Correction to: BMC Nephrology (2020) 21:387 10.1186/s12882-020-02034-x
Following publication of the original article [1], the authors identified some errors in Abstract, Tables 1, 2 and 3; Fig. 3 and Supplementary files – correcting an error in the calculation of the eGFR in the published version of the paper.
Table 1.
Sociodemographic and anthropometric characteristics of study participants without diabetes, hypertension, and heavy proteinuria) n = 821
| Variable | eGFR | eGFR Categories, n(%)b | |||
|---|---|---|---|---|---|
| N = 821 | N = 17 | N = 115 | N = 689 | ||
| N (%) a | Mean (SD) | < 60 | ≥ 60, < 90 | ≥ 90 | |
| Age | |||||
| < 20 | 60 (7) | 129.2 (21.4) | 1 (1.7) | 1 (1.7) | 58 (96.7) |
| 20–29 | 312 (38) | 120.1 (21.5) | 4 (1.3) | 33 (10.6) | 275 (88.1) |
| 30–39 | 232 (28) | 110.9 (20.6) | 6 (2.6) | 25 (10.8) | 201 (86.6) |
| 40–49 | 130 (16) | 102.7 (19.0) | 3 (2.3) | 27 (20.7) | 100 (76.9) |
| 50–59 | 46 (6) | 97.7 (14.2) | 0 | 10 (21.7) | 36 (78.3) |
| 60+ | 41 (5) | 83.1 (17.4) | 3 (7.3) | 19 (46.3) | 19 (46.3) |
| Sex | |||||
| Female | 504 (61) | 111.8 (23.6) | 14 (2.8) | 70 (13.9) | 420 (83.3) |
| Male | 317 (39) | 113.1 (21.7) | 3 (0.95) | 45 (14.1) | 269 (84.8) |
| Area | |||||
| Urban (Area 25) | 243 (29) | 110.4 (23.9) | 7 (2.9) | 46 (18.9) | 190 (78.1) |
| Rural (Bonje) | 578 (71) | 113.1 (22.4) | 10 (1.7) | 69 (11.9) | 499 (86.3) |
| Education (years) | |||||
| ≤ 5 | 59 (7) | 104.6 (22.9) | 1 (1.7) | 17 (28.8) | 41 (69.5) |
| > 5 ≤ 10 | 301 (36) | 112.1 (23.4) | 8 (2.7) | 35 (11.6) | 258 (85.7) |
| > 10 | 461 (56) | 113.4 (22.4) | 8 (1.7) | 63 (13.7) | 390 (84.6) |
| Occupation | |||||
| Agricultural worker | 383 (47) | 109.9 (20.8) | 7 (1.8) | 48 (12.5) | 328 (85.6) |
| Non-agricultural worker | 438 (53) | 114.3 (24.4) | 10 (2.3) | 67 (15.3) | 361 (82.4) |
| Household monthly income (MK) c | |||||
| Unknown | 17 (1) | 113.2 (32.0) | 1 (5.9) | 1 (5.9) | 15 (88.2) |
| MK 0 ≤ 20,000 | 406 (50) | 113.7 (22.7) | 7 (1.7) | 53 (13.1) | 346 (85.2) |
| MK > 20,000 | 398 (49) | 110.8 (22.6) | 9 (2.3) | 61 (15.3) | 328 (82.4) |
| Healthy lifestyle choices | |||||
| Non-smoker/never drink alcohol | 630 (77) | 111.8 (23.3) | 16 (2.6) | 86 (13.7) | 528 (83.8) |
| Smoker/alcohol drinker | 191 (23) | 113.7 (21.3) | 1 (0.5) | 29 (15.2) | 161 (84.3) |
| Regular meat eater | |||||
| Yes | 621 (76) | 111.3 (23.5) | 14 (2.3) | 87 (14.0) | 520 (83.7) |
| No | 200 (24) | 112.6 (21.0) | 3 (1.5) | 28 (14.0) | 169 (84.5) |
| Body mass index (kg/m 2 ) | |||||
| Underweight (≤ 18.5) | 45 (6) | 118.0 (22.9) | 0 | 8 (17.8) | 37 (82.2) |
| Normal (> 18.5 - ≤ 25) | 545 (66) | 113.9 (22.2) | 8 (1.5) | 72 (13.2) | 465 (85.3) |
| Overweight (> 25 - ≤30) | 177 (22) | 108.4 (22.5) | 4 (2.3) | 25 (14.1) | 148 (83.6) |
| Obese (> 30) | 54 (7) | 104.3 (27.4) | 5 (9.3) | 10 (18.5) | 39 (72.2) |
| Fat-free mass (kg) | |||||
| 1st tertile (≤ 37) | 124 (15) | 112.7 (19.3) | 0 | 17 (13.7) | 107 (86.3) |
| 2nd tertile (> 37 - < 45) | 354 (43) | 111.3 (24.5) | 9 (2.5) | 57 (16.1) | 288 (81.4) |
