Clin Exp Nephrol DOI 10.1007/s10157-014-0945-6
ORIGINAL ARTICLE
Body mass index and preclinical kidney disease in Indian adults aged 40 years and above without chronic kidney disease Charumathi Sabanayagam • Tien Yin Wong Jiemin Liao • Sunil Sethi • Boon Wee Teo
•
Received: 18 September 2013 / Accepted: 22 January 2014 Ó Japanese Society of Nephrology 2014
Abstract Background Obesity is associated with diabetes and hypertension, two major risk factors for chronic kidney disease (CKD). Recently, it has been shown that obesity is associated with preclinical kidney disease defined by elevated levels of cystatin C among those without CKD in US adults. However, the association of obesity with cystatin C is not known in industrialized Asian populations. Methods We examined 2,052 Indian adults aged 40–80 years in Singapore who were free of CKD defined as a serum creatinine-based estimated glomerular filtration rate (eGFRcr) \60 mL/min/1.73 m2 and/or the presence of microalbuminuria. Body mass index (BMI) values were categorized into normal (18.5–24.9), overweight (25–29.9) and obese (C30 kg/m2). Elevated serum cystatin C was defined as cystatin C C1 mg/L.
Results Overweight and obesity were significantly associated with elevated levels of cystatin C after adjusting for potential confounders including diabetes and hypertension and eGFRcr. Compared to those with normal weight, the odds ratio (95 % confidence interval) of elevated cystatin C was 1.49 (1.17–1.88) for overweight and 3.20 (2.33–4.39) for obese. This association was consistently present when BMI was analyzed as a continuous variable and also in subgroups of men, women and in those without diabetes mellitus or hypertension. Conclusions Higher BMI levels are associated with preclinical kidney disease in Indian adults aged 40 years and above without CKD. Keywords
CKD Cystatin C Indians Overweight
Introduction C. Sabanayagam (&) T. Y. Wong Singapore Eye Research Institute, 11 Third Hospital Avenue, #06-13, SNEC Bldg, Singapore 168751, Singapore e-mail: [email protected] C. Sabanayagam T. Y. Wong Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore, Singapore C. Sabanayagam T. Y. Wong J. Liao Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore S. Sethi Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore B. W. Teo Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Obesity is an emerging public health problem in industrialized Asian countries including Singapore [1], Hong Kong [2], Taiwan [3], and South Korea [4] associated with diabetes, hypertension and cardiovascular disease (CVD) [5].Chronic kidney disease (CKD) [6, 7], defined by serum creatinine-based estimated glomerular filtration rate (eGFRcr) \60 mL/min/1.73 m2 is another emerging public health problem in Asian populations paralleling the rising prevalence of diabetes and hypertension, two of the major risk factors for CKD [8]. Obesity is an established risk factor of CKD in Western populations [6, 9, 10]; however, the association of obesity with CKD has not been consistent in Asian populations with some showing a positive association [11], some with no significant association [12, 13] and some showing a gender-specific association observed only among men [14, 15].
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Serum cystatin C, a cysteine protease inhibitor has recently been included as an alternative marker of CKD by KDIGO [16]. Elevated levels of cystatin C in the preclinical stages of CKD have been shown to be predictive of adverse outcomes including the development of CKD and CVD [16–19]. Two recent studies from the US utilizing data from different cycles of the National Health and Nutritional Examination Survey reported that overweight and obesity are associated with preclinical kidney disease defined by elevated levels of cystatin C among those without CKD [20, 21]. However, the association of obesity with cystatin C is not known in Asian populations. In this context, we examined the association between body mass index (BMI) and preclinical kidney disease in a populationbased sample of Indian adults in Singapore, who were free of CKD.
Methods Study population The present study utilized data from the Singapore Indian Eye Study, a population-based cross-sectional study of 3,400 Indians aged 40–80 years conducted from 2007 to 2009 with detailed methodology reported elsewhere [22]. In brief, from a computer-generated random list of 11,616 Indian names provided by the Ministry of Home Affairs, 6,350 adults were selected by an age-stratified random sampling method. Of the 4,497 eligible participants, 3,400 participated in the study with a response rate of 75.6 %. For the current analysis, we included those with information available on cystatin C measurements (n = 2,919 included). We excluded those with CKD (defined as an eGFRcr of \60 mL/min/1.73 m2 from serum creatinine [8] using the recently developed chronic kidney disease epidemiology collaboration (CKD-EPI) equation [23], n = 192) and/or microalbuminuria (defined as a urinary albumin-to-creatinine ratio C30 mg/g from spot urine sample [8], n = 599). We further excluded those who were underweight (BMI \18.5 kg/m2, n = 49) and those with missing information on variables included in the multivariable model (n = 27). The final sample available for the current analysis was 2,052. Written informed consent was obtained from all participants and the study was approved by the National Healthcare Group and the Singapore Eye Research Institute Institutional Review Boards. Outcome of interest The main outcome of interest in the current study was preclinical kidney disease defined by cystatin C C1 mg/L among those without CKD or microalbuminuria [16–19].
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Standard serum cystatin c assay was performed in a central clinical laboratory accredited by the College of American Pathologists using particle-enhanced turbidimetric assay on the Siemens Advia platform. The CV for cystatin C results was 5.2–6.2 %. Assessment of exposure and covariates Height was measured in centimeters using a wall-mounted measuring tape and weight was measured in kilograms using a digital scale (SECA, model 782 2321009; Vogel & Halke, Germany). BMI was calculated as weight in kilograms divided by the square of height in meters squared (kg/m2). Based on the World Health Organization definition [24], overweight status was defined as a BMI between 25 and 29.9 kg/m2, and obesity as a BMI over 30 kg/m2. Information on participant demographics, educational attainment, personal and medical history was obtained using a standardized questionnaire administered by trained interviewers. Education level was categorized into (1) primary and below (B6 years), (2) secondary (7–10 years) and (3) high school and above (C11 years). Cigarette smoking was categorized into current, former and never smoker and alcohol consumption into drinkers and nondrinkers. BP measurements were taken using a digital automatic blood pressure monitor (Dinamap model Pro Series DP110X-RW, 100V2; GE Medical Systems Information Technologies, Inc., USA) on 2 occasions 5 min apart, after the participants were seated for at least 5 min. If these two BP measurements differed by more than 10 mmHg systolic and 5 mmHg diastolic, a third measurement was taken and the average of the two closest readings was taken as the BP value. 40 mL venous blood was collected to measure serum lipids, creatinine and casual glucose in the non-fasting state. eGFRcr was estimated from serum creatinine using the CKD-EPI equation [23]. Statistical analysis BMI was analyzed both as a categorical and a continuous variable. We examined the association of BMI with elevated cystatin C in two logistic regression models: (1) adjusted for age (years), and sex (men, women), (2) multivariable model additionally adjusted for education (primary and below, secondary and above), smoking status (never, former, current), alcohol consumption (absent, present), diabetes (absent, present), hypertension (absent, present), total cholesterol (mmol/L), and eGFRcr (mL/min/ 1.73 m2). Tests for trend were performed, modeling BMI categories as an ordinal variable in the corresponding multivariable logistic regression models. We also analyzed the association of BMI with elevated cystatin C using BMI
Clin Exp Nephrol
as a continuous variable. To explore further potential nonlinear association between BMI and elevated levels of cystatin C, we used a restricted quadratic spline model with knots at the 10, 50 and 90th percentiles (21.4, 25.8, 31.7 kg/m2) of BMI. To examine the consistency of the association between BMI and cystatin C, we performed subgroup analyses of BMI categories stratified by sex, diabetes and hypertension status. Statistical interaction between the BMI categories and each of the stratifying variables was performed by including cross-product interaction terms in the multivariable models. In supplementary analyses, we repeated the multivariable analyses in Table 2 (1) using quartiles of BMI, and (2) after excluding participants with diabetes, hypertension or self-reported CVD [cystatin C levels were significantly higher among those with self-reported CVD compared to those without, mean (SD) = 1.01 (0.2) vs. 0.94 (0.18), P \ 0.001]. All statistical analyses were performed using STATA version 12.1 (Texas, USA).
