CI)	P value
Age, y^a	478/478 (100)	57.2 (12.2) [58.0]	222/222 (100)	59.6 (12.8) [60.0]	−2.3 (−4.3 to −0.4)	.02
Sex^b
Female	186/268 (69.4)	NA	82/268 (62.7)	NA	Reference	.62
Male	292/432 (67.6)	NA	140/432 (60.7)	NA	−0.02 (0.28 to 0.37)	.62
Race and ethnicity^b
Non-Hispanic Black	45/81 (55.6)	NA	36/81 (44.4)	NA	−0.14 (0.26 to −0.03)	.07
Hispanic	6/8 (75.0)		2/8 (25.0)		0.05 (−0.26 to 0.35)
Non-Hispanic White	382/547 (69.8)		165/547 (30.2)		Reference
Other^c	45/64 (70.3)		19/64 (29.7)		0.005 (−0.114 to 0.123)
Insurance^b	208/44.24 (55.8)		165/373 (44.2)
Private	269/373 (72.1)	NA	104/72.12 (27.9)	NA	Reference	.06
Public	186/293 (63.5)		107/63.48 (36.5)		−0.08 (−0.16 to −0.15)
None	23/34 (67.7)		11/67.65 (32.4)		−0.04 (−0.21 to −0.12)
Neighborhood-level characteristics		Mean (SD) [median]/total No.		Mean (SD) [median]/total No.
Area Deprivation Index, national percentile rank^a	NA	25.5 (19.5) [20.0]/478	NA	31.0 (21.3) [25.0]/222	−5.5 (−8.7 to −2.3)	<.001
Per capita income, $^a		49 425.70 (20 269.10) [46 172.00]/474		45 582.40 (21 086.70) [42 192.00]/221	3843.30 (559.70 to 7126.90)	.02
Workers who drove to work in 2017-2021 (%)^a		78.2 (13.1) [80.6]/392		80.4 (11.8) [82.4]/190	−2.3 (−4.5 to 0.0)	.046
Workers who commuted to work using public transit in 2017-2021 (%)^a		4.7 (7.4) [7.4]/392		190.0 (4.4) [1.4]/190	0.3 (−1.0 to 1.6)	.64
Workers who commuted to work by bicycle in 2017-2021 (%)^a		0.3 (1.0) [0]/392		0.2 (0.7) [0]/190	0.1 (−0.1 to 0.2)	.23
Workers who commuted to work by walking in 2017-2021 (%)^a		2.0 (4.5) [0]/392		1.4 (2.6) [0]/190	0.6 (−0.1 to 1.3)	.07
People who worked from home in 2017-2021 (%)^a		13.7 (8.5) [13.7]/392		12.3 (9.9) [10.8]/190	1.4 (−0.1 to 3.0)	.07
People who commuted to work using other transport 2017-2021 (%)^a		0.9 (1.9) [0]/392		1.0 (2.5) [0]/190	−0.1 (−0.4 to 0.3)	.66
Mean No. cars per household (No.)		1.8 (0.5) [1.9]/278		1.9 (0.5) [1.9]/136	−0.1 (−0.2 to 0.0)	.19
Distance to nearest transit stop in 2021, m^a		514.7 (466.7) [104]/223		538.6 (299.4) [517.7]/104	−24.0 (−92.8 to 44.9)	.49
Total road network density in 2021 (No. per square mile)^a		15.0 (9.6) [14.3]/474		14.2 (9.6) [13.2]/221	0.9 (−0.7 to 2.4)	.63
National walkability index in 2021 (score)^a		9.9 (4.2) [9.5]/474		9.7 (4.1) [9.2]/221	0.2 (−0.4 to 0.9)	.80
Index of Medical Underservice score, as of 2022^a		58.0 (7.4) [60.1]/94		58.7 (6.7) [60.3]/52	−0.8 (−3.2 to 1.7)	.54
Aggregate cost of medical care in 2019, $^a		41 000 000.00 (16 600 000.00) [38 800 000.00]/474		40 200 000.00 (17 300 000.00) [37 300 000.00]/221	788 674.90 (−1 897 034.00 to 3 474 384.00)	.76
Percentage uninsured (%)^a		3.6 (4.0) [2.4]/474		4.3 (4.5) [2.9]/221	−0.7 (−1.4 to −0.1)	.04
Percentage renter (%)^a		22.3 (22.7) [14.2]/474		25.2 (23.9) [17.3]/221	−2.9 (−6.6 to 0.8)	.04
Percentage rent burden (%)^a		41.1 (26.7) [41.6]/447		40.1 (27.0) [38.6]/210	0.9 (−3.5 to 5.3)	.20
Percentage using food assistance program (%)^a		8.0 (10.7) [4.5]/474		8.9 (11.1) [5.1]/221	−1.0 (−2.7 to 0.8)	.11

Open in a new tab

Abbreviation: NA, not applicable.