| 3rd tertile (≥ 45) | 343 (42) | 111.3 (22.4) | 8 (2.3) | 41 (11.9) | 294 (85.7) |
| HIV status | |||||
| Positive | 3 (0.4) | 109.7 (21.7) | 0 | 1 (33.3) | 2 (66.6) |
| Negative | 595 (73) | 112.3 (21.8) | 11 (1.8) | 75 (12.6) | 509 (85.5) |
| Unknown | 223 (27) | 112.2 (25.8) | 6 (2.7) | 39 (17.5) | 178 (79.8) |
apercentage in columns
bpercentage in rows
cExchange rate (MK to USD) 0.001 at time of questionnaire
Table 2.
Associations between sociodemographic and anthropometric characteristics and eGFR < 90 in participants without diabetes, hypertension, proteinuria, n = 821
| Model 1 minimal adjustment | Model 2 full adjustment | Model 3 minimal adjustment | Model 4 full adjustment | |
|---|---|---|---|---|
| eGFR | eGFR | eGFR < 90 | eGFR < 90 | |
| Variable | Coefficient (95%CI)a | Coefficient (95%CI)b | Coefficient (95%CI)a | Coefficient (95%CI)b |
| Age (per 10-year increase) c | -9.07 (-10.17, -7.98) | -9.20 (-10.44, -7.97) | 1.77 (1.54, 2.06) | 1.79 (1.53, 2.13) |
| Sex d | ||||
| Male | 1.57 (-1.23, 4.38) | 0.45 (-2.85, 3.76) | 0.85 (0.56, 1.28) | 0.90 (0.55, 1.49) |
| Female | Ref. | Ref. | Ref. | Ref. |
| Study area | ||||
| Urban (Area 25) | Ref. | Ref. | Ref | Ref. |
| Rural (Bonje) | 7.39 (4.34, 10.44) | 7.47 (3.43, 11.52) | 0.37 (0.24, 0.57) | 0.43 (0.24, 0.79) |
| Education (years) | ||||
| ≤ 5 | 5.27 (-0.53, 11.09) | 5.04 (-0.84, 10.93) | 1.13 (0.53, 2.34) | 1.08 (0.50, 2.27) |
| > 5 ≤ 10 | 1.16 (-2.00, 4.33) | 1.20 (-1.99, 4.41) | 0.87 (0.54, 1.41) | 0.87 (0.53, 1.41) |
| > 10 | Ref. | Ref. | Ref. | Ref. |
| Occupation | ||||
| Agricultural worker | -1.05 (-4.59, 2.47) | -1.07 (-4.65, 2.51) | 0.69 (0.41, 1.21) | 0.69 (0.40, 1.21) |
| Non-agricultural worker | Ref. | Ref. | Ref. | |
| Household monthly income (MK) e | ||||
| Unknown | -1.86 (-11.57, 7.84) | -2.95 (-12.75, 6.83) | 0.73 (0.11, 3.04) | 0.80 (0.11, 3.35) |
| MK 0 ≤ 20,000 | 0.10 (-2.99, 3.20) | -0.36 (-3.54, 2.80) | 1.21 (0.77, 1.94) | 1.29 (0.81, 2.11) |
| MK > 20,000 | Ref. | Ref. | Ref. | Ref. |
| BMI (kg/m 2 ) | ||||
| Per 5 kg increase | -1.64(-3.48, 0.20) | -1.59 (-3.45, 0.27) | 1.09 (0.85, 1.39) | 1.10 (0.86, 1.42) |
| Fat-free mass | ||||
| Per 5 kg increase | -0.02 (-0.10, 0.05) | -0.01 (-0.10, 0.06) | 0.99 (0.93, 1.01) | 0.99 (0.00, 1.01) |
| Healthy lifestyle choices | ||||
| Non-smoker or alcohol drinker | -2.43 (-5.97, 1.10) | -2.34 (-5.92, 1.22) | 1.02 (0.62, 1.73) | 1.00 (0.60, 1.71) |
| Smoker and alcohol drinker | Ref. | Ref. | Ref. | Ref. |
| Regular meat eater | ||||
| Yes | -0.35 (-2.91, 3.62) | -0.29 (-3.04, 3.63) | 0.90 (0.55, 1.44) | 0.91 (0.55, 1.48) |
| No | Ref. | Ref. | Ref. | Ref. |
Hypertension = systolic bp ≥ 140 mmHg, or diastolic bp ≥ 90 mmHg; Diabetes = fasting glucose > = 7 mg/l; Proteinuria = ACR > = 30 mg/mmol
aminimal adjustment for age, sex and area
ball variables mutually adjusted
cadjusted for sex and area
dadjusted for age and area
eExchange rate (MK to USD) 0.001 at time of questionnaire
Table 3.
