Endocrine DOI 10.1007/s12020-014-0411-y
ORIGINAL ARTICLE
Relationship between dyslipidemia and albuminuria in prediabetic adults: The Korea National Health and Nutrition Examination Survey 2011–2012 Ga Eun Nam • Kyungdo Han • Do Hoon Kim • Yong Gyu Park • Yeo Joon Yoon • Young Eun Kim Sangsu Lee • Sungho Lee • Yong Kyun Roh
•
Received: 9 July 2014 / Accepted: 27 August 2014 Ó Springer Science+Business Media New York 2014
Abstract This study aimed to estimate the relationship between various lipid abnormalities and albuminuria in Korean prediabetic adults. Data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) 2011–2012 were analyzed. The study consisted of 4,811 subjects in the normal glucose group and 3,872 in the prediabetic group. Prediabetes was defined by the fasting plasma glucose or hemoglobin A1c level. Albuminuria was defined as a urine albumin to creatinine ratio (UACR) C30 mg/g. Various parameters of dyslipidemia were assessed. No differences were observed in the prevalence of lipid abnormalities in prediabetic men with different values of UACR. Prediabetic women with increased urinary albumin excretion showed a significantly higher prevalence of lipid abnormalities. The proportion of mixed dyslipidemia was significantly higher in prediabetic women with albuminuria. Higher levels of total cholesterol, triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (nonHDL-C), and TC to HDL-C ratio, TG to HDL-C ratio, and
G. E. Nam D. H. Kim Y. J. Yoon Y. E. Kim S. Lee S. Lee Department of Family Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan-Si, Republic of Korea K. Han Y. G. Park Department of Biostatistics, Catholic University College of Medicine, Seoul, Republic of Korea Y. K. Roh (&) Department of Family Medicine, Kangnam Sacred Heart Hospital, College of Medicine, Hallym University, 948-1 Daelim-dong, Youngdungpo-Gu, Seoul 150-071, Republic of Korea e-mail: [email protected]
LDL-C to HDL-C ratio were significantly associated with increased risk of albuminuria in prediabetic women. Conclusions: Several lipid abnormalities were significantly associated with the increased risk of albuminuria in prediabetic women. Hence, screening for lipid abnormalities may be helpful for identification of risk for albuminuria in prediabetic subjects. Keywords Prediabetes Albuminuria Dyslipidemia Urine albumin to creatinine ratio
Introduction Dyslipidemia is a major preventable risk factor for cardiovascular disease (CVD) that is highly prevalent in the general population, and the rate escalates in patients with renal insufficiency [1, 2]. It has generally been defined by elevated levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), or low levels of high-density lipoprotein cholesterol (HDL-C) [3]. Recently, non-HDL-C levels and lipid-related ratios have been noted to be more predictive for CVD, than the individual lipid profile [4, 5]. Prediabetes, which is defined by fasting plasma glucose (FPG), the oral glucose tolerance test results, or hemoglobin A1c (HbA1c) level is a high-risk factor for the development of diabetes and is associated with increased cardiovascular risk [6]. The prevalence of prediabetes in South Korea and worldwide has dramatically increased with increasing rates of diabetes. The largest surge is expected to occur in developing countries including South Korea [7, 8]. Although there were ethnic differences, prediabetic status was shown to be associated with target organ damage including albuminuria [9]. Moreover,
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albuminuria might predict progression of prediabetes to diabetes [10]. The presence of albuminuria is an early marker for the progression of diabetic nephropathy, and is strongly related to future CVD morbidity and mortality in both diabetic and non-diabetic subjects [11]. Mounting evidence has revealed that dyslipidemia plays a significant role in the development of albuminuria in diabetic patients [12]. A few interventional studies have demonstrated the possible positive effect of lipid-lowering agents on the improvement of albuminuria in these patients [13]. However, in prediabetic subjects, the relationship between dyslipidemia and albuminuria has not been sufficiently investigated yet. Therefore, the purpose of this study was to estimate the relationship between various parameters of dyslipidemia and albuminuria in Korean prediabetic adults using nationally representative data.
Materials and methods Survey overview and study subjects This study was based on the data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) 2011–2012, which has been conducted by the Division of Chronic Disease Surveillance at the Korean Center for Disease Control and Prevention (KCDC) since 1998. The survey was designed to evaluate nationwide health and nutrition status, and comprised a health interview, a nutritional assessment, and a health examination. A stratified, multistage, and cluster-sampling design with proportional allocation based on geographic areas, sex, and age from the National Census Registry was used for the selection of survey subjects to represent the entire non-institutionalized civilian population in South Korea. Of 16,576 participants chosen based on the health interview and health examination, 7,893 individuals were excluded on the following grounds: \19 years of age, missing data, cancer, menstruation, pregnancy, fasting period less than 8 h, estimated glomerular filtration rate (eGFR) \60 mL/min/1.73 m2, or diabetes mellitus (DM). DM was defined by an FPG level C126 mg/dL, treatment with insulin or oral hypoglycemic agents, or diagnosis by a physician. Prediabetes was defined by FPG levels ranging from 100–125 mg/dL or HbA1c levels ranging from 5.7–6.4 % (39–46 mmol/mol) [6]. Of 8,683 non-diabetic subjects, 4,811 were included in the normal glucose group, while 3,872 were grouped in the prediabetic group. All the participants provided written informed consent, and the Institutional Review Board of the KCDC approved the study protocol.
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Lifestyle variables Alcohol consumption, smoking status, and physical activity were investigated in the self-reported questionnaire. Based on the amount of alcohol consumed per day up to 1 month before the interview, subjects who had consumed C30 g/day of alcohol were classified as heavy drinkers [14]. Subjects were classified as current smokers or non-smokers. Physical activity was assessed by using the International Physical Activity Questionnaire short form modified for the Korean population [15]. Subjects who exercised moderately for over 30 min per session more than 5 times per week, or those who exercised vigorously for over 20 min per session more than 3 times per week were defined as regular physical exercisers. Anthropometric measurements Height and body weight were measured to the nearest 0.1 cm, and 0.1 kg, respectively. Body mass index (BMI) was calculated using the formula: body weight (kg)/height2 (m2). Waist circumference (WC) was measured at the midpoint between the lower costal margin and the iliac crest during expiration. Blood pressure (BP) was measured in the sitting position using a standard mercury sphygmomanometer (Baumanometer, WA Baum Co., New York, USA) three times in 5-min intervals. The average of the second and third measurements was used in the analyses. Hypertension was defined as systolic BP C140 mmHg or diastolic BP C90 mmHg, or treatment with anti-hypertensive agents. Biochemical measurements and definitions Blood samples were obtained in the morning following a fasting period lasting 8 h or more, and single-spot, midstream urine samples were collected in the first morning void. The samples were properly processed, immediately refrigerated, and transported via cold storage units to the Central Testing Institute in Seoul, Korea, and analyzed within 24 h. HbA1c level was measured using an HLC723G7 (Tosoh, Japan) by high performance liquid chromatography. Serum FPG, TC, TG, and HDL-C levels were measured using a Hitachi automatic analyzer 7600 (Hitachi, Tokyo, Japan) by enzymatic methods. LDL-C level was calculated using Friedewald’s formula [16] in subjects with TG \400 mg/dL, or measured directly using a commercially available kit (CholestestÒ LDL; Sekisui, Medical, Tokyo, Japan) in subjects with TG C400 mg/dL. NonHDL-C level was calculated as TC level minus HDL-C level. Conventional parameters of dyslipidemia were defined according to the criteria of the National Cholesterol Education Program Adult Treatment Panel III [3]:
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hypercholesterolemia, TC level C240 mg/dL or the use of lipid-lowering drugs; hypo-HDL-cholesterolemia, HDL-C level \40 mg/dL; hyper-LDL-cholesterolemia, LDL-C level C160 mg/dL; hypertriglyceridemia, TG level C200 mg/dL. Additionally, we defined hyper-non-HDLcholesterolemia (non-HDL-C C160 mg/dL), high TC to HDL-C ratio (TC/HDL-C [5), high TG to HDL-C ratio (TG/HDL-C[3.8) and high LDL-C to HDL-C ratio (LDLC/HDL-C[2) as lipid abnormalities [4, 17–19]. Serum and urine creatinine levels were measured using a Hitachi automatic analyzer 7600 by kinetic colorimetry. Urine albumin level was measured using the same equipment by means of a turbidimetric assay. Albuminuria is defined as a urine albumin to creatinine ratio (UACR) C30 mg/g [20]. We calculated the eGFR using the formula referred to in the Modification of Diet in Renal Disease study [21]. Statistical analysis Statistical analysis was performed by using the SAS survey procedure (version 9.2; SAS Institute, Cary, North Carolina, USA) in a manner reflecting sampling weights and providing nationally representative estimates. P values \ 0.05 were considered to be statistically significant. Independent t-test or v2 test was performed for the assessment of differences in clinical and biochemical characteristics between normal glucose, and prediabetic groups. Age- and multivariateadjusted logistic regression analyses were conducted to evaluate the relationship of dyslipidemia parameters with albuminuria, and odds ratios (ORs) and confidence intervals (CIs) were estimated. Age, BMI, alcohol consumption, smoking status, physical activity, hypertension, and menopause in women were considered to be confounding factors in multivariate analyses.
