Baseline characteristics of participants
Table 1 shows the demographic and clinical characteristics of the study participants. In the present study, 202,320 individuals were included. The mean age was 41.57 ± 12.36 years old. 109,410 (54.08%) individuals were men, and 92,910 (45.92%) individuals were women. A total of 202,320 individuals developed prediabetes after a follow-up period of an average of 3.12 years. PP divided into four groups based on quartiles: Q1 ≤ 36 mmHg; 37 < Q2 ≤ 42 mmHg; 43 < Q3 ≤ 50 mmHg; Q4 > 51 mmHg. As shown in Table 1, compared to Q1, the Q4 group had higher levels of age, systolic blood pressure (SBP), diastolic blood pressure (DBP), BMI, AST, ALT, TG, LDL-C, TC, BUN, Scr. Additionally, the Q4 group had a higher proportion of males, smokers, drinkers, and individuals with a family history of diabetes. In comparison to Q4, the Q1 group had higher levels of HDL-C.
Table 1
The baseline characteristics of participants.
PP (quartile) (mmHg)
|
Q1 (≤ 36)
|
Q2 (37–42)
|
Q3 (43–50)
|
Q4 (≥ 51)
|
P-value
|
participants
|
49325
|
45002
|
54047
|
53946
|
|
Age (years)
|
40.16 ± 10.13
|
40.33 ± 10.49
|
40.70 ± 11.54
|
44.78 ± 15.49
|
< 0.001
|
Height (cm)
|
165.54 ± 7.99
|
166.10 ± 8.15
|
166.99 ± 8.27
|
166.92 ± 8.74
|
< 0.001
|
Weight (kg)
|
61.54 ± 11.55
|
63.24 ± 11.75
|
65.14 ± 11.93
|
67.06 ± 12.37
|
< 0.001
|
BMI (kg/m2)
|
22.34 ± 3.15
|
22.81 ± 3.17
|
23.25 ± 3.22
|
23.96 ± 3.38
|
< 0.001
|
SBP (mmHg)
|
105.24 ± 10.87
|
112.31 ± 10.65
|
119.93 ± 10.80
|
134.38 ± 14.21
|
< 0.001
|
DBP (mmHg)
|
73.92 ± 10.77
|
72.75 ± 10.49
|
73.61 ± 10.46
|
75.09 ± 10.90
|
< 0.001
|
TC (mmol/L)
|
4.63 ± 0.86
|
4.65 ± 0.87
|
4.68 ± 0.89
|
4.78 ± 0.94
|
< 0.001
|
TG (mmol/L)
|
1.20 ± 0.91
|
1.25 ± 0.93
|
1.32 ± 0.99
|
1.43 ± 1.06
|
< 0.001
|
HDL-c (mmol/L)
|
1.39 ± 0.31
|
1.38 ± 0.31
|
1.37 ± 0.30
|
1.36 ± 0.30
|
< 0.001
|
LDL-c (mmol/L)
|
2.72 ± 0.66
|
2.73 ± 0.67
|
2.76 ± 0.67
|
2.83 ± 0.70
|
< 0.001
|
ALT (U/L)
|
16 (11.8, 24.1)
|
17 (12.0, 26.0)
|
18.2 (13.0–28.0)
|
19.7 (14.0-29.2)
|
< 0.001
|
AST (U/L)
|
21 (18.0, 25.0)
|
21.2 (18.0, 26.0)
|
22 (18.5, 26.4)
|
23 (19.0, 27.8)
|
< 0.001
|
BUN (mmol/L)
|
4.52 ± 1.15
|
4.57 ± 1.15
|
4.65 ± 1.17
|
4.79 ± 1.22
|
< 0.001
|
Scr (µmol/L)
|
67.50 ± 14.98
|
68.78 ± 15.18
|
70.63 ± 15.16
|
72.43 ± 17.12
|
< 0.001
|
Sex
|
|
|
|
|
< 0.001
|
Male
|
21633 (43.84%)
|
22180 (49.29%)
|
31329 (57.97%)
|
34278 (63.54%)
|
< 0.001
|
Female
|
27712 (56.16%)
|
22822 (50.71%)
|
22718 (42.03%)
|
19668 (36.46%)
|
|
Smoking status
|
|
|
|
|
< 0.001
|
Current smoker
|
2581 (18.38%)
|
2414 (19.32%)
|
3113 (20.16%)
|
3025 (19.95%)
|
|
Ever smoker
|
496 (3.53%)
|
484 (3.87%)
|
727 (4.71%)
|
685 (4.52%)
|
|
Never
|
10964 (78.09%)
|
9598 (76.81%)
|
11603 (75.13%)
|
11452 (75.53%)
|
|
Drinking status
|
|
|
|
|
< 0.001
|
Current drinker
|
216 (1.54%)
|
290 (2.32%)
|
332 (2.15%)
|
373 (2.46%)
|
|
Ever drinker
|
