| Literature DB >> 30509207 |
Tamiru Adugna1, Hailu Merga2, Esayas Kebede Gudina3.
Abstract
BACKGROUND: Chronic Kidney Disease (CKD), the worldwide Public Health problem, is also one of the rising non-communicable diseases in low and middle-income countries. Its early detection and treatment using readily available, inexpensive therapies can slow or prevent progression to end-stage renal disease. Hence, this study was aimed at assessing impaired estimated glomerular filtration rate (eGFR), high grade albuminuria, and associated factors among adult patients admitted to Jimma University Medical Center in South west Ethiopia.Entities:
Keywords: Albuminuria; Chronic kidney disease; Creatinine; Glomerular filtration rate; Jimma University medical center
Mesh:
Year: 2018 PMID: 30509207 PMCID: PMC6278145 DOI: 10.1186/s12882-018-1153-5
Source DB: PubMed Journal: BMC Nephrol ISSN: 1471-2369 Impact factor: 2.388
Socio-demographic characteristics of study participants, Jimma University Medical Center, Ethiopia, 2017
| Socio-demographic characteristics | Category | Frequency | Percentage |
|---|---|---|---|
| Age | <40 year | 175 | 41.5 |
| 40–59 year | 122 | 28.9 | |
| > = 60 year | 125 | 29.6 | |
| Mean ± SD | 45.37 ± 18.5 | ||
| Sex | Male | 215 | 50.9 |
| Female | 207 | 49.1 | |
| Marital status | Married | 343 | 81.3 |
| Single | 54 | 12.8 | |
| Widowed | 16 | 3.8 | |
| Divorced | 9 | 2.1 | |
| Religion | Muslim | 293 | 69.4 |
| Christian | 129 | 30.6 | |
| Occupation | Farmer | 162 | 38.4 |
| Housewife | 105 | 24.9 | |
| Merchant | 63 | 14.9 | |
| Student | 40 | 9.5 | |
| Employee | 27 | 6.4 | |
| Daily laborer | 12 | 2.8 | |
| Others | 13 | 3.1 | |
| Educational status | Illiterate | 191 | 45.3 |
| Grade 1–8 | 167 | 39.6 | |
| Grade 9–12 | 31 | 7.3 | |
| College/University | 33 | 7.8 | |
| Residence | Rural | 254 | 60.2 |
| Urban | 168 | 39.8 | |
Life style and clinical characteristics of study participants, Jimma University Medical Center, Ethiopia, 2017
| Life style and clinical characteristics | Category | Frequency | Percentage |
|---|---|---|---|
| Cigarette smoking | Never | 400 | 94.8 |
| Past | 17 | 4.0 | |
| Current | 5 | 1.2 | |
| Alcohol drinking | Never | 378 | 89.6 |
| Occasionally | 25 | 5.9 | |
| < 3 times/week | 13 | 3.1 | |
| 3–6 times/week | 4 | 0.9 | |
| Daily | 2 | 0.5 | |
| Alcohol use problem | No | 413 | 97.9 |
| Yes | 9 | 2.1 | |
| Khat chewing | Never | 273 | 64.7 |
| Past | 82 | 19.4 | |
| Current | 67 | 15.9 | |
| NSAIDs use with two weeks | No | 354 | 83.9 |
| Yes | 68 | 16.1 | |
| History of DM | No | 368 | 87.2 |
| Yes | 54 | 12.8 | |
