Background and purpose
Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, with its prevalence closely tied to diabetes control and access to healthcare. This study analyzes data from NHANES 1999–2020 to examine whether the family income to poverty ratio (PIR), a standardized measure of socioeconomic status, can predict DR prevalence among U.S. adults aged 20 and older. The goal is to understand how income-related factors relate to DR risk and whether PIR could serve as a practical indicator for targeted screening and prevention efforts.
Data and methods
The analysis drew on NHANES data from 1999–2020, comprising 39,210 adults after applying exclusion criteria. PIR was calculated using NHANES guidelines by dividing family income by poverty guidelines, adjusting for family size and survey cycle. PIR values were capped at 5.00 or more, with participants categorized into two groups: PIR < 5 (Group 1) and PIR ≥ 5 (Group 2).
DR status was based on self-reported physician diagnosis: “Has any doctor ever told you that diabetes has affected your eyes or that you had retinopathy?” Covariates included age, sex, race, education, BMI, waist circumference, smoking, diabetes duration, insulin use, HbA1c, albumin, systolic blood pressure, total cholesterol, and HDL-C. The study applied univariate and multivariate logistic regression, restricted cubic splines for nonlinear assessments, subgroup analyses, and ROC curve analysis to evaluate predictive performance.
Key findings
Among the weighted sample, 81.37% were in the PIR < 5 group, while 18.63% fell into PIR ≥ 5. DR prevalence was 2.7% in Group 1 and 1.5% in Group 2. After adjusting for potential confounders, PIR demonstrated a significant inverse association with DR: odds ratio (OR) 0.91 (95% CI 0.86–0.97), p = 0.002. In race-specific analyses, Non-Hispanic Whites showed a notable benefit (OR 0.87, 95% CI 0.80–0.96; p = 0.005).
Receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.747 (95% CI 0.74–0.76) after age adjustment, indicating moderate discriminative ability of the model to predict DR presence. A PIR-focused subgroup analysis suggested a linear negative relationship within PIR < 5, with consistent results across most subgroups. The findings support the potential use of PIR as an economic indicator to help identify populations at higher risk for DR and guide targeted screening strategies.
Interpretation and implications
The study suggests that higher PIR, reflecting greater household resources relative to poverty thresholds, is associated with a lower likelihood of DR among U.S. adults. This aligns with broader evidence linking socioeconomic status to health outcomes through improved access to care, healthier living environments, and greater treatment adherence. The modest but meaningful predictive value of PIR implies it could supplement clinical risk stratification, especially in resource-limited settings where universal screening is impractical.
Public health actions should emphasize enhanced DR screening and preventive education for low-income populations. Policymakers might consider integrating PIR with clinical risk assessments to prioritize outreach, eye examinations, and diabetes management programs in economically disadvantaged communities.
Limitations and future directions
Limitations include the cross-sectional design, reliance on self-reported DR data, and potential residual confounding. PIR was categorized, which may mask nuanced income effects; future research should explore longitudinal datasets to establish causality and examine the mechanisms linking income, access to care, and DR progression. Distinguishing type 1 and type 2 diabetes-related DR would further refine understanding but was not possible with NHANES data in this study.
Conclusion
In a large U.S. adult cohort, higher PIR is associated with lower DR prevalence, underscoring PIR’s potential value as an economical indicator for predicting DR risk and guiding targeted screening. Expanding access to eye health services for low-income groups could help reduce the social and health burdens imposed by diabetic eye disease.
