Abstract
This study evaluated the association between systolic blood pressure (SBP) and diabetic retinopathy (DR) across different glycemic levels in a Japanese population. We analyzed data from 1,049 residents aged ≥ 40 years with diabetes who underwent ophthalmic screening in Chikusei City. Participants were stratified into four groups by glycated hemoglobin (HbA1c) level (< 7% or ≥ 7%) and SBP (< 140 or ≥ 140 mmHg). Logistic regression was used to examine associations between SBP and prevalent DR within HbA1c strata. DR was present in 136 participants (13.0%), including 82 (7.8%) with mild-to-moderate nonproliferative DR (NPDR) and 54 (5.1%) with severe NPDR or proliferative DR (PDR). Among participants with lower HbA1c levels, higher SBP was significantly associated with greater odds of DR (odds ratio, 2.21; 95% confidence interval, 1.16–4.23). A similar association was observed among those with mild-to-moderate NPDR, but not among participants with higher HbA1c levels. SBP was not significantly associated with severe NPDR or PDR in any group. These findings suggest that elevated SBP may contribute to the development of early-stage DR even in individuals with well-controlled blood glucose levels, underscoring the importance of blood pressure management in DR prevention strategies.
Subject terms: Diseases, Endocrinology, Health care, Medical research, Risk factors
Introduction
Diabetic retinopathy (DR), the leading cause of vision loss among working-age adults1, is the most common complication of diabetes. A meta-analysis of 59 population-based studies indicated that global prevalence was 22.27% for DR, 6.17% for vision-threatening DR (VTDR), and 4.07% for clinically significant macular edema2.
Hypertension, along with hyperglycemia, is a major risk factor for DR1. Reportedly, blood pressure (BP) management reduces the risk of DR onset and progression in individuals with type 2 diabetes3–6. However, whether the impact of systolic BP (SBP) differs across levels of glycemic control remains unclear. In addition, whether the relationship between SBP and DR risk differs between individuals with well-controlled versus poorly controlled glycated hemoglobin (HbA1c) has not been investigated in most previous studies.
Previous population-based studies have reported inconsistent associations between SBP and severe forms of DR, such as proliferative DR (PDR), diabetic macular edema, and VTDR1,7–11. Differences in glycemic status across cohorts, such as the higher HbA1c levels seen in the Los Angeles Latino Eye Study compared with the Singapore Epidemiology of Eye Diseases (SEED) study and the China DiaChronic Study, raise the possibility that the effect of SBP on DR severity may depend on glycemic control7,10,11. However, this potential interaction has not been systematically evaluated.
To address these gaps, we examined the cross-sectional associations between SBP and the prevalence and severity of DR, stratifying analyses by blood glucose levels, in a Japanese cohort from the Japan Public Health Center-based Prospective Study for the Next Generation (JPHC-NEXT) Eye Study. This approach allows us to clarify whether BP remains a relevant risk factor for DR under well-controlled glycemia and whether its influence differs by DR stage.
Results
Associations between BP and prevalence of DR stratified by HbA1c level
Of the 1,049 participants (610 males and 439 females) with diabetes included in this study, 136 (13.0%) had DR. The participants’ baseline characteristics, stratified by HbA1c level and SBP, are presented in Table 1. Among those with lower HbA1c levels (< 7.0%), those with lower SBP (< 140 mmHg) had a mean SBP of 123.3 mmHg, whereas a mean of 151.6 mmHg was observed for those with higher SBP (≥ 140 mmHg). Among participants with higher HbA1c levels (≥ 7.0%), those with lower SBP had a mean SBP of 124.9 mmHg, whereas a mean of 153.4 mmHg was observed for those with higher SBP. The mean HbA1c levels observed in these four groups were 6.45%, 6.45%, 7.96%, and 8.01%, respectively.
Table 1.