^{^a}

Continuous variable.

^{^b}

Categorical variable.

^{^c}

Other race and ethnicity includes Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, other, unknown, choose not to disclose, unable to obtain, or 2 or more races.

Among the baseline characteristics, patients who presented with visual acuity worse than 20/40 were older than patients who presented with better vision (mean [SD], 59.7 [12.5] years vs 55.2 [11.7] years; P < .001). Patients who had a fovea-involving RRD were similarly older than patients who had fovea-sparing RRD (mean [SD], 59.6 [12.8] years vs 57.2 [12.2] years; P = .01) (Table 2 and Table 3). In univariable logistic regression models, every year increase in age was associated with increased odds of presenting with worse vision (odds ratio [OR], 1.03; 95% CI, 1.02-1.04; P < .001) or fovea-involving RRD (OR, 1.02; 95% CI, 1.00-1.03; P = .02) (eTable in Supplement 1). Compared with non-Hispanic White patients, non-Hispanic Black patients had increased odds of presenting with worse vision and fovea-involving RRD (OR, 2.00; 95% CI, 1.18-3.38; P = .01 vs OR, 0.70; 95% CI, 0.17-2.82; P =.62 and OR, 1.85; 95% CI, 1.15-2.98; P = .01 vs OR, 0.77; 95% CI, 0.15-3.86; P =.75, respectively) (eTable in Supplement 1). Compared with private insurance, having public insurance was associated with increased odds of presenting with worse vision and fovea-involving RRD (OR, 1.60; 95% CI, 1.17-2.20; P = .004 and OR, 1.49; 95% CI, 1.07-2.07; P = .02, respectively), and having no insurance was associated with increased odds of presenting with worse vision (OR, 2.58; 95% CI, 1.14-5.84; P = .02) (eTable in Supplement 1).

Among the neighborhood-level SDOH, patients who presented with vision worse than 20/40 or fovea-involving RRD resided in neighborhoods with more socioeconomic disadvantage with a mean (SD) ADI score of 29.3 (20.3) vs 23.9 (19.7; P < .001) for visual acuity and 31.0 (21.3) vs 25.5 (19.5; P < .001) for fovea status (Table 2 and Table 3). In the multivariable analysis, every decile increase in ADI was associated with increased odds of presenting with worse visual acuity and fovea-involving RRD (OR, 1.14; 95% CI, 1.04-1.24; P = .004 and OR, 1.13; 95% CI, 1.04-1.22; P = .005, respectively) (Figure 2). Patients who presented with worse vision and fovea-involving RRD resided in neighborhoods with lower mean (SD) per capita income ($45 891.90 [$19 693.80] vs $51 886.80 [$21 483.80] for visual acuity; P < .001 and $45 582.40 [$21 086.70] vs $49 425.70 [$20 269.10] for fovea status; P = .02) (Table 2 and Table 3). Each $1000 increase in per capita income was associated with lower odds of presenting with worse vision (OR, 0.99; 95% CI, 0.98-0.99; P = .001) (Figure 2). Patients who presented with worse vision and fovea-involving RRD typically resided in neighborhoods with a higher percentage of workers who drove to work (mean [SD], 79.9 [12.2] vs 77.2 [13.5] for visual acuity; P = .01 and 80.4 [11.8] vs 78.2 [13.1] for fovea status; P = .046) (Table 2 and Table 3). Every 1% increase in percentage of workers who drove to work was associated with increased odds of presenting with worse vision and fovea-involving RRD (OR, 1.02; 95% CI, 1.01-1.03; P = .005 and OR, 1.01; 95% CI, 1.00-1.03; P = .04, respectively) (Figure 2). The predicted probabilities of presenting with vision worse than 20/40 and fovea-involving RRD by ADI, per capita income, and percentage of workers who drove to work are shown in the eFigure in Supplement 1. No other neighborhood-level SDOH had statistically significant associations with the dependent variables in multivariable models.

Figure 2. — ^aMultivariable analysis adjusting for age, sex, race and ethnicity, and insurance. ADI indicates Area Deprivation Index; IMU, Index of Medical Underservice.

