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Published in final edited form as: Surv Ophthalmol. 2025 Dec 31;71(3):997–1005. doi: 10.1016/j.survophthal.2025.12.008 Search in PMC Search in PubMed View in NLM Catalog Add to search Assessing the 3 pillars of housing for eye and vision health outcomes: A scoping review Sofia E Parellada Sofia E Parellada , MS a University of Miami Miller School of Medicine, Miami, FL, United States Find articles by Sofia E Parellada a , Kishan Avaiya Kishan Avaiya , BS b Georgetown University School of Medicine, Washington, DC, United States Find articles by Kishan Avaiya b , Khawla M Elnour Khawla M Elnour , BS c Howard University College of Medicine, Washington, DC, United States Find articles by Khawla M Elnour c , Mikhayla L Armstrong Mikhayla L Armstrong , BA d University of Chicago Pritzker School of Medicine, Chicago, IL, United States Find articles by Mikhayla L Armstrong d , Tiffani R Spaulding Tiffani R Spaulding , MD MPH e Department of Ophthalmology and Visual Science, University of Chicago, Chicago, IL, United States Find articles by Tiffani R Spaulding e , Kate M Saylor Kate M Saylor , MSI f Taubman Health Sciences Library, University of Michigan, Ann Arbor, MI, United States Find articles by Kate M Saylor f , Maria A Woodward Maria A Woodward , MD MS g Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States h Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States Find articles by Maria A Woodward g, h , Angela R Elam Angela R Elam , MD MPH g Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States h Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States Find articles by Angela R Elam g, h , Roshanak Mehdipanah Roshanak Mehdipanah , PhD MS i Department of Health Behavior and Health Education, School of Public Health, University of Michigan, Ann Arbor, MI, United States j Housing Solutions for Health Equity, University of Michigan, Ann Arbor, MI, United States Find articles by Roshanak Mehdipanah i, j , Paula Anne Newman-Casey Paula Anne Newman-Casey , MD MS g Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States h Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States Find articles by Paula Anne Newman-Casey g, h , Patrice M Hicks Patrice M Hicks , PhD MPH g Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States h Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States j Housing Solutions for Health Equity, University of Michigan, Ann Arbor, MI, United States Find articles by Patrice M Hicks g, h, j, * Author information Article notes Copyright and License information a University of Miami Miller School of Medicine, Miami, FL, United States b Georgetown University School of Medicine, Washington, DC, United States c Howard University College of Medicine, Washington, DC, United States d University of Chicago Pritzker School of Medicine, Chicago, IL, United States e Department of Ophthalmology and Visual Science, University of Chicago, Chicago, IL, United States f Taubman Health Sciences Library, University of Michigan, Ann Arbor, MI, United States g Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, United States h Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States i Department of Health Behavior and Health Education, School of Public Health, University of Michigan, Ann Arbor, MI, United States j Housing Solutions for Health Equity, University of Michigan, Ann Arbor, MI, United States * Correspondence to: 1000 Wall Street, Ann Arbor, MI 48105, United States. [email protected] (P.M. Hicks). Issue date 2026 May-Jun. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). PMC Copyright notice PMCID: PMC13084688 NIHMSID: NIHMS2159711 PMID: 41482135 The publisher's version of this article is available at Surv Ophthalmol Abstract In this scoping review, we examine the implications of 3 pillars (housing conditions and quality, residential consistency, and housing affordability) of healthy housing on vision health outcomes. We examine barriers based on geographical locations of the studies and World Health Organization income levels. We identified 11,190 abstracts, with 10,996 articles retrieved. Sixty-three met inclusion criteria. Among these, housing conditions emerged as the most frequently observed housing pillar associated with adverse vision health outcomes, cited in 62.1 % of the studies. Environmental pollution, particularly indoor air quality and exposure to harmful substances, was the most common condition associated with poor vision outcomes. Keywords: Housing, Social risk factors, Social determinants of health, Vision, Eye 1. Introduction Social determinants of health are estimated to account for 80–90 % of modifiable health factors, including those that impact vision health outcomes. 1 The Neighborhood and Built Environment domain is one of the five domains of Social Determinants of Health (SDoH) as defined by Healthy People 2030. 2 Factors within the Neighborhood and Built Environment domain that can impact vision health outcomes include pollution, transportation, housing, and neighborhood resources. Challenges in accessing adequate housing can have significant implications on health. 3 Populations experiencing housing disparities often face disproportionately high rates of chronic diseases, including HIV, diabetes, hypertension, asthma, and increased risk of cancer, anxiety, and depression. 