Results Table 1 shows the characteristics of the study participants. More than half of the adults were either overweight or Table 1 Baseline characteristics of the study participants Characteristics
n = 2,052
Age (years)
55.9 (9.27)
Women (%)
944 (46.0)
Education categories (%) Primary and below Secondary and above
1,055 (51.4) 997 (48.6)
Discussion
Smoking status (%) Never smoker Past smoker Current smoker Alcohol drinker (%) Diabetes mellitus (%) Hypertension (%)
1,500 (73.1) 217 (10.6) 335 (16.3) 285 (13.9) 536 (26.1) 1,010 (49.2)
Body mass index, kg/m2 (%) \25 25–29.9 C30
850 (41.4) 862 (42.0) 340 (16.6)
Total cholesterol (mmol/L)
5.23 (1.08)
Serum cystatin C (mg/L)
0.95 (0.19)
Serum cystatin C [1 mg/L
670 (32.7)
Data presented are number (%) or mean (SD)
obese. Nearly a third of the adults had cystatin C levels C1 mg/L. 26 % had diabetes and 49 % had hypertension. Table 2 shows the association between BMI and cystatin C in the whole population. 32.7 % of the subjects had elevated cystatin C levels. When BMI was analyzed in categories, a significant graded association was observed between increasing categories of BMI and cystatin C C1 mg/L in both the age, sex-adjusted and the multivariable models (P trend \0.001). This positive association persisted when BMI was analyzed as a continuous variable. The multivariable adjusted OR (95 % CI) of elevated cystatin C was 1.55 (1.39–1.73) per SD (4.74 kg/m2) increase in BMI value. The association between increasing levels of BMI and greater odds of elevated cystatin C was also evident in models based on restricted cubic splines (Fig. 1). In Table 3, we examined the association of BMI categories within subgroups of sex, diabetes and hypertension status. The strong positive association between BMI categories and cystatin C C1 mg/L was consistently present among these subgroups also, and no significant interactions were detected between BMI and any of the stratifying variables (P interaction [0.1 for all stratifying variables). In supplementary analyses, when we repeated the main analysis in Table 2 with quartiles of BMI, the results remain unaltered; compared with quartile of BMI (referent), the multivariable OR (95 % CI) of cystatin C C1 mg/L was 1.14 (0.84–1.55), 1.49 (1.10–2.02) and 2.91 (2.13–3.97) in BMI quartiles 2, 3 and 4. Excluding participants with diabetes, hypertension or self-reported CVD (n = 793 included), the results were essentially similar; compared with persons with normal weight, the multivariable OR (95 % CI) of cystatin C C1 mg/L was 1.63 (1.12–2.37) and 3.84 (2.24–6.60) in overweight and obese categories.
In a large population-based sample of Indian adults without CKD and/or microalbuminuria, we found increasing levels of BMI were significantly associated with elevated cystatin C levels (cystatin C C1 g/L), a marker for preclinical kidney disease independent of potential confounders including diabetes, hypertension, total cholesterol and eGFRcr levels. This association was consistently present when BMI was analyzed as either a categorical or a continuous variable and the association was consistent across subgroups of men, women, and those with and without diabetes or hypertension. To our knowledge, this is the first study showing an association between BMI and preclinical kidney disease in an Asian population where the contribution of BMI to CKD has been shown to be different from Western populations.
