The relationship between dietary inflammatory index (DII) and early renal injury in population with/without hypertension: analysis of the National health and nutrition examination survey 2001–2002

Figures & data

Figure 1. Flow chart of the screening process for the selection of eligible participants.

Table 1. Characteristics of participants aged 20 years and older from the NHANES (2001-2002).

Characteristics	Overall (N = 2108)	Anti-inflammatory diet (N = 404)	Pro-inflammatory diet (N = 1704)	p-value
Age, mean (SD)	53.90(0.69)	52.80(1.24)	54.18(0.60)	0.16
Gender, n (%)				<0.0001
Male	1044(49.53)	251(26.52)	793(73.48)
Female	1064(50.47)	153(14.09)	911(85.91)
Race, n (%)				0.3
Non-Hispanic White	1228(58.25)	253(21.03)	975(78.97)
Mexican American	398(18.88)	75(21.32)	323(78.68)
Non-Hispanic Black	360(17.08)	52(14.55)	308(85.45)
Other Hispanic	65(3.08)	9(13.57)	56(86.43)
Other Race	57(2.7)	15(19.91)	42(80.09)
Education astatus, n (%)				<0.0001
Less Than 9th Grade	361(17.13)	42(11.61)	319(88.39)
9-11th Grade	332(15.75)	44(12.64)	288(87.36)
High School Grad/GED	515(24.43)	96(18.20)	419(81.80)
Some College or AA degree	494(23.43)	97(18.41)	397(81.59)
College Graduate or above	406(19.26)	125(30.84)	281(69.16)
BMI, mean (SD)	28.20(0.28)	27.28(0.38)	28.43(0.30)	0.02
PIR, mean (SD)	2.98(0.07)	3.49(0.08)	2.85(0.07)	<0.0001
Smoking status, n (%)				0.08
Never Smoker	1027(48.72)	208(21.70)	819(78.30)
Former Smoker	721(34.2)	146(20.67)	575(79.33)
Current Smoker	360(17.08)	50(14.82)	310(85.18)
Alcohol consumption, n (%)				0.02
Non-drinker	743(35.25)	110(15.72)	633(84.28)
Drinker	1365(64.75)	294(22.09)	1071(77.91)
Diabetes, n (%)				0.74
Non-diabetes	1725(81.83)	338(20.18)	1387(79.82)
Diabetes	383(18.17)	66(19.19)	317(80.81)
Hypertension, n (%)				0.13
Non-hypertension	851(40.37)	185(21.63)	666(78.37)
Hypertension	1257(59.63)	219(18.68)	1038(81.32)
DII, mean (SD)	1.54(0.07)	−1.18(0.07)	2.23(0.05)	<0.0001
UACR, mean (SD)	51.78(8.04)	34.73(19.80)	56.06(6.59)	0.24
B2M, mean (SD)	2.34(0.04)	2.13(0.05)	2.39(0.04)	<0.001
CysC, mean (SD)	0.88(0.01)	0.83(0.02)	0.89(0.01)	0.01
eGFRs, mean (SD)	85.08(0.95)	87.00(1.48)	84.60(0.94)	0.08
eGFRc, mean (SD)	86.57(1.27)	91.97(1.76)	85.22(1.23)	<0.001
eGFRs&c, mean (SD)	85.93(1.00)	89.88(1.46)	84.94(0.98)	0.001

Normally distributed continuous variables were displayed as means and standard deviations (SDs), categorical variables were displayed as proportions. Analysis of Variance (ANOVA) was used for the comparison of Continuous variables and Pearson’s χ2 test were used for comparison of categorical variables. The mobile examination center sample weights were accounted and the results represented the US civilian resident population. eGFRs: eGFR based on Scr; eGFRc: eGFR based on CysC; eGFRs&c: eGFR based on Scr and CysC.

Table 2. The linear relationship between DII and early renal injury indicators among participants aged 20 years and older from the NHANES (2001–2002).