Associations between sociodemographic and anthropometric characteristics and estimated glomerular filtration rate (eGFR) (fully adjusted) after removal of those with hypertension, diabetes and proteinuria, Area 25 (n = 243) and Bonje (n = 578)
| Bonje | Bonje | Area 25 | Area 25 | |
|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | |
| Variable | eGFR | eGFR group (< 90) | eGFR | eGFR group (< 90) |
| Coefficient (95%CI)a | Coefficient (95%CI)b | Coefficient (95%CI)a | Coefficient (95%CI)b | |
| Age (per 10-year increase) c | -9.42 (-10.71, -8.14) | 1.81 (1.50, 2.22) | -7.99 (-11.48, -4.50) | 1.73 (1.22, 2.51) |
| Sex d | ||||
| Male | 0.58 (-3.25, 4.43) | 1.05 (0.53, 2.21) | -0.76 (-7.46, 5.93) | 0.81 (0.37, 1.72) |
| Female | Ref. | Ref. | Ref. | Ref. |
| Education (years) | ||||
| ≤ 5 | 4.34 (-1.89, 10.58) | 1.16 (0.46, 2.81) | 8.97 (-6.02, 23.97) | 0.70 (0.12, 3.05) |
| > 5 ≤ 10 | 1.88 (-1.45, 5.23) | 0.66 (0.37, 1.20) | -3.05 (-11.92, 5.82) | 1.89 (0.78, 4.45) |
| > 10 | Ref. | Ref. | Ref. | Ref. |
| Occupation | ||||
| Agricultural worker | -1.03 (-4.47, 2.40) | 0.68 (0.38, 1.23) | 5.81 (-21.09, 32.71) | 0.68 (0.03, 8.22) |
| Non-agricultural worker | Ref. | Ref. | Ref. | Ref. |
| Household monthly income (MK) e | ||||
| Unknown | -8.33 (-20.50, 3.82) | 1.08 (0.05, 7.34) | 3.90 (-13.64, 21.44) | 0.89 (0.04, 5.88) |
| MK 0 ≤ 20,000 | -1.07 (-4.39, 2.25) | 1.28 (0.74, 2.28) | 2.98 (-5.62, 11.59) | 1.25 (0.45, 3.20) |
| MK > 20,000 | Ref. | Ref. | Ref. | Ref. |
| BMI (kg/m 2 ) | ||||
| Per 5 kg increase | -1.46 (-3.69, 0.75) | 1.33 (0.94, 1.93) | -2.03 (-5.59, 1.53) | 0.93 (0.64, 1.35) |
| Fat-free mass | ||||
| Per 5 kg increase | -0.02 (-0.11, 0.07) | 0.98 (0.00, 1.01) | 0.01 (-0.16, 0.16) | 0.99 (0.00, 1.02) |
| Healthy lifestyle choices | ||||
| Non-smoker or alcohol drinker | -2.37 (-6.55, 1.80) | 1.00 (0.50, 2.05) | -3.13 (-10.41, 4.13) | 1.05 (0.16, 1.57) |
| Smoker and alcohol drinker | Ref. | Ref. | Ref. | Ref. |
| Regular meat eater | ||||
| Yes | -0.13 (-3.57, 3.30) | 1.06 (0.60, 1.86) | -3.31 (-6.56, 13.20) | 0.55 (0.47, 2.54) |
| No | Ref. | Ref. | Ref. | Ref. |
Hypertension = systolic bp ≥ 140 mmHg, or diastolic bp ≥ 90 mmHg; Diabetes = fasting glucose > = 7 mg/l; Proteinuria = ACR > = 30 mg/mmol
aminimal adjustment for age and sex
ball variables mutually adjusted
cadjusted for sex and area
dadjusted for age and area
eExchange rate (MK to USD) 0.001 at time of questionnaire
Fig. 3.