Baseline characteristics stratified by HbA1c levels and SBP.
| HbA1C < 7, SBP < 140 | HbA1C < 7, SBP ≥ 140 | HbA1C ≥ 7, SBP < 140 | HbA1C ≥ 7, SBP ≥ 140 | |
|---|---|---|---|---|
| Variables | No. (%) or Mean (SD) | |||
| N | 458 | 209 | 254 | 128 |
| Age, years | 68.2 (7.8) | 69.4 (7.2) | 67.2 (8.8) | 67.6 (7.8) |
| Sex, % male | 259 (56.6) | 123 (58.9) | 150 (59.1) | 78 (60.9) |
| Diabetic retinopathy | ||||
| Mild | 0 | 2 (1.0) | 5 (2.0) | 1 (0.8) |
| Moderate | 14 (3.1) | 11 (5.3) | 32 (12.6) | 17 (13.3) |
| Severe | 8 (1.8) | 6 (2.9) | 22 (8.7) | 14 (10.9) |
| Proliferative | 2 (0.4) | 0 | 1 (0.4) | 1 (0.8) |
| BMI, kg/m2 | 24.0 (3.5) | 25.1 (3.4) | 24.7 (4.2) | 25.3 (3.5) |
| SBP (mmHg) | 123.3 (11.2) | 151.6 (9.8) | 124.9 (10.4) | 153.4 (10.9) |
| DBP (mmHg) | 71.1 (9.2) | 82.2 (9.6) | 71.4 (9.0) | 83.3 (10.7) |
| Hypertension | 10 (2.2) | 209 (100) | 4 (1.6) | 128 (100) |
| Antihypertensive medication | 239 (52.2) | 152 (72.7) | 135 (53.2) | 74 (57.8) |
| Dyslipidemia | 285 (62.2) | 140 (67.0) | 171 (67.3) | 87 (68.0) |
| Antilipid medication | 165 (36.0) | 75 (35.9) | 99 (39.0) | 48 (37.5) |
|
Smoking exposure (pack-years), n (%) (never / <20 / ≥20) |
246 (53.7)/ 56 (12.2)/ 156 (34.1) |
107 (51.2)/ 22 (10.5)/ 80 (38.3) |
120 (47.2)/ 28 (11.0)/ 106 (41.7) |
66 (51.6)/ 9 (7.0)/ 53 (41.4) |
| Diabetes medication, n (%) | 313 (68.3) | 116 (55.5) | 194 (76.4) | 98 (76.6) |
| HbA1c, %, | 6.45 (0.35) | 6.45 (0.32) | 7.96 (1.37) | 8.01 (1.23) |
| Total cholesterol, mmol/L | 5.01 (0.89) | 5.30 (0.88) | 5.11 (0.99) | 5.32 (0.96) |
| HDL- cholesterol, mmol/L | 1.48 (0.39) | 1.51 (0.36) | 1.43 (0.36) | 1.47 (0.35) |
| LDL- cholesterol, mmol/L | 2.95 (0.78) | 3.18 (0.79) | 3.06 (0.86) | 3.15 (0.82) |
| Triglycerides, mmol/L | 1.41 (0.76) | 1.51 (0.85) | 1.49 (0.90) | 1.64 (1.06) |
| Creatinine, mg/dL | 0.79 (0.23) | 0.80 (0.25) | 0.74 (0.24) | 0.77 (0.30) |
HbA1c, glycated hemoglobin; SBP, systolic blood pressure; BMI, body mass index; DBP, diastolic blood pressure; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
The associations between BP and DR prevalence are presented in Table 2. In the fully adjusted model (Model 2), participants with higher SBP had a significantly higher prevalence of DR than those with lower SBP (odds ratio [OR], 1.73; 95% confidence interval [CI], 1.07–2.77).
Table 2.
Associations between BP and prevalence of DR stratified by HbA1c levels.
