Table 3. Results of subgroup analysis for the outcome: chronic kidney disease.
| Outcome | Item Assessed in Analysis | Study Feature | Cross-sectional Studies | Longitudinal Studies |
| OR (95% CI), I2 (95% CI), p-Value, n-Comparisons, Participants | HR (95% CI), I2 (95%CI), p-Value, n-Comparisons, Participants | |||
| CKD in NAFLD vs. non-NAFLD | STROBE score | Item (g) fulfilled | 2.11 (1.82–2.44) I2 = 29% (21%–34%), p<0.00001, n = 16, 15,543 participants | 1.79 (1.65–1.95), I2 = 0% (0%–18%), p<0.00001, n = 12, 28,680 participants |
| Item (g) not fulfilled | 1.04 (0.89–1.21), I2 = NA, p = 0.62, n = 1, 11,469 participants | No study | ||
| Item (p) fulfilled | 2.09 (1.65–2.65), I2 = 78% (70%–83%), p<0.00001, n = 12, 26,667 participants | 1.79 (1.65–1.95), I2 = 0% (0%–10%), p<0.00001, n = 11, 27,960 participants | ||
| Item (p) not fulfilled | 2.61(1.44–4.76) I2 = 0% (0%–21%), p = 0.002, n = 2, 345 participants | 1.94 (0.53–7.16), I2 = NA, p = 0.32, n = 1, 720 participants | ||
| Item (s) fulfilled | 2.09 (1.61–2.70), I2 = 79% (71%–85%), p<0.00001, n = 14, 24,838 participants | 1.79(1.64–1.95), I2 = 0% (0%–13%), p<0.00001, n = 11, 26,202 participants | ||
| Item (s) not fulfilled | 2.26 (1.62–3.15), I2 = 0% (0%–12%), p<0.00001, n = 3, 2,174 participants | 1.87 (1.31–2.67), I2 = NA, p = 0.0005, n = 1, 2,478 participants | ||
| Item (t) fulfilled | 2.14 (1.68–2.72), I2 = 78% (71%–84%), p<0.00001, n = 16, 25,600 participants | 1.79 (1.64–1.95), I2 = 0% (0%–9%), p<0.00001, n = 11, 26,202 participants | ||
| Item (t) not fulfilled | 2.00 (1.22–3.26), I2 = NA, p<0.00001, n = 1, 1,412 participants | 1.87 (1.31–2.67), I2 = NA, p = 0.0005, n = 1, 2,478 participants | ||
| Item (v) fulfilled | 2.21 (1.71–2.86), I2 = 78% (71%–84%), p<0.00001, n = 16, 25,306 participants | 1.78 (1.62–1.95), I2 = 0% (0%–10%), p<0.00001, n = 11, 18,343 participants | ||
| Item (v) not fulfilled | 1.69 (1.34–2.12), I2 = NA, p<0.00001, n = 1, 1,706 participants | 1.85 (1.50–2.28), I2 = NA, p<0.00001, n = 1, 10,337 participants | ||
| Presence of diabetes | Non-diabetic participants | 2.37 (1.92–2.93), I2 = 23% (11%–31%), p<0.00001, n = 9, 9,687 participants | 1.85 (1.22–2.28), I2 = 0% (0%–9%), p<0.00001, n = 7, 25,166 participants | |
| Diabetic participants | 1.84 (1.43–2.37), I2 = 24% (18%–29%), p = 0.0001, n = 8, 4,149 participants | 1.67 (1.47–1.91), I2 = 0% (0%–11%), p<0.00001, n = 4, 2,046 participants | ||
| Adjustment for age and BMI and Met Sy and hypertension and smoking | Studies adjusting | 2.06 (1.59–2.66), I2 = 81% (73%–87%), p<0.00001, n = 10, 25,959 participants | 1.79 (1.64–1.95), I2 = 0% (0–10%), p<0.00001, n = 10, 25,482 participants | |
| Studies not adjusting | 2.45 (1.69–3.54), I2 = 0% (0%–10%), p<0.00001, n = 4, 1,053 participants | 1.88 (1.33–2.65), I2 = 0% (0%–11%), p = 0.0003, n = 2, 3,198 participants | ||
| Study design | Population-based | 1.96 (1.49–2.59), I2 = 85% (77%–90%), p<0.00001, n = 8, 25,179 participants | 1.78 (1.63–1.93), I2 = 0% (0%–11%), p<0.00001, n = 9, 28,077 participants | |