Results The baseline characteristics of the subjects are presented in Table 1. Prediabetic subjects among both men and women were significantly older, and displayed higher values of BMI, WC, SBP, DBP, FPG, HbA1c, and UACR than those with normal glucose levels. The mean values of UACR for normal glucose and prediabetic subjects were 3.52 mg/g and 4.36 mg/g for men, and 4.45 mg/g and 5.94 mg/g for women, respectively. All the parameters for dyslipidemia, with the exception of HDL-C were observed to be significantly higher, while HDL-C levels were lower in prediabetic subjects compared to subjects with a normal glucose level in both sexes. The rates of hypertensives and lipidlowering medication use were also higher among prediabetic subjects in both sexes. In men, lifestyle factors such as a higher prevalence of heavy alcohol consumption or
smoking were found to be associated with prediabetic subjects, than those with normal glucose levels. There were no differences in the level of physical activity as defined by glucose levels in either sex. Table 2 shows means of metabolic variables according to urinary albumin excretion in the normal glucose and prediabetic groups. In men with normal glucose levels, means of age, BMI, SBP, FPG, TG, and TG/HDL-C were significantly higher in subjects with albuminuria compared to those without albuminuria. Mean age and SBP levels were higher in subjects with albuminuria among prediabetic men. Age, WC, SBP, DBP, FPG, HbA1c, TG, TC/ HDL-C, TG/HDL-C, and LDL-C/HDL-C levels were significantly higher in subjects with albuminuria than those without albuminuria among women with normal glucose level. In prediabetic women, subjects with albuminuria had higher levels of age, BMI, WC, SBP, DBP, FPG, TC, TG, non-HDL-C, TC/HDL-C, TG/HDL-C, and LDL-C/HDL-C than those without albuminuria. Figure 1 shows the sex-specific prevalence of lipid abnormalities as defined by the UACR both in normal glucose and prediabetic groups. In men with normal glucose levels, prevalence of hypertriglyceridemia and high TG/HDL-C ratio were higher in subjects with UACR C30 mg/g, than in those with UACR \30 mg/g. However, no differences were observed in the prevalence of any of the lipid abnormalities between the UACR groups among prediabetic men. Meanwhile, a higher prevalence of hyperLDL-cholesterolemia, high ratios of TC/HDL-C, TG/HDLC, and LDL-C/HDL-C were observed in women with normal glucose and UACR C30 mg/g. Subjects with UACR C30 mg/g showed a significantly higher prevalence of hypercholesterolemia, hypertriglyceridemia, hyper-nonHDL-cholesterolemia, and high ratios of TC/HDL-C, TG/ HDL-C, and LDL-C/HDL-C than those with UACR \30 mg/g among prediabetic women. Figure 2 summarizes the proportions of subjects with albuminuria classified according to the number of conventional parameters of dyslipidemia. The proportion of occurrence of mixed dyslipidemia with two or more lipid abnormalities was significantly higher in prediabetic women with albuminuria. Table 3 shows age- and multivariate-adjusted ORs for the prevalence of albuminuria classified according to sex and glucose levels. In men, TG and TG/HDL-C ratio was associated with the risk of albuminuria only when adjusted for age in normal glucose group and TG was in prediabetic group. None of the lipid abnormalities was associated with the risk of albuminuria in women with normal glucose levels. However, in prediabetic women, increased levels of TG, non-HDL-C, TC/HDL-C ratio, and TG/HDL-C ratio, and lower levels of HDL-C were independently associated with the risk of albuminuria in age-adjusted analyses. In multivariate analyses,
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Endocrine Table 1 Baseline characteristics of subjects in normal glucose and prediabetic groups Men Normal glucose
Women Prediabetes
P value
a
Normal glucose
Prediabetes
P valuea
n
2,041
1,788
2,770
2,084
Age (years)
38.91 ± 0.38
47.58 ± 0.47
\0.001
40.62 ± 0.35
53.90 ± 0.44
\0.001
BMI (kg/m2)
23.65 ± 0.10
24.67 ± 0.11
\0.001
22.44 ± 0.09
24.33 ± 0.11
\0.001
WC (cm)
82.12 ± 0.28
86.11 ± 0.32
\0.001
75.07 ± 0.23
81.20 ± 0.31
\0.001
SBP (mmHg)
117.22 ± 0.34
121.55 ± 0.46
\0.001
110.86 ± 0.36
120.03 ± 0.54
\0.001
DBP (mmHg)
77.86 ± 0.30
80.31 ± 0.34
\0.001
72.35 ± 0.26
75.18 ± 0.30
\0.001
FPG (mg/dL) HbA1c (%)
88.96 ± 0.19 5.32 ± 0.006
99.39 ± 0.32 5.77 ± 0.008
\0.001 \0.001
87.66 ± 0.16 5.32 ± 0.005
96.73 ± 0.30 5.84 ± 0.008
\0.001 \0.001
Creatinine (mg/dL)
0.97 ± 0.003
0.96 ± 0.004
0.69
0.71 ± 0.003
0.72 ± 0.003
0.017
eGFR (mL/min/1.73 m2)
95.33 ± 0.44
91.54 ± 0.47
\0.001
100.34 ± 0.47
93.03 ± 0.53
\0.001
UACR (mg/g)b
3.52 (3.35, 3.69)
4.36 (4.12, 4.61)
\0.001
4.45 (4.23, 4.67)
5.94 (5.54, 6.37)
TC (mg/dL)
182.85 ± 1.03
196.53 ± 1.15
\0.001
183.39 ± 0.79
201.84 ± 1.09
\0.001
TG (mg/dL)b
110.80 (107.40, 114.30)
140.53 (135.56, 145.66)
\0.001
81.72 (79.68, 83.81)
112.79 (109.05, 116.66)
\0.001
\.0001
HDL-C (mg/dL)
50.40 ± 0.36
49.06 ± 0.35
57.68 ± 0.33
53.26 ± 0.35
\0.001
LDL-C (mg/dL)
107.2 ± 0.90
115.46 ± 1.00
\0.001
106.98 ± 0.64
122.53 ± 0.98
\0.001
Non-HDL-C
132.46 ± 1.03
147.47 ± 1.19
\0.001
125.71 ± 0.75
148.58 ± 1.12
\0.001
0.005
TC/HDL-C
3.79 ± 0.03
4.21 ± 0.04
\0.001
3.31 ± 0.02
3.96 ± 0.03
\0.001
TG/HDL-Cb LDL-C/HDL-C
3.42 (3.33, 3.51) 2.23 ± 0.02
4.14 (4.01, 4.27) 2.47 ± 0.03
\0.001 \0.001
2.57 (2.52, 2.62) 1.95 ± 0.02
3.33 (3.24, 3.43) 2.40 ± 0.03
\0.001 \0.001
Lipid-lowering drug use (%)
1.16 (0.22)
4.02 (0.49)
\0.001
1.52 (0.22)
7.77 (0.69)
\0.001
\0.001
\0.001
Hypertension (%)
44.47 (1.94)
55.53 (1.94)
39.05 (1.87)
60.95 (1.87)
Thyroid diseases (%)
0.83 (0.20)
0.82 (0.22)
0.982
4.89 (0.47)
5.71 (0.57)
0.282
Heavy drinker (%)
30.27 (1.34)
34.06 (1.50)
0.06
6.55 (0.65)
4.14 (0.58)
0.004
Current smoker (%)
40.49 (1.37)
45.17 (1.65)
0.038
6.25 (0.62)
4.60 (0.68)
0.096
Regular exerciser (%)
23.72 (1.18)
21.00 (1.24)
0.133
Menopause (%)
15.69 (0.87)
16.09 (1.21)
0.788
21.33 (0.93)
59.65 (1.62)
\0.001
Value represents mean ± standard error or proportion (standard error) BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FPG fasting plasma glucose, HbA1c glycated hemoglobin, eGFR estimated glomerular filtration rate, UACR urinary albumin to creatinine ratio, TC total cholesterol, TG triglyceride, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol a
Obtained by t-test or v2test
b
Log transformation was performed to obtain P values, and value represents geometric mean (95 % confidence intervals)
most of lipid parameters except HDL-C were also associated with the risk of albuminuria (OR [95 % CI]: 1.05 [1.01–1.10] for TC; 1.59 [1.14–2.20] for TG; 1.06 [1.01–1.12] for LDL-C; 1.06 [1.02–1.11] for non-HDL-C; 1.18 [1.02–1.36] for TC/ HDL-C ratio; 1.60 [1.12–2.27] for TG/HDL-C ratio; 1.24 [1.01–1.52] for LDL-C/HDL-C ratio).