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Clin Exp Nephrol Table 2 Association between BMI and elevated serum cystatin C BMI categories Normal weight
Total sample size 850
Elevated cystatin C (%)
Serum cystatin C, mg/L (mean, SD)
Age- and sex-adjusted OR (95 % CI)
Multivariable OR (95 % CI)a
28.5
0.93 (0.19)
1 (Referent)
1 (Referent)
Overweight
862
33.1
0.94 (0.18)
1.52 (1.22–1.90)
1.49 (1.17–1.88)
Obese
340
42.1
0.99 (0.20)
2.71 (2.03–3.61)
3.20 (2.33–4.39)
\0.001
\0.001
2,052
32.7
1.44 (1.31–1.60)
1.55 (1.39–1.73)
P trend One SD (4.74 kg/m2) increase in BMI a
Adjusted for age (years), sex (men, women), education (primary and below, secondary and above), smoking status (never, former, current), alcohol consumption (absent, present), diabetes (absent, present), hypertension (absent, present), total cholesterol (mmol/L), and eGFRcr (mL/ min/1.73 m2)
Fig. 1 Plot of restricted cubic spline model showing the association between body mass index (BMI) and elevated levels of serum cystatin C. Knots specified at 10, 50 and 90th percentiles of BMI (21.4, 25.8, 31.7 kg/m2). Model adjusted for age, sex, education, smoking status, alcohol consumption, diabetes status, hypertension status, total cholesterol, and eGFRcr. X-axis, body mass index (kg/m2). Y-axis, odds ratio and 95 % confidence interval (dotted lines) of elevated cystatin C levels
Serum cystatin C, an alternative marker of GFR has been shown to be a sensitive marker of renal function in early stages of CKD when serum creatinine levels are in the normal range [25–27]. In addition, cystatin C has also been shown to be predictive of adverse clinical outcomes including prediabetes [28, 29], diabetes [30], CVD [18], ESRD and all-cause mortality [31] in the preclinical state of kidney dysfunction that is not detected by serum creatinine-based eGFRcr [32]. In the current study, we found that both overweight and obesity are associated with elevated cystatin C levels among those without CKD or albuminuria. In addition, we found that the association between BMI and cystatin C remained strong after removing those with diabetes, hypertension and CVD. This suggests that higher BMI could contribute to early renal function decline in the absence of diabetes and hypertension. An alternative
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explanation is that overweight and obese people have relatively lower muscle mass resulting in falsely low serum creatinine, which tends to overestimate GFR [33]. However, serum cystatin C-based GFR estimations tend to under-estimate GFR. Therefore, in obese patients, preclinical CKD detection using estimated GFR may be improved using serum cystatin C. Our finding of an association between higher BMI levels and cystatin C is consistent with two previous studies that reported similar associations between BMI and cystatin C in US adults [20, 21] and extends the associations to Asian Indians. Muntner et al. [20] utilizing data from the Third National Health and Nutrition Examination Survey (NHANES-III) in the US reported a positive association between elevated levels of BMI and cystatin C and Shankar and Teppala [21] utilizing data from the NHANES 1999–2002 survey data confirmed the findings reported by Muntner et al. Few other studies have also reported correlations between BMI and serum cystatin C levels [34, 35]. In the current study, we found that the associations between elevated BMI and preclinical CKD defined by elevated cystatin C levels are significant in both men and women consistent with the two studies conducted in the US [20, 21]. BMI has been shown to be a risk factor for CKD in Western populations [6, 9, 10]. However, the contribution of BMI to CKD has been shown to be inconsistent in Asian populations. In a previous study involving a multiethnic Asian population in Singapore, we showed a positive association between BMI and CKD [11]. However, few studies involving Malay and Japanese populations have shown a gender-specific association with the association being observed only in men [14, 15], while a study from China [13] have shown no significant association between BMI and CKD. The reason for the observed inconsistency in the association between BMI and CKD within Asian populations is not clear. It could possibly be explained by differences in the definitions of obesity between the studies (BMI C25 kg/m2 in the Singapore Malay Eye Study vs. BMI C23 kg/m2 in the Beijing study)
Clin Exp Nephrol Table 3 Association between BMI and elevated cystatin C within subgroups BMI categories
Total sample size
Elevated cystatin C, n (%)
Multivariable OR (95 % CI)a
Men (n = 1,108)
Total sample size
Elevated cystatin C, n (%)
Multivariable OR (95 % CI)a
Women (n = 944)
Normal
526
177 (33.7)
1 (Referent)
324
65 (20.1)
1 (Referent)
Overweight
463
195 (42.1)
1.60 (1.20–2.14)
399
90 (22.6)
1.27 (0.84–1.91)
Obese
119
64 (53.8)
3.57 (2.25–5.68)
221
79 (35.8)
\0.001
P trend Diabetes (n = 536) Normal Overweight
191 238
47 (24.6) 76 (31.9)
Obese
107
47 (43.9)
No diabetes (n = 1,516) 1 (Referent) 1.68 (1.01–2.80)
659 624
195 (29.6) 209 (33.5)
3.99 (2.09–7.59)
233
96 (41.2)
\0.001
P trend
2.84 (1.79–4.49) \0.001
Hypertension (n = 1,010)
1 (Referent) 1.46 (1.12–1.91) 3.05 (2.10–4.41) \0.001
No hypertension (n = 1,042)
Normal
364
132 (36.3)
1 (Referent)
486
110 (22.6)
1 (Referent)
Overweight
444
166 (37.4)
1.37 (0.98–1.92)
418
119 (28.5)
1.60 (1.14–2.24)
Obese
202
89 (44.1)
2.78 (1.80–4.28)
138
54 (39.1)
P trend
\0.001
4.01 (2.49–6.44) \0.001
P interaction (BMI categories 9 sex = 0.4; BMI categories 9 diabetes status = 0.3; BMI categories 9 hypertension status = 0.4) a
Adjusted for age (years), sex (men, women), education (primary and below, secondary and above), smoking status (never, former, current), alcohol consumption (absent, present), diabetes (absent, present), hypertension (absent, present), total cholesterol (mmol/L), and eGFRcr (mL/ min/1.73 m2)
and the very high prevalence of overweight/obese observed in Malay women compared to men (65 % in women vs. 49 % in men). Future prospective studies may clarify the association between BMI and CKD. The observed association between higher BMI and cystatin C could be mediated by mechanisms including hyperfiltration, inflammation, insulin resistance, and oxidative stress [7, 36, 37]. In addition, thyroid dysfunction [38] could also play a role. The major strengths of the study include its populationbased sample, including ethnically homogeneous Indian population thus eliminating confounding by race-ethnicity, the large sample size allowing for subgroup analysis by potential confounders. Our study has some limitations. First, the cross-sectional nature of the study design limits our ability to identify the temporality of the association. Second, it is possible that the observed association could be due to residual confounding by unmeasured risk factors for e.g., inflammation. However, due to the persistence of the strong positive association after accounting for several potential confounders, it is unlikely for some unmeasured factors to significantly alter our results. Third, we do not have information on other measures of adiposity such as waist circumference, waist to hip ratio or fat mass to corroborate our findings. Fourth, we did not measure GFR to confirm that an elevated serum cystatin C is associated with a true reduction of GFR. Fifth, we did not include adults younger than 40 years as the parent study which provided
data for the current study was aimed to study the prevalence and risk factors of age-related eye diseases and thus limited the age of the population to 40–80 years. In conclusion, we found that overweight and obesity are associated with elevated levels of cystatin C in a population-based sample of Indian adults aged 40 years and above without CKD. Our findings suggest that overweight and obesity may play a key role in early kidney function decline even before the onset of CKD in Indian adults. Future prospective studies may provide more insights into this association. Acknowledgments This work was supported by the Singapore Ministry of Education, Academic Research Fund tier 1 No T1-2012 Feb-01; National Medical Research Council Grant STaR/0003/2008; Singapore Biomedical Research Grant (BMRC) 08/1/35/19/550; Singapore Ministry of Health’s National Medical Research Council under its Talent Development Scheme NMRC/TA/0008/2012 (CS). Laboratory and data handling was supported by Qi Chun Toh and Hwee Min Loh. Conflict of interest interest exists.
The authors have declared that no conflict of
References 1. Ministry of Health: National health survey. http://www.moh.gov. sg/content/dam/moh_web/Publications/Reports/2011/NHS2010% 20-%20low%20res.pdf (2010). Accessed 04 May 2013. 2. Li PK, Kwan BC, Leung CB, Kwan TH, Wong KM, Lui SL, et al. Prevalence of silent kidney disease in Hong Kong: the screening
123
Clin Exp Nephrol
3. 4. 5.