| Number at risk (cases) | Cases, % | OR (95% CI) | ||
|---|---|---|---|---|
| Model 1 | Model 2 | |||
| SBP < 140 | 712 | 84 (11.8) | Reference | Reference |
| SBP ≥ 140 | 337 | 52 (15.4) | 1.38 (0.95, 2.00) | 1.73 (1.07, 2.77) |
| HbA1C < 7, SBP < 140 | 458 | 24 (5.2) | Reference | Reference |
| HbA1C < 7, SBP ≥ 140 | 209 | 19 (9.1) | 1.82 (0.97, 3.40) | 2.21 (1.16, 4.23) |
| HbA1C ≥ 7, SBP < 140 | 254 | 60 (23.6) | 5.52 (3.34, 9.14) | 5.61 (3.34, 9.41) |
| HbA1C ≥ 7, SBP ≥ 140 | 128 | 33 (25.8) | 6.21 (3.50, 10.99) | 6.26 (3.47, 11.29) |
Categories stratified by SBP: Model 1 was adjusted for age and sex; Model 2 was further adjusted for HbA1c, dyslipidemia, serum creatinine, smoking exposure (pack-years), antihypertensive use, lipid-lowering medication use, and diabetes medication status. Categories stratified by SBP and HbA1c levels: Model 1 was adjusted for age and sex; Model 2 was adjusted for the same set of covariates, excluding HbA1c.
BP, blood pressure; DR, diabetic retinopathy; HbA1c, glycated hemoglobin; OR, odds ratio; CI, confidence interval; SBP, systolic blood pressure.
*Significant values are in bold.
Additional subgroup analyses were conducted, stratified by HbA1c level. Among participants with lower HbA1c levels, those with higher SBP had a significantly higher prevalence of DR (OR, 2.21; 95% CI 1.16–4.23) than those with lower SBP. Among participants with higher HbA1c levels, the prevalence of DR was significantly high in both those with lower SBP (OR, 5.61; 95% CI 3.34–9.41) and those with higher SBP (OR, 6.26; 95% CI 3.47–11.29). Notably, among participants with higher HbA1c levels, the prevalence of DR did not significantly differ between those with lower SBP and those with higher SBP (OR, 1.12; 95% CI 0.67–1.86) (not presented in the tables).
Associations between BP and severity of DR stratified by HbA1c level
Further analysis was performed to examine the relationship between BP and DR severity. The baseline characteristics stratified by DR severity are shown in Table 3. Of the total participants, 82 (7.8%) had mild-to-moderate nonproliferative DR (NPDR), whereas 54 (5.1%) had severe NPDR or PDR. The mean SBP was 132.5 mmHg in participants without DR, 135.3 mmHg in those with mild-to-moderate NPDR, and 138.4 mmHg in those with severe NPDR and PDR. HbA1c level tended to increase across groups, with mean values of 6.9%, 7.3%, and 7.8% in participants without DR, those with mild-to-moderate NPDR, and those with severe NPDR and PDR, respectively.
Table 3.
Baseline characteristics stratified by severity of DR.
| No DR | Mild and moderate | Severe NPDR and PDR | |
|---|---|---|---|
| Variables | No. (%) or Mean (SD) | ||
| N (1049) | 913 (87.0) | 82 (7.8) | 54 (5.1) |
| Age, years | 68.2 (8.0) | 68.6 (7.8) | 65.5 (8.0) |
| Sex, % male | 525 (57.5) | 55 (67.1) | 30 (55.6) |
| BMI, kg/m2 | 24.6 (3.6) | 24.9 (3.9) | 23.8 (3.7) |
| SBP (mmHg) | 132.5 (16.8) | 135.3(18.2) | 138.4 (19.2) |
| DBP (mmHg) | 74.8 (10.7) | 74.9 (11.7) | 76.1 (12.0) |
| Hypertension | 298 (32.6) | 31 (37.8) | 22 (40.7) |
| Antihypertensive medication | 519 (56.9) | 54 (65.9) | 27 (50.0) |
| Dyslipidemia | 608 (66.6) | 46 (56.1) | 29 (53.7) |
| Antilipid medication | 344 (37.7) | 29 (35.4) | 14 (25.9) |
