| Literature DB >> 35570994 |
Doris Winitzki1,2, Helena U Zacharias3,4, Jennifer Nadal5, Seema Baid-Agrawal6, Elke Schaeffner7, Matthias Schmid5, Martin Busch8, Manuela M Bergmann9, Ulla Schultheiss10, Fruzsina Kotsis10, Helena Stockmann11, Heike Meiselbach12, Gunter Wolf8, Vera Krane13, Claudia Sommerer14, Kai-Uwe Eckardt11,12, Markus P Schneider12,15, Georg Schlieper1,16, Jürgen Floege1, Turgay Saritas1.
Abstract
Introduction: Prospective data on impact of educational attainment on prognosis in patients with chronic kidney disease (CKD) are scarce. We investigated the association between educational attainment and all-cause mortality, major adverse cardiovascular (CV) events (MACEs), kidney failure requiring dialysis, and CKD etiology.Entities:
Keywords: CASMIN; CKD; biomarker; chronic kidney disease; educational attainment; socioeconomic status
Year: 2022 PMID: 35570994 PMCID: PMC9091575 DOI: 10.1016/j.ekir.2022.02.001
Source DB: PubMed Journal: Kidney Int Rep ISSN: 2468-0249
Baseline characteristics by educational attainment of GCKD cohort study participants included in the current analyses
| Characteristics | All patients, 5095 (100%) | Educational attainment | ||
|---|---|---|---|---|
| Low, 2718 (53.3%) | Medium, 1586 (31.1%) | High, 791 (15.5%) | ||
| Age, yr | 60.1 ± 11.9 | 63.2 ± 9.8 | 55 ± 13.3 | 59.8 ± 12 |
| Male, | 3057 (60) | 1648 (60.6) | 834 (52.6) | 575 (72.7) |
| BMI, (kg/m2) | 28.9 (7.5) | 29.9 (7.3) | 28.1 (8) | 27.4 (6.5) |
| Alcohol consumption | ||||
| ≥3×/wk | 964 (18.9) | 471 (17.3) | 270 (17.0) | 223 (28.2) |
| <3×/wk | 4103 (80.5) | 2232 (82.1) | 1303 (82.2) | 568 (71.8) |
| Smoking status, | ||||
| (Former) smoker | 3003 (58.9) | 1663 (61.2) | 920 (58.2) | 420 (53.1) |
| Never smoker | 2079 (40.8) | 1047 (38.5) | 662 (41.7) | 370 (46.8) |
| Annual income, | ||||
| <25,000€ | 1742 (34.2) | 1144 (42.1) | 456 (28.8) | 142 (18.0) |
| ≥25,000€ | 1989 (39.1) | 784 (28.8) | 718 (45.3) | 487 (61.6) |
| Unknown | 1364 (26.8) | 790 (29.1) | 412 (26.0) | 162 (20.5) |
| Physical activity, | ||||
| <3×/wk | 2106 (41.3) | 1093 (40.2) | 678 (42.7) | 335 (42.3) |
| ≥3×/wk | 2918 (57.3) | 1580 (58.2) | 890 (56.1) | 448 (56.6) |
| Unknown | 66 (1.3) | 42 (1.5) | 17 (1.1) | 7 (0.9) |
| Private health insurance, | 353 (6.9) | 84 (3.1) | 105 (6.6) | 164 (20.7) |
| Medical history | ||||
| Diabetes mellitus, | 1824 (35.8) | 1125 (41.4) | 458 (28.9) | 241 (30.5) |
| Hypertension, | 4903 (96.2) | 2656 (97.7) | 1485 (94.3) | 752 (95.1) |
| SBP, mm Hg | 140 ± 20 | 141.1 ± 20.9 | 137.2 ± 19.5 | 138.8 ± 19.7 |
| DBP, mm Hg | 79 ± 12 | 78.5 ± 11.8 | 80.5 ± 11.8 | 79.6 ± 11.4 |