| History of hypertension | No | 259 | 61.4 |
| Yes | 114 | 27.0 | |
| Not checked for previously | 49 | 11.6 | |
| Physical exercise | No | 204 | 48.3 |
| < 150 min/week | 77 | 18.2 | |
| > = 150 min/week | 141 | 33.4 | |
| BP | < 120/80 | 249 | 59.0 |
| 120–139/80–89 | 57 | 13.5 | |
| > = 140/90 | 116 | 27.5 | |
| BMI | < 25 | 397 | 94.1 |
| > = 25 | 25 | 5.9 | |
| HIV status | Nonreactive | 396 | 93.8 |
| Reactive | 26 | 6.2 |
Fig. 1Admission diagnosis of study participants, Jimma University Medical Center, Ethiopia, 2017
Pattern of high grade albuminuria according to level of eGFR, Jimma University Medical Center, Ethiopia, 2017
| eGFR by CG equation | eGFR by MDRD-4 equation | |||
|---|---|---|---|---|
| < 60 ml/min | > = 60 ml/min ( | < 60 ml/min/1.73 m2 ( | > = 60 ml/min/1.73 m2 ( | |
| Albuminuria (> = + 1) | 30 (21.7%) | 22 (7.7%) | 26 (32.1%) | 26 (7.6%) |
Bi-variate logistic regression analysis of factors associated with impaired eGFR using CG-equation, Jimma University Medical Center, Ethiopia, 2017
| Variables | Impaired eGFR by CG | ||||
|---|---|---|---|---|---|
| Yes | No | COR (95%CI) | |||
| Age | > = 60 year | 60 (43.5%) | 65 (22.9%) | 3.56 (2.146, 5.920) | .000 |
| 40-59 year | 42 (30.4%) | 80 (28.2%) | 2.027 (1.201, 3.421) | .008 | |
| <40 year | 36 (26.1%) | 139 (48.9%) | 1 | ||
| Sex | Male | 87 (63.0%) | 128 (45.1%) | 2.079 (1.370, 3.156) | .001 |
| Female | 51 (37.0%) | 156 (54.9%) | 1 | ||
| Residence | Rural | 98 (71.0%) | 156 (54.9%) | 2.01 (1.3, 3.108) | .002 |
| Urban | 40 (29.0%) | 128 (45.1%) | 1 | ||
| Formal education | Yes | 58 (42%) | 173 (60.9%) | 0.465 (.308, .703) | .000 |
| No | 80 (58%) | 111 (39.1%) | 1 | ||
| Occupation | Non-farmer | 72 (52.2%) | 189 (66.5%) | 0.548 (.362, .830) | .005 |
| Farmer | 66 (47.8%) | 95 (33.5%) | 1 | ||
| Cigarette smoking | Yes | 11 (8.0%) | 11 (3.9%) | 2.150 (.908, 5.089) | .082 |
| No | 127 (92.0%) | 273 (96.1%) | 1 | ||
| Khat chewing | Yes | 60 (43.5%) | 89 (31.3%) | 1.685 (1.108, 2.564) | .015 |
| No | 78 (56.5%) | 195 (68.7%) | 1 | ||
| Physical exercise | > = 150 min/week | 55 (39.9%) | 86 (30.3%) | 1.610 (1.021, 2.538) | .040 |
| < 150 min/week | 25 (18.1%) | 52 (18.3%) | 1.210 (.687, 2.131) | .509 | |
| No | 58 (42.0%) | 146 (51.4%) | 1 | ||
| History of known HTN | Yes | 72 (52.2%) | 91 (32.0%) | 2.31 (1.525, 3.510) | .000 |
| No | 66 (47.8%) | 193 (68.0%) | 1 | ||
| BP (mmHg) | > = 140/90 | 54 (39.1%) | 62 (21.8%) | 2.805 (1.758, 4.476) | .000 |
| 120–139/80–89 | 25 (18.1%) | 32 (11.3%) | 2.52 (1.382, 4.581) | .003 | |
| < 120/80 | 59 (42.8%) | 190 (66.9%) | 1 | ||
