Cadmium exposure is associated with chronic kidney disease in a superfund site lead smelter community in Dallas, Texas

Figures & data

Table 3. Selected studies examining the relationship between Cd and CKD ≥ stage 3/ESKD (exposure based on blood or urine [Cd] [A] and dietary surveys or proximity to battery plants (ie ecological fallacy) [B]).

A
Author	Population	Study	CKD measure	Result
Ferraro 2010 (15)	NHANES 1999–2006	Cross-sectional N = 5426	CKD-EPI (GFR only)	Blood [Cd] > 1 mcg/L associated with eGFR <60 ml/min/1.73m^2, OR: 1.48 (95% CI, 1.02,2.17)
Navas-Acien 2009 (18)	NHANES 2007–2012	Cross-sectional N = 14,778	MDRD (GFR only)	Highest vs lowest quartile blood Cd associated with eGFR <60 ml/min/1.73m^2, OR: 1.32 (95% CI, 1.04,1.68), interaction with smoking, lead and HTN, lead and Cd co-exposure a strong determinant of CKD
Lin et al. 2014 (52)	NHANES 2011–2012 age >20	Cross-sectional N = 1545	CKD-EPI (GFR only), same result MDRD	Blood [Cd] > 0.53 mcg/L vs blood [Cd] < 0.18 mcg/L associated with eGFR <60 ml/min/1.73m^2, OR- 2.21 (95% CI, 1.09,4.5), low serum [Zn] increases risk
Lee 2020 (40)	NHANES 1999–2016	EWAS N = 46,748	CKD-EPI (GFR only)	Divided into discovery and validation sets, discovery set: OR 1.30 (95% CI, 1.19–1.42), validation set: OR 1.20 (95% CI, 1.1,1.3). Meta-analysis discovery set: OR: 1.3 (95% CI, 1.19,1.42), validation set: OR: 1.20 (95% CI, (1.1,1.3)
Kim et al. 2015 (24)	KNHANES 2011	Cross-sectional N = 1797	MDRD	Blood Cd. No association total population, association in those with HTN or DM, HTN: OR 1.52 (95% CI, 1.05,2.19), DM: OR 1.92 (95% CI, 1.14–3.25) with eGFR <60 ml/min/1.73m^2, Cd may contribute to CKD risk in those with HTN or DM
Chung 2014 (14)	KNHANES 2008	Cross-sectional N = 8641	CKD-EPI (GFR only)	Blood [Cd] quartiles Q4 vs Q1–3, OR 1.467 (95% CI, 1.077,1.999) associated with eGFR <60/ml/min/1.73m^2.
Kim and Lee 2012 (45)	KNHANES 2008–2010	Cross-sectional N = 5924	MDRD/not <60 ml/min/1.73m^2	Log transformed [Cd] quartiles OR: 0.806 (95% CI, 0.602,1.08. Non-standard definition for reduced renal function, 25^th percentile, cut-off <80.63 ml/min/1.73m^2
Myong et al. 2012 (23)	KNHANES 2005–2008	Cross-sectional N = 2992	MDRD	Whole blood Cd quartiles, compared Q4 vs Q1, association with eGFR <60 ml/min/1.73m^2 only in women OR: 2.48 (95% CI, 1.74,3.54), men OR: 0.74 (0.5,1.1)
Hwangbo 2011 (44)	KNHANES 2005, age >20	Cross-sectional N = 1909	CKD-EPI/not <60 ml/min/1.73m^2	Non-standard definition for reduced renal function, 25^th percentile using sex-specific cut-offs, men- <74.7 ml/min/1.73m^2, women <65.4 ml/min/1.73m^2
Mason 1988 (29)	UK occupational exposure	75 exposed, 75 matched controls	Cockcroft-Gault corrected for BSA	13/75 exposed with C-G < 50 ml/min/1.73m^2, 3/74 age and sex matched controls with C-G < 50 ml/min/1.73m^2, Chi-square p < .009