3 , 4 Indices such as the Area Deprivation Index and the Distressed Communities Index, which include measures of housing quality, crowding, and affordability, have been associated with worse vision outcomes. Higher levels of neighborhood deprivation have also been independently associated with a greater odds of vision difficulty and blindness, underscoring the importance of examining the housing-related components within these indices. 5 This is consistent with the Tiebout hypothesis, which proposes that an individual’s income and wealth influence their residential choices and access to various amenities, including healthcare. 6 Consequently, individuals with limited financial resources may have limited housing options, making it more difficult to receive routine eye care. The pillars of housing and health include housing affordability, housing conditions and quality, residential consistency, and neighborhood factors. Our study utilized the housing framework by Hernández and Swope to both assess and organize the literature. 7 The housing conditions and quality pillar examines whether the physical hardware or environmental conditions of a building or unit are adequate. Poor housing conditions have been linked to general health issues, which in turn can affect vision health. Exposure to pollutants has been associated with an increased risk of dry eye disease, glaucoma, and age-related macular degeneration, emphasizing the need to consider environmental factors in housing that may contribute to ocular diseases. 2 The residential consistency pillar assesses the stability of the residents and whether they can reside in that home for as long as they wish or if they are faced with multiple moves or eviction. People who do not have stable, safe, secure housing have disproportionately high rates of chronic diseases. 8 For example, according to Maslow’s hierarchy, meeting basic needs like shelter takes priority over seeking preventive healthcare, so individuals facing housing insecurity are less likely to prioritize routine eye care, and traditional clinics may not address their pressing social needs. 9 – 12 The housing affordability pillar examines whether a resident can pay their rent or mortgage without financial burden. It is estimated that nearly half of renter households are cost-burdened, as their incomes allocate greater than 30 % of their income to rent each month. 13 This financial burden diverts financial resources away from health maintenance, which may then negatively impact health outcomes. Finally, the neighborhood factors pillar encompasses the positive or negative health-relevant resources in the surrounding neighborhood. This includes walkability, access to transportation, green spaces and parks for physical activity, and institutions such as grocery stores. Lack of access to transportation can make it difficult for patients to access eye care and limited resources such as grocery stores and green spaces can make it difficult to manage chronic disease such as diabetes, and uncontrolled diabetes can lead to complications including diabetic retinopathy. This scoping review explored the impact of the pillars of housing on vision health in the United States and internationally. We aim to provide a comprehensive understanding of how housing may impact vision health, which can provide insight into policies and interventions that address housing as a social risk factor impacting eye and vision health outcomes. 2. Methods The proposed search frameworks of Arksey and O’Malley and Levac and colleagues were used for this scoping review, which follows the JBI Manual for Evidence Synthesis: Chapter 11 -Scoping Reviews. 14 – 16 A protocol was formulated in advance and reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for Protocols (PRISMA-P) and is available here: ( https://dx.doi.org/10.7302/23639 ). This review was reported according to the PRISMA extension for scoping review (PRISMA-ScR). The team followed a multi-step, iterative process for developing and refining the search strategy. 2.1. Search strategy The review team collaborated with an informationist (K.M.S) in May, 2023, to identify the target outcomes and created a relevant search strategy, which was utilized to select potential databases to acquire search terms, concepts, and evidence. A study team member ( P.M.H ) reviewed search terms and results for the databases and provided feedback to obtain the final searches for the databases. EndNote 20 (Clarivate, London, UK) was utilized to manage citations and remove duplicate articles. The databases used for this review include Ovid MEDLINE, Embase (Elsevier), CINAHL Complete (EBSCO), PsycINFO (EBSCO), SocINDEX with Full Text (EBSCO), Web of Science (SCI-EXPANDED, SSCI, and ESCI), and Scopus (Elsevier). The final MEDLINE search strategy can be accessed in Supplemental Figure 1 . 