Discussion The present study showed that several lipid abnormalities could be associated with elevated UAE in prediabetic subjects. The prevalence of lipid abnormalities and mixed
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dyslipidemia was high in prediabetic women with albuminuria. Several parameters of dyslipidemia were independently associated with the risk for increased UAE in prediabetic women. Among conventional parameters of dyslipidemia, higher TG and lower HDL-C levels were significant determinants for an increased risk of albuminuria. These associations were also observed between elevated levels of non-HDL-C, TC/HDL-C ratio, and albuminuria. TC/HDL-C ratio reflects the incorporation of TG-rich lipoproteins, and non-HDL-C is a marker for atherogenic particles [4, 5]. Previous studies that evaluated the association between dyslipidemia and albuminuria have reported inconsistent
Endocrine Table 2 Means of metabolic variables according to urinary albumin excretion by glucose status Normal glucose UACR \30 mg/g
UACR C30 mg/g
n
1,980
61
1,699
89
Age (years)
38.74 ± 0.38
45.48 ± 2.33
0.004
47.16 ± 0.48
57.74 ± 1.67
BMI (kg/m2)
23.59 ± 0.10
25.78 ± 0.76
0.004
24.66 ± 0.12
24.98 ± 0.50
0.555
WC (cm)
81.98 ± 0.28
87.74 ± 2.02
0.005
86.04 ± 0.33
88.00 ± 1.44
0.191
SBP (mmHg)
116.96 ± 0.35
127.53 ± 2.51
\0.001
121.18 ± 0.47
130.16 ± 2.27
\0.001
DBP (mmHg) FPG (mg/dL)
77.66 ± 0.30 88.88 ± 0.20
85.84 ± 2.06 91.95 ± 0.67
\0.001 \0.001
80.22 ± 0.35 99.31 ± 0.32
82.48 ± 1.46 101.12 ± 1.48
0.133 0.229
P valuea
Prediabetes UACR \30 mg/g
UACR C30 mg/g
P valuea
Men \0.001
HbA1c (%)
5.32 ± 0.007
5.32 ± 0.029
0.890
5.77 ± 0.008
5.79 ± 0.039
0.531
Creatinine (mg/dL)
0.97 ± 0.003
0.97 ± 0.023
0.708
0.96 ± 0.004
0.95 ± 0.019
0.321
eGFR (mL/min/1.73 m2)
95.41 ± 0.44
92.13 ± 3.12
0.294
91.59 ± 0.47
90.47 ± 2.11
0.599
UACR (mg/g)
b
3.26 (3.13, 3.39)
75.97 (59.38, 97.18)
TC (mg/dL)
182.63 ± 1.04
191.54 ± 4.62
TG (mg/dL)b
109.91 (106.54, 113.40)
152.06 (130.19, 177.61)
\0.001 0.057 \0.001
\0.001
3.87 (3.69, 4.06)
73.13 (60.98, 87.72)
196.45 ± 1.19
198.5 ± 4.68
0.674
139.76 (134.69, 145.01)
159.80 (137.17, 186.16)
0.093
HDL-C (mg/dL)
50.41 ± 0.36
49.86 ± 1.67
0.744
48.96 ± 0.36
51.38 ± 2.39
0.326
LDL-C (mg/dL)
107.14 ± 0.91
109.43 ± 4.82
0.638
115.73 ± 1.05
109.29 ± 3.83
0.113
Non-HDL-C
132.22 ± 1.03
141.68 ± 5.18
0.070
147.48 ± 1.22
147.12 ± 5.10
0.944
TC/HDL-C TG/HDL-Cb
3.79 ± 0.03 3.40 (3.31, 3.49)
4.06 ± 0.19 4.30 (3.72, 4.98)
0.167 0.002
4.21 ± 0.04 4.13 (3.99, 4.26)
4.17 ± 0.19 4.44 (3.81, 5.17)
0.834 0.358
LDL-C/HDL-C
2.22 ± 0.02
2.32 ± 0.17
0.552
2.48 ± 0.03
2.32 ± 0.13
0.231
Lipid-lowering drug use (%)
1.05 (0.21)
5.37 (3,74)
0.014
3.91 (0.50)
6.40 (2.83)
0.285
Hypertension (%)
17.75 (1.01)
49.48 (7.98)
31.86 (1.51)
68.11 (6.85)
n
2,645
125
1,907
177
Age (years)
40.19 ± 0.34
50.77 ± 2.11
\0.001
53.33 ± 0.46
60.00 ± 1.27
\0.001
BMI (kg/m2)
22.42 ± 0.09
23.06 ± 0.38
0.095
24.21 ± 0.12
25.69 ± 0.30
\0.001
WC (cm)
74.95 ± 0.23
77.76 ± 1.14
0.015
80.78 ± 0.31
85.75 ± 0.75
\0.001
\0.001
\0.001
Women
SBP (mmHg)
110.43 ± 0.34
120.98 ± 2.12
DBP (mmHg) FPG (mg/dL)
72.24 ± 0.26 87.60 ± 0.16
74.97 ± 1.09 89.09 ± 0.63
\0.001 0.013 0.020
118.81 ± 0.52
133.23 ± 1.85
\0.001
74.63 ± 0.29 96.44 ± 0.29
81.10 ± 1.09 99.90 ± 1.20
\0.001 0.005
HbA1c (%)
5.31 ± 0.005
5.38 ± 0.019
0.002
5.84 ± 0.007
5.88 ± 0.03
0.206
Creatinine (mg/dL)
0.71 ± 0.003
0.72 ± 0.014
0.622
0.72 ± 0.003
0.72 ± 0.010
0.870
eGFR (mL/min/1.73 m2)
100.52 ± 0.48
95.96 ± 2.37
0.058
93.19 ± 0.56
91.27 ± 1.74
0.296
b
3.94 (3.79, 4.09)
79.63 (62.83, 100.92) \0.001
4.64 (4.40, 4.89)
86.55 (72.20, 103.75) \0.001
TC (mg/dL)
183.13 ± 0.79
189.61 ± 5.03
0.201
201.09 ± 1.14
209.96 ± 3.42
TG (mg/dL)b
81.24 (79.21, 83.32)
93.92 (83.74, 105.32)
0.014
109.91 (106.22, 113.73)
149.19 (134.71, 165.21)
\0.001 \0.001
UACR (mg/g)
0.013
HDL-C (mg/dL)
57.79 ± 0.34
55.05 ± 1.40
0.060
53.59 ± 0.37
49.71 ± 0.96
LDL-C (mg/dL)
106.84 ± 0.64
110.5 ± 2.95
0.222
122.18 ± 1.03
126.47 ± 3.16
0.199
Non-HDL-C
125.34 ± 0.73
134.56 ± 5.06
0.070
147.5 ± 1.17
169.25 ± 3.14
\0.001
TC/HDL-C
3.30 ± 0.02
3.59 ± 0.12
0.018
3.92 ± 0.03
4.35 ± 0.08
\0.001
TG/HDL-Cb LDL-C/HDL-C
2.55 (2.51, 2.60) 1.94 ± 0.02
2.88 (2.62, 3.16) 2.11 ± 0.08
0.012 0.046
3.26 (3.17, 3.36) 2.39 ± 0.03
4.22 (3.86, 4.62) 2.59 ± 0.07
\0.001 0.008
Lipid-lowering drug use (%)
1.44 (0.22)
3.58 (2.12)
0.127
7.53 (0.71)
10.34 (2.30)
0.176
Hypertension (%)
11.82 (0.77)
37.47 (6.17)
29.89 (1.44)
71.67 (4.54)
\0.001
\0.001
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Endocrine Table 2 continued
Menopause (%)
Normal glucose UACR \30 mg/g
UACR C30 mg/g
P valuea
Prediabetes UACR \30 mg/g
UACR C30 mg/g
20.44 (0.91)
43.59 (5.40)
\0.001
58.19 (1.71)
75.56 (4.73)
P valuea 0.002
Value represents mean ± standard error or proportion (standard error) UACR urinary albumin to creatinine ratio, BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FPG fasting plasma glucose, HbA1c glycated hemoglobin, eGFR estimated glomerular filtration rate, UACR urinary albumin to creatinine ratio, TC total cholesterol, TG triglyceride, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol a
Obtained by t-test or v2test
b
Log transformation was performed to obtain P values, and value represents geometric mean (95 % confidence intervals)
Fig. 1 Sex-specific prevalence of lipid abnormalities according to UACR both in normal glucose and prediabetic groups (*P value \ 0.05 by v2 test)
results. In the general population, greater UACR was associated with higher TG and lower HDL-C levels only in women; these factors were also associated with higher atherogenic lipoprotein abnormalities including higher intermediate density lipoprotein particle and small LDL particle concentrations in the Multi-Ethnic Study of Atherosclerosis [22]. A 9.5-years follow-up study from the Framingham Offspring Cohort showed that incident albuminuria was inversely associated with HDL-C levels [23]. A recent study on the risk factors for albuminuria in the South Korean population showed that TG level is related to
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an increased risk of albuminuria in non-diabetic and nonhypertensive women [24]. Studies conducted in diabetic patients showed that a high concentration of TG, but not low HDL-C levels was correlated with incident albuminuria among type 1 diabetic subjects of a prospective cohort [25]. A cross-sectional study in Chinese type 2 diabetic patients found that a high TG level is associated with albuminuria [26]. A more recent study on an Asian population showed that a high TG/HDL-C ratio was an important marker for nephropathy in type 2 diabetic subjects [27]. However, only a few studies have reported the
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Fig. 2 Proportions according to the number of conventional parameters of dyslipidemia in subjects with albuminuria (*P value \ 0.05 by v2 test)
relationship between dyslipidemia and albuminuria in prediabetic subjects. In a cross-sectional study on Spanish hypertensive patients with impaired fasting glucose (IFG), a greater prevalence of CVD was observed in the group with increased UAE compared to that with lower UAE; however, there were no differences in TC or LDL-C levels between the two groups [28]. A study on healthy Korean men with IFG showed that using apolipoprotein B/A1 ratio as a predictive marker for coronary heart disease was positively associated with microalbuminuria [29]. Prediabetes, albuminuria, and dyslipidemia are components of metabolic syndromes that have been known to be associated with a higher risk for CVD and chronic kidney disease. Each of them reflects generalized inflammation