1770 (12.61%)
|
1788 (14.31%)
|
2501 (16.20%)
|
2394 (15.79%)
|
|
Never
|
12055 (85.86%)
|
10418 (83.37%)
|
12610 (81.66%)
|
12395 (81.75%)
|
|
Family history of diabetes
|
|
|
|
|
< 0.001
|
No
|
48164 (97.61%)
|
44052 (97.89%)
|
52986 (98.04%)
|
53104 (98.44%)
|
|
Yes
|
1181 (2.39%)
|
950 (2.11%)
|
1061 (1.96%)
|
843 (1.56%)
|
|
Continuous variables were summarized as mean (SD) or medians (quartile interval); categorical variables were displayed as percentage (%)
Abbreviations: BMI, body mass index; SBP, systolic blood pressure; DBP; diastolic blood pressure; TC, total cholesterol; TG triglyceride; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; AST aspartate aminotransferase; ALT, alanine aminotransferase; BUN, blood urea nitrogen; Scr, serum creatinine.
The incidence rate of prediabetes
Among the study population, a total of 6,392 individuals developed prediabetes, with an incidence rate of 3.16% (95% CI: 3.08, 3.24). The cumulative reversal rates in each quartile (Q1-Q4) were as follows: Q1: 2.14%, Q2: 2.45%, Q3: 2.78% and Q4: 5.06% (Figure 2). Compared to individuals in the lower Q1 quartile, those in the Q4 quartile had a significantly lower reversal rate (p<0.001, trend test) (Figure 2). The incidence rates for Q1-Q4 were as follows: 2.14% (2.01-2.27), 2.45% (2.31-2.60), 2.78% (2.64-2.92), and 5.06% (4.88-5.25) (Table 2). Additionally, the overall incidence rate of prediabetes was 62.462 per 10,000 person-years. The incidence rates for Q1-Q4 were 67.204, 78.141, 89.628, and 164.530 per 10,000 person-years, respectively.
As depicted in Figure 3, the Kaplan-Meier curves demonstrate the survival probability of not progressing to prediabetes. There is a significant variation in the risk of developing prediabetes among the four PP groups (P < 0.0001). With an increase in PP levels, the probability of not developing prediabetes gradually declines. This indicates that the group with the highest PP exhibits the highest risk of progressing to prediabetes.
Table 2
The Incidence rate of prediabetes (% or Per 10000 person-year).
PP (quartile)
|
Participants (n)
|
prediabetes
events (n)
|
Cumulative inci-
dence (95%CI) (%)
|
Per 10000 person-year
|
Total
|
202320
|
6392
|
3.16 (3.08–3.24)
|
62.462
|
Q1
|
49325
|
1057
|
2.14 (2.01–2.27)
|
67.204
|
Q2
|
45002
|
1104
|
2.45 (2.31–2.60)
|
78.141
|
Q3
|
54047
|
1501
|
2.78 (2.64–2.92)
|
89.628
|
Q4
|
53946
|
2730
|
5.06 (4.88–5.25)
|
164.530
|
P for trend
|
|
|
|
< 0.001
|
Univariate analysis
As shown in Table 3, age, BMI, TC, TG, AST, ALT, LDL-C, BUN, Scr, and PP were positively associated with the risk of prediabetes. Conversely, HDL-C showed a negative association with the risk of prediabetes. Furthermore, women exhibited a lower risk of developing prediabetes compared to men. Additionally, individuals who abstained from alcohol and tobacco had a reduced risk of developing prediabetes.