Wu 2019 (19)	Taiwan	N = 220 CKD, N = 438 controls	MDRD (GFR only)	Age and sex matched controls. RBC [Cd] tertiles, <0.80 mcg/L: referent, 0.8–1.3 mcg/L: OR 2.4 (95% CI: 1.14–5.07), >1.3 mcg/L: OR 8.77 (95% CI, 5.13–14.98)
Tsai 2021 (22)	Taiwan	Cross sectional N = 2447	CKD-EPI (GFR only)	Participants invited to take health survey. Urine [Cd] (log per 1 mcg/L) multivariate analysis, OR: 0.758 (95% CI, 0.404,1.423)
Kaewnate 2012 (46)	Thailand	Cross sectional	Cockcroft-Gault	Urinary Cd, multiple logistic regression OR: 3.73 (95% CI, 2.5,5.57) contaminated (n = 563) vs non-contaminated (n = 522) villages
Wang 2016 (47)	China Jiangshan City	Random sample N = 934	None	Kidney disease excluded. Looked at urine Cd and LMW proteinuria. No measure of eGFR
Anupama 2019 (53)	South India	Case-control	MDRD	69 matched CKD cases and controls, ESKD excluded. Cd in blood detected in one case and 5 controls. OR: 0.16 (95% CI, 0.01,1.12) not significant
Yuan 2020 (20)	Taiwan, residents near petrochemical plant	Exposure cohort N = 2069	CKD-EPI Taiwan	Urine Cd. High exposure within 10 km of plant, low exposure >10 km from plant. % change in eGFR for one-fold increase in exposure. OR: 0.96 high vs low exposure (95% CI 0.87,1.06) listed as significant, but apparently not.
Sommar 2013 (21)	Sweden	Matched case-control	ESKD, GFR <10–15 ml/min, dialysis, transplant	118 ESKD cases and 347 matched controls, matched for sex, age and area, time of blood sample. Erythrocyte Cd mcg/L, OR: 1.17 (95% CI, 0.99,1.38)
B
Author	Population	Study	CKD measure	Result
Shi 2018 (30)	China Health Nutrition Survey N = 8429	Nutritional survey: cross sectional	MDRD (GFR only) No difference MDRD	Quartiles of estimated Cd intake based on dietary survey. Highest vs lowest quartile OR: 4.05 (95% CI, 2.91–5.43). OR higher in those with DM (8.10) and HTN (7.85).
Hellström 2001 (33)	Kalmar County Sweden, age 20–79, resident 1978–1995	Retrospective cohort, occupational and residential exposure	ESKD or transplant	Risk stratification based on an exposure index based on proximity to Ni-Cd battery plants, high: worker > 1 year n = 655, moderate: within 2 km of plant n = 8825, low: 2–10 km away n = 7200, unexposed: >10 km, n = 152,477. Age and sex standardised Mantel–Haenszel rate ratio 1.8 (95% CI, 1.3–2.3) exposed vs unexposed. Higher in women OR 2.3 (95% CI, 1.5.3.5).
Wang 2021 (31)	China, contaminated area from Zn-Cd smelter	Dietary survey N = 467	CKD-EPI (GFR only)	Dietary survey estimated lifetime intake and divided individuals into high ≥2.2 g) and low (<2.2 g) intake. OR: 18.16 (95% CI, 1.75–188.85) high vs low
Thomas 2014 (32)	Sweden	Dietary survey Prospective cohort, no CKD at baseline.	National Hospital Discharge Register	Tertiles of estimated Cd intake. Cohort of Swedish Men (N = 40,378), Swedish Mammography Cohort (N = 33,929). No relationship between Cd intake and CKD using a Cox proportional-hazard model. HR in men: 0.97 (95% CI, 0.77–1.21), HR in women 0.74 (95% CI, 0.53–1.04).