and vascular endothelial dysfunction. However, the pathophysiological mechanism linking them is not fully elucidated [30]. Prediabetic status has been reported to be associated with an increased prevalence of albuminuria [31]. Renal vasodilation and elevated glomerular filtration rate accompanied by hyperinsulinemia are thought to be involved in controlling UAE [32]. Evidence suggests that insulin resistance could be the link between microalbuminuria and lipoprotein abnormalities [33]. Meanwhile, abnormal lipid metabolism could possibly cause increased UAE and renal dysfunction due to acceleration of renovascular atherosclerosis. Hypertriglyceridemia could cause tubulointerstitial damage progression through the infiltration and deposition of fat in renal tubules [34]. HDL potentially contributes to the release of cholesterol from cells and has antioxidative effects, which may be related to renal injury. Moreover, both increased TG and decreased HDL-C are associated with higher small LDL particle levels, which are known to be more susceptible to oxidation and more difficult to be eliminated from plasma compared to larger ones [35]. Previous studies have shown that elevated TG or low HDL-C levels are mainly associated with abnormal UAE or progression of kidney disease predominantly in diabetic patients [25, 26, 36, 37]. Results from our study appear to be in accordance with these studies. Elevated UAE may also lead to abnormal lipid and lipoprotein metabolism. The changes in LDL-C
Table 3 Multivariate logistic regression analyses for having albuminuria according to parameters of dyslipidemia Normal glucose Model 1a OR (95 % CI)
P value
Model 2b,c OR (95 % CI)
P value
Prediabetes Model 1a OR (95 % CI)
P value
Model 2b,c OR (95 % CI)
P value
Men TC (10 mg/dL)
1.03 (0.94–1.11)
0.555
1.01 (0.93–1.10)
0.792
1.01 (0.95–1.08)
0.759
1.01 (0.94–1.08)
0.834
TG (1 mg/dL)d
1.84 (1.27–2.67)
0.001
1.32 (0.85–2.06)
0.216
1.61 (1.15–2.24)
0.005
1.33 (0.92–1.92)
0.125
HDL-C (10 mg/dL)
1.05 (0.85–1.31)
0.634
1.20 (0.94–1.54)
0.143
1.13 (0.93–1.37)
0.215
1.07 (0.87–1.30)
0.540
LDL-C (10 mg/dL)
0.96 (0.88–1.05)
0.404
0.97 (0.88–1.06)
0.475
0.94 (0.88–1.00)
0.064
0.96 (0.90–1.03)
0.238
Non-HDL-C (10 mg/dL)
1.02 (0.94–1.10)
0.682
0.99 (0.90–1.08)
0.795
1.00 (0.93–1.06)
0.888
1.00 (0.93–1.07)
0.992
TC/HDL-C
1.03 (0.79–1.34)
0.830
0.89 (0.64–1.24)
0.500
0.95 (0.78–1.17)
0.644
0.98 (0.79–1.22)
0.859
TG/HDL-Cd
1.68 (1.11–2.53)
0.014
1.13 (0.68–1.90)
0.636
1.42 (0.98–2.06)
0.064
1.22 (0.82–1.81)
0.332
LDL-C/HDL-C
0.90 (0.63–1.28)
0.568
0.82 (0.54–1.24)
0.345
0.79 (0.60–1.03)
0.079
0.87 (0.66–1.14)
0.302
Women TC (10 mg/dL)
0.97 (0.91–1.03)
0.317
0.995 (0.93–1.06)
0.874
1.04 (1.00–1.08)
0.087
1.05 (1.01–1.10)
0.024
TG (1 mg/dL)d
1.28 (0.91–1.80)
0.159
1.12 (0.76–1.65)
0.559
1.94 (1.45–2.60)
\0.001
1.59 (1.14–2.20)
0.006
HDL-C (10 mg/dL)
0.93 (0.80–1.08)
0.320
0.99 (0.84–1.16)
0.871
0.85 (0.75–0.97)
0.013
0.90 (0.78–1.03)
0.123
LDL-C (10 mg/dL)
0.96 (0.90–1.02)
0.180
0.98 (0.92–1.05)
0.570
1.03 (0.98–1.08)
0.311
1.06 (1.01–1.12)
0.033
Non-HDL-C (10 mg/dL)
0.98 (0.92–1.04)
0.493
0.996 (0.93–1.07)
0.913
1.05 (1.01–1.10)
0.014
1.06 (1.02–1.11)
0.009
TC/HDL-C
1.02 (0.84–1.25)
0.839
0.98 (0.79–1.23)
0.887
1.18 (1.04–1.35)
0.009
1.18 (1.02–1.36)
0.029
TG/HDL-Cd
1.37 (0.90–2.09)
0.146
1.09 (0.67–1.77)
0.734
1.96 (1.44–2.68)
\0.001
1.60 (1.12–2.27)
0.010
LDL-C/HDL-C
0.96 (0.76–1.23)
0.829
0.94 (0.72–1.22)
0.632
1.16 (0.97–1.39)
0.102
1.24 (1.01–1.52)
0.037
OR, odd ratio; CI, confidence interval; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol a
Adjusted for age
b
Adjusted for age, body mass index, alcohol consumption, smoking status, physical activity, and hypertension in men
c
Adjusted for age, body mass index, alcohol consumption, smoking status, physical activity, hypertension, and menopause in women
d
Log transformation was performed to obtain OR, 95 % CI, and P values
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presented in patients with nephrotic syndrome have been reported to be mediated by enhanced activity of cholesterol ester transfer protein and increased concentrations of TGrich very low-density lipoproteins [38]. This mechanism may also explain the relationship between lipid abnormalities and elevated UAE. Gender differences in the relationship between dyslipidemia parameters and increased UAE were observed in the current study; however, the reason is not clear due to the cross-sectional nature of this study. Lipid abnormalities seem to contribute more to elevated UAE in women, since the effects of other factors including obesity or testosterone levels are less predominant in them than in men. Inflammation may be a common denominator between abnormal lipid metabolism and albuminuria. A study on a Chinese population showed that C-reactive protein, which is a wellknown inflammatory marker is more strongly associated with metabolic syndrome in women, which is similar to our findings [39]. Sex hormones are also likely to be involved in the underlying mechanism. Higher estrogen levels might be associated with higher serum levels of inflammatory markers such as soluble CD40 ligand which has been implicated in inflammatory processes related to atherosclerotic CVD [40]. Additional studies are necessary to elucidate the mechanism linking dyslipidemia and albuminuria with gender differences. This study has certain limitations. First, the cross-sectional design cannot be used to deduce the causal relationship between lipid abnormalities and elevated UAE. Second, UACR was measured from a single-spot urine sample and this could result in an incorrect classification of albuminuria. Third, the specific types of anti-hypertensive medication that may influence albuminuria or renal function were not considered, since a self-reported questionnaire was used to report drug use. Despite these limitations, our study presents epidemiological evidence from a large population-based study using nationally representative data reflecting a single ethnicity. The study also assessed various parameters of lipid abnormalities including non-HDLC and lipid-related ratios. In conclusion, a higher prevalence of several lipid abnormalities and mixed dyslipidemia was found in prediabetic women with albuminuria. Higher levels of TG, non-HDL-C, and TC/HDL-C ratio, and lower levels of HDL-C were significantly associated with the increased risk of albuminuria in prediabetic women. Identification of lipid abnormalities may be helpful for prediabetic subjects with increased UAE, given that albuminuria is strongly associated with the risk of adverse outcomes during prediabetes. Acknowledgments We greatly appreciate the participants in the Korea National Health and Nutrition Examination Survey 2011-2012.
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Conflict of interest The authors declare that they have no conflict of interest or funding source.