| CVD, | 1591 (30.5) | 1004 (19.7) | 348 (6.8) | 199 (3.9) |
| Gout, | 1255 (24.6) | 1918 (27.6) | 330 (20.8) | 176 (22.3) |
| Laboratory findings | ||||
| eGFR, ml/min per 1.73 m2 | 49.4 ± 18.2 | 45.7 ± 16.3 | 52.6 ± 20.2 | 51.3 ± 19.2 |
| UACR, mg/g | 50.9 (382.3) | 45.3 (306.7) | 59.6 (499.7) | 58.3 (488.8) |
| UACR categories, | ||||
| <30 mg/g | 2118 (41.6) | 1171 (43.1) | 630 (39.7) | 317 (40.1) |
| 30–300 mg/g | 1550 (30.4) | 847 (31.2) | 462 (29.1) | 241 (30.5) |
| >300 mg/g | 1408 (27.6) | 689 (25.3) | 489 (30.8) | 230 (29.1) |
| Cholesterol, mg/dl | 211.2 ± 53 | 208.2 ± 52 | 215.7 ± 53.4 | 212.6 ± 56.3 |
| HDL, mg/dl | 52 ± 18.1 | 50.5 ± 17.3 | 54.5 ± 19.4 | 52.5 ± 18 |
| LDL, mg/dl | 118.3 ± 43.5 | 116.1 ± 42.6 | 121 ± 44 | 120.2 ± 46.5 |
| Triglycerides, mg/dl | 199 ± 128 | 202.3 ± 131.6 | 194.9 ± 125.9 | 197.4 ± 119.5 |
| Uric acid, mg/dl | 7.2 ± 1.9 | 7.3 ± 1.9 | 7 ± 1.9 | 7.2 ± 1.9 |
| Hb, g/dl | 13.6 ± 1.7 | 13.6 ± 1.7 | 13.6 ± 1.7 | 13.8 ± 1.8 |
| CRP, mg/l | 2.3 (4) | 2.6 (4.5) | 2 (3.6) | 1.7 (2.8) |
| HbA1c, % | 6.0 (0.9) | 6.1 (1) | 5.9 (0.8) | 6 (0.8) |
| Calcium, mmol/l | 2.3 ± 0.1 | 2.3 ± 0.1 | 2.3 ± 0.1 | 2.3 ± 0.1 |
| Phosphorus, mmol/l | 1.1 ± 0.2 | 1.1 ± 0.2 | 1.1 ± 0.2 | 1.1 ± 0.2 |
| Sodium, mmol/l | 139.7 ± 2.9 | 139.7 ± 3.0 | 139.7 ± 2.8 | 139.8 ± 2.9 |
| Serum NGAL, ng/ml | 82.1 (46) | 84.9 (46.9) | 79.6 (44.4) | 78.9 (41.4) |
| OPN, ng/ml | 29.2 (21.1) | 30.6 (21.9) | 27.3 (19.9) | 28 (20) |
| hs-TropT, mg/ml | 12 (11.3) | 13 (11.2) | 9.7 (9.8) | 12 (11.4) |
| NT-proBNP, pg/ml | 178 (327) | 214 (405.2) | 147 (245) | 146 (245.3) |
| H-FABP, ng/ml | 3.8 (2.6) | 4.1 (2.6) | 3.6 (2.5) | 3.6 (2.6) |
| BAP, μg/l | 16.4 (8.3) | 16.8 (8.8) | 16.7 (7.9) | 15.5 (7.6) |
| iPTH, pg/ml | 37.4 (33.8) | 39.3 (34.5) | 34.1 (33.4) | 35.6 (33.9) |
| Medication use | ||||
| Antihypertensive medication, | 4703 (92.3) | 2552 (93.9) | 1437 (90.6) | 714 (90.3) |
| Antidiabetic medication, | 1453 (28.5) | 915 (33.7) | 360 (22.7) | 178 (22.5) |
| Lipid-lowering medication, | 2602 (51.1) | 1495 (55.0) | 716 (45.1) | 391 (49.4) |
| Gout medication, | 1673 (32.8) | 988 (36.4) | 446 (28.1) | 239 (30.2) |
| NSAIDs, | 334 (6.6) | 195 (7.2) | 103 (6.5) | 36 (4.6) |
BMI, body mass index; CVD, cardiovascular disease; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate based on Chronic Kidney Disease-Epidemiology Collaboration equation; GCKD, German Chronic Kidney Disease; Hb, hemoglobin; HbA1c, glycated hemoglobin; HDL, high-density lipoprotein; iPTH, intact plasma parathyroid hormone; LDL, low-density lipoprotein; NSAID, nonsteroidal anti-inflammatory drug; SBP, systolic blood pressure; UACR, urine albumin-to-creatinine ratio.