Discussion

In this cohort study, we found associations between adverse neighborhood-level SDOH and the severity of the initial presentation among patients with RRD. Although the lower bounds of the CI is close to 1.0 for many of these associations and the values of the individual associations investigated were not adjusted for multiple analyses, patients who resided in neighborhoods with more socioeconomic deprivation (with higher ADI percentile rank and lower per capita income) had greater odds of presenting with visual acuity worse than 20/40 or fovea-involving RRD, even after accounting for multiple individual-level characteristics including age, sex, race and ethnicity, and insurance. Likewise, patients from neighborhoods where a higher percentage of people drove to work had greater odds of presenting with more severe RRD.

We examined baseline visual acuity and fovea status to determine RRD severity because these 2 baseline characteristics have remained the strongest and most consistent prognostic risk factors for postoperative visual acuity across decades of research.⁷ In 1982, Burton²⁷ demonstrated in a nonlinear regression model that duration of macular detachment was the only modifying factor in visual recovery after RRD repair. In 1998, Ross and Kozy²⁸ showed that good preoperative visual acuity portended good postoperative visual acuity and further clarified that after macular detachment, postoperative visual acuity did not differ across groups as long as the RRDs were repaired within the first 7 days. More recently, studies^29,30 have shown a benefit to postoperative visual acuity if macula-involving RRDs are repaired within the first 2 to 3 days instead of within 1 week. Early detection and surgical repair are also important to reduce complications, including retinal redetachment requiring repeat surgical repair, because chronic RRDs are associated with the development of proliferative vitreoretinopathy.³¹ This published body of work led us to our goals of identifying individual characteristics and neighborhood-level SDOH that are associated with baseline preoperative visual acuity and fovea status in RRD.

At the individual level, we found that non-Hispanic Black patients and those with public insurance had worse visual acuity and fovea-involving RRD, whereas older patients and those without medical insurance had worse visual acuity. Sex was not associated with either visual acuity or fovea status at baseline. These findings agree with a study of 1090 patients from the Cleveland Clinic Foundation that found that Black patients had worse visual acuity and macula-off status at baseline, whereas those with public insurance were more likely to have macula-off status compared with those with private insurance.³² In comparison, authors from the Wills Eye Hospital in a study with 4061 participants found that older, male, and non-White patients (dichotomized as White and non-White for statistical analysis purposes; self-reported races obtained from the medical record were recorded based on the US Census Bureau social groups) were more likely to have fovea-off status.¹⁶

The ADI, Social Deprivation Index, and Neighborhood Socioeconomic Status Index are composite measures of neighborhood-level SDOH in the US. In this study, we used the ADI because it has been associated with disease severity in many ophthalmic conditions. Patients with microbial keratitis who come from areas with higher ADI ranks, indicating more socioeconomic disadvantage, have greater odds of presenting with visual acuity worse than 20/40.³³ In a case series of patients with viral retinitis, those from neighborhoods with higher ADI ranks had worse visual acuity outcomes even after repair of RD.³⁴ In our study, the ADI was highly associated with both baseline visual acuity and fovea status even after controlling for age, sex, race and ethnicity, and insurance. These results concur with findings from the Scottish RD study, which collected all incident RRDs over a 2-year prospective period and examined neighborhood SDOH using the Scottish Index of Multiple Deprivation. The authors found that patients from the most economically deprived areas were more likely to present with macular detachments and total RRD.¹ In contrast, investigators from New Zealand found that the New Zealand Deprivation Index had no association with macula-off status at baseline.³⁵

The ADI includes median family income as one indicator of poverty. Other authors have similarly found an association between median household income and fovea and macula-off status.^16,32 Similarly, we examined per capita income as a separate measure of economic stability and found an inverse relationship with presenting visual acuity but not with fovea status. Although per capita income has not been previously explored in RRD, higher per capita income has been associated with higher cataract surgical rate.^36,37 Our finding that higher per capita income was associated with better baseline visual acuity but not foveal involvement could partially be confounded by the association with cataract surgery rate.

Although we hypothesized that other neighborhood-level SDOH related to the physical environment, such as transportation, housing conditions, and health care access, might be associated with more severe RRD at presentation, we found an association only with the neighborhoods with a high percentage of workers who drove to work. We postulate that patients without cars who live in neighborhoods where cars are necessary for work might have difficulty accessing health care and thus present later in the context of RRD. A prior study³³ of patients with microbial keratitis found that neighborhoods with a higher percentage of households with no cars were associated with increased odds of presenting with worse visual acuity. We did not specifically evaluate the percentage of occupied housing units without a motor vehicle as a separate variable because it is already reflected in the ADI.