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ORIGINAL ARTICLE
Relationship between dyslipidemia and albuminuria in prediabetic adults: The Korea National Health and Nutrition Examination Survey 2011–2012 Ga Eun Nam • Kyungdo Han • Do Hoon Kim • Yong Gyu Park • Yeo Joon Yoon • Young Eun Kim Sangsu Lee • Sungho Lee • Yong Kyun Roh
•
Received: 9 July 2014 / Accepted: 27 August 2014 Ó Springer Science+Business Media New York 2014
Abstract This study aimed to estimate the relationship between various lipid abnormalities and albuminuria in Korean prediabetic adults. Data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) 2011–2012 were analyzed. The study consisted of 4,811 subjects in the normal glucose group and 3,872 in the prediabetic group. Prediabetes was defined by the fasting plasma glucose or hemoglobin A1c level. Albuminuria was defined as a urine albumin to creatinine ratio (UACR) C30 mg/g. Various parameters of dyslipidemia were assessed. No differences were observed in the prevalence of lipid abnormalities in prediabetic men with different values of UACR. Prediabetic women with increased urinary albumin excretion showed a significantly higher prevalence of lipid abnormalities. The proportion of mixed dyslipidemia was significantly higher in prediabetic women with albuminuria. Higher levels of total cholesterol, triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (nonHDL-C), and TC to HDL-C ratio, TG to HDL-C ratio, and
G. E. Nam D. H. Kim Y. J. Yoon Y. E. Kim S. Lee S. Lee Department of Family Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan-Si, Republic of Korea K. Han Y. G. Park Department of Biostatistics, Catholic University College of Medicine, Seoul, Republic of Korea Y. K. Roh (&) Department of Family Medicine, Kangnam Sacred Heart Hospital, College of Medicine, Hallym University, 948-1 Daelim-dong, Youngdungpo-Gu, Seoul 150-071, Republic of Korea e-mail: [email protected]
LDL-C to HDL-C ratio were significantly associated with increased risk of albuminuria in prediabetic women. Conclusions: Several lipid abnormalities were significantly associated with the increased risk of albuminuria in prediabetic women. Hence, screening for lipid abnormalities may be helpful for identification of risk for albuminuria in prediabetic subjects. Keywords Prediabetes Albuminuria Dyslipidemia Urine albumin to creatinine ratio
Introduction Dyslipidemia is a major preventable risk factor for cardiovascular disease (CVD) that is highly prevalent in the general population, and the rate escalates in patients with renal insufficiency [1, 2]. It has generally been defined by elevated levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), or low levels of high-density lipoprotein cholesterol (HDL-C) [3]. Recently, non-HDL-C levels and lipid-related ratios have been noted to be more predictive for CVD, than the individual lipid profile [4, 5]. Prediabetes, which is defined by fasting plasma glucose (FPG), the oral glucose tolerance test results, or hemoglobin A1c (HbA1c) level is a high-risk factor for the development of diabetes and is associated with increased cardiovascular risk [6]. The prevalence of prediabetes in South Korea and worldwide has dramatically increased with increasing rates of diabetes. The largest surge is expected to occur in developing countries including South Korea [7, 8]. Although there were ethnic differences, prediabetic status was shown to be associated with target organ damage including albuminuria [9]. Moreover,
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albuminuria might predict progression of prediabetes to diabetes [10]. The presence of albuminuria is an early marker for the progression of diabetic nephropathy, and is strongly related to future CVD morbidity and mortality in both diabetic and non-diabetic subjects [11]. Mounting evidence has revealed that dyslipidemia plays a significant role in the development of albuminuria in diabetic patients [12]. A few interventional studies have demonstrated the possible positive effect of lipid-lowering agents on the improvement of albuminuria in these patients [13]. However, in prediabetic subjects, the relationship between dyslipidemia and albuminuria has not been sufficiently investigated yet. Therefore, the purpose of this study was to estimate the relationship between various parameters of dyslipidemia and albuminuria in Korean prediabetic adults using nationally representative data.
Materials and methods Survey overview and study subjects This study was based on the data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) 2011–2012, which has been conducted by the Division of Chronic Disease Surveillance at the Korean Center for Disease Control and Prevention (KCDC) since 1998. The survey was designed to evaluate nationwide health and nutrition status, and comprised a health interview, a nutritional assessment, and a health examination. A stratified, multistage, and cluster-sampling design with proportional allocation based on geographic areas, sex, and age from the National Census Registry was used for the selection of survey subjects to represent the entire non-institutionalized civilian population in South Korea. Of 16,576 participants chosen based on the health interview and health examination, 7,893 individuals were excluded on the following grounds: \19 years of age, missing data, cancer, menstruation, pregnancy, fasting period less than 8 h, estimated glomerular filtration rate (eGFR) \60 mL/min/1.73 m2, or diabetes mellitus (DM). DM was defined by an FPG level C126 mg/dL, treatment with insulin or oral hypoglycemic agents, or diagnosis by a physician. Prediabetes was defined by FPG levels ranging from 100–125 mg/dL or HbA1c levels ranging from 5.7–6.4 % (39–46 mmol/mol) [6]. Of 8,683 non-diabetic subjects, 4,811 were included in the normal glucose group, while 3,872 were grouped in the prediabetic group. All the participants provided written informed consent, and the Institutional Review Board of the KCDC approved the study protocol.
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Lifestyle variables Alcohol consumption, smoking status, and physical activity were investigated in the self-reported questionnaire. Based on the amount of alcohol consumed per day up to 1 month before the interview, subjects who had consumed C30 g/day of alcohol were classified as heavy drinkers [14]. Subjects were classified as current smokers or non-smokers. Physical activity was assessed by using the International Physical Activity Questionnaire short form modified for the Korean population [15]. Subjects who exercised moderately for over 30 min per session more than 5 times per week, or those who exercised vigorously for over 20 min per session more than 3 times per week were defined as regular physical exercisers. Anthropometric measurements Height and body weight were measured to the nearest 0.1 cm, and 0.1 kg, respectively. Body mass index (BMI) was calculated using the formula: body weight (kg)/height2 (m2). Waist circumference (WC) was measured at the midpoint between the lower costal margin and the iliac crest during expiration. Blood pressure (BP) was measured in the sitting position using a standard mercury sphygmomanometer (Baumanometer, WA Baum Co., New York, USA) three times in 5-min intervals. The average of the second and third measurements was used in the analyses. Hypertension was defined as systolic BP C140 mmHg or diastolic BP C90 mmHg, or treatment with anti-hypertensive agents. Biochemical measurements and definitions Blood samples were obtained in the morning following a fasting period lasting 8 h or more, and single-spot, midstream urine samples were collected in the first morning void. The samples were properly processed, immediately refrigerated, and transported via cold storage units to the Central Testing Institute in Seoul, Korea, and analyzed within 24 h. HbA1c level was measured using an HLC723G7 (Tosoh, Japan) by high performance liquid chromatography. Serum FPG, TC, TG, and HDL-C levels were measured using a Hitachi automatic analyzer 7600 (Hitachi, Tokyo, Japan) by enzymatic methods. LDL-C level was calculated using Friedewald’s formula [16] in subjects with TG \400 mg/dL, or measured directly using a commercially available kit (CholestestÒ LDL; Sekisui, Medical, Tokyo, Japan) in subjects with TG C400 mg/dL. NonHDL-C level was calculated as TC level minus HDL-C level. Conventional parameters of dyslipidemia were defined according to the criteria of the National Cholesterol Education Program Adult Treatment Panel III [3]:
Endocrine
hypercholesterolemia, TC level C240 mg/dL or the use of lipid-lowering drugs; hypo-HDL-cholesterolemia, HDL-C level \40 mg/dL; hyper-LDL-cholesterolemia, LDL-C level C160 mg/dL; hypertriglyceridemia, TG level C200 mg/dL. Additionally, we defined hyper-non-HDLcholesterolemia (non-HDL-C C160 mg/dL), high TC to HDL-C ratio (TC/HDL-C [5), high TG to HDL-C ratio (TG/HDL-C[3.8) and high LDL-C to HDL-C ratio (LDLC/HDL-C[2) as lipid abnormalities [4, 17–19]. Serum and urine creatinine levels were measured using a Hitachi automatic analyzer 7600 by kinetic colorimetry. Urine albumin level was measured using the same equipment by means of a turbidimetric assay. Albuminuria is defined as a urine albumin to creatinine ratio (UACR) C30 mg/g [20]. We calculated the eGFR using the formula referred to in the Modification of Diet in Renal Disease study [21]. Statistical analysis Statistical analysis was performed by using the SAS survey procedure (version 9.2; SAS Institute, Cary, North Carolina, USA) in a manner reflecting sampling weights and providing nationally representative estimates. P values \ 0.05 were considered to be statistically significant. Independent t-test or v2 test was performed for the assessment of differences in clinical and biochemical characteristics between normal glucose, and prediabetic groups. Age- and multivariateadjusted logistic regression analyses were conducted to evaluate the relationship of dyslipidemia parameters with albuminuria, and odds ratios (ORs) and confidence intervals (CIs) were estimated. Age, BMI, alcohol consumption, smoking status, physical activity, hypertension, and menopause in women were considered to be confounding factors in multivariate analyses.