Abbreviations: CI: confidence interval; CKD: chronic kidney disease; CKD-EPI: Chronic Kidney Disease Epidemiology Collaboration; DM: diabetes mellitus; EWAS: environmental wide association study; GFR: glomerular filtration rate; KNHANES: Korean National Health and Nutrition Examination Survey; NHANES: National Health and Nutrition Examination Survey; HTN: hypertension; OR: odds ratio; RBC: red blood cell.

Table 1. Baseline characteristics for total sample and subgroups.

	CKD stage >3^a					CKD < 3					Total sample
	(n = 51)					(n = 766)					(n = 875)
Variables	M	SE	Lo	Hi	M	SE	Lo	Hi	p^b	M	SE	Lo	Hi
Age	63	1.9	24	86	45.9	0.5	19	86	.001	46.9	0.49	19	86
BMI	32.2	1	15	53	32.5	0.3	16	87	.0001	32.5	0.29	15	87
Arsenic (µg/L)	0.16	0.11	0	4	0.1	0.02	0	5	.6	0.1	0.02	0	5
Cadmium (µg/L)	0.24	0.09	0	3	0.08	0.05	0	4.5	.006	0.09	0.01	0	4.5
Lead (µg/dL)	3.92	0.7	0	33	2.16	0.08	0	23	.48	2.27	0.09	0	33
Mercury (µg/L)	0.06	0.04	0	2	0.06	0.01	0	7	.11	0.06	0.01	0	7
Duration of residence (years)	26.5	2.4	2	64	18.8	0.5	1	71	.11	1.93	0.04	0.1	7.1
	n	%			n	%			p^b	n	%
Females	28	54.9			510	61.9			.07	534	61.4
Smoking	9	17.6			256	31.1			.37	265	30.3
Age ≥50 years	42	82.4			310	37.6			.0001	352	59.8
GGT abnormal	18	16.5			106	12.9			.16	114	13
Smelter worker	9	17.6			46	21.8			.03	55	7.4
T2DM	16	31.4			93	11.3			.0004	109	12.5

^aProportion of individuals with CKD Stages ≤ 3 = 5.83% (95% CI: 0.045–0.076).

^bComparison of CKD ≤3 vs. >3 groups.

Table 2. Binary logistic regression of CKD Stage≥ 3 and covariates on Cd.

95% CI for OR
Independent variables	OR	Lower	Upper	p Value
Duration (decades)	1.34	1.10	1.64	.003
Male gender	1.32	0.62	2.80	.477
Abnormal GGT	1.06	0.43	2.60	.908
Hypertension	3.15	1.15	8.59	.025
Smelter worker	2.294	0.83	6.31	.108
Diabetes mellitus	2.51	1.24	5.07	.011
BMI	0.99	0.95	1.03	.512
Active smoker	0.26	0.11	0.62	.002
Cd	1.89	1.02	3.49	.044
Lead	1.13	1.02	1.24	.017
Mercury	0.63	0.22	1.78	.383
Age ≥50 years	4.41	1.98	9.82	.0001
<50 years old (n = 523)
Duration (decades)	1.38	0.79	2.39	.254
Male gender	1.98	0.40	9.86	.407
Abnormal GGT	0.10	0.004	2.68	.171
Hypertension	8.82	0.98	79.28	.052
Smelter worker	7.19	0.64	80.74	.110
Diabetes mellitus	4.38	0.53	36.13	.170
BMI	0.94	0.84	1.05	.253
Active smoker	0.46	0.09	2.49	.368
Cd	2.27	0.39	13.17	.362
Lead	1.02	0.76	1.37	.912
Mercury	–	–	–	^a
>50 years old (n = 352)
Duration (decades)	1.38	1.11	1.72	.004
Male gender	1.15	0.47	2.82	.764
Abnormal GGT	1.59	0.59	4.29	.359
Hypertension	2.46	0.77	7.85	.129
Smelter worker	2.22	0.67	7.41	.194
Diabetes mellitus	2.58	1.19	5.58	.016
BMI	1.00	0.95	1.05	.903
Active smoker	0.21	0.07	0.60	.003
Cd	2.13	1.01	4.47	.047
Lead	1.14	1.03	1.27	.013
Mercury	0.83	0.28	2.49	.738

^a16/523 values were non-zero, and the OR is inestimable.