2.2. Selection of evidence The Rayyan-Intelligent Systematic Review program (Rayyan Systems Inc., Cambridge, MA) was utilized to review citations. The exclusion criteria were as follows: articles that are reviews, abstracts, case reports, or opinion pieces. We exclusively looked at articles written in English, as we were not able to provide translations of non-English articles. All review screeners completed an initial training by studying the protocol developed for this scoping review. A pilot test was conducted on 10 % of the total articles found, and the screening began once a 75 % agreement was met between two primary screeners for the pilot test (P.M.H. and M. L.A. or S.E.P. or K.E.). During the screening process, at least 2 reviewers analyzed each source at each level (title abstract and full-article review), and disagreements were reconciled by consensus or by a third reviewer. In accordance with the PRISMA-ScR statement, a flowchart and narrative description of the evidence selection process were created and presented in Fig. 1 . Fig. 1. Open in a new tab PRISMA flow diagram of study selection for the housing and eye health scoping review. 2.2.1. Data extraction Data extracted from the articles included: title, author(s), year of publication, country, aims of the study, location, topic of the study (vision condition or eye care), housing pillar (cost, conditions, consistency) and social risk factor assessed, type of study, and how source findings were obtained (interview, survey, electronic medical record, etc.). Income group by the World Health Organization (WHO) classification system was also identified. Housing pillar information was categorized into explored and observed categorizations, where explored refers to if a study assessed the housing pillar within their study and observed means that the study found the housing pillar was linked to the eye or vision outcome. 2.2.2. Pillars of housing We analyzed pillars of housing (conditions and quality, residential consistency, affordability) across the sources reviewed to understand if and which of them impact vision health and eye care. The pillars of conditions (housing quality), consistency (residential stability), and cost (housing affordability) come from Swope and Hernández. Reviewers (P. M.H. and M.L.A.) sorted the outcomes of all included studies and categorized them into 1 or more of the 3 pillars. 3. Results 3.1. Search results and studies included A search was conducted utilizing the search terms from Supplemental Figure 1 . The search yielded a total of 11,190 records. After 194 duplicate records were removed, the remaining 10,996 records were screened by title and abstract. A total of 196 articles were selected for full-text review, of which 133 were excluded for various reasons, including wrong outcome (n = 51), article did not explore housing/social risk factors (n = 33), publication type (32), article did not mention eye care (n = 15), and children under 18 (n = 2). A total of 63 articles (n = 22 in the US, n = 41 international) published between February 2013 and January 2024 were included in this scoping review. A narrative description and flowchart of the evidence selection process is provided in Fig. 1 . The explored and observed pillars of housing for each article by eye condition are found in Supplemental Table 1 . Explored and observed risk factors were organized into the 3 pillars of housing according to the codebook outlined in Supplemental Table 2 . All articles included and the identified pillars of housing are summarized in Table 1 . An explored pillar of housing means that the study looked for correlation between that pillar of housing and an eye condition. If the explored pillar of housing was seen to correlate with an eye condition, it is listed as observed. Multiple eye conditions 5 , 17 – 36 (n = 20) had the most number of articles, followed by visual impairment 37 – 45 (n = 9), diabetic retinopathy 46 – 50 (n = 5), eye irritation 51 – 54 (n = 4), dry eye 55 – 57 (n = 3), glaucoma 58 – 60 (n = 3), trachoma 61 – 63 (n = 3), eye infections 64 – 66 (n = 3), cataract 67 , 68 (n = 2), conjunctivitis 3 , 29 (n = 2), eyesight 30 , 69 (2 articles), refractive error 49 , 63 (n = 2), retinal vein occlusion 70 (n = 1), neuromyelitis optica spectrum disorder 71 (n = 1), ocular toxoplasmosis 72 (n = 1), exfoliation syndrome 73 (n = 1), and ambylopia 74 (n = 1). The housing pillars included the following: 2 articles identified affordability, 42 articles identified conditions and quality, and 23 articles identified residential consistency. While studies may have explored more than one pillar of housing, they may have either not observed or only observed a specific pillar of housing in their study. Associations with housing conditions were the most explored (66.7 %) and observed (60.3 %) pillar of housing from the 63 total studies. Affordability was the least explored (3.2 %) and observed (3.2 %) pillar of housing from all the studies. For both US and international studies, conditions were the most explored pillar of housing (59.1 % and 70.7 %, respectively), and affordability was the least explored pillar of housing (9.1 % and 0.0 %, respectively). Of the 59.1 % of US studies that explored conditions, 92.3 % also observed conditions. Of the 70.7 % of international studies that explored conditions, 89.7 % observed conditions. US articles explored all 3 pillars of housing, whereas international articles only explored 2 of the pillars. From the articles explored, US articles observed all 3 pillars of housing: affordability (100.0 %), conditions and quality (92.3 %), and