Results The baseline characteristics of the subjects are presented in Table 1. Prediabetic subjects among both men and women were significantly older, and displayed higher values of BMI, WC, SBP, DBP, FPG, HbA1c, and UACR than those with normal glucose levels. The mean values of UACR for normal glucose and prediabetic subjects were 3.52 mg/g and 4.36 mg/g for men, and 4.45 mg/g and 5.94 mg/g for women, respectively. All the parameters for dyslipidemia, with the exception of HDL-C were observed to be significantly higher, while HDL-C levels were lower in prediabetic subjects compared to subjects with a normal glucose level in both sexes. The rates of hypertensives and lipidlowering medication use were also higher among prediabetic subjects in both sexes. In men, lifestyle factors such as a higher prevalence of heavy alcohol consumption or
smoking were found to be associated with prediabetic subjects, than those with normal glucose levels. There were no differences in the level of physical activity as defined by glucose levels in either sex. Table 2 shows means of metabolic variables according to urinary albumin excretion in the normal glucose and prediabetic groups. In men with normal glucose levels, means of age, BMI, SBP, FPG, TG, and TG/HDL-C were significantly higher in subjects with albuminuria compared to those without albuminuria. Mean age and SBP levels were higher in subjects with albuminuria among prediabetic men. Age, WC, SBP, DBP, FPG, HbA1c, TG, TC/ HDL-C, TG/HDL-C, and LDL-C/HDL-C levels were significantly higher in subjects with albuminuria than those without albuminuria among women with normal glucose level. In prediabetic women, subjects with albuminuria had higher levels of age, BMI, WC, SBP, DBP, FPG, TC, TG, non-HDL-C, TC/HDL-C, TG/HDL-C, and LDL-C/HDL-C than those without albuminuria. Figure 1 shows the sex-specific prevalence of lipid abnormalities as defined by the UACR both in normal glucose and prediabetic groups. In men with normal glucose levels, prevalence of hypertriglyceridemia and high TG/HDL-C ratio were higher in subjects with UACR C30 mg/g, than in those with UACR \30 mg/g. However, no differences were observed in the prevalence of any of the lipid abnormalities between the UACR groups among prediabetic men. Meanwhile, a higher prevalence of hyperLDL-cholesterolemia, high ratios of TC/HDL-C, TG/HDLC, and LDL-C/HDL-C were observed in women with normal glucose and UACR C30 mg/g. Subjects with UACR C30 mg/g showed a significantly higher prevalence of hypercholesterolemia, hypertriglyceridemia, hyper-nonHDL-cholesterolemia, and high ratios of TC/HDL-C, TG/ HDL-C, and LDL-C/HDL-C than those with UACR \30 mg/g among prediabetic women. Figure 2 summarizes the proportions of subjects with albuminuria classified according to the number of conventional parameters of dyslipidemia. The proportion of occurrence of mixed dyslipidemia with two or more lipid abnormalities was significantly higher in prediabetic women with albuminuria. Table 3 shows age- and multivariate-adjusted ORs for the prevalence of albuminuria classified according to sex and glucose levels. In men, TG and TG/HDL-C ratio was associated with the risk of albuminuria only when adjusted for age in normal glucose group and TG was in prediabetic group. None of the lipid abnormalities was associated with the risk of albuminuria in women with normal glucose levels. However, in prediabetic women, increased levels of TG, non-HDL-C, TC/HDL-C ratio, and TG/HDL-C ratio, and lower levels of HDL-C were independently associated with the risk of albuminuria in age-adjusted analyses. In multivariate analyses,
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Endocrine Table 1 Baseline characteristics of subjects in normal glucose and prediabetic groups Men Normal glucose
Women Prediabetes
P value
a
Normal glucose
Prediabetes
P valuea
n
2,041
1,788
2,770
2,084
Age (years)
38.91 ± 0.38
47.58 ± 0.47
\0.001
40.62 ± 0.35
53.90 ± 0.44
\0.001
BMI (kg/m2)
23.65 ± 0.10
24.67 ± 0.11
\0.001
22.44 ± 0.09
24.33 ± 0.11
\0.001
WC (cm)
82.12 ± 0.28
86.11 ± 0.32
\0.001
75.07 ± 0.23
81.20 ± 0.31
\0.001
SBP (mmHg)
117.22 ± 0.34
121.55 ± 0.46
\0.001
110.86 ± 0.36
120.03 ± 0.54
\0.001
DBP (mmHg)
77.86 ± 0.30
80.31 ± 0.34
\0.001
72.35 ± 0.26
75.18 ± 0.30
\0.001
FPG (mg/dL) HbA1c (%)
88.96 ± 0.19 5.32 ± 0.006
99.39 ± 0.32 5.77 ± 0.008
\0.001 \0.001
87.66 ± 0.16 5.32 ± 0.005
96.73 ± 0.30 5.84 ± 0.008
\0.001 \0.001
Creatinine (mg/dL)
0.97 ± 0.003
0.96 ± 0.004
0.69
0.71 ± 0.003
0.72 ± 0.003
0.017
eGFR (mL/min/1.73 m2)
95.33 ± 0.44
91.54 ± 0.47
\0.001
100.34 ± 0.47
93.03 ± 0.53
\0.001
UACR (mg/g)b
3.52 (3.35, 3.69)
4.36 (4.12, 4.61)
\0.001
4.45 (4.23, 4.67)
5.94 (5.54, 6.37)
TC (mg/dL)
182.85 ± 1.03
196.53 ± 1.15
\0.001
183.39 ± 0.79
201.84 ± 1.09
\0.001
TG (mg/dL)b
110.80 (107.40, 114.30)
140.53 (135.56, 145.66)
\0.001
81.72 (79.68, 83.81)
112.79 (109.05, 116.66)
\0.001
\.0001
HDL-C (mg/dL)
50.40 ± 0.36
49.06 ± 0.35
57.68 ± 0.33
53.26 ± 0.35
\0.001
LDL-C (mg/dL)
107.2 ± 0.90
115.46 ± 1.00
\0.001
106.98 ± 0.64
122.53 ± 0.98
\0.001
Non-HDL-C
132.46 ± 1.03
147.47 ± 1.19
\0.001
125.71 ± 0.75
148.58 ± 1.12
\0.001
0.005
TC/HDL-C
3.79 ± 0.03
4.21 ± 0.04
\0.001
3.31 ± 0.02
3.96 ± 0.03
\0.001
TG/HDL-Cb LDL-C/HDL-C
3.42 (3.33, 3.51) 2.23 ± 0.02
4.14 (4.01, 4.27) 2.47 ± 0.03
\0.001 \0.001
2.57 (2.52, 2.62) 1.95 ± 0.02
3.33 (3.24, 3.43) 2.40 ± 0.03
\0.001 \0.001
Lipid-lowering drug use (%)
1.16 (0.22)
4.02 (0.49)
\0.001
1.52 (0.22)
7.77 (0.69)
\0.001
\0.001
\0.001
Hypertension (%)
44.47 (1.94)
55.53 (1.94)
39.05 (1.87)
60.95 (1.87)
Thyroid diseases (%)
0.83 (0.20)
0.82 (0.22)
0.982
4.89 (0.47)
5.71 (0.57)
0.282
Heavy drinker (%)
30.27 (1.34)
34.06 (1.50)
0.06
6.55 (0.65)
4.14 (0.58)
0.004
Current smoker (%)
40.49 (1.37)
45.17 (1.65)
0.038
6.25 (0.62)
4.60 (0.68)
0.096
Regular exerciser (%)
23.72 (1.18)
21.00 (1.24)
0.133
Menopause (%)
15.69 (0.87)
16.09 (1.21)
0.788
21.33 (0.93)
59.65 (1.62)
\0.001
Value represents mean ± standard error or proportion (standard error) BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FPG fasting plasma glucose, HbA1c glycated hemoglobin, eGFR estimated glomerular filtration rate, UACR urinary albumin to creatinine ratio, TC total cholesterol, TG triglyceride, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol a
Obtained by t-test or v2test
b
Log transformation was performed to obtain P values, and value represents geometric mean (95 % confidence intervals)
most of lipid parameters except HDL-C were also associated with the risk of albuminuria (OR [95 % CI]: 1.05 [1.01–1.10] for TC; 1.59 [1.14–2.20] for TG; 1.06 [1.01–1.12] for LDL-C; 1.06 [1.02–1.11] for non-HDL-C; 1.18 [1.02–1.36] for TC/ HDL-C ratio; 1.60 [1.12–2.27] for TG/HDL-C ratio; 1.24 [1.01–1.52] for LDL-C/HDL-C ratio).