| Hospital-based | 2.37 (1.80–3.13), I2 = 0% (0%–14%), p<0.00001, n = 9, 1,833 participants | 2.15 (1.49–3.15), I2 = 0% (0%–9%), p<0.0001, n = 3, 607 participants | ||
| Ethnicity | Non-Asian | 1.97 (1.71–2.27), I2 = 0% (0%–13%), p<0.00001, n = 11, 3,418 participants | 1.70 (1.49–1.96), I2 = 0% (0%–10%), p<0.00001, n = 7, 5,937 participants | |
| Asian | 2.32 (1.74–3.09), I2 = 61% (53%–68%), p<0.00001, n = 7, 6,131 participants | 1.84 (1.65–2.06), I2 = 0% (0%–9%), p<0.00001, n = 4, 20,257 participants | ||
| Presence of cirrhosis | Studies of non-cirrhotic participants | 2.12 (1.67–2.69), I2 = 78% (66%–86%), p<0.00001, n = 16, 26,450 participants | 1.79 (1.65–1.95), I2 = 0% (0%–18%, p<0.00001, n = 12, 28,680 participants | |
| Studies of cirrhotic participants | 2.20 (1.22–3.95), I2 = NA, p = 0.008, n = 1, 562 participants | No study | ||
| Equation used to estimate GFR | Studies using MDRD equation | 1.80 (1.38–2.34), I2 = 83% (76%–88%), p<0.0001, n = 9, 23,109 participants | 1.75 (1.58–1.95), I2 = 0% (0%–35%), p<0.00001, n = 6, 22,737 participants | |
| Studies using CKD-EPI equation | 2.82 (2.15–3.69), I2 = 0% (0%–11%), p<0.00001, n = 8, 3,941 participants | 1.99 (1.60–2.46), I2 = 0% (0%–10%), p<0.00001, n = 5, 3,465 participants | ||
| Outcomes related to CKD | Studies assessing both eGFR and proteinuria | 2.08 (1.62–2.68), I2 = 81% (76%–85%), p<0.00001, n = 13, 26,107 participants | 1.78 (1.63–1.95), I2 = 0% (0%–11%), p<0.00001, n = 9, 25,357 participants | |
| Studies assessing only eGFR | 2.39 (1.55–3.68), I2 = 0% (0%–36%), p<0.00001, n = 4, 905 participants | 1.95 (1.02–3.71), I2 = 0% (0%–11%), p = 0.04, n = 2, 845 participants | ||
| Studies assessing only proteinuria | No study | 1.87 (1.31–2.67), I2 = NA, p = 0.0005, n = 1, 1,508 participants | ||
| Study data | IPD | 1.99 (1.56–2.52), I2 = 0% (0%–13%), p<0.00001, n = 7, 3,538 participants | 1.89 (1.70–2.11), I2 = 0% (0%–8%) p<0.00001, n = 8, 22,984 participants | |
| AD | 2.14 (1.59–2.89) I2 = 76% (80%–90%), p<0.00001, n = 10, 23,474 participants | 1.64 (1.43–1.88) I2 = 0% (0%–10%), p<0.00001, n = 4, 5,696 participants | ||
| CKD in NASH vs. simple steatosis | STROBE item | Item (v) fulfilled | 2.85 (1.72–4.72), I2 = 0% (0%–10%), p<0.0001, n = 7, 800 participants | 2.12 (1.42–3.17), I2 = 0% (0%–19%), p = 0.0002, n = 7, 429 participants |
| Item (v) not fulfilled | 1.22 (0.35–4.31), I2 = NA, p = 0.75, n = 1, 87 participants | No study | ||
| Presence of diabetes | Non-diabetic participants | 2.26 (1.37–3.73), I2 = 0% (0%–13%), p = 0.001, n = 7, 769 participants | 2.03 (1.30–3.17), I2 = 0% (0%–12%), p = 0.002, n = 5, 334 participants | |
| Diabetic participants | 3.80 (1.47–9.81), I2 = 0% (0%–10%), p = 0.003, n = 3, 119 participants | 2.54 (1.05–6.17), I2 = 0% (0%–10%), p = 0.04, n = 3, 96 participants | ||