Table 3
Risk of prediabetes analyzed by univariate Cox proportional hazards regression.
Variable
|
Characteristics
|
HR (95% CI)
|
P-value
|
Age (years)
|
41.57 ± 12.36
|
1.05 (1.05, 1.06)
|
< 0.0001
|
Sex
|
|
|
|
Male
|
109411 (54.08%)
|
Ref
|
< 0.0001
|
Female
|
92910 (45.92%)
|
0.60 (0.57, 0.63)
|
< 0.0001
|
BMI (kg/m2)
|
23.12 ± 3.29
|
1.19 (1.18, 1.20)
|
< 0.0001
|
TC (mmol/L)
|
4.69 ± 0.89
|
1.38 (1.34, 1.41)
|
< 0.0001
|
TG (mmol/L)
|
1.31 ± 0.98
|
1.24 (1.23, 1.26)
|
< 0.0001
|
HDL-c(mmol/L)
|
1.38 ± 0.31
|
0.81 (0.74, 0.90)
|
< 0.0001
|
LDL-c(mmol/L)
|
2.76 ± 0.68
|
1.39 (1.33, 1.45)
|
< 0.0001
|
ALT (U/L)
|
23.56 ± 21.82
|
1.00 (1.00, 1.00)
|
< 0.0001
|
AST (U/L)
|
23.89 ± 12.32
|
1.01 (1.00, 1.01)
|
< 0.0001
|
BUN (mmol/L)
|
4.64 ± 1.18
|
1.23 (1.21, 1.26)
|
< 0.0001
|
Scr (mmol/L)
|
69.93 ± 15.78
|
1.01 (1.01, 1.01)
|
< 0.0001
|
Smoking status
|
|
|
|
Current smoker
|
11132 (5.50%)
|
1.0
|
|
Ever smoker
|
2392 (1.18%)
|
0.66 (0.52, 0.83)
|
0.0005
|
Never
|
43615 (21.56%)
|
0.56 (0.50, 0.62)
|
< 0.0001
|
Drinking status
|
|
|
|
Current drinker
|
1211 (0.60%)
|
1.0
|
|
Ever drinker
|
8453 (4.18%)
|
0.47 (0.36, 0.60)
|
< 0.0001
|
Never
|
47475 (23.47%)
|
0.43 (0.34, 0.55)
|
< 0.0001
|
Family history of diabetes
|
|
|
|
No
|
198287 (98.01%)
|
1.0
|
|
Yes
|
4034 (1.99%)
|
1.03 (0.88, 1.21)
|
0.6852
|
PP (mmHg)
|
44.62 ± 11.48
|
1.04 (1.03, 1.04)
|
< 0.0001
|
The relationship between PP and prediabetes
As shown in Table 4, in the unadjusted model, the HR (95% CI) for the association between PP and prediabetes was 1.42 (1.39, 1.44). In the minimally-adjusted model, after adjusting for gender and age, the HR (95% CI) was 1.19 (1.16, 1.21). In the fully-adjusted model, after further adjusting for gender, age, BMI, TG, LDL-C, HDL-C, AST, ALT, BUN, Scr, family history of diabetes, drinking status, and smoking status, the HR (95% CI) was 1.15 (1.11, 1.18). This indicates that for every 10-mmHg increase in PP, the risk of prediabetes increases by 15%. Additionally, when we categorized PP into four groups, in the fully-adjusted model, the risk of developing prediabetes in Q4 was 1.64 times higher than in Q1 (HR (95% CI): 1.64 (1.44, 1.87).