6.
7.
8.
9.
10. 11.
12. 13.
14.
15.
16.
17. 18.
19. 20.
21.
22.
for Hong Kong asymptomatic renal population and evaluation (SHARE) program. Kidney Int Suppl. 2005;94:S36–40. Chu NF. Prevalence of obesity in Taiwan. Obes Rev. 2005;6:271–4. Kim DM, Ahn CW, Nam SY. Prevalence of obesity in Korea. Obes Rev. 2005;6:117–21. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282:1523–9. Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS. Body mass index and risk for end-stage renal disease. Ann Intern Med. 2006;144:21–8. Wahba IM, Mak RH. Obesity and obesity-initiated metabolic syndrome: mechanistic links to chronic kidney disease. Clin J Am Soc Nephrol. 2007;2:550–62. K/DOQI. Clinical practice guidelines for chronic kidney disease evaluation, classification, and stratification. Am J Kidney Dis. 2002;39:S1–266. Fox CS, Larson MG, Leip EP, Culleton B, Wilson PW, Levy D. Predictors of new-onset kidney disease in a community-based population. JAMA. 2004;291:844–50. Vupputuri S, Sandler DP. Lifestyle risk factors and chronic kidney disease. Ann Epidemiol. 2003;13:712–20. Sabanayagam C, Lim SC, Wong TY, Lee J, Shankar A, Tai ES. Ethnic disparities in prevalence and impact of risk factors of chronic kidney disease. Nephrol Dial Transplant. 2010;25:2564–70. Kuo HW, Tsai SS, Tiao MM, Yang CY. Epidemiological features of CKD in Taiwan. Am J Kidney Dis. 2007;49:46–55. Zhang L, Zhang P, Wang F, Zuo L, Zhou Y, Shi Y, et al. Prevalence and factors associated with CKD: a population study from Beijing. Am J Kidney Dis. 2008;51:373–84. Iseki K, Ikemiya Y, Kinjo K, Inoue T, Iseki C, Takishita S. Body mass index and the risk of development of end-stage renal disease in a screened cohort. Kidney Int. 2004;65:1870–6. Shankar A, Leng C, Chia KS, Koh D, Tai ES, Saw SM, et al. Association between body mass index and chronic kidney disease in men and women: population-based study of Malay adults in Singapore. Nephrol Dial Transplant. 2008;23:1910–8. Shlipak MG, Praught ML, Sarnak MJ. Update on cystatin C: new insights into the importance of mild kidney dysfunction. Curr Opin Nephrol Hypertens. 2006;15:270–5. Madero M, Sarnak MJ. Association of cystatin C with adverse outcomes. Curr Opin Nephrol Hypertens. 2009;18:258–63. Meng L, Yang Y, Qi LT, Wang XJ, Xu GB, Zhang BW. Elevated serum cystatin C is an independent predictor of cardiovascular events in people with relatively normal renal function. J Nephrol. 2012;25:426–30. Summaries for Patients. Preclinical kidney disease in elderly people. Ann Intern Med. 2006;145:I22. Muntner P, Winston J, Uribarri J, Mann D, Fox CS. Overweight, obesity, and elevated serum cystatin C levels in adults in the United States. Am J Med. 2008;121:341–8. Shankar A, Teppala S. Relationship between body mass index and high cystatin levels among US adults. J Clin Hypertens (Greenwich). 2011;13:925–30. Lavanya R, Jeganathan VS, Zheng Y, Raju P, Cheung N, Tai ES, et al. Methodology of the Singapore Indian Chinese Cohort (SICC) eye study: quantifying ethnic variations in the
123
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37. 38.
epidemiology of eye diseases in Asians. Ophthalmic Epidemiol. 2009;16:325–36. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF III, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604–12. Obesity: Preventing and Managing the Global Epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i-253. Coll E, Botey A, Alvarez L, Poch E, Quinto L, Saurina A, et al. Serum cystatin C as a new marker for noninvasive estimation of glomerular filtration rate and as a marker for early renal impairment. Am J Kidney Dis. 2000;36:29–34. Dharnidharka VR, Kwon C, Stevens G. Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis. 2002;40:221–6. Roos JF, Doust J, Tett SE, Kirkpatrick CM. Diagnostic accuracy of cystatin C compared to serum creatinine for the estimation of renal dysfunction in adults and children—a meta-analysis. Clin Biochem. 2007;40:383–91. Sabanayagam C, Wong TY, Xiao J, Shankar A. Serum cystatin C and prediabetes in non-obese US adults. Eur J Epidemiol. 2013;28:311–6. Donahue RP, Stranges S, Rejman K, Rafalson LB, Dmochowski J, Trevisan M. Elevated cystatin C concentration and progression to pre-diabetes: the Western New York study. Diabetes Care. 2007;30:1724–9. Sahakyan K, Lee KE, Shankar A, Klein R. Serum cystatin C and the incidence of type 2 diabetes mellitus. Diabetologia. 2011;54:1335–40. Ristiniemi N, Lund J, Tertti R, Christensson A, Ilva T, Porela P, et al. Cystatin C as a predictor of all-cause mortality and myocardial infarction in patients with non-ST-elevation acute coronary syndrome. Clin Biochem. 2012;45:535–40. Shlipak MG, Katz R, Sarnak MJ, Fried LF, Newman AB, Stehman-Breen C, et al. Cystatin C and prognosis for cardiovascular and kidney outcomes in elderly persons without chronic kidney disease. Ann Intern Med. 2006;145:237–46. Teo BW, Xu H, Wang D, Li J, Sinha AK, Shuter B, et al. Estimating glomerular filtration rates by use of both cystatin C and standardized serum creatinine avoids ethnicity coefficients in Asian patients with chronic kidney disease. Clin Chem. 2012;58:450–7. Knight EL, Verhave JC, Spiegelman D, Hillege HL, de Zeeuw D, Curhan GC, et al. Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. Kidney Int. 2004;65:1416–21. Shlipak MG. Cystatin C as a marker of glomerular filtration rate in chronic kidney disease: influence of body composition. Nat Clin Pract Nephrol. 2007;3:188–9. Lee SH, Park SA, Ko SH, Yim HW, Ahn YB, Yoon KH, et al. Insulin resistance and inflammation may have an additional role in the link between cystatin C and cardiovascular disease in type 2 diabetes mellitus patients. Metabolism. 2010;59:241–6. Zoccali C. Overweight, obesity and metabolic alterations in chronic kidney disease. Prilozi. 2009;30:17–31. Wiesli P, Schwegler B, Spinas GA, Schmid C. Serum cystatin C is sensitive to small changes in thyroid function. Clin Chim Acta. 2003;338:87–90.