|
Smoking exposure (pack-years), n (%) (never / <20 / ≥20) |
470 (51.5)/101 (11.1)/342 (37.5) | 45 (54.9)/ 8 (9.8)/29 (35.4) | 24 (44.4)/6 (11.1)/24 (44.4) |
| Diabetes medication, n (%) | 598 (65.5) | 78 (95.1) | 45 (83.3) |
| HbA1c, %, | 6.9 (1.1) | 7.3 (0.9) | 7.8 (1.4) |
| Total cholesterol, mmol/L | 5.13 (0.91) | 5.03 (1.03) | 5.24 (1.12) |
| HDL- cholesterol, mmol/L | 1.47 (0.37) | 1.49 (0.35) | 1.50 (0.38) |
| LDL- cholesterol, mmol/L | 3.05 (0.80) | 3.04 (0.83) | 3.09 (0.99) |
| Triglycerides, mmol/L | 1.50 (0.87) | 1.19 (0.53) | 1.41 (0.99) |
| Creatinine, mg/dL | 0.78 (0.24) | 0.81 (0.30) | 0.74 (0.23) |
DR, diabetic retinopathy; NPDR, nonproliferative DR; PDR, proliferative DR; SD, standard deviation; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HbA1c, glycated hemoglobin; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
After full adjustment, SBP was not associated with the prevalence of DR in those with mild-to-moderate NPDR (Table 4). However, when stratified by HbA1c level, among participants with lower HbA1c levels, those with higher SBP had a significantly higher prevalence of DR (OR, 2.51; 95% CI 1.13–5.59) than those with lower SBP. Meanwhile, among participants with higher HbA1c levels, the prevalence of DR was significantly high in both those with lower SBP (OR, 5.78; 95% CI 3.00–11.12) and those with higher SBP (OR, 5.37; 95% CI 2.52–11.41), showing nearly the same ORs.
Table 4.
Association between BP and severity of DR stratified by HbA1c levels.
| Number at risk (cases) | Cases, % | OR (95% CI) | ||
|---|---|---|---|---|
| Model 1 | Model 2 | |||
| Mild and moderate NPDR | ||||
| SBP < 140 | 679 | 51 (7.5) | Reference | Reference |
| SBP ≥ 140 | 316 | 31 (9.8) | 1.33 (0.83, 2.13) | 1.40 (0.85, 2.29) |
| HbA1C < 7, SBP < 140 | 448 | 14 (3.1) | Reference | Reference |
| HbA1C < 7, SBP ≥ 140 | 203 | 13 (6.4) | 2.09 (0.96, 4.53) | 2.51 (1.13, 5.59) |
| HbA1C ≥ 7, SBP < 140 | 231 | 37 (16.0) | 5.91 (3.12, 11.19) | 5.78 (3.00, 11.12) |
| HbA1C ≥ 7, SBP ≥ 140 | 113 | 18 (15.9) | 5.84 (2.80, 12.17) | 5.37 (2.52, 11.41) |
| Severe NPDR and PDR | ||||
| SBP < 140 | 661 | 33 (5.0) | Reference | Reference |
| SBP ≥ 140 | 306 | 21 (6.9) | 1.47 (0.83, 2.60) | 1.72 (0.94, 3.13) |
| HbA1C < 7, SBP < 140 | 434 | 10 (2.3) | Reference | Reference |
| HbA1C < 7, SBP ≥ 140 | 196 | 6 (3.1) | 1.44 (0.51, 4.02) | 1.91 (0.66, 5.53) |
| HbA1C ≥ 7, SBP < 140 | 217 | 23 (10.6) | 4.97 (2.31, 10.68) | 5.36 (2.44, 11.77) |
| HbA1C ≥ 7, SBP ≥ 140 | 110 | 15 (13.6) | 6.82 (2.97, 15.70) | 7.67 (3.24, 18.17) |
Categories stratified by SBP: Model 1 was adjusted for age and sex; Model 2 was further adjusted for HbA1c, dyslipidemia, serum creatinine, smoking exposure (pack-years), antihypertensive use, lipid-lowering medication use, and diabetes medication status. Categories stratified by SBP and HbA1c levels: Model 1 was adjusted for age and sex; Model 2 was adjusted for the same set of covariates, excluding HbA1c.
BP, blood pressure; DR, diabetic retinopathy; HbA1c, glycated hemoglobin; OR, odds ratio; CI, confidence interval; NPDR, nonproliferative DR; SBP, systolic blood pressure; PDR, proliferative DR.
*Significant values are in bold.