Histogram of eGFR distribution in the sample population
NB: although these corrections mean that the numbers for the eGFR analyses (e.g. eGFR < 60) have changed, the main findings of the paper have not changed.
Also, the authors wanted to have removed the following sentence under the section “urban rural comparison of eGFR”
Due to the small proportion of participants in the eGFR < 90 category in the urban population, we could not conduct logistic regression analyses for Area 25.
Corrected Abstract
Background
An epidemic of chronic kidney disease of unknown cause (CKDu) is occurring in rural communities in tropical regions of low-and middle-income countries in South America and India. Little information is available from Southern African countries which have similar climatic and occupational characteristics to CKDu-endemic countries. We investigated whether CKDu is prevalent in Malawi and identified its potential risk factors in this setting.
Methods
We conducted a cross-sectional study from January–August 2018 collecting bio samples and anthropometric data in two Malawian populations. The sample comprised adults > 18 years (n = 821) without diabetes, hypertension, and proteinuria. Estimates of glomerular filtration rate (eGFR) were calculated using the CKD-EPI2009 equation. Linear and logistic regression models were applied with potential risk factors, to estimate risk of reduced eGFR.
Results
The mean eGFR was 112.3 ± 22.9 ml/min per 1.73m2 and the mean participant age was 33.5 ± 12.7 years. The prevalence of eGFR < 60 was 2.1% (95% confidence interval (95% CI) 1.2, 3.2); the prevalence of eGFR < 90 was 16.1% (95% CI = 13.6, 18.7). We observed a higher prevalence of eGFR < 90 in the urban population (21.8% (16.8, 27.5)), versus rural (13.7% (10.9, 16.7)). Age was associated with increased risk of eGFR < 90 [Odds ratio (OR) (95%CI) = 1.79 (1.53, 2.13) per ten-year increment]. Lower risk of eGFR < 90 was observed for rural participants [OR (95%CI) = 0.43 (0.24, 0.79)].
Conclusions
Reduced kidney function consistent with the definition of CKDu is not common in the areas of Malawi sampled, compared to that observed in other tropical or sub-tropical countries in Central America and South Asia. Reduced eGFR < 90 was related to age and was more common in urban areas. These findings are important as they contradict some current hypothesis that CKDu is endemic across tropical and sub-tropical countries. This study has enabled standardized comparisons of impaired kidney function between and within tropical/subtropical regions of the world and will help form the basis for further etiological research, surveillance strategies, and the implementation and evaluation of interventions.
Corrected Tables
Supplementary files
Table S1.