| Adjustment for age and BMI and Met Sy and hypertension and smoking | Studies adjusting | 2.53 (1.58–4.05), I2 = 0% (0%–14%), p = 0.0001, n = 8, 887 participants | 2.12 (1.42–3.17), I2 = 0% (0%–19%), p = 0.0002, n = 7, 429 participants | |
| Studies not adjusting | No study | No study | ||
| Study design | Population-based | No study | No study | |
| Hospital-based | 2.53 (1.58–4.05), I2 = 0% (0%–14%), p = 0.0001, n = 8, 887 participants | 2.12 (1.42–3.17), I2 = 0% (0%–19%), p = 0.0002, n = 7, 429 participants | ||
| Ethnicity | Non-Asian | 2.53 (1.35–4.73), I2 = 0% (0%–12%), p = 0.004, n = 6, 622 participants | 1.98 (1.28–3.06), I2 = 0% (0%–10%), p = 0.002, n = 5, 327 participants | |
| Asian | 2.64 (1.05–6.62), I2 = 40% (37%–46%), p = 0.04, n = 2, 263 participants | 3.08 (1.09–8.72), I2 = 0% (0%–9%), p = 0.03, n = 2, 102 participants | ||
| Presence of cirrhosis | Studies of non- cirrhotic participants | 2.53 (1.58–4.05), I2 = 0% (0%–14%), p = 0.0001, n = 8, 887 participants | 2.12 (1.42–3.17), I2 = 0% (0%–19%), p = 0.0002, n = 7, 429 participants | |
| Studies of cirrhotic participants | No study | No study | ||
| Equation used to estimate GFR | Studies using MDRD equation | No study | No study | |
| Studies using CKD-EPI equation | 2.53 (1.58–4.05), I2 = 0% (0%–14%), p = 0.0001, n = 8, 887 participants | 2.12 (1.42–3.17), I2 = 0% (0%–19%), p = 0.0002, n = 7, 429 participants | ||
| Outcomes related to CKD | Both eGFR and proteinuria | 2.37 (1.40–4.01), I2 = 0% (0%–13%), p = 0.0001, n = 5, 622 participants | 2.01 (1.16–3.48), I2 = 0% (0%–10%), p = 0.01, n = 4, 282 participants | |
| Only eGFR | 3.25 (1.18–8.98), I2 = 0% (0%–19%), p = 0.02, n = 3, 265 participants | 2.26 (1.26–4.05), I2 = 0% (0%–12%), p = 0.006, n = 3, 147 participants | ||
| Only proteinuria | No study | No study | ||
| Study data | IPD | 2.53 (1.58–4.05), I2 = 0% (0%–14%), p = 0.0001, n = 8, 887 participants | 2.12 (1.42–3.17), I2 = 0% (0%–19%), p = 0.0002, n = 7, 429 participants | |
| AD | No study | No study | ||
| CKD in advanced (stage F3) vs. non-advanced (stage F0–2) fibrosis | STROBE item | Item (v) fulfilled | 4.97 (2.89–8.55), I2 = 0% (0%–12%), p<0.00001, n = 8, 882 participants | 3.29 (2.30–4.71), I2 = 0% (0%–18%), p<0.00001, n = 7, 429 participants |
| Item (v) not fulfilled | 6.94 (1.73–17.76), I2 = NA, p = 0.006, n = 1, 87 participants | No study | ||
| Presence of diabetes | Non-diabetic participants | 5.84(3.25–10.49), I2 = 0% (0%–12%), p<0.00001, n = 8, 844 participants | 2.82 (1.86–4.28), I2 = 0% (0%–11%), p<0.00001, n = 4, 307 participants | |
| Diabetic participants | 5.01 (1.46–17.21), I2 = 0% (0%–13%), p = 0.01, n = 3, 120 participants | 4.19 (2.10–8.38), I2 = 0% (0%–11%), p<0.0001, n = 3, 97 participants | ||
| Adjustment for age and BMI and Met Sy and hypertension and smoking | Studies adjusting | 5.20 (3.14–8.61), I2 = 0% (0%–17%), p<0.00001, n = 9, 969 participants | 3.29 (2.30–4.71), I2 = 0% (0%–18%), p<0.00001, n = 7, 429 participants | |
| Studies not adjusting | No study | No study | ||