Figure 1. Meta-analysis of cadmium and chronic kidney disease (CKD).

Ferraro PM, Costanzi S, Naticchia A, Sturniolo A, Gambaro G. 2010. Low level exposure to cadmium increases the risk of chronic kidney disease: analysis of the NHANES. BMC Public Health. 10:304. doi: 10.1186/1471-2458-10-304.

 PubMed Web of Science ®Google Scholar

Navas-Acien A, Tellez-Plaza M, Guallar E, Muntner P, Silbergeld E, Jaar B, Weaver V. 2009. Blood cadmium and lead and chronic kidney disease in US adults: a joint analysis. Am J Epidemiol. 170(9):1156–1164. doi: 10.1093/aje/kwp248.

 PubMed Web of Science ®Google Scholar

Lin YS, Ho WC, Caffrey JL, Sonawane B. 2014. Low serum zinc is associated with elevated risk of cadmium nephrotoxicity. Environ Res. 134:33–38. doi: 10.1016/j.envres.2014.06.013.

 PubMed Web of Science ®Google Scholar

Lee J, Oh S, Kang H, Kim S, Lee G, Li L, Kim CT, An JN, Oh YK, Lim CS, et al. 2020. Environment-wide association study of CKD. Clin J Am Soc Nephrol. 15(6):766–775. doi: 10.2215/CJN.06780619.

 PubMed Web of Science ®Google Scholar

Kim NH, Hyun YY, Lee KB, Chang Y, Ryu S, Oh KH, Ahn C. 2015. Environmental heavy metal exposure and chronic kidney disease in the general population. J Korean Med Sci. 30(3):272–277. doi: 10.3346/jkms.2015.30.3.272.

 PubMed Web of Science ®Google Scholar

Chung S, Chung JH, Kim SJ, Koh ES, Yoon HE, Park CW, Chang YS, Shin SJ. 2014. Blood lead and cadmium levels and renal function in Korean adults. Clin Exp Nephrol. 18 (5):735–736. doi: 10.1007/s10157-014-0959-0.

 Web of Science ®Google Scholar

Kim Y, Lee B-K. 2012. Associations of blood lead, cadmium, and mercury with estimated glomerular filtration rate in the Korean general population: analysis of 2008-2010 Korean National Health and Nutrition Examination Survey data. Environ Res. 118:124–129. doi: 10.1016/j.envres.2012.06.003.

 PubMed Web of Science ®Google Scholar

Myong JP, Kim HR, Baker D, Choi B. 2012. Blood cadmium and moderate-to-severe glomerular dysfunction in Korean adults: analysis of KNHANES 2005-2008 data. Int Arch Occup Environ Health. 85(8):885–893. doi: 10.1007/s00420-012-0737-9.

 PubMed Web of Science ®Google Scholar

Hwangbo Y, Weaver VM, Tellez-Plaza M, Guallar E, Lee B-K, Navas-Acien A. 2011. Blood cadmium and estimated glomerular filtration rate in Korean adults. Environ Health Perspect 119(12):1800–1805. doi: 10.1289/ehp.1003054.

 PubMed Web of Science ®Google Scholar

Mason HJ, Davison AG, Wright AL, Guthrie CJ, Fayers PM, Venables KM, Smith NJ, Chettle DR, Franklin DM, Scott MC. 1988. Relations between liver cadmium, cumulative exposure, and renal function in cadmium alloy workers. Br J Ind Med. 45(12):793–802. doi: 10.1136/oem.45.12.793.