For participants with severe NPDR and PDR, SBP was not associated with the prevalence of DR (Table 4). Among participants with lower HbA1c levels, the DR prevalence did not differ between the groups with higher and lower SBP (OR, 1.91; 95% CI 0.66–5.53). Meanwhile, among participants with higher HbA1c levels, the prevalence of DR was significantly high in both those with lower SBP (OR, 5.36; 95% CI 2.44–11.77) and those with higher SBP (OR, 7.67; 95% CI 3.24–18.17). The odds ratio was numerically higher in the higher SBP group than in the lower SBP group; however, this difference was not statistically significant (OR, 1.43; 95% CI 0.70–2.93, not shown in tables).
Discussion
Population-based studies have consistently shown an association between SBP and DR1,7–13. The Los Angeles Latino Eye Study found that higher SBP increased the risk of any DR (per 20 mmHg, OR, 1.26, P = 0.002)7, and the SEED study reported that SBP was an independent risk factor for any-DR (per 10 mmHg, OR, 1.14; 95% CI 1.09–1.19)10. Consistent with these findings, the current study revealed a significant association between higher SBP and the prevalence of DR. Mechanistically, hyperglycemia may impair retinal microvascular autoregulation, increasing endothelial vulnerability to BP-related stress, which can promote capillary injury and retinal nonperfusion, contributing to DR initiation and progression14,15.
A unique contribution of this study is the stratified analysis by HbA1c level, which clarifies how the relationship between SBP and DR may differ under varying glycemic control. Among participants with lower HbA1c levels (< 7%), higher SBP was significantly associated with DR, indicating that SBP remains a relevant DR risk factor even when blood glucose levels are well-controlled. However, among participants with higher HbA1c levels (≥ 7%), DR prevalence did not significantly differ across SBP categories, suggesting that the effects of hyperglycemia may overshadow the contribution of BP at higher glycemic levels.
Prior population-based studies have reported inconsistent associations between SBP and severe DR1,7–11,13,16 For example, the Los Angeles Latino Eye Study reported that higher SBP was an independent risk factor associated with PDR when compared with NPDR,7 suggesting that SBP may contribute more strongly to advanced stages. In contrast, the SEED study and the China DiaChronic Study found comparable effect sizes of SBP for any DR and VTDR,10,11 indicating that SBP uniformly influences DR risk across severity levels.
One potential explanation for these discrepancies is the substantial variation in glycemic profiles across cohorts. The Los Angeles Latino Eye Study7, for instance, included participants with considerably higher mean HbA1c levels compared with those in the SEED study10 and the China DiaChronic Study11. Hyperglycemia accelerates cumulative microvascular damage; therefore, elevated BP has been hypothesized to play a more prominent role in the progression to severe or advanced DR with poor glycemic control. Differences in the distribution of blood glucose across cohorts may explain the conflicting findings regarding the impact of SBP on DR severity.
In the current study, the association between SBP and DR varied by glycemic status and disease severity. Among participants with higher HbA1c levels, the association between SBP and mild-to-moderate DR appeared relatively uniform, whereas odds ratios for severe DR were numerically higher among those with elevated SBP; however, these associations were not statistically significant. In contrast, among participants with lower HbA1c levels, the point estimates for the association between SBP and DR were numerically close for mild and severe disease, while the estimate for severe DR was not statistically significant. Given the limited number of severe DR cases, these findings do not reflect definitive conclusions regarding the association between SBP and severe DR, and should be interpreted with caution.
When focusing on mild-to-moderate NPDR, the association between SBP and DR differed by glycemic status. Stratified analyses showed that higher SBP was significantly associated with increased odds of DR among participants with lower HbA1c levels, although no overall association with SBP was observed. This finding suggests that SBP may play a more prominent role in the early stages of DR development when glycemic control is relatively good, highlighting the potential benefit of BP management even in patients without poor glycemic control.
Collectively, these findings indicate that BP management may be particularly relevant for preventing DR onset or early progression, especially among individuals with well-controlled blood glucose levels. In contrast, its role in influencing advanced DR was less evident in the current study, possibly reflecting the dominant contribution of other disease-related factors at later stages. These results underscore the importance of early intervention and support a comprehensive approach to DR risk management that integrates BP and glycemic control across the disease course.