| Study design | Population-based | No study | No study | |
| Hospital-based | 5.20 (3.14–8.61), I2 = 0% (0%–17%), p<0.00001, n = 9, 969 participants | 3.29 (2.30–4.71), I2 = 0% (0%–18%), p<0.00001, n = 7, 429 participants | ||
| Ethnicity | Non-Asian | 6.00 (3.15–11.43), I2 = 0% (0%–10%), p<0.00001, n = 7, 704 participants | 2.86 (1.93–4.22), I2 = 0% (0%–11%), p<0.00001, n = 5, 317 participants | |
| Asian | 4.15 (1.85–9.32), I2 = 0% (0%–9%), p = 0.0006, n = 2, 265 participants | 6.01 (2.25–16.09), I2 = 34% (27%–39%), p = 0.004, n = 2, 102 participants | ||
| Presence of cirrhosis | Studies of non- cirrhotic participants | 5.20 (3.14–8.61), I2 = 0% (0%–17%), p<0.00001, n = 9, 969 participants | 3.29 (2.30–4.71), I2 = 0% (0%–18%), p<0.00001, n = 7, 429 participants | |
| Studies of cirrhotic participants | No study | No study | ||
| Equation used for estimating GFR | MDRD-equation | 4.07 (1.52–10.09), I2 = 0% (0%–11%), p = 0.005, n = 2, 176 participants | No study | |
| CKD-EPI equation | 5.67 (3.15–10.20), I2 = 0% (0%–19%), p<0.00001, n = 7, 793 participants | 3.29 (2.30–4.71), I2 = 0% (0%–18%), p<0.00001, n = 7, 429 participants | ||
| Outcomes related to CKD | Both eGFR and p proteinuria | 5.05 (2.95–8.66), I2 = 0% (0%–9%), p<0.00001, n = 6, 702 participants | 3.56 (2.05–6.17), I2 = 16% (10%–21%), p<0.0001, n = 4, 282 participants | |
| Studies assessing only eGFR | 6.36 (1.50–26.91), I2 = 0% (0%–16%), p = 0.01, n = 3, 267 participants | 3.11 (1.85–5.22), I2 = 0% (0%–11%), p<0.0001, n = 3, 147 participants | ||
| Studies assessing only proteinuria | No study | No study | ||
| Study data | IPD | 5.28 (3.06–9.12), I2 = 0% (0%–10%) p<0.00001, n = 8, 889 participants | 3.29 (2.30–4.71), I2 = 0% (0%–18%), p<0.00001, n = 7, 429 participants | |
| AD | 4.71 (1.25–17.72), I2 = NA, p = 0.02, n = 1, 80 participants | No study |
Subgroup analysis was planned a priori to assess the impact of the following items on the association between NAFLD and CKD: (1) Fulfilment of STROBE items: we planned to repeat the analysis after excluding studies not fulfilling each STROBE item (different STROBE items are described in footnote to Table 1). (2) Diabetes: studies including exclusively non-diabetic individuals versus studies including diabetic individuals. (3) Studies simultaneously adjusting versus studies not adjusting for all the following risk factors for CKD: age and BMI and metabolic syndrome (overall or each of its components) and hypertension and smoking. (4) Study design (population-based versus community-based). (5) Ethnicity (Caucasian versus Asian). (6) Studies including only non-cirrhotic patients versus studies including cirrhotic patients. (7) Studies using the CKD-EPI versus studies using the MDRD equation to estimate GFR. (8) Outcomes related to CKD: studies assessing both eGFR and proteinuria versus studies assessing either eGFR or proteinuria. (9) Type of data available: studies with IPD versus studies with AD.