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. 2016 Apr 22;95(16):e3224. doi: 10.1097/MD.0000000000003224

Relationship Between Dyslipidemia and Albuminuria in Hypertensive Adults

A Nationwide Population-Based Study

Sung-Ho Lee 1, Do Hoon Kim 1, Yang-Hyun Kim 1, Yong Kyun Roh 1, Sang Yhun Ju 1, Hyo-Yun Nam 1, Ga-Eun Nam 1, Jun-Seok Choi 1, Jong-Eun Lee 1, Jung-Eun Sang 1, Kyungdo Han 1, Yong-Gyu Park 1
Editor: Erika Boesen1
PMCID: PMC4845816  PMID: 27100412

Abstract

This study aimed to estimate the relationship between various lipid abnormalities and albuminuria in hypertensive Korean adults. Data obtained from the Korea National Health and Nutrition Examination Survey in 2011 to 2012 were analyzed. The study included 2330 hypertensive participants. Total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were measured. Dyslipidemia parameters were defined as high TG ≥200 mg/dL, low HDL-C as HDL-C <40 mg/dL, high TC/HDL-C as TC/HDL-C ratio ≥4, high TG/HDL-C as TG/HDL-C ratio ≥3.8, and high LDL-C/HDL-C as LDL-C/HDL-C ratio ≥2.5. Albuminuria was defined as a urine albumin to creatinine ratio (ACR) ≥30 mg/g. Women with albuminuria showed significantly higher levels of TG, TC/HDL-C, and TG/HDL-C and a lower level of HDL-C than women without albuminuria (all P < 0.05). LogTG, TC/HDL-C, and logTG/HDL-C were positively correlated with ACR in both men and women; however, HDL-C was negatively correlated with ACR in women and non-HDL-C was positively correlated with ACR in men. In men, there was no association between ACR and lipid parameters. However, in women, higher values for logTG, TC/HDL-C, and logTG/HDL-C were associated with an increased odds ratio (OR) for albuminuria (OR [95% confidence interval]: 1.53 [1.06–2.21], 1.21 [1.02–1.45], and 1.78 [1.21–2.63], respectively) and HDL-C with a decreased OR for albuminuria (0.78 [0.67–0.92]) after adjusting for all covariates. LogTG, TC/HDL-C, and logTG/HDL-C were associated with an increased prevalence of albuminuria in hypertensive women. Screening and treatment for dyslipidemia may be necessary for hypertensive women to address potential albuminuria.

INTRODUCTION

For decades, many countries have attempted to reduce cardiovascular risk factors such as hypertension (HTN), diabetes mellitus (DM), and dyslipidemia.1–3 HTN is a major preventable risk factor for cardiovascular disease (CVD) and one of the leading causes of mortality and morbidity. Albuminuria is also a risk factor for CVD, and excess urinary albumin is related to increased all-cause mortality.4,5 In patients with HTN, urinary albumin leakage has been used as a marker of cardiovascular complications and a reliable predictor of ischemic heart disease.6,7

Many studies have shown a positive relationship between HTN and albuminuria.8–13 High blood pressure seems to affect urinary albumin excretion via general vascular damage, such as endothelial dysfunction and atherosclerosis,14 and directly via elevated glomerular pressure in the kidney.15,16 Subsequently, HTN leads to an increase in the occurrence of CVD and accelerates the deterioration of renal function.17,18 Dyslipidemia, which is associated with the atherosclerotic process, is also a major preventable risk factor for CVD.19,20 It has generally been defined as elevated levels of total cholesterol (TC), triglyceride (TG), and low-density lipoprotein cholesterol (LDL-C), or low levels of high-density lipoprotein cholesterol (HDL-C).21 Recently, fasting TG was found to independently predict both coronary artery calcification and incidental albuminuria in type 1 diabetes,22 and nonhigh density lipoprotein cholesterol (non-HDL-C) levels and lipid-related ratios were found to be more predictive of CVD than an individual lipid profile.23,24 Furthermore, abnormal lipid parameters are associated with albuminuria or reduced kidney function.25 There was a Korean study on the relationship between TG/HDL-C and albuminuria in hypertensive subjects; however, they only included subjects who were >40 years and resided in rural areas.26

We hypothesized that the comorbidity of dyslipidemia and HTN could exacerbate albuminuria. Therefore, we investigated the relationship between various dyslipidemia parameters and albuminuria in Korean adults with HTN.