Research has documented a persistent relationship between individual health and neighborhood conditions. These conditions are reflected in numerous overlapping forms, including the quality of the built environment, the strength of social organization and community ties, and living and working conditions. These relationships are complex.³⁸ Some of the neighborhood-level SDOH included here, such as the ADI, are ecological measures that reflect the socioeconomic deprivation of the neighborhood, whereas others, such as road density and Index of Medical Underservice score, more directly reflect the availability of resources. History, social policy, family and social ties, as well as personal taste combine to shape the demographics and resources of a neighborhood. Neighborhoods with high levels of socioeconomic disadvantage will be home to individuals with a gradient of incomes including high-income individuals.³⁹ It is thus important not to deterministically impute ecological measures onto individuals.⁴⁰

Limitations

This study has several limitations. Some of the neighborhood-level SDOH measures were calculated at a different time from when patients presented with an RRD. It would be ideal to align the neighborhood-level SDOH measure with when patients presented, but data limitations make this impossible. Some patients did not have all neighborhood-level SDOH information available due to data limitations. This study was conducted at a single institution in an urban environment. Therefore, we cannot determine how generalizable these results are to other places. Our cohort was predominantly non-Hispanic White, which could also limit its generalizability. Some neighborhood-level SDOH variables, eg, the ADI, could reflect ecological measures of socioeconomic deprivation rather than individual metrics for targeted policy. We were also limited in our ability to adjust certain variables such as aggregated cost of medical care by the population size. We also did not adjust for multiple comparisons as we did not want to reduce statistical power. The lower boundaries of the CIs for some of the associations were close to 1 suggesting that some of these findings could be within the realm of confounding factors.

Conclusions

In this cohort study, we found associations between neighborhood-level SDOH and how patients present with RRD. More work may be needed to better understand why these associations might be in place. For example, does access to health care or other individual-level characteristics prevent patients from seeking care early in the disease course? Findings from this study might help highlight neighborhoods that will benefit from policy changes and interventions that promote earlier presentation with RRD. Ultimately, interventions targeting these vulnerable populations may lead to earlier surgical repair, improved functional outcomes, reduced complication rates, and reduced health care spending. Future directions will examine how SDOH influence anatomic and visual outcomes after surgical repair of RRD.

Supplement 1.

eTable. Odds of Presenting With Visual Acuity Worse Than 20/40 or Fovea Involving Rhegmatogenous Retinal Detachment in Univariable Logistic Regression Models of Baseline Characteristics and Neighborhood-Level Social Determinants of Health

eFigure. Predicted Probability of Presenting With Vision Worse Than 20/40 and Fovea Involving Rhegmatogenous Retinal Detachment for Variables That Were Statistically Significant in the Multivariable Analysis

jamaophthalmol-e242889-s001.pdf^{(338.6KB, pdf)}

Supplement 2.

Data Sharing Statement.

jamaophthalmol-e242889-s002.pdf^{(13.5KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

jamaophthalmol-e242889-s001.pdf^{(338.6KB, pdf)}

Supplement 2.

Data Sharing Statement.

jamaophthalmol-e242889-s002.pdf^{(13.5KB, pdf)}

[eoi240045r1] 1.Mitry D, Charteris DG, Fleck BW, Campbell H, Singh J. The epidemiology of rhegmatogenous retinal detachment: geographical variation and clinical associations. Br J Ophthalmol. 2010;94(6):678-684. doi: 10.1136/bjo.2009.157727 [DOI] [PubMed] [Google Scholar]

[eoi240045r2] 2.Starr MR, Ryan EH, Yonekawa Y. Primary retinal detachment outcomes study: summary of reports number 1 to number 18. Curr Opin Ophthalmol. 2023;34(3):211-217. doi: 10.1097/ICU.0000000000000942 [DOI] [PubMed] [Google Scholar]

[eoi240045r3] 3.Feltgen N, Heimann H, Hoerauf H, Walter P, Hilgers RD, Heussen N; Writing group for the SPR study investigators . Scleral buckling vs primary vitrectomy in rhegmatogenous retinal detachment study (SPR study): risk assessment of anatomical outcome—SPR study report no. 7. Acta Ophthalmol. 2013;91(3):282-287. doi: 10.1111/j.1755-3768.2011.02344.x [DOI] [PubMed] [Google Scholar]

[eoi240045r4] 4.Ong SS, Ahmed I, Gonzales A, et al. Management of uncomplicated rhegmatogenous retinal detachments: a comparison of practice patterns and clinical outcomes in a real-world setting. Eye (Lond). 2023;37(4):684-691. doi: 10.1038/s41433-022-02028-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[eoi240045r5] 5.Klaas JE, Rechl P, Feucht N, et al. Functional recovery after macula involving retinal detachment and its correlation with preoperative biomarkers in optical coherence tomography. Graefes Arch Clin Exp Ophthalmol. 2021;259(9):2521-2531. doi: 10.1007/s00417-021-05113-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