Table 4
Relationship between PP and risk of prediabetes in different models
Exposure
|
Crude model (HR,95%CI) P
|
Model I(HR,95%CI) P
|
Model II(HR,95%CI) P
|
Model III(HR,95%CI) P
|
PP (10 mmHg)
|
1.42 (1.39, 1.44) < 0.0001
|
1.19 (1.16, 1.21) < 0.0001
|
1.15 (1.11, 1.18) < 0.0001
|
1.19 (1.15, 1.23) < 0.0001
|
PP (quartile)
|
|
|
|
|
Q1
|
Ref
|
Ref
|
Ref
|
Ref
|
Q2
|
1.21 (1.11, 1.32) < 0.0001
|
1.17 (1.08, 1.27) 0.0002
|
1.02 (0.88, 1.19) 0.7549
|
1.03 (0.89, 1.20) 0.6699
|
Q3
|
1.44 (1.33, 1.56) < 0.0001
|
1.32 (1.22, 1.42) < 0.0001
|
1.15 (1.00, 1.32) 0.0576
|
1.17 (1.01, 1.35) 0.0315
|
Q4
|
2.70 (2.52, 2.90) < 0.0001
|
1.85 (1.72, 1.99) < 0.0001
|
1.64 (1.44, 1.87) < 0.0001
|
1.73 (1.52, 1.97) < 0.0001
|
P for trend
|
< 0.0001
|
< 0.0001
|
< 0.0001
|
<0.0001
|
Crude model: we did not adjust other covariates.
Model I: we adjusted age, sex.
Model II: we adjusted age, sex, BMI, ALT, AST, BUN, Scr, TG, LDL-c, HDL-c, family history of diabetes, drinking status, and smoking status.
Model III: we adjusted age(smooth), sex, BMI (smooth), Scr(smooth), TG (smooth), ALT (smooth), AST (smooth), LDL-c(smooth), HDL-c(smooth), smoking status, drinking status, family history of diabetes. HR, Hazard ratios; CI, confidence, Ref, reference.
The results of sensitivity analysis
We conducted a series of sensitivity analyses to ensure the reliability of our research findings (Table 4 and table 5). Firstly, we used a Generalised Additive Model (GAM) to incorporate a continuous covariate as a curve into the equation. The results from Model III, as shown in Table 4, were consistent with those from the fully adjusted model (HR 95% CI: 1.19 (1.15-1.23), p<0.001). Additionally, we performed sensitivity analyses on participants with a BMI below 28. After adjusting for potential confounding variables (including age, sex, BMI, HDL-c, TG, LDL-c, BUN, Scr, ALT, AST, family history of diabetes, smoking and drinking status), the results indicated a positive association between PP and the risk of prediabetes (HR 95% CI: 1.19 (1.15-1.23), p<0.001). We also excluded participants aged 60 years or older for further sensitivity analysis. After adjusting for confounding variables, the results still showed a positive correlation between PP and the incidence of prediabetes (HR 95% CI: 1.28(1.23-1.34), p<0.001). Moreover, when excluding participants without a family history of diabetes and adjusting for relevant variables, the results demonstrated a positive association between PP and the risk of prediabetes (HR 95% CI: 1.15 (1.11-1.18), p<0.001) (Table 5).
Table 5
Relationship between PP and the risk of prediabetes in different sensitivity analyses.
Exposure
|
Crude model I (HR,95%CI) P
|
Model II(HR,95%CI) P
|
Model III(HR,95%CI) P
|
PP (10 mmHg)
|
1.19 (1.15, 1.23) < 0.0001
|
1.28 (1.23, 1.34) < 0.0001
|
1.15 (1.11, 1.18) < 0.0001
|
PP (quartile)
|
|
|
|
Q1
|
Ref
|
Ref
|
Ref
|
Q2
|
1.10 (0.94, 1.30) 0.2440
|
0.98 (0.83, 1.17) 0.0002
|
1.02 (0.88, 1.19) 0.7549
|
Q3
|
1.22(1.05, 1.43) 0.0101
|
1.12 (0.95, 1.31) 0.1725
|
1.15 (1.00, 1.32) 0.0583
|
Q4
|
1.94 (1.69, 2.24) < 0.0001
|
1.86 (1.61, 2.16) < 0.0001
|
1.64 (1.44, 1.87) < 0.0001
|
P for trend
|
< 0.0001
|
< 0.0001
|
< 0.0001
|
Crude model I was a sensitivity analysis performed after excluding participants with BMI≥28 mmol/L (N= 15967). we adjusted age, sex, ALT, AST, BUN, Scr, TG, LDL-c, HDL-c, family history of diabetes, drinking status, and smoking status.