residential consistency (62.5 %). Of the 2 pillars that the international articles explored, they observed conditions (89.7 %) and residential consistency (66.7 %). ( Table 2 ). Table 1. Explored and observed pillars of housing by eye condition. Author / Year Country Explored Pillars of Housing Pillars of Housing Observed WHO income group Cost Conditions Consistency Cost Conditions Consistency Dry Eye Kaplan et al. 2019 USA X X High Huang et al. 2021 USA X X High Rock et al. 2022 USA X X High Glaucoma Bhorade et al. 2013 USA X X High Ramulu et al. 2022 USA X X High Yonge et al. 2018 USA X High Cataract Vashist et al. 2020 India X X Lower middle Quintana et al. 2013 Spain X X High Diabetic Retinopathy Thomas et al. 2021 UK X X High Chauhan et al. 2020 India X X Lower middle Silverberg et al. 2021 USA X High Davis et al. 2017 USA X X High Cai et al. 2021 USA X X High Retinal Vein Occlusion McDermott et al. 2022 USA X X High Neuromyelitis Optica Spectrum Disorder Rafiee et al. 2020 Iran X X Upper middle Ocular Toxoplasmosis Abu et al. 2016 Ghana X Lower middle Exfoliation Syndrome Aygun et al. 2023 Turkey X X Upper middle Amblyopia Bountziouka et al. 2021 UK X High Conjunctivitis Reboux et al. 2018 France X High Suryani et al. 2021 Indonesia X X Upper middle Trachoma Debrah et al. 2017 Ghana X Lower middle Chen et al. 2021 Tanzania X X Lower middle Silva et al. 2020 Brazil X X X Upper middle Eye Irritation Youssef et al. 2021 Morocco X X Lower middle Zhang et al. 2018 China X X Upper middle Johnston et al. 2022 USA X X High Yang et al. 2021 Sweden X X X High Eye Infections Firdaus et al. 2012 India X X Lower middle Lopez et al. 2024 USA X X High Carnt et al. 2020 UK X X High Eyesight Melody et al. 2016 Australia X X High Shiue et al. 2015 USA X X High Visual Impairment Lee et al. 2018 Korea X X High Brown et al. 2016 USA X X High Lebrun-Harris et al. 2012 USA X High Pesonen et al. 2022 Finland X X High Tham et al. 2018 Singapore X X High Pooprasert et al. 2020 UK X X High Alvarado-Esquivel et al. 2015 Mexico X X Upper middle Wong et al. 2020 Hong Kong X X High Andersson et al. 2020 USA X X High Refractive Error D’ath et al. 2016 UK X X High Marmamula et al. 2020 India X X Lower middle Multiple Eye Conditions Haanes et al. 2015 Norway X X High Hom et al. 2021 USA X X High Hennein et al. 2021 USA X X High French et al. 2019 USA X X X X High Slomovic et al. 2023 Canada X X High Abdu et al. 2013 Nigeria X X X Lower middle Wang et al. 2023 China X X Upper middle Sutradhar et al. 2019 Bangladesh X X Lower middle Hennein et al. 2020 USA X High Sukhsohale et al. 2013 India X X Lower middle Elliott et al. 2019 USA X X High Park et al. 2024 Canada X High Jiang et al. 2020 Canada X X High Low et al. 2020 Singapore X X High Yelle et al. 2022 Canada X X High Sawers et al. 2016 UK X X High Marmamula et al. 2023 India X X Lower middle Yekta et al. 2019 Iran X X Upper middle Noel et al. 2015 Canada X X High Ryu et al. 2018 USA X X High Open in a new tab Notes: “X” indicates that the pillar was explored or observed in the study. WHO = World Health Organization. Table 2. Pillars of housing and percentage by location. Pillars of Housing Explored Pillars of Housing Pillars of Housing Observed Total (n = 63) United States (n = 22) International (n = 41) Total (n = 63) United States (n = 22) International (n = 41) Cost 3.2 % (2) 9.1 % (2) 0.0 % (0) 3.2% (2) 100.0 % (2) 0.0 % (0) Conditions 66.7 % (42) 59.1% (13) 70.7 % (29) 60.3 % (38) 92.3% (12) 89.7 % (26) Consistency 36.5 % (23) 36.4 % (8) 36.6 % (15) 23.8 % (15) 62.5 % (5) 66.7 % (10) Open in a new tab Out of 17 different categories of eye conditions studied from the articles included in the review, only “multiple eye conditions” explored all 3 pillars of housing: affordability (10.0 %), conditions and quality (60.0 %), and residential consistency (40.0). 5 , 17 – 22 , 24 – 36 This category was defined as articles that researched more than one ophthalmic condition. Of these explored pillars, 100 % of articles observed affordability, 100 % observed conditions, and 62.5 % observed residential consistency. Affordability was only explored and observed by articles that studied multiple eye conditions. Studies that looked at dry eye disease 1 , 56 , 57 (n = 3), glaucoma 58 – 60 (n = 3), ocular toxoplasmosis 72 (n = 1), exfoliation syndrome 73 (n = 1), conjunctivitis 75 , 76 (n = 2), and eyesight 69 , 77 (n = 2) only explored conditions, and studies that looked at retinal vein occlusion 70 (n = 1) and neuromyelitis optica spectrum disorder 71 (n = 1) only explored consistency. Articles about ocular toxoplasmosis and amblyopia explored correlation between the three pillars of housing but none were observed ( Table 3 ). Studies were also analyzed by income groups based on the World Health Organization (WHO) classification system. Most studies were published or conducted in countries from the High WHO income group (n = 43), with no studies identified from the Low WHO income group. The housing conditions and quality pillar was the most explored across all WHO income groups: High (57.8 %), Upper Middle (87.5 %), and Lower Middle (100.0 %). Of the articles that explored housing conditions and quality, the percentage that also observed conditions was: High (91.3 %), Upper Middle (100 %), and Lower Middle (83.3 %). Interestingly, affordability was only explored and observed by countries that identified in the High WHO income group. ( Table 4 ). Table 3. Pillars of housing and percentage by eye condition. Explored Pillars of Housing Pillars of Housing Observed Condition Cost Conditions Consistency Cost Conditions Consistency Dry eye disease (3) 0.0 % (0) 100 % (3) 0.0 % (0) 0.0 % (0) 100.0 % (3) 0.0 % (0) Glaucoma (3) 0.0 % (0) 100 % (3) 0.0 % (0) 0.0 % (0) 66.7 % (2) 0.0 % (0) Cataract (2) 0.0 % (0) 50 % (1) 50 % (1) 0.0 % (0) 100.0% (1) 100.0 % (1) Diabetic Retinopathy (5) 0.0 % (0) 40.0 % (2) 60.0 % (3) 0.0 % (0) 100.0 % (2) 66.7 % (2) Retinal Vein Occlusion (1) 0.0 % (0) 0.0 % (0) 100.0 % (1) 0.0 % (0) 0.0 % (0) 100.0 % (1) Neuromyelitis Optica Spectrum Disorder (1) 0.0 % (0) 0.0 % (0) 100.0 % (1) 0.0 % (0) 0.0 % (0) 100.0 % (1) Ocular Toxoplasmosis (1) 0.0 % (0) 100.0% (1) 0.0 % (0) 0.0 % (0) 0.0 % (0) 0.0 % (0) Exfoliation Syndrome (1) 0.0 % (0) 100.0% (1) 0.0 % (0) 0.0 % (0) 100.0% (1) 0.0 % (0) Amblyopia (1) 0.0 % (0) 0.0 % (0) 100.0 % (1) 0.0 % (0) 0.0 % (0) 0.0 % (0) Conjunctivitis (2) 0.0 % (0) 100.0 % (2) 0.0 % (0) 0.0 % (0) 50.0 % (1) 0.0 % (0) Trachoma (3) 0.0 % (0) 100.0 % (3) 33.3 % (1) 0.0 % (0) 66.7 % (2) 0.0 % (0) Eye Irritation (4) 0.0 % (0) 100.0 % (4) 25.0 % (1) 0.0 % (0) 100.0 % (4) 0.0 % (0) Eye Infections (3) 0.0 % (0) 66.7 % (2) 33.3 % (1) 0.0 % (0) 100.0 % (2) 100.0 % (1) Eyesight (2) 0.0 % (0) 100.0 % (2) 0.0 % (0) 0.0 % (0) 100.0 % (2) 0.0 % (0) Visual Impairment (9) 0.0 % (0) 55.6 % (5) 44.4 % (4) 0.0 % (0) 100.0 % (5) 75.0 % (3) Refractive Error (2) 0.0 % (0) 50 % (1) 50 % (1) 0.0 % (0) 100.0% (1) 100.0 % (1) Multiple Eye Conditions (20) 10.0 % (2) 60.0% (12) 40.0 % (8) 100.0 % (2) 100.0% (12) 62.5 % (5) Open in a new tab Table 4. Pillars of housing and percentage and frequency by WHO income groups. Explored Pillars of Housing Pillars of Housing Observed WHO income group WHO income group Pillars of Housing Total (n = 63) High (n = 43) Upper Middle (n = 8) Lower Middle (n = 12) Low (n = 0) Total (n = 63) High (n = 43) Upper Middle (n = 8) Lower Middle (n = 12) Low (n = 0) Cost 3.2 % (2) 4.7 % (2) 0.0 % (0) 0.0 % (0) 0.0 % (0) 3.2% (2) 100.0 % (2) 0.0 % (0) 0.0 % (0) 0.0 % (0) Conditions 66.7 % (42) 57.8 % (23) 87.5 % (7) 100.0 %(12) 0.0 % (0) 60.3 % (38) 91.3 % (21) 100.0 % (7) 83.3 % (10) 0.0 % (0) Consistency 36.5 % (23) 46.5 % (20) 25.0 % (2) 8.3 %(1) 0.0 % (0) 23.8 % (15) 70.0 % (14) 50.0 % (1) 0.0 % (0) 0.0 % (0) Open in a new tab 3.1.1. Housing pillars assessed for review 3.1.1.1. Housing conditions and quality. Factors related to the housing conditions and quality pillar were the most reported association with eye and vision outcomes, observed in 62.1 % of studies ( Table 2 ). All housing conditions and quality measures explored and observed were simplified into 13 categories: pollution, humidity, temperature, home hazards, home age, lighting, location, home type, number of persons residing in the home, home cleanliness, home damage, proper heating and ventilation, and marginal housing. Marginal housing is defined as which is defined as shelters, rooming houses, or single room occupancy hotels, observed a relationship with vision health. Each study that examined and identified an association within these categories was counted accordingly. A total of 8 studies examined the impact of pollution on eye health, with all reporting a significant effect on vision health. 19 , 32 , 52 , 53 , 55 , 56 , 65 , 68 , 77 Five studies assessed home humidity levels, with 60 % identifying an association between higher humidity in the home and negative ocular symptoms and higher rate of microbial growth in the home. 54 , 55 , 57 Zhang and colleagues controlled for potential confounders, such as age, smoking status, location, and use of air cleaning equipment. 54 Rock and colleagues controlled for age and sex, but not all environmental factors. 57 Regarding home temperature, 4 studies explored the influence, but only 1 observed that lower temperatures in the home may be associated with a higher amount of particle surface area on the ocular surface. 56 Nine studies investigated various home hazards as potential risk factors for vision health, with 4 reporting a significant effect. 17 , 37 , 40 , 53 , 63 , 65 All 5 studies that examined the role of home lighting found a connection to vision health. 20 , 34 , 40 , 58 , 59 Conversely, only 40 % of studies assessing the number of residents in a home observed an effect. 19 , 46 , 52 , 70 , 77 No studies reported an association between home damage in the past 12 months and vision health; however, home cleanliness was found to be a contributing factor in 5 out of the 9 studies that considered it. 52 – 54 , 57 , 61 , 63 , 64 Proper heating and ventilation were evaluated in eight studies. In 2 studies, particulate matter (PM) exposure in the home was observed to affect the human ocular surface. 55 , 56 Lastly, all studies that examined home type (n = 10) 17 , 18 , 25 , 26 , 29 , 36 , 44 , 53 , 63 , 73 and marginal housing (n = 3). 