I9ndicator	β (95% CI), p-value
	Model 1		Model 2		Model 3
UACR	0.094(0.058,0.129)	<0.0001	0.049(−0.003, 0.100)	0.058	0.048(0.017, 0.078)	0.004
B2M	0.028(0.017,0.038)	<0.0001	0.02(0.007, 0.034)	0.018	0.019(0.010, 0.027)	<0.001
CysC	0.018(0.010,0.027)	<0.001	0.014(0.002, 0.027)	0.035	0.012(0.004, 0.021)	0.006
eGFRc	−2.063(−2.725, −1.400)	<0.0001	−1.348(−2.000, −0.696)	0.007	−1.126(−1.554, −0.699)	<0.0001
eGFRs&c	−1.468(−2.123, −0.813)	<0.001	−1.208(−2.028, −0.388)	0.018	−1.101(–1.653,-0.549)	<0.001

Model 1 was unadjusted, Model 2 was adjusted for covariates including gender, age, race, education level, and poverty index, and Model 3 added hypertension, diabetes, smoking, and drinking as covariates on the basis of Model 2. Sampling weights were considered in linear regression analyses to obtain nationally representative estimates. UACR: urinary albumin to creatinine; B2M: β-2 microglobulin; CysC: cystatin C; eGFRc: eGFR based on CysC; eGFRs&c: eGFR based on Scr and CysC; OR: odds ratio; CI: Confidence interval.

Table 3. The logistic regression model between DII and the abnormality of early renal injury indicators among participants aged 20 years and older from the NHANES (2001–2002).

Indicator	OR (95% CI), p-value
	Model 1		Model 2		Model 3
UACR	1.161(1.059,1.272)	0.004	1.087(0.945, 1.250)	0.156	1.080(0.990,1.179)	0.08
B2M	1.252(1.165,1.345)	<0.0001	1.226(1.089,1.379)	0.012	1.206(1.114,1.307)	<0.001
CysC	1.231(1.133,1.338)	<0.001	1.224(1.072,1.398)	0.017	1.203(1.100,1.316)	<0.001
eGFRc	1.250(1.174,1.332)	<0.0001	1.210(1.052,1.393)	0.023	1.186(1.063,1.323)	0.005
eGFRs&c	1.256(1.153,1.369)	<0.0001	1.222(1.042,1.432)	0.028	1.204(1.082,1.339)	0.002

Model 1 was unadjusted, Model 2 was adjusted for covariates including gender, age, race, education level, and poverty index, and Model 3 added hypertension, diabetes, smoking, and drinking as covariates on the basis of Model 2. Sampling weights were considered in logistic regression analyses to obtain nationally representative estimates. UACR: urinary albumin to creatinine; B2M: β-2 microglobulin; CysC: cystatin C; eGFRc: eGFR based on CysC; eGFRs&c: eGFR based on Scr and CysC; OR: odds ratio; CI: Confidence interval.

Table 4. The logistic regression model between hypertension status and the abnormality of early renal injury indicators among participants aged 20 years and older from the NHANES (2001–2002).

Indicator	OR (95% CI)	p-value
UACR	1.525 (0.871,2.672)	0.129
B2M	1.560 (1.182,2.061)	0.004
CysC	1.408 (1.061,1.868)	0.021
eGFRs	1.321 (0.994,1.755)	0.054
eGFRc	1.875 (1.339,2.626)	0.001
eGFRs&c	1.691 (1.106,2.586)	0.019

Model was adjusted for covariates including gender, age, race, education level, poverty index, hypertension, diabetes, smoking, and drinking. Sampling weights were considered in logistic regression analyses to obtain nationally representative estimates.

Figure 2. The relationship between DII and abnormality of early renal injury indicators differed by hypertension status among participants aged 20 years and older from the NHANES (2001–2002). Model was adjusted for covariates including gender, age, race, education level, poverty index, hypertension, diabetes, smoking, and drinking. Sampling weights were considered in logistic regression analyses to obtain nationally representative estimates.

Data availability statement

All data can be downloaded from the NHANES website (https://www.cdc.gov/nchs/nhanes/about_nhanes.htm).