The strengths of this study include the use of standardized grading protocols for DR diagnosis, as assessed by ophthalmologists, including retinal specialists, and detailed questionnaires to collect data on lifestyle and medical history. Nevertheless, some limitations should be acknowledged. First, the cross-sectional design precludes assessment of temporal relationships and raises the possibility of reverse causation. Advanced DR itself is unlikely to directly elevate BP; nevertheless, severe DR may coexist with systemic factors that influence BP regulation. Therefore, the direction of the observed associations cannot be determined. Second, detailed information on the duration of diabetes was not available. Notably, diabetes medication status (newly diagnosed vs. previously diagnosed diabetes) was included as a proxy indicator; however, this measure cannot fully capture the cumulative effects of disease duration. In addition, information on the use of specific antihypertensive drug classes, including renin–angiotensin system blockers, was not available, and antihypertensive use was only adjusted for as a binary variable. Third, the exact timing of BP measurement and the interval since the last use of antihypertensives were not recorded, which may have introduced nondifferential measurement variability. Finally, subgroup analyses stratified by HbA1c level and DR severity included relatively small numbers in some categories, particularly for severe NPDR/PDR, which may have limited statistical precision.
In conclusion, the current study highlights that higher SBP is associated with DR, particularly among individuals with lower HbA1c levels, and may contribute to early disease development. While the effect of SBP on advanced DR remains unclear, our findings underscore the importance of a dual approach incorporating glycemic and BP control for comprehensive DR prevention, particularly in clinical settings where early intervention is feasible.
Methods
Study population
The JPHC-NEXT Eye Study is an ancillary study conducted in accordance with the JPHC-NEXT Study protocol17–19. In Chikusei City, Ibaraki Prefecture, residents aged ≥ 40 years underwent a systemic and ophthalmological survey. This study included 9,940 individuals who participated in the survey between 2013 and 2017. After excluding 14 participants with missing fundus images or suboptimal image quality (e.g., poor focus, eyelash artifacts, uneven illumination), 1,049 participants with diabetes were included in the analysis.
This study was performed following the Ethical Guidelines for Medical and Health Research Involving Human Subjects in Japan. Approval was granted by the institutional ethics committees of Keio University School of Medicine (Tokyo), University of Tsukuba (Ibaraki), Osaka University (Osaka), and the National Cancer Center (Tokyo). Written informed consent was obtained from every participant before enrollment.
Data and sample collection
As part of the ophthalmic examinations, nonmydriatic color fundus photographs were captured from both eyes using a 45° nonmydriatic fundus camera (CR-1; Canon Inc., Tokyo, Japan). Each image was centered on the optic disc and macula. In addition, blood samples were obtained to measure serum glucose (fasting or nonfasting), HbA1c (%), total cholesterol (mmol/L), high-density lipoprotein cholesterol (HDL-C) (mmol/L), low-density lipoprotein cholesterol (LDL-C) (mmol/L), triglyceride (TG) (mmol/L), and creatinine (mg/dL) levels. The nonfasting state was defined as < 8 h after the last meal. Diabetes was defined as the use of any antidiabetic medication, a fasting serum glucose level ≥ 7.0 mmol/L, a nonfasting serum glucose level ≥ 11.1 mmol/L, or an HbA1c level ≥ 6.5% (National Glycohemoglobin Standardization Program)20. Participants were further classified as previously diagnosed with diabetes if they were using antidiabetic medication; those whose status was identified using laboratory measurements alone were classified as newly diagnosed. To evaluate glycemic control, participants were stratified into HbA1c < 7% and ≥ 7%. The 7% threshold is widely used as the general treatment target for most adults with diabetes, as recommended by the American Diabetes Association Standards of Care21. Dyslipidemia was defined as the use of a lipid-lowering medication, an LDL-C level ≥ 3.6 mmol/L, an HDL-C level < 1.0 mmol/L, or a TG level ≥ 1.7 mmol/L22. Body mass index was calculated as weight (kg) divided by height squared (m2). BP was measured twice using the right upper arm while the participant was seated. The average of the two measurements was used for the analysis. Hypertension was defined as the use of any antihypertensive medication, an SBP ≥ 140 mm Hg, or a diastolic BP ≥ 90 mm Hg23. For BP classification, SBP < 140 mmHg and ≥ 140 mmHg were adopted in accordance with the World Health Organization/International Society of Hypertension definition of hypertension23.