METHODS

Survey Overview and Study Participants

This study used the data obtained from the Korea National Health and Nutrition Examination Survey (KNHANES) of 2011 to 2012, which was conducted by the Korean Center for Disease Control for Health Statistics. The survey was designed to evaluate nationwide health and nutrition status, and it comprised a health interview, nutritional assessment, and health examination. A stratified, multistage, cluster-sampling design with proportional allocation based on geographic area, sex, and age from the National Census Registry was used for the selection of survey participants to represent the entire noninstitutionalized civilian population in South Korea. A total of 16,576 participants were included in the KNHANES of 2011 to 2012. Of these, 14,246 individuals were excluded for the following reasons: <19 years of age (3717), missing data (2423), cancer (53), estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 (133), DM (808), or lacking HTN (7112). Finally, 2330 patients who had HTN or take antihypertensive medications were included in this study. All participants provided written informed consent, and the Institutional Review Board of the Division of Chronic Disease Surveillance under the Korea Centers for Disease Control and Prevention approved the study protocol.

Lifestyle Variables

The sociodemographic and lifestyle factors were considered confounding variables, including age, smoking, alcohol drinking, physical activity, and menopause status. Self-report questionnaires were adapted to survey smoking, alcohol consumption, and physical activity. Heavy drinkers were defined as those who drank >30 g/day of alcohol according to the amount of alcohol consumption per day up to 1 month before the interview. Current smokers were defined as those who currently smoked and had smoked >100 cigarettes. We assessed physical activity by means of the modified short form of International Physical Activity Questionnaire for the Korean population.27 Regular physical exercise was defined as moderate exercise for >30 minutes per session more than 5 times/week or vigorous exercise for >20 minutes per session more than 3 times/week.

Anthropometric and Biochemical Measurements

We measured body weight, height, and waist circumference (WC) to the nearest 0.1 kg, 0.1 cm, and 0.1 cm, respectively. Body mass index was estimated as follows: body weight/height2 (kg/m2). WC was measured on the mid-axillary line between the upper margin of the iliac crest and the lower border of the rib cage during expiration. We used a standard mercury sphygmomanometer (Baumanometer, WA Baum Co., NY) to measure blood pressure (BP) and checked BP 3 times in 5-minute intervals in a sitting position. The mean of the 2nd and 3rd BP was used in final analyses. HTN was defined by systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg, or use of anti-HTN drugs. Blood samples were acquired after fasting for at least 8 hours. A Hitachi Automatic Analyzer 7600 (Hitachi, Tokyo, Japan) was used to measure serum levels of creatinine, TC, HDL-C, LDL-C, and TG. A 1470 Wizard gamma-counter (Perkin-Elmer, Turku, Finland) with an immunoradiometric assay using an INS-IRMA kit (Biosource Europe SA, Nivelles, Belgium) was adapted to assess fasting serum insulin levels.

Nutritional Assessment

Daily food intake was evaluated using the 24-hour recall method and a food frequency questionnaire. Daily intake of total energy and fat were estimated using a food database developed for the KNHANES and the food composition table published by the National Rural Living Science Institute.

Definition of Albuminuria and eGFR

The urine albumin to creatinine ratio (ACR) was used as the index of urinary albumin excretion. A urine sample was collected during the first morning voiding. Conventionally, subjects with ACR < 30 mg/g were defined as having normal albuminuria. Microalbuminuria was defined as 30 ≤ ACR < 300 mg/g and macroalbuminuria as ACR ≥ 300 mg/g.28,29 According to this definition of albuminuria, hypertensive subjects with urinary ACR less than 30 mg/g were considered the normal group and subjects with a urinary ACR of 30 mg/g or more as the albuminuria group. We calculated eGFR by Modification of Diet in Renal Disease (MDRD) equation.30

Definition of Dyslipidemia Parameters

We defined the dyslipidemia parameters according to the criteria of the National Cholesterol Education Program Adult Treatment Panel III:31 high TC, TC level ≥240 mg/dL, or the use of lipid-lowering drugs; high TG, TG levels ≥200 mg/dL; and low HDL-C, HDL-C level <40 mg/dL. Additionally, we defined high non-HDL-C (non-HDL-C ≥ 160 mg/dL), high TC to HDL-C ratio (TC/HDL-C ≥ 4), high TG to HDL-C ratio (TG/HDL-C ≥ 3.8), and high LDL-C to HDL-C ratio (LDL-C/HDL-C ≥ 2.5) as abnormal dyslipidemia parameters.32,33