Model II was a sensitivity analysis performed after excluding participants with age≥60 mmol/L (N= 21599). we adjusted sex, BMI, ALT, AST, BUN, Scr, TG, LDL-c, HDL-c, family history of diabetes, drinking status, and smoking status.
Model III was a sensitivity analysis performed on participants without family of diabetes. We adjusted age, sex, BMI, ALT, AST, BUN, Scr, TG, LDL-c, HDL-c, smoking status and drinking status. HR, Hazard ratios; CI, confidence, Ref, referenc.
The non-linear relationship between PP and prediabetes
We utilized a Cox proportional hazards regression model with cubic spline functions and found a non-linear correlation between PP and the probability of developing prediabetes (Figure 4). To better fit the data, we employed a standard binary two-piecewise Cox proportional hazards regression model and selected the best model using the log-likelihood ratio test (Table 6). The p-value for the log-likelihood ratio test was less than 0.05. Using a recursive technique, we identified 40mmHg as the inflection point for PP. After the inflection point, the hazard ratio (HR) for PP and the risk of developing prediabetes was 1.17 (95% CI: 1.13, 1.22, P<0.0001). However, before the inflection point, the HR for PP and the risk of developing prediabetes was 1.01 (95% CI: 0.89, 1.15, P=0.8916), which was not statistically significant.
Table 6
The result of the two-piecewise Cox proportional hazards regression model
Outcome: prediabetes
|
HR, 95%CI P
|
value
|
Fitting model by standard Cox regression
|
1.15 (1.11, 1.18)
|
<0.0001
|
Fitting model by two-piecewise Cox regression
|
|
|
Inflection points of PP (mmHg)
|
40
|
40
|
<40 mmHg
|
1.01 (0.89, 1.15)
|
0.8916
|
≥40 mmHg
|
1.17 (1.13, 1.22)
|
<0.0001
|
P for log-likelihood ratio test
|
|
0.047
|
Subgroup analysis
We conducted subgroup analysis to investigate potential additional risk factors that could influence the relationship between PP and prediabetes risk. We examined the impact of BMI, age, gender, smoking status, drinking status, and family history of diabetes as stratification factors. However, our analysis revealed that drinking status, smoking status, family history of diabetes had no significant impact on the association between PP and prediabetes risk. Additionally, there was a stronger connection between PP and risk of prediabetes in individual with age<60 years, BMI<24, and females (Table 7).
Table 7
Stratified associations between PP and risk of prediabetes by age, sex, smoking status, and drinking status.
Variable
|
|
HR (95% CI)
|
P-value
|
Age(years)
|
|
|
|
<60
|
180722
|
1.27(1.21, 1.33)
|
< 0.0001
|
≥60
|
21599
|
1.17 (1.12, 1.22)
|
< 0.0001
|
BMI
|
|
|
|
<24
|
125936
|
1.20(1.14, 1.26)
|
< 0.0001
|
24–28
|
60418
|
1.17 (1.09, 1.20)
|
< 0.0001
|
≥ 28
|
15967
|
1.06(0.98, 1.14)
|
0.1738
|
Sex
|
|
|
|
Male
|
109411
|
1.11(1.07, 1.16)
|
< 0.0001
|
female
|
92910
|
1.19 (1.13, 1.25)
|
< 0.0001
|
Drinking status
|
|
|
|
Current drinker
|
1211
|
1.17(0.72, 1.89)
|
0.5209
|
Ever drinker
|
8452
|
1.05 (0.86, 1.28)
|
0.6598
|
Never
|
47475
|
1.10(0.99, 1.21)
|
0.0726
|
Smoking status
|
|
|
|
Current smoker
|
11132
|
1.05(0.89, 1.24)
|
0.5346
|
Ever smoker
|
2392
|
1.32(0.85, 2.05)
|
0.2197
|
Never
|
43615
|
1.08 (0.97, 1.20)
|
0.1804
|
Family history of diabetes
|
|
|
|
Yes
|
198287
|
1.15(1.11, 1.18)
|
< 0.0001
|
No
|
4034
|
1.26(0.96, 1.64)
|
0.0912
|