利用多层次模型分析邻里层面的社会风险因素测量值与青光眼发病严重程度之间的关系

IF 3.2 Q1 OPHTHALMOLOGY Ophthalmology science Pub Date : 2024-08-22 DOI:10.1016/j.xops.2024.100598
Patrice M. Hicks PhD, MPH , Ming-Chen Lu MS , Maria A. Woodward MD, MS , Leslie M. Niziol MS , Deborah Darnley-Fisch MD , Michele Heisler MD , Kenneth Resnicow PhD , David C. Musch PhD, MPH , Jamie Mitchell PhD, MSW , Roshanak Mehdipanah PhD, MS , Nauman R. Imami MD , Paula Anne Newman-Casey MD MS
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引用次数: 0

摘要

目的邻里和建筑环境是健康的社会决定因素,其中有几个社会风险因素 (SRF),可通过政策努力加以改变。我们在密歇根大学的电子健康记录(EHR)中对 2012 年 8 月至 2022 年 5 月期间的横断面研究进行了调查。方法根据《国际疾病分类》第九版和第十版修订代码 (365.x/H40.x) 确定符合纳入标准的患者。从电子病历(EHR)中提取的数据包括患者的人口统计学特征、地址、出现的平均偏差(MD)和 VF 可靠性。地址被映射到人口普查区、街区组和县一级的 SRF 指标。多层次线性回归模型用于估算每个 SRF 对 MD 的固定效应,然后再对患者层面的人口统计学因素和邻里随机效应进行调整。结果总共有 4428 名患者被纳入分析,他们的平均年龄为 70.3 岁(标准差 = 11.9),52.6% 自认为是女性,75.8% 自认为是白种人,8.9% 有医疗补助。出现 MD 的中位值为-4.94 分贝(dB)(四分位间范围 = -11.45 至 -2.07dB)。邻近地区的差异占呈现 MD 变异的 4.4%。邻里层面的衡量指标,包括更严重的地区贫困(估计值,β = 每增加 1 个单位为 -0.31;P <;0.001)、更严重的隔离(Theil's H 指数每增加 0.1 个单位为 β = -0.92;P <;0.001)和更严重的邻里医疗补助(Medicaid)(β = -0.68;P <;0.001),均与更严重的出现 MD 相关。结论虽然患者的邻里 SRF 指标只占现症 MD 变异的一小部分,但大多数邻里 SRF 是可以改变的,并且与现症 MD 的临床意义差异有关。旨在通过解决资源分配问题减少邻里不平等的政策可能会对视力结果产生持久影响。
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Relationship between Neighborhood-Level Social Risk Factor Measures and Presenting Glaucoma Severity Utilizing Multilevel Modeling

Purpose

The neighborhood and built environment social determinant of health domain has several social risk factors (SRFs) that are modifiable through policy efforts. We investigated the impact of neighborhood-level SRFs on presenting glaucoma severity at a tertiary eye care center.

Design

A cross-sectional study from August 2012 to May 2022 in the University of Michigan electronic health record (EHR).

Participants

Patients with a diagnosis of any open-angle glaucoma with ≥1 eye care visit at the University of Michigan Kellogg Eye Center and ≥1 reliable visual field (VF).

Methods

Participants who met inclusion criteria were identified by International Classification of Diseases ninth and tenth revision codes (365.x/H40.x). Data extracted from the EHR included patient demographics, address, presenting mean deviation (MD), and VF reliability. Addresses were mapped to SRF measures at the census tract, block group, and county levels. Multilevel linear regression models were used to estimate the fixed effects of each SRF on MD, after adjusting for patient-level demographic factors and a random effect for neighborhood. Interactions between each SRF measure with patient-level race and Medicaid status were tested for an additive effect on MD.

Main Outcome Measures

The main outcome measure was the effect of SRF on presenting MD.

Results

In total, 4428 patients were included in the analysis who were, on average, 70.3 years old (standard deviation = 11.9), 52.6% self-identified as female, 75.8% self-identified as White race, and 8.9% had Medicaid. The median value of presenting MD was −4.94 decibels (dB) (interquartile range = −11.45 to −2.07 dB). Neighborhood differences accounted for 4.4% of the variability in presenting MD. Neighborhood-level measures, including worse area deprivation (estimate, β = −0.31 per 1-unit increase; P < 0.001), increased segregation (β = −0.92 per 0.1-unit increase in Theil’s H index; P < 0.001), and increased neighborhood Medicaid (β = −0.68; P < 0.001) were associated with worse presenting MD. Significant interaction effects with race and Medicaid status were found in several neighborhood-level SRF measures.

Conclusions

Although patients’ neighborhood SRF measures accounted for a minority of the variability in presenting MD, most neighborhood-level SRFs are modifiable and were associated with clinically meaningful differences in presenting MD. Policies that aim to reduce neighborhood inequities by addressing allocation of resources could have lasting impacts on vision outcomes.

Financial Disclosure(s)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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来源期刊
Ophthalmology science
Ophthalmology science Ophthalmology
CiteScore
3.40
自引率
0.00%
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审稿时长
89 days
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