Statistical Analysis

Statistical analysis was performed using the SAS survey procedure using sampling weights to provide nationally representative estimates. P values <0.05 were considered statistically significant. The SAS software package version 9.2 for Windows (SAS institute, Cary, NC) was used. To assess the differences in the baseline clinical and biochemical characteristics between the normal and the albuminuria groups, Student t tests were used to compare continuous variables and Chi-squared tests were used to compare categorical variables. Since the variables such as TG and TG/HDL-C were right-skewed, we used the natural log transformation on TG/HDL-C after evaluating for normality by Q–Q plot. Pearson correlation analysis was performed to assess the correlation between urinary ACR and various dyslipidemia parameters. Age- and multivariable-adjusted logistic regression analyses were conducted to evaluate the odds ratios (ORs) and 95% confidence intervals (CIs) for albuminuria according to increases in dyslipidemia parameters. Age, body mass index, alcohol consumption, smoking status, physical activity, total energy intake, fat intake, use of lipid or BP-lowering drugs, and menopause status (in analyses of women) were considered confounding factors34–36 in the multivariate analyses.

RESULTS

Baseline Characteristics of the Subjects

Men with albuminuria were older and had an increased proportion of subjects with a lower income (Q1) than men without albuminuria. In men, all lipid parameters did not differ between the 2 groups. WC, systolic blood pressure, TG, TC/HDL-C, and TG/HDL-C were significantly higher in women with albuminuria than women without albuminuria. However, HDL-C and current smoking were lower in women with albuminuria compared to women without albuminuria (Table 1).

TABLE 1.

General Characteristics of Subjects With and Without Albuminuria

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Correlation Between ACR and Dyslipidemia Parameters

In men, ACR had a significant positive correlation with logTG, non-HDL-C, TC/HDL-C, and logTG/HDL-C. In women, ACR also had a positive correlation with logTG, TC/HDL-C, and logTG/HDL-C. However, HDL-C was negatively correlated with ACR in women (Table 2).

TABLE 2.

The Correlation Between ACR and Dyslipidemia Parameters in Men and Women

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Prevalence of Dyslipidemia Parameters and Urinary Albumin Excretion

Figure 1 shows the proportion of subjects who satisfied the diagnostic criteria for each dyslipidemia parameter in men and women, categorized by ACR. In men, the prevalence of all dyslipidemia parameters did not differ significantly between the 2 groups (Figure 1A). However, in women, the prevalence of low HDL-C, high TG, high TC/HDL-C, high TG/HDL-C, and high LDL-C/HDL-C were significantly elevated in women with albuminuria compared to women without albuminuria (Figure 1B).

FIGURE 1.

FIGURE 1

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The prevalence of dyslipidemia parameters in hypertensive adults with ACR < 30 mg/g or ACR ≥ 30 mg/g. ∗P value < 0.05. ACR = albumin to creatinine ratio, HDL-C = high-density lipoprotein cholesterol, LDL-C = low-density lipoprotein cholesterol, non-HDL-C = nonhigh density lipoprotein cholesterol, TC = total cholesterol, TG = triglycerides.

Multivariable-Adjusted ORs and 95% CIs for Albuminuria According to the Increase in the Dyslipidemia Parameters

In men, ACR was not associated with any lipid parameters after adjusting for all covariates. In women, increases in logTG, TC/HDL-C, and logTG/HDL-C were associated with elevated ORs for albuminuria after adjusting for all covariates (OR [95% CI]: 1.53 [1.06–2.21], 1.21 [1.02–1.45], and 1.78 [1.21–2.63], respectively). However, HDL-C was associated with a decreased OR for albuminuria in women after adjusting for all covariates (0.78 [0.67–0.92]) (Table 3).

TABLE 3.

Multivariable-Adjusted ORs and 95% CIs for Albuminuria According to the Increase in Dyslipidemia Parameters in Men and Women

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DISCUSSION

In this study, logTG, TC/HDL-C, and logTG/HDL-C were weak, but positively correlated with ACR in men and women. However, non-HDL-C was also weak, but positively correlated with ACR in men and HDL-C was negatively correlated with ACR in women. The prevalence of high TG, high TG/HDL-C, high TC/HDL-C, and high LDL-C/HDL-C were significantly elevated in women with albuminuria compared to women without albuminuria. LogTG, TC/HDL-C, and logTG/HDL-C were associated with elevated ORs for albuminuria, and HDL-C was associated with a decreased OR for albuminuria only in women.