ORIGINAL ARTICLE
Body mass index and preclinical kidney disease in Indian adults aged 40 years and above without chronic kidney disease Charumathi Sabanayagam • Tien Yin Wong Jiemin Liao • Sunil Sethi • Boon Wee Teo
•
Received: 18 September 2013 / Accepted: 22 January 2014 Ó Japanese Society of Nephrology 2014
Abstract Background Obesity is associated with diabetes and hypertension, two major risk factors for chronic kidney disease (CKD). Recently, it has been shown that obesity is associated with preclinical kidney disease defined by elevated levels of cystatin C among those without CKD in US adults. However, the association of obesity with cystatin C is not known in industrialized Asian populations. Methods We examined 2,052 Indian adults aged 40–80 years in Singapore who were free of CKD defined as a serum creatinine-based estimated glomerular filtration rate (eGFRcr) \60 mL/min/1.73 m2 and/or the presence of microalbuminuria. Body mass index (BMI) values were categorized into normal (18.5–24.9), overweight (25–29.9) and obese (C30 kg/m2). Elevated serum cystatin C was defined as cystatin C C1 mg/L.
Results Overweight and obesity were significantly associated with elevated levels of cystatin C after adjusting for potential confounders including diabetes and hypertension and eGFRcr. Compared to those with normal weight, the odds ratio (95 % confidence interval) of elevated cystatin C was 1.49 (1.17–1.88) for overweight and 3.20 (2.33–4.39) for obese. This association was consistently present when BMI was analyzed as a continuous variable and also in subgroups of men, women and in those without diabetes mellitus or hypertension. Conclusions Higher BMI levels are associated with preclinical kidney disease in Indian adults aged 40 years and above without CKD. Keywords
CKD Cystatin C Indians Overweight
Introduction C. Sabanayagam (&) T. Y. Wong Singapore Eye Research Institute, 11 Third Hospital Avenue, #06-13, SNEC Bldg, Singapore 168751, Singapore e-mail: [email protected] C. Sabanayagam T. Y. Wong Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore, Singapore C. Sabanayagam T. Y. Wong J. Liao Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore S. Sethi Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore B. W. Teo Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Obesity is an emerging public health problem in industrialized Asian countries including Singapore [1], Hong Kong [2], Taiwan [3], and South Korea [4] associated with diabetes, hypertension and cardiovascular disease (CVD) [5].Chronic kidney disease (CKD) [6, 7], defined by serum creatinine-based estimated glomerular filtration rate (eGFRcr) \60 mL/min/1.73 m2 is another emerging public health problem in Asian populations paralleling the rising prevalence of diabetes and hypertension, two of the major risk factors for CKD [8]. Obesity is an established risk factor of CKD in Western populations [6, 9, 10]; however, the association of obesity with CKD has not been consistent in Asian populations with some showing a positive association [11], some with no significant association [12, 13] and some showing a gender-specific association observed only among men [14, 15].
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Serum cystatin C, a cysteine protease inhibitor has recently been included as an alternative marker of CKD by KDIGO [16]. Elevated levels of cystatin C in the preclinical stages of CKD have been shown to be predictive of adverse outcomes including the development of CKD and CVD [16–19]. Two recent studies from the US utilizing data from different cycles of the National Health and Nutritional Examination Survey reported that overweight and obesity are associated with preclinical kidney disease defined by elevated levels of cystatin C among those without CKD [20, 21]. However, the association of obesity with cystatin C is not known in Asian populations. In this context, we examined the association between body mass index (BMI) and preclinical kidney disease in a populationbased sample of Indian adults in Singapore, who were free of CKD.
Methods Study population The present study utilized data from the Singapore Indian Eye Study, a population-based cross-sectional study of 3,400 Indians aged 40–80 years conducted from 2007 to 2009 with detailed methodology reported elsewhere [22]. In brief, from a computer-generated random list of 11,616 Indian names provided by the Ministry of Home Affairs, 6,350 adults were selected by an age-stratified random sampling method. Of the 4,497 eligible participants, 3,400 participated in the study with a response rate of 75.6 %. For the current analysis, we included those with information available on cystatin C measurements (n = 2,919 included). We excluded those with CKD (defined as an eGFRcr of \60 mL/min/1.73 m2 from serum creatinine [8] using the recently developed chronic kidney disease epidemiology collaboration (CKD-EPI) equation [23], n = 192) and/or microalbuminuria (defined as a urinary albumin-to-creatinine ratio C30 mg/g from spot urine sample [8], n = 599). We further excluded those who were underweight (BMI \18.5 kg/m2, n = 49) and those with missing information on variables included in the multivariable model (n = 27). The final sample available for the current analysis was 2,052. Written informed consent was obtained from all participants and the study was approved by the National Healthcare Group and the Singapore Eye Research Institute Institutional Review Boards. Outcome of interest The main outcome of interest in the current study was preclinical kidney disease defined by cystatin C C1 mg/L among those without CKD or microalbuminuria [16–19].
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Standard serum cystatin c assay was performed in a central clinical laboratory accredited by the College of American Pathologists using particle-enhanced turbidimetric assay on the Siemens Advia platform. The CV for cystatin C results was 5.2–6.2 %. Assessment of exposure and covariates Height was measured in centimeters using a wall-mounted measuring tape and weight was measured in kilograms using a digital scale (SECA, model 782 2321009; Vogel & Halke, Germany). BMI was calculated as weight in kilograms divided by the square of height in meters squared (kg/m2). Based on the World Health Organization definition [24], overweight status was defined as a BMI between 25 and 29.9 kg/m2, and obesity as a BMI over 30 kg/m2. Information on participant demographics, educational attainment, personal and medical history was obtained using a standardized questionnaire administered by trained interviewers. Education level was categorized into (1) primary and below (B6 years), (2) secondary (7–10 years) and (3) high school and above (C11 years). Cigarette smoking was categorized into current, former and never smoker and alcohol consumption into drinkers and nondrinkers. BP measurements were taken using a digital automatic blood pressure monitor (Dinamap model Pro Series DP110X-RW, 100V2; GE Medical Systems Information Technologies, Inc., USA) on 2 occasions 5 min apart, after the participants were seated for at least 5 min. If these two BP measurements differed by more than 10 mmHg systolic and 5 mmHg diastolic, a third measurement was taken and the average of the two closest readings was taken as the BP value. 40 mL venous blood was collected to measure serum lipids, creatinine and casual glucose in the non-fasting state. eGFRcr was estimated from serum creatinine using the CKD-EPI equation [23]. Statistical analysis BMI was analyzed both as a categorical and a continuous variable. We examined the association of BMI with elevated cystatin C in two logistic regression models: (1) adjusted for age (years), and sex (men, women), (2) multivariable model additionally adjusted for education (primary and below, secondary and above), smoking status (never, former, current), alcohol consumption (absent, present), diabetes (absent, present), hypertension (absent, present), total cholesterol (mmol/L), and eGFRcr (mL/min/ 1.73 m2). Tests for trend were performed, modeling BMI categories as an ordinal variable in the corresponding multivariable logistic regression models. We also analyzed the association of BMI with elevated cystatin C using BMI
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as a continuous variable. To explore further potential nonlinear association between BMI and elevated levels of cystatin C, we used a restricted quadratic spline model with knots at the 10, 50 and 90th percentiles (21.4, 25.8, 31.7 kg/m2) of BMI. To examine the consistency of the association between BMI and cystatin C, we performed subgroup analyses of BMI categories stratified by sex, diabetes and hypertension status. Statistical interaction between the BMI categories and each of the stratifying variables was performed by including cross-product interaction terms in the multivariable models. In supplementary analyses, we repeated the multivariable analyses in Table 2 (1) using quartiles of BMI, and (2) after excluding participants with diabetes, hypertension or self-reported CVD [cystatin C levels were significantly higher among those with self-reported CVD compared to those without, mean (SD) = 1.01 (0.2) vs. 0.94 (0.18), P \ 0.001]. All statistical analyses were performed using STATA version 12.1 (Texas, USA).