31 3.1.2. Residential consistency Residential consistency was reported to have an association with a variety of eye and vision outcomes in 22.7 % of studies ( Table 2 ). Consistency was simplified into 5 categories: number of persons in the home, home ownership, location, length of stay in the home, and housing status (housed vs. unhoused). Of the 5 studies that explored the impact of number of residents in the house, only 40 % found an impact. 67 , 73 In a similar fashion, home ownership (renting vs. owned) was explored in eight studies and observed to have an association in 25 % of studies. 67 , 70 One study explored location as a factor in housing stability and found it to be influential. 26 Of the 4 studies assessing the length of stay, 2 identified an association. 21 , 50 , 70 Lastly, housing status was the most frequently reported factor under consistency, with 77 % (10 out of 13 studies) finding a significant link to vision health. 21 , 24 , 27 , 30 , 35 , 39 , 43 , 48 , 66 , 71 , 78 3.1.3. Housing affordability Cost of housing was the least reported association with eye and vision outcomes, observed in only two studies (3.2 %) ( Table 2 ). Both investigated housing payments and the impact on vision health and found a significant association. 23 No other cost-related factors were explored or observed ( Table 3 ). 4. Discussion This scoping review mapped the current literature on the impact of housing on eye and vision health utilizing 3 of the 4 pillars of housing as defined by Swope and Hernandez. 76 We identified 63 studies that explored housing and eye and vision health. In total, 42 studies explored an association between housing conditions and quality and vision health, 23 studies explored an association between residential consistency and vision health, and 2 studies explored housing affordability and vision health. Of these studies, 10 reported an association between housing conditions and quality and vision health, 10 reported an association between residential consistency and vision health, and 2 reported an association between housing affordability and vision health. This is the first review to examine the different dimensions of housing and their associations with eye and vision health outcomes. Regarding housing conditions and quality, Kaplan and colleagues studied PM in the eye in both clinic and home environments and found that they were associated with select signs of dry eye syndrome (DES). 56 Specifically, there was a Relationship between PM type, home environment, and DES metrics including tear osmolarity (ρ = −0.60, P = 0.02), inflammation (ρ = 0.53, P = 0.04), and tear break-up time (ρ = 0.56, P = 0.03). Huang and colleagues found similar results, stating that some aspects of DES, such as evoked pain and palpebral conjunctival abnormalities, correlated with PM in the home. 55 Exposure to PM2.5 may lead to DES through corneal epithelial inflammation and mitochondrial dysfunctions. 79 Several housing conditions were observed to contribute to symptomatology in patients with eye irritation and infections, including building characteristics (age of building, housing type, and number of persons in the home), home humidity levels, cleanliness, proper heating and ventilation, and pollution. 52 , 53 , 61 , 63 – 65 Youssef and colleagues collected data from 73 houses in Morocco on the characteristics of the house and the clinical manifestations of the inhabitants. 53 They found that there is a statistically significant association between dust in the home and clinical manifestations including eye irritation and blurred vision (Relative Risk = 1.20, 95 % CI:1.05–1.37, p < 0.05). In Brazil, Silva and colleagues found an association between trachoma in students aged 7–16 years old and inadequate living conditions, including unfinished houses i.e., no plastering, painting, flooring, and unfinished bathrooms (OR: 2.27; 95 % CI:1.12–6.48, p = 0.027) and lack of sewage systems (OR: 3.37; 95 % CI: 1.53–7.35, p < 0.001). 63 It is well recognized that individuals that have unstable housing or who are unhoused have an increased risk of poor health outcomes and hospitalization due to a lack of access to medical care, including but not limited to increased rates of diabetes, myocardial infarctions, cancers, and addiction. 24 , 80 , 81 When looking at residential consistency and visual impairment, a study by Yelle and colleagues examined 95 individuals who were unhoused in 5 different shelters in Montreal. 35 Ophthalmologists provided examinations and found an age-adjusted 4 times the prevalence of visual impairment in the population (23.6 %), compared to the general Canadian (6 %) population (p < 0.0001). Study participants were also significantly less likely (18.9 % vs. 41.4 %; p < 0.0001) to have had an eye exam in the last year compared to the general population. 35 Similar trends were observed in other studies, including a study by Noel and colleagues reporting that a population experiencing homelessness in Toronto was found to have an increased prevalence of visual impairment, based on presenting visual impairment with a visual acuity worse than 20/40 in the better eye, compared to the general Canadian population (10.3 % vs 0.5 %; p < 0.001). 27 The final pillar of housing we examined was housing affordability, examining the association between cost of living and access to eye and vision health. This measure includes expenses such as rent, mortgage, and utilities. 