Values are expressed as mean values ± SD, medians (interquartile range), or percentages where appropriate.
Association between educational attainment and CKD etiology obtained by binary regression analysis, adjusted for age and gender, in GCKD cohort study participants included in the current analyses
| Outcome | Educational attainment | ||
|---|---|---|---|
| Low | Medium | High (reference) | |
| Diabetic nephropathy | 1.0 | ||
| Vascular nephropathy | 0.983 (0.830–1.164) | 0.984 (0.816–1.187) | 1.0 |
| Primary GN | 0.870 (0.716–1.058) | 1.0 | |
| MPGN | 1.017 (0.421–2.454) | 1.062 (0.438–2.575) | 1.0 |
| Postinfectious GN | 0.867 (0.308–2.440) | 0.765 (0.244–2.392) | 1.0 |
| IgA nephropathy | 0.757 (0.566–1.011) | 1.0 | |
| FSGS | 1.493 (0.970–2.297) | 1.209 (0.773–1.892) | 1.0 |
| Rapidly progressive pauci-immune GN | 0.928 (0.396–2.173) | 1.161 (0.468–2.878) | 1.0 |
| Minimal change GN | 1.928 (0.841–4.421) | 1.476 (0.636–3.424) | 1.0 |
| Rapidly progressive anti-GBM GN | 2.569 (0.291–22.645) | 0.284 (0.017–4.690) | 1.0 |
| Membranous GN | 0.951 (0.625–1.447) | 1.0 | |
| Other | 0.936 (0.652–1.345) | 0.829 (0.562–1.222) | 1.0 |
| Systemic disease | 1.096 (0.842–1.426) | 1.115 (0.846–1.469) | 1.0 |
| Granulomatosis with polyangiitis | 0.756 (0.434–1.315) | 1.476 (0.851–2.561) | 1.0 |
| Scleroderma | 0.197 (0.026–1.484) | 0.179 (0.016–2.036) | 1.0 |
| Microscopic polyangiitis | 0.753 (0.395–1.436) | 0.856 (0.428–1.712) | 1.0 |
| TTP | 0.359 (0.070–1.850) | 0.239 (0.039–1.477) | 1.0 |
| Amyloidosis | 1.055 (0.115–9.684) | 2.203 (0.260–18.676) | 1.0 |
| Lupus erythematosus | 0.953 (0.552–1.645) | 0.872 (0.514–1.478) | 1.0 |
| Sarcoidosis | 1.324 (0.437–4.010) | 1.300 (0.412–4.109) | 1.0 |
| Gout nephropathy | 1.622 (0.925–2.844) | 0.911 (0.463–1.794) | 1.0 |
| Interstitial nephropathy | 0.981 (0.727–1.325) | 1.206 (0.877–1.657) | 1.0 |
| Analgesic nephropathy | 1.701 (0.942–3.072) | 1.786 (0.952–3.352) | 1.0 |
| Hereditary disease | 0.829 (0.539–1.275) | 1.038 (0.673–1.601) | 1.0 |
| ADPKD | 0.831 (0.551–1.278) | 1.024 (0.664–1.581) | 1.0 |
| Acute kidney injury | 1.158 (0.728–1.840) | 1.0 | |
| Single kidney | 0.841 (0.605–1.170) | 1.205 (0.850–1.709) | 1.0 |
| Obstructive nephropathy | 1.015 (0.732–1.408) | 0.190 (0.844–1.678) | 1.0 |
| Miscellaneous | 1.075 (0.719–1.606) | 1.080 (0.701–1.662) | 1.0 |
| Undetermined | 0.879 (0.640–1.208) | 0.815 (0.573–1.160) | 1.0 |
ADPKD, autosomal dominant polycystic kidney disease; anti-GBM, antiglomerular basement membrane; CKD, chronic kidney disease; FSGS, focal segmental glomerulosclerosis; GCKD, German Chronic Kidney Disease; GN, glomerulonephritis; MPGN, membranoproliferative glomerulonephritis; TTP, thrombotic thrombocytopenic purpura.