Results Table 1 shows the characteristics of the study participants. More than half of the adults were either overweight or Table 1 Baseline characteristics of the study participants Characteristics
n = 2,052
Age (years)
55.9 (9.27)
Women (%)
944 (46.0)
Education categories (%) Primary and below Secondary and above
1,055 (51.4) 997 (48.6)
Discussion
Smoking status (%) Never smoker Past smoker Current smoker Alcohol drinker (%) Diabetes mellitus (%) Hypertension (%)
1,500 (73.1) 217 (10.6) 335 (16.3) 285 (13.9) 536 (26.1) 1,010 (49.2)
Body mass index, kg/m2 (%) \25 25–29.9 C30
850 (41.4) 862 (42.0) 340 (16.6)
Total cholesterol (mmol/L)
5.23 (1.08)
Serum cystatin C (mg/L)
0.95 (0.19)
Serum cystatin C [1 mg/L
670 (32.7)
Data presented are number (%) or mean (SD)
obese. Nearly a third of the adults had cystatin C levels C1 mg/L. 26 % had diabetes and 49 % had hypertension. Table 2 shows the association between BMI and cystatin C in the whole population. 32.7 % of the subjects had elevated cystatin C levels. When BMI was analyzed in categories, a significant graded association was observed between increasing categories of BMI and cystatin C C1 mg/L in both the age, sex-adjusted and the multivariable models (P trend \0.001). This positive association persisted when BMI was analyzed as a continuous variable. The multivariable adjusted OR (95 % CI) of elevated cystatin C was 1.55 (1.39–1.73) per SD (4.74 kg/m2) increase in BMI value. The association between increasing levels of BMI and greater odds of elevated cystatin C was also evident in models based on restricted cubic splines (Fig. 1). In Table 3, we examined the association of BMI categories within subgroups of sex, diabetes and hypertension status. The strong positive association between BMI categories and cystatin C C1 mg/L was consistently present among these subgroups also, and no significant interactions were detected between BMI and any of the stratifying variables (P interaction [0.1 for all stratifying variables). In supplementary analyses, when we repeated the main analysis in Table 2 with quartiles of BMI, the results remain unaltered; compared with quartile of BMI (referent), the multivariable OR (95 % CI) of cystatin C C1 mg/L was 1.14 (0.84–1.55), 1.49 (1.10–2.02) and 2.91 (2.13–3.97) in BMI quartiles 2, 3 and 4. Excluding participants with diabetes, hypertension or self-reported CVD (n = 793 included), the results were essentially similar; compared with persons with normal weight, the multivariable OR (95 % CI) of cystatin C C1 mg/L was 1.63 (1.12–2.37) and 3.84 (2.24–6.60) in overweight and obese categories.
In a large population-based sample of Indian adults without CKD and/or microalbuminuria, we found increasing levels of BMI were significantly associated with elevated cystatin C levels (cystatin C C1 g/L), a marker for preclinical kidney disease independent of potential confounders including diabetes, hypertension, total cholesterol and eGFRcr levels. This association was consistently present when BMI was analyzed as either a categorical or a continuous variable and the association was consistent across subgroups of men, women, and those with and without diabetes or hypertension. To our knowledge, this is the first study showing an association between BMI and preclinical kidney disease in an Asian population where the contribution of BMI to CKD has been shown to be different from Western populations.
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Clin Exp Nephrol Table 2 Association between BMI and elevated serum cystatin C BMI categories Normal weight
Total sample size 850
Elevated cystatin C (%)
Serum cystatin C, mg/L (mean, SD)
Age- and sex-adjusted OR (95 % CI)
Multivariable OR (95 % CI)a
28.5
0.93 (0.19)
1 (Referent)
1 (Referent)
Overweight
862
33.1
0.94 (0.18)
1.52 (1.22–1.90)
1.49 (1.17–1.88)
Obese
340
42.1
0.99 (0.20)
2.71 (2.03–3.61)
3.20 (2.33–4.39)
\0.001
\0.001
2,052
32.7
1.44 (1.31–1.60)
1.55 (1.39–1.73)
P trend One SD (4.74 kg/m2) increase in BMI a
Adjusted for age (years), sex (men, women), education (primary and below, secondary and above), smoking status (never, former, current), alcohol consumption (absent, present), diabetes (absent, present), hypertension (absent, present), total cholesterol (mmol/L), and eGFRcr (mL/ min/1.73 m2)
Fig. 1 Plot of restricted cubic spline model showing the association between body mass index (BMI) and elevated levels of serum cystatin C. Knots specified at 10, 50 and 90th percentiles of BMI (21.4, 25.8, 31.7 kg/m2). Model adjusted for age, sex, education, smoking status, alcohol consumption, diabetes status, hypertension status, total cholesterol, and eGFRcr. X-axis, body mass index (kg/m2). Y-axis, odds ratio and 95 % confidence interval (dotted lines) of elevated cystatin C levels
Serum cystatin C, an alternative marker of GFR has been shown to be a sensitive marker of renal function in early stages of CKD when serum creatinine levels are in the normal range [25–27]. In addition, cystatin C has also been shown to be predictive of adverse clinical outcomes including prediabetes [28, 29], diabetes [30], CVD [18], ESRD and all-cause mortality [31] in the preclinical state of kidney dysfunction that is not detected by serum creatinine-based eGFRcr [32]. In the current study, we found that both overweight and obesity are associated with elevated cystatin C levels among those without CKD or albuminuria. In addition, we found that the association between BMI and cystatin C remained strong after removing those with diabetes, hypertension and CVD. This suggests that higher BMI could contribute to early renal function decline in the absence of diabetes and hypertension. An alternative