7 Hom and colleagues based out of the United States, conducted a retrospective cross-sectional study using data from the 2017 National Health Interview Survey to assess worry of housing payments in individuals with eye disease. 23 Results showed that 17.06 % of individuals with eye conditions reported worrying about housing payments, and individuals that identified as Black race (adjusted odds ratio (aOR): 1.44, 1.16–1.80, p = 0.001) or Hispanic ethnicity (aOR:1.57, 95 % CI: 1.20–2.06, p < 0.001) reported worrying about housing payments more than White individuals. In addition, women (aOR: 1.19, 95 % CI: 1.02–1.38, p = 0.023) were more likely to worry about housing payments compared to men. Individuals living at 100–200 % of the federal poverty line (aOR:2.06; 95 % CI: 1.70–2.49) or below the poverty line (aOR:1.96, 95 % CI: 1.54–2.49, <0.001) were also more likely to report worry about housing payments. 23 French and colleagues reported that Medicare ocular hospitalizations were greater in communities where severe housing problems were present, including housing costs over 50 % of household monthly income (OR:1.13, 95 % CI: 1.09–1.18, p < 0.01). 19 Housing cost, as well as housing operating costs, can directly impact eye and vision outcomes by diverting financial resources that could otherwise be allocated to essential health services such as eye examinations and follow-up appointments, treatments including glasses or glaucoma medication, or transportation to access appointments or treatment. 7 Recent work by Ige and colleagues demonstrates that financial strain can directly impact the quality of eye care, as glaucoma patients in the lowest wealth quartile were significantly less likely to achieve the US National Quality Forum’s recommended intraocular pressure reduction targets and were more likely to be lost to follow-up. These findings reinforce that economic hardship can impede sustained engagement with crucial eye care services. 82 Of the 63 articles, 41 of them were conducted internationally. The most represented countries were England, India, and Canada. Many of these articles focused on multiple eye conditions (34.1 %), closely followed by issues in visual impairment (14.6 %), eye irritation (7.3 %), and trachoma (7.3 %). The most observed pillar in the international articles was housing conditions and quality with 68.2 % of articles reporting an observed condition. In total, 24.4 % observed problems with residential consistency. None examined housing affordability in their studies. The most observed conditions for international studies included home cleanliness, indoor air pollution, proper heating and ventilation, and home type. The 3 articles that studied trachoma, the leading cause of preventable blindness in the world, were from Brazil, Ghana, and Tanzania. It is well known that the prevalence of trachoma is higher in low-resourced countries. 12 While Brazil is generally classified as an upper-middle-income country, several regions—particularly in the North, where the study was conducted—face significant unmet needs in healthcare services, access to medications, and poor sanitation. 63 , 83 In Tanzania, Chen and colleagues conducted a household survey in the Kongwa region focused on facial cleanliness, a protective factor against trachoma. They found that the household cleanliness index directly correlates with levels of infection. 61 Specifically, a 0.5-point increase in the community average household cleanliness score was linked to a 2.28 times greater likelihood of reducing trachoma prevalence by one category (i.e., from ≥10 % to 5–9.9 %, or from 5 to 9.9 % to <5 %; odds ratio = 2.28, 95 % CI = 1.17–4.80). This scoping review identified several gaps in eye and vision research related to the housing pillars. Almost a third of the studies included in the review assessed multiple eye conditions; thus, it is important to examine individual housing pillars associated with each eye condition to draw more precise conclusions about their unique impacts. No studies assessing housing pillars in relation to eye and vision health outcomes were conducted in WHO-designated low-income countries, indicating a need for research in these areas. In the conditions pillar of housing, the air pollutants studied included both Particulate Matter 2.5 and 10. Future research should assess additional air pollutants, such as indoor air pollutants like wood smoke, mold spores, cooking fuels, that have yet to be examined for associations with eye disease and vision health. For the consistency pillar, the factors considered included length of stay in the home, number of people in the home, home ownership, and location of the home. A key measure that was not directly assessed in any of the studies was the impact of short-term housing situations, such as involuntary removal from one’s home and community (i.e., natural disasters, eviction, gentrification, or foreclosure), and their hindrance to eye and vision health-related resources, including healthcare, employment, and social support. 