Although abnormal lipid values predicted the progression of kidney function in some cohort studies,37–39 the relationship between dyslipidemia and albuminuria is controversial. Some studies found that high TG was associated with ACR in patients with DM.40–42 In the Framingham Offspring cohort study, HDL-C was negatively associated with ACR.43 In a community-based Korean population study, microalbuminuria was also associated with high TG and low HDL-C, but not with TC and LDL-C.44 However, in the Third National Health and Nutrition Examination Survey (NHANES III), microalbuminuria was associated with increased TC and LDL-C, but not HDL-C.45 Aside from these conventional lipid parameters, recent studies have found that high TG/HDL-C, or the atherogenic index, is associated with the presence of small dense LDL-C,46 which is associated with an increased risk for cardiovascular events in many studies.47–49 Small dense LDL-C can penetrate the arterial wall more easily and is susceptible to oxidization compared to large LDL-C.50,51 Some Asian studies have found a relationship between the TG/HDL-C and nephropathy in prediabetic patients or those with DM.52,53 High TG and low HDL-C were also associated with ACR, and small dense LDL-C was associated with increased ACR in the general population.54

TG/HDL-C reflects not only atherogenic dyslipidemia, but also insulin resistance,55 which is also associated with abdominal obesity.56 Since albuminuria itself is also associated with abdominal obesity,57 insulin resistance may explain the association between TG/HDL-C and albuminuria.

Previous studies have already found the association between dyslipidemia, especially TG/HDL-C, and albuminuria in Chinese and Korean subjects.26,58 In both studies, the subjects were limited to ages more than 40 and living in rural area, whereas our representative sample of Korean population were aged more than 18 and had HTN. Unlike aforementioned studies, Japanese population study showed that TG/HDL-C was associated with albuminuria not only in the subjects with HTN but also without HTN.59 These results indicate that dyslipidemic features such as high TG/HDL-C level may deteriorate kidney function by means of eGFR and albuminuria.

Moreover, the association between the TG/HDL-C ratio and the risk of mortality was abolished after additional adjustment for renal function measures (eGFR and albuminuria) in an Italian cohort study.60 This indicates that the prediction of cardiovascular and all-cause mortality by TG/HDL-C might be largely influenced by the status of kidney dysfunction in type 2 DM.

Abnormal lipid profiles, such as high TC and high TG, could cause tubulointerstitial damage via the infiltration and deposition of fat in the renal tubules25 and may also develop in association with inflammation in the vessel walls.61–63 Additionally, abnormal lipid metabolism could cause increased urine albumin excretion and renal dysfunction via the acceleration of renovascular atherosclerosis. In hypertensive patients, the direct transmission of pulsatile stress to the glomeruli contributes to glomerular damage and arterial atherosclerotic changes.15,64,65 Therefore, hypertensive patients with dyslipidemia may have a higher ACR than those without dyslipidemia.

Similar to the current study, some studies have shown gender differences in the relationship between albuminuria and dyslipidemia.53,54 Although the reason for this is not clear, some studies suggest that the gender differences are due to the favorable lipoprotein profile more commonly seen in women, including less small dense LDL-C and higher HDL-C, compared with men.66,67 As other factors such as testosterone levels and visceral fat are less dominant in women compared to men, abnormalities in the lipid profile due to hormonal or metabolic changes could have a greater influence on the development of albuminuria in women than in men.54

There are some limitations in this study. First, this is a cross-sectional study, so it does not show causal relationships. Second, only the morning urine sample was measured to evaluate albuminuria. Indeed, a 24-hour urine collection is the most exact urine sampling method for evaluating albuminuria. However, a single morning urine sample is known to correlate with the 24-hour urine albumin excretion ratio.68 Since the morning urine sample after fasting is more concentrated than other urine samples collected at other times, it could mislead the diagnosis of microalbuminuria. Third, the specific types of antihypertensive medication that may influence albuminuria or renal function, such as angiotensin converting enzyme inhibitors or angiotensin II receptor blockers, were not considered because a self-report questionnaire was used to assess drug use. Forth, the adjustment of lipid lowering drugs remains controversial. We adjusted the use of lipid lowering drug in model 2 of Table 3, based on the result of a meta-analysis that there was a modest reduction of proteinuria in the subjects with statin therapy.69 However, in the 2 recent meta-analyses, the lipid-lowering therapy with statin did not improve kidney outcomes such as proteinuria in the subjects with chronic kidney disease.70,71

Despite these limitations, this study has several strengths. This study showed epidemiological evidence from a large population-based study using nationally representative data reflecting a single ethnicity. To the best of our knowledge, this is the 1st study to examine the relationship between albuminuria and dyslipidemia in hypertensive subjects using a traditional lipid profile and an atherogenic lipid profile including TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, and non-HDL-C in South Korean individuals.

