Study population
A total of 14,271 participants were eventually enrolled in our study, including 52.07% men and 47.93% women (Fig. 1). Among them, 2511 (17.60%) participants had NAFLD and 11760 participants (82.40%) did not suffer from NAFLD. The average age of the study population was 43.53 ± 8.90 years. During a median follow-up of 2206.64 ± 1376.42 days, 324 participants developed DM. Some baseline variables were statistically significant differences between NAFLD participants and non-NAFLD participants before conducting PSM. Higher age, BMI, WC, SBP, DBP, FPG, HbA1c, AST, ALT, GGT, TC and TG were observed in participants with NAFLD. We also found participants with NAFLD had a higher proportion of males, ever smoker and current smoker. Participants with non-NAFLD had a higher level of HDL-C and rates of regular exerciser. 1711 NAFLD patients were matched with 1711 non-NAFLD subjects by using one-to-one PSM. The standardized differences of almost all variables were less than 10.0% after PSM, showing an exact match. In other words, the differences in baseline characteristics between the two groups were minimal.
The Incidence Of Diabetes
The incidence of DM caused by NAFLD exposure before and after PSM was shown in Table 2. Our study included a total of 14,271 participants, 324 of whom developed DM during follow-up before PSM. The diabetes incidence rate in the overall population, NAFLD participants and non-NAFLD participants were 375.536/ 100,000 person-years, 1354.974/100,000 person-years and 168.512/100,000 person-years. NAFLD group and non-NAFLD group corresponding cumulative incidence of DM were 8.124 (7.055–9.194) and 1.020 (0.839–1.202), respectively. After PSM, the approximate incidence difference between the two groups changed greatly (687.960/100,000 person-years in the overall population, 907.082/100,000 person-years in the NAFLD participants, and 458.980/100,000 person-years in the non-NAFLD participants). The corresponding cumulative incidence in the NAFLD and non-NAFLD groups were 5.552 (4.466–6.638) and 2.688 (1.921–3.456).
Table 2
Incidence of incident DM before and after propensity score matching.
Variable
|
Participants(n)
|
DM events(n)
|
Cumulative incidence
(95% CI)
|
Per 100,000 person-year
|
Before Matching
|
|
|
|
|
Total
|
14271
|
324
|
2.270(2.026–2.515)
|
375.536
|
NAFLD
|
2511
|
204
|
8.124(7.055–9.194)
|
1354.974
|
Non- NAFLD
|
11760
|
120
|
1.020(0.839–1.202)
|
168.512
|
After Matching
|
|
|
|
|
Total
|
3422
|
141
|
4.120(3.454–4.787)
|
687.960
|
NAFLD
|
1711
|
95
|
5.552(4.466–6.638)
|
907.082
|
Non- NAFLD
|
1711
|
46
|
2.688(1.921–3.456)
|
458.980
|
CI, confidence interval; DM, diabetes mellitus. |
Kaplan–Meier analysis revealed that the cumulative incidence of DM in the participants with NAFLD was significantly higher than that in non-NAFLD participants before PSM (p < 0.0001 by the log-rank; Fig. 2a). There are still significant differences in the cumulative incidence of diabetes between the two groups in the PSM cohort (log-rank test; P < 0.0001; Fig. 2b). Besides, we also found that the cumulative incidence of diabetes was significantly higher in participants with higher propensity scores(Fig. 3).
Association Between Nafld And Incident Diabetes
The Cox proportional hazards regression model was applied to assess the association between NAFLD and DM risk in the PSM cohort. Table 3 showed the unadjusted, partially adjusted, fully adjusted and propensity-score adjusted models in detail. NAFLD was significantly associated with the incidence of DM in the unadjusted model (HR = 1.92, 95%CI: 1.35–2.74, P = 0.0003). In other words, participants with NAFLD were 1.92 times more likely to develop diabetes than non-NAFLD participants. The results remained significant after adjusting for the partial confounding variables (age, gender, BMI, waist circumference, smoking status, alcohol consumption, regular exerciser, SBP, DBP) (HR: 2.00, 95%CI: 1.40–2.84, P = 0.0001). In the fully adjusted model (adjusted for age, gender, BMI, WC, smoking status, alcohol consumption, regular exerciser, SBP, DBP, ALT, AST, GGT, HbA1c, FPG, TC, TG, HDL-C), we could still observe the association between NAFLD and incidence of DM (HR = 2.15, 95%CI: 1.48–3.11, P < 0.0001). It showed that participants with NAFLD were 2.15-fold more likely to develop diabetes than non-NAFLD participants. This association was still detected in the PSM model, and participants with NAFLD had an 89% increased risk of diabetes (HR = 1.89, 95%CI: 1.33–2.69, P = 0.0004).