[eoi240045r6] 6.Cai LZ, Lin J, Starr MR, et al. ; Primary Retinal Detachment Outcomes (PRO) Study Group . PRO score: predictive scoring system for visual outcomes after rhegmatogenous retinal detachment repair. Br J Ophthalmol. 2023;107(4):555-559. doi: 10.1136/bjophthalmol-2021-320440 [DOI] [PubMed] [Google Scholar]

[eoi240045r7] 7.Wykoff CC, Smiddy WE, Mathen T, Schwartz SG, Flynn HW Jr, Shi W. Fovea-sparing retinal detachments: time to surgery and visual outcomes. Am J Ophthalmol. 2010;150(2):205-210.e2. doi: 10.1016/j.ajo.2010.03.002 [DOI] [PubMed] [Google Scholar]

[eoi240045r8] 8.Chang CJ, Lai WW, Edward DP, Tso MO. Apoptotic photoreceptor cell death after traumatic retinal detachment in humans. Arch Ophthalmol. 1995;113(7):880-886. doi: 10.1001/archopht.1995.01100070054025 [DOI] [PubMed] [Google Scholar]

[eoi240045r9] 9.Kubay OV, Charteris DG, Newland HS, Raymond GL. Retinal detachment neuropathology and potential strategies for neuroprotection. Surv Ophthalmol. 2005;50(5):463-475. doi: 10.1016/j.survophthal.2005.06.004 [DOI] [PubMed] [Google Scholar]

[eoi240045r10] 10.Elam AR, Andrews C, Musch DC, Lee PP, Stein JD. Large disparities in receipt of glaucoma care between enrollees in medicaid and those with commercial health insurance. Ophthalmology. 2017;124(10):1442-1448. doi: 10.1016/j.ophtha.2017.05.003 [DOI] [PMC free article] [PubMed] [Google Scholar]

[eoi240045r11] 11.Nwanyanwu KH, Newman-Casey PA, Gardner TW, Lim JI. Beyond HbA_1c: environmental risk factors for diabetic retinopathy. J Clin Exp Ophthalmol. 2015;6(2):405. doi: 10.4172/2155-9570.1000405 [DOI] [PMC free article] [PubMed] [Google Scholar]

[eoi240045r12] 12.More P, Almuhtaseb H, Smith D, Fraser S, Lotery AJ. Socioeconomic status and outcomes for patients with age-related macular degeneration. Eye (Lond). 2019;33(8):1224-1231. doi: 10.1038/s41433-019-0393-3 [DOI] [PMC free article] [PubMed] [Google Scholar]

[eoi240045r13] 13.Moxon NR, Wang A, Margo CE, Greenberg PB, French DD. The association between complex cataract surgery and social determinants of health in Florida. Ophthalmic Epidemiol. 2022;29(3):279-285. doi: 10.1080/09286586.2021.1939888 [DOI] [PubMed] [Google Scholar]

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PERMALINK

Neighborhood-Level Social Determinants of Health and Presenting Characteristics for Rhegmatogenous Retinal Detachments

Sally S Ong, MD

Diep Tran, MSc

Erik Westlund, PhD

Ishrat Ahmed, MD

Gregory B Russell, MS

Anthony Gonzales, OD

James T Handa, MD

Cindy X Cai, MD, MS

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Patients

Neighborhood-Level SDOH

Dependent Variables and Other Characteristics at Baseline

Statistical Analysis

Results

Figure 1. Flow Diagram for Identification of Patients Included in the Study.

Table 1. Baseline Characteristics (Demographic Characteristics and Neighborhood-Level Social Determinants of Health) of Patients With Rhegmatogenous Retinal Detachments Evaluated at the Wilmer Eye Institute (N =700).

Table 2. Association of Presenting Visual Acuity (VA) Better Than or Equal to 20/40 or Worse Than 20/40 With Demographic Characteristics and Neighborhood-Level Social Determinants of Health.

Table 3. Association of Presenting Fovea Status (Fovea Sparing or Fovea Involving) With Demographic Characteristics and Neighborhood-Level Social Determinants of Health.

Figure 2. Odds Ratio (OR) and 95% CI of Presenting With Visual Acuity Worse Than 20/40 or Fovea-Involving Rhegmatogenous Retinal Detachment (RRD) in Multivariable Logistic Regression Models Adjusting for Age, Sex, Race and Ethnicity, and Insurance.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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