In conclusion, higher levels of TG, TG/HDL-C, and TC/HDL-C and lower levels of HDL-C were significantly associated with increased adjusted ORs for albuminuria in hypertensive women. Physicians should consider the lipid profile of patients with albuminuria, especially hypertensive women. Further prospective studies are needed to evaluate the causal relationship and mechanism of the association between dyslipidemia and albuminuria in hypertensive patients.

Acknowledgments

The authors thank the participants of this study for their dedication.

Footnotes

Abbreviations: ACR = albumin to creatinine ratio, CI = confidence interval, CVD = cardiovascular disease, DM = diabetes mellitus, HDL-C = high-density lipoprotein cholesterol, HTN = hypertension, KNHANES = Korea National Health and Nutrition Examination Survey, LDL-C = low-density lipoprotein cholesterol, Non-HDL-C = nonhigh density lipoprotein cholesterol, OR = odds ratio, TC = total cholesterol, TG = triglyceride, WC = waist circumference.

D HK and Y-HK contributed equally to this work.

The authors have no funding conflicts of interest to disclose.

REFERENCES

  • 1.Deaton C, Froelicher ES, Wu LH, et al. The global burden of cardiovascular disease. J Cardiovasc Nurs 2011; 26:S5–S14. [DOI] [PubMed] [Google Scholar]
  • 2.Chobanian AV, Bakris GL, Black HR, et al. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension 2003; 42:1206–1252. [DOI] [PubMed] [Google Scholar]
  • 3.Lawes CM, Rodgers A, Bennett DA, et al. Blood pressure and cardiovascular disease in the Asia Pacific region. J Hypertens 2003; 21:707–716. [DOI] [PubMed] [Google Scholar]
  • 4.Roest M, Banga JD, Janssen WM, et al. Excessive urinary albumin levels are associated with future cardiovascular mortality in postmenopausal women. Circulation 2001; 103:3057–3061. [DOI] [PubMed] [Google Scholar]
  • 5.Yuyun MF, Khaw KT, Luben R, et al. Microalbuminuria independently predicts all-cause and cardiovascular mortality in a British population: The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) population study. Int J Epidemiol 2004; 33:189–198. [DOI] [PubMed] [Google Scholar]
  • 6.Jensen JS, Feldt-Rasmussen B, Strandgaard S, et al. Arterial hypertension, microalbuminuria, and risk of ischemic heart disease. Hypertension 2000; 35:898–903. [DOI] [PubMed] [Google Scholar]
  • 7.Karalliedde J, Viberti G. Microalbuminuria and cardiovascular risk. Am J Hypertens 2004; 17:986–993. [DOI] [PubMed] [Google Scholar]
  • 8.Flack JM, Duncan K, Ohmit SE, et al. Influence of albuminuria and glomerular filtration rate on blood pressure response to antihypertensive drug therapy. Vasc Health Risk Manag 2007; 3:1029–1037. [PMC free article] [PubMed] [Google Scholar]
  • 9.Liu X, Wang K, Wang L, et al. Microalbuminuria, macroalbuminuria and uncontrolled blood pressure among diagnosed hypertensive patients: the aspect of racial disparity in the NHANES study. Hypertens Res 2013; 36:1100–1106. [DOI] [PubMed] [Google Scholar]
  • 10.Ong KL, Tso AW, Lam KS, et al. Gender difference in blood pressure control and cardiovascular risk factors in Americans with diagnosed hypertension. Hypertension 2008; 51:1142–1148. [DOI] [PubMed] [Google Scholar]
  • 11.Bianchi S, Bigazzi R, Campese VM. Microalbuminuria in essential hypertension: significance, pathophysiology, and therapeutic implications. Am J Kidney Dis 1999; 34:973–995. [DOI] [PubMed] [Google Scholar]
  • 12.Knight EL, Kramer HM, Curhan GC. High-normal blood pressure and microalbuminuria. Am J Kidney Dis 2003; 41:588–595. [DOI] [PubMed] [Google Scholar]
  • 13.Tanaka S, Takase H, Dohi Y, et al. The prevalence and characteristics of microalbuminuria in the general population: a cross-sectional study. BMC Res Notes 2013; 6:256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Deckert T, Feldt-Rasmussen B, Borch-Johnsen K, et al. Albuminuria reflects widespread vascular damage. The Steno hypothesis. Diabetologia 1989; 32:219–226. [DOI] [PubMed] [Google Scholar]