Discussion The present study showed that several lipid abnormalities could be associated with elevated UAE in prediabetic subjects. The prevalence of lipid abnormalities and mixed
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dyslipidemia was high in prediabetic women with albuminuria. Several parameters of dyslipidemia were independently associated with the risk for increased UAE in prediabetic women. Among conventional parameters of dyslipidemia, higher TG and lower HDL-C levels were significant determinants for an increased risk of albuminuria. These associations were also observed between elevated levels of non-HDL-C, TC/HDL-C ratio, and albuminuria. TC/HDL-C ratio reflects the incorporation of TG-rich lipoproteins, and non-HDL-C is a marker for atherogenic particles [4, 5]. Previous studies that evaluated the association between dyslipidemia and albuminuria have reported inconsistent
Endocrine Table 2 Means of metabolic variables according to urinary albumin excretion by glucose status Normal glucose UACR \30 mg/g
UACR C30 mg/g
n
1,980
61
1,699
89
Age (years)
38.74 ± 0.38
45.48 ± 2.33
0.004
47.16 ± 0.48
57.74 ± 1.67
BMI (kg/m2)
23.59 ± 0.10
25.78 ± 0.76
0.004
24.66 ± 0.12
24.98 ± 0.50
0.555
WC (cm)
81.98 ± 0.28
87.74 ± 2.02
0.005
86.04 ± 0.33
88.00 ± 1.44
0.191
SBP (mmHg)
116.96 ± 0.35
127.53 ± 2.51
\0.001
121.18 ± 0.47
130.16 ± 2.27
\0.001
DBP (mmHg) FPG (mg/dL)
77.66 ± 0.30 88.88 ± 0.20
85.84 ± 2.06 91.95 ± 0.67
\0.001 \0.001
80.22 ± 0.35 99.31 ± 0.32
82.48 ± 1.46 101.12 ± 1.48
0.133 0.229
P valuea
Prediabetes UACR \30 mg/g
UACR C30 mg/g
P valuea
Men \0.001
HbA1c (%)
5.32 ± 0.007
5.32 ± 0.029
0.890
5.77 ± 0.008
5.79 ± 0.039
0.531
Creatinine (mg/dL)
0.97 ± 0.003
0.97 ± 0.023
0.708
0.96 ± 0.004
0.95 ± 0.019
0.321
eGFR (mL/min/1.73 m2)
95.41 ± 0.44
92.13 ± 3.12
0.294
91.59 ± 0.47
90.47 ± 2.11
0.599
UACR (mg/g)
b
3.26 (3.13, 3.39)
75.97 (59.38, 97.18)
TC (mg/dL)
182.63 ± 1.04
191.54 ± 4.62
TG (mg/dL)b
109.91 (106.54, 113.40)
152.06 (130.19, 177.61)
\0.001 0.057 \0.001
\0.001
3.87 (3.69, 4.06)
73.13 (60.98, 87.72)
196.45 ± 1.19
198.5 ± 4.68
0.674
139.76 (134.69, 145.01)
159.80 (137.17, 186.16)
0.093
HDL-C (mg/dL)
50.41 ± 0.36
49.86 ± 1.67
0.744
48.96 ± 0.36
51.38 ± 2.39
0.326
LDL-C (mg/dL)
107.14 ± 0.91
109.43 ± 4.82
0.638
115.73 ± 1.05
109.29 ± 3.83
0.113
Non-HDL-C
132.22 ± 1.03
141.68 ± 5.18
0.070
147.48 ± 1.22
147.12 ± 5.10
0.944
TC/HDL-C TG/HDL-Cb
3.79 ± 0.03 3.40 (3.31, 3.49)
4.06 ± 0.19 4.30 (3.72, 4.98)
0.167 0.002
4.21 ± 0.04 4.13 (3.99, 4.26)
4.17 ± 0.19 4.44 (3.81, 5.17)
0.834 0.358
LDL-C/HDL-C
2.22 ± 0.02
2.32 ± 0.17
0.552
2.48 ± 0.03
2.32 ± 0.13
0.231
Lipid-lowering drug use (%)
1.05 (0.21)
5.37 (3,74)
0.014
3.91 (0.50)
6.40 (2.83)
0.285
Hypertension (%)
17.75 (1.01)
49.48 (7.98)
31.86 (1.51)
68.11 (6.85)
n
2,645
125
1,907
177
Age (years)
40.19 ± 0.34
50.77 ± 2.11
\0.001
53.33 ± 0.46
60.00 ± 1.27
\0.001
BMI (kg/m2)
22.42 ± 0.09
23.06 ± 0.38
0.095
24.21 ± 0.12
25.69 ± 0.30
\0.001
WC (cm)
74.95 ± 0.23
77.76 ± 1.14
0.015
80.78 ± 0.31
85.75 ± 0.75
\0.001
\0.001
\0.001
Women
SBP (mmHg)
110.43 ± 0.34
120.98 ± 2.12
DBP (mmHg) FPG (mg/dL)
72.24 ± 0.26 87.60 ± 0.16
74.97 ± 1.09 89.09 ± 0.63
\0.001 0.013 0.020
118.81 ± 0.52
133.23 ± 1.85
\0.001
74.63 ± 0.29 96.44 ± 0.29
81.10 ± 1.09 99.90 ± 1.20
\0.001 0.005
HbA1c (%)
5.31 ± 0.005
5.38 ± 0.019
0.002
5.84 ± 0.007
5.88 ± 0.03
0.206
Creatinine (mg/dL)
0.71 ± 0.003
0.72 ± 0.014
0.622
0.72 ± 0.003
0.72 ± 0.010
0.870
eGFR (mL/min/1.73 m2)
100.52 ± 0.48
95.96 ± 2.37
0.058
93.19 ± 0.56
91.27 ± 1.74
0.296
b
3.94 (3.79, 4.09)
79.63 (62.83, 100.92) \0.001
4.64 (4.40, 4.89)
86.55 (72.20, 103.75) \0.001
TC (mg/dL)
183.13 ± 0.79
189.61 ± 5.03
0.201
201.09 ± 1.14
209.96 ± 3.42
TG (mg/dL)b
81.24 (79.21, 83.32)
93.92 (83.74, 105.32)
0.014
109.91 (106.22, 113.73)
149.19 (134.71, 165.21)
\0.001 \0.001
UACR (mg/g)
0.013
HDL-C (mg/dL)
57.79 ± 0.34
55.05 ± 1.40
0.060
53.59 ± 0.37
49.71 ± 0.96
LDL-C (mg/dL)
106.84 ± 0.64
110.5 ± 2.95
0.222
122.18 ± 1.03
126.47 ± 3.16
0.199
Non-HDL-C
125.34 ± 0.73
134.56 ± 5.06
0.070
147.5 ± 1.17
169.25 ± 3.14
\0.001
TC/HDL-C
3.30 ± 0.02
3.59 ± 0.12
0.018
3.92 ± 0.03
4.35 ± 0.08
\0.001
TG/HDL-Cb LDL-C/HDL-C
2.55 (2.51, 2.60) 1.94 ± 0.02
2.88 (2.62, 3.16) 2.11 ± 0.08
0.012 0.046
3.26 (3.17, 3.36) 2.39 ± 0.03
4.22 (3.86, 4.62) 2.59 ± 0.07
\0.001 0.008
Lipid-lowering drug use (%)
1.44 (0.22)
3.58 (2.12)
0.127
7.53 (0.71)
10.34 (2.30)
0.176
Hypertension (%)
11.82 (0.77)
37.47 (6.17)
29.89 (1.44)
71.67 (4.54)
\0.001
\0.001
123
Endocrine Table 2 continued
Menopause (%)
Normal glucose UACR \30 mg/g
UACR C30 mg/g
P valuea
Prediabetes UACR \30 mg/g
UACR C30 mg/g
20.44 (0.91)
43.59 (5.40)
\0.001
58.19 (1.71)
75.56 (4.73)
P valuea 0.002
Value represents mean ± standard error or proportion (standard error) UACR urinary albumin to creatinine ratio, BMI body mass index, WC waist circumference, SBP systolic blood pressure, DBP diastolic blood pressure, FPG fasting plasma glucose, HbA1c glycated hemoglobin, eGFR estimated glomerular filtration rate, UACR urinary albumin to creatinine ratio, TC total cholesterol, TG triglyceride, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol a
Obtained by t-test or v2test
b
Log transformation was performed to obtain P values, and value represents geometric mean (95 % confidence intervals)
Fig. 1 Sex-specific prevalence of lipid abnormalities according to UACR both in normal glucose and prediabetic groups (*P value \ 0.05 by v2 test)
results. In the general population, greater UACR was associated with higher TG and lower HDL-C levels only in women; these factors were also associated with higher atherogenic lipoprotein abnormalities including higher intermediate density lipoprotein particle and small LDL particle concentrations in the Multi-Ethnic Study of Atherosclerosis [22]. A 9.5-years follow-up study from the Framingham Offspring Cohort showed that incident albuminuria was inversely associated with HDL-C levels [23]. A recent study on the risk factors for albuminuria in the South Korean population showed that TG level is related to
123
an increased risk of albuminuria in non-diabetic and nonhypertensive women [24]. Studies conducted in diabetic patients showed that a high concentration of TG, but not low HDL-C levels was correlated with incident albuminuria among type 1 diabetic subjects of a prospective cohort [25]. A cross-sectional study in Chinese type 2 diabetic patients found that a high TG level is associated with albuminuria [26]. A more recent study on an Asian population showed that a high TG/HDL-C ratio was an important marker for nephropathy in type 2 diabetic subjects [27]. However, only a few studies have reported the
Endocrine
Fig. 2 Proportions according to the number of conventional parameters of dyslipidemia in subjects with albuminuria (*P value \ 0.05 by v2 test)
relationship between dyslipidemia and albuminuria in prediabetic subjects. In a cross-sectional study on Spanish hypertensive patients with impaired fasting glucose (IFG), a greater prevalence of CVD was observed in the group with increased UAE compared to that with lower UAE; however, there were no differences in TC or LDL-C levels between the two groups [28]. A study on healthy Korean men with IFG showed that using apolipoprotein B/A1 ratio as a predictive marker for coronary heart disease was positively associated with microalbuminuria [29]. Prediabetes, albuminuria, and dyslipidemia are components of metabolic syndromes that have been known to be associated with a higher risk for CVD and chronic kidney disease. Each of them reflects generalized inflammation