7 For the affordability pillar, no international studies were conducted; thus, there is a significant need to assess the implications of this housing pillar on eye care utilization and vision health outcomes in diverse settings. Furthermore, the only studies conducted for this pillar were in a high-income country (the US), which do show that lower cost burden improves vision outcomes. As this review has highlighted, the housing pillars have implications for both eye and vision outcomes, so future research is needed in these understudied areas. There are limitations to this review. First, the results are subject to the limitations of a scoping review which include selection bias, date limitations, and database selection. In addition to this, 41 of the 63 studies included were conducted internationally, limiting the generalizability to the United States. Finally, the pillar of neighborhood factors was not assessed, as that focuses on the residential area and built environment context and not on the home itself. Housing is a social determinant of health that can contribute to vision health disparities. This review highlights the potential impact that the pillars of housing can have on eye and vision health. It is important to note that in the context of eye care and vision research, each of these pillars has largely been explored in isolation, despite evidence that they influence one another, thus it is important to consider that the impact of a single housing factor on eye and vision health outcomes could also shaped by other related social and housing factors. 7 For example, if a patient with diabetes utilizes the majority of their income to pay for housing, they may be unable to afford nutritious foods, their medication, and routine care for diabetes management which can lead to unmanaged diabetes and greater risk for diabetic retinopathy. 84 It could be helpful for eye care clinics to implement a social risk factor screening to account for not only food insecurity, transportation, and medication affordability but also to identify housing instability and quality. Patients that have housing needs can be connected with social workers who can aid in facilitating referrals to rent assistance programs, housing quality improvement programs, and independent living services. At the systems level, developing health policy solutions to address housing insecurity are vital for improving general health and eye and vision health in the United States. 5. Conclusion The housing pillars conditions and quality were reported as most associated with eye and vision outcome. The housing affordability and its association to eye and vision health was the least studied. As the majority of existing studies were conducted internationally, additional research is needed in the United States on the impacts of housing on eye and vision health outcomes. Overall, pillars of health of housing are key social risk factors impacting eye and vision health outcomes, which should be considered when addressing eye and vision health disparities. Methods of literature search This scoping review included peer-reviewed qualitative, quantitative, or mixed-methods studies written in English that examined housing in relation to eye care and vision health among adults aged 18 years and older. We excluded reviews, abstracts, case reports, opinion pieces, and non-English articles due to translation limitations. The full study protocol including methods of literature search has been deposited: https://dx.doi.org/10.7302/23639 . Supplementary Material 1 NIHMS2159711-supplement-1.docx (58.9KB, docx) 2 NIHMS2159711-supplement-2.docx (24.8KB, docx) 3 NIHMS2159711-supplement-3.docx (19.8KB, docx) 4 NIHMS2159711-supplement-4.docx (25.1KB, docx) Funding The authors have no proprietary or commercial interest in any materials discussed in this article. This research was supported by the National Institutes of Health (NEI R01EY031337–03S1, Hicks; NIGMS K12GM111725, Hicks; P30 EY007003, Hicks and Woodward), National Institutes of Health National Cancer Institute Grant numbers: U54CA280805 (PMH) and National Institute on Minority Health and Health Disparities Grant numbers: K23MD016430 (ARE). Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at doi: 10.1016/j.survophthal.2025.12.008 . Footnotes Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: NORC Consultant – Patrice Hicks does not directly pertain to this work, but reporting. CRediT authorship contribution statement Sofia E. Parellada: Writing – review & editing, Writing – original draft, Visualization, Investigation, Formal analysis, Data curation, Conceptualization. Kishan Avaiya: Writing – review & editing, Writing – original draft, Visualization, Investigation, Formal analysis. Khawla M. Elnour: Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation. Mikhayla L. Armstrong: Writing – review & editing, Writing – original draft, Investigation, Data curation. Tiffani R. Spaulding: Writing – review & editing, Writing – original draft, Investigation. Kate M. Saylor: Validation, Software, Methodology, Data curation. Maria A. Woodward: Writing – review & editing, Writing – original draft, Validation, Methodology. Angela R. Elam: Writing – review & editing, Writing – original draft, Investigation. Roshanak Mehdipanah: Writing – review & editing, Writing – original draft, Methodology, Investigation, Conceptualization. Paula Anne Newman-Casey: Writing – review & editing, Writing – original draft, Resources, Methodology. 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