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explanation is that overweight and obese people have relatively lower muscle mass resulting in falsely low serum creatinine, which tends to overestimate GFR [33]. However, serum cystatin C-based GFR estimations tend to under-estimate GFR. Therefore, in obese patients, preclinical CKD detection using estimated GFR may be improved using serum cystatin C. Our finding of an association between higher BMI levels and cystatin C is consistent with two previous studies that reported similar associations between BMI and cystatin C in US adults [20, 21] and extends the associations to Asian Indians. Muntner et al. [20] utilizing data from the Third National Health and Nutrition Examination Survey (NHANES-III) in the US reported a positive association between elevated levels of BMI and cystatin C and Shankar and Teppala [21] utilizing data from the NHANES 1999–2002 survey data confirmed the findings reported by Muntner et al. Few other studies have also reported correlations between BMI and serum cystatin C levels [34, 35]. In the current study, we found that the associations between elevated BMI and preclinical CKD defined by elevated cystatin C levels are significant in both men and women consistent with the two studies conducted in the US [20, 21]. BMI has been shown to be a risk factor for CKD in Western populations [6, 9, 10]. However, the contribution of BMI to CKD has been shown to be inconsistent in Asian populations. In a previous study involving a multiethnic Asian population in Singapore, we showed a positive association between BMI and CKD [11]. However, few studies involving Malay and Japanese populations have shown a gender-specific association with the association being observed only in men [14, 15], while a study from China [13] have shown no significant association between BMI and CKD. The reason for the observed inconsistency in the association between BMI and CKD within Asian populations is not clear. It could possibly be explained by differences in the definitions of obesity between the studies (BMI C25 kg/m2 in the Singapore Malay Eye Study vs. BMI C23 kg/m2 in the Beijing study)
Clin Exp Nephrol Table 3 Association between BMI and elevated cystatin C within subgroups BMI categories
Total sample size
Elevated cystatin C, n (%)
Multivariable OR (95 % CI)a
Men (n = 1,108)
Total sample size
Elevated cystatin C, n (%)
Multivariable OR (95 % CI)a
Women (n = 944)
Normal
526
177 (33.7)
1 (Referent)
324
65 (20.1)
1 (Referent)
Overweight
463
195 (42.1)
1.60 (1.20–2.14)
399
90 (22.6)
1.27 (0.84–1.91)
Obese
119
64 (53.8)
3.57 (2.25–5.68)
221
79 (35.8)
\0.001
P trend Diabetes (n = 536) Normal Overweight
191 238
47 (24.6) 76 (31.9)
Obese
107
47 (43.9)
No diabetes (n = 1,516) 1 (Referent) 1.68 (1.01–2.80)
659 624
195 (29.6) 209 (33.5)
3.99 (2.09–7.59)
233
96 (41.2)
\0.001
P trend
2.84 (1.79–4.49) \0.001
Hypertension (n = 1,010)
1 (Referent) 1.46 (1.12–1.91) 3.05 (2.10–4.41) \0.001
No hypertension (n = 1,042)
Normal
364
132 (36.3)
1 (Referent)
486
110 (22.6)
1 (Referent)
Overweight
444
166 (37.4)
1.37 (0.98–1.92)
418
119 (28.5)
1.60 (1.14–2.24)
Obese
202
89 (44.1)
2.78 (1.80–4.28)
138
54 (39.1)
P trend
\0.001
4.01 (2.49–6.44) \0.001
P interaction (BMI categories 9 sex = 0.4; BMI categories 9 diabetes status = 0.3; BMI categories 9 hypertension status = 0.4) a
Adjusted for age (years), sex (men, women), education (primary and below, secondary and above), smoking status (never, former, current), alcohol consumption (absent, present), diabetes (absent, present), hypertension (absent, present), total cholesterol (mmol/L), and eGFRcr (mL/ min/1.73 m2)
and the very high prevalence of overweight/obese observed in Malay women compared to men (65 % in women vs. 49 % in men). Future prospective studies may clarify the association between BMI and CKD. The observed association between higher BMI and cystatin C could be mediated by mechanisms including hyperfiltration, inflammation, insulin resistance, and oxidative stress [7, 36, 37]. In addition, thyroid dysfunction [38] could also play a role. The major strengths of the study include its populationbased sample, including ethnically homogeneous Indian population thus eliminating confounding by race-ethnicity, the large sample size allowing for subgroup analysis by potential confounders. Our study has some limitations. First, the cross-sectional nature of the study design limits our ability to identify the temporality of the association. Second, it is possible that the observed association could be due to residual confounding by unmeasured risk factors for e.g., inflammation. However, due to the persistence of the strong positive association after accounting for several potential confounders, it is unlikely for some unmeasured factors to significantly alter our results. Third, we do not have information on other measures of adiposity such as waist circumference, waist to hip ratio or fat mass to corroborate our findings. Fourth, we did not measure GFR to confirm that an elevated serum cystatin C is associated with a true reduction of GFR. Fifth, we did not include adults younger than 40 years as the parent study which provided
data for the current study was aimed to study the prevalence and risk factors of age-related eye diseases and thus limited the age of the population to 40–80 years. In conclusion, we found that overweight and obesity are associated with elevated levels of cystatin C in a population-based sample of Indian adults aged 40 years and above without CKD. Our findings suggest that overweight and obesity may play a key role in early kidney function decline even before the onset of CKD in Indian adults. Future prospective studies may provide more insights into this association. Acknowledgments This work was supported by the Singapore Ministry of Education, Academic Research Fund tier 1 No T1-2012 Feb-01; National Medical Research Council Grant STaR/0003/2008; Singapore Biomedical Research Grant (BMRC) 08/1/35/19/550; Singapore Ministry of Health’s National Medical Research Council under its Talent Development Scheme NMRC/TA/0008/2012 (CS). Laboratory and data handling was supported by Qi Chun Toh and Hwee Min Loh. Conflict of interest interest exists.
The authors have declared that no conflict of
References 1. Ministry of Health: National health survey. http://www.moh.gov. sg/content/dam/moh_web/Publications/Reports/2011/NHS2010% 20-%20low%20res.pdf (2010). Accessed 04 May 2013. 2. Li PK, Kwan BC, Leung CB, Kwan TH, Wong KM, Lui SL, et al. Prevalence of silent kidney disease in Hong Kong: the screening
123
Clin Exp Nephrol
3. 4. 5.
6.
7.
8.
9.