Sociodemographic and anthropometric characteristics of overall study participants (prior to exclusion of population with diabetes, hypertension and heavy proteinuria)
| eGFR categories, n(%)b | ||||||
|---|---|---|---|---|---|---|
| Variable | eGFR n = 1076 | n = 36 | n = 167 | n = 873 | ||
| n(%)a | Mean (SD) | < 60 | >=60,<90 | >=90 | ||
| Age (years) | ||||||
| < 20 | 66 (6) | 129.8(22.3) | 1 (2) | 2 (3) | 63 (96) | |
| 20–29 | 362 (34) | 120.2(21.8) | 6 (2) | 36 (9) | 320 (88) | |
| 30–39 | 280 (26) | 110.6(20.7) | 8 (3) | 32 (11) | 240 (86) | |
| 40–49 | 185 (17) | 101.5 (21.2) | 7 (4) | 36 (19) | 142 (77) | |
| 50–59 | 79 (7) | 97.1(15.1) | 2 (3) | 16 (20) | 61 (77) | |
| 60+ | 104 (10) | 82.9(19.8) | 12 (12) | 45 (43) | 47 (45) | |
| Sex | ||||||
| Female | 654 (61) | 109.3(24.8) | 27 (4) | 96 (15) | 531(81) | |
| Male | 422 (39) | 110.5(23.2) | 9 (2) | 71 (17) | 342 (81) | |
| Education (no of years) | ||||||
| ≤ 5 | 108 (10) | 96.8.(24.3) | 7 (6) | 31 (29) | 70 (65) | |
| > 5 ≤ 10 | 399 (37) | 110.1(23.7) | 15 (4) | 48 (12) | 336 (84) | |
| > 10 | 569 (53) | 112.0(23.9) | 14 (3) | 88 (15) | 467 (82) | |
| Occupation | ||||||
| Office worker | 245 (23) | 115.0(25.2) | 6 (2) | 29 (12) | 210 (86) | |
| Self-employed | 133 (12) | 109.2(23.1) | 5 (4) | 22 (17) | 106 (79) | |
| Farmer | 493 (46) | 107.2(23.0) | 18 (3) | 75 (15) | 400 (81) | |
| Fisherman | 18 (2) | 99.1(19.2) | 1 (6) | 3 (16) | 14 (78) | |
| Unemployed | 59 (6) | 112.4(23.2) | 1 (1) | 12 (20) | 46 (79) | |
| Unpaid/domestic worker | 113 (11) | 114.2(26.0) | 3 (3) | 18 (16) | 92 (81) | |
| Retired | 12 (1) | 79.4(19.7) | 2 (17) | 7(58) | 3 (25) | |
| Refused | 3 (0.3) | 96.7(26.1) | 0 | 1 (33) | 2 (67) | |
| Household monthly income (MK) c | ||||||
| < 5000 | 145 (14) | 113.5(26.4) | 5 (3) | 22 (15) | 117 (81) | |
| > 5,000 < 10,000 | 177 (16) | 110.4(24.4) | 5 (3) | 23 (13) | 149 (84) | |
| > 10,000 < 20,000 | 193 (18) | 110.5(24.1) | 6 (3) | 28 (15) | 159 (83) | |
| > 20,000 < 40,000 | 219 (20) | 111.3(22.3) | 7 (3) | 28 (13) | 184 (84) | |
| > 40,000 | 321 (30) | 106.3(23.5) | 11 (3) | 63 (20) | 247 (77) | |
| Don’t know | 17 (2) | 107.4(35.1) | 2 (12) | 2 (12) | 13 (76) | |
| Refused | 4 (0.4) | 111.6(26.2) | 0 | 1(25) | 3 (75) | |
| Area | ||||||
| Urban (Area 25) | 326 (30) | 108.5(23.9) | 11 (3) | 63 (19) | 252 (77) | |
| Rural (Bonje) | 750 (70) | 110.3(24.3) | 25(3) | 104 (14) | 621 (83) | |
| Healthy lifestyle choices | ||||||
| Non-smoker/ alcohol drinker | 820 (77) | 109.5(24.5) | 31 (4) | 127 (15) | 662 (81) | |
| Smoker/ alcohol drinker | 256 (24) | 114.8(16.1) | 5 (2) | 40 (16) | 211 (83) | |
| Regular meat-eater | ||||||
| Yes | 247 (23) | 109.9(24.9) | 6 (2) | 36 (14) | 205 (83) | |
| No | 829 (77) | 109.2(22.0) | 30 (2) | 131 (16) | 668 (81) | |
| Body mass index (kg/m2) | ||||||
| Underweight (≤ 18.5) | 55 (5) | 115.5(25.1) | 1(2) | 12 (22) | 42 (76) | |
| Normal (> 18.5 - ≤ 25) | 677 (63) | 111.8(23.80) | 19 (3) | 95 (14) | 563 (83) | |
| Overweight (> 25 - ≤30) | 242 (23) | 106.2(22.9) | 8 (3) | 39 (16) | 195 (81) | |
| Obese (> 30) | 102 (10) | 101.3(26.9) | 8 (8) | 21 (21) | 73 (72) | |
| Fat-free mass (kg) | ||||||
| 1st tertile (≤ 37) | 171 (16) | 106.5(23.4) | 7 (4) | 31 (18) | 133 (78) | |
| 2nd tertile (> 37 - <45) | 442 (41) | 109.4(25.3) | 15 (4) | 73 (17) | 354 (80) | |
| 3rd tertile (≥ 45) | 463 (43) | 111.3(23.3) | 14 (3) | 63 (14) | 386 (83) | |
a Percentages in columns; b percentages in rows; Hypertension = systolic bp ≥ 140 mm Hg, or diastolic bp ≥ 90 mm Hg; Diabetes = fasting glucose > = 7 mg/l; Proteinuria = ACR > = 30 mg/mmol; c Exchange rate (MK to USD) 0.001 at time of questionnare
Table S2.