Table 3
Association between NAFLD and incident diabetes in different models.
Variable
|
Non-adjusted(HR,95%CI,P)
|
Model I (HR,95%CI, P)
|
Model II (HR,95%CI, P)
|
Model III (HR,95%CI, P)
|
Non-NAFLD
|
Ref.
|
Ref.
|
Ref.
|
Ref.
|
NAFLD
|
1.92 (1.35, 2.74) 0.0003
|
2.00 (1.40, 2.84) 0.0001
|
2.15 (1.48, 3.11) < 0.0001
|
1.89 (1.33, 2.69) 0.0004
|
Crude model: we did not adjust for other covariates. |
Model I: we adjusted for age, gender, BMI, waist circumference, smoking status, alcohol consumption, regular exerciser, SBP, DBP. |
Model II: we adjusted for age, gender, BMI, waist circumference, smoking status, alcohol consumption, regular exerciser, SBP, DBP, ALT, AST, GGT, HbA1c, FPG, TC, TG, HDL-C. |
Model III: we adjusted for propensity score. |
HR, Hazard ratios; CI, Confidence interval; Ref, Reference |
Subgroup Analysis
Subgroup analysis was applied to discover potential confounding variables that might affect the association between NAFLD and DM risk. To assess the trend of effect size in potential confounding variables, we used gender, BMI, WC, TC, TG, HDL-C, FPG, HbA1c, ALT, AST, GGT and propensity score as stratification variables. Table 4 revealed that most potential confounding variables did not influence the association between NAFLD and DM risk after PSM, except for BMI (P for interaction = 0.0140) and visceral fat obesity (P for interaction = 0.0157). Specifically, compared with non-NAFLD participants with a BMI < 25kg/m2, the hazard ratios of BMI < 25kg/m2 and BMI ≥ 25kg/m2 in the NAFLD participants were 1.22 (0.64, 2.30), and 4.77 (1.98, 11.49), respectively. Concerning the non-NAFLD participants without the visceral fat obesity, the hazard ratios of non-visceral fat obesity and visceral fat obesity in the NAFLD participants were1.25 (0.74, 2.11) and 10.95 (1.57, 76.47). Thus, there was a more significant association between NAFLD and incidence of DM in the participants with BMI ≥ 25kg/m2 or visceral fat obesity.
Table 4
Effect size of NAFLD on incident diabetes in prespecified and exploratory subgroups
Characteristic
|
No of participants
|
HR (95%CI)
|
P value
|
P for interaction
|
Gender
|
|
|
|
0.6889
|
Male
|
2082
|
1.86 (1.15, 2.98)
|
0.0107
|
|
Female
|
218
|
164.87 (0.00, Inf)
|
0.9997
|
|
BMI(Kg/m2)
|
|
|
|
0.0140
|
< 25
|
1580
|
1.22 (0.64, 2.30)
|
0.5461
|
|
≥ 25
|
668
|
4.77 (1.98, 11.49)
|
0.0005
|
|
Visceral fat obesity
|
|
|
|
0.0157
|
NO
|
2008
|
1.25 (0.74, 2.11)
|
0.4145
|
|
YES
|
242
|
10.95 (1.57, 76.47)
|
0.0158
|
|
FPG (mg/dL)
|
|
|
0.8589
|
|
Low
|
786
|
2.74 (0.69, 10.93)
|
0.1533
|
|
High
|
1056
|
2.43 (1.43, 4.16)
|
0.0011
|
|
HbA1c (%)
|
|
|
|
0.8433
|
Low
|
522
|
4.19 (0.16, 111.82)
|
0.3929
|
|
High
|
1306
|
2.48 (1.55, 3.98)
|
0.0002
|
|
TC (mg/dL)
|
|
|
|
0.5314
|
Low
|
792
|