Multi-variable logistic regression analysis of factors associated with impaired eGFR using CG equation, Jimma University Medical Center, Ethiopia, 2017
| COR (95%CI) | AOR (95%CI) | |||
|---|---|---|---|---|
| Age | > = 60 year | 3.564 (2.146, 5.920) | 2.376 (1.378, 4.095) | 0.002 |
| 40-59 year | 2.027 (1.201, 3.421) | |||
| <40 year | 1 | |||
| Sex | Male | 2.079 (1.370, 3.156) | 1.609 (1.029, 2.515) | 0.037 |
| Female | 1 | |||
| Residence | Rural | 2.01 (1.3, 3.108) | 1.882 (1.181, 3.000) | 0.008 |
| Urban | 1 | |||
| BP (mmHg) | > = 140/90 | 2.805 (1.758, 4.476) | 1.974 (1.142, 3.411) | 0.015 |
| 120–139/80–89 | 2.516 (1.382, 4.581) | 2.112 (1.114, 4.025) | 0.022 | |
| < 120/80 | 1 | |||
Bi-variate logistic regression analysis of factors associated with impaired eGFR by MDRD-4 equation, Jimma University Medical Center, Ethiopia, 2017
| Variables | Impaired eGFR by MDRD | ||||
|---|---|---|---|---|---|
| Yes | No | COR (95% CI) | |||
| Age | > = 60 year | 25 (30.9%) | 100 (29.3%) | 1.433 (.783, 2.623) | 0.244 |
| 40–59 year | 30 (37.0%) | 92 (27.0%) | 1.869 (1.040, 3.358) | 0.036 | |
| < 40 year | 26 (32.1%) | 149 (43.7%) | 1 | ||
| Sex | Male | 53 (65.4%) | 162 (47.5%) | 2.091 (1.262, 3.465) | 0.004 |
| Female | 28 (34.6%) | 179 (52.5%) | 1 | ||
| Residence | Rural | 62 (76.5%) | 192 (56.3%) | 2.532 (1.451, 4.419) | 0.001 |
| Urban | 19 (23.5%) | 149 (43.7%) | 1 | ||
| Formal education | Yes | 38 (46.9%) | 193 (56.6%) | .678 (.417, 1.102) | 0.117 |
| No | 43 (53.1%) | 148 (43.4%) | 1 | ||
| Occupational status | Farmer | 40 (49.4%) | 121 (35.5%) | 1 | |
| Others | 41 (50.6%) | 220 (64.5%) | .564 (.346, .919) | 0.022 | |
| Cigarette smoking | Yes | 7 (.6%) | 15 (4.4%) | 2.056 (.810, 5.221) | 0.130 |
| No | 74 (91.4%) | 326 (95.6%) | 1 | ||
| Physical exercise | > = 150 min | 31 (38.3%) | 110 (32.3%) | 1.515 (.875, 2.622) | 0.138 |
| < 150 min/week | 18 (22.2%) | 59 (17.3%) | 1.640 (.857, 3.137) | 0.135 | |
| No | 32 (39.5%) | 172 (50.4%) | 1 | ||
| History of known HTN | Yes | 43 (53.1%) | 113 (33.1%) | 3.254 (1.971, 5.374) | 0.000 |
| No | 38 (47.9%) | 228 (66.9%) | 1 | ||
| NSAIDs use within two weeks | Yes | 8 (9.9%) | 60 (17.6%) | .513 (.235, 1.121) | 0.094 |
| No | 73 (90.1%) | 281 (82.4%) | 1 | ||
| BP (mmHg) | > = 140/90 | 39 (48.1%) | 77 (22.6%) | 3.562 (2.079, 6.103) | 0.000 |
| 120–139/80–89 | 11 (13.6%) | 46 (13.5%) | 1.682 (.788, 3.588) | 0.179 | |
| < 120/80 | 31 (38.3%) | 218 (63.9%) | 1 | ||
Multi-variable logistic regression analysis of factors associated with impaired eGFR by MDRD-4 equation, Jimma University Medical center, Ethiopia, 2017
| Variables | ||||
|---|---|---|---|---|