Linear and logistic regression models, showing both minimally and fully adjusted models Bonje (n = 578)
| Bonje | Bonje | Bonje | Bonje | |
|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | |
| Variable | eGFR | eGFR | eGFR < 90 | eGFR < 90 |
| Coefficient (95%CI)a; | Coefficient (95%CI)b; | Coefficient (95%CI)a; | Coefficient (95%CI)b; | |
| Agec | ||||
| Per 10-year increase | -9.28 (-10.41, -8.14) | -9.42 (-10.71, -8.14) | 1.81 (1.54, 2.16) | 1.81 (1.50, 2.22) |
| Sexd | ||||
| Male | 1.70 (-1.39, 4.81) | 0.58 (-3.25, 4.43) | 0.90 (0.54, 1.51) | 1.05 (0.53, 2.21) |
| Female | Ref | Ref. | Ref | Ref. |
| Education (years) | ||||
| ≤ 5 | 4.49 (-1.64, 10.64) | 4.34 (-1.89, 10.58) | 1.21 (0.50, 2.81) | 1.16 (0.46, 2.81) |
| > 5 ≤ 10 | 1.70 ( -1.60, 5.00) | 1.88 (-1.45, 5.23) | 0.68 (0.38, 1.22) | 0.66 (0.37, 1.20) |
| > 10 | Ref | Ref. | Ref | Ref. |
| Occupation | ||||
| Agricultural worker | -1.01 ( -4.39, 2.37) | -1.03 (-4.47, 2.40) | 0.67 (0.39, 1.20) | 0.68 (0.38, 1.23) |
| Non-agricultural worker | Ref | Ref. | Ref | Ref. |
| Household monthly income (MK)e | ||||
| Unknown | -7.06 (-18.97, 4.84) | -8.33 (-20.50, 3.82) | 0.76 (0.04, 5.27) | 1.08 (0.05, 7.34) |
| MK 0 ≤ 20,000 | -0.70 (-3.94, 2.53) | -1.07 (-4.39, 2.25) | 1.18 (0.70, 2.06) | 1.28 (0.74, 2.28) |
| MK > 20,000 | Ref. | Ref. | Ref. | Ref. |
| BMI (kg/m2) | ||||
| 5 kg/m2 increase | -1.52 ( -3.72, 0.66) | -1.46 (-3.69, 0.75) | 1.26 (0.90, 1.75) | 1.33 (0.94, 1.93) |
| Fat Free Mass (kg) | ||||
| (Per 5 kg unit increase) | -0.03 (-0.13, 0.05) | -0.02 (-0.11, 0.07) | 0.99 (0.00, 1.01) | 0.98 (0.00, 1.01) |
| Healthy lifestyle choices | ||||
| Non-smoker or alcohol drinker | -2.52 (-6.62, 1.57) | -2.37 (-6.55, 1.80) | 1.06 (0.54, 2.15) | 1.00 (0.50, 2.05) |
| Smoker and alcohol drinker | Ref | Ref. | Ref | Ref. |
| Regular meat-eater | ||||
| Yes | -0.32 ( -3.66, 3.01) | -0.13 (-3.57, 3.30) | 1.01 (0.58, 1.72) | 1.06 (0.60, 1.86) |
| No | Ref | Ref. | Ref | Ref. |
a Exchange rate (MK to USD) 0.001 at time of questionnaire; Hypertension = systolic bp ≥ 140 mm Hg, or diastolic bp ≥ 90 mm Hg; Diabetes = fasting glucose > = 7 mg/l; Proteinuria = ACR > = 30 mg;
aminimal adjustment for age and sex
ball variables mutually adjusted
cadjusted for sex and
dadjusted for age and
eExchange rate (MK to USD) 0.001 at time of questionnaire
Table S3.