10. 11.
12. 13.
14.
15.
16.
17. 18.
19. 20.
21.
22.
for Hong Kong asymptomatic renal population and evaluation (SHARE) program. Kidney Int Suppl. 2005;94:S36–40. Chu NF. Prevalence of obesity in Taiwan. Obes Rev. 2005;6:271–4. Kim DM, Ahn CW, Nam SY. Prevalence of obesity in Korea. Obes Rev. 2005;6:117–21. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282:1523–9. Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS. Body mass index and risk for end-stage renal disease. Ann Intern Med. 2006;144:21–8. Wahba IM, Mak RH. Obesity and obesity-initiated metabolic syndrome: mechanistic links to chronic kidney disease. Clin J Am Soc Nephrol. 2007;2:550–62. K/DOQI. Clinical practice guidelines for chronic kidney disease evaluation, classification, and stratification. Am J Kidney Dis. 2002;39:S1–266. Fox CS, Larson MG, Leip EP, Culleton B, Wilson PW, Levy D. Predictors of new-onset kidney disease in a community-based population. JAMA. 2004;291:844–50. Vupputuri S, Sandler DP. Lifestyle risk factors and chronic kidney disease. Ann Epidemiol. 2003;13:712–20. Sabanayagam C, Lim SC, Wong TY, Lee J, Shankar A, Tai ES. Ethnic disparities in prevalence and impact of risk factors of chronic kidney disease. Nephrol Dial Transplant. 2010;25:2564–70. Kuo HW, Tsai SS, Tiao MM, Yang CY. Epidemiological features of CKD in Taiwan. Am J Kidney Dis. 2007;49:46–55. Zhang L, Zhang P, Wang F, Zuo L, Zhou Y, Shi Y, et al. Prevalence and factors associated with CKD: a population study from Beijing. Am J Kidney Dis. 2008;51:373–84. Iseki K, Ikemiya Y, Kinjo K, Inoue T, Iseki C, Takishita S. Body mass index and the risk of development of end-stage renal disease in a screened cohort. Kidney Int. 2004;65:1870–6. Shankar A, Leng C, Chia KS, Koh D, Tai ES, Saw SM, et al. Association between body mass index and chronic kidney disease in men and women: population-based study of Malay adults in Singapore. Nephrol Dial Transplant. 2008;23:1910–8. Shlipak MG, Praught ML, Sarnak MJ. Update on cystatin C: new insights into the importance of mild kidney dysfunction. Curr Opin Nephrol Hypertens. 2006;15:270–5. Madero M, Sarnak MJ. Association of cystatin C with adverse outcomes. Curr Opin Nephrol Hypertens. 2009;18:258–63. Meng L, Yang Y, Qi LT, Wang XJ, Xu GB, Zhang BW. Elevated serum cystatin C is an independent predictor of cardiovascular events in people with relatively normal renal function. J Nephrol. 2012;25:426–30. Summaries for Patients. Preclinical kidney disease in elderly people. Ann Intern Med. 2006;145:I22. Muntner P, Winston J, Uribarri J, Mann D, Fox CS. Overweight, obesity, and elevated serum cystatin C levels in adults in the United States. Am J Med. 2008;121:341–8. Shankar A, Teppala S. Relationship between body mass index and high cystatin levels among US adults. J Clin Hypertens (Greenwich). 2011;13:925–30. Lavanya R, Jeganathan VS, Zheng Y, Raju P, Cheung N, Tai ES, et al. Methodology of the Singapore Indian Chinese Cohort (SICC) eye study: quantifying ethnic variations in the
123
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37. 38.
epidemiology of eye diseases in Asians. Ophthalmic Epidemiol. 2009;16:325–36. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF III, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604–12. Obesity: Preventing and Managing the Global Epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i-253. Coll E, Botey A, Alvarez L, Poch E, Quinto L, Saurina A, et al. Serum cystatin C as a new marker for noninvasive estimation of glomerular filtration rate and as a marker for early renal impairment. Am J Kidney Dis. 2000;36:29–34. Dharnidharka VR, Kwon C, Stevens G. Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis. 2002;40:221–6. Roos JF, Doust J, Tett SE, Kirkpatrick CM. Diagnostic accuracy of cystatin C compared to serum creatinine for the estimation of renal dysfunction in adults and children—a meta-analysis. Clin Biochem. 2007;40:383–91. Sabanayagam C, Wong TY, Xiao J, Shankar A. Serum cystatin C and prediabetes in non-obese US adults. Eur J Epidemiol. 2013;28:311–6. Donahue RP, Stranges S, Rejman K, Rafalson LB, Dmochowski J, Trevisan M. Elevated cystatin C concentration and progression to pre-diabetes: the Western New York study. Diabetes Care. 2007;30:1724–9. Sahakyan K, Lee KE, Shankar A, Klein R. Serum cystatin C and the incidence of type 2 diabetes mellitus. Diabetologia. 2011;54:1335–40. Ristiniemi N, Lund J, Tertti R, Christensson A, Ilva T, Porela P, et al. Cystatin C as a predictor of all-cause mortality and myocardial infarction in patients with non-ST-elevation acute coronary syndrome. Clin Biochem. 2012;45:535–40. Shlipak MG, Katz R, Sarnak MJ, Fried LF, Newman AB, Stehman-Breen C, et al. Cystatin C and prognosis for cardiovascular and kidney outcomes in elderly persons without chronic kidney disease. Ann Intern Med. 2006;145:237–46. Teo BW, Xu H, Wang D, Li J, Sinha AK, Shuter B, et al. Estimating glomerular filtration rates by use of both cystatin C and standardized serum creatinine avoids ethnicity coefficients in Asian patients with chronic kidney disease. Clin Chem. 2012;58:450–7. Knight EL, Verhave JC, Spiegelman D, Hillege HL, de Zeeuw D, Curhan GC, et al. Factors influencing serum cystatin C levels other than renal function and the impact on renal function measurement. Kidney Int. 2004;65:1416–21. Shlipak MG. Cystatin C as a marker of glomerular filtration rate in chronic kidney disease: influence of body composition. Nat Clin Pract Nephrol. 2007;3:188–9. Lee SH, Park SA, Ko SH, Yim HW, Ahn YB, Yoon KH, et al. Insulin resistance and inflammation may have an additional role in the link between cystatin C and cardiovascular disease in type 2 diabetes mellitus patients. Metabolism. 2010;59:241–6. Zoccali C. Overweight, obesity and metabolic alterations in chronic kidney disease. Prilozi. 2009;30:17–31. Wiesli P, Schwegler B, Spinas GA, Schmid C. Serum cystatin C is sensitive to small changes in thyroid function. Clin Chim Acta. 2003;338:87–90.