Grading of fundus photographs for DR
DR was defined as an Early Treatment DR Study level ≥ 20 in either eye. Its prevalence was determined by two ophthalmologists who were blinded to the participant’s clinical data (T.K., H.T., E.Y., Y.K., K.M., or H.K.). In cases of disagreement, the diagnosis was made by a retinal specialist (Y.T. or N.O.).
Statistical analyses
Baseline characteristics were summarized and stratified based on HbA1c level and SBP status. In this analysis, HbA1c level and SBP were categorized irrespective of medication use as follows: HbA1c: lower (< 7%) vs. higher (≥ 7%); SBP: lower (< 140 mmHg) vs. higher (≥ 140 mmHg). The associations between BP and DR prevalence were examined using multivariable logistic regression models and expressed as ORs with 95% CIs. For analyses stratified by SBP, the first model was adjusted for age and sex. The second model was further adjusted for HbA1c, dyslipidemia, and serum creatinine levels, as well as smoking exposure (pack-years), antihypertensive use, lipid-lowering medication use, and diabetes medication status (newly diagnosed vs. previously diagnosed diabetes). For categories stratified by SBP and HbA1c levels, the first model was adjusted for age and sex, whereas the second model was adjusted for the same set of covariates, excluding HbA1c to avoid overadjustment. Baseline characteristics stratified by DR severity were calculated for the overall sample. The associations between SBP and DR severity were examined using multivariable logistic regression models. These models were adjusted for the same covariates as those used to examine the associations between BP and DR prevalence. P-values < 0.05 were considered statistically significant. All statistical analyses were performed using SAS for Windows, version 9.4 (SAS Institute Inc., Cary, NC, USA).
Acknowledgements
We sincerely thank the medical staff for their skilled technical support and the dedicated personnel of Chikusei City for their invaluable assistance in conducting the survey. We are also deeply grateful to Dr. Hidemasa Torii, Dr. Yusaku Katada, Dr. Erisa Yotsukura, Dr. Hiromitsu Kunimi, and Dr. Mari Ibuki of Keio University School of Medicine for their essential contributions to the evaluation of retinal fundus images.
Author contributions
Design of the study (MS); Conduct of the study (MS, KYa, KYu); collection and management of the data (MS, KYu, AH, KYa, TK, YT, KM, NO, YOz); analysis of the data (MS); interpretation of the data (MS, AH); preparation of the manuscript (MS, YOf); review and approval of the manuscript (MS, YOf, AH, TK, YT, KM, NO, YOz, Kya, Kyu, NS, KT, KN, ST, HI).
Funding
The authors have no proprietary or commercial interest in any materials discussed in this article (no financial or nonfinancial). This study was supported in part by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science, Japan (JSPS KAKENHI, 20K10490) to MS. The cohort study was originally supported by the National Cancer Center Research and Development Fund.
Data availability
The data that support the findings of this study are available on request from the corresponding author, MS or KYa. The data are not publicly available due to their containing information that could compromise the privacy of research participants.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
The original online version of this Article was revised: The original version of this Article contained an error in the Methods section under the Study population subsection where the description of the source population and survey period were incorrect. Full information can be found in the correction for this Article.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Mariko Sasaki and Yoshiko Ofuji contributed equally to this work as first authors.
Mariko Sasaki and Kazumasa Yamagishi contributed equally to this work.
Change history
4/7/2026
A Correction to this paper has been published: 10.1038/s41598-026-47168-4
Contributor Information
Mariko Sasaki, Email: marii.kt@gmail.com.
Kazumasa Yamagishi, Email: yamagishi.kazumas.ge@u.tsukuba.ac.jp.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author, MS or KYa. The data are not publicly available due to their containing information that could compromise the privacy of research participants.