and vascular endothelial dysfunction. However, the pathophysiological mechanism linking them is not fully elucidated [30]. Prediabetic status has been reported to be associated with an increased prevalence of albuminuria [31]. Renal vasodilation and elevated glomerular filtration rate accompanied by hyperinsulinemia are thought to be involved in controlling UAE [32]. Evidence suggests that insulin resistance could be the link between microalbuminuria and lipoprotein abnormalities [33]. Meanwhile, abnormal lipid metabolism could possibly cause increased UAE and renal dysfunction due to acceleration of renovascular atherosclerosis. Hypertriglyceridemia could cause tubulointerstitial damage progression through the infiltration and deposition of fat in renal tubules [34]. HDL potentially contributes to the release of cholesterol from cells and has antioxidative effects, which may be related to renal injury. Moreover, both increased TG and decreased HDL-C are associated with higher small LDL particle levels, which are known to be more susceptible to oxidation and more difficult to be eliminated from plasma compared to larger ones [35]. Previous studies have shown that elevated TG or low HDL-C levels are mainly associated with abnormal UAE or progression of kidney disease predominantly in diabetic patients [25, 26, 36, 37]. Results from our study appear to be in accordance with these studies. Elevated UAE may also lead to abnormal lipid and lipoprotein metabolism. The changes in LDL-C
Table 3 Multivariate logistic regression analyses for having albuminuria according to parameters of dyslipidemia Normal glucose Model 1a OR (95 % CI)
P value
Model 2b,c OR (95 % CI)
P value
Prediabetes Model 1a OR (95 % CI)
P value
Model 2b,c OR (95 % CI)
P value
Men TC (10 mg/dL)
1.03 (0.94–1.11)
0.555
1.01 (0.93–1.10)
0.792
1.01 (0.95–1.08)
0.759
1.01 (0.94–1.08)
0.834
TG (1 mg/dL)d
1.84 (1.27–2.67)
0.001
1.32 (0.85–2.06)
0.216
1.61 (1.15–2.24)
0.005
1.33 (0.92–1.92)
0.125
HDL-C (10 mg/dL)
1.05 (0.85–1.31)
0.634
1.20 (0.94–1.54)
0.143
1.13 (0.93–1.37)
0.215
1.07 (0.87–1.30)
0.540
LDL-C (10 mg/dL)
0.96 (0.88–1.05)
0.404
0.97 (0.88–1.06)
0.475
0.94 (0.88–1.00)
0.064
0.96 (0.90–1.03)
0.238
Non-HDL-C (10 mg/dL)
1.02 (0.94–1.10)
0.682
0.99 (0.90–1.08)
0.795
1.00 (0.93–1.06)
0.888
1.00 (0.93–1.07)
0.992
TC/HDL-C
1.03 (0.79–1.34)
0.830
0.89 (0.64–1.24)
0.500
0.95 (0.78–1.17)
0.644
0.98 (0.79–1.22)
0.859
TG/HDL-Cd
1.68 (1.11–2.53)
0.014
1.13 (0.68–1.90)
0.636
1.42 (0.98–2.06)
0.064
1.22 (0.82–1.81)
0.332
LDL-C/HDL-C
0.90 (0.63–1.28)
0.568
0.82 (0.54–1.24)
0.345
0.79 (0.60–1.03)
0.079
0.87 (0.66–1.14)
0.302
Women TC (10 mg/dL)
0.97 (0.91–1.03)
0.317
0.995 (0.93–1.06)
0.874
1.04 (1.00–1.08)
0.087
1.05 (1.01–1.10)
0.024
TG (1 mg/dL)d
1.28 (0.91–1.80)
0.159
1.12 (0.76–1.65)
0.559
1.94 (1.45–2.60)
\0.001
1.59 (1.14–2.20)
0.006
HDL-C (10 mg/dL)
0.93 (0.80–1.08)
0.320
0.99 (0.84–1.16)
0.871
0.85 (0.75–0.97)
0.013
0.90 (0.78–1.03)
0.123
LDL-C (10 mg/dL)
0.96 (0.90–1.02)
0.180
0.98 (0.92–1.05)
0.570
1.03 (0.98–1.08)
0.311
1.06 (1.01–1.12)
0.033
Non-HDL-C (10 mg/dL)
0.98 (0.92–1.04)
0.493
0.996 (0.93–1.07)
0.913
1.05 (1.01–1.10)
0.014
1.06 (1.02–1.11)
0.009
TC/HDL-C
1.02 (0.84–1.25)
0.839
0.98 (0.79–1.23)
0.887
1.18 (1.04–1.35)
0.009
1.18 (1.02–1.36)
0.029
TG/HDL-Cd
1.37 (0.90–2.09)
0.146
1.09 (0.67–1.77)
0.734
1.96 (1.44–2.68)
\0.001
1.60 (1.12–2.27)
0.010
LDL-C/HDL-C
0.96 (0.76–1.23)
0.829
0.94 (0.72–1.22)
0.632
1.16 (0.97–1.39)
0.102
1.24 (1.01–1.52)
0.037
OR, odd ratio; CI, confidence interval; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol a
Adjusted for age
b
Adjusted for age, body mass index, alcohol consumption, smoking status, physical activity, and hypertension in men
c
Adjusted for age, body mass index, alcohol consumption, smoking status, physical activity, hypertension, and menopause in women
d
Log transformation was performed to obtain OR, 95 % CI, and P values
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presented in patients with nephrotic syndrome have been reported to be mediated by enhanced activity of cholesterol ester transfer protein and increased concentrations of TGrich very low-density lipoproteins [38]. This mechanism may also explain the relationship between lipid abnormalities and elevated UAE. Gender differences in the relationship between dyslipidemia parameters and increased UAE were observed in the current study; however, the reason is not clear due to the cross-sectional nature of this study. Lipid abnormalities seem to contribute more to elevated UAE in women, since the effects of other factors including obesity or testosterone levels are less predominant in them than in men. Inflammation may be a common denominator between abnormal lipid metabolism and albuminuria. A study on a Chinese population showed that C-reactive protein, which is a wellknown inflammatory marker is more strongly associated with metabolic syndrome in women, which is similar to our findings [39]. Sex hormones are also likely to be involved in the underlying mechanism. Higher estrogen levels might be associated with higher serum levels of inflammatory markers such as soluble CD40 ligand which has been implicated in inflammatory processes related to atherosclerotic CVD [40]. Additional studies are necessary to elucidate the mechanism linking dyslipidemia and albuminuria with gender differences. This study has certain limitations. First, the cross-sectional design cannot be used to deduce the causal relationship between lipid abnormalities and elevated UAE. Second, UACR was measured from a single-spot urine sample and this could result in an incorrect classification of albuminuria. Third, the specific types of anti-hypertensive medication that may influence albuminuria or renal function were not considered, since a self-reported questionnaire was used to report drug use. Despite these limitations, our study presents epidemiological evidence from a large population-based study using nationally representative data reflecting a single ethnicity. The study also assessed various parameters of lipid abnormalities including non-HDLC and lipid-related ratios. In conclusion, a higher prevalence of several lipid abnormalities and mixed dyslipidemia was found in prediabetic women with albuminuria. Higher levels of TG, non-HDL-C, and TC/HDL-C ratio, and lower levels of HDL-C were significantly associated with the increased risk of albuminuria in prediabetic women. Identification of lipid abnormalities may be helpful for prediabetic subjects with increased UAE, given that albuminuria is strongly associated with the risk of adverse outcomes during prediabetes. Acknowledgments We greatly appreciate the participants in the Korea National Health and Nutrition Examination Survey 2011-2012.
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Conflict of interest The authors declare that they have no conflict of interest or funding source.
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