Linear regression models, showing both minimally and fully adjusted models, Area 25 (n = 243)
| Area 25 | Area 25 | Area 25 | Area 25 | |
|---|---|---|---|---|
| Variable | Model 1 | Model 2 | Model 3 | Model 4 |
| eGFR | eGFR | eGFR < 90 | eGFR < 90 | |
| Coefficient (95%CI)a; | Coefficient (95%CI)b; | Coefficient (95%CI)a; | Coefficient (95%CI)b; | |
| Age c | ||||
| Per 10-year increase | -8.20 ( -11.08, -5.32) | -7.99 (-11.48, -4.50) | 1.64 (1.23, 2.22) | 1.73 (1.22, 2.51) |
| Sex d | ||||
| Male | 1.20 (-4.87, 7.27) | -0.76 (-7.46, 5.93) | 0.77 (0.38, 1.50) | 0.81 (0.37, 1.72) |
| Female | Ref | Ref. | Ref | Ref. |
| Education (years) | ||||
| ≤ 5 | 9.01 (-5.67, 23.71) | 8.97 (-6.02, 23.97) | 0.71 (0.13, 2.97) | 0.70 (0.12, 3.05) |
| > 5 ≤ 10 | -2.13 (-10.79, 6.52) | -3.05 (-11.92, 5.82) | 1.81 (0.76, 4.14) | 1.89 (0.78, 4.45) |
| > 10 | Ref | Ref. | Ref | Ref. |
| Occupation | ||||
| Agricultural worker | 3.23 (-23.29, 29.75) | 5.81(-21.09, 32.71) | 0.88 (0.04, 9.97) | 0.68 (0.03, 8.22) |
| Non-agricultural worker | Ref | Ref. | Ref | Ref. |
| Household monthly income (MK)e | ||||
| Unknown | 5.89 (-11.37, 23.16) | 3.90 (-13.64, 21.44) | 0.68 (0.03, 4.72) | 0.89 (0.04, 5.88) |
| MK 0 ≤ 20,000 | 3.66 (-4.74, 12.06) | 2.98 (-5.62, 11.59) | 1.29 (0.47, 3.20) | 1.25 (0.45, 3.20) |
| MK > 20,000 | Ref, | Ref. | Ref. | Ref. |
| BMI (kg/m2) | ||||
| 5 kg/m2 increase | -2.07 (-5.56, 1.41) | -2.03 (-5.59, 1.53) | 0.93 (0.64, 1.34) | 0.93 (0.64, 1.35) |
| Fat Free Mass (kg) | ||||
| (Per 5 kg increase) | 0.01 (-0.16, 0.17) | 0.01 (-0.16, 0.16) | 0.99 (0.00, 1.01) | 0.99 (0.00, 1.02) |
| Healthy lifestyle choices | ||||
| Non-smoker or alcohol drinker | -2.64 (-9.81, 4.52) | -3.13 (-10.41, 4.13) | 1.04 (0.48, 2.44) | 1.05 (0.16, 1.57) |
| Smoker and alcohol drinker | Ref | Ref. | Ref | Ref. |
| Regular meat-eater | ||||
| Yes | -3.87 (-5.73, 13.47) | -3.31 (-6.56, 13.20) | 0.64 (0.20, 1.76) | 0.55 (0.47, 2.54) |
| No | Ref | Ref. | Ref | Ref. |
a Exchange rate (MK to USD) 0.001 at time of questionnaire; Hypertension = systolic bp ≥ 140 mm Hg, or diastolic bp ≥ 90 mm Hg; Diabetes = fasting glucose > = 7 mg/l; Proteinuria = ACR > = 30 mg;
aminimal adjustment for age and sex
ball variables mutually adjusted
cadjusted for sex
dadjusted for age
eExchange rate (MK to USD) 0.001 at time of questionnaire
Footnotes
The online version of the original article can be found at 10.1186/s12882-020-02034-x.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Hamilton, et al. BMC Nephrol. 2020;21387. 10.1186/s12882-020-02034-x.