Numbers represent odds ratio and 95% CI. Bold values indicate statistical significance.
Figure 1Variables independently associated with low or medium educational attainment compared with high educational attainment identified by the MGM algorithm in GCKD cohort study participants included in the current analyses. In the network representation, yellow nodes represent clinical chemistry parameters. Continuous variables are represented as circles and discrete variables as rectangles. Positive and negative associations are illustrated as blue and red edges, respectively. The strength of the association, that is, the weight of the corresponding coefficient, is encoded by the edge width. (a) First-order neighborhood of low versus high educational attainment. The first-order neighborhood as identified by the MGM comprises only nodes that are directly associated with low versus high educational attainment. The edges are ordered according to their strength in a clockwise manner for positive (from low income to CRP) and in an anticlockwise manner for negative associations (from private insurance to sodium), respectively. (b) First-order neighborhood of medium versus high educational attainment. The edges are ordered according to their strength in a clockwise manner for positive (from low income to HbA1c) and in an anticlockwise manner for negative associations (from private insurance to hemoglobulin), respectively. BMI, body mass index; CRP, C-reactive protein; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; GCKD, German Chronic Kidney Disease; HbA1c, hemoglobin A1c; HDL, high-density lipoprotein; iPTH, intact plasma parathyroid hormone; MGM, mixed graphical model; trigly, triglyceride.
Figure 2Association of educational attainment with all-cause mortality, MACE, and kidney failure in GCKD cohort study participants included in the current analyses. Results are presented as HRs with 95% CIs given in parentheses. The size of the square representing a relative risk is proportional to its inverse variance. High educational attainment served as the reference group. Model 1: Cox proportional hazard model adjusted for age and gender. Model 2: Cox proportional hazard model adjusted for age, gender, eGFR, urine albumin-to-creatinine ratio, and all potential mediators identified by mixed graphical model including BMI, smoking status (former + current vs. never smoker), alcohol consumption (≥3×/wk vs. <3×/wk), cardiovascular disease (yes vs. no), systolic blood pressure, antihypertensive medication (yes vs. no), HDL cholesterol, triglycerides, uric acid, calcium, urea, sodium, serum neutrophil gelatinase-associated lipocalin, bone-specific alkaline phosphatase, C-reactive protein, intact plasma parathyroid hormone, N-terminal pro–B-type natriuretic peptide, high-sensitive troponin T, OPN, H-FABP, income (<25,000€ vs. ≥25,000€), and health insurance (private vs. public). BMI, body mass index; eGFR, estimated glomerular filtration rate; GCKD, German Chronic Kidney Disease; HDL, high-density lipoprotein; HR, hazard ratio; MACE, major adverse cardiovascular event; UACR, urine albumin-to-creatinine ratio.
Figure 3Low educational attainment effect on outcomes by mediators in GCKD cohort study participants included in the current analyses. The mediation model aims to evaluate the mediators between low educational attainment and outcomes, after adjustment for age, sex, estimated glomerular filtration rate, and urine albumin-to-creatinine ratio. The percentages describe the proportion which is mediated by each mediator with respect to the total effect of low educational attainment on outcomes. The percentage is calculated by dividing the average casual mediation effects by the total effect (direct and indirect effects of low educational attainment on outcomes). For example, the mediated effect of low educational attainment on death by smoking status was 21%. Each mediator was analyzed separately, and therefore estimates of proportion mediated do not take into account potential overlapping mediation effects. (a) Mediated effect of low educational attainment on death. (b) Mediated effect of low educational attainment on MACE. CRP, C-reactive protein; CVD, cardiovascular disease; GCKD, German Chronic Kidney Disease; MACE, major adverse cardiovascular event.