1.83 (0.55, 6.05)
|
0.3248
|
|
High
|
834
|
2.94 (1.54, 5.61)
|
0.0011
|
|
TG (mg/dL)
|
|
|
|
0.3118
|
Low
|
970
|
1.45 (0.62, 3.38)
|
0.3914
|
|
High
|
990
|
2.65 (1.44, 4.87)
|
0.0018
|
|
HDL-C(mg/dL)
|
|
|
|
0.4346
|
Low
|
944
|
3.42 (1.76, 6.66)
|
0.0003
|
|
High
|
950
|
6.36 (1.61, 25.06)
|
0.0082
|
|
ALT(U/L)
|
|
|
|
0.5752
|
Low
|
974
|
2.29 (0.85, 6.15)
|
0.0995
|
|
High
|
1006
|
3.08 (1.59, 5.99)
|
0.0009
|
|
AST(U/L)
|
|
|
|
0.8560
|
Low
|
822
|
2.43 (0.81, 7.29)
|
0.1134
|
|
High
|
1030
|
2.60 (1.34, 5.03)
|
0.0047
|
|
GGT(U/L)
|
|
|
|
0.0986
|
Low
|
934
|
6.55 (1.81, 23.71)
|
0.0042
|
|
High
|
988
|
2.16 (1.19, 3.92)
|
0.0111
|
|
propensity score
|
|
|
|
0.4530
|
Low
|
1684
|
1.61 (0.76, 3.40)
|
0.2121
|
|
High
|
1684
|
2.28 (1.47, 3.53)
|
0.0002
|
|
Note 1: The above model has been adjusted for age, gender, BMI, waist circumference, smoking status, alcohol consumption, regular exerciser, SBP, DBP, ALT, AST, GGT, HbA1c, FPG, TC, TG, HDL-C. |
Sensitivity Analysis
We applied the estimated propensity score as the weight and generated a weighted cohort by establishing an IPTW model. Our study evaluated the association between NAFLD and incidence of DM in the original cohort and the weighted cohort through the Cox proportional hazards regression model, which could increase the robustness of results. Besides, the unadjusted, partially and fully adjusted models were established in both cohorts in Table 5. We demonstrated that NAFLD was closely associated with the risk of DM in the original cohort or the weighted cohort. In the fully adjusted models, participants with NAFLD had an 82% increase in the risk of DM in the original cohort (HR = 1.82, 95% CI: 1.33–2.48, P = 0.0001), and a 70% increase in the weighted cohort ( HR = 1.70, 95% CI: 1.40–2.06, P < 0.00001).
Table 5 Association between NAFLD and incident diabetes in different models of the original and the weighted cohort.
A
Variable
|
Non-adjusted
|
Model I (HR,95%CI,P)
|
Model II (HR,95%CI,P)
|
Non-NAFLD
|
Ref.
|
Ref.
|
Ref.
|
NAFLD
|
8.08 (6.45, 10.13) <0.0001
|
3.84 (2.92, 5.05) <0.0001
|
1.82 (1.33, 2.48) 0.0001
|
B
Variable
|
Non-adjusted
|
Model I (HR,95%CI, P)
|
Model II (HR,95%CI, P)
|
Non-NAFLD
|
Ref.
|
Ref.
|
Ref.
|
NAFLD
|
3.06 (2.60, 3.60) <0.0001
|
2.79 (2.37, 3.29) <0.0001
|
1.70 (1.40, 2.06) <0.0001
|
A In the original cohort; B In the weighted cohort.
Crude model: we did not adjust for other covariates.
Model I: we adjusted for age, gender, BMI, waist circumference, smoking status, alcohol consumption, regular exerciser, SBP, DBP.
Model II: we adjusted for age, gender, BMI, waist circumference, smoking status, alcohol consumption, regular exerciser, SBP, DBP, ALT, AST, GGT, HbA1c, FPG, TC, TG, HDL-C.
HR, Hazard ratios; CI, Confidence interval; Ref, Reference