 PubMedGoogle Scholar

Wu CY, Wong CS, Chung CJ, Wu MY, Huang YL, Ao PL, Lin YF, Lin YC, Shiue HS, Su CT, et al. 2019. The association between plasma selenium and chronic kidney disease related to lead, cadmium and arsenic exposure in a Taiwanese population. J Hazard Mater. 375:224–232. doi: 10.1016/j.jhazmat.2019.04.082.

 PubMed Web of Science ®Google Scholar

Tsai HJ, Hung CH, Wang CW, Tu HP, Li CH, Tsai CC, Lin WY, Chen SC, Kuo CH. 2021. Associations among heavy metals and proteinuria and chronic kidney disease. Diagnostics. 11(2):282. doi: 10.3390/diagnostics11020282.

 Web of Science ®Google Scholar

Kaewnate Y, Niyomtam S, Tangvarasittichai O, Meemark S, Pingmuangkaew P, Tangvarasittichai S. 2012. Association of elevated urinary cadmium with urinary stone, hypercalciuria and renal tubular dysfunction in the population of cadmium-contaminated area. Bull Environ Contam Toxicol. 89(6):1120–1124. doi: 10.1007/s00128-012-0856-8.

 PubMed Web of Science ®Google Scholar

Wang X, Wang Y, Feng L, Tong Y, Chen Z, Ying S, Chen T, Li T, Xia H, Jiang Z, et al. 2016. Application of the benchmark dose (BMD) method to identify thresholds of cadmium-induced renal effects in non-polluted areas in China. PLoS One. 11(8):e0161240. doi: 10.1371/journal.pone.0161240.

 PubMed Web of Science ®Google Scholar

Anupama YJ, Kiran SK, Hegde SN. 2019. Heavy metals and pesticides in chronic kidney disease–results from a matched case–control study from a rural population in Shivamogga district in South India. Indian J Nephrol. 29(6):402–409. doi: 10.4103/ijn.IJN_325_18.

 PubMed Web of Science ®Google Scholar

Yuan TH, Ke DY, Wang JE, Chan CC. 2020. Associations between renal functions and exposure of arsenic and polycyclic aromatic hydrocarbon in adults living near a petrochemical complex. Environ Pollut. 256:113457. doi: 10.1016/j.envpol.2019.113457.

 PubMed Web of Science ®Google Scholar

Sommar JN, Svensson MK, Björ BM, Elmståhl SI, Hallmans G, Lundh T, Schön SMI, Skerfving S, Bergdahl IA. 2013. End-stage renal disease and low-level exposure to lead, cadmium and mercury; a population-based, prospective nested case-referent study in Sweden. Environ Health. 12:9. doi: 10.1186/1476-069X-12-9.

 PubMed Web of Science ®Google Scholar

Shi Z, Taylor AW, Riley M, Byles J, Liu J, Noakes M. 2018. Association between dietary patterns, cadmium intake and chronic kidney disease among adults. Clin Nutr. 37(1):276–284. doi: 10.1016/j.clnu.2016.12.025.

 PubMed Web of Science ®Google Scholar

Hellström L, Elinder CG, Dahlberg B, Lundberg M, Järup L, Persson B, Axelson O. 2001. Cadmium exposure and end-stage renal disease. Am J Kidney Dis. 38(5):1001–1008. doi: 10.1053/ajkd.2001.28589.

 PubMed Web of Science ®Google Scholar

Wang X, Cui W, Wang M, Liang Y, Zhu G, Jin T, Chen X. 2021. The association between life-time dietary cadmium intake from rice and chronic kidney disease. Ecotoxicol Environ Saf. 211:111933. doi: 10.1016/j.ecoenv.2021.111933.

 PubMed Web of Science ®Google Scholar

Thomas LD, Elinder CG, Wolk A, Åkesson A. 2014. Dietary cadmium exposure and chronic kidney disease: a population-based prospective cohort study of men and women. Int J Hyg Environ Health. 217(7):720–725. doi: 10.1016/j.ijheh.2014.03.001.

 PubMed Web of Science ®Google Scholar

Data availability statement

Data sharing is not available as this is protected by stipulations in the IRB.