  • 15.Deen WM. What determines glomerular capillary permeability? J Clin Invest 2004; 114:1412–1414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Williams SA, Boolell M, MacGregor GA, et al. Capillary hypertension and abnormal pressure dynamics in patients with essential hypertension. Clin Sci (Lond) 1990; 79:5–8. [DOI] [PubMed] [Google Scholar]
  • 17.Kidney Disease Outcomes Quality Initiative Clinical practice guidelines on hypertension and antihypertensive agents in chronic kidney disease. Am J Kidney Dis 2004; 43:S1–S290. [PubMed] [Google Scholar]
  • 18.Choi HJ. Blood pressure variability and its management in hypertensive patients. Korean J Fam Med 2012; 33:330–335. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Lee MH, Kim HC, Ahn SV, et al. Prevalence of dyslipidemia among Korean adults: Korea National Health and Nutrition Survey 1998–2005. Diabetes Metab J 2012; 36:43–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Habib AN, Baird BC, Leypoldt JK, et al. The association of lipid levels with mortality in patients on chronic peritoneal dialysis. Nephrol Dial Transplant 2006; 21:2881–2892. [DOI] [PubMed] [Google Scholar]
  • 21.Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA 2001; 285:2486–2497. [DOI] [PubMed] [Google Scholar]
  • 22.Bjornstad P, Maahs DM, Wadwa RP, et al. Plasma triglycerides predict incident albuminuria and progression of coronary artery calcification in adults with type 1 diabetes: the Coronary Artery Calcification in Type 1 Diabetes Study. J Clin Lipidol 2014; 8:576–583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Boekholdt SM, Arsenault BJ, Mora S, et al. Association of LDL cholesterol, non-HDL cholesterol, and apolipoprotein B levels with risk of cardiovascular events among patients treated with statins: a meta-analysis. JAMA 2012; 307:1302–1309. [DOI] [PubMed] [Google Scholar]
  • 24.Barzi F, Patel A, Woodward M, et al. A comparison of lipid variables as predictors of cardiovascular disease in the Asia Pacific region. Ann Epidemiol 2005; 15:405–413. [DOI] [PubMed] [Google Scholar]
  • 25.Weinberg JM. Lipotoxicity. Kidney Int 2006; 70:1560–1566. [DOI] [PubMed] [Google Scholar]
  • 26.Kang HT, Kim JK, Kim JY, et al. Independent association of TG/HDL-C with urinary albumin excretion in normotensive subjects in a rural Korean population. Clin Chim Acta 2012; 413:319–324. [DOI] [PubMed] [Google Scholar]
  • 27.Hagstromer M, Oja P, Sjostrom M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr 2006; 9:755–762. [DOI] [PubMed] [Google Scholar]
  • 28.Mogensen CE, Chachati A, Christensen CK, et al. Microalbuminuria: an early marker of renal involvement in diabetes. Uremia Invest 1985; 9:85–95. [DOI] [PubMed] [Google Scholar]
  • 29.Eknoyan G, Hostetter T, Bakris GL, et al. Proteinuria and other markers of chronic kidney disease: a position statement of the national kidney foundation (NKF) and the national institute of diabetes and digestive and kidney diseases (NIDDK). Am J Kidney Dis 2003; 42:617–622. [DOI] [PubMed] [Google Scholar]
  • 30.Levey AS, Bosch JP, Lewis JB, et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999; 130:461–470. [DOI] [PubMed] [Google Scholar]
  • 31.Expert Panel on Detection E, Treatment of High Blood Cholesterol in A. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA 2001; 285:2486–2497. [DOI] [PubMed] [Google Scholar]
  • 32.Natarajan S, Glick H, Criqui M, et al. Cholesterol measures to identify and treat individuals at risk for coronary heart disease. Am J Prev Med 2003; 25:50–57. [DOI] [PubMed] [Google Scholar]
  • 33.Hanak V, Munoz J, Teague J, et al. Accuracy of the triglyceride to high-density lipoprotein cholesterol ratio for prediction of the low-density lipoprotein phenotype B. Am J Cardiol 2004; 94:219–222. [DOI] [PubMed] [Google Scholar]
  • 34.Chen F, Yang W, Weng J, et al. Albuminuria: prevalence, associated risk factors and relationship with cardiovascular disease. J Diabetes Investig 2014; 5:464–471. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Gutierrez-Repiso C, Rojo-Martinez G, Soriguer F, et al. Factors affecting levels of urinary albumin excretion in the general population of Spain: the Di@bet.es study. Clin Sci (Lond) 2013; 124:269–277. [DOI] [PubMed] [Google Scholar]