| COR (95% CI) | AOR (95% CI) | |||
| Sex | Male | 2.091 (1.262, 3.465) | 2.084 (1.167, 3.721) | 0.013 |
| Female | 1 | 1 | ||
| Residence | Rural | 2.532 (1.451, 4.419) | 2.954 (1.556, 5.609) | 0.001 |
| Urban | 1 | |||
| Physical exercise | > = 150 min | 1.515 (.875, 2.622) | .902 (.473, 1.721) | 0.754 |
| < 150 min/week | 1.640 (.857, 3.137) | 2.290 (1.120, 4.685) | 0.023 | |
| No | 1 | |||
| History of known HTN | Yes | 3.254 (1.971, 5.374) | 2.233 (1.244, 4.010) | 0.007 |
| No | 1 | |||
| BP (mmHg) | > = 140/90 | 3.562 (2.079, 6.103) | 2.597 (1.378, 4.893) | 0.003 |
| 120–139/80–89 | 1.682 (.788, 3.588) | 1.676 (0.757, 3.706) | 0.203 | |
| < 120/80 | 1 | |||
Bi-variate logistic regression analysis of factors associated with high grade albuminuria, JUMC, Ethiopia, 2017
| Variables | High grade albuminuria | ||||
|---|---|---|---|---|---|
| Yes | No | COR (95% CI) | |||
| Age | > = 60 year | 14 (26.9%) | 111 (30.0%) | .977 (.473, 2.019) | 0.951 |
| 40–59 year | 18 (34.6%) | 104 (28.1%) | 1.341 (.677, 2.657) | 0.400 | |
| < 40 year | 20 (38.5%) | 155 (41.9%) | 1 | ||
| Sex | Male | 32 (61.5%) | 183 (49.5%) | 1.635 (.902, 2.96) | 0.105 |
| Female | 20 (38.5%) | 187 (50.5%) | 1 | ||
| Alcohol drinking | Yes | 9 (17.3%) | 35 (9.5%) | 2.0 (.902, 4.451) | 0.088 |
| No | 43 (82.7%) | 335 (90.5%) | 1 | ||
| BMI | > = 25 | 7 (13.5%) | 18 (4.9%) | 3.04 (1.204, 7.68) | 0.019 |
| < 25 | 45 (86.5%) | 352 (95.1%) | 1 | ||
| History of known HTN | Yes | 33 (63.5%) | 130 (35.1%) | 3.206 (1.754, 5.86) | 0.000 |
| No | 19 (36.5%) | 240 (64.9%) | 1 | ||
| History of DM | Yes | 14 (26.9%) | 40 (10.8%) | 3.039 (1.517, 6.09) | 0.002 |
| No | 38 (73.1%) | 330 (89.2%) | 1 | ||
| BP (mmHg) | > = 140/90 | 29 (55.7%) | 87 (23.5%) | 6.583 (3.21, 13.47) | 0.000 |
| 120–139/80–89 | 11 (21.2%) | 46 (12.4%) | 4.723 (1.96, 11.3) | 0.001 | |
| < 120/80 | 12(23.1%) | 237(64.1%) | 1 | ||
Multi-variable logistic analysis of factors associated with high grade albuminuria, Jimma University Medical Center, Ethiopia, 2017
| Variables | OR with 95% CI | |||
|---|---|---|---|---|
| COR (95% CI) | AOR (95%CI) | |||
| History of DM | Yes | 3.039 (1.517, 6.091) | 2.785 (1.332, 5.825) | 0.006 |
| No | 1 | |||
| BP (mmHg) | > = 140/90 | 6.583 (3.21, 13.474) | 6.303 (3.059, 12.987) | 0.000 |
| 120–139/80–89 | 4.723 (1.965, 11.352) | 4.757 (1.962, 11.533) | 0.001 | |
| < 120/80 | 1 | |||
Fig. 2Estimated GFR using serum creatinine based equations, Jimma University Medical Center, Ethiopia, 2017
Fig. 3Comparison of the three serum creatinine based equations, Jimma University Medical Center, Ethiopia, 2017