  • 36.Li D, Hou X, Ma X, et al. Association between an increment of 30-minute postchallenge plasma glucose and urine albumin excretion exists in postmenopausal women but not in premenopausal women. Menopause 2011; 18:1303–1308. [DOI] [PubMed] [Google Scholar]
  • 37.Muntner P, Coresh J, Smith JC, et al. Plasma lipids and risk of developing renal dysfunction: the atherosclerosis risk in communities study. Kidney Int 2000; 58:293–301. [DOI] [PubMed] [Google Scholar]
  • 38.Kurella M, Lo JC, Chertow GM. Metabolic syndrome and the risk for chronic kidney disease among nondiabetic adults. J Am Soc Nephrol 2005; 16:2134–2140. [DOI] [PubMed] [Google Scholar]
  • 39.Molitch ME, Rupp D, Carnethon M. Higher levels of HDL cholesterol are associated with a decreased likelihood of albuminuria in patients with long-standing type 1 diabetes. Diabetes Care 2006; 29:78–82. [DOI] [PubMed] [Google Scholar]
  • 40.Penno G, Solini A, Zoppini G, et al. Hypertriglyceridemia is independently associated with renal, but not retinal complications in subjects with type 2 diabetes: a cross-sectional analysis of the Renal Insufficiency and Cardiovascular Events (RIACE) Italian Multicenter Study. PLoS One 2015; 10:e0125512. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Tolonen N, Forsblom C, Thorn L, et al. Lipid abnormalities predict progression of renal disease in patients with type 1 diabetes. Diabetologia 2009; 52:2522–2530. [DOI] [PubMed] [Google Scholar]
  • 42.Tien KJ, Tu ST, Chen HC, et al. Triglycerides are independently associated with albuminuria in Taiwanese Type 2 diabetic patients. J Endocrinol Invest 2012; 35:800–803. [DOI] [PubMed] [Google Scholar]
  • 43.O'Seaghdha CM, Hwang SJ, Upadhyay A, et al. Predictors of incident albuminuria in the Framingham Offspring cohort. Am J Kidney Dis 2010; 56:852–860. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Kim YI, Kim CH, Choi CS, et al. Microalbuminuria is associated with the insulin resistance syndrome independent of hypertension and type 2 diabetes in the Korean population. Diabetes Res Clin Pract 2001; 52:145–152. [DOI] [PubMed] [Google Scholar]
  • 45.Shankar A, Klein R, Moss SE, et al. The relationship between albuminuria and hypercholesterolemia. J Nephrol 2004; 17:658–665. [PubMed] [Google Scholar]
  • 46.Jia L, Long S, Fu M, et al. Relationship between total cholesterol/high-density lipoprotein cholesterol ratio, triglyceride/high-density lipoprotein cholesterol ratio, and high-density lipoprotein subclasses. Metabolism 2006; 55:1141–1148. [DOI] [PubMed] [Google Scholar]
  • 47.Kuller L, Arnold A, Tracy R, et al. Nuclear magnetic resonance spectroscopy of lipoproteins and risk of coronary heart disease in the cardiovascular health study. Arterioscler Thromb Vasc Biol 2002; 22:1175–1180. [DOI] [PubMed] [Google Scholar]
  • 48.Otvos JD, Collins D, Freedman DS, et al. Low-density lipoprotein and high-density lipoprotein particle subclasses predict coronary events and are favorably changed by gemfibrozil therapy in the Veterans Affairs High-Density Lipoprotein Intervention Trial. Circulation 2006; 113:1556–1563. [DOI] [PubMed] [Google Scholar]
  • 49.Blake GJ, Otvos JD, Rifai N, et al. Low-density lipoprotein particle concentration and size as determined by nuclear magnetic resonance spectroscopy as predictors of cardiovascular disease in women. Circulation 2002; 106:1930–1937. [DOI] [PubMed] [Google Scholar]
  • 50.Bjornheden T, Babyi A, Bondjers G, et al. Accumulation of lipoprotein fractions and subfractions in the arterial wall, determined in an in vitro perfusion system. Atherosclerosis 1996; 123:43–56. [DOI] [PubMed] [Google Scholar]
  • 51.Tribble DL, Holl LG, Wood PD, et al. Variations in oxidative susceptibility among six low density lipoprotein subfractions of differing density and particle size. Atherosclerosis 1992; 93:189–199. [DOI] [PubMed] [Google Scholar]
  • 52.Lee IT, Wang CY, Huang CN, et al. High triglyceride-to-HDL cholesterol ratio associated with albuminuria in type 2 diabetic subjects. J Diabetes Complications 2013; 27:243–247. [DOI] [PubMed] [Google Scholar]
  • 53.Nam GE, Han K, Kim do H, et al. Relationship between dyslipidemia and albuminuria in prediabetic adults: the Korea National Health and Nutrition Examination Survey 2011–2012. Endocrine 2015; 48:557–565. [DOI] [PubMed] [Google Scholar]
  • 54.de Boer IH, Astor BC, Kramer H, et al. Mild elevations of urine albumin excretion are associated with atherogenic lipoprotein abnormalities in the Multi-Ethnic Study of Atherosclerosis (MESA). Atherosclerosis 2008; 197:407–414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.McLaughlin T, Abbasi F, Cheal K, et al. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med 2003; 139:802–809. [DOI] [PubMed] [Google Scholar]
  • 56.Michaud A, Laforest S, Pelletier M, et al. Abdominal adipocyte populations in women with visceral obesity. Eur J Endocrinol 2016; 174:227–239. [DOI] [PubMed] [Google Scholar]
  • 57.Nam GE, Han K, Park YG, et al. Abdominal obesity is associated with albuminuria in women: the 2011 Korea National Health and Nutrition Examination Survey. J Womens Health (Larchmt) 2014; 23:267–274. [DOI] [PubMed] [Google Scholar]
  • 58.Sun K, Lin D, Li F, et al. Discordant associations of lipid parameters with albuminuria and chronic kidney disease: a population-based study. Lipids Health Dis 2015; 14:152. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Tsuruya K, Yoshida H, Nagata M, et al. Association of the triglycerides to high-density lipoprotein cholesterol ratio with the risk of chronic kidney disease: analysis in a large Japanese population. Atherosclerosis 2014; 233:260–267. [DOI] [PubMed] [Google Scholar]
  • 60.Zoppini G, Targher G, Negri C, et al. Usefulness of the triglyceride to high-density lipoprotein cholesterol ratio for predicting mortality risk in type 2 diabetes: role of kidney dysfunction. Atherosclerosis 2010; 212:287–291. [DOI] [PubMed] [Google Scholar]
  • 61.Abrass CK. Cellular lipid metabolism and the role of lipids in progressive renal disease. Am J Nephrol 2004; 24:46–53. [DOI] [PubMed] [Google Scholar]
  • 62.Stehouwer CD, Smulders YM. Microalbuminuria and risk for cardiovascular disease: analysis of potential mechanisms. J Am Soc Nephrol 2006; 17:2106–2111. [DOI] [PubMed] [Google Scholar]
  • 63.Weir MR. Microalbuminuria and cardiovascular disease. Clin J Am Soc Nephrol 2007; 2:581–590. [DOI] [PubMed] [Google Scholar]
  • 64.O’Rourke MF, Safar ME. Relationship between aortic stiffening and microvascular disease in brain and kidney: cause and logic of therapy. Hypertension 2005; 46:200–204. [DOI] [PubMed] [Google Scholar]
  • 65.Smulyan H, Safar ME. Systolic blood pressure revisited. J Am Coll Cardiol 1997; 29:1407–1413. [DOI] [PubMed] [Google Scholar]
  • 66.Freedman DS, Otvos JD, Jeyarajah EJ, et al. Sex and age differences in lipoprotein subclasses measured by nuclear magnetic resonance spectroscopy: the Framingham Study. Clin Chem 2004; 50:1189–1200. [DOI] [PubMed] [Google Scholar]
  • 67.Pascot A, Lemieux I, Bergeron J, et al. HDL particle size: a marker of the gender difference in the metabolic risk profile. Atherosclerosis 2002; 160:399–406. [DOI] [PubMed] [Google Scholar]
  • 68.Hutchison AS, O’Reilly DS, MacCuish AC. Albumin excretion rate, albumin concentration, and albumin/creatinine ratio compared for screening diabetics for slight albuminuria. Clin Chem 1988; 34:2019–2021. [PubMed] [Google Scholar]
  • 69.Sandhu S, Wiebe N, Fried LF, et al. Statins for improving renal outcomes: a meta-analysis. J Am Soc Nephrol 2006; 17:2006–2016. [DOI] [PubMed] [Google Scholar]
  • 70.Palmer SC, Navaneethan SD, Craig JC, et al. HMG CoA reductase inhibitors (statins) for kidney transplant recipients. Cochrane Database Syst Rev 2014; 1:CD005019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Sanguankeo A, Upala S, Cheungpasitporn W, et al. Effects of statins on renal outcome in chronic kidney disease patients: a systematic review and meta-analysis. PLoS One 2015; 10:e0132970. [DOI] [PMC free article